2022 IEEE Bombay Section Signature Conference (IBSSC)最新文献_第6页

Multi-Part Knowledge Distillation for the Efficient Classification of Colorectal Cancer Histology Images 基于多部分知识精馏的结直肠癌组织学图像高效分类

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037360

Shankey Garg, Pradeep Singh

{"title":"Multi-Part Knowledge Distillation for the Efficient Classification of Colorectal Cancer Histology Images","authors":"Shankey Garg, Pradeep Singh","doi":"10.1109/IBSSC56953.2022.10037360","DOIUrl":"https://doi.org/10.1109/IBSSC56953.2022.10037360","url":null,"abstract":"Colorectal cancer is the most common type of cancer after breast cancer in women and third in men after lungs and prostrate cancer. The disease rank third in incidence and second in terms of mortality, hence early diagnosis is necessary for the correct line of treatment. Knowledge distillation based models boost the performance of small neural network and are performing efficiently for various image classification based tasks. In this work, a novel knowledge distillation based technique is developed to efficiently classify colorectal cancer histology images. Unlike traditional distillation, out method performs distillation in parts. Instead of supervising the student with a converged knowledge of teacher, the proposed method is fetching the teacher's knowledge at regular intervals and providing these knowledge to the student model during student training process. Through this multi-part distillation technique student can effectively learn the intermediate representational knowledge rather than the abstract knowledge of the teacher and hence boost the overall performance of the model. The the proposed model has achived 92.10% accuracy.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"6 4 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":"126910041","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

Intelligent Farm Monitoring System using LoRa Enabled IoT 使用LoRa支持物联网的智能农场监控系统

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037261

Shraddha Gore, Shital Patil, Vivek Khalane

{"title":"Intelligent Farm Monitoring System using LoRa Enabled IoT","authors":"Shraddha Gore, Shital Patil, Vivek Khalane","doi":"10.1109/IBSSC56953.2022.10037261","DOIUrl":"https://doi.org/10.1109/IBSSC56953.2022.10037261","url":null,"abstract":"A change in agricultural practices is necessary to prevent future food shortages caused by global overpopulation. With the Internet of Things (IoT) and low-power and low-cost devices, the agriculture industry can automate irrigation systems to efficiently use water resources by monitoring farm fields. Low Power Wide Area Networks (LPWAN), along with IoT, can solve bandwidth, coverage and power problems which are the main drawbacks of other wireless communication technologies. Long Range Wide Area Network (LoRaWAN) protocol is known as LoRa in LPWAN space. This protocol provides additional benefits like security, scalability, and robustness. In this paper, a smart agriculture model is proposed to assist in farmers' decision-making and help them to get more productive results. The result of this paper is a prototype equipment for measuring humidity and soil moisture content done by combining the data obtained from the sensors via a LoRaWAN network. This model sends sensor Data such as temperature (degree Celsius), soil moisture (percentage), and humidity (percentage) from the transmitter node to the receiver node using the LoRa communication method. The readings from these nodes are transmitted and then forwarded to the network server through a single gateway. The Wi-Fi-enabled receiving node track data daily on the ThingSpeak platform. The primary goal of this paper is to help farmers monitor their farms more effectively.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"26 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":"131697713","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

Classification Of Brain Images For Identification Of Tumors 用于肿瘤识别的脑图像分类

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037548

Jayashree Shetty, Manjula K Shenoy, Vedant Rishi Das, Mahek Mishra, Rohan Prasad, Sarthak Seth

引用次数: 0

Robust deep learning framework for the detection of melanoma in images 图像中黑色素瘤检测的鲁棒深度学习框架

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037456

Trisha Sarkar, Anushka Khare, Mohit Parekh, Param Mehta, Avani Bhuva

引用次数: 0

Automatic Twitter Rumour Detection using Machine Learning 使用机器学习的自动Twitter谣言检测

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037317

Devarsh Patel, Nicole D'Souza, Riddhi Gawande

引用次数: 0

Prediction of Student's Wellbeing from Stress and Sleep Questionnaire data using Machine Learning Approach 利用机器学习方法从压力和睡眠问卷数据预测学生的健康状况

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037549

Sharisha Shanbhog M, Jeevan M

{"title":"Prediction of Student's Wellbeing from Stress and Sleep Questionnaire data using Machine Learning Approach","authors":"Sharisha Shanbhog M, Jeevan M","doi":"10.1109/IBSSC56953.2022.10037549","DOIUrl":"https://doi.org/10.1109/IBSSC56953.2022.10037549","url":null,"abstract":"A sound mental health has its benefits for the overall well-being of an individual. The decline in mental health conditions has a critical impression on other vital functionalities of the human system both psychologically and physiologically. And a student's well-being is largely contributed by the level of perceived stress and overall quality of nighttime sleep which might have evolved by various external factors over a while. The main objective of this study is to understand the correlation between Perceived Stress Scale (PSS) scores and Pittsburgh Sleep Quality Index (PSQI) global scores from StudentLife, a publicly available dataset over the period, and classify the well-being factor as ‘Good’ ‘Average’ and ‘Bad’ The linear regression model significantly demonstrated the association between PSS scores and Pittsburgh Sleep Quality Index (PSQI) scores. Machine Learning techniques like Decision Trees (DT), Support Vector Machine (SVM), and K-nearest neighbors(K-NN) were implemented on both Pre-Test and Post-test questionnaire data. While SVM resulted in better accuracy for Pre-test data, the K-NN classifier resulted in best accuracy for Post-test data, and the performance was evaluated using performance metrics like accuracy Precision, recall, and F1 score.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"17 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":"133402348","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

Case Study On Transport Of Petroleum In Nigerian Cities 尼日利亚城市石油运输案例研究

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037348

Snehee Chheda, Anisha Gharat, Kruttika Abhyankar, Sheetal Gonsalves

{"title":"Case Study On Transport Of Petroleum In Nigerian Cities","authors":"Snehee Chheda, Anisha Gharat, Kruttika Abhyankar, Sheetal Gonsalves","doi":"10.1109/IBSSC56953.2022.10037348","DOIUrl":"https://doi.org/10.1109/IBSSC56953.2022.10037348","url":null,"abstract":"Every company in today's time intends to maximize their profits. As we are in a fast-growing world, the need for products has increased drastically. Price of products depends on majorly two things, the cost of production (including transportation costs) and profit margins. Transportation problems are used to either minimize transportation cost or to maximize profits on shipping commodities. In this paper, we focus on how to minimize transportation cost while fulfilling the supply and demand conditions. The problem taken by us contain 3 sources and 3 destinations based in Nigeria and the Cost matrix was converted from Nigerian currency (Naira) to Dollars (conversion done according to rates on 15th October, 2022) for ease of calculation. Using Vogel's Approximation Method (VAM), Least Cost Method (LCM) and the North-West Corner Method (NWCM), we found that VAM was the most optimal. Self-written Python codes were used to verify the manual solutions. The unavailable or forbidden routes have also been considered in the code. The output displayed the allocations for the 3x3 matrix, and printed the total cost. After this, MS-Excel and Excel-QM software were used for verification. We found that VAM is 25.11 percent better than the LCM and 52.65 percent better than the NWCM for this problem. In every enterprise, generating higher revenue remains one of the most essential objectives. If codes for such methods are made universally available, enterprises would benefit highly. Use of transportation problems for optimal solutions have great potential, if one has knowledge about them.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"635 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":"115111320","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

Forensic Analysis of Windows 11 Prefetch Artifact Windows 11预取工件的取证分析

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037260

Akash Budhrani, Upasna Singh, Bhupendra Singh

引用次数: 0

A research attempt to predict and model personalities through users' social media details 一项试图通过用户的社交媒体细节来预测和塑造个性的研究

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037272

Muskan Goyal, Prachi Tawde

{"title":"A research attempt to predict and model personalities through users' social media details","authors":"Muskan Goyal, Prachi Tawde","doi":"10.1109/IBSSC56953.2022.10037272","DOIUrl":"https://doi.org/10.1109/IBSSC56953.2022.10037272","url":null,"abstract":"Users of products and services, as human beings have a wide range of personalities. This is being experienced right from the initial days of e-commerce and m-commerce in India. In this research an attempt has been made to predict personalities using MBTI (Myers Briggs Type Indicator) based approach making use of natural language based processing, machine learning and transformer based modelling. As each human being is unique and exhibits different personality trait, therefore it is impractical to offer a generalized treatment for all users. But it is possible to categorize individuals, in terms of their defining characteristics based on MBTI based approach, which groups personalities/users into 16 groups and thus helps in predicting personalities. In this study authors made an attempt to extract social media based information of users through their accounts to characterize users into one of the 16 MBTI personality types. For this prediction and modelling, authors made use of pre-processed data from Kaggle, which was then fed into the transformer for modelling/processing. Based on the information it gets, like comments, post captions, reviews, etc., the transformer is fine-tuned to predict the user's personality. The required qualities of the model were taken into account while coding the transformer's parameters. Additionally, an attempt is also made to compare the outcomes of two trained transformer models. Authors report that the prediction accuracy of their modelling as 64%, outperforming all other models used. The testing data had a 76% precision.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"26 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":"116245104","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

Monkeypox Skin Lesion Classification Using Transfer Learning Approach 基于迁移学习方法的猴痘皮肤病变分类

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037374

Arya Shah

引用次数: 1