{"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
{"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}
{"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}
{"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}
{"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}
{"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}
{"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}
{"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}
{"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}
{"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}