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IEEE Ukraine Conference on Electrical and Computer Engineering

作者： Oleksandr I. Marchenko Oleksii O. Marchenko Department of System Programming and Specialized Computer Systems National Technical University of Ukraine "Igor Sikorsky Kyiv polytechnic institute"

ISBN: (纸本)9781509030071

The paper, basing on analysis of the Monte-Carlo Tree Search (MCTS) method and specific features of its behavior for various cases of usage, proposes a new variant of the method, which was called as Monte-Carlo Tree Search with Tree Shape Control (MCTS-TSC) and which uses original Depth-Width Criteria (DWCs) for both tree shape estimation and control during search and for estimation and selection of potentially better options for search continuation. Proposed Tree Shape Control (TSC) technique can be used with some other tuning, pruning, and learning techniques. Besides, it can provide better scheduling of MCTS parallelization.

关键词： Monte-Carlo Tree Search (MCTS) Game tree MCTS improvement techniques Exploitation-exploration dilemma Tree shape control MCTS parallelization

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Forecasting nonlinear nonstationary processes in machine learning task 3

Forecasting nonlinear nonstationary processes in machine lea...

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3rd IEEE International Conference on Data Stream Mining and Processing, DSMP 2020

作者： Bidyuk, Peter Gozhyj, Aleksandr Kalinina, Irina Vysotska, Victoria Vasilev, Mikhail Malets, Romanna Department of Mathematical Methods of System Analysis National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Petro Mohyla Black Sea National University Department of Intelligent Information Systems Nikolaev Ukraine National University Lvivska Politechnika Department of Information Systems and Networks Lviv Ukraine Ivan Franko Lviv National University Programming Department Lviv Ukraine

ISBN: (纸本)9781728132143

The article discusses the features of the solving the forecasting problems using machine learning techniques. The issues of accounting and correctly processing non-linear non-stationary processes in the problems of modeling and forecasting time series in various areas are considered. The analysis of stages and methods for solving machine learning problems. As an example, consider the problem of predicting currency pairs based on historical data. A comparative analysis of the normalization methods in data clustering is given. For the six currency pairs a short-term forecast is proposed. © 2020 IEEE.

关键词： Machine learning

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Image noise reduction by denoising autoencoder

Image noise reduction by denoising autoencoder

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IEEE International Conference on Dependable systems, Services and Technologies (DESSERT)

作者： Lev Yasenko Yaroslav Klyatchenko Oksana Tarasenko-Klyatchenko Department of System Programming and Specialized Computer Systems National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" Kyiv Ukraine

ISBN: (数字)9781728199573

ISBN: (纸本)9781728199580

Neural networks are used in many tasks today. One of them is the images processing. Autoencoder is very popular neural networks for such problems. Denoising autoencoder is an important autoencoder because some tasks we need a preprocessed image to get less noisy result. This research describes ways to analyze noisy images produced by a physically-based render engine and how to reduce that noise. The results showed that the algorithms are logarithmic.

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Towards safe data flow processing by integration of design by contract in deterministic UML activities

Towards safe data flow processing by integration of design b...

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XXII International Symposium on Information, Communication and Automation Technologies, ICAT

作者： Zamira Daw Marcus Vetter Josef Boercsoek Institute of Embedded Systems Hochschule Mannheim-University of Applied Sciences Mannheim Germany Department of Computer Architecture and System Programming University of Kassel Kassel Germany

Data flow processing is a common task of embedded systems which is usually modeled as a pipeline. Errors in a block of this pipeline can be propagated through it thus leading to unexpected and erroneous behaviors. For safety related applications, this pipeline has to be able to identify and react to failures. The DMOSES model-driven development method uses deterministic UML activities to describe and implement data flow processing. This method ensures deterministic behavior of concurrent processing. Design by Contract defines formal, precise and verifiable interfaces for software components. We propose a development method for safe data flow processing based on the integration of this concept in deterministic UML activities. This integration allows the identification of errors by detection of contracts violation. This paper presents an extension of the DMOSES tool for contracts verification at the model level and their monitoring at runtime.

关键词： Unified modeling language Contracts Monitoring Embedded systems Object oriented modeling Safety Pins

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Sensing Metric-Based Hybrid Underlay/Overlay Transmission Framework for CR-IoT Networks for Smart City Applications 7

Sensing Metric-Based Hybrid Underlay/Overlay Transmission Fr...

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7th IET Smart Cities Symposium, SCS 2023

作者： Bala, Indu Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Ibrahim, Abdelhameed School of Electrical and Electronics Engineering Lovely Professional University Punjab India Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

With the increasing number of IoT devices, there is a growing need for bandwidth to support their communication. Unfortunately, there is a shortage of available bandwidth due to preallocated bands for various services. To address this issue, Cognitive Internet of Things (CR-IoT) enables devices to optimize their efficiency and enhance their communication capabilities by intelligently accessing available bandwidth. This is achieved through the use of soft sensing metrics, where devices continuously monitor the RF environment and transmit data opportunistically in overlay mode if a free channel is detected, or in underlay mode if not. In this paper, a soft sensing metric based hybrid transmission framework is proposed for CR-IoT devices to meet the data rate requirement for the smart city applications. The efficacy of this approach is demonstrated through simulation results. © The Institution of Engineering & Technology 2023.

关键词： Smart city

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Al-Biruni Earth Radius Optimization for COVID-19 Forecasting

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Computer systems Science & Engineering 2023年第7期46卷 883-896页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Tatiana Makarovskikh Amal H.Alharbi Doaa Sami Khafaga Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of System Programming South Ural State University454080ChelyabinskRussia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Several instances of pneumonia with no clear etiology were recorded in Wuhan,China,on December 31,*** world health organization(WHO)called it COVID-19 that stands for“Coronavirus Disease 2019,”which is the second version of the previously known severe acute respiratory syndrome(SARS)Coronavirus and identified in short as(SARSCoV-2).There have been regular restrictions to avoid the infection spread in all countries,including Saudi *** prediction of new cases of infections is crucial for authorities to get ready for early handling of the virus ***:Analysis and forecasting of epidemic patterns in new SARSCoV-2 positive patients are presented in this research using metaheuristic optimization and long short-term memory(LSTM).The optimization method employed for optimizing the parameters of LSTM is Al-Biruni Earth Radius(BER)***:To evaluate the effectiveness of the proposed methodology,a dataset is collected based on the recorded cases in Saudi Arabia between March 7^(th),2020 and July 13^(th),*** addition,six regression models were included in the conducted experiments to show the effectiveness and superiority of the proposed *** achieved results show that the proposed approach could reduce the mean square error(MSE),mean absolute error(MAE),and R^(2)by 5.92%,3.66%,and 39.44%,respectively,when compared with the six base *** the other hand,a statistical analysis is performed to measure the significance of the proposed ***:The achieved results confirm the effectiveness,superiority,and significance of the proposed approach in predicting the infection cases of COVID-19.

关键词： COVID-19 prediction meta-heuristic optimization LSTM Al-Biruni earth radius algorithm

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A Case Study of Valency Patterns for Motion Verbs in Vakh Khanty by Means of Lingvodoc

A Case Study of Valency Patterns for Motion Verbs in Vakh Kh...

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Ivannikov ISPRAS Open Conference (ISPRAS)

作者： Irina Novitskaya Victoria Vorobeva Department of Foreign Languages National Research Tomsk State University Tomsk Russian Federation Information Systems Department Ivannikov Institute for System Programming of the RAS TPU Moscow Tomsk Russian Federation

The article presents a study of the syntactic compatibility of verbs of motion in the Vakh dialect of the Khanty language. The study was conducted with the help of the tools of the platform for documentation of the Uralic languages Lingvodoc. The purpose of the article is to describe patterns of syntactic valency that Vakh Khanty verbs of motion have.

关键词： Documentation Syntactics

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Optimizing Machine Learning Algorithms to Enhance Blood Donation for Liver Patients: A Case Study 7

Optimizing Machine Learning Algorithms to Enhance Blood Dona...

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7th IET Smart Cities Symposium, SCS 2023

作者： Mijwil, Maad M. El-Kenawy, El-Sayed M. Bala, Indu Aljanabi, Mohammad Abotaleb, Mostafa Ibrahim, Abdelhameed Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt School of Electrical and Electronics Engineering Lovely Professional University Punjab India Department of Computer Aliraqia University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Blood is vital for transporting oxygen, nutrients, and hormones to all body parts as it circulates through arteries and veins. It removes carbon dioxide, regulates body temperature, and maintains the body's immune system. Individuals constantly need blood and its derivatives to save their lives and improve their health through medical treatments and surgical operations. Liver diseases are one of the diseases that affects the health of individuals and requires blood to continue living. These diseases cause significant damage to people's health, and early diagnosis plays a crucial role in saving lives. In this paper, machine learning algorithms (support vector machine and random forest) are involved in detecting liver diseases and determining whether donors are suitable to donate blood from blood values. This paper is applied research that found that the performance measures of the random forest algorithm achieved excellent performance in identifying suitable people to donate blood. © The Institution of Engineering & Technology 2023.

关键词： Support vector machines

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Multi-Timescale Trading Strategy for Renewable Power to Ammonia Virtual Power Plant in the Electricity, Hydrogen, and Ammonia Markets

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2023年第4期1卷 322-335页

作者： Wu, Sirui Lin, Jin Li, Jiarong Liu, Feng Song, Yonghua Xu, Yanhui Cheng, Xiang Yu, Zhipeng Tsinghua University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Beijing100087 China Tsinghua University Sichuan Energy Internet Research Institute Chengdu610213 China University of Macau Department of Electrical and Computer Engineering Macau999078 China Tsinghua University Department of Electrical Engineering Beijing100087 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China

Renewablepower to ammonia (RePtA) is a prominent zero-carbon pathway for decarbonization. Due to the imbalance between renewables and production energy demand, the RePtA system relies on electricity exchange with the power grid. Participating in the electricity market as a virtual power plant (VPP) may help to reduce energy costs. However, the power profile of local photovoltaics and wind turbines is similar to those in the market, resulting in rising energy costs under the conventional strategy. Hence, we develop a multi-timescale trading strategy for the RePtA VPP in the electricity, hydrogen, and ammonia markets. By utilizing the hydrogen and ammonia buffer systems, the RePtA VPP can optimally coordinate production planning. Moreover, we find it possible to describe the trading of electricity, ammonia, and hydrogen in a unified timeframe. The two-stage robust optimization model of the electricity market is extended to multiple markets and solved by the column and constraint generation (CC&G) algorithm. The case is derived from an actual project in the Inner Mongolia Autonomous Region. Sensitivity analysis demonstrates the economic advantages of the RePtA VPP joining multiple markets over the conventional strategy and reveals the necessity of the hydrogen and ammonia buffer and reactor flexibility. © 2023 IEEE.

关键词： Ammonia

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Control and Stability of Large-scale Power system with Highly Distributed Renewable Energy Generation:Viewpoints from Six Aspects

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CSEE Journal of Power and Energy systems 2023年第1期9卷 8-14页

作者： Qing-Hua Wu Anjan Bose Chanan Singh Joe H.Chow Gang Mu Yuanzhang Sun Zhaoxi Liu Zhigang Li Yang Liu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China School of Electrical Engineering&Computer Science Washington State UniversityPullmanWA 99164USA Department of Electrical and Computer Engineering Texas A&M UniversityCollege StationTX 77843USA Department of Electrical Computer and Systems EngineeringRensselaer Polytechnic Institute(RPI)TroyNYUSA Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin 132012China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

Power systems are moving toward a low-carbon or carbon-neutral future where high penetration of renewables is *** conventional fossil-fueled synchronous generators in the transmission network being replaced by renewable energy generation which is highly distributed across the entire grid,new challenges are emerging to the control and stability of large-scale power *** analysis and control methods are needed for power systems to cope with the ongoing *** the CSEE JPES forum,six leading experts were invited to deliver keynote speeches,and the participating researchers and professionals had extensive exchanges and discussions on the control and stability of power ***,potential changes and challenges of power systems with high penetration of renewable energy generation were introduced and explained,and advanced control methods were proposed and analyzed for the transient stability enhancement of power grids.

关键词： Distributed energy resources high converter penetration power system control renewable energy generation stability control transient stability

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