Titlebook: Intelligent Systems and Networks; Selected Articles fr Duc-Tan Tran,Gwanggil Jeon,Thu-Do Xuan Conference proceedings 2021 The Editor(s) (if

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Lecture Notes in Networks and Systemshttp://image.papertrans.cn/i/image/470055.jpg

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Designing a Remote Monitoring System for Lakes Based on Internet of Things,to collect relevant data from the environment. This paper proposes a system that allows remote data collection to support environmental parameters monitoring and provide warnings about water levels for lakes based on the IoT platform. The research results show that our proposed system works well wit

Adornment

The Role of Blockchain Security in the Internet of Things,dger to stockpile various transactions within the nodes of IoT. A Blockchain comprises of sequences of blocks with each component linked to the previous block sequences. Individual blocks contain previous block hash, cryptography hash code, and stored sets of knowledge. The transactions, which happe

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指耕作

An Enhanced Model for DGA Botnet Detection Using Supervised Machine Learning,ication. A number of approaches using statistics and machine learning to detect DGA botnets based on classifying botnet and legitimate domain-names have been proposed. This paper extends the machine learning-based detection model proposed by [.] by adding new classification features in order to impr

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guardianship

Designing Bidding Systems in Supply Chain Management Using Blockchain Technology,upply chain lies not only in the optimization of conventional administration costs, but also in its legality, transparency and trust. The article describes how to implement a bidding system. This bidding system is used to select carriers for e-commerce sites. Blockchain’s smart contract with its tra

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Feature Selection Using Genetic Algorithm and Bayesian Hyper-parameter Optimization for LSTM in Shos are widely applied to solve this problem. Data used in forecasting are collected from advanced SCADA system, smart sensors and other related sources. Therefore, feature selection should be carefully optimized for machine learning models. In this study, we propose a forecasting model using long sho