2019 IEEE Conference on Information and Communication Technology最新文献_第6页

Partitioned Based Image Segmentation 基于分割的图像分割

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066268

S. Shrivastava, Ajay Kumar

引用次数: 1

Classification of Arrhythmia using Time-domain Features and Support Vector Machine 基于时域特征和支持向量机的心律失常分类

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066181

M. Dhaka, Poras Khetarpal

{"title":"Classification of Arrhythmia using Time-domain Features and Support Vector Machine","authors":"M. Dhaka, Poras Khetarpal","doi":"10.1109/CICT48419.2019.9066181","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066181","url":null,"abstract":"Cardiac arrhythmia is a heart condition where the heart does not beat in a regular way. This is one of those diseases which are easy to diagnose. A doctor can detect arrhythmia by just looking at the Electrocardiogram (ECG) of the patient because it has many visual clues, which a doctor is trained to identify. All these visual clues are the time-domain feature. Hence, in this paper, an algorithm is presented which uses only time-domain features to classify between normal sinus rhythm and arrhythmia using Support Vector Machine (SVM). The paper also compares the classification results when the frequency domain features are used along with the time-domain features. The frequency-domain features increase the computational complexity of the algorithm and make it harder to create a portable and reliable hardware device for the realtime detection and classification of arrhythmia. The proposed algorithm can be incorporated in a portable, lightweight and robust device which can detect arrhythmia in real-time. The accuracy of the algorithm is 99.36% on MIT-BIH arrhythmia database, which in comparison to other algorithm is an improvement.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"28 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":"127484929","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

Certificate-less Public Key Encryption For Secure e-Healthcare Systems 用于安全电子医疗保健系统的无证书公钥加密

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066190

Mayank K. Aditia, Srikar Paida, Fahiem Altaf, Soumyadev Maity

引用次数: 1

Defect Classification for Silk Fabric Based on Four DFT Sector Features 基于四种DFT扇形特征的真丝织物缺陷分类

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066106

Shweta Loonkar, D. Mishra

{"title":"Defect Classification for Silk Fabric Based on Four DFT Sector Features","authors":"Shweta Loonkar, D. Mishra","doi":"10.1109/CICT48419.2019.9066106","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066106","url":null,"abstract":"We cannot imagine a world without textile and textile industry. Vital role is played by textile industry in today's world of business. Quality inspection, reliability, durability and fabric with less defects are an important factors for good apparel organizations. Fabric defect classification holds an inimitable position in demand of worthy products. In this paper we have experimented to classify the fabric defects for silk material based on its structural failures. We have used the DFT sectorization process on TILDA textile images to extract features in order to classify the defects. The Feature Vector Database (FVDB) is generated by means of four DFT sectors. FVDB is used as input in WEKA for defect classification based on two test options i.e. 10-fold cross validation and full training set. It has been observed that the rate of classification for silk cloth declines in 10-fold cross validation as compared to full training set. All characterization calculations are analyzed dependent on their accuracy and Kappa statistics. It has been observed that the Random Forest is most efficient algorithm for defect classification for silk fabric due to its high rate of classification.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"640 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":"116687681","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

Performance analysis of MIMO-NOMA-Based Indoor Visible Light Communication in Single Reflection Environment 单反射环境下基于mimo - noma的室内可见光通信性能分析

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066201

A. Mishra, A. Trivedi

引用次数: 2

Efficient Method for Data Synchronization in Mobile Database 移动数据库中有效的数据同步方法

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066122

Nidhi Singh, M. Hasan

引用次数: 1

Fusion of Heterogeneous Range Sensors Dataset for High Fidelity Surface Generation 面向高保真曲面生成的异构距离传感器数据集融合

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066172

M. Singh, K. Venkatesh, A. Dutta

引用次数: 0

Decentralised and Distributed System for Organ/Tissue Donation and Transplantation 器官/组织捐赠和移植的分散式和分布式系统

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066225

Pratyush Ranjan, Shubhanker Srivastava, Vidit Gupta, S. Tapaswi, Neetesh Kumar

{"title":"Decentralised and Distributed System for Organ/Tissue Donation and Transplantation","authors":"Pratyush Ranjan, Shubhanker Srivastava, Vidit Gupta, S. Tapaswi, Neetesh Kumar","doi":"10.1109/CICT48419.2019.9066225","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066225","url":null,"abstract":"In today's era of digitisation, many technologies have evolved that every manual work can be digitally automatized. In the digital automatizing process, security and privacy are the most important and highly demanding aspects. Blockchain offers many features that can be used in almost every sphere of life. Features like decentralisation, transparency, privacy makes it an extremely useful technology. Therefore, by making use of all these features, several problems in healthcare sector can be solved like removing complex network of third parties and lack of traceability of transactions. This paper presents a decentralised, secure and transparent organ and tissue transplant web application (also called DApp), which not only nullifies the role of any third party involved in the organ transplantation, but also is a cost effective solution that saves the patient's from high cost of transplantation. The details and Electronic Medical Record(EMR) are hashed using the IPFS(a distributed file server), which reduces the cost of upload to a great extent as shown in the results section of this paper.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"13 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":"114560684","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: 7

Thinning of Concentric Circular Antenna Array Using Binary Salp Swarm Algorithm 基于二元Salp群算法的同心圆形天线阵列减薄

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066249

A. Mondal, Prerna Saxena

引用次数: 5

Analysis of Multitasking in Divided Attention using Machine Learning 用机器学习分析分散注意下的多任务处理

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066233

Bhanu Pratap Singh Bankoti, C. Gupta, O. Bandyopadhyay, Mallika Banerjee

{"title":"Analysis of Multitasking in Divided Attention using Machine Learning","authors":"Bhanu Pratap Singh Bankoti, C. Gupta, O. Bandyopadhyay, Mallika Banerjee","doi":"10.1109/CICT48419.2019.9066233","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066233","url":null,"abstract":"Evaluation of cognitive functionality plays an important role in the career choice of students as well as for the selection of employee for the employer. Divided attention is one such cognitive ability that deals with allocation of attention to multiple tasks simultaneously. An accurate analysis of divided attention would help us to identify cognitive decline, as well as provides a quantifiable indicator of a salient feature viz., vigilance which is highly relevant for defence personnel as well as pilots in air, water and road. The close observation of divided attention in home or classroom environment is an essential component for early detection of cognitive problems. It also helps in assessing the effectiveness of learning patterns. This work proposes a new method to determine the ability of relative divided attention through unobtrusive monitoring of use of a software game. The process measures the performance of a user (college student) on a multi-task cognitive software by computing the scores as part of the test for divided attention. This metric indicates the user's ability of multitasking in divided attention, i.e whether user is efficiently paying attention to all the tasks at once, or is primarily attending to one task at a time (sacrificing optimal performance). The data set is labelled based on statistical analysis. After classifying the data using machine learning model (random forest), the academic performance of the user is analysed against the divided attention levels to establish a correlation among them.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"37 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":"122640919","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