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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Xinxin Zhu F. Richard Yu Ying He Biao He College of Computer Science and Software Engineering Shenzhen University China Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) Shenzhen China Research Institute for Smart Cities School of Architecture and Urban Planning Shenzhen University Shenzhen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The latest Segment Anything Model enables realtime scene annotation and understanding for autonomous driving systems, enhancing driving safety. However, effectively allocating resources for real-time performance and accuracy remains challenging in edge-cloud architectures. Traditional reinforcement learning struggles with poor generalization and the explorationexploitation dilemma, making it difficult to define clear reward functions. To address this, we propose a likelihood active inference approach to optimize resource allocation and improve system resource utilization. We use "intelligence" as a high-level indicator to quantify the efficiency of cognition in active inference, evaluating the difference between predicted and actual states during policy exploration. Experimental results show our algorithm outperforms mainstream deep reinforcement learning algorithms, improving sample efficiency and suitability for dynamically changing task workloads.

关键词： Accuracy Heuristic algorithms Signal processing algorithms Signal processing Prediction algorithms Inference algorithms Real-time systems Resource management Speech processing Autonomous vehicles

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Enhancing the Uplink of Cell-Free Massive MIMO Through Prioritized Sampling and Personalized Federated Deep Reinforcement Learning

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Mendoza, Charmae Franchesca Kaneko, Megumi Rupp, Markus Schwarz, Stefan Technische Universität Wien Institute of Telecommunications Sustainable Radio Access Networks Christian Doppler Laboratory Digital Twin Assisted AI Vienna1040 Austria National Institute of Informatics Information Systems Architecture Science Research Division Tokyo101-8430 Japan Department of Computer Science University of Tokyo Tokyo Japan Technische Universität Wien Institute of Telecommunications Vienna1040 Austria

Effective power control is key to solving the inter-user interference problem that degrades performance in cell-free massive multiple-input multiple-output (MIMO) systems. Motivated by its ability to operate online and model-free, without relying on training datasets, we leverage deep reinforcement learning (DRL) for uplink power control, aiming to maximize the guaranteed rate. We propose a fully centralized single-agent framework and two distributed schemes that employ several agents for improved scalability, leveraging prioritized experience replay to enable fast adaptation to the dynamic changes of the wireless environment. We investigate the performance of two multi-agent system architectures: (1) centralized training, decentralized execution (CTDE), where each agent forwards its RL experience to a central trainer, and (2) personalized federated learning (FedPer), where the training is performed locally at each agent, and only the base layer of the local deep neural network (DNN) model is forwarded periodically for aggregation at a server. We focus on the realistic scenario of dynamic device (de-)activation, combined with user mobility. Numerical evaluations demonstrate that the proposed FedPer with prioritized sampling achieves near-optimal rate and power performance while incurring the least amount of communication overhead. © 2015 IEEE.

关键词： Deep reinforcement learning

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The Importance of Being Earnest: Multiple Heterogeneous Container Loading with a Simple Genetic Algorithm 28th

The Importance of Being Earnest: Multiple Heterogeneous Con...

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28th European Conference on Applications of Evolutionary Computation, EvoApplications 2025, held as part of EvoStar 2025

作者： Rusin, Francesco Fiala, Jan Sanker, Julian Bhattarai, Suyesh Ekárt, Anikó Department of Engineering and Architecture University of Trieste Trieste Italy Institute of Automation and Computer Science Brno University of Technology Brno Czech Republic Yale College Yale University New Haven United States Mechatherm International Limited Cradley Heath United Kingdom Aston Centre for Artificial Intelligence Research and Application Aston University Birmingham United Kingdom

ISBN: (纸本)9783031900617

In this study we address the complex practical problem of multiple heterogeneous container loading with a simple genetic algorithm. We demonstrate that with a well-chosen representation including a heuristic and a suitable fitness function the other aspects of the genetic algorithm do not need extensive work for good results. Following systematic study of our method on synthetically generated data, we visually showcase the solution for a company-based problem instance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Genetic algorithms

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City models: past, present and future prospects

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Frontiers of Urban and Rural Planning 2025年第1期3卷 1-24页

作者： Ritter, Helge Herzog, Otthein Rothermel, Kurt Cohn, Anthony G. Wu, Zhiqiang Faculty of Technology Bielefeld University Bielefeld Germany College of Architecture and Urban Planning Tongji University Shanghai People’s Republic of China FB 03 University of Bremen Bremen Germany Institute of Parallel and Distributed Systems University of Stuttgart Stuttgart Germany School of Computer Science University of Leeds Leeds UK The Alan Turing Institute London UK

This paper attempts to take a comprehensive look at the challenges of representing the spatio-temporal structures and dynamic processes that define a city’s overall characteristics. For the task of urban planning and urban operation, we take the stance that even if the necessary representations of these structures and processes can be achieved, the most important representation of the relevant mindsets of the citizens are, unfortunately, mostly neglected. After a review of major “traditional” urban models of structures behind urban scale, form, and dynamics, we turn to major recent modeling approaches triggered by recent advances in AI that enable multimodal generative models. Some of these models can create representations of geometries, networks and images, and reason flexibly at a human-compatible semantic level. They provide huge amounts of knowledge extracted from huge collections of text and image documents and cover the required rich representation spectrum including geographic knowledge by different knowledge sources, degrees of granularity and scales. We then discuss what these new opportunities mean for coping with the modeling challenges posed by cities, in particular with regard to the role and impact of citizens and their interactions within the city infrastructure. We propose to integrate these possibilities with existing approaches, such as agent-based models, which opens up new modeling spaces including rich citizen models which are able to also represent social interactions. Finally, we put forward some thoughts about a vision of a “social AI in a city ecosystem” that adds relevant citizen models to state-of-the-art structural and process models. This extended city representation will enable urban planners to establish citizen-oriented planning of city infrastructures, to make them into inviting environments that reconcile and foster human culture, city resilience and sustainability.

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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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A SystemC Based Framework for Cycle Accurate Processor Simulation and Parameter Analysis

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IFAC-PapersOnLine 2016年第25期49卷 92-97页

作者： Kohl, Johannes Reichenbach, Marc Demel, Carsten Fey, Dietmar Department of Computer Science Chair of Computer Architecture Friedrich-Alexander-University Erlangen-Nuremberg Germany

The development of new domain specific microprocessors architectures is a very complex task. Hardware designers are confronted with several hundred design parameters (e.g. cache size, ALU operation, etc.) which can be combined in a nearly arbitrary way to develop new architectures. Often these parameters are guessed by the designer or best practice is used to find an apparently good parameter set. The utilization of virtual hardware can be one solution to solve this problem. Different parameter sets can be evaluated inside a simulation environment, without the need for designing any real hardware. Unfortunately, most virtual hardware simulators are either to inflexible or not accurate enough to get valuable results. Therefore, this paper presents a SystemC based framework, which enables the construction of highly parameterizable virtual hardware processor models, directed at parameter analysis. The structure and working principle of two exemplary processors are showcasing the use of this framework. A presentation of how different parameter sets impact the programs execution time and power consumption of the processor will be given, as a result of the virtual hardwares execution. © 2016

关键词： Integrated circuit design Application programs Hardware Simulators Cycle accurate Design space exploration Design tool Emulators Microprocessor based control

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Plausibility in Early Stages of Architectural Design: A New Tool for High-Rise Residential Buildings

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Tsinghua science and Technology 2009年第3期14卷 327-332页

作者： Dirk Donath Danny Lobos Chair of Computer Science in Architecture Faculty of Architecture Bauhaus-UniversityWeimar 99423 Germany

This paper analyzes the problem of the design of envelopes for high-rise isolated residential buildings. The phenomenon of envelope creation appears in the early stages of the architectural design. Variables that influence the final shape and size of such envelopes are then identified. This paper presents the state-of-the-art tools for the current solutions at the commercial and academic/scientific level. The variables identified in this research are the client＇s needs, the urban code and architectural practice, and their specific components for the final creation of a new decision support system tool based on the building information modeling （BIM） software platform, to facilitate the work in the project development and drawing production stages. This tool generates several options for building envelopes according to the parameters required by the city Zoning Planning Commission. These options then lead to deliver reliable data and a geometry that can be analyzed in a timely fashion by the engineers, builders, architects, government, and clients in the early stages of the building＇s design. The results show that use of specific information and communication technologies （ICT） tools in the early stages of a building design helps reduce the working time, increases confidence in the generated solution, and contributes to the exploration of alternatives in a short period of time.

关键词： constraint based design parametric programming urban modeling optimization architectural design

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An interpretable spatially weighted machine learning approach for revealing spatial nonstationarity impacts of the built environment on air pollution

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Building and Environment 2025年 280卷

作者： Wang, Shumin Hu, Mingxing Li, Jianyu Liu, Guoao Hu, Wanqi Qi, Junheng Huang, Jingyue Liu, Ziye Wang, Hui Han, Bing School of Architecture Southeast University Si Pailou Campus Nanjing210096 China School of Computer and Information Science University of Pennsylvania PhiladelphiaPA 19104 United States College of Landscape Architecture Nanjing Forestry University 159 Longpan Road Nanjing210037 China College of Horticulture Jinling Institute of Technology Nanjing210038 China

With urbanization acceleration, air pollution has become increasingly severe, and the built environment plays a crucial role in pollutant dispersion and accumulation. In this study, the central urban area of Nanjing is analysed in a case study, focusing on the plot scale to systematically explore spatial heterogeneity and nonlinear interactive mechanisms of built environment impacts. To accurately capture the complex spatial nonstationarity effects of the built environment on air pollution, a geographically weighted machine learning (GeoML) approach driven by an adjacency-based spatial mechanism integrated with the SHapley Additive exPlanations (SHAP) framework for interpretability is established. The findings reveal that the GeoML model outperforms other models (the ordinary least squares (OLS), random forest (RF), geographically weighted regression (GWR), and geographically weighted random forest (GWRF) models), with an R² value of 0.74, effectively capturing spatial heterogeneity and nonlinearity. Further analysis reveals significant variations in the impact of spatial weighting on the contributions of different feature variables: the explanatory power of most variables increases with the inclusion of spatial effects, whereas the contributions of variables such as population density, road network density, and parcel compactness are reduced. The SHAP framework is employed to provide interpretable analysis of the patterns in the impacts of various feature variables on air pollution. This study emphasizes the importance of spatial effects at the microscale plot level in understanding the mechanisms of air pollution and highlights their importance for developing urban environmental policies, thus promoting the transformation of air pollution control towards spatially refined management. © 2025

关键词： Air quality

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VHF Band III Spectrum Availability and Utilization for Cognitive Radio Implementation in Malaysia

VHF Band III Spectrum Availability and Utilization for Cogni...

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Learning and Technology Conference (L&T)

作者： Hashim Elshafie Hafizal Mohamad Rashid A. Saeed Mosab Hamdan Mahmoud M. Khattab Abdelmoty M. Ahmed College of Computer Science King Khalid University Saudi Arabia Faculty of Engineering and Built Environment Universiti Sains Islam Malaysia Nilai Negeri Sembilan Malaysia College of Computers and Information Technology (CIT) Taif University Taif Saudi Arabia Walton Institute for Information and Communication Systems Science South East Technological University Waterford Ireland College of Engineering and Architecture Al Yamamah University Riyadh Saudi Arabia Faculty of Computer Science Nahda University Beni Suef Egypt

ISBN: (数字)9798331532215

ISBN: (纸本)9798331532222

The VHF Band III spectrum (174-230 MHz), recognized for its low utilization, was opened by the FCC in 2002 for opportunistic use by communication technologies. This paper presents a quantitative analysis of the availability of VHF Band III for cognitive radio CR access in Malaysia. Measurements were conducted over a week in 18 Malaysian cities to analyze spectrum utilization and received signal strength, alongside the impact of broadcasts from neighboring countries. The findings highlight actual utilization patterns and reveal the spectrum’s potential for opportunistic access, especially post-digital switchover (DSO).

关键词： Regulators Statistical analysis Urban areas Switches FCC Time measurement Communications technology Cognitive radio

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Energy duality methods for Piecewise Bezier Curve construction

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computer GRAPHICS FORUM 1996年第2期15卷 143-154页

作者： Bercovier, M Volpin, O Institute of Computer Science The Hebrew University of Jerusalem Jerusalem Israel †Bertold Badler Chair of Computer Science.

Piecewise Bezier Curves are constructed using a minimization principle. C-k and GC(k) continuity is imposed by linear constraints. The corresponding quadratic programming with linear constraints problem is introduced and solved by duality methods. Bordering matrices methods are implemented to deal with local refinement (subdivision). The result is a versatile tool for defining/editing contours made of piecewise Bezier curves.

关键词： finite-element method(FEM) stiffness matrix Piecewise Bezier Curve local refinement computer-aided geometric design Lagrange multiplier duality minimization under constraints

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