2019 IEEE Conference on Information and Communication Technology最新文献_第2页

A Defocus Based Novel Keyboard Design 基于散焦的新型键盘设计

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066224

Priyanshu Gupta, Tushar Goswamy, Himanshu Kumar, K. Venkatesh

引用次数: 1

AN INTRODUCTION AND REVIEW ON MACHINE LEARNING APPLICATIONS IN MEDICINE AND HEALTHCARE 机器学习在医学和医疗保健中的应用综述

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066250

Preeti Singh, S. Singh, D. Singh

{"title":"AN INTRODUCTION AND REVIEW ON MACHINE LEARNING APPLICATIONS IN MEDICINE AND HEALTHCARE","authors":"Preeti Singh, S. Singh, D. Singh","doi":"10.1109/CICT48419.2019.9066250","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066250","url":null,"abstract":"Machine learning techniques can extensively apply in the solution of the medicine domain problems by applying classification models and systems that can support medical personnel in the diagnosis and predication of diagnosis diseases. Though, it's hard to extract knowledge and information from medical records and data because this data and information is in mixed, unorganized, and high dimensional. This data also contains noise in collected data and outliers exist in collected data. Main applicable method will be used applies by checking different machine learning techniques. The performance of machine learning technique is checked by verifying and validating machine learning techniques' performances through accuracy. Present research paper has been discussing about the usability and applicability of different machine learning techniques i.e. decision tree algorithm, support vector machine method, random forest method, evolutionary algorithms based models and swarm intelligence based techniques in the diagnosis and treatment of the diseases. Advance medical diagnosis criteria generates confidence in diagnosis by using imagining techniques in the diagnosis of a disease is extensively used by doctors. In view of the fact that analyzing medical images is very complex and difficult task, by using machine learning methods for analysis of imaging will support and give major help in disease diagnosis. Application of different Machine learning methods is used by applying its techniques on big data for interpretation for diagnosis because machine learning methods show their capability and shows their easiness to solve the problems of bioinformatics domain.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131305667","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: 10

A new method of multi color image encryption 一种新的多色图像加密方法

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066198

Anand Ballabh Joshi, Dhanesh Kumar

引用次数: 5

Regularised Encoder-Decoder Architecture for Anomaly Detection in ECG Time Signals 用于心电时间信号异常检测的正则化编码器-解码器结构

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066261

Ashutosh Chandra, R. Kala

{"title":"Regularised Encoder-Decoder Architecture for Anomaly Detection in ECG Time Signals","authors":"Ashutosh Chandra, R. Kala","doi":"10.1109/CICT48419.2019.9066261","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066261","url":null,"abstract":"Electrocardiography(ECG) is a procedure to record the electrical activity of the human heart. The recorded time series ECG signal are often used by medical professionals to detect any arrhythmia the subject may have. Work has been done to automate the task by modelling the problem as anomaly detection using encoder-decoder based techniques, training on just normal data and using distribution of loss to predict normal or abnormal data. We argue that normal encoder-decoder with just reconstruction loss suffers from two problem: 1. Latent vector is not smooth and continuous, which might lead to memorising signals 2. Network is prone to outliers as mean squared error is used for reconstruction loss. We propose a regularised encoder-decoder based architecture with KL divergence as regulariser for latent vector which solves the above two problem. The regulariser will enforce the network to minimise the distance between latent vector distribution and normal distribution, hence making latent vector smooth and continuous, at the same time as diverse as possible. We have experimented with various architectures such as Multilayer Perceptrons, Recurrent Neural Networks, Long Short Term Memory Networks, 1D Convolutional Neural Networks for encoder and decoder and found that regularised network outperforms normal network in all the cases. More specifically our regularised network with F1-score of 0.90 outperformed the current state of art for ECG anomaly detection which uses Long Short Term Memory networks for both encoder and decoder, resulting in F1-score of 0.88. As a result we present a regularise encoder-decoder network in this paper which outperforms current techniques for anomaly detection on ECG data.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121304300","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

An Approach for Human Machine Interaction using Dynamic Hand Gesture Recognition 基于动态手势识别的人机交互方法

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066173

Aquib Ansari, D. Singh

引用次数: 8

Design Automation of 5-T OTA using gm/ID methodology 使用gm/ID方法设计5-T OTA自动化

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066119

T. B. Kumar, Gopal Sharma, A. Johar, Deepak Gupta, S. Kar, D. Boolchandani

引用次数: 4

UWB Monopole Antenna with Triple-Band Notch Rejection 带三波段陷波抑制的超宽带单极天线

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066183

Abhishek J Patel, M. Parihar

引用次数: 5

Decentralized Patient Centric e- Health Record Management System using Blockchain and IPFS 使用区块链和IPFS的分散式以患者为中心的电子健康记录管理系统

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066212

Gaganjeet Singh Reen, Manasi Mohandas, S. Venkatesan

引用次数: 20

Smart Platform for Film Shooting Management 电影拍摄管理智能平台

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066193

S. Senarath, M.T.K. Perera, D.G.R. Viduranga, H.M.C.S. Wijayananda, W. Rankothge

引用次数: 4

Optimized Hybrid Clustered Protocol for IoT Heterogeneous Wireless Sensor Networks 物联网异构无线传感器网络的优化混合集群协议

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066258

R. Prakash, Parul Kansal, Varun Kumar Kakar

{"title":"Optimized Hybrid Clustered Protocol for IoT Heterogeneous Wireless Sensor Networks","authors":"R. Prakash, Parul Kansal, Varun Kumar Kakar","doi":"10.1109/CICT48419.2019.9066258","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066258","url":null,"abstract":"For the past few years, the Wireless Sensor Networks (WSNs) have become very popular because of the advancements and innovation in the micro-electro-mechanical system (MEMS) which creates more opportunities to utilize the WSN with their outstanding capability of sensing various type of environments as well as other physical conditions. WSN consists of huge number of small and less expensive sensor nodes, these nodes communicate with one another with different set of rules called protocols. Performance of these sensor nodes generally affected by some set of rules by which they perform in the network these are called protocols. Nodes are mostly operated on battery power therefore the energy utilization will always be the prime concern of WSNs. The Same analogy is applied for the WSN in the Cyber-Physical system and for IoT environment where different types of nodes or end devices have been found with different amount of initial energy. This paper optimizes the existing routing protocol and proposes a different protocol with improvised features such as new data relaying scheme and improved CHs selection procedure. Thereby linking the difference between the real world Wireless Sensor Networks and the genuine heterogeneous environment. The simulation results shows the comparison between the Hy-IoT and proposed protocol by using the performance measures shown in the result section.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128014136","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