2023 6th International Conference on Information Systems and Computer Networks (ISCON)最新文献_第10页

3D AttU-NET for Brain Tumor Segmentation with a Novel Loss Function 基于新型损失函数的三维AttU-NET脑肿瘤分割

2023 6th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2023-03-03 DOI: 10.1109/ISCON57294.2023.10112146

R. Roy, B. Annappa, Shubham Dodia

引用次数: 0

User Adaptive Video Summarization 用户自适应视频摘要

2023 6th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2023-03-03 DOI: 10.1109/ISCON57294.2023.10112154

Vasudha Tiwari, C. Bhatnagar

引用次数: 0

An Efficient Integrated approach of Fuzzy C-Means Map Reduce for Weather Forecasting Data Collection 天气预报数据收集中一种有效的模糊c均值图约简综合方法

2023 6th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2023-03-03 DOI: 10.1109/ISCON57294.2023.10112170

Malathy Sathyamoorthy, Rakesh Kumar, C. Vanitha, B. Sharma, V. Syamraj, Subrata Chowdhury

引用次数: 0

Data Preprocessing for Stock Price Prediction Using LSTM and Sentiment Analysis 基于LSTM和情绪分析的股票价格预测数据预处理

2023 6th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2023-03-03 DOI: 10.1109/ISCON57294.2023.10112026

Aditya Singh Rajpurohit, H. Mhaske, P. Gaikwad, Shravani P. Ahirrao, Nutan Bhairu Dhamale

{"title":"Data Preprocessing for Stock Price Prediction Using LSTM and Sentiment Analysis","authors":"Aditya Singh Rajpurohit, H. Mhaske, P. Gaikwad, Shravani P. Ahirrao, Nutan Bhairu Dhamale","doi":"10.1109/ISCON57294.2023.10112026","DOIUrl":"https://doi.org/10.1109/ISCON57294.2023.10112026","url":null,"abstract":"Stock market marks an intrinsic aspect of a nation’s economy. Being the current buzzword, people are curious to learn how to effectively invest in order to benefit themselves. Right investments have led people to earn enormous profit whereas some had to forfeit. The risk factor in the stock market has always been dreadful for new investors and into the bargains of the experienced ones, but with the evolving technologies it is now trouble-free to make predictions about the stocks. The company’s historic performance succor the investors furthermore different algorithms assist the prediction. In order to extrapolate predictions it becomes indispensable to preprocess the data. In this paper we have made an attempt to model the historic prices of the TCS- Tata Consultancy Services and calculated its accuracy for different epochs and batch sizes, forbye the ramifications of data preprocessing. Further the tweets related to it are scrutinized for the model. Our paper makes an attempt in providing a panorama over different data manipulations and the fidelity procured, we have provided a comparative study herein.","PeriodicalId":280183,"journal":{"name":"2023 6th International Conference on Information Systems and Computer Networks (ISCON)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133094587","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

Performance Analysis of Machine Learning Algorithms Using Bagging Ensemble Technique for Software Fault Prediction 基于Bagging集成技术的软件故障预测机器学习算法性能分析

2023 6th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2023-03-03 DOI: 10.1109/ISCON57294.2023.10111952

Roshan Samantaray, Himansu Das

{"title":"Performance Analysis of Machine Learning Algorithms Using Bagging Ensemble Technique for Software Fault Prediction","authors":"Roshan Samantaray, Himansu Das","doi":"10.1109/ISCON57294.2023.10111952","DOIUrl":"https://doi.org/10.1109/ISCON57294.2023.10111952","url":null,"abstract":"Software development comes with a lot of challenges. Developers face various issues with performance and bugs. These issues increase with the scale of the project and if fewer individuals work on the development. It has become necessary to fix various bugs during development to ensure better performance and reduce the chances of failure during the deployment of the software. As a result of this, faults in the software must be predicted during the earlier stages of development. This would help in reducing the cost of maintenance of the software post-deployment. Multiple software fault prediction (SFP) approaches have been proposed to tackle this problem. These approaches can be improved by implementing ensemble techniques. In this paper, we study the effect of the bagging technique and how it helps to improve the predictive capability across various datasets. These datasets are provided and made open source by NASA. Decision Tree Classifier (DTC), Logistic Regression (LR), K-Nearest Neighbors (KNN), Gaussian Naive Bayes (GNB), and Support Vector Classifier (SVC) were used as base classifiers for the bagging method. Random forest (RFC) is an ensemble learning algorithm that uses the bagging technique. Based on the outcome of the results, it was concluded that RFC was the best-performing algorithm.","PeriodicalId":280183,"journal":{"name":"2023 6th International Conference on Information Systems and Computer Networks (ISCON)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133213717","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

Investigating Challenges to Internet of Things (IoT)Applications and Technologies 研究物联网(IoT)应用和技术的挑战

2023 6th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2023-03-03 DOI: 10.1109/ISCON57294.2023.10111967

Sonam Khattar, Ravinder Kaur, Tushar Verma, B. Sharma

{"title":"Investigating Challenges to Internet of Things (IoT)Applications and Technologies","authors":"Sonam Khattar, Ravinder Kaur, Tushar Verma, B. Sharma","doi":"10.1109/ISCON57294.2023.10111967","DOIUrl":"https://doi.org/10.1109/ISCON57294.2023.10111967","url":null,"abstract":"IoT is becoming more and more popular in both household and commercial settings, but its implementation is fraught with difficulties. It has been used to a variety of industries, including home life, urban infrastructure, healthcare, agriculture, workplace automation, and more. The Internet of Things has an endless supply of cutting-edge applications, including smarter cities, improved cars, and improved health and fitness equipment. Many concerns directly linked to the IoT still need to be resolved since its development is still in its early stages. IoT-related challenges, such as security and privacy, are on the increase as a result of the industry’s fast expansion. We need a system that solves scalability, security, efficiency, and privacy simultaneously since IoT is utilized in many different industries. Although a lot of research is being done to lessen these concerns, many issues still need to be resolved. The potential of AI and IoT must be merged in order to solve these issues. The current articles provide a succinct overview of IoT applications, technology, and difficulties. In this article, many technologies and difficulties will be examined.","PeriodicalId":280183,"journal":{"name":"2023 6th International Conference on Information Systems and Computer Networks (ISCON)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126078906","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

A Survey of Software Defects Research Based on Deep Learning 基于深度学习的软件缺陷研究综述

2023 6th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2023-03-03 DOI: 10.1109/ISCON57294.2023.10112194

Fanqi Meng, Ruihong Huang, Jingdong Wang

{"title":"A Survey of Software Defects Research Based on Deep Learning","authors":"Fanqi Meng, Ruihong Huang, Jingdong Wang","doi":"10.1109/ISCON57294.2023.10112194","DOIUrl":"https://doi.org/10.1109/ISCON57294.2023.10112194","url":null,"abstract":"In the process of software development, software defects are inevitable. How to quickly and accurately identify defects and accurately deliver bug reports to the most appropriate repair personnel is very important for defect repair. In recent years, with the development of artificial intelligence, deep learning has been widely used in software defect research. This paper summarizes and analyzes the progress of software defect research based on deep learning in the past three years from four perspectives of software defect prediction, software defect identification, software defect analysis and bug report assignment. They are software defect prediction technology based on the TextCNN model and TextRNN model, a software defect identification technology based on LSTM, BiLSTM, DNCC, a software defect analysis technology based on the DAKSM model, and a software bug report assignment technology based on Atten-CRNN model. And compared these mentioned deep learning-based techniques with previous techniques in the field. After experiments, it is concluded that these models have good accuracy. At the same time, the related technologies involved are introduced in detail, as the problems that may be encountered in future research in this field and the development prospects prospect.","PeriodicalId":280183,"journal":{"name":"2023 6th International Conference on Information Systems and Computer Networks (ISCON)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122315079","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

Plant Leaf Diseases Severity Estimation using Fine-Tuned CNN Models 利用微调CNN模型估算植物叶片病害严重程度

2023 6th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2023-03-03 DOI: 10.1109/ISCON57294.2023.10111948

Raj Kumar, A. Chug, A. Singh

{"title":"Plant Leaf Diseases Severity Estimation using Fine-Tuned CNN Models","authors":"Raj Kumar, A. Chug, A. Singh","doi":"10.1109/ISCON57294.2023.10111948","DOIUrl":"https://doi.org/10.1109/ISCON57294.2023.10111948","url":null,"abstract":"The quantity and quality of agricultural harvests are both severely impacted by crop diseases. Accurately measuring the severity of a disease is vital because it allows farmers to use the appropriate amount and kind of pesticides on the crops that are threatened. Incorrect estimates of disease severity in plants can lead to wasteful or ineffective use of pesticides, making it a difficult assignment even for researchers and plant pathologists. Recently, there has been a rapid rise in the application of machine vision and deep learning methods to smart farming. To guarantee food security, we need to raise output and improve crop quality, but doing so requires a more precise and innovative method of assessing the severity of the crop disease. This research proposes a transfer-learning based strategy for estimating the severity of diseases on tomato leaves with the use of learned VGG-16 / VGG-19 CNN networks and tested on a hybrid dataset consisting of both images captured in the field with a Canon EOS 1500D camera on a white background and images captured under controlled laboratory conditions from the plant village dataset. In addition, the authors made hyper- adjustments to the hyperparameters of pre-trained CNN models to boost their efficacy. To evaluate the efficacy of finely tuned CNN models, the study uses accuracy and loss measurements over multiple iterations on training and validation datasets. When compared to another CNN model evaluated on the same dataset, VGG-16 was shown to obtain superior classification accuracy (92.46%).","PeriodicalId":280183,"journal":{"name":"2023 6th International Conference on Information Systems and Computer Networks (ISCON)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126193153","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

An Improved HVC based blind watermarking algorithm using SVD and DWT 基于SVD和DWT的改进HVC盲水印算法

2023 6th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2023-03-03 DOI: 10.1109/ISCON57294.2023.10111993

Abhishek Toofani, Hitendra Garg

引用次数: 0

Load balancing in Cloud Computing Environment using Modified Genetic Algorithm 基于改进遗传算法的云计算环境负载均衡

2023 6th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2023-03-03 DOI: 10.1109/ISCON57294.2023.10111981

N. Verma, Bhavesh N. Gohil, Aditi S. Kansara

引用次数: 0