2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)最新文献

A Comprehensive Analysis of the Effectiveness of Machine Learning Algorithms for Predicting Water Quality 机器学习算法预测水质有效性的综合分析

2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA) Pub Date : 2023-03-14 DOI: 10.1109/ICIDCA56705.2023.10099968

Priyanshu Rawat, Madhvan Bajaj, Vikrant Sharma, Satvik Vats

{"title":"A Comprehensive Analysis of the Effectiveness of Machine Learning Algorithms for Predicting Water Quality","authors":"Priyanshu Rawat, Madhvan Bajaj, Vikrant Sharma, Satvik Vats","doi":"10.1109/ICIDCA56705.2023.10099968","DOIUrl":"https://doi.org/10.1109/ICIDCA56705.2023.10099968","url":null,"abstract":"This study provides a comprehensive analysis of the effectiveness of eight different machine learning algorithms for predicting water quality. The algorithms, which include Gaussian Naive Bayes, Extreme Gradient Boost Classifier, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), Logistic Regression, Random Forest, and Decision Tree, were tested using the water potability dataset. This study's main goals were to identify the best accurate machine learning algorithm for predicting water quality and to present a thorough comparison of these methods. Algorithm's effectiveness. The study's findings demonstrated that one algorithm performed better than the others, with the lowest mean squared error and maximum accuracy. The results of this study may be used as a guide for future research in this area and offer a strong foundation for selecting the best machine learning algorithm for predicting water quality, Predicting water quality is often hampered by a lack of data, especially in developing or rural areas. Machine learning techniques may be used to predict water quality. This study highlights how crucial it is to use a suitable machine learning algorithm for predicting water quality since the precision and efficiency of these algorithms may have a big influence on the outcomes. Organizations that manage and monitor water quality, as well as academics and experts in the field of water quality forecasting, can benefit from the study's findings.","PeriodicalId":108272,"journal":{"name":"2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116686785","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: 9

Smart Helmet for Coal Mine Employees: Enhancing Safety and Efficiency 煤矿职工智能头盔:提高安全与效率

2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA) Pub Date : 2023-03-14 DOI: 10.1109/ICIDCA56705.2023.10099883

R. P. Kumar, Hariprasadh. R. R, Gowthamraj. A, Harinivash. K

引用次数: 0

Applicant Screening System Using NLP 使用NLP的申请人筛选系统

2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA) Pub Date : 2023-03-14 DOI: 10.1109/ICIDCA56705.2023.10099953

B. Lalitha, Sirisha Kadiyam, Ritisha Varma Kalidindi, Sri Maukthika Vemparala, Kshiraja Yarlagadda, Sri Vinutna Chekuri

{"title":"Applicant Screening System Using NLP","authors":"B. Lalitha, Sirisha Kadiyam, Ritisha Varma Kalidindi, Sri Maukthika Vemparala, Kshiraja Yarlagadda, Sri Vinutna Chekuri","doi":"10.1109/ICIDCA56705.2023.10099953","DOIUrl":"https://doi.org/10.1109/ICIDCA56705.2023.10099953","url":null,"abstract":"This research work is mainly focused on selecting or short-listing the eligible candidates from the pool of applicants in a relatively short span of time. As technology is rapidly progressing, manpower requirement also increases exponentially. Thus, to calibrate the cream of the crop, this online application screens the applicants resume for a specific recruitment ad. This is designed in such a way that the applicant as well as the hiring agency can both be benefited, i.e., the applicant can use it to avail the job opportunities, apply for it and improve their abilities if they don't meet the criteria. Hiring agencies can mention the details of the job openings available. This bilateral website allows applicant to upload their resume, the resume uploaded will be compared with the job occupation requirement posted by the hiring agencies by using Natural Language Processing [NLP]. Results are generated using cosine similarity, then the similarity of both the uploaded documents in percentage is displayed. The eligibility of the candidate is decided based on the displayed result. Recent techniques include CNN KNN algorithms which are complex and time consuming, this project uses NLP tools, which simplifies the process, reduces the time consumption and also gives accurate answers.","PeriodicalId":108272,"journal":{"name":"2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127367595","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 Study on Cervical Cancer Prediction using Various Machine Learning Approaches 基于各种机器学习方法的宫颈癌预测研究

2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA) Pub Date : 2023-03-14 DOI: 10.1109/ICIDCA56705.2023.10099493

Priyanshu Rawat, Madhvan Bajaj, Shreshtha Mehta, Vikrant Sharma, Satvik Vats

{"title":"A Study on Cervical Cancer Prediction using Various Machine Learning Approaches","authors":"Priyanshu Rawat, Madhvan Bajaj, Shreshtha Mehta, Vikrant Sharma, Satvik Vats","doi":"10.1109/ICIDCA56705.2023.10099493","DOIUrl":"https://doi.org/10.1109/ICIDCA56705.2023.10099493","url":null,"abstract":"Cervical cancer is a major cause of mortality for women, and early detection is crucial for successful treatment Recent studies have investigated the use of machine learning for early detection of cervical cancer, but challenges remain. This paper evaluates the performance of different machine learning algorithms, including logistic regression, bagging, random forest, and XG Boost, for predicting cervical cancer. The study analyzes challenges in working with cervical cancer data, such as dealing with imbalanced datasets and limited data availability. To address these challenges, the paper proposes an approach that combines the strengths of the different algorithms to develop a more accurate and reliable model for early detection of cervical cancer. To assess the effectiveness of the proposed approach, the study uses standard metrics, including accuracy, precision, recall, and F1 score. The findings indicate that the proposed approach outperforms the individual machine learning algorithms in terms of predictive accuracy and precision. The paper emphasizes the need for further research in this area and highlights the potential of machine learning to enhance the early detection of cervical cancer. By proposing a new approach that addresses the challenges faced by existing methods, the paper aims to contribute to efforts to improve cervical cancer detection and treatment.","PeriodicalId":108272,"journal":{"name":"2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115564084","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: 9

Drug Recommendation System in Medical Emergencies using Machine Learning 基于机器学习的医疗紧急情况药物推荐系统

2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA) Pub Date : 2023-03-14 DOI: 10.1109/ICIDCA56705.2023.10099607

C. Silpa, B. Sravani, D. Vinay, C. Mounika, K. Poorvitha

{"title":"Drug Recommendation System in Medical Emergencies using Machine Learning","authors":"C. Silpa, B. Sravani, D. Vinay, C. Mounika, K. Poorvitha","doi":"10.1109/ICIDCA56705.2023.10099607","DOIUrl":"https://doi.org/10.1109/ICIDCA56705.2023.10099607","url":null,"abstract":"Online recommender systems are being used increasingly often for hospitals, medical professionals, and drugs. Today, the great majority of consumers look online before asking their doctors for prescription suggestions for a range of health conditions. The medical suggestion system can be valuable when pandemics, floods, or cyclones hit. In the age of Machine Learning (ML), recommender systems give more accurate, precise, and reliable clinical predictions while using less resources. The medicine recommendation system gives the patient reliable information about the medication, the dosage, and any possible adverse effects. Medication is given based on the patient's symptoms, blood pressure, diabetes, temperature, and other parameters. Drug recommendation systems provide precise information at any time while improving the performance, integrity, and privacy of patient data in the decision-making process. Recommender system, the decision tree produces the most accurate results. In times of medical emergency, a drug recommendation system is helpful for giving patients recommendations for safe medications.","PeriodicalId":108272,"journal":{"name":"2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116078999","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

English to Hindi Translation using Transformer 英语到印地语翻译使用变压器

2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA) Pub Date : 2023-03-14 DOI: 10.1109/ICIDCA56705.2023.10100193

Abhinav Y. Watve, Madhuri A. Bhalekar

引用次数: 0

Grapes Insect Detection and Monitoring using YOLOv4 基于YOLOv4的葡萄害虫检测与监测

2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA) Pub Date : 2023-03-14 DOI: 10.1109/ICIDCA56705.2023.10099496

Nandinee Mudegol, A. Kamble, V. Jadhav, Shivkanya Ram Birajdar

引用次数: 1

Machine Learning based Iris Recognition Modern Voting System 基于机器学习的虹膜识别现代投票系统

2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA) Pub Date : 2023-03-14 DOI: 10.1109/ICIDCA56705.2023.10099580

Aparna D K, Dharshini V S, Rajeshkumar G, Mohana Priya D, P. Balasubrarnanie, S. Hamsanandhini

{"title":"Machine Learning based Iris Recognition Modern Voting System","authors":"Aparna D K, Dharshini V S, Rajeshkumar G, Mohana Priya D, P. Balasubrarnanie, S. Hamsanandhini","doi":"10.1109/ICIDCA56705.2023.10099580","DOIUrl":"https://doi.org/10.1109/ICIDCA56705.2023.10099580","url":null,"abstract":"A paper ballot or an Electronic Voting Machine (EVM) based on Direct Response Electronic (DRE) or Identical Ballot Boxes have traditionally been used for voting. This study recommends a digital voting system based on Machine Learning algorithm that uses Iris recognition to address the flaws in the current voting process in order to fix the traditional voting system's flaws. A program called the Iris recognition-based Voting System identifies people based on the iris pattern of their eyes. Iris recognition is an automated biometric identification technology that analyses video evidence of one or both of an individual's iris to identify complex patterns that are distinct, stable, and visible from a distance. A voter may only cast one ballot, where the proposed technology prohibits multiple votes from the same person because it can spot duplicate entries. Additionally, this technique does away with the need for the user to carry a voter ID that has the relevant information since the Aadhar is incorporated with the voter ID thus enhancing the digitalization by means of digital verification of biometric and iris pattern available in Aadhar card of every user. At the voting venue, a simple iris scan will allow the voter's iris to be collected and used as identification. The iris recognition process consists of the following four steps: image acquisition, iris segmentation, feature extraction, and pattern matching. Iris recognition is one of the most trustworthy biometric modalities due to its high identification rate. Thereby this system eliminates the major drawbacks of traditional voting systems and enhances the digital voting by incorporating the modern transformation.","PeriodicalId":108272,"journal":{"name":"2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)","volume":"344 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122104187","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

Machine Learning based Mobile App for Heart Disease Prediction 基于机器学习的心脏病预测移动应用程序

2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA) Pub Date : 2023-03-14 DOI: 10.1109/ICIDCA56705.2023.10099714

S. Reddy, S. Lohitha, Fathimabi Shaik

{"title":"Machine Learning based Mobile App for Heart Disease Prediction","authors":"S. Reddy, S. Lohitha, Fathimabi Shaik","doi":"10.1109/ICIDCA56705.2023.10099714","DOIUrl":"https://doi.org/10.1109/ICIDCA56705.2023.10099714","url":null,"abstract":"The world's leading cause of death is heart disease. A variety of modern technologies are utilized to treat cardiac disease The most common problem in medical centers around the world is that many medical personnel lack equal knowledge and courage to treat their patients, so they develop their own opinions, which leads in bad outcomes and, in some cases, death. Predictions of cardiac illness are employed to overcome these issues. This study has used various criteria to predict cardiac disease. These characteristics are Age, Gender, Cerebral Palsy (CP), Blood Pressure (BP), Fasting blood sugar test (FBS), and so on. The major goal of the research is to create a mobile app that reduces the cost of medical tests while also avoiding human bias. The outcome of the research is to forecast cardiac disease. The research made advantage of the built-in dataset and used PHR data to make predictions. Machine Learning is being used to build the model. This study utilizes a variety of machine learning algorithms, including Logistic Regression, ANN Multi-Layer Perceptron (MLP), and Random Forest (RF). Random Forest (RF) outperforms the other two algorithms in terms of accuracy. As a result, this study employs random forest to forecast heart healthand builds the mobile app with MIT App Inventor and stores the data in the Firebase database. The App could be to maintain personal health records and share our info with doctors. It will forecast heart health when you enter the criteria.","PeriodicalId":108272,"journal":{"name":"2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117012574","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

Machine Learning Approach for Gesticulation System Using Hand 手部手势系统的机器学习方法

2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA) Pub Date : 2023-03-14 DOI: 10.1109/ICIDCA56705.2023.10100159

N. Kumar, P. Deivendran, S. Raju, V. D. Kumar, C. M. Krishnan

{"title":"Machine Learning Approach for Gesticulation System Using Hand","authors":"N. Kumar, P. Deivendran, S. Raju, V. D. Kumar, C. M. Krishnan","doi":"10.1109/ICIDCA56705.2023.10100159","DOIUrl":"https://doi.org/10.1109/ICIDCA56705.2023.10100159","url":null,"abstract":"Hand gestures play a crucial role in both nonverbal cues and our interactions with the outside world. Notably, millions of individuals with disabilities benefit from sign language, a system of hand signals. The versatility of hand gesture recognition technologies to successfully collaborate with machines has spurred their rapid development in recent years. The most intuitive form of communication between humans and PCs in a virtual environment is seen to be gesturing. The proposed work focus on hand gestures to convey ideas because they are an evocative form of nonverbal communication. In this programme, the camera on our PC captures a live video from which a preview is obtained with the aid of its features or operations. The entry onto the market of inexpensive webcams with at least acceptable characteristics opens up new avenues for the application of human-computer interaction (HCI) interfaces. The paper offers an HCI mouse cursor control interface. The implemented solution's goal is to enable user hand motions to move the mouse cursor while viewed on a webcam.","PeriodicalId":108272,"journal":{"name":"2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129828953","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