In this article,a novel metaheuristic technique named Far and Near Optimization(FNO)is introduced,offeringversatile applications across various scientific domains for optimization tasks.The core concept behind FNO lie...In this article,a novel metaheuristic technique named Far and Near Optimization(FNO)is introduced,offeringversatile applications across various scientific domains for optimization tasks.The core concept behind FNO lies inintegrating global and local search methodologies to update the algorithm population within the problem-solvingspace based on moving each member to the farthest and nearest member to itself.The paper delineates the theoryof FNO,presenting a mathematical model in two phases:(i)exploration based on the simulation of the movementof a population member towards the farthest member from itself and(ii)exploitation based on simulating themovement of a population member towards the nearest member from itself.FNO’s efficacy in tackling optimizationchallenges is assessed through its handling of the CEC 2017 test suite across problem dimensions of 10,30,50,and 100,as well as to address CEC 2020.The optimization results underscore FNO’s adeptness in exploration,exploitation,and maintaining a balance between them throughout the search process to yield viable solutions.Comparative analysis against twelve established metaheuristic algorithms reveals FNO’s superior performance.Simulation findings indicate FNO’s outperformance of competitor algorithms,securing the top rank as the mosteffective optimizer across a majority of benchmark functions.Moreover,the outcomes derived by employing FNOon twenty-two constrained optimization challenges from the CEC 2011 test suite,alongside four engineering designdilemmas,showcase the effectiveness of the suggested method in tackling real-world scenarios.展开更多
The usage of electric vehicles holds a crucial role in lowering the diminishing of the ozone layer because electric vehicles are not dependent on fossil fuels.With more research,evaluation,and its characteristics on e...The usage of electric vehicles holds a crucial role in lowering the diminishing of the ozone layer because electric vehicles are not dependent on fossil fuels.With more research,evaluation,and its characteristics on electric vehicles,the infrastructure of charging points,production of electric vehicles,and network modelling,this paper provides a comprehensive overview of electric vehicles,and hybrid vehicles,including an analysis of their market growth,as well as different types of optimization used in the current scenario.In developing countries like India,the biggest barrier is their unfulfilled facility over the charging.Without renewable energy sources,vehicle-to-grid technology facilitates the enhancement of additional power requirements.The mobility factor has been considered an important and special characteristic of electric vehicles.展开更多
This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspi...This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards.The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases:(i)an exploration phase,which mimics the lizard’s sudden attack on its prey,and(ii)an exploitation phase,which simulates the lizard’s retreat to the treetops after feeding.To assess FLO’s efficacy in addressing optimization problems,its performance is rigorously tested on fifty-two standard benchmark functions.These functions include unimodal,high-dimensional multimodal,and fixed-dimensional multimodal functions,as well as the challenging CEC 2017 test suite.FLO’s performance is benchmarked against twelve established metaheuristic algorithms,providing a comprehensive comparative analysis.The simulation results demonstrate that FLO excels in both exploration and exploitation,effectively balancing these two critical aspects throughout the search process.This balanced approach enables FLO to outperform several competing algorithms in numerous test cases.Additionally,FLO is applied to twenty-two constrained optimization problems from the CEC 2011 test suite and four complex engineering design problems,further validating its robustness and versatility in solving real-world optimization challenges.Overall,the study highlights FLO’s superior performance and its potential as a powerful tool for tackling a wide range of optimization problems.展开更多
Energy storage, such as lead acid batteries, is necessary for renewable energy sources’ autonomy because of their intermittent nature, which makes them more frequently used than traditional energy sources to reduce o...Energy storage, such as lead acid batteries, is necessary for renewable energy sources’ autonomy because of their intermittent nature, which makes them more frequently used than traditional energy sources to reduce operating costs. The battery storage system has to be monitored and managed to prevent serious problems such as battery overcharging, over-discharging, overheating, battery unbalancing, thermal runaway, and fire dangers. For voltage balancing between batteries in the pack throughout the charging period and the SOC estimate, a modified lossless switching mechanism is used in this research’s suggested battery management system. The OCV state of charge calculation, in the beginning, was used in conjunction with the coulomb counting approach to estimate the SOC. The results reveal that correlation factor K has an average value of 0.3 volts when VM ≥ 12 V and an average value of 0.825 when VM ≤ 12 V. The battery monitoring system revealed that voltage balancing was accomplished during the charging process in park one after 80 seconds with a SOC difference of 1.4% between Batteries 1 and 2. On the other hand, the system estimates the state of charge during the discharging process in two packs, with a maximum DOD of 10.8 V for all batteries. The project’s objectives were met since the BMS estimated SOC and achieved voltage balance.展开更多
This paper introduces the Wolverine Optimization Algorithm(WoOA),a biomimetic method inspired by the foraging behaviors of wolverines in their natural habitats.WoOA innovatively integrates two primary strategies:scave...This paper introduces the Wolverine Optimization Algorithm(WoOA),a biomimetic method inspired by the foraging behaviors of wolverines in their natural habitats.WoOA innovatively integrates two primary strategies:scavenging and hunting,mirroring the wolverine’s adeptness in locating carrion and pursuing live prey.The algorithm’s uniqueness lies in its faithful simulation of these dual strategies,which are mathematically structured to optimize various types of problems effectively.The effectiveness of WoOA is rigorously evaluated using the Congress on Evolutionary Computation(CEC)2017 test suite across dimensions of 10,30,50,and 100.The results showcase WoOA’s robust performance in exploration,exploitation,and maintaining a balance between these phases throughout the search process.Compared to twelve established metaheuristic algorithms,WoOA consistently demonstrates a superior performance across diverse benchmark functions.Statistical analyses,including paired t-tests,Friedman test,and Wilcoxon rank-sum tests,validate WoOA’s significant competitive edge over its counterparts.Additionally,WoOA’s practical applicability is illustrated through its successful resolution of twenty-two constrained scenarios from the CEC 2011 suite and four complex engineering design challenges.These applications underscore WoOA’s efficacy in tackling real-world optimization challenges,further highlighting its potential for widespread adoption in engineering and scientific domains.展开更多
The United Nations’Sustainable Development Goals(SDGs)highlight the importance of affordable and clean energy sources.Solar energy is a perfect example,being both renewable and abundant.Its popularity shows no signs ...The United Nations’Sustainable Development Goals(SDGs)highlight the importance of affordable and clean energy sources.Solar energy is a perfect example,being both renewable and abundant.Its popularity shows no signs of slowing down,with solar photovoltaic(PV)panels being the primary technology for converting sunlight into electricity.Advancements are continuously being made to ensure cost-effectiveness,high-performing cells,extended lifespans,and minimal maintenance requirements.This study focuses on identifying suitable locations for implementing solar PVsystems at theUniversityMalaysia PahangAl SultanAbdullah(UMPSA),Pekan campus including buildings,water bodies,and forest areas.A combined technical and economic analysis is conducted using Helioscope for simulations and the Photovoltaic Geographic Information System(PVGIS)for economic considerations.Helioscope simulation examine case studies for PV installations in forested areas,lakes,and buildings.This approach provides comprehensive estimations of solar photovoltaic potential,annual cost savings,electricity costs,and greenhouse gas emission reductions.Based on land coverage percentages,Floatovoltaics have a large solar PV capacity of 32.3 Megawatts(MW);forest-based photovoltaics(Forestvoltaics)achieve maximum yearly savings of RM 37,268,550;and Building Applied Photovoltaics(BAPV)have the lowest CO2 emissions and net carbon dioxide reduction compared to other plant sizes.It also clarifies the purpose of using both software tools to achieve a comprehensive understanding of both technical and economic aspects.展开更多
Energy in its varied forms and applications has become the main driver of today’s modern society. However, recent changes in power demand and climatic changes (decarbonization policy) has awakened the need to rethink...Energy in its varied forms and applications has become the main driver of today’s modern society. However, recent changes in power demand and climatic changes (decarbonization policy) has awakened the need to rethink through the current energy generating and distribution system. This led to the exploration of other energy sources of which renewable energy (like thermal, solar and wind energy) is fast becoming an integral part of most energy system. However, this innovative and promising energy source is highly unreliable in maintaining a constant peak power that matches demand. Energy storage systems have thus been highlighted as a solution in managing such imbalances and maintaining the stability of supply. Energy storage technologies absorb and store energy, and release it on demand. This includes gravitational potential energy (pumped hydroelectric), chemical energy (batteries), kinetic energy (flywheels or compressed air), and energy in the form of electrical (capacitors) and magnetic fields. This paper provides a detailed and comprehensive overview of some of the state-of-the-art energy storage technologies, its evolution, classification, and comparison along with various area of applications. Also highlighted in this paper is a plethora of power electronic Interface technologies that plays a significant role in enabling optimum performance and utilization of energy storage systems in different areas of application.展开更多
In the present study, the effect of the exchange-correlation functional on the structural, mechanical, and optoelectronic properties of orthorhombic RbSrBr3 perovskite has been investigated using various functionals i...In the present study, the effect of the exchange-correlation functional on the structural, mechanical, and optoelectronic properties of orthorhombic RbSrBr3 perovskite has been investigated using various functionals in Density Functional Theory (DFT) with the CASTEP code. The optimized lattice parameters are quite similar for all the functionals. The electronic properties have shown that RbSrBr3 perovskite is a wide direct band gap compound with a band gap energy ranging from 4.296 eV to 4.494 eV for all the functionals. The mechanical parameters like elastic constants, Young’s modulus, Shear modulus, Poisson’s ratio, Pugh’s ratio, and an anisotropic factor reveal that the RbSrBr3 perovskite has ductile behavior and an anisotropic nature which signifies the mechanical stability of the compound. The Debye temperature might withstand lattice vibration heat. High absorption coefficient (>104 cm−1), high optical conductivity, and very low reflectivity have been found in the RbSrBr3 perovskite for all functions. The computed findings on the RbSrBr3 perovskite suggested that the presented studied material is potentially applicable for photodetector and optoelectronic devices.展开更多
In the context of induction motor control, there are various control strategies used to separately control torque and flux. One common approach is known as Field-Oriented Control (FOC). This technique involves transfo...In the context of induction motor control, there are various control strategies used to separately control torque and flux. One common approach is known as Field-Oriented Control (FOC). This technique involves transforming the three-phase currents and voltages into a rotating reference frame, commonly referred to as the “dq” frame. In this frame, the torque/speed and flux components are decoupled, allowing for independent control, by doing so, the motor’s speed can be regulated accurately and maintain a constant flux which is crucial to ensure optimal motor performance and efficiency. The research focused on studying and simulating a field-oriented control system using fuzzy control techniques for an induction motor. The aim was to address the issue of parameter variations, particularly the change in rotor resistance during motor operation, which causes the control system to deviate from the desired direction. This deviation implies to an increase in the magnetic flux value, specifically the flux component on the q-axis. By employing fuzzy logic techniques to regulate flux vector’s components in the dq frame, this problem was successfully resolved, ensuring that the magnetic flux value remains within the nominal limits. To enhance the control system’s performance, response speed, and efficiency of the motor, sliding mode controllers were implemented to regulate the current in the inner loop. The simulation results demonstrated the proficiency of the proposed methodology.展开更多
The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical r...The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.展开更多
Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment planning.Liver Tumors(LTs)vary significantly in size,shape,and location,and can present wi...Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment planning.Liver Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and challenging.This review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and resilience.Performance metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical contexts.The review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging conditions.It suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular methods.This paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.展开更多
The rise of social media platforms has revolutionized communication, enabling the exchange of vast amounts of data through text, audio, images, and videos. These platforms have become critical for sharing opinions and...The rise of social media platforms has revolutionized communication, enabling the exchange of vast amounts of data through text, audio, images, and videos. These platforms have become critical for sharing opinions and insights, influencing daily habits, and driving business, political, and economic decisions. Text posts are particularly significant, and natural language processing (NLP) has emerged as a powerful tool for analyzing such data. While traditional NLP methods have been effective for structured media, social media content poses unique challenges due to its informal and diverse nature. This has spurred the development of new techniques tailored for processing and extracting insights from unstructured user-generated text. One key application of NLP is the summarization of user comments to manage overwhelming content volumes. Abstractive summarization has proven highly effective in generating concise, human-like summaries, offering clear overviews of key themes and sentiments. This enhances understanding and engagement while reducing cognitive effort for users. For businesses, summarization provides actionable insights into customer preferences and feedback, enabling faster trend analysis, improved responsiveness, and strategic adaptability. By distilling complex data into manageable insights, summarization plays a vital role in improving user experiences and empowering informed decision-making in a data-driven landscape. This paper proposes a new implementation framework by fine-tuning and parameterizing Transformer Large Language Models to manage and maintain linguistic and semantic components in abstractive summary generation. The system excels in transforming large volumes of data into meaningful summaries, as evidenced by its strong performance across metrics like fluency, consistency, readability, and semantic coherence.展开更多
Interval type-2 fuzzy neural networks(IT2FNNs)can be seen as the hybridization of interval type-2 fuzzy systems(IT2FSs) and neural networks(NNs). Thus, they naturally inherit the merits of both IT2 FSs and NNs. Althou...Interval type-2 fuzzy neural networks(IT2FNNs)can be seen as the hybridization of interval type-2 fuzzy systems(IT2FSs) and neural networks(NNs). Thus, they naturally inherit the merits of both IT2 FSs and NNs. Although IT2 FNNs have more advantages in processing uncertain, incomplete, or imprecise information compared to their type-1 counterparts, a large number of parameters need to be tuned in the IT2 FNNs,which increases the difficulties of their design. In this paper,big bang-big crunch(BBBC) optimization and particle swarm optimization(PSO) are applied in the parameter optimization for Takagi-Sugeno-Kang(TSK) type IT2 FNNs. The employment of the BBBC and PSO strategies can eliminate the need of backpropagation computation. The computing problem is converted to a simple feed-forward IT2 FNNs learning. The adoption of the BBBC or the PSO will not only simplify the design of the IT2 FNNs, but will also increase identification accuracy when compared with present methods. The proposed optimization based strategies are tested with three types of interval type-2 fuzzy membership functions(IT2FMFs) and deployed on three typical identification models. Simulation results certify the effectiveness of the proposed parameter optimization methods for the IT2 FNNs.展开更多
The rapid consumption of fossil fuel and increased environmental damage caused by it have given a strong impetus to the growth and development of fuelefficient vehicles. Hybrid electric vehicles (HEVs) have evolved fr...The rapid consumption of fossil fuel and increased environmental damage caused by it have given a strong impetus to the growth and development of fuelefficient vehicles. Hybrid electric vehicles (HEVs) have evolved from their inchoate state and are proving to be a promising solution to the serious existential problem posed to the planet earth. Not only do HEVs provide better fuel economy and lower emissions satisfying environmental legislations, but also they dampen the effect of rising fuel prices on consumers. HEVs combine the drive powers of an internal combustion engine and an electrical machine. The main components of HEVs are energy storage system, motor, bidirectional converter and maximum power point trackers (MPPT, in case of solar-powered HEVs). The performance of HEVs greatly depends on these components and its architecture. This paper presents an extensive review on essential components used in HEVs such as their architectures with advantages and disadvantages, choice of bidirectional converter to obtain high efficiency, combining ultracapacitor with battery to extend the battery life, traction motors’ role and their suitability for a particular application. Inclusion of photovoltaic cell in HEVs is a fairly new concept and has been discussed in detail. Various MPPT techniques used for solar-driven HEVs are also discussed in this paper with their suitability.展开更多
Cellular metabolism is a very complex process. The biochemical pathways are fundamental structures of biology. These pathways possess a number of regeneration steps which facilitate energy shuttling on a massive scale...Cellular metabolism is a very complex process. The biochemical pathways are fundamental structures of biology. These pathways possess a number of regeneration steps which facilitate energy shuttling on a massive scale. This facilitates the biochemical pathways to sustain the energy currency of the cells. This concept has been mimicked using electronic circuit components and it has been used to increase the efficiency of bio-energy generation. Six of the carbohydrate biochemical pathways have been chosen in which glycolysis is the principle pathway. All the six pathways are interrelated and coordinated in a complex manner. Mimic circuits have been designed for all the six biochemical pathways. The components of the metabolic pathways such as enzymes, cofactors etc., are substituted by appropriate electronic circuit components. Enzymes are related to the gain of transistors by the bond dissociation energies of enzyme-substrate molecules under consideration. Cofactors and coenzymes are represented by switches and capacitors respectively. Resistors are used for proper orientation of the circuits. The energy obtained from the current methods employed for the decomposition of organic matter is used to trigger the mimic circuits. A similar energy shuttle is observed in the mimic circuits and the percentage rise for each cycle of circuit functioning is found to be 78.90. The theoretical calculations have been made using a sample of domestic waste weighing 1.182 kg. The calculations arrived at finally speak of the efficiency of the novel methodology employed.展开更多
The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords:smaller,faster,and smarter.(1)Smaller:Devices are becoming more compact by integrating previously separated component...The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords:smaller,faster,and smarter.(1)Smaller:Devices are becoming more compact by integrating previously separated components such as sensors,memory,and processing units.As a prime example,the transition from traditional sensory vision computing to in-sensor vision computing has shown clear benefits,such as simpler circuitry,lower power consumption,and less data redundancy.(2)Swifter:Owing to the nature of physics,smaller and more integrated devices can detect,process,and react to input more quickly.In addition,the methods for sensing and processing optical information using various materials(such as oxide semiconductors)are evolving.(3)Smarter:Owing to these two main research directions,we can expect advanced applications such as adaptive vision sensors,collision sensors,and nociceptive sensors.This review mainly focuses on the recent progress,working mechanisms,image pre-processing techniques,and advanced features of two types of neuromorphic vision sensors based on near-sensor and in-sensor vision computing methodologies.展开更多
Mass attenuation coefficients, effective atomic numbers, effective electron densities and Kerma relative to air for adipose, muscle and bone tissues have been investigated in the photon energy region from 20 keV up to...Mass attenuation coefficients, effective atomic numbers, effective electron densities and Kerma relative to air for adipose, muscle and bone tissues have been investigated in the photon energy region from 20 keV up to 50 MeV with Geant4 simulation package and theoretical calculations. Based on Geant4 results of the mass attenuation coefficients, the effective atomic numbers for the tissue models have been calculated. The calculation results have been compared with the values of the Auto-Zeff program and with other studies available in the literature. Moreover, Kerma of studied tissues relative to air has been determined and found to be dependent on the absorption edges of the tissue constituent elements.展开更多
Boron-doped NiO thin films were prepared on glass substrates at 400℃ by airbrush spraying method using a solution of nickel nitrate hexahydrate. Their physical properties were investigated as a function of dopant con...Boron-doped NiO thin films were prepared on glass substrates at 400℃ by airbrush spraying method using a solution of nickel nitrate hexahydrate. Their physical properties were investigated as a function of dopant concentration. From X-ray diffraction patterns, it is observed that the films have cubic structure with lattice parameters varying with boron concentration. The morphologies of the films were examined by using scanning electron microscopy, and the grain sizes were measured to be around 30-50 nm. Optical measurements show that the band gap energies of the films first decrease then increase with increasing boron concentration. The resistivities of the films were determined by four point probe method, and the changes in resistivity with boron concentration were investigated.展开更多
As wind energy is becoming one of the fastestgrowing renewable energy resources,controlling large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties.T...As wind energy is becoming one of the fastestgrowing renewable energy resources,controlling large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties.The main goal of the current work is to propose an intelligent control of the wind turbine system without the need for model identification.For this purpose,a novel model-independent nonsingular terminal slidingmode control(MINTSMC)using the basic principles of the ultralocal model(ULM)and combined with the single input interval type-2 fuzzy logic control(SIT2-FLC)is developed for non-linear wind turbine pitch angle control.In the suggested control framework,the MINTSMC scheme is designed to regulate the wind turbine speed rotor,and a sliding-mode(SM)observer is adopted to estimate the unknown phenomena of the ULM.The auxiliary SIT2-FLC is added in the model-independent control structure to improve the rotor speed regulation and compensate for the SM observation estimation error.Extensive examinations and comparative analyses were made using a real-time softwarein-the-loop(RT-SiL)based on the dSPACE 1202 board to appraise the efficiency and applicability of the suggested modelindependent scheme in a real-time testbed.展开更多
Development of metal matrix composite is becoming widespread in most engineering applications where excellent mechanical properties are required.Mechanical and microstructural properties of aluminium reinforced with s...Development of metal matrix composite is becoming widespread in most engineering applications where excellent mechanical properties are required.Mechanical and microstructural properties of aluminium reinforced with silicon carbide was investigated.Ingot of aluminium was melted in a furnace at temperature ranging between 650-700℃.Ferrotitanium and silicon carbide were preheated in a muffle furnace before addition to molten aluminium in a crucible furnace.Fixed proportions of magnesium,ferrotitanium and varying proportions of silicon carbide were utilized as reinforcements.Stirring was carried out manually for a minimum of 10 mins after the addition of each weight percent of silicon carbide.Resulting as-cast samples were sectioned for various mechanical and microstructural analysis.Microstructural studies from optical microscopy and scanning electron microscopy(SEM)showed the dispersion of reinforcements in the aluminium matrix.Mechanical properties which includes hardness and tensile strength of fabricated composites were observed to increase,while XRD analysis showed various phases formed from reaction between the matrix and reinforcements.展开更多
文摘In this article,a novel metaheuristic technique named Far and Near Optimization(FNO)is introduced,offeringversatile applications across various scientific domains for optimization tasks.The core concept behind FNO lies inintegrating global and local search methodologies to update the algorithm population within the problem-solvingspace based on moving each member to the farthest and nearest member to itself.The paper delineates the theoryof FNO,presenting a mathematical model in two phases:(i)exploration based on the simulation of the movementof a population member towards the farthest member from itself and(ii)exploitation based on simulating themovement of a population member towards the nearest member from itself.FNO’s efficacy in tackling optimizationchallenges is assessed through its handling of the CEC 2017 test suite across problem dimensions of 10,30,50,and 100,as well as to address CEC 2020.The optimization results underscore FNO’s adeptness in exploration,exploitation,and maintaining a balance between them throughout the search process to yield viable solutions.Comparative analysis against twelve established metaheuristic algorithms reveals FNO’s superior performance.Simulation findings indicate FNO’s outperformance of competitor algorithms,securing the top rank as the mosteffective optimizer across a majority of benchmark functions.Moreover,the outcomes derived by employing FNOon twenty-two constrained optimization challenges from the CEC 2011 test suite,alongside four engineering designdilemmas,showcase the effectiveness of the suggested method in tackling real-world scenarios.
文摘The usage of electric vehicles holds a crucial role in lowering the diminishing of the ozone layer because electric vehicles are not dependent on fossil fuels.With more research,evaluation,and its characteristics on electric vehicles,the infrastructure of charging points,production of electric vehicles,and network modelling,this paper provides a comprehensive overview of electric vehicles,and hybrid vehicles,including an analysis of their market growth,as well as different types of optimization used in the current scenario.In developing countries like India,the biggest barrier is their unfulfilled facility over the charging.Without renewable energy sources,vehicle-to-grid technology facilitates the enhancement of additional power requirements.The mobility factor has been considered an important and special characteristic of electric vehicles.
文摘This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards.The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases:(i)an exploration phase,which mimics the lizard’s sudden attack on its prey,and(ii)an exploitation phase,which simulates the lizard’s retreat to the treetops after feeding.To assess FLO’s efficacy in addressing optimization problems,its performance is rigorously tested on fifty-two standard benchmark functions.These functions include unimodal,high-dimensional multimodal,and fixed-dimensional multimodal functions,as well as the challenging CEC 2017 test suite.FLO’s performance is benchmarked against twelve established metaheuristic algorithms,providing a comprehensive comparative analysis.The simulation results demonstrate that FLO excels in both exploration and exploitation,effectively balancing these two critical aspects throughout the search process.This balanced approach enables FLO to outperform several competing algorithms in numerous test cases.Additionally,FLO is applied to twenty-two constrained optimization problems from the CEC 2011 test suite and four complex engineering design problems,further validating its robustness and versatility in solving real-world optimization challenges.Overall,the study highlights FLO’s superior performance and its potential as a powerful tool for tackling a wide range of optimization problems.
文摘Energy storage, such as lead acid batteries, is necessary for renewable energy sources’ autonomy because of their intermittent nature, which makes them more frequently used than traditional energy sources to reduce operating costs. The battery storage system has to be monitored and managed to prevent serious problems such as battery overcharging, over-discharging, overheating, battery unbalancing, thermal runaway, and fire dangers. For voltage balancing between batteries in the pack throughout the charging period and the SOC estimate, a modified lossless switching mechanism is used in this research’s suggested battery management system. The OCV state of charge calculation, in the beginning, was used in conjunction with the coulomb counting approach to estimate the SOC. The results reveal that correlation factor K has an average value of 0.3 volts when VM ≥ 12 V and an average value of 0.825 when VM ≤ 12 V. The battery monitoring system revealed that voltage balancing was accomplished during the charging process in park one after 80 seconds with a SOC difference of 1.4% between Batteries 1 and 2. On the other hand, the system estimates the state of charge during the discharging process in two packs, with a maximum DOD of 10.8 V for all batteries. The project’s objectives were met since the BMS estimated SOC and achieved voltage balance.
文摘This paper introduces the Wolverine Optimization Algorithm(WoOA),a biomimetic method inspired by the foraging behaviors of wolverines in their natural habitats.WoOA innovatively integrates two primary strategies:scavenging and hunting,mirroring the wolverine’s adeptness in locating carrion and pursuing live prey.The algorithm’s uniqueness lies in its faithful simulation of these dual strategies,which are mathematically structured to optimize various types of problems effectively.The effectiveness of WoOA is rigorously evaluated using the Congress on Evolutionary Computation(CEC)2017 test suite across dimensions of 10,30,50,and 100.The results showcase WoOA’s robust performance in exploration,exploitation,and maintaining a balance between these phases throughout the search process.Compared to twelve established metaheuristic algorithms,WoOA consistently demonstrates a superior performance across diverse benchmark functions.Statistical analyses,including paired t-tests,Friedman test,and Wilcoxon rank-sum tests,validate WoOA’s significant competitive edge over its counterparts.Additionally,WoOA’s practical applicability is illustrated through its successful resolution of twenty-two constrained scenarios from the CEC 2011 suite and four complex engineering design challenges.These applications underscore WoOA’s efficacy in tackling real-world optimization challenges,further highlighting its potential for widespread adoption in engineering and scientific domains.
基金the financial support provided by Universiti Malaysia Pahang Al Sultan Abdullah(www.umpsa.edu.my,accessed 10 April 2024)through the Doctoral Research Scheme(DRS)toMr.Rittick Maity and the Postgraduate Research Scheme(PGRS220390).
文摘The United Nations’Sustainable Development Goals(SDGs)highlight the importance of affordable and clean energy sources.Solar energy is a perfect example,being both renewable and abundant.Its popularity shows no signs of slowing down,with solar photovoltaic(PV)panels being the primary technology for converting sunlight into electricity.Advancements are continuously being made to ensure cost-effectiveness,high-performing cells,extended lifespans,and minimal maintenance requirements.This study focuses on identifying suitable locations for implementing solar PVsystems at theUniversityMalaysia PahangAl SultanAbdullah(UMPSA),Pekan campus including buildings,water bodies,and forest areas.A combined technical and economic analysis is conducted using Helioscope for simulations and the Photovoltaic Geographic Information System(PVGIS)for economic considerations.Helioscope simulation examine case studies for PV installations in forested areas,lakes,and buildings.This approach provides comprehensive estimations of solar photovoltaic potential,annual cost savings,electricity costs,and greenhouse gas emission reductions.Based on land coverage percentages,Floatovoltaics have a large solar PV capacity of 32.3 Megawatts(MW);forest-based photovoltaics(Forestvoltaics)achieve maximum yearly savings of RM 37,268,550;and Building Applied Photovoltaics(BAPV)have the lowest CO2 emissions and net carbon dioxide reduction compared to other plant sizes.It also clarifies the purpose of using both software tools to achieve a comprehensive understanding of both technical and economic aspects.
文摘Energy in its varied forms and applications has become the main driver of today’s modern society. However, recent changes in power demand and climatic changes (decarbonization policy) has awakened the need to rethink through the current energy generating and distribution system. This led to the exploration of other energy sources of which renewable energy (like thermal, solar and wind energy) is fast becoming an integral part of most energy system. However, this innovative and promising energy source is highly unreliable in maintaining a constant peak power that matches demand. Energy storage systems have thus been highlighted as a solution in managing such imbalances and maintaining the stability of supply. Energy storage technologies absorb and store energy, and release it on demand. This includes gravitational potential energy (pumped hydroelectric), chemical energy (batteries), kinetic energy (flywheels or compressed air), and energy in the form of electrical (capacitors) and magnetic fields. This paper provides a detailed and comprehensive overview of some of the state-of-the-art energy storage technologies, its evolution, classification, and comparison along with various area of applications. Also highlighted in this paper is a plethora of power electronic Interface technologies that plays a significant role in enabling optimum performance and utilization of energy storage systems in different areas of application.
文摘In the present study, the effect of the exchange-correlation functional on the structural, mechanical, and optoelectronic properties of orthorhombic RbSrBr3 perovskite has been investigated using various functionals in Density Functional Theory (DFT) with the CASTEP code. The optimized lattice parameters are quite similar for all the functionals. The electronic properties have shown that RbSrBr3 perovskite is a wide direct band gap compound with a band gap energy ranging from 4.296 eV to 4.494 eV for all the functionals. The mechanical parameters like elastic constants, Young’s modulus, Shear modulus, Poisson’s ratio, Pugh’s ratio, and an anisotropic factor reveal that the RbSrBr3 perovskite has ductile behavior and an anisotropic nature which signifies the mechanical stability of the compound. The Debye temperature might withstand lattice vibration heat. High absorption coefficient (>104 cm−1), high optical conductivity, and very low reflectivity have been found in the RbSrBr3 perovskite for all functions. The computed findings on the RbSrBr3 perovskite suggested that the presented studied material is potentially applicable for photodetector and optoelectronic devices.
文摘In the context of induction motor control, there are various control strategies used to separately control torque and flux. One common approach is known as Field-Oriented Control (FOC). This technique involves transforming the three-phase currents and voltages into a rotating reference frame, commonly referred to as the “dq” frame. In this frame, the torque/speed and flux components are decoupled, allowing for independent control, by doing so, the motor’s speed can be regulated accurately and maintain a constant flux which is crucial to ensure optimal motor performance and efficiency. The research focused on studying and simulating a field-oriented control system using fuzzy control techniques for an induction motor. The aim was to address the issue of parameter variations, particularly the change in rotor resistance during motor operation, which causes the control system to deviate from the desired direction. This deviation implies to an increase in the magnetic flux value, specifically the flux component on the q-axis. By employing fuzzy logic techniques to regulate flux vector’s components in the dq frame, this problem was successfully resolved, ensuring that the magnetic flux value remains within the nominal limits. To enhance the control system’s performance, response speed, and efficiency of the motor, sliding mode controllers were implemented to regulate the current in the inner loop. The simulation results demonstrated the proficiency of the proposed methodology.
文摘The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.
基金the“Intelligent Recognition Industry Service Center”as part of the Featured Areas Research Center Program under the Higher Education Sprout Project by the Ministry of Education(MOE)in Taiwan,and the National Science and Technology Council,Taiwan,under grants 113-2221-E-224-041 and 113-2622-E-224-002.Additionally,partial support was provided by Isuzu Optics Corporation.
文摘Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment planning.Liver Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and challenging.This review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and resilience.Performance metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical contexts.The review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging conditions.It suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular methods.This paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.
文摘The rise of social media platforms has revolutionized communication, enabling the exchange of vast amounts of data through text, audio, images, and videos. These platforms have become critical for sharing opinions and insights, influencing daily habits, and driving business, political, and economic decisions. Text posts are particularly significant, and natural language processing (NLP) has emerged as a powerful tool for analyzing such data. While traditional NLP methods have been effective for structured media, social media content poses unique challenges due to its informal and diverse nature. This has spurred the development of new techniques tailored for processing and extracting insights from unstructured user-generated text. One key application of NLP is the summarization of user comments to manage overwhelming content volumes. Abstractive summarization has proven highly effective in generating concise, human-like summaries, offering clear overviews of key themes and sentiments. This enhances understanding and engagement while reducing cognitive effort for users. For businesses, summarization provides actionable insights into customer preferences and feedback, enabling faster trend analysis, improved responsiveness, and strategic adaptability. By distilling complex data into manageable insights, summarization plays a vital role in improving user experiences and empowering informed decision-making in a data-driven landscape. This paper proposes a new implementation framework by fine-tuning and parameterizing Transformer Large Language Models to manage and maintain linguistic and semantic components in abstractive summary generation. The system excels in transforming large volumes of data into meaningful summaries, as evidenced by its strong performance across metrics like fluency, consistency, readability, and semantic coherence.
基金supported by the National Natural Science Foundation of China (61873079,51707050)
文摘Interval type-2 fuzzy neural networks(IT2FNNs)can be seen as the hybridization of interval type-2 fuzzy systems(IT2FSs) and neural networks(NNs). Thus, they naturally inherit the merits of both IT2 FSs and NNs. Although IT2 FNNs have more advantages in processing uncertain, incomplete, or imprecise information compared to their type-1 counterparts, a large number of parameters need to be tuned in the IT2 FNNs,which increases the difficulties of their design. In this paper,big bang-big crunch(BBBC) optimization and particle swarm optimization(PSO) are applied in the parameter optimization for Takagi-Sugeno-Kang(TSK) type IT2 FNNs. The employment of the BBBC and PSO strategies can eliminate the need of backpropagation computation. The computing problem is converted to a simple feed-forward IT2 FNNs learning. The adoption of the BBBC or the PSO will not only simplify the design of the IT2 FNNs, but will also increase identification accuracy when compared with present methods. The proposed optimization based strategies are tested with three types of interval type-2 fuzzy membership functions(IT2FMFs) and deployed on three typical identification models. Simulation results certify the effectiveness of the proposed parameter optimization methods for the IT2 FNNs.
文摘The rapid consumption of fossil fuel and increased environmental damage caused by it have given a strong impetus to the growth and development of fuelefficient vehicles. Hybrid electric vehicles (HEVs) have evolved from their inchoate state and are proving to be a promising solution to the serious existential problem posed to the planet earth. Not only do HEVs provide better fuel economy and lower emissions satisfying environmental legislations, but also they dampen the effect of rising fuel prices on consumers. HEVs combine the drive powers of an internal combustion engine and an electrical machine. The main components of HEVs are energy storage system, motor, bidirectional converter and maximum power point trackers (MPPT, in case of solar-powered HEVs). The performance of HEVs greatly depends on these components and its architecture. This paper presents an extensive review on essential components used in HEVs such as their architectures with advantages and disadvantages, choice of bidirectional converter to obtain high efficiency, combining ultracapacitor with battery to extend the battery life, traction motors’ role and their suitability for a particular application. Inclusion of photovoltaic cell in HEVs is a fairly new concept and has been discussed in detail. Various MPPT techniques used for solar-driven HEVs are also discussed in this paper with their suitability.
文摘Cellular metabolism is a very complex process. The biochemical pathways are fundamental structures of biology. These pathways possess a number of regeneration steps which facilitate energy shuttling on a massive scale. This facilitates the biochemical pathways to sustain the energy currency of the cells. This concept has been mimicked using electronic circuit components and it has been used to increase the efficiency of bio-energy generation. Six of the carbohydrate biochemical pathways have been chosen in which glycolysis is the principle pathway. All the six pathways are interrelated and coordinated in a complex manner. Mimic circuits have been designed for all the six biochemical pathways. The components of the metabolic pathways such as enzymes, cofactors etc., are substituted by appropriate electronic circuit components. Enzymes are related to the gain of transistors by the bond dissociation energies of enzyme-substrate molecules under consideration. Cofactors and coenzymes are represented by switches and capacitors respectively. Resistors are used for proper orientation of the circuits. The energy obtained from the current methods employed for the decomposition of organic matter is used to trigger the mimic circuits. A similar energy shuttle is observed in the mimic circuits and the percentage rise for each cycle of circuit functioning is found to be 78.90. The theoretical calculations have been made using a sample of domestic waste weighing 1.182 kg. The calculations arrived at finally speak of the efficiency of the novel methodology employed.
基金This work was supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.NRF-2019R1A2C2002447)This research also was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.NRF-2014R1A6A1030419)This work also was supported by Korea Institute for Advancement of Technology(KIAT)grant funded by the Korea Government(MOTIE)(P0020967,Advanced Training Program for Smart Sensor Engineers).
文摘The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords:smaller,faster,and smarter.(1)Smaller:Devices are becoming more compact by integrating previously separated components such as sensors,memory,and processing units.As a prime example,the transition from traditional sensory vision computing to in-sensor vision computing has shown clear benefits,such as simpler circuitry,lower power consumption,and less data redundancy.(2)Swifter:Owing to the nature of physics,smaller and more integrated devices can detect,process,and react to input more quickly.In addition,the methods for sensing and processing optical information using various materials(such as oxide semiconductors)are evolving.(3)Smarter:Owing to these two main research directions,we can expect advanced applications such as adaptive vision sensors,collision sensors,and nociceptive sensors.This review mainly focuses on the recent progress,working mechanisms,image pre-processing techniques,and advanced features of two types of neuromorphic vision sensors based on near-sensor and in-sensor vision computing methodologies.
文摘Mass attenuation coefficients, effective atomic numbers, effective electron densities and Kerma relative to air for adipose, muscle and bone tissues have been investigated in the photon energy region from 20 keV up to 50 MeV with Geant4 simulation package and theoretical calculations. Based on Geant4 results of the mass attenuation coefficients, the effective atomic numbers for the tissue models have been calculated. The calculation results have been compared with the values of the Auto-Zeff program and with other studies available in the literature. Moreover, Kerma of studied tissues relative to air has been determined and found to be dependent on the absorption edges of the tissue constituent elements.
文摘Boron-doped NiO thin films were prepared on glass substrates at 400℃ by airbrush spraying method using a solution of nickel nitrate hexahydrate. Their physical properties were investigated as a function of dopant concentration. From X-ray diffraction patterns, it is observed that the films have cubic structure with lattice parameters varying with boron concentration. The morphologies of the films were examined by using scanning electron microscopy, and the grain sizes were measured to be around 30-50 nm. Optical measurements show that the band gap energies of the films first decrease then increase with increasing boron concentration. The resistivities of the films were determined by four point probe method, and the changes in resistivity with boron concentration were investigated.
文摘As wind energy is becoming one of the fastestgrowing renewable energy resources,controlling large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties.The main goal of the current work is to propose an intelligent control of the wind turbine system without the need for model identification.For this purpose,a novel model-independent nonsingular terminal slidingmode control(MINTSMC)using the basic principles of the ultralocal model(ULM)and combined with the single input interval type-2 fuzzy logic control(SIT2-FLC)is developed for non-linear wind turbine pitch angle control.In the suggested control framework,the MINTSMC scheme is designed to regulate the wind turbine speed rotor,and a sliding-mode(SM)observer is adopted to estimate the unknown phenomena of the ULM.The auxiliary SIT2-FLC is added in the model-independent control structure to improve the rotor speed regulation and compensate for the SM observation estimation error.Extensive examinations and comparative analyses were made using a real-time softwarein-the-loop(RT-SiL)based on the dSPACE 1202 board to appraise the efficiency and applicability of the suggested modelindependent scheme in a real-time testbed.
文摘Development of metal matrix composite is becoming widespread in most engineering applications where excellent mechanical properties are required.Mechanical and microstructural properties of aluminium reinforced with silicon carbide was investigated.Ingot of aluminium was melted in a furnace at temperature ranging between 650-700℃.Ferrotitanium and silicon carbide were preheated in a muffle furnace before addition to molten aluminium in a crucible furnace.Fixed proportions of magnesium,ferrotitanium and varying proportions of silicon carbide were utilized as reinforcements.Stirring was carried out manually for a minimum of 10 mins after the addition of each weight percent of silicon carbide.Resulting as-cast samples were sectioned for various mechanical and microstructural analysis.Microstructural studies from optical microscopy and scanning electron microscopy(SEM)showed the dispersion of reinforcements in the aluminium matrix.Mechanical properties which includes hardness and tensile strength of fabricated composites were observed to increase,while XRD analysis showed various phases formed from reaction between the matrix and reinforcements.
