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Urban Governance 2025年第1期5卷 1-19页

作者： Hossain, Sk Tahsin Yigitcanlar, Tan Nguyen, Kien Xu, Yue City 4.0 Lab School of Architecture and Built Environment Queensland University of Technology 2 George Street Brisbane 4000 QLD Australia School of Electrical Engineering and Robotics Queensland University of Technology 2 George Street Brisbane 4000 QLD Australia School of Computer Science Queensland University of Technology 2 George Street Brisbane 4000 QLD Australia

Cybersecurity has emerged as a critical concern in modern urban governance, as local governments now extend their responsibilities beyond traditional infrastructure management to safeguard digital systems and citizen data in increasingly digitised smart city environments. Despite the importance of robust cybersecurity measures, there is a concerning gap—i.e., local governments often exhibit a cybersecurity posture that is inadequately prepared to counter the rising cyber threats. This discrepancy underscores the urgency for a comprehensive understanding of the challenges restricting effective cybersecurity in local governmental settings. This paper aims to elucidate these challenges of local governments in a structured framework utilising a systematic literature review method named the PRISMA protocol. The findings reveal that the stakes are high when it comes to cybersecurity for local governments, with the key challenges being financial resource constraints, technological vulnerabilities, human factors, and the regulatory framework. This study recommends improving interdepartmental coordination, adopting relevant policies, and executing targeted cybersecurity training to address these challenges. The study also highlights unconventional approaches to mitigate financial and skill resource limitations, including the utilisation of open-source security tools, outsourcing specific cybersecurity functions, and establishing collaborations with local cybersecurity agencies, academic institutions, and the private sector to obtain expertise and advanced resources. Overall, this study offers valuable insights into the critical cybersecurity challenges faced by local governments and provides specific recommendations, equipping urban policymakers, administrators, and researchers with valuable guidance to enhance cybersecurity resilience within this critical yet understudied research domain. © 2024 The Author(s)

关键词： Cyber threat Cybersecurity Local government Municipality Smart city Urban governance

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Platform Urbanism for Resident Safety: A Real-Time Predictive Microclimate Risk Monitoring and Alert System

SSRN

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SSRN 2025年

作者： Hossain, Sk Tahsin Yigitcanlar, Tan Nguyen, Kien Xu, Yue City 4.0 Lab School of Architecture and Built Environment Queensland University of Technology 2 George Street BrisbaneQLD4000 Australia School of Electrical Engineering and Robotics Queensland University of Technology 2 George Street BrisbaneQLD4000 Australia School of Computer Science Queensland University of Technology 2 George Street BrisbaneQLD4000 Australia

Urban microclimates significantly impact public health, liveability, and emergency preparedness, yet traditional weather alert systems often rely on centralised data that fails to capture the spatial variability of conditions within cities. This study presents an innovative platform that integrates ArcGIS GeoEvent Server with AIoT-driven predictive analytics to deliver hyper-localised weather alerts. The platform’s adaptable design enables the incorporation of location-specific AI/ML-based predictive models and context-aware notifications, tailored to at-risk populations based on their location, health conditions, and disabilities. Featuring three GeoEvent Services and two ArcGIS Notebook Schedules, the system facilitates real-time data ingestion, processing, predictive modelling, and dissemination. A case study in Brisbane, Australia, demonstrates its capacity to address microclimatic variability, revealing significant differences in thermal stress and precipitation patterns across suburbs. Unlike traditional city-wide alerts, the platform provides targeted notifications prioritising vulnerable groups such as children, the elderly, and individuals with chronic conditions or disabilities. This approach enhances urban resilience and offers a scalable framework for applications in health monitoring, emergency response, and public safety. © 2025, The Authors. All rights reserved.

关键词： Emergency services

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Self-Adjusting Network Slicing for Dynamic Heterogeneous Task Offloading in UAV-Enabled Mobile Edge Computing

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Li, Xulong Mao, Wencan Xu, Xinyi Liu, Yaxi Zhang, Huifeng Huangfu, Wei Long, Keping University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China National Institute of Informatics Information Systems Architecture Science Research Division Tokyo101-8430 Japan Zhejiang Lab Hangzhou311500 China

Unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) has received wide attention for its ability to significantly reduce latency with flexible mobile aerial nodes. However, the existing works merely consider a fixed periodic network slicing and usually neglect the characterization of computing tasks in practical applications. Motivated by this, we envision a novel scenario where the dynamics and heterogeneity of users and tasks are considered in UAV-enabled MEC networks. We propose a novel self-adjusting two-timescale network slicing scheme based on the internal mechanism in deep reinforcement learning (DRL) to automatically determine whether and when network slicing needs to be reconstructed. Such a novel scheme balances reconstruction cost and system performance compared with traditional fixed schemes. We build an optimization to minimize total system cost for joint UAV trajectory planning and resource allocation at both network and user slice levels. To tackle this problem, we design a novel self-adjusting two-timescale proximal policy optimization (PPO) algorithm that utilizes the property of the critic network, referred to as SaTPPO. Experiment results manifest the effectiveness of the proposed SaTPPO, and it has a lower system cost than the traditional fixed schemes. Moreover, the proposed SaTPPO outperforms the state-of-the-art baselines concerning effectiveness and efficiency. © 2015 IEEE.

关键词： Micro air vehicle (MAV)

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Underwater Perception and Autonomous Operation for Underwater Vehicle-Manipulator Systems: Methodology and Experiment

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IEEE/ASME Transactions on Mechatronics 2025年

作者： Jiang, Chaicheng Xiong, Xinyang Xiang, Xianbo Zeng, Zhigang Zhang, Fumin Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan 430074 China Huazhong University of Science and Technology School of Naval Architecture and Ocean Engineering Wuhan 430074 China Huazhong University of Science and Technology School of Naval Architecture and Ocean Engineering School of Artificial Intelligence and Automation State Key Lab of Intelligent Manufacturing Equipment and Technology Wuhan 430074 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control The Education Ministry of China Wuhan 430074 China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Hong Kong Hong Kong

Camera-equipped underwater vehicle-manipulator systems (UVMS) can achieve autonomous underwater operations through visual servoing. However, current methods excessively rely on auxiliary means for target's visual information and do not sufficiently consider the target's pose when designing visual servoing schemes. As a result, UVMS can only perform dynamic positioning or grasp simple-shaped targets like sea urchins. In this article, we are devoted to making the UVMS autonomously complete more complex underwater operations, such as valve switching and pipe handling. First, an underwater target perception system is proposed to address the issue of discontinuous target position estimation caused by various interferences. Second, a deep neural network-based grasping mechanism controller is proposed to enable the manipulator to grasp targets in various initial poses using the target image. Third, a decoupled visual servoing scheme is proposed for the motion control of the UVMS, and in collaboration with a designed task supervisor to ensure that the UVMS can complete the underwater operation autonomously. To validate the effectiveness of the proposed methods, underwater experiments are conducted based on a UVMS prototype. The UVMS succeeds to autonomously switch different types of valves and handle the pipe. Experiments conducted under dynamic currents validated the reliability and robustness of the proposed methods. © 1996-2012 IEEE.

关键词： Autonomous underwater operations deep neural network underwater vehicle-manipulator systems (UVMS) visual perception visual servoing

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Integrating Simulation and AI for Optimal Electric Vehicle Charging Infrastructure: Achievements and Future Directions 16th

Integrating Simulation and AI for Optimal Electric Vehicle...

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16th EAI International Conference on Simulation Tools and Techniques, SIMUTools 2024

作者： Guisado-Lizar, José-Luis Ragel-Díaz-Jara, David Navas-Orozco, Antonio Morera-Figueroa, José Diaz-del-Rio, Fernando Morón-Fernández, María José Cerezuela-Escudero, E. Cardenas-Montes, Miguel Jiménez-Moreno, Gabriel Department of Computer Architecture and Technology Universidad de Sevilla Avenida Reina Mercedes s/n Sevilla41012 Spain I3US Research Institute Universidad de Sevilla Seville Spain SCORE Lab Universidad de Sevilla Seville Spain CIEMAT Centro Inv. Energéticas Medioambientales y Tecnológicas Madrid Spain

ISBN: (纸本)9783031873447

Electric vehicles (EVs) are the most prominent technology for reducing road transport emissions. Their rapid adoption necessitates efficient deployment of charging infrastructure. This study presents works in progress in an innovative approach integrating simulation and artificial intelligence (AI) to optimize EV charging station placement. We develop a microscopic traffic simulation model combining cellular automata and agent-based techniques to capture the dynamic interactions between vehicles, charging stations, and urban environments. Genetic algorithms and neural networks are employed to navigate the complex solution space and identify optimal configurations. The model considers multiple factors including traffic patterns, air quality, grid impacts, and urban mobility. The objective of this holistic approach is to improve charging infrastructure planning, leading to reduced congestion, lower emissions, and enhanced urban mobility. We discuss achievements to date and outline future research directions. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Genetic algorithms

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Joint high-resolution feature learning and vessel-shape aware convolutions for efficient vessel segmentation

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computers in Biology and Medicine 2025年 191卷 109982-109982页

作者： Zhang, Xiang Zhu, Qiang Hu, Tao Guo, Song Bian, Genqing Dong, Wei Hong, Rao Lin, Xia Ling Wu, Peng Zhou, Meili Yan, Qingsen Mohi-ud-din, Ghulam Ai, Chen Li, Zhou College of Information and Control Engineering Xi'an University of Architecture and Technology Xi'an China Shaanxi Provincial Key Lab of Bigdata of Energy and Intelligence Processing School of Physics and Electronic Information Yanan University Yanan China School of Computer Science and Engineering Northwestern Polytechnical University Xi'an China School of Software Nanchang University Nanchang China School of Cyber Security Zhejiang University Hangzhou China Department of Basic Education and Research Jiangxi Police College Nanchang China Northwestern Polytechnical University China

Clear imagery of retinal vessels is one of the critical shreds of evidence in specific disease diagnosis and evaluation, including sophisticated hierarchical topology and plentiful-and-intensive capillaries. In this work, we propose a new topology- and shape-aware model named Multi-branch Vessel-shaped Convolution Network (MVCN) to adaptively learn high-resolution representations from retinal vessel imagery and thereby capture high-quality topology and shape information thereon. Two steps are involved in our pipeline. The former step is proposed as Multiple High-resolution Ensemble Module (MHEM) to enhance high-resolution characteristics of retinal vessel imagery via fusing scale-invariant hierarchical topology thereof. The latter is a novel vessel-shaped convolution that captures the retinal vessel topology to emerge from unrelated fundus structures. Moreover, our MVCN of separating such topology from the fundus is a dynamical multiple sub-label generation via using epistemic uncertainty, instead of manually separating raw labels to distinguish definitive and uncertain vessels. Compared to other existing methods, our method achieves the most advanced AUC values of 98.31%, 98.80%, 98.83%, and 98.65%, and the most advanced ACC of 95.83%, 96.82%, 97.09%,and 96.66% in DRIVE, CHASE_DB1, STARE, and HRF datasets. We also employ correctness, completeness, and quality metrics to evaluate skeletal similarity. Our method's evaluation metrics have doubled compared to previous methods, thereby demonstrating the effectiveness thereof. © 2025 Elsevier Ltd

关键词： Ophthalmology

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Prevention from Soft Errors via architecture Elasticity

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Journal of computer Science & technology 2014年第2期29卷 247-254页

作者：尹一笑陈云霁郭崎陈天石 State Key Lab of Computer Architecture and Microprocessor Research Center Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Loongson Technology Corporation Limited IBM Research-China

Due to the decreasing threshold voltages, shrinking feature size, as well as the exponential growth of on-chip transistors, modern processors are increasingly vulnerable to soft errors. However, traditional mechanisms of soft error mitigation take actions to deal with soft errors only after they have been detected. Instead of the passive responses, this paper proposes a novel mechanism which proactively prevents from the occurrence of soft errors via architecture elasticity. In the light of a predictive model, we adapt the processor architectures h01istically and dynamically. The predictive model provides the ability to quickly and accurately predict the simulation target across different program execution phases on any architecture configurations by leveraging an artificial neural network model. Experimental results on SPEC CPU 2000 benchmarks show that our method inherently reduces the soft error rate by 33.2% and improves the energy efficiency by 18.3% as compared with the static configuration processor.

关键词： soft error energy efficiency architecture elasticity

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Prevention flow-control for low latency torus networks-on-chip 11

Prevention flow-control for low latency torus networks-on-ch...

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Proceedings of the Fifth ACM/IEEE International Symposium on Networks-on-Chip

作者： Joshi, Arpit Mutyam, Madhu Computer Architecture and Systems Lab. Department of Computer Science and Engineering Indian Institute of Technology Madras India

ISBN: (纸本)9781450307208

The challenge for on-chip networks is to provide low latency communication in a very low power budget. To reduce the latency and keep the simplicity of a mesh network, torus network is proposed. As torus networks have inherent circular dependency, additional effort is needed to prevent deadlock, even if deadlock free routing algorithms are used. We describe a novel flow-control mechanism to address cost/performance constraints in torus networks and ensure freedom from deadlock. Flow-control is achieved using a prevention mechanism which uses virtual cut-through switching, and deadlock freedom is achieved by considering only a single packet buffer per input port. We can simplify the router design by having a simple switch allocator, which prioritizes in-flight packets, and a single packet buffer per input port, which eliminates the need for virtual channels. Experimental validation reveals that our design achieves significant improvement in throughput, as compared to the traditional design, using significantly fewer buffers. © 2011 ACM.

关键词： Flow control

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A MAPLE PACKAGE OF AUTOMATED DERIVATION OF HOMOTOPY ANALYSIS SOLUTION FOR PERIODIC NONLINEAR OSCILLATIONS

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Journal of Systems Science & Complexity 2012年第3期25卷 594-616页

作者： Yinping LIU Shijun LIAO Zhibin LI Department of Computer Science and Technology East China Normal University State Key Lab of Ocean Engineering School of Naval ArchitectureOcean and Civil EngineeringDepartment of MathematicsShanghai Jiaotong University Department of Computer Science East China Normal University

Based on the homotopy analysis method, a general analytic technique for strongly nonlinear problems, a Maple package of automated derivation （ADHO） for periodic nonlinear oscillation systems is presented. This Maple package is valid for periodic oscillation systems in rather general, and can automatically deliver the accurate approximations of the frequency co and the mean of motion δof a nonlinear periodic oscillator. Based on the homotopy analysis method which is valid even for highly nonlinear problems, this Maple package can give accurate approximate expressions even for nonlinear oscillation systems with strong nonlinearity. Besides, the package is user-friendly： One just needs to input a governing equation and initial conditions, and then gets satisfied analytic approximations in few seconds. Several different types of examples are given in this paper to illustrate the validity of this Maple package. Such kind of package provides us a helpful and easy-to-use tool in science and engineering to analyze periodic of this Maple package from the is published publicly. nonlinear oscillations. And it is free address http：//*** to download the electronic version ***/*** once the paper

关键词： Automated derivation homotopy analysis method homotopy Pade technique nonlinear oscillation Wu＇s elimination method.

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POSTER: STAR (Space-Time Adaptive and Reductive) Algorithms for Real-World Space-Time Optimality

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ACM SIGPLAN Notices 2017年第8期52卷 455-456页

作者： Tang, Yuan You, Ronghui School of Computer Science School of Software Fudan University Shanghai Key Lab. of Intelligent Information Processing State Key Lab. of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China

It's important to hit a space-time balance for a real-world algorithm to achieve high performance on modern shared-memory multi-core or many-core systems. However, a large class of dynamic programs with more than $O(1)$ dependency achieve optimality either in space or time, but not both. In the literature, the problem is known as the fundamental space-time tradeoff. By exploiting properly on the runtime system, we show that our STAR (Space-Time Adaptive and Reductive) technique can help these dynamic programs to achieve sublinear parallel time bounds while still maintaining work-, space-, and cache-optimality in a processor- and cache-oblivious fashion. © 2017 ACM.

关键词： Real time systems

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