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7th International Conference on Geographical Information systems Theory, Applications and Management, GISTAM 2021

作者： Fyleris, Tautvydas Kriščiūnas, Andrius Gružauskas, Valentas Čalnerytė, Dalia Kaunas University of Technology Faculty of Informatics Department of Software Engineering Lithuania Kaunas University of Technology Faculty of Informatics Department of Applied Informatics Lithuania Kaunas University of Technology School of Economics and Business Sustainable Management Research Group Lithuania

ISBN: (纸本)9789897585036

Urban growth estimation is an essential part of urban planning in order to ensure sustainable regional development. For such purpose, analysis of remote sensing data can be used. The difficulty in analysing a time series of remote sensing data lies in ensuring that the accuracy stays stable in different periods. In this publication, aerial images were analysed for three periods, which lasted for 9 years. The main issues arose due to the different quality of images, which lead to bias between periods. Consequently, this results in difficulties in interpreting whether the urban growth actually happened, or it was identified due to the incorrect segmentation of images. To overcome this issue, datasets were generated to train the convolutional neural network (CNN) and transfer learning technique has been applied. Finally, the results obtained with the created CNN of different periods enable to implement different approaches to detect, analyse and interpret urban changes for the policymakers and investors on different levels as a map, grid, or contour map. © 2021 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Urban growth

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Modification of the Genetic Algorithm for Building and Reconfiguring Schedules of Order Completion in the Field of Service Provision 12

Modification of the Genetic Algorithm for Building and Recon...

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12th International Conference on Advanced Computer Information Technologies, ACIT 2022

作者： Hrybkov, Serhii Seidykh, Olga Vlasenko, Lidia Lytvynov, Valerii National University of Food Technologies Department of Information Systems Kyiv Ukraine National University of Food Technologies Department of Informatics Kyiv Ukraine National University of Trade and Economics Department of Software Engineering and Cyber Security Kyiv Ukraine Institute of Mathematical Machines and Systems Problems of Nasu Research Department № 220 'Intelligent Information-analytical System' Kyiv Ukraine

ISBN: (数字)9781665410502

ISBN: (纸本)9781665466479

The paper offers a solution to an important scientific and applied problem of scheduling to complete the orders for the provision of services aimed at maintenance and support of computer networks and equipment. This problem is relevant for companies providing such services. The main idea is to form an effective schedule for the completion of orders, as well as to enable its modification in the shortest time when getting orders. The paper also proposes an evaluation function that takes into account bonuses for the timely completion of orders and penalties for the late ones. A combination of a genetic algorithm with the methods of additional improvement on the basis of local optimization is offered. It allows reducing the time for the construction of effective alternative variants of decisions and their estimation. The use of the proposed approach to combining algorithms allows creating and reconfiguring the schedule for the completion of orders in the operational mode in a short time, and optimization makes it possible to reduce the completion of orders by up to 20%. Thus, the application of the proposed approaches will allow effective distribution of tasks among performers and give an economic effect by reducing the time to complete all orders. © 2022 IEEE.

关键词： Genetic algorithms

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Electricity Markets in a Time of Change: A Call to Arms for Business research

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Schmalenbach Journal of Business research 2022年第1期74卷 77-102页

作者： Bichler, Martin Buhl, Hans Ulrich Knörr, Johannes Maldonado, Felipe Schott, Paul Waldherr, Stefan Weibelzahl, Martin Department of Informatics Technical University of Munich Boltzmannstr. 3 Garching 85748 Germany FIM Research Center Project Group Business & Information Systems Engineering of the Fraunhofer FIT Alter Postweg 101 Augsburg 86159 Germany FIM Research Center University of Bayreuth Project Group Business & Information Systems Engineering of the Fraunhofer FIT Wittelsbacherring 10 Bayreuth 95444 Germany School of Business and Economics Vrije Universiteit Amsterdam De Boelelaan 1105 Amsterdam 1081 HV Netherlands

Europe’s clean energy transition is imperative to combat climate change and represents an economic opportunity to become independent of fossil fuels. As such, the energy transition has become one of the most important, but also one of the most challenging economic and societal projects today. Electricity systems of the past were characterized by price-inelastic demand and only a small number of large electricity generators. The transition towards intermittent renewable energy sources changes this very paradigm. Future electricity systems will consist of many thousands of electricity generators and consumers that actively participate in markets, offering flexibility to balance variable electricity supply in markets with a high spatial and temporal resolution. These structural changes have ample consequences for market operators, generators, industrial consumers as well as prosumers. While a large body of the literature is devoted to the energy transition in engineering and the natural sciences, it has received relatively little attention in the recent business research literature, even though many of the central challenges for a successful energy transition are at the core of business research. Therefore, we provide an up-to-date overview of key questions in electricity market design and discuss how changes in electricity markets lead to new research challenges in business research disciplines such as accounting, business & information systems engineering, finance, marketing, operations management, operations research, and risk management. © 2021, The Author(s).

关键词： Demand response Electricity market design Energy transition Renewable energy sources

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Navigable Architectures for Complex Communication Networks 2

Navigable Architectures for Complex Communication Networks

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2nd IEEE Virtual Conference on Communications, VCC 2024

作者： Majdan, Andras Pasic, Lejla Heszberger, Zalan Vida, Rolland Biro, Jozsef Budapest University of Technology and Economics High Speed Networks Laboratory Department of Telecommunications and Artificial Intelligence Müegyetem rkp. 3. BudapestH-1111 Hungary Budapest University of Technology and Economics HUNREN-BME Information Systems Research Group Faculty of Electrical Engineering and Informatics Müegyetem rkp. 3. BudapestH-1111 Hungary

ISBN: (纸本)9798331530099

The anticipated complexity of future communication networks (e.g. 6G) demands the use of advanced complex network analysis tools and methodologies during their conceptualization, design, and operation. In this paper, we introduce a new family of navigation architectures and algorithms based on a specialized geometric embedding of complex networks. We demonstrate that this approach is scalable with respect to routing table sizes and allows nodes to make navigation decisions without full knowledge of the system's topology. While this method requires additional connections to extend the original network, the cost is minimal, as these extra links represent only a small fraction of the network's size and can be factored into the design. We showcase the effectiveness of this approach within prospective communication architectures. © 2024 IEEE.

关键词： Trees (mathematics)

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The Traveling Salesman Problem on the Hyperbolic Plane

The Traveling Salesman Problem on the Hyperbolic Plane

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International Conference on Computational Science and Computational Intelligence (CSCI)

作者： D. Ficzere G. Hollósi A. Frankó P. Varga J. Bíró Department of Telecommunications and Artificial Intelligence HUNREN-BME Information Systems Research Group Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary

ISBN: (数字)9798350361513

ISBN: (纸本)9798350372304

This paper is concerned with the traveling salesman problem (TSP) on the two-dimensional hyperbolic space. We provide an efficient heuristic to find near optimal tour along the cities, where the distance measure is the hyperbolic distance between the points (cities) placed randomly and uniformly on a hyperbolic disk. Our approach is mainly experimental, that is for a large number instances of points randomly generated on hyperbolic disks with different size are performed and statistics on our TSP heuristic are provided and compared to the results of standard TSP solvers. Nevertheless, we also show analytical approximations on the expected tour length in our heuristic solution of the TSP. We also perform an application possibility of our TSP solution for designing optimal address space of hop-by-hop routing in hyperbolic complex networks.

关键词： Scientific computing Urban areas Complex networks Traveling salesman problems Routing Mathematics computing Space exploration

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Separated Artificial Neural Network Based Distribution System State Estimation

Separated Artificial Neural Network Based Distribution Syste...

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IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia)

作者： Lejla Pašić Azra Pašić Alija Pašić István Vokony József Bíró Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary Department of Telecommunications and Media Informatics Budapest Hungary ELKH-BME Information Systems Research Group Budapest Hungary Department of Electric Power Engineering Budapest Hungary

Distribution system state estimation is becoming an increasingly important feature in the modern power grid, but the lack of real measurements makes its implementation particularly difficult. A solution for this problem could be the implementation of Artificial Neural Networks for direct distribution system state estimation. In our work, we created an ANN-based distribution system state estimation which can function based on sparse data, the accuracy of the ANN-based state estimation can be further improved utilizing a separated distribution system state estimation (S-ANN), which estimates the state of the network separately according to measurement type based on the same input data. With this method, the root mean square error and standard deviation of the state estimation can be significantly decreased.

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Assisting Visually Impaired Subjects Using Large Language Models: A Comprehensive Evaluation

Assisting Visually Impaired Subjects Using Large Language Mo...

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Novel Intelligent and Leading Emerging Sciences Conference (NILES)

作者： Heidi Ahmed Holiel Sahar Ali Fawzi Walid Al-Atabany Medical Imaging and Image Processing Research Group Center for Informatics Science Nile University Sheikh Zayed City Egypt Systems and Biomedical Engineering Department Cairo University Giza Egypt Biomedical Engineering Department Helwan University Helwan Egypt

ISBN: (数字)9798350378511

ISBN: (纸本)9798350378528

Visual impairment significantly challenges an individual's ability to navigate and interact with their environment independently. While retinal prostheses have provided partial vision restoration, they offer limited support for complex visual tasks such as object recognition, text reading, and real-time navigation. Recent advancements in technology have introduced Large Language Models (LLMs) as promising tools to enhance these assistive technologies, potentially enhancing the capabilities of existing devices. This study explores the integration of LLMs into assistive devices for visually impaired individuals, evaluating several models, including MiniCPM-Llama3-V-2_5, PaliGemma, Blip2, Microsoft Git Large COCO, and LLaVA-Next. The models are assessed in tasks like image captioning, object detection, and optical character recognition (OCR), focusing on their effectiveness in enhancing user independence and quality of life. Our findings indicate that MiniCPM-Llama3-V-2_5 and PaliGemma excel in providing accurate, detailed, and practical outputs, crucial for real-world applications. These models demonstrate significant potential in transforming retinal prostheses from passive aids into interactive tools that enhance user engagement with their surroundings. The study concludes with discussions on the implications of these findings and suggests future research directions to further improve the integration of LLMs in assistive technologies for visually impaired individuals.

关键词： Visualization Accuracy Navigation Large language models Optical character recognition Visual impairment Object detection Retina Real-time systems Standards

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Numerical investigation of Marangoni natural convection and entropy generation using the RBF meshless method 12

Numerical investigation of Marangoni natural convection and ...

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12th International Conference on Physics and Its Applications, ICOPIA 2024

作者： Pranowo Kubota, Mitsuhiro Wijayanta, Agung Tri Setyohadi, Djoko Budiyanto Itaya, Yoshinori Department of Informatics Universitas Atma Jaya Yogyakarta Jl. Babarsari 44 Yogyakarta55281 Indonesia Research Group of Sustainable Thermofluids Universitas Sebelas Maret Jl. Ir. Sutami 36A Kentingan Surakarta57126 Indonesia Graduate School of Engineering Chemical Systems Engineering Nagoya University Furo-Cho Chikusa Nagoya464-8601 Japan Department of Mechanical Engineering Graduate School of Engineering Universitas Sebelas Maret Jl. Ir. Sutami 36A Kentingan Surakarta57126 Indonesia Environmental and Renewable Energy Systems Division Graduate School of Engineering Gifu University 1-1 Yanagido Gifu-shi Gifu501-1193 Japan

The entropy study of fluid flow and heat transfer in an open square cavity with simultaneous natural and Marangoni convection is presented in this paper. Sidewall heating drives natural convection fluid flow. Marangoni convection is invoked to account for thermal interaction through the free surface at the top. Through numerical calculations, the evolution of thermal-hydraulic flow physics is thoroughly studied. The Navier-Stokes, continuity and energy equations are cast using the fractional step method, and the governing equations are discretized using the Radial Basis Function (RBF) meshless approach. Using relevant parameters such as the Marangoni number (Ma = 10-1000), Prandtl number (Pr = 0.71-7.0), and Rayleigh number (Ra = 1000-100000), the results show various flow patterns. A comparative analysis that takes into account Marangoni convection demonstrates how its presence can improve heat transmission. Additionally the entropy creation of the specified parameters is examined and analyzed. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Natural convection

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DAFNI: A computational platform to support infrastructure systems research

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Proceedings of the Institution of Civil Engineers: Smart Infrastructure and Construction 2023年第3期176卷 108-116页

作者： Matthews, Brian Hall, Jim Batty, Michael Blainey, Simon Cassidy, Nigel Choudhary, Ruchi Coca, Daniel Hallett, Stephen Harou, Julien J James, Phil Lomax, Nik Oliver, Peter Sivakumar, Aruna Tryfonas, Theodoros Varga, Liz Scientific Computing Department Science and Technology Facilities Council Didcot United Kingdom School of Geography and the Environment University of Oxford Oxford United Kingdom Centre for Advanced Spatial Analysis University College London London United Kingdom Transportation Research Group Faculty of Engineering and Physical Sciences University of Southampton Southampton United Kingdom Department of Civil Engineering University of Birmingham Birmingham United Kingdom Department of Engineering University of Cambridge Cambridge United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Centre for Environmental and Agricultural Informatics Cranfield University Cranfield United Kingdom Department of Mechanical Aerospace and Civil Engineering University of Manchester Manchester United Kingdom School of Engineering Newcastle University Newcastle United Kingdom School of Geography University of Leeds Leeds United Kingdom Department of Civil and Environmental Engineering Imperial College London London United Kingdom Department of Civil Engineering University of Bristol Bristol United Kingdom Department of Civil Environmental and Geomatic Engineering University College London London United Kingdom

research into the engineering of infrastructure systems is increasingly data intensive. researchers build computational models to explore scenarios such as investigating the merits of infrastructure plans, analysing historical data to inform system operations or assessing the impacts of infrastructure on the environment. Models are more complex, at higher resolution and with larger coverage. researchers also require a 'multi-systems' approach to explore interactions between systems, such as energy and water with urban development, and across scales, from buildings and streets to regions or nations. Consequently, researchers need enhanced computational resources to support cross-institutional collaboration and sharing at scale. The Data and Analytics Facility for National Infrastructure (DAFNI) is an emerging computational platform for infrastructure systems research. It provides high-throughput compute resources so larger data sets can be used, with a data repository to upload data and share these with collaborators. Users' models can also be uploaded and executed using modern containerisation techniques, giving platform independence, scaling and sharing. Further, models can be combined into workflows, supporting multi-systems modelling and generating visualisations to present results. DAFNI forms a central resource accessible to all infrastructure systems researchers in the UK, supporting collaboration and providing a legacy, keeping data and models available beyond the lifetime of a project. © 2023 Emerald Publishing Limited: All rights reserved.

关键词： Urban growth

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Modeling of Sensor Enabled IrrigationManagement for Intelligent Agriculture Using Hybrid Deep Belief Network

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Computer systems Science & engineering 2023年第8期46卷 2319-2335页

作者： Saud Yonbawi Sultan Alahmari B.R.S.S.Raju Chukka Hari Govinda Rao Mohamad Khairi Ishak Hend Khalid Alkahtani JoséVarela-Aldás Samih M.Mostafa Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia King Abdul Aziz City for Science and Technology RiyadhKingdom of Saudi Arabia Aditya Engineering College Affiliated to JNTUK(Kakinada) SurampalemIndia Department of MBA Vignan’s Institute of Information and Technology(A)DuvvadaVisakhapatnamAP530049India School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains Malaysia(USM)Nibong TebalPenang14300Malaysia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11564Saudi Arabia SISAu Research Group Universidad Tecnológica IndoaméricaAmbato180103Ecuador Faculty of Computers and Information South Valley UniversityQena83523Egypt

Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual *** the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart *** irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation *** learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an *** this motivation,this study develops a modified black widow optimization with a deep belief network-based smart irrigation system(MBWODBN-SIS)for intelligent *** MBWODBN-SIS algorithm primarily enables the Internet of Things(IoT)based sensors to collect data forwarded to the cloud server for examination ***,the MBWODBN-SIS technique applies the deep belief network(DBN)model for different types of irrigation classification:average,high needed,highly not needed,and not *** MBWO algorithm is used for the hyperparameter tuning process.A wideranging experiment was conducted,and the comparison study stated the enhanced outcomes of the MBWODBN-SIS approach to other DL models with maximum accuracy of 95.73%.

关键词： Agriculture smart farming hyperparameter tuning artificial intelligence irrigation management sensors deep learning

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