Advances in Computational Intelligence in Materials Science最新文献

Self-Regulating Water Management system using Programmable Logic Controller 采用可编程逻辑控制器的自调节水管理系统

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_19

Yesvanthkrishna V, R. B, Kracose Nishanth J, Anbarasu P, M. C

引用次数: 0

A Study on Palmistry Analysis using Deep Learning 基于深度学习的手相分析研究

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_10

Sarmila K B, Hariboobaalan P N, J. P., K. C, Kavin P

引用次数: 0

Improving Data Security in Cloud Computing 提高云计算中的数据安全

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_5

Subha R, Vaijayanth S, S. j., S. R, S. T

引用次数: 0

Circularly Polarized Metamaterial Based Fractal Wearable Antenna for Wireless Applications 基于圆极化超材料的无线可穿戴分形天线

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_4

Mehaboob Mujawar, Bhagyashree Goudar, Kaveri Basarakod, Aishwarya Kalal

引用次数: 0

Data Validation using ETL – A Theoretical Perspective 使用ETL进行数据验证——一个理论视角

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_2

S. S, Roshaan J. S, S. V, S. S, Sreemathy J

{"title":"Data Validation using ETL – A Theoretical Perspective","authors":"S. S, Roshaan J. S, S. V, S. S, Sreemathy J","doi":"10.53759/acims/978-9914-9946-9-8_2","DOIUrl":"https://doi.org/10.53759/acims/978-9914-9946-9-8_2","url":null,"abstract":"Data is more readily available than ever, but when it is erroneous or insufficient, it can be challenging to interpret. As a result, data validation is essential to improving the quality of data for sound decision-making. The authors have discussed some of the most important concepts and challenges in data validation. It is obvious that human oversight cannot be completely removed from this process. Information priceless human qualities that cannot be taught. Humans are still cautious to take action on decisions that have not been validated by another person, despite today's highly advanced data validation technology or automated approaches. A data validation dashboard can be used by an expert data practitioner to monitor the complete data analysis procedure. The dashboard may make it easier for teams or project managers to assign tasks and resources while also more efficiently monitoring the progress and success of their work. This paper offers insightful discussions of the fundamental ideas, key points, and validation procedure for data validation and quality assurance. Additionally, the article compares several data validation technologies, and several significant industry players are explored. Additionally, the main problems, difficulties, and requirements are explored.","PeriodicalId":261928,"journal":{"name":"Advances in Computational Intelligence in Materials Science","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128479005","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

E-mail Spam Detection and Phishing link Detection Using Machine Learning 使用机器学习的垃圾邮件检测和网络钓鱼链接检测

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_9

Keerthika J, Adisvara A, Akash S, Jayanesh B, Arul Prakash T

引用次数: 0

Identification of Diabetes with Mobile Applications using Cloud Based Expert System 基于云专家系统的移动应用识别糖尿病

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_15

P. M, Santhoshkumar S P, Chandramohan S

{"title":"Identification of Diabetes with Mobile Applications using Cloud Based Expert System","authors":"P. M, Santhoshkumar S P, Chandramohan S","doi":"10.53759/acims/978-9914-9946-9-8_15","DOIUrl":"https://doi.org/10.53759/acims/978-9914-9946-9-8_15","url":null,"abstract":"The integration of expert systems, mobile intelligence, and the cloud for diabetes diagnosis was the study's main objective. An expert system is a computer programme that makes use of a knowledge base and an inference engine to resolve problems considerably more quickly and effectively than they would otherwise. To lessen the limitations of mobile applications, the cloud has provided developers with a variety of services to create, manage, and deploy. Because of population expansion, ageing, addiction, urbanization, obesity, lack of exercise, and other complex diseases, there are more people with diabetes than ever before. Furthermore, these issues are made worse by a lack of specialists, inaccurate diagnoses, and inadequate medical facilities. Thus, diabetics require ongoing care such as dietary restriction, exercise, and insulin management. A hospital's knowledge was drawn from in order to create the prototype using a purposive sampling technique. Case studies are chosen for testing and assessing the prototype system in order to determine whether or not it is accurate and meets end-user criteria.","PeriodicalId":261928,"journal":{"name":"Advances in Computational Intelligence in Materials Science","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134029204","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

Encrypted Image Retrieval Scheme on Blockchain 区块链加密图像检索方案

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_7

Chandiya C, Dhanushya D, Harithaa G

{"title":"Encrypted Image Retrieval Scheme on Blockchain","authors":"Chandiya C, Dhanushya D, Harithaa G","doi":"10.53759/acims/978-9914-9946-9-8_7","DOIUrl":"https://doi.org/10.53759/acims/978-9914-9946-9-8_7","url":null,"abstract":"Blockchainhas flourished in a variety of industries throughout a period known as the \"digital economy\", including finance and digital copyright. Blockchain is highlighting the storage issue more and more. In order to lessen the demand for node storage, the existing blockchain maintains block information in external storage devices. Blockchain transaction retrieval issue is brought on by the new blockchain storage approach. The issue arises when the user is required to download the decentralized blockchain ledger information from the external storage system. Since, they couldn't locate the node comprising that particular transaction, therefore which results in significant communication overhead. We take advantage of the data that is Blockchain is semi-structured for this issue and obtain the common traits of blockchain transactions like the Date and account address. Next, we create a method for retrieving blockchain transactions. Because of the absence of an effective account-specific secondary search data structure addresses, we suggest the scalable B+ tree. For encryption and decryption of Images we have used Elliptic curve Cryptography algorithm and AES algorithm. For Generating Hash value we have used ECDSA Algorithm.","PeriodicalId":261928,"journal":{"name":"Advances in Computational Intelligence in Materials Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129515012","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

Advancements in Machine Learning Techniques for Optimizing Cognitive Radio Networks: A Comprehensive Review 优化认知无线电网络的机器学习技术进展:综述

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_20

Niranjani V, Premkumar Duraisamy, Priyadharshan M, Gayathri B

引用次数: 4

A New Approach of Machine Learning and Deep Learning Algorithms Based Crop Yield Prediction 基于机器学习和深度学习算法的作物产量预测新方法

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_18

S. S, Venkata Sai Vaishnavi K, S. B, Vijitha B, Vineela Reddy B

{"title":"A New Approach of Machine Learning and Deep Learning Algorithms Based Crop Yield Prediction","authors":"S. S, Venkata Sai Vaishnavi K, S. B, Vijitha B, Vineela Reddy B","doi":"10.53759/acims/978-9914-9946-9-8_18","DOIUrl":"https://doi.org/10.53759/acims/978-9914-9946-9-8_18","url":null,"abstract":"The science and skill of nurturing plants and wildlife are referred to as agriculture. India ranks second in the world for farming, which takes up 60.45% of the country's territory. The economy of India is primarily supporting agricultural, agro-industrial sectors. Crop rotation, the consistency of the soil, air and surface temperatures, precipitation, and other elements all have an impact on how well crops are grown. Further crucial are soil constituents including nitrogen, phosphate, and potassium. The corpus of work currently being done in this field includes a crop choice model that makes use of ML methods (Random Forest, Decision Tree, ANN). In this paper, recommended model enhanced using Deep Learning techniques, in addition to crop prediction, precise data on the amounts of necessary soil components and their individual prices are attained. Compared to the present model, it provides a better degree of accuracy. In order to help farmers to predict a profitable crop, analyses the available data. Variables related to the soil and climate taken into consideration to anticipate an acceptable yield. This objective show’s that Python-Based System using cunning strategies for predicting, bountiful harvest possible while using the least amount of resources. In this work, the SVM machine learning algorithm is combined with the LSTM and RNN deep learning algorithms.","PeriodicalId":261928,"journal":{"name":"Advances in Computational Intelligence in Materials Science","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121235630","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