Titlebook: Big Data Intelligence for Smart Applications; Youssef Baddi,Youssef Gahi,Loai Tawalbeh Book 2022 The Editor(s) (if applicable) and The Aut

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Introduction to Cardinal Arithmetices in human lives, the rise of adversarial attempts to manipulate those MLAs and influence their choices is not a surprise. The main goal of this paper is to present recent approaches, models and progresses in AMLs. Additionally, our goal is to focus on AML research trends and challenges.

Ondines-curse

https://doi.org/10.1007/978-1-4614-6283-5ibuted clustering, classification, and prediction. Different distributed DM (DDM) techniques, MASs, the advantages of MAS-based DDM, and various MAS-based DDM approaches proposed by researchers are reviewed in this study.

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Vldl379

Adversarial Machine Learning, Research Trends and Applications,es in human lives, the rise of adversarial attempts to manipulate those MLAs and influence their choices is not a surprise. The main goal of this paper is to present recent approaches, models and progresses in AMLs. Additionally, our goal is to focus on AML research trends and challenges.

Armory

Multi-agent Systems for Distributed Data Mining Techniques: An Overview,ibuted clustering, classification, and prediction. Different distributed DM (DDM) techniques, MASs, the advantages of MAS-based DDM, and various MAS-based DDM approaches proposed by researchers are reviewed in this study.

含沙射影

A Conceptual Analysis of IoT in Healthcare,ossible using Wireless Body Area Network (WBAN). This chapter proposes a machine learning model to discover hidden facts and to predict the future behavior of patients based on current health conditions. Further, a conceptual analysis is presented using a heart disease dataset.

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朦朧

Identification of Heavenly Bodies,at can prevent false identification of a mimicked walk or leg swing in sitting posture as a real walk activity, using conventional and convolutional deep learning algorithms. The system shows remarkable capability of identifying an actual walk from a mimicked walk activity using CNN 95% of the time.

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欺騙世家

A Low-Cost IMU-Based Wearable System for Precise Identification of Walk Activity Using Deep Convoluat can prevent false identification of a mimicked walk or leg swing in sitting posture as a real walk activity, using conventional and convolutional deep learning algorithms. The system shows remarkable capability of identifying an actual walk from a mimicked walk activity using CNN 95% of the time.