2022 Smart Technologies, Communication and Robotics (STCR)最新文献_第3页

Optimised Hardware Implementation of AES for Improving Energy Efficiency of Low-Power Devices 优化AES硬件实现，提高低功耗器件的能效

2022 Smart Technologies, Communication and Robotics (STCR) Pub Date : 2022-12-10 DOI: 10.1109/STCR55312.2022.10009468

Naseer Ahmad Lone, Mir Nazish, Ishfaq Sultan, M. T. Banday

{"title":"Optimised Hardware Implementation of AES for Improving Energy Efficiency of Low-Power Devices","authors":"Naseer Ahmad Lone, Mir Nazish, Ishfaq Sultan, M. T. Banday","doi":"10.1109/STCR55312.2022.10009468","DOIUrl":"https://doi.org/10.1109/STCR55312.2022.10009468","url":null,"abstract":"Most commercial ultra-low power microcontrollers available in the market have inbuilt circuitry for crypto operations, radio for transmission and multiple sleep modes. Sleep modes put the processor into sleep mode while using integrated peripherals, thereby saving the power and battery life of the constrained devices. The add-on circuitry in the microcontrollers has promised higher security at extremely low power by optimising the sleep modes using low-level programming. Dedicated hardware blocks carry out most encryption techniques within the processor for energy, time, and memory efficiency. This necessitates the power optimisation in embedded applications to be an integral part of the development process for overall efficiency, as it is essential to understand how crypto accelerators, software algorithms, and power-saving modes work together. In this work, different optimisation techniques have been adopted to enhance the power consumption of EFM32PG12, an IoT hardware platform developed by Silicon Labs, using sleep modes and the hardware accelerator of the board. The sleep modes have been utilised in the AES encryption algorithm to reduce the overall power consumption on a hardware mote. The combination of the hardware accelerator and the sleep modes significantly improved the performance and reduced the power consumption of AES encryption and decryption on the hardware platform.","PeriodicalId":338691,"journal":{"name":"2022 Smart Technologies, Communication and Robotics (STCR)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133173542","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

Improved Local Vector Pattern Descriptor for Face Recognition 改进的局部矢量模式描述符人脸识别

2022 Smart Technologies, Communication and Robotics (STCR) Pub Date : 2022-12-10 DOI: 10.1109/STCR55312.2022.10009318

M. Abdullah, S. Prakash, Kedir Beshir, Alemayehu Kebede Abebe, Habtemarium Hailu Takore

{"title":"Improved Local Vector Pattern Descriptor for Face Recognition","authors":"M. Abdullah, S. Prakash, Kedir Beshir, Alemayehu Kebede Abebe, Habtemarium Hailu Takore","doi":"10.1109/STCR55312.2022.10009318","DOIUrl":"https://doi.org/10.1109/STCR55312.2022.10009318","url":null,"abstract":"With the rising demands of visual observation systems, vehicle and public recognition at a distance has gained extra notice for the researchers in recent times. Real-world face recognition systems require cautious balancing of two important concerns: Elapse Time, recognition rate. In this paper Improved Local Vector Pattern (ILVP) feature extraction technique and Nearest Neighbor (NN) classification techniques are worked out to improve the recognition rate as well as to enhance the computational time. The Improved Local Vector Pattern (ILVP) computes the values between the adjacent pixels and β reference pixels in various distance D and different direction for every pixel. A micropattern is created with respect to the reference pixels using Comparative Space Transform (CST). CST is used to encode the spatial information of a face image into binary pattern. The binary patterns generated using CST is lower when compared to the number of binary patterns generated using Local Multi Code Pattern (LMCP). ILVP generates 8(8×1) binary patterns for each pixel. These binary patterns are collected by histogram bins. ILVP outperforms the existing LVP for ORL face dataset.","PeriodicalId":338691,"journal":{"name":"2022 Smart Technologies, Communication and Robotics (STCR)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122084555","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

GM-LAMP with Residual Learning Network for Millimetre Wave MIMO Architectures 毫米波MIMO结构的残差学习网络GM-LAMP

2022 Smart Technologies, Communication and Robotics (STCR) Pub Date : 2022-12-10 DOI: 10.1109/STCR55312.2022.10009163

S. k, P. T, Sajan P Phihlip, L. M, Poongodi C

引用次数: 0

A Novel Microwave Imaging using Flexible Triangular Fractal Monopole and Antipodal Vivaldi Antennas 一种利用柔性三角形分形单极子和对映维瓦尔第天线的新型微波成像方法

2022 Smart Technologies, Communication and Robotics (STCR) Pub Date : 2022-12-10 DOI: 10.1109/STCR55312.2022.10009593

Satheesh Kumar S, Vanathi P T

引用次数: 0

PV Array Reconfiguration Methods based on Game Theory to Eliminate Shading Effect during Non-uniform Irradiations: Experimental Feasibility 基于博弈论的光伏阵列重构方法消除非均匀照射时遮阳效应:实验可行性

2022 Smart Technologies, Communication and Robotics (STCR) Pub Date : 2022-12-10 DOI: 10.1109/STCR55312.2022.10009493

R. Pachauri, A. Minai, P. Kuchhal, Vandana Jha, Shashikant

引用次数: 0

A PD ANN Machine Learning Framework for Reliability Optimization in Application Software 应用软件可靠性优化的PD - ANN机器学习框架

2022 Smart Technologies, Communication and Robotics (STCR) Pub Date : 2022-12-10 DOI: 10.1109/STCR55312.2022.10009626

Sudharson D, D. P, Ratheeshkumar M, S. A., Nithiyashree V K, S. J

引用次数: 2

Performance Breakdown and Redistribution Amidst OSPF, EIGRP & IS-IS Dynamic Routing Protocols in IPv6 Network IPv6网络中OSPF、EIGRP和IS-IS动态路由协议的性能分解与重分配

2022 Smart Technologies, Communication and Robotics (STCR) Pub Date : 2022-12-10 DOI: 10.1109/STCR55312.2022.10009222

G. C, Banupriya N, Nagarajan N

引用次数: 0

Stimuli based Paralyzed Patient Monitor 基于刺激的瘫痪病人监测器

2022 Smart Technologies, Communication and Robotics (STCR) Pub Date : 2022-12-10 DOI: 10.1109/STCR55312.2022.10009479

B. Sakthivel, R. Sneha, M. Vijayalakshmi, B. Vidhya, H. Harshene

{"title":"Stimuli based Paralyzed Patient Monitor","authors":"B. Sakthivel, R. Sneha, M. Vijayalakshmi, B. Vidhya, H. Harshene","doi":"10.1109/STCR55312.2022.10009479","DOIUrl":"https://doi.org/10.1109/STCR55312.2022.10009479","url":null,"abstract":"The issues in the peripheral nervous system and central nervous systems leads to paralysis. Motor neurons send electrical signals to muscles, causing them to contract. Nerves that are not harmed provide information to muscles. Muscles move as a result of these impulses. The inability to perform these voluntary motions is known as paralysis. Strokes, spinal cord injuries, and multiple sclerosis like pain, fatigue are all common causes of paralysis. Physical therapy (using muscle stimulators), occupational therapy and nerve transfer surgery are all viable therapies for paralysis. Neuromuscular electrical stimulation is a technique for causing paretic muscles to contract using an electrical current that can efficiently produce muscle contractions which are used on paralyzed patients. Electromyograms are used to evaluate the electrical activity in response to nerve stimulation of the muscle. EMG data can be used to examine the disorders of nerve, muscles and communication between them. The proposed system uses an EMG in conjunction with a muscle stimulator to detect the muscle movement of the patient through which the physiotherapist will be able to treat the muscle with proper intensity and stimulate it better. This will help to increase the recovery rate of the patient.","PeriodicalId":338691,"journal":{"name":"2022 Smart Technologies, Communication and Robotics (STCR)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121032821","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

Predicting Breast Cancer Malignancy using Deep Neural Networks 使用深度神经网络预测乳腺癌恶性

2022 Smart Technologies, Communication and Robotics (STCR) Pub Date : 2022-12-10 DOI: 10.1109/STCR55312.2022.10009523

S. V, G. Vadivu

引用次数: 1

Performance Analysis of Cat Swarm Optimization with Soft Discriminant Classifier for Diagnosis of Epilepsy using EEG Signals 基于软判别分类器的Cat群算法在脑电信号癫痫诊断中的性能分析

2022 Smart Technologies, Communication and Robotics (STCR) Pub Date : 2022-12-10 DOI: 10.1109/STCR55312.2022.10009226

H. Rajaguru, G. M., Rishikesan J, S. K

{"title":"Performance Analysis of Cat Swarm Optimization with Soft Discriminant Classifier for Diagnosis of Epilepsy using EEG Signals","authors":"H. Rajaguru, G. M., Rishikesan J, S. K","doi":"10.1109/STCR55312.2022.10009226","DOIUrl":"https://doi.org/10.1109/STCR55312.2022.10009226","url":null,"abstract":"A seizure caused by epilepsy is characterized by the rapid excitation of a significant number of neuronal cells in quick succession. Patients have a great deal of difficulties as a result of an unanticipated anomalous function that occurs in their brains. Due to the neurons' high rate of electrical discharge, the usual bodily functions are greatly perturbed. Electroencephalography (EEG), a visual representation of these electrical brain movements, is used to record them. In this study, dimensionality reduction and feature extraction algorithms are used to minimize the dimensionality of EEG data. The Power Spectral Density (PSD) and Singular Value Decomposition (SVD) algorithms are employed to lower dimensionality. The Cat Swarm Optimization (CSO) algorithm is employed as a feature extraction method. Softmax Discriminant classifier is used to identify epilepsy. Results show that the when PSD with CSO is identified with soft discriminant classifier model gives the best accuracy of 97.19%. When SVD with CSO is identified with soft discriminant classifier model gives the accuracy of 95.55%.","PeriodicalId":338691,"journal":{"name":"2022 Smart Technologies, Communication and Robotics (STCR)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126365007","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