2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)最新文献

Multi-Label Classification using Q-Learning 基于q -学习的多标签分类

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9988212

Abhishek Bhola, S. Athithan, K. Srinivas, Naresh Poloju, S. Mittal, Yogesh Kumar Sharma

{"title":"Multi-Label Classification using Q-Learning","authors":"Abhishek Bhola, S. Athithan, K. Srinivas, Naresh Poloju, S. Mittal, Yogesh Kumar Sharma","doi":"10.1109/ICTACS56270.2022.9988212","DOIUrl":"https://doi.org/10.1109/ICTACS56270.2022.9988212","url":null,"abstract":"Multi-label classification is an important but difficult topic that involves assigning the most appropriate subset of class labels to each document from a large label collection. The enormous label space presents a number of research obstacles, including data sparsity and scalability. In recent years, breakthrough machine learning algorithms such as tree induction using large margin partitions of the instance spaces and label vector embedding in the target space have resulted in substantial progress. Example: The input text may be a narrative document from chinastory.cn, with the labels representing storey categories that infer the possible meaning of the content. However, applying standard neural network models to the Multi-label classification problem in a haphazard manner results in sub-optimal performance because to the wide output space as well as the label sparsity problem. Despite its widespread success in other fields, Q-learning has not been investigated for multi-label classification. This paper presents the Q-learning algorithm to Multi-label classification, which was the first attempt of applying to Multi-label classification.","PeriodicalId":385163,"journal":{"name":"2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120963808","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

Query Expansion for Information Retrieval using Word Embeddings: A Comparative Study 基于词嵌入的信息检索查询扩展比较研究

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9988667

Namrata Nagpal

引用次数: 0

Intelligent Assessment of the Visual Ecology of the Urban Environment 城市环境视觉生态智能评价

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9988692

D. Ather, N. Rashevskiy, D. Parygin, A. Gurtyakov, S. Katerinina

引用次数: 0

A Real Time Monitoring System for Home Isolated COVID-19 Patients 新型冠状病毒肺炎居家隔离患者实时监测系统

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9988589

Awakash Prasad, Sapna Kumari, A. Rao, V. Chaubey, Arun Kumar

{"title":"A Real Time Monitoring System for Home Isolated COVID-19 Patients","authors":"Awakash Prasad, Sapna Kumari, A. Rao, V. Chaubey, Arun Kumar","doi":"10.1109/ICTACS56270.2022.9988589","DOIUrl":"https://doi.org/10.1109/ICTACS56270.2022.9988589","url":null,"abstract":"During this Covid-19-time number of patients in hospital are increased. The covid-19 patients are mainly of two types one who has a serious condition and the other who has a mild covid-19 symptom. On the other way, the patients who have very serious conditions generally have all facilities, they have doctors around them and other medical staff also there to take care of the situation, but the patients who have not very serious conditions are generally isolated in their home, a problem with this home isolated patients are they do not consult with doctor day to day and what happens if patients condition become serious basically this paper is going to solve this two problem and also monitoring the patients while getting different data like a heartbeat, SpO2, body temperature, etc. along with that we used a location sharing and nearest hospitals identification. Here we design IoT, GSM/GPS-based system through which we send the patients' health data directly to the hospital and if the patients' conduction becomes serious then it sends an alert to the hospital along with the patient's location and it also sends the hospital location to the patients.","PeriodicalId":385163,"journal":{"name":"2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)","volume":"12 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123690990","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

Prediction of Crop Yield Based-on Soil Moisture using Machine Learning Algorithms 基于土壤湿度的机器学习作物产量预测

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9988186

S. G, S. Paudel, Riyaz Nakarmi, Prashant Giri, Shanta Karki

{"title":"Prediction of Crop Yield Based-on Soil Moisture using Machine Learning Algorithms","authors":"S. G, S. Paudel, Riyaz Nakarmi, Prashant Giri, Shanta Karki","doi":"10.1109/ICTACS56270.2022.9988186","DOIUrl":"https://doi.org/10.1109/ICTACS56270.2022.9988186","url":null,"abstract":"Agriculture planning is playing an important role as the economic growth is very high day by day in our daily life. There is lot of research study going on as there are few important issues like soil nutrients, crop prediction, farming system, crop monitoring in agriculture with modern farming system. Crop prediction and crop monitoring is main factor to produce good quality of crops for farmers to predict crop yield based on soil moisture. Prediction of crop yield includes forecasting factors like temperature, humidity, rainfall, etc., and crop yield based on soil moisture includes few measures like NPK (Nitrogen, Phosphorous and potassium) and pH values using various sensors. Machine learning (ML) is a useful decision-making model for estimating crop yields, and also for deciding what crops to plant and what to do during the crop's growing seasons. To aid agricultural yield prediction studies, a number of analytical techniques have been used. In this study Farmers can predict or come to a decision the type of soil moisture values; Farmers can choose the type of crop they want to sow. In this paper, Author proposed decision tree supervised machine learning algorithm to improve the results for the prediction of crop yield based on soil moisture parameters to achieve better error rate and accuracy for economic growth. It also includes the few machine learning algorithms which are discussed in literature survey, further Author highlighted the proposed system in methodology, and compared the analysis in results to give it a balance view. The future scope is also mentioned to improve it for further studies. This paper will be sufficient for those who are keener in learning about the expectation of crop yield based on soil moisture using ML Algorithms.","PeriodicalId":385163,"journal":{"name":"2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125500259","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 Intelligent Power Grid with CENELEC A used in Integrated Electronic Devices 集成电子设备用CENELEC A智能电网

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9987974

Subha T D, Mukhil R, Sree Saran, V. T., Aswin Kumar V V

引用次数: 0

Fire Detection System with Artificial Intelligence 人工智能火灾探测系统

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9987921

Mrinal Paliwal, D. Singh

引用次数: 0

Image processing of Sentinel-2MSI data for Lake Water Quality Analysis 基于Sentinel-2MSI数据的湖泊水质分析图像处理

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9987788

Srikrishna B.R, R. Sivakumar

引用次数: 1

Internet of Things and Machine Learning Based Intelligent Irrigation System for Agriculture 基于物联网和机器学习的农业智能灌溉系统

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9988387

T. Aravinda, K. Krishnareddy

{"title":"Internet of Things and Machine Learning Based Intelligent Irrigation System for Agriculture","authors":"T. Aravinda, K. Krishnareddy","doi":"10.1109/ICTACS56270.2022.9988387","DOIUrl":"https://doi.org/10.1109/ICTACS56270.2022.9988387","url":null,"abstract":"A large level of interest has been shown in precision farming recently due to the growing demand for water and food worldwide. Producers will thus need there must be adequate water and agriculturally appropriate land to meet this need. Because with the limitations both materials are readily accessible, thus farmers need a strategy that modifies their behaviour. The secret to efficient irrigation is finding a way to provide a greater, better, and more profitable output while using less resources. There are many machine learning based Irrigation methods have been suggested to effectively utilize more water. Unusual weather conditions are not suitable for these algorithms since they have a limited learning ability. This innovation, which integrates intelligence, keeps performing better for longer periods of time despite the weather in any place. DLiSA forecasts the overall soil moisture levels for the next day, the duration of the irrigated, and the geographical extent of the water required to irrigate the field using a lengthy short attention span network. The simulation outcomes demonstrate that DLiSA makes better use of water over cutting-edge technology. prototypes used for research agriculture in the area.","PeriodicalId":385163,"journal":{"name":"2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130574847","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

Efficient Prediction of Heart Diseases by using Machine Learning Classifiers 利用机器学习分类器有效预测心脏病

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9988582

B. Venkataramanaiah, Sasikar A., V. P. Naveen Kumar Reddy, V. L. Prasanna Kumar

引用次数: 0