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11th International Conference on Electrical and Electronics engineering, ICEEE 2024

作者： Solmaz, Seher Dursun, Mahir Graduate School Of Informatics Gazi University Dept of Information Systems Ankara Turkey Gazi University Faculty of Technology Dept. of Electrical and Electronics Engineering Ankara Turkey

ISBN: (纸本)9798350362541

Since text recognition studies in the literature are generally carried out in English, tokenization processes of Turkish legal texts in the Ural-Altaic language family cannot be used much. In this study, we tokenize Turkish legal texts and perform decision prediction using a deep learning Convolutional Neural Network (CNN) model. Artificial intelligence (AI), which is developing at a rapid pace, has become applicable to almost all fields of study and has started to be used effectively. Developments in AI have affected the field of law as well as other fields of study. The use and spread of AI in the field of law has increased significantly in recent years. One of the most important factors in this increase is that there is a huge amount of data in the field of law. It has become a need to analyze this data and transform it into meaningful and usable information. This paper aims to make decision prediction using artificial intelligence in judicial applications. In the study, using CNN, a neural network-based deep learning model, decision prediction was made with the data published by the Ombudsman's Office on the institution's website, which is free from publicly accessible personal data. The model was trained on the applicant information and the type of decision in the decision text. An F1 score of 0.63 was achieved for decision prediction. © 2024 IEEE.

关键词： Convolutional neural networks

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SGNR: A Social Graph Neural Network Based Interactive Recommendation Scheme for E-Commerce

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Tsinghua Science and Technology 2023年第4期28卷 786-798页

作者： Dehua Ma Yufeng Wang Jianhua Ma Qun Jin School of Communications and lnformation Engineering Nanjing University of Posts and TelecommunicationsNanjing 210003China Department the Faculty of Computer and Information SciencesHosei UniversityTokyo 194-0298Japan Networked Information Systems Laboratory Department of Human Informatics and Cognitive SciencesFaculty of Human SciencesWaseda UniversityTokyo 169-8050Japan

Interactive Recommendation(IR)formulates the recommendation as a multi-step decision-making process which can actively utilize the individuals’feedback in multiple steps and optimize the long-term user benefit of *** Reinforcement Learning(DRL)has witnessed great application in IR for ***,user cold-start problem impairs the learning process of the DRL-based recommendation ***,most existing DRL-based recommendations ignore user relationships or only consider the single-hop social relationships,which cannot fully utilize the social *** fact that those schemes can not capture the multiple-hop social relationships among users in IR will result in a sub-optimal *** address the above issues,this paper proposes a Social Graph Neural network-based interactive Recommendation scheme(SGNR),which is a multiple-hop social relationships enhanced DRL *** this framework,the multiple-hop social relationships among users are extracted from the social network via the graph neural network which can sufficiently take advantage of the social network to provide more personalized recommendations and effectively alleviate the user cold-start *** experimental results on two real-world datasets demonstrate that the proposed SGNR outperforms other state-of-the-art DRL-based methods that fail to consider social relationships or only consider single-hop social relationships.

关键词： Interactive Recommendation(IR) Deep Reinforcement Learning(DRL) Graph Neural Network(GNN)

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Wheat Supply Chain Network Design: Lesson for Resilience and Sustainability in a Situation of War and Crisis

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Journal of the Knowledge Economy 2025年 1-45页

作者： Rahbari, Misagh Tavakkoli-Moghaddam, Reza Razavi Hajiagha, Seyed Hossein Jafari, Mohammad Javad Department of Industrial Engineering Faculty of Engineering Kharazmi University Tehran Iran School of Industrial Engineering College of Engineering University of Tehran Tehran Iran Research Center of Performance and Productivity Analysis Istinye University Istanbul Turkey Department of Management Faculty of Management and Finance Khatam University Tehran Iran Department of Informatics Bioengineering Robotics and Systems Engineering University of Genova Genova Italy

Global crises, such as the Russia–Ukraine war and the COVID-19 pandemic, have caused disruptions to the agri-food supply chains. Resilience strategies can be used to address these disruptions. Therefore, this study aims to analyze the design of a bi-objective resilient and sustainable wheat supply chain problem, considering disruptions caused by the Russia-Ukraine war. Resilience strategies for inventory prepositioning and backup suppliers were employed to deal with these disruptions. Also, a carbon cap-and-trade mechanism was used to reduce carbon emissions in the wheat supply chain. The Minimax Relative Regret Scenario-based Stochastic Programming (MRRSSP) and p-Robust Scenario-based Stochastic Programming (PRSSP) were simultaneously used to control the uncertainty stemming from these disruptions. Furthermore, we investigated the possibility of the simultaneous occurrence of multiple global crises and their impacts on demand parameters in the wheat supply chain. Sensitivity analysis revealed that in the case study, a simultaneous decrease in the foreign retailers’ demand and an increase in the domestic retailers’ demand resulted in the location and resilience strategy costs, accounting for more than 90% of the total costs. Moreover, using the Robust Scenario-based Stochastic Programming (RSSP) approach provided a 10% advantage over the nominal approach. If the RSSP is not employed, the cost due to lack of access to perfect information would be increased by 27%. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Disruption Resilience strategies Robust scenario-based stochastic programming Sustainable wheat supply chain War crisis

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Identifying and Involving the Real End User in Software Development: Towards a Pattern Language 27

Identifying and Involving the Real End User in Software Deve...

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2022 27th European Conference on Pattern Languages of Programs, EuroPLoP 2022

作者： Daud Haiderzai, Mohammad Vranic, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Slovakia

ISBN: (纸本)9781450395946

Software development demand and identification of end users involvement have been increasing rapidly, but identifying the real end user and involving them in software development is challenging for software developers reported in the literature. One of the problems is the difficulty of designing the business domain. It takes longer to find the actual business domain when different and inexpert domain end users are engaged with developers. Another problem is the difficulty of incorporating all types of end users needs in software development. Several expectations and different information make the development process more complex and overload the project scope. Software development also takes more time, and the project goal is challenging. The above problems are the leading causes that create a complex process and difficulty in software development. To overcome these problems, we established a pattern language composed of eight organizational patterns observed and documented during in practical work on many projects. These patterns and other known organizational patterns relation are described in a patterns story of a real company. © 2022 ACM.

关键词： Software design

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Organizational Patterns for Improving the Understanding between a Customer and the Development Team 27

Organizational Patterns for Improving the Understanding betw...

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2022 27th European Conference on Pattern Languages of Programs, EuroPLoP 2022

作者： Khattab, Mohammad Ismail Vranic, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Slovakia

ISBN: (纸本)9781450395946

During a software development process, a customer and the development team need to communicate and understand each other. Poor communication between a customer and the development team is one of the most common challenges in the software development process, which leads to software failures and further increases the budget. In our practical experience and from the literature, we found that lack of customer involvement, no common communication language, complex business processes, end-user resistance toward system development, lack of trust, lack of leadership, and and end-user capacity are the main challenges toward the development team understanding. We bring six newly discovered patterns that address these problems and improve the understanding between a customer and the development team during the software development process. We also bring some of the known organizational patterns that also mitigate these problems into relation to the newly discovered patterns. To create a pattern language from these patterns, we illustrated the sequences of the patterns so that the development team and customer could understand each other. © 2022 ACM.

关键词： Software design

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Advancing Quantum Communications: Q-OFDM with Quantum Fourier Transforms for Enhanced Signal Integrity 32

Advancing Quantum Communications: Q-OFDM with Quantum Fourie...

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32nd International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2024

作者： Sabaawi, Abdulbasit M. A. Almasaoodi, Mohammed R. Imre, Sandor Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Networked Systems and Services Budapest Hungary Ninevah University College of Electronics Engineering Mosul Iraq Kerbala University Kerbala Iraq

ISBN: (纸本)9789532901382

The integration of Orthogonal Frequency-Division Multiplexing (OFDM) with contemporary communication systems faces challenges, notably the requirement of a cyclic prefix (CP), which affects spectral efficiency. This paper proposes a novel quantum OFDM transmission method that utilizes quantum mechanisms for encoding, decoding, and channel processes, replacing the need for Discrete Fourier Transforms (DFT) and Inverse Discrete Fourier Transform (IDFT). This advanced quantum OFDM model eliminates the CP requirement and, when compared to a standard quantum transmission scheme, shows improved accuracy in quantum state measurement, especially in channels with higher resistivity. The results have been validated using simulations on IBM's Qiskit platform. © 2024 University of Split, FESB.

关键词： Orthogonal frequency division multiplexing

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Large Language Models and Adversarial Reinforcement Learning to Automate PLCs Programming: A Preliminary Investigation 9

Large Language Models and Adversarial Reinforcement Learning...

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9th International Conference on Control, Decision and Information Technologies, CoDIT 2023

作者： Boudribila, Abderrahmane Chadi, Mohamed-Amine Tajer, Abdelouahed Boulghasoul, Zakaria Cadi Ayyad University National School of Applied Sciences Systems Engineering Applications Laboratory Marrakech Morocco Cadi Ayyad University Faculty of Sciences Semlalia Informatics Systems Engineering Laboratory Marrakech Morocco

ISBN: (纸本)9798350311402

The manual programming of Programmable Logic Controllers (PLCs) is a time-consuming and error-prone task, particularly for complex systems. Researchers have proposed various techniques, such as the modular, decentralized, hierarchical, and distributed approaches, which all fall under the Supervisory Control Theory (SCT) whose main goal is to generate a supervisor that ensures that the controller's behavior satisfies the specifications. While these techniques have demonstrated efficiency in systems of low complexity, high-complexity systems and probabilistic ones remain a major challenge. In this paper, we propose a novel pipeline that relies solely on Artificial Intelligence (AI)-techniques, namely, Reinforcement Learning (RL) and Natural Language Processing (NLP) techniques, including Named Entity Recognition (NER) and Large Language Models (LLMs). As a preliminary result, we demonstrate the potential of the proposed pipeline using the recent ChatGPT model by making a sample dataset in this context and generating Structured Text code from specifications presented in a natural language format. Finally, we outline future directions toward a fully automated AI-based PLC programming tool. © 2023 IEEE.

关键词： Reinforcement learning

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Comparison of Visual Occupancy Detection Approaches for Parking Lots and Dedicated Containerized REST-API Server Application 9

Comparison of Visual Occupancy Detection Approaches for Park...

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9th Workshop on Software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2022

作者： Petričko, Andrej Dakić, Pavle Vranić, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology Bratislava Slovakia

With the development of new technology, the urban infrastructure, which is necessary to meet the social, economic, and physical needs of the population, is also gradually improving. Therefore, cities face significant urban planning challenges. With the increasing population and number of cars on the road parking space occupancy detection techniques are of great importance for efficient parking space management. Knowing the availability of parking spaces within a city in real-time and informing residents can be of great help in reducing the number of car park councils, reducing traffic congestion in cities, or improving the scalability of car parks and the time needed to find empty parking space. In many car parks, ground sensors are used to determine occupancy status. However, this requires the installation and maintenance of these sensors in every parking space. This can be expensive, especially in car parks with a large number of available spaces. With increasing computing power, new approaches to parking space occupancy detection using computer vision are emerging. However, these approaches are tailored to the site of application. In this work, we propose a comparison of two general approaches: classification and object detection. The reliability, precision, and scalability of these approaches are compared using a REST-API server application implemented in Python. In order to get as close as possible to general use, we use docker, which enables us easier develop and deploy this application independently of the hardware. © 2022 Copyright for this paper by its authors.

关键词： Object detection

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ECONOMIC BALANCE OF THE SORTING LINE FOR MUNICIPAL WASTE PROCESSING 24

ECONOMIC BALANCE OF THE SORTING LINE FOR MUNICIPAL WASTE PRO...

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24th International Multidisciplinary Scientific Geoconference: Ecology, Economics, Education and Legislation, SGEM 2024

作者： Zyder, Václav Chlopecký, Jakub Hubáček, Jaroslav Rokosz, David Hrouda, Matěj Faculty of Materials Science and Technology Department of Industrial Systems Management VSB - Technical University of Ostrava Czech Republic Faculty of Economics Department of Systems Engineering VSB - Technical University of Ostrava Czech Republic Faculty of Economics Department of Applied Informatics VSB - Technical University of Ostrava Czech Republic

ISBN: (纸本)9786197603743

The contribution focuses on the optimization of the economic balance of the sorting line for the processing of municipal waste with the aim of increasing the efficiency and sustainability of waste management. This abstract provides an overview of the key economic aspects that affect sorting line operations, including cost, revenue and financial return analysis. Major cost items include investment in modern sorting line technology, installation and commissioning costs, and operating costs associated with maintenance, energy and labor. On the revenue side, the income from the sale of sorted materials such as plastics, metals and paper and the savings achieved by reducing the volume of waste sent to landfills are analysed. The study also takes into account possible subsidies and financial support available for environmental projects. The economic analysis of a purely municipal project (without the involvement of foreign capital, the involvement of public funds and subsidies) CEVYKO includes an assessment of the overall financial efficiency, the identification of potential risks and obstacles, and the proposal of measures to increase profitability and sustainability. Special emphasis is placed on long-term economic and environmental benefits, including improving the local economy, creating jobs and reducing the ecological footprint. The results of this analysis provide valuable information for decision-making processes and strategic planning in the field of municipal waste management. The recommendations arising from this study support the efficient allocation of resources and contribute to the achievement of the CEVYKO project goals. in the field of economic sustainability. © 2024 International Multidisciplinary Scientific Geoconference. All rights reserved.

关键词： Sustainable development

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Toward Organizational Pattern Ontology 27

Toward Organizational Pattern Ontology

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2022 27th European Conference on Pattern Languages of Programs, EuroPLoP 2022

作者： Waseeb, Shakirullah Vranic, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Slovakia

ISBN: (纸本)9781450395946

Organizational patterns of agile software development are proven practices for dealing organizational principles. Finding and selecting the right pattern is difficult. One way to select a pattern is to follow the sequence and compositions given in a pattern language. However, in general, pattern languages do not always reveal every reliable connection. Patterns are described in informal and unstructured text, making it difficult to understand their connections. This work attempts to provide a conceptual ontology model for organizational patterns-describing the collection of concepts (terms) and their relations. This contribution can be an attempt to express, expose, and share semantic knowledge between patterns using ontology. The resulting ontology can be used on top of the organizational patterns repositories to help retrieve patterns based on their logical connections. © 2022 ACM.

关键词： Semantics

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