International Journal of Innovative Research in Computer Science and Technology最新文献_第4页

Analysis of Bituminous Concrete Mixes Using H.D.P.E & Crumb Rubber as Admixtures 掺加聚乙烯和橡胶屑的沥青混凝土掺合料分析

International Journal of Innovative Research in Computer Science and Technology Pub Date : 2023-05-31 DOI: 10.55524/ijircst.2023.11.3.14

Dr. A. Ranganathan, M. Kranthikumar, D. Sudheerbabu, N. Badulla, T. Tejaswini, D. Nagarjuna, Y. Durgaprasad

{"title":"Analysis of Bituminous Concrete Mixes Using H.D.P.E & Crumb Rubber as Admixtures","authors":"Dr. A. Ranganathan, M. Kranthikumar, D. Sudheerbabu, N. Badulla, T. Tejaswini, D. Nagarjuna, Y. Durgaprasad","doi":"10.55524/ijircst.2023.11.3.14","DOIUrl":"https://doi.org/10.55524/ijircst.2023.11.3.14","url":null,"abstract":"Flexible pavements need more attention in selection of Resources and preparation of mixes now a day’s temperature is the main criteria which affect the mix quality, strength and durability. Rapid changes in temperature now a day’s big problem to face worst situations, Durability point is a big factor which affects the life period of the pavement surface and its components, Nominal mixes which consists of inert material doesn’t gives better Durability in severe traffic and climate conditions Today’s flexible pavements are Required to perform better as they are facing increased volume of traffic, increased loads and increased variations in daily or seasonal temperature over what has been Challenged in the past. In addition, the performance of bituminous roads is to be identified that they are poor in high drainage situations. Present scenario on using various additives for better drainage is not satisfying the expected results. However, the additive that is to be used for modification of mix or binder should satisfy both the strength, durability requirements as well as economical aspects. Plastics are using extensively in all over world and developing country like India. As these are non-biodegradable there is a major problem posed to the society with regard to the management of these solid wastes. Even, the reclaimed polyethylene originally made of HDPE has been observed to modify bitumen. In the present study, an attempt has been made to use HDPE and CRUMB RUBBER as admixtures in nominal bitumen mix to overcome the problem of resistance to weathering actions and repetitive wheel load","PeriodicalId":218345,"journal":{"name":"International Journal of Innovative Research in Computer Science and Technology","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116311982","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

Mutual Coupling Reduction Using 8x8 MIMO Antenna for MM Wave Applications 相互耦合减少使用8x8 MIMO天线的毫米波应用

International Journal of Innovative Research in Computer Science and Technology Pub Date : 2023-05-26 DOI: 10.55524/ijircst.2023.11.3.11

M. R. Kumar, M. Rao, G. Jyothi, SK. Durshid, D. Kumar, B. Mahesh, G. Rajesh

引用次数: 0

Machine Learning Prospects: Insights for Social Media Data Mining and Analytics 机器学习前景:社交媒体数据挖掘和分析的见解

International Journal of Innovative Research in Computer Science and Technology Pub Date : 2023-05-22 DOI: 10.55524/ijircst.2023.11.3.3

Anu Sharma, Vivek Kumar

{"title":"Machine Learning Prospects: Insights for Social Media Data Mining and Analytics","authors":"Anu Sharma, Vivek Kumar","doi":"10.55524/ijircst.2023.11.3.3","DOIUrl":"https://doi.org/10.55524/ijircst.2023.11.3.3","url":null,"abstract":"Social network has increased surprising consideration in the most recent decade. Social network deals with enormous volume of composite as well as unstructured data and they are very hard to handle. Due to expanding dimensions and demand, one of the encouraging and interesting research field becomes social network. Data Mining affirms to get knowledge by discovery patterns among data. We have discussed social media mining and Social Media analytics. We have insights on the social media effect of our lives, some facts and reports from various sources. We have Integrated this growing research field of social networks with Machine Learning with one simple example of sentiment analysis of Twitter data using Machine Learning. We have also proposed the algorithms to improve the social media analytics results using Machine Learning. In this paper, we will exhibit how machine learning will utilizing for social networking systems like Twitter. In this procedure, a framework is proposed that will collect the tweets messages from the and we will inspect the item’s input to show the positive, negative, or nonpartisan tweets, for this this purpose we have proposed new machine learning algorithms Naive Bayes, maximum entropy to find these outputs. Our proposed Model will help new researchers, companies, Industries, business community, practitioners, new integrated application designers, and the global community to solve the new research problem and may reducing design failure rate of 80% by large through social media mining and networks.","PeriodicalId":218345,"journal":{"name":"International Journal of Innovative Research in Computer Science and Technology","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132702463","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

Content-Based Movie Recommendation System: An Enhanced Approach to Personalized Movie Recommendations 基于内容的电影推荐系统:一种增强的个性化电影推荐方法

International Journal of Innovative Research in Computer Science and Technology Pub Date : 2023-05-20 DOI: 10.55524/ijircst.2023.11.3.12

S. Sinha, Treya Sharma

{"title":"Content-Based Movie Recommendation System: An Enhanced Approach to Personalized Movie Recommendations","authors":"S. Sinha, Treya Sharma","doi":"10.55524/ijircst.2023.11.3.12","DOIUrl":"https://doi.org/10.55524/ijircst.2023.11.3.12","url":null,"abstract":"With the exponential growth of digital media platforms and the vast amount of available movie content, users are often overwhelmed when selecting movies that match their preferences. Recommender systems have emerged as an effective solution to assist users in discovering relevant and enjoyable movies. Among these systems, content-based recommendation approaches have gained popularity due to their ability to recommend items based on the content characteristics of movies, such as genres, actors, directors, and plot summaries. The first stage of our system involves the collection and preprocessing of movie metadata from various sources, including genres, actors, directors, and plot summaries. Feature extraction techniques are applied to transform the textual information into meaningful representations that capture the essential characteristics of each movie. Next, a content-based filtering algorithm is employed to compute similarity scores between the user's movie preferences and the extracted features of the available movies. The proposed approach contributes to the advancement of movie recommendation systems and has the potential to enhance user engagement and satisfaction in movie selection.","PeriodicalId":218345,"journal":{"name":"International Journal of Innovative Research in Computer Science and Technology","volume":"308 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133662969","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

Real Time Prevention of Driver Fatigue Using Deep Learning and MediaPipe 利用深度学习和MediaPipe实时预防驾驶员疲劳

International Journal of Innovative Research in Computer Science and Technology Pub Date : 2023-05-10 DOI: 10.55524/ijircst.2023.11.3.2

Swapnil Dalve, Ishwar Ramdasi, Ganesh Kothawade, Yash Khadke, Manasi Wete

{"title":"Real Time Prevention of Driver Fatigue Using Deep Learning and MediaPipe","authors":"Swapnil Dalve, Ishwar Ramdasi, Ganesh Kothawade, Yash Khadke, Manasi Wete","doi":"10.55524/ijircst.2023.11.3.2","DOIUrl":"https://doi.org/10.55524/ijircst.2023.11.3.2","url":null,"abstract":"This paper describes the development of a system for detecting driver drowsiness whose goal is to alert drivers of their sleepy state to prevent traffic accidents. It is essential that drowsiness detection in a driving environment be conducted in a non-intrusive manner and that the driver not be troubled by alerts when they are not sleepy. We make use of the MediaPipe Facemesh framework to extract facial features and the Binary Classification Neural Network to precisely detect drowsy states in our solution to this open problem. The solution that minimize false positives is created to determine whether or not the driver exhibits sleepiness symptoms. The approach extracts numerical features from images using deep learning techniques, which are then added to a fuzzy logic-based system. This system typically achieve 91% accuracy on training data and 92% accuracy on test data. The fuzzy logic-based approach, however, stands out because it doesn't raise erroneous alerts (percentage of correctly identified footage where the driver is not tired). Although the findings are not particularly satisfying, the recommendations offered in this study are promising and may be used as a strong platform for future work.","PeriodicalId":218345,"journal":{"name":"International Journal of Innovative Research in Computer Science and Technology","volume":"209 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128164475","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

Analysing the Impact of Substrate Thickness on Antenna Performance for GPS Application 分析基板厚度对GPS天线性能的影响

International Journal of Innovative Research in Computer Science and Technology Pub Date : 2023-05-05 DOI: 10.55524/ijircst.2023.11.3.10

R. S, Guganesh R, Harinee V, S. S

引用次数: 0

Review Analysis of Cyber Security in Healthcare System: A Systematic Approach of Modern Development 医疗保健系统网络安全综述分析:现代发展的系统方法

International Journal of Innovative Research in Computer Science and Technology Pub Date : 2023-05-04 DOI: 10.55524/ijircst.2023.11.3.7

Venkateswaran Radhakrishnan

引用次数: 0

Stress Alarm Raiser Based on Facial Expressions 基于面部表情的压力警报器

International Journal of Innovative Research in Computer Science and Technology Pub Date : 2023-05-04 DOI: 10.55524/ijircst.2023.11.3.9

S. Sinha, Aakarsh Sharma

引用次数: 0

Techniques for Data Mining Prediction in the Health Care Sector 医疗保健领域的数据挖掘预测技术

International Journal of Innovative Research in Computer Science and Technology Pub Date : 2023-05-03 DOI: 10.55524/ijircst.2023.11.3.6

Aditya Tripathi, Amit Kumar Sharma

引用次数: 0

EEG-Based Multi-Class Emotion Recognition using Hybrid LSTM Approach 基于eeg的混合LSTM方法的多类情感识别

International Journal of Innovative Research in Computer Science and Technology Pub Date : 2023-05-01 DOI: 10.55524/ijircst.2023.11.3.1

Md Momenul Haque, S. Paul, Rakhi Rani Paul, Mursheda Nusrat Della, Md. Kamrul Islam, Sultan Fahim

{"title":"EEG-Based Multi-Class Emotion Recognition using Hybrid LSTM Approach","authors":"Md Momenul Haque, S. Paul, Rakhi Rani Paul, Mursheda Nusrat Della, Md. Kamrul Islam, Sultan Fahim","doi":"10.55524/ijircst.2023.11.3.1","DOIUrl":"https://doi.org/10.55524/ijircst.2023.11.3.1","url":null,"abstract":"Emotion recognition is a crucial task in human-computer interaction, psychology, and neuroscience. Electroencephalogram (EEG)-based multi-class emotion recognition is a novel approach that aims to identify and classify human emotions by analysing EEG signals. Traditional methods of emotion recognition often face challenges in accurately identifying and classifying human emotions due to their complexity and subjectivity. EEG-based emotion recognition provides a direct and objective measure of three emotional states (positive, neutral, and negative), making it a promising tool for emotion recognition. The proposed hybrid LSTM approach combines the strengths of different traditional machine learning algorithms: Gaussian Naive Bayes (GNB), Support Vector Machine (SVM), Logistic Regression (LR), and Decision Tree (DT). The approach was tested on the EEG brainwave dataset, and LSTM achieved an accuracy of 95%, while the proposed hybrid LSTM-GNB, LSTM-SVM, LSTM-LR, and LSTM-DT models achieved 65%, 96%, 97%, and 96% accuracy, respectively. The contribution of this study is the development of a hybrid LSTM approach that combines the strengths of two different algorithms, resulting in higher accuracy for multi-class emotion recognition using EEG signals. The results demonstrate the potential of the hybrid LSTM approach for real-world applications such as emotion-based human-computer interaction and mental health diagnosis.","PeriodicalId":218345,"journal":{"name":"International Journal of Innovative Research in Computer Science and Technology","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126429210","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