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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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發(fā)表于 2025-3-21 18:31:20 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Emerging Technologies in Data Mining and Information Security
副標(biāo)題Proceedings of IEMIS
編輯Ajith Abraham,Paramartha Dutta,Soumi Dutta
視頻videohttp://file.papertrans.cn/309/308448/308448.mp4
概述Comprises original research work by academics, scientists, and research scholars along with professionals, decision-makers, and industrial practitioners
叢書名稱Advances in Intelligent Systems and Computing
圖書封面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
關(guān)鍵詞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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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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