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Scientific Workflow Provenance Management: system Requirements and a Reference Architecture 20th

Scientific Workflow Provenance Management: System Requiremen...

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20th International conference on Grid, Cloud, and Cluster Computing, GCC 2024, 3rd International conference on Quantum Technologies, ICEQT 2024, and 21st International conference on modeling, Simulation and Visualization Methods, MSV 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024

作者： Kashliev, Andre Department of Computer Science Eastern Michigan University Ypsilanti United States

ISBN: (纸本)9783031858833

Scientific workflows have emerged as a new paradigm to facilitate and automate scientific processes. During workflow execution, the need often arises to capture and store the data derivation history, known as provenance, which describes the steps that yielded workflow output results. Workflow tools available today address this need by employing systems that capture provenance, store it in a database, and provide an interface for scientists to explore the stored data. However, these systems differ both in their functional and non-functional characteristics. this fact indicates that there is no agreement yet in the community about the essential capabilities that a provenance system has to provide. It is therefore important to develop a set of requirements for a scientific workflow provenance system. Furthermore, due to the lack of understanding of what these standard requirements should be, it is only natural that a standard system architecture for provenance management is missing. To address these shortcomings, in this paper, we 1) identify a set of functional and non-functional requirements for scientific workflow provenance management systems that cover key aspects of provenance storage, exploration, and reasoning, and 2) propose a reference system architecture for scientific workflow provenance management. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Provenance provenance system requirements scientific workflow

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Incumbent Perspective to the Sustainability Transitions: District Heating Companies and the Rise of Energy Communities

Incumbent Perspective to the Sustainability Transitions: Dis...

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International conference on European Electricity Market, EEM

作者： Marja Heikkinen Tuomas Vanhanen Jussi Valta Faculty of Information Technology and Communication Sciences Tampere University Tampere Finland Pertti Järventausta Faculty of Information Technology and Communication Sciences Tampere University Tampere Finland Faculty of Management and Business Tampere University Tampere Finland

ISBN: (数字)9798350381740

ISBN: (纸本)9798350381757

Energy communities and solutions are gaining more attention as a part of the sustainability transition. District heating (DH) companies are not traditionally part of those communities or solutions, although the literature suggests that DH companies should seek to develop prosumer-centric business models.. In this study, four different scenarios are created, each scenario with different involvement of DH company and DH. Four case studies are selected to shed more light on the scenarios and three main topics studied in this paper: Actor network, regulation and policy, and technology and material aspects. this study discusses the role of DH and DH company in energy communities and energy solutions, and how their involvement affects their revenue.

关键词： District heating Biological system modeling Buildings Europe Companies Regulation Sustainable development

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Optimal Design of a Fuzzy system with a Real-Coded Genetic Algorithm for Diabetes Classification 20th

Optimal Design of a Fuzzy System with a Real-Coded Genetic A...

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20th International conference on Hybrid Intelligent systems, HIS 2020 and 12th World Congress on Nature and Biologically Inspired Computing, NaBIC 2020

作者： Monica, Julio C. Melin, Patricia Sanchez, Daniela Tijuana Institute of Technology TijuanaBC22414 Mexico

ISBN: (纸本)9783030730499

In this work a real-coded genetic algorithm for parameter optimization of the membership functions of the inputs and the outputs of a fuzzy inference system applied to diabetes classification is proposed. the main goal of this article is to show the advantages that parameter optimization of all the inputs and output using a real-coded genetic algorithm. the dataset used in this work to validate the approach is the PIMA Indian Diabetes dataset, where we have selected five attributes to perform the parameter optimization. Being the Diabetes a disease that has been affecting many lives in the world, for this reason, this work seeks to find a better classification. © 2021, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Membership functions

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Understanding Public Policy Effects on Alcohol-Related Behaviors and Outcomes Using system Dynamics 20th

Understanding Public Policy Effects on Alcohol-Related Beha...

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作者： Ogungbesan, Damilare Adeogun, Ashiat Adekoya, Aanuoluwapo Faezipour, Misagh Middle Tennessee State University MurfreesboroTN37132 United States

ISBN: (纸本)9783031858833

Public policies, such as alcohol taxation policy, age restriction policy, production and sales regulation policy, advertising restriction, and rehabilitation, significantly impact alcohol consumption-a complex social issue with wide-ranging implications for public health and safety. this study employs system dynamics methodology to explore the intricate relationships among crucial factors, policies, and their effects on behaviors and outcomes resulting from alcohol consumption. the research identifies various influential factors, including socioeconomic conditions, cultural norms, rehabilitation policies, alcohol pricing, healthcare costs, and societal consequences. these elements are integrated into a dynamic model that captures feedback loops and causal links guiding changes in alcohol consumption, accidents, and long-term effects. through causal loop analysis, diverse policy scenarios are evaluated for their potential impacts, revealing the intricate influences surrounding alcohol use and the multifaceted repercussions of policy interventions. this research offers a comprehensive perspective on public policy’s role in shaping alcohol-related behaviors and outcomes. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： system theory

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Xpress: A system for Dynamic, Context-Aware Robot Facial Expressions Using Language Models 25

Xpress: A System for Dynamic, Context-Aware Robot Facial Exp...

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ACM/IEEE International conference on Human-Robot Interaction (HRI)

作者： Victor Nikhil Antony Maia Stiber Chien-Ming Huang Johns Hopkins University Baltimore MD USA

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

Facial expressions are vital in human communication and significantly influence outcomes in human-robot interaction (HRI), such as likeability, trust, and companionship. However, current methods for generating robotic facial expressions are often labor-intensive, lack adaptability across contexts and platforms, and have limited expressive ranges-leading to repetitive behaviors that reduce interaction quality, particularly in long-term scenarios. We introduce Xpress, a system that leverages language models (LMs) to dynamically generate context-aware facial expressions for robots through a three-phase process: encoding temporal flow, conditioning expressions on context, and generating facial expression code. We demonstrated Xpress as a proof-of-concept through two user studies $(n=15\times 2)$ and a case study with children and parents $(n=13)$ , in storytelling and conversational scenarios to assess the system's context-awareness, expressiveness, and dynamism. Results demonstrate Xpress's ability to dynamically produce expressive and contextually appropriate facial expressions, highlighting its versatility and potential in HRI applications.

关键词： Adaptation models Codes Social robots Human-robot interaction Oral communication Encoding Faces Context modeling

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Impact Analysis and Optimized Solution for Electric Vehicle Integration in Densely Populated Distribution Networks: A Case Study in Bangladesh

Impact Analysis and Optimized Solution for Electric Vehicle ...

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Clean and Green Energy Engineering (CGEE), International conference on

作者： Md. Samsul Alam Istiak Ahmed Md. Abdur Razzak Research and Technical Service Power Grid Company of Bangladesh Dhaka Bangladesh Department of Electrical and Electronic Engineering Independent University Bangladesh Dhaka Bangladesh

ISBN: (数字)9798350377491

ISBN: (纸本)9798350377507

this study investigates the dynamics of electric vehicle (EV) integration within an authentic distribution network in Bangladesh by leveraging DigSilent Powerfactory for modeling. through simulations encompassing 10%, 20%, and 30% EV integration in an 11 kV distributed system, the research scrutinizes the network's robustness against heightened loads from both EV charging stations and household EV charging. By employing load flow and quasi-dynamic simulations, the analysis accounts for the stochastic variability in load consumption, mirroring the load profile of Bangladesh based on peak/off-peak hours and seasonal fluctuations. Key parameters, including voltage profiles, active power flows, and power losses, are thoroughly examined to reveal the network's resilience to accommodate augmented loads. the outcomes advocate for optimization strategies for both residential and commercial charging stations, showcasing how the existing infrastructure can adeptly absorb additional charging facilities without requiring extensive network overhauls and hence improving the hosting capacity. this study offers pragmatic insights for distribution system operators in Bangladesh and beyond, providing a framework for managing challenges arising from the escalating integration of electric vehicles.

关键词： Schedules Loading Distribution networks Voltage Electric vehicle charging Voltage control optimization Load modeling Resilience Load flow

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Space-Time-Processing optimization for Accurate DOA Estimation in Ultra Wideband DF system

Space-Time-Processing Optimization for Accurate DOA Estimati...

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International Bhurban conference on Applied Sciences & Technology, IBCAST

作者： Waqas Ahmed Muhammad Umair N aveed Ahsan CESAT Islamabad Pakistan

ISBN: (数字)9798350308259

ISBN: (纸本)9798350308266

this research paper presents a novel direction of arrival (DOA) estimation technique that fuses multiple processing techniques to enhance accuracy while mitigating cost and space constraints. In order to reduce the system cost owing to hardware, the number of antenna elements restricted to six. the antenna orientation especially designed in co-prime ratios of 2:5:3 to minimize ambiguity and to ensure that the DOA estimation is insensitive to the orientation of the platform, carrying the antennas. the proposed scheme fuses common angle search(CAS) technique, amplitude comparison and correlative interferometry with interpolation technique to address the limitations offered by each individual technique. the proposed scheme achieves nearly real-time DOA estimation with maximum RMSE around $1^{\circ}$ , field of view $40^{\circ}$ and maximum antenna separation around 200mm.

关键词： Direction-of-arrival estimation Accuracy Costs Fuses Estimation Real-time systems Antennas optimization Ultra wideband technology Interferometry

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Multiprocessor Task Scheduling - Comparison of Some Heuristics and Metaheuristics

Multiprocessor Task Scheduling - Comparison of Some Heurist...

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20th International conference on Dependability of Computer systems, DepCoS-RELCOMEX 2025

作者： Dorota, Dariusz Cracow University of Technology st. Warszawska 24 Cracow31-155 Poland

ISBN: (纸本)9783031927331

the article concentrates on the so-called multiprocessor task scheduling problem with deterministic task duration and independent tasks. Executing a task on more than one processor can be perceived as a tool for improving system dependability through hardware and software redundancyOur aim is to compare and evaluate some heuristics for solving the multiprocessor task scheduling problem with deterministic task duration. We compare three models to address this problem: the classical approach [doc], the TS (Tabu Search) algorithm, and PSO (Particle Swarm optimization). the previous model introduced multiprocessor tasks and a higher level of dependability. the latter models consider other popular heuristics for this type of problem. the previous methodology for multiprocessor task scheduling involved the application of a modified Muntz-Coffman algorithm. In this paper, we compare the previous model with other adapted heuristics (TS, PSO). the article is an extension of the author’s previous research, considering deterministic task duration in different models. Computational experiments were conducted to compare the results obtained for each model. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Particle swarm optimization (PSO)

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Optimized classification system for MRIs with MOO technique and SVM

Optimized classification system for MRIs with MOO technique ...

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IEEE SSD International Multi-conference on systems, Signals and Devices

作者： Syrine Neffati Mohsen Machhout Faculty of Sciences of Monastir Electronics and Micro-Electronic Laboratory (LEME) University of Monastir Monastir Tunisia

the phase of feature extraction and dimensionality reduction in pattern recognition is the way to capture the visual content images. During this phase raw images are presented in their reduced form in order to facilitate decision making in pattern recognition in general and in classification problems in particular. In this paper we propose a Magnetic Resonance Images (MRIs) classifier based on an Optimized Kernel Principal Component Analysis (OKPCA) and Support Vector Machine (SVM) named OKPCA+SVM. the ultimate objective of the proposed study is to suggest a new optimized technique of feature extraction and dimensionality reduction named OKPCA based on the Multi-Objective optimization (MOO) method. this work is based on the following phases; preprocessing (including data acquisition), feature selection (including feature extraction and dimensionality reduction) and finally classification. the k-fold cross validation technique was applied to generalize the suggested scheme on other independent benchmarks. Two benchmarks used in our experiments are DATASET 66 and DATASET 160. the images used in the benchmarks were collected from the ‘Harvard Medical School’ website. We have found a 90.5% as accuracy rate on Dataset-66 and 91.6% as accuracy rate on Dataset-160. From the experiment results we can say that the proposed classifier is robust and effective compared to other recent studies.

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AI-Optimized Genetic Algorithm for Enhancing Resource Recovery in the Circular Economy

AI-Optimized Genetic Algorithm for Enhancing Resource Recove...

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Innovative Research in Applied Science, Engineering and Technology (IRASET),conference on

作者： Abderrahman Mansouri Bellat Abdelouahad Idriss Bennis Ali Siadat Fatiha Akef Modeling and Simulation of Intelligent Industrial Systems Laboratory (M2S2I) ENSET Mohammedia Hassan II University Casablanca Morocco Laboratory of Design Manufacturing and Control Arts et Metiers ParisTech Metz France Laboratory of Mechanical and Thermal Processes and Control (PCMT) ENSAM Rabat Mohammed V University in Rabat Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

this paper presents a Genetic Algorithm (GA)- based optimization approach aimed at improving circular economy strategies by optimizing recyclability and economic value, while minimizing disassembly complexity and environmental impact. A multi-objective function is established, incorporating essential parameters such recyclability rate, component reuse value, disassembly expenses, carbon footprint, and waste minimization. the GA investigates an optimal balance between sustainability and economic viability using an evolutionary search method that identifies and enhances solutions throughout several generations. the dataset comprises 50 components of end-of-life products, categorized as metals (40%), plastics (30%), and electronic materials (30%), exhibiting recyclability rates between 35% and 95%. the results indicate that the GA attains a 25% enhancement in recyclability, a 30% reduction in disassembly complexity, and a 20% decrease in carbon footprint relative to traditional approaches. the suggested method offers a versatile and scalable decision-making instrument for manufacturers, recyclers, and policymakers, enhancing a more sustainable resource recovery system.

关键词： systematics Instruments Computational modeling Search methods Decision making Complexity theory Sustainable development optimization Carbon footprint Genetic algorithms

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