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The Digital Twin City in Enhancing Flood Evacuation Systems: Future Opportunities and Challenges

IEEE Access 2025年 13卷 32371-32383页

作者： Setijadi Prihatmanto, Ary Prasetyadi, Abdurrakhman Yoganingrum, Ambar Sutriadi, Ridwan Hadiana, Ana Bandung Institute of Technology School of Electrical and Informatics Engineering Bandung40132 Indonesia National Research and Innovation Agency Research Center for Data and Information Science Bandung40231 Indonesia Bandung Institute of Technology School of Architecture Planning and Policy Development Bandung40132 Indonesia

In recent decades, the increasing frequency and severity of natural disasters have necessitated the development of more effective disaster management systems. This paper explores the potential of digital twin technology to enhance flood evacuation systems. A digital twin-city model can simulate urban environments, predict flood inundation, and identify optimal evacuation routes in real-time. The study conducts a systematic literature review to assess current advancements, evaluating the integration of 3D city models, artificial intelligence, and Internet of things sensors in flood evacuation planning. Results indicate that digital twin technology significantly improves predictive capabilities and evacuation efficiency, although data integration, model accuracy, and computational demands remain. Future research should focus on enhancing data integration, refining simulation models, improving predictive analytics, developing advanced visualization tools, and validating models across diverse environments to ensure reliability and effectiveness. © 2025 The Authors.

关键词： Digital elevation model

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RoLargeSum: A Large Dialect-Aware Romanian News Dataset for Summary, Headline, and Keyword Generation 31

RoLargeSum: A Large Dialect-Aware Romanian News Dataset for ...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Avram, Andrei-Marius Timpuriu, Mircea Iuga, Andreea Matei, Vlad-Cristian Tăiatu, Iulian-Marius Găină, Tudor Cercel, Dumitru-Clementin Pop, Florin Cercel, Mihaela-Claudia National University of Science and Technology POLITEHNICA Bucharest Romania Paris 1 Panthéon-Sorbonne University Paris France University of Bucharest Bucharest Romania National Institute for Research and Development in Informatics - ICI Bucharest Romania

ISBN: (纸本)9798891761964

Using supervised automatic summarisation methods requires sufficient corpora that include pairs of documents and their summaries. Similarly to many tasks in natural language processing, most of the datasets available for summarization are in English, posing challenges for developing summarization models in other languages. Thus, in this work, we introduce RoLargeSum, a novel large-scale summarization dataset for the Romanian language crawled from various publicly available news websites from Romania and the Republic of Moldova that were thoroughly cleaned to ensure a high-quality standard. RoLargeSum contains more than 615K news articles, together with their summaries, as well as their headlines, keywords, dialect, and other metadata that we found on the targeted websites. We further evaluated the performance of several BART variants and open-source large language models on RoLargeSum for benchmarking purposes. We manually evaluated the results of the best-performing system to gain insight into the potential pitfalls of this data set and future development. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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Models for Network Traffic Behavioral Analysis in IoT Systems

Models for Network Traffic Behavioral Analysis in IoT System...

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23rd International Conference on informatics in Economy, IE 2024

作者： Zamfiroiu, Alin Floroiu, Iustin Savu, Daniel Bătăgan, Lorena Ghai, Anupriya Sharma National Institute for Research & Development in Informatics Bucharest Romania Bucharest University of Economic Studies Bucharest Romania School of Computing Graphic Era Hill University Dehradun India

ISBN: (纸本)9789819601608

In today's interconnected world, the proliferation of Internet of Things (IoT) devices has revolutionized the way we interact with technology. From smart homes and wearable devices to industrial sensors and autonomous vehicles, IoT systems have permeated nearly every aspect of our daily lives. However, with this exponential growth in IoT adoption comes a host of challenges, particularly concerning the security and performance of these interconnected networks. One of the key methodologies employed to address these challenges is network traffic behavioral analysis. Moreover, network traffic behavioral analysis plays a crucial role in threat intelligence and incident response. By aggregating and analyzing network data over time, organizations can identify recurring attack patterns and indicators of compromise. This rich contextual information enhances their ability to anticipate and preempt future cyber threats. Additionally, in the event of a security incident, network traffic analysis provides invaluable forensic evidence, allowing investigators to reconstruct the sequence of events, attribute responsibility, and mitigate the impact of the breach. In this paper, we propose some models for the network traffic generated by sensors and actuators in IoT systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Computer forensics

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Design of Network Environment Advertisable Multipath Transmission Control System for Mobile Device Support 5

Design of Network Environment Advertisable Multipath Transmi...

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5th Asia Conference on Information Engineering, ACIE 2025

作者： Kitagawa, Naoya Kashiwagi, Takehiko Ohshima, Kohta National Institute of Informatics Research and Development Center for Academic Networks Tokyo Japan The University of Electro-Communications Parallel Networks LLC. Tokyo Japan Tokyo University of Marine Science and Technology Marine Electromechanical Engineering Division Tokyo Japan

ISBN: (纸本)9798331528409

Uninterrupted wireless communication on the move is important for remote drone/robot operation, self-driving cars, and maritime autonomous surface ships. This paper describes a functional extension design of our previously developed fieldprogrammable gate array (FPGA)-based multipath transmission control system. The new network environment advertisable method uses the Wi-Fi round-trip time (RTT) and low-power wide-area (LPWA) networks to address the issue of not knowing whether handover is possible until the device is in motion, because Wi-Fi AP scanning is limited to the wireless communication range. We show how to apply the method to the hardware that we previously developed and its practical applicability through performance evaluation of Wi-Fi RTT and LPWA communication. © 2025 IEEE.

关键词： Field programmable gate arrays (FPGA)

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LaVCa: LLM-assisted Visual Cortex Captioning

arXiv

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arXiv 2025年

作者： Matsuyama, Takuya Nishimoto, Shinji Takagi, Yu Osaka University Japan National Institute of Information and Communications Technology Japan National Institute of Informatics Research and Development Center for Large Language Models Japan

Understanding the property of neural populations (or voxels) in the human brain can advance our comprehension of human perceptual and cognitive processing capabilities and contribute to developing brain-inspired computer models. Recent encoding models using deep neural networks (DNNs) have successfully predicted voxel-wise activity. However, interpreting the properties that explain voxel responses remains challenging because of the black-box nature of DNNs. As a solution, we propose LLM-assisted Visual Cortex Captioning (LaVCa), a data-driven approach that uses large language models (LLMs) to generate natural-language captions for images to which voxels are selective. By applying LaVCa for image-evoked brain activity, we demonstrate that LaVCa generates captions that describe voxel selectivity more accurately than the previously proposed method. Furthermore, the captions generated by LaVCa quantitatively capture more detailed properties than the existing method at both the inter-voxel and intra-voxel levels. Furthermore, a more detailed analysis of the voxel-specific properties generated by LaVCa reveals fine-grained functional differentiation within regions of interest (ROIs) in the visual cortex and voxels that simultaneously represent multiple distinct concepts. These findings offer profound insights into human visual representations by assigning detailed captions throughout the visual cortex while highlighting the potential of LLM-based methods in understanding brain representations. Please check out our webpage at https://***/view/lavca-llm/. © 2025, CC BY.

关键词： Deep neural networks

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A Cross-Lingual Meta-Learning Method Based on Domain Adaptation for Speech Emotion Recognition 25th

A Cross-Lingual Meta-Learning Method Based on Domain Adapta...

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25th International Conference on Web Information Systems Engineering, WISE 2024

作者： Ion, David-Gabriel Smădu, Răzvan-Alexandru Cercel, Dumitru-Clementin Pop, Florin Cercel, Mihaela-Claudia Faculty of Automatic Control and Computers National University of Science and Technology Politehnica Bucharest Bucharest Romania National Institute for Research and Development in Informatics - ICI Bucharest Bucharest Romania Academy of Romanian Scientists Bucharest Romania Paris 1 Panthéon-Sorbonne University Paris France University of Bucharest Bucharest Romania

ISBN: (纸本)9789819605781

Best-performing speech models are trained on large amounts of data in the language they are meant to work for. However, most languages have sparse data, making training models challenging. This shortage of data is even more prevalent in speech emotion recognition. Our work explores the model’s performance in limited data, specifically for speech emotion recognition. Meta-learning specializes in improving the few-shot learning. As a result, we employ meta-learning techniques on speech emotion recognition tasks, accent recognition, and person identification. To this end, we propose a series of improvements over the multistage meta-learning method. Unlike other works focusing on smaller models due to the high computational cost of meta-learning algorithms, we take a more practical approach. We incorporate a large pre-trained backbone and a prototypical network, making our methods more feasible and applicable. Our most notable contribution is an improved fine-tuning technique during meta-testing that significantly boosts the performance on out-of-distribution datasets. This result, together with incremental improvements from several other works, helped us achieve accuracy scores of 83.78% and 56.30% for Greek and Romanian speech emotion recognition datasets not included in the training or validation splits in the context of 4-way 5-shot learning. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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Real-Time Two-Stage Detection and Mitigation System for DDoS Attacks in SDN 5

Real-Time Two-Stage Detection and Mitigation System for DDoS...

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5th Asia Conference on Information Engineering, ACIE 2025

作者： Sato, Jumpei Ohshima, Kohta Kitagawa, Naoya Graduate School of Marine Science and Technology Tokyo University of Marine Science and Technology Tokyo Japan Tokyo University of Marine Science and Technology Marine Electromechanical Engineering Division Tokyo Japan National Institute of Informatics Research and Development Center for Academic Networks Tokyo Japan

ISBN: (纸本)9798331528409

In this study, we propose a two-stage anomaly detection system aimed at real-time detection and mitigation of distributed denial of service (DDoS) attacks within Software Defined Networking (SDN). In the first stage, lightweight, threshold-based detection is performed on edge switches to quickly identify abnormal traffic. This detected anomalous traffic is reported to an SDN controller. Then, in the second stage, detailed analysis using a convolutional neural network-long short-term memory (CNN-LSTM) model optimized for time-series data, is conducted. This approach effectively distributes the load of the SDN controller, which handles both route control and anomaly detection. In addition, it enables high-precision anomaly detection. For traffic deemed anomalous, a mitigation strategy involving bandwidth throttling is applied to achieve rapid traffic control. Compared with existing methods, the proposed system improves both detection accuracy and mitigation efficiency, contributing to enhanced security in real SDN environments. © 2025 IEEE.

关键词： Convolutional neural networks

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Sleeping Multi-Armed Bandit-Based Path Selection in Space-Ground Semantic Communication Networks

Sleeping Multi-Armed Bandit-Based Path Selection in Space-Gr...

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IEEE Conference on Wireless Communications and Networking

作者： Hanlu Wu Yang Xu Shouxin Cao Jia Liu Hiroki Takakura Shiratori Norio School of Computer Science and Technology Xidian University Xi'an China Center for Strategic Cyber Resilience Research and Development National Institute of Informatics Tokyo Japan Research and Development Initiative Chuo University Tokyo Japan

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Semantic communication, an emerging AI-driven communication paradigm, offers great potential for multimodal data delivery in space-ground integrated networks (SGINs). However, the dynamic nature of SGINs presents severe challenges for path selection, making it difficult to ensure the quality of service (QoS) at the semantic level. To this end, we propose in this paper a novel path selection scheme in space-ground multimodal semantic communication networks based on the sleeping multi-armed bandit (MAB) approach. Specifically, we first model the approximate semantic entropy and semantic rate, formulating an optimal path selection problem that integrates link state information and semantic data transmission volume. Then, we convert the path selection problem into a sleeping MAB problem and meticulously design an upper confidence bound (UCB)-based algorithm to solve it, called Periodic Probability Sleeping Path Selection (PPSPS), which copes with the dynamic feature of SGINs. We further theoretically verify the bounded regret of the PPSPS algorithm, indicating that it can ensure good semantic communication QoS. Simulation results demonstrate the superiority of the proposed path selection scheme compared to traditional reinforcement learning methods.

关键词： Solid modeling Upper bound Heuristic algorithms Simulation Quality of service Reinforcement learning Semantic communication Entropy Data models Data communication

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Complexity of computing the anti-Ramsey numbers for paths

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Theoretical Computer Science 2025年 1044卷

作者： Akhoondian Amiri, Saeed Popa, Alexandru Roghani, Mohammad Shahkarami, Golnoosh Soltani, Reza Vahidi, Hossein University of Cologne Cologne Germany University of Bucharest Romania National Institute of Research and Development in Informatics Bucharest Romania MPI for Informatics Saarland Informatics Campus Saarbrücken Germany Sharif University of Technology Tehran Iran Saarbrücken Graduate School of Computer Science Saarbrücken Germany

The anti-Ramsey numbers are a fundamental notion in graph theory, introduced in 1978, by Erdős, Simonovits and Sós. For given graphs G and H the anti-Ramsey number ar(G,H) is defined to be the maximum number k such that there exists an assignment of k colors to the edges of G in which every copy of H in G has at least two edges with the same color. Usually, combinatorists study extremal values of anti-Ramsey numbers for various classes of graphs. There are works on the computational complexity of the problem when H is a star. Along this line of research, we study the complexity of computing the anti-Ramsey number ar(G,Pk), where Pk is a path of length k. First, we observe that when k is close to n (the number of vertices in G), the problem is hard;hence, the challenging part is the computational complexity of the problem when k is a fixed constant. We provide a characterization of the problem for paths of constant length. Our first main contribution is to prove that computing ar(G,Pk) for every integer k≥3 is NP-hard. We obtain this by providing several structural properties of such coloring in graphs. We also study the exact complexity of the precolored version and show that there is no subexponential algorithm for the problem unless ETH fails for any fixed constant k. © 2025 The Author(s)

关键词： NP-hard

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MANUFACTURING DEFECTS, INTERFACIAL ADHESION, IMPACT AND WATER ABSORPTION PROPERTIES OF HYBRID POLYESTER COMPOSITE IN BOAT CONSTRUCTION

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Archives of Metallurgy and Materials 2025年第1期70卷 461-466页

作者： Jusoh, S.M. Ghazali, C.H.M.R. Nik, W.N.W. Zulkifli, M.F.R. Abdullah, S. Mustapha, R. Abdan, K. Radzi, F.S.M. Zainulabidin, S.H. Rosli, M.H. Sandu, A.V. UNIVERSITI MALAYSIA TERENGGANU FACULTY OF OCEAN ENGINEERING TECHNOLOGY AND INFORMATICS KUALA NERUS TERENGGANU21030 Malaysia UNIVERSITI MALAYSIA TERENGGANU MARINE MATERIALS RESEARCH GROUP FACULTY OF OCEAN ENGINEERING TECHNOLOGY AND INFORMATICS KUALA NERUS TERENGGANU21030 Malaysia SELANGOR SERDANG43400 Malaysia UNIVERSITI PUTRA MALAYSIA FACULTY OF ENGINEERING DEPARTMENT OF BIOLOGICAL AND AGRICULTURAL ENGINEERING SELANGOR SERDANG43400 Malaysia GHEORGHE ASACHI TECHNICAL UNIVERSITY OF LASI FACULTY OF MATERIAL SCIENCE AND ENGINEERING 41D. MANGERON ST. LASI700050 Romania ROMANIAN INVENTORS FORUM STR. SF. P. MOVILA 3 LASI700089 Romania NATIONAL INSTITUTE FOR RESEARCH AND DEVELOPMENT FOR ENVIRONMENTAL PROTECTION INCDPM 294 SPLAIUL INDEPENDENTEI BUCHAREST060031 Romania

Fibre composite boat construction industry is one of the largest industries that greatly contributes to most of the countries' economies. Synthetic fibre composite like fibreglass is widely used in making the composite boat hull. The use of fibreglass is costly and it gives a huge effect on the environmental pollution. Nowadays, the green fibres have growth as a demand in hull construction and another industry, because of their light mass, great relative mechanical properties, and more advantages to the fibreglass. The demand for boat from green hybrid materials has gone in striking. Green hybrid materials, like any other composite components used in industries, went through the process of incorporating the reinforcement which is the natural fibre into composite or matrix. All imperfections such as voids, area where resin has unevenly wetted the fibre and misaligned fibres have been determined using non-destructive techniTue (NDT) namely Infrared Thermal (IR) imaging techniTue. Then composite specimens were observed via the Scanning Electron Microscopy (SEM). SEM micrograph had been validated the results of IR thermal imaging, impact test and water absorption by following ASTM D6110 and ASTM D570 standard respectively. 45% of the woven kenaf/glass fibre to polyester determines the highest impact properties of 542.22 kJ/m2 and shows the least percentage of moisture absorption at the same time showing the greatest water resistance for the composite material. The defects and interfacial adhesion were observed on the specimen by IR thermal imaging and SEM techniTue. It was revealed that 45% of the woven kenaf/glass fibre to polyester demonstrated less manufacturing defects and possessed a good interfacial adhesion, while 60% of the woven kenaf/glass fibre to polyester showed the highest manufacturing defects. The conseTuence of fibre contents had crucial effect towards manufacturing defects and interfacial adhesion of composite testing coupon. As conclusion, the specime

关键词： Thermography (imaging)

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