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Titlebook: Information and Communication Technology and Applications; Third International Sanjay Misra,Bilkisu Muhammad-Bello Conference proceedings

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978-3-030-69142-4Springer Nature Switzerland AG 2021
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Multi-class Model MOV-OVR for Automatic Evaluation of Tremor Disorders in Huntington’s Diseasebtained during research from subjects and patients with HD in Lithuania. The proposed SVM model achieved an accuracy of 97.09% in relation to 14 different classes, which were built according to the Shoulson-Fahn Total Functional Capacity (TFC) scale for assessing the patient’s tremor condition.
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1865-0929 ations, ICTA 2020, held in Minna, Nigeria, in November 2020. Due to the COVID-19 pandemic the conference was held online. .The 67 full papers were carefully reviewed and selected from 234 submissions. The papers are organized in the topical sections on Artificial Intelligence, Big Data and Machine L
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Conference proceedings 2021TA 2020, held in Minna, Nigeria, in November 2020. Due to the COVID-19 pandemic the conference was held online. .The 67 full papers were carefully reviewed and selected from 234 submissions. The papers are organized in the topical sections on Artificial Intelligence, Big Data and Machine Learning; I
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A Survey for Recommender System for Groupser, ACM and Google Scholar, from which 300 publications were screened. Irrelevant, duplicate and ambiguous papers were removed. At the end, 26 papers were used for depth analysis. This study provides a systematic review of the available evidence based literature concerning recommender systems for groups.
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A Conceptual Hybrid Model of Deep Convolutional Neural Network (DCNN) and Long Short-Term Memory (LS detecting such attack has proven to be ineffective as rate of false positives is always on the high side and True positives are low. This paper presents an automatic deep learning method of Convolutional Neural Network (CNN) with Long Short Term Memory (LSTM) model using the dataset from Greenberg and Schonlau.
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An Automated Framework for Swift Lecture Evaluation Using Speech Recognition and NLPuses speech recognition and NLP tools to produce frequency graph of mostly used words, which can help to identify the topics need to be revised. An experiment was successfully conducted to test the framework among 3. year undergraduate students.
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