2022 IEEE Bombay Section Signature Conference (IBSSC)最新文献_第8页

SC Connect: Secure Server Access from Mobile Device SC连接:安全的服务器访问从移动设备

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037430

Wilfred Almeida

引用次数: 0

Realtime Deepfake Detection using Video Vision Transformer 使用视频视觉变压器的实时深度伪造检测

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037344

Abhishek Doshi, Abhinav Venkatadri, Sayali Kulkarni, Vedant Athavale, Akhila Jagarlapudi, Shraddha Suratkar, F. Kazi

引用次数: 0

Comparative Study of CNN Models on the Classification of Dyslexic Handwriting CNN模型对阅读困难笔迹分类的比较研究

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037428

Subha Sreekumar, Lijiya A

{"title":"Comparative Study of CNN Models on the Classification of Dyslexic Handwriting","authors":"Subha Sreekumar, Lijiya A","doi":"10.1109/IBSSC56953.2022.10037428","DOIUrl":"https://doi.org/10.1109/IBSSC56953.2022.10037428","url":null,"abstract":"Developmental Dyslexia, one of the learning disabilities is a topic of scientific interest in a variety of disciplines such as psychology, speech and language therapy, data science, etc. While the reason for Dyslexia and its symptoms are still being researched by psychologists, data science is providing ways to intervene and detect them with the aid of technological advancements. Dyslexia is a neurological condition that impairs reading comprehension and has long-lasting impacts. But timely detection and intervention programs can alleviate its effects to a certain extent. This study aims to classify images of handwritten English characters into three classes namely: normal, corrected, and reversed, where normal class refers to normal handwriting, and corrected or reversed constitutes handwriting of children with Dyslexia. The dataset used for the study is available publicly on Kaggle. The building of an efficient CNN (Convolutional Neural Network) model for classifying dyslexic handwriting is the major emphasis of this work. This is accomplished by comparing several CNN models and evaluating how well they detect Dyslexia on the same dataset. The proposed CNN approach has demonstrated a sizable improvement in reliably classifying dyslexic handwritten images.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123658897","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

Deep-3DConvNet: A Network to Detect Abnormal Activities at Megastores Deep-3DConvNet:一种检测大型商店异常活动的网络

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037326

Mohd. Aquib Ansari, D. Singh

{"title":"Deep-3DConvNet: A Network to Detect Abnormal Activities at Megastores","authors":"Mohd. Aquib Ansari, D. Singh","doi":"10.1109/IBSSC56953.2022.10037326","DOIUrl":"https://doi.org/10.1109/IBSSC56953.2022.10037326","url":null,"abstract":"These days, there has been a rapid increase in cases of abnormal human behavior at megastores/shops, where people commit theft by stealing, consuming, or unwrapping packets when no one is seeing and then leaving the place without paying. Such unusual actions cause huge losses in business. Therefore, there is an urgent need to attract the research community's attention to detect abnormal events at megastores. To address this issue, we have designed an advanced three-dimensional convolutional neural architecture to identify abnormal activities at megastores. The proposed network is 15 layers deep, takes a video stream of resolution 120× 120 as input, and produces classification results as output. It extracts fine-tuned as well as general details from the video feed using small and large-sized 3D convolutional filters and categorizes them into respective classes. The proposed architecture is trained and tested on a synthesized action dataset that consists of human actions distributed into five classes: normal, stealing, eating, drinking, and damaging acts. Experimental results show that our model outperforms other state-of-the-art approaches with an accuracy of 88.88%.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121527475","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

Empirical Evaluation of Traffic Shaping Algorithms for Time Sensitive Networking 时间敏感网络流量整形算法的实证评价

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037572

Kuni Naik, D. Kumari, M. Tahiliani

{"title":"Empirical Evaluation of Traffic Shaping Algorithms for Time Sensitive Networking","authors":"Kuni Naik, D. Kumari, M. Tahiliani","doi":"10.1109/IBSSC56953.2022.10037572","DOIUrl":"https://doi.org/10.1109/IBSSC56953.2022.10037572","url":null,"abstract":"Standard Ethernet networks cannot provide solutions to handle latency sensitive applications efficiently. The packet scheduling algorithms like First In First Out (FIFO), Class Based Queueing (CBQ), and others do not provide efficient solutions to Quality of Service (QoS) parameters like end-toend delay, packet loss, and jitter. Time Sensitive Networking (TSN) can be used as a solution to provide QoS to time sensitive applications. TSN has emerged as a future of realtime communication. The main advantage of TSN is that it enables determinism by supporting time critical traffic while the best effort traffic is also present in the network. This paper explores two of the most popular and widespread traffic shaping mechanisms in TSN: Time Aware Shaper (TAS) and Credit Based Shaper (CBS). IEEE 802.1Qbv is used for delivering time assurance using TAS. CBS is a key traffic shaping algorithm to provide bandwidth assurance to the time critical and real time traffic, such as the audio traffic. This paper evaluates TAS and CBS using TSN enabled Network Interface Cards (NIC) with time synchronization, real time kernel and real traffic, which includes time sensitive traffic and elastic background traffic.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116572119","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

Antennas in Airborne Applications 航空应用中的天线

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037463

A. Shaikh, M. Joshi

引用次数: 0

Computationally efficient image encryption technique based on selective pixel diffusion 基于选择性像素扩散的高效计算图像加密技术

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037561

Malik Obaid Ul Islam, S. A. Parah, B. A. Malik

{"title":"Computationally efficient image encryption technique based on selective pixel diffusion","authors":"Malik Obaid Ul Islam, S. A. Parah, B. A. Malik","doi":"10.1109/IBSSC56953.2022.10037561","DOIUrl":"https://doi.org/10.1109/IBSSC56953.2022.10037561","url":null,"abstract":"Medical images play a vital role in disease diagnosis. When the medical images are communicated through an insecure transmission channel, their chances of being accessed by an unauthorized user increase resulting in the loss of patients' sensitive personal data. Thus, providing security to such image data while transmitting it over an insecure communication network becomes crucial. This work presents a computationally efficient cryptosystem for encrypting medical images. The encryption process consists of multiple phases. In the first phase the control parameters and initial values for the various chaotic maps used, are evaluated. This phase is followed by encryption in which these evaluated values are used to obtain the chaotic sequences for encryption. In the subsequent phases, we make use of a new approach of selective, pixel-dependent diffusion to obtain the cipher image. The effectiveness of our cryptosystem is evaluated using security analysis and execution time analysis. The obtained outcome shows a high-security level compared to already existing state-of-the-art techniques. In addition, the computational complexity of our scheme is very small (0.1sec for encrypting a 256×256 image) making it suitable for real-time smart health applications.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116913667","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

Design and Implementation of IoT Based Local Weather Station - An Experimental Setup 基于物联网的本地气象站的设计与实现——一个实验装置

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037309

Nikuni Tandan, Anup Kanse, Oj Uparkar, Riya Modi, Harish Karnam, Saurabh Mehta, Akshaj Raut, Sonali Bedade

引用次数: 1

An approach to detect abusive content incorporating Word2Vec and Multilayer Perceptron 结合Word2Vec和多层感知机的滥用内容检测方法

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037274

S. Ghosal, Amit Jain, D. Tayal

引用次数: 0

PSO Adaptive Fading Memory Kalman Filter Based State Estimation of Indoor Thermal Model with Unknown Inputs 基于PSO自适应衰落记忆卡尔曼滤波的未知输入室内热模型状态估计

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037453

Bed Prakash Das, K. D. Sharma, A. Chatterjee, J. Bera

引用次数: 0