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Condition attributes, properties of decision rules, and discretisation: Analysis of relations and dependencies

Procedia computer Science 2021年 192卷 3922-3931页

作者： Beata Zielosko Urszula Stańczyk University of Silesia in Katowice Będzińska 39 41-200 Sosnowiec Poland Department of Graphics Computer Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A 44-100 Gliwice Poland

When mining of input data is focused on rule induction, knowledge, discovered in exploration of existing patterns, is stored in combinations of certain conditions on attributes included in rule premises, leading to specific decisions. Through their properties, such as lengths, supports, cardinalities of rule sets, inferred rules characterise relations detected among variables. The paper presents research dedicated to analysis of these dependencies, considered in the context of various discretisation methods applied to the input data from stylometric domain. For induction of decision rules from data, Classical Rough Set Approach was employed. Next, based on rule properties, several factors were proposed and evaluated, reflecting characteristics of available condition attributes. They allowed to observe how variables and rule sets changed depending on applied discretisation algorithms.

关键词： Discretisation Decision rule Rule length Support Attribute Rough Sets

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Application of genetic algorithms in the multiplayer video game “hram light” for personal qualities training

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AIP Conference Proceedings 2023年第1期2939卷

作者： Teodor Ukov Georgi Tsochev Technical University of Sofia Faculty of Computer Systems and Control 8 Kl. Ohridski str. 1000 Sofia Bulgaria

The inspiration that has been drawn from the newly discovered natural phenomena, finds substantial application in computer science. Genetic algorithms are a metaheuristic gear for finding solutions of problems that the explorer does not even understand and the results are beneficial to many industrial spheres. However, can that inspiration be applied in a computer game trainer for personal qualities development and this way closing the cycle: from nature to machine and from it to the inner nature of a person? This would require research on the inner occurrences or more precisely the semi-conscious reactions of the player, derived as a response from their insight. Although the fact that the various characters of people are a challenge for the development, maintaining more “individuals” - behaviour of bots generated with genetic algorithms would help in the searching of a useful opponent for the improving player. As much as challenging the goal of “teaching a machine to be a teacher for a person” may seem, it should definitely be set because once accomplished it would bring, not only discovery of the benefits of video games, but would also lead us to the inspiring question: “How much more can a modern software be useful to people and nature?”

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Artificial intelligence methods suitable for lateral movement detection

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AIP Conference Proceedings 2023年第1期2939卷

作者： Alexander Rusev Maksim Sharabov Georgi Tsochev Roumen Trifonov Technical University of Sofia Faculty of Computer Systems and Control 8 Kl. Ohridski str. 1000 Sofia Bulgaria

The COVID-19 pandemic forced many companies to send their employees to work from home, which led to a significant increase in cyberattacks over RDP. Remote Desktop Protocol (RDP) is a Microsoft protocol that allows administrators to access desktop computers remotely. As it gives the user full control over the device, it is a valuable entry point for adversaries. Every cyberattack goes through several stages before its termination. Lateral Movement is one of those stages that is of particular importance. This article presents the first step of a project for Designing a remote connection protection system based on artificial intelligence methods. The research reviews the problems in lateral movement detection. A literature review is conducted, outlining techniques for automatic detection of malicious lateral movements. There is a discussion about the possibility of using artificial intelligence methods in lateral movement detection and the choice of an appropriate method.

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Distributed design of deterministic discrete-time privacy preserving average consensus for multi-agent systems through network augmentation

arXiv

引用

arXiv 2021年

作者： Ramos, Guilherme Pedro Aguiar, A. Kar, Soummya Pequito, Sérgio The Department of Electrical and Computer Engineering Faculty of Engineering University of Porto Portugal The Department of Electrical and Computer Engineering Carnegie Mellon University United States The Delft University of Technology The Delft Center for Systems and Control Netherlands

Average consensus protocols emerge with a central role in distributed systems and decision-making such as distributed information fusion, distributed optimization, distributed estimation, and control. A key advantage of these protocols is that agents exchange and reveal their state information only to their neighbors. Yet, it can raise privacy concerns in situations where the agents' states contain sensitive information. In this paper, we propose a novel (noiseless) privacy preserving distributed algorithms for multi-agent systems to reach an average consensus. The main idea of the algorithms is that each agent runs a (small) network with a crafted structure and dynamics to form a network of networks (i.e., the connection between the newly created networks and their interconnections respecting the initial network connections). Together with a re-weighting of the dynamic parameters dictating the inter-agent dynamics and the initial states, we show that it is possible to ensure that the value of each node converges to the consensus value of the original network. Furthermore, we show that, under mild assumptions, it is possible to craft the dynamics such that the design can be achieved in a distributed fashion. Finally, we illustrate the proposed algorithm with examples. Copyright © 2021, The Authors. All rights reserved.

关键词： Multi agent systems

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Numerical approach to design of low frequency magnetic field irradiation system for lab on chip experiments

Numerical approach to design of low frequency magnetic field...

引用

ELEKTRO

作者： Roman Radil Marek Bajtoš Lucia Č arnecká Klaudia Hargaš ová Patrik Kamencay Department of Electromagnetic and Biomedical Engineering University of Zilina Zilina Slovakia Department of Systems Biology and Engineering Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Dept. of Electromagnetic and Biomedical Engineering Organization University of Zilina Zilina Slovakia

ISBN: (数字)9781665467261

ISBN: (纸本)9781665467278

The article is focused on design of specific electromagnetic coil system using numerical modelling and simulation methods. The proposed solution would be capable of delivering magnetic field of desired strength/ flux density and homogeneity within the specific area to affect the cultivation process of single cells in lab on chip experiments.

关键词： Radiation effects Numerical models Magnetic fields Electromagnetics

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Assessing quality of decision reducts 24

Assessing quality of decision reducts

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24th KES International Conference on Knowledge-Based and Intelligent Information and Engineering systems, KES 2020

作者： Stanczyk, Urszula Zielosko, Beata Department of Graphics Computer Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland Institute of Computer Science University of Silesia in Katowice Bedzinska 39 Sosnowiec41-200 Poland

The paper presents research focused on decision reducts, a feature reduction mechanism inherent to rough sets theory. As a reduct enables to protect the discriminative properties of attributes with respect to described concepts, from the point of data representation, a reduct length is considered to be the most important measure of its quality. However, such approach is insufficient while taking into account the performance of a reduct-based rule classifier applied to test samples. When many reducts of the same length are available, they can lead to vastly different predictions. The paper provides a description for the proposed procedure for iterative reduct generation, which results in decrease of diversity in the observed levels of accuracy, supporting reduct selection. The procedure was applied for binary classification with balanced classes, for the stylometric task of authorship attribution. © 2020 The Authors. Published by Elsevier B.V.

关键词： Rough set theory

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Analyzing Hepatotoxicity of Marine Venoms Using Artificial Intelligence: An Ecoinformatics Perspective

Analyzing Hepatotoxicity of Marine Venoms Using Artificial I...

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Information Technology (ACIT)

作者： Heider Wahsheh Mohammad Wahsha Tariq Al-Najjar Maroof Khalaf Haya Al-Tarawneh Department of Information Systems College of Computer Science and Information Technology King Faisal University Al-Ahsa Saudi Arabia Marine Science Station The University of Jordan Aqaba Branch Aqaba Jordan Faculty of Basic and Marine Sciences The University of Jordan Aqaba Branch Aqaba Jordan Control Health Division Aqaba Special Economic Zone Authority Aqaba Jordan

Marine toxins present considerable challenges to public health due to their intricate biochemical profiles that complicate effectual analysis. In addressing this, our study utilizes a pioneering Ecoinformatics method, employing artificial intelligence to meticulously examine the hepatotoxic effects of stonefish venom on murine models. The convergence of biochemical assays, histopathological scrutiny, and cutting-edge machine learning algorithms is strategically designed to unravel the complex modalities of venom-induced toxicity. Our findings offer unprecedented insight into the hepatotoxic dynamics of marine venoms, underscoring the utility of AI in advancing marine toxin research. This multifaceted research not only deepens our comprehension of venom pathology but also forges a pathway toward enhanced antivenom solutions, thereby reinforcing public health measures in marine and coastal ecosystems.

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Distributed Constrained Online Nonconvex Optimization with Compressed Communication

arXiv

引用

arXiv 2025年

作者： Zhang, Kunpeng Xu, Lei Yi, Xinlei Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai201210 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents. For a time-varying graph, we propose a distributed online primal–dual algorithm with compressed communication to efficiently utilize communication resources. We show that the proposed algorithm establishes an O(T max{1−θ1,θ1}) network regret bound and an O(T 1−θ1/2) network cumulative constraint violation bound, where T is the number of iterations and θ1 ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints at all iterations), the network cumulative constraint violation bound is reduced to O(T 1−θ1). These bounds are comparable to the state-of-the-art results established by existing distributed online algorithms with perfect communication for distributed online convex optimization with (time-varying) inequality constraints. Finally, a simulation example is presented to validate the theoretical results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

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Integrated Simulation of Process of Steel Casting on the Continuous Steel Casting Unit 2

Integrated Simulation of Process of Steel Casting on the Con...

引用

2nd International Conference on control systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2020

作者： Galkin, Alexander Pimenov, Vladimer Saraev, Pavel Tyrin, Dmitry Lipetsk State Technical University Faculty of Automation and Computer Science Lipetsk Russia Novolipetsk Steel Corporation Lipetsk Russia Lipetsk State Technical University Department of Automated Control Systems Lipetsk Russia

ISBN: (纸本)9781728188409

Studying technological processes on real production equipment is associated with a large costs of resources: financial, time, etc. Therefore, various types of modeling are actively used to analyze and optimize these processes. With the development of digital technologies, it is possible to collect data about the process directly during the production. This data can be used both for direct control of the process, and for building (adjusting) the model of the process, which allows to get a "digital twin"repeating both the main properties of the modeled object and its current state. Many complex manufacturing processes involve a set of different interconnected models. In this case, the "digital twin"should contain information about the object characteristics, individual models of its functioning, the connections between these models, and the current state. These processes include many stages of metallurgical production. The paper considers complex modeling of the casting process in continuous steel casting unit. The set of models includes a model of the thermal state of the ingot during casting, a model of the stress-strain state, a model of the melt hydrodynamics, structural and concentration models of the ingot. Mathematical models of thermal and stress-strain states and the connections between them are presented. Examples of temperature fields and deformations calculation during the process of casting are given. © 2020 IEEE.

关键词： Steel ingots

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A scalable distributed dynamical systems approach to compute the strongly connected components and diameter of networks

arXiv

引用

arXiv 2021年

作者： Reed, Emily A. Ramos, Guilherme Bogdan, Paul Pequito, Sérgio Ming Hsieh Electrical and Computer Engineering Department University of Southern California United States Department of Electrical and Computer Engineering Faculty of Engineering University of Porto Portugal Delft University of Technology Delft Center for Systems and Control

Finding strongly connected components (SCCs) and the diameter of a directed network play a key role in a variety of discrete optimization problems, and subsequently, machine learning and control theory problems. On the one hand, SCCs are used in solving the 2-satisfiability problem, which has applications in clustering, scheduling, and visualization. On the other hand, the diameter has applications in network learning and discovery problems enabling efficient internet routing and searches, as well as identifying faults in the power grid. In this paper, we leverage consensus-based principles to find the SCCs in a scalable and distributed fashion with a computational complexity of O (Ddmax in-degree ) , where D is the (finite) diameter of the network and dmax in-degree is the maximum in-degree of the network. Additionally, we prove that our algorithm terminates in D + 1 iterations, which allows us to retrieve the diameter of the network. We illustrate the performance of our algorithm on several random networks, including Erdos-Rényi, Barabási- Albert, and Watts-Strogatz networks. Copyright © 2021, The Authors. All rights reserved.

关键词： Optimization

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