This paper introduces two meta-heuristic approaches utilizing Swarm Intelligence and ant colony optimization techniques. The strategy comprises applying smart routing technology to optimize a dynamic IoT network computed path. The issue of route selection to achieve the target and critical factors such as network energy, left energy in each gadget, run out IoT nodes count has been explored. After rigorous iterations extending up to 1000, the simulation has yielded results for two distinctive routing approaches. The ABED (ACO- Breadth first search- Euclidean- Dynamic) and the ADED (ACODijkstra algorithm -Euclidean- Dynamic) have simulated and compared their network efficiencies using MATLAB. At node 200, ABED exhibits a performance advantage over ADED of 1.6%. This efficiency differential between ABED and ADED expands to 2.9% at 300 nodes and further to 2.6% at 400 nodes. Furthermore, ABED showcases superior network stability in routing techniques compared to ADED. Specifically, ABED's routing technique achieves a more consistent network compared to ADED. In networks comprising 500 nodes, ABED surpasses ADED by 13.33% in the context of HND (Half Node Dead) and by 6.7% in the case of LND (Last Node Dead).
{"title":"Intelligent Routing Approaches Based on Ant Colony Optimization for\u0000Dynamic Internet of Things Network","authors":"Anukriti Sharma, Sharad Sharma, Dushyant Gupta, Neeru Kashyap, Raj Kumar, Sunil Kumar","doi":"10.2174/0123520965316826240705072158","DOIUrl":"https://doi.org/10.2174/0123520965316826240705072158","url":null,"abstract":"\u0000\u0000This paper introduces two meta-heuristic approaches utilizing Swarm\u0000Intelligence and ant colony optimization techniques. The strategy comprises applying smart routing technology to optimize a dynamic IoT network computed path.\u0000\u0000\u0000\u0000The issue of route selection to achieve the target and critical factors such as network energy, left energy in each gadget, run out IoT nodes count has been explored. After rigorous iterations extending up to 1000, the simulation has yielded results for two distinctive routing approaches. The ABED (ACO- Breadth first search- Euclidean- Dynamic) and the ADED (ACODijkstra algorithm -Euclidean- Dynamic) have simulated and compared their network efficiencies\u0000using MATLAB.\u0000\u0000\u0000\u0000At node 200, ABED exhibits a performance advantage over ADED of 1.6%. This efficiency differential between ABED and ADED expands to 2.9% at 300 nodes and further to 2.6%\u0000at 400 nodes. Furthermore, ABED showcases superior network stability in routing techniques\u0000compared to ADED. Specifically, ABED's routing technique achieves a more consistent network\u0000compared to ADED.\u0000\u0000\u0000\u0000In networks comprising 500 nodes, ABED surpasses ADED by 13.33% in the context of HND (Half Node Dead) and by 6.7% in the case of LND (Last Node Dead).\u0000","PeriodicalId":506996,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering)","volume":" 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-15DOI: 10.2174/0123520965304622240703052236
Yao Zhou, Jianbo He, Wuqiang Yu, Xueming Shen, Fengbin Wu, Xiaobin He, Zuopeng Li, Wenjun Ning
Tree-contact single-phase-to-ground fault (TSF) is a kind of common fault in the distribution grid. Since the initial electrical signal of TSF is weak, it is difficult to detect and remove it in time. Finally, it may evolve into more severe faults such as arc faults. Therefore, establishing a numerical model capable of depicting the trend of TSF transition resistance can contribute to clarifying the development of TSF and provide a reference for early fault detection. The moisture content of branches is one of the important factors affecting TSF development, yet the mechanism of moisture content affecting the fault development is still ambiguous. In order to explore the fault development process of branches with various moisture content, a TSF experimental platform of a 10kV distribution network line is built to evolve a characteristic curve of transition resistance influenced by moisture content and the temperature change curve during the development of TSF. Based on the experimental data, a numerical model of TSF transition resistance considering moisture content of trees is established. According to the trend of experimental data, a segmented model with the first peak of leakage current as the dividing point is established. The segmented model takes the change of tree resistivity with temperature as the core, reduces the dependence on the traditional empirical parameters, and improves the fitting degree with different tree branch parameters. The improved model has a higher matching degree with the experimental measurement data. The comparison between simulation results and experimental data shows that the improved model can efficiently predict the development process of TSF transition resistance under various tree parameters.
{"title":"Numerical Simulation of Transition Resistance for TSF: Influence of Moisture Content","authors":"Yao Zhou, Jianbo He, Wuqiang Yu, Xueming Shen, Fengbin Wu, Xiaobin He, Zuopeng Li, Wenjun Ning","doi":"10.2174/0123520965304622240703052236","DOIUrl":"https://doi.org/10.2174/0123520965304622240703052236","url":null,"abstract":"\u0000\u0000Tree-contact single-phase-to-ground fault (TSF) is a kind of common\u0000fault in the distribution grid. Since the initial electrical signal of TSF is weak, it is difficult to detect\u0000and remove it in time. Finally, it may evolve into more severe faults such as arc faults.\u0000\u0000\u0000\u0000Therefore, establishing a numerical model capable of depicting the trend of TSF transition\u0000resistance can contribute to clarifying the development of TSF and provide a reference for\u0000early fault detection. The moisture content of branches is one of the important factors affecting\u0000TSF development, yet the mechanism of moisture content affecting the fault development is still\u0000ambiguous.\u0000\u0000\u0000\u0000In order to explore the fault development process of branches with various moisture\u0000content, a TSF experimental platform of a 10kV distribution network line is built to evolve a\u0000characteristic curve of transition resistance influenced by moisture content and the temperature\u0000change curve during the development of TSF. Based on the experimental data, a numerical model\u0000of TSF transition resistance considering moisture content of trees is established. According to the\u0000trend of experimental data, a segmented model with the first peak of leakage current as the dividing\u0000point is established.\u0000\u0000\u0000\u0000The segmented model takes the change of tree resistivity with temperature as the core,\u0000reduces the dependence on the traditional empirical parameters, and improves the fitting degree\u0000with different tree branch parameters. The improved model has a higher matching degree with\u0000the experimental measurement data.\u0000\u0000\u0000\u0000The comparison between simulation results and experimental data shows that the\u0000improved model can efficiently predict the development process of TSF transition resistance under\u0000various tree parameters.\u0000","PeriodicalId":506996,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering)","volume":" 44","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141832895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-04DOI: 10.2174/0123520965291435240508111712
G. Ansari, S. S. Bhat, Mohd Dilshad Ansari
Diabetes has been rising in recent years and prior research has demonstrated Machine Learning Techniques (MLTs) to be useful tools for predicting diabetes. This research has examined the accuracy of six different MLTs for predicting diabetes using lifestyle data gathered from UCI (University of California). To improve medical outcomes and prevent its onset, the prediction of diabetes is necessary. This research has proposed a new framework based on the early detection of diabetes using lifestyle factors. Various MLTs, such as Logistic Regression (LR), Decision Tree Classification (DTC), Random Forest Classification (RFC), Support Vector Classification (SVC), and K-Nearest Classification (KNC) have been used for tenfold cross-validation and the results obtained from different techniques have been verified. Among all classification techniques, LR has achieved the highest accuracy of 93%, the precision of 92%, the recall score of 94%, the F1 score of 93%, and the weighted average of 90%, respectively. The proposed framework is utilized by the healthcare sector to predict diabetes early. It can also be used with datasets from various sectors that share diabetes-related data. In this paper, we have used the proposed framework to predict diabetes mellitus in the healthcare system, diagnose various ailments, and assess if MLA performs well. The proposed system has been developed based on the MLT for the classification of DM. An intelligent framework for Diabetes Mellitus (DM) that has been developed using MLT illustrates the full workflow from data input to output. The five algorithms, Logistic Regression (LR), Decision Tree Classification (DTC), Random Forest Classification (RFC), Support Vector Classification (SVC), and K-Nearest Classification (KNC), have been compared in terms of accuracy, precision, recall, and F1 score. Results from the experimental setting using MLTs for DM prediction based on lifestyle predictors have been obtained. Descriptive statistics of lifestyle characteristics have been displayed along with their corresponding metrics, such as mean, standard deviation, minimum, maximum, etc. For instance, the age parameters’ mean, standard, and minimum at 25%, 50%, 75%, and maximum values were as follows: 520.0, 48.02, 12.151, 16.0, 39.0, 47.5, 57.0, and 90.0 respectively, as shown in Fig. (10). Feature engineering is crucial to the process of constructing MLT. Insignificant or incorrect characteristics may have a negative impact on the way a model runs. The training time is drastically reduced and accuracy is increased with careful feature selection. In machine learning frameworks, some feature selection strategies include embedding, filter, wrapper, embedded, and hybrid techniques. An alarming number of people around the world suffer from the chronic and dangerous disease of diabetes. Using MLT, early DM prediction-based biological variables have been obtained in this research work. Data on patients’ lifestyles have been thoroug
{"title":"Machine Learning Techniques for Diabetes Mellitus Based on Lifestyle Predictors","authors":"G. Ansari, S. S. Bhat, Mohd Dilshad Ansari","doi":"10.2174/0123520965291435240508111712","DOIUrl":"https://doi.org/10.2174/0123520965291435240508111712","url":null,"abstract":"\u0000\u0000Diabetes has been rising in recent years and prior research has demonstrated\u0000Machine Learning Techniques (MLTs) to be useful tools for predicting diabetes. This research\u0000has examined the accuracy of six different MLTs for predicting diabetes using lifestyle\u0000data gathered from UCI (University of California). To improve medical outcomes and prevent its\u0000onset, the prediction of diabetes is necessary. This research has proposed a new framework based\u0000on the early detection of diabetes using lifestyle factors. Various MLTs, such as Logistic Regression\u0000(LR), Decision Tree Classification (DTC), Random Forest Classification (RFC), Support\u0000Vector Classification (SVC), and K-Nearest Classification (KNC) have been used for tenfold\u0000cross-validation and the results obtained from different techniques have been verified. Among all\u0000classification techniques, LR has achieved the highest accuracy of 93%, the precision of 92%, the\u0000recall score of 94%, the F1 score of 93%, and the weighted average of 90%, respectively. The\u0000proposed framework is utilized by the healthcare sector to predict diabetes early. It can also be\u0000used with datasets from various sectors that share diabetes-related data.\u0000\u0000\u0000\u0000In this paper, we have used the proposed framework to predict diabetes mellitus in the\u0000healthcare system, diagnose various ailments, and assess if MLA performs well. The proposed\u0000system has been developed based on the MLT for the classification of DM. An intelligent framework\u0000for Diabetes Mellitus (DM) that has been developed using MLT illustrates the full workflow from\u0000data input to output. The five algorithms, Logistic Regression (LR), Decision Tree Classification\u0000(DTC), Random Forest Classification (RFC), Support Vector Classification (SVC), and K-Nearest\u0000Classification (KNC), have been compared in terms of accuracy, precision, recall, and F1 score.\u0000\u0000\u0000\u0000Results from the experimental setting using MLTs for DM prediction based on lifestyle\u0000predictors have been obtained. Descriptive statistics of lifestyle characteristics have been displayed\u0000along with their corresponding metrics, such as mean, standard deviation, minimum, maximum,\u0000etc. For instance, the age parameters’ mean, standard, and minimum at 25%, 50%, 75%, and\u0000maximum values were as follows: 520.0, 48.02, 12.151, 16.0, 39.0, 47.5, 57.0, and 90.0 respectively,\u0000as shown in Fig. (10). Feature engineering is crucial to the process of constructing MLT. Insignificant\u0000or incorrect characteristics may have a negative impact on the way a model runs. The training\u0000time is drastically reduced and accuracy is increased with careful feature selection. In machine learning\u0000frameworks, some feature selection strategies include embedding, filter, wrapper, embedded, and\u0000hybrid techniques. An alarming number of people around the world suffer from the chronic and dangerous\u0000disease of diabetes. Using MLT, early DM prediction-based biological variables have been\u0000obtained in this research work. Data on patients’ lifestyles have been thoroug","PeriodicalId":506996,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering)","volume":" 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141679377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-04DOI: 10.2174/0123520965308169240616144800
Muskan Dixit, I. Kansal, Vikas Khullar, Rajeev Kumar, Sunil Kumar
Artificial intelligence (AI) has become an important driver in the current dynamic technological environment, presenting itself as a revolutionary power capable of reconfiguring various sectors, economies, and social structures. The paper aims to address a wide range of readers, encompassing AI practitioners, academics, and people in general. Its primary objective is to connect the complex technical aspects of AI and the ethical problems inherent in its creation and implementation. In an era marked by the growing integration of AI systems into various aspects of human existence, the book offers fundamental ideas that contribute to cultivating an environment where these systems function with transparency, ethical considerations, and reliability. The paper's comprehensive coverage spans various subjects that contribute to a complete comprehension of the intricate terrain of reliable AI. The analysis is initiated by conducting an indepth examination of the architectural aspects of AI systems, elucidating the progression from the input of data to the generation of decision-making outcomes. The text introduces the core functions of AI, explores its conceptual framework, and emphasizes the significance of data processing modules, computations, Machine Learning models (ML), and integrating software. This foundational framework establishes a basis for subsequent investigation into the pivotal concepts of integrity, trust, and ethics. This paper bravely tackles urgent issues about bias, justice, and the erosion of data privacy while offering practical solutions to increase AI system openness and explainability by 20%. This paper examines various strategies to improve transparency and explainability, recognizing the importance of strengthening user understanding and confidence. Within the realm of healthcare, the paper acquaints readers with the pioneering notion of Federated Deep Learning, which can improve data privacy by up to 30%. This includes a dedicated part that delves into the concept of explainable AI, introducing various methodologies such as LIME and SHAP, which are employed to interpret predictions made by AI models. The paper provides readers with the knowledge to traverse the ever-changing environment of AI safely and ethically. It emphasizes the importance of utilizing AI's transformative potential for improving humanity while maintaining the utmost adherence to ethical principles.
{"title":"Analyzing Trustworthiness and Explainability in Artificial Intelligence: A Comprehensive Review","authors":"Muskan Dixit, I. Kansal, Vikas Khullar, Rajeev Kumar, Sunil Kumar","doi":"10.2174/0123520965308169240616144800","DOIUrl":"https://doi.org/10.2174/0123520965308169240616144800","url":null,"abstract":"\u0000\u0000Artificial intelligence (AI) has become an important driver in the current dynamic\u0000technological environment, presenting itself as a revolutionary power capable of reconfiguring\u0000various sectors, economies, and social structures. The paper aims to address a wide range of\u0000readers, encompassing AI practitioners, academics, and people in general. Its primary objective is\u0000to connect the complex technical aspects of AI and the ethical problems inherent in its creation\u0000and implementation. In an era marked by the growing integration of AI systems into various aspects\u0000of human existence, the book offers fundamental ideas that contribute to cultivating an environment\u0000where these systems function with transparency, ethical considerations, and reliability.\u0000The paper's comprehensive coverage spans various subjects that contribute to a complete comprehension\u0000of the intricate terrain of reliable AI. The analysis is initiated by conducting an indepth\u0000examination of the architectural aspects of AI systems, elucidating the progression from\u0000the input of data to the generation of decision-making outcomes. The text introduces the core\u0000functions of AI, explores its conceptual framework, and emphasizes the significance of data processing\u0000modules, computations, Machine Learning models (ML), and integrating software. This\u0000foundational framework establishes a basis for subsequent investigation into the pivotal concepts\u0000of integrity, trust, and ethics. This paper bravely tackles urgent issues about bias, justice, and the\u0000erosion of data privacy while offering practical solutions to increase AI system openness and\u0000explainability by 20%. This paper examines various strategies to improve transparency and explainability,\u0000recognizing the importance of strengthening user understanding and confidence.\u0000Within the realm of healthcare, the paper acquaints readers with the pioneering notion of Federated\u0000Deep Learning, which can improve data privacy by up to 30%. This includes a dedicated\u0000part that delves into the concept of explainable AI, introducing various methodologies such as\u0000LIME and SHAP, which are employed to interpret predictions made by AI models. The paper\u0000provides readers with the knowledge to traverse the ever-changing environment of AI safely and\u0000ethically. It emphasizes the importance of utilizing AI's transformative potential for improving\u0000humanity while maintaining the utmost adherence to ethical principles.\u0000","PeriodicalId":506996,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering)","volume":" 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141678891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-02DOI: 10.2174/0123520965299128240430041219
Hao Bai, Yu Fu, Guangze Ouyang, Yongxiang Cai, Song Zhang, Yu Miao, Weichen Yang, Min Xu
When the superior power grid fails and loses power, due to the traditional single power supply radial grid structure of low-voltage substation areas, all loads in the lowvoltage substation area will lose power, causing a poor electricity consumption experience for low-voltage users. To enhance the resilience of low-voltage distribution areas against faults and power outages from higher-tier power grids, a collaborative planning and comprehensive evaluation method for grid-forming energy storage systems (GFM-ESS) and flexible interconnection in distribution networks, considering island operation, is proposed. This method integrates GFM-ESS and flexible interconnections, taking islanding operations into account. Firstly, the structure of GFM-ESS and voltage source converters is analyzed. The control modes of GFM-ESS in parallel or off-grid scenarios are also scrutinized. Secondly, minimizing the annual comprehensive cost and the annual power outage load are the objective functions. A bilevel programming model for GFM-ESS and flexible interconnection of lowvoltage distribution networks, considering island operation, has been established. Moreover, a comprehensive evaluation method based on the analytic hierarchy process for proposed lowvoltage distribution network structural schemes is introduced. An evaluation index system is established to assess the rationality of these proposed network structural planning schemes. Finally, the superiority of the proposed collaborative planning method is verified through a comparative analysis of three planning methods. The proposed collaborative planning method can effectively ensure the continuous power supply of low-voltage distribution networks under the fault scenario of the upper power network. Moreover, the rationality of the results obtained from the proposed collaborative planning method is verified through a comprehensive evaluation method of grid structure schemes based on the analytic hierarchy process. The proposed comprehensive evaluation method can determine which two areas are optimal for grid planning. The superiority of the proposed collaborative planning method was verified by comparative analysis of three planning methods. And the rationality of the proposed collaborative planning method results was verified by the comprehensive evaluation method of grid structure schemes based on analytic hierarchy process.
{"title":"Collaborative Planning and Comprehensive Evaluation Method for Energy Storage System and Flexible Interconnection in Distribution Networks\u0000Considering Island Operation","authors":"Hao Bai, Yu Fu, Guangze Ouyang, Yongxiang Cai, Song Zhang, Yu Miao, Weichen Yang, Min Xu","doi":"10.2174/0123520965299128240430041219","DOIUrl":"https://doi.org/10.2174/0123520965299128240430041219","url":null,"abstract":"\u0000\u0000When the superior power grid fails and loses power, due to the traditional\u0000single power supply radial grid structure of low-voltage substation areas, all loads in the lowvoltage\u0000substation area will lose power, causing a poor electricity consumption experience for\u0000low-voltage users. To enhance the resilience of low-voltage distribution areas against faults and\u0000power outages from higher-tier power grids, a collaborative planning and comprehensive evaluation\u0000method for grid-forming energy storage systems (GFM-ESS) and flexible interconnection in\u0000distribution networks, considering island operation, is proposed.\u0000\u0000\u0000\u0000This method integrates GFM-ESS and flexible interconnections, taking islanding operations\u0000into account. Firstly, the structure of GFM-ESS and voltage source converters is analyzed.\u0000The control modes of GFM-ESS in parallel or off-grid scenarios are also scrutinized. Secondly,\u0000minimizing the annual comprehensive cost and the annual power outage load are the objective\u0000functions. A bilevel programming model for GFM-ESS and flexible interconnection of lowvoltage\u0000distribution networks, considering island operation, has been established. Moreover, a\u0000comprehensive evaluation method based on the analytic hierarchy process for proposed lowvoltage\u0000distribution network structural schemes is introduced. An evaluation index system is established\u0000to assess the rationality of these proposed network structural planning schemes. Finally,\u0000the superiority of the proposed collaborative planning method is verified through a comparative\u0000analysis of three planning methods.\u0000\u0000\u0000\u0000The proposed collaborative planning method can effectively ensure the continuous power\u0000supply of low-voltage distribution networks under the fault scenario of the upper power network.\u0000\u0000\u0000\u0000Moreover, the rationality of the results obtained from the proposed collaborative\u0000planning method is verified through a comprehensive evaluation method of grid structure schemes\u0000based on the analytic hierarchy process. The proposed comprehensive evaluation method can determine\u0000which two areas are optimal for grid planning.\u0000\u0000\u0000\u0000The superiority of the proposed collaborative planning method was verified by comparative analysis of three planning methods. And the rationality of the proposed collaborative planning method results was verified by the comprehensive evaluation method of grid structure schemes based on analytic hierarchy process.\u0000","PeriodicalId":506996,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering)","volume":"27 40","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141684564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-02DOI: 10.2174/0123520965302195240612043038
Qiyuan Xiao, Jiawen Yu, Jie Wang, Yufei Zhuang, Qiang Zhu
The rapid development of Industry 4.0 has opened up new power systems, which face a more complex network topology and a broader range of security threats. This has led to an urgent demand for a coordinated, lightweight, and secure communication management method. This paper presents a general power communication framework with a joint security protection mechanism that is suitable for coordinated management and transmission safety. The framework manages the protocol’s thread management of the device by converting it to the framework’s process management. It formulates specifications for protocols and equipment that access the framework to achieve support for multiple protocols and equipment. This reduces the difficulty of system operation and maintenance, as well as system complexity, and improves management efficiency. Additionally, the joint security protective mechanism for plugin authentication and protocol encryption is introduced to enable secure data transmission and guarantee the framework's security management. Finally, two experiments have been conducted to discuss and confirm the effectiveness and safety of the framework. The results of the two experiments and the following analysis show that our framework is superior to the chosen well-known industrial commercial communication platforms, and the time delay cost by our mechanism doesn’t significantly affect the real-time data transmission in the power industry, proving its feasibility in both IoT and power applications. Our framework demonstrates exceptional performance in terms of time lag and packet loss during the experiment, surpassing other IoT communication frameworks. Furthermore, it maintains its high standards even under rigorous security analysis.
{"title":"Research and Application of a Generalized Power Communication Framework with Joint Security Protection Mechanism","authors":"Qiyuan Xiao, Jiawen Yu, Jie Wang, Yufei Zhuang, Qiang Zhu","doi":"10.2174/0123520965302195240612043038","DOIUrl":"https://doi.org/10.2174/0123520965302195240612043038","url":null,"abstract":"\u0000\u0000The rapid development of Industry 4.0 has opened up new power systems,\u0000which face a more complex network topology and a broader range of security threats. This\u0000has led to an urgent demand for a coordinated, lightweight, and secure communication management\u0000method.\u0000\u0000\u0000\u0000This paper presents a general power communication framework with a joint security\u0000protection mechanism that is suitable for coordinated management and transmission safety. The\u0000framework manages the protocol’s thread management of the device by converting it to the\u0000framework’s process management. It formulates specifications for protocols and equipment that\u0000access the framework to achieve support for multiple protocols and equipment. This reduces the\u0000difficulty of system operation and maintenance, as well as system complexity, and improves\u0000management efficiency. Additionally, the joint security protective mechanism for plugin authentication\u0000and protocol encryption is introduced to enable secure data transmission and guarantee\u0000the framework's security management. Finally, two experiments have been conducted to discuss\u0000and confirm the effectiveness and safety of the framework.\u0000\u0000\u0000\u0000The results of the two experiments and the following analysis show that our framework is\u0000superior to the chosen well-known industrial commercial communication platforms, and the time\u0000delay cost by our mechanism doesn’t significantly affect the real-time data transmission in the\u0000power industry, proving its feasibility in both IoT and power applications.\u0000\u0000\u0000\u0000Our framework demonstrates exceptional performance in terms of time lag and packet\u0000loss during the experiment, surpassing other IoT communication frameworks. Furthermore, it\u0000maintains its high standards even under rigorous security analysis.\u0000","PeriodicalId":506996,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering)","volume":"6 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141683961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-07DOI: 10.2174/0123520965313603240529110810
Ahmed Abo Dahab, Rasha Elazab, M. A. Abo Adma, H. Hassan
This study aims to investigate the global transition towards 100% renewable energy (RE) grids while analyzing associated challenges and economic prospects. The scientific aim of the work is to examine national and regional plans, revealing shared research challenges such as neglect of system stability, reliance on specific RE sources, and limitations on capacity share growth. The subject of the research was to obtain insights into the economic feasibility of this transition, underscored by projections of creating 24.3 million new jobs by 2050 and substantial annual savings in air pollution and environmental costs. This study extends the existing research by analyzing promising examples from countries like Norway and Costa Rica, demonstrating diverse approaches with hydropower playing a pivotal role, while Canada and New Zealand showcase adaptability based on local resources. Addressing key research challenges, from technological uncertainties to socio-economic considerations, the paper emphasizes the need for robust policies and infrastructure development. Despite challenges, the transition promises economic benefits, with estimated annual savings in healthcare and global warming costs. The literature and global examples affirm the technical and financial feasibility of transitioning to 100% RE. In conclusion, this paper contributes to understanding the intricate economic and technological landscape of achieving a sustainable global energy transition.
{"title":"Global Challenges and Economic Feasibility in Achieving 100% Renewable Energy","authors":"Ahmed Abo Dahab, Rasha Elazab, M. A. Abo Adma, H. Hassan","doi":"10.2174/0123520965313603240529110810","DOIUrl":"https://doi.org/10.2174/0123520965313603240529110810","url":null,"abstract":"\u0000\u0000This study aims to investigate the global transition towards 100% renewable energy\u0000(RE) grids while analyzing associated challenges and economic prospects. The scientific aim of\u0000the work is to examine national and regional plans, revealing shared research challenges such as\u0000neglect of system stability, reliance on specific RE sources, and limitations on capacity share\u0000growth. The subject of the research was to obtain insights into the economic feasibility of this\u0000transition, underscored by projections of creating 24.3 million new jobs by 2050 and substantial\u0000annual savings in air pollution and environmental costs. This study extends the existing research\u0000by analyzing promising examples from countries like Norway and Costa Rica, demonstrating diverse\u0000approaches with hydropower playing a pivotal role, while Canada and New Zealand showcase\u0000adaptability based on local resources. Addressing key research challenges, from technological\u0000uncertainties to socio-economic considerations, the paper emphasizes the need for robust policies\u0000and infrastructure development. Despite challenges, the transition promises economic benefits,\u0000with estimated annual savings in healthcare and global warming costs. The literature and\u0000global examples affirm the technical and financial feasibility of transitioning to 100% RE. In conclusion,\u0000this paper contributes to understanding the intricate economic and technological landscape\u0000of achieving a sustainable global energy transition.\u0000","PeriodicalId":506996,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering)","volume":" 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141375490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Due to experimental equipment limitations, it is usually difficult to measure the quasi-static hysteresis loop at extremely low frequencies, which inevitably introduces errors in the static hysteresis model. This study aims to propose a method for calculating the static hysteresis loops of grainoriented silicon steel sheets so as to improve the accuracy of the static and dynamic hysteresis model. The parameters n0 and V0 in the magnetic field strength expression of the excess loss are determined by the measured losses within the range of 0-100Hz. Subsequently, the dynamic components in the quasi-static hysteresis loops are eliminated. Furthermore, a dynamic hysteresis model is established based on the loss and field separation theory, which incorporates the inverse Preisach model. The dynamic hysteresis loops of the grain-oriented silicon steel sheets are measured in the range of 8-250Hz and compared with the results of both the improved model and the original model. Experimental results demonstrate the effectiveness and accuracy of the improved model. The proposed method for calculating static hysteresis loops has universal applicability and is meaningful for accurate simulation and prediction of magnetic properties in soft magnetic materials.
{"title":"A Calculation Method for Static Hysteresis Loop and its Applications","authors":"Yu Fu, Yu Miao, Xinhao Li, Xiaojun Zhao, Ziyi Qian, Haoming Wang","doi":"10.2174/0123520965290791240507054649","DOIUrl":"https://doi.org/10.2174/0123520965290791240507054649","url":null,"abstract":"\u0000\u0000Due to experimental equipment limitations, it is usually difficult to\u0000measure the quasi-static hysteresis loop at extremely low frequencies, which inevitably introduces\u0000errors in the static hysteresis model.\u0000\u0000\u0000\u0000This study aims to propose a method for calculating the static hysteresis loops of grainoriented silicon steel sheets so as to improve the accuracy of the static and dynamic hysteresis\u0000model.\u0000\u0000\u0000\u0000The parameters n0 and V0 in the magnetic field strength expression of the excess loss are\u0000determined by the measured losses within the range of 0-100Hz. Subsequently, the dynamic components in the quasi-static hysteresis loops are eliminated. Furthermore, a dynamic hysteresis\u0000model is established based on the loss and field separation theory, which incorporates the inverse\u0000Preisach model.\u0000\u0000\u0000\u0000The dynamic hysteresis loops of the grain-oriented silicon steel sheets are measured in\u0000the range of 8-250Hz and compared with the results of both the improved model and the original\u0000model.\u0000\u0000\u0000\u0000Experimental results demonstrate the effectiveness and accuracy of the improved\u0000model. The proposed method for calculating static hysteresis loops has universal applicability and\u0000is meaningful for accurate simulation and prediction of magnetic properties in soft magnetic materials.\u0000","PeriodicalId":506996,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering)","volume":"50 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141116718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-16DOI: 10.2174/0123520965296747240426053259
Hao Bai, Yang Wang, Song Zhang, Wei Li, Mingjun He, Yongxiang Cai
The distribution systems are gradually transformed into active systems with the large-scale integration of renewable resources, which brings greater potential to the fault recovery of the distribution networks and higher requirements for the power scheduling capability under fault conditions. Power electronic devices such as soft open points (SOPs) can break the radial constraints of the traditional distribution network, provide cross-station power support in fault scenarios, and enhance the resilience of the distribution networks. This paper focuses on the distribution systems with multi-transformer flexible interconnection, and a multi-device coordinated fault restoration method is proposed. Firstly, the characteristics of different transformer fault scenes and the fault restoration process coordinated by the bus-bar switches and SOPs in each scene are sorted out. Secondly, an optimization model of the fault restoration for DC-interconnected distribution system is established considering the network operation and the equipment constraints in the fault restoration process. The proposed model aims at the maximization of the weighted load restoration amount, and is transformed into a second-order cone programming model to be solved quickly. Lastly, the effectiveness of the proposed method is verified in a typical flexible interconnection distribution system. The simulation results prove that it can effectively improve the capability of preserving power supply for important loads after transformer failure.
{"title":"A Fault Restoration Method for DC-interconnected Distribution Systems\u0000with Renewable Resources Considering Multiple Fault Scenes","authors":"Hao Bai, Yang Wang, Song Zhang, Wei Li, Mingjun He, Yongxiang Cai","doi":"10.2174/0123520965296747240426053259","DOIUrl":"https://doi.org/10.2174/0123520965296747240426053259","url":null,"abstract":"\u0000\u0000The distribution systems are gradually transformed into active systems\u0000with the large-scale integration of renewable resources, which brings greater potential to the fault\u0000recovery of the distribution networks and higher requirements for the power scheduling capability\u0000under fault conditions. Power electronic devices such as soft open points (SOPs) can break the\u0000radial constraints of the traditional distribution network, provide cross-station power support in\u0000fault scenarios, and enhance the resilience of the distribution networks.\u0000\u0000\u0000\u0000This paper focuses on the distribution systems with multi-transformer flexible interconnection,\u0000and a multi-device coordinated fault restoration method is proposed. Firstly, the\u0000characteristics of different transformer fault scenes and the fault restoration process coordinated\u0000by the bus-bar switches and SOPs in each scene are sorted out. Secondly, an optimization model\u0000of the fault restoration for DC-interconnected distribution system is established considering the\u0000network operation and the equipment constraints in the fault restoration process.\u0000\u0000\u0000\u0000The proposed model aims at the maximization of the weighted load restoration amount,\u0000and is transformed into a second-order cone programming model to be solved quickly. Lastly, the\u0000effectiveness of the proposed method is verified in a typical flexible interconnection distribution\u0000system.\u0000\u0000\u0000\u0000The simulation results prove that it can effectively improve the capability of preserving\u0000power supply for important loads after transformer failure.\u0000","PeriodicalId":506996,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering)","volume":"33 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140966483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emotion recognition, both verbal and non-verbal, is a crucial component of artificial intelligence, psychology, and human-computer interaction. Emotion recognition is an integral component that significantly contributes to the improvement of communication and interaction. The research endeavors to conduct a thorough analysis and synthesis of the most recent developments in Deep Learning (DL) and Machine Learning (ML) techniques. Specifically, the study concentrates on the recognition of both verbal and non-verbal emotions. In contrast to previous research concentrated on verbal or non-verbal emotion detection separately, the study attempts to reconcile the gap between the two by demonstrating how ML and DL can be utilized effectively to detect emotions. The study also examines new methods, including multimodal data and integration of contextual information. Additionally, the research has examined the ethical implications and difficulties associated with emotion detection technologies. Findings have also revealed the wide-reaching implications for various sectors, including healthcare, education, customer service, and entertainment, where comprehending human emotions plays a crucial role in enhancing user experience and outcomes. In conclusion, the study provides invaluable knowledge to practitioners and researchers, which may facilitate the development of more advanced and accurate systems.
情感识别（包括语言和非语言）是人工智能、心理学和人机交互的重要组成部分。本研究致力于对深度学习（DL）和机器学习（ML）技术的最新发展进行全面分析和综合。具体来说，该研究侧重于语言和非语言情绪的识别。与以往分别专注于语言或非语言情绪检测的研究不同，本研究试图通过展示如何有效利用 ML 和 DL 来检测情绪，从而弥补两者之间的差距。研究还探讨了新方法，包括多模态数据和上下文信息的整合。此外，研究还探讨了与情绪检测技术相关的伦理影响和困难。研究结果还揭示了情绪检测技术对医疗保健、教育、客户服务和娱乐等各个领域的深远影响，在这些领域中，理解人类情绪对提升用户体验和结果起着至关重要的作用。总之，这项研究为从业人员和研究人员提供了宝贵的知识，有助于开发更先进、更准确的系统。
{"title":"Recent Trends in Machine and Deep Learning for Verbal and Non-verbal Emotion Detection","authors":"Muskan Chawla, Surya Narayan Panda, Vikas Khullar, I. Kansal, Rajeev Kumar","doi":"10.2174/0123520965303142240430101645","DOIUrl":"https://doi.org/10.2174/0123520965303142240430101645","url":null,"abstract":"\u0000\u0000Emotion recognition, both verbal and non-verbal, is a crucial component of artificial\u0000intelligence, psychology, and human-computer interaction. Emotion recognition is an integral\u0000component that significantly contributes to the improvement of communication and interaction.\u0000The research endeavors to conduct a thorough analysis and synthesis of the most recent developments\u0000in Deep Learning (DL) and Machine Learning (ML) techniques. Specifically, the study\u0000concentrates on the recognition of both verbal and non-verbal emotions. In contrast to previous\u0000research concentrated on verbal or non-verbal emotion detection separately, the study attempts to\u0000reconcile the gap between the two by demonstrating how ML and DL can be utilized effectively to\u0000detect emotions. The study also examines new methods, including multimodal data and integration\u0000of contextual information. Additionally, the research has examined the ethical implications\u0000and difficulties associated with emotion detection technologies. Findings have also revealed the\u0000wide-reaching implications for various sectors, including healthcare, education, customer service,\u0000and entertainment, where comprehending human emotions plays a crucial role in enhancing user\u0000experience and outcomes. In conclusion, the study provides invaluable knowledge to practitioners\u0000and researchers, which may facilitate the development of more advanced and accurate systems.\u0000","PeriodicalId":506996,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering)","volume":"135 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140977059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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