The human brain is asymmetrical in function, with each of its two hemispheres being somewhat responsible for distinct cognitive and motor tasks, to include writing. It stands to reason that engineering students who ha...The human brain is asymmetrical in function, with each of its two hemispheres being somewhat responsible for distinct cognitive and motor tasks, to include writing. It stands to reason that engineering students who have established entrance into their upper-division programs will have demonstrated cognitive proficiency in math and logical operations, abstract and analytical reasoning and language usage, to include writing. In this study the question was asked: is there a correlation between an upper-division electrical engineering students’ analytical reasoning ability and their descriptive writing ability? Descriptive writing is taken here to mean a students’ ability to identify key physical aspects of a mathematical model and to express—in words—a concise and well-balanced description that demonstrates a deep conceptual understanding of the model. This includes more than a description of the variables or the particular application to an engineering problem;it includes a demonstrated recognition of the basic physics that govern the model, certain limitations (idealizations) inherent in the model, and an understanding of how to make practical experimental measurements to verify the governing physics in the model. A student at this level may demonstrate proficiency in their analytical reasoning skills and hence be capable of correctly solving a given problem. However, this does not guarantee that the same student is skilled in associating equations with their physical meaning on a deep conceptual level or in understanding physical limitations of the equation. Consequently, such a student may demonstrate difficulty in mapping their comprehension of the model into written language that demonstrates a sound conceptual understanding of the governing physics. The findings represent a sample of two independent class sections of Electrical and Computer Engineering junior’s first course in Microe-lectronic Devices and Circuits during fall semesters 2012 and 2013 at a private mid-size university in NW Oregon. A total of three exams were administered to each of the 2012/2013 groups. Correlations between exam scores that students achieved on their descriptive writing of microelectronics phenomena and their analytical problem-solving abilities were examined and found to be quite significant.展开更多
The project analyzes the student＇s participation in complementary activities such as Education Tutorial Program, Junior Company and Academic Center. These organizations have the goal to improve, expand and connect kn...The project analyzes the student＇s participation in complementary activities such as Education Tutorial Program, Junior Company and Academic Center. These organizations have the goal to improve, expand and connect knowledge learned during classes with several practical activities. They can provide a huge integration between the students and the professors in order to achieve better results in the pedagogical, structural and organizational parts of an engineering major degree. Therefore, the project goes through the impact of each entity in the student＇s life and the advantages to professional future, focusing the presence of these organizations in the Electrical Engineering Course of Federal University of Rio Grande do Norte.展开更多
Microelectromechanical systems(MEMS)technology has gained significant attention over the past decade for measuring inertial angular velocity.However,due to inherent complexity,MEMS gyroscopes typically feature up to t...Microelectromechanical systems(MEMS)technology has gained significant attention over the past decade for measuring inertial angular velocity.However,due to inherent complexity,MEMS gyroscopes typically feature up to ten times more parameters than traditional sensors,making selection a challenging task even for experts.This study addresses this challenge,focusing on defensive guidance,navigation,and control(GNC)systems where precise and reliable angular velocity measurement is critical to overall performance.A comprehensive mathematical model is introduced to encapsulate all key MEMS parameters,accompanied by discussions on calibration and Allan variance interpretation.For six leading MEMS gyroscope applications,namely inertial navigation,integrated navigation,autopilot systems,rotating projectiles,homing guidance,and north finding,the most critical parameters are identified,distinguishing suitable and unsuitable sensor choices.Special emphasis is placed on inertial navigation systems,where practical rules of thumb for error evaluation are derived using six degrees of freedom motion equations.Rigorous simulations demonstrate the influence of various sensor parameters through real-world case studies,including static navigation,multi-rotor attitude estimation,gimbal stabilization,and north finding via a turntable.This work aims to be a beacon for practitioners across diverse fields,empowering them to make more informed design decisions.展开更多
In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and ta...In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and targeted marketing.However,existing computer vision solutions often rely on facial recognition to gather such insights,raising significant privacy and ethical concerns.To address these issues,this paper presents a privacypreserving customer analytics system through two key strategies.First,we deploy a deep learning framework using YOLOv9s,trained on the RCA-TVGender dataset.Cameras are positioned perpendicular to observation areas to reduce facial visibility while maintaining accurate gender classification.Second,we apply AES-128 encryption to customer position data,ensuring secure access and regulatory compliance.Our system achieved overall performance,with 81.5%mAP@50,77.7%precision,and 75.7%recall.Moreover,a 90-min observational study confirmed the system’s ability to generate privacy-protected heatmaps revealing distinct behavioral patterns between male and female customers.For instance,women spent more time in certain areas and showed interest in different products.These results confirm the system’s effectiveness in enabling personalized layout and marketing strategies without compromising privacy.展开更多
We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers...We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers based on the Lambert W function:a voltage-driven V-Lambert solver for high-fidelity I–V computation and a resistance-driven R-Lambert solver designed for seamless integration in a closed-loop PV emulator.Unlike Taylor-linearized explicit models,our proposed formulation retains the exponential nonlinearity of the PV equations.It employs a numerically stable analytical evaluation that eliminates the need for lookup tables and root-finding,all while maintaining limited computational costs and a small memory footprint.The R-Lambert model is integrated into a buck-converter emulator equipped with a discrete PI regulator,which generates current references directly from sensed operating points,thus supporting hardware-constrained implementation.Comprehensive numerical experiments conducted on six commercial modules from various technologies(mono,poly,and multicrystalline)demonstrate significant accuracy improvements under the IEC EN 50530 near-MPP criterion:the V-Lambert solver reduces the±10%Vmpp band error by up to 61 times compared to an explicit-model baseline.Dynamic simulations under varying irradiance,temperature,and load conditions achieve millisecond-scale settling with accurate trajectory tracking.Additionally,processor-in-the-loop experimental validation on an embedded microcontroller supports the simulation results.By unifying exact analytical modeling with embedded realization,this work advances computer modeling for PV emulation,MPPT benchmarking,and controller verification in integrated renewable energy systems.展开更多
As renewable energy penetration continues to rise,enhancing power system flexibility has become a critical requirement.Photovoltaic–storage–charging stations(PSCSs)are key components for enhancing local regulation c...As renewable energy penetration continues to rise,enhancing power system flexibility has become a critical requirement.Photovoltaic–storage–charging stations(PSCSs)are key components for enhancing local regulation capability and promoting renewable integration.However,evaluating the adjustable capability of such hybrid stations while considering security constraints remains a major challenge.This paper first analyzes the adjustable capabilities of all the resources within such a station based on the power-energy boundary(PEB)model.Then,an optimal formulation is proposed to obtain the adjusted parameters of the aggregate feasible region(AFR)model,which embeds low-dimensional linear models within high-dimensional linear models to improve the accuracy.To solve this formulation,it is transformed using duality theory and an alternating optimization algorithm is designed to obtain the solution.Finally,a multi-station adjustable capability aggregation method considering security constraints is introduced.Simulation results verify that the proposed method effectively reduces infeasible regions and improves smoothness of aggregated boundaries,providing an accurate and practical tool for flexibility evaluation in PSCSs and offering guidance for aggregators and system planners.展开更多
In real industrial microgrids(MGs),the length of the primary delivery feeder to the connection point of the main substation is sometimes long.This reduces the power factor and increases reactive power absorption along...In real industrial microgrids(MGs),the length of the primary delivery feeder to the connection point of the main substation is sometimes long.This reduces the power factor and increases reactive power absorption along the primary delivery feeder from the external network.Besides,the giant induction electro-motors as the working horse of industries requires remarkable amounts of reactive power for electro-mechanical energy conversions.To reduce power losses and operating costs of the MG as well as to improve the voltage quality,this study aims at providing an insightful model for optimal placement and sizing of reactive power compensation capacitors in an industrial MG.In the presented model,the objective function considers voltage profile and network power factor improvement at the MG connection point.Also,it realizes power flow equations within which all operational security constraints are considered.Various reactive power compensation strategies including distributed group compensation,centralized compensation at the main substation,and distributed compensation along the primary delivery feeder are scrutinized.A real industrial MG,say as Urmia Petrochemical plant,is considered in numerical validations.The obtained results in each scenario are discussed in depth.As seen,the best performance is obtained when the optimal location and sizing of capacitors are simultaneously determined at the main buses of the industrial plants,at the main substation of the MG,and alongside the primary delivery feeder.In this way,74.81%improvement in power losses reduction,1.3%lower active power import from the main grid,23.5%improvement in power factor,and 37.5%improvement in network voltage deviation summation are seen in this case compared to the base case.展开更多
Driven by the global energy transition and carbon neutrality targets,alkaline water electrolysis has emerged as a key technology for coupling variable renewable generation with clean hydrogen production,offering consi...Driven by the global energy transition and carbon neutrality targets,alkaline water electrolysis has emerged as a key technology for coupling variable renewable generation with clean hydrogen production,offering considerable potential for absorbing surplus power and enhancing grid flexibility.However,conventional control architectures typically treat the power converter and electrolyzer as independent units,neglecting their dynamic interactions and thereby limiting overall system performance under practical operating conditions.This review critically examines existing control approaches,ranging from classical proportional-integral schemes to model predictive control,fuzzy-logic algorithms,and data-driven methods,evaluating their effectiveness in managing dynamic response,multivariable coupling,and operational constraints as well as their inherent limitations.Attention is then focused on the performance requirements of the hydrogen-production converter,including current ripple suppression,rapid transient response,adaptive thermal regulation,and stable power delivery.An integrated co‑control framework is proposed,aligning converter output with electrolyzer demand across steady-state operation,variable renewable input,and emergency shutdown scenarios to achieve higher efficiency,extended equipment lifetime,and enhanced operational safety.Finally,prospects for advancing unified control methodologies are outlined,with emphasis on constraint-aware predictive control,machine-learning-enhanced modeling,and real‑time co‑optimization for future alkaline electrolyzer systems.展开更多
This study explores the thin-layer convective solar drying of Marrubium vulgare L.leaves under conditions typical of sun-rich semi-arid climates.Drying experiments were conducted at three inlet-air temperatures(40℃,5...This study explores the thin-layer convective solar drying of Marrubium vulgare L.leaves under conditions typical of sun-rich semi-arid climates.Drying experiments were conducted at three inlet-air temperatures(40℃,50℃,60℃)and two air velocities(1.5 and 2.5 m·s^(-1))using an indirect solar dryer with auxiliary temperature control.Moisture-ratio data were fitted with eight widely used thin-layer models and evaluated using correlation coefficient(r),root-mean-square error(RMSE),and Akaike information criterion(AIC).A complementary heattransfer analysis based on Reynolds and Prandtl numbers with appropriate Nusselt correlations was used to relate flow regime to drying performance,and an energy balance quantified the relative contributions of solar and auxiliary heat.The logarithmic model consistently achieved the lowest RMSE/AIC with r>0.99 across all conditions.Higher temperature and air velocity significantly reduced drying time during the decreasing-rate period,with no constantrate stage observed.On average,solar input supplied the large majority of the thermal demand,while the auxiliary heater compensated short irradiance drops to maintain setpoints.These findings provide a reproducible dataset and a modelling benchmark for M.vulgare leaves,and they support energy-aware design of hybrid solar dryers formedicinal plants in sun-rich regions.展开更多
This work presents a systematic analysis of proton-induced total ionizing dose(TID)effects in 1.2 k V silicon carbide(SiC)power devices with various edge termination structures.Three edge terminations including ring-a...This work presents a systematic analysis of proton-induced total ionizing dose(TID)effects in 1.2 k V silicon carbide(SiC)power devices with various edge termination structures.Three edge terminations including ring-assisted junction termination extension(RA-JTE),multiple floating zone JTE(MFZ-JTE),and field limiting rings(FLR)were fabricated and irradiated with45 Me V protons at fluences ranging from 1×10^(12) to 1×10^(14) cm^(-2).Experimental results,supported by TCAD simulations,show that the RA-JTE structure maintained stable breakdown performance with less than 1%variation due to its effective electric field redistribution by multiple P+rings.In contrast,MFZ-JTE and FLR exhibit breakdown voltage shifts of 6.1%and 15.2%,respectively,under the highest fluence.These results demonstrate the superior radiation tolerance of the RA-JTE structure under TID conditions and provide practical design guidance for radiation-hardened Si C power devices in space and other highradiation environments.展开更多
Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstruc...Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstructions,and substantial computational demands,especially in complex forest terrains.To address these challenges,this study proposes a novel forest fire detection model utilizing audio classification and machine learning.We developed an audio-based pipeline using real-world environmental sound recordings.Sounds were converted into Mel-spectrograms and classified via a Convolutional Neural Network(CNN),enabling the capture of distinctive fire acoustic signatures(e.g.,crackling,roaring)that are minimally impacted by visual or weather conditions.Internet of Things(IoT)sound sensors were crucial for generating complex environmental parameters to optimize feature extraction.The CNN model achieved high performance in stratified 5-fold cross-validation(92.4%±1.6 accuracy,91.2%±1.8 F1-score)and on test data(94.93%accuracy,93.04%F1-score),with 98.44%precision and 88.32%recall,demonstrating reliability across environmental conditions.These results indicate that the audio-based approach not only improves detection reliability but also markedly reduces computational overhead compared to traditional image-based methods.The findings suggest that acoustic sensing integrated with machine learning offers a powerful,low-cost,and efficient solution for real-time forest fire monitoring in complex,dynamic environments.展开更多
Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these netw...Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these networks continue to grow in scale and complexity,the need for energy-efficient,scalable,and robust communication protocols becomes more critical than ever.Metaheuristic algorithms have shown significant promise in addressing these challenges,offering flexible and effective solutions for optimizing WSN performance.Among them,the Grey Wolf Optimizer(GWO)algorithm has attracted growing attention due to its simplicity,fast convergence,and strong global search capabilities.Accordingly,this survey provides an in-depth review of the applications of GWO and its variants for clustering,multi-hop routing,and hybrid cluster-based routing in WSNs.We categorize and analyze the existing GWO-based approaches across these key network optimization tasks,discussing the different problem formulations,decision variables,objective functions,and performance metrics used.In doing so,we examine standard GWO,multi-objective GWO,and hybrid GWO models that incorporate other computational intelligence techniques.Each method is evaluated based on how effectively it addresses the core constraints of WSNs,including energy consumption,communication overhead,and network lifetime.Finally,this survey outlines existing gaps in the literature and proposes potential future research directions aimed at enhancing the effectiveness and real-world applicability of GWO-based techniques for WSN clustering and routing.Our goal is to provide researchers and practitioners with a clear,structured understanding of the current state of GWO in WSNs and inspire further innovation in this evolving field.展开更多
The growing global energy demand and worsening climate change highlight the urgent need for clean,efficient and sustainable energy solutions.Among emerging technologies,atomically thin two-dimensional(2D)materials off...The growing global energy demand and worsening climate change highlight the urgent need for clean,efficient and sustainable energy solutions.Among emerging technologies,atomically thin two-dimensional(2D)materials offer unique advantages in photovoltaics due to their tunable optoelectronic properties,high surface area and efficient charge transport capabilities.This review explores recent progress in photovoltaics incorporating 2D materials,focusing on their application as hole and electron transport layers to optimize bandgap alignment,enhance carrier mobility and improve chemical stability.A comprehensive analysis is presented on perovskite solar cells utilizing 2D materials,with a particular focus on strategies to enhance crystallization,passivate defects and improve overall cell efficiency.Additionally,the application of 2D materials in organic solar cells is examined,particularly for reducing recombination losses and enhancing charge extraction through work function modification.Their impact on dye-sensitized solar cells,including catalytic activity and counter electrode performance,is also explored.Finally,the review outlines key challenges,material limitations and performance metrics,offering insight into the future development of nextgeneration photovoltaic devices encouraged by 2D materials.展开更多
The effect of sintering temperature on microstructure, electrical properties, and pulse aging behavior of （V2O5-Mn3O4-Er2O3）-doped zinc oxide varistor ceramics was systematically studied. When the sintering temperat...The effect of sintering temperature on microstructure, electrical properties, and pulse aging behavior of （V2O5-Mn3O4-Er2O3）-doped zinc oxide varistor ceramics was systematically studied. When the sintering temperature increased, the average grain size increased from 6.1 to 8.7μm and the sintered density decreased from 5.52 to 5.43 g/cm3. The breakdown field decreased from 3856 to 922 V/cm with an increase in the sintering temperature up to 900 °C, whereas a further increase to 2352 V/cm at 925 °C. The nonlinear coefficient increased pronouncedly from 4.6 to 30.0 with an increase in the sintering temperature. The varistor ceramics sintered at 850 °C exhibited the best clamping characteristics, with the clamp voltage ratio of the range of 2.22-2.88 for pulse current of 1-25 A. The varistor ceramics sintered at 925 °C exhibited the strongest stability, with %ΔE1 mA/cm2=-8.8% after applying the multi-pulse current of 25 A.展开更多
Due to its capability of solving decision-making problems involving multiple entities and objectives, as well as complex action sequences, game theory has been a basic mathematical tool of economists, politicians, and...Due to its capability of solving decision-making problems involving multiple entities and objectives, as well as complex action sequences, game theory has been a basic mathematical tool of economists, politicians, and sociologists for decades. It helps them understand how strategic interactions impact rational decisions of individual players in competitive and uncertain environment, if each player aims to get the best payoff. This situation is ubiquitous in engineering practices. This paper streamlines the foundations of engineering game theory, which uses concepts, theories and methodologies to guide the resolution of engineering design, operation, and control problems in a more canonical and systematic way. An overview of its application in smart grid technologies and power systems related topics is presented, and intriguing research directions are also envisioned.展开更多
The characteristic evaluation of aluminum oxide （A1203）/carbon nanotubes （CNTs） hybrid composites for micro-electrical discharge machining （EDM） was described. Alumina matrix composites reinforced with CNTs were...The characteristic evaluation of aluminum oxide （A1203）/carbon nanotubes （CNTs） hybrid composites for micro-electrical discharge machining （EDM） was described. Alumina matrix composites reinforced with CNTs were fabricated by a catalytic chemical vapor deposition method. A1203 composites with different CNT concentrations were synthesized. The electrical characteristic of A1203/CNTs composites was examined. These composites were machined by the EDM process according to the various EDM parameters, and the characteristics of machining were analyzed using field emission scanning electron microscope （FESEM）. The electrical conductivity has a increasing tendency as the CNTs content is increased and has a critical point at 5% A1203 （volume fraction）. In the machining accuracy, many tangles of CNT in A1203/CNTs composites cause violent spark. Thus, it causes the poor dimensional accuracy and circularity. The results show that conductivity of the materials and homogeneous distribution of CNTs in the matrix are important factors for micro-EDM of A1203/CNTs hybrid composites.展开更多
Large engineering plants(LEPs)have certain unique features that necessitate a maintenance strategy that is a combination of both time and condition based maintenance.Although this requirement is appreciated to varying...Large engineering plants(LEPs)have certain unique features that necessitate a maintenance strategy that is a combination of both time and condition based maintenance.Although this requirement is appreciated to varying degrees by asset owners,applied research leading to a systematic development of such a maintenance strategy is the need of the day.Such a strategy should also adopt a wholesome"systemic"approach so that the realization of the overall objectives of maintenance is maximized.E-maintenance has several potential benefits for large engineering plants.In this paper,a three pronged strategy is suggested for the successful implementation of e-maintenance for LEPs.Firstly,an integrated condition and time based maintenance framework is proposed for LEPs.Secondly,reference is drawn to models for condition and time based maintenance at systemic levels.As a part of the ab initio development of a condition monitoring system for a LEP,one of the characteristics of the condition monitoring system,namely,predictability,is discussed in detail as a sample for a systemic study.Thirdly,emphasis is laid on the information and expertise available in the domain of plant design,operation and maintenance and the same is tapped for incorporation in maintenance decision making.展开更多
Wind power,solar power,and electrical load forecasting are essential works to ensure the safe and stable operation of the electric power system.With the increasing permeability of new energy and the rising demand resp...Wind power,solar power,and electrical load forecasting are essential works to ensure the safe and stable operation of the electric power system.With the increasing permeability of new energy and the rising demand response load,the uncertainty on the production and load sides are both increased,bringing new challenges to the forecasting work and putting forward higher requirements to the forecasting accuracy.Most review/survey papers focus on one specific forecasting object(wind,solar,or load),a few involve the above two or three objects,but the forecasting objects are surveyed separately.Some papers predict at least two kinds of objects simultaneously to cope with the increasing uncertainty at both production and load sides.However,there is no corresponding review at present.Hence,our study provides a comprehensive review of wind,solar,and electrical load forecasting methods.Furthermore,the survey of Numerical Weather Prediction wind speed/irradiance correction methods is also included in this manuscript.Challenges and future research directions are discussed at last.展开更多
Electrical explosion of a wire(EEW)has been investigated for more than ten years at Tsinghua University,and the main results are reviewed in this paper.Based onEEWin vacuum,an X-pinch was used as an x-ray source for p...Electrical explosion of a wire(EEW)has been investigated for more than ten years at Tsinghua University,and the main results are reviewed in this paper.Based onEEWin vacuum,an X-pinch was used as an x-ray source for phase-contrast imaging of small insects such as mosquitoes and ants in which it was possible to observe clearly their detailed internal structures,which can never be seen with conventional x-ray radiography.Electrical explosion of a wire array(EEWA)in vacuum is the initial stage in the formation of a wire-array Z-pinch.The evolution ofEEWAwas observed with x-ray backlighting using two X-pinches as x-ray sources.It was found that each wire in an EEWA exhibits a core–corona structure instead of forming a fully vaporized metallic vapor.This structure is detrimental to the plasma implosion of a Z-pinch.By inserting an insulator as a flashover switch into the cathode,formation of a core–corona structure was suppressed and core-freeEEWAwas realized.EEWin gases was used for nanopowder production.Three parameters(vaporization rate,gas pressure,and energy deposited in the exploding plasma)were found to influence the nanoparticle size.EEWin water was used for shock-wave generation.The shock wave generated by melting could be recorded with a piezoelectric gauge only in underheat EEW.ForEEW with a given stored energy but different energy-storage capacitor banks,the small capacitor bank produced a rapidly rising current that deposited more energy into the wire and generated a stronger shock wave.展开更多
Multi-function,multiband,cost-effective,miniaturized reconfigurable radio frequency(RF)components are highly demanded in modern and future wireless communication systems.This paper discusses the needs and implementati...Multi-function,multiband,cost-effective,miniaturized reconfigurable radio frequency(RF)components are highly demanded in modern and future wireless communication systems.This paper discusses the needs and implementation of multiband reconfigurable RF components with microfabrication techniques and advanced materials.RF applications of fabrication methods such as surface and bulk micromachining techniques are reviewed,especially on the development of RF microelectromechanical systems(MEMS)and other tunable components.Works on the application of ferroelectric and ferromagnetic materials are investigated,which enables RF components with continuous tunability,reduced size,and enhanced performance.Methods and strategies with nano-patterning to improve high frequency characteristics of ferromagnetic thin film(e.g.,ferromagnetic resonance frequency and losses)and their applications on the development of fully electrically tunable RF components are fully demonstrated.展开更多
文摘The human brain is asymmetrical in function, with each of its two hemispheres being somewhat responsible for distinct cognitive and motor tasks, to include writing. It stands to reason that engineering students who have established entrance into their upper-division programs will have demonstrated cognitive proficiency in math and logical operations, abstract and analytical reasoning and language usage, to include writing. In this study the question was asked: is there a correlation between an upper-division electrical engineering students’ analytical reasoning ability and their descriptive writing ability? Descriptive writing is taken here to mean a students’ ability to identify key physical aspects of a mathematical model and to express—in words—a concise and well-balanced description that demonstrates a deep conceptual understanding of the model. This includes more than a description of the variables or the particular application to an engineering problem;it includes a demonstrated recognition of the basic physics that govern the model, certain limitations (idealizations) inherent in the model, and an understanding of how to make practical experimental measurements to verify the governing physics in the model. A student at this level may demonstrate proficiency in their analytical reasoning skills and hence be capable of correctly solving a given problem. However, this does not guarantee that the same student is skilled in associating equations with their physical meaning on a deep conceptual level or in understanding physical limitations of the equation. Consequently, such a student may demonstrate difficulty in mapping their comprehension of the model into written language that demonstrates a sound conceptual understanding of the governing physics. The findings represent a sample of two independent class sections of Electrical and Computer Engineering junior’s first course in Microe-lectronic Devices and Circuits during fall semesters 2012 and 2013 at a private mid-size university in NW Oregon. A total of three exams were administered to each of the 2012/2013 groups. Correlations between exam scores that students achieved on their descriptive writing of microelectronics phenomena and their analytical problem-solving abilities were examined and found to be quite significant.
文摘The project analyzes the student＇s participation in complementary activities such as Education Tutorial Program, Junior Company and Academic Center. These organizations have the goal to improve, expand and connect knowledge learned during classes with several practical activities. They can provide a huge integration between the students and the professors in order to achieve better results in the pedagogical, structural and organizational parts of an engineering major degree. Therefore, the project goes through the impact of each entity in the student＇s life and the advantages to professional future, focusing the presence of these organizations in the Electrical Engineering Course of Federal University of Rio Grande do Norte.
文摘Microelectromechanical systems(MEMS)technology has gained significant attention over the past decade for measuring inertial angular velocity.However,due to inherent complexity,MEMS gyroscopes typically feature up to ten times more parameters than traditional sensors,making selection a challenging task even for experts.This study addresses this challenge,focusing on defensive guidance,navigation,and control(GNC)systems where precise and reliable angular velocity measurement is critical to overall performance.A comprehensive mathematical model is introduced to encapsulate all key MEMS parameters,accompanied by discussions on calibration and Allan variance interpretation.For six leading MEMS gyroscope applications,namely inertial navigation,integrated navigation,autopilot systems,rotating projectiles,homing guidance,and north finding,the most critical parameters are identified,distinguishing suitable and unsuitable sensor choices.Special emphasis is placed on inertial navigation systems,where practical rules of thumb for error evaluation are derived using six degrees of freedom motion equations.Rigorous simulations demonstrate the influence of various sensor parameters through real-world case studies,including static navigation,multi-rotor attitude estimation,gimbal stabilization,and north finding via a turntable.This work aims to be a beacon for practitioners across diverse fields,empowering them to make more informed design decisions.
文摘In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and targeted marketing.However,existing computer vision solutions often rely on facial recognition to gather such insights,raising significant privacy and ethical concerns.To address these issues,this paper presents a privacypreserving customer analytics system through two key strategies.First,we deploy a deep learning framework using YOLOv9s,trained on the RCA-TVGender dataset.Cameras are positioned perpendicular to observation areas to reduce facial visibility while maintaining accurate gender classification.Second,we apply AES-128 encryption to customer position data,ensuring secure access and regulatory compliance.Our system achieved overall performance,with 81.5%mAP@50,77.7%precision,and 75.7%recall.Moreover,a 90-min observational study confirmed the system’s ability to generate privacy-protected heatmaps revealing distinct behavioral patterns between male and female customers.For instance,women spent more time in certain areas and showed interest in different products.These results confirm the system’s effectiveness in enabling personalized layout and marketing strategies without compromising privacy.
基金funded by Scientific Research Deanship at University of Ha’il-Saudi Arabia through project number(RG-24014).
文摘We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers based on the Lambert W function:a voltage-driven V-Lambert solver for high-fidelity I–V computation and a resistance-driven R-Lambert solver designed for seamless integration in a closed-loop PV emulator.Unlike Taylor-linearized explicit models,our proposed formulation retains the exponential nonlinearity of the PV equations.It employs a numerically stable analytical evaluation that eliminates the need for lookup tables and root-finding,all while maintaining limited computational costs and a small memory footprint.The R-Lambert model is integrated into a buck-converter emulator equipped with a discrete PI regulator,which generates current references directly from sensed operating points,thus supporting hardware-constrained implementation.Comprehensive numerical experiments conducted on six commercial modules from various technologies(mono,poly,and multicrystalline)demonstrate significant accuracy improvements under the IEC EN 50530 near-MPP criterion:the V-Lambert solver reduces the±10%Vmpp band error by up to 61 times compared to an explicit-model baseline.Dynamic simulations under varying irradiance,temperature,and load conditions achieve millisecond-scale settling with accurate trajectory tracking.Additionally,processor-in-the-loop experimental validation on an embedded microcontroller supports the simulation results.By unifying exact analytical modeling with embedded realization,this work advances computer modeling for PV emulation,MPPT benchmarking,and controller verification in integrated renewable energy systems.
基金supported by Science and Technology Project of China Southern Power Grid Company(036000KK52222007(GDKJXM20222121)).
文摘As renewable energy penetration continues to rise,enhancing power system flexibility has become a critical requirement.Photovoltaic–storage–charging stations(PSCSs)are key components for enhancing local regulation capability and promoting renewable integration.However,evaluating the adjustable capability of such hybrid stations while considering security constraints remains a major challenge.This paper first analyzes the adjustable capabilities of all the resources within such a station based on the power-energy boundary(PEB)model.Then,an optimal formulation is proposed to obtain the adjusted parameters of the aggregate feasible region(AFR)model,which embeds low-dimensional linear models within high-dimensional linear models to improve the accuracy.To solve this formulation,it is transformed using duality theory and an alternating optimization algorithm is designed to obtain the solution.Finally,a multi-station adjustable capability aggregation method considering security constraints is introduced.Simulation results verify that the proposed method effectively reduces infeasible regions and improves smoothness of aggregated boundaries,providing an accurate and practical tool for flexibility evaluation in PSCSs and offering guidance for aggregators and system planners.
文摘In real industrial microgrids(MGs),the length of the primary delivery feeder to the connection point of the main substation is sometimes long.This reduces the power factor and increases reactive power absorption along the primary delivery feeder from the external network.Besides,the giant induction electro-motors as the working horse of industries requires remarkable amounts of reactive power for electro-mechanical energy conversions.To reduce power losses and operating costs of the MG as well as to improve the voltage quality,this study aims at providing an insightful model for optimal placement and sizing of reactive power compensation capacitors in an industrial MG.In the presented model,the objective function considers voltage profile and network power factor improvement at the MG connection point.Also,it realizes power flow equations within which all operational security constraints are considered.Various reactive power compensation strategies including distributed group compensation,centralized compensation at the main substation,and distributed compensation along the primary delivery feeder are scrutinized.A real industrial MG,say as Urmia Petrochemical plant,is considered in numerical validations.The obtained results in each scenario are discussed in depth.As seen,the best performance is obtained when the optimal location and sizing of capacitors are simultaneously determined at the main buses of the industrial plants,at the main substation of the MG,and alongside the primary delivery feeder.In this way,74.81%improvement in power losses reduction,1.3%lower active power import from the main grid,23.5%improvement in power factor,and 37.5%improvement in network voltage deviation summation are seen in this case compared to the base case.
基金supported by Natural Science Foundation of Shanghai,under the Shanghai Action Plan for Science,Technology and Innovation(22ZR1464800).
文摘Driven by the global energy transition and carbon neutrality targets,alkaline water electrolysis has emerged as a key technology for coupling variable renewable generation with clean hydrogen production,offering considerable potential for absorbing surplus power and enhancing grid flexibility.However,conventional control architectures typically treat the power converter and electrolyzer as independent units,neglecting their dynamic interactions and thereby limiting overall system performance under practical operating conditions.This review critically examines existing control approaches,ranging from classical proportional-integral schemes to model predictive control,fuzzy-logic algorithms,and data-driven methods,evaluating their effectiveness in managing dynamic response,multivariable coupling,and operational constraints as well as their inherent limitations.Attention is then focused on the performance requirements of the hydrogen-production converter,including current ripple suppression,rapid transient response,adaptive thermal regulation,and stable power delivery.An integrated co‑control framework is proposed,aligning converter output with electrolyzer demand across steady-state operation,variable renewable input,and emergency shutdown scenarios to achieve higher efficiency,extended equipment lifetime,and enhanced operational safety.Finally,prospects for advancing unified control methodologies are outlined,with emphasis on constraint-aware predictive control,machine-learning-enhanced modeling,and real‑time co‑optimization for future alkaline electrolyzer systems.
文摘This study explores the thin-layer convective solar drying of Marrubium vulgare L.leaves under conditions typical of sun-rich semi-arid climates.Drying experiments were conducted at three inlet-air temperatures(40℃,50℃,60℃)and two air velocities(1.5 and 2.5 m·s^(-1))using an indirect solar dryer with auxiliary temperature control.Moisture-ratio data were fitted with eight widely used thin-layer models and evaluated using correlation coefficient(r),root-mean-square error(RMSE),and Akaike information criterion(AIC).A complementary heattransfer analysis based on Reynolds and Prandtl numbers with appropriate Nusselt correlations was used to relate flow regime to drying performance,and an energy balance quantified the relative contributions of solar and auxiliary heat.The logarithmic model consistently achieved the lowest RMSE/AIC with r>0.99 across all conditions.Higher temperature and air velocity significantly reduced drying time during the decreasing-rate period,with no constantrate stage observed.On average,solar input supplied the large majority of the thermal demand,while the auxiliary heater compensated short irradiance drops to maintain setpoints.These findings provide a reproducible dataset and a modelling benchmark for M.vulgare leaves,and they support energy-aware design of hybrid solar dryers formedicinal plants in sun-rich regions.
基金supported by the IITP(Institute for Information&Communications Technology Planning&Evaluation)under the ITRC(Information Technology Research Center)support program(IITP-2025-RS-2024-00438288)grant funded by the Korea government(MSIT)+1 种基金National Research Council of Science&Technology(NST)grant by the MSIT(Aerospace Semiconductor Strategy Research Project No.GTL25051-000)supported by the IC Design Education Center(IDEC),Korea。
文摘This work presents a systematic analysis of proton-induced total ionizing dose(TID)effects in 1.2 k V silicon carbide(SiC)power devices with various edge termination structures.Three edge terminations including ring-assisted junction termination extension(RA-JTE),multiple floating zone JTE(MFZ-JTE),and field limiting rings(FLR)were fabricated and irradiated with45 Me V protons at fluences ranging from 1×10^(12) to 1×10^(14) cm^(-2).Experimental results,supported by TCAD simulations,show that the RA-JTE structure maintained stable breakdown performance with less than 1%variation due to its effective electric field redistribution by multiple P+rings.In contrast,MFZ-JTE and FLR exhibit breakdown voltage shifts of 6.1%and 15.2%,respectively,under the highest fluence.These results demonstrate the superior radiation tolerance of the RA-JTE structure under TID conditions and provide practical design guidance for radiation-hardened Si C power devices in space and other highradiation environments.
基金funded by the Directorate of Research and Community Service,Directorate General of Research and Development,Ministry of Higher Education,Science and Technologyin accordance with the Implementation Contract for the Operational Assistance Program for State Universities,Research Program Number:109/C3/DT.05.00/PL/2025.
文摘Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstructions,and substantial computational demands,especially in complex forest terrains.To address these challenges,this study proposes a novel forest fire detection model utilizing audio classification and machine learning.We developed an audio-based pipeline using real-world environmental sound recordings.Sounds were converted into Mel-spectrograms and classified via a Convolutional Neural Network(CNN),enabling the capture of distinctive fire acoustic signatures(e.g.,crackling,roaring)that are minimally impacted by visual or weather conditions.Internet of Things(IoT)sound sensors were crucial for generating complex environmental parameters to optimize feature extraction.The CNN model achieved high performance in stratified 5-fold cross-validation(92.4%±1.6 accuracy,91.2%±1.8 F1-score)and on test data(94.93%accuracy,93.04%F1-score),with 98.44%precision and 88.32%recall,demonstrating reliability across environmental conditions.These results indicate that the audio-based approach not only improves detection reliability but also markedly reduces computational overhead compared to traditional image-based methods.The findings suggest that acoustic sensing integrated with machine learning offers a powerful,low-cost,and efficient solution for real-time forest fire monitoring in complex,dynamic environments.
文摘Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these networks continue to grow in scale and complexity,the need for energy-efficient,scalable,and robust communication protocols becomes more critical than ever.Metaheuristic algorithms have shown significant promise in addressing these challenges,offering flexible and effective solutions for optimizing WSN performance.Among them,the Grey Wolf Optimizer(GWO)algorithm has attracted growing attention due to its simplicity,fast convergence,and strong global search capabilities.Accordingly,this survey provides an in-depth review of the applications of GWO and its variants for clustering,multi-hop routing,and hybrid cluster-based routing in WSNs.We categorize and analyze the existing GWO-based approaches across these key network optimization tasks,discussing the different problem formulations,decision variables,objective functions,and performance metrics used.In doing so,we examine standard GWO,multi-objective GWO,and hybrid GWO models that incorporate other computational intelligence techniques.Each method is evaluated based on how effectively it addresses the core constraints of WSNs,including energy consumption,communication overhead,and network lifetime.Finally,this survey outlines existing gaps in the literature and proposes potential future research directions aimed at enhancing the effectiveness and real-world applicability of GWO-based techniques for WSN clustering and routing.Our goal is to provide researchers and practitioners with a clear,structured understanding of the current state of GWO in WSNs and inspire further innovation in this evolving field.
基金supported by the IITP(Institute of Information & Communications Technology Planning & Evaluation)-ITRC(Information Technology Research Center) grant funded by the Korea government(Ministry of Science and ICT) (IITP-2025-RS-2024-00437191, and RS-2025-02303505)partly supported by the Korea Basic Science Institute (National Research Facilities and Equipment Center) grant funded by the Ministry of Education. (No. 2022R1A6C101A774)the Deanship of Research and Graduate Studies at King Khalid University, Saudi Arabia, through Large Research Project under grant number RGP-2/527/46
文摘The growing global energy demand and worsening climate change highlight the urgent need for clean,efficient and sustainable energy solutions.Among emerging technologies,atomically thin two-dimensional(2D)materials offer unique advantages in photovoltaics due to their tunable optoelectronic properties,high surface area and efficient charge transport capabilities.This review explores recent progress in photovoltaics incorporating 2D materials,focusing on their application as hole and electron transport layers to optimize bandgap alignment,enhance carrier mobility and improve chemical stability.A comprehensive analysis is presented on perovskite solar cells utilizing 2D materials,with a particular focus on strategies to enhance crystallization,passivate defects and improve overall cell efficiency.Additionally,the application of 2D materials in organic solar cells is examined,particularly for reducing recombination losses and enhancing charge extraction through work function modification.Their impact on dye-sensitized solar cells,including catalytic activity and counter electrode performance,is also explored.Finally,the review outlines key challenges,material limitations and performance metrics,offering insight into the future development of nextgeneration photovoltaic devices encouraged by 2D materials.
文摘The effect of sintering temperature on microstructure, electrical properties, and pulse aging behavior of （V2O5-Mn3O4-Er2O3）-doped zinc oxide varistor ceramics was systematically studied. When the sintering temperature increased, the average grain size increased from 6.1 to 8.7μm and the sintered density decreased from 5.52 to 5.43 g/cm3. The breakdown field decreased from 3856 to 922 V/cm with an increase in the sintering temperature up to 900 °C, whereas a further increase to 2352 V/cm at 925 °C. The nonlinear coefficient increased pronouncedly from 4.6 to 30.0 with an increase in the sintering temperature. The varistor ceramics sintered at 850 °C exhibited the best clamping characteristics, with the clamp voltage ratio of the range of 2.22-2.88 for pulse current of 1-25 A. The varistor ceramics sintered at 925 °C exhibited the strongest stability, with %ΔE1 mA/cm2=-8.8% after applying the multi-pulse current of 25 A.
基金This work was supported by National Natural Science Foundation of China （No. 51621065）.
文摘Due to its capability of solving decision-making problems involving multiple entities and objectives, as well as complex action sequences, game theory has been a basic mathematical tool of economists, politicians, and sociologists for decades. It helps them understand how strategic interactions impact rational decisions of individual players in competitive and uncertain environment, if each player aims to get the best payoff. This situation is ubiquitous in engineering practices. This paper streamlines the foundations of engineering game theory, which uses concepts, theories and methodologies to guide the resolution of engineering design, operation, and control problems in a more canonical and systematic way. An overview of its application in smart grid technologies and power systems related topics is presented, and intriguing research directions are also envisioned.
基金Project(2010-0008-277) supported by Program of Establishment of an Infrastructure for Public Usepartly by NCRC (National Core Research Center) through the National Research Foundation of Korea funded by the Ministry of Education
文摘The characteristic evaluation of aluminum oxide （A1203）/carbon nanotubes （CNTs） hybrid composites for micro-electrical discharge machining （EDM） was described. Alumina matrix composites reinforced with CNTs were fabricated by a catalytic chemical vapor deposition method. A1203 composites with different CNT concentrations were synthesized. The electrical characteristic of A1203/CNTs composites was examined. These composites were machined by the EDM process according to the various EDM parameters, and the characteristics of machining were analyzed using field emission scanning electron microscope （FESEM）. The electrical conductivity has a increasing tendency as the CNTs content is increased and has a critical point at 5% A1203 （volume fraction）. In the machining accuracy, many tangles of CNT in A1203/CNTs composites cause violent spark. Thus, it causes the poor dimensional accuracy and circularity. The results show that conductivity of the materials and homogeneous distribution of CNTs in the matrix are important factors for micro-EDM of A1203/CNTs hybrid composites.
文摘Large engineering plants(LEPs)have certain unique features that necessitate a maintenance strategy that is a combination of both time and condition based maintenance.Although this requirement is appreciated to varying degrees by asset owners,applied research leading to a systematic development of such a maintenance strategy is the need of the day.Such a strategy should also adopt a wholesome"systemic"approach so that the realization of the overall objectives of maintenance is maximized.E-maintenance has several potential benefits for large engineering plants.In this paper,a three pronged strategy is suggested for the successful implementation of e-maintenance for LEPs.Firstly,an integrated condition and time based maintenance framework is proposed for LEPs.Secondly,reference is drawn to models for condition and time based maintenance at systemic levels.As a part of the ab initio development of a condition monitoring system for a LEP,one of the characteristics of the condition monitoring system,namely,predictability,is discussed in detail as a sample for a systemic study.Thirdly,emphasis is laid on the information and expertise available in the domain of plant design,operation and maintenance and the same is tapped for incorporation in maintenance decision making.
基金supported by China Three Gorges Corporation(Key technology research and demonstration application of large-scale source-net-load-storage integration under the vision of carbon neutrality)Fundamental Research Funds for the Central Universities(2020MS021).
文摘Wind power,solar power,and electrical load forecasting are essential works to ensure the safe and stable operation of the electric power system.With the increasing permeability of new energy and the rising demand response load,the uncertainty on the production and load sides are both increased,bringing new challenges to the forecasting work and putting forward higher requirements to the forecasting accuracy.Most review/survey papers focus on one specific forecasting object(wind,solar,or load),a few involve the above two or three objects,but the forecasting objects are surveyed separately.Some papers predict at least two kinds of objects simultaneously to cope with the increasing uncertainty at both production and load sides.However,there is no corresponding review at present.Hence,our study provides a comprehensive review of wind,solar,and electrical load forecasting methods.Furthermore,the survey of Numerical Weather Prediction wind speed/irradiance correction methods is also included in this manuscript.Challenges and future research directions are discussed at last.
文摘Electrical explosion of a wire(EEW)has been investigated for more than ten years at Tsinghua University,and the main results are reviewed in this paper.Based onEEWin vacuum,an X-pinch was used as an x-ray source for phase-contrast imaging of small insects such as mosquitoes and ants in which it was possible to observe clearly their detailed internal structures,which can never be seen with conventional x-ray radiography.Electrical explosion of a wire array(EEWA)in vacuum is the initial stage in the formation of a wire-array Z-pinch.The evolution ofEEWAwas observed with x-ray backlighting using two X-pinches as x-ray sources.It was found that each wire in an EEWA exhibits a core–corona structure instead of forming a fully vaporized metallic vapor.This structure is detrimental to the plasma implosion of a Z-pinch.By inserting an insulator as a flashover switch into the cathode,formation of a core–corona structure was suppressed and core-freeEEWAwas realized.EEWin gases was used for nanopowder production.Three parameters(vaporization rate,gas pressure,and energy deposited in the exploding plasma)were found to influence the nanoparticle size.EEWin water was used for shock-wave generation.The shock wave generated by melting could be recorded with a piezoelectric gauge only in underheat EEW.ForEEW with a given stored energy but different energy-storage capacitor banks,the small capacitor bank produced a rapidly rising current that deposited more energy into the wire and generated a stronger shock wave.
基金Projects(1253929,1910853)supported by the National Natural Science Foundation of China。
文摘Multi-function,multiband,cost-effective,miniaturized reconfigurable radio frequency(RF)components are highly demanded in modern and future wireless communication systems.This paper discusses the needs and implementation of multiband reconfigurable RF components with microfabrication techniques and advanced materials.RF applications of fabrication methods such as surface and bulk micromachining techniques are reviewed,especially on the development of RF microelectromechanical systems(MEMS)and other tunable components.Works on the application of ferroelectric and ferromagnetic materials are investigated,which enables RF components with continuous tunability,reduced size,and enhanced performance.Methods and strategies with nano-patterning to improve high frequency characteristics of ferromagnetic thin film(e.g.,ferromagnetic resonance frequency and losses)and their applications on the development of fully electrically tunable RF components are fully demonstrated.
