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Titlebook: Emerging Technologies in Data Mining and Information Security; Proceedings of IEMIS Ajith Abraham,Paramartha Dutta,Soumi Dutta Conference p

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发表于 2025-3-21 18:31:20 | 显示全部楼层 |阅读模式
书目名称Emerging Technologies in Data Mining and Information Security
副标题Proceedings of IEMIS
编辑Ajith Abraham,Paramartha Dutta,Soumi Dutta
视频video
概述Comprises original research work by academics, scientists, and research scholars along with professionals, decision-makers, and industrial practitioners
丛书名称Advances in Intelligent Systems and Computing
图书封面Titlebook: Emerging Technologies in Data Mining and Information Security; Proceedings of IEMIS Ajith Abraham,Paramartha Dutta,Soumi Dutta Conference p
描述.This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2018) held at the University of Engineering & Management, Kolkata, India, on February 23–25, 2018. It comprises high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, and case studies related to all the areas of data mining, machine learning, Internet of Things (IoT) and information security..
出版日期Conference proceedings 2019
关键词Data Science; Information Security; Artificial Intelligence; Cognitive Science; Computer Graphics; Roboti
版次1
doihttps://doi.org/10.1007/978-981-13-1951-8
isbn_softcover978-981-13-1950-1
isbn_ebook978-981-13-1951-8Series ISSN 2194-5357 Series E-ISSN 2194-5365
issn_series 2194-5357
copyrightSpringer Nature Singapore Pte Ltd. 2019
The information of publication is updating

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Crop Prediction Models—A Review Crop prediction models have proven to be successful in increasing the crop yield. Soil parameters and atmospheric parameters are used by the models to predict the suitable crop. Parameters such as type of soil, pH, phosphate, potassium, organic carbon, sulphur, manganese, copper, iron, depth, tempe
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Prediction of Bacteriophage Protein Locations Using Deep Neural Networkslays an important role here. In this paper, we propose a supervised learning based method to predict the locations of bacteriophage proteins. First, we address the problem of predicting whether a bacteriophage is extracellular or located in the host cell. Second, we also address the subcellular loca
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Classification of Phishing Websites Using Moth-Flame Optimized Neural Network the Internet database, masquerading as the trusted website. They even use the logo and the website address of the original website to come off as the original one to the user. In this project, we deal with the classification of such websites from the real ones using the standards set by W3C. The Mo
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Design and Analysis of Intrusion Detection System via Neural Network, SVM, and Neuro-Fuzzyesign, and analysis of intrusion detection system via neuro-fuzzy, neural network and SVM technique for the improvement misuse detection system. The proposed approachable to enhancement anomaly detection and improve these techniques for anomaly detection.
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Grammar-Based White-Box Testing via Automated Constraint Path Generationdyssey. In this paper, the author presents a grammar-basedwhite-box testing which integrates some source code analysis, grammar-based test generation, and constraint solving as a whole. A preliminary implementation of grammar-based white-box testing, Java White-box Unit Tester (JWBUT), has been deve
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Gender Recognition Inclusive with Transgender from Speech Classificationiminal investigation. Focus of substantial past researches was limited towards the discrimination of male and female gender only. Recently transgender has achieved legal recognition. So, any gender classification system should consider this third gender also. But unfortunately there is a lack of goo
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