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arXiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Shen, Xuemin Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering University of Waterloo Canada The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

Artificial Intelligence-Generated Content (AIGC) refers to the use of AI to automate the information creation process while fulfilling the personalized requirements of users. However, due to the instability of AIGC models, e.g., the stochastic nature of diffusion models, the quality and accuracy of the generated content can vary significantly. In wireless edge networks, the transmission of incorrectly generated content may unnecessarily consume network resources. Thus, a dynamic AIGC service provider (ASP) selection scheme is required to enable users to connect to the most suited ASP, improving the users’ satisfaction and quality of generated content. In this article, we first review the AIGC techniques and their applications in wireless networks. We then present the AIGC-as-a-service (AaaS) concept and discuss the challenges in deploying AaaS at the edge networks. Yet, it is essential to have performance metrics to evaluate the accuracy of AIGC services. Thus, we introduce several image-based perceived quality evaluation metrics. Then, we propose a general and effective model to illustrate the relationship between computational resources and user-perceived quality evaluation metrics. To achieve efficient AaaS and maximize the quality of generated content in wireless edge networks, we propose a deep reinforcement learning-enabled algorithm for the optimal ASP selection. Simulation results show that the proposed algorithm can provide a higher quality of generated content to users and achieve fewer crashed tasks by comparing with four benchmarks, i.e., overloading-avoidance, random, round-robin policies, and the upper-bound schemes. © 2023, CC BY.

关键词： Reinforcement learning

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An ultra thin,bright,and sensitive interactive tactile display based on organic mechanoluminescence for dual-mode handwriting identification

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InfoMat 2024年第6期6卷 76-87页

作者： Tingting Hou Wenlang Li Haoyu Wang Yuantian Zheng Chaojie Chen Haoran Zhang Kai Chen Huilin Xie Xin Li Shaoshuai He Siwei Zhang Dengfeng Peng Cheng Yang Jacky W.Y.Lam Ben Zhong Tang Yunlong Zi Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong Kongthe People's Republic of China Department of Chemistry Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction and Institute for Advanced StudyThe Hong Kong University of Science and TechnologyHong Kongthe People's Republic of China Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhenthe People's Republic of China Thrust of Sustainable Energy and Environment The Hong Kong University of Science and Technology(Guangzhou)Guangzhouthe People's Republic of China The Hong Kong University of Science and Technology Interdisciplinary Program Office Hong Kong SARthe People's Republic of China Institute of Materials Research Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhenthe People's Republic of China School of Science and Engineering Shenzhen Institute of Aggregate Science and TechnologyThe Chinese University of Hong KongShenzhenthe People's Republic of China HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute Shenzhenthe People's Republic of China Guangzhou HKUST Fok Ying Tung Research Institute Guangzhouthe People's Republic of China

Visible light-based human–machine interactive media is capable of transmitting electrical readouts to machines and providing intuitive feedback to users ***,many inorganic mechanoluminescent(ML)materials-based interactive media,typically ZnS-loaded phosphors(ZLPs),have been successfully ***,organic ML materials-based solutions were rarely exploited despite their huge merits of strong structural modification,abundant luminescence property,low cost,easy preparation,and so ***,we propose a novel interactive tactile display(ITD)based on organic ML materials(Cz-A6-dye)and triboelectric nanogenerator,with ultra-brightness(130%enhancement)and ultra-low threshold pressure(57%reduction)as compared to *** proposed ITD achieves the conversion of weak mechanical stimuli into visible light and electrical signals simultaneously,without extra power ***,the relationship between the luminous performance of organic ML materials and mechanical force is quantified,benefiting from the uniform ML layer *** by convolutional neural networks,the high-accuracy recognition(97.1%)for handwriting and identity of users is realized at the same ***,the ITD has great potential for intelligent wearable electronics and classified military applications.

关键词： interactive media organic mechanoluminescence triboelectric nanogenerators

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THE ADVANCED TOMAHAWK WEAPONS CONTROL-SYSTEM FOR SUBMARINES

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NAVAL ENGINEERS JOURNAL 1995年第3期107卷 35-40页

作者： BAEHR, JS LCdr. Joseph S. Baehr:is serving as the Submarine Advanced Systems Engineer tor the TOMAHAWK Weapons Control System Program Office PMA-282. He received his B.S. degree in Systems Engineering from the U.S. Naval Academy in 1983 and his M.S. degree in Electrical Engineering from the Naval Post Graduate School in 1990. He has served in several positions on board Sturgeon and Los Angeles class nuclear fast attack submarines including three years as Combat Systems Officer on USS Helena (SSN 725). He has been in his current assignment at the Cruise Missiles Project since June 1994 with primary responsibility for the Submarine ATWCS program.

The Advanced TOMAHAWK Weapons Control System (ATWCS) is being developed to support current and future tactical cruise missiles onboard navy ships. The ATWCS utilizes the Navy's standard Tactical Advanced Computer (TAC) 3 components and commercial standard Local Area Networks (LANs) to provide a flexible, robust system with excellent growth potential. Aggressive use of systems engineering principles has refined the system design so that it is adaptable to various Navy platforms. An excellent example of the success in meeting this design goal is the Submarine ATWCS. The primary data pathway for ATWCS is a Fiber Distributed Data Interface (FDDI) LAN connecting the four TAC 3 processors. Existing Common Display Consoles (CDCs) are used for display and control of the TAC 3 processors. The Submarine ATWCS builds on software already developed for surface ships. The open system architecture of this software is based on Computer Software Configuration Items (CSCIs) and several are obtained from other programs. Direct weapons interface in the Combat Control System (CCS) provides optimum efficiency in weapons control while gaining the functionality advantages of ATWCS. This paper describes the systems engineering solutions for both software and hardware to achieve a modern cruise missile weapons control capability for submarines utilizing non-development items (NDI), Commercial Off The Shelf (COTS) technology LANs and open system architecture.

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Accelerating the Artificial Bee Colony Algorithm by Hardware Parallel Implementations

Accelerating the Artificial Bee Colony Algorithm by Hardware...

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IEEE Latin American Symposium on Circuits and systems

作者： Daniel M. Mufioz Carlos H. Llanos Leandro dos S. Coelho Mauricio Ayala-Rincon Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Industrial and Systems Engineering Graduate Program LAS/PPGEPS Pontifical Catholic University of Parana Department of Computer Science and Mathematics University of Brasilia

ISBN: (纸本)9781467312073

Artificial bee colony (ABC) is an optimization algorithm inspired on the intelligent behavior of honey bee swarms. It is suitable to be applied when mathematical techniques are impractical or provide suboptimal solutions. As a population-based algorithm, the ABC suffers on large execution times specifically for embedded optimization problems with computational limitations. For that we propose a hardware parallel architecture of the opposition-based ABC algorithm (HPOABC) that facilitates the implementation in Field programmable Gate Arrays (FPGAs). Numerical simulations using four well-known benchmark problems demonstrate that the opposition-based approach allows the algorithm to improve its functionality, preserving the swarm diversity. Additionally, synthesis results point outs that the HPOABC architecture is effectively mapped in hardware and is suitable for embedded applications.

关键词： Global optimization Swarm intelligence Artificial bee colony FPGAs Floating-point arithmetic

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Experimental Analyses of the Combustion Instability Parameters in an Ammonia/Methane Fuelled Low Eddy Premix Burner for Gas Turbine Power Generation

SSRN

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SSRN 2022年

作者： Ilbas, Mustafa Kumuk, Osman Alabas, Bugrahan Department of Energy Systems Engineering Faculty of Technology Gazi University Teknikokullar Ankara Turkey Graduate School of Natural and Applied Science Gazi University Teknikokullar Ankara Turkey Unmanned Aerial Vehicle Technology and Operatorship Program Electronic and Automation Department Iskenderun Vocational School of Higher Education Iskenderun Technical University Hatay Turkey Department of Aeronautical Engineering Faculty of Aeronautics and Astronautics Erciyes University Kayseri Turkey

The main factor that directs scientists to work on alternative energy sources is the environmental damage caused by the waste gases generated by the use of fossil fuels. Since ammonia is a carbonless substance and contains hydrogen atoms per unit volume, it can be used as an alternative fuel. In this study, experimental analyzes were carried out to examine the combustion instability properties of methane-ammonia mixed fuels for a low eddy and premix burner. The aim of this study is to determine the effect of ammonia addition on combustion instability with different compelling acoustic frequencies, dynamic pressure amplitude and light emission intensity. In addition, the effects of ammonia addition to methane fuel gas on temperature and emissions were also investigated. Pure methane and three different methane-ammonia mixtures (by volume 100% CH4, 90% CH 4 - 10 NH3, 80% CH4 - 20% NH3 and 70% CH4-30 NH3) as fuel at 0.7 equivalents and with three different acoustics have been used for analyzes. The burner power was determined as 5 kW and the excitation frequencies of the combustion chamber were determined as 95, 160 and 300 Hz. In this study, as the ammonia addition increased, there was an increase in the flame instability values up to 30% NH3, especially at the 95 Hz frequency, where the highest distortion effect occurred. It was observed that there was no significant change in the combustion performance with the addition of ammonia to methane fuel. The predicted NOX emission levels were found to increase significantly due to nitrogen bound to ammonia. However, it is seen that the NOx emission levels in the exhaust measurements are not very high (Maximum 560 ppm). Therefore, it can be concluded that ammonia supplemented methane fuels have significant potential as an alternative fuel. © 2022, The Authors. All rights reserved.

关键词： Ammonia

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Diffusion-based Reinforcement Learning for Edge-enabled AI-Generated Content Services

TechRxiv

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TechRxiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Huang, Huawei Mao, Shiwen School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore School of Software Engineering Sun Yat-Sen University Zhuhai China Department of Electrical and Computer Engineering Auburn University Auburn United States

As Metaverse emerges as the next-generation Internet paradigm, the ability to efficiently generate content is paramount. AI-Generated Content (AIGC) emerges as a key solution, yet the resource-intensive nature of large Generative AI (GAI) models presents challenges. To address this issue, we introduce an AIGC-as-a-Service (AaaS) architecture, which deploys AIGC models in wireless edge networks to ensure broad AIGC services accessibility for Metaverse users. Nonetheless, an important aspect of providing personalized user experiences requires carefully selecting AIGC Service Providers (ASPs) capable of effectively executing user tasks, which is complicated by environmental uncertainty and variability. Addressing this gap in current research, we introduce the AI-Generated Optimal Decision (AGOD) algorithm, a diffusion model-based approach for generating the optimal ASP selection decisions. Integrating AGOD with Deep Reinforcement Learning (DRL), we develop the Deep Diffusion Soft Actor-Critic (D2SAC) algorithm, enhancing the efficiency and effectiveness of ASP selection. Our comprehensive experiments demonstrate that D2SAC outperforms seven leading DRL algorithms. Furthermore, the proposed AGOD algorithm has the potential for extension to various optimization problems in wireless networks, positioning it as a promising approach for future research on AIGC-driven services. The implementation of our proposed method is available at: https://***/Lizonghang/AGOD. © 2023, CC BY.

关键词： Reinforcement learning

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Diffusion-based Reinforcement Learning for Edge-enabled AI-Generated Content Services

arXiv

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arXiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Huang, Huawei Mao, Shiwen The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The School of Software Engineering Sun Yat-Sen University Zhuhai China The Department of Electrical and Computer Engineering Auburn University Auburn United States

关键词： Reinforcement learning

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Correction to "Combining of Chaotic Differential Evolution and Quadratic programming for Economic Dispatch Optimization with Valve-Point Effect"

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IEEE Transactions on Power systems 2006年第3期21卷 1465-1465页

作者： L. Dos Santos Coelho V.C. Mariani Production and Systems Engineering Graduate Program Automation and Systems Laboratory PUCPR/CCET/PPGEPS/LAS Pontifical Catholic University of Paraná Curitiba Parana Brazil Mechanical Engineering Graduate Program PUCPR/CCET/PPGEPS/LAS Pontifical Catholic University of Paraná Curitiba Parana Brazil

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Numerically Tractable Stability Tests for 2-D Singular Discrete-Time systems

Numerically Tractable Stability Tests for 2-D Singular Discr...

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IEEE Annual Conference on Decision and Control

作者： Andre F. Caldeira Daniel Coutinho Carlos E. de Souza Valter J. S. Leite Graduate Program on Systems and Control Engineering (PPGEAS) at the Universidade Federal de Santa Catarina (UFSC) PO Box 476 88040-900 Florianopolis SC Brazil Department of Automation and Systems (DAS) UFSC PO BOX 476 88040-900 Florianopolis SC Brazil Department of Systems and Control Laboratorio Nacional de Computacao Cientifica (LNCC/MCTI) Av. Getulio Vargas 333 25651-075 Petropolis RJ Brazil CEFET-MG / Campus Divinopolis R. Alvares Azevedo 400 35503-822 Divinopolis MG Brazil

ISBN: (纸本)9781467357159

This paper presents numerically tractable strict and non-strict linear matrix inequality conditions to the internal stability analysis of 2-D singular discrete-time systems. Two classes of 2-D singular systems are considered: (i) a general singular Fornasini-Marchesini model, and (ii) a singular Roesser model. In addition, the proposed conditions also guarantee that the 2-D singular system is acceptable and jump modes free. Numerical examples are presented to illustrate the proposed approach.

关键词： Singular Singular system stability study digitally Stability analysis

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Fusion of Mixture of Experts and Generative Artificial Intelligence in Mobile Edge Metaverse

arXiv

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arXiv 2024年

作者： Liu, Guangyuan Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Jamalipour, Abbas Mao, Shiwen Kim, Dong In The College of Computing and Data Science The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The College of Computing and Data Science Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering Auburn University Auburn United States The School of Electrical and Computer Engineering University of Sydney Australia The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

In the digital transformation era, Metaverse offers a fusion of virtual reality (VR), augmented reality (AR), and web technologies to create immersive digital experiences. However, the evolution of the Metaverse is slowed down by the challenges of content creation, scalability, and dynamic user interaction. Our study investigates an integration of Mixture of Experts (MoE) models with Generative Artificial Intelligence (GAI) for mobile edge computing to revolutionize content creation and interaction in the Metaverse. Specifically, we harness an MoE model's ability to efficiently manage complex data and complex tasks by dynamically selecting the most relevant experts running various sub-models to enhance the capabilities of GAI. We then present a novel framework that improves video content generation quality and consistency, and demonstrate its application through case studies. Our findings underscore the efficacy of MoE and GAI integration to redefine virtual experiences by offering a scalable, efficient pathway to harvest the Metaverse's full potential. © 2024, CC BY.

关键词： Augmented reality

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