2019 IEEE Conference on Information and Communication Technology最新文献_第7页

Electronically Tunable First Order Universal Filter based on CCDDCCTA 基于CCDDCCTA的电子可调谐一阶通用滤波器

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066264

Priyanka Singh, Vikrant Varshney, Ankur Kumar, R. Nagaria

引用次数: 7

Emergency Signal Classification for the Hearing Impaired using Multi-channel Convolutional Neural Network Architecture 基于多通道卷积神经网络的听力损伤应急信号分类

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066252

Swarup Padhy, Juhi Tiwari, S. Rathore, Neetesh Kumar

{"title":"Emergency Signal Classification for the Hearing Impaired using Multi-channel Convolutional Neural Network Architecture","authors":"Swarup Padhy, Juhi Tiwari, S. Rathore, Neetesh Kumar","doi":"10.1109/CICT48419.2019.9066252","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066252","url":null,"abstract":"Hearing impaired people have to tackle a lot of challenges, particularly during emergencies, making them dependent on others. The presence of emergency situations is mostly comprehended through auditory means. This raises a need for developing such systems that sense emergency sounds and communicate it to the deaf effectively. The present study is conducted to differentiate emergency audio signals from non-emergency situations using Multi-Channel Convolutional Neural Networks (CNN). Various data augmentation techniques have been explored, with particular attention to the method of Mixup, in order to improve the performance of the model. The experimental results showed a cross-validation accuracy of 88.28 % and testing accuracy of 88.09 %. To put the model into practical lives of the hearing impaired an android application was developed that made the phone vibrate every time there was an emergency sound. The app could be connected to an android wear device such as a smartwatch that will be with the wearer every time, effectively making them aware of emergency situations.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"4 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":"124740971","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

Virtual Workplaces Testing Method on Accordance with the Technical Task 根据技术任务的虚拟工作场所测试方法

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066128

N. Voit, S. Bochkov, S. Kirillov

引用次数: 0

Physical Layer Security in Intervehicular Cognitive Relaying Communication Systems 车际认知中继通信系统的物理层安全

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066185

Anshul Pandey, S. Yadav

引用次数: 1

Cyber-Physical Interdependencies in Power Plant Systems: A Review of Cyber Security Risks 电厂系统的网络-物理相互依赖:网络安全风险综述

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066188

Aida Akbarzadeh, Pankaj Pandey, S. Katsikas

{"title":"Cyber-Physical Interdependencies in Power Plant Systems: A Review of Cyber Security Risks","authors":"Aida Akbarzadeh, Pankaj Pandey, S. Katsikas","doi":"10.1109/CICT48419.2019.9066188","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066188","url":null,"abstract":"Realizing the importance of the concept of “smart city” and its impact on the quality of life, many infrastructures, such as power plants, began their digital transformation process by leveraging modern computing and advanced communication technologies. Unfortunately, by increasing the number of connections, power plants become more and more vulnerable and also an attractive target for cyber-physical attacks. The analysis of interdependencies among system components reveals interdependent connections, and facilitates the identification of those among them that are in need of special protection. In this paper, we review the recent literature which utilizes graph-based models and network-based models to study these interdependencies. A comprehensive overview, based on the main features of the systems including communication direction, control parameters, research target, scalability, security and safety, is presented. We also assess the computational complexity associated with the approaches presented in the reviewed papers, and we use this metric to assess the scalability of the approaches.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"140 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":"131485401","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

Comparison of Multi Chopper Amplifiers for Capacitive MEMS Transducer 电容式MEMS传感器多斩波放大器的比较

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066253

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

引用次数: 0

Weapon Classification using Deep Convolutional Neural Network 基于深度卷积神经网络的武器分类

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066227

Neelam Dwivedi, D. Singh, D. S. Kushwaha

{"title":"Weapon Classification using Deep Convolutional Neural Network","authors":"Neelam Dwivedi, D. Singh, D. S. Kushwaha","doi":"10.1109/CICT48419.2019.9066227","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066227","url":null,"abstract":"Increasing crimes in public nowadays pose a serious need of active surveillance systems to overcome such happenings. Type of weapon used in the crime determines its seriousness and nature of crime. An active surveillance with weapon classification can help deciding the course of action while identifying the possibilities of any crime happening. This paper presents a novel approach for weapon classification using Deep Convolutional Neural Networks (DCNN). That is based on the VGGNet architecture. VGGNet is the most recognized CNN architecture which got its place in ImageNet competition 2014, organized for image classification problems. Thus, weights of pre-trained VGG 16 model are taken as the initial weights of convolutional layers for the proposed architecture, where three classes: knife, gun and no-weapon are used to train the classifier. To fine tune the weights of the proposed DCNN, it is trained on the images of these classes downloaded from internet and other captured in the lab. Experiments are performed on Nvidia GeForce GTX1050 Ti G PU to achieve faster and exhaustive training on a large image set. A higher accuracy level of 98.41 % is achieved for weapon classification.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"10 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":"125301495","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

Vehicle Tracking and Monitoring in Surveillance Video 监控视频中的车辆跟踪与监控

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066256

Ashish Singh Patel, O. Vyas, Muneendra Ojha

引用次数: 4

FIR Filter Realization Under the Trade-Off Between Implementation Complexity and Computation Rate 在实现复杂度和计算速率之间权衡的FIR滤波器实现

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066232

Abhishek Kumar, S. Yadav, N. Purohit

{"title":"FIR Filter Realization Under the Trade-Off Between Implementation Complexity and Computation Rate","authors":"Abhishek Kumar, S. Yadav, N. Purohit","doi":"10.1109/CICT48419.2019.9066232","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066232","url":null,"abstract":"We propose a flexible finite impulse response (FIR) filter structure which can avail the benefits of trade-off between computation units and clock rate. For designing such flexible FIR filter, we first present two supporting structures viz., Structure I and Structure II. Structure I realizes the FIR filter via single multiplier, single adder, and $N$ delays, where all units operate at the rate of $Nf_{in}$ (i.e., high clock rate), and $N$ and $f_{mathrm{i}n}$ denote the order of FIR filter and input sampling frequency, respectively, whereas Structure II implements the FIR filter using NM multipliers, M N - M2 adders, and M N - M2 delays in the filter unit with clock rate $displaystyle frac{f_{in}}{M}$ (i.e., computationally low-speed realization), and $M-1$ adders and delays at the output unit operate at $f_{in}$, where 2 $leq M leq N$ and $M$ denotes the upsampler/downsampler. Then, we propose Structure III via Structures I & II, which provides the flexible realization of FIR filters under the trade-off between computational units and clock rate. We also analyze the performance of these structures in terms of number of multipliers $(C_{M})$, number of adders $(C_{A})$, number of delays $(C_{D})$, and operating frequency $(F_{opt})$ with the help of numerical example in comparison of the direct form FIR filter.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"42 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":"126177501","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

Vulnerability Discovery Modelling With Vulnerability Severity 基于漏洞严重性的漏洞发现模型

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066187

Ankur Shukla, Basel Katt, Livinus Obiora Nweke

{"title":"Vulnerability Discovery Modelling With Vulnerability Severity","authors":"Ankur Shukla, Basel Katt, Livinus Obiora Nweke","doi":"10.1109/CICT48419.2019.9066187","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066187","url":null,"abstract":"Web browsers are primary targets of attacks because of their extensive uses and the fact that they interact with sensitive data. Vulnerabilities present in a web browser can pose serious risk to millions of users. Thus, it is pertinent to address these vulnerabilities to provide adequate protection for personally identifiable information. Research done in the past has showed that few vulnerability discovery models (VDMs) highlight the characterization of vulnerability discovery process. In these models, severity which is one of the most crucial properties has not been considered. Vulnerabilities can be categorized into different levels based on their severity. The discovery process of each kind of vulnerabilities is different from the other. Hence, it is essential to incorporate the severity of the vulnerabilities during the modelling of the vulnerability discovery process. This paper proposes a model to assess the vulnerabilities present in the software quantitatively with consideration for the severity of the vulnerabilities. It is possible to apply the proposed model to approximate the number of vulnerabilities along with vulnerability discovery rate, future occurrence of vulnerabilities, risk analysis, etc. Vulnerability data obtained from one of the major web browsers (Google Chrome) is deployed to examine goodness-of-fit and predictive capability of the proposed model. Experimental results justify the fact that the model proposed herein can estimate the required information better than the existing VDMs.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"39 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":"127902189","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