This study presents a detailed comparative analysis of three electron transport layer(ETL)materials for perovskite solar cells(PSCs),namely titanium dioxide(TiO_(2)),barium titanate(BaTiO_(3)or BTO),and strontium-dope...This study presents a detailed comparative analysis of three electron transport layer(ETL)materials for perovskite solar cells(PSCs),namely titanium dioxide(TiO_(2)),barium titanate(BaTiO_(3)or BTO),and strontium-doped barium titan-ate(Ba_(1−x)Sr_(x)TiO_(3)or BST),and their impact on the quantum efficiency(QE)and power conversion efficiency(PCE)of CH_(3)NH_(3)PbI_(3)(MAPbI_(3))PSCs.The optimized structure demonstrates that devices utilizing BST as an ETL achieved the highest PCE of 29.85%,exhibiting superior thermal stability with the lowest temperature coefficient of−0.43%/K.This temperature-induced degradation is comparable to that of commercially available silicon cells.Furthermore,BST-based ETLs show 29.50%and 26.48%higher PCE than those of TiO_(2)-based and BTO-based ETLs.The enhanced internal QE and favorable current density–voltage(J–V)characteristics of BST compared with those of TiO_(2)and BTO are attributed to its improved charge carrier separation,reduced recombination rates,and robust electrical characteristics under varied environmental conditions.Furthermore,the electric field and generation rate of the BST-based ETLs show a more favorable distribution than those of the TiO_(2)-based and BTO-based ETLs.These findings provide significant insights into the role of different ETLs in enhancing QE,indicating that BST is a superior ETL that enhances both the efficiency and stability of PSCs.This study contributes to the understanding of how perovskite-structured ETLs can be used to design and optimize highly efficient and stable photovoltaic devices.展开更多
Objective:To assess the effects of turmeric extract and its compounds on oxidative stress,inflammation,and apoptosis in acetaminophen-induced liver injury.Methods:HepG2 cells were administered with acetaminophen(40 mM...Objective:To assess the effects of turmeric extract and its compounds on oxidative stress,inflammation,and apoptosis in acetaminophen-induced liver injury.Methods:HepG2 cells were administered with acetaminophen(40 mM)to induce hepatotoxicity,followed by treatment with turmeric extract and its isolated compounds including curcumin,demethoxycurcumin,bis-demethoxycurcumin and ar-turmerone at 5,25,and 125μg/mL.IL-1β,IL-6,and IL-10 levels were quantified with ELISA kits.Further,qRT-PCR was used to analyze the mRNA expression of JNK,Casp-9,and Casp-3.Meanwhile,the levels of nitric oxide and lactate dehydrogenase were analyzed using colorimetric assay.Results:Acetaminophen administration caused an increase in the levels of lactate dehydrogenase,nitric oxide,IL-1β,IL-6,and the mRNA expression of JNK,Casp-9,and Casp-3 in HepG2 cells while reducing IL-10 levels.Treatment with turmeric extract,curcumin,demethoxycurcumin,bis-demethoxycurcumin,and ar-turmerone lowered IL-1β,IL-6,nitric oxide,and lactate dehydrogenase levels,downregulated the mRNA expression of JNK,Casp-9,and Casp-3,and increased IL-10 levels.Conclusions:Turmeric extract and its compounds have significant hepatoprotective activity and could be further explored for the treatment of liver damage.展开更多
This paper proposes to study the impacts of electrical line losses due to the connection of distributed generators (DG) to 22kV distribution system of Provincial Electricity Authority (PEA). Data of geographic informa...This paper proposes to study the impacts of electrical line losses due to the connection of distributed generators (DG) to 22kV distribution system of Provincial Electricity Authority (PEA). Data of geographic information systems (GIS) including the distance of distribution line and location of load being key parameter of PEA is simulated using digital simulation and electrical network calculation program (DIgSILENT) to analyze power loss of the distribution system. In addition, the capacity and location of DG installed into the distribution system is considered. The results are shown that, when DG is installed close to the substation, the electrical line losses are reduced. However, if DG capacity becomes larger and the distance between DG and load is longer, the electrical line losses tend to increase. The results of this paper can be used to create the suitability and fairness of the fee for both DG and utility.展开更多
Multi-phase machines are so attractive for electrical machine designers because of their valuable advantages such as high reliability and fault tolerant ability.Meanwhile,fractional slot concentrated windings(FSCW)are...Multi-phase machines are so attractive for electrical machine designers because of their valuable advantages such as high reliability and fault tolerant ability.Meanwhile,fractional slot concentrated windings(FSCW)are well known because of short end winding length,simple structure,field weakening sufficiency,fault tolerant capability and higher slot fill factor.The five-phase machines equipped with FSCW,are very good candidates for the purpose of designing motors for high reliable applications,like electric cars,major transporting buses,high speed trains and massive trucks.But,in comparison to the general distributed windings,the FSCWs contain high magnetomotive force(MMF)space harmonic contents,which cause unwanted effects on the machine ability,such as localized iron saturation and core losses.This manuscript introduces several new five-phase fractional slot winding layouts,by the means of slot shifting concept in order to design the new types of synchronous reluctance motors(SynRels).In order to examine the proposed winding’s performances,three sample machines are designed as case studies,and analytical study and finite element analysis(FEA)is used for validation.展开更多
Over the past years,many efforts have been accomplished to achieve fast and accurate meta-heuristic algorithms to optimize a variety of real-world problems.This study presents a new optimization method based on an unu...Over the past years,many efforts have been accomplished to achieve fast and accurate meta-heuristic algorithms to optimize a variety of real-world problems.This study presents a new optimization method based on an unusual geological phenomenon in nature,named Geyser inspired Algorithm(GEA).The mathematical modeling of this geological phenomenon is carried out to have a better understanding of the optimization process.The efficiency and accuracy of GEA are verified using statistical examination and convergence rate comparison on numerous CEC 2005,CEC 2014,CEC 2017,and real-parameter benchmark functions.Moreover,GEA has been applied to several real-parameter engineering optimization problems to evaluate its effectiveness.In addition,to demonstrate the applicability and robustness of GEA,a comprehensive investigation is performed for a fair comparison with other standard optimization methods.The results demonstrate that GEA is noticeably prosperous in reaching the optimal solutions with a high convergence rate in comparison with other well-known nature-inspired algorithms,including ABC,BBO,PSO,and RCGA.Note that the source code of the GEA is publicly available at https://www.optim-app.com/projects/gea.展开更多
The research aimed to propose a non-destructive technology to control subterranean termites Coptotermes curvignathus Holmgren infestation based on electromagnetic waves. A portable apparatus for this technology has be...The research aimed to propose a non-destructive technology to control subterranean termites Coptotermes curvignathus Holmgren infestation based on electromagnetic waves. A portable apparatus for this technology has been built and its experiment is presented in this paper. Some electrical parameters were measured and analyzed along with their effects to the termites. The experiment using frequency range between 30 Hz - 600 kHz has been done. The average error of the apparatus by comparing the result with the direct measurement using oscilloscope was also measured. The highest error value appeared at 600 kHz with frequency error 6.05 kHz. The highest error of voltage (i.e. 0.186 Volt) appeared at 100 kHz. For safetiness, the highest magnetic field at 300 kHz was 0.1815 μT and at 500 kHz was 0.00725 μT which were safe for human. The average value of termites mortality was higher on irradiation time 120 minutes than 60 minutes respectively in all test frequency: 300 kHz, 400 kHz, 500 kHz and 600 kHz. This paper presents an important information of the electromagnatic-based technology for environmental friendly termites control in spite of using the insecticides.展开更多
Quantum resources such as entanglement and coherence are the holy grail for modern quantum technologies. Although the unwanted environmental effects tackle quantum information processing tasks, suprisingly these key q...Quantum resources such as entanglement and coherence are the holy grail for modern quantum technologies. Although the unwanted environmental effects tackle quantum information processing tasks, suprisingly these key quantum resources may be protected and even enhanced by the implementation of some special hybrid open quantum systems. Here, we aim to show how a dissipative atom-cavity-system can be accomplished to generate enhanced quantum resources.To do so, we consider a couple of dissipative cavities, where each one contains two effective two-level atoms interacting with a single-mode cavity field. In practical applications, a classical laser field may be applied to drive each atomic subsystem. After driving the system, a Bell-state measurement is performed on the output of the system to quantify the entanglement and coherence. The obtained results reveal that the remote entanglement and coherence between the atoms existing inside the two distant cavities are not only enhanced, but can be stabilized, even under the action of dissipation. In contrast, the local entanglement between two atoms inside each dissipative cavity attenuates due to the presence of unwanted environmental effects.Nevertheless, the local coherence may show the same behavior as the remote coherence.Besides, the system provides the steady state entanglement in various interaction regimes,particularly in the strong atom-cavity coupling and with relatively large detuning. More interestingly, our numerical analyses demonstrate that the system may show a memory effect due to the fact that the death and revival of the entanglement take place during the interaction. Our proposed model may find potential applications for the implementation of long distance quantum networks. In particular, it facilitates the distribution of quantum resources between the nodes of large-scale quantum networks for secure communication.展开更多
Recently,nano-systems based on molecular communications via diffusion(MCvD)have been implemented in a variety of nanomedical applications,most notably in targeted drug delivery system(TDDS)scenarios.Furthermore,becaus...Recently,nano-systems based on molecular communications via diffusion(MCvD)have been implemented in a variety of nanomedical applications,most notably in targeted drug delivery system(TDDS)scenarios.Furthermore,because the MCvD is unreliable and there exists molecular noise and inter symbol interference(ISI),cooperative nano-relays can acquire the reliability for drug delivery to targeted diseased cells,especially if the separation distance between the nano transmitter and nano receiver is increased.In this work,we propose an approach for optimizing the performance of the nano system using cooperative molecular communications with a nano relay scheme,while accounting for blood flow effects in terms of drift velocity.The fractions of the molecular drug that should be allocated to the nano transmitter and nano relay positioning are computed using a collaborative optimization problem solved by theModified Central Force Optimization(MCFO)algorithm.Unlike the previous work,the probability of bit error is expressed in a closed-form expression.It is used as an objective function to determine the optimal velocity of the drug molecules and the detection threshold at the nano receiver.The simulation results show that the probability of bit error can be dramatically reduced by optimizing the drift velocity,detection threshold,location of the nano-relay in the proposed nano system,and molecular drug budget.展开更多
Spirulina platensis is a special and unique cyanobacteria that is produced worldwide with a varied cost of cultivation media. In this study, five main experiments with different treatments were performed to evaluate t...Spirulina platensis is a special and unique cyanobacteria that is produced worldwide with a varied cost of cultivation media. In this study, five main experiments with different treatments were performed to evaluate the possibility of using cheap aquaculture water for Spirulina production, to test if solutions made by plant ash (PAS) could be used for Spirulina production, to determine if brackish water (BW) and mining water have a good impact on Spirulina production, to create a medium composed of cheap chemicals and fertilizers to be used for Spirulina cultivation, and to test if a mixture made from local components could be used to produce Spirulina. All experiments were performed via growth and dry weight measurements, including determination of chemical and physical characteristics of the samples with a comparison with Zarrouk medium (ZM) as a reference for each experiment, and all experiments were performed for 21 days to determine the best media type that lasts longer for commercial purposes. In all experiments, pH values were between 8 and 11, and EC was between 9.8 and 30 ms/cm, while temperature was at 30°C and 35°C, and light was at 1500 and 5000 Lux for 16 h light and 8 h dark. Spirulina can grow in (FW). It can also grow in FW diluted with BW. Also a 3% PAS can be used as a source to cultivate Spirulina at a very low price compared to ZM. The chemical fertilizer formula was one of the best types among all treatments with a good price. A mixture of these local resources could be a very good cheap alternative source. The main result that was obtained from all experiments in this study is the ability of Spirulina to grow within a wide range of chemical parameters at a lower price.展开更多
Purpose–Material selection,driven by wide and often conflicting objectives,is an important,sometimes difficult problem in material engineering.In this context,multi-criteria decision-making(MCDM)methodologies are eff...Purpose–Material selection,driven by wide and often conflicting objectives,is an important,sometimes difficult problem in material engineering.In this context,multi-criteria decision-making(MCDM)methodologies are effective.An approach of MCDM is needed to cater to criteria of material assortment simultaneously.More firms are now concerned about increasing their productivity using mathematical tools.To occupy a gap in the previous literature this research recommends an integrated MCDM and mathematical Bi-objective model for the selection of material.In addition,by using the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS),the inherent ambiguities of decision-makers in paired evaluations are considered in this research.It goes on to construct a mathematical bi-objective model for determining the best item to purchase.Design/methodology/approach–The entropy perspective is implemented in this paper to evaluate the weight parameters,while the TOPSIS technique is used to determine the best and worst intermediate pipe materials for automotive exhaust system.The intermediate pipes are used to join the components of the exhaust systems.The materials usually used to manufacture intermediate pipe are SUS 436LM,SUS 430,SUS 304,SUS 436L,SUH 409 L,SUS 441 L and SUS 439L.These seven materials are evaluated based on tensile strength(TS),hardness(H),elongation(E),yield strength(YS)and cost(C).A hybrid methodology combining entropy-based criteria weighting,with the TOPSIS for alternative ranking,is pursued to identify the optimal design material for an engineered application in this paper.This study aims to help while filling the information gap in selecting the most suitable material for use in the exhaust intermediate pipes.After that,the authors searched for and considered eight materials and evaluated them on the following five criteria:(1)TS,(2)YS,(3)H,(4)E and(5)C.The first two criteria have been chosen because they can have a lot of influence on the behavior of the exhaust intermediate pipes,on their performance and on the cost.In this structure,the weights of the criteria are calculated objectively through the entropy method in order to have an unbiased assessment.This essentially measures the quantity of information each criterion contribution,indicating the relative importance of these criteria better.Subsequently,the materials were ranked using the TOPSIS method in terms of their relative performance by measuring each material from an ideal solution to determine the best alternative.The results show that SUS 309,SUS 432L and SUS 436 LM are the first three materials that the exhaust intermediate pipe optimal design should consider.Findings–The material matrix of the decision presented in Table 3 was normalized through Equation 5,as shown in Table 5,and the matrix was multiplied with weighting criteriaß_j.The obtained weighted normalized matrix V_ij is presented in Table 6.However,the ideal,worst and best value was ascertained by employing Equation 7.This study is based on the selection of material for the development of intermediate pipe using MCDM,and it involves four basic stages,i.e.method of translation criteria,screening process,method of ranking and search for methods.The selection was done through the TOPSIS method,and the criteria weight was obtained by the entropy method.The result showed that the top three materials are SUS 309,SUS 432L and SUS 436 LM,respectively.For the future work,it is suggested to select more alternatives and criteria.The comparison can also be done by using different MCDM techniques like and Choice Expressing Reality(ELECTRE),Decision-Making Trial and Evaluation Laboratory(DEMATEL)and Preference Ranking Organization Method for Enrichment Evaluation(PROMETHEE).Originality/value–The results provide important conclusions for material selection in this targeted application,verifying the employment of mutual entropy-TOPSIS methodology for a series of difficult engineering decisions in material engineering concepts that combine superior capacity with better performance as well as cost-efficiency in various engineering design.展开更多
This article deals with the methods of finding partial discharge(PD)location in power transformers using ultra high frequency(UHF)measurements.The UHF technique utilises two methods to find the PD location,that is,the...This article deals with the methods of finding partial discharge(PD)location in power transformers using ultra high frequency(UHF)measurements.The UHF technique utilises two methods to find the PD location,that is,the shortest path method and hyperbolic method.The shortest path method works based on the comparison of the measured data and the ones in the database.In the hyperbolic method,a hyperbolic equation is obtained between each two element subset of sensors.The coordinate that best fits all equations is known as the PD location,and can be obtained in three different ways,that is,iterative algorithms,the Fang method and Chan method.The convergence of iterative algorithms is limited by poor initial estimate,overshoot,mitigation of non-convergence etc.The Fang and Chan methods are two closed-form solutions that are used in the communication system to find the radiation source location.This article explains how to use these two methods to obtain the PD coordinate inside the power transformer.These two methods can find exactly the coordinate that best fits all hyperbolic equations.At the end of this article,several tests are carried out through CST software and the PD locations is estimated by all presented methods.The simulation results show how the Fang and Chan methods can overcome the limitations of the iterative method.展开更多
Epilepsy is a long-term neurological condition marked by recurrent seizures,which result from abnormal electrical activity in the brain that disrupts its normal functioning.Traditional methods for detecting epilepsy t...Epilepsy is a long-term neurological condition marked by recurrent seizures,which result from abnormal electrical activity in the brain that disrupts its normal functioning.Traditional methods for detecting epilepsy through machine learning typically utilize discrete-time models,which inadequately represent the continuous dynamics of electroencephalogram(EEG)signals.To overcome this limitation,we introduce an innovative approach that employs Neural Ordinary Differential Equations(NODEs)to model EEG signals as continuous-time systems.This allows for effective management of irregular sampling and intricate temporal patterns.In contrast to conventional techniques,such as Convolutional Neural Networks(CNNs)and Recurrent Neural Networks(RNNs),which necessitate fixedlength inputs and often struggle with long-term dependencies,our framework incorporates:(1)a NODE block to capture continuous-time EEG dynamics,(2)a feature extraction module tailored for seizure-specific patterns,and(3)an attention-based fusion mechanism to enhance interpretability in classification.When evaluated on three publicly accessible EEG datasets,including those from Boston Children’s Hospital and the Massachusetts Institute of Technology(CHB-MIT)and the Temple University Hospital(TUH)EEG Corpus,the model demonstrated an average accuracy of 98.2%,a sensitivity of 97.8%,a specificity of 98.3%,and an F1-score of 97.9%.Additionally,the inference latency was reduced by approximately 30%compared to standard CNN and Long Short-Term Memory(LSTM)architectures,making it well-suited for real-time applications.The method’s resilience to noise and its adaptability to irregular sampling enhance its potential for clinical use in real-time settings.展开更多
We demonstrated a new type of MAX phase material,chromium titanium aluminum carbide(Cr_(2)TiAlC_(2)) polymer film,to generate a passively Q-switched erbium-doped fiber laser(EDFL).The film thickness was measured to be...We demonstrated a new type of MAX phase material,chromium titanium aluminum carbide(Cr_(2)TiAlC_(2)) polymer film,to generate a passively Q-switched erbium-doped fiber laser(EDFL).The film thickness was measured to be around 45 μm,which was fabricated using the embedding method with polyvinyl alcohol(PVA) polymer as hoster.The saturable absorber(SA) film demonstrates a dual-wavelength passively Q-switched EDFL which operates at 1 531 nm and 1 560.19 nm,respectively.The Q-switching pulse duration could be varied from 2.46 μs to 770 ns,while the repetition rate varied from 92.76 kHz to 106.6 kHz with an increasing input pumping range from 154 mW to 300 mW.The maximum output power and pulse energy of 15.05 mW and 141.18 nJ were obtained at the maximum input power of 300 mW,respectively.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
The forthcoming 6G wireless networks have great potential for establishing AI-based networks that can enhance end-to-end connection and manage massive data of real-time networks.Artificial Intelligence(AI)advancements...The forthcoming 6G wireless networks have great potential for establishing AI-based networks that can enhance end-to-end connection and manage massive data of real-time networks.Artificial Intelligence(AI)advancements have contributed to the development of several innovative technologies by providing sophisticated specific AI mathematical models such as machine learning models,deep learning models,and hybrid models.Furthermore,intelligent resource management allows for self-configuration and autonomous decision-making capabilities of AI methods,which in turn improves the performance of 6G networks.Hence,6G networks rely substantially on AI methods to manage resources.This paper comprehensively surveys the recent work of AI methods-based resource management for 6G networks.Firstly,the AI methods are categorized into Deep Learning(DL),Federated Learning(FL),Reinforcement Learning(RL),and Evolutionary Learning(EL).Then,we analyze the AI approaches according to optimization issues such as user association,channel allocation,power allocation,and mode selection.Thereafter,we provide appropriate solutions to the most significant problems with the existing approaches of AI-based resource management.Finally,various open issues and potential trends related to AI-based resource management applications are presented.In summary,this survey enables researchers to understand these advancements thoroughly and quickly identify remaining challenges that need further investigation.展开更多
Following publication of the original article[1],the authors found that they pasted the same data when drawing XRD for sample NCO-1 and NCO-2 in Fig.2a,however,the XRD of all four samples in the manuscript was tested,...Following publication of the original article[1],the authors found that they pasted the same data when drawing XRD for sample NCO-1 and NCO-2 in Fig.2a,however,the XRD of all four samples in the manuscript was tested,and XRD raw data were kept and can be offered.The correct Fig.2 has been provided in this Correction.展开更多
Email communication plays a crucial role in both personal and professional contexts;however,it is frequently compromised by the ongoing challenge of spam,which detracts from productivity and introduces considerable se...Email communication plays a crucial role in both personal and professional contexts;however,it is frequently compromised by the ongoing challenge of spam,which detracts from productivity and introduces considerable security risks.Current spam detection techniques often struggle to keep pace with the evolving tactics employed by spammers,resulting in user dissatisfaction and potential data breaches.To address this issue,we introduce the Divide and Conquer-Generative Adversarial Network Squeeze and Excitation-Based Framework(DaC-GANSAEBF),an innovative deep-learning model designed to identify spam emails.This framework incorporates cutting-edge technologies,such as Generative Adversarial Networks(GAN),Squeeze and Excitation(SAE)modules,and a newly formulated Light Dual Attention(LDA)mechanism,which effectively utilizes both global and local attention to discern intricate patterns within textual data.This approach significantly improves efficiency and accuracy by segmenting scanned email content into smaller,independently evaluated components.The model underwent training and validation using four publicly available benchmark datasets,achieving an impressive average accuracy of 98.87%,outperforming leading methods in the field.These findings underscore the resilience and scalability of DaC-GANSAEBF,positioning it as a viable solution for contemporary spam detection systems.The framework can be easily integrated into existing technologies to enhance user security and reduce the risks associated with spam.展开更多
In this study,a completely different approach to optimization is introduced through the development of a novel metaheuristic algorithm called the Barber Optimization Algorithm(BaOA).Inspired by the human interactions ...In this study,a completely different approach to optimization is introduced through the development of a novel metaheuristic algorithm called the Barber Optimization Algorithm(BaOA).Inspired by the human interactions between barbers and customers,BaOA captures two key processes:the customer’s selection of a hairstyle and the detailed refinement during the haircut.These processes are translated into a mathematical framework that forms the foundation of BaOA,consisting of two critical phases:exploration,representing the creative selection process,and exploitation,which focuses on refining details for optimization.The performance of BaOA is evaluated using 52 standard benchmark functions,including unimodal,high-dimensional multimodal,fixed-dimensional multimodal,and the Congress on Evolutionary Computation(CEC)2017 test suite.This comprehensive assessment highlights BaOA’s ability to balance exploration and exploitation effectively,resulting in high-quality solutions.A comparative analysis against twelve widely known metaheuristic algorithms further demonstrates BaOA’s superior performance,as it consistently delivers better results across most benchmark functions.To validate its real-world applicability,BaOA is tested on four engineering design problems,illustrating its capability to address practical challenges with remarkable efficiency.The results confirm BaOA’s versatility and reliability as an optimization tool.This study not only introduces an innovative algorithm but also establishes its effectiveness in solving complex problems,providing a foundation for future research and applications in diverse scientific and engineering domains.展开更多
In this paper, a fuzzy behavior-based approach for a three wheeled omnidirectional mobile robot(TWOMR) navigation has been proposed. The robot has to track either static or dynamic target while avoiding either static ...In this paper, a fuzzy behavior-based approach for a three wheeled omnidirectional mobile robot(TWOMR) navigation has been proposed. The robot has to track either static or dynamic target while avoiding either static or dynamic obstacles along its path. A simple controller design is adopted, and to do so, two fuzzy behaviors "Track the Target" and "Avoid Obstacles and Wall Following" are considered based on reduced rule bases(six and five rules respectively). This strategy employs a system of five ultrasonic sensors which provide the necessary information about obstacles in the environment. Simulation platform was designed to demonstrate the effectiveness of the proposed approach.展开更多
We propose a position sensorless control scheme for a four-switch,three-phase brushless DC motor drive,based on the zero crossing point detection of phase back-EMF voltages using newly defined error functions(EFs). Th...We propose a position sensorless control scheme for a four-switch,three-phase brushless DC motor drive,based on the zero crossing point detection of phase back-EMF voltages using newly defined error functions(EFs). The commutation in-stants are 30° after detected zero crossing points of the EFs. Developed EFs have greater magnitude rather than phase or line voltages so that the sensorless control can work at a lower speed range. Moreover,EFs have smooth transitions around zero voltage level that reduces the commutation errors. EFs are derived from the filtered terminal voltages vao and vbo of two low-pass filters,which are used to eliminate high frequency noises for calculation of the average terminal voltages. The feasibility of the proposed sensorless control is demonstrated by simulation and experimental results.展开更多
基金funded by the Geran Universiti Penyelidikan(GUP),under the grant number GUP-2022-011 funded by the Universiti Kebangsaan Malaysia。
文摘This study presents a detailed comparative analysis of three electron transport layer(ETL)materials for perovskite solar cells(PSCs),namely titanium dioxide(TiO_(2)),barium titanate(BaTiO_(3)or BTO),and strontium-doped barium titan-ate(Ba_(1−x)Sr_(x)TiO_(3)or BST),and their impact on the quantum efficiency(QE)and power conversion efficiency(PCE)of CH_(3)NH_(3)PbI_(3)(MAPbI_(3))PSCs.The optimized structure demonstrates that devices utilizing BST as an ETL achieved the highest PCE of 29.85%,exhibiting superior thermal stability with the lowest temperature coefficient of−0.43%/K.This temperature-induced degradation is comparable to that of commercially available silicon cells.Furthermore,BST-based ETLs show 29.50%and 26.48%higher PCE than those of TiO_(2)-based and BTO-based ETLs.The enhanced internal QE and favorable current density–voltage(J–V)characteristics of BST compared with those of TiO_(2)and BTO are attributed to its improved charge carrier separation,reduced recombination rates,and robust electrical characteristics under varied environmental conditions.Furthermore,the electric field and generation rate of the BST-based ETLs show a more favorable distribution than those of the TiO_(2)-based and BTO-based ETLs.These findings provide significant insights into the role of different ETLs in enhancing QE,indicating that BST is a superior ETL that enhances both the efficiency and stability of PSCs.This study contributes to the understanding of how perovskite-structured ETLs can be used to design and optimize highly efficient and stable photovoltaic devices.
基金funded by Maranatha Christian University,Bandung,Indonesia for Productive Lecturer Research under grant number:011/SK/ADD/UKM/IV/2024.
文摘Objective:To assess the effects of turmeric extract and its compounds on oxidative stress,inflammation,and apoptosis in acetaminophen-induced liver injury.Methods:HepG2 cells were administered with acetaminophen(40 mM)to induce hepatotoxicity,followed by treatment with turmeric extract and its isolated compounds including curcumin,demethoxycurcumin,bis-demethoxycurcumin and ar-turmerone at 5,25,and 125μg/mL.IL-1β,IL-6,and IL-10 levels were quantified with ELISA kits.Further,qRT-PCR was used to analyze the mRNA expression of JNK,Casp-9,and Casp-3.Meanwhile,the levels of nitric oxide and lactate dehydrogenase were analyzed using colorimetric assay.Results:Acetaminophen administration caused an increase in the levels of lactate dehydrogenase,nitric oxide,IL-1β,IL-6,and the mRNA expression of JNK,Casp-9,and Casp-3 in HepG2 cells while reducing IL-10 levels.Treatment with turmeric extract,curcumin,demethoxycurcumin,bis-demethoxycurcumin,and ar-turmerone lowered IL-1β,IL-6,nitric oxide,and lactate dehydrogenase levels,downregulated the mRNA expression of JNK,Casp-9,and Casp-3,and increased IL-10 levels.Conclusions:Turmeric extract and its compounds have significant hepatoprotective activity and could be further explored for the treatment of liver damage.
文摘This paper proposes to study the impacts of electrical line losses due to the connection of distributed generators (DG) to 22kV distribution system of Provincial Electricity Authority (PEA). Data of geographic information systems (GIS) including the distance of distribution line and location of load being key parameter of PEA is simulated using digital simulation and electrical network calculation program (DIgSILENT) to analyze power loss of the distribution system. In addition, the capacity and location of DG installed into the distribution system is considered. The results are shown that, when DG is installed close to the substation, the electrical line losses are reduced. However, if DG capacity becomes larger and the distance between DG and load is longer, the electrical line losses tend to increase. The results of this paper can be used to create the suitability and fairness of the fee for both DG and utility.
文摘Multi-phase machines are so attractive for electrical machine designers because of their valuable advantages such as high reliability and fault tolerant ability.Meanwhile,fractional slot concentrated windings(FSCW)are well known because of short end winding length,simple structure,field weakening sufficiency,fault tolerant capability and higher slot fill factor.The five-phase machines equipped with FSCW,are very good candidates for the purpose of designing motors for high reliable applications,like electric cars,major transporting buses,high speed trains and massive trucks.But,in comparison to the general distributed windings,the FSCWs contain high magnetomotive force(MMF)space harmonic contents,which cause unwanted effects on the machine ability,such as localized iron saturation and core losses.This manuscript introduces several new five-phase fractional slot winding layouts,by the means of slot shifting concept in order to design the new types of synchronous reluctance motors(SynRels).In order to examine the proposed winding’s performances,three sample machines are designed as case studies,and analytical study and finite element analysis(FEA)is used for validation.
文摘Over the past years,many efforts have been accomplished to achieve fast and accurate meta-heuristic algorithms to optimize a variety of real-world problems.This study presents a new optimization method based on an unusual geological phenomenon in nature,named Geyser inspired Algorithm(GEA).The mathematical modeling of this geological phenomenon is carried out to have a better understanding of the optimization process.The efficiency and accuracy of GEA are verified using statistical examination and convergence rate comparison on numerous CEC 2005,CEC 2014,CEC 2017,and real-parameter benchmark functions.Moreover,GEA has been applied to several real-parameter engineering optimization problems to evaluate its effectiveness.In addition,to demonstrate the applicability and robustness of GEA,a comprehensive investigation is performed for a fair comparison with other standard optimization methods.The results demonstrate that GEA is noticeably prosperous in reaching the optimal solutions with a high convergence rate in comparison with other well-known nature-inspired algorithms,including ABC,BBO,PSO,and RCGA.Note that the source code of the GEA is publicly available at https://www.optim-app.com/projects/gea.
文摘The research aimed to propose a non-destructive technology to control subterranean termites Coptotermes curvignathus Holmgren infestation based on electromagnetic waves. A portable apparatus for this technology has been built and its experiment is presented in this paper. Some electrical parameters were measured and analyzed along with their effects to the termites. The experiment using frequency range between 30 Hz - 600 kHz has been done. The average error of the apparatus by comparing the result with the direct measurement using oscilloscope was also measured. The highest error value appeared at 600 kHz with frequency error 6.05 kHz. The highest error of voltage (i.e. 0.186 Volt) appeared at 100 kHz. For safetiness, the highest magnetic field at 300 kHz was 0.1815 μT and at 500 kHz was 0.00725 μT which were safe for human. The average value of termites mortality was higher on irradiation time 120 minutes than 60 minutes respectively in all test frequency: 300 kHz, 400 kHz, 500 kHz and 600 kHz. This paper presents an important information of the electromagnatic-based technology for environmental friendly termites control in spite of using the insecticides.
文摘Quantum resources such as entanglement and coherence are the holy grail for modern quantum technologies. Although the unwanted environmental effects tackle quantum information processing tasks, suprisingly these key quantum resources may be protected and even enhanced by the implementation of some special hybrid open quantum systems. Here, we aim to show how a dissipative atom-cavity-system can be accomplished to generate enhanced quantum resources.To do so, we consider a couple of dissipative cavities, where each one contains two effective two-level atoms interacting with a single-mode cavity field. In practical applications, a classical laser field may be applied to drive each atomic subsystem. After driving the system, a Bell-state measurement is performed on the output of the system to quantify the entanglement and coherence. The obtained results reveal that the remote entanglement and coherence between the atoms existing inside the two distant cavities are not only enhanced, but can be stabilized, even under the action of dissipation. In contrast, the local entanglement between two atoms inside each dissipative cavity attenuates due to the presence of unwanted environmental effects.Nevertheless, the local coherence may show the same behavior as the remote coherence.Besides, the system provides the steady state entanglement in various interaction regimes,particularly in the strong atom-cavity coupling and with relatively large detuning. More interestingly, our numerical analyses demonstrate that the system may show a memory effect due to the fact that the death and revival of the entanglement take place during the interaction. Our proposed model may find potential applications for the implementation of long distance quantum networks. In particular, it facilitates the distribution of quantum resources between the nodes of large-scale quantum networks for secure communication.
基金the Researchers Supporting Project Number(RSP2023R 102)King Saud University,Riyadh,Saudi Arabia.
文摘Recently,nano-systems based on molecular communications via diffusion(MCvD)have been implemented in a variety of nanomedical applications,most notably in targeted drug delivery system(TDDS)scenarios.Furthermore,because the MCvD is unreliable and there exists molecular noise and inter symbol interference(ISI),cooperative nano-relays can acquire the reliability for drug delivery to targeted diseased cells,especially if the separation distance between the nano transmitter and nano receiver is increased.In this work,we propose an approach for optimizing the performance of the nano system using cooperative molecular communications with a nano relay scheme,while accounting for blood flow effects in terms of drift velocity.The fractions of the molecular drug that should be allocated to the nano transmitter and nano relay positioning are computed using a collaborative optimization problem solved by theModified Central Force Optimization(MCFO)algorithm.Unlike the previous work,the probability of bit error is expressed in a closed-form expression.It is used as an objective function to determine the optimal velocity of the drug molecules and the detection threshold at the nano receiver.The simulation results show that the probability of bit error can be dramatically reduced by optimizing the drift velocity,detection threshold,location of the nano-relay in the proposed nano system,and molecular drug budget.
文摘Spirulina platensis is a special and unique cyanobacteria that is produced worldwide with a varied cost of cultivation media. In this study, five main experiments with different treatments were performed to evaluate the possibility of using cheap aquaculture water for Spirulina production, to test if solutions made by plant ash (PAS) could be used for Spirulina production, to determine if brackish water (BW) and mining water have a good impact on Spirulina production, to create a medium composed of cheap chemicals and fertilizers to be used for Spirulina cultivation, and to test if a mixture made from local components could be used to produce Spirulina. All experiments were performed via growth and dry weight measurements, including determination of chemical and physical characteristics of the samples with a comparison with Zarrouk medium (ZM) as a reference for each experiment, and all experiments were performed for 21 days to determine the best media type that lasts longer for commercial purposes. In all experiments, pH values were between 8 and 11, and EC was between 9.8 and 30 ms/cm, while temperature was at 30°C and 35°C, and light was at 1500 and 5000 Lux for 16 h light and 8 h dark. Spirulina can grow in (FW). It can also grow in FW diluted with BW. Also a 3% PAS can be used as a source to cultivate Spirulina at a very low price compared to ZM. The chemical fertilizer formula was one of the best types among all treatments with a good price. A mixture of these local resources could be a very good cheap alternative source. The main result that was obtained from all experiments in this study is the ability of Spirulina to grow within a wide range of chemical parameters at a lower price.
文摘Purpose–Material selection,driven by wide and often conflicting objectives,is an important,sometimes difficult problem in material engineering.In this context,multi-criteria decision-making(MCDM)methodologies are effective.An approach of MCDM is needed to cater to criteria of material assortment simultaneously.More firms are now concerned about increasing their productivity using mathematical tools.To occupy a gap in the previous literature this research recommends an integrated MCDM and mathematical Bi-objective model for the selection of material.In addition,by using the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS),the inherent ambiguities of decision-makers in paired evaluations are considered in this research.It goes on to construct a mathematical bi-objective model for determining the best item to purchase.Design/methodology/approach–The entropy perspective is implemented in this paper to evaluate the weight parameters,while the TOPSIS technique is used to determine the best and worst intermediate pipe materials for automotive exhaust system.The intermediate pipes are used to join the components of the exhaust systems.The materials usually used to manufacture intermediate pipe are SUS 436LM,SUS 430,SUS 304,SUS 436L,SUH 409 L,SUS 441 L and SUS 439L.These seven materials are evaluated based on tensile strength(TS),hardness(H),elongation(E),yield strength(YS)and cost(C).A hybrid methodology combining entropy-based criteria weighting,with the TOPSIS for alternative ranking,is pursued to identify the optimal design material for an engineered application in this paper.This study aims to help while filling the information gap in selecting the most suitable material for use in the exhaust intermediate pipes.After that,the authors searched for and considered eight materials and evaluated them on the following five criteria:(1)TS,(2)YS,(3)H,(4)E and(5)C.The first two criteria have been chosen because they can have a lot of influence on the behavior of the exhaust intermediate pipes,on their performance and on the cost.In this structure,the weights of the criteria are calculated objectively through the entropy method in order to have an unbiased assessment.This essentially measures the quantity of information each criterion contribution,indicating the relative importance of these criteria better.Subsequently,the materials were ranked using the TOPSIS method in terms of their relative performance by measuring each material from an ideal solution to determine the best alternative.The results show that SUS 309,SUS 432L and SUS 436 LM are the first three materials that the exhaust intermediate pipe optimal design should consider.Findings–The material matrix of the decision presented in Table 3 was normalized through Equation 5,as shown in Table 5,and the matrix was multiplied with weighting criteriaß_j.The obtained weighted normalized matrix V_ij is presented in Table 6.However,the ideal,worst and best value was ascertained by employing Equation 7.This study is based on the selection of material for the development of intermediate pipe using MCDM,and it involves four basic stages,i.e.method of translation criteria,screening process,method of ranking and search for methods.The selection was done through the TOPSIS method,and the criteria weight was obtained by the entropy method.The result showed that the top three materials are SUS 309,SUS 432L and SUS 436 LM,respectively.For the future work,it is suggested to select more alternatives and criteria.The comparison can also be done by using different MCDM techniques like and Choice Expressing Reality(ELECTRE),Decision-Making Trial and Evaluation Laboratory(DEMATEL)and Preference Ranking Organization Method for Enrichment Evaluation(PROMETHEE).Originality/value–The results provide important conclusions for material selection in this targeted application,verifying the employment of mutual entropy-TOPSIS methodology for a series of difficult engineering decisions in material engineering concepts that combine superior capacity with better performance as well as cost-efficiency in various engineering design.
文摘This article deals with the methods of finding partial discharge(PD)location in power transformers using ultra high frequency(UHF)measurements.The UHF technique utilises two methods to find the PD location,that is,the shortest path method and hyperbolic method.The shortest path method works based on the comparison of the measured data and the ones in the database.In the hyperbolic method,a hyperbolic equation is obtained between each two element subset of sensors.The coordinate that best fits all equations is known as the PD location,and can be obtained in three different ways,that is,iterative algorithms,the Fang method and Chan method.The convergence of iterative algorithms is limited by poor initial estimate,overshoot,mitigation of non-convergence etc.The Fang and Chan methods are two closed-form solutions that are used in the communication system to find the radiation source location.This article explains how to use these two methods to obtain the PD coordinate inside the power transformer.These two methods can find exactly the coordinate that best fits all hyperbolic equations.At the end of this article,several tests are carried out through CST software and the PD locations is estimated by all presented methods.The simulation results show how the Fang and Chan methods can overcome the limitations of the iterative method.
基金extend their appreciation to the King Salman Center for Disability Research for funding this work through Research Group No.KSRG-2024-223.
文摘Epilepsy is a long-term neurological condition marked by recurrent seizures,which result from abnormal electrical activity in the brain that disrupts its normal functioning.Traditional methods for detecting epilepsy through machine learning typically utilize discrete-time models,which inadequately represent the continuous dynamics of electroencephalogram(EEG)signals.To overcome this limitation,we introduce an innovative approach that employs Neural Ordinary Differential Equations(NODEs)to model EEG signals as continuous-time systems.This allows for effective management of irregular sampling and intricate temporal patterns.In contrast to conventional techniques,such as Convolutional Neural Networks(CNNs)and Recurrent Neural Networks(RNNs),which necessitate fixedlength inputs and often struggle with long-term dependencies,our framework incorporates:(1)a NODE block to capture continuous-time EEG dynamics,(2)a feature extraction module tailored for seizure-specific patterns,and(3)an attention-based fusion mechanism to enhance interpretability in classification.When evaluated on three publicly accessible EEG datasets,including those from Boston Children’s Hospital and the Massachusetts Institute of Technology(CHB-MIT)and the Temple University Hospital(TUH)EEG Corpus,the model demonstrated an average accuracy of 98.2%,a sensitivity of 97.8%,a specificity of 98.3%,and an F1-score of 97.9%.Additionally,the inference latency was reduced by approximately 30%compared to standard CNN and Long Short-Term Memory(LSTM)architectures,making it well-suited for real-time applications.The method’s resilience to noise and its adaptability to irregular sampling enhance its potential for clinical use in real-time settings.
文摘We demonstrated a new type of MAX phase material,chromium titanium aluminum carbide(Cr_(2)TiAlC_(2)) polymer film,to generate a passively Q-switched erbium-doped fiber laser(EDFL).The film thickness was measured to be around 45 μm,which was fabricated using the embedding method with polyvinyl alcohol(PVA) polymer as hoster.The saturable absorber(SA) film demonstrates a dual-wavelength passively Q-switched EDFL which operates at 1 531 nm and 1 560.19 nm,respectively.The Q-switching pulse duration could be varied from 2.46 μs to 770 ns,while the repetition rate varied from 92.76 kHz to 106.6 kHz with an increasing input pumping range from 154 mW to 300 mW.The maximum output power and pulse energy of 15.05 mW and 141.18 nJ were obtained at the maximum input power of 300 mW,respectively.
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.
基金funded by Universiti Kebangsaan Malaysia,Fundamental Research Grant Scheme having Grant number FRGS/1/2023/ICT07/UKM/02/1Universiti Kebangsaan Malaysia Geran Universiti Penyelidikan having Grant number GUP-2024-009.
文摘The forthcoming 6G wireless networks have great potential for establishing AI-based networks that can enhance end-to-end connection and manage massive data of real-time networks.Artificial Intelligence(AI)advancements have contributed to the development of several innovative technologies by providing sophisticated specific AI mathematical models such as machine learning models,deep learning models,and hybrid models.Furthermore,intelligent resource management allows for self-configuration and autonomous decision-making capabilities of AI methods,which in turn improves the performance of 6G networks.Hence,6G networks rely substantially on AI methods to manage resources.This paper comprehensively surveys the recent work of AI methods-based resource management for 6G networks.Firstly,the AI methods are categorized into Deep Learning(DL),Federated Learning(FL),Reinforcement Learning(RL),and Evolutionary Learning(EL).Then,we analyze the AI approaches according to optimization issues such as user association,channel allocation,power allocation,and mode selection.Thereafter,we provide appropriate solutions to the most significant problems with the existing approaches of AI-based resource management.Finally,various open issues and potential trends related to AI-based resource management applications are presented.In summary,this survey enables researchers to understand these advancements thoroughly and quickly identify remaining challenges that need further investigation.
文摘Following publication of the original article[1],the authors found that they pasted the same data when drawing XRD for sample NCO-1 and NCO-2 in Fig.2a,however,the XRD of all four samples in the manuscript was tested,and XRD raw data were kept and can be offered.The correct Fig.2 has been provided in this Correction.
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,Saudi Arabia under Grant No.(GPIP:71-829-2024).
文摘Email communication plays a crucial role in both personal and professional contexts;however,it is frequently compromised by the ongoing challenge of spam,which detracts from productivity and introduces considerable security risks.Current spam detection techniques often struggle to keep pace with the evolving tactics employed by spammers,resulting in user dissatisfaction and potential data breaches.To address this issue,we introduce the Divide and Conquer-Generative Adversarial Network Squeeze and Excitation-Based Framework(DaC-GANSAEBF),an innovative deep-learning model designed to identify spam emails.This framework incorporates cutting-edge technologies,such as Generative Adversarial Networks(GAN),Squeeze and Excitation(SAE)modules,and a newly formulated Light Dual Attention(LDA)mechanism,which effectively utilizes both global and local attention to discern intricate patterns within textual data.This approach significantly improves efficiency and accuracy by segmenting scanned email content into smaller,independently evaluated components.The model underwent training and validation using four publicly available benchmark datasets,achieving an impressive average accuracy of 98.87%,outperforming leading methods in the field.These findings underscore the resilience and scalability of DaC-GANSAEBF,positioning it as a viable solution for contemporary spam detection systems.The framework can be easily integrated into existing technologies to enhance user security and reduce the risks associated with spam.
文摘In this study,a completely different approach to optimization is introduced through the development of a novel metaheuristic algorithm called the Barber Optimization Algorithm(BaOA).Inspired by the human interactions between barbers and customers,BaOA captures two key processes:the customer’s selection of a hairstyle and the detailed refinement during the haircut.These processes are translated into a mathematical framework that forms the foundation of BaOA,consisting of two critical phases:exploration,representing the creative selection process,and exploitation,which focuses on refining details for optimization.The performance of BaOA is evaluated using 52 standard benchmark functions,including unimodal,high-dimensional multimodal,fixed-dimensional multimodal,and the Congress on Evolutionary Computation(CEC)2017 test suite.This comprehensive assessment highlights BaOA’s ability to balance exploration and exploitation effectively,resulting in high-quality solutions.A comparative analysis against twelve widely known metaheuristic algorithms further demonstrates BaOA’s superior performance,as it consistently delivers better results across most benchmark functions.To validate its real-world applicability,BaOA is tested on four engineering design problems,illustrating its capability to address practical challenges with remarkable efficiency.The results confirm BaOA’s versatility and reliability as an optimization tool.This study not only introduces an innovative algorithm but also establishes its effectiveness in solving complex problems,providing a foundation for future research and applications in diverse scientific and engineering domains.
文摘In this paper, a fuzzy behavior-based approach for a three wheeled omnidirectional mobile robot(TWOMR) navigation has been proposed. The robot has to track either static or dynamic target while avoiding either static or dynamic obstacles along its path. A simple controller design is adopted, and to do so, two fuzzy behaviors "Track the Target" and "Avoid Obstacles and Wall Following" are considered based on reduced rule bases(six and five rules respectively). This strategy employs a system of five ultrasonic sensors which provide the necessary information about obstacles in the environment. Simulation platform was designed to demonstrate the effectiveness of the proposed approach.
文摘We propose a position sensorless control scheme for a four-switch,three-phase brushless DC motor drive,based on the zero crossing point detection of phase back-EMF voltages using newly defined error functions(EFs). The commutation in-stants are 30° after detected zero crossing points of the EFs. Developed EFs have greater magnitude rather than phase or line voltages so that the sensorless control can work at a lower speed range. Moreover,EFs have smooth transitions around zero voltage level that reduces the commutation errors. EFs are derived from the filtered terminal voltages vao and vbo of two low-pass filters,which are used to eliminate high frequency noises for calculation of the average terminal voltages. The feasibility of the proposed sensorless control is demonstrated by simulation and experimental results.
