2022 2nd International Conference on Intelligent Technologies (CONIT)最新文献_第8页

High Performance Energy Efficient CMOS Voltage Level Shifter Design 高性能高能效CMOS电压电平转换器设计

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9847677

Ravi Nandan Ray, M. M. Tripathi, Chaudhary Indra Kumar

引用次数: 0

Analysis of Software Bug Prediction and Tracing Models from a Statistical Perspective Using Machine Learning 用机器学习从统计角度分析软件Bug预测和跟踪模型

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9848385

Darshana N. Tambe, L. Ragha

{"title":"Analysis of Software Bug Prediction and Tracing Models from a Statistical Perspective Using Machine Learning","authors":"Darshana N. Tambe, L. Ragha","doi":"10.1109/CONIT55038.2022.9848385","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848385","url":null,"abstract":"Software is the heart of over 99% of all modern-day devices which include smartphones, personal computers, internet of things (IoT) networks, etc. This software is built by a team of engineers which divide the final product into multiple smaller components and these components are integrated together to build the final software, due to which inherent interfacing vulnerabilities & bugs are injected into it. Multiple bugs are also injected into the system due to inexperience or mistakes made by software engineers & programmers. To identify these mistakes, a wide variety of bug prediction & tracing models are proposed by researchers, which assist programmers to predict & track these bugs. But these models have large variations in terms of accuracy, precision, recall, delay, computational complexity, cost of deployment and other performance metrics, due to which it is ambiguous for software designers to identify best bug tracing method(s) for their application deployments. To reduce this ambiguity, a discussion about design of different bug tracing & prediction models and their statistical comparison is done in this paper. This comparison includes evaluation of accuracy, precision, recall, computational complexity and scalability under different scenarios. Based on this comparison, in this paper experiments were performed on five publically available datasets from NASA MDP repository using different algorithms i.e. DRF, LSVM, LR, RF, and kNN. From the results it was observed that kNN algorithm outperforms average 98.8% accuracy on these five datasets and hence kNN were considered to be the most significant with its selected features. In the future, this performance can be improved via use of CNN & LSTM based models, which can utilize the base kNN layer, and estimate highly dense features for efficient classification performance.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"359 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114079192","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

CARE: IoT enabled Cow Health Monitoring System CARE:启用物联网的奶牛健康监测系统

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9847701

Akash Trivedi, P. S. Chatterjee

引用次数: 1

Web Extension for Lexical Simplification of Text 文本的词法简化的Web扩展

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9847720

Karan Bhat, Vaibhavi Ghumare, Siddhesh Khadake, H. Gadade

{"title":"Web Extension for Lexical Simplification of Text","authors":"Karan Bhat, Vaibhavi Ghumare, Siddhesh Khadake, H. Gadade","doi":"10.1109/CONIT55038.2022.9847720","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847720","url":null,"abstract":"Lexical simplification means the process of providing alternatives to the complex words in the sentence with texts that are much more simpler to understand, while also preserving the context and grammar of the original text to make the whole sentence more easier to understand. All of the recent work involving lexical simplification relies on unsupervised tasks to learn simpler alternatives of complex words. But the drawback of most of these researches has been the fact that they provide simpler words without taking the context of the complex word in the sentence in account. In this paper, we are proposing a lexical simplifier which is based on contextual learnings from the sentence. We have applied the pre-trained representation model, BERT. It is a very powerful tool which can make use of the wider context of the sentence in both forward and backward direction. We have also taken the word frequency indicator from the Subtlex list, to produce results that will be more correct both semantically and grammatically. We have also added a web extension for the simplification of the text on the webpage, which takes the input from the user, processes the text on the server end, and gives the result in return after computation is over.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124524666","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 Neural Network based Forecasting of Short-Term Solar Photovoltaic Power output 基于深度神经网络的太阳能光伏发电短期输出预测

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9847769

Sravankumar Jogunuri, F. T. Josh

引用次数: 0

A Reliable Software Defifined Networking based Framework for IoT Devices 基于物联网设备的可靠软件定义网络框架

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9848104

S. Anand, Neha Manjunath

{"title":"A Reliable Software Defifined Networking based Framework for IoT Devices","authors":"S. Anand, Neha Manjunath","doi":"10.1109/CONIT55038.2022.9848104","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848104","url":null,"abstract":"With the help of IoT (Internet of Things) devices, the world is becoming more connected. To accomplish this, a vast amount of data must be safely stored and accessed, yet IoT devices have limited memory and computing time. As a result, a huge storage room with secure space for storage is required. SDN (Software-Defined Networking) is a revolutionary network technology that incorporates a new paradigm of unsecured apps and Internet-of- Things (IoT) services. Enemies hoping to upset the activity of an IoT framework can use the malevolent bundle change assault (MP A), a basic however powerful assault that has recently been found in loT in light of remote sensor organizations. We offer a strategy for securing and dependably conveying information within the sight of dynamic aggressors to oppose MP As that takes advantage of SDN's programmability and flexibility. Our method ensures that loT devices are aware of any changes. The suggested solution's effectiveness and performance were assessed in a series of extensive tests using a prototype implementation. The findings show that even if malicious forwarding devices only modify a small percentage of the data, they may be reliably and promptly identified and circumvented. We examined the exhibition of our proposed framework utilizing OMNeT++ to recreate our whole situation and affirmed that the framework is secure and dependable in loT applications.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"17 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126965318","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

Analysis of Pitta Imbalance in young Indian adult using Machine Learning Algorithm 用机器学习算法分析印度年轻人皮塔失衡

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9847813

M. Chinnaiah, Sanjay Dubey, N. Janardhan, V. Pathi, Nandan K, Anusha M

引用次数: 0

An Intelligent Decision Support System for Bid Prediction of Undervalued Football Players 低估球员报价预测的智能决策支持系统

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9847972

Manaswita Datta, Bhawana Rudra

{"title":"An Intelligent Decision Support System for Bid Prediction of Undervalued Football Players","authors":"Manaswita Datta, Bhawana Rudra","doi":"10.1109/CONIT55038.2022.9847972","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847972","url":null,"abstract":"The process of selecting football team players will determines a team's performance. An effective team is made up of a successful group of individual talented players. In general, a football team player selection is a decision made by the club based on the best available information. Club managers and scouts travel to different countries to watch matches and hire the best talent that can help their club to perform better. But for the lower leagues, it becomes difficult to hire the same talents because of strict budget. Here we devise a method so that we can leverage the undervalued players to get selected by the clubs. Clearly the benefit will be in two fold. First, the smaller clubs can get better players at an affordable cost. Second, the bigger clubs can get same performance players at a lower price helping them in cost cutting. We employ novelty detection methods to find out the undervalued players from our data and investigate our method by using five machine learning models. For performance evaluation, the five machine learning models used are support vector machine, Random Forest, Decision Tree, Linear Regression and XGBoost. Here XGboost performed best both for 10 fold cross-validation and external testing with a RMSE of 0.0122 and 0.0107 respectively.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"10 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120922034","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

Security Access Control System Enhanced with Face Mask Detection and Temperature Monitoring for Pandemic Trauma 安全访问控制系统增强了口罩检测和温度监测流行病创伤

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9848266

S. Sanjay, S. Soorya, R. Vengatesh, K. C. S. H. Priya

引用次数: 0

Harmonic Ratio and Detrended Fluctuation Analysis Aided Reliable Estimation of contamination Level On Outdoor Suspension Insulators 谐波比和趋势波动分析辅助室外悬架绝缘子污染程度的可靠估计

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9847920

Padam Dhar Dwivedi, Ariiit Baral, S. Dutta

引用次数: 0