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Titlebook: Smartphone Instrumentations for Public Health Safety; Abbas Jamalipour,Md Arafat Hossain Book 2019 Springer Nature Switzerland AG 2019 sma

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发表于 2025-3-21 19:37:23 | 显示全部楼层 |阅读模式
书目名称Smartphone Instrumentations for Public Health Safety
编辑Abbas Jamalipour,Md Arafat Hossain
视频videohttp://file.papertrans.cn/870/869117/869117.mp4
概述Provides a concise and unique look at unconventional applications of smartphone and extraordinary lessons that can be done with them.Offers a research-based design and fabrication guide for smartphone
丛书名称Wireless Networks
图书封面Titlebook: Smartphone Instrumentations for Public Health Safety;  Abbas Jamalipour,Md Arafat Hossain Book 2019 Springer Nature Switzerland AG 2019 sma
描述.A significant and convenient approach to detection and analysis of biological, environmental and agricultural items is the harnessing of features in widely available smartphones to create field-deployable scientific instruments, allowing measurements to be made onsite and in real-time. This book will cover a number of self-contained smartphone instruments with the particular focus on spectroscopic-based measurements. Measurement and analysis on precision of such low-cost instrumentations are provided to compare with more expensive commercial equipment...This book also discusses some limitations, possible recommendations and scopes for further instrumentations using smartphones and other smart devices. Particularly, the opportunity to integrate the devices into the global Internet-of-Things (IoT) platform will be discussed.    .Researchers and instrumentation designers in optical and photonic sensing, smart and IoT-based sensing, biological and environmental analysts, agricultural, and food quality researchers (and public health authorities) will find this book useful as reference. Students in science and engineering disciplines for teaching and educational purposes will also find
出版日期Book 2019
关键词smartphones; Internet of Things; IoT; fluorimeter; spectrometer; pH measurement; colorimetry; microscopy; sp
版次1
doihttps://doi.org/10.1007/978-3-030-02095-8
isbn_ebook978-3-030-02095-8Series ISSN 2366-1186 Series E-ISSN 2366-1445
issn_series 2366-1186
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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发表于 2025-3-21 20:49:01 | 显示全部楼层
Abbas Jamalipour,Md Arafat Hossain wide variety of sensing hardware. On the other hand there are urgent growing and pressing demands from many application domains such as: in-home health monitoring especially for the elderly, smart cities, safe driving by monitoring and predicting driver’s behavior, healthcare applications, entertai
发表于 2025-3-22 00:50:25 | 显示全部楼层
Abbas Jamalipour,Md Arafat Hossain wide variety of sensing hardware. On the other hand there are urgent growing and pressing demands from many application domains such as: in-home health monitoring especially for the elderly, smart cities, safe driving by monitoring and predicting driver’s behavior, healthcare applications, entertai
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发表于 2025-3-22 15:09:26 | 显示全部楼层
Abbas Jamalipour,Md Arafat Hossaintial or full system control to the attackers. To overcome these issues, researchers have applied machine learning techniques for malicious URL detection. However, these techniques fall to identify distinguishable generic features that are able to define the maliciousness of a given domain. Generally
发表于 2025-3-22 19:04:42 | 显示全部楼层
cognitive artificial intelligence solutions that complement and extend machine learning. In this book.,. author Rohit Kumar explores the challenges when these concepts intersect in IT systems by presenting detailed descriptions and business scenarios. He starts with the basics of how artificial int
发表于 2025-3-22 23:14:48 | 显示全部楼层
features in the continuously evolving distribution of malicious URLs. So, the suggested model adapts a bio-inspired feature selection technique to choose an optimal feature set in order to reduce the cost and running time of a given system, as well as achieving an acceptably high recognition rate. M
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发表于 2025-3-23 07:50:49 | 显示全部楼层
Abbas Jamalipour,Md Arafat Hossaino model and classify ADL activities. To the best of our knowledge, almost all techniques for activity recognition are based on methods from the machine learning literature (particularly, supervised learning). Our comparative study widens the scope of techniques that can be used for automatic analysi
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