This research aims to explore factors that influence sustainable music learning system from psychological perspective, and innovatively constructs a combination of qualitative and quantitative approaches. For first time, combines nonlinear system and identifies relevant factors affecting music learning by establishing data system for questionnaire answering and a quantitative model for actual academic performance. Existing research mainly looks at several factors that affect fragmented music learning system from perspective of teachers' teaching rules, emphasizing phased teaching state and learning goals of teachers as main body, thus ignoring music learning students, who are a large group of music learning objects. The research fills gap in this type of research object, focusing on sustainable music learning system from emotional perspective and students who occupy a dominant position in music learning, so as to more accurately explore impact of their emotional influencing factors on music learning system. The most prominent innovation of this study lies in construction of stochastic nonlinear system for psychological influencing factors of student music learning and a quantitative model for actual learning effect. Through analysis of nonlinear system, weight values of several negative emotions on music learning system are obtained. The comprehensive impact of emotional factors and practical learning on music learning system can be obtained by weighting them together.

This paper reviews the design and component of two types of RWHS, namely roof harvesting system (RHS) and pond harvesting system (PHS). The performance in terms of quantity and quality of collected rainwater and energy consumption for RWHS with different capacities were evaluated, as well as the benefits and challenges particularly in environmental, economic and social aspects. Presently, RHS is more commonly applied but its effectiveness is limited by its small scale. The PHS is of larger scale and has greater potentials and effectiveness as an alternative water supply system. Results also indicate the many advantages of PHS especially in terms of economics, environmental aspects and volume of water harvested. While RHS may be suited to individual or existing buildings, PHS has greater potentials and should be applied in newly developed urban areas with wet equatorial climate.

The United Arab Emirates (UAE) is significantly dependent on desalinated water and groundwater resource, which is expensive and highly energy intensive. Despite the scarce water resource, only 54% of the recycled water was reused in 2015. In this study, an “Oasis” complex comprised of Sustainable Farming Compartments (SFCs) was proposed for reusing treated wastewater to decrease the ambient temperature of the SFC via an evaporative cooling system. A prototype SFC with half the original scale (width = 1.8 m, depth = 1.5 m, front height = 1.2 m back height = 0.9 m) was designed, built, and tested in an environmentally controlled laboratory and field site to evaluate the feasibility and effectiveness of the SFC under the climatic conditions in Abu Dhabi. Based on the experimental results, the temperature drops obtained from the SFC in the laboratory and field site were 5 ̊C at initial relative humidity of 60% and 7- 15 ̊C at initial relative humidity of 50%, respectively. An energy simulation using dynamic numerical simulations was performed in comparison to the results of the experiment. The energy-based dynamic simulation shows good agreement with the experimental results. The total power consumption of the SFC system was approximately three and a half times lower than that of an electrical air conditioner.

This research aims to explore factors that influence sustainable music learning system from psychological perspective, and innovatively constructs a combination of qualitative and quantitative approaches. For first time, combines nonlinear system and identifies relevant factors affecting music learning by establishing data system for questionnaire answering and a quantitative model for actual academic performance. Existing research mainly looks at several factors that affect fragmented music learning system from perspective of teachers' teaching rules, emphasizing phased teaching state and learning goals of teachers as main body, thus ignoring music learning students, who are a large group of music learning objects. The research fills gap in this type of research object, focusing on sustainable music learning system from emotional perspective and students who occupy a dominant position in music learning, so as to more accurately explore impact of their emotional influencing factors on music learning system. The most prominent innovation of this study lies in construction of stochastic nonlinear system for psychological influencing factors of student music learning and a quantitative model for actual learning effect. Through analysis of nonlinear system, weight values of several negative emotions on music learning system are obtained. The comprehensive impact of emotional factors and practical learning on music learning system can be obtained by weighting them together.

This paper presents a new methodology to evaluate the performance of an electric vehicle hybrid power system consisting of a fuel cell and a supercapacitor. The study compares the results with those obtained for a battery-electric vehicle. The methodology extends to three driving modes, ECO, NORMAL, and SPORT, corresponding to conservative, moderate, and aggressive acceleration, and three driving conditions, low, medium, and high energy demand. We develop a simulation process to evaluate the energy consumption and the energy rate of a specific electric vehicle used as a prototype for the study. The methodology applies to a driving route that includes acceleration, deceleration, braking, and constant speed segments reproducing standard driving conditions in urban journeys. The proposed method considers combined driving modes, ECO, NORMAL, and SPORT, in each acceleration process, with variable fractions, 0% to 100%, for each mode. This methodology optimizes the simulation results as it fits the current driving way in urban environments. The simulation results show an average reduction in energy consumption of 37% and 27.1% in vehicle weight, contributing to lower energy use. The study concludes that using a hybrid power system, fuel cell/supercapacitor, instead of a battery in electric vehicles is beneficial, especially in journeys with frequent acceleration processes.

The sustainable development of an area is highly dependable on reliable electrical energy supply. Microgrids are important in integrating distributed energy resources (DERs) using power electronic converters. However, microgrid control becomes challenging with the increasing number of distributed generators and loads. With the conventional droop control method, power contributions from DER converters cannot be accurately shared due to a mismatch of line impedances. In this paper, an augmented hierarchical control mechanism is proposed to solve the issues mentioned above. This hierarchical control mechanism consists of primary and secondary controllers. The primary stage utilized the droop controller to improve optimal power flow, mainly for the resistive network. The secondary stage is based on an improved methodology to compensate for the voltage and frequency variations during small and large signal disturbances. Moreover, the modelling and analysis for PMSG-based wind energy conversion systems are also presented. The response of the primary controller for the active and reactive power sharing is investigated. The analysis emphasizes the demonstration of optimal power-sharing under normal and abnormal conditions for the considered load. Finally, the suggested robust controller's performance is evaluated in MATLAB environment and simulation results show the proposed scheme's superiority under different operating conditions.

This study aims to develop a performance evaluation system that can facilitate performance evaluation at region, hospital, and department levels to enable better cost management for sustainable development. A multi-level system of performance evaluation informs a hierarchical assessment of cost management from regions to hospitals to departments using diagnosis-related group (DRGs). Various metrics are developed employing the variances between targets and actuals where targets are determined from two perspectives: benchmarking using external regional prices and change management using internal data. Targets for the latter are statistically based and specifically incorporate variability. The model is applied to two hospitals, twenty departments, nine DRGs and 1071 inpatients. The analyses indicate that the approach can provide a practical evaluation tool that allows for particular characteristics at multiple levels. The system provides macro-micro and external-internal perspectives in performance, enabling high-level variances to be decomposed thereby identifying sources of performance variability and financial impact.

This research focuses on developing a Student Performance Evaluation System to enhance effectiveness and oversight in higher education. The system aims to address challenges faced by instructors in evaluating student performance using a distributed system approach. Agile methodology is employed in development, and database replication techniques are applied for data synchronization. System features include registration, assessment form creation, assessment submission, statistical visualization, and access to assessment history. The system is designed to improve efficiency and transparency in the assessment process. Key features of the system include registration process, assessment form creation, assessment submission, statistical visualization, and access to assessment history. Its goal is to enhance efficiency and transparency throughout the assessment process. The article details the system workflow and the roles played by Admins, Instructors, and students in system usage. Additionally, it discusses the back-end development model and pathways, as well as the performance testing results. Performance testing indicates that the system achieves high throughput of up to 21.55 requests per second, with an average response time of only 34 milliseconds and an error rate of zero percent. These results affirm that the system efficiently handles user loads and nearly instantaneously responds to requests, providing an optimal user experience in the context of student performance evaluation in higher education.

Establishing systemic communications between the project plan, stakeholders, and the organization through integrated management meets stakeholders' demands and managerial expectations in project-oriented organizations. Performance assessment can be defined as a control system in any company that reviews its daily operations and evaluates how well it has achieved its goals. This study aims to investigate the impact of an integrated project management system on the financial performance of the Organization for Renovation, Development, and Equipment of Schools. This applied research is descriptive-analytical. The statistical population comprises 2,700 employees of the organization, with a sample size of 340 individuals examined. The reliability of the designed questionnaire was confirmed by experts in the organization using Cronbach's alpha (α=0.91). Data were analyzed using SPSS version 20 and AMOS 18 software through descriptive statistics and confirmatory factor analysis. The results indicate that the seven dimensions of the integrated project management system (cost management, quality management and continuous control, change management, systems and information management, human resources management, interaction and communication management, procurement management) have a positive and significant impact on the financial performance of the Organization for Renovation, Development, and Equipment of Schools.

The plant water status is crucial for growth and production, but the current climate change scenario makes it challenging to match the water plant demand. Blueberry is an economically important crop and plays an acknowledged role in human health due to its antioxidant compounds. This research aimed to determine whether exogenous methyl jasmonate application improves the antioxidant defense mechanisms for protecting the photosynthetic performance in blueberry plants under the stress condition of water deficit. A greenhouse experiment was carried out under a 16-h light period; 20ºC; and 60-80% relative humidity for 2 weeks before treatment application of methyl jasmonate (MeJA) to blueberry plants (Vaccinium corymbosum, Brigitta cultivar). The following treatments were maintained for 7-days: (i) 80% field capacity (NoWD); (ii) 80% field capacity plus MeJA application (NoWD + MeJA); (iii) 20% field capacity (WD); and (iv) 20% field capacity plus MeJA application (WD + MeJA). The MeJA was sprayed as an aqueous solution of 10 µM MeJA (Sigma-Aldrich) over the plant's foliar system. At the end of the assay; blueberry leaves were analyzed for the relative water content; specific leaf area; lipid peroxidation; total antioxidant activity; total phenols; total anthocyanins; anthocyanidin compounds and photosynthetic performance. Brigitta cultivar showed a significant decrease in the oxidative stress at leaf levels; with an increase in antioxidant activity; phenolic compounds; total anthocyanins; delphinidin; petunidin; antheraxanthin; zeaxanthin; and an improvement in photosynthetic performance parameters. Blueberry Brigitta cultivar was shown to be susceptible to WD decreased mainly photosynthesis. However; the MeJA application on leaves induced metabolic changes; through an increase of antioxidant strategy within the plant to counteract the negative effects of WD; protecting the photosynthetic apparatus; which allows the Brigitta cultivar to withstand the period of WD.

This paper presents a novel micro-segmented genetic algorithm (μsGA) to identify the best solution for the locomotion of a quadruped robot designed on a rectangular ABS plastic platform. We compare our algorithm with three similar algorithms found in the specialized literature: a standard genetic algorithm (GA), a micro-genetic algorithm (μGA), and a micro artificial immune system (μAIS). The quadruped robot prototype guarantees the same conditions for each test. The platform was developed using 3D printing for the structure and can accommodate the mechanisms, sensors, servomechanisms as actuators. It also has an internal battery and a multicore embedded system (mES) to process and control the robot locomotion. This research proposes a μsGA that segments the individual into specific bytes. μGA techniques are applied to each segment to reduce the processing time; the same benefits as the GA are obtained, while the use of a computer and the high computational resources characteristic of the GA are avoided. This is the reason why some research in robot locomotion is limited to simulation. The results show that the performance of μsGA is better than the three other algorithms (GA, μGA and AIS). The processing time was reduced using a mES architecture that enables parallel processing, meaning that the requirements for resources and memory were reduced. This research solves the problem of continuous locomotion of a quadruped robot, and gives a feasible solution with real performance parameters using a μsGA bio-micro algorithm and a mES architecture.

This research aims to investigate psychological anxiety factors, particularly Music Performance Anxiety (MPA), that influence the sustainability of music learning systems. This study employs an innovative integration of qualitative and quantitative methodologies, marking the first use of a nonlinear system paired with a comprehensive data framework for analyzing questionnaire responses. This approach allows for a detailed examination of the effects of these factors on academic outcomes. Previous research has primarily focused on the fragmented music learning system from the perspective of teachers' instructional strategies, emphasizing phased teaching methods and learning objectives which focus often neglected a significant subset of music learners. Addressing this oversight, the current study specifically centers on the emotional aspects of anxiety within music learning systems, with a particular emphasis on students, who play a crucial role in music education. This perspective enables a deep exploration of how MPA and other related emotional factors affect music learning systems. A notable innovation of this research is the development of a stochastic nonlinear system designed to model the psychological factors impacting student music learning, complemented by a quantitative model that assesses actual learning outcomes. By analyzing this nonlinear system, the research identifies weight values for various negative emotions, particularly those related to MPA, that significantly influence the music learning process. The integration of MPA and other anxiety related emotional factors with practical learning outcomes provides a comprehensive understanding of their combined impact on the music learning system. These insights are invaluable for educators and policymakers aiming to enhance both the effectiveness and emotional well-being within music education. This comprehensive approach offers a novel perspective in understanding and improving the dynamics of music education through a more empathetic and scientifically grounded lens.

Battery Management System helps to improve the transient performance and life of electro-chemical rechargeable batteries like a Li-ion, lead–acid, etc. The investigation here was focused on the crucial part of the Battery Management System that is, Cell balancing, State of charge of the battery, etc. By analyzing the different control strategies a new optimal control strategy is developed to improve the battery performance according to application. The Control strategy is developed using an active and passive cell balancing model with the help of AVL Cruise and MATLAB/SIMULINK software. For the active cell balancing technique, a switched capacitor technique is chosen. To have longer battery life, the time required for the cell balancing must be as low as possible for which many control logics have been defined. The effect of these cell balancing techniques on the performance of battery packs is investigated and it is observed to produce a promising result.

The amount of solar energy produced is directly proportional to the surface area of solar panels exposed to sun rays. To increase the productivity of solar panels, a number of techniques are proposed by curving the surface or protruding the panel surface to maximise the surface area, e.g. Protruding panel surfaces with shapes such as pyramidal, cone, spherical cap, sinusoidal wavy curve, etc. These techniques are analysed to determine whether the panel surface area increases. The geometrical design analysis showed that, depending on the chosen surface curving method, the panel can achieve a remarkable increase in surface area.The system advisor model was used to assess a sample of solar cells with standard measurements of 6 by 6 inches that were organised in a zigzag pattern with different angles of inclination (10°, 15°, 20°, 25°, 30°, and 35°). Overall, the maximum power pump and annual AC energy performance increase by 1.4%, 4.2%, 6.8%, 10.8%, 14.9%, and 21.6%, respectively, over a one-year period of productivity. However, by applying the concept of solar panel efficiency degradation due to tilting solar panels at an angle by Mamun et al. (2022), for each 5° increase in tilt angle beyond the ideal 10°, the efficiency decreases by approximately 0.76%. In conclusion, the overall efficiency is greater than that of standard flat solar panels, provided the tilt angle is within a reasonable range.

Fall detection systems play a crucial role in addressing the significant health concern of elderly falls, a leading cause of health deterioration and mortality. As the aging population grows and life expectancy increases, the development of accessible tools becomes vital for predicting and preventing falls, offering a practical and widely applicable solution in contrast to costly and expertise-dependent assessment tools. In contrast, due to the formidable challenges encountered, a comprehensive investigation into the comparative performance of standard ML models within this field still needs to be explored. This paper proposes a standard pipeline for pre-processing, training, and evaluating ML models for fall detection on the SisFall dataset. We conducted extensive experiments to evaluate the performance of various ML models for fall detection. The results validate the efficiency of the deep model in identifying the time windows in which a fall occurred. Among the deep models, the architecture, including a combination of convolutional neural networks and fully connected layers, outperforms the others by macro-averaged Precision, macro-averaged Recall, and macro-averaged F1-Score of 87.03\%, 86.83\%, and 86.93\%, respectively.

This article deals with the denoising of signals from sensors (current and voltage) in a photovoltaic conversion chain using wavelet theory. The idea is to reduce the noise as much as possible without distorting or losing the original signal information. To see the reliability of this proposed method, a comparative study between our proposed method (WDD) and the classic low-pass filter method was presented. The contribution in this work is the improvement of the DC-DC boost converter via the use of wavelet theory, however, that’s why we set two objectives: the first is to obtain reliable control of the DC-DC boost converter via the proposed WDD and the second to increase the overall system efficiency. The experimental results show a very great improvement in the quality of the signals of the proposed method compared to the classic method of filtering by low-pass filter.

Everyone should therefore consistently get access to enough and safe water. The operation of the existing distribution network as well as the proper optimization and implementation of the new distribution systems are required for a sufficient and safe water supply. In Sekota town sufficient amount of water was not reached to the beneficiaries due to shortage of water at the source. The primary goal of this study was to evaluate the performance and optimize the existing Sekota water supply distribution system using Bentley Water GEMS.The system's hydraulic modeling is carried out by considering as a continuous supply system, and the evaluation procedure used the extended period simulation approach after calibration was done. Calibration is used to ensure the performance of the model using the observed pressure values. The output of the existing system shows pressure is very high means above the maximum pressure and velocity is very low at peak hour demand. The results of velocity and pressure before optimization have negative effect on the performance of the system. The number of pipes and junctions their velocities and pressures which were in admissible ranges are 15 and 42 pipes for velocities and zero and 59 junctions for pressure before and after optimization were evaluated respectively.

Phase change materials (PCMs) have emerged as promising solutions for latent heat thermal energy storage (LHTES) systems, offering considerable potential for storing energy derived from renewable sources across various engineering applications. The present study focused on optimization of solar cooling system by integrating LHTES with different PCM tank configuration. TRNSYS simulation software was selected for the study and collected experimental data from laboratory system prototype was used for system validation. The results indicate that the use of PCM led to a noteworthy decrease of 6.2% in auxiliary energy consumption. Furthermore, the duration during which the heat carrier temperature flow exceeded 90°C from the storage tank to the auxiliary heater was extended by 27.8% when PCM was utilized, compared to its absence. The use of PCM in LHTES is more effective under variable weather conditions. On the day when changes in weather conditions were observed, around 98% of the cooling load was provided by produced sun energy. The results of the research can be used to optimize the solar cooling system, which will help reduce the environmental impact of cooling systems running on non-renewable fuels.

6G is already being planned and will employ much higher frequencies, leading to a revolutionary era in communication between people as well as things. It is well known that weather, especially rain, can cause increased attenuation of signal transmission for higher frequencies. The standard methods for evaluating the effect of rain on symbol error rate are based on long-term averaging. These methods are an inaccurate, which results with an inefficient system design. This is critical regarding bandwidth scarcity and energy consumption and requires a more significant margin of effort to cope with the imprecision. Recently we have developed a new and more precise method for calculating communication system performance in case of rain, using the probability density function of rain rate. For high rain rate (above 10mm/hr), for a typical set of parameters, our method shows the symbol error rate in this range to be higher by orders of magnitude than that found by ITU standard methods. Our model also indicates that sensing and measuring the rain rate probability is important in order to provide the required bit error rate to the users. To the best knowledge of the authors, this novel analysis is unique. It can constitute a more effi-cient performance metric for the new era of 6G communication and prevent disruption due to incorrect system design. Keywords: atmospheric propagation, communication system performance, attenuation, com-munication

Recently, the phase-sensitive OTDR (Φ-OTDR) based vibration sensor system has gained the focus of many researchers and some efforts have been undertaken to push further the limitations imposed on the performance of the Φ-OTDR sensor system. Then, progress in the different areas of its performance evaluation factors such as: improvement of the signal-to-noise ratio (SNR), spatial resolution (SR) in the sub-meter range, enlargement of the sensing range, frequency response bandwidth over the conventional limit and phase signal demodulation for quantitative measurement have been realized. This paper presents an overview of the recent progress in the Φ-OTDR based vibration sensing system in the different areas mentioned above.

Environmental regulation has dual effects on water resource utilization performance through various channels such as the "three red lines" and the "Porter hypothesis". Based on the detailed analysis of the impact path of environmental regulation on water resource utilization performance, the two-step system GMM method was adopted to test the dual effects of environmental regulation on water resource utilization performance by using panel data of 30 provinces and cities from 2004 to 2020. The results show that: (1) Environmental regulation has a significant direct impact on water resource utilization performance, and is currently in the stage of positive relationship of an inverted u-shaped relationship. (2) Environmental regulation has a significant indirect impact on water resource utilization Environmental regulation has dual effects on water resource utilization performance through various channels such as the "three-red lines" and the "Porter hypothesis". In accordance with a detailed examination of the influence path of environmental regulation on the performance of water resource utilization, the double effects of environmental regulation on water resource utilization performance were examined using panel statistics from 30 provinces and cities from 2004 to 2020 using the two-step system GMM approach. The results demonstrate that: (1) Environmental regulation has a direct effect on water resource utilization performance which is currently in the stage of the positive relationship of an inverted u-shaped relationship. (2) The influence of environmental regulation on water resource utilization performance through government intervention and industrial structure adjustment is indirect, among which government intervention can significantly improve water resource utilization performance, while the growth of the tertiary industry as a percentage can lower water resource utilization performance. (3) Both direct and indirect impacts indicate that enhancing the efficiency of the use of water resources is sustainable, and the water resource utilization performance of the preceding period had a major positive impact over the present phase. Therefore, the paper sets out a few policy suggestions, such as choosing reasonable environmental regulation tools, actively guiding the market-oriented reform with constraints, and upgrading the industrial structure in a green way.

Wireless Sensor Networks (WSN) is the network of the resource-constrained network which forms the foundation of the Internet of Things (IoT). The Routing Protocol for Low-power and Lossy Networks (RPL) is responsible for generating and managing data routing paths. Nodes implementing RPL uses the mechanics of Objective Function (OF) to select the preferred next-hop node – parent node, and optimal routing path to the destination node. If routing decisions are not efficiently made, this results in increased collision domain, leading to packet losses and packet retransmission which impairs the network operational lifetime. In this study, we present the Contiki Operating System (OS), a state-of-the-art OS for IoTs, ContikiRPL; Contiki variant of RPL. We investigated the performance of RPL with respect to its two OFs; Objective Function Zero (OF0) and the Minimum Rank with Hysteresis Objective Function (MRHOF). The performance of these OFs was evaluated on the following metrics; Packet Delivery Ratio (PDR), Power consumption, and network latency. The result shows that MRHOF outperformed OF0 on all metrics with an overall average PDR of 91.5%, a latency of 44ms, and power consumption of 1.72mW across all nodes. This results in optimal network performance with improved network operational lifetime.

This study investigates the implementation and performance benefits of using a MongoDB replica set compared to a single node setup. The primary objective was to evaluate the efficiency and reliability improvements provided by replication in a NoSQL database cluster. The research involved configuring a single node and a three-node replica set, followed by conducting performance tests using CRUD operations on both setups. The results indicated that while the single node exhibited faster write operations, the replica set significantly improved read performance and provided high availability and fault tolerance. The findings highlight the advantages of using a replica set for applications requiring robust data access and consistent performance under varying workloads.

Software-defined networking (SDN) divides a traditional network into a programmable data plane and a centralized control plane. This technology is expected to transform traditional network companies that provide flexible and intelligent network operations. The core component utilized to oversee every data plane action is the controller in the control plane. In order to achieve optimal performances, the controller’s performance and capabilities are therefore crucial. There are lots of controller research available in existing literature. Nevertheless, no qualitative comparison study of OpenFlow-enabled distributed but logically centralized controllers exists for them. This article also includes a quantitative investigation of the performance of several distributed but logically centralized SDN controllers in custom network scenarios using Mininet, as well as a thorough qualitative comparison of them. More precisely, we give a qualitative evaluation of their attributes and classify and categorize 13 distributed but logically centralized SDN controllers according to their capabilities. Additionally, we offer a comprehensive SDN emulation tool called Mininet-based SDN controller performance assessment in this study. Using six performance metrics—bandwidth, round- trip time, delay, jitter, packet loss, and throughput—this work also assesses five distributed but logically centralized controllers against two custom network scenarios (uniform and non-uniform host distribution). Our investigation shows that the OpenDayLight controller performs the best across all performance criteria, with the exception of delay, packet loss and round trip time, where the Ryu controller excels. In the entire experiment, the HyperFlow and ONOS controller performs the worst in terms of all performance metrics. Finally, we discuss detailed research findings on the performance. These experimental results provide a decision-making guideline when selecting a controller.

Monitoring of the surface operations using movement and surveying radar (MSR) can prevent loss of life, equipment, production and loss of the mine. Slope monitoring using MSR is an important aspect of open-pit mining as it provides real-time movement of deformation data for the slope. It is therefore important that the radar is accurately geo-referenced in order to provide accurate real-time movement data. Geo-referencing is defined as the process of determining an instrument’s position (in the form of Easting, Northing, Height) as well as the orientation with respect to the mine’s local coordinate system. This helps in getting geo-referenced data points from the radar that are identified by a unique set of coordinates in relation to the mine’s coordinate system which allows the radar to track movement for a specific set of coordinates. In this research, we assess the performance of geo-referencing a radar using the total station method and compare it with the integration of Advance Navigation – Spatial Dual GPS system connected via RS422 on the MSR. This includes usage of the Spatial Dual navigation coordinates output to calculate the radar’s position relative to the mine local coordinates and mapping the radar’s azimuth, elevation and Range (Az, El and Rl) values to the measured pit-slope data points. Furthermore, a comparison of key attributes of both methods of geo-referencing is performed using a matrix system and giving an overall performance appraisal of both systems. Integrating a navigation system allows the radar to have an auto geo-referencing functionality that will reduce the time spent in completing this process. The findings reveal that the GPS obtained a higher score than the total station with prism method on the weighted matrix system. The total station was found to be more accurate than the GPS however, the deployment time for the GPS is quicker than that of the total station. This is important for different operation such as strip and open-pit mining to choose the preferred method of geo-referencing depending on the level of accuracy required.

Enhancing energy efficiency within the building sector is imperative to curbing energy losses, given that this sector alone contributes to over 34% of global energy consumption. Employing a building management system, along with its regular updates, presents a strategic avenue to decrease energy usage, enhance building energy efficiency, and more. Tailored control strategies, aligned with the unique characteristics and usage patterns of each building, are essential for achieving energy savings. This article presents an evaluation of HVAC system efficiency in office buildings, utilizing a data-driven approach coupled with simulations conducted in IDA ICE software. The research explores the control strategy of an office building equipped with a constant air volume HVAC system, featuring a regularly controlled air handling unit. The objective is to boost energy efficiency while striking a balance between occupant comfort and energy consumption. Findings indicate that by analyzing measured data and adjusting configurable parameters, building energy consumption can be significantly reduced. Close monitoring of indoor parameters by building operators and corresponding adjustments to the HVAC system can yield energy savings of up to 16%. Leveraging these insights, the paper suggests integrating data-driven and dynamic simulation methods into building management system models to optimize HVAC systems, enhance energy efficiency, and advance ambitious carbon neutrality objectives.

This research focuses on developing a Student Performance Evaluation System to enhance effectiveness and oversight in higher education. The system aims to address challenges faced by instructors in evaluating student performance using a distributed system approach. Agile methodology is employed in development, and database replication techniques are applied for data synchronization. System features include registration, assessment form creation, assessment submission, statistical visualization, and access to assessment history. The system is designed to improve efficiency and transparency in the assessment process. Key features of the system include registration process, assessment form creation, assessment submission, statistical visualization, and access to assessment history. Its goal is to enhance efficiency and transparency throughout the assessment process. The article details the system workflow and the roles played by Admins, Instructors, and students in system usage. Additionally, it discusses the back-end development model and pathways, as well as the performance testing results. Performance testing indicates that the system achieves high throughput of up to 21.55 requests per second, with an average response time of only 34 milliseconds and an error rate of zero percent. These results affirm that the system efficiently handles user loads and nearly instantaneously responds to requests, providing an optimal user experience in the context of student performance evaluation in higher education.

Ghana, blessed with abundant solar resources and has strategically invested in solar photovoltaic (PV) technologies to diversify its energy mix and reduce the environmental impacts of traditional energy technologies. The 50 MW solar PV installation by the Bui Power Authority exemplifies the nation's dedication to utilizing clean energy for sustainable growth. This study seeks to close the knowledge gap by providing a detailed analysis of the system's performance under different weather conditions, particularly on days with abundant sunshine and those with cloudy skies. The research consists of one-year monitoring data of the climatic and AC energy output fed into the grid. This data was used to analyze PV performance on each month's sunniest and cloudiest days. The results show that the total amount of AC energy output fed into the grid each month on the sunniest day varies between 229.3 MWh in December and 278.0 MWh in November, while the total amount of AC energy output fed into the grid each month on the cloudiest day varies between16.1 MWh in August and 192.8 MWh in February. Also, the percentage variation in energy produced between the sunniest and cloudiest days within a month ranges from 16.9% (December) to 94.1% (August). The reference and system yield analysis showed that the PV plant has a high conversion efficiency of 91.3%; however, only the sunniest and overcast days had an efficiency of 38% and 92%, respectively. The BPA plant's performance can be enhanced by using this analysis to identify erratic power generation on sunny days and schedule timely maintenance to keep the plant's performance from deteriorating. Optimizing a solar PV system's design, installation, and operation can significantly improve its AC energy output, performance ratio, and capacity factor on sunny and cloudy days.

The combination of different wood modification technologies to obtain improved performance is increasingly receiving attention in research. In this study, Scots Pine (Pinus sylvestris) sapwood was impregnated with furfuryl alcohol (FFA) in pure aqueous 20, 40 and 60% solution strength without adding any catalyst. In a second step, the FFA was polymerized while simultaneously performing thermal modification in a closed system at 130, 150 or 180 °C. After leaching and ageing tests, the 9 different combinations were tested for use class 4 applications according to CEN/TS 15083-2 (2005) decay lab test. It was noted that even the minimum intensity combination of 20% FFA at 130 °C resulted in maximum durability class (DC) 1 performance. On the contrary, DC 4 was assigned to thermally modified control samples, even at the maximum intensity of thermal modification. Similarly, for FFA modifications, previous research has suggested that an uptake of 35% solution strength is required to obtain an adequate durability performance for use class 4 applications. High levels of resistance against termites were also noted by corresponding termite lab tests. Moisture studies showed the combined treatments resulted in improved stability and reduced moisture uptakes. Thus, the results obtained by this study revealed synergistic performance effects which originate from the combined thermo-chemical modification approach and which were higher than simple accumulation of the individual performance of purely thermally or chemically modified wood. Thus, the presented findings have provided positive implications for industrial applications of thermo-chemical modification techniques and offers an array of new research opportunities.

In this paper, we present a novel approach for managing the file system in Linux using a voice assistant. Our system allows users to perform file system operations such as creating directories, renaming files, and deleting files by issuing voice commands. We develop a voice assistant using Python libraries and integrate it with the file system in Linux. The voice assistant is capable of understanding natural language and executing commands based on the user's voice inputs. We conduct experiments to evaluate the performance of the system and demonstrate that our approach is effective and efficient in managing the file system using voice commands. Our system can enhance the accessibility and usability of the file system in Linux for individuals with disabilities or those who prefer a hands-free approach to file management.

Structural systems in housing projects contribute to the energy consumption of buildings during and after construction, and the climate plays a significant role in this energy consumption. Housing projects in harsh environments such in the United Arab Emirates (UAE) directly contribute to energy performance, specifically in low-density residential areas. By selecting the most efficient structural system, prior construction can enhance energy performance in such housing projects. The present study investigates the energy performance of three different structural systems used in UAE national housing: precast concrete, reinforced concrete, and light gauge steel (LGS). The case studies used for this study were constructed in Abu Dhabi, the capital of the UAE, specifically in Alain city. Second, through qualitative analysis and average annual billing of each housing project, the study identifies the thermal defects and determines the electricity consumptions of each system. The results indicate that the LGS system provides high thermal conductivity through its structural elements whereas reinforced concrete leads to the highest annual energy consumption in kW h/m². Finally, precast concrete has few thermal defects in its junctions and structural elements. The results indicate that LGS and reinforced concrete should be further studied, especially with regard to insulation and improvement, prior to implementation in housing systems.

There are ~200.000 households living in the detached houses and ger (yurt) with the small-coal stove which burns a raw coal in the Ulaanbaatar city. The proper heating system and improvement on the energy efficiency of residential dwellings is vital important for Ulaanbaatar city to reduce an air pollution as well as for the operation of current central energy system. This study shows the experimental results of two Gers with two different heating system and different thermal insulation. Technical availability of the system consisting of ETS heater with daytime charging schedule and areal PV system is also examined by using a simulation of MATLAB programming. As a result of the experiment, the indoor comfort level and energy efficiency of the Ger with added insulation and ETS heater with nighttime charging was enhanced to compare with the reference Ger. The Ger with added insulation and ETS heater consumed 3169 kWh for electric appliances and 5989 kWh for the heating season. The simulation was resulted that the ETS heater to be installed in the Ger 2 had prospected to increase the PV self-consumption rate by 76% because of the daytime charging schedule of ETS heater. The PV system supplied 31% of the total energy consumption with remained 69% of the main grid.

The current emphasis in the advancement of space-based synthetic aperture radar (SAR) is on lightweight payloads under 100kg with resolutions surpassing 1m. This focus is directed towards meeting the launch criteria for multiple satellites on a single rocket and cutting costs. This article discusses the creation and progress of a Ku-band SAR payload for the Taijing-4(03) Satellite, launched on January 23, 2024 accompanied by four other satellites. The SAR payload design was customized to meet the demands of a micro-nano satellite platform, resulting in a lightweight, flat design weighing less than 80kg, seamlessly integrated with the plate-shaped satellite platform. The article also introduces a beam optimization strategy for the phased array SAR antenna, significantly boosting the SAR system’s performance. The SAR payload provides various operating modes like slide-spot, strip, scan 1, scan 2, and others, with a maximum achievable resolution exceeding 1m. Extensive in-orbit testing of the payload produced numerous high-quality SAR images with potential uses in emergency disaster mitigation, safeguarding ecosystems, monitoring forests, managing crops, tracking sea ice, and more.

The present study is to address performance of the dairy supply chain and emphasizes the significance of reliability of the chain as a fundamental and critical attribute for fulfilling the safety requirements. In order to evaluate the performance of the dairy supply chain, the present study utilizes the reliability attribute, which is an essential and informative system performance indicator. The study considers not only the inputs and outputs but also internal activities and relationships between customers, manufacturers, and suppliers. To minimize calculations and resolve uncertainties and vagueness that may be experienced in the performance evaluation process, this study proposes the use of the Fuzzy Inference System (FIS) approach and evaluates the reliability at each level of the supply chain: supply, manufacturing, and distribution. Combining the reliability of different levels, the study finally calculates the reliability of the entire supply chain. The proposed methodology offers a practical approach for evaluating the reliability performance of a dairy supply chain and can be easily extended to other industries as well. To verify the proposed methodology, a real case in the Iranian dairy industry is chosen to be studied. Results indicate that the proposed methodology can effectively identify bottlenecks or weaknesses in the dairy supply chain and help develop effective strategies to address them. Analyzing factors influencing supply chain reliability can optimize operations, reduce costs, and improve the overall quality of dairy product quality delivered to consumers.

Corporate governance is widely suggested by economists and regulators as a solution to reduce agency problems and improve firm performance. However previous studies have failed to generate consistent results. Using a dynamic panel system GMM estimator to alleviate endogeneity concerns we determine the effect of corporate board structure on the performance of a panel of 1265 Chinese firms listed on the Shanghai and Shenzhen stock exchanges from 2010 to 2016. We compare the dynamic system GMM estimator to some commonly used estimators; ordinary least squares (OLS), fixed effects (FE) and the dynamic OLS, and show that these estimates are biased due to endogeneity. The dynamic system GMM estimator incorporates the dynamic nature of internal governance choices to provide valid and powerful instruments that address unobserved heterogeneity and simultaneity. Our results show support for the board model corporate governance mechanism. We find that board size is positive and significantly related to both return on assets and total net profit margin. In addition board independence is positive and significantly related to return on assets but insignificantly related to total net profit margin. Duality was found to have a negative but statistically insignificant relation with firm performance.

The present article is dealing with the state of question about building-energy monitoring systems used for data collection to estimate the Heat Lost Coefficient (HLC) with existing methods and so determinate buildings’ Envelope Energy Performance (EEP). In addition, the data requirements of HLC estimation methods are related with commonly used methods for fault detection, calibration and supervision of energy monitoring systems in buildings. Based on an extended review of experimental tests since 1978, a qualitative and quantitative analysis of Monitoring and Controlling System (MCS) specifications has been carried out. Although most actual Buildings Automation Systems (BAS) may measure the required parameters, further research is still needed to ensure that these data are accurate enough to rigorously apply the HLC estimation methods.

The review scrutinizes the currently performed research on the new methods for enhancing bituminous binder performance through radiation and radical grafting of polymer modifers of bitumen. It investigates innovative methods, including using waste polymers as modifiers, and applying radiation for polymer grafting, to overcome challenges like high costs, low aging resistance and storage stability issues, of which separation of phases polymer/bitumen is the most significant obstacle. These advanced modification techniques promise sustainability through the decrease of the carbon footprint of transportation systems by improving the properties and durability of binders. Additionally, the review discusses the parameters and mechanistic aspects from a scientific perspective, shedding light on the underlying processes that contribute to the improved performance of modified bituminous binders.

Aquifer Thermal Energy Storage (ATES) systems are garnering attention as high-efficiency air conditioning technologies that contribute to the realization of a carbon-neutral society. This study focuses on an ATES system constructed in Japan, characterized by its complex geological conditions and thin aquifer layers. Through performance analysis using four years of operational data, we achieved a Coefficient of Performance (COP) of 5 on the building load side. This paper confirms the equivalence of the dimensionless production temperature and heat recovery rate, observing nearly identical changes in the dimensionless production temperature over four cycles (eight seasons). Furthermore, we propose an operational method for the following fiscal year that maintains the balance between accumulated storage quantity and pumping volume, based on predictions from this plant's operational pattern.

Glacial meltwater has been lifeline of agriculture in Gilgit-Baltistan for centuries which is being effected by the climatic changes and associated challenges. The government line institutions and development agencies have been investing to sustain and further extend the cultivated areas by leveraging the available glacial meltwater source. However, approximately 13% arable land, laying mainly along river banks, has limited access to glacial meltwater. Moreover, already cultivated areas also need alternate and sustainable irrigation water supplies to insurefood security. Hence, there is need to explore more potential options to address these challenges and bringing arable land under irrigation for regional prosperity and environmental gains. The International Centre for Integrated Mountain Development (ICIMOD) and its partners piloted solutions for aforementioned issues in Gojal, District Hunza. These solutions included river water lifting through solar and Hydraulic Ram Pumps, uphill water storages and application through drip irrigation systems. In order to assess the technical and economical viabilities of these piloted systems, a semi-structured questionnaire survey, field observation visits to collect data and economic assessment studies were carried out in Morkhun and Khyber. Both piloted systems have been proven as climate resilient, adaptable, environment friendly and economically viable. The cost to benefit ratio for solar powered drip irrigation and Hydraulic Ram Pump drip irrigation systems are 2.96 and 4.21 respectively, with payback period of 9.21 and 8.25 years respectively. The drip irrigation systems at Khyber and Morkhun sites have exhibited excellent hydraulic performance with Coefficient of Uniformity 92.61 and 93 % respectively. However, the field application efficiency of drip irrigation systems estimated for Khyber and Morkhun sites are 85.24 and 88.88% which are lower than the optimal value mainly due to lesser water holding capacity. The Hydraulic Ram Pump can lift four times more water to greater height, while comparing to solar pump of approximately similar capacity and higher capital costs. Both water lifting systems have some limitations and requires local customization for sustainable use.

A significant electromotive force is induced in the rotor circuit of a doubly fed induction generator (DFIG) due to its high vulnerability to grid faults. Therefore, the system performance must be increased with appropriate control actions that can successfully offset such abnormalities in order to provide consistent and stable operations during grid disturbances. In this regard, this paper presents a solution based on a combination of an energy storage-based crowbar and a rotor-side crowbar that makes the effective transient current and voltage suppression for wind-driven DFIG possible. The core of the solution is its ability to restrict the transient rotor and stator overcurrents and DC-link overvoltages within their prescribed limits, aiming to protect the DFIG and power converters, and consequently, improve the system’ ability to ride-through faults. Further, the capacity of an energy storage device for transient suppression is estimated. Finally, simulation results show that the proposed approach is effective in achieving transient control objectives precisely and maintaining a stable grid connection during the faults.

Automatic Milking Systems (AMS) are revolutionizing the dairy industry by boosting herd effi-ciency, primarily through increased milk yield per cow and reduced labor costs. The performance of milking machines, whether traditional or automated, can be evaluated using advanced vacuum meters through dynamic testing. This process involves scrutinizing the system and milking rou-tine to identify critical points, utilizing the VaDia™ logger (BioControl AS, Rakkestad, NO). Vacuum recordings were downloaded and analyzed using the VaDia Suite™ software under the guidance of a milking specialist. Access to data from AMS across various manufacturers and herds facilitated a retrospective study aimed at describing and comparing key milk emission parameters for different AMS brands while identifying potential mastitis risk factors. Using proper statistical procedures of SPSS 29.1 (IBM Corp, USA), researchers analyzed data from 4,878 individual quarter milkings from cows in 48 dairy herds. Results indicated significant variability in milking pa-rameters associated to quarter milk yield and AMS brand. Notably, despite AMS standardizing teat preparation and stimulation, the study revealed a surprisingly high frequency of two major mastitis risk factors—bimodality and irregular vacuum fluctuations—occurring more frequently than in conventional milking systems. This study, one of the few comparing different AMS brands and their performance, highlights the crucial role of dynamic testing in evaluating AMS perfor-mance under real-world conditions.

A significant replacement for numerous fossil fuels is solar energy as the main type of renewable energy resource. However, solar cells need battery energy storage units to handle the intermittent and uncontrollable nature of solar energy. In this light, there is a significant market for small, portable battery charge controllers that automate battery charging. However, the issue of slow charging and premature battery life loss plagues current industry-standard or innovative battery technology. This study proposes a quick pulse charging technique that stops battery deterioration and minimizes the overall charging period. The primary goal of this study is to develop, construct, and execution of a practical, versatile, and compact photovoltaic charge controller at cut rates. The suggested charge controller can disconnect and reconnect the battery during battery overcharging and deep discharging conditions using sensors with relays. The laboratory model is tested using a less expensive PV panel, battery, and DSP controller. The charging behavior of the solar-powered PWM charge controller is studied compared to that of the Constant Voltage - Constant Current (CV-CC) method. The proposed method is pertinent for minimizing energy issues in impoverished placesat a reasonable price.

The conventional method used for calculating pavement condition index (PCI) has two major drawbacks: safety problems during pavement inspection, and human error. This paper proposes a method for removing these problems. The proposed method uses surface deflection data in falling weight Deflectometer test to estimate PCI. The data used in this study were derived from 236 pavement segments taken from Tehran-Qom freeway in Iran. The data set was analyzed using multi layers perceptron (MLP) and radial basis function (RBF) neural networks. These neural networks were optimized by levenberg-marquardt (MLP-LM), scaled conjugate gradient (MLP-SCG), imperialist competitive (RBF-ICA), and genetic (RBF-GA) algorithms. After initial modeling with four neural networks mentioned, the committee machine intelligent systems (CMIS) method was adopted to combine the results and improve the accuracy of the modeling. The results of analysis have been verified by the four criteria of average percent relative error (APRE), average absolute percent relative error (AAPRE), root mean square error (RMSE) and standard error (SD). The best reported results belonged to CMIS, including APRE=2.3303, AAPRE=11.6768, RMSE=12.0056, and SD=0.0210.

The potential impact of a specific physical activity program on biomechanical gait parameters and neuromuscular strategies around the ankle joint in older adults with sarcopenic obesity (SO) remains largely unexplored. The objective of this study was to investigate the effectiveness of a 24-week Posture, Strengthening, and Motricity (PSM) program in improving neuromuscular strategies and biomechanical gait parameters in older adults with SO. 40 Participants were randomly assigned to either the trained group (TG) and the control group (CG). Only the TG received the PSM program. Standardized evaluations were performed before and after the intervention, including walking tests on an instrumented gait analysis treadmill to evaluate biomechanical gait parameters and EMG activity of ankle muscles. After the PSM program, TG exhibited an increase in comfortable walking speed (+80%, p<0.001) and step length (+38%, p<0.05). Moreover, TG demonstrated a reduction in CoP velocity (-26%, p<0.01). These gait modifications were associated with a decreased muscle activity during the different gait phases (p<0.05). The PSM program effectively improved gait, and neuromuscular capacities in older adults with SO. Notably, Results sheds light on the remarkable trainability of neuromuscular capacities in older adults with SO, despite the adverse effects of aging and obesity.

The link between the world of communication and the world of racing is provided by telemetry systems in electric racing cars. These systems send real-time data about the vehicle’s behavior and systems to enable informed decisions during the race. The aim of this research was to integrate telemetry into the battery bank of a racing electric vehicle to find the optimal values of current and voltage that optimize the charging process, thus improving the vehicle’s performance in competition using Response Surface Analysis. Particularly, the telemetry system consisted of an Arduino Mega, a digital wattmeter, and temperature sensors, all installed in the vehicle. Once the telemetry data was obtained, a response surface design was adapted with current, voltage, and temperature as factors, varying from low to high values, with the objective function being to minimize the battery’s charging time. Applying the response surface methodology and the steepest descent algorithm, it was found that all factors significantly affect the charging time, with the minimum charge time being 6961 seconds, obtained with a current of 2.4 amps and voltages of 50.5 volts and 43.6 volts.

The paper aims to study the workflow of the detection center of stealthy attacks on industrial installations that generate increase in energy consumption while avoiding triggering fault detection and damaging the installation. Such long-lasting attacks on industrial facilities make production more expensive and less competitive. We present the concept of the remote detection system of cyberattacks directed at maliciously changing the controlled variable in an industrial process air conditioning system. The monitored signals are gathered at the PLC-controlled installation and sent to the remote detection system, where the discrepancies of signals are analyzed based on the Control Performance Assessment indices. The results of performed tests prove the legitimacy of the adopted approach.

The purpose of this study is to improve the performance of walls under out-of-plane loads, particularly when subjected to the hammering action of the floors. The idea behind the paper is to provide the masonry walls with a device that behaves like a buttress, without having to build a traditional buttress. The solution presented here consists of a mechanical coupling between the three-dimensional net of steel ribbons of the CAM system and the CFRP strips. Since the steel ribbons of the CAM system have a pre-tension, the mechanical coupling allows the steel ribbons to establish a semi-rigid transverse link between the CFRP strips bonded on two opposite sides of a wall. Therefore, two vertical CFRP strips tied by the steel ribbons behave like the flanges of an I-beam and the flexural strength of the ideal I-beam counteracts the out-of-plane displacements of the wall. The experimental results showed that the combined technique inherits the strong points of both constituent techniques: the delamination load is comparable to that of the specimens reinforced with the CFRP strips and the overall behavior is ductile as for the specimens reinforced with the CAM system. They also allowed us to design a more performing combined technique.

In this study, the resource blocks (RB) are allocated to user equipment (UE) according to the evolutional algorithms for long term evolution (LTE) systems. Particle Swarm Optimization (PSO) algorithm is one of the evolutionary algorithms, based on the imitation of a flock of birds foraging behavior through learning and grouping the best experience. In previous work, the Simple Particle Swarm Optimization (SPSO) algorithm was proposed for RB allocation to enhance the throughput of Device-to-Device (D2D) communications and improve the system capacity performance. In simulation results, with less population size of M = 10, the SPSO can perform quickly convergence to sub-optimal solution in the 100^th generation and obtained sub-optimum performance with more 2 UEs than the Rand method. Genetic algorithm (GA) is one of the evolutionary algorithms, based on Darwinian models of natural selection and evolution. Therefore, we further proposed a Refined PSO (RPSO) and a novel GA to enhance the throughput of UEs and to improve the system capacity performance. Simulation results show that the proposed GA with 100 populations, in 200 generations can converge to suboptimal solutions. Therefore, with comparing with the SPSO algorithm the proposed GA and RPSO can improve system capacity performance with 1.8 and 0.4 UEs, respectively.

The solar water heater must be integrated into future residential buildings as the main energy source, which will subsequently reduce the energy cost of water heating. An original configuration for efficient Domestic Hot Water "DHW" storage tank is developed and experimentally evaluated under Saharan climate. This novel DHW configuration includes a hybrid (solar and electric) energy system with a flat plate solar collector coupled with an electric heater. Additionally, phase change material "PCM" mixture that is composed of paraffin wax and animal fat with a melting temperature between 35.58°C and 62.58°C and latent heat between 180 and 210 kJ/kg is integrated into this novel tank configuration. The experimental results indicated that hot water production by using latent heat storage could be economically attractive. In this proposed configuration, one liter of hot water may cost around 0.1362 DZD/liter (i.e., 0.00096 US$/liter) compared to 0.4431 DZD/liter for the conventional water heater, an average energy cost savings of 69.26%. On a yearly basis, the average energy cost savings may reach up to 80.25% if optimal tilt for the solar collector is adopted on a monthly basis. The flat plate collector may be vulnerable to convective heat transfer, and therefore, other solar collectors such as vacuum tube collectors may provide enhanced energy performance.

The hybrid personal cooling system (HPCS) consisted of ventilation fans and phase change materials (PCMs) covered with insulation pads is a promising wearable cooling system to mitigate heat strain and heat-related illnesses of occupational workers with heavy labor in hot environments. Effects of clothing characteristics (e.g., thermal resistance of insulation pads, latent heat and melting temperature of PCMs) on the thermal performance of the HPCS have been investigated in detail in our previous study. Apart from the aforementioned factors, environmental conditions, i.e., environmental temperature and relative humidity, also significantly affect the thermal performance of the HPCS. In this paper, a numerical parametric study was performed to investigate the effects of the environmental temperature and relative humidity (RH) on the thermal management of the HPCS. Five levels of air temperature under environmental RH=50% were chosen (i.e., 32, 34, 36, 38 and 40 ºC) to study the impact of environmental temperature on the HPCS’s cooling performance. In addition, four levels of environmental RH at ambient temperatures of 36 and 40 ºC were selected (i.e., 30, 50, 70 and 90%) to examine the effect of RH on cooling performance of the HPCS. Results show that high environmental temperatures could accelerate the PCM melting process and thereby weaken the cooling performance of HPCS. In the moderately hot environment (36 °C), the HPCS presented good cooling performance with the maximum core temperature at around 37.5 °C during excise when the ambient RH≤70%, whereas good cooling performance could be only seen under RH≤50% in the extremely hot environment (40 °C). Thus, it may be concluded that the maximum environmental RH for the HPCS exhibiting good cooling performance decreases with the increase in the environmental temperature.

The paper presents the design and the implementation of different advanced control strategies that are applied to a nonlinear model of a thermal unit. A data–driven grey–box identification approach provided the physically meaningful nonlinear continuous–time model, which represents the benchmark exploited in this work. The control problem of this thermal unit is important since it constitutes the key element of passive air conditioning systems. The advanced control schemes analysed in this paper are used to regulate the outflow air temperature of the thermal unit by exploiting the inflow air speed, whilst the inflow air temperature is considered as an external disturbance. The reliability and robustness issues of the suggested control methodologies are verified with a Monte–Carlo analysis for simulating modelling uncertainty, disturbance and measurement errors. The achieved results serve to demonstrate the effectiveness and the viable application the suggested control solutions to air conditioning systems. The benchmark model represents one of the key issues of this study, which is exploited for benchmarking different model–based and data–driven advanced control methodologies through extensive simulations. Moreover, this work highlights the main features of the proposed control schemes, while providing practitioners and heating, ventilating and air conditioning engineers with tools to design robust control strategies for air conditioning systems.

China is facing the development requirements of the dual carbon goal and the construction needs of resilient cities. Currently, high-strength composite structural systems are a feasible solution, but their research and application in the construction field are insufficient, especially for the combination forms of concrete above C100 and steel above Q550. In response to this issue, this paper proposes a new high-performance structural system, namely the composite frame - high-strength steel plate wall core tube resilient structure system, which includes high-strength steel plate (Q550) - ultra-high strength concrete (C100) shear walls, replaceable energy dissipation coupling beams, and composite frames. Taking a 200 meter building as an example, this paper designs and establishes calculation models for a conventional reinforced concrete frame-core tube structure and a high-performance structure based on PKPM software, and establishes elastoplastic analysis models for both based on SAUSAGE software, and then conducts dynamic elastoplastic time history analysis and seismic resilience assessment of structures under design basis earthquakes (DBEs), maximum considered earthquake (MCEs) and extremely rare earthquakes (EREs). Research has shown that compared to conventional structures, new high-performance structures can effectively reduce the size of shear walls, reduce the self-weight of the structure, and enhance the space for building use; The story drift ratio has higher redundancy than specification limits, lower plastic damage and overall stiffness degradation of the structure, and better seismic performance; The seismic resilience has significantly improved, especially in the case of casualties, which can better ensure the safety of people's lives and property.

There is a potential for synergy effects in utilizing CO2 for both enhanced gas recovery (EGR) and geothermal energy extraction (CO2-plume geothermal, CPG) from natural gas reservoirs. This “combined CO2-EGR–CPG system” has been introduced as a feasible approach that constitutes a CO2 Capture double-Utilization and Storage (CCUUS) system. In this study, we carry out reservoir simulations, using TOUGH2, to evaluate the sensitivity of the natural gas recovery, pressure buildup, and geothermal power generation performance of the combined system to various key reservoir and operational parameters. The reservoir parameters include horizontal permeability, permeability anisotropy, reservoir temperature, and pore-size-distribution index; while the operational parameters include wellbore diameter and ambient surface temperature. Using an example of a natural gas reservoir model, we also investigate the effects of different strategies of transitioning from the CO2-EGR stage to the CPG stage on the energy-recovery performance metrics and on the two-phase fluid-flow regime in the production well. The simulation results show that overlapping the CO2-EGR and CPG stages and having a relatively brief period of CO2 injection but no production (which we call the CO2-plume establishment stage) achieves the best overall energy (natural gas and geothermal) recovery performance. Permeability anisotropy and reservoir temperature are the parameters the natural gas recovery performance of the combined system is most sensitive to. The geothermal power generation performance is most sensitive to the reservoir temperature and the production wellbore diameter. The results of this study pave the way for future CPG-based geothermal power-generation optimization studies. For a CO2-EGR–CPG project, the results can be a guide regarding the required accuracy of the reservoir parameters during exploration and data acquisition.

This study identified, analysed, and prioritised significant factors for standardising the Korean smart city project evaluation system. We analysed the efficiency and productivity of companies currently providing smart city services to consider both policy and practical aspects. The prioritisation of smart city planning reflects the latest trends in South Korea, where urban planning is moving towards smart city planning. Furthermore, the capacity building of public-private/private-private partnerships indicate the importance of business scalability. This indicates that smart city services are only stabilised when the private sector is involved and leads the project, rather than focusing on public development. The feasibility of building intelligent facilities indicates that smart city projects should be implemented after securing cost-benefit feasibility. The results were used as the basis for building an evaluation system, showing that in smart city convergence alliances, small- and medium-sized enterprises achieved the highest efficiency by reducing inputs to 81% and 86%, under the assumptions of constant and variable returns to scales, respectively. As the operational aspect is more problematic than the technical aspect, policy alternatives are necessary for smooth business progress, including increased flexibility of laws and institutions and the activation of policies that temporarily relieve regulations to demonstrate smart city projects.

This study established a relationship between computerized accounting information systems (CAISs) and performance of SMS business enterprises in Burao, Somaliland. The main three objectives of this study were; (1) to assess the impact of computerized accounting information System on the performance of SMS business enterprises in Burao. (2) To measure the role of CAIS in the control system and management performance of SMS business enterprises in Burao. (3) To measure the impact of CAIS on the financial and operational performances in SMS business enterprises in Burao. The research approach of the study was quantitative research approach. The data used in this study was primary data obtained from the results of questionnaire survey on respondents. It was also utilized secondary data from the national documents, reports, different books, published materials and websites on the topic under the study. Using Slovene's formula, a sample size of 150 was used to collect data from respondents at SMS business enterprises in Burao through purposive sampling techniques. The data was analyzed through use of descriptive and inferential statistics. Reliability test and Validity test were also employed to test consistency of the measure and validity of data collected. The research findings indicated that there is a positive relationship between CAIS and the Performance of SMS business enterprises in Burao. This study recommended that SMS business should take advantage of the excellent benefits derivable from the adaption of well-designed CAIS because this will help to achieve a high and acceptable standard of quality in the performance of their business operations. The Management of SMS business enterprises (using CAIS) will benefit from this study understanding the impact of CAIS on their business practices. The academic generation and researchers will also benefit from the study in terms of literature review in matters of computerized accounting systems. In other terms, this will act as a point of reference for other future researchers.

Solar heating technology is a promising solution to promote China to achieve the “3060 double carbon” target as soon as possible. And seasonal thermal storage (STS) can effectively solve the mismatch problem of solar heating systems between the supply and demand of thermal energy. Due to the instability of solar radiation resources and heat demand, it is necessary to analyze the dynamic response characteristics of the system. Yet, related studies are still scarce. In this study, a solar heating system with a solar tower receiver and STS was introduced in north China. The dynamic performance of the system is analyzed with a dynamic simulated method in a typical day or typical operation modes, and the switch mechanism between multiple operation modes is also revealed. The impact of different heating strategies on system performance was analyzed. Results showed that the solar fraction of the system reached 89.4% in the third year, which was 3.6% higher than the first year. The quality-quantity heating operation strategies can be effective ways to improve the discharge efficiency of STS and the system performance without any heat pump. The electricity consumption of the pump on the heating side could be significantly reduced by 44.6% compared with the quality control.

The hybridization of conventional thermal power plants by incorporation of renewable energy systems has witnessed widespread adoption in recent years. This trend aims not only to mitigate carbon emissions but also to enhance the overall efficiency and performance of these power generation facilities. However, calculating the performance of such intricate systems using fundamental thermodynamic equations proves to be both laborious and time-intensive. Nevertheless, possessing accurate and real-time insights into their performance is of utmost significance to ensure optimal plant operation, facilitate decision-making, and streamline power production planning. In this paper, we delve into the application of machine learning techniques, particularly hybrid methodologies, to predict the performance of power plants. Specifically, we employ three approaches: the Adaptive Neuro-Fuzzy Inference System (ANFIS), the ANFIS optimized via Particle Swarm Optimization (ANFIS-PSO), and the ANFIS optimized through Genetic Algorithm (ANFIS-GA). These techniques are alternatively applied to a complex hybrid thermal power plant, namely an Integrated Solar Combined Cycle Power Plant (ISCCPP). This ISCCPP comprises a steam turbine section, a gas turbine section, and a concentrated solar power system utilizing troughs as collectors. The energy transfer fluid, in conjunction with exhaust from the gas turbine section, heats water within a vessel or steam generator, producing steam to propel the steam turbine's rotor. Electricity generation is facilitated by both gas and steam turbines, which are coupled to a generator. The findings of this study underscore the accuracy and appropriateness of ANFIS-based models in evaluating and predicting the performance of intricate hybrid power plants. The ANFIS model exhibited an impressive overall coefficient of correlation of 0.9991. Notably, the integration of evolutionary algorithms (PSO and GA) into the ANFIS framework elevated model performance, yielding correlation coefficients of 0.9994 for ANFIS-PSO and 0.9997 for ANFIS-GA. It is noteworthy that ANFIS-GA demonstrated superior predictive capability. The modeling framework developed in this research offers valuable support to designers, energy managers, and decision-makers. It provides a robust and dependable tool to assess the performance of hybrid thermal power plants, which are poised for a global surge in numbers amid the ongoing energy transition.

This article presents a field-performance investigation on an Integrated Solar Water Supply System (SWSS) at two isolated agricultural areas in Thailand. The two case-study villages (Pongluek and Bangkloy ) have experienced severe draughts in the last decades, and therefore water supply has become a major issue. A stand-alone 15.36 kW solar power and a 15 kW solar submersible pump were installed along with the input power generated by solar panels supported by four solar trackers. The aim is to lift water at the static head of 64 and 48 m via piping length of 400 metres for each village to be stored in 1,000 m3 and 1,800 m3 reservoirs at an average of 300 m3 and 400 m3 per day, respectively for Pongluek and Bangkloy villages. The case study results have shown that the real costs of electricity generated by SWSS using solar PV systems intergraded with the solar tracking system yield better performance and are more advantageous compared with the non-tracking system. This study illustrates how system integration has been employed. System design and commercially available simulation predictions are elaborated. Construction, installation, and field tests for SWSS are discussed and highlighted. Performances of the SWSS in different weather conditions such as sunny, cloudy, and rainy days were analysed to make valuable suggestions for higher efficiency of the integrated solar water supply systems.

The arrival of new developments in the field of power electronics circuit’s applications in power systems builds new control strategy to improve voltage quality for power grid by overcome interruptions. Wind energy resources are unconventional resources and get advanced problems to power grid when it is connected. Uncertainty of load sharing, peak energy management, climatic conditions, wind velocity and wind energy injected into power grid leads many of power quality problems on power grid based on the existing guidelines specified in IEC-61400 standard. This system plans efficient operation of DFIG to eliminate the voltage collapse and mismatch frequency to power grid. The DFIG connected diode rectifier and rotor side converter wind generator works as an Efficient Static Synchronous Compensator (E-SATCOM) for supplying the demand of reactive power for power grid to mitigate PQ problems. The benefit of using a combined controller was verified by simulink/Matlab and its simulated results used Doubly Fed Induction Generator (DFIG), wind Turbine. This simulation results gives good quality transient and stable state response to manage and support reactive power for both symmetrical and unsymmetrical faults in connection of grid codes to provide continuous quality of power supply, multiple wind generators are required for 140 bus power grid.

The UIN Sunan Gunung Djati Journal House Information System encounters significant usability challenges stemming from inadequate UI/UX design and sub-optimal integration across its components, resulting in diminished user efficiency and adoption rates. To tackle these issues effectively, a bespoke acquisition approach coupled with prototype development was implemented. This method facilitated a structured software development life cycle emphasizing iterative feedback loops and active stakeholder participation. By iteratively refining requirements and ensuring continuous alignment with user expectations, the prototype development process aimed to deliver a final system that not only meets but exceeds user needs. Rigorous testing, ongoing support, and a commitment to continuous improvement were pivotal in transforming the initial prototype into a robust and user-friendly system. This approach not only promises to enhance overall system effectiveness but also ensures sustained value delivery to stakeholders over the system's lifecycle.

The increasing demand for water in agriculture and the need for more efficient irrigation systems has led to the development of smart irrigation systems based on the Internet of Things. In this system, an Arduino microcontroller is used to control and monitor the watering of crops. The system is equipped with sensors that measure soil moisture which are used to optimize the irrigation process. The data collected by the sensors is transmitted to the Arduino, which then adjusts the watering schedule based on the information received. The use of IoT in smart irrigation systems provides several benefits, including reduced water waste, increased crop yields, and improved plant health. The implementation of this system using an Arduino platform is relatively simple, cost-effective, and can be easily integrated into existing irrigation systems. Overall, the use of IoT in smart irrigation using an Arduino platform has the potential to revolutionize the way we manage water resources in agriculture.

N-palmitoylethanolamine (PEA) is an endocannabinoid-like compound first encountered within lipid fractions of specific foods and has intrigued researchers since the 1950s due to its therapeutic effects. This study aims to explore the therapeutic promise held by PEA as an anti-inflammatory and immunomodulatory agent. Therapeutic impact of PEA reverberates across diverse physiological systems, as the central nervous system, gastrointestinal tract, vascular network, digestive and respiratory system. Additionally, it was effective in pain management, reduction of inflammation and immune responses. These attributes have fostered collaborations targeting conditions such as Alzheimer's disease, multiple sclerosis, cerebral ischemia, neuroinflammation, general inflammation, pain, coagulopathy, steatohepatitis, and acute lung injury. PEA operates both independently and in synergy with other compounds, like paracetamol, luteolin, and oxymetazoline. This efficacy stems from its interactions with pivotal targets including PPARα, PPAR-δ, PPAR-γ, CB1, CB2, GPR55, and TRPV1. Additionally, PEA exerts a direct influence on the inflammatory cascade, orchestrating precise adjustments in immune responses. Numerous animal studies have elucidated the inherent potential of PEA. Nevertheless, the imperative of reinforcing clinical investigation is evident. This review notably underscores the pivotal necessity for methodologically rigorous clinical trials to definitively establish the translational efficacy of PEA in ameliorating diverse inflammatory pathologies within the human milieu.

This research work aims to develop a mathematical modeling for production-inventory systems. Two mathematical models are present: An infinite dimensional, partial differential equation (PDE), production level modeling is present and a finite dimensional system for a coupled dynamic pricing, production rate and inventory level ordinary differential equations (ODE), integrating a proper Lyapunov stability analysis of the dynamical system and simulations.

The power utility, Tanzania Electric Supply Company Limited (TANESCO) is faced with challenges of supplying adequate power to the ever-increasing demand. To this end, this paper explores the installed Ubungo Gas Power Plant (UGP II) located in Dar es Salaam to find means of utilizing it in co-generation method. The study embarked on detailed modelling of the system and run simulations which indicated that the co-generation can result to power generation efficiency increase between 10.42 to 50.92%. It is recommended to change the UGP II to exploit this co-generation method. Further, the study could be improved by including more parameters of the gas and steam plant and verify them experimentally.

Combining wind and solar photovoltaic (PV) generation can provide complementary renewable power production, but depends on correlated resources. This study analyzed 10 years of wind data from Naama, Algeria to evaluate the potential for evening wind generation to offset the loss of solar at sunset. Average wind speeds showed a distinct increase during evening hours, coinciding with the decrease in solar irradiance. Wind turbine simulations using a 1.5 MW turbine and the wind data showed sufficient resources for profitable power production after sunset. Statistical analyses confirmed significantly higher wind speeds and simulated power output in evening vs daylight periods (p&lt;0.05). The Pearson correlation coefficient between evening wind speeds and decreasing solar irradiance was 0.63, supporting a strong positive relationship. These findings indicate Naama has adequate wind resources to deploy economically viable wind power capacity that can complement existing solar infrastructure and provide renewable electricity after dark , .

The inverse system identification toolbox named INVSID 1.0 for MATLAB, which is used to identify the inversion of single-input single-output systems, is developed. The complete process of developing the toolbox is demonstrated. Afterwards, a numerical example is illustrated to describe how the toolbox can be used to solve inverse identification problems. Simulation results demonstrate the effectiveness of the toolbox.

Innovative practices in irrigation systems can bring improvements in terms of economic efficiency and in the same time can reduce environmental impact. Investment in high tech technologies frequently involves additional costs, but an efficient water management can increase the lifetime of the equipment. The main objective of this article is to reduce the energy consumption by one thousand cubic meters pumped and automatically to increase the economic efficiency of the pumping groups. This paper develops a new operating algorithm that ensures the operation of the pumping group at safe operating intervals and in the same time identifies the equivalent pump operating points for the entire flow range and pumping height of the pumping group. This methodology is based on the principles of an Expert System to perform the optimization process of the energy consumption in pumping groups. The resulting methodology avoids the combinatorial explosion of the solutions to be analyzed and determines the point of maximum efficiency without violation of any of the system constraints under any operating condition. The proposed methodology is tested on an irrigation system that includes a pumping group with 5 pumps, showing its effectiveness in obtaining the optimal solution with a relatively low computational burden.

It is not plausible to predict disasters; however, still the least that may be done is to get ready for that. In disaster circumstances, nowadays, the existing internet of things (IoT) technology is rather developed and capable of being highly beneficial. For many countries, the early warning system for natural catastrophes is a crucial challenge, especially for high seismic hazard countries. Primary function of an early warning system is to assist individuals and authorities to save lives and reduce secondary damage once a disaster occurs. Even though such systems have been defined for the earthquake on the basis of IoT, the least attention has been focused on the post decisions for substructure monitoring systems which can control the gas and electric lifelines given the critical time. Combination of Fuzzy system with IoT can improve the decision making process after the disasters occur. This program minimizes costs and destruction in cities. Tehran is a high seismic hazard area which contains an expanded network of the gas transmission system. Hence, a major seismic event may cause serious loss directly and indirectly owing to the damage to the gas and electric transmission network. The proposed early warning system contains a grid of strong ground motion stations. Each station contains five sensors to collect accurate data and send the data to the cloud server, then the server executes relevant scenarios.

A novel approach to the remote-control system for the compact multi-crystal energy-dispersive spectrometer for x-ray emission spectroscopy (XES) applications has been developed. This new approach is based on asynchronous communication between software components and on reactive design principles. In this paper, we identify the challenges we have faced, our solution to them as well as the implementation and future development prospects. The main motivation of this work was the development of a new holistic communication protocol that can be implemented to control various hardware components.

Spodoptera frugiperda (Lepidoptera: Noctuidae) commonly known as fall armyworm was first detected in Uganda in 2016 and has spread to all the maize-growing districts. Different methods have been deployed to control this pest. However, there is a limited understanding of the role of the environment and farmers' practices on the incidence and damage by S. frugiperda in Uganda. This study, therefore, assessed the abundance of S. frugiperda and leaf damage levels in three different districts and explored the association between agronomic practices, crop phenology and weather parameters on S. frugiperda damage and abundance in smallholder farmers’ maize fields using a longitudinal monitoring survey in 69 farmers’ fields of Kole, Kiryandongo and Nakaseke for three seasons. Leaf damage and incidence of damaged plants differed significantly between locations and seasons. Leaf damage and abundance of larvae varied significantly in the different growth stages. Conservation tillage resulted in reduced leaf damage. No significant relationship was observed between pesticide or fertilizer use with S. frugiperda leaf damage. There were non-significant negative relationships between leaf damage and rainfall. Timely and vigilant scouting, proper timing of control measures, minimum tillage practices, and crop diversity should be included in an IPM strategy for S. frugiperda.

The major goal of this paper is to use image enhancement techniques for enhancing and extracting data in FANET applications to improve the efficiency of surveillance. The proposed conceptual system design can improve the likelihood of FANET operations in oil pipeline surveillance, and sports and media coverage with the ultimate goal of providing efficient services to those who are interested. The system architecture model is based on current scientific principles and developing technologies. A FANET, which is capable of gathering image data from video-enabled drones, and an image processing system that permits data collection and analysis are the two primary components of the system. Based on the image processing technique, a proof of concept for efficient data extraction and enhancement in FANET situations and possible services is illustrated

The process of modelling energy systems is accompanied by challenges inherently connected with mathematical modelling. However, due to modern realities in the 21st century, existing challenges are gaining in magnitude and are supplemented with new ones. Modellers are confronted with a rising complexity of energy systems and high uncertainties on different levels. In addition, interdisciplinary modelling is necessary for getting insight in mechanisms of an integrated world. At the same time models need to meet scientific standards as public acceptance becomes increasingly important. In this intricate environment model application as well as result communication and interpretation is also getting more difficult. In this paper we present the open energy modelling framework (oemof) as a novel approach for energy system modelling and derive its contribution to existing challenges. Therefore, based on literature review, we outline challenges for energy system modelling as well as existing and emerging approaches. Based on a description of the philosophy and elementary structural elements of oemof, a qualitative analysis of the framework with regard to the challenges is undertaken. Inherent features of oemof such as the open source, open data, non-proprietary and collaborative modelling approach are preconditions to meet modern realities of energy modelling. Additionally, a generic basis with an object-oriented implementation allows to tackle challenges related to complexity of highly integrated future energy systems and sets the foundation to address uncertainty in the future. Experiences from the collaborative modelling approach can enrich interdisciplinary modelling activities. Our analysis concludes that there are remaining challenges that can neither be tackled by a model nor a modelling framework. Among these are problems connected to result communication and interpretation.

Conditions under which compositions of component systems form a well-defined system-of-systems here are formulated at a fundamental level. Statement of what defines a well-defined composition and sufficient conditions guaranteeing such a result offers insight into exemplars that can be found in special cases such as differential equation and discrete event systems. For any given global state of a composition, two requirements can be stated informally as: 1) the system can leave this state, i.e., there is at least one trajectory defined that starts from the state, and 2) the trajectory evolves over time without getting stuck at a point in time. Considered for every global state, these conditions determine whether the resultant is a well-defined system and if so, whether it is non-deterministic or deterministic. We formulate these questions within the framework of iterative specifications for mathematical system models that are shown to be behaviorally equivalent to the Discrete Event System Specification (DEVS) formalism. This formalization supports definitions and proofs of the afore-mentioned conditions. Implications are drawn at the fundamental level of existence where the emergence of a system from an assemblage of components can be characterized. We focus on systems with feedback coupling where existence and uniqueness of solutions is problematic.

This paper presents a novel approach to power management techniques in energy storage system (ESS) interoperability with the energy power system (EPS) by inserting a SCADA controlled directional protection relay for improving the mode switching sequence. According with latest European standards, all necessary measures for re-synchronization and reconnection for health work of the system must be taken. The proposed approach intends to improve the “interface” between storage systems and electric power grid by using a directional relay which provides interoperability improvement by automatic recognizing and differentiating the switching sequence of the mode of operation from the fault mode. Simulated results from a small scale electrical generating system are provided. The results demonstrate that the proposed power management solution is technically ideal to achieve high quality energy while retaining the stability of the power grid network. The interoperability of PHS systems integrated with the electric power grid usually leads to perturbations in terms of frequency of the generated voltage, and for improving it we designed an automatic treating and re-connecting software module. This work regards the importance of producing electricity from green and renewable energy sources, while retaining the stability and reliability of the power grid. ESS systems are widely used to help balancing of intermittent forms of load demand on the electrical power grid at specific key moments. In this article, the pumped hydro storage (PHS) technologies are proposed as an economical way to utilize smoothly the off-peak energy or surplus energy, by pumping water to a reservoir at a higher level. During peak load periods, the stored water is discharged through the reversible pump-turbine to generate electricity to meet the peak demand controlled by designed SCADA application.

When we are asleep we lose the ability to promptly respond to external stimuli and yet we spend many hours every day in this inherently risky behavioral state. This simple fact strongly suggests that sleep must serve essential functions that rely on the brain going offline, on a daily basis, and for long periods of time. If these functions did not require partial sensory disconnection, it would be difficult to explain why they are not performed during waking. Paradoxically, despite its central role in defining sleep and what sleep does, sensory disconnection during sleep remains a mystery. We have a limited understanding of how it is implemented along the sensory pathways, we do not know whether the same mechanisms apply to all sensory modalities, nor do we know to which extent these mechanisms are shared between non-rapid eye movement (NREM) sleep and REM sleep. The main goal of this contribution is to review some knowns and unknowns about sensory disconnection during sleep as a first step to fill this gap.

Energy management, especially in communities, is attracting growing interest, but is often marred by confusion between the terms "Energy Information System" (EIS) and "Energy Man-agement System" (EMS). This ambiguity hinders understanding of their use and role in improv-ing energy performance. Our objective is to clarify these terms and their contribution to energy management. We used a mixed qualitative and quantitative approach to evaluate and compare the criteria of definition, objective, functionality, role, as well as correlated elements such as or-ganizational structure, responsibilities, planning and policy, according to the requirements of ISO 50001, in addition to criteria specific to the two systems. The study reveals differences in the roles of the EIS and the SME, with a complementarity of 40% between the two systems, depend-ing on the positioning of the EIS in relation to the elements of the SME process. The EIS plays a crucial role in facilitating the implementation of the EMS according to ISO 50001. This clarifica-tion contributes to a better understanding of the respective roles of these systems in energy management, thus helping communities to improve their energy performance in an effective manner.

The effectiveness of Fuzzy Inference Systems (FISs) in manipulating uncertainty and nonlinearity makes them a subject of significant interest for decision-making in embedded systems. Accordingly, optimizing FIS hardware improves its performance, efficiency, and capabilities, leading to a better user experience, increased productivity, and cost savings. To be compatible with the limited power budget in most embedded systems, this paper presents a framework to realize ultra-low power FIS hardware. It supports optimizations for both conventional arithmetic as well as MSDF-computing to be highly consistent with MSDF-based sensors. In MSDF-computing FIS all the processes of fuzzification, inference, and defuzzification are done on serially coming data bits. To demonstrate the efficiency of the proposed framework, we utilized Matlab, Chisel3, and Vivado to implement it from high-level descriptions of FIS to hardware synthesis. We also developed a Scala library in Chisel3 to establish a connection between these tools, bridging the gap, and facilitating design space exploration at the arithmetic level. Furthermore, we realized an FIS for the navigation of autonomous mobile robots in unknown environments. Synthesis results show the superiority of the output of our suggested design framework in terms of resource usage as well as power and energy consumption compared to the Matlab HDL code generator output.

Although the effect of thermal modification (TM) on teak wood color is well documented, a few studies were carried out in closed system processes, as well as it remains unclear the effect of different processes on the same material. This work aimed to verify the effect of closed and open system processes of TM on the color of fast-growing teak wood. Thermally modified wood was evaluated in a closed system at 160 °C (CS160) and in an open system at 185 °C and 210 °C (OS185 and OS210). We measured the moisture content (initial and final) of wood, and the corrected mass loss (CML). The chemical analyses encompassed the contents of alpha-cellulose, hemicelluloses, lignin, and extractives (total, in acetone and dichloromethane). Wood color was measured before and after TM according to the CIEL*a*b* color space. It was possible to achieve the same color using different processes of thermal modification (CS160 and OS210). TM reduced wood lightness (L*), red-green chromaticity coordinate (a*), and yellow-blue chromaticity coordinate (b*). L* and a* had the bigger and lower variations, respectively. The color of thermally modified wood was significantly changed, even at the mildest condition tested (OS185, 0.33% CML).

In this paper, we investigate the cumulative historical entropy of the lifetime of an n-component coherent system under the assumption that all system components have failed at time t. Using the system signature, we can calculate the cumulative historical entropy of the system’s lifespan, which is an important aspect in determining a system’s predictability. This research produces a number of significant results, including expressions, bounds, and ordering aspects for this measure. In addition, we offer a method for finding a preferred system based on cumulative Kullback-Leibler discriminating information that is closely related to the parallel system. These findings provide important insights into the predictability and dependability of coherent systems, emphasizing the importance of this field.

Recently, there has been growing interest in alternative measures of uncertainty, including cumulative residual entropy. In this paper, we consider a mixed system consisting of n components, assuming that all components are operational at time t. We use the system signature to calculate the cumulative residual entropy of the mixed system’s remaining lifetime. This measure is a useful criterion for assessing the predictability of a system’s lifetime. We study several results related to the cumulative residual entropy of mixed systems, including expressions, limits, and order properties. These results shed light on the behavior of the measure and provide insights into the predictability of mixed systems. In addition, we propose a criterion for selecting a preferred system based on the relative residual cumulative entropy. This criterion is closely related to the parallel system and provides a practical way to choose the best system configuration. Overall, the present study of cumulative residual entropy and the proposed selection criterion provide valuable insights into the predictability of mixed systems and can be applied in various fields.

For a system that turns out to be inactive in time t, the past entropy is considered as an uncertainty measure for the past lifetime distribution. In this study, we consider a coherent system that includes n components and has the property that all the components of the system have failed at time t. To assess the predictability of the coherent system’s lifetime, we use the system’s signature to determine the Rényi entropy of its past lifetime. We study several analytical results, including expressions, bounds, and order properties for this measure.

FPGA-based data acquisition and processing systems play an important role in modern high-speed, multichannel measurement systems, especially in High-Energy and Plasma Physics. Such FPGA-based systems require an extended control and diagnostics part corresponding to the complexity of the controlled system. Managing the complex structure of registers while keeping the tight coupling between hardware and software is a tedious and potentially error-prone process. Various existing solutions aimed at helping that task do not perfectly match all specific requirements of that application area. The paper presents a new solution based on the XML system description, facilitating the automated generation of the control system’s HDL code and software components and enabling easy integration with the control software. The emphasis is put on reusability, ease of maintenance in case of system modification, easy detection of mistakes, and the possibility of use in modern FPGAs. The presented system has been successfully used in data acquisition and preprocessing projects in High-Energy Physics experiments. It enables easy creation and modification of the control system definition and convenient access to the control and diagnostic blocks. The presented system is an open-source solution and may be adopted by the user for particular needs.

The process model is very essential for the model based control design. The model of the process can be identified using system identification algorithm. The system identification is done through the open loop and closed loop approaches. In this work, the lab scale conical tank setup configured as a non square MIMO system. The conical tank system is identified through the both appraoches, the effectiveness and need of the both approaces are discussed. Based on the open loop identified model the controller designed and the controller implemented in the real time the to record the process data. From this data the closed loop identification are conducted uisng N4SID algorithm. The controller seetings are obtained using the smith predcitor based IMC based PI controller for the obtained model. The proposed identification algorithm and controller tuning show the better reults over the conventional method. Moreover, this method is applicable for all the non square MIMO system.

There has been rampant fold-ups, merger and acquisitions occurring in the Ghanaian banking industry. Then, the questions arise: Is the Ghanaian Financial System in Crisis? This study was conducted to find answers to these problems unsolved with prior literature. A sample of seventy customers of the Royal Bank, 8 employees of the Royal Bank and 2 managers of the Royal Bank were selected for a case-survey. The study also monitored the Trend of the Ghanaian Financial System through the reading and monitoring of daily news on the Financial System and reports of banks. The data from the field and the secondary data from news and reports were analysed symmetrically. The study drew on Minsky’s Financial Crisis Theory to explain the phenomenon in the Ghanaian economy and to draw predictions of what would happen in other developing economies. The study found out that: (1) The Ghanaian financial system is fragile and it holds true for most developing economies; (2) The financial system suffers greatly when the confidence level of customers falls significantly; (3) Management information systems raises the confidence level of customers (borrowers and lenders) such that there is a greater fall and impact in times of instability in the economy; (4) The higher the level of MIS adoption in an unstable economy, the more fragile the Financial System becomes and (5) A higher adoption of Management Information Systems in a Fragile Financial System indirectly contributes to Financial Crisis of the Financial System.

This paper deals with the problem of real-time management of Smart Grids. For this sake, the energy management is integrated with the power system through a telecommunication system. The use of Multiagent Systems leads the proposed algorithm to find the best-integrated solution, taking into consideration the operating scenario and the system characteristics. The proposed technique is tested with the help of an academic microgrid, so the results may be replicated.

Age-in-place can reduce the progress of dementia syndrome and improve the quality of life of the sufferers and their families. This work proposes an innovative information home support system to be established at the houses of people suffering from dementia. The main innovation of the system are its transparent character that overcomes the need for training of the sufferer, as well as the exploitation of a well-known technique for dementia, namely music therapy. It addresses the need of people suffering from dementia as well as their familiars to be recognized by them and have better interaction and collaboration. The system offers a ubiquitous recognition system, just by using smart devices like smart-phones or smart-wristbands. When a familiar person is detected in the house, then a sound file is reproduced on smart speakers placed in the house, in order to trigger the memory, based on the principles of music therapy. The system reproduced the appropriate time at 100% of the cases and the benefits of music therapy are evident daily. To the best of the authors' knowledge, this is the first system of its kind ever reported in the literature.

In graduate programs such as social work, field education is the signature pedagogy of education. As such, student placement with an appropriate field education agency is critical to ensure academic success and career readiness. A variety of Learning Management System (LMS) and Integrated Planning and Advising Service (IPAS) technologies have been developed to fully integrate technology into the educational system and streamline and improve the learning experience for students, educators, and administrators. Few (if any) of the existing solutions have capabilities to match students with field educators on the basis of an individual student’s completed coursework and area of specialization, as well as field educator needs and opportunities. This paper describes our experience developing a custom LMS/IPAS system—the School of Social Work information System (SSWiS)—that was designed specifically for student learning, faculty advising, and academic administration within our social work graduate program. We present the challenges that motivated the design of the SSWiS before describing the architecture and functionality of our solution. We then discuss our preliminary evaluation results. We conclude with a discussion of the benefits and limitations of our system in the context of today’s technical needs in graduate education in social work and other fields.

Background. The markerless motion capture system (MLS) is a new technology that uses deep learning to detect body segments from digital images. This study tested the agreement between the MLS and a force-plate based system (FPS, “gold standard”) to quantify stability control and motor performance (MP) during gait initiation (GI). Methods. Healthy adults (young and elderly) and patients with Parkinson’s disease (PD) performed GI series at spontaneous and maximal velocity on an FPS while being filmed by an MLS. Signals from both systems were used to compute the peak of forward center-of-mass velocity (indicator of MP) and the braking index (BI, indicator of stability control). Results. Descriptive statistics indicated that both systems detected between-groups differences and velocity effects similarly, while a Bland-Altman (BA) plot anal-ysis showed that BI and MP mean biases were virtually zero in all groups and conditions. Bayes factor 01 indicated strong (for BI) and moderate (for MP) evidence that both systems provided equivalent values. However, trial-by-trial analysis of BA plots revealed the possibility of differ-ences > 10% between the two systems. Conclusion. Although non-negligible differences do occur, MLS appears to be as efficient as FPS in detecting PD and velocity condition effects on BI and MP

Since the advent of the Internet, there has been a significant shift from wired to wireless communication between devices. The volume of data transmitted has surged, primarily driven by the exponential growth of network services, Internet of Things (IoT) devices, and online users. This trend became especially pronounced with the onset of the COVID-19 pandemic, as the Internet's role and significance expanded dramatically. People began to spend more time online, engaging in activities like e-learning, remote work, and online shopping. Concurrently, concerns about the security of wireless communication channels have escalated. As more data is stored and transmitted over the Internet, cybercriminals are actively seeking unauthorized access to it to further their malicious objectives. Through a comprehensive literature review in the realm of wireless network security and privacy, it has become evident that several factors render these networks susceptible to vulnerabilities. The aim of this paper is to shed light on the major and common security and privacy challenges faced by existing wireless networks. Additionally, it seeks to demonstrate the array of techniques available to mitigate these issues. Ultimately, this paper will culminate in an in-depth analysis of cybersecurity measures to address the issues in wireless networks.

The ever-evolving landscape of technology continually drives the demand for more robust and secure systems. Intrusion Detection and Prevention Systems (IPS) play a pivotal role in safeguarding digital infrastructures. IPS harnesses a blend of cutting-edge technologies, specifically Network-Based, Wireless-Based, and Host-Based Intrusion Detection Systems (IDS), to fortify network security. This multifaceted approach enhances the system's capacity to scrutinize incoming data and network traffic, effectively reducing the risk of intrusion. In the realm of malicious activity detection, IPS employs a diverse array of techniques and mechanisms. Our proposed IPS integrates both anomaly-based and signature-based analysis approaches. In signature-based analysis, intrusions are identified by matching data collected from various activities with pre-defined signatures, employing rule-based methods to detect anomalies effectively. In the anomaly-based analysis approach, the system juxtaposes current activities with a baseline of normal behaviour to flag any deviations. This is achieved through distance-based methods, ensuring a well-rounded approach to threat detection. Our comprehensive prevention system encompasses a suite of security measures, including anti-virus software, Deep Packet Inspection, and Quarantine. These components work in synergy to detect and thwart malicious activities effectively. Even when concealed or hidden, the IPS remains a reliable sentinel, ensuring the integrity of your digital ecosystem. This review delves into the intricate web of terminologies and concepts surrounding Intrusion Detection and Prevention Systems, shedding light on the evolving technology landscape and the critical role IPS plays in bolstering cybersecurity.

Runway Safety Assistant Foreseeing Excursions (RUN.S.A.F.E.) is a complete embedded system solution that predicts a potential runway overrun of a civil aviation aircraft, during the Take off and Landing. This work examines the feasibility of such a system, through the algorithms and computations that predict the overruns. The system executes both static and dynamic calculations, the former being dependent, while the latter independent to the user’s inputs. Both outcomes and the runway’s length continuously estimate in real time if the process will end up in an overrun. All inputs are specifically selected, to either be available to the pilots, or to be retrieved from the existing avionics systems of the cockpit. A performance evaluation is conducted on both static and dynamic calculations, and metrics unveil the accuracy of the predictions and the time needed to converge to a reliable result. The solution is adapted for a Boeing 737-800 aircraft, with CFM56-7B engines, yet the calculations also apply for similar aicrafts, equipped with a tricycle Landing gear and turbofan engines, namely the whole Boeing 737 family, the Airbus A320 family etc.. The system is aligned with current standards and certification specifications, where applicable.

The proliferation of Unmanned Aerial Vehicle (UAV) networks is increasing, driven by their capacity to deliver automated services tailored to the varied demands of numerous smart city applications. Trust, security, and privacy remain paramount in the public domain. Traditional centralized network designs fall short of ensuring device authentication, data integrity, and privacy within UAV networks’ highly dynamic and adaptable environments. Decentralized reputation systems emerge as a promising solution to enhance the reliability and trustworthiness of data and communications within these networks while safeguarding UAV security. This paper presents an exhaustive survey of trust and reputation systems, exploring existing frameworks and proposed innovations alongside their inherent challenges. It highlights the crucial role of reputation systems in strengthening trust, security, and privacy throughout these networks and discusses various strategies to mitigate existing vulnerabilities. As a useful resource for researchers and practitioners seeking to advance the state of the art in UAV network security, we hope this survey will spark further community discussion and stimulate innovative ideas in this burgeoning field.

Italy has been defined as the "logistics platform" of the Mediterranean Sea. The Italian port system, with 11,6 million TEUs handled and 61,4 million passengers by 2022 (Assoporti data Jan‐Dec 2022) [1] is the key to guarantee this condition through adequate levels of reliability, safety and sustainability. This contribution addresses port logistics and shipping, focusing on primary issues related to the energy sector with a specific focus on what can be observed in the Italian context. Specifically, decarbonization of the maritime sector and related infrastructural problems (e.g. Cold Ironing or alternative fuels, where the uncertainty about resources availability and related cost do not allow for an easy strategic planning by both the shipowner and the port authority), as well as policies such the Emission Trading System (ETS) will be analyzed. All these issues, if addressed with a critical review, could represent the driving force of the national port sector for its growth and its competitiveness at a global scale.

In an agricultural system, finding suitable watering, pesticide, and soil content to provide the right nutrients for the right plant is a mystery so far. Plants cannot speak and cannot ask which food they require. These problems can be addressed by applying intelligent (fuzzy logic) controllers to IoT devices in order to enhance communication between crops, ground mobile robots, aerial robots, and the entire farm system. The application of fuzzy logic in agriculture is a promising technology that can be used to optimize crop yields and reduce water usage. It was developed based on language and the air properties in the agricultural fields were formulated. The entire system was simulated in the MATLAB/SIMULINK environment with Cisco Packet Tracer integration. The inputs for the system were soil moisture sensors, temperature sensors, humidity sensors, and outputs were pump flow, valve opening, water level, and moisture in sounding. The obtained results were the output of opening valve, moisture in sound, pump flow rate, outflows, water level, and ADH values, which are 10.00000013 rad/sec, 34.72%, 4.494%, 0.025 m^3/sec, 73.31 cm^3, and 750 values respectively. The outflow rate increase indicates that the water is released from the tanks, and the control signal fluctuates, indicating that the valve is opening.

This article develops applications of the generalized method of lines to numerical solutions of the time-independent, incompressible Navier-Stokes system in fluid mechanics. We recall that for such a method, the domain of the partial differential equation in question is discretized in lines (or more generally in curves), and the concerning solutions are written on these lines as functions of the boundary conditions and the domain boundary shape.

Rice wheat cropping system prevailed in more than fifty percent areas of rice belt of central and upper Punjab. In this area yield of wheat is curtailed every year due to late harvesting of rice crop. In addition to this, lack of machinery for direct sowing of wheat into combine harvested rice is a major limitation for timely wheat sowing due to presence of heavy straw load dropped by the combine harvester. A field experiment was planned and executed during two consecutive years 2017-18 and 2018-19 at Agronomic Research Station Farooqabad to evaluate the various stubble management techniques for the sowing of wheat in a rice-wheat cropping system. The Experiment consist of four treatments Happy seeder (Zero tillage), conventional sowing without burning of rice stubble, Rotavator two times, and Conventional sowing with the burning of rice stubble. The trail was arranged as a Randomized Complete Block Design with four replications having a net plot size of 8 m x 20 m. The Treatments have significant effects on Plant height, Number of productive tillers, 1000- grain weight, and grain yield. Maximum plant height (94.74 and 94.25 cm), numbers of productive tillers/m2 (324.00 and 322.25), 1000-grain weight (36.35 and 36.20 g), grain yield (3780 and 3613 kg/ha), and benefit-cost ratio (2.54 and 2.43) were recorded from the treatment happy seeder (Zero tillage) during both years respectively. It is concluded that the sowing of wheat with a happy seeder (Zero tillage) is an appropriate technique in the rice-wheat cropping system by protecting the environment and soil health from the burning of rice stubbles.

Differential equation models to understand interaction between plant and nutrient solution are presented. The root cells selectively emit H+ ions with active transport consuming ATPs to establish electrical gradient along the cell membrane. It establishes electrical field with Nernst potential to make positively charged ions outside the cell membrane flow into the root cell. Anion influx is also modulated by H+ ion concentration because plant root cell absorbs negatively charged particles with symport. If an anion collides with H+ cell to make net charge as neutral, at symport channel, it can flow through. In this paper, mathematical models for cation and anion absorption are introduced. Cation absorption model was induced from Ohm's law combined with Goldman's equation. Anion absorption model is similar to chemical reaction rate model. Both models have physiological terms influenced by gene expression pattern, species or phenotypes. Cation model also includes terms for ion's kinetic and electrical properties, growth of plant and interaction between the root and the surroundings. Simulation for 20 different sets of coefficients showed that the physiology-related coefficient has important role on nutrition absorption tendencies of plants.

We have presented a controllable and human-readable polynomial neural network (CR-PNN) that is the first human-readable neural network. One can imagine its influence on system identification. Subsequently, we developed a relation spectrum in a medical application, which is likely to stand alongside the Fourier spectrum. However, the system analysis methodology is incomplete in contrast to signal processing methodology. Here, we presented the system filters for the first time. In this paper, we used the simulation system to verify the availability of the system analysis methodology. The system analysis methodology showed great properties in system identification and filter. The contribution of this paper is the system analysis methodology: transform method (CR-PNN), relation spectrum, and system filter design.

Climate projections show that southern Indonesia such as West Nusa Tenggara is projected to experience a lower precipitation and higher temperatures. To date, research on climate change impact on Indonesian rice production yield is limited. As climate change is projected to decrease rainfall and to increase temperatures, this paper offers a qualitative analysis using system archetypes to understand the impacts of climate change on rice production. Two system archetypes are identified including Limits to Growth and Success to Successful. Both archetypes explain that rice production is hampered by high minimum temperature as photosynthesis output is decreased by increasing respiration. This paper shows that using a simple tool, system archetypes, we can describe the impacts of climate change on rice production. The outputs of this study such as a causal loop diagram and system archetypes can be a basis to develop a simulation model in understanding the impacts of climate change on main crops.

In this article, we consider the three dimensional $\alpha$-fractional nonlinear delay differential system of the form \begin{align*} D^{\alpha}\left(u(t)\right)&=p(t)g\left(v(\sigma(t))\right),\\D^{\alpha}\left(v(t)\right)&=-q(t)h\left(w(t))\right),\\D^{\alpha}\left(w(t)\right)&=r(t)f\left(u(\tau(t))\right),~ t \geq t_0, \end{align*} where $0 < \alpha \leq 1$, $D^{\alpha}$ denotes the Katugampola fractional derivative of order $\alpha$. We have established some new oscillation criteria of solutions of differential system by using generalized Riccati transformation and inequality technique. The obtained results are illustrated with suitable examples.