The aspirated hypersonic air-breathing propulsion system requires a large amount of power generation, but its special structure makes it impossible to adopt common power generation methods. The high-temperature gaseous hydrocarbon fuel thermal power generation (TPG) system was developed to solve the power generation problem for hypersonic air-breathing propulsion system. But off-design operating conditions of the hypersonic propulsion system results in a more complex process for both propulsion system and the TPG system. To better analyzing the dynamic thermos-physical characteristics of hypersonic airbreathing propulsion system considering thermal-mechanical coupling process among cooling/TPG system, a dynamic analytical model was developed, and the dynamic thermos-physical characteristics of TPG system under different off-design working conditions were conducted. It can be concluded from the analytical results that the dynamic process of thermos-physical characteristics shows a complex trend under the flight Mach number and fuel equivalence ratio off-design working conditions. Such complexity of dynamic characteristics brings difficulties in fuel supply for the propulsion system.

Designing and development of agricultural robot is always a challenging issue, because of robot intends to work an unstructured environment and at the same time, it should be safe for the surrounded plants. Therefore, traditional robots cannot meet the high demands of modern challenges, such as working in confined and unstructured workspaces. Based on current issues, we developed a new tomato harvesting wire-driven discrete continuum robot arm with a flexible backbone structure for working in confined and extremely constrained spaces. Moreover, we optimized a tomato detaching process by using newly designed gripper with passive stem cutting function. Moreover, by designing the robot we also developed ripe tomato recognition by using machine learning. This paper explains the proposed continuum robot structure, gripper design, and development of tomato recognition system.

Joints between walls are very important for structural analysis of each masonry building at the global and local level. This issue was often neglected in case of traditional joints and relatively squat walls. Nowadays the issue of wall joints is becoming particularly important due to the continuous strive for simplifying structures, introducing new technologies and materials. Eurocode 6 and other standards (USA, Canadian, Chinese, and Japanese) recommend inspecting joints between walls, but no detail procedures have been specified. This paper presents our own tests on joints between walls made of autoclaved aerated concrete (AAC) masonry units. Tests included reference models composed of two wall panels joined perpendicularly with a masonry bond (6 models), traditional steel and modified connectors (12 models). A shape and size of test models and structure of a test stand were determined on the basis of the analysis of the current knowledge, pilot studies and numerical analyses of FEM. The analysis referred to the morphology and failure mechanism of models. Load-displacement relationships for different types of joints were compared and obtained results were referred to results for reference models. A mechanism of cracking and failure was found to vary, and clear differences in behaviour and load capacity of each type of joints were observed. Individual working phases of joints were determined and defined, and the empirical approach was suggested to determine forces and displacement of wall joints.

In this paper we show how to efficiently implement parallel discrete simulations on Multi-Core and GPU architectures through a real example of application: a cellular automata model of laser dynamics. We describe the techniques employed to build and optimize the implementations using OpenMP and CUDA frameworks. We have evaluated the performance on two different hardware platforms that represent different target market segments: high-end platforms for scientific computing, using an Intel Xeon Platinum 8259CL server with48cores and also an NVIDIA Tesla6V100 GPU, both running on Amazon Web Server (AWS) Cloud, and on a consumer-oriented platform, using an Intel Core i9 9900k CPU and an NVIDIA GeForce GTX 1050 TI GPU. Performance results are compared and analysed in detail. We show that excellent performance and scalability can be obtained in both platforms, and we extract some important issues that imply a performance degradation for them. We also found that current Multi-Core CPUs with large core numbers can bring a performance very near to that of GPUs, even similar in some cases.

Hand and arm gesture recognition using radio frequency (RF) sensing modality proves valuable in man-machine interface and smart environment. In this paper, we use time series analysis method for accurately measuring the similarity of the micro-Doppler (MD) signatures between the training and test data, thus providing improved gesture classification. We characterize the MD signatures by the maximum instantaneous Doppler frequencies depicted in the spectrograms. In particular, we apply the dynamic time warping (DTW) method and compare its performance with that of the long short-term memory (LSTM) network. Both methods take into account the values as well as the temporal evolution and trends of time series data. It is shown that the DTW method achieves high gesture classification rates and is robust to time misalignment.

The separation of microparticles with respect to different properties such as size and material is a research field of great interest. Dielectrophoresis, a phenomenon which is capable of addressing multiple particle properties at once, can be used to perform a chromatographic separation. However, the selectivity of current dielectrophoretic particle chromatography (DPC) techniques is limited. Here we show a new approach for DPC based on differences in the dielectrophoretic mobilities and the crossover frequencies of polystyrene particles. Both differences are addressed by modulating the frequency of the electric field to generate positive and negative dielectrophoretic movement to achieve multiple trap and release cycles of the particles. A chromatographic separation of different particle sizes revealed a voltage dependency of this method. Additionally, we showed the frequency bandwidth influence on separation using one example. The DPC method developed was tested with model particles but offers possibilities to separate a broad range of plastic and metal microparticles or cells and to overcome currently existing limitations in selectivity.

Information and communication technologies play an increasingly important role in the process of acquiring knowledge from a territory and managing it at different scales. ICTs allow a rapid diffusion of data not only through institutional channels but also through social networks where the smart community share experiences and perceptions. In this sense, ICTs become strategic to support the promotion of sustainable tourism development of territories. An important tool to implement it, can be a circular smart dashboard, a decision support system in which the digital data are organized and processed to produce an information output, to be used, after the evaluation by the decision makers, as a new input for the system. The present paper deals with a wider research the authors are involved in, related to the reconversion and valorization of a former mining area towards slow tourism, as the Santa Barbara Walk (SBW), an ancient mining route in the Sulcis Iglesiente area (Sardinia, Italy) . In particular, we here focus on the design proposal of a dashboard, capable of organizing information concerning the main features of the walk, in order to facilitate a shared governance for an effective tourism promotion. The paper is based on a thorough recognition of the main characteristics of the Walk, both the material ones and the digital, immaterial ones. The SBW represents in fact a network connecting the main points of interest along the Walk. On the contrary, its digital network – consisting of intangible infrastructure and flows - is however fragmented in terms of policies and contents Also a state of disorganization in slow tourism promotion activities can be observed. The goal of this paper is to present and analysis of the area, and to propose an evaluation and planning tool as the design of a circular dashboard of the SBW.

The purpose of this study is to propose a consecutive manufacturing process system to secure the productivity of excellent STKN540B steel tube in the respect of economy and safety as the supporting material for mega structures such as building, bridge and ship. The components of consecutive manufacturing are press-bending, orbital auto welding and steel tube correction. By using STKN540B a high-strength steel material with low yield point that requires a special manufacturing process unlike other steel materials, an actual tube manufacturing is carried out at each stage in this experimental study. With this, the quality of steel tube and the efficiency of the manufacturing process are analyzed to draw out some points to improve in the future.

In this paper an integrated methodology for the coupling between 1D- and 3D-CFD simulation codes is presented, which has been developed to support the design and calibration of new diesel engines. The aim of the proposed methodology is to couple 1D engine models, which may be available in the early-stage engine development phases, with 3D predictive combustion simulations, in order to obtain reliable estimates of engine performance and emissions for newly designed automotive diesel engines. The coupling procedure features simulations performed in 1D-CFD by means of GT-SUITE and in 3D-CFD by means of Converge, executed within a specifically designed calculation methodology. An assessment of the coupling procedure has been performed by comparing its results with experimental data acquired on an automotive Diesel engine, considering different working points including both part load and full load conditions. Different multiple injection schedules have been evaluated for part-load operation, including pre and post injections. The proposed methodology, featuring detailed 3D chemistry modeling, was proven to be capable to properly assess pollutant formation, specifically to estimate NOx concentrations. Soot formation trend was also well-matched for most of the explored working points. The proposed procedure can therefore be considered as a suitable methodology to support the design and calibration of new Diesel engines, thanks to its ability to provide reliable engine performance and emissions estimations from the early-stage of a new engine development.

The aim of this document is to present how the interpretation of the RVM (Recovery Voltage Measurement) test can be improved through the use of a Debye equivalent circuit. As it is described in the literature the interpretation of the RVM test requires expertise and if the transformer presents a high interfacial polarization it is not possible to diagnose it in detail. Debye model is proposed in this work for enhancing RVM interpretation. This model is based on an electrical circuit that includes basic R-L-C components, that allows two interesting features: on one hand, isolation physical effects can be separately represented and, on the other, the values of the R-C components can be calculated from the RVM response (L components are not used in this work as long as no magnetic field effects are taken into account). Thus, the different isolation effects that are indistinguishable merged in the RVM transient response can be split into different R-C branches, each one corresponding with a single (not merged) isolation effect. Finally, several case studies are presented, in which it is correlated a dielectric oil treatment carried out and the equivalent circuit changes.

In the present paper four passive micromixers designs (G1, G2, G3 and G4) inspired on distillation columns trays were proposed. The devices performance was assessed by numerical simulations. The mixing performance was investigated for a Reynolds number range from 0.01 to 100 and channel height of 200 µm, 500 µm and 1000 µm for oil/ethanol flow. G1 and G4 designs provided high mixing index (> 0.975). The G1 device achieved superior mixing performance with a moderate pressure drop (about 0.5 MPa) due to the induced flow recirculation pattern for a relative high flow rate of 0.21 L/min, highlighting the potential use of such microdevice for scale-up and numbering-up of microdevices in modular chemical plant processing.

The underground injection and geological sequestration of carbon dioxide (CO₂) is a promising approach for reducing the levels of CO₂ in the atmosphere. To mitigate the leakage of CO₂ resulting from natural fracture networks in rock masses, the sequestration process is commonly accompanied by the injection of reactive Portland cement representing a coupled hydro-chemo-mechanical process. In this work, a numerical approach based on the unified pipe network method (UPM) is presented that considers the coupled permeation and diffusion processes with chemical precipitation. Most input parameters are derived from the published literature. The proposed approach is validated through a comparison with analytical solutions, which are applied to simulate the CO₂ sequestration process in a fractured rock mass. The results indicate that the long-term sequestration effect, which is highly influenced by the fracture distribution, can be captured effectively by the model. Consequently, the presented approach can assist engineers in properly designing the arrangement of boreholes and determining the concentration of the grouting material.

Standard Ethernet (IEEE 802.3 and the TCP/IP protocol suite) is gradually applied in industrial control system (ICS) with the development of information technology. It breaks the natural isolation of ICS, but contains no security mechanism. A modified intrusion detection system (IDS), which is strongly correlated to specific industrial scenario, is necessary for modern ICS. On the one hand, this paper outlines attack models, including infiltration attacks and our creative forging attack. On the other hand, we proposes a hierarchical IDS, which contains a traffic prediction model and an anomaly detection model. The traffic prediction model, which is based on autoregressive integrated moving average (ARIMA), can forecast the traffic of ICS network in the short term and precisely detect the infiltration attacks according to abnormal changes in traffic pattern. The anomaly detection model using one-class support vector machine (OCSVM) is able to detect malicious control instructions by analyzing the key field in EtherNet/IP packets. The experimental results show that the hierarchical IDS has an outstanding performance in detecting infiltration attacks and forging attack compared with other two innovative IDSs.

The objective of this study is to conduct a mineralogical and chemical characterization of the mortars Roman archaeological site of Volubilis to rebuild spare mortars for restoration. We take samples of mortar, broken tile palate garden, and pavement mosaic Falavius Germanus houses. The analysis by X-ray diffraction reveals the coarse mortar Flavius Germanus is made of quartz and calcite with feldspar and probably, mica and dolomite in small amounts. The binder end is formed calcite and quartz. However, the broken tile mortar is formed by coarse particles, clay base mixed with a binder phase dominated by calcite. These results allowed us to reformulate spare mortars for the restoration of damaged Roman mosaics. The mortars are made up by 63.6% of lime and 36.4% of sand(with 4.19% of large grain, 71, 04% of coarse sand, 24.22%, of fine sand and 0.55% fines parts).The performance of these mortars was tested by mechanical testing.

Welding of dissimilar aluminium alloys has been a challenge for a long period until the discovery of the solid state welding technique called friction stir welding (FSW). The discovery of this technique encouraged different research interests revolving around the optimization of this technique. This involves the welding parameters optimization and this optimization is categorized into two classes i.e. similar alloys and dissimilar alloys. This paper reports about the mechanical properties of the friction stir welded dissimilar AA1050-H14 and AA5083-H111 joint. The main focus is to compare the mechanical properties of specimens extracted from different locations of the welds i.e. the beginning, middle and the end of the weld. The specimen extracted at the beginning of the weld showed low tensile properties compared to specimens extracted from different locations of the weld. There was no certain trend noted through the bending results. All three specimens showed dimpled fracture which is the characterization of the ductile fracture.

As is well known, the main contribution of the FRP strips to the strength of load-bearing walls is an improvement in the in-plane strength. This paper deals with the possibility of applying the FRP strips in way to modify the strengthening mechanism of the FRP reinforcing system, from an in-plane to an out-of-plane strengthening mechanism. In order to achieve this goal, a second reinforcement system – derived from the CAM system (Active Confinement of Masonry) – provides connections between the FRP strips placed on the opposite sides of the wall. This new strengthening technique – called the straps/strips technique – establishes a stiffness constraint that forces the opposing FRP strips to behave like two flanges of an FRP I-beam embedded in the wall. Consequently, the use of FRP strips also improves the flexural strength of the wall. The present paper briefly summarizes the results obtained in previous works with the straps/strips technique and proposes an improvement of this strengthening technique, based on some weak-points emerged in the early experimentations. The paper also shows the results of a further experimental test, performed with the improved straps/strips technique. Finally, the similarity between FRP strips with transversal connection and concrete wythes of a sandwich panel with flexible connectors leads to interpret the behavior of the ideal I-beam in terms of composite action established between the FRP strips. This paves the way for analytical modeling of the straps/strips technique.

In addition to the traditional QoS metrics of delay, delay jitter, and packet loss probability (PLP), Quality of Experience (QoE) is now widely accepted as a numerical proxy for actual user experience. The literature has reported many mathematical mappings between QoE and QoS. These QoS parameters are measured by the network providers using sampling. There are some papers studying sampling errors in QoS measurements; however there is no account of propagation of these sampling errors to QoE evaluation. In this paper, we used industrially acquired measurements of PLP and jitter to evaluate the sampling errors and correlation in measurements. Focussing on Video-on-demand (VoD) applications, we use subjective testing and regression to map QoE metrics onto PLP and jitter. The resulting mathematical functions of QoE and theory of error propagation was used to evaluate the propagated error in QoE, and this error was represented as confidence interval. Using the guidelines of UK government for sampling, our results indicate that confidence intervals around estimated QoE in a busy hour can be between MOS=1 to MOS=5 at targeted operating point of QoS parameters. These results are a new perspective on QoE evaluation, and are of great significance to all organisations that need to estimate the QoE VoD applications precisely.

Immense challenges arise in the Quality Assurance area due to contemporary development in Internet of Things (IoT) technology. Current issues are mainly related to test coverage, test diversity, IoT Stability, Use of Cellular Networks in IoTs, IoT Devices updates, Security, Data Integration, and interoperability. In this paper, we present all those issues with suggestions for tackling those issues.

The complex systems that require safety are the Safety Critical Systems. Maintaining these systems is a big challenge. Now a days, safety is a very critical requirement for the latest systems. Safety critical systems must be safe. Different approaches to ensure quality and safety in safety critical systems has been discussed in this paper. A comparison is also conducted between these various approaches. Safety critical systems must remain more influential in future.

Risk assessment management have been a hot topic for the researchers since a very long time. Software risk management is an important part of project management as it contains the identification, analysis, estimation and monitoring of different risks present in the system. This helps developers in decision making while assessing the problems that could arise in the software systems. Risk management is very complex in large scale system as these systems have very complex development. The paper describes risk management techniques for large scale system. Furthermore we have provided a detailed comparative analysis of these techniques with commonly identified risks in software systems and have provided a systematic order for risk management process to ensure risk mitigation.

The radio activity in Wireless Sensor Networks (WSN) and Internet of Things (IoT) applications are the most common reason for power consumption. However, recognizing and controlling the factors affecting radio activity can be valuable for managing node power. ContikiMAC is a low-power Radio Duty-Cycle protocol in Contiki OS that uses Clear Channel Assessments (CCA) to check radio status periodically. The time taken to check the radio in receive mode WakeUp, is one of the most important reasons for power consumption which in most the cases can lead to negative WakeUp in Radio Duty-Cycles and ContikiMAC especially. Here, we present a detailed analysis of idle listening time factors on the ContikiMAC. Then, we propose Light Weight CCA(LW-CCA) as an extension to ContikiMAC to reduce power consumption by reducing the radio check time in receive mode WakeUp’s, while maintaining up to 99% the Packet Delivery Rate (PDR). The simulation results show that the proposed method reduces significantly energy consumption in nodes compared to ContikiMAC and thus it helps maintain a high network performance.

Estimating heat emission losses of heating systems is an important task of energy efficiency assessments in buildings. To this aim, the present international standards contain tabulated values for different emitter and control system configurations, without however explaining how to compute the effect of increased setpoint temperatures on the system losses. Moreover, the effects of each component are treated as independent, while e.g. vertical stratification and temperature control of the system are cross-related. In this paper we attempt to fill this gap by proposing a calculation method to calculate the product category specific setpoint variations for space heating emitters, accounting for the overall heat balance in the enclosure and including the cross-correlations of each component as well. The emission losses of a heating system are computed using a temperature setpoint variation method that is imposed on annual energy calculations. This complements the procedure presented in the Standard EN15316-2, also providing the possibility to use product-specific values of setpoint variations instead of tabulated values. As the main finding of the study, the calculation process is defined for a European Reference Room, namely for a specific enclosure that allows an accurate and transparent evaluation of the total setpoint variation. The product-specific values of setpoint variations are calculated from measured vertical stratification and control parameters with an annual simulation model of the European Reference Room. The total setpoint variations were simulated for a set of heat emitters and controllers in order to quantify and compare the energy performance of a new and an old type building located in Strasbourg. We find that the total setpoint variation required to overcome emission losses is up to 2.00 °C in the old building and 1.20 °C in the new building, corresponding respectively to an increase in total heating energy usage of up to 22% and 20%.

Over the last few decades there has been an exponential growth in IT, motivating IT professionals and scientists to explore new dimensions resulting in the advancement of artificial intelligence and its subcategories like computer vision, deep learning and augmented reality. AR is comparatively a new area which was initially explored for gaming but recently a lot of work has been done in education using AR. Most of this focuses on improving students understanding and motivation. Like any other project, the performance of an AR based project is determined by the customer satisfaction which is usually affected by the theory of triple constraints; cost, time and scope. many studies have shown that most of the projects are under development because they are unable to overcome these constraints and meet project objectives. We were unable to find any notable work done regarding project management for augmented reality systems and application. Therefore, in this paper, we propose a system for management of AR applications which mainly focuses on catering triple constraints to meet desired objectives. Each variable is further divided into subprocesses and by following these processes successful completion of the project can be achieved.

A lightweight image encryption algorithm based on chaos induction via a 5-dimensional hyperjerk oscillator (5DHO) is presented. First, the dynamics of our 5DHO network is investigated and shown to exhibit up to five coexisting hidden attractors in the state space that depend exclusively on the system’s initial values. Further, a simple implementation of the circuit was used to validate its ability to exhibit chaotic dynamical properties. Second, an Arduino UNO platform is used to confirm the usability of our oscillator in digital implementation of the system. Finally, an efficient image encryption application is executed using the proposed chaotic networks based on the use of permutation-substitution sequences. The superior qualities of the proposed strategy are traced to the dynamic set of keys used in the substitution process which heralds the generation of the final ciphered image. Based on the results obtained from the entropy analysis (7.9976), NPCR values (99.62), UACI tests (33.69) and encryption execution time for 512x512 images (0.1179 sec), the proposed algorithm is adjudged to be fast and robust to differential and statistical attacks relative to similar approaches.

Real data obtained from ship in operation are processed and analyzed in this paper. The intention was to provide software which would predict ship’s fuel consumption in some future time instant. It is showed that it is possible to develop such software based on numeric fitting of known data. In order to check how well the prediction of future fuel consumption is, we used only the first half of data for obtaining prediction curve. The second part of data was used to compare different prediction curves goodness. Hence, the presented research used actually a “real future data” and forecasted future data, which are used to numerically evaluate goodness of prediction. The research is of interest for companies logistics, to provide adequate fuel for fleet when and where actually needed. It is concluded that there are several prediction functions which satisfy used statistical quality measures.

Based on K-ε Standard Wall turbulence model (2-Equation) and Navier-Stokes (N-S) equations defined for incompressible fluids, fluid flow behaviour around hyperloop pods in an evacuated tube was simulated using ANSYS fluent solver assuming steady state and two dimensional conditions. In this research, to develop the case studies, using combination of different head and tail shape profile, four kind of hyperloop pods were developed with the aid of SolidWorks. These four pods have been investigated for their aerodynamic behaviour as four different case scenarios. The results of simulation depicts that an atmospheric pressure of 100 Pa with blockage ratio of 0.36 in tube provides the best possible aerodynamic behaviour for the designed hyperloop pod models. This research finds that overall aerodynamic behaviour of hyperloop pods can be varied by changing the head and tail shape profile of pods and a particular combination of head and tail shape profile can provide optimally best aerodynamic capabilities. Thus, this research paper provides a novel method of obtaining best aerodynamic capabilities in hyperloop pods by designing head profile optimally in combination with tail profile. This outcome will provide major contribution towards the development of hyperloop pods in future with better aerodynamic behaviour resulting in lesser electrical energy required to propel the hyperloop pods in evacuated tube.

The study presents a comparison of the common Child Restraint Systems (CRS) which reduces the value of dynamic loads affecting the child's body during car accidents. The analyzed systems were: child seats, Combi Booster Seats, and straps adjusting vehicle seat belts to children's sizes. The effectiveness of the analyzed devices was assessed on the basis of experimental tests carried out in the accredited laboratory approving the Child Restraint Systems. The tests were carried out accordingly to the new Regulation No. 129 UN / ECE. Whether the tested devices meet the guidelines of the new Regulations No. 129 despite approval in accordance with Regulation No. 44. Based on the research result, better safety parameters of some new solutions dedicated to children's safety could be observed. The final results show that there is still space for improving the safety of young vehicle passengers.

Recently, inter-vehicle communication, which helps to avoid collision accidents (by driving safety support system) and facilitate self-driving (by dissemination of road and traffic information), has attracted much attention. In this paper, in order to efficiently collect road / traffic information in the request / response manner, first a basic method, Content-centric network (CCN) for Vehicular network (CV), is proposed, which applies CCN cache function to inter-vehicle communication. Content naming and routing, which take vehicle mobility into account, are investigated. On this basis, the CV method is extended (named as ECV) to avoid the cache miss problem caused by vehicle movement, and is further enhanced (named as ECV+) to more efficiently exploit cache buffer in vehicles, caching content according to a probability decided by channel usage rate. Extensive evaluations on network simulator Scenargie, with realistic open street map, confirm that the CV method and its extensions (ECV, ECV+) effectively reduce the average number of hops of data packets (by up to 47%, 63%, 83% respectively) and greatly improve the content acquisition success rate (by up to 356%, 444%, 689%, respectively), compared to the method without cache mechanism.

This work presents a linear smoothing scheme over high-order triangular elements in the framework of a cell-based strain smoothed finite element method for two-dimensional nonlinear problems. The main idea behind the proposed linear smoothing scheme for strain-smoothed finite element method (S-FEM) is no subdivision of finite element cells to sub-cells while the classical S-FEM needs sub-cells. Since the linear smoothing function is employed, S-FEM is able to use quadratic triangular or quadrilateral elements. The modified smoothed matrix obtained node-wise is evaluated. In the same manner with the computation of the strain-displacement matrix, the smoothed stiffness matrix and deformation graident are obtained over smoothing domains. A series of benchmark tests are investigated to demonstrate validity and stability of the proposed scheme. The validity and accuracy are confirmed by comparing the obtained numerical results with the standard FEM using 2nd-order triangular element and the exact solutions.

Growing popularity of buildings with integrated sub-systems, requires a review of methods to optimize the preheat of ventilation air. An integrated system permits using geothermal heat storage parallel to the direct outdoor air intake with additional treatment in the mechanical room as a part of building automatic control system. Earth Air Heat Exchanger (EAHX) has many advantages but also has many unanswered questions. Some of the drawbacks are: a possible entry of radon gas, high humidity in the shoulder seasons as well as the need for two different air intake sources with a choice that depends on the actual weather conditions. While in winter, the EAHX may be used continuously to ensure thermal comfort, in other seasons, its operation must be automatically controlled. To generate the missing information about the EAHX technology we have examined two nearly identical EAHX systems, one placed in ground next to the building and the other under the basement slab. In another project, we have reinforced the ground storage action by heat exchanger placed on the return pipes of the hydronic heating system. Effectively, the information provided in this paper, shows advantages of merging both these approaches while the EAHX could be placed under the house or near the basement foundation that is using an exterior basement insulation.

Directional Modulation (DM) technique, as an emerging promising approach to secure wireless communications, has been attracting increasing attention for its unique characteristic in the past decade. The baseband signal is synthesized at the antenna level for maintaining the standard constellation format along the prescribed direction(s) while simultaneously distorting the signal constellations in other undesired directions. In this paper, we present a novel DM signal synthesis method based on phased array using a hybrid genetic algorithm (GA) and particle swarm optimization (PSO) algorithm, which takes advantages of both GA and PSO algorithm. Then, the bit error rate of the proposed method is analyzed and simulated. Simulation results are presented to verify that the proposed DM signal have a narrower information beam-width. Therefore, it can offer a better physical layer security (PLS) performance compared with the conventional directional modulation signal.

Accurate prediction of defects in software components plays a vital role in administrating the quality of the quality and efficiency of the system to be developed. So we have written a systematic literature review in order to evaluate the four main defect prediction techniques. Defect prediction paves way for the testers to find bugs and modify them in order to achieve input to output conformance. In this paper we have discussed the open issues in predicting software defects and have provided with a detailed analyzation of different methods including Machine Learning, Integrated Approach, Cross-Project and Deep Forest algorithm in order to prevent these flaws. However, it is almost impossible to rule which method is better than the other so every technique can be analyzed separately and the best technique according to the problem at hand can be used or can be altered to create hybrid technique suitable for the cause.

Directional modulation (DM), as an emerging promising physical layer security (PLS) technique at the transmitter side with the help of an antenna array, has developed rapidly over decades. In this study, a DM technique using a polarization sensitive array (PSA) to produce the modulation with different polarization states (PSs) at different directions is investigated. A PSA, as a vector sensor, can be employed for more effective DM for an additional degree of freedom (DOF) provided in the polarization domain. The polarization information can be exploited to transmit different data streams simultaneously at the same directions, same frequency, but with different PSs in the desired directions to increase the channel capacity, and with random PSs off the desired directions to enhance PLS. The proposed method has the capability of concurrently projecting independent signals into different specified spatial directions while simultaneously distorting signal constellation in all other directions. The symbol error rate (SER), secrecy rate, and the robustness of the proposed DM scheme are analyzed. Design examples for single- and multi-beam DM systems are also presented. Simulations corroborate that 1) the proposed method is more effective for PLS; 2) the proposed DM scheme is more power-efficient than the traditional artificial noise aided DM schemes; and 3) the channel capacity is significantly improved compared with conventional scalar antenna arrays.

Today project management in every field of life is prerequisite for the success of project by increasing quality reduces cost and schedule. But selecting tools and techniques to achieve our objectives and implement our plan fully is very difficult task because choice creates complexity. So, we discuss AHP to make decision simple. Ranking critical success factor, cloud computing services, risk prioritization, selection of right ETL software and many other systems AHP plays its important role. For the improvement of today’s complex systems it is very important to prioritize and select projects to remove the root cause of the problem. To attain the right selection of construction equipment for carrying out schedule tasks with high efficiency, production and financial capability is the main purpose of procurement of construction equipment process. Certain conflicts can occur due to the construction of UML models in a collaborative way. AHP is used to remove these conflicts and for establishing and evaluating modelers judgments. Nowadays it is very important and critical decision to choose the best option from multiple alternatives for a successful career after passing 12th standard and also it affects our future. “AHP and TOPSIS” methods are used for this purpose. In this paper, an “AHP and Fuzzy AHP” based hierarchical trust model has been used to rate the service providers and their various plans for infrastructure as a service.

With the advancement in AR technology, more education-based applications are being developed using Augmented Reality, which has revolutionized the learning experience. However, in order to determine the application’s impact on student’s motivation, performance and their communication with the lecturer, various studies are conducted. These studies use one of the three research methodologies for data analysis and evaluation. In this systematic review, we have analyzed various research methodologies for system evaluation of the AR learning applications and recorded the student response toward the system. Also, we checked which methodology is preferred by researchers and why. A total number of 25 studies were analyzed which were published during the year of 2015 and 2019. The results indicate that most popular research technique is mixed methodology as it combines both qualitative and quantitative techniques. The purpose of this review is to offer new insights to researchers and provide them with advice about evaluation of AR applications and which tool or technique is more effective.

The complexity of software is increasing day by day due to the increase in the size of the projects being developed. For better planning and management of large software projects, estimation of software quality is important. During the development processes, complexity metrics are used for the indication of the attributes/characteristics of the quality software. There are many studies about the effect of the complexity of the software on the cost and quality. In this study, we discussed the effects of software complexity on the quality attributes of the software for open source and closed source software. Though, the quality metrics for open and closed source software are not distinct from each other. In this paper, we comparatively analyzed the impact of complexity metrics on open source and private software. We also presented various models for the management of the project complexity such as William’s Model, Stacey’s Agreement and Certainty matrix, Kahane’s Approach and UCP Model. Quality metrics here refer to the standards for the measurement of the quality of software which contains certain attributes or characteristics of the software that are related to the quality of the software. Certain quality attributes addressed in this study are Usability, Reliability, Security, Portability, Maintainability, Efficiency, Cost, Standards and Availability, etc. Both Open source and Closed source software are evaluated on the basis of these quality attributes. This study also recommended future approaches to manage the quality of project Open source and Closed source software and specify which one of them is mostly used in the industry.

Scope, time, and cost permanently effects each other and most of Information Technology projects fails due to these three factors. Scope shifting mostly occur due to time and cost. At project start, lack of understanding of project and product scope is focal involvement that leads to unsuccessful projects. Complete software scope definition determines quality of project. Defining the customer requirement and the definite scope of project has key role for implementation of project management. The complications originates when systems are developed from impractical expectations and misunderstanding requirements. These problems are cause of many changes, occurs in system development and leads to poor scope management. Scope creep is one of the momentous prompting parameter on the success of project. The failure in manage scope creep leads for 80 percent of software projects failure. However, using agile approach the impact of scope creep on projects become insignificant. A correctly distinct scope tends us to develop a quality product, within identified plans and decided cost to the stake-holders.

State-of-the-art dielectrophoretic (DEP) separation techniques provide unique properties to separate particles from a liquid or particles with different properties such as material, morphology or size from each other. However, such separators do not operate at throughput that is sufficient for a vast fraction of separation tasks. The reason for this limitation is that, in order to move particles by dielectrophoresis, high electric field gradients to drive the separation are required. Conventionally, those gradients are generated by electrode microstructures that limit the maximum channel size. Here, we investigate DEP filtration, a technique that uses open porous microstructures instead of microfluidic devices to easily increase the filter cross section and therefore also the processable throughput by several orders of magnitude. Previously, we already separated baker’s yeast by DEP filtration in open porous ceramic structures. Now, we give a more elaborate experimental study about DEP filtration in these open porous structures and separate model particles, that are an order of magnitude smaller (500 nm, polystyrene), from aqueous suspensions. Almost 100% separation at flow rates of up to 9 mL min^-1 was achieved while the majority of the trapped particles could be recovered. We show how particle separation depends on key parameters (voltage, throughput, filter structure size). Further, we work towards selective particle separation and show that particle separation is very dependent on the particle polarizability: This creates the possibility to adjust selectivity by changing the electrical conductivity of the suspension around that of the particle. This study highlights the unique qualities of dielectrophoretic filtration enabling switchable, selective, and scalable particle separation to solve existing problems such as cell separation or precious metal recovery.

Software project complexity increases day by day because the software engineering products is being used in the solution of more technically difficult problem and the size of project continuous to grow. The increase complexity causes to high numbers of software project failures in term of time, cost and quality. The main question regarding to this problem is how to handle or cope with this complexity. There is no single way to handle this, software engineer uses different perspective to handle complexity without affecting the overall project performance. A management perspective recognizes that the success of complex project requires good project management. A technically perspective reveals new paradigms for software development i.e.; object oriented and formal methods etc. and software engineer also look for automation perspective in order to reduce the complexity issues. In this paper we will find out the main software project complexity factors by focusing on the management aspects of software project development and also the problems of managing complexity in software engineering products from these different perspectives. The paper is divided in three main sections; paradigms of software development, project management in term of time, cost and quality and third one is automated support that includes methods and tools used to manage the complexity.

The ongoing electrification of the heat and transport sectors is expected to lead to a substantial increase in peak electricity demand over the coming decades, which may drive significant investment in network reinforcement in order to maintain a secure supply of electricity to consumers. The traditional way of security provision has been based on conventional investments such as the upgrade of the capacity of electricity transmission or distribution lines. However, the energy storage technology can also provide security of supply, thereby constituting a cost-efficient alternative to expensive conventional reinforcements. In this context, the current paper presents a methodology for the economic quantification of the security contribution of energy storage. This methodology makes use of mathematical optimization for the calculation of the F-factor metric, which reflects the optimal amount of peak demand reduction as compared to the power capability of the energy storage asset. In this context, a case study is presented in which the security contribution of energy storage is analyzed as a function of its power capability, energy capacity and efficiency as well as of characteristics of load patterns.

The history of Artificial Intelligence (AI) development dates to the 40s. The researchers showed strong expectations until the 70s, when they began to encounter serious difficulties and investments were greatly, reduced. With the introduction of the Industry 4.0, one of the techniques adopted for AI implementation is Machine Learning (ML) that focuses on the machines ability to receive data series and learn on their own. Given the considerable importance of the subject, researchers have completed many studies on ML to ensure that machines are able to replace or relieve human tasks. This research aims to analyze, systematically, the literature on several aspects, including publication year, authors, scientific sector, country, institution, keywords. Analyzing existing literature on AI is a necessary stage to recommend policy on the matter. The analysis has been done using Web of Science and SCOPUS database. Furthermore, UCINET and NVivo 12 software have been used to complete them. Literature review on ML and AI empirical studies published in the last century was carried out to highlight the evolution of the topic before and after Industry 4.0 introduction, from 1999 to now. Eighty-two articles were reviewed and classified. A first interesting result is the greater number of works published by USA and the increasing interest after the birth of Industry 4.0.

Cooperative non-orthogonal multi access communication is a promising paradigm for the future wireless networks because of its advantages in terms of energy efficiency, wider coverage and interference mitigating. In this paper, we study the secrecy performance of a downlink cooperative non-orthogonal multi access (NOMA) communication system under the presence of an eavesdropper node. Smart node selection based on feed forward neural networks (FFNN) is proposed in order to improve the physical layer security (PLS) of a cooperative NOMA network. The selected cooperative relay node is employed to enhance the channel capacity of the legal users, where the selected cooperative jammer is employed to degrade the capacity of the wiretapped channel. Simulations of the secrecy performance metric namely the secrecy capacity ($C_S$) are presented and compared with the conventional technique based on fuzzy logic node selection technique. Based on our simulations and discussions the proposed technique outperforms the existing technique in term the of secrecy performance.

Gas Path Analysis and matching turbine engine models to experimental data are inverse problems of mathematical modelling which are characterized by parametric uncertainty. This results from the fact that the number of measured parameters is significantly lower than the number of components’ performance parameters needed to describe the real engine. In these conditions, even small measurement errors can result in a high variation of results, and obtained efficiency, loss factors etc. can appear out of the physical range. The current methods of engine model identification have developed considerably to provide stable, precise and physically adequate solutions. Presented in this work is an estimation method of engine components’ parameters based on multi-criteria identification which provides stable estimations of parameters and their confidence intervals with the known measurement errors. A priori information about the engine, its parameters and performance is used directly in the regularised identification procedure. The mathematical basis for this approach is the fuzzy sets theory. Forming objective functions and scalar convolutions synthesis of these functions is used to estimate gas-path components’ parameters. A comparison of the proposed approach with traditional methods showed that its main advantage is high stability of estimation in the parametric uncertainty conditions. Regularization reduces scattering, excludes incorrect solutions which do not correspond to a priori assumptions, and also helps to implement the Gas Path Analysis at the limited number of measured parameters. The method can be used for matching thermodynamic models to experimental data, Gas Path Analysis and also adapting dynamic models for the needs of the engine control system.

In recent decades, widespread damage to structures due to destructive earthquakes has encouraged researchers to use seismic control systems. One of the most important structures is bridges, which should maintain their service after severe earthquakes. One of the ways to control the bridge is to isolation the deck from the substructure, which results in high displacements at different points in the bridge and the residual displacements within the separator itself, thus requiring repair and replacement of these systems after severe earthquakes. Therefore, the use of new seismic separation systems on bridges has always been important. The purpose of this project is to utilize a new memory-shaped seismic separator system to investigate the seismic performance of v-shaped column bridges , in which case the effect of earthquake orientation and its effects on responses the earthquake will also be assessed. Due to the ever-increasing advances in various intelligent materials, such as shape memory alloys, and their unique capacities, such as back-centering, and high fatigue and corrosion resistance, in this study, these materials have been used as a complementary component along with lead core separators. The shape memory alloy has been used as 4 vertical rods that connect two separating parts to each other and in this research the diameter and location of these rods will be calculated using optimization algorithm in Matlab software.

During the extraction of hard coal in Polish conditions, methane is emitted, which is referred to as mine gas. As a result of the desorption of methane, a greenhouse gas is released from coal seams. In order to reduce atmospheric emissions, methane from coal seams is captured by a methane drainage system. On the other hand, methane, which has been separated into underground mining excavations, is discharged into the atmosphere with a stream of ventilation air. For many years, Polish hard coal mines have been capturing methane to ensure the safety of the crew and the continuity of mining operations. As a greenhouse gas, methane has a significant potential, as it is more effective at absorbing and re-emitting radiation than carbon dioxide. The increase in the amount of methane in the atmosphere is a significant factor influencing global warming, however, it is not as strong as the increase in carbon dioxide. Therefore, in Polish mines, the methane-air mixture captured in the methane drainage system is not emitted to the atmosphere, but burned as fuel in systems, including cogeneration systems, to generate electricity, heat and cold. However, in order for such use to be possible, the methane-air mixture must meet appropriate quality and quantity requirements. The article presents an analysis of changes in selected parameters of the captured methane-air mixture from one of the hard coal mines in the Upper Silesian Coal Basin in Poland. The paper analyses the changes in concentration and size of the captured methane stream through the methane capturing system. The gas captured by the methane drainage system, as an energy source, can be used in cogeneration, when the methane concentration is greater than 40%. Considering the variability of CH4 concentration in the captured mixture, it was also indicated which pure methane stream must be added to the gas mixture in order for this gas to be used as a fuel for gas engines. The balance of power of produced electric energy in gas engines is presented. Possible solutions ensuring constant concentration of the captured methane-air mixture are also presented.

Application of solid catalysts synthesized from agricultural wastes provides an environmentally benign and low-cost process route to the synthesis of biodiesel. An ash containing equal mixture of cocoa pod husk, plantain peel and kola nut pod husk ashes (CPK) which was obtained by open combustion of each biomass in air and calcined at 500 oC for 4 h. The calcined CPK ash was characterized to determine its catalytic potential. Two-level transesterification technique was used to synthesize biodiesel using the developed catalyst. The process parameters involved were optimized for the microwave-aided transesterification of a blend of honne, rubber seed and neem oils in volumetric ratio 20:20:60, respectively. The study showed that ash derived from combination of various biomass wastes provides a catalyst which consists all necessary catalytic ingredients in their relative abundance. The calcined CPK consists of 47.67% of potassium, 5.56% calcium and 4.21% magnesium attesting to its heterogenous status. The physisorption isotherms reveals that it was dominantly mesoporous in structure made up of nanoparticles. Maximum of 98.45 wt.% biodiesel was obtained through MeOH:oil blend of 12:1, CPK concentration of 1.158 wt.% and reaction time of 6 min under microwave irradiation. Quality of the synthesized biodiesel satisfied the requirements stipulated by standard specifications. Thus, this work demonstrates that blend of agrowastes and mixture of non-edible oils could be used to synthesize quality and sustainable biodiesel that can replace fossil diesel.

Aiming at the current optimization problem of electric vehicle charging path planning, a charging path optimization strategy for electric vehicles under the "Traffic-Price-Distribution" mode is proposed. This strategy builds an electric vehicle charging and navigation system based on road traffic network model, real-time electricity price model and distribution network model. Based on Dijkstra shortest path algorithm and Monte Carlo time-space prediction method, the goal is to minimize the charging cost of electric vehicles. Optimal charging path. The simulation results of MATLAB and MATPOWER show that the electric vehicle charging path optimization strategy can better solve the local traffic congestion problem and improve the safety and stability of the distribution network on the basic of fully considering the convenience of electric vehicle charging.

This paper presents the systematic development and performance characterization of a non-proprietary 3D-printable ultra-high-performance fiber-reinforced concrete (UHPFRC) for digital construction. Several fresh and hardened properties of the developed 3D-printable UHPFRC matrix (without fiber) and composite (with 2% volume fraction of steel fibers) were evaluated and compared to that of conventionally mold-cast UHPFRC. Additionally, the effects of testing direction on the compressive and flexural strengths of the printed UHPFRC were investigated. The fresh properties of the UHPFRC developed in this study satisfied the criteria for extrudability, buildability, and shape-retention-ability, which are relevant for ensuring printability. The printed UHPFRC exhibited superior flexural performance to the mold-cast UHPFRC due to alignment of the short fibers in the printing direction. The high compressive and flexural strengths, along with the deflection-hardening behavior, of the developed UHPFRC can enable the production of thin 3D-printed components with significant reduction or complete elimination of conventional steel bars.

Metal matrix composite are used in such fields of technology, such as: aerospace, electronics, energy, industry, defense, automotive, aviation, shipbuilding, and more. Composite coatings of ceramic - metals is used primarily to enhance the durability of machine parts. Therefore, new materials are permanently looked for, what has resulted in the past in development of composite materials. The coatings dispersed are consisting of metallic matrix (metals and their alloys) and small non-metallic particles. The deposition of ceramic particles simultaneously with metallic matrix leads often to composite coatings possessing properties much better than those of metallic coating. The nickel and less often, other iron group elements are usually used as a matrix and Al2O3 as tough particles. The welding technology of applying alloy and composite coatings is widely used. The technology of infrasound thermal spraying of metal matrix composite coatings was presented. It is a simple technology and a very useful one in ship machinery regeneration during the cruise craft (e.g. internal combustion engines, torque pumps, separators). The metal matrix composite coatings must undergo finishing due to high surface roughness after application. In the article to used finishing by plastic working and machining of coatings nickel matrix composite was proposed.

Since World War I, the commercial aviation industry has seen many improvements that now allow people and goods to reach the other side of the world in few hours, consuming much less fuel than in recent decades. Improvements in cargo capacity and energy efficiency were significant and, in this scenario, commercial airlines were able to thrive and bring great benefits to world economy. However, this sector is facing environmental challenges due to the intensive use of aviation fuel. Brazil is one of the largest domestic air passenger markets in the world and still has great growth potential, considering its economic potential and territorial dimensions: roughly the same size as the US and twice the size of the European Union. This paper discusses partial productivity of jet fuel in Brazilian domestic aviation and proposes an econometric method to support public regulators and airlines decisions. The proposed model uses variables such as aircraft size, route characteristics and idle flight capacity in a panel data analysis. The results show that reducing idle capacity is one of the best ways to achieve better short-term fuel efficiency and therefore will reduce environmental impacts and have positive economic effects on commercial air transport activities.

Over the past few years, we have experienced great technological advancements in the information and communication field, which has significantly contributed to reshaping the Intelligent Transportation System (ITS) concept. Evolving from the platform of a collection of sensors aiming to collect data, the data exchanged paradigm among vehicles is shifted from the local network to the cloud. With the introduction of cloud and edge computing along with ubiquitous 5G mobile network, it is expected to see the role of Artificial Intelligence (AI) in data processing and smart decision imminent. So as to fully understand the future automobile scenario in this verge of industrial revolution 4.0, it is necessary first of all to get a clear understanding of the cutting-edge technologies that going to take place in the automotive ecosystem so that the cyber-physical impact on transportation system can be measured. CIoV, which is abbreviated from Cognitive Internet of Vehicle, is one of the recently proposed architectures of the technological evolution in transportation, and it has amassed great attention. It introduces cloud-based artificial intelligence and machine learning into transportation system. What are the future expectations of CIoV? To fully contemplate this architecture’s future potentials, and milestones set to achieve, it is crucial to understand all the technologies that leaned into it. Also, the security issues to meet the security requirements of its practical implementation. Aiming to that, this paper presents the evolution of CIoV along with the layer abstractions to outline the distinctive functional parts of the proposed architecture. It also gives an investigation of the prime security and privacy issues associated with technological evolution to take measures.

An ion exchange dialysis (IED) is used in the recovery of aluminium from residue. In this papers, the face-centered central composite design (FC-CCD) of the response surface methodology (RSM) and desirability approach is used for experimental design, modelling and process optimization of a counter flow IED system. The feed concentration, feed flowrate, sweep flowrate and sweep concentration are selected as the process variables, with the Al-transport across a Nafion 117 membrane as the target response. A total of 30 experimental runs were conducted with 6 center points. The response obtained was analysed by analysis of variance (ANOVA) and fitted to a second-order polynomial model using multiple regression analysis. The actual R2 and standard deviation of the model are 0.9548 and 0.2932 respectively. The influences of significant variables are plotted on 3D surface and contour plots. The designed variables were numerically optimized by applying the desirability function to achieve the maximum Al-transport. The optimised condition values were found to be feed concentration (1600 ppm), feed flowrate (61.76%), sweep flowrate (37.50%) and sweep concentration (0.75 N) for the 80% target response at 32hrs. Overall, the model can be used to effectively predict Al-recovery using the designed system

Due to the advantages such as low power consumption and higher concealment, deceptive jamming against synthetic aperture radar (SAR) receives extensive attention during the past decades. However, the large scene deception jamming is still a challenge because of the huge computing burden. In this paper, we propose a new large scene deceptive jamming algorithm. First, the time-delay and frequency-shift (TDFS) algorithm is introduced to improve the jamming processing speed. The system function of jammer (JSF) for a fake scatter is simplified to the multiplication of the scattering coefficient, a time-delay term in range dimension and a frequency-shift term in azimuth dimension. Then, in order to solve the problem that the effective region of the TDFS algorithm is limited, the scene deceptive jamming template is divided into several blocks according to the SAR parameters and imaging quality control factor. The JSF of each block is calculated by the TDFS algorithm and added together to achieve the large scene jamming. Finally, the correction algorithm in squint mode is derived. The simplification and parallel block processing could improve the calculation efficiency significantly. The simulation results verified the validity of the algorithm.

The water and wastewater sectors are energy-intensive, and so a growing number of utility companies are seeking to identify opportunities to reduce energy use. Though England’s water sector is of international interest, in particular due to the early experience with privatisation, for the time being very little published data on energy usage exists. We analyse telemetry data from Thames Water Utilities Ltd. (TWUL), which is the largest water and wastewater company in the UK and serves one of the largest mega-cities in the world, London. In our analysis, we (1) break down sectoral energy use into their components, (2) present a statistical method to analyse the long-term trends in use, as well as the seasonality and irregular effects in the data, (3) derive energy-intensity (kWh m³) figures for the system, and (4) compare the energy-intensity of the network against other regions in the world. Our results show that electricity use grew during the period 2009 to 2014 due to capacity expansions to deal with growing water demand and storm water flooding. The energy-intensity of the system is within the range of reported figures for systems in other OECD countries. Plans to improve the efficiency of the system could yield benefits in lower the energy-intensity, but the overall energy saving would be temporary as external pressures from population and climate change are driving up water and energy use.

The Blended Wing Body (BWB) configuration is considered to have the potential of providing significant advantages when compared to conventional aircraft designs. At the same time, numerous studies have reported that technical challenges exist in many areas of its design, including stability and control. This study aims to create a novel BWB design to test its flying and handling qualities using an engineering flight simulator and as such, to identify potential design solutions which will enhance its controllability and manoeuvrability characteristics. This aircraft is aimed toward the commercial sector with a range of 3,000 nautical miles, carrying a payload of 20,000kg. In the engineering flight simulator a flight test was undertaken; first, to determine the BWB design’s static stability through a standard commercial mission profile, and then to determine its dynamic stability characteristics through standard dynamic modes. Its flying qualities suggested its stability with a static margin of 8.652% of the Mean Aerodynamic Chord (MAC) and consistent response from the pilot input. In addition, the aircraft achieved a maximum lift-to-drag ratio of 28.1; a maximum range of 4,581 nautical miles; zero-lift drag of 0.005; and meeting all the requirements of the dynamic modes.

Fatigue in any material is a result of continuous irreversible degradation process. Traditionally, fatigue life is predicted by extrapolating experimentally curve fitted empirical models. In the current study, unified mechanics theory is used to predict fatigue life of Ti-6Al-4V under monotonic tensile, compressive and cyclic load conditions. The unified mechanics theory is used to derive constitutive model for fatigue life prediction using a three-dimensional computational model. The proposed analytical and computational models have been used to predict the low cycle fatigue life of Ti-6Al-4V alloys. It is shown that the unified mechanics theory can be used to predict fatigue life of Ti-6Al-4V alloys by using simple predictive models that are based on fundamental equation of the material, which is based on thermodynamics associated with degradation of materials.

The measurement range of a conventional current sensor is narrow because it is used with signals relative to the rated values of the measurement range from a voltage-type device. Consequently, multiple current sensors must be used in accordance with the measurement range. To address this problem, this paper proposes a new current sensor with a clamp-shaped part for low current measurement and a simple straight structure for high current measurement. The output signals of the proposed current sensor are amplified with a Hall element using the magnetic force of a rectangular air gap inside the clamp. To verify the characteristics of the proposed current sensor, a current was applied to an external load, and the value determined by the current sensor noted. Then, electromagnetic field analysis was performed through current sensor modeling and the results obtained compared to the actual sensor results. The proposed sensor had a 1% linearity in the output signals and exhibited dynamic characteristics over a wide current range.

Microfluidics is facing critical challenges in the quest of miniaturizing, integrating, and automating in vitro diagnostics, including the increasing complexity of assays, the gap between the macroscale world and the microscale devices, and the diverse throughput demands in various clinical settings. Here a “3D extensible” microfluidic design paradigm that consists of a set of basic structures and unit operations was developed for constructing any application-specific assay. Four basic structures- check valve (in), check valve (out), double-check valve (in and out), and on-off valve, were designed to mimic basic acts in biochemical assays. By combining these structures linearly, a series of unit operations can be readily formed. We then proposed a “3D extensible” architecture to fulfill the needs of the function integration, the adaptive “world-to-chip” interface, and the adjustable throughput in the X, Y, and Z directions, respectively. To verify this design paradigm, we developed a fully integrated loop-mediated isothermal amplification microsystem that can directly accept swab samples and detect Chlamydia trachomatis automatically with a sensitivity one order higher than that of the conventional kit. This demonstration validated the feasibility of using this paradigm to develop integrated and automated microsystems in a less risky and more consistent manner.

Canopy characteristics are crucial for accurately and safely determining the pesticide quantity and volume of water used for spray applications in vineyards. The inevitably high degree of intra-plot variability makes it difficult to develop a global solution for the optimal volume application rate. Here, the design procedure of, and the results obtained from, a variable rate application (VRA) sprayer are presented. Prescription maps were generated after detailed canopy characterization, using a multispectral camera embedded on an unmanned aerial vehicle, throughout the entire growing season in Torrelavit (Barcelona) in four vineyard plots of Chardonnay (2.35 ha), Merlot (2.97 ha), and Cabernet Sauvignonn (4.67 ha). The maps were obtained by merging multispectral images with information provided by DOSAVIÑA®, a decision support system, to determine the optimal volume rate. They were then uploaded to the VRA prototype, obtaining actual variable application maps after the application processes were complete. The prototype had an adequate spray distribution quality and exhibited similar results in terms of biological efficacy on powdery mildew compared to conventional (and constant) application volumes. The VRA results demonstrated an accurate and reasonable pesticide distribution, with potential for reduced disease damage even in cases with reduced amounts of plant protection products and water.

Unmanned surface vehicles have the advantages of maneuverability, concealment, wide activity area and low cost of use. Therefore, they have broad application prospects. This makes unmanned surface vehicles a research hotspot at home and abroad, and the sensing technology is the basis for the unmanned surface vehicles to perform tasks. The perception technology based on optical vision has the advantages of convenient application, relatively low cost, easy data acquisition and large amount of information, and has been widely studied by scholars at home and abroad. This paper mainly discusses the research of optical vision in unmanned surface vehicles from five aspects: Firstly, the water surface image preprocessing based on unmanned surface vehicles, mainly including water surface image stabilization research and defogging enhancement research; two water boundary detection; It is the use of light vision target detection; the fourth is the surface target tracking method. Finally, the light vision research of unmanned surface vehicles is summarized and forecasted.

The renewable energy source plays a major role in the grid side power production. The stability analysis is very essential in the renewable energy converters. In this paper the bifurcation is analyzed in ZETA converter and Continuous input and output(CIO) power Buck Boost converter. The ZETA converter gives positive step down and step up output voltage and the CIO power converter gives the negative step up and step down output voltage. These converters are used in the DC micro grid with renewable energy as the source. The current mode control technique is applied to analyze the bifurcation behavior and the reference current is taken as the bifurcation parameter. When the reference current is varied, both the converters loses its stability and it enters into chaotic region through period doubling bifurcation. The simulation results are presented to study the performance behavior of both the converters. The stability region of both the converters are determined by deriving the Monodromy matrix approach.

Considering the fault "N-1" checksum and the power flow, the single-phase power flow model is further transformed into a three-phase power flow model, and the asymmetry of the three-phase power flow is measured by the three-phase unbalance factor. The calculation model is linearized by the second-order cone relaxation and the Big-M method. At the same time, the load response and distribution network reconstruction are used to improve the reliability of the power supply network to cope with the power failure. The relationship between power supply capability and power flow constraints, main transformer capacity and distributed power parameters is analyzed by IEEE 33-node three-phase power distribution system. The feasibility of the proposed model and the accuracy of the second-order cone relaxation are verified by numerical examples, which provides a technical reference for distribution network planning.

Complex blade responses such as a rotating stall or simultaneous resonances are common in modern engines and their observation can be a challenge even for state-of-the-art tip-timing systems and trained operators. This paper analyses forced vibrations of axial compressor blades, measured during the bench tests of the SO-3 turbojet. In relation to earlier studies conducted in ITWL with a small number of sensors, a multichannel tip-timing system let us observe simultaneous responses or higher-order modes. To find possible symptoms of a failure, blade responses in a healthy and unhealthy engine configuration with an inlet blocker were studied. The used analysis methods covered all-blade spectrum and the circumferential fitting of blade deflections to the harmonic oscillator model. The proposed modal solver can track the vibration frequency and adjust the engine order on the fly. That way, synchronous and asynchronous vibrations are observed and analysed together with an extended variant of least squares. The proposed approach helps to avoid common mistakes and saves a lot of work related to configuring the conventional solver.

A cognitive radio sensor network (CRSN) based Smart Grid (SG) is a new paradigm for a modern SG. It is totally different from the traditional power grid and also different from the conventional SG that uses a static resource allocation technique to allocate resources to sensor nodes and communication devices in the SG network. Due to the challenges associated with competitive sensor nodes and communication devices in accessing and utilizing radio resources, the need for dynamic radio resource allocation (RRA) has been proposed as a solution for allocating radio resources to sensor nodes in a CRSN based smart grid ecosystem (network). These challenges include energy/power constraints, poor quality of service (QoS), interference, delay, spectrum efficiency issues, and excessive spectrum hand-offs. Hence, the optimization of resource allocation criteria, such as energy efficiency, throughput maximization, QoS guarantee, fairness, priority, interference mitigation/avoidance, etc., will go a long way in addressing the problems of RRA in a CRSN based SG. Consequently, this work explores RRA in CRSNs for SGs. Various resource allocation schemes, as well as its architecture in a CRSN for SG environment, are presented. The work reported in this paper introduces a model called the “guaranteed network connectivity channel allocation” for throughput maximization (GNC-TM) and optimal spectrum band determination in RRA for improved throughput criteria in CRSNs for SGs. The results show that the model outperforms the existing protocol in terms of throughput and error probability. Finally, the contribution to knowledge and future research direction, such as energy efficiency and hybrid energy harvesting schemes are highlighted.

The purpose of feature selection is to find important features from the original high-dimensional space. As atypical feature selection algorithm, Locally linear embedding(LLE)-based feature selection algorithm, which applies the idea of LLE to the graph-preserving feature selection framework, has been received wide attention. However, LLE-based feature selection framework is sensitive to noise and K-nearest neighbors. To address these problems, an improved LLE-based feature selection algorithm, robust LLE (RLLE) vote, is proposed. In this algorithm, $l_1$ and $l_2$ regularization are introduced into the high-dimensional reconstruction model of LLE. Furthermore, RLLE vote also proposes a criterion to measure the difference between the reconstruction features and the original features, and then the importance features can be selected by this criteria. Extensive experiments are carried out on a benchmark fault data set and the bearing data set collected from our own laboratory, and the experimental results demonstrate that RLLE vote achieves the most significant performance compared existing state-of-art methods.

In the present trend of constructing taller and longer structures, the application of lightweight aggregate concrete is becoming an increasing important advanced solution in the modern construction industry. In engineering practice, the analysis of lightweight concrete elements is performed using the same algorithms used for normal concrete elements. As an alternative to traditional engineering methods, nonlinear numerical algorithms based on constitutive material models may be used. The paper presents a comparative analysis of curvature calculations for flexural lightweight concrete elements, incorporating analytical code methods EN 1992-1 and ACI 318-14, as well as a numerical analysis using the constitutive model of cracked tensile lightweight concrete recently proposed by the authors. To evaluate the adequacy of the theoretical predictions, experimental data of 51 lightweight concrete beams tested during five different programmes were collected. A comparison of theoretical and experimental results showed that the most accurate predictions are obtained using numerical analysis and the constitutive model proposed by the authors. In the future, the latter algorithm can be used as a reliable tool for improving the design standard methods or numerical modelling of lightweight concrete elements subjected to short-term loading.

Demand responsive transport (DRT) is operated according to flexible routes, dispatch intervals, and dynamic demand, is attracting a lot of attention. The biggest characteristic of DRT service is that the vehicle routes and schedules are operated optimally based on real-time travel requests of using passengers without fixed operating schedules. Today, the smart-city era has arrived, particularly because of progress in the wireless communications technology and technology related to location information service and real-time passenger demands and requests, and services that change the vehicles’ operating schedules in real-time according to dynamic demand have attracted more attention. In this study, we analyze the effects of the DRT system to solve the first mile/last mile problem based on a proposed DRT routing algorithm considering real-time travel behavior. The algorithm is modified from the dynamic vehicle routing problem (DVRP), in which a DRT-based routing algorithm tends to minimize users’ cost and providers’ operation cost. So far, the DVRP has only been able to serve a single request per vehicle at a time. However, this needs to be extended for the purpose of DRT, wherein several passengers board a vehicle at the same time. The routing algorithm can serve multiple requests at a time and schedule picks ups, drop offs, and rides according to the requests and as calculated by the dispatch algorithm. The basic principle of routing is as follows. The DRT vehicle moves on an attractive path and picks up a passenger if boarding is requested, but it does not simply hang around as a DVRP would. In this step, if another DRT vehicle is present near another passenger, the vehicle that would minimize that passenger’s total travel time picks up the passenger. The optimal routing algorithm developed in this study is applied to the activity-based model; that is, a microscopic traffic demand estimation method is implemented through an activity-based model by using an open-source, activity-based model package called Multi-Agent Transport Simulation (MATSim). MATSim is used for the simulation, because it combines a multi-modal traffic flow simulation with a scoring model for agents, and it provides co-evolutionary algorithms that can alter agents’ daily routines. This process is applied to a type of mode choice and route choice repeatedly over several iterations until some form of user equilibrium has been reached. This study analyzed the feasibility of implementing the DRT service by analyzing the benefits for the users and cost of the operator from the effects of increasing public transportation use and providing personalized mobility service based on DRT implementation by the introduction of DRT will be analyzed according to the scale of DRT supply. Through the simulation, the DRT is expected to provide convenient, fast, and cost-effective mobility services to customers; provide an optimal vehicle scale to providers; and, ultimately, achieve a safe and efficient transportation system.

This study presents a path planning method for a mobile robot to be effectively operated through a multi-objective decision-making problem. Specifically, the proposed Fuzzy analytic hierarchy process (FAHP) determines an optimal position as a sub-goal within the multi-objective boundary. The key features of the proposed FAHP are evaluating the candidates according to the fuzzified relative importance among objectives to select an optimal solution. In order to incorporate FAHP into path planning, an AHP framework is defined, which includes the highest level (goal), middle level (objectives), and the lowest level (alternatives). The distance to the target, robot’s rotation, and safety against collision between obstacles are considered as objective functions. Comparative results obtained from the artificial potential field and AHP/FAHP simulations show that FAHP is much preferable for the mobile robot’s path planning than typical AHP.

The paper presents an extensometer designed to measure two mechanical strains at the same time—one from tensile load and the other from torsion load. Strain transducers provide different electric signals, which, after calibration, lead to the simultaneous measurement of linear (ε) and angular (γ) strains. Each of these two signals depends on the measured process and is not influenced by the other strain process. This extensometer is designed to be easily mounted on the sample with only two mounting points and can be used to measure the combined cyclical fatigue of tensile and torsional loadings. This extensometer has two bars—one rigid, reported at the resulting stress points, and one elastic and deformable. The elastic deformable bar has two beams with different orientations. When the sample is deformed, both beams are loaded by two bending moments (perpendicular to each other and both perpendicular on the longitudinal axis of the bars).

Dams design and their operation cause strong environmental alteration and therefore a long-term debate is ongoing for the scale of these projects. At the same time, the concept of Environmental Flow Assessment (EFA) is a crucial element of modified ecosystems featuring large infrastructure such as dams and reservoirs for mitigating potential environmental degradation while they operate. Nowadays, integrated scientific frameworks are required to quantify the risks caused by large infrastructure. Through the use of stochastic analysis, it is possible to quantify these uncertainties, and present a solution that incorporates long-term persistence and environmental sustainability into a balanced reservoir simulation model. In this work, an attempt is made to determine a benchmark reservoir size incorporating hydrological and ecological criteria though stochastic analysis. The primary goal is to ensure the best possible conditions for the ecosystem, and then secondarily to allow a steady supply of water for other uses. Using a synthetic timeseries based on historical inputs, it is possible to determine and preserve essential statistical characteristics of a river’s streamflow, and use these to detect the optimal reservoir capacity that maximizes environmental and local water demand reliability.

In Safety Management System (SMS), the risk management plays a key role for the prevention of accidents. The aim of this paper is to propose a Safety Management model using a system dynamic approach to update conventional industrial safety into the new industrial safety 4.0 that is time to developed. This study analyzes some safety 4.0 aspects lacked in the Bhopal incidental event by considering different data detected in the industrial Plant. The model proposed in this paper discusses the relationships among the main causes that have contributed to the occurrence of the incidental event studied, such as broken safety devices, inadequate personnel experience, operator decisions, manager production strategy, policy decision, as deduced from the relevant literature about Bhopal incidental dynamic.

Influence of core flow inlet swirl angle on aerodynamic performances of an exhaust nozzle with scarfed lobed mixer was studied by the validated computational approach. The computational simulation was conducted by resolving the steady form of discretized three-dimensional Reynolds Averaged Navier-Stokes equations with the shear stress transport k-Ω turbulence model. Simulation results depict that swirling motions have ignorable influence on the flow field of the top part in the cross sections slightly downstream of the lobed trailing edge. Besides, for the flow field downstream of the L/D=0.1 cross section, the swirling motions are suggested to cause the clockwise stream-wise vortex to stretch into several smaller-scale vortexes. When the case with a bigger swirling angle is investigated, the induced smaller-scale vortexes are more strengthened by the swirling motions. Concerning the 15° swirling case, the loss caused by the destroyed vortex pattern and the benefit induced by the improved smaller-scale vortexes almost counteract with each other with respect to the thermal mixing efficiency. In the last studied cross section as compared with the baseline case, the case with a maximum swirling angle of 30° has increased 6.94% for the thermal mixing efficiency and decreased 0.42% for the total pressure recovery coefficient.

Modeling fluid flow in three-dimensional (3D) Discrete Fracture Networks (DFNs) is of relevance in many engineering applications, such as hydraulic fracturing, oil/gas production, geothermal energy extraction, nuclear waste disposal and CO₂ sequestration. A new Boundary Element Method (BEM) technique with discontinuous quadratic elements and a parallel Domain Decomposition Method (DDM) is presented herein for the simulation of the steady-state fluid flow in 3D DFN systems with wellbores, consisting of planar fractures having arbitrary properties and wellbore trajectories. Numerical examples characterized by DFNs of increasing complexity are investigated to evaluate the accuracy and efficiency of the presented technique. The results show that accurate solutions can be obtained with less nodes than with mesh-based methods (e.g. Finite Element Method). In addition, the DDM algorithm used provides a quite fast convergence. The simulation results of the fluid flow around intersections among traces (linear intersections between fractures), intersections between traces and a fracture boundaries, and wellbore intersections is accurate. Source code is available at : https://github.com/BinWang0213/PyDFN3D.

In recent years, the anticipation of sustainable commercial supersonic jet operations has elevated again. Advances in propulsion together with the increased usage of composite materials favour the potential of sustained and cost efficient supersonic commercial operations. However, obstacles remain with regards to the certification of the new supersonic aircraft platforms, while the two main certification bodies EASA and FAA are under pressure to develop certification requirements which will reassure that the supersonic operations are going to have the least possible environmental impact. From a design perspective, past and current research suggests that a trade-off exists between the aircraft performance and the environmental impact, which should be balanced. The current study attempts to balance this trade-off and to conceptually design a SuperSonic Business Jet (SSBJ) by taking into account environmental concerns of the supersonic flight together with design methods that facilitate a sustained supersonic cruise. An environmental impact assessment is undertaken for the SSBJ design and its results are compared to a typical commercial subsonic airliner.

The current rapidly changing and highly competitive market has put companies under a great pressure not only to be successful, but also to sustain their success into the future. In addition, in recent years, companies have become more aware of the fact that it is no longer enough to take care of economic aspects, being crucial to also take care of environmental and social aspects in order to actually succeed and lead in the current and future markets. In this context, companies are urged to move towards more innovative manufacturing practices that maintain a healthy balance among economic, environmental and social performances, which are the three pillars of the sustainability performance. To give some insight into this issue, a Systematic Literature Review (SLR) is conducted in this paper regarding the current trends in the field, doing special focus on the link between lean-green manufacturing and the different sustainability aspects. The SLR concluded that lean and green implementations as stand-alone systems are usually not enough to ensure the required balance between the three pillars of sustainability, suggesting further combining them into a single approach. Researchers expect to achieve further improvements in the sustainability performance moving towards the next level of sustainability.

Planning and implementation of construction projects are difficult processes and are burdened with many risk elements. The budget spread over time, which is developed on the basis of the schedule, presents the expected distribution of costs throughout the duration of the works, which during the implementation of the project is subject to constant changes resulting from time, cost and organizational factors. Managing construction contracts requires managers to be able to analyze on an ongoing basis the variances of production costs - from the values calculated in the offer cost estimate and assumed in the Budgeted Cost of Work Scheduled. The article attempts to analyze the emerging time and cost variances using proprietary C-S and S-C monitoring, based on simple indicators of the EVM method. An example of construction of a multi-family housing development was used to study the variances of planned and incurred costs.

Wi-Fi fingerprinting positioning systems have been deployed for a long time in location-based services for indoor environments. Combining mobile crowdsensing and Wi-Fi fingerprinting systems could reduce the high cost for collecting the necessary data enabling the deployment of the resulting system for outdoor positioning in areas with dense Wi-Fi coverage. In this paper, we present the results attained in the designing and evaluation of an urban fingerprinting positioning system based on crowdsensed Wi-Fi measurements. We first asses the quality of the collected measurements, highlighting the influence of received signal strength on data collection. We then, evaluate the proposed system by comparing the influence of the crowdsensed fingerprints on the overall positioning accuracy for different scenarios. The evaluation helps gain valuable insight into the design and deployment of urban Wi-Fi positioning systems while also allowing the proposed system to match GPS-like accuracy in similar conditions.

The next generation of wireless and mobile networks will have to handle a significant increase in traffic load compared to the actual one. This situation calls for novel ways to increase spectral efficiency. Therefore in this paper, we propose a wireless spectrum hypervisor architecture that abstracts a radio frequency (RF) front-end into a configurable number of virtual RF front-ends. The proposed architecture has the ability to enable flexible spectrum access in existing wireless and mobile networks, which is a challenging task due to the limited spectrum programmability, $i.e.$, the capability a system has to change the spectral properties of a given signal to fit an arbitrary frequency allocation. The main goal of the proposed approach is to improve spectral efficiency by efficiently using vacant gaps in congested spectrum-bandwidths or adopting network densification through infrastructure sharing. We demonstrate mathematically how our proposed approach works and present several simulation results proving its functionality and efficiency. Additionally, we designed and implemented an open-source and free proof of concept prototype of the proposed architecture, which can be used by researchers and developers to run experiments or extend the concept to other applications. We present several experimental results used to validate the proposed prototype. We demonstrate that the prototype can easily handle up to 12 concurrent physical layers.

Research shows that in earthquakes the ground response changes in areas where there are underground cavities. Due to the fact that subways and underground tunnels pass from beneath buildings in urban areas, these changes in ground response have a direct impact on the seismic behavior of structures. In this study, first by model validity and reliability of the results, steel structures modeling was conducted and steel structure behavior was evaluated due to Tunnel-Soil-Structure seismic interaction. Parameters studied are number of stories, soil type, tunnel depth, horizontal tunnel-structural distance and dynamic loading. Considering that one of the most important parameters of structural control is drift and story displacement, so this important factor will be considered. The results show that tunneling has a direct effect on the rate of structural displacement and increases the structural response. Also, the behavior of the structure is affected by the position of the structure at the ground level and the position of the tunnel and this should be considered during the design phase of the structures.

Internet of things security will be a big challenge for the enterprises working behind the build-up of the internet of things, and it’s application. With IoT, another buzzword is blockchain-based cryptocurrency bitcoin. Blockchain technology has proven itself as one of the most secured existing technology. In this paper, we have discussed the significant challenges that will come up in identity management due to the heterogeneity of devices. We have proposed a solution for privacy preservation using secure identity management and possible communication methodology by using public key-based cryptography used in the blockchain. We have taken the ecosystem of smart home management and smart health management. At last, we have concluded with the discussion of futuristic applications of blockchain in other applications of the internet of things.

Free Floating Car Sharing (FFCS) services are a flexible alternative to car ownership. These transportation services show highly dynamic usage both over different hours of the day, and across different city areas. In this work, we study the problem of predicting FFCS demand patterns -- a problem of great importance to an adequate provisioning of the service. We tackle both the prediction of the demand i) over time and ii) over space. We rely on months of real FFCS rides in Vancouver, which constitute our ground truth. We enrich this data with detailed socio-demographic information obtained from large open-data repositories to predict usage patterns. Our aim is to offer a thorough comparison of several machine learning algorithms in terms of accuracy and easiness of training, and to assess the effectiveness of current state-of-art approaches to address the prediction problem. Our results show that it is possible to predict the future usage with relative errors down to 10%, and the spatial prediction can be estimated with relative errors of about 40%. Our study also uncovered the socio-demographic features that most strongly correlate with FFCS usage, providing interesting insights for providers opening service in new regions.

Recent works in mechanical fatigue consider that a threshold of entropy exists, the fracture fatigue entropy. The determination of this quantity is usually done considering empirical models for the mechanical power estimation. In this paper, we experimentally observe the existence of a threshold of entropy and exergy in low cycle fatigue for a flat Al-2024 specimen avoiding the use of a model, solely measuring the heat generated during a fatigue test. Results are then compared considering various hypotheses (1D heat dissipation with convection and radiation considered as heat sources, and, heat transfer from a fin with convection and radiation as boundary conditions) to an empirical mechanical model known in the literature and deviations between them are discussed.

The high consumption of firewood in Honduras requires the search for alternatives that reduce its negative effects on health, economy, and the environment. One of these alternatives has been the promotion of improved cooking stoves, which achieve a large reduction in firewood consumption. This paper shows a cost-benefit analysis for an improved cooking stove adoption strategy for Honduras. The methodology uses the Long-range Energy Alternatives Planning System, LEAP, a tool globally used in the analysis and formulation of energy policies and strategies. The energy model considers the demand for firewood as well as the gradual introduction of improved cooking stoves, according to premises of a National Strategy. Hence, it is demonstrated that the costs of implementing this adoption strategy are lower than the costs of not implementing it, taking into consideration various scenarios up to and including the year 2030.

Additive manufacturing (AM) is a promising new technology that is having a very fast growth from home workshops to high-tech cutting-edge factories. As any manufacturing technique, adequate metrology services are needed to assure the quality of items manufactured by AM. One of the most widely used instruments to measure the characteristics of surfaces manufactured with AM is the confocal microscope. In this paper, authors present a whole calibration procedure for confocal microscopes designed to be implemented preferably in workshops or industrial environments rather than in research and development departments. Because of that, it is as simple as possible. The procedure is designed without forgetting any of the key aspects that need to be taken into account and based on classical reference material standards. These standards can be easily found in industrial dimensional laboratories and easily calibrated in accredited calibration laboratories.

Permanent magnet synchronous motor (PMSM) AC servo system shows the characteristics of uncertainty, time-varying and non-linearity, which makes it difficult for traditional PID control to achieve ideal control effect. Fuzzy control has strong adaptability to the problems of parameter variation, non-linearity and model inaccuracy of the controlled object. Vector control strategy is used to study its control principle and the realization of SVPWM. Because the motor object has certain fractional order characteristics, the fuzzy parameter self-tuning PIλ control is chosen as the position regulator of servo motor. It combines the accuracy of fractional order PI control and the adaptability of fuzzy control. A simulation model of PMSM three-closed-loop system is built in MATLAB/Simulink environment. The results show that the control method is effective and can satisfy the trajectory tracking of servo control.

In this study the processes taking place on the surfaces of nanostructurized Cu/CuO and Cu/CuO/Pd electrodes at different potential, $E$, values in the solutions of 0.1 M KOH in H$_2$O and D$_2$O (heavy water) were probed by the surface enhanced Raman spectroscopy (SERS) and analysis of electrochemical reactions occurring under experimental conditions is presented. Bands of the SERS spectra of Cu/CuO/Pd electrode observed in the range of $E$ values from +0.3~V to 0 V~(SHE) at 1328 - 1569~cm$^{-1}$ are consistent with the existence of species which are adsorbed or weakly bound to the surface with the energy of interaction close to 15 - 21~kJ mol$^{-1}$. These bands can be attributed to the ad(ab)sorbed (H$_3$O$^+$)$\rm{_{ad}}$, (H$_2^+$)$\rm{_{ab}}$ and (H$_2^+$)$\rm{_{ad}}$ ions as intermediates in reversible HER/HOR processes taking place on Cu/CuO/Pd electrode. There was no isotopic effect observed; this is consistent with a dipole nature of electron-ion pair formation of adsorbed (H$_3$O$^+$)$\rm{_{ad}}$ and (H$_2^+$)$\rm{_{ad}}$ or (D$_3$O$^+$)$\rm{_{ad}}$ and (D$_2^+$)$\rm{_{ad}}$. In accordance with literature data SERS bands at 125-146~cm$^{-1}$ and $\sim 520-565$~cm$^{-1}$ were assigned to Cu(I) and Cu(II) oxygen species. These findings corroborate the mechanism of cascading reduction of water.

Millimeter wave wide-band imaging is widely studied for a variety of applications. However real-time millimeter wave wide-band imaging at frequencies above 30GHz for moving targets in a large field of view has not been realized commercially. A 2D sparse array with transmitter multiplexing is a promising solution to this problem. In this article, a method combining compressed sensing and orthogonal coded multiplexing was proposed, and the imaging performance was analyzed for different reconstruction algorithms and observation matrices by imaging simulation for a continuous object. Also the influence on the dynamic range of the original signal introduced by orthogonal coded multiplexing was studied. This work demonstrated that the proposed method was effective in reconstructing the image with a real-time capability. It is shown that different algorithms and matrices resulted in distinct performances, while the evaluation parameter selection also played a role. This work provided useful instructions for both the hardware and software design of a real-time 3D millimeter wave imaging system in the future.

Laser metal deposition with wire (LMD-w) is a developing additive manufacturing (AM) technology that has a high deposition material rate and efficiency, and is suitable for fabrication of large aerospace components. However, control of material properties, geometry, and residual stresses is needed before LMD-w technology can be widely adopted for the construction of critical structural components. In this study, we investigated the effect of interlayer cooling time, clamp constraints, and tool path strategy on part distortion and residual stresses in large-scale laser additive manufactured Ti-6Al-4V components using finite element method (FEM). The simulations were validated with the temperature and the distortion measurements obtained from a real LMD-w process. We found that a shorter interlayer cooling time, full clamping constraints on the build plates, and a bidirectional tool path with 180⁰ rotation minimized part distortion and residual stresses and resulted in symmetric stress distribution.

In 2015, the new installed capacity of global renewable energy power generation exceeded the newly installed capacity of conventional energy power generation, marking a structural change in the construction of the global power system. With the continuous improvement of wind energy utilization technology, the global wind power industry has developed rapidly in recent years. The world's available wind energy is 20 billion kilowatts and has become one of the most economical green power. In China, wind power has become the third largest source of electricity, with the installed capacity increasing from 3.1% in 2010 to 9.2% in 2017. In 2017, China's new installed capacity was 19,660 MW, accounting for 37.45% of the world's new installed capacity. This paper evaluates and compares the efficiency of wind power industry in the four regions of eastern, central, western and northeastern China through EBM models based on radial and non-radial factors. This paper discusses the contribution of China's wind power industry to CO2 emission reduction from the relationship between installed capacity efficiency and CO2 emission reduction efficiency. The conclusions show that the overall efficiency score and ranking of wind power in 2013-2017 is the best in the eastern region, followed by the northeast region and the western and central regions.

In the framework of 2D circular membrane Micro-Electric-Mechanical-Systems (MEMS), a new non-linear second-order differential model with singularity in the steady-state case is presented in this paper. In particular, starting from the fact that the electric field magnitude is locally proportional to the curvature of the membrane, the problem is formalized in terms of the mean curvature. Then, a result of existence of at least one solution is achieved. Finally, two different approaches prove that the uniqueness of the solutions is not ensured.

The introduction of electrical vehicle charging infrastructure including EV charger, renewable energy resource at secondary feeder in distribution system has been increased as one of countermeasure for global environmental issues. However, the Electric Vehicle Charging (EVC) infrastructure may act as the peak load in distribution system, which can adversely impact on the voltage stability when the electric vehicle is quickly charged. Therefore, to keep within the limit capacity of secondary feeder and allowable limit for feeder voltage, this paper proposes a stabilization method by the Energy Storage System (ESS) control strategy at secondary feeder in order to be not violated over than lower and upper limit. Also, this paper presents the estimation method to keep the proper standard value of State of Charge (SOC). From the simulation results, the voltage stabilization operation by ESS should make the feeder voltages of the distribution system(secondary feeder) introduced EVC Infra keep better voltage conditions, also estimation method to keep the proper standard value is confirmed that the SOC of ESS when is the standby condition could be exactly kept within the proper reference range.

The diffusion coefficients of ions are measured in a microchip filled with a cationic charged 3D hydrogel in order to study the effect of cationic charged 3D hydrogel on the diffusivity of ions. In this study, poly-diallyl-dimethyl-ammoniumchloride (poly-DADMAC) is used to produce a 3D hydrogel. Four different fluorophores are used in the 3D hydrogel rhodamine 6G, rhodamine-BSA, fluorescein isothio-cyanate (FITC) and FITC-BSA. The rhodamine 6G and rhodamine-BSA are positively charged (cations), while fluorescein isothio-cyanate (FITC) and FITC-BSA are negatively charged (anions). Two widely used techniques which are short time diffusivity measurement technique and long time diffusivity measurement techniques are used to measure the diffusion coefficients. For the short time measurement, Fluorescence recovery after photo-bleaching (FRAP) is used by a 3D confocal microscope. For the long time measurement, fluorescence images are taken for 11 days to observe a pure diffusivity without any convective movement. As a result, the diffusivity of the cations was found to be lower than that of the anions in the cationic charged hydrogel.

Multiphase systems are important in minerals processing, and usually include solid-solid and solid-fluid systems. Examples of operations in multiphase systems include flotation, dewatering, and magnetic separation, among several other unit operations. In this paper, the current trends in the process system engineering tasks of modeling, design, and optimization, in multiphase systems, are analyzed. Different scales of size and time are included, and therefore the analysis includes modeling at the molecular level and unit operation level, and the application of optimization for the design of a plant. New strategies for the modeling and optimization of multiphase systems are also included, with a strong focus on the application of artificial intelligence (AI) and the combination of experimentation and modeling with response surface methodology (RSM). The paper finishes with tools to study the uncertainty, both epistemic and stochastic, which is present in all mineral processing operations. It is shown that all these areas are very active and can help to understand, operate, design, and optimize mineral processing that involves multiphase systems.

Sector coupling is one of the emerging topics in recent energy and climate change policy discussions. It can play a significant role in creating the pathway of a renewable-based energy system in the European energy sector. The North Sea region is very likely to play a key role in the transition to a sustainable energy system. Though different energy modelling approaches allow a versatile use, they lead to the problem of an unclear understanding of specific aspects of sector coupling, and the relevance of existing tools and techniques to model and analyze such a system. This paper is aimed at providing a comprehensive understanding of sector coupling and its incorporation in energy system models. Followed by a thorough literature review on sector coupling and energy system modelling, the paper outlines an approach to select an appropriate tool based on the specific rationales of the research. The paper also presents ‘Oemof’ as an open model tool to address the complex challenges of energy systems. The conclusions from the literature review provide a detailed understanding of the concept of sector coupling and indicate that it can be advantageous from the viewpoints of decarbonization, flexibility, network optimization, and system efficiency. To solve the coupling barriers, diversified techno-socio-economic circumstances should be taken into account through the use of model collaboration. It is also demonstrated how a list of appropriate tools for model collaboration can be picked up methodologically from an available wide range of models. Finally, ‘Oemof’ is hypothesized as a progressive tool to design a sector-coupled and renewable-based energy system in the North Sea region.

Risk-based redispatch optimization is proposed as a methodology to support the Transmission System Operator (TSO) with preventive remedial actions obtained by extending the security constrained unit commitment/economic dispatch with constraints resulting from the risk assessed for the power system. Although being heuristic, the methodology is based on comprehensive dynamic security assessment as time-domain simulations are used, allowing to express the degree of all types of instabilities, e.g., caused by contingencies, in monetary terms. Therefore, the risk is assessed as the expected value of the cost incurred by the TSO. Such approach forms a new pathway to including risk in planning procedures already used by TSOs. Results obtained for the IEEE39 dynamic power system, with costs assigned to load shedding and generator tripping due to single transmission lines short-circuits, are shown as a reference case.

Low Power Wide Area Networks (LPWAN) enable a growing number of Internet-of-Things (IoT) applications with large geographical coverage, low bit-rate, and long lifetime requirements. LoRa (Long Range) is a well-known LPWAN technology that uses a proprietary Chirp Spread Spectrum (CSS) physical layer, while the upper layers are defined by an open standard - LoRaWAN. In this paper, we propose a simple yet effective method to improve the Quality-of-Service (QoS) of LoRa networks by fine-tuning specific radio parameters. Through a Mixed Integer Linear Programming (MILP) problem formulation, we find optimal settings for the Spreading Factor (SF) and Carrier Frequency (CF) radio parameters, considering the network traffic specifications as a whole, to improve the Data Extraction Rate (DER) and to reduce the packet collision rate and the energy consumption in LoRa networks. The effectiveness of the optimization procedure is demonstrated by simulations, using LoRaSim for different network scales. In relation to the traditional LoRa radio parameter assignment policies, our solution leads to an average increase of 6% in DER, and a number of collisions 13 times smaller. In comparison to networks with dynamic radio parameter assignment policies, there is an increase of 5%, 2.8%, and 2% of DER, and a number of collisions 11, 7.8 and 2.5 times smaller than equal-distribution, Tiurlikova's (SoTa), and random distribution, respectively. Regarding the network energy consumption metric, the proposed optimization obtained an average consumption similar to Tiurlikova's, and 2.8 times lower than the equal-distribution and random dynamic allocation policies. Furthermore, we approach the practical aspects of how to implement and integrate the optimization mechanism proposed in LoRa, guaranteeing backward compatibility with the standard protocol.

In April 2019, a team of Keio University and Bucknell University students was assembled to participate in Ericsson Innovation Awards with a novel concept for generating renewable energy. This conceptual system consists of a vertical axis wind turbine, a crossflow marine hydrokinetic turbine, a floating platform integrated with a quadcopter system, and three to four temporary mooring lines with ship-type anchors. The proposed designed aims to offer solutions to two current problems of floating offshore wind energy: high construction cost of floating platforms and difficulties in maintenance of mooring lines. The combination of two vertical-axis turbines into a single floating platform would enable the system, namely ESwift, to extract energy from both wind and current resources. Additionally, due to the utilization of vertical axis turbines, the center of gravity of the proposed concept is significantly lower with respect to water level, compared to that of existing floating horizontal axis wind turbines, which would potentially reduce the floater's size and construction cost. Lastly, the integrated quadcopter mechanism would assist the floater in terms of stability and mobility, and enables an array of ESwifts to automatically rearrange for maximal energy generation. The authors hope that readers would find the idea described in this open access letter worth pursuing and would further develop and commercialize the ESwift concept.

This paper analyses the health and performance of 12-stage axial compressor of the TV3-117VM/VMA turboshaft operated in a desert environment. The results of the dimensional control of 4,800 worn blades are analysed to model the wear process. Operational experience and numerical simulations are used to assess the effectiveness of an Inlet Particle Separator. Numerical modal analysis is performed to generate the Campbell diagram of worn blades and identify resonant blade vibration which can lead to high cycle fatigue (HCF). It is shown that the gradual loss of the stall margin over time determines the serviceability limits of compressor blades. Recommendations setting out go / no-go criteria are made to maintenance and repair organisations.

Objects recognition is a necessary task in smart city environments. This recognition can be used in processes such as the reconstruction of the environment map or the intelligent navigation of vehicles. This paper proposes an architecture that integrates heterogeneous distributed information to recognize objects in intelligent environments. The architecture is based on the IoT / Industry 4.0 model to interconnect the devices, called Smart Resources. Smart Resources can process local sensor data and send information to other devices. These other devices can be located in the same operating range, the Edge, in the same intranet, the Fog, or on the Internet, the Cloud. Smart Resources must have an intelligent layer in order to be able to process the information. A system with two Smart Resources equipped with different image sensors has been implemented to validate the architecture. Experiments show that the integration of information increases the certainty in the recognition of objects between 2\% and 4\%. Consequently, in the field of intelligent environments, it seems appropriate to provide the devices with intelligence, but also capabilities to collaborate closely with other devices.

Information and communication technologies play an increasingly important role in the process of knowledge and management of places at different scales. ICTs allow a rapid diffusion of data not only through institutional channels but also through social networks where the smart community share experiences and perceptions. In this sense, ICTs become strategic tools to support the promotion of sustainable tourism development of territories, especially if the digital data are organised within a circular smart dashboard. This research focuses on the case study of the Santa Barbara Walk (SBW), an ancient mining route in the Sulcis Iglesiente region (Sardinia, Italy), where the authors have recognized a state of disorganization in slow tourism promotion activities. In fact, if the SBW represents a network - material infrastructure - which connects the main points of interest along the Walk, its digital network - intangible infrastructure - is fragmented in terms of policies and contents. The goal of this study is to provide a comprehensive set of data and to propose the architecture and design for a circular dashboard of the SBW, capable of organizing information concerning the main features of the walk, in order to facilitate a shared governance for an effective tourism promotion.