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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Afroditi Zamanidou Despoina Kothona Paris Fokaides Georgios C. Christoforidis Electrical & Computer Engineering Department Faculty of Engineering University of Western Macedonia Greece Faculty of Civil Engineering and Architecture Kaunas University of Technology Kaunas Lithuania

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

The European Union developed the Smart Readiness Indicator (SRI) to enhance energy efficiency and encourage the adoption of smart technologies in buildings, tackling their high energy usage and carbon emissions. This study evaluates the SRI methodology through the assessment of 20 diverse use cases, including residential and non-residential buildings, using Methods A and B of the SRI assessment scheme. Key variables such as climate zone, building type, year of construction, and the integration of smart-ready services were considered to ensure a comprehensive *** engineers assessed the buildings using the SRI EU Excel Tool and rated the methodology based on criteria including accuracy, usability, comprehensiveness, flexibility, and impact on decision-making. The results revealed high ratings for accuracy (45% rated as "Very Good" and 30% as "Excellent") and usability (50% rated as "Very Good"), while comprehensiveness was rated more moderately (40% "Good"). However, flexibility and adaptability emerged as areas requiring improvement, with 45% of assessments rated as "Fair." The SRI methodology demonstrated strong potential but requires further refinement to address the needs of diverse building types and more complex smart technologies. The study concludes that the SRI framework is a valuable tool for promoting energy efficiency and smart technology adoption across the EU building sector. However, additional research is recommended to integrate real-time data and automation technologies, and to enhance the framework's scalability and adaptability for future building systems.

关键词： Accuracy Automation Scalability Buildings Decision making Europe Solids Energy efficiency Real-time systems Usability

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Risk Management for 5G-Enabled Internet of Things by Using Machine Learning: A Survey

Risk Management for 5G-Enabled Internet of Things by Using M...

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ICT Conference (AICTC), Arab

作者： Aysha Alfaw Wael Elmedany Mhd Saeed Sharif College of Information Technology University of Bahrain Sakir Bahrain Department Computer Science and Digital Technologies School of Architecture Computing and Engineering London UEL UK

ISBN: (数字)9798350342086

ISBN: (纸本)9798350342093

Nowadays, there is a noticeable increase in the development and use of the Internet of Things(loT). With this rapid increase, IoT devices may face several challenges when used in the real world through applications. Using 5G with large numbers of Internet-connected devices of IoT puts many devices at risk and requires risk management. The growing of IoT leads to the growth of cyber-attackers and allow them to expose the vulnerabilities. This paper will present the risk management of 5G-enabled IoT technology and the use of machine learning to mitigate the risk and reduce the attacks on these technologies, and finding solutions through previous researches. This research aims to identify and eliminate potential risks in the IoT based 5G by machine learning. The paper also aims to present a solution to the security problems and risks faced when integrating the fifth-generation network and the Internet of Things. With 5G-enabled IoT, the risk management helps organizations use emerging technologies effectively while mitigating potential underlying risks such as security breaches, and data loss. Authentication,encryption, access control, and communication security are essential for making security. Machine learning algorithms have the potential to remove many obstacles to implementing the security of the Internet of Things, paving the door for the use of sophisticated technology like 5G. With new 5G networks, it is expected that the current IoT will be significantly expanded, which will improve cellular operations and the security of IoT, as well as push the future of the Internet to its edges. Machine learning (ML) creates a secure and intelligent system and provides a robust security mechanism and dynamic for 5G networks. Therefore, this time will also present previous solutions with machine learning against the risks to IoT and 5G. This paper will present a set of previous studies related to insurance of risk management for the 5G-enabled IoT, Which aims to find previ

关键词： Surveys Machine learning algorithms 5G mobile communication Insurance Machine learning Organizations Internet of Things Security Risk management Intelligent systems

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Investigating Context-Aware Collaborative Text Entry on Smartphones using Large Language Models 25

Investigating Context-Aware Collaborative Text Entry on Smar...

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Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

作者： Weihao Chen Yuanchun Shi Yukun Wang Weinan Shi Meizhu Chen Cheng Gao Yu Mei Yeshuang Zhu Jinchao Zhang Chun Yu Department of Computer Science and Technology Tsinghua University Beijing China Department of Computer Science and Technology Tsinghua University Beijing China and Qinghai University Xining Qinghai China School of Architecture Tsinghua University Beijing China Pattern Recognition Center WeChat AI Tencent Inc. Beijing China

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Improving social media use for disaster resilience: challenges and strategies

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International Journal of Digital Earth 2023年第1期16卷 3023-3044页

作者： Nina S.N.Lam Michelle Meyer Margaret Reams Seungwon Yang Kisung Lee Lei Zou Volodymyr Mihunov Kejin Wang Ryan Kirby Heng Cai Department of Environmental Sciences Louisiana State UniversityBaton RougeUSA Landscape Architecture and Urban Planning Texas A&M UniversityCollege StationUSA School of Information Studies Center for Computation and TechnologyLouisiana State UniversityBaton RougeUSA Division of Computer Science and Engineering Louisiana State UniversityBaton RougeUSA Department of Geography Texas A&M UniversityCollege StationUSA Escambia County Natural Resources Management PensacolaFloridaUSA

This paper develops a social media-disaster resilience analysis framework by categorizing types of social media use and their challenges to better understand and assess its role in disaster resilience research and *** framework is derived primarily from several case studies of Twitter use in three hurricane events in the United States-Hurricanes Isaac,Sandy,and *** paper first outlines four major contributions of social media data for disaster resilience research and management,which include serving as an effective communication platform,providing ground truth information for emergency response and rescue operations,providing information on people's sentiments,and allowing predictive ***,there are four_key challenges to its uses,which include,easy spreading of false information,social and geographical disparities of Twitter use,technical issues on processing and analyzing big and noisy data,especially on improving the locational accuracy of the tweets,and algorithm bias in Al and other types of ***,the paper proposes twenty strategies that the four sectors of the social media community-organizations,individuals,social media companies,and researchers-could take to improve social media use to increase disaster resilience.

关键词： Twitter use challenges and strategies disaster resilience social and geographical disparities emergency rescue Hurricane Isaac Hurricane Sandy Hurricane Harvey

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Energy-Time Profiling for Machine Learning Methods to EEG Classification 1st

Energy-Time Profiling for Machine Learning Methods to EEG Cl...

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1st International Conference on Bioengineering and Biomedical Signal and Image Processing, BIOMESIP 2021

作者： Gómez-López, Juan Carlos Escobar, Juan José González, Jesús Gil-Montoya, Francisco Ortega, Julio Burmester, Mike Damas, Miguel Department of Computer Architecture and Technology CITIC University of Granada Granada Spain Department of Engineering University of Almería Almería Spain Department of Computer Science Florida State University Tallahassee United States

ISBN: (纸本)9783030881627

The Electroencephalography discipline studies a type of signals called Electroencephalograms (EEGs), which represent the electrical activity of different parts of the brain. EEGs are composed of a massive number of features that could be used to create an intelligent recognition system. Nevertheless, the high number of available features difficult the correct classification of the signals as most of them do not contain relevant information. The use of Feature Selection (FS) techniques allows the reduction of the number of features by extracting a reduced but powerful feature subset. Afterwards, the problem can be addressed by using both the reduced features along with classification methods. In this sense, this work proposes a comparison of five supervised classifiers to solve an Electroencephalography problem in the context of Motor Imagery-based BCI tasks. The predictive models are evaluated in terms of classification rate and performance (execution time and energy consumption), with the idea of determining which alternative offers the best trade-off among all the objectives. © 2021, Springer Nature Switzerland AG.

关键词： Classification (of information)

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A Clustering-BIST Design for Inter-Layer Vias in 3D ICs Based on Walking Pattern Approach

TechRxiv

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TechRxiv 2023年

作者： Menbari, Ahmad Rahimi, Hemin Jahanirad, Hadi Ziener, Daniel The Department of Electrical Engineering University of Kurdistan Sanandaj Iran The Department of Computer Architecture and Embedded Systems Ilmenau University of Technology Ilmenau Germany

In the realm of 3D monolithic integrated circuits, inter-layer vias are prone to defects during fabrication, assembly, and operation that necessitates robust Built-In Self-Test solutions. This paper introduces an innovative BIST design aimed at the detection and localization of different types of faults in irregularly placed ILVs using a walking pattern methodology. In the proposed BIST methodology, the ILVs are clustered based on the fault occurrence probability distribution. Then, an effective detection approach is developed for all stuck-at faults, bridging faults, and almost all multiple faults in a single cluster. This approach allows designers to adjust different parameters such as fault coverage percentage, fault localization, and test time in alignment with specific requisites. The proposed BIST method reduces test configurations to two and test time to just 20 cycles by dividing ILVs into more clusters, overcoming a key limitation of recent approach. This methodology also demonstrates improved efficiency in terms of power consumption, area, and hardware utilization, particularly for large-scale benchmarks. For instance, when considering LU32PEENG and the scenario where ILVs are divided into 64 clusters, the power, area, and hardware overhead are 0.82% and 1.03%, and 1.14%, respectively. © 2023, CC BY.

关键词： Built-in self test

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DESIGNING AN ONLINE TRAINING MODULE TO DEVELOP VIRTUAL AND BLENDED INTERNATIONAL MODALITIES IN HIGHER EDUCATION 21

DESIGNING AN ONLINE TRAINING MODULE TO DEVELOP VIRTUAL AND B...

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21st International Conferences on Mobile Learning, ML 2025 and 10th International Conference on Educational Technologies, ICEduTech 2025

作者： Barana, Alice Chatzea, Vasiliki Eirini Henao, Kelly Hildebrandt, Ania Maria Conte, Marina Marchisio Samoilovich, Daniel Triantafyllidis, Georgios Vidakis, Nikolas Department of Molecular Biotechnology and Health Sciences University of Turin Piazza Nizza 44 Torino10153 Italy Department of Electrical & Computer Engineering Hellenic Mediterranean University Estavromenos Heraklion71410 Greece Columbus Association 1 rue Moillis Paris75015 France Department of Architecture Design and Media Technology Aalborg University A. C. Meyers Vænge Copenhagen152450 Denmark

ISBN: (纸本)9789898704665

Virtual and blended international collaboration activities, including Collaborative Online International Learning and Blended Intensive Programmes, offer inclusive and sustainable alternatives to traditional mobility programmes. Effective training programmes for teachers and administrative staff are indispensable to enhance the higher education institutions’ capability to implement similar activities. This paper introduces an online training module aimed at providing higher education teachers and staff with competencies to implement virtual and blended modalities of international collaboration. The module is designed according to the principles of the Self-Determination Theory and the Analysis, Design, Development, Implementation and Evaluation (ADDIE) model. The paper explores whether the design of the module is effective in creating a valuable learning experience and what its strengths and areas for improvement are. Results were derived from 150 responses to the final survey questions completed by participants who completed the online training module, analysed qualitatively and quantitatively. Findings show that the autonomy, structure, and involvement support were perceived as effective in achieving the desired learning outcomes. The results offer valuable insights into the design of training modules for higher education staff to develop international collaboration modalities. © 2025 Proceedings of the International Conferences on Mobile Learning 2025 and Educational Technologies 2025. All rights reserved.

关键词： Virtual environments

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Modelling Exchange with Blockchain for the Collaborative Design of a Building Envelope in BIM

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Open Construction and Building technology Journal 2024年 18卷

作者： Hsu, Chih Lin Wang, Jui Tang Xie, Huang Jun Department of Architecture National Taiwan University of Science and Technology Taipei Taiwan Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei Taiwan

Introduction: The main challenge in using building information modelling (BIM) is the centralised collaborative framework in the various design software (e.g., AutoCAD, Revit, RHINO, and ArchiCAD) used by professionals across various disciplines, which causes difficulties during data exchange. Methods: The existing framework may increase the project lead time, require more effort, and result in design conflicts and misunderstandings. Thus, this paper has proposed a dynamic information storage with blockchain system (DISBS) using a physical curtain wall project for practical implementation. In addition, this paper has further discussed the linkages and verified and analysed the effectiveness of the proposed methodology. Results: Through the DISBS proposed in this research, the characteristics and achievable functions of blockchain technology are presented. Various applications for the field of construction engineering are highly developable within this research. Conclusion: The DISBS can improve not only the management quality of construction projects, but also promote mutual trust in the construction industry and optimize architecture, engineering, and construction (AECO) productivity. © 2024 The Author(s).

关键词： AECO architecture Blockchain Construction DISBS Engineering Physical curtain

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Towards understanding digital support contributing to climate neutral, inclusive, and beautiful cities: A systematic literature review

Towards understanding digital support contributing to climat...

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International Workshop on Green and Sustainable Software (GREENS)

作者： Alicia JW Takaoka Dirk Ahlers Ferdinand Ward Ådlandsvik Eivind Syrdalen Dovland Letizia Jaccheri Department of Computer Science Norwegian University of Science and Technology (NTNU) Trondheim Norway Department of Architecture and Planning Norwegian University of Science and Technology (NTNU) Trondheim Norway

Climate change is an existential threat to Europe and the world, and is impacting and influencing people. At the same time, the urbanization of the world is increasing, meaning that these challenges need to be solved mainly in cities. Cities are also increasingly using digital technologies to become smarter, which will be a crucial part of the future cities. The EU has initiated the European Green Deal in order to overcome these challenges, and to make Europe the first climate neutral continent by 2050. A part of this is the EU Cities Mission aiming for climate-neutral transitions in frontrunner cities by 2030. The EU-funded project Creating Actionable Futures (CrAFt) bridges these ambitions with the New European Bauhaus principles, to ensure that climate-neutral transitions in cities will be sustainable, inclusive, and beautiful. This systematic literature review was performed to understand digital tools in this specific context.

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Totipotent Neural Controllers for Modular Soft Robots: Achieving Specialization in Body-Brain Co-Evolution Through Hebbian Learning

SSRN

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SSRN 2024年

作者： Ferigo, Andrea Iacca, Giovanni Medvet, Eric Nadizar, Giorgia Department of Information Engineering and Computer Science University of Trento Italy Department of Engineering and Architecture University of Trieste Italy Department of Mathematics and Geosciences University of Trieste Italy Department of Information and Communication Technology

Multi-cellular organisms typically originate from a single cell, the zygote, that then develops into a multitude of structurally and functionally specialized cells. The potential of generating all the specialized cells that make up an organism is referred to as cellular "totipotency", a concept introduced by the German plant physiologist Haberlandt in the early 1900s. In an attempt to reproduce this mechanism in synthetic organisms, we present a model based on a kind of modular robot called Voxel-based Soft Robots (VSRs), where both the body, i.e., the arrangement of voxels, and the brain, i.e., the Artificial Neural Network (ANN) controlling each module, are subject to an evolutionary process aimed at optimizing the locomotion capabilities of the robot. In an analogy between totipotent cells and totipotent ANN-controlled modules, we then include in our model an additional level of adaptation provided by Hebbian learning, which allows the ANNs to adapt their weights during the execution of the locomotion task. Our in silico experiments reveal two main findings. Firstly, we confirm the common intuition that Hebbian plasticity effectively allows better performance and adaptation. Secondly and more importantly, we verify for the first time that the performance improvements yielded by plasticity are in essence due to a form of specialization at the level of single modules (and their associated ANNs): thanks to plasticity, modules specialize to react in different ways to the same set of stimuli, i.e., they become functionally and behaviorally different even though their ANNs are initialized in the same way. This mechanism, which can be seen as a form of totipotency at the level of ANNs, can have, in our view, profound implications in various areas of AI and applications thereof, such as modular robotics and multi-agent systems. © 2024, The Authors. All rights reserved.

关键词： Neural networks

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