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Communications in Mathematics and Statistics 2022年第3期10卷 565-579页

作者： Zhigang Wang Jin Guo Inna N.Safonova Alexander N.Skiba School of Science Hainan UniversityHaikou 570228HainanPeople’s Republic of China Department of Applied Mathematics and Computer Science Belarusian State University220030 MinskBelarus Department of Mathematics and Technologies of Programming Francisk Skorina Gomel State University246019 GomelBelarus

Throughout this paper,all groups are finite and G always denotes a finite group;σis some partition of the set of all primes P.A group G is said to beσ-primary if G is aπ-group for someπ∈σ.Aπ-semiprojector of G[29]is a subgroup H of G such that HN/N is a maximalπ-subgroup of G/N for all normal subgroups N of ***П⊆σ.Then we say thatχ={X_(1),...,X_(t)}is aП-covering subgroup system for a subgroup H in G if all members of the setχareσ-primary subgroups of G and for eachπ∈Пwithπ∩π(H)≠φthere are an index i and aπ-semiprojector U of H such that U≤X_(i).We study the embedding properties of subgroups H of G under the hypothesis that G has aП-covering subgroup systemχsuch that H permutes with X^(x)for all X∈χand x∈*** well-known results are generalized.

关键词： Finite group σ-nilpotent group П-semiprojector П-covering subgroup system σ-subnormal subgroup

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Optimal Control in the Problem With Two Gas Fields

Optimal Control in the Problem With Two Gas Fields

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International Conference on Management of Large-Scale System Development (MLSD)

作者： Alexander Skiba Department of Mathematical Methods of Regional Programming Federal Research Center “Computer Science and Control” of RAS Moscow Russia

ISBN: (数字)9798350375718

ISBN: (纸本)9798350375725

We explore a continuous aggregated dynamic model for developing two gas fields. The new borehole commissioning rates are the control parameters. Changes in the average flow rate of producing boreholes and current natural gas production are proportional. It is necessary to solve the problem of maximizing discounted accumulated income for two gas fields. We analyze the optimal control problem with an unrestricted right end and a fixed time. The Pontryagin maximum principle is a main tool for solving the problem. The special optimal control mode is of particular interest. We highlight the critical aspects of all possible optimal controls.

关键词： Drilling Road transportation Limiting Optimal control Switches Production Trajectory Planning Large-scale systems Natural gas

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Evaluating Keyphrase Extraction Methods for Clustering Influenza-Related Scientific Papers 8

Evaluating Keyphrase Extraction Methods for Clustering Influ...

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8th International Iranian Conference on Signal Processing and Intelligent Systems, ICSPIS 2022

作者： Forghani, Majid Firstkov, Artyom Alyannezhadi, Mohammad. M. Forghani, Kazem Krasovskii Institute of Mathematics & Mechanics Mathematical Programming Lab. Yekaterinburg Russia University of Science and Technology of Mazandaran Department of Science Behshahr Iran Iran University of Science and Technology Computer Science Department Tehran Iran

ISBN: (纸本)9781665476232

The number of annual scientific publications is growing year by year, which has led to the accumulation and formation of large databases. This increases the complexity of the search for relevant articles. Modern search engines leverage keyphrases to improve the performance of search results. Keyphrases (or keywords) are a set of single or multi-word expressions which provide a very compact summary of contents and describe the overall topic of a document. Implementation of keyphrase extraction can be varied for specific-domain databases. This motivated us to evaluate these methods on a database of influenza scientific literature. In this work, we considered 9 well known methods for extracting keyphrases. Our preliminary results show txhat graph-based methods which employ topics outperform others using our database. We also determined that influenza-related papers can be grouped into three general topics: public health & medical care;molecular biology & immunology;and phylogenetic & epidemiological studies. © 2022 IEEE.

关键词： Database systems

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AbotalebNet: A Novel Deep Learning Architecture for Time Series Forecasting with Convolutional and LSTM Layers Enhanced by Multi-Head Attention 2

AbotalebNet: A Novel Deep Learning Architecture for Time Ser...

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2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Abotaleb, Mostafa Makarovskikh, Tatiana Mijwil, Maad M. Bala, Indu Hiran, Kamal Kant Doshi, Ruchi South Ural State University Dep. of System Programming Chelyabinsk454080 Russia Baghdad College of Economic Sciences University Computer Techniques Engineering Department Baghdad Iraq Lovely Professional University Electrical and Electronics Engineering Punjab India Sir Padampat Singhania University Dep. of Computer Science Udaipur India Universidad Azteca Dep. of Computer Science and Engineering Chalco Mexico

ISBN: (纸本)9798350384277

This paper introduces AbotalebNet, a novel deep learning architecture optimized for time series forecasting, with a particular focus on the complexities of COVID-19 data. AbotalebNet's architecture is mathematically represented as:\begin{equation*}\hat Y = {\text{Attention}}(\operatorname{LSTM} ({\text{CNN}}(X)))\tag{1}\end{equation*}Here, X represents the input time series data, and Ŷ is the forecasted output. AbotalebNet integrates the feature extraction capabilities of Convolutional Neural Networks (CNNs) with the sequential data processing power of Long Short-Term Memory (LSTM) networks, further enhanced by a Multi-Head Attention *** address overfitting, a key challenge in deep learning, the model incorporates regularization strategies, dropout mechanisms, and batch normalization:\begin{equation*}\mathop {\min }\limits_\Theta ( Loss (X,\hat Y;\Theta ) + \lambda R(\Theta ))\tag{2}\end{equation*}In this equation, Θ denotes the model parameters, R(Θ) represents regularization terms, and λ is the regularization coefficient. These additions aid in preventing the model from overfitting to the training data, ensuring robust performance on unseen *** evaluation on COVID-19 time series data demonstrates AbotalebNet's enhanced predictive accuracy over traditional models, solidifying its potential for advanced non-linear time series analysis. © 2024 IEEE.

关键词： Convolutional neural networks

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Using LSTM as Intelligent Machine Learning Method to Forecast the Annual Average Relative Humidity: A Case Study for Konya, Turkiye

Using LSTM as Intelligent Machine Learning Method to Forecas...

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Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference

作者： Mayanja, Abubakar Eryürük, Şule Eryürük, Kağan Graduate School in Science Department of Computer Engineering Selcuk University Konya Turkey Vocational School of Commerce and Industry Department of Computer Programming KTO Karatay University Konya Turkey Department of Industrial Engineering KTO Karatay University Konya Turkey Department of Civil Engineering Necmettin Erbakan University Konya Turkey

ISBN: (纸本)9783031397769

Nowadays, one of the most demanding areas of Artificial Intelligence application is to forecast the weather condition as rapid and accurate as possible. The ratio of air vapor pressure to saturation vapor pressure is defined as relative humidity which is represented by a percentage of how much moisture the atmosphere can hold at the same temperature and pressure. The relative humidity has a significant impact on climate change and global warming which have had a negative impact on agriculture, economy, food security, and public health. In addition, accurate weather information and humidity forecasts are frequently required to warn of natural disasters result from unexpected changes in climatic conditions such as relative humidity. Therefore, recent decades have seen a rise in interest in this field of study. The aim of this study is to use Long Short-Term Memory (LSTM) models to forecast the annual relative humidity in Konya, Turkey between 1931 and 2010 by utilizing the annual average amounts of rain, sunlight, wind speed, and temperature. This paper represents a novel approach to predict annual relative humidity in Konya, which has not been previously explored in this location and between the given dates. As a result, the findings were able to forecast the monthly average humidity for next five years in advance with a mean square error of 0.1705% within 150 episodes. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Long short-term memory

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Metasystems in the Strategic Management of the Region

Metasystems in the Strategic Management of the Region

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International Conference on Management of Large-Scale System Development (MLSD)

作者： Alexander Solomatin Department of Mathematical Methods of Regional Programming Federal Research Center “Computer Science and Control” of RAS Moscow Russia

ISBN: (数字)9798350375718

ISBN: (纸本)9798350375725

Instead of the traditional “system-environment” pair for objects of the regional economy, it is proposed to consider metasystems - these objects together with all interacting objects of the microenvironment. Each object is considered as a point in the multidimensional space of characteristics. Objects are visualized to reflect their development and interaction with other objects.

关键词： Visualization Reflection Large-scale systems

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Optimistic Versioning for Conflict-tolerant Collaborative Blended Modeling 10

Optimistic Versioning for Conflict-tolerant Collaborative Bl...

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STAF 2022 Workshop: 10th International Workshop on Bidirectional Transformations, BX 2022, 2nd International Workshop on Foundations and Practice of Visual Modeling, FPVM 2022 and 2nd International Workshop on MDE for Smart IoT Systems, MeSS 2022

作者： Exelmans, Joeri Pietron, Jakob Raschke, Alexander Vangheluwe, Hans Tichy, Matthias Department of Computer Science University of Antwerp - Flanders Make Antwerp Belgium Institute of Software Engineering and Programming Languages Ulm University Ulm Germany

Optimistic versioning is a key component in supporting collaborative workflows. Text-based versioning has been widely adopted for versioning code, but in model-driven engineering, dealing with visual concrete syntaxes, new methods are required. In the case of blended modeling, a mixture of both textual and visual syntaxes, concurrently editable and synchronizable, introduces additional challenges. We propose a type of operation-based versioning to record not only user edits, but also bi-directional change propagations between concrete and abstract syntax. This way we can support blended modeling with layout continuity, and flexible handling of missing information (e. g., layout information) when rendering changes from abstract to concrete syntax. In addition, the proposed versioning approach enables collaborative conflict resolution by allowing partial conflict resolution, thus deferring a final resolution. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Abstracting

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Data Poisoning: Issues, Challenges, and Needs 7

Data Poisoning: Issues, Challenges, and Needs

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7th IET Smart Cities Symposium, SCS 2023

作者： Aljanabi, Mohammad Omran, Alaa Hamza Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Mohammed, Sahar Yousif Ibrahim, Abdelhameed Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq 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 Science Department Computer Science &Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence. © The Institution of Engineering & Technology 2023.

关键词： Machine learning

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Sports programming as a Tool for Regional Development of the Digital Industry and Higher Education 4

Sports Programming as a Tool for Regional Development of the...

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4th International Conference on Technology Enhanced Learning in Higher Education, TELE 2024

作者： Galkin, Alexander Miroshnikov, Artem Sapronov, Daniil Skarzhinskaya, Elena Lipetsk State Technical University Faculty of Automation and Computer Science Lipetsk Russia Lipetsk State Technical University Department of Applied Mathematics Lipetsk Russia The Russian Federation of Sports Programming Lipetsk branch Lipetsk Russia Moscow Financial and Industrial University 'Synergy' Department of Cybersport Moscow Russia

ISBN: (纸本)9798350353532

The article presents the history of the development of sports programming as a sport in Russia. The main stages of the formation of the legislative basis for this sport are given. The rationale and description of the process of training athletes in higher education institutions are given - possible traj ectories in the disciplines of 'algorithmic programming' and 'product programming', the influence of the development of sports programming on improving the quality of IT education. As an example, the organization of training students in the discipline of 'algorithmic programming' at the Lipetsk State Technical University is given. The activities of the Lipetsk regional branch of the All- Russian Sports Federation to popularize this sport including among students are also described. © 2024 IEEE.

关键词： Students

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Direct and Inverse Optimization Problems in a Gas Deposit Model 15

Direct and Inverse Optimization Problems in a Gas Deposit Mo...

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15th International Conference Management of Large-Scale System Development, MLSD 2022

作者： Skiba, Alexander Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Design Methods for Developing Systems Department of Mathematical Methods of Regional Programming Moscow Russia

ISBN: (数字)9781665497015

ISBN: (纸本)9781665497015

A continuous dynamic model for the development of a gas field is studied. Two mathematical problems are posed, solved and analyzed. In the direct problem, we are looking for the maximum accumulated profit on a set of temporary functions of a certain type. In the inverse optimization problem, we define the entire set of planning horizons. We subject the assigned tasks to a comprehensive analysis. © 2022 IEEE.

关键词： Profitability

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