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The problem of localization of nodes of a wireless sensor network placed in different physical media (anchor nodes above ground and sensor nodes underground) is addressed in this article. We use time of arrival of signals transmitted between neighboring sensor nodes and between satellite nodes and sensor nodes as the ranging measurement. The localization problem is formulated as a parameter estimation of the joint distribution of the time of arrival values. The probability distribution of the time of arrival of a signal is derived based on rigorous statistical analysis and its parameters are expressed in terms of the location coordinates of the sensor nodes. Maximum likelihood estimates of the nodes’ location coordinates as parameters of the joint distribution of the various time of arrival variables in the network are computed. Sensitivity analysis to study the variation in the estimates with respect to error in measured soil complex permittivity and magnetic permeability is presented to validate the model and methodology.

Nowadays, supplying demand load and maintaining sustainable energy are important issues that have created many challenges in power systems. In these types of problems, short-term load forecasting has been proposed as one of the management and energy supply modes in power systems. In this paper, after reviewing various load forecasting techniques, a deep learning method called bidirectional long short-term memory (Bi-LSTM) is presented for short-term load forecasting in a microgrid. By collecting relevant features available in the input data at the training stage, it is shown that the proposed procedure enjoys important properties, such as its great ability to process time series data. A microgrid in rural Sub-Saharan Africa, including household and commercial loads, was selected as the case study. The parameters affecting the formation of household and commercial load profiles are considered as input variables, and the total household and commercial load profiles of the microgrid are considered as the target. The Bi-LSTM network is trained by input variables to forecast the microgrid load on an hourly basis by recognizing the consumption pattern. Various performance evaluation indicators such as the correlation coefficient (R), mean squared error (MSE), and root mean squared error (RMSE) are utilized to analyze the forecast results. In addition, in a comparative approach, the performance of the proposed method is compared and evaluated with other methods used in similar studies. The results presented for the training phase show an accuracy of R = 99.81% for the Bi-LSTM network. The test and load forecasting stage are performed by the Bi-STLM network, with an accuracy of R = 99.34% and forecasting errors of MSE = 0.1042 and RMSE = 0.3243. The results confirm the high performance of the proposed Bi-LSTM technique, with a high correlation coefficient when compared to other methods used for short-term load forecasting.

Discrete feeding of forest seeds is an urgent task for accurate detection of seeds during grading and reducing the seeding rate. The study used Pinus sylvestris L. seeds from cones collected in a natural stand of the Lisinsky educational-and-experimental forestry farm, Leningrad region, Russia, in 2017. Well-known methods for determining the properties of bulk materials were used, the results were processed by mathematical statistics using the MS Excel program. The physical and mechanical properties of uncalibrated seeds as a bulk material were determined. The angle of repose of Pinus sylvestris L. seeds, determined using a hollow cylinder by calculation, is 24.92&deg, The angle of repose of Pinus sylvestris L. seeds, determined using a hollow cylinder and a goniometer, is 32.7&deg, The significant discrepancy (~8&deg, ) in the values obtained by these methods is explained by the seeds shape. The flowability of Pinus sylvestris L. seeds corresponds to an excellent (free) category. The study will enable correct seed treatment protocols for sustainable forest management. However, some questions remained unresolved: how to orient a single seed in the right direction? How does seed-size calibration affect the angle of repose?

In measurement systems operating under various disturbances the probabilistic characteristics of measurement noises are usually known approximately. To improve the observation accuracy, a new approach to the Kalman&rsquo, s filter adaptation is proposed. In this approach, the Covariance Matrix of Measurement Noises (CMMN) is estimated by accurate measurements detected irregularly by the mobile object observation system (from radiofrequency identifiers, etalon reference, fixed points etc.). The problem of adaptive estimation of the observer&rsquo, s noises covariance matrix in the Kalman filter is solved analytically for two cases: mutual noises correlation, and its absence. The numerical example for adaptive filtration of complexing navigation system parameters of a mobile object using irregular accurate measurements is given to illustrate the effectiveness of the proposed algorithm. Coordinate estimating errors have changed in comparison with the traditional scheme from 100 m to 2 m in latitude, and from 200 m to 1.5 m in longitude.

This paper aims to highlight the potential of solar water heater installations in Morocco. The project involves the comparison of active and passive solutions for energy efficiency in buildings. To this end, a numerical simulation model of solar water heater installations is created under TRNsys. Three hot water demand scenarios (Low, Standard, and High) were taken into account for the six climatic zones defined in the Moroccan thermal regulation of constructions. The same software (TRNsys) is used to model a pilot building consisting of 16 flats. Energy efficiency actions have been applied to the building envelope (insulation and glazing) and simulations are made for the six areas. The simulation results comparing energy and financial savings show the influence of subsidized gas prices on solar water heaters&rsquo, relevance despite significant energy savings. This work proves that solar water heaters will be a primary obligation for Morocco, taking into account changes in butane gas prices.

The present inquiry studies the influence of mass transfer in magnetohydrodynamics (MHD) upper-convected Maxwell (UCM) fluid flow on a stretchable, porous subsurface. The governing partial differential equations for the flow problem are reformed to ordinary differential equations through similarity transformations. The numerical outcomes for the arising non-linear boundary value problem are determined by implementing the successive linearization method (SLM) via Matlab software. The accuracy of the SLM is confirmed through known methods, and convergence analysis is also presented. The graphical behavior for all the parametric quantities in the governing equations across the velocity and concentration magnitudes, as well as the skin friction and Sherwood number, is presented and debated in detail. A comparability inquiry of the novel proposed technique, along with the preceding explored literature, is also provided. It is expected that the current achieved results will furnish fruitful knowledge in industrious utilities and correlate with the prevailing literature.

In recent years, machine learning (ML) tools have gained tremendous momentum and received wide-spread attention in different segments of modern-day life. As part of digital transformation, the power system industry is one of the pioneers in adopting such attractive and efficient tools for various applications. Apparently, a nonthreatening, but slow-burning issue of the electric power systems is the low-frequency oscillations (LFO), which, if not dealt with appropriately and on time, could result in complete network failure. This paper addresses the role of a prominent ML family member, particle swarm optimization (PSO) tuned adaptive neuro-fuzzy inference system (ANFIS) for real-time enhancement of LFO damping in electric power system networks. It adopts and models two power system networks where in the first network, the synchronous machine is equipped with only a power system stabilizer (PSS), and in the other, the PSS of the synchronous machine is coordinated with the unified power flow controller (UPFC), a second-generation flexible alternating current transmission system (FACTS) device. Then, it develops the proposed ML approach to enhance LFO damping for both adopted networks based on the customary practices of statistical judgment. The performance measuring metrics of power system stability, including the minimum damping ratio (MDR), eigenvalue, and time-domain simulation, were used to analyze the developed approach. Moreover, the paper presents a comparative analysis and discussion with the referenced works&rsquo, achieved results to conclude the proposed PSO-ANFIS technique&rsquo, s ability to enhance power system stability in real-time by damping out the unwanted LFO.

Nowadays, by increasing energy demand and considering the importance of environmental issues in recent decades, the use of renewable energies is expanding. Among renewable energies, wind power and its technology are growing and evolving more rapidly. Resource assessment in Iran has revealed the significant potential of wind energy around the country. To further develop wind energy in the country and create large-scale wind power plants, the consideration of distributed power generation using small wind turbines for applications in agricultural and residential use is needed. Conventional small wind turbines and small wind lens turbines have been developed in recent years. In this research project, a small wind lens turbine is designed. The advantages of this turbine are an increased production capacity and reduced cut-in speed and noise pollution. In this study, a lens (or shroud) is added to a small turbine, and the maximized annual energy production (AEP) and minimization of the levelized cost of energy (LCOE) are modeled. We applied the NSGA-II algorithm for optimization to find the best answer. The input parameters in the objective function of the AEP are cut-in, cut-out, rated speeds, scale factor, and shape factor. Additionally, the input parameters in the objective function of the LCOE are the power production, initial capital cost, annual operating expenses, and balance of energy. The results indicate that installing a wind lens turbine in Kish Island led to an LCOE decrease of 56% on average, and we can see an 83% increase in the AEP. In the Firoozkooh area, an average reduction of 59% in the LCOE and 74% increase in the AEP for a wind lens turbine is observed.

The aim of this paper is to address the gap in the academic literature towards the development of methodological approaches to the industrial ecosystem sustainability assessment. This study was focused on the industrial ecosystems formed based on an entropy model and implementing the principles of complex systems. This article systematizes the problem of applying the ecosystem approach to cross-industry interaction. A contribution to the literature was achieved by providing a systemic perspective on the sustainable industrial process. In this paper, we develop the methodological foundations to improve the understanding of integration processes&rsquo, influence on the industrial ecosystem potential. For a relevant analysis of industrial ecosystem potential, the existing patterns of system functioning were taken into account, including entropy equilibrium and the Harrington model. We illustrate our assumptions with an empirical case study of the National University of Science and Technology (NUST) &ldquo, MISIS&rdquo, ecosystem&mdash, &ldquo, Green technologies for resource conservation&rdquo, (Russia), with an assessment of ecosystem sustainability through the actors&rsquo, collaboration level. The propositions arising from this analysis provide information to help academics, policymakers, government, and individual enterprises with a more adequate understanding of the practical mechanisms and tools that help trigger the self-organization and sustainability of the industrial ecosystems.

This study analyzes transient turbulent modeling of three-dimensional multiple dimpled fin array using large eddy simulation (LES). The Navier&ndash, Stokes equations as well as the energy equation were constructed by the finite volume method and then discretized to form algebraic equations, which were solved by semi-implicit method for pressure-linked equation (SIMPLE). The solutions of temperature and velocity were obtained by iterating computation until it converged within each step. This simulation places nine fins on the bottom surface of a channel and changes the height of the dimple (0.4, 0.8, and 1.2 mm) with three different levels of Reynolds number (Re) (3500, 5000, and 6500) to investigate the temperature and flow field without gravity in forced convection. The results indicate that the dimpled fin array can generate vortices between the convex/concave dimples and the fin base and increase the influences of the height of the dimple on the flow field around the fin array. The averaged time-mean of the Nusselt number (Nu) for the dimple height of 0.8 mm is higher than that of the no-dimple case up to 14.4%, while the averaged time-mean Nu for the dimple height of 1.2 mm is lower than that of the no-dimple case up to 11.6%.

In a growing number of battery-driven applications the need of removing any position and speed transducer is taking over due to space, cost and mechanical reliability constraints, further than making the installation easier as requiring less wiring. This paper presents the development of a sensorless algorithm capable of running an Interior Permanent Magnet Synchronous Machine (IPMSM), assuring constant torque production in the whole speed range, form standstill to high speeds. This is achieved with an hybrid method: at standstill and very low speeds the saliency of the IPM is exploited through an High Frequency Signal Injection (HFSI), which assures a robust estimation of the rotor position. At medium to high speeds an advanced V-I estimator is adopted in order to enhance the motor performances. The developed algorithm comes out of being highly scalable as it requires very little tuning, resulting in a multi-purpose application which can be employed with any motor size.

This paper presents the results of an experimental study on a two-phase ejector. The main objective is to assess the effects of the nozzle&rsquo, s divergent and the throat diameter on performance under various working conditions. Under the same conditions, ejector operation with a convergent nozzle, results in higher critical primary mass flow rate and lower critical pressure than with a convergent-divergent nozzle version. Experiments show as well that the flow expansion is higher in the convergent-divergent nozzle. The throat diameter turns out to have an important impact only on the amount of the critical mass flow rate. The nozzle geometry has no impact on its optimal position in the ejector. Globally, the ejector with the convergent-divergent nozzle provides a higher entrainment ratio, due to a reduced primary mass flow rate and an increased secondary flow induction. Tests also show that the ejector with a lower throat diameter provides a higher entrainment ratio, due to better suction with less primary flow. Unlike the convergent-divergent nozzle, the convergent nozzle permits an entrainment ratio almost insensitive to a wide range of primary inlet sub-cooling levels. Primary and secondary mass flow rates increase proportionally with the subcooling level and result in a quasi-constant entrainment ratio.

The through-feed method in centerless grinding allows manufacturers to produce cylindrical parts at much higher levels of productivity than can be achieved with in-feed grinding, so it has been extensively employed in industry. However, its rounding mechanism is not yet well understood due to the complexity of the through-feed process. This paper presents the fundamental parameters, such as material removal rates, forces, and so on in the through-feed grinding, and analyses on the grinding system with feedback loops, including regenerative functions and the machine dynamic functions. Further, the characteristic roots of the system, representing the number of waves and the growth rates of the harmonics in roundness, are identified at each grinding position from entry to exit. To evaluate the grinding process stability, a rounding stability index (RSI) was proposed. It was demonstrated that the analytical tool modeled in this paper can identify the optimum operational conditions by the RSI for achieving desired grinding productivity and accuracy. Finally, the model is verified with grinding tests, and the nm-order roundness obtained by the tests is shown.

We present a powerful and compact batch-mode mixing and dilution technique for centrifugal microfluidic platforms. Siphon structures are designed to discretize continuous flows into a sequence of droplets of volumes as low as 100 nL. Using a passive, self-regulating 4-step mechanism, discrete volumes of two fluids are alternatingly issued into a common intermediate chamber. At its base, a capillary valve acts as a fluidic shift register, a single droplet is held in place while two or more droplets merge and pass through the capillary stop. These merged droplets are advectively mixed as they pass through the capillary valve and into the receiving chamber. Mixing is demonstrated for various combinations of liquids such as aqueous solutions as well as saline solutions and human plasma. The mixing quality is assessed on a quantitative scale by using a colorimetric method based on the mixing of potassium thiocyanate and iron(III) chloride, and in the case of human plasma using a spectroscopic method. For instance, volumes of 5 &micro, L have been mixed in less than 20 s. Single-step dilutions up to 1:5 of plasma in a standard phosphate buffer solution are also demonstrated. This work describes the preliminary development of the mixing method which has since been integrated into a commercially available microfluidic cartridge.

This study aimed to develop a simple and cost-effective method to measure blood flow in zebrafish by using an image-based approach. Three days post fertilization (dpf) zebrafish embryos were mounted with methylcellulose and subjected to video recording for tracking blood flow under an inverted microscope equipped with a high-speed CCD camera. In addition, Hoffman lens was used to enhance the blood cell contrast. The red blood cell movement was tracked by using the TrackMate plug-in in the ImageJ image processing program. Moreover, Stack Difference and Time Series Analyzer plug-in were used to detect dynamic pixel changes over time to calculate the blood flow rate. In addition to blood flow velocity and heart rate, the effect of drug treatments on other cardiovascular function parameters, such as stroke volume and cardiac output remains to be explored. Therefore, by using this method, the potential side effects on the cardiovascular performance of ethyl 3-aminobenzoate methanesulfonate (MS222) and 3-isobutyl-1-methylxanthine (IBMX) were evaluated. MS222 is a common anesthetic, while IBMX is a naturally occurring methylxanthine. Compared to normal embryos, MS222- and IBMX-treated embryos had a reduced blood flow velocity by approximately 72% and 58%, respectively. This study showed that MS222 significantly decreased the heart rate, whereas IBMX increased the heart rate. Moreover, it also demonstrated that MS222 treatment reduced 50% of the stroke volume and cardiac output. While IBMX decreased the stroke volume only. The results are in line with previous studies that used expensive instruments and complicated software analysis to assess cardiovascular function. In conclusion, a simple and low-cost method can be used to study blood flow in zebrafish embryos for compound screening. Furthermore, it could provide a precise measurement of clinically relevant cardiac functions, specifically heart rate, stroke volume, and cardiac output.

Energy storage technologies are developing rapidly, and their application in different industrial sectors is increasing considerably. Electric rail transit systems use energy storage for different applications, including peak demand reduction, voltage regulation, and energy saving through recuperating regenerative braking energy. In this paper, a comprehensive review of supercapacitors and flywheels is presented. Both are compared based on their general characteristics and performances, with a focus on their roles in electric transit systems when used for energy saving, peak demand reduction, and voltage regulation. A cost analysis is also included to provide initial guidelines on the selection of the appropriate technology for a given transit system.

Nowadays, quality of life and livability are controversial phenomenon. A high quality of life and livability are demanded in cities, however, rapid and unplanned urbanization creates a lot of challenges such as poverty, slums, social instability, insecurity, diseases, environmental challenges and climate change, unemployment, economic problems, etc., which threaten the livability of the world. Therefore, it is vital to tackle urbanization challenges and create a sustainable urban setting with a high quality of life in order to make the world a better place to live. In particular, literature reviews, surveys, exploratory case studies, and the Kiwi and Kampenhood methodology based on Persian Zarathustra that is utilized in social science, engineering and management are the main method tools in this study. Fundamentally, modern livable and sustainable urban settings are suggested as a path to deal with urbanization challenges in order to improve livability and quality of life. Although sustainable cities provide opportunities to improve quality of life, urban planning and good governance with effective regulatory frameworks to create such modern settings are required. Thus, an innovative sustainable project management is introduced as a tool to design modern livable and sustainable areas. Innovation is declared as an accelerator to achieve sustainable project management in this research.

Research Highlights: Forest owners will be able to solve the problem of testing and selection of viable forest seeds on location and save financial, time, and material resources. The possibility of integrating non-destructive quality control and separation functions in a single portable apparatus is extremely promising. The speed of the contemporary optoelectronic grader is limited by the speed of the slowest component&mdash, the mechanical system. Background and Objectives: The technological process of forest seed establishment and design of optoelectronic graders is based on a priori mathematical modeling of structural characteristics, taking into account these criteria. Known models of industrial photoseparators are expensive and have a high energy and material consumption not applicable in the field. Laboratory seed analyzers are characterized by a long time exposure, and the overall size and level of climatic performance do not allow them to be used in the field. Consequently, for small amounts of seed treatment, it is necessary to orient the seeds one by one and ensure clear and rapid coordinated actions of optoelectronic and mechanical systems. The main goal of this research is to increase the efficiency of grading forest seeds by patterning the speed of the mobile device. We will answer the following questions. What are effective geometric parameters for the seed pipe? What factors affect the speed of a single seed&rsquo, s movement? Materials and Methods: This study is based on mathematical modeling, taking into account the basic principles of mechanics, using MatLab software. Results: A mechanical model of a single Scots pine seed&rsquo, s motion in different zones of the seed pipe is designed, taking into account air resistance. The effective height of the seed pipe, taking into account the response time of optoelectronic grader systems, is determined. Conclusions: The time and speed of single seed movement through grader systems depends on the seed pipe&rsquo, s height and radius of curvature. Other things being equal, through the use of the same optical scheme with a microprocessor to solve various problems, the compactness of the photodetector scheme allows, if necessary, to upgrade the grader to solve research problems and for use in forestry.

This paper introduces an information security threat modeling (ISTM) scheme, which leverages the strengths of software engineering and risk management approaches, called I-SERM. The proposed I-SERM scheme effectively and efficiently prioritizes information security threats for IT systems that utilize a large number of sensors, such as Internet of Things (IoT)-based energy systems. I-SERM operations include determining functional components, identifying associated threat types, analyzing threat items, and prioritizing key threats with the use of software engineering tools such as product flow diagrams, use case diagrams, and data flow diagrams. By simultaneously referring to a proposed STRIDE+p matrix and a defined threat breakdown structure with reference score (TBS+r) scheme, the I-SERM approach enables systematic ISTM. To demonstrate the usability of I-SERM, this study presents a practical case aimed at electricity load balancing on a smart grid. In brief, this study indicates a substantive research direction that combines the advantages of software engineering and risk management into a systematic ISTM process. In addition, the demonstration of I-SERM in practice provides a valuable and practical reference for I-SERM application, and contributes to research in the field of information security designs for IoT-based Energy Internet systems.

The transformation of a standard 4-stroke cylinder head into a torque-improved and gradually more efficient 2-stroke design is discussed. The concept with an effective loop scavenging via an extended inlet valve holds promise for engines at low- to medium-rotational speeds for typical designs of conventional 4-stroke cylinder heads. Calculations, flow simulations, and visualizations of experimental flows in relevant geometries and time scales indicate feasibility, followed by a small engine demonstration. Based on presumably long-forgotten and outdated patents, and the central topic of this contribution, an additional jockey rides on the inlet valve&rsquo, s disk (facing away from the combustion chamber) and reshapes the in-cylinder flow into a reverted tumble. A quick gas exchange with a well-suppressed shortcut into the open exhaust is approached. For overall mechanical efficiency, the required charge pressure for scavenging is of paramount importance due to the short scavenging time and the intake&rsquo, s reduced cross-section. Herein, still acceptable charging pressures are reported for scavenging periods equivalent to low or medium rotational speeds, as characteristic for heavy-duty applications. Using widely available components (charger, direct injection, variable camshaft angles) an increased engine efficiency is suggested due to the 2-stroke&rsquo, s downsizing effect (relatively less internal friction as well as the promise of more torque and a decreased size).

Lithium-ion batteries are well known in numerous commercial applications. Using accurate and efficient models, system designers can predict the behavior of batteries and optimize the associated performance management. Model-based development comprises the investigation of electrical, electro-chemical, thermal, and aging characteristics. This paper focuses on the analysis of models describing the electrical behavior. In particular, it investigates how cell voltage and state of charge can be determined with sufficient accuracy for a given load profile. For this purpose, the Thevenin-based, the Rint, and the Shepherd&rsquo, s models, as well as a generic library model of an electronic circuit simulation software package, are compared. The procedure for determining model parameters is discussed in detail. All models are evaluated for the application in the analysis of distributed power generation. The validation is carried out by comparing simulation and measurement results with the help of a case study.

The United States (U.S.) electric infrastructure urgently needs renovation, as highlighted by recent major outages in California, New York, Texas, and Florida. The media has discussed the aging power infrastructure, and the Public Utilities Commission called for a comprehensive review of the causes of recent power outages. Without optimization algorithms to account for the many operating parameters and outage scenarios, planning engineers may inadvertently choose non-optimal locations for new components such as automated distribution switches, thereby impacting circuit reliability. This study aims to address this problem by answering the research question: &ldquo, How may location analytics should be used to enhance the reliability of the smart grid?&rdquo, To address this problem, Insights for ArcGIS was used to build worksheets using a geographic information systems (GIS)-based approach to resolve the challenges faced by utilities to reduce power outage frequency. Three case studies demonstrate various risk scenarios wherein a utility can prepare for the unexpected. An artefact in Insights for ArcGIS was created using a design science research methodology. This research proposes a solution to facilitate storm/disaster planning and vegetation management, identify optimal grid locations needing inspection or work, and detect regions where new distribution switches may provide benefits, considering the many operating parameters and outage scenarios. The artefact demonstrates that GIS can play an integral role in resolving this problem.

Greece has a large number of islands that are isolated from the main interconnected Greek power system, however, a majority of them are to be interconnected in the mainland grid over the next decade. A large number of these islands present a significant amount of wind and solar potential. The nature of load demand and renewable production is stochastic, thus, the operation of such isolated power systems can be improved significantly by the installation of a large-scale energy storage system. The role of storage is to compensate for the long and short-term imbalances between power generation and load demand. Pumped hydro storage (PHS) systems represent one of the most mature technologies for large-scale energy storage. However, their advantages have not been proven in practice for cases of medium and small-sized isolated insular systems. Regarding Greece, which contains a large number of isolated insular systems, a PHS system in the island of Ikaria started its test operation in 2019, whereas in Europe only one PHS system operates in El Hierro (Canary Islands). This paper studies the effect of installing a wind-PHS hybrid power station in the operation of the insular power system of Samos, Greece, according to the latest regulatory framework. The implemented analysis uses real hourly data for a whole year, and examines the effects of such an installation considering investors&rsquo, and power system operators&rsquo, viewpoints. More specifically, the economic viability of this project under different billing scenarios is compared, and its impact on the insular power system operation for various PHS sizes is examined.

In microgrids a major share of the energy production comes from renewable energy sources such as photovoltaic panels or wind turbines. The intermittent nature of these types of producers along with the fluctuation in energy demand can destabilize the grid if not dealt with properly. This paper presents a multi-agent-based energy management approach for a non-isolated microgrid with solar and wind units and in the presence of demand response, considering uncertainty in generation and load. More specifically, a modified version of the lightning search algorithm, along with the weighted objective function of the current microgrid cost, based on different scenarios for the energy management of the microgrid, is proposed. The probability density functions of the solar and wind power outputs, as well as the demand of the households, have been used to determine the amount of uncertainty and to plan various scenarios. We also used a particle swarm optimization algorithm for the microgrid energy management and compared the optimization results obtained from the two algorithms. The simulation results show that uncertainty in the microgrid normally has a significant effect on the outcomes, and failure to consider it would lead to inaccurate management methods. Moreover, the results confirm the excellent performance of the proposed approach. Refereed/Peer-reviewed

The paper deals with the problems of delayed transfer signals in the direct digital synthesizer (DDS) phase accumulator adders. Transfer delay is one of the factors that affect the maximum output frequency of the DDS synthesizer. The main types of adders used in DDS synthesizers are described. Separately, attention was paid to the adder with a consistent transfer of the transfer signal, adders with a transmission carry signal with a fixed block length, adders with a signal transmission delay with a variable block length, and a mathematical analysis of the origin and duration of the delay of the transfer signal in them. It was found that the use of a transfer adder with a variable length of a block in the core of a direct digital synthesizer would increase the maximum output frequency by 2.4 times compared to the adder with a parallel transfer, and by 1.43 times as compared with the adder with a fixed length the block.

The electrical energy from the sun can be extracted using solar photovoltaic (PV) modules. This energy can be maximized if the connected load resistance matches that of the PV panel. In search of the optimum matching between the PV and the load resistance, the maximum power point tracking (MPPT) technique offers considerable potential. This paper aims to show how the modelling process of an efficient PV system with a DC load can be achieved using a fuzzy neural network (FNN) controller. This is applied via an innovative methodology, which senses the irradiance and temperature of the PV panel and produces an optimal value of duty ration for the boost converter to obtain the MPPT. The coefficients of this controller have been refined based upon previous data sets using the irradiance and temperature. A gradient descent algorithm is employed to improve the parameters of the FNN controller to achieve an optimal response. The validity of the PV system using the MPPT technique based on the FNN controller is further demonstrated via a series of experimental tests at different ambient conditions. The simulation results show how the MPPT technique based on the FNN controller is more effective in maintaining the optimal power values compared with conventional techniques.

This investigation introduces a mathematical model of entropy generation for Magnetohydrodynamic (MHD) peristaltic wave of nanofluid. The governing equations have been created by the supposition of low Reynolds number and long wavelength estimation. The scientific arrangement has been procured with the help of perturbation technique. The concentration profile, temperature profile, pressure distribution and friction forces are shown graphically for some important parameters. Further, the eventual outcomes of connection between the entropy generation and some various parameters have been plotted by means of correlation and regression. It is fundamental to find the affectability of each parameter on entropy generation.

In this paper, a new memristive chaotic system is designed, analyzed, tested, and proposed. An adaptive control synchronization mechanism for both master and slave chaotic systems is also designed. The adaptive control law of this mechanism is derived based on the Lyapunov theory. A single parameter in the slave system has been assumed to be unknown. As the parameters of the master and slave are asymptotically matched, the unknown slave parameters will be identified according to the master&rsquo, s parameters. The proposed system is used in a secure communication system. The achieved results prove a simple system implementation with a high security of data transmission.

Considered the world&rsquo, s largest industry, manufacturing transforms billions of raw materials into useful products. Like all real processes and systems, manufacturing processes and equipment are subject to the first and second laws of thermodynamics and can be modeled via thermodynamic formulations. This article presents a simple thermodynamic model of a manufacturing sub-process or task, assuming multiple tasks make up the entire process. For example, to manufacture a machined component such as an aluminum gear, tasks include cutting the original shaft into gear blanks of desired dimensions, machining the gear teeth, surfacing, etc. The formulations presented here, assessing the workpiece and the machinery via entropy generation, apply to hand-crafting. However, consistent isolation and measurement of human energy changes due to food intake and work output alone pose a significant challenge, hence, this discussion focuses on standardized product-forming processes typically via machine fabrication.

Presented is a lithium-ion battery degradation model, based on irreversible thermodynamics, which was experimentally verified, using commonly measured operational parameters. The methodology, applicable to all lithium-ion batteries of all chemistries and composition, combined fundamental thermodynamic principles, with the Degradation&ndash, Entropy Generation theorem, to relate instantaneous capacity fade (loss of useful charge-holding capacity) in the lithium-ion battery, to the irreversible entropy generated via the underlying dissipative physical processes responsible for battery degradation. Equations relating capacity fade&mdash, aging&mdash, to battery cycling were also formulated and verified. To show the robustness of the approach, nonlinear data from abusive and inconsistent battery cycling was measured and used to verify formulations. A near 100% agreement between the thermodynamic battery model and measurements was achieved. The model also gave rise to new material and design parameters to characterize all lithium-ion batteries.

Tidal power technology is at its mature stage and large deployments are soon expected. The characteristics of tidal energy and its advantage to be predictable make it an ideal type of resource to be coupled with energy storage facilities. Despite this, most energy storage facilities are expensive. The fact that water has a high specific heat capacity makes this a potential cost-effective medium to be used for storing large amounts of thermal energy for balancing renewable energy output. This paper is an investigation on the possible application of integrating hot water reservoirs for storing tidal energy during power output peaks for domestic use. The main objective of this study is to evaluate the major factors incident on the proposed solution and to provide considerations on which real remunerations the proposed idea could bring to communities or to single families. For this purpose, a simplified numerical analysis, concerning three different scenarios, was performed. These scenarios differ by type of buildings and type of thermal energy demand. The study mainly concerns remote communities. Findings indicated that the proposed idea is technically feasible and if applied in the context of residential compounds, this could be more attractive in economic terms.

In this work, HVAC (Heating, Ventilation and Air Conditioning) systems applied in university buildings with control based on PMV (Predicted Mean Vote) and aPMV (adaptive Predicted Mean Vote) indexes are discussed. The building&rsquo, s thermal behavior with complex topology, in transient thermal conditions, for summer and winter conditions is simulated by software. The university building is divided into 124 spaces, on two levels with an area of 5931 m2, and is composed of 201 transparent surfaces and 1740 opaque surfaces. There are 86 compartments equipped with HVAC systems. The simulation considers the actual occupation and ventilation cycles, the external environmental variables, the internal HVAC system and the occupants&rsquo, and building&rsquo, s characteristics. In this work, a new HVAC control system, designed to simultaneously obtain better occupants&rsquo, thermal comfort levels according to category C of ISO 7730 with less energy consumption, is presented. This new HVAC system with aPMV index control is numerically implemented, and its performance is compared with the performance of the same HVAC system with the usual PMV index control. Both HVAC control systems turn on only when the PMV index or the aPMV index reaches values below &minus, 0.7, in winter conditions, and when the PMV index or the aPMV index reaches values above +0.7, in summer conditions. In accordance with the results obtained, the HVAC system guarantees negative PMV and aPMV indexes in winter conditions and positive PMV and aPMV indexes in summer conditions. The energy consumption level is higher in winter conditions than in summer conditions for compartments with shading, and it is lower in winter conditions than in summer conditions for compartments exposed to direct solar radiation. The consumption level is higher using the PMV control than with the aPMV control. Air temperature, in accordance with Portuguese standards, is higher than 20 &deg, C in winter conditions and lower than 27 &deg, C in summer conditions. In Mediterranean climates, the HVAC systems with aPMV control provide better occupants&rsquo, thermal comfort levels and less energy consumption than the HVAC system with PMV control.

A microfluidic cell stretch device was developed to investigate the effects of stretching stress on pulmonary artery smooth muscle cell (PASMC) proliferation in pulmonary arterial hypertension (PAH). The microfluidic device harbors upper cell culture and lower control channels, separated by a stretchable poly(dimethylsiloxane) membrane that acts as a cell culture substrate. The lower channel inlet was connected to a vacuum pump via a digital switch-controlled solenoid valve. For cyclic stretch at heartbeat frequency (80 bpm), the open or close time for each valve was set to 0.38 s. Proliferation of normal PASMCs and those obtained from patients was enhanced by the circumferential stretching stimulation. This is the first report showing patient cells increased in number by stretching stress. These results are consistent with the abnormal proliferation observed in PAH. Circumferential stretch stress was applied to the cells without increasing the pressure inside the microchannel. Our data may suggest that the stretch stress itself promotes cell proliferation in PAH.

Post-fault event report analysis is a crucial skill set for electric power engineers in the protection industry. This paper serves as a reference which elucidates the preprocessing procedures involved in transforming data present in event reports to phasors that can be used in various post-fault analysis application algorithms. The paper discusses key elements of this process such as interpreting the data and calculating voltage and current phasors from instantaneous sample values present in a fault record. A crucial component of event report analysis is choosing the appropriate time instant for calculating phasors for event report analysis. Conventionally, protection engineers manually perform event report analysis and arbitrarily select time instants after certain cycles of fault inception for this purpose. This approach prevents the process from being successfully automated. Furthermore, arbitrary selection of time instant does not utilize the entire fault data and may fail in several cases such as short time fault scenario and evolving fault scenario. For this purpose, this paper proposes an adaptive novel technique which utilizes the entire data present in the event report to select the most suitable time instant for event report analysis. The superiority of the proposed algorithm over conventional methods is demonstrated using three real-world scenarios.

International audience; Although distributed additive manufacturing can provide high returns on investment, the current markup on commercial filament over base polymers limits deployment. These cost barriers can be surmounted by eliminating the entire process of fusing filament by three-dimensional (3-D) printing products directly from polymer granules. Fused granular fabrication (FGF) (or fused particle fabrication (FPF)) is being held back in part by the accessibility of low-cost pelletizers and choppers. An open-source 3-D printable invention disclosed here allows for precisely controlled pelletizing of both single thermopolymers as well as composites for 3-D printing. The system is designed, built, and tested for its ability to provide high-tolerance thermopolymer pellets with a number of sizes capable of being used in an FGF printer. In addition, the chopping pelletizer is tested for its ability to chop multi-materials simultaneously for color mixing and composite fabrication as well as precise fractional measuring back to filament. The US$185 open-source 3-D printable pelletizer chopper system was successfully fabricated and has a 0.5 kg/h throughput with one motor, and 1.0 kg/h throughput with two motors using only 0.24 kWh/kg during the chopping process. Pellets were successfully printed directly via FGF as well as indirectly after being converted into high-tolerance filament in a recyclebot.

In wide voltage range applications such as electric vehicles (EVs) onboard charging, conventional frequency modulated LLC topology has its intrinsic limitations. Its frequency span is extremely wide and the soft switching feature might get lost. To address this issue, this paper proposes a novel LLC resonant converter. The pulse width and frequency hybrid modulation are adopted to narrow down its switching frequency span. The operating principles, circuit modeling, and the design methodology are presented. A 1 kW rated prototype has been built to realize an efficient power flow between the 400 V DC bus and 200&ndash, 440 V battery pack. The designed prototype validates the effectiveness of the proposed topology and modulation method. 96.8% peak efficiency is measured for the constructed experimental prototype.

The measurement of multiple behavior endpoints in zebrafish can provide informative clues within neurobehavioral field. However, multiple behavior evaluations usually require complicated and costly instrumental settings. Here, we reported a versatile setting that applied ten acrylic tanks arranging into five vertical layers and two horizontal columns to perform multiple behavior assays simultaneously, such as the novel tank diving test, mirror-biting test, social interaction, shoaling, and predator escape assay. In total, ten behavioral performance were collected in a single video, and the XY coordination of fish locomotion can be tracked by using open source software of idTracker and ImageJ. We validated our setting by examining zebrafish behavioral changes after exposure to low dose ethanol (EtOH) for 96 h. Fish were observed staying longer time at bottom of the tank, less mirror biting interest, higher freezing time, less fear in predator test, and tight shoaling behaviors which indicated the anxiogenic effect was induced by low dosage exposure of EtOH in zebrafish. In conclusion, the setting in this study provided a simple, versatile and cost-effective way to assess multiple behavioral endpoints in zebrafish with high reliability and reproducibility for the first time.

According to UNESCO, cultural heritage does not only include monuments and collections of objects, but also contains traditions or living expressions inherited from our ancestors and passed to our descendants. Folk dances represent part of cultural heritage and their preservation for the next generations appears of major importance. Digitization and visualization of folk dances form an increasingly active research area in computer science. In parallel to the rapidly advancing technologies, new ways for learning folk dances are explored, making the digitization and visualization of assorted folk dances for learning purposes using different equipment possible. Along with challenges and limitations, solutions that can assist the learning process and provide the user with meaningful feedback are proposed. In this paper, an overview of the techniques used for the recording of dance moves is presented. The different ways of visualization and giving the feedback to the user are reviewed as well as ways of performance evaluation. This paper reviews advances in digitization and visualization of folk dances from 2000 to 2018.

How to automatically monitor wide critical open areas is a challenge to be addressed. Recent computer vision algorithms can be exploited to avoid the deployment of a large amount of expensive sensors. In this work, we propose our object tracking system which, combined with our recently developed anomaly detection system. can provide intelligence and protection for critical areas. In this work. we report two case studies: an international pier and a city parking lot. We acquire sequences to evaluate the effectiveness of the approach in challenging conditions. We report quantitative results for object counting, detection, parking analysis, and anomaly detection. Moreover, we report state-of-the-art results for statistical anomaly detection on a public dataset.

Control as a Service (CaaS) is an emerging paradigm where low-level control of a device is moved from a local controller to the Cloud, and provided to the device as an on-demand service. Among its many benefits, CaaS gives the device access to advanced control algorithms which may not be executable on a local controller due to computational limitations. As a step toward 3D printer CaaS, this paper demonstrates the control of a 3D printer by streaming low-level stepper motor commands (as opposed to high-level G-codes) directly from the Cloud to the printer. The printer is located at the University of Michigan, Ann Arbor, while its stepper motor commands are calculated using an advanced motion control algorithm running on Google Cloud computers in South Carolina and Australia. The stepper motor commands are sent over the internet using the user datagram protocol (UDP) and buffered to mitigate transmission delays, checks are included to ensure accuracy and completeness of the transmitted data. All but one part printed using the cloud-based controller in both locations were hitch free (i.e., no pauses due to excessive transmission delays). Moreover, using the cloud-based controller, the parts printed up to 54% faster than using a standard local controller, without loss of accuracy.

The focus of this work is to examine the effect of flow rate ratio (quotient of the dispersed phase flow rate over the continuous phase flow rate) on a regime transition from squeezing to dripping at constant capillary numbers. The effect of the flow rate ratio on the volume of droplets generated in a microfluidic T-junction is discussed, and a new scaling law to estimate their volume is proposed. Existing work on a regime transition reported by several researchers focuses on the effect of the capillary number on regime transition, and the results that are presented in this paper advance the current understanding by indicating that the flow rate ratio is another parameter that dictates regime transition. In this paper, the transition between squeezing and dripping regimes is reported at constant capillary numbers, with a transition region identified between squeezing and dripping regimes. Dripping is observed at lower flow rate ratios and squeezing at higher flow rate ratios, with a transition region between the two regimes at flow rate ratios between 1 and 2. This is presented in a flow regime map that is constructed based on the observed mechanism. A scaling model is proposed to characterise droplet volume in terms of flow rate ratio and capillary number. The effect of flow rate ratio on the non-dimensional droplet volume is presented, and lastly, the droplet volume is expressed in terms of a range of parameters, such as the viscosity ratio between the dispersed and the continuous phase, capillary number, and the geometrical characteristics of the channels.

Alcohol consumption affects the function of the brain and long-term excessive alcohol intake can lead to severe brain disorders. Wearable electroencephalogram (EEG) recording devices combined with Brain Computer Interface (BCI) software may serve as a tool for alcohol-related brain wave assessment. In this paper, a method for mental state assessment from alcohol-related EEG recordings is proposed. EEG recordings are acquired with the Emotiv EPOC+, after consumption of three separate doses of alcohol. Data from the four stages (alcohol-free and three levels of doses) are processed using the OpenViBE platform. Spectral and statistical features are calculated, and Grammatical Evolution is employed for discrimination across four classes. Obtained results in terms of accuracy reached high levels (89.95%), which renders the proposed approach suitable for direct assessment of the driver&rsquo, s mental state for road safety and accident avoidance in a potential in-vehicle smart system.

High mechanical rigidity, chemical resistance, and ultraviolet-visible light transmissivity of thermoplastics are attractive characteristics in microfluidics because various biomedical microfluidic devices require solvent, acid, or base manipulation, and optical observation or detection. The cyclic block copolymer (CBC) is a new class of thermoplastics with excellent optical properties, low water absorption, favorable chemical resistance, and low density, which make it ideal for use in polymer microfluidic applications. In the polymer microfabrication process, front-end microchannel fabrication and post-end bonding are critical steps that determine the success of polymer microfluidic devices. In this study, for the first time, we verified the performance of CBC created through front-end microchannel fabrication by applying hot embossing and post-end sealing and bonding, and using thermal fusion and ultraviolet (UV)/ozone surface-assist bonding methods. Two grades of CBC were evaluated and compared with two commonly used cyclic olefin polymers, cyclic olefin copolymers (COC), and cyclic olefin polymers (COP). The results indicated that CBCs provided favorable pattern transfer (&gt, 99%) efficiency and high bonding strength in microchannel fabrication and bonding procedures, which is ideal for use in microfluidics.

In this study, we investigate the interfacial droplet jetting characteristics and thermal stability of a focused surface acoustic wave device (F-SAW). An F-SAW device capable of generating a 20 MHz surface acoustic wave by applying sufficient radio frequency power (2&ndash, 19 W) on a 128&deg, rotated YX-cut piezoelectric lithium niobate substrate for interfacial droplet jetting is proposed. The interfacial droplet jetting characteristics were visualized by a shadowgraph method using a high-speed camera, and a heat transfer experiment was conducted using K-type thermocouples. The interfacial droplet jetting characteristics (jet angle and height) were analyzed for two different cases by applying a single interdigital transducer and two opposite interdigital transducers. Surface temperature variations were analyzed with radio frequency input power increases to evaluate the thermal stability of the F-SAW device in air and water environments. We demonstrate that the maximum temperature increase of the F-SAW device in the water was 1/20 of that in the air, owing to the very high convective heat transfer coefficient of the water, resulting in prevention of the performance degradation of the focused acoustic wave device.

An integrated system consisting of a paper-based chip and a smart detection device is proposed for determining the human serum creatinine concentration based on Jaffé reaction theory. In the proposed approach, the reaction zone of the paper-based chip is implanted with picric acid and NaOH reagent and dried at 35 °C for 20 min. Human serum creatinine is dripped onto the reaction zone of the chip. A Jaffé reaction is induced by heating the chip at 37 °C for 5 min and the creatinine concentration is then derived by analyzing the RGB (red, green and blue) intensity of the resulting Janovsky complex using self-written analysis software installed on a smartphone. The validity of the proposed method is demonstrated using control samples with creatinine concentrations ranging from 0.2~8 mg/dL. The detection results obtained for 32 real-world creatinine samples are shown to be in excellent agreement with those obtained using a standard macroscale method (R2 = 0.9994). Overall, the results show that the proposed system provides a compact, low-cost and reliable approach for human serum creatinine concentration detection.

In this work, pool boiling heat transfer tests were conducted for investigating the effects of the size and pitch of the hydrophobic square patterns on a copper test piece with the following dimensions: 40 mm long, 25 mm outer diameter, and 18 mm inner diameter. The size of the square patterns and the pitch were varied with an increment of 0.5 mm from 1 mm to 3 mm and from 4.5 to 5.5 mm, respectively. Among the various square patterns of different size and pitch, the 2 mm size square pattern with 5 mm pitch (inter-distance 3 mm) was found to be the best because it gives the advantage of bubble coalescence behavior and also the rewetting phenomenon. The observed bubble departure diameter was 2.35 mm, and using this diameter, we predicted the maximum inter-distance between the patterns for producing inter coalescence of bubbles in the axial direction was 3.12 mm. Therefore, a side-by-side distance of 3 mm, which was closed to the estimated inter-distance graphically, can avoid the earlier inter coalescence of the bubbles between patterns on the surface in the axial direction. This results in better pool boiling heat transfer performance. Highlights: (1) Heterogeneous wettable structures were obtained on the copper surface using screen printing techniques; (2) The effect of the size and pitch of the hydrophobic patterns on the bubble dynamics was determined; (3) The wall superheats of all the heterogeneous wettable surfaces were less than the plain copper surface; (4) The highest heat transfer coefficient was obtained from the hydrophobic pattern with 2 mm size and 5 mm pitch.

This paper aims to understand how the common phenomenon of fluctuations in propulsion and service load demand contribute to frequency transients in hybrid electric ship power systems. These fluctuations arise mainly due to changes in sea conditions resulting in significant variations in the propulsion load demand of ships. This leads to poor power quality for the power system that can potentially cause hazardous conditions such as blackout on board the ship. Effects of these fluctuations are analysed using a hybrid electric ship power system model and a proposed Model Predictive Control (MPC) strategy to prevent propagation of transients from the propellers into the shipboard power system. A battery energy storage system, which is directly connected to the DC-link of the frequency converter, is used as the smoothing element. Case studies that involve propulsion and service load changes have been carried out to investigate the efficacy of the proposed solution. Simulation results show that the proposed solution with energy storage and MPC is able to contain frequency transients in the shipboard power system within the permissible levels stipulated by the relevant power quality standards. These findings will help ship builders and operators to consider using battery energy storage systems controlled by advanced control techniques such as MPC to improve the power quality on board ships.

With Tangible User Interfaces, the computer user is able to interact in a fundamentally different and more intuitive way than with usual 2D displays. By grasping real physical objects, information can also be conveyed haptically, i.e., the user not only sees information on a 2D display, but can also grasp physical representations. To recognize such objects (“tangibles”) it is skillful to use capacitive sensing, as it happens in most touch screens. Thus, real objects can be located and identified by the touch screen display automatically. Recent work already addressed such capacitive markers, but focused on their coding scheme and automated fabrication by 3D printing. This paper goes beyond the fabrication by 3D printers and, for the first time, applies the concept of capacitive codes to laser cutting and another immediate prototyping approach using modeling clay. Beside the evaluation of additional properties, we adapt recent research results regarding the optimized detection of tangible objects on capacitive screens. As a result of our comprehensive study, the detection performance is affected by the type of capacitive signal processing (respectively the device) and the geometry of the marker. 3D printing revealed to be the most reliable technique, though laser cutting and immediate prototyping of markers showed promising results. Based on our findings, we discuss individual strengths of each capacitive marker type.

With the increasingly common use of industrial automation for mass production, there are many computer numerical control (CNC) machine tools that require the collection of data from intelligent sensors in order to analyze their processing quality. In general, for high speed rotating machines, an accelerometer can be attached on the spindle to collect the data from the detected vibration of the CNC. However, due to their cost, accelerometers have not been widely adopted for use with typical CNC machine tools. This study sought to develop an embedded miniature MEMS microphone array system (Radius 5.25 cm, 8 channels) to discover the vibration source of the CNC from spatial phase array processing. The proposed method utilizes voice activity detection (VAD) to distinguish between the presence and absence of abnormal noise in the pre-stage, and utilizes the traditional direction of arrival method (DOA) via multiple signal classification (MUSIC) to isolate the spatial orientation of the noise source in post-processing. In the numerical simulation, the non-interfering noise source location is calibrated in the anechoic chamber, and is tested with real milling processing in the milling machine. As this results in a high background noise level, the vibration sound source is more accurate in the presented energy gradation graphs as compared to the traditional MUSIC method.

This study investigates the feasibility of a novel concept, contact-free support structures, for part overhangs in powder-bed metal additive manufacturing. The intent is to develop alternative support designs that require no or little post-processing, and yet, maintain effectiveness in minimizing overhang distortions. The idea is to build, simultaneously during part fabrications, a heat sink (called “heat support”), underneath an overhang to alter adverse thermal behaviors. Thermomechanical modeling and simulations using finite element analysis were applied to numerically research the heat support effect on overhang distortions. Experimentally, a powder-bed electron beam additive manufacturing system was utilized to fabricate heat support designs and examine their functions. The results prove the concept and demonstrate the effectiveness of contact-free heat supports. Moreover, the method was tested with different heat support parameters and applied to various overhang geometries. It is concluded that the heat support proposed has the potential to be implemented in industrial applications.