Advances in Computational Intelligence in Materials Science最新文献_第3页

A Review Paper on Identification of Ayurvedic Prakriti Types 阿育吠陀植物类型鉴定综述

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_26

Swati Dhole, Yedey S.E.

{"title":"A Review Paper on Identification of Ayurvedic Prakriti Types","authors":"Swati Dhole, Yedey S.E.","doi":"10.53759/acims/978-9914-9946-9-8_26","DOIUrl":"https://doi.org/10.53759/acims/978-9914-9946-9-8_26","url":null,"abstract":"Human prakriti and tridosha are important for human health and fitness according to Ayurveda. A person's prakriti can be identified in Ayurveda in several ways. According to Ayurveda, every person born has five elements: earth, air, water, fire and space.We own distinctive balance of these five elements in assorted degrees. The balance of these elements is known as Tridosha. There are three basic doshas: Vata, Pitta and Kapha, and good health is considered a balance of these three doshas. Doctors evaluate these characteristics through examination and palpation to determine Prakriti in patients.The physician decides on diagnosis, primary prevention, and therapy based on the Prakriti of each individual. Prakriti assessment involves clinical examination including questions about physiological and behavioural traits. There is requirement to develop models correctly for predicting prakriti classes that have been used for foretell various diseases. Ayurvedic doctors examine the prakriti of a person either by accessing the physical features and or by inspecting the nature of their pulsation. Based on this investigation, they identify, prevent and cure disease in patients by prescribing medicine.","PeriodicalId":261928,"journal":{"name":"Advances in Computational Intelligence in Materials Science","volume":"42 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":"127662463","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

Implementation of Data Migration and Validation to Azure using Talend 使用Talend实现数据迁移和验证到Azure

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_13

Niranjani V, Logapriya K, Pavani R, K. M, Ranjith V

引用次数: 0

Image forgery detection using Convolutional Neural Networks 基于卷积神经网络的图像伪造检测

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_23

P. Babu, Sivanagireddy A, Narsireddy M, Yogapriya Jaganathan

{"title":"Image forgery detection using Convolutional Neural Networks","authors":"P. Babu, Sivanagireddy A, Narsireddy M, Yogapriya Jaganathan","doi":"10.53759/acims/978-9914-9946-9-8_23","DOIUrl":"https://doi.org/10.53759/acims/978-9914-9946-9-8_23","url":null,"abstract":"Digital forensics vital aspect of picture identity theft has drawn a lot of notice recently. In order to establish the primitive character of images, earlier studies looked at residual pattern noise, wavelet-transformed data and facts, image pixel resolution histograms, and additional characteristics of images. In an attempt to attain high-level picture illustration with the advancement of neural network-based innovations, convolutional neural networks have recently been utilized for recognizing image counterfeiting. This model suggests constructing a convolutional neural network with a structure that is distinct from previous studies in which we attempt to interpret the features derived from each layer of convolution to recognize a variety of picture manipulation using automated feature recognition. Three convolutional layers, one fully interconnected layer, and a SoftMax classifier constitute the suggested system. Our study utilizes our own data collection as the training data, which includes genuine pictures, spliced images, and further enhanced replicates with retouched and re-compressed images. Experimental findings make it abundantly obvious that the proposed network is optimal and versatile.","PeriodicalId":261928,"journal":{"name":"Advances in Computational Intelligence in Materials Science","volume":"45 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":"130269279","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

Home Automation Using ARM-7 Microcontroller with Improved Security 使用ARM-7微控制器提高安全性的家庭自动化

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_21

Praveenkumar Babu, A. T, Bashkaran K, Selvi C, Srinivas Reddy, Vijayakumar Ch

{"title":"Home Automation Using ARM-7 Microcontroller with Improved Security","authors":"Praveenkumar Babu, A. T, Bashkaran K, Selvi C, Srinivas Reddy, Vijayakumar Ch","doi":"10.53759/acims/978-9914-9946-9-8_21","DOIUrl":"https://doi.org/10.53759/acims/978-9914-9946-9-8_21","url":null,"abstract":"The Internet of Things (IoT) is a next-generation technology that enables easy remote control of home appliances and offers people a simple and convenient lifestyle. Home automation system based on ARM7 and IoT technology infrastructure (ARM7, communication devices, NodeMCU) enables remote control without human intervention. Home automation is a major advancement in technology that allows you to control lighting, security, temperature, alarms and appliances. This study presents the development of three modules that allow homeowners to remotely monitor readings with their mobile devices. The modules include dust monitoring, house light activation and gas sensors. Each module contains a microcontroller and a sensor that records the data and transmits it over the Internet, ultimately producing a report. The mobile app interprets the data and provides a readable report that homeowners can use to make future decisions. In summary, this study shows the potential of IoT and home automation systems to enable efficient and convenient control of various home appliances and devices, providing a better lifestyle for homeowners.","PeriodicalId":261928,"journal":{"name":"Advances in Computational Intelligence in Materials Science","volume":"42 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":"126350156","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

Multi Trend Twitter Sentiment Analysis: Collaborative Approach for Improved Results 多趋势推特情绪分析:改进结果的协作方法

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI: 10.53759/acims/978-9914-9946-9-8_12

Keerthika J, Hemapriya N, A. R, Karpagathareni S, B. S

{"title":"Multi Trend Twitter Sentiment Analysis: Collaborative Approach for Improved Results","authors":"Keerthika J, Hemapriya N, A. R, Karpagathareni S, B. S","doi":"10.53759/acims/978-9914-9946-9-8_12","DOIUrl":"https://doi.org/10.53759/acims/978-9914-9946-9-8_12","url":null,"abstract":"Twitter has a significant number of daily users through which tweets are utilized to communicate their thoughts in this era of growing social media users. This paper offers a way to haul out sentiments from tweets as well as a method for sorting out various tweets as optimistic, adverse, or unbiased. It refers to identifying and classifying the sentiments expressed in the text source. The existing Twitter APIs for data extraction are used to mine public Twitter data. Tweets would be chosen based on a few carefully chosen keywords related to the domain of our concern. In our proposed method, we collected various sentiment data from a variety of tweets to train and produce more precise and reliable sentiment classifiers for each trend. This method automatically extracts the key elements of subjects from online user evaluations. Since tweets are generally unstructured in format, they must first be converted into structured format. And after that, the data is fed into several models for training and used to rank the best sentiment classifier. The intention of this design is to arrive at a model that can classify sentiments of real-world data using Twitter.","PeriodicalId":261928,"journal":{"name":"Advances in Computational Intelligence in Materials Science","volume":"18 7 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":"125770308","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 Survey on Encryption Framework Against Insider Keyword-Guessing Attack in Cloud Storage 针对云存储内部关键字猜测攻击的加密框架研究

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-01 DOI: 10.53759/acims/978-9914-9946-9-8_8

Subha R, S. B, Sivaram C, S. S., Vikram S S, VimalKumar M

引用次数: 0