Two-dimensional materials are very promising for ultra-short channel future devices. This paper investigates, for the first time, the viability of the junction less transistors based on 2-D materials for future state-of-the-art technology nodes. Specifically, we investigate the performance of a Junction less monolayer black phosphorus (BP) FET (JLFET) with 12nm gate length using ab initio quantum transport simulations. The electrostatic control mechanism of the device and various intrinsic static and dynamic characteristics of the device are studied. The results reveal that BP JLFET performance can fulfill the benchmark requirement of International Roadmap for Devices and Systems (IRDS 2021) for 2028 in terms of HP and HD applications. Therefore, JLFET based on 2D materials can be a promising alternative for nano scale future device applications.
二维材料在未来的超短沟道器件中大有可为。本文首次研究了基于二维材料的无结晶体管在未来最先进技术节点上的可行性。具体来说，我们利用 ab initio 量子输运模拟研究了栅极长度为 12nm 的无结单层黑磷 (BP) FET (JLFET) 的性能。研究了器件的静电控制机制以及器件的各种内在静态和动态特性。研究结果表明，BP JLFET 的性能可以满足 2028 年国际器件和系统路线图（IRDS 2021）在惠普和高清应用方面的基准要求。因此，基于二维材料的 JLFET 可以成为未来纳米级器件应用的一个有前途的替代方案。
{"title":"Performance assessment of monolayer Black Phosphorus DG-JLFET","authors":"Pankaj Kumar Sanda","doi":"10.52783/jes.3371","DOIUrl":"https://doi.org/10.52783/jes.3371","url":null,"abstract":"Two-dimensional materials are very promising for ultra-short channel future devices. This paper investigates, for the first time, the viability of the junction less transistors based on 2-D materials for future state-of-the-art technology nodes. Specifically, we investigate the performance of a Junction less monolayer black phosphorus (BP) FET (JLFET) with 12nm gate length using ab initio quantum transport simulations. The electrostatic control mechanism of the device and various intrinsic static and dynamic characteristics of the device are studied. The results reveal that BP JLFET performance can fulfill the benchmark requirement of International Roadmap for Devices and Systems (IRDS 2021) for 2028 in terms of HP and HD applications. Therefore, JLFET based on 2D materials can be a promising alternative for nano scale future device applications.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141000843","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}
Yakub Banothu, Swapna Peravali, D. V. Rama, Koti Reddy, CH.D. Uma Sankar, S. R. Srither, P. S. S. Babu, Syed Shameem
Agricultural-waste-derived porous carbon and vegetable-waste-derived porous carbon materials have been extensively studied as electrode materials for high-performance supercapacitors due to their abundance and ability to be consistently reproduced. This paper focuses on utilizing eggplant waste, the primary by-product, as a precursor for producing porous carbon through the easy carbonization and activation process. The resultant porous carbon is then employed as an electrode material for supercapacitors. The Eggplant waste-derived porous carbon exhibits a notable surface area of 1095.4 m2 g-1. This carbon material possesses the benefits of being cost-effective and environmentally friendly while exhibiting superior electrochemical performance in comparison to materials obtained from agricultural waste. The carbon electrode made from eggplant demonstrates an energy density of 9.19 Wh Kg-1 and a power density of 2880 W Kg-1, indicating its outstanding energy storage capacity.
农业废弃物衍生的多孔碳和蔬菜废弃物衍生的多孔碳材料因其丰富性和可持续复制性，已被广泛研究用作高性能超级电容器的电极材料。本文的重点是利用主要副产品茄子废料作为前体，通过简单的碳化和活化过程生产多孔碳。然后将得到的多孔碳用作超级电容器的电极材料。从茄子废料中提取的多孔碳的表面积高达 1095.4 m2 g-1。与从农业废弃物中提取的材料相比，这种碳材料具有成本低、环保的优点，同时还表现出卓越的电化学性能。由茄子制成的碳电极的能量密度为 9.19 Wh Kg-1，功率密度为 2880 W Kg-1，表明其具有出色的储能能力。
{"title":"Biodegradable Activated Carbon Material Derived from Eggplant Waste for Enhanced Supercapacitor Performance","authors":"Yakub Banothu, Swapna Peravali, D. V. Rama, Koti Reddy, CH.D. Uma Sankar, S. R. Srither, P. S. S. Babu, Syed Shameem","doi":"10.52783/jes.3544","DOIUrl":"https://doi.org/10.52783/jes.3544","url":null,"abstract":"Agricultural-waste-derived porous carbon and vegetable-waste-derived porous carbon materials have been extensively studied as electrode materials for high-performance supercapacitors due to their abundance and ability to be consistently reproduced. This paper focuses on utilizing eggplant waste, the primary by-product, as a precursor for producing porous carbon through the easy carbonization and activation process. The resultant porous carbon is then employed as an electrode material for supercapacitors. The Eggplant waste-derived porous carbon exhibits a notable surface area of 1095.4 m2 g-1. This carbon material possesses the benefits of being cost-effective and environmentally friendly while exhibiting superior electrochemical performance in comparison to materials obtained from agricultural waste. The carbon electrode made from eggplant demonstrates an energy density of 9.19 Wh Kg-1 and a power density of 2880 W Kg-1, indicating its outstanding energy storage capacity.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141129231","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}
The role of digital and intelligent technology in social risk governance and assessment is increasingly prominent. However, existing research often focuses on the technical aspects of development, neglecting the synergy and integration between technology and administrative practices. To address this, the paper constructs a four-dimensional theoretical analysis framework based on collaborative governance theory, which includes “subject integration, object unification, relationship coupling, and function complementation.” This framework is applied in a case study to analyze the generation logic and pathway construction of the third-party stability assessment the “big data” model adopted by City A. The study concludes that the dominant role of administrative efficiency is core, the supportive role of technological empowerment is key, and the participatory role of social forces is essential in building the pathway. These findings provide empirical support for the digital construction of major decision-making third-party stability assessment nationwide. They offer new perspectives to enhance governance efficiency and contribute to the ongoing improvement and high-quality development of major decision-making processes in social stability risk governance and assessment.
数字和智能技术在社会风险治理和评估中的作用日益突出。然而，现有研究往往关注技术层面的发展，忽视了技术与行政管理实践之间的协同与融合。针对这一问题，本文以协同治理理论为基础，构建了包括 "主体融合、客体统一、关系耦合、功能互补 "在内的四维理论分析框架。该框架被应用于案例研究，分析了 A 市采用的 "大数据 "模式中第三方稳评的生成逻辑和路径构建。研究认为，在构建路径时，行政效率的主导作用是核心，技术赋能的支撑作用是关键，社会力量的参与作用至关重要。这些发现为全国重大决策第三方稳评数字化建设提供了实证支持。它们为提升治理效率提供了新视角，有助于社会稳定风险治理与评估重大决策流程的不断完善和高质量发展。
{"title":"Big Data Model for Third-party Stability Assessment of Major Decisions: Generation Logic and Path Construction","authors":"Mingxin Xu, Longgui Zhen, Shuang Tan","doi":"10.52783/jes.3530","DOIUrl":"https://doi.org/10.52783/jes.3530","url":null,"abstract":"The role of digital and intelligent technology in social risk governance and assessment is increasingly prominent. However, existing research often focuses on the technical aspects of development, neglecting the synergy and integration between technology and administrative practices. To address this, the paper constructs a four-dimensional theoretical analysis framework based on collaborative governance theory, which includes “subject integration, object unification, relationship coupling, and function complementation.” This framework is applied in a case study to analyze the generation logic and pathway construction of the third-party stability assessment the “big data” model adopted by City A. The study concludes that the dominant role of administrative efficiency is core, the supportive role of technological empowerment is key, and the participatory role of social forces is essential in building the pathway. These findings provide empirical support for the digital construction of major decision-making third-party stability assessment nationwide. They offer new perspectives to enhance governance efficiency and contribute to the ongoing improvement and high-quality development of major decision-making processes in social stability risk governance and assessment.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141129131","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}
This review paper presents an analysis of the most recent advancements in sub-1V voltage references, addressing the growing demand for ultra-low power consumption and high precision in modern integrated circuits (ICs). Voltage references are critical components in numerous applications, including IoT devices, wearable electronics, and energy-harvesting systems, where power efficiency and accuracy are paramount. It briefly discusses the challenges associated with designing voltage references at such low voltages, such as limited headroom, reduced noise margin, and process variations. Topics include high-order curvature compensation, modified differential pair configurations, and energy-efficient solutions for integrated energy harvesting. These advancements enhance precision and reliability in low-voltage circuits, paving the way for sustainable, low-power electronics and compact devices in the modern digital landscape. It emphasizes the importance of benchmarking different designs against criteria such as power consumption, line regulation, temperature stability, and supply voltage rejection ratio (PSRR). The paper include insights into the state-of-the-art sub-1V voltage reference designs, identification of design trade-offs, and recommendations for future research directions. It underscores the importance of continuous innovation in voltage reference design to address the evolving requirements of ultra-low power electronics. The study here is setting the stage for a detailed analysis of the latest developments in sub-1V voltage references.
{"title":"CMOS Based Voltage Reference Designs for Sub - 1V","authors":"Garima Kapur","doi":"10.52783/jes.3538","DOIUrl":"https://doi.org/10.52783/jes.3538","url":null,"abstract":"This review paper presents an analysis of the most recent advancements in sub-1V voltage references, addressing the growing demand for ultra-low power consumption and high precision in modern integrated circuits (ICs). Voltage references are critical components in numerous applications, including IoT devices, wearable electronics, and energy-harvesting systems, where power efficiency and accuracy are paramount. It briefly discusses the challenges associated with designing voltage references at such low voltages, such as limited headroom, reduced noise margin, and process variations. Topics include high-order curvature compensation, modified differential pair configurations, and energy-efficient solutions for integrated energy harvesting. These advancements enhance precision and reliability in low-voltage circuits, paving the way for sustainable, low-power electronics and compact devices in the modern digital landscape. It emphasizes the importance of benchmarking different designs against criteria such as power consumption, line regulation, temperature stability, and supply voltage rejection ratio (PSRR). The paper include insights into the state-of-the-art sub-1V voltage reference designs, identification of design trade-offs, and recommendations for future research directions. It underscores the importance of continuous innovation in voltage reference design to address the evolving requirements of ultra-low power electronics. The study here is setting the stage for a detailed analysis of the latest developments in sub-1V voltage references.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141129232","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}
Female breast malignancy is the exceedingly prevalent reason for the demise of women around the world. Women who are revealed to have breast cancer earlier in life get a lower death rate from the disease and increase the life expectancy of patients. Mammography screening is one of the effortless, efficient, and affordable ways to identify breast cancer in advance. The early investigators pioneered many methods based on statistical measurements and textural traits for the earliest identification of carcinoma of the breast. Due to artefacts, noise, pectoral muscles, and irregular illumination, the accuracy of cancer prediction in these works is relatively low. The accuracy of predictions made by employing textural characteristics for forecasting breast cancer in earlier work is 83.33%. The research proposal processes of mammograms to remove noise, artefacts, pectoralis, and inconsistent illumination in an endeavor to increase forecast accuracy. The proposed research uses an Artificial Neural Network (ANN) to classify breast masses as benign or malignant based on geometric pattern features. Its prediction accuracy is 86.67%, which is superior to research studies based on textural and statistical characteristics of breast mammograms.
女性乳腺恶性肿瘤是全世界女性死亡的主要原因。早期发现患有乳腺癌的女性死亡率较低，并能延长患者的预期寿命。乳房 X 射线照相筛查是提前发现乳腺癌的省力、高效、经济的方法之一。早期的研究人员开创了许多基于统计测量和纹理特征的方法，用于尽早识别乳腺癌。由于伪影、噪音、胸肌和不规则光照等原因，这些方法预测癌症的准确率相对较低。 在早期的研究中，利用纹理特征预测乳腺癌的准确率为 83.33%。该研究建议对乳房 X 光照片进行处理，去除噪音、伪影、胸膜和不一致的光照，以努力提高预测准确率。建议的研究使用人工神经网络（ANN）根据几何模式特征将乳腺肿块分为良性和恶性。其预测准确率为 86.67%，优于基于乳房 X 光照片纹理和统计特征的研究。
{"title":"Advancements in Breast Cancer Detection: Harnessing Artificial Neural Networks for Improved Accuracy","authors":"P.Narasimhaiah","doi":"10.52783/jes.3540","DOIUrl":"https://doi.org/10.52783/jes.3540","url":null,"abstract":"Female breast malignancy is the exceedingly prevalent reason for the demise of women around the world. Women who are revealed to have breast cancer earlier in life get a lower death rate from the disease and increase the life expectancy of patients. Mammography screening is one of the effortless, efficient, and affordable ways to identify breast cancer in advance. The early investigators pioneered many methods based on statistical measurements and textural traits for the earliest identification of carcinoma of the breast. Due to artefacts, noise, pectoral muscles, and irregular illumination, the accuracy of cancer prediction in these works is relatively low. The accuracy of predictions made by employing textural characteristics for forecasting breast cancer in earlier work is 83.33%. The research proposal processes of mammograms to remove noise, artefacts, pectoralis, and inconsistent illumination in an endeavor to increase forecast accuracy. The proposed research uses an Artificial Neural Network (ANN) to classify breast masses as benign or malignant based on geometric pattern features. Its prediction accuracy is 86.67%, which is superior to research studies based on textural and statistical characteristics of breast mammograms.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141129297","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}
This dataset presents data on the percentage of problem priorities, solution priorities and appropriate strategy priorities for developing a pharmaceutical salt business using the Analytic Network Process (ANP). This data consists of data on problems, solutions and strategies. Problem data includes production problems, supporting problems, market problems and stakeholder problems. Solution data includes fundamental solutions, technical solutions, macro strategic solutions and roadmap solutions. Meanwhile, strategy data includes a strategy for preparing a grand design for a community salt agribusiness pattern, a strategy for BUMN and salt processing companies to collaborate with salt farmer cooperatives, a strategy to increase human resource development, and a strategy for fulfilling permits to support the production of packaged salt. Numerical data was obtained from Forum Group Discussion with five experts, five practitioners and five regulators using a priority scale. Cluster priority analysis using Super Decision software version 2.10.
本数据集采用分析网络过程（ANP）展示了发展药用盐业务的问题优先级、解决方案优先级和适当战略优先级的百分比数据。该数据包括问题、解决方案和战略数据。问题数据包括生产问题、支持问题、市场问题和利益相关者问题。解决方案数据包括基本解决方案、技术解决方案、宏观战略解决方案和路线图解决方案。同时，战略数据包括社区食盐农业综合企业模式大设计的编制战略、BUMN 和食盐加工公司与盐农合作社合作的战略、加强人力资源开发的战略以及履行许可证以支持包装食盐生产的战略。通过与五位专家、五位从业人员和五位监管人员进行论坛小组讨论，使用优先级量表获得了数字数据。使用 Super Decision 软件 2.10 版进行分组优先级分析。
{"title":"Dataset for Pharmaceutical Salt Business to Improve the Welfare of Salt's Farmers","authors":"Irfat Hista Saputra","doi":"10.52783/jes.3671","DOIUrl":"https://doi.org/10.52783/jes.3671","url":null,"abstract":"This dataset presents data on the percentage of problem priorities, solution priorities and appropriate strategy priorities for developing a pharmaceutical salt business using the Analytic Network Process (ANP). This data consists of data on problems, solutions and strategies. Problem data includes production problems, supporting problems, market problems and stakeholder problems. Solution data includes fundamental solutions, technical solutions, macro strategic solutions and roadmap solutions. Meanwhile, strategy data includes a strategy for preparing a grand design for a community salt agribusiness pattern, a strategy for BUMN and salt processing companies to collaborate with salt farmer cooperatives, a strategy to increase human resource development, and a strategy for fulfilling permits to support the production of packaged salt. Numerical data was obtained from Forum Group Discussion with five experts, five practitioners and five regulators using a priority scale. Cluster priority analysis using Super Decision software version 2.10. ","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141013718","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}
Evolution in engineering and technology added large size of data storage and transmission through the web application over the internet. This huge amount of data primarily used for exchange of information in between users and devices and in secondary aspects it has utilization as feedback, ratings and reviews that is supporting in generation of useful information of products, services, incidents etc. The data as opinion, feedback, view & suggestion is explored, organized & analyzed for selection of appropriate options. Sentiment analysis using the opinion extraction is a challenging task that is based on feature extraction and the concepts of Natural Language Processing that is applied in identification of the opinions of a user in terms of positive, neutral or negative ratings hidden in the form of comments typed as the text. Presently many data-processing based feature evaluation techniques for opinion extraction are used for solving the issues faced under sentiment classification applications. This article is based on development and application of algorithms for opinion extraction from text data available on web resources by K-Nearest Neighbor (KNN), Support vector machine (SVM) and hybrid of both named as SVM+KNN for classification of multi-label opinions from extracted text from review data of Twitter and Amazon. The performance of all the classification models (KNN, SVM and SVM+KNN) on both datasets is evaluated in terms of different parameters.
{"title":"Opinion Extraction using Hybrid Learning Algorithm with Feature Set Optimization Approach","authors":"Devendra Kumar","doi":"10.52783/jes.3694","DOIUrl":"https://doi.org/10.52783/jes.3694","url":null,"abstract":"Evolution in engineering and technology added large size of data storage and transmission through the web application over the internet. This huge amount of data primarily used for exchange of information in between users and devices and in secondary aspects it has utilization as feedback, ratings and reviews that is supporting in generation of useful information of products, services, incidents etc. The data as opinion, feedback, view & suggestion is explored, organized & analyzed for selection of appropriate options. Sentiment analysis using the opinion extraction is a challenging task that is based on feature extraction and the concepts of Natural Language Processing that is applied in identification of the opinions of a user in terms of positive, neutral or negative ratings hidden in the form of comments typed as the text. Presently many data-processing based feature evaluation techniques for opinion extraction are used for solving the issues faced under sentiment classification applications. This article is based on development and application of algorithms for opinion extraction from text data available on web resources by K-Nearest Neighbor (KNN), Support vector machine (SVM) and hybrid of both named as SVM+KNN for classification of multi-label opinions from extracted text from review data of Twitter and Amazon. The performance of all the classification models (KNN, SVM and SVM+KNN) on both datasets is evaluated in terms of different parameters.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141012919","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}
Image segmentation is a key task in computer vision, with applications ranging from medical diagnosis to autonomous driving. The Ant Colony Algorithm (ACO), modeled after ant foraging behavior, has emerged as a viable segmentation methodology. However, ACO-based segmentation algorithms frequently generate segmented outputs with jagged or uneven boundaries, which reduces their interpretability and usability. To alleviate this problem, they study the use of boundary-smoothing approaches in ACO-based segmentation. In this paper, they investigate image segmentation technology based on the Ant Colony Algorithm, with a focus on border smoothing. They examine the fundamentals of ACO and its application to image segmentation, emphasizing its strengths and limits. They also look at several boundary smoothing strategies, such as morphological operations, edge-preserving filters, and active contours (snakes), and how they affect segmentation performance. Through experimental validation and comparative analysis, they show that boundary smoothing improves the accuracy and visual quality of segmented images produced by ACO-based segmentation algorithms. These results help to design more robust and visually appealing segmentation algorithms, which have potential applications in medical imaging, remote sensing, and industrial automation.
{"title":"Image Segmentation Technology Based on Ant Colony Algorithm","authors":"Xiaoyan Wang","doi":"10.52783/jes.3485","DOIUrl":"https://doi.org/10.52783/jes.3485","url":null,"abstract":"Image segmentation is a key task in computer vision, with applications ranging from medical diagnosis to autonomous driving. The Ant Colony Algorithm (ACO), modeled after ant foraging behavior, has emerged as a viable segmentation methodology. However, ACO-based segmentation algorithms frequently generate segmented outputs with jagged or uneven boundaries, which reduces their interpretability and usability. To alleviate this problem, they study the use of boundary-smoothing approaches in ACO-based segmentation. In this paper, they investigate image segmentation technology based on the Ant Colony Algorithm, with a focus on border smoothing. They examine the fundamentals of ACO and its application to image segmentation, emphasizing its strengths and limits. They also look at several boundary smoothing strategies, such as morphological operations, edge-preserving filters, and active contours (snakes), and how they affect segmentation performance. Through experimental validation and comparative analysis, they show that boundary smoothing improves the accuracy and visual quality of segmented images produced by ACO-based segmentation algorithms. These results help to design more robust and visually appealing segmentation algorithms, which have potential applications in medical imaging, remote sensing, and industrial automation.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141013350","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}
With the proliferation of vehicles and the integration of technology into daily transportation, ensuring road safety has become paramount. Traffic accidents, often resulting in substantial damage and casualties, persist as a global concern. The Automatic Braking System (ABS) stands as a pivotal safety innovation adopted by vehicle manufacturers worldwide. This paper explores the significance and functionality of ABS in preventing wheel lock-up during braking, thereby enabling drivers to maintain steering control. Through an examination of ABS technology, its effectiveness, limitations, and potential advancements, this research aims to contribute to the ongoing discourse on enhancing road safety measures in the modern automotive landscape.
{"title":"Automatic Braking System","authors":"Dr. Manik Deosarkar","doi":"10.52783/jes.3476","DOIUrl":"https://doi.org/10.52783/jes.3476","url":null,"abstract":"With the proliferation of vehicles and the integration of technology into daily transportation, ensuring road safety has become paramount. Traffic accidents, often resulting in substantial damage and casualties, persist as a global concern. The Automatic Braking System (ABS) stands as a pivotal safety innovation adopted by vehicle manufacturers worldwide. This paper explores the significance and functionality of ABS in preventing wheel lock-up during braking, thereby enabling drivers to maintain steering control. Through an examination of ABS technology, its effectiveness, limitations, and potential advancements, this research aims to contribute to the ongoing discourse on enhancing road safety measures in the modern automotive landscape.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141012891","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}
This paper presents a novel university financial management system leveraging multi-scale deep learning. With rising college enrollment and teaching complexities, traditional financial models require adaptation to mitigate risks and improve management quality. The system integrates hardware and software innovations: multiple sensors enhance data scanning, coordinated by a central coordinator, ensuring comprehensive financial database coverage. Software-wise, a structured database establishes attribute-based financial connections, crucial for weight assignment. Employing a multilayer perceptual network topology, a full interconnection model based on multi-scale deep learning facilitates profound data extraction. Experimental evaluations demonstrate the system's superior financial risk assessment capabilities compared to traditional approaches, extracting a broader spectrum of financial parameters for comprehensive risk warnings. By embracing multi-scale deep learning, this system promises significant advancements in university financial management, enhancing adaptability and risk mitigation in college finance departments.
{"title":"Innovative Financial Management in Higher Education: A Multi-Scale Deep Learning Approach for Risk Reduction and Quality Enhancement","authors":"Hongbin Yue","doi":"10.52783/jes.3254","DOIUrl":"https://doi.org/10.52783/jes.3254","url":null,"abstract":"This paper presents a novel university financial management system leveraging multi-scale deep learning. With rising college enrollment and teaching complexities, traditional financial models require adaptation to mitigate risks and improve management quality. The system integrates hardware and software innovations: multiple sensors enhance data scanning, coordinated by a central coordinator, ensuring comprehensive financial database coverage. Software-wise, a structured database establishes attribute-based financial connections, crucial for weight assignment. Employing a multilayer perceptual network topology, a full interconnection model based on multi-scale deep learning facilitates profound data extraction. Experimental evaluations demonstrate the system's superior financial risk assessment capabilities compared to traditional approaches, extracting a broader spectrum of financial parameters for comprehensive risk warnings. By embracing multi-scale deep learning, this system promises significant advancements in university financial management, enhancing adaptability and risk mitigation in college finance departments.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141014433","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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