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arXiv 2021年

作者： Li, Songhua Li, Minming Duan, Lingjie Lee, Victor C.S. Department of Computer Science City University of Hong Kong Kowloon Hong Kong Engineering Systems and Design Pillar Singapore University of Technology and Design Singapore Singapore Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong

The unmanned aerial vehicle (UAV) has emerged as a promising solution to provide delivery and other mobile services to cus-tomers rapidly, yet it drains its stored energy quickly when travelling on the way and (even if solar-powered) it takes time for charging power on the way before reaching the destination. To address this issue, existing works focus more on UAV's path planning with designated system vehi-cles providing charging service. However, in some emergency cases and rural areas where system vehicles are not available, public trucks can provide more feasible and cost-saving services and hence a silver lining. In this paper, we explore how a single UAV can save ying distance by exploiting public trucks, to minimize the travel time of the UAV. We give the first theoretical work studying online algorithms for the prob-lem, which guarantees a worst-case performance. We first consider the offline problem knowing future truck trip information far ahead of time. By delicately transforming the problem into a graph satisfying both time and power constraints, we present a shortest-path algorithm that outputs the optimal solution of the problem. Then, we proceed to the online set-ting where trucks appear in real-time and only inform the UAV of their trip information some certain time fit beforehand. As a benchmark, we propose a well-constructed lower bound that an online algorithm could achieve. We propose an online algorithm MyopicHitching that greedily takes truck trips and an improved algorithm Adaptive that further tolerates a waiting time in taking a ride. Our theoretical analysis shows that Adaptive is asymptotically optimal in the sense that its ratio ap-proaches the proposed lower bounds as fit increases. © 2021, CC BY.

关键词： Unmanned aerial vehicles (UAV)

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Semantic segmentation of longitudinal thermal images for identification of hot and cool spots in urban areas

arXiv

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arXiv 2023年

作者： Ramani, Vasantha Arjunan, Pandarasamy Poolla, Kameshwar Miller, Clayton Berkeley Education Alliance for Research in Singapore CREATE Tower 1 Create Way 138602 Singapore Robert Bosch Centre for Cyber-physical Systems Indian Institute of Science Karnataka Bengaluru560012 India Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA94720-1770 United States Department of the Built Environment College of Design and Engineering National University of Singapore 4 Architecture Drive 117566 Singapore

This work presents the analysis of semantically segmented, longitudinally, and spatially rich thermal images collected at the neighborhood scale to identify hot and cool spots in urban areas. An infrared observatory was operated over a few months to collect thermal images of different types of buildings on the educational campus of the National University of Singapore. A subset of the thermal image dataset was used to train state-of-the-art deep learning models to segment various urban features such as buildings, vegetation, sky, and roads. It was observed that the U-Net segmentation model with ‘resnet34’ CNN backbone has the highest mIoU score of 0.99 on the test dataset, compared to other models such as DeepLabV3, DeeplabV3+, FPN, and PSPnet. The masks generated using the segmentation models were then used to extract the temperature from thermal images and correct for differences in the emissivity of various urban features. Further, various statistical measures of the temperature extracted using the predicted segmentation masks are shown to closely match the temperature extracted using the ground truth masks. Finally, the masks were used to identify hot and cool spots in the urban feature at various instances of time. This forms one of the very few studies demonstrating the automated analysis of thermal images, which can be of potential use to urban planners for devising mitigation strategies for reducing the urban heat island (UHI) effect, improving building energy efficiency, and maximizing outdoor thermal comfort. © 2023, CC BY-NC-SA.

关键词： Observatories

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Effects of Air Exposure on the Interfacial Capacitance of Laser-Induced Graphene (LIG) with and without Silver (Ag) Nanoparticle Loading

Effects of Air Exposure on the Interfacial Capacitance of La...

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IEEE International Conference on Sensors and Nanotechnology

作者： Rou Xuan Goh Suhana Mohamed Sultan Suan Hui Pu Pei Ling Leow Hing Wah Lee Sam J. Fishlock Harold M. H. Chong Ting Yang Ling Smart Manufacturing and Systems Research Group University of Southampton Malaysia Iskandar Puteri Johor Malaysia Faculty of Electrical Engineering Universiti Teknologi Malaysia Skudai Johor Malaysia Centre for Semiconductor & Thin Film Research MIMOS Berhad Technology Park Malaysia Kuala Lumpur Malaysia The Engineering & Design Institute TEDI-London London U.K. School of Electronics and Computer Science University of Southampton Southampton U.K.

Research on laser-induced graphene (LIG) and LIG with silver nanoparticles loading (Ag-LIG) are increasing by the day as more of its potential are uncovered each day. With the LIG fabrication looking to increase further in the future, it will be useful to confirm and verify any changes in the quality of LIG when it is exposed to the ambient air. In normal laboratory conditions, researchers store samples in petri dishes or any other covered storage, but inevitably the air within the storage will still be in contact with the samples. In this study, we left LIG and Ag-LIG samples in a lidded petri dish after its fabrication and measured the interfacial capacitance of each sample using a standard three-electrode electrochemical setup with a potential range from 0 V to 0.4 V on different days. Results show that the interfacial capacitance of both LIG and Ag-LIG drops as it is left in the storage container longer after its fabrication, with Ag-LIG showing a greater decrease after 10 days compared to LIG. This indicates that the silver nanoparticles played an important part during the oxidation process, making Ag-LIG more sensitive to its environment during prolonged unuse. The findings from this study shows the potential usage of LIG and Ag-LIG as a low-cost single-use indicator for air exposure.

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A Numerical Method to Analyze Electromagnetic Scattering from Composite Plasmonic Structures Involving a Metal-Metal Interface

A Numerical Method to Analyze Electromagnetic Scattering fro...

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Antennas and Propagation Society International Symposium

作者： Doolos Aibek Uulu Rui Chen Liang Chen Ping Li Hakan Bagci Division of Computer Electrical and Mathematical Science and Engineering King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Department of Mathematics and Natural Sciences University of Central Asia (UCA) Naryn Kyrgyzstan Key Laboratory of Ministry of Education of Design and Electromagnetic Compatibility of High-Speed Electronic Systems Shanghai Jiao Tong University Shanghai China

A coupled system of volume integral and hydrodynamic equations is formulated to analyze electromagnetic scattering from composite plasmonic structures involving a metal-metal interface. This coupled system in unknowns electric flux and free electron velocity is discretized using Schaubert-Wilton-Glisson basis functions. Inserting these expansions into the coupled system of equations and applying Galerkin testing yield a matrix equation. Two-level iterative scheme is used to solve this matrix equation for the unknown expansion coefficients. To demonstrate the accuracy of the proposed method, numerical results are compared to those obtained using an extended Mie series approach that takes into account the hydrodynamic equation and the boundary conditions it requires.

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Cooperative Double-IRS Aided Communication: Beamforming design and Power Scaling

arXiv

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arXiv 2020年

作者： Han, Yitao Zhang, Shuowen Duan, Lingjie Zhang, Rui Engineering Systems and Design Pillar Singapore University of Technology and Design Department of Electrical and Computer Engineering National University of Singapore Department of Electrical and Computer Engineering National University of Singapore

Intelligent reflecting surface (IRS) is a promising technology to support high performance wireless communication. By adaptively configuring the reflection amplitude and/or phase of each passive reflecting element on it, the IRS can reshape the electromagnetic environment in favour of signal transmission. This letter advances the existing research by proposing and analyzing a double-IRS aided wireless communication system. Under the reasonable assumption that the reflection channel from IRS 1 to IRS 2 is of rank 1 (e.g., line-of-sight channel), we propose a joint passive beamforming design for the two IRSs. Based on this, we show that deploying two cooperative IRSs with in total K elements can yield a power gain of order O(K4), which greatly outperforms the case of deploying one traditional IRS with a power gain of order O(K2). Our simulation results validate that the performance of deploying two cooperative IRSs is significantly better than that of deploying one IRS given a sufficient total number of IRS elements. We also extend our line-of-sight channel model to show how different channel models affect the performance of the double-IRS aided wireless communication system. Copyright © 2020, The Authors. All rights reserved.

关键词： Beamforming

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Life-Span Expectancy and Cycle Size in the Original Autopoiesis Algorithm

Life-Span Expectancy and Cycle Size in the Original Autopoie...

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2020 Conference on Artificial Life, ALIFE 2020

作者： Priya, Siddharth Nehaniv, Chrystopher L. Dept. of Electrical and Computer Engineering University of Waterloo WaterlooON Canada Dept. of Systems Design Engineering University of Waterloo WaterlooON Canada Royal Society Wolfson Biocomputation Research Laboratory University of Hertfordshire Hatfield United Kingdom

We implement Varela, Maturana and Uribe’s original autopoiesis algorithm with suitable modifications as proposed by McMullin. We further investigate how environmental factors affect formation of autopoietic entities - namely how long an entity remains a whole after formation and to what size does it grow in its life span i.e. Life span and Cycle size respectively. We find that ratios of different basic elements like Holes, Substrates and Catalysts do not affect Life span and Cycle size meaningfully but both properties are affected negatively if disintegration probability—the probability of a Link element to transform into a Substrate element—is increased. © 2020 Massachusetts Institute of Technology.

关键词： Disintegration

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FIRE: A Failure-Adaptive Reinforcement Learning Framework for Edge Computing Migrations

arXiv

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arXiv 2022年

作者： Siew, Marie Sharma, Shikhar Li, Zekai Guo, Kun Xu, Chao Lorido-Botran, Tania Quek, Tony Q.S. Joe-Wong, Carlee The Information Systems and Technology and Design Pillar Singapore University of Technology and Design Singapore487372 Singapore The Electrical and Computer Engineering department Carnegie Mellon University PittsburghPA15213 United States The Shanghai Key Laboratory of Multidimensional Information Processing School of Communications and Electronics Engineering East China Normal University Shanghai200241 China The School of Information Engineering Northwest A&F University Yangling712100 China Roblox United States

In edge computing, users’ service profiles are migrated between edge servers due to user mobility. Reinforcement learning (RL) frameworks have been proposed to do so, often trained on simulated data. However, existing RL frameworks overlook occasional server failures, which although rare, impact latency-sensitive applications like AR/VR and real- time obstacle detection. These rare failures, being not adequately represented in historical training data, pose a challenge for data-driven RL algorithms. We introduce FIRE, a framework that adapts to rare events by training a RL policy in an edge computing digital twin environment. We propose FIRE-ImRE, an importance sampling-based Q-learning algorithm, which samples rare events proportionally to their impact on the value function. FIRE considers delay, migration, failure, and backup placement costs across individual and shared service profiles. We prove FIRE-ImRE’s boundedness and convergence to optimality. Next, we introduce novel deep Q-learning (FIRE-ImDQL) and actor critic (FIRE-ImACRE) versions of our algorithm to enhance scalability. We extend our framework to accommodate users with varying risk tolerances of rare failure events. Through trace-driven experiments, we show that FIRE reduces edge computing costs compared to vanilla RL and the greedy baseline in the event of failures. © 2022, CC BY.

关键词： Mobile edge computing

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Joint transmit precoding and reflect beamforming design for IRS-assisted MIMO cognitive radio systems

arXiv

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arXiv 2021年

作者： Jiang, Weiheng Zhang, Yu Zhao, Jun Xiong, Zehui Ding, Zhiguo The School of Microelectronics and Communication Engineering Chongqing University Chongqing China The School of Computer Science and Engineering Nanyang Technological University Singapore The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The School of Electrical and Electronic Engineering University of Manchester Manchester United Kingdom

Cognitive radio (CR) is an effective solution to improve the spectral efficiency (SE) of wireless communications by allowing the secondary users (SUs) to share spectrum with primary users (PUs). Meanwhile, intelligent reflecting surface (IRS) has been recently proposed as a promising approach to enhance SE and energy efficiency (EE) of wireless communication systems through intelligently reconfiguring the channel environment. In this paper, we consider an IRS-assisted downlink CR system, in which a secondary access point (SAP) communicates with multiple SUs without affecting multiple PUs in the primary network and all nodes are equipped with multiple antennas. Our design objective is to maximize the achievable weighted sum rate (WSR) of SUs subject to the total transmit power constraint at the SAP and the interference constraints at PUs, by jointly optimizing the transmit precoding at the SAP and the reflecting coefficients at the IRS. To deal with the complex objective function, the problem is reformulated by employing the well-known weighted minimum mean-square error (WMMSE) method and an alternating optimization (AO)-based algorithm is proposed. Furthermore, a special scenario with only one PU is considered and AO algorithm is adopted again. It is worth mentioning that the proposed algorithm has a much lower computational complexity than the above algorithm without the performance loss. Finally, some numerical simulations have been provided to demonstrate that the proposed algorithm outperforms other benchmark schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Cognitive radio

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Emotional voice conversion: Theory, databases and ESD

arXiv

引用

arXiv 2021年

作者： Zhou, Kun Sisman, Berrak Liu, Rui Li, Haizhou Department of Electrical and Computer Engineering National University of Singapore Singapore Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore Machine Listening Lab. University of Bremen Germany

In this paper, we first provide a review of the state-of-the-art emotional voice conversion research, and the existing emotional speech databases. We then motivate the development of a novel emotional speech database (ESD) that addresses the increasing research need. With this paper, the ESD database1 is now made available to the research community. The ESD database consists of 350 parallel utterances spoken by 10 native English and 10 native Chinese speakers and covers 5 emotion categories (neutral, happy, angry, sad and surprise). More than 29 h of speech data were recorded in a controlled acoustic environment. The database is suitable for multi-speaker and cross-lingual emotional voice conversion studies. As case studies, we implement several state-of-the-art emotional voice conversion systems on the ESD database. This paper provides a reference study on ESD in conjunction with its release. © 2021, CC BY.

关键词： Database systems

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Accelerating the Evolution of Personalized Automated Lane Change through Lesson Learning

arXiv

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arXiv 2024年

作者： Hu, Jia Lei, Mingyue Li, Duo Li, Zhenning So, Jaehyun Wang, Haoran Key Laboratory of Road and Traffic Engineering The Ministry of Education Institute for Advanced Study Tongji University 4800 Cao’an Road Shanghai China Key Laboratory of Road and Traffic Engineering The Ministry of Education Tongji University 4800 Cao’an Road Shanghai China Department of Civil and Geospatial Engineering Newcastle University Newcastle upon TyneNE1 7RU United Kingdom State Key Laboratory of Internet of Things for Smart City Departments of Civil and Environmental Engineering and Computer and Information Science University of Macau Avenida da Universidade Taipa China Department of Transportation Systems Engineering Ajou University 206 World cup-ro Yeongtong-gu Gyeonggi-do Suwon-si16499 Korea Republic of State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China

Personalization is crucial for the widespread adoption of advanced driver assistance system. To match up with each user's preference, the online evolution capability is a must. However, conventional evolution methods learn from naturalistic driving data, which requires a lot computing power and cannot be applied online. To address this challenge, this paper proposes a lesson learning approach: learning from driver's takeover interventions. By leveraging online takeover data, the driving zone is generated to ensure perceived safety using Gaussian discriminant analysis. Real-time corrections to trajectory planning rewards are enacted through apprenticeship learning. Guided by the objective of optimizing rewards within the constraints of the driving zone, this approach employs model predictive control for trajectory planning. This lesson learning framework is highlighted for its faster evolution capability, adeptness at experience accumulating, assurance of perceived safety, and computational efficiency. Simulation results demonstrate that the proposed system consistently achieves a successful customization without further takeover interventions. Accumulated experience yields a 24% enhancement in evolution efficiency. The average number of learning iterations is only 13.8. The average computation time is 0.08 seconds. © 2024, CC BY.

关键词： Discriminant analysis

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