2022 IEEE VLSI Device Circuit and System (VLSI DCS)最新文献_第5页

DC and Analog/RF Performance Comparison of Renovated GAA JLFET Structures 改进GAA JLFET结构的直流和模拟/射频性能比较

2022 IEEE VLSI Device Circuit and System (VLSI DCS) Pub Date : 2022-02-26 DOI: 10.1109/vlsidcs53788.2022.9811488

Sudipta Ghosh, Abhiroop Jana, Agnivesh Kumar Agnihotri, Shirsha Kundu, Dyuti Das, S. Sarkar

引用次数: 1

ZnO-WO3 Mixed Metal Thin Film Capacitive Biosensor for Food Quality Measurement 用于食品质量检测的ZnO-WO3混合金属薄膜电容式生物传感器

2022 IEEE VLSI Device Circuit and System (VLSI DCS) Pub Date : 2022-02-26 DOI: 10.1109/VLSIDCS53788.2022.9811441

G. Jana, J. Nandy, Moumita Chakraborty, Subhashis Roy, B. Kantha

引用次数: 0

DC and Analog/RF Performance Analysis of Gate-Drain Underlapped and Channel Engineered TFET 栅极-漏极叠加和通道工程ttfet的直流和模拟/射频性能分析

2022 IEEE VLSI Device Circuit and System (VLSI DCS) Pub Date : 2022-02-26 DOI: 10.1109/VLSIDCS53788.2022.9811483

Sudipta Ghosh, Sayan Bose, Wahid Anwar, Madhusree Banerjee, P. Venkateswaran, S. Sarkar

{"title":"DC and Analog/RF Performance Analysis of Gate-Drain Underlapped and Channel Engineered TFET","authors":"Sudipta Ghosh, Sayan Bose, Wahid Anwar, Madhusree Banerjee, P. Venkateswaran, S. Sarkar","doi":"10.1109/VLSIDCS53788.2022.9811483","DOIUrl":"https://doi.org/10.1109/VLSIDCS53788.2022.9811483","url":null,"abstract":"In this paper, the DC and RF performance of a dual material double gate-drain underlapped tunnel FET (DMUDG TFET) and a DMUDG TFET with channel pocketing (DMUDG-CP TFET) are analyzed. It has been shown in the work that the proposed devices delivered a high ON current without compromising the ambipolar current of a conventional DMDG TFET. The proposed structural engineering served the device to have a reasonably good subthreshold swing (SS) and optimize the gate capacitance and gate-to-drain capacitance. The electrical characteristics of the proposed devices are analyzed in terms of subthreshold swing, ambipolar current, intrinsic capacitances, cut-off frequency, and transconductance. The work aims to improve the analog performance of the proposed devices without forfeiting the digital performance much. A detailed simulation study of the proposed structures is performed using the Silvaco Atlas 2-D device simulator and compared with existing structures of contemporary literature. The study reveals that the proposed structures can be utilized in RF applications and low-power VLSI applications as well.","PeriodicalId":307414,"journal":{"name":"2022 IEEE VLSI Device Circuit and System (VLSI DCS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124414660","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

K Nearest Neighbor and Flexible Neural Tree Based IDS in Mobile Ad- hoc Network 移动自组织网络中基于K近邻和柔性神经树的入侵检测

2022 IEEE VLSI Device Circuit and System (VLSI DCS) Pub Date : 2022-02-26 DOI: 10.1109/VLSIDCS53788.2022.9811467

Indrajit Das, Piyali Roy, Debanjan Das, Sayan Das, P. Ghosal

{"title":"K Nearest Neighbor and Flexible Neural Tree Based IDS in Mobile Ad- hoc Network","authors":"Indrajit Das, Piyali Roy, Debanjan Das, Sayan Das, P. Ghosal","doi":"10.1109/VLSIDCS53788.2022.9811467","DOIUrl":"https://doi.org/10.1109/VLSIDCS53788.2022.9811467","url":null,"abstract":"Mobile ad-hoc networks (MANETs) have brought about a lot of importance to recent researches because of its popularity and developing benefit. However, they seem to be defenseless against the various security threats that decrease their efficiency in comparison to other networks, by all accounts. Intrusion Detection Systems (IDS) creates a second line of safeguard against the various vulnerabilities to MANETs, as they scan the network for malicious activities performed by attackers. Because of the distributed characteristic of MANET, traditional cryptography mechanisms cannot shield MANETs entirely as far as novel attacks and vulnerabilities are concerned. Hence by applying machine learning strategies for IDS, these difficulties can be resolved. In this paper, numerous research works based on ML techniques over four types of attacks (DOS, Probe, U2R and R2L) have been reviewed and their performance is observed. From the above reviewed work, it can be inferred that KNN and FNT algorithm would perform better than the rest. After applying KNN and FNT in the proposed intrusion detection MANET model, KNN performed better than FNT. Accuracy of KNN for detection of DOS, Probe, U2R and R2L was 99.24%, 99.13, 98.89% and 98.42% respectively, whereas accuracy of FNT for detection of the same attacks was 98.35%, 98.07%, 97.84% and 98.01% respectively. So the detection accuracy of KNN is better than FNT. For KNN, the TP, FP, FN and precision value is 0.931, 0.015, 0.063 and 0.983 respectively , whereas for FNT, the TP, FP, FN and precision value is 0.815, 0.153, 0.274 and 0.826 respectively. From these above results, it is clear that KNN is better than FNT as the True Positive value and Precision is higher while the False Positive value and False Negative value is lower for KNN.","PeriodicalId":307414,"journal":{"name":"2022 IEEE VLSI Device Circuit and System (VLSI DCS)","volume":"os-56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127717728","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

Emergency Medical Assistance by Ambulance Drone Using Machine Learning, Light-Weight Cryptography and Variable Image Steganography 救护车无人机使用机器学习，轻量级加密和可变图像隐写的紧急医疗援助

2022 IEEE VLSI Device Circuit and System (VLSI DCS) Pub Date : 2022-02-26 DOI: 10.1109/VLSIDCS53788.2022.9811471

Indrajit Das, Sanjoy Roy, Sumagna Dey, Tulsi Dey, Piyali Roy

{"title":"Emergency Medical Assistance by Ambulance Drone Using Machine Learning, Light-Weight Cryptography and Variable Image Steganography","authors":"Indrajit Das, Sanjoy Roy, Sumagna Dey, Tulsi Dey, Piyali Roy","doi":"10.1109/VLSIDCS53788.2022.9811471","DOIUrl":"https://doi.org/10.1109/VLSIDCS53788.2022.9811471","url":null,"abstract":"A huge amount of people suffer or eventually die every day waiting for the rescue vehicle to reach the spot on time. The primary cause for this delay is traffic jams, blockage in streets, inaccessibility of ambulance and so forth. An emergency ambulance drone or UAV (Unmanned Aerial Vehicle) could be a better feasible solution to this problem travel the aerial path and is unaffected by any terrestrial obstacles, as proposed in this paper. The ambulance drone would be controlled by a human sitting in the hospital control room. This would be the quickest possible medical assistance in case of an emergency. The drone would carry medical aid and using the patient's GPS location, which it receives from the mobile application, can reach the spot without any hindrance. Thereafter the drone can start the audio and video streaming of patient's data to the hospitals, medical centers and necessary instructions can be communicated to the nearby spectators or local doctors for using the right equipment (ECG, Pulse Sensor, Oximeter, etc) for patients diagnosis and detect the face with Haar cascade classifier and recognize the face with LBPH algorithm. In this, a comparative study has been done over face recognition between still and video images, the average accuracy of still and video images is 99.4% and 99.34% respectively. Also, for the situation, when doctors are not present in the hospital, an autonomous system has been designed with the help decision tree that can determine the probable cause of the disease by the patient. The secure information transfer is done via lightweight cryptography and Variable MSB – LSB Image steganography.","PeriodicalId":307414,"journal":{"name":"2022 IEEE VLSI Device Circuit and System (VLSI DCS)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134399740","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

Assessment of Filter Design for 5G Applications 5G应用滤波器设计评估

2022 IEEE VLSI Device Circuit and System (VLSI DCS) Pub Date : 2022-02-26 DOI: 10.1109/vlsidcs53788.2022.9811462

G. Bhargava, S. Majumdar

引用次数: 0

Enhanced Prediction of Thyroid Disease Using Machine Learning Method 使用机器学习方法增强甲状腺疾病的预测

2022 IEEE VLSI Device Circuit and System (VLSI DCS) Pub Date : 2022-02-26 DOI: 10.1109/vlsidcs53788.2022.9811472

Madhumita Pal, Smita Parija, G. Panda

{"title":"Enhanced Prediction of Thyroid Disease Using Machine Learning Method","authors":"Madhumita Pal, Smita Parija, G. Panda","doi":"10.1109/vlsidcs53788.2022.9811472","DOIUrl":"https://doi.org/10.1109/vlsidcs53788.2022.9811472","url":null,"abstract":"Thyroid disease is becoming increasingly in men, women and children but commonly occurring among women over the age of 30. It causes heart problem, eye problem, fertility and pregnancy problems over its effect for long time. As a result, it is critical to evaluate the thyroid information in order to forecast the early prediction of disease and take steps to avoid the deadly condition of thyroid cancer. This study is based upon designing a model for timely detection of thyroid disease by observing the features from thyroid disease dataset which was accessed from UCI repository site by using machine learning algorithms. We have used three machine learning models such as K-Nearest Neighbors (K- NN), decision tree (DT) and multilayer perceptron (MLP) for prediction of thyroid disease and measure the performance of these models in form of accuracy and area under the curve. Comparative analysis of these three models reveals that MLP performs better in classifying thyroid disease with an accuracy value of 95.73 and Area Under the curve with value of 94.23. The planned experiment was carried out on 3163 cases and 24 thyroid characteristics.","PeriodicalId":307414,"journal":{"name":"2022 IEEE VLSI Device Circuit and System (VLSI DCS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132890517","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

VLSI DCS 2022 Cover Page VLSI DCS 2022封面页

2022 IEEE VLSI Device Circuit and System (VLSI DCS) Pub Date : 2022-02-26 DOI: 10.1109/vlsidcs53788.2022.9811454

引用次数: 0

Effect of Asymmetric Space Charge Region on Current Densityof Heterojunction Solar Cell 非对称空间电荷区对异质结太阳能电池电流密度的影响

2022 IEEE VLSI Device Circuit and System (VLSI DCS) Pub Date : 2022-02-26 DOI: 10.1109/VLSIDCS53788.2022.9811453

Sayoni Chakraborty, A. Deyasi

引用次数: 0

Study the Sensing Performance with Catalytic Metals of Passivated InAlN/GaN Schottky Diode Gas Sensor 钝化InAlN/GaN肖特基二极管气体传感器的金属催化传感性能研究

2022 IEEE VLSI Device Circuit and System (VLSI DCS) Pub Date : 2022-02-26 DOI: 10.1109/VLSIDCS53788.2022.9811443

Bhaskar Roy, M. A. Billaha, R. Dutta, Debasis Mukherjee

{"title":"Study the Sensing Performance with Catalytic Metals of Passivated InAlN/GaN Schottky Diode Gas Sensor","authors":"Bhaskar Roy, M. A. Billaha, R. Dutta, Debasis Mukherjee","doi":"10.1109/VLSIDCS53788.2022.9811443","DOIUrl":"https://doi.org/10.1109/VLSIDCS53788.2022.9811443","url":null,"abstract":"In this proposed work, InAlN/GaN Schottky hetero-structure diode has been inspected using a physics-based analytical modeling approach for highly linear and sensitive gas sensing applications. Here, the hetero-interface and surface attributes are taken into considerations. The device is primarily modeled using 2-DEG’s reliance on the surface charges, which is reliant on the Sc2O3 passivation layer. The electrode of the gas sensor plays a key part in determining the sensitivity and other vital parameters of the sensors. The proposed structure of the Schottky diode with catalytic electrodes such as Pd, Pt, and other metals on GaN-based sensors has been studied. A Silvaco TCAD simulation tool is used to simulate the Schottky diode-based sensor model and we obtained I-V curves in the presence of different gas concentrations. On biasing voltage of 0.95 V, the I-V curves show a response of nearly 75% in the influence of 500 ppm gas concentration. Also, we observed the change in the sensor response with the temperature at different gas concentrations for various Schottky contacts.","PeriodicalId":307414,"journal":{"name":"2022 IEEE VLSI Device Circuit and System (VLSI DCS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114901734","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