2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)最新文献_第7页

Juxtaposing Deep Learning Models Efficacy for Ocular Disorder Detection of Diabetic Retinopathy for Ophthalmoscopy 深度学习模型在糖尿病视网膜病变眼科检查中的并置效果

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609368

Subhash Arun Dwivedi, Amit Attry

引用次数: 1

Intrusion Detection Systems: Conceptual Study and Review 入侵检测系统:概念研究与回顾

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609481

Charvi Vij, H. Saini

引用次数: 2

Condition Monitoring of Machinery: A Case Study 机械状态监测:个案研究

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609512

P. Samant, Megha Bhushan, Ashok Kumar, R. Arya, Sharad Tiwari, S. Bansal

引用次数: 2

A Protected Cloud Information Sharing Convention for Big Business Supporting Various Leveled Catchphrase Search 支持多级口头禅搜索的大企业受保护云信息共享约定

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609465

S. Gowri Manohar, A. Mohana Krishna Kumar, K. Visweswaran, R. Freeda

{"title":"A Protected Cloud Information Sharing Convention for Big Business Supporting Various Leveled Catchphrase Search","authors":"S. Gowri Manohar, A. Mohana Krishna Kumar, K. Visweswaran, R. Freeda","doi":"10.1109/ISPCC53510.2021.9609465","DOIUrl":"https://doi.org/10.1109/ISPCC53510.2021.9609465","url":null,"abstract":"Distributed storage turns into the need for putting away and sharing information for big business clients. Scrambling before transferring information to the cloud is the best appreciation to defending organisation favored experiences, in any case, it forestalls the invaluable technique on plaintexts, like exploring the cloud data. Furthermore, staff in the partner endeavor has different layers structures and the following layer laborer have some of the the advantage to notice the bottom layer representatives' information to check whether these clients abuse the guideline while not holding the specialist's recollect of. private and public cryptography with watchword search could be a notable cryptanalytic crude fitting for secure distributed storage, that upholds catchphrase search while not coding public and private key cryptography Unfortunately, no current public and private key encrypted with data search topic upholds the watching execution while not approval from the To deal with this issue, we to will, in general, propose a variation of public-key encryption with keyword search named hierarchic Public Key cryptography with Catchphrase Search and supply a semi-conventional development using a public key tree and public encryption key with the data search.","PeriodicalId":113266,"journal":{"name":"2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"42 25","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120815933","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}

引用次数: 0

A Comparative Analysis of Early Stage Diabetes Prediction using Machine Learning and Deep Learning Approach 机器学习与深度学习方法在早期糖尿病预测中的比较分析

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.36227/techrxiv.16870623.v1

Md. Abu Rumman Refat, Md. Al Amin, Chetna Kaushal, Mst. Nilufa Yeasmin, Md. Khairul Islam

{"title":"A Comparative Analysis of Early Stage Diabetes Prediction using Machine Learning and Deep Learning Approach","authors":"Md. Abu Rumman Refat, Md. Al Amin, Chetna Kaushal, Mst. Nilufa Yeasmin, Md. Khairul Islam","doi":"10.36227/techrxiv.16870623.v1","DOIUrl":"https://doi.org/10.36227/techrxiv.16870623.v1","url":null,"abstract":"Diabetes is a disease that affects how your body processes blood sugar and is often referred to as diabetes mellitus. Insulin insufficiency and ineffective insulin use coincide when the pancreas cannot produce enough insulin or the human body cannot use the insulin that is produced. Insulin is a hormone produced by the pancreas that helps in the transport of glucose from food into cells for use as energy. The common effect of uncontrolled diabetes is hyper-glycemia, or high blood sugar, which plus other health concerns, raises serious health issues, majorly towards the nerves and blood vessels. According to 2014 statistics, people aged 18 or older had diabetes and, according to 2019 statistics, diabetes alone caused 1.5 million deaths. However, because of the rapid growth of machine learning(ML) and deep learning (DL) classification algorithms, indifferent sectors, like health science, it is now remarkably easy to detect diabetes in its early stages. In this experiment, we have conducted a comparative analysis of several ML and DL techniques for early diabetes disease prediction. Additionally, we used a diabetes dataset from the UCI repository that has 17 attributes, including class, and evaluated the performance of all proposed machine learning and deep learning classification algorithms using a variety of performance metrics. According to our experiments, the XGBoost classifier outperformed the rest of the algorithms by approximately 100.0%, while the rest of the algorithms were over 90.0% accurate.","PeriodicalId":113266,"journal":{"name":"2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129668205","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}

引用次数: 18

Circuits Based on the Memristor for Fundamental Operations 基于忆阻器的基本运算电路

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609439

A. Nandini, R. A. Kumar, Maneesh Kumar Singh

{"title":"Circuits Based on the Memristor for Fundamental Operations","authors":"A. Nandini, R. A. Kumar, Maneesh Kumar Singh","doi":"10.1109/ISPCC53510.2021.9609439","DOIUrl":"https://doi.org/10.1109/ISPCC53510.2021.9609439","url":null,"abstract":"The memristor, which is the fourth passive element that is lacking, is a nonvolatile device with two terminals. It promises advancement in future technology, which will aid in the reduction of power consumption, the reduction of cost, and the increase of performance of integrated circuits. This work presents a thorough investigation of memristor modeling through the use of Mat lab simulations. For the purpose of anticipating the behavior of the memristor device, we consider three different modeling strategies. In addition to the solid-state thin film memristor device, a spintronic memristor device based on magnetic technology was also simulated in this study. The fact that it has nanoscale geometry means that it is susceptible to process fluctuations during the fabrication process. The electrical behavior of the memristor deviates from the desired values as a result of process changes. As a result, the yield of a memristor-based memory design is lowered as a result. Also discussed in this study is a concrete model of a spintronic device that is based on the mechanism of magnetic-domain-wall motion and is described in detail.","PeriodicalId":113266,"journal":{"name":"2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129718963","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}

引用次数: 2

Applications of Statistical Machine Learning Algorithms in Agriculture Management Processes 统计机器学习算法在农业管理过程中的应用

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609476

Karri Divya Jyothi, M. Sekhar, Sanjeev Kumar

{"title":"Applications of Statistical Machine Learning Algorithms in Agriculture Management Processes","authors":"Karri Divya Jyothi, M. Sekhar, Sanjeev Kumar","doi":"10.1109/ISPCC53510.2021.9609476","DOIUrl":"https://doi.org/10.1109/ISPCC53510.2021.9609476","url":null,"abstract":"In any country's economic growth, agriculture plays a crucial function. In crops management, machine learning techniques are mainly employed, following the control of farming conditions and the management of animals. They are used in agriculture to anticipate crop yield and quality and the production of livestock. As the population increases, the climate changes are frequent and the resources are limited, it becomes a challenge to meet food demands of the people today. Machine learning (ML) is the mechanism for driving this advanced technology. It allows to the machine for learn without being programmed directly. The agricultural machinery enabled by ML and Internet of Things (IoT) is an important part of the future farm revolution. There has been a rigorous discussion on IOT based network technology involving network architecture and layers. In this research paper described a systematic examination of agricultural with ML applications. The focus areas are the prediction of soil factors including organic carbon and moisture content in the prediction of crop yields, diseases and the detection of weeds in crops as well as species.","PeriodicalId":113266,"journal":{"name":"2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134496021","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}

引用次数: 3

A Design of Customer Service Request Desk to Improve the Efficiency using Robotics Process Automation 利用机器人过程自动化提高客户服务请求台效率的设计

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609338

N. Goyal, Harpreet Singh

引用次数: 1

Compact ten element antenna array for thin 5G smartphone applications 紧凑型十元天线阵列，适用于超薄5G智能手机应用

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609508

Vishakha Thakur, Naveen Jaglan, S. D. Gupta

引用次数: 0

Design of Global Interconnects using Adiabatic Dynamic Logic employing FinFET Technology 采用FinFET技术的绝热动态逻辑全局互连设计

2021 6th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2021-10-07 DOI: 10.1109/ISPCC53510.2021.9609385

Himani Bhardwaj, Shruti Jain, Harsh Sohal

{"title":"Design of Global Interconnects using Adiabatic Dynamic Logic employing FinFET Technology","authors":"Himani Bhardwaj, Shruti Jain, Harsh Sohal","doi":"10.1109/ISPCC53510.2021.9609385","DOIUrl":"https://doi.org/10.1109/ISPCC53510.2021.9609385","url":null,"abstract":"CMOS technology has been dominating VLSI design for a few decades. Although, it provides high speed and packing density, there also arises the problem of short channel effects as we scale down the technology size. Also, with the decrease in technology size, power consumption issues have started to dominate which further increases as the technology reaches to deep sub-micron level. This is one of the factors which provide a cause to switch to advanced technologies like FinFETs. FinFETs are used to reduce leakage currents but also proves to be a promising technology in terms of power consumption. In this paper, digital inverters are presented using MOSFET technology and FinFET technology. Further, the inverter circuits are implemented using adiabatic dynamic logic to conserve power consumption. These inverter circuits are inserted in between the interconnect circuits as an application. The circuits are implemented using 45nm technology with the input supply of 1V. The proposed interconnect circuit using ADL CMOS inverter using FinFET technology shows 62% decrease in power consumption as compared to the interconnect circuit using ADL Schmitt trigger circuit.","PeriodicalId":113266,"journal":{"name":"2021 6th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134540922","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}

引用次数: 1