2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)最新文献_第6页

Quarantine Quibbles: A Sentiment Analysis of COVID-19 Tweets 检疫问题:对COVID-19推文的情绪分析

2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Pub Date : 2020-11-04 DOI: 10.1109/IEMCON51383.2020.9284875

Jason Nguyen, Ritu Chaturvedi

引用次数: 3

Design of an IoT interface for a solar energy system with vehicle to home option for Newfoundland conditions 为纽芬兰条件下具有车到家选项的太阳能系统设计物联网接口

2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Pub Date : 2020-11-04 DOI: 10.1109/IEMCON51383.2020.9284859

R. Sundararajan, M. Iqbal

引用次数: 1

A Single-Tier Fog Architecture for Delay-Sensitive and Computation-Intensive SFC Requests 用于延迟敏感和计算密集型SFC请求的单层雾架构

2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Pub Date : 2020-11-04 DOI: 10.1109/IEMCON51383.2020.9284860

M. Jasim, N. Siasi, S. Malapaka, D. Oliveira, O. Ugweje

引用次数: 0

A Novel Sensor Design to Sense Liquid Chemical Mixtures using Photonic Crystal Fiber to Achieve High Sensitivity and Low Confinement Losses 一种利用光子晶体光纤实现高灵敏度和低约束损耗的新型液体化学混合物传感器设计

2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Pub Date : 2020-11-04 DOI: 10.1109/IEMCON51383.2020.9284897

M. Maswood, Md Ashif Uddin, Uzzwal Kumar Dey, Md Mainul Islam Mamun, Moriom Akter, Shamima Sultana Sonia, Abdullah G. Alharbi

{"title":"A Novel Sensor Design to Sense Liquid Chemical Mixtures using Photonic Crystal Fiber to Achieve High Sensitivity and Low Confinement Losses","authors":"M. Maswood, Md Ashif Uddin, Uzzwal Kumar Dey, Md Mainul Islam Mamun, Moriom Akter, Shamima Sultana Sonia, Abdullah G. Alharbi","doi":"10.1109/IEMCON51383.2020.9284897","DOIUrl":"https://doi.org/10.1109/IEMCON51383.2020.9284897","url":null,"abstract":"Chemical sensing is an important issue in food, water, environment, biomedical, and pharmaceutical field. Conventional methods used in laboratory for sensing the chemical are costly, time consuming, and sometimes wastes significant amount of sample. Photonic Crystal Fiber (PCF) offers high compactness and design flexibility and it can be used as biosensor, chemical sensor, liquid sensor, temperature sensor, mechanical sensor, gas sensor, and so on. In this work, we designed PCF to sense different concentrations of different liquids by one PCF structure. We designed different structure for silica cladding hexagonal PCF to sense different concentrations of benzene-toluene and ethanol-water mixer. Core diameter, air hole diameter, and air hole diameter to lattice pitch ratio are varied to get the optimal result as well to explore the effect of core size, air hole size and the pitch on liquid chemical sensing. Performance of the chemical sensors was examined based on confinement loss and sensitivity. The performance of the sensor varied a lot and basically it depends not only on refractive index of the liquid but also on sensing wavelengths. Our designed sensor can provide comparatively high sensitivity and low confinement loss.","PeriodicalId":6871,"journal":{"name":"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"44 1","pages":"0686-0691"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90491917","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

Graph Theory for Dimensionality Reduction: A Case Study to Prognosticate Parkinson's 图论降维:一个预测帕金森病的案例研究

2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Pub Date : 2020-11-04 DOI: 10.1109/IEMCON51383.2020.9284926

Shithi Maitra, Tonmoy Hossain, Khan Md Hasib, Fairuz Shadmani Shishir

{"title":"Graph Theory for Dimensionality Reduction: A Case Study to Prognosticate Parkinson's","authors":"Shithi Maitra, Tonmoy Hossain, Khan Md Hasib, Fairuz Shadmani Shishir","doi":"10.1109/IEMCON51383.2020.9284926","DOIUrl":"https://doi.org/10.1109/IEMCON51383.2020.9284926","url":null,"abstract":"In the present world, the commotion centering Big Data is somewhat obscuring the craft of mining information from smaller samples. Populations with limited examples but huge dimensionality are a common phenomenon, otherwise known as the curse of dimensionality-especially in the health sector-thanks to the recently-discovered potential of data mining and the enthusiasm for feature engineering. Correlated, noisy, redundant features are byproducts of this tendency, which makes learning algorithms converge with greater efforts. This paper proposes a novel feature-pruning technique relying on computational graph theory. Restoring the appeal of pre-AI conventional computing, the paper applies Disjoint Set Union (DSU) on unidirectional graphs prepared basis thresholded Spearman's rank correlation coefficient, r. Gradual withdrawal of leniency on Spearman's r caused a greater tendency in features to form clusters, causing the dimensionality to shrink. The results-extracting out finer, more representative roots as features-have been $k$-fold cross-validated on a case study examining subjects for Parkinson's. Qualitatively, the method overcomes Principal Component Analysis's (PCA) limitation of inexplicit merging of features and Linear Discriminant Analysis's (LDA) limitation of inextendibility to multiple classes. Statistical inference verified a significant rise in performance, establishing an example of conventional hard computing reinforcing modern soft computing.","PeriodicalId":6871,"journal":{"name":"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"36 1","pages":"0134-0140"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88565664","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

Interpretive Structural Modelling to assess the enablers of blockchain technology in supply chain 解释结构建模以评估供应链中区块链技术的推动者

2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Pub Date : 2020-11-04 DOI: 10.1109/IEMCON51383.2020.9284828

A. Pundir, L. Ganapathy, Pratik Maheshwari, Shashikant Thakur

{"title":"Interpretive Structural Modelling to assess the enablers of blockchain technology in supply chain","authors":"A. Pundir, L. Ganapathy, Pratik Maheshwari, Shashikant Thakur","doi":"10.1109/IEMCON51383.2020.9284828","DOIUrl":"https://doi.org/10.1109/IEMCON51383.2020.9284828","url":null,"abstract":"The purpose of this paper is to identify, analyze the enablers for blockchain technology in supply chain. We have proposed Interpretive Structural Modeling (ISM) to analyze the different types of enablers like autonomous enablers, dependent enablers, linkage enablers and driver enablers from SSIM (Structural Self-Interaction Matrix) in MATLAB software by using partition level and iterations for the prioritization of enablers. We have prioritized the different enablers and proposed cluster diagram of enablers for blockchain technology in supply chain. On the basis of our analysis, we have formed five clusters and found that traceability transparency, seamless connectivity, verifiability of transaction enablers are highly driven and dependent on the other input variables included in the supply chain system. The present work suggested the platform for both academicians and researchers to understand the relationship between enablers of blockchain technology in supply chain. This paper also provides the future direction to the practitioners for optimally assign the efforts and available resources to increase the current performance of supply chain system. This article prioritizes the enablers of block chain in clusters according to their level of impact.","PeriodicalId":6871,"journal":{"name":"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"19 1","pages":"0223-0229"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77687026","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: 4

On the Impact of Gabor Phase for Spectro-Temporal Feature Extraction in Building an ASR System 构建ASR系统中Gabor相位对光谱-时间特征提取的影响

2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Pub Date : 2020-11-04 DOI: 10.1109/IEMCON51383.2020.9284872

Anirban Dutta, G. Prabhakar, C. V. R. Rao

引用次数: 0

Activity Recognition and Localization based on UWB Indoor Positioning System and Machine Learning 基于超宽带室内定位系统和机器学习的活动识别与定位

2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Pub Date : 2020-11-04 DOI: 10.1109/IEMCON51383.2020.9284937

Long Cheng, Anguo Zhao, Kexin Wang, Hengguang Li, Yifan Wang, Ruofei Chang

{"title":"Activity Recognition and Localization based on UWB Indoor Positioning System and Machine Learning","authors":"Long Cheng, Anguo Zhao, Kexin Wang, Hengguang Li, Yifan Wang, Ruofei Chang","doi":"10.1109/IEMCON51383.2020.9284937","DOIUrl":"https://doi.org/10.1109/IEMCON51383.2020.9284937","url":null,"abstract":"Joint activity recognition and localization plays an important role in many fields such as smart healthcare system, smart home, human-computer interaction, and robotics. Ultrawideband (UWB) is considered as a promising technology for high-precision indoor positioning system. But few studies have been done to simultaneously recognize and localize human activities based on the UWB indoor positioning system. In this paper, the possibility of simultaneously recognizing and localizing human activities with a self-developed UWB indoor positioning system is investigated. First, a few signal processing and machine learning techniques are applied to improve the positioning accuracy of the UWB indoor positioning system. Three machine learning methods based on support vector machine, artificial neural network, and hidden Markov model are then used to recognize five types of human activities based on the range measurements from the UWB indoor positioning system. Experimental results show that our approach achieves satisfactory performances in the joint activity recognition and localization task.","PeriodicalId":6871,"journal":{"name":"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"26 1","pages":"0528-0533"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84096516","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: 8

Simple Approximations for Fast and Secure Deep Learning on Genomic Data 基因组数据快速安全深度学习的简单近似

2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Pub Date : 2020-11-04 DOI: 10.1109/IEMCON51383.2020.9284891

Delica S. Leboe-McGowan, Md Momin Al Aziz, N. Mohammed

{"title":"Simple Approximations for Fast and Secure Deep Learning on Genomic Data","authors":"Delica S. Leboe-McGowan, Md Momin Al Aziz, N. Mohammed","doi":"10.1109/IEMCON51383.2020.9284891","DOIUrl":"https://doi.org/10.1109/IEMCON51383.2020.9284891","url":null,"abstract":"State-of-the-art frameworks for privacy-preserving artificial neural networks often rely on secret sharing to protect sensitive data. Unfortunately, operating on secret shared data complicates a number of non-linear functions that are central to deep learning, such as batch normalization and rectified linear units (ReLUs). We offer simple procedures for approximating these non-linear operations. The approximations we propose significantly reduce the training runtime of a privacy-preserving convolutional neural network (CNN) that we designed to diagnose breast cancer from secret shared gene expression profiles. In just over five minutes of training, our approximation-based privacy-preserving CNN achieves an average test accuracy of 96%. When we apply an exact garbled circuit solution for the ReLU function, we find that the privacy-preserving model requires days of computation to achieve the same level of accuracy. The dramatic improvement in training runtime yielded by our ReLU approximation may prove useful for other medical applications of privacy-preserving neural networks.","PeriodicalId":6871,"journal":{"name":"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"41 1","pages":"0860-0866"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81677778","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

Moving Target Defense Application and Analysis in Software-Defined Networking 移动目标防御在软件定义网络中的应用与分析

2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Pub Date : 2020-11-04 DOI: 10.1109/IEMCON51383.2020.9284847

Charan Gudla, A. Sung

引用次数: 2