International Journal of Advanced Research in Science, Communication and Technology最新文献_第4页

Health Analysis and Recommendation Based on Food Using Data Mining 利用数据挖掘进行基于食物的健康分析和推荐

International Journal of Advanced Research in Science, Communication and Technology Pub Date : 2024-07-10 DOI: 10.48175/ijetir-1250

Dr. Krithika. D. R., Dr. A. Poongodi, T. Swathi

{"title":"Health Analysis and Recommendation Based on Food Using Data Mining","authors":"Dr. Krithika. D. R., Dr. A. Poongodi, T. Swathi","doi":"10.48175/ijetir-1250","DOIUrl":"https://doi.org/10.48175/ijetir-1250","url":null,"abstract":"Suitable nutritional diets have been widely recognized as important measures to prevent and control non-communicable diseases (NCDs). However, there is little research on nutritional ingredients in food now, which are beneficial to the rehabilitation of NCDs. In this project, we profoundly analyzed the relationship between nutritional ingredients and diseases by using data mining methods. First, more than n number of diseases was obtained, and we collected the recommended food and taboo food for each disease. The experiments on reallife data show that our method based on data mining improves the performance compared with the traditional statistical approach. We can assist doctors and disease researchers to find out positive nutritional ingredients that are conducive to the rehabilitation of the diseases as accurately as possible. At present, some data is not available, because they are still in the medical verification. The dataset uploaded will be pre-processed, Feature Extraction, noisy data will be removed, and classification of dataset will take places using random forest algorithm based on this analysis the diseases prediction takes places for the food intake by the individual","PeriodicalId":341984,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"11 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141660895","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

Design & Development of An Web Application for Tracking and Deducting Missing Person 设计和开发用于追踪和扣押失踪人员的网络应用程序

International Journal of Advanced Research in Science, Communication and Technology Pub Date : 2024-07-10 DOI: 10.48175/ijetir-1244

Arshathkhan A, Priya. R

引用次数: 0

Feasibility Study of Aquawall - An Alternative for Conventional Rain Water Harvesting System Aquawall - 传统雨水收集系统的替代品 - 可行性研究

International Journal of Advanced Research in Science, Communication and Technology Pub Date : 2024-07-10 DOI: 10.48175/ijarsct-19140

Shreyas Satpute, Shamal Rajane, Anil Repale, Sakshi Kedari, Sonali Raut

引用次数: 0

Production Floor Digitalization 生产车间数字化

International Journal of Advanced Research in Science, Communication and Technology Pub Date : 2024-07-10 DOI: 10.48175/ijetir-1235

Sneha.K. S, A.Poongodi

{"title":"Production Floor Digitalization","authors":"Sneha.K. S, A.Poongodi","doi":"10.48175/ijetir-1235","DOIUrl":"https://doi.org/10.48175/ijetir-1235","url":null,"abstract":"The digitalization of production floors is becoming increasingly important in the context of e-commerce manufacturers' interactions with customers. This paper investigates the nuances of production floor digitalization in the context of e-commerce manufacturing, examining the implications for both manufactures and buyers. E-commerce manufacturers, faced with the unique challenges of online retail, are leveraging digital technologies to optimize production processes and improve customer experiences. Data-driven demand forecasting, agile manufacturing practices, and seamless integration with e-commerce platforms are all important aspects of production floor digitalization in this context.Digitalization of the production floor provides opportunities for manufacturers to improve efficiency, reduce costs, and respond more quickly to market demand. Manufacturers can improve customer satisfaction and loyalty by implementing real-time data analytics and automation to streamline production workflows, reduce lead times, and ensure timely order fulfillment.On the other hand, production floor digitalization provides significant benefits to e-commerce buyers. Buyers can make more informed purchasing decisions and enjoy greater convenience and reliability in their online transactions thanks to improved product visibility, accurate delivery estimates, and customized purchasing procedures.","PeriodicalId":341984,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"72 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141662818","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

Heterogeneous Social Network Location Aware Multi Party Data Protection and Privacy System 异构社交网络位置感知多方数据保护和隐私系统

International Journal of Advanced Research in Science, Communication and Technology Pub Date : 2024-07-10 DOI: 10.48175/ijetir-1223

J. Ranjithkumar, Dr. Lipsa Nayak

引用次数: 0

Predicting Employee Promotion using Machine Learning 利用机器学习预测员工晋升

International Journal of Advanced Research in Science, Communication and Technology Pub Date : 2024-07-10 DOI: 10.48175/ijetir-1240

K. Durves Mohideen, S. Prasanna

引用次数: 0

Leukemia Cancer Cells Segmentation and Classification using Machine Learning 利用机器学习对白血病癌细胞进行分割和分类

International Journal of Advanced Research in Science, Communication and Technology Pub Date : 2024-07-10 DOI: 10.48175/ijetir-1227

M. Rajamanickam, Dr. C. Meenakshi

{"title":"Leukemia Cancer Cells Segmentation and Classification using Machine Learning","authors":"M. Rajamanickam, Dr. C. Meenakshi","doi":"10.48175/ijetir-1227","DOIUrl":"https://doi.org/10.48175/ijetir-1227","url":null,"abstract":"Determining the aim of the project is to detect the leukemia at earlier stage with the help of image processing techniques. Leukemia means blood cancer which is featured by the uncontrolled and abnormal production of white blood cells (leukocytes) by the bone marrow in the blood. Acute Lymphoblastic Leukemia (ALL) is a type of leukemia which is more common in children. The term Acute‟ means that leukemia can progress quickly and if not treated may lead to fatal death within few months. Due to its non specific nature of the symptoms and signs of ALL leads wrong diagnosis. Even hematologist finds it difficult to classify the leukemia cells, there manual classification of blood cells is not only time consuming but also inaccurate. Therefore, early identification of leukemia yields in providing the appropriate treatment to the patient. Detection through images is fast and cheap method as there is no special need of equipment for lab testing. We have focused on the changes in the geometry of cells like area, perimeter and statistical parameters like mean and standard deviation which separates white blood cells from other blood components using processing tools like MATLAB. After recognizing its statistical properties, types of leukemia will be identified based on the irregularities in the shape.","PeriodicalId":341984,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"18 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141659138","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

Lexicon-Enhanced Long Short-Term Memory (LSTM) for Detecting of Fake News using Deep Learning 利用深度学习检测假新闻的词典增强型长短期记忆（LSTM）

International Journal of Advanced Research in Science, Communication and Technology Pub Date : 2024-07-10 DOI: 10.48175/ijetir-1226

A. Mohammed Yasar, Dr. C. Meenakshi

{"title":"Lexicon-Enhanced Long Short-Term Memory (LSTM) for Detecting of Fake News using Deep Learning","authors":"A. Mohammed Yasar, Dr. C. Meenakshi","doi":"10.48175/ijetir-1226","DOIUrl":"https://doi.org/10.48175/ijetir-1226","url":null,"abstract":"Due to its increasing popularity, low cost, and easy-to-access nature, online social media (OSM) networks have evolved as a powerful platform for people to access, consume, and share news.However, this has led to the large-scale distribution of fake news, i.e., deliberate, false, or misleading information. Spreading fake news is roughly as dangerous as spreading the virus. Fake news detection attracts many researchers' attention due to the negative impacts on the society Over the past years, many fake news detection approaches have been introduced, and most of the existing methods rely on either news content or the social context of the news dissemination process on social media platforms. In this work, we propose a lexicon-enhanced LSTM an automated model that is able to take into account both the news content and the social context for the identification of fake news. The model first uses sentiment lexicon as an extra information pre-training a word sentiment classifier and then get the sentiment embeddings of words including the words not in the lexicon. Combining the sentiment embedding and its word embedding can make word representation more accurate and to detect fake news and better predict fake user accounts and posts.We used five performance metrics to evaluate the proposed framework: accuracy, the area under the curve, precision, recall, and f1-score.The model achieves an accuracy of 99.55% compared to 93.62% against discourse structure analysis. Also, it shows an average improvement of 18.76% against other approaches, which indicates its viability against fake-classifier-based models","PeriodicalId":341984,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"23 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141660594","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

Comprehensive Child Welfare Information System (CCWIS) 儿童福利综合信息系统（CCWIS）

International Journal of Advanced Research in Science, Communication and Technology Pub Date : 2024-07-10 DOI: 10.48175/ijetir-1242

Duwaita. C, Dr. S. Prasanna

{"title":"Comprehensive Child Welfare Information System (CCWIS)","authors":"Duwaita. C, Dr. S. Prasanna","doi":"10.48175/ijetir-1242","DOIUrl":"https://doi.org/10.48175/ijetir-1242","url":null,"abstract":"Child welfare encompasses a broad spectrum of factors crucial for the overall well-being of children, including their physical, emotional, and social health, as well as ensuring their safety and protection from harm. This abstract delves into the multifaceted nature of child welfare and advocates for a holistic approach to address the complex challenges faced by vulnerable children .\u0000An effective strategy for child welfare should emphasize prevention and early intervention, aiming to mitigate risks and foster healthy development from infancy through adolescence. This entails establishing supportive environments within families, communities, and institutions that empower caregivers and offer necessary resources to cater to the diverse needs of children.\u0000Moreover, a comprehensive approach to child welfare necessitates collaboration among various stakeholders, including government agencies, non-profit organizations, educational institutions, healthcare providers, and community members. Through coordinated efforts and partnerships, services can be streamlined, gaps in care can be identified and addressed, and the impact of interventions can be maximized.\u0000Furthermore, it is imperative to tackle systemic issues such as poverty, discrimination, and insufficient access to healthcare and education to enhance child welfare outcomes. Policies and programs must be crafted with a lens of equity and inclusivity, ensuring that all children, irrespective of their backgrounds or circumstances, have equitable opportunities to thrive and succeed..","PeriodicalId":341984,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"48 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141659966","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

Stock Market Prediction Analysis using Deep Learning 利用深度学习进行股市预测分析

International Journal of Advanced Research in Science, Communication and Technology Pub Date : 2024-07-10 DOI: 10.48175/ijetir-1224

Ranjitha. M, Dr. Lipsa Nayak

引用次数: 0