An antenna sensor is proposed to execute dual functions of antenna and sensor in the wireless sensor system, in order to reduce data loss and to increase transmission rate by omitting a certain interface. The as-made sensor was test at a center frequency of 46 MHz for measuring human finger postures using principle of dipole antenna. The antenna sensor was attached on a wearable glove. The results showed that the motion sensor can accurately identify finger angles at 0°, 20°, 40°, 60° and 80°.

The use of large-scale antenna arrays grants considerable benefits in energy and spectral efficiency to wireless systems due to spatial resolution and array gain techniques. By assuming a dominant line-of-sight environment in a massive MIMO scenario with favorable propagation, we derive analytical expressions for the sum-capacity. % Then, we show that convenient simplifications on the sum-capacity expressions are possible when working at low and high SNR regimes. % Furthermore, in the case of a high SNR regime, it is demonstrated that the Gamma PDF can approximate the PDF of the instantaneous channel sum-capacity as the number of BS antennas grows. A second important demonstration presented in this work is that a Gamma PDF can also be used to approximate the PDF of the summation of the channel's singular values as the number of devices increases. Finally, it is important to highlight that the presented framework is useful for LPWAN's as we show that the transmit power of each device can be made inversely proportional to the number of BS antennas.

With the fast development of the mobile Internet, the online platforms of social networks have rapidly been developing for the purpose of making friends, sharing information, etc. In these online platforms, users being related to each other forms social networks. Literature reviews have shown that social networks have community structure. Through the studies of community structure, the characteristics and functions of networks structure and the dynamical evolution mechanism of networks can be used for predicting user behaviours and controlling information dissemination. Therefore, this study proposes a deep community detection method which includes (1) matrix reconstruction method, (2) spatial feature extraction method and (3) community detection method. The original adjacency matrix in social network is reconstructed based on the opinion leader and nearer neighbors for obtaining spatial proximity matrix. The spatial eigenvector of reconstructed adjacency matrix can be extracted by an auto-encoder based on convolution neural network for the improvement of modularity. In experiments, four open datasets of practical social networks were selected to evaluate the proposed method, and the experimental results show that the proposed deep community detection method obtained higher modularity than other methods. Therefore, the proposed deep community detection method can effectively detect high quality communities in social networks.

Phase Change Materials (PCMs) are latent heat storage media with high potential of integration in building structures and technical systems. Their solid-liquid transition is commonly utilized for thermal energy storage in building applications. It also means that some kind of encapsulation is necessary. This is often solved with metal containers that also have high thermal conductivity and resistance to mechanical damage enhancing the performance these so called latent heat thermal energy storage (LHTES) systems. However selection of suitable metal is rather challenging. It depends, among other things, on the elimination of undesirable interaction between storage medium and surrounding metal. Heat storage medium must be reliably sealed in metal container especially when the storage system is integrated in systems like domestic hot water storage tanks, where PCM leaks can negatively affect human health. The aim of this study was evaluation of interaction between selected commercially available organic and inorganic PCMs and metals. The evaluation is based on the calculation of corrosion rate and use gravimetric method for determination of the weigh variations of the metal samples. Results show that aluminium is the most suitable container material with lowest mass loss and suffered only minimal visual changes on the surface after prolonged exposure to PCMs.

The objective of this work was to evaluate the removal of phosphorus and carbon dioxide capture of a conventional septic system upgraded with a sidestream steel slag filter used in recirculation mode. A pilot scale sidestream experiment was conducted with two septic tank and drainfield systems, one with and one without a sidestream slag filter. The experimental system was fed with real domestic wastewater. Recirculation ratios of 25%, 50% and 75% were tested. Limestone soils and silica soils were used as drainfield media. The phosphorus removal efficiency observed in the second compartment of the septic tank was 30% in the slag filter upgraded system, compared to -3% in the control system. The drainfield of silica soils achieved very high phosphorus removal in both control and upgraded systems. In the drainfield of limestone soil, the slag filtration reduced the groundwater phosphorus contamination load by up to 75%. Phosphorus removal in the septic tank with a slag filter was attributed to either sorption on newly precipitated calcium carbonate or precipitation of vivianite, or both. Recirculation ratio design criteria were proposed based on simulations. Simulations showed that the steel slag filter partly inhibited biological production of carbon dioxide in the septic tank. The influent alkalinity strongly influenced the recirculation ratio needed to raise the pH in the septic tank. The control septic tank produced carbon dioxide, whereas the slag filter upgraded septic tank was a carbon dioxide sink.

The kinetics of biogas production from biomass depends on several factors such as: carbon to nitrogen ratio (C/N), reactor temperature (T), and retention time (RT). The purpose of this study was to obtain a new model for predicting biogas production. Spent Mushroom Compost (SMC) was used to produce biogas in a batch type reactor. The experiments were carried out with different C/N ratios (12.1, 20, 30 and 40) and in both mesophilic (35°C) and thermophilic (55°C) temperatures. The results showed that the Maximum biogas production at 35°C, C/N=20 was equal to 41.9 mL/gVS and 55°C, C/N=30 was equal to 51.6 mL/gVS. By using experimental data, a new kinetic model was proposed to predict biogas production. Comparing the values of the results indicate that the total values of RMSE for Logistics, Gampartz and new kinetic models was 0.1906, 0.1830 and 0.1617, respectively. Therefore, the process of anaerobic digestion of biomass can be assumed to be just a chemical reaction, and the new kinetic model is an appropriate alternative to microbial growth models.

Wearable sensors have the potential to enable comprehensive patient characterization and optimized clinical intervention. Critical to realizing this vision is accurate estimation of biomechanical time-series in daily-life, including joint, segment, and muscle kinetics and kinematics, from wearable sensor data. The use of physical models for estimation of these quantities often requires many wearable devices making practical implementation more difficult. However, regression techniques may provide a viable alternative by allowing the use of a reduced number of sensors for estimating biomechanical time-series. Herein, we review 46 articles that used regression algorithms to estimate joint, segment, and muscle kinematics and kinetics. We present a high-level comparison of the many different techniques identified and discuss the implications of our findings concerning practical implementation and further improving estimation accuracy. In particular, we found that several studies report the incorporation of domain knowledge often yielded superior performance. Further, most models were trained on small datasets in which case nonparametric regression often performed best. No models were open-sourced, and most were subject-specific and not validated on impaired populations. Future research should focus on developing open-source algorithms using complementary physics-based and machine learning techniques that are validated in clinically impaired populations. This approach may further improve estimation performance and reduce barriers to clinical adoption.

In the case that ship operators may not be aware of the potential risks of environmental factors in situation of high causation probability during the initial stage of the geometric probability analysis process, it is likely that higher-grade collision accident measures will not be taken. However, if any risks is told to the ship operators, more effective and intentional measures can be taken in time. Moreover, if the causation probability corresponding to environmental factors is no less than the risk early warning critical value calculated based on historical collision accident data, there would be a high-risk level that a collision may occur. A new method is put forward based on quantitative analysis of environmental factors and previous collision statistics to provide early warning of any accident risk, and a risk early-warning critical value (REWCV) can be obtained based on this simple but highly operational and practical method. A case study of Three Gorges Reservoir in China indicates that the range of environmental factors where the probability of collision accident grows rapidly is consistent with environmental limits defined by Chinese maritime standards. In addition, the relationship between the risk early-warning critical value and the number of previous collision accident is also clarified.

Photoelectrochemical systems have the potential to contribute to de-carbonation of the energy system because solar energy can be directly converted to hydrogen which can be burnt without the release of greenhouse gases. However, meaningful deployment of photoelectrochemical (PEC) technology in the global energy system, even when highly efficient scaled up devices become available, shall only be a reality when their safe and reliable operation can be guaranteed over serveral years of service life. The first part of the review discusses the importance of hermetic sealing of up scaled PEC device provided by the casing and sealing joints from a reliability and risk perspective. The second part of the review presents a survey of fully functional devices and early demonstrators and uses this to establish the extent to which the state of the art in PEC device design address the issue of hermetic sealing. The survey revealed that current material choices and sealing techniques are still unsuitable for scale –up and commercialization. Accordingly, we examined possible synergies with related photovoltaic and electrochemical devices that have been commericalised and derived therefrom, recommendations for future research routes that could accelerate the development of hermetic sealings of PEC devices.

Growing popularity of smart and integrated buildings requires a review of methods to optimize the preheat of ventilation air. An integrated system permits using heat ex-changers located in the mechanical room or in the future even using an exterior wall as a heat exchanger. One may ask the question how does the earth-air heat exchanger (EAHX) technology fitts into this function. 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 reviewed literature and examined two nearly identical EAHX systems, placed either in ground next to the building or under the basement slab. Effectively, the information provided in this paper, shows advantages of merging both these approaches while the EAHX shoud be placed under the house or near the basement foundation.

The emission of carbon compounds (in the form of soot) to the atmosphere has a significant impact on the environment and human health. Air pollution with combustion products, having a unique combination of physical and chemical properties, is an important component of very fine suspended dust, which is emitted from various sources related to combustion processes. The carbon compounds in the aerosol and deposited in the substrate are found all over the Earth. The paper presents results of comparative research on the content of 16 polycyclic aromatic hydrocarbons (PAHs) in soot samples obtained as a result of combustion of solid fuels such as hard coal with granulation above 60 mm, coal with a grain size of 25-80 mm, coal with a grain size of 8-25 mm, pellets and dry wood. On the basis of the conducted tests, it was found that the soot obtained in the combustion of coal in different granulation contains more cytotoxic PAHs in comparison to the combustion of wood pellets or dry firewood.

In this study, to reduce the use of cement and sand, porous feldspar with excellent economic efficiency was used as a substitute in heat storage concrete layer. When cement was replaced with porous feldspar, the compressive strength was approximately 16%–63% higher compared with when cement was replaced with silicate minerals. To compensate for the reduction in strength owing to the decreased cement content, mechanical and chemical activation methods were employed. When the specific surface area of porous feldspar was increased, the unit weight was reduced by approximately 30% and the compressive strength was increased by up to 90%. When chemical activation was applied using a solidifying agent, the strength was increased by approximately 30% even though 70% of the cement content was replaced with porous feldspar. When cement and sand were replaced with porous feldspar, the compressive strength was approximately two times that of ordinary cement mortar. When the heat storage concrete layer material was replaced with porous feldspar in a pilot scale experiment, the thermal conductivity and heat storage characteristics were better than those of ordinary cement mortar, and an energy-saving effect of approximately 57% was observed, confirming the excellent applicability of porous feldspar as a building material.

Evidence is growing that mankind must learn from nature, a self-sufficient and self-organized system that adopts all the opportunities to develop life and ingeniously makes the most of whatever energy source. Attempting to satisfy the requirements of our energy-consuming world, we cannot afford to disregard any available source of energy, mainly those characterized by zero-CO₂ emissions. In this context an alternative scenario could be opened by the use of the nuclear radiations emitted from naturally occurring or artificially produced radionuclides. Abandoned mines of U, Th and Rare Earths , as well as storage areas of artificially produced isotopes all over the globe are available and affordable sources of radiations that can be converted in electrical power. The transition from laboratory-scale nuclear batteries to large-area converting modules would allow to safely re-use a big amount of already existing radionuclides, converting a trouble into a resource.

Directional protective relaying based on amplitude comparison of traveling wave on continuous co-phase auto-transformer(AT) power transmission system was proposed. Phase-model transformation is used for decoupling transient fault signals and get aerial mode component. The forward and backward traveling wave are obtained by calculating aerial mode component, then the intrinsic mode function(IMF) components can be obtained through Variational Mode Decomposition(VMD), the module maxima are obtained through calculating the IMF components. The fault direction is determined by the ratio of fault components. If two faults relays at the ends of electric traction networks detect a fault to be in the forward direction, the fault occurred in the internal area, the protection would operate properly. The simulation tests indicate that the protection scheme is feasible, and the proposed protection method can discriminate internal faults from external faults under various fault types, and its performances are immune to fault initial angle, ground resistance, etc.

A new design scheme is proposed for twisting the walls of a microchannel, and its performance is demonstrated numerically. The numerical study was carried out for a T-shaped microchannel with twist angles in the range of 0 to 34π. The Reynolds number range was 0.15 to 6. The T-shaped microchannel consists of two inlet branches and an outlet branch. The mixing performance was analyzed in terms of the degree of mixing and relative mixing cost. All numerical results show that the twisting scheme is an effective way to enhance the mixing in a T-shaped microchannel. The mixing enhancement is realized by the swirling of two fluids in the cross section and is more prominent as the Reynolds number decreases. The twist angle was optimized to maximize the DOM, which increases with the length of the outlet branch. The twist angle was also optimized in terms of the relative mixing. The two optimum twisting angles are generally not coincident. The optimum twist angle shows a dependence on the length of the outlet branch but it is not affected much by the Reynolds number.

Given the importance of the development of urban infrastructure and environmental impacts produced by the civil construction waste (CCW), it is important to correct the handling of CCW with objective solutions that are more environmentally friendly. In that sense the present study aimed to determine indicators that make it possible to estimate the amount of CCW generated from construction sites in the city of Londrina, Parana State, Brazil. The generation of CCW was estimated in a general way, regarding the composition of its mixture, correlated to the gross areas of the buildings studied and their generated volumes of RCC. This generating rate was evaluated in a general way and specifies two types of sites: the new residential and new non-residential constructions. The data required for the development of these indicators was obtained through extensive survey and interviews carried out at the environment secretariat of the City Hall. The generating rate of CCW obtained for non-residential buildings was 0.2052m3/m2 or 170.44kg/m2, for new residential sites was 0.2054m3/m2 or 170.60kg/m2 and for new commercial or non-residential construction sites, it was 0.20453 m3/m2 or 169.85kg/m2. It was also possible to estimate the amount generated annually per inhabitant in the municipality, which is 0.60m3/inhabit.year or 498.55kg/inhabit.year.

The aim of this paper is the presentation of an analytical model of insulator flashover and its application for air at atmospheric pressure and pressurized SF6. After a review of the main existing models in air and compressed gases, we develop a relationship of flashover voltage on the basis of an electrical equivalent circuit and the thermal properties of the discharge. The model includes the discharge resistance, the insulator impedance, and the gas interface impedance. The application of this model to a cylindrical resin-epoxy insulators in air medium and SF6 gas with different pressures gives results close to the experimental measurements.

This paper aims to analyse the mechanical properties response of polylactic acid (PLA) parts manufactured through fused filament fabrication. The influence of six manufacturing factors (layer height, filament width, fill density, layer orientation, printing velocity, and infill pattern) on the flexural resistance of PLA specimens is studied through an L27 Taguchi experimental array. Different geometries have been tested on a four-point bending machine and on a rotating bending machine. From the first experimental phase, an optimal set of parameters deriving in the highest flexural resistance have been determined. Results show that layer orientation is the most influential parameter, followed by layer height, filament width, and printing velocity, whereas the fill density and infill pattern show no significant influence. Finally, the fatigue fracture behaviour is evaluated and compared with previous studies results, to present a comprehensive study of the mechanical properties of the material under different kind of solicitations.

The military areas in Sardinia are around 234 km2, which constitutes 59.97% of the national surface affected by military easements. This situation is due to its geographic centrality in the Mediterranean. This contribution evaluates the performance of the Local Coastline Plan (LCP) and the Site Management Plan of Community Interest (SCI) in conditions of military constraint. The case study is the Municipality of Villaputzu where an important coastal military easement and the use of the coast for recreational tourism purposes coexist together through specific planning, a consequence of institutional agreements between the Municipal Administration of Villaputzu and the Ministry of Defense. The evaluation of the congruence of the specific objectives of the LCP and the SCI shows how their combined action favors the environmental enhancement of Sardinia, contributing to the formation of ecosystem services, even in particular conditions arising from military easements. These are sites that pass from the status of "anti-commons" to "semi-commons". In fact, the military release process in Sardinia, together with the promiscuous military and civil use, activates unique governance policies of their kind that find a significant field of application in Sardinia to guarantee a sustainable renewal of economic development of the ‘semi-commons’ awaiting to become ‘commons’

A study about influence of heat input on welding defects in vertical upward welding position for dissimilar material and thickness using a new variation of TIG welding torch is done with support of advanced inspection methods SEM and EBSD. With vertical upward welding position, control heat input plays an important role to keep the weld stabilization without defects. On the other hand, TIG welding process using a conventional TIG torch (conventional TIG welding process) has low efficiency and it is difficult to control heat input with high accuracy. So, it is considered that using conventional TIG torch is still a challenge for welding thin plates. In this case, a new variation of TIG torch has been developed. This torch used a constricted nozzle to improve plasma arc characteristics. As a result, it can control efficiently the heat input to prevent the excessive or insufficiency for joining thin sheets. For evaluation of welding quality, advanced examination methods SEM and EBSD were applied to directly observe the welding defects. From the results, the formation mechanism of blowhole inside weld zone in case of welding dissimilar material and thickness was discussed. It is pointed out that when sufficient welding current, the change from weld zone to base metal is uniform, no welding defects such as blowhole was seen. However, in case of low welding current, the thinner base metal is insufficient fusion and the change between weld zone and base metal is not uniform. The blowhole was observed at SS400 material side.

Endemic freshwater fish from semiarid environments are among the most threated species in the world due to the water overexploitation and habitat fragmentation problems. Stepped or pool-type fishways are used worldwide to reestablish longitudinal connectivity and mitigate fish migration problems. Many of them are being installed or planned in rivers of semiarid environments, however, very few studies about fish passage performance through pool-type fishways has been carried out to date on these regions. The present work focuses on the passage performance of two potamodromous cyprinids endemic of these regions, with different ecological and swimming behavior: southern Iberian barbel (Luciobarbus sclateri) and Iberian straight-mouth nase (Pseudochondrostoma polylepis), in two of the most common types of stepped fishways: vertical slot and submerged notch with bottom orifice fishways. Experiments were carried out during the spawning season in the Segura River (South-Eastern Spain), using a PIT tag and antennas system. Ascent success was greater than 80%, with a median transit time lower than 17 minutes per meter of height in all trials and for both species and fishway types. Results show that both types of fishways, if correctly designed and built, provide interesting alternatives for the restoration of fish migration pathways on these regions.

Fish schooling implies an awareness of the swimmers for their companions. In flow mediated environments, in addition to visual cues, pressure and shear sensors on the fish body are critical for providing quantitative information that assists the quantification of proximity to other swimmers. Here we examine the distribution of sensors on the surface of an artificial swimmer so that it can optimally identify a leading group of swimmers. We employ Bayesian experimental design coupled with two-dimensional Navier Stokes equations for multiple self-propelled swimmers. The follower tracks the school using information from its own surface pressure and shear stress. We demonstrate that the optimal sensor distribution of the follower is qualitatively similar to the distribution of neuromasts on fish. Our results show that it is possible to identify accurately the center of mass and even the number of the leading swimmers using surface only information.

The 21^st century has witnessed precipitous changes spanning from the way of life to the technologies that emerged. We have entered a nascent paradigm shift (industry 4.0) where science fictions have become science facts, and technology fusion is the main driver. Thus, ensuring that any advancement in technology reach and benefit all is the ideal opportunity for everyone. In this study, disruptive technologies of industry 4.0 was explored and quantified in terms of the number of their appearances in published literature. The study aimed at identifying industry 4.0 key technologies which have been ill-defined by previous researchers and to enumerate the required skills of industry 4.0. Comprehensive literature survey covering the field of engineering, production, and management was done from multidisciplinary databases: Google scholar, ScienceDirect, Scopus, Sage, Taylor & Francis and Emerald insight. Results of the electronic survey showed that 35 disruptive technologies were quantified and 13 key technologies: Internet of things, Big data, 3D printing, Cloud computing, Autonomous robots, Virtual and Augmented reality, Cyber physical system, Artificial intelligence, Smart sensors, Simulation, Nanotechnology, Drones and Biotechnology were identified. Both technical and personal skills to be imparted into the human workforce for industry 4.0 were reported. The study identified the need to investigate the capability and the readiness of developing countries in adapting industry 4.0 in terms of the changes in the education systems and industrial manufacturing settings. The study proposes the need to address integration of industry 4.0 concepts into the current education system.

An experimental series of shearing tests with water infiltration were performed on compacted unsaturated soil to simulate the behavior of shallow slope failures. Soil samples were compacted at moisture contents from dry to wet of optimum moisture content with the degree of saturation varying from 24.0% to 59.5% while maintaining the degree of compaction at 80%. Two series of shearing with infiltration tests were performed in this study. In Series-I, just before the start of shearing, matric suction was decreased by increasing pore water pressure to start water infiltration i.e. shearing is carried simultaneously with water infiltration. In Series-II, the soil was first sheared with drained pore air and undrained pore water to pre-defined value of deviatoric stress, after which matric suction was decreased by increasing pore water pressure to start water infiltration and shearing is performed by keeping deviatoric stress constant on the specimen. The test results showed that the decrease in matric suction has an effect on the volume of infiltrated water and degree of saturation. The soil slopes compacted on the dry side of optimum moisture content showed better performance than other soils, they require more decrease in matric suction to start water infiltration and showed higher deviatoric stress. In addition to this, water infiltration alone can cause the failure of shallow slopes without having to have any further loading.

This paper presents a novel adaptive fault-tolerant neural-based control design for wind turbines with unknown dynamic and unknown wind speed. By utilizing the barrier Lyapunov function in the analysis of the Lyapunov direct method, the constrained behavior of the system is provided in which the rotor speed, its variation and generated power remain in the desired bounds. In addition, input saturation is also considered in terms of smooth pitch actuator bounding. Furthermore, by utilizing a Nussbaum-type function in designing the control algorithm, the unpredictable wind speed variation is captured without requiring accurate wind speed measurement, observation or estimation. Moreover, with the proposed adaptive analytic algorithms, together with the use of radial basis function neural networks, a robust adaptive and fault-tolerant control scheme is developed without the need for precise information about the wind turbine model nor the pitch actuator faults. Additionally, the computational cost of the resultant control law is reduced by utilizing a dynamic surface control technique. The effectiveness of the developed design is verified using theoretical analysis tools and illustrated by numerical simulations on a high-fidelity wind turbine benchmark model with different fault scenarios. Comparison of the achieved results to the ones that can be obtained via an available industrial controller shows the advantages of the proposed scheme.

In this paper, we present a finite element simulation of an adaptive piezoelectric fluid-membrane lens modeled in COMSOL Multiphysics. The simulation couples the piezoelectric effect with the fluid dynamics to model the interaction between piezoelectric forces and fluid forces. Also, the simulation is extended to model the thermal expansion of the fluid. Finally, we compare the simulation and experimental results of the adaptive lens refractive power at different actuation levels and temperatures.

The stability between the limited available energy resources and their consumption is an important concern of the modern world. The study deals with the development of the methods for measuring the energy performance of different renewable and non-renewable resources used for electricity generation with the help of an energy performance indicator called the Primary Energy Factor (PEF). This study takes account of all energy stages from the resources extraction to its transportation, conversion, combustion and then finally to utilization. The study conducted a comparative approach to calculate the PEF values of electricity generated in South Korea from the period of 1980 to 2017. Four different methodologies namely Eurostat methodology, Life cycle methodology, Modified Eurostat methodology, and upper-end methodology have been used. A set of Programs has been written in MATLAB to calculate the i. PEF values of electricity generated. ii. Impact of different renewable and non-renewable energy sources on PEF values. iii. Future trend of PEF values of electricity in South Korea At the national and local level, this study will help the government and other law-making institutions to make policies regarding annual purchase consumptions of energies by different industrial, residential, public and transportation sectors and at the Global level, the implementation of this study will be the catastrophe of maintaining the stability between the available energy resources, and consumptions. This, in turn, will lead to suitable living conditions for future generations

Efficiency improvement is the new challenge in all fields of design. In this scenario the reduction of power losses is becoming more and more a main concern also in the design of power transmissions. Appropriate models to predict power losses are therefore from the earliest stages of the design phase. The aim of the project is to carry on lubrication simulations of several variants of a cylindrical-roller-bearing to understand the lubricant distribution and the related churning power losses. Several strategies to reduce the computational effort have been used. Among them the sectorial symmetry and three innovative meshing strategies (purely analytical with and without interfaces and analytical/subtractive) that have been implemented in the OpenFOAM® environment. The results of the different approaches were compared among them and with experimental observations showing good agreement and reasonable savings in terms of computational effort.

We analyze damage propagation modeling of turbo-engines in a data-driven approach. We investigate subspace tracking assuming a low dimensional manifold structure and a static behavior during the healthy state of the machines. Our damage propagation model is based on the deviation of the data from the static behavior and uses the notion of health index as a measure of the condition. Hence, we incorporate condition-based maintenance and estimate the remaining useful life based on the current and previous health indexes. This paper proposes an algorithm that adapts well to the dynamics of the data and underlying system, and reduces the computational complexity by utilizing the low dimensional manifold structure of the data. A significant performance improvement is demonstrated over existing methods by using the proposed algorithm on CMAPSS Turbo-engine datasets.

Cultural heritage is the most important resource providing communication between the past and future. The societies utilizing this resource in the best way, have had an inventory of cultural heritage and contributed to world culture. The efforts made for being able to the accurate and healthy data in the documentation of cultural heritage led the new techniques to emerge other than documentation and, together with the developing technology, documentation with traditional method replaced with modern documentation techniques using new technological devices. One of these documentation techniques is the use of Unmanned Aerial Vehicles (UAVs) in the documentation studies. In this study, the usability of unmanned aerial vehicles in the studies of cultural heritage was studied.

The study utilizes the energy-flux-vector method to analyze the heat transfer characteristics of natural convection in a wavy-wall porous square cavity with a partially-heated bottom surface. The effects of the modified Darcy number and modified Rayleigh number on the energy-flux-vector distribution and mean Nusselt number are examined. The results show that when a low modified Darcy number with any value of modified Rayleigh number is given, the recirculation regions are not formed in the energy-flux-vector distribution within the porous cavity. Therefore, a low mean Nusselt number is obtained. The recirculation regions do still not form and thus the mean Nusselt number has a low value when a low modified Darcy number with a high modified Rayleigh number is given. However, when the values of the modified Darcy number and modified Rayleigh number are high, the energy flux vectors generate recirculation regions and thus a high mean Nusselt number is obtained.

In this paper, a technique of image watermarking using multiple images as watermarks is presented. The technique is based on transform domain functions including discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) with an image as the host signal i.e. the watermarks will be used as proofs of the authenticity of the host image. The technique is executed by performing multilevel DWT followed by applying DCT and SVD to both the host and watermark. Multiple watermarks are used for the insurance of better security level. The scheme is immune to common image processing operations & some attacks and exhibits PSNR of 108.3781dB, normalized cross correlation (NCC) over 0.99 and normalized correlation (NC) over 0.99.

The role of hydrogen in a future energy system with a high share of variable renewable energy sources (VRES) is regarded as crucial in order to balance fluctuations in electricity generation. These fluctuations can be compensated for by flexibility measures such as the expansion of transmission, flexible generation, larger back-up capacity and storage. Salt cavern storage is the most promising technology due to its large storage capacity, followed by pumped hydro storage. For the underground storage of chemical energy carriers such as hydrogen, salt caverns offer the most promising option owing to their low investment cost, high sealing potential and low cushion gas requirement. This paper provides a suitability assessment of European subsurface salt structures in terms of size, land eligibility and storage capacity. Two distinct cavern volumes of 500,000 m³ and 750,000 m³ are considered, with preference being given for salt caverns over bedded salt deposits and salt domes. The storage capacities of individual caverns are estimated on the basis of thermodynamic considerations based on site-specific data. The results are analyzed using three different scenarios: onshore and offshore salt caverns, only onshore salt caverns and only onshore caverns within 50 km of the shore. The overall technical storage potential across Europe is estimated at 84.8 PWh_H2, 27% of which constitutes only onshore locations. Furthermore, this capacity decreases to 7.3 PWh_H2 with a limitation of 50 km distance from shore. In all cases, Germany has the highest technical storage potential, with a value of 9.4 PWh_H2, located onshore only in salt domes in the north of the country. Moreover, Norway has 7.5 PWh_H2 of storage potential for offshore caverns, which are all located in the subsurface of the North Sea Basin.

Magnetic properties of soft magnetic composites are highly sensitive to the processing conditions. In this paper we focus on the possibility to model this effect using the Jiles-Atherton-Sablik theory. It is assumed that the effect of varying compaction pressure may be described by direct introduction of stress-dependent term in the model equations. The values of model parameters are kept constant. Verification of the proposed approach is carried out using measurement data from self-developed iron-based composite cores.

In the year 2017, about 89 percent of the total energy consumed in the US was produced using non-renewable energy sources, and about 43 percent of tenant households were cost-burdened. Local governments are in a unique position to facilitate green affordable housing that could reduce cost burdens, environmental degradation, and environmental injustice. Nonetheless, limited studies have made progress on costs and benefits of green affordable housing to guide decision-making, particularly in small communities. This study investigates density bonus options for green affordable housing by analyzing construction costs, sale prices, and spillover effects for green certifications and affordable housing units. The authors employ construction costs and sale data from 422 Low-Income Housing Tax Credit (LIHTC) projects and 11,418 Multiple Listing Service (MLS) transactions in Virginia. Using hedonic regression analyses controlling for mediating factors, we find that the new construction of market-rate green certified houses is associated with small upfront costs but large and statistically significant price premiums. The construction of market-rate green certified houses has large and statistically significant spillover effects on existing non-certified houses. Existing non-certified affordable housing units show small and statistically insignificant negative price impacts on transactions of surrounding properties. The magnitude of social benefits associated with green building justifies the local provision of voluntary programs for green affordable housing where housing is expensive relative to its basic costs of production to promote sustainable development.

The highest efficiency solar cell won in the efficiency race does not always give the most excellent annual energy yield in the real world solar condition that the spectrum is ever-changing. The study of the radiative coupling of the concentrator solar cells implied that the efficiency could increase by the recycle of the radiative recombination generated by the surplus current in upper junction. Such configuration is called by a super-multi-junction cell. We expanded the model in the concentrator solar cell to non-concentrating installation. It was shown that this super-multi-junction cell configuration was found robust and can keep the maximum potential efficiency (50 % in realistic spectrum fluctuation) up to 10 junctions. The super-multi-junction cell is also robust in the bandgap engineering of each junction. Therefore, the future multi-junction may not be needed to tune the bandgap for matching the standard solar spectrum, as well as relying upon artificial technologies like ELO (Epitaxial lift-off), wafer-bonding, mechanical-stacking, and reverse-growth, but merely uses up-right and lattice-matching growth technologies. We have two challenging techniques; one is the optical cap layer that may be the directional photon coupling layer in the application of the photonics technologies, and another is the high-quality epitaxial growth with almost 100 % of the radiative efficiency.

Effective maintenance of railways requires a comprehensive assessment of the actual condition of the construction materials involved. In this regard, Ground-Penetrating Radar (GPR) stands as a viable alternative to the invasive and time-consuming traditional techniques for the inspection of these infrastructures. This work reports the experimental activities carried out on a test-site area within a railway depot in Rome, Italy. Specifically, a 30 m-long railway section was divided into 10 sub-sections reproducing different various physical and structural conditions of the track-bed. In more detail, combinations of varying scenarios of fragmentation and fouling of the ballast were reproduced. The set-up was then investigated using different multi-frequency GPR horn antenna systems. The effects of the different physical conditions of ballast on the electromagnetic response of the material were analysed for each scenario using time- and frequency-domain signal processing techniques. Parallel to this, modelling was provided to estimate fouling content. Interpretation of results has proven the viability of the GPR method in detecting signs of decay at the network level, thereby proving this technique to be worthy for implementation in asset management systems.

Cloud robotics is becoming an alternative to support advanced services of robots with low computing power as network technology advances. Recently, fog robotics has gained attention since the approach has merit relieving latency and security issues over the conventional cloud robotics. In this paper, a Function-as-a-Service based Fog Robotic (FaaS-FR) for cognitive robots is proposed. The model distributes the cognitive functions according to the computational power, latency and security with a public robot cloud and fog robot server. During the experiment with a Raspberry Pi as an edge, the proposed FaaS-FR model shows efficient and practical performance in the proper distribution of the computational work of the cognitive system.

The transition towards a renewable energy system is essential in order to reduce greenhouse gas emissions. The increase in the share of variable renewable energy sources (VRES), which mainly comprise wind and solar energy, necessitates storage technologies by which the intermittency of VRES can be compensated for. Although hydrogen has been envisioned to play a significant role as a promising alternative energy carrier in a future European VRES-based energy concept, the optimal design of this system remains uncertain. In this analysis, a hydrogen infrastructure is posited that would meet the electricity and hydrogen demand for a 100% renewable energy-based European energy system in the context of 2050. The overall system design is optimized by minimizing the total annual cost. Onshore and offshore wind energy, open-field photovoltaics (PV), rooftop PV and hydro energy, as well as biomass, are the technologies employed for electricity generation. The electricity generated is then either transmitted through the electrical grid or converted into hydrogen by means of electrolyzers and then distributed through hydrogen pipelines. Battery, hydrogen vessels and salt caverns are considered as potential storage technologies. In the case of a lull, stored hydrogen can be re-electrified to generate electricity to meet demand during that time period. For each location, eligible technologies are introduced, as well as their maximum capacity and hourly demand profiles, in order to build the optimization model. In addition, a generation time series for VRES has been exogenously derived for the model. The generation profiles of wind energy have been investigated in detail by considering future turbine designs with high spatial resolution. In terms of salt cavern storage, the technical potential for hydrogen storage is defined in the system as the maximum allowable capacity per region. Whether or not a technology is installed in a region, the hourly operation of these technologies, as well as the cost of each technology, are obtained within the optimization results. It is revealed that a 100 percent renewable energy system is feasible and would meet both electricity demand and hydrogen demand in Europe.

This paper presents the methodology to detect and identify the type of fault that occurs in shunt connected static synchronous compensator (STATCOM) transmission line using a combination of Discrete Wavelet Transform (DWT) and Naive Bayes classifier. To study this, the network model is designed using Mat-lab/Simulink. The different faults such as Line to Ground (LG), Line to Line (LL), Double Line to Ground (LLG) and three-phase (LLLG) fault are applied at different zones of system with and without STATCOM considering the effect of varying fault resistance. The three-phase fault current waveforms obtained are decomposed into several levels using daubechies mother wavelet of db4 to extract the features such as standard deviation and Energy values. The extracted features are used to train the classifiers such as Multi-Layer Perceptron Neural Network (MLP), Bayes and Naive Bayes (NB) classifier to classify the type of fault that occurs in the system. The results reveal that the proposed NB classifier outperforms in terms of accuracy rate, misclassification rate, kappa statistics, mean absolute error (MAE), root mean square error (RMSE), relative absolute error (RAE) and root-relative square error (RRSE) than MLP and Bayes classifier.

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

The basic equation for estimating the aerodynamic power captured by an Anderson Vertical Axis Wind Turbine (AVAWT) is a solution of the Navier-Stokes(N-S) equations for a baroclinic, inviscid flow. In a nutshell, the pressure difference across the AVAWT is derived from Bernoulli’s equation; an upshot of the integration of the N-S momentum equation for a baroclinic inviscid flow, Euler’s momentum equation. The resulting expression for the pressure difference across the AVAWT rotor is plotted as a function of freestream speed. Experimentally determined airstream speeds at the AVAWT inlet and outlet, coupled with corresponding freestream speeds are used in estimating the aerodynamic power captured. The aerodynamic power is subsequently used in calculating the aerodynamic power coefficient of the AVAWT. The actual power coefficient is calculated from the power generated by the AVAWT at various free stream speeds and plotted as a function of the latter. Experimental results show that, at all free stream speeds and tip speed ratios, the aerodynamic power coefficient is higher than the actual power coefficient of the AVAWT. Consequently, the power generated by the AVAWT prototype is lower than the aerodynamic power captured, given the same inflow wind condition.

The aim of the research was a comprehensive evaluation of concrete using the EIPI method. In the evaluation the compressive strength of concrete and its durability properties represented by sorptivity and air permeability were taken into account. Since copper slag waste with increased natural radioactivity was used in the assessed concrete, additional evaluation was carried out taking into account the influence of natural radioactivity within the performance index. Also the reference concrete, which was made without the use of copper slag waste, was evaluated for comparative purposes. In order to make the evaluation as comprehensive as possible, the concrete made with the use of three types of cement was subjected to the assessment: CEM I, CEM II and CEM III. The results show that in both approaches the best result was achieved by concrete with CEM III cement. If natural radioactivity is not taken into account in the evaluation, the best result is obtained by concrete made with copper slag waste, and if radioactivity is considered, the best result is obtained with concrete without addition of the waste. It follows from the above that although natural radioactivity has a significant impact on the EIPI evaluation result, the decisive factor is still the type of cement.

Precipitation processes are technologies commonly used in hydrometallurgical plants to recover metals or to treat wastewaters. Moreover, solid-liquid separation technologies, such as thickening or filtering, are relevant unit operations, included in the precipitation technologies. These methods are strongly dependent on the characteristics of the solid precipitates formed during the specific precipitation reaction. One of these characteristics is the particle size distribution (PSD) of the solid precipitates which are fed into a solid-liquid separation process. Therefore, PSD determination is a typical practice for the characterization of the slurries generated in a precipitation plant. Furthermore, the precipitates generated in these processes have a colloidal or aggregation behavior, depending on the operational conditions. Nevertheless, the conventional methods used to estimate PSD (e.g., laser diffraction and/or ciclosizer) have not been designed to measure particles that tend to aggregate or disaggregate, since they include external forces (e.g., centrifugal, agitation, pumping and sonication). These forces affect the true size of the aggregates formed in a unit operation, thereby losing representativity in terms of aggregates particle size. This study presents an alternative method of measuring the size distribution of particles with aggregation behavior, particularly, by using non-invasive microscopy and image processing and analysis. The samples used have been obtained from an experimental precipitation process by applying sulfidization to treat the cyanide-copper complexes contained in a cyanidation solution. This method has been validated with statistical tools and compared with a conventional analysis based on laser diffraction. Our results show significant differences between the methods analyzed, demonstrating that image processing and analysis by microscopy is an excellent and non-invasive alternative to obtaining size distribution of aggregates in precipitation processes.

DARPA, the Defense Advanced Research Projects Agency from the United States, has started the Spectrum Collaboration Challenge with the aim to encourage research and development of coexistence and collaboration techniques of heterogeneous networks in the same wireless spectrum bands. Team SCATTER has been participating in the challenge since its beginning, back in 2016. SCATTER’s open-source software-defined physical layer (SCATTER PHY) has been developed as a standalone application, with the ability to communicate with higher layers of SCATTER’s system via ZeroMQ, and uses USRP X310 software-defined radio devices to send and receive wireless signals. SCATTER PHY relies on USRP’s ability to schedule timed commands, uses both physical interfaces of the radio devices, utilizes the radio’s internal FPGA board to implement custom high-performance filtering blocks in order to increase its spectral efficiency as well as enable reliable usage of neighboring spectrum bands. This paper describes the design and main features of SCATTER PHY and showcases the experiments performed to verify the achieved benefits.

This paper details the evolution of access network sharing models from legacy DSL to the most recent fibre-based technology and the main challenges faced from a technical and business perspectives. We first give an overview of existing access sharing models, that span physical local loop unbundling and virtual unbundled local access. We then describe different types of optical access technologies and highlight how they support network sharing. Next, we examine how the concept of SDN and network virtualization has been pivotal in enabling the idea of “true multi-tenancy”, through the use of programmability, flexible architecture and resource isolation. We give examples of recent developments of cloud central office and OLT virtualization. Finally, we provide an insight into the role that novel business models, such as blockchain and smart contract technology, could play in 5G networks. We discuss how these might evolve, to provide flexibility and dynamic operations that are needed in the data and control planes.

In CCS projects, the transportation of CO₂ by ship can be an attractive alternative to transportation using a pipeline, particularly when the distance between source and disposal location is large. However, the energy consumption of the liquefaction process can be significant, making the selection of an energy-efficient design an important factor in the minimization of operating costs. Since the liquefaction process operates at low temperature, its energy consumption will vary with ambient temperature, which could be a factor that influences the trade-off point between pipelines and shipping in different geographic locations. A consistent set of data showing the relationship between energy consumption and cooling temperature is therefore potentially useful to CCS system modelling. This study compares the performance of a wide range of CO₂ liquefaction schemes. It applies a methodical approach to the optimization of process operating parameters and studies performance across a range of operating temperatures. A set of data for the minimum energy consumption cases is presented. The main findings are that open-cycle CO₂ processes often offer minimum energy consumption; NH₃ based schemes often offer better performance at higher ambient temperatures; and that for the cooling temperature range 15 to 50 °C, the energy consumption for the best performing liquefaction process rises by around 40%.

The use of biodiesel fuels in compression ignition engines leads to decrease CO, PM, HC and smoke opacity. However, NOx emissions increase importantly. Various methods to reduce NOx are used namely the EGR, the water injection method and the steam injection method. In this study, the steam injection method has been used instead of the other methods because of its benefits. This study examines the effects of steam injection on combustion products of diesel and biodiesel fuels by considering chemical equilibrium in order to determine the equilibrium combustion products involving 10 combustion products. A developed simulation code determing the equilibrium mole fractions and thermodynamic properties of combustion products is used for diesel and biodiesel fuels. It can be used for any fuel consisting of carbon, hydrogen or any oxygenated fuel. The results show that the mole fraction of CO2 and CO decrease with the steam injection ratios. NO mole fractions decrease with steam injection for lean mixtures but they increase slightly in the case of rich mixtures. The specific heat of combustion products increase with the steam injection ratios. Thus, the engine performance can be improved using the method. The model has been validated by comparing model results with the ones of NASA CEA software and GASEQ software using the methane as fuel. The relative errors of equilibrium mole fractions and thermodynamic properties of combustion products are less than 0.98 %.

Reducing emissions from the iron and steel industry is essential to achieve the Paris climate goals. A new system to reduce the carbon footprint of steel production is proposed in this article by coupling hydrogen direct reduction of iron ore (H-DRI) and natural gas pyrolysis on liquid metal surface inside a bubble column reactor. If grid electricity from EU is used, the emissions would be 435 kg CO₂/tls without considering methane leakage from the extraction, storage and transport of natural gas. Solid carbon, produced as a by-product of natural gas decomposition, finds applications in many industrial sectors, including as a replacement for coal in coke ovens. Specific energy consumption (SEC) of the proposed system is approximately 6.3 MWh per ton of liquid steel(tls). It is higher than other competing technologies, 3.48 MWh/tls for water electrolysis based DRI, and, 4.3-4.5 MWh/tls for natural gas based DRI and blast furnace-basic oxygen furnace (BF-BOF) respectively. Utilization of large quantities of natural gas, where the carbon remains unused, is the major reason for high SEC. Preliminary analysis of the system revealed that it has the potential to compete with existing technologies to produce CO₂ free steel, if renewable electricity is used. Further studies on the kinetics of the bubble column reactor, H-DRI shaft furnace, design and sizing of components, along with building of industrial prototypes are required to improve the understanding of the system performance.

MAACS is a software architecture which layers multiple standard cipher algorithms together to increase the overall strength of the encrypted data stream, without modifying the standard algorithms, which have been heavily vetted from a cryptanalysis perspective and are already widely deployed. This layering technique makes the combination of algorithms significantly more resistant to traditional cryptanalysis attacks, while also addressing increased concerns over future quantum computing attacks against these algorithms. For example, concerns over published attacks against 256-bit AES and potential future attacks emanating from Grover’s algorithm and other unknowns in the quantum computing era are explored. Several approaches for evolving AES are considered. MAACS uses a concept termed "aperiodic modulation", whereby of a set of cryptographic algorithms are modified by an- other, independent software algorithm in an unpredictable, pseudo-random manner. In the MAACS reference architecture, a 256-bit ChaCha20 cryptographically secure pseudorandom number generator (CSPRNG) drives an aperiodic modulator that orchestrates encryption/decryption processes multiplexed across eight parallel 128-bit AES instances, yielding a cryptosystem with a composite strength of 1,376 bits or more in larger configurations.

In the last decade, the drone market has grown rapidly for both civil and military purposes. Due to their versatility, drones demand is constantly increasing, with several industrial players joining the venture to transfer urban mobility to the air. This has exacerbated the problem of noise pollution, mainly due to the relatively lower altitude of these vehicles and to the proximity of their routes to extremely densely populated areas. In particular, both the aerodynamic and aeroacoustic optimization of the propulsive system and of its interaction with the airframe are key aspects of the design of aerial vehicles for the success or the failure of their mission. The industrial challenge involves finding the best performance in terms of loading, efficiency and weight, and, at the same time, the most silent configuration. For this reason, research has focused on an initial localization of the noise sources and, on further analysis, of the noise generation mechanism, focusing particularly on directivity and scattering. The aim of the present study is to review the noise source mechanisms and the state-of-the-art technologies available in literature for its suppression, focusing especially on the fluid-dynamic aspects of low Reynolds numbers of the propulsive system and on the interaction of the propulsive-system flow with the airframe.

The building sector accounts for nearly 40% of total primary energy consumption in the U.S. and E.U. and 20% of worldwide delivered energy consumption. Climate projections predict an increase of average annual temperatures between 1.1-5.4°C by 2100. As urbanization is expected to continue increasing at a rapid pace, the energy consumption of buildings is likely to play a pivotal role in the overall energy budget. In this study we used EnergyPlus building energy models to estimate the future energy demands of commercial buildings in Salt Lake County, Utah, USA, using locally-derived climate projections. We found significant variability in the energy demand profiles when simulating the study buildings under different climate scenarios, based on the energy standard the building was designed to meet, with reductions ranging from 10% to 60% in natural gas consumption for heating and increases ranging from 10% to 30% in electricity consumption for cooling. A case study, using projected 2040 building stock, showed a weighted average decrease in heating energy of 25% and an increase of 15% in cooling energy. We also found that building standards between ASHRAE 90.1-2004 and 90.1-2016 play a comparatively smaller role than variation in climate scenarios on the energy demand variability within building types. Our findings underscore the large range of potential future building energy consumption which depend on climatic conditions, as well as building types and standards.

Demand for green technologies and energy is in continuous growth in the last years. Compact efficient antennas are crucial for energy harvesting portable systems. Small antennas have low efficiency. The efficiency of communication and energy harvesting systems may be improved by using efficient passive and active antennas. The system dynamic range may be improved by connecting amplifiers to the printed antenna feed line. Design, design considerations, computed and measured results of wearable meta-materials antennas with high efficiency for energy harvesting applications are presented in this paper. All antennas were analyzed by using 3D full-wave software. The antennas electrical parameters on human body are presented. The directivity and gain of the antennas with Split-ring resonators, SRR, is higher by 2.5dB than the antennas without SRR. The resonant frequency of the antennas with SRR is lower by 5% to 10% than the antennas without SRR.

Epoxy asphalt (EA) concrete is widely used in constructing long-span steel bridge pavements (SBDPs). This study aims to derive a fatigue damage evolution law, conducting an experimental investigation of SBDP. First, a general theoretical form of the fatigue damage evolution law of materials is established based on the thermal motion of atoms. Then, fatigue experiments demonstrate that this evolution law well represents the known damage–life relationships of SBDP. Taking into account the experimental relationships between damage and fatigue life under symmetrical cyclic loadings with different overload amplitudes and temperature variations, a detailed damage evolution law is deduced. Finally, the role of damage accumulation is discussed on the basis of the proposed damage evolution law for the extreme situation of heavy overload and severe environments. The results show that both heavy loading and falling temperatures increase the fatigue damage of SBDP considerably; therefore, SBDP should avoid heavy loading combined with winter temperatures. EA shows a fatigue life two to three times longer than that of modified matrix asphalt (SMA) or guss asphalt (GA). For the same thickness, EA pavement is demonstrated to be more suitable for an anti-fatigue design of large-span SBDP under high traffic flows and low temperatures.

Fusarium head blight (FHB) disease is extensively distributed worldwide. This disease damages grain quality and reduces yield. The detection of this disease in a high throughput way is crucial to planters and breeders. Our study focused on developing a method for processing wheat color images and accurately detecting disease areas using deep learning and image processing techniques. The color images of wheat at the milky stage were collected and processed to construct datasets, which were used to retrain a deep convolutional neural network model using transfer learning. Testing results showed that the model can detect spikes, and the coefficient of determination of the number of spikes between the manual count and the detection was 0.80. The model was assessed, and the mean average precision for the testing dataset was 0.9201. On the basis of the results of spike detection, a new color feature was applied to obtain the gray image of each spike. Then, a modified region growing algorithm was implemented to segment and detect the diseased areas of each spike. Results show that the region growing algorithm performs better than K-means and Otsu’s method in segmenting the FHB disease. Overall, this study demonstrates that deep learning techniques enable the accurate detection of FHB in wheat using color images, and the proposed method can effectively detect spikes and diseased areas, thereby improving the efficiency of FHB detection.

Fibre reinforced cementitious materials (FRC) have become an attractive alternative for structural applications. Among such FRC, steel and polyolefin fibre reinforced concrete and glass fibre reinforced concrete are the most used ones. However, in order to exploit the properties of such materials structural designers need constitutive relations that reproduce FRC fracture behaviour accurately. This contribution analyses the suitability of multilinear softening functions combined with a cohesive crack approach for reproducing the fracture behaviour of the FRC previously mentioned. The implementation performed accurately simulates the fracture behaviour while being versatile, robust and efficient from a numerical point of view.

The authors of the paper have made an attempt to detect the fibre content and fibre spacing in a steel fibre reinforced concrete (SFRC) industrial floor. Two non-destructive testing (NDT) methods: an electromagnetic induction technique and a radar-based technique were applied. The first method allowed to detect the spacing in subsequent layers located in the thickness of the slab. The result of the second method was a 3D visualization of the detected fibre in the volume of concrete slab. The conducted tests showed aptitude and limitations of the applied methods in estimating fibre volume and spacing. The two techniques also allowed to locate the areas with relatively low fibre concentration which are very likely to be characterized by low mechanical properties.

Almost all single-family detached house in Canada consume huge electricity for space heating and domestic hot water (DHW) purposes. There are many possibilities to design an energy-efficient house. A solar water heating system can be used for domestic water and space heating. Water temperature can be kept constant always by connecting a heat pump or oil burner because solar energy is intermittent. Proper and optimized solar photovoltaic and collector design, tank design, heat pump selection, house insulation, total demand calculation in each section are essential. Energy-Efficient house design has been proposed with water heating and space heating system and compared with the existing system, solar PV based systems, and solar collector based system. The tracking and non-tracking based solar thermal collector based and the solar photovoltaic based system has been compared in this paper and investigate the suitable one for practically applicable and acceptable by the people. Simulation has been done by using the PolySun software. It found that by implementing the proposed PV based system with tracking is highly suitable considering lower cost, high output power, flexibility, easy installation.

In this paper, a recent meta-heuristic optimization algorithm called the discrete-continuous hyper-spherical search algorithm is used to solve the mixed-integer nonlinear problem of soft open points (SOPs) and renewable distributed generators allocation along with new network reconfiguration methodology under different loading conditions to minimize the total power loss in balanced distribution systems. Multi-scenario studies, which aim to improve the investigation of the overall performance of the strategies, are conducted on IEEE 33-node and 83-node balanced distribution systems. The contributions of SOP losses to the total active losses, as well as the effect of increasing the number of SOPs connected to the system, are investigated to determine the real benefits gained from their allocation. The results obtained validate, with proper justifications, the effectiveness of allocating both SOPs and renewable distributed generators with the proposed network reconfiguration methodology to provide the best operation of distribution networks with minimum losses and enhanced power quality performance. It was also shown that SOPs successfully assist the growing integration plans of the renewable distributed generators units and can address issues related to voltage violations and network losses efficiently.

Electric vehicles (EVs) are being endorsed as the uppermost successor to fuel-powered cars, with timetables for banning the sale of petrol-fueled vehicles announced in many countries. However, the range and charging times of EVs are still considerable concerns. Fast charging could be a solution to consumers' range anxiety and the acceptance of EVs. Nevertheless, it is a complicated and systematized challenge to realize the fast charging of EVs because it includes the coordinated development of battery cells, including electrode materials, EV battery power systems, charging piles, electric grids, etc. This paper aims to serve as an analysis for the development of fast-charging technology, with a discussion of the current situation, constraints and development direction of EV fast-charging technologies from the macroscale and microscale perspectives of fast-charging challenges. It is emphasized that to essentially solve the problem of fast charging, the development of new battery materials, especially anode materials with improved lithium ion diffusion coefficients, is the key. It is highlighted that red phosphorus is the most promising anode that can simultaneously satisfy the double standards of high-energy density and fast-charging performance to a maximum degree.

In the steeply inclined and extremely thick coal seams (SIETCS) mined using the horizontal sublevel top-coal caving (HSTCC) method, the uncertainty of gas emission is a safety threat to the mining operations. In order to reduce the occurrence of accidents, the determination of gas emission is crucial. In this paper, we first proposed a prediction model for workers at the floor coalbed to calculate gas emission on site. We then put forward a finite element numerical simulation for researchers to predict gas emission from the floor coalbed. At last, we measured gas emitted from the floor coalbed of SIETCS in Wudong Coal Mine in a specific mining period and used the data to verify the applicability and accuracy of these two gas-emission prediction methods. The results showed that the gas emission from Wudong Coal Mine was 1.08 m³/min calculated based on the prediction model and 1.07 m³/min obtained using the user-defined integration method. Both methods have their own advantages, disadvantages and applicable objects, and are important in predicting gas emission from SIETCS mined using HSTCC method.

A variety of techniques have been utilized in metal additive manufacturing (AM) for melt pool size management, including modeling and feed-forward approaches. In a few cases, closed-loop control has been demonstrated. In this research, closed-loop melt pool size control for large-scale, laser-wire based Directed Energy Deposition is demonstrated with a novel modification: site-specific changes to the controller set-point were commanded at trigger points, the locations of which were generated by the projection of a secondary geometry onto the primary 3D-printed component geometry. The present work shows that, through this technique, it is possible to print a specific geometry that occurs beyond the actual toolpath of the print head. This is denoted as an extra-toolpath geometry and is fundamentally different from other methods of generating component features in metal AM. A proof-of-principle experiment is presented in which a complex oak leaf geometry was embossed on an otherwise ordinary double-bead wall made from Ti-6Al-4V. The process is introduced and characterized primarily from a controls perspective with reports on the performance of the control system, the melt pool size response, and the resulting geometry. The implications of this capability, which extend beyond localized control of bead geometry to the potential mitigations of defects and functional grading of component properties, are discussed.

An experimental ultra wideband ground penetrating radar based on Golay complementary sequences is proposed to locate underground pipes. Golay complementary sequences with the code length of 1024 and frequency of 1 GHz are used as the probe signals. Two-dimensional image of the buried pipes is achieved by correlation method and back projection algorithm. The experimental results show that both the plastic pipe and metallic pipe can be located with a range resolution of 10 cm. Furthermore, as the Golay complementary sequences are a pair of complementary sequences, the sum of their correlation function yields twice the value of the peak at the target position and zero elsewhere. Thus, compared with the stepped frequency signal radar or chaotic signal radar, the Golay-based radar can significantly improve the signal noise ratio and has capability of deep detection.

This work is aimed at the development of innovative, easy and cheap methods for the stabilization, inertization and valorisation of the organic fraction of municipal solid waste (OFMSW). For the first time, two original processes for transforming the organic waste into an inert, odorless and sanitized material were here proposed. The first one, called dual step, starts with grinding of the OFMSW, by means of an industrial shredder. After being finely ground, the organic waste was exposed to a sterilization process by means of UV/ozone radiations or thermal treatment (stabilization phase) in order to obtain a complete removal of the OFMSW’s bacterial activity. By means of several microbiological analyses, the best sterilization method was chosen. The incorporation in a thermosetting matrix was, then, carried out through mixing the sterilized and finely ground organic waste into a water soluble urea formaldehyde (UF) based resin, with a formaldehyde content less than 1% wt, followed by a thermal treatment for UF-resin crosslinking (inertization phase). An alternative cheaper and easier process, called one step, was also proposed and investigated, by combining the sterilization with the curing thermal process (at higher temperature) of the thermosetting matrix. The preliminary experimental results reported in this paper suggest that both the proposed methods could be considered suitable for the production of high valorized innovative OFMSW-derived panels or bricks, that could find application in several fields, such as building or constructions materials. Finally a brief description of the prototype machinery is reported properly designed for implementing OFMSW stabilization and valorisation processes developed in this research work.

In recent years, several Ultrawideband (UWB) localization systems have already been proposed and evaluated for accurate position estimation of pedestrians. However, most of them are evaluated for a particular wearable sensor position; hence the accuracy obtained is subject to a given wearable sensor position. In this paper, we study the effects of body wearable sensor positions i.e., chest, arm, ankle, wrist, thigh, fore-head, hand, on the localization accuracy. The conclusion drawn is that the fore-head is the best, and the chest is the worst body sensor location for tracking a pedestrian. While the fore-head position is able to set an error lower than 0.35 m (90th percentile), the chest is able to set 4 m. The reason for such a contrast in the performance lies in the fact that in NLOS situations, the chest as an obstacle is larger in size and thickness than any other part of the human body, which the UWB signal needs to overcome to reach the target wearable sensor. And so, the large errors arise due to the signal arriving at the target wearable sensor from reflections of a nearby object or a wall in the environment.

In this study, a tuned mass damper is proposed as a seismic acceleration mitigating technique of an electrical cabinet inside the nuclear power plant. In order to know the mitigation performance, the electrical cabinet and the tuned mass damper were modeled using SAP2000. The sine sweep wave was used to confirm the vibration characteristics of the cabinet over a wide frequency range, and the several various earthquakes were applied to the cabinet to verify the control performance of the tuned mass damper. After analyzing the numerical results, it is summarized that the application of the proposed technique can reduce the acceleration response of the cabinet.

Light alloys machining is a widely implemented process that have usually used in presence of cutting fluids to reduce the wear impact and increase tool life. However, current environmental protection policies require their elimination in order to improve process sustainability. This fact forces to work under aggressive cutting conditions, producing adhesion wear that affects the integrity of the part surface. This study describes cutting tool wear mechanisms in machining of UNS A92024 samples under dry cutting conditions. EDS analysis showed the different composition of the adhered layers, while roughness was also positively affected by the change of the cutting geometry produced in the tool.

In addition to provide an extremely clean environment for primary loop of high-temperature gas-cooled reactor (HTR), the primary helium circulator (PHC) using electromagnetic levitation technology also provides an effective means for vibration control. Besides synchronous vibration produced by mass imbalance and sensor runout, double-frequency vibration produced by unbalanced magnetic pull (UMP) is serious in PHC engineering prototype (PHC-EP). In this paper, we firstly analyzed the mechanism of UMP and the multi-frequency vibration characteristics in combination with the PHC-EP. Then we put forward a distributed iterative learning control (ILC) algorithm and a parallel control scheme to suppress the periodic vibrations. Finally, we verified the methods by carrying out experimental researches on the active magnetic bearing (AMB) bench of PHC-EP. The results show that the methods put forward in this paper have significant control effect on the double-frequency vibration generated by UMP of the PHC-EP, and provide theoretical and practical references for the PHC safe operation in HTR.

With the development of computer science and software engineering, software becomes more and more complex. Traditional software reliability assurance techniques including software testing and evaluation can't ensure software reliable execution after being deployed. Software failure prediction techniques based on failure indicators can predict software failures according to abnormal indicator values. The latter can be collected using runtime monitoring techniques. An essential part of this method is finding proper indicators which have strong correlation with software failures. We propose a novel type of indicators in this work named software runtime entropy, which takes both software module execution time and call times into consideration. Three common open source software, grep, flex and gzip are used as study cases for finding the relationships between the indicators and software failures. Firstly, a series of fault injection experiments are conducted on those three software respectively. The decision tree algorithm is used to train those data to build the correlation models between software runtime entropy and software failures. Several common measures in machine learning domains such as accuracy, recall rates, and F-measure are used to evaluate the models. The decision tree models can be used as failure mechanisms to assist the failure prediction work. One can examine the value of runtime entropy and make a warning report when it ranges from the normal interval to abnormal one.

The article introduces a new solution approach to grid-connected single-stage three-phase PV inverter whereby a dc-link voltage can successfully achieve the desired performance. As a single-stage, the variable output of perturb and observe maximum power point tracking (P&O based-MPPT) is fully utilized as dc-link voltage reference in inverter control scheme. As a result, it is challenging for the dc-link voltage to preserve energy balance by tracking its variable dc-link voltage reference under unpredictable environmental changes. To overcome this challenge, an adaptive reference proportional-integral (ARPI) controller, self-tuning, is designed and implemented to compel the dc-link voltage tracking its voltage reference to be equal as closely as possible; hence, the capability of the dc-link under abnormal events substantially guarantees the best energy balance and transient performance enhancement. To verify the validity of the method, simulation results for multiple events scenarios on 250 KW single-stage grid-connected PV systems show the effectiveness of the ARPI controller compared with PI controller.

In recent times, with the increase of Artificial Neural Network (ANN), deep learning has brought a dramatic twist in the field of machine learning by making it more Artificial Intelligence (AI). Deep learning is used remarkably used in vast ranges of fields because of its diverse range of applications such as surveillance, health, medicine, sports, robotics, drones etc. In deep learning, Convolutional Neural Network (CNN) is at the center of spectacular advances that mixes Artificial Neural Network (ANN) and up to date deep learning strategies. It has been used broadly in pattern recognition, sentence classification, speech recognition, face recognition, text categorization, document analysis, scene, and handwritten digit recognition. The goal of this paper is to observe the variation of accuracies of CNN to classify handwritten digits using various numbers of hidden layer and epochs and to make the comparison between the accuracies. For this performance evaluation of CNN, we performed our experiment using Modified National Institute of Standards and Technology (MNIST) dataset. Further, the network is trained using stochastic gradient descent and the backpropagation algorithm.

Instead of simplified steady-state models, with modern computers, one can solve the complete aero-thermodynamics happening in gas turbine engines. In the present article, we describe a mathematical model and numerical procedure to represent the transient response of a PT6A gas turbine engine operating at off-design conditions. The aero-thermal model consists of a set of algebraic and ordinary differential equations that arise from the application of the mass, linear momentum, angular momentum, and energy balances in each engine's component. The solution code has been developed in Matlab-Simulink using a block-oriented approach. Transient simulations of the PT6A engine start-up have been carried out by changing the original Jet-A1 fuel with biodiesel blends. Time plots of the main thermodynamic variables are shown, especially those regarding the structural integrity of the burner. Numerical results have been validated against reported experimental measurements and GasTurb simulations. The computer model has been capable to predict acceptable fuel blends, such that the real PT6A engine can be substituted to avoid the risk of damaging it.

The purpose of this paper is to provide a structural review of the progress made on detection and localization of leaks in pipelines by using approaches based on the Kalman filter. This is, to the best of our knowledge, the first review on the t opic. In particular, it is the first to try to draw the attention of the leak detection community to the important contributions that use the Kalman filter as the core of a computational pipeline monitoring system. Without being exhaustive, we try to gather the results from different research groups and present them in a unified fashion. For this reason, we propose a classification of the current approaches based on the Kalman filter. For each of the existing approaches within this classification, the basic concepts, fundamental results, and relations with the other approaches are discussed in detail. The review starts from a short summary of basic concepts about state observers. Then, a brief history of the use of the Kalman filter for diagnosing leaks is described by mentioning the most outstanding approaches. At last, we briefly discuss some emerging research problems, such as the leak detection in pipelines transporting heavy oils, and we discuss the main challenges and some open problems.

Modeling brain dynamics to better understand and control complex behaviors underlying various cognitive brain functions are of interests to engineers, mathematicians, and physicists from the last several decades. With a motivation of developing computationally efficient models of brain dynamics to use in designing control-theoretic neurostimulation strategies, we have developed a novel data-driven approach in a long short-term memory (LSTM) neural network architecture to predict the temporal dynamics of complex systems over an extended long time-horizon in future. In contrast to recent LSTM-based dynamical modeling approaches that make use of multi-layer perceptrons or linear combination layers as output layers, our architecture uses a single fully connected output layer and reversed-order sequence-to-sequence mapping to improve short time-horizon prediction accuracy and to make multi-timestep predictions of dynamical behaviors. We demonstrate the efficacy of our approach in reconstructing the regular spiking to bursting dynamics exhibited by an experimentally-validated 9-dimensional Hodgkin-Huxley model of hippocampal CA1 pyramidal neurons. Through simulations, we show that our LSTM neural network can predict the multi-time scale temporal dynamics underlying various spiking patterns with reasonable accuracy. Moreover, our results show that the predictions improve with increasing predictive time-horizon in the multi-timestep deep LSTM neural network.

We discuss a topological method of storing and retrieving information from flash memory. We first present a sensing method where the threshold voltage level, as represented by a sensing time, is extracted in one sensing cycle. The sense time distribution from one set of flash cells, e.g. one physical row, is then processed in software to decode the digital state of each cell. The decoding method uses topological constraints but no rigid or predetermined voltage thresholds to digitize the distribution. The software defined nature of the topologically defined flash (TDF) allows greater flexibility for allocating cells to arbitrary number of digital states.

Plants Microbial Fuel Cells (PMFC) is a new technology that generates electricity in a renewable, clean and sustainable way. In spite of these advantages, it still faces limitations in power generation and current density, reaching lower production values than other renewable technologies. Different studies maintain that the high resistivity of the cathode is the main limitation in the generation of energy; therefore, non-metallic materials to obtain a better performance are replacing the metallic electrodes. The implementation of these materials applied to PMFC requires a complex interdisciplinary work. Through three experimental tests using metallic electrodes for the extraction of electrons, this research study shows that the treatment of the substrate with natural materials, the volume plant roots, and substrate temperature and humidity control have a significant influence in the increase of the electric potential and the generated current.

Drying food involves complex physical atmospheric mechanisms with non-linear relations from the air-food interactions and those relations are strongly dependent on the moisture contents and the type of food. Such dependence makes it complex to design suitable dryers dedicated to a single drying process. To streamline the design of a novel compact food-drying machine, a heat pump dryer component design optimization algorithm was developed as a subprogram of a Computer Aided Engineering tool. The algorithm requires inputting food and air properties, the volume of the drying container and the technical specifications of the heat-pump off-the shelf components. The heat required to dehumidify the food supplied by the heat exchange process from condenser to evaporator, and the compressor’s requirements (refrigerant mass flow rate and operating pressures) are then calculated. Compressors can then be selected based in the volume and type of food to be dried. The algorithm is shown via a flow chart to guide the user through 3 different stages: Changes in drying air properties, Heat flow within dryer and Product moisture content. Example results of how different compressors are selected for different type of produces and quantities (Agaricus Blazei mushroom with 3 different moisture contents or fish from Thunnini tribe) conclude this article.

Mobile elevating work platforms (MEWPs) consist of a work platform, extending structure, and chassis, and are used to move persons to working positions. MEWPs are useful but are composed of pieces of equipment, and accidents do occur owing to equipment defects. Among these defects, accidents caused by the fracture of bolts fixed to the extension structure and swing system are increasing. This paper presents a failure analysis of the fixing bolts of MEWP. Standard procedure for failure analysis was employed in this investigation. Visual inspection, chemical analysis, tensile strength measurement, and finite element analysis (FEA) were used to analyze the failure of the fixing bolts. Using this failure analysis approach, we found the root cause of failure and proposed a means for solving this type of failure in the future. First, the chemical composition of the fixing bolt is obtained by a spectroscopy chemical analysis method, which determined that the chemical composition matched the required standard. The tensile test showed that the tensile and yield strengths were within the required capacity. The stress analysis was carried out at five different boom angles, and it was determined that the fixing bolt of MEWP can withstand the loads at all the boom angles. The outcomes of the fatigue analysis revealed that the fixing bolt fails before reaching the design requirements. The results of the fatigue analysis showed primarily that the failure of the fixing bolt was due to fatigue. A visual inspection of the fractured section of the fixing bolt also confirmed the fatigue failure. We propose a method to prevent failure of the fixing bolt of the MEWP from four different standpoints: the manufacturer, safety certification authority, safety inspection agency, and owner.

In the environments of all kinds open coal storage sites , mining-affected coalbeds, and goafs, parts of coal body at low moisture content (≤8%) are prone to spontaneous combustion under the influence of some external environmental factors. In order to examine the influence effect of low moisture content on the spontaneous combustion tendency of coals with different metamorphic grade, we conducted temperature programmed oxidation (TPO) experiment and differential scanning calorimetry (DSC) experiment to study the spontaneous combustion characteristics of coals with different metamorphic grade at four different low moisture content, and comparatively analyzed the change laws of the characteristic parameters of four different metamorphic grade coals at four different low moisture content. The experimental results indicate that: 1) Compared other low moisture content, anthracite and fat coal at low moisture content of 1.2% show stronger tendency to undergo spontaneous combustion, long flame coal and lignite at low moisture content of 3.4% and 5.6% are more prone to spontaneous combustion. 2) Four different metamorphic grade coals at low moisture content of 7.8% are less prone to spontaneous combustion; 3) Coals with different metamorphic grade have different tendency to undergo spontaneous combustion.

Ongoing climate change causes abnormal climate events worldwide such as increasing temperatures and changing rainfall patterns. With South Korea facing growing damage from the increased frequency of localized heavy rains, the country is not an exception. In particular, its steep slope lands, including mountainous areas, are vulnerable to damage from landslides and debris flows. In addition, localized short-term heavy rains that occur in urban areas with extremely high intensity tend to lead a sharp increase in damage from soil-related disasters and cause huge losses of life and property. Currently, South Korea predicts landslides and debris flows using the standards for forecasting landslides and heavy rains. However, as the forecasting is conducted separately for rainfall intensity and accumulated rainfall, this lacks a technique that reflects both amount and intensity of rainfall in an episode of localized heavy rainfall. This study, therefore, aims to develop such a technique by collecting past cases of debris flow occurrences and rainfall events that accompanied debris flows to calculate the rainfall triggering index (RTI) reflecting accumulated rainfall and rainfall intensity. In addition, the RTI is converted into the critical accumulated rainfall (Rc) to use precipitation information and provide real-time forecasting. The study classifies the standards for flow debris forecasting into three levels: ALERT (10%–50%), WARNING (50%–70%), and EMERGENCY (70% or higher), to provide a nomogram for 6 hr, 12 hr, and 24 hr. As a result of applying this classification into the actual cases of Seoul, Chuncheon, and Cheongju, it is found that about 2–4 hr of response time is secured from the point of the Emergency level to the occurrence of debris flows.

The study focused on two climatic variables i.e. precipitation and stream flow for analysing change in trend of rainfall for the River Ssezibwa Catchment area and stream flow of River Ssezibwa. This Catchment is found in the districts of Mukono and Buikwe in Uganda. In this area agriculture is majorly dependent on rainfall and irrigation on a small scale. However, rainfall occurrence has become unpredictable over the past few years as result of the changes in patterns of weather. This has caused severe effects on the agricultural cropping system as well as caused negative effects on the natural water resources. Stream flow data of 57 years (1960 – 2017) and rainfall data for 35 years (1982 – 2017) on a daily basis was analysed to find out the trend and detect change point. Trend analysis was done by using the non-parametric analysis while the change point detection was carried out by using the Pettit test (1979).Magnitude of trend for the time series data was carried out using Sen’s Slope estimator and Mann – Kendall test was done to determine the trend. Results from the statistical analysis highlighted that; for stream flow the trend was generally positive and change point detected to be in the year 2000 while for rainfall data analysis indicated that the trend was predominantly negative and change point was in the year 1998.

The study concentrates on researching possibilities of using computer image analysis and neural modeling in order to assess selected quality discriminants of spray-dried chokeberry powder. The aim of the paper is quality identification of chokeberry powders on account of their highest dying power, the highest bioactivity as well as technologically satisfying looseness of powder. The article presents neural models with vision technique backed up by devices such as digital camera as well as electron microscope. Reduction in size of input variables with PCA has influence on improving the processes of learning data sets, thus increasing effectiveness of identifying chokeberry fruit powders included in digital pictures, which is shown in the results of the conducted research. The effectiveness of image recognition are presented by classifying abilities as well as low Root Mean Square Error (RMSE), for which the best results are achieved with typology of network type Multi-Layer Perceptron (MLP). The selected networks type MLP are characterized by the highest degree of classification at 0.99 and RMSE at 0.11 at most at the same time.

Thermal-based actuators are known for generating large force and displacement strokes at mesoscale (millimeter) regime. In particular, two-phase thermal actuators are found to benefit from the scaling laws of physics at mesoscale to offer large force and displacement strokes; but they have low thermal efficiencies. As an alternative, a combustion-based thermal actuator is proposed and its performance is studied in both open and closed cycle operations. Through a physics-based lumped-parameter model, we investigate the behavior and performance of the actuator using a spring-mass-damper analogy and taking an air standard cycle approach. Three observations are reported: (1) the mesoscale actuator can generate peak forces of up to 400 N and displacement strokes of about 16 cm suitable for practical applications; (2) an increase in heat input to the actuator results in increasing the thermal efficiency of the actuator for both open and closed cycles; and (3) for a specific heat input, both the open and closed cycle operations respond differently \textemdash different stroke lengths, peak pressures, and thermal efficiencies.

This paper presents the experimental implementations of the mathematical models and algorithms developed in Part I. Two experiments are carried out. The first experiment aims at the determinations of the correction coefficients of the mathematical model. The dot grid target is measured and the measurement data are processed by our developed and validated algorithms introduced in Part I. The values of the coefficients are indicated and analysed. Uncertainties are evaluated with implementation of the Monte Carlo method. The second experiment measures a different area of the dot grid target. The measurement results are corrected according to the coefficients determined in the first experiment. The mean residual between the measured points and their corresponding certified values reduced 29.6% after the correction. The sum of squared errors reduced 47.7%. The methods and the algorithms for raw data processing, such as data partition, fittings of dots’ centres, K-means clustering, etc., are the same for both two experiments. The experimental results demonstrate that our method for the correction of the errors produced by the movement of lateral stage of confocal microscope is meaningful and practicable.

We propose a 10-Gb/s 64-quadrature amplitude modulation (QAM) signal-based Radio over Fiber (RoF) system for 50 km of standard single mode fiber length which utilizes Reinforcement Learning (RL) SARSA based decision method to indicate an effective decision which mitigates nonlinearity. By utilizing RL-SARSA algorithm, the results demonstrate that significant reduction can be obtained in terms of bit error rate.

While the container crane is an important part of daily port operations, it has received little attention compared with other infrastructures, such as buildings and bridges. Crane collapse due to earthquake affects the operation of the port, and indirectly impacts the economy. This study proposes fragility analyses for various damage levels of the container crane that allow the port owner and partners to better understand the seismic vulnerability presented by container cranes. A large quantity of nonlinear time history analyses was applied for a three-dimensional (3D) finite element model to quantify the vulnerability of the container crane in considering the uplift and derailment behavior. The uncertainty of demand and capacity of the crane structures were also considered through random variables, i.e. elastic modulus of members, ground motion profile, and intensity. The results analyzed in the case of a Korean container crane showed that the probability of exceeding the first uplift with or without derailment is shown before the crane reaches the structure’s limit states. This means that under low seismic excitation, the crane might be derailed without any structural damage. But when the crane reaches the minor damage state, it is always coupled with a certain probability of uplift with or without derailment. This study also proposes the fragility curves developed for different structural periods to enable port stakeholders to assess the risk of their container crane.

Abstract: Current models in design of urban water management systems and their corresponding infrastructure using centralized designs have commonly failed from the perspective of cost effectiveness and inability to adapt to the future changes. These challenges are driving cities towards using decentralized systems. While there is great consensus on the benefits of decentralization; currently no methods exist which guide decision-makers to define the optimal boundaries of decentralized water systems. A new clustering methodology and tool to decentralize water supply systems (WSS) into small and adaptable units is presented. The tool includes two major components: (i) minimization of the distance from source to consumer by assigning demand to the closest water source, and (ii) maximization of the intra-cluster homogeneity by defining the cluster boundaries such that the variation in population density, land use, socio-economic level, and topography within the cluster is minimized. The methodology and tool are applied to Arua Town in Uganda. Four random cluster scenarios and a centralized system were created and compared with the optimal clustered WSS. It was observed that the operational cost of the four cluster scenarios is up to 13.9 % higher than the optimal, and the centralized system is 26.6% higher than the optimal clustered WSS, consequently verifying the efficacy of the proposed method to determine an optimal cluster boundary for WSS. In addition, optimal homogeneous clusters improve efficiency by encouraging reuse of wastewater and stormwater within a cluster and by minimizing leakage through reduced pressure variations.

Land engineering is a specific new academic discipline in China. Although the undergraduate major of land engineering was officially approved and established lately since 2017, the birth of land engineering as an academic discipline dates back 40 years ago. It has passed through four development stages: the incubation stage in 1978-1985, the initial stage in 1986-1997, the growth stage in 1998-2011, and the expanding stage from 2012 to present. However, land engineering as an academic discipline remains immature and seriously lags behind practice. There are still no unified academic community and broad academic consensus. After a historical overview of the four development stages, this study gave a strategic consideration to five key questions. We argue that the study object of the discipline is land engineering activity, which is defined as the artificial transformation of a land complex combined by various natural and human elements. The uniqueness of the discipline is rooted in its ability to study the comprehensive and integrated reorganization or rebuilding of various elements of land as a complex, with the theory of land complex reconstruction being the core theory. The discipline of land engineering is based on land pure science and land technology, and is one basis of land management. It consists of two modules (rural land engineering and urban land engineering), five secondary disciplines of each module (land development, land rearrangement, land improvement, land protection, and land remediation), and more than 30 research directions. Various technologies are only instrumental but not essential components of land engineering as an academic discipline.

This work aims to develop an integrated fault location and restoration approach for microgrids (MGs). This work contains two parts. Part I presents the fault location algorithm, and Part II shows the restoration algorithm. The proposed algorithms are implemented by particle swarm optimization (PSO). The fault location algorithm is based on network connection matrices, which are the modifications of bus-injection to branch-current and branch-current to bus-voltage (BCBV) matrices, to form the new system topology. The backward/forward sweep approach is used for the prefault power flow analysis. After the occurrence of fault, the voltage variation at each bus is calculated by using the Zbus modification algorithm to modify Zbus. Subsequently, the voltage error matrix is computed to search for the fault section by using PSO. After the allocation of the fault section, the multi-objective function is implemented by PSO for optimal restoration with its constraints. Finally, the IEEE 37-bus test system connected to distributed generations is utilized as the sample system for a series simulation and analysis. The outcomes demonstrated that the proposed optimal algorithm can effectively solve the fault location and restoration problem in MGs.

The key goal of the current study was to determine suitable areas of water pumping for drinking and agricultural harvest in Tabriz aquifer, located in East Azerbaijan province, northwest Iran. In the study area, groundwater is the key foundation of water for drinking and farming requirements. Groundwater compatibility study was conducted by analyzing Electrical conductivity (EC), Total dissolved solids (TDS), Chloride (Cl), Calcium (Ca), Magnesium (Mg), Sodium (Na), Potassium (K), Sulfate (SO4), Total hardness (TH), Bicarbonate (HCO3), pH, carbonate (CO3) and Sodium Adsorption Ratio (SAR) obtained from 39 wells in the period of 2003 to 2014. For this purpose, the Water Quality Index (WQI) and irrigation water quality (IWQ) index were utilized. The WQI index zoning exposed that the groundwater of the study area for drinking purposes is categorized as excellent, good and poor water. Most drinking water harvested for urban and rural areas are in the class of 'excellent water'. The results revealed that about 37 percent (296 km2) of groundwater has high compatibility, and 63 percent of the study area (495 km2) has average compatibility for agricultural purposes. The trend of IWQ and WQI indexes demonstrates that the groundwater is getting worse over the time.

In recent years, distributed generation technology has developed rapidly. Renewable energy, represented by wind energy and solar energy, has been widely studied and utilized. In order to give full play to the advantages of Distributed Generation (DG) and meet the challenges after power grid access, Active Distribution Network (ADN) is considered as the future development direction of traditional distribution network because of its ability of active management. Nowadays, multi-scenario analysis is widely used in the research of optimal allocation of distributed power supply in active distribution network. Aiming at the problems that may arise when using multi-scenario analysis to plan DG with uncertainties in large-scale scenarios, a scenario reduction method based on improved clustering algorithm is proposed. The validity of the scene reduction method is tested, and the feasibility of the method is verified. At present, there are few studies on the optimal allocation of DG in ADN under fault state. In this paper, comprehensive safety indicators are introduced. Considering the timing characteristics of DG and the influence of active management mode, a bi-level programming model is established, which aims at minimizing the investment of annual life cycle and the removal of active power. The bi-level model is a complex mixed integer non-linear programming model. A hybrid algorithm combining cuckoo search algorithm and primal dual interior point method is used to solve the model. Finally, through the simulation of the IEEE-33 node system, the superiority of the scenario reduction method and the comprehensive security index used in this paper to optimize the configuration of DG in ADN is verified.

Due to an increase of the monocrystalline PV systems installations, for a drive towards the sustainable smart cities in the hot arid developing country such as Pakistan, pose challenges of the performance and degradation issues. Monocrystalline PV module efficiencies are declining and damaging under the continuous exposure to higher surface day-time temperatures in the different parts of the country. A MATLAB simulations were performed based on the validated mathematical approach. This paper investigates the hot arid surface temperature impacts on the performance of PV modules during the summer and winter seasons in Pakistan. The investigations are performed examining the power generating efficiency of the PV system. This paper also investigates the influence of installations of PV-system in the North, South, East and West regions of Pakistan. It was examined that the northern areas of Pakistan are more suitable for maintaining the long-term durability of the PV system. Investigations are performed for the peak summer and peak winter days. During summer months, cooling strategies have to be implemented to overcome the heating effects whilst reducing degradation effect on installed PV-system.

As more end devices are getting connected, the Internet will become more congested. A variety of congestion control techniques have been developed either on transport or network layers. Active Queue Management (AQM) is a paradigm that aims at mitigating the congestion on the network layer by active buffer control to avoid overflow. However, finding the right parameters for an AQM scheme is challenging, due to the complexity and dynamics of the networks. On the other hand, the Explicit Congestion Notification (ECN) mechanism is a solution that makes visible incipient congestion on the network layer to the transport layer. In this work, we propose to exploit the ECN information to improve AQM algorithms by applying Machine Learning techniques. Our intelligent method uses an artificial neural network to predict congestion and an AQM parameter tuner based on reinforcement learning. The evaluation results show that our solution can enhance the performance of deployed AQM, using the existing TCP congestion control mechanisms.

Fluid mechanics of flow in hydrophobic, rectangular microchannels with finite aspect ratios is of paramount importance. In such microchannels, not only the effect of the side walls should be taken into account, but also the classical assumption of no-slip boundary condition (BC) is no longer valid at the solid-liquid interface. Accordingly, slip flow can occur in microchannels fabricated from surfaces with low wetting conditions, hydrophobic surfaces. Determining the interactions of liquid molecules adjacent to solid surface is still a challenging issue, and it is especially important in small scale domains. Herein, the fluid mechanics of flow through rectangular hydrophobic microchannels has been reconsidered by taking into account the general Navier-slip BCs at the solid-liquid interface. For fully developed incompressible flow in microchannels at low Reynolds number, partial differential equation (PDE) of the momentum equation simplifies to the classical Poisson equation. Accordingly, by analytically solving the Poisson equations with general Navier-slip BCs, the most general forms of velocity distributions, flow rate, friction factor and Poiseuille number have been obtained.

Lake Manzala, the largest of the northern Delta lakes of Egypt, has a great economic importance as a major natural resource of fish and salt. Unfortunately, the lake is suffering from the high inputs of pollutants from industrial, domestic, and agricultural sources. The present study aims to develop the proposed water quality management scenarios to assess and control lake pollution, the pollution sources as well as the pollution spread from the lake to the connected Mediterranean Sea. To apply study methodology, the work tasks divided into two main parts, the first part involved in modelling the lake environments by using Delft3D-WAQ hydrodynamic and water quality model to study the current status and predict the dynamic state of the Lake. This model was calibrated and validated by using various water quality datasets to simulate different scenarios. In the second part, the required lake water quality improvement scenarios were developed to solve the lake water quality problems. The study results showed that the first three developed scenarios that focusing on treatment drain effluent using primary, secondary treatment and surface wetland techniques respectively have a limited efficiency on lake water quality improvement. While the fourth scenario that involved on using biological biofilm techniques can improve lake water quality parameters. Moreover, the fifth scenario that proposed adding a new artificial inlet has a limitation due to the noted increases in lake salinity levels. The sixth scenario that proposed a diversion of some drains can improve lake water quality parameters but it can lead to a decrease in Lake water level. From water quality view point, the last scenario that applying a combination biological biofilm activated technique and also adding a new artificial inlet at northern lake region can represent the optimum scenario. Hopefully, this research will preserve the lake environment and contribute to the benefit of the man health as well. This approach could be extended to the hydrodynamic studies in similar large, shallow lakes anywhere in the world.

Research results of the relationships between air-volume in air-entrained cement paste, mortar and concrete, all designed according to PN-EN 480-1 guidelines are presented in the paper. The cement paste, mortar and concrete, with w/c=0,5 ratio, were prepared using innovative air-entraining cement CEM II/B-V. The air-entraining cement CEM II/B-V was produced using two methods: mixed together with natural or synthetic aerated admixture. The air volume test of the volumetric method was carried out in case of fresh cement paste, mortar and concrete mix. Fresh concretes were evaluated in terms of stability of air entrainment and consistency for 5, 20 and 40 min. The porosity structure parameters, like summarized air-content, specific surface of air voids, air-voids spacing factor and micropores content of hardened concrete, were estimated using computed tomography with a resolution of 2-5 μm. The aim of the research was to determine the dependence between air-content of cement paste, mortar and concrete on the measurement of air-entrainment of cement paste or mortar with the same w/c ratio and type of cement, all designed according to PN-EN 480-1 guidelines. Test results proved that there is a good correlation between the measured air-content of the cement paste, mortar and concrete. Therefore, it is possible to predict the aeration of concrete on the air-entrainment of the mortar.

Although the complexity of physically based models continues to increase, they still need to be calibrated. In recent years, there has been an increasing interest in using new satellite technologies and products with high resolution in model evaluations and decision-making. The aim of this study is to investigate the value of different remote sensing products and groundwater level measurements in the temporal calibration of a well-known hydrologic model i.e. HBV. This has been rarely done for conceptual models as satellite data are often used in spatial calibration of the distributed models. Three different soil moisture products from ESA CCI SM v04.4, AMSR-E and SMAP, and total water storage anomalies from GRACE are collected and spatially averaged over the Moselle River Basin in Germany and France. Different combinations of objective functions and search algorithms all targeting a good fit between observed and simulated streamflow, groundwater and soil moisture are used to analyse the contribution of each individual source of information. Firstly, the most important parameters are selected using sensitivity analysis and then, these parameters are included in a subsequent model calibration. The results of our multi-objective calibration reveal substantial contribution of remote sensing products to the lumped model calibration even if their spatially distributed information is lost during the spatial aggregation. Inclusion of new observations such as groundwater levels from wells and remotely sensed soil moisture to the calibration improves the model’s physical behaviour while it keeps a reasonable water balance that is the key objective of every hydrologic model.

Shanghai is experiencing water supply problems caused by heavy pollution of its raw water supply, deficiencies in its treatment processes and water quality deteoriation in the distribution system. However, little attention has been paid these problems of water quality in raw water, water treatment and household drinking water. Based on water quality data we show that the raw water sources of the Huangpu River and the Changjiang (Yangtze River) estuary are polluted by microbes (TBC), eutrophication (TP, TN and NH3-N), heavy metals (Fe, Mn and Hg) and organic contamination (chemical oxygen demand [COD], detergent and volatile phenols [VP]). The average concentrations of these contaminants in the Huangpu River are almost double that of the Changjiang estuary forcing a rapid shift to the Changjiang estuary for raw water. In spite of filtering and treatment, TN, NH3-N, Fe, COD and chlorine maxima of the treated water and drinking water still exceed the Chinese National Standard (GB5749). We determine that the relevant threats from water source to household water in Shanghai are: 1) eutrophication arising from highly concentrated TN, TP, COD and algal density in the raw water; 2) increasing salinity in the river estuary, especially at the Qingcaosha Reservoir (currently the major freshwater source for Shanghai); 3) more than 50% of organic constituents and by-products remain in treated water; 4) bacteria and turbidity increase in the course of water delivery to users. The analysis presents an holistic assessment of the water quality threats to metropolitan Shanghai in relation to the city’s rapid development.

The formal transfer of GNSS under water is not possible. It probably makes sense to talk only about the transformation of GPS into LPS, that is, in the Local Position System. However, the basic methods that are used to solve the problem of Spoofing Detection above water can be used under water. It should be understood that engineering problems are significantly different, since the nature of the propagation of acoustic waves in water and electromagnetic waves in the atmosphere are fundamentally different. In this article, we will limit the navigation with acoustically passive receiver. The receiver “listens” to the buoys and solves the problem of finding its own position based on the coordinates of the buoys (such systems are called GNSS-like Underwater Positioning Systems or GNSS-like UPS). Depending on the scale of system service areas, GNSS-like UPS are divided into global, regional, zonal and local system. In this article, we will limit ourselves to considering only local GNSS-like UPS. The acoustic signal generator transmits a signal simulation of several satellites. If the level of the simulated signal exceeds the signal strength of real satellites, the receiver of UPS will “capture” the fake signal and calculate the false position based on it.

Abstract In order to reduce the failure accidents of conventional packers, a kind of sealing structure of retrievable packers is designed, which can provide reference for optimizing the sealing performance and pressure capacity of packers. And theoretical calculation and experimental research on its sealing performance and pressure capacity are carries out through the finite element analysis on the contact with large deformation based on Abaqus and experimental. The results show that when the rubber cylinder of retrievable packers in the sealing process, the upper packer is subjected to greater stress and mainly plays a sealing role. In order to improve the sealing performance of packer, the height of upper and lower packer should be preferentially selected about 60 mm, the height of middle rubber cylinders should be about 50 mm, and the thickness of packer should be about 21 mm. The newly designed rubber cylinders can meet 150 ℃. Sealing and pressure-bearing function under the condition of 10000 Psi. The rubber cylinder of newly designed can satisfy the function of sealing and pressure-bearing under 140 ℃ and 10000 Psi. The whole experiment shows that the capacity of bearing pressure and sealing is stable, which can better meet the requirements of field use.