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5th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Antipina, Evgenia Mustafina, Svetlana Antipin, Andrey Ufa University of Science and Technology Department of Scientific Research Ufa Russia Ufa University of Science and Technology Faculty of Mathematics and Information Technologies Ufa Russia Sterlitamak Branch of Ufa University of Science and Technology Department of Applied Informatics and Programming Sterlitamak Russia

ISBN: (纸本)9798350309126

The paper formulates an algorithm for searching the optimal temperature regime of the catalytic process in an ideal mixing reactor. The problem of optimal control of the catalytic process is formulated in a general form. To find its numerical solution, an algorithm based on the method of differential evolution is described. The algorithm allows to obtain an approximate solution of the optimization problem in a time acceptable from the practical point of view. A computational experiment for the dimerization process of alphamethylstyrene is carried out. The optimal temperature profile for achieving the maximum yield of reaction products - linear dimers - is obtained. © 2023 IEEE.

关键词： Evolutionary algorithms

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Ensuring the reliability of remote online monitoring systems

Ensuring the reliability of remote online monitoring systems

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2022 International Conference on Information Science and Communications Technologies, ICISCT 2022

作者： Alexandr, Sergeev Mikhail, Sergeev Saint Petersburg State University of Aerospace Instrumentation Department of Computer Technology and Programming Saint Petersburg Russia

ISBN: (纸本)9781665472296

the issue of ensuring the reliability of the functioning of global systems of remote online monitoring of the condition of patients is considered. Remote monitoring is in demand when supervision the health status of disabled people with cardiovascular diseases, pregnant women and children. It is especially in demand in the context of a pandemic and the accompanying restrictions on movement. Monitoring is carried out 'transparently' for the patient, without involving him in the subtleties of the process of interaction with a medical institution, ensuring the preservation of his mobility due to the proposed concept of implementing a wearable online monitor device. The procedures of the online monitor initialization and distribution of functions in it are considered. Threats to the normal functioning of distributed systems with online monitors are presented, including existing problems of a general nature related mainly to global communications. Solutions are offered to ensure reliable operation of wearable devices as part of online monitors. © 2022 IEEE.

关键词： Reliability

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Pricing Policy with the Effect of Fairness Concern, Imprecise Greenness, and Prices in Imprecise Market for a Dual Channel

Pricing Policy with the Effect of Fairness Concern, Imprecis...

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International Conference on Nonlinear Applied Analysis and Optimization, ICNAAO-2021

作者： Ganguly, Sanchari Das, Pritha Maiti, Manoranjan Department of Mathematics Indian Institute of Engineering Science and Technology Shibpur WB Howrah711103 India Department of Applied Mathematics Oceanology and Computer Programming Vidyasagar University WB Midnapore721102 India

ISBN: (纸本)9789819905966

Fairness concern behavior, a well-known cognitive bias, refers to a person’s attitude of dissatisfaction for unequal pay-offs in someone’s favor. Against environmental pollution, many firms are focused on green manufacturing to maintain sustainable development. The adoption of online shopping by customers around the globe has altered the dynamics of competitiveness in the retail supply chain (SC). Considering the above facts, the effect of fairness concern on optimal prices and channel members’ profits in a two-level dual channel SC is investigated. Here, we consider an SC comprising a green manufacturer and a fair-minded retailer where the manufacturer produces and sells the green product through both offline and online channels to consumers. Due to uncertainty in the real world, the fuzziness is associated with market demand, price elasticity, and the coefficient of greenness. The fuzzy objectives and constraints are reduced to crisp ones using expectation and possibility measures, respectively. Both centralized and decentralized models (with and without cognitive bias) are formulated and solved by the Stackelberg game for the optimal prices and product greenness level. The models’ optimal solutions are analyzed and compared with the deterministic models numerically. The effects of the fairness concern coefficient on the optimal prices, product greenness level, and channel members’ profits are investigated. The sensitivity analyses are presented to study the effects of the fuzzy degree of customers’ sensitivity toward greenness on channel members’ profits. Retailer’s fairness is harmful to the manufacturer but beneficial for her own profit. Finally, some conclusions and managerial insights are presented. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Game theory

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An application of graph theory to the optimization of costs in trilateration networks

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manuscripta geodaetica 2024年第4期12卷 296-308页

作者： Kortesis, S. Dermanis, A. Faculty of Technology — General Department Division Computational Mathematics and Programming University of Thessaloniki Thessaloniki Greece Department of Geodesy and Surveying University of Thessaloniki Thessaloniki Greece

The problem of the minimization of the cost for a given trilateration network design by optimizing the planning and execution of fieldwork is studied with the help of graph theory tools. The case with one instrument and one reflector is shown to be a problem in graph theory which has some of the characteristics of the travelling salesman problem but is much more complicated. Since the determination of the optimal solution requires enormous computational time, a heuristic algorithm which leads to a sub-optimal solution is developed, along the lines of a similar heuristic algorithm for the much simpler travelling salesman problem. The algorithm is elaborated with the help of a computer program written for this purpose. Finally the problems where a) instrument and reflector have the same transportation cost, b) each distance is observed twice, c) instrument and reflector have a common means of transportation and d) observations extend over more than one day with returns to home-base, are shortly discussed in the light of graph theory.

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Educational Research Trends of the Use of Gaze Learning Data Through Topic Modeling and Scientometric Analysis 1st

Educational Research Trends of the Use of Gaze Learning D...

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1st International workshop on AI for Research, AI4Research 2024 and 4th International workshop on Democracy and AI, DemocrAI 2024, held in conjunction with 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024

作者： Lee, Jungmin Shin, Huigon Yoo, YoungJoon Choi, Jongwon Kim, Mi Song Department of Advanced Imaging GSAIM Chung-Ang University Seoul Korea Republic of Computer Programming and Analysis School of Information Technology Fanshawe College London Canada Department of Artificial Intelligence Chung-Ang University Seoul Korea Republic of Curriculum Studies Western University London Canada

ISBN: (纸本)9789819795352

Multimodal learning analytics have become increasingly important in enabling a deeper understanding of teaching and learning in educational research. However, in comparison to other multimodal learning data, there is a limited understanding of the trends within gaze learning data. To address this challenge, this study aims to identify latent topics in gaze learning data through topic modeling and scientometric analysis. We analyzed the abstracts of 573 peer-reviewed and conference proceeding papers that used gaze learning data, written in English, and published between 2008 and February 2024. The findings are as follows. First, three main topics were identified through topic modeling analysis: (learning analytics, multimodal learning, and inclusive learning). Second, the scientometric analysis revealed the structure in which diverse clusters in cited references and institutions are connected around the emerging topics. Based on these findings, the study would provide insights into research directions in both educational research and applications using gaze learning data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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A Case Study on Data Protection for a Cloud- and AI-Based Homecare Medical Device 43rd

A Case Study on Data Protection for a Cloud- and AI-Based...

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43rd International Conference on Application and Theory of Petri Nets and Concurrency , Petri Nets 2022

作者： Bende, Philipp Vovk, Olga Caraveo, David Pechmann, Ludwig Leucker, Martin Institute for Software Engineering and Programming Languages University of Lübeck Lübeck Germany School of Information Technologies Department of Health Technologies Tallinn University of Technology Tallinn Estonia UniTransferKlinik Lübeck GmbH Lübeck Germany

ISBN: (纸本)9783662681909

To improve the treatment of many diseases, continuous monitoring of the patient at home with the ability of doctors to interact with individual cases demands an increasing number of medical devices connected to the cloud. To support the doctor’s duties, such devices may benefit from AI-based diagnosis routines. In order for such devices to be approved and placed on the market, they need to comply with various legal, regulatory, economic, and social requirements. An integral part of these requirements is the protection of the patients’ data. In this paper, based on a current use case, we describe a workflow on how to identify risks and address their mitigations. To this end, we recall the relevant legal, regulatory, economic, and social data protection requirements. We pursue our findings on a Homecare OCT device that is intended to be used by elderly patients on a daily basis, by taking images of their eyes and sending them for further analysis to a cloud- and AI-based system. The patient’s ophthalmologist gets notified for further dedicated treatment depending on the result. We then compare the Homecare OCT device with a clinical OCT System in regard to various risks to patient data which arise when a medical system is used outside of a secure hospital environment. To perform the risk management, we describe (i) the architecture of both systems, (ii) analyze their data flow, (iii) discuss several vectors of attack, (iv) propose ways to mitigate the risks, and (v) discuss the handling of potential data breaches. © 2024, The Author(s), under exclusive license to Springer-Verlag GmbH, DE, part of Springer Nature.

关键词： Decision support systems

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Social Engineering Attacks Detection Approach 13

Social Engineering Attacks Detection Approach

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13th International Conference on Dependable Systems, Services and Technologies, DESSERT 2023

作者： Lysenko, Sergii Vorobiov, Volodymyr Bokhonko, Oleksandr Gaj, Piotr Savenko, Oleg Woloszyn, Jacek Khmelnitsky National University Department of Computer Engineering and Information Systems Khmelnitsky Ukraine Silesian University of Technology Gliwice Poland Khmelnitsky National University Department of Computer Engineering and System Programming Khmelnitsky Ukraine Kazimierz Pulaski University of Technology and Humanities in Radom Department of Informatics and Teleinformatics Radom Poland

ISBN: (纸本)9798350396119

The paper focuses on the problem of technical social engineering attacks that encompass the manipulation of individuals to reveal sensitive information, execute actions, or breach security systems. These exploits frequently capitalize on human psychology, trust, and a lack of vigilance to attain unauthorized entry to networks, systems, or data. In contrast to traditional social engineering tactics that center on psychological manipulation, technical social engineering attacks employ technological means and strategies to manipulate and beguile individuals. The paper presents an attempt to detect social engineering attacks. The approach utilized four machine learning algorithms (decision tree, random forest, K-nearest neighbor, and extreme gradient boosting). The analysis is centered on data collected from network hosts, which may serve as indicators of a potential social engineering attack. The empirical results demonstrated high detection accuracy. © 2023 IEEE.

关键词： Cybersecurity

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Classification Algorithms with a Complex Structure in Pattern Recognition 25

Classification Algorithms with a Complex Structure in Patter...

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Nishanov, Akram Kh. Allamov, Oybek Rakhmanov, Askar T. Yusupova, Janar Ruzibaev, Ortik B. Department of Systematic and Practical Programming Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Department of Software Engineering Urgench Branch of Tashkent University of Information Technology named after Muhammad al Khwarizmi Urgench Uzbekistan Department of Systematic and Practical Programming Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Faculty of Software Engineering Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

ISBN: (纸本)9798350389234

The article considers in the intellectual processing of information, moving from a large unit of measurement to a smaller, more important unit of measurement, selecting sets of informative symbols and classifying symbols, developing modern recognition systems that help specialists in the field, as well as evaluating the states of objects to be classified, developing a classification algorithm for multi-class cases of educational samples. The development of a multi-class algorithm for symbol classification serves to develop the theory of symbol recognition. It deals with the construction of a decision rule construction algorithm. Its main purpose is to determine which of the given classes the recognized object belongs to. The complexity or simplicity of the proposed algorithm depends on the number of classes participating in the study sample. If the number of classes is two, then the formulation of decision rules is simple. That is why the classification algorithms proposed by most authors are solved for cases where the number of classes is three or more, the decisive rule in the matter of classification of objects is solved by making two classes. The construction of a multi-class decision rule for classification, which takes into account all classes at the same time, is a complex and urgent issue. In the article, in the classification of objects, a multi-level complex structured decision rule was developed based on special inequalities, and two-, three- and multi-class classification algorithms were developed. © 2024 IEEE.

关键词： Consensus algorithm

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PREDICTION OF HEART DISEASE USING CLASSIFICATION AND FEATURE SELECTION METHODS 17

PREDICTION OF HEART DISEASE USING CLASSIFICATION AND FEATURE...

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17th International Symposium on Operational Research in Slovenia, SOR 2023

作者： Akarçay Pervin, Özlem Yapici Pehlivan, Nimet Weber, Gerhard Wilhelm KTO Karatay University Department of Computer Programming Konya Turkey Selçuk University Department of Statistics Konya Turkey Poznan University of Technology Poznan Poland Middle East Technical University Institute of Applied Mathematics Ankara Turkey

ISBN: (纸本)9789616165617

Heart disease, known as cardiovascular disease has been one of the main causes of death worldwide in recent years. It is affected by various risk factors such as high blood pressure, high cholesterol, diabetes, smoking, obesity, physical inactivity, etc. In this study, Cleveland database of UCI repository of heart disease patients is used. The dataset includes 303 instances and 76 variables which of 14 variables are considered. At first, three different feature selection techniques, namely LASSO, Elastic Net and Adaptive LASSO under specific tuning parameters determined by cross-validation, are applied to reduce the number of independent variables used for the prediction. Then, five different classification techniques, K-nearest neighbor, Support Vector Machine, Decision Tree, Random Forest, and Logistic Regression are performed to predict heart disease. Performances of these methods are measured by different metrics, such as accuracy, sensitivity, specificity, and Matthew correlation coefficient. © Proceedings of the 17th International Symposium on Operational Research in Slovenia, SOR 2023. All rights reserved.

关键词： Decision trees

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Application-based spam detection with machine learning algorithms 27

Application-based spam detection with machine learning algor...

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27th International Conference on Information Society and University Studies, IVUS 2022

作者： Erbey, Ali Barışçı, Necaattin Uşak University Distance Education Vocational School Department of Computer Programming Uşak Turkey Gazi University Faculty of Technology Department of Computer Engineering Ankara Turkey

We investigated the process of unsupervised generative learning and the structure of informative generative representations of images of handwritten digits (MNIST dataset). Learning models with the architecture of sparse convolutional autoencoder with constraints to produce low-dimensional representations achieved successful generative learning demonstrated by high accuracy of generation of images. A well-defined, continuous and connected structure of generative representations was observed and described. Structured informative representations of unsupervised generative models can be an effective platform for investigation of origins of intelligent behaviors in artificial and biological learning systems. © 2022 Copyright for this paper by its authors.

关键词： Neural networks

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