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arXiv 2021年

作者： Wei, Li Huang, Chongwen Guo, Qinghua Yang, Zhaohui Zhang, Zhaoyang Alexandropoulos, George C. Debbah, Mérouane Yuen, Chau Pillar Singapore University of Technology and Design Singapore487372 Singapore College of Information Science and Electronic Engineering Zhejiang University Hangzhou310007 China Hangzhou310007 China International Joint Innovation Center Zhejiang University Haining314400 China Zhejiang-Singapore Innovation and AI Joint Research Lab Hangzhou310027 China Zhejiang Laboratory Hangzhou31121 China School of Electrical Computer and Telecommunications Engineering University of Wollongong WollongongNSW2522 Australia Department of Informatics and Telecommunications National and Kapodistrian University of Athens Panepistimiopolis Ilissia Athens15784 Greece Technology Innovation Institute Masdar City Abu Dhabi9639 United Arab Emirates CentraleSupelec University Paris-Saclay Gif-sur-Yvette91192 France

Reconfigurable intelligent surfaces (RISs) have been recently considered as a promising candidate for energy-efficient solutions in future wireless networks. Their dynamic and low-power configuration enables coverage extension, massive connectivity, and low-latency communications. Due to a large number of unknown variables referring to the RIS unit elements and the transmitted signals, channel estimation and signal recovery in RIS-based systems are the ones of the most critical technical challenges. To address this problem, we focus on the RIS-assisted wireless communication system and present two joint channel estimation and signal recovery schemes based on message passing algorithms in this paper. Specifically, the proposed bidirectional scheme applies the Taylor series expansion and Gaussian approximation to simplify the sum-product procedure in the formulated problem. In addition, the inner iteration that adopts two variants of approximate message passing algorithms is incorporated to ensure robustness and convergence. Two ambiguities removal methods are also discussed in this paper. Our simulation results show that the proposed schemes show the superiority over the state-of-art benchmark method. We also provide insights on the impact of different RIS parameter settings on the proposed schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Channel estimation

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PiaNet: A pyramid input augmented convolutional neural network for GGO detection in 3D lung CT scans

arXiv

引用

arXiv 2020年

作者： Liu, Weihua Liu, Xiabi Luo, Xiongbiao Wang, Murong Zheng, Guangyuan Han, Guanghui Beijing Lab of Intelligent Information School of Computer Science Beijing Institute of Technology 5 South Zhongguancun Street Haidian District Beijing100081 China Department of computer science Xiamen University No. 422 Siming South Road XiamenFujian361005 China School of Biomedical Engineering Sun Yat-sen University No.132 Outer Ring Road East University Town Panyu District Guangzhou510006 China

This paper proposes a new convolutional neural network with multiscale processing for detecting ground-glass opacity (GGO) nodules in 3D computed tomography (CT) images, which is referred to as PiaNet for short. PiaNet consists of a feature-extraction module and a prediction module. The former module is constructed by introducing pyramid multiscale source connections into a contracting-expanding structure. The latter module includes a bounding-box regressor and a classifier that are employed to simultaneously recognize GGO nodules and estimate bounding boxes at multiple scales. To train the proposed PiaNet, a two-stage transfer learning strategy is developed. In the first stage, the feature-extraction module is embedded into a classifier network that is trained on a large data set of GGO and non-GGO patches, which are generated by performing data augmentation from a small number of annotated CT scans. In the second stage, the pretrained feature-extraction module is loaded into PiaNet, and then PiaNet is fine-tuned using the annotated CT scans. We evaluate the proposed PiaNet on the LIDC-IDRI data set. The experimental results demonstrate that our method outperforms state-of-the-art counterparts, including the Subsolid CAD and Aidence systems and S4ND and GA-SSD methods. PiaNet achieves a sensitivity of 91.75% with only one false positive per scan. Copyright © 2020, The Authors. All rights reserved.

关键词： Feature extraction

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A Double Auction for Charging Scheduling among Vehicles Using DAG-Blockchains

arXiv

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arXiv 2020年

作者： Guo, Jianxiong Ding, Xingjian Wu, Weili Du, Ding-Zhu Advanced Institute of Natural Sciences Beijing Normal University Zhuhai519087 China Guangdong Key Lab of AI and Multi-Modal Data Processing BNU-HKBU United International College Zhuhai519087 China Faculty of Information Technology Beijing University of Technology Beijing100124 China Department of Computer Science Erik Jonsson School of Engineering and Computer Science The University of Texas at Dallas RichardsonTX75080 United States

Electric Vehicles (EVs) are becoming more and more popular in our daily life, which replaces traditional fuel vehicles to reduce carbon emissions and protect the environment. EVs need to be charged, but the number of charging piles in a Charging Station (CS) is limited and charging is usually more time-consuming than fueling. According to this scenario, we propose a secure and efficient charging scheduling system based on a Directed Acyclic Graph (DAG)-blockchain and double auction mechanism. In a smart area, it attempts to assign EVs to the available CSs in the light of their submitted charging requests and status information. First, we design a lightweight charging scheduling framework that integrates DAG-blockchain and modern cryptography technology to ensure security and scalability during performing scheduling and completing tradings. In this process, a constrained multi-item double auction problem is formulated because of the limited charging resources in a CS, which motivates EVs and CSs in this area to participate in the market based on their preferences and statuses. Due to this constraint, our problem is more complicated and harder to achieve truthfulness as well as system efficiency compared to the existing double auction model. To adapt to it, we propose two algorithms, namely Truthful Mechanism for Charging (TMC) and Efficient Mechanism for Charging (EMC), to determine an assignment between EVs and CSs and pricing strategies. Then, both theoretical analysis and numerical simulations show the correctness and effectiveness of our proposed algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Blockchain

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Localized heat diffusion in topological thermal materials

arXiv

引用

arXiv 2021年

作者： Qi, Minghong Wang, Dong Cao, Pei-Chao Zhu, Xue-Feng Qiu, Cheng-Wei Chen, Hongsheng Li, Ying Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou310027 China International Joint Innovation Center Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang The Electromagnetics Academy Zhejiang University Zhejiang University Haining314400 China School of Physics Innovation Institute Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

Various unusual behaviors of artificial materials are governed by their topological properties, among which the edge state at the boundary of a photonic or phononic lattice has been captivated as a popular notion. However, this remarkable bulk-boundary correspondence and the related phenomena are missing in thermal materials. One reason is that heat diffusion is described in a non-Hermitian framework because of its dissipative nature. The other is that the relevant temperature field is mostly composed of modes that extend over wide ranges, making it difficult to be rendered within the tight-binding theory as commonly employed in wave physics. Here, we overcome the above challenges and perform systematic studies on heat diffusion in thermal lattices. Based on a continuum model, we introduce a state vector to link the Zak phase with the existence of the edge state, and thereby analytically prove the thermal bulk-boundary correspondence. We experimentally demonstrate the predicted edge states with a topologically protected and localized heat dissipation capacity. Our finding sets up a solid foundation to explore the topology in novel heat transfer manipulations. © 2021, CC BY.

关键词： Topology

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Adaptive Random Testing in Detecting Layout Faults of Web Applications

Adaptive Random Testing in Detecting Layout Faults of Web Ap...

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作者： Selay, Elmin Zhou, Zhi Quan Chen, Tsong Yueh Kuo, Fei-Ching Institute of Cybersecurity and Cryptology School of Computing and Information Technology University of Wollongong WollongongNSW Australia Department of Computer Science and Software Engineering Swinburne University of Technology HawthornVIC3122 Australia

As part of a software testing process, output verification poses a challenge when the output is not numeric or textual, such as graphical. The industry practice of using human oracles (testers) to observe and verify the correctness of the actual results is both expensive and error-prone. In particular, this practice is usually unsustainable when developing web applications - the most popular software of our era. This is because web applications change frequently due to the fast-evolving requirements amid popular demand. To improve the cost effectiveness of browser output verification, in this study we design failure-based testing techniques and evaluate the effectiveness and efficiency thereof in the context of web testing. With a novel application of the concept of adaptive random sequence (ARS), our approach leverages peculiar characteristics of failure patterns found in browser layout rendering. An empirical study shows that the use of failure patterns and inclination to guide the testing flow leads to more cost-effective results than other classic methods. This study extends the application of ARSs from the input space of programs to their output space, and also shows that adaptive random testing (ART) can outperform random testing (RT) in both failure detection effectiveness (in terms of F-measure) and failure detection efficiency (in terms of execution time). © 2018 World Scientific Publishing Company.

关键词： Cost effectiveness

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Comparative modelling and verification of Pthreads and Dthreads

Comparative modelling and verification of Pthreads and Dthre...

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作者： Fei, Yuan Zhu, Huibiao Wu, Xi Fang, Huixing Qin, Shengchao Shanghai Key Laboratory of Trustworthy Computing MOE International Joint Laboratory of Trustworthy Software International Research Center of Trustworthy Software East China Normal University Shanghai China School of Computing University of Teesside Middlesbrough United Kingdom School of Computer Science and Software Engineering Shenzhen University Shenzhen China School of Information Technology and Electrical Engineering University of Queensland Brisbane Australia School of Information Engineering Yangzhou University Jiangsu China

The POSIX threads (Pthreads) library is a thread API for C/C++ to control parallel threads and spawn concurrent process flows. Programming in Pthreads usually suffers from undesirable deadlock, data race, and race condition problems due to the potential nondeterministic execution behaviors between parallel threads. Dthreads, as another multithreading model that re-implements Pthreads, was proposed by Liu et al for efficient deterministic multithreading. They found out that, under specific test cases, Dthreads can effectively prevent data races. However, no comparison test has been made with Pthreads. To perform a formal comparison between Pthreads and Dthreads over deadlocks, data races, and race conditions, in this paper, we adopt CSP (communicating sequential processes) as a formal model for specifying part of API functions in Pthreads and Dthreads and illustrate the model construction using 4 classical example programs. By feeding the models into the model checker PAT (process analysis toolkit), we have verified that deadlocks and data races exist in Pthreads, but do not exist in Dthreads, for the considered programs. We have also found that neither of them can prevent race conditions. Our comparative modelling and verification of Pthreads and Dthreads show that though Dthreads cannot prevent all the deadlock situations, shown by verification results of another 2 example programs, Dthreads is better than Pthreads on eliminating data races and preventing deadlocks. Considering limited scalability of Dthreads, we have introduced a new programming model to support coarse granularity in bank transfer. Our modelling is also extended by covering the synchronization operations in Liu et al work. Copyright © 2017 John Wiley & Sons, Ltd.

关键词： C++ (programming language)

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Multi-Layer Graph Generative Model Using AutoEncoder for Recommendation Systems

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Journal on Big Data 2019年第1期1卷 1-7页

作者： Syed Falahuddin Quadri Xiaoyu Li Desheng Zheng Muhammad Umar Aftab Yiming Huang School of Information and Software Engineering University of Electronics Science and Technology of ChinaChengdu610054China School of Computer Science Southwest Petroleum University8 Xindu AvenueChengdu610500China University of Maryland Institute for Advanced Computer Studies Bldg 224 Stadium Dr Room 3100College ParkMaryland20742USA

Given the glut of information on the web,it is crucially important to have a system,which will parse the information appropriately and recommend users with relevant information,this class of systems is known as Recommendation Systems(RS)-it is one of the most extensively used systems on the web ***,Deep Learning(DL)models are being used to generate recommendations,as it has shown state-of-the-art(SoTA)results in the field of Speech Recognition and computer Vision in the last ***,the RS is a much harder problem,as the central variable in the recommendation system’s environment is the chaotic nature of the human’s purchasing/consuming behaviors and their *** user-item interactions cannot be fully represented in the Euclidean-Space,as it will trivialize the interaction and undermine the implicit interactions *** to preserve the implicit as well as explicit interactions of user and items,we propose a new graph based recommendation *** fundamental idea behind this framework is not only to generate the recommendations in the unsupervised fashion but to learn the dynamics of the graph and predict the short and long term interest of the *** this paper,we propose the first step,a heuristic multi-layer high-dimensional graph which preserves the implicit and explicit interactions between users and items using SoTA Deep Learning models such as *** generate recommendation from this generated graph a new class of neural network architecture-Graph Neural Network-can be used.

关键词： Recommendation systems autoencoder knowledge representation representation learning graph-structured data

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Target tracking based on KCF combining with spatio-temporal context learning

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International Journal of Performability engineering 2018年第2期14卷 386-395页

作者： Wang, Aili Yang, Zhennan Chen, Yushi Iwahori, Yuji Higher Education Key Lab for Measure and Control Technology and Instrumentations of Heilongjiang Harbin University of Science and Technology Harbin150080 China School of Electronics and Information Engineering Harbin Institute of Technology Harbin150001 China Dept of Computer Science Chubu University Aichi Japan

Most target tracking is based on a lot of samples training to build the model of the target, which is then carried on the tracking processing. This will need to choose a lot of tracked target samples for learning and training. However, there are all kinds of deformation of the training samples, including variety of light and scale, and so on, causing the long computation time, high computational complexity, and less robustness. The traditional kernel correlation filtering (KCF) tracking is through online learning of the first frame in the target vide. It then uses cyclic matrix to strengthen samples robustness, reducing the complexity of the calculation and time. But, the traditional KCF nuclear is unsatisfactory used for complex scenarios and quick treatment. In this paper, under the framework of the KCF, the target context information is introduced to make the tracking have better robustness and a better effect to deal with complex scenarios. © 2018 Totem Publisher, Inc. All rights reserved.

关键词： Target tracking

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Online Intelligent Resource Management for Power-Delay Tradeoff in Backhaul-Limited Mobile Edge Computing Systems

Online Intelligent Resource Management for Power-Delay Trade...

引用

Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Yuan Sun Gang Yang Xing-She Zhou Science and Technology on Information Systems Engineering Laboratory The 28th Research Institute of China Electronics Technology Group Corporation Nanjing China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing China School of Computer Science and Engineering Northwestern Polytechnical University Xi???an China

ISBN: (数字)9781728140346

ISBN: (纸本)9781728140353

Mobile edge computing (MEC) has emerged as a promising paradigm to enhance the quality of experience for mobile device users, as it can offload computation intensive tasks from mobile devices to edge clouds. Nevertheless, task offloading also incurs additional overhead in both power consumption and execution delay. In essence, energy consumption and task delay cannot be optimized simultaneously as these two objectives contradict each other. Although many studies have been conducted to make tradeoff between them, the backhaul limitation of MEC-enabled wireless networks has not been tackled. In this paper, we study the power-delay tradeoff for MEC in backhaul-limited wireless networks. An average weighted sum power consumption minimization problem with task buffer stability constraints is formulated to investigate the problem, and a Lyapunouv Optimization based online intelligent computation and communication resource management algorithm is also proposed to solve it. In particular, at each time slot, optimal CPU-cycle frequencies, transmit power and backhaul capacity allocation are efficiently determined. Performance analysis indicates that under the proposed algorithm an [O(1/V), O(V)] tradeoff exists between the power consumption and execution delay, where V is a control parameter. Finally, simulations are conducted to validate the analytic results and demonstrate the changes of the system performance with various algorithm parameters.

关键词： Task analysis Mobile handsets Power demand Resource management Delays Optimization Wireless communication

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Is heuristic sampling necessary in training deep object detectors?

arXiv

引用

arXiv 2019年

作者： Chen, Joya Liu, Dong Xu, Tong Wu, Shiwei Cheng, Yifei Chen, Enhong Anhui Province Key Lab of Big Data Analysis and Application University of Science and Technology of China School of Computer Science and Technology School of Data Science Department of Electronic Engineering and Information Science University of Science and Technology of China

To train accurate deep object detectors under the extreme foreground-background imbalance, heuristic sampling methods are always necessary, which either re-sample a subset of all training samples (hard sampling methods, e.g. biased sampling, OHEM), or use all training samples but re-weight them discriminatively (soft sampling methods, e.g. Focal Loss, GHM). In this paper, we challenge the necessity of such hard/soft sampling methods for training accurate deep object detectors. While previous studies have shown that training detectors without heuristic sampling methods would significantly degrade accuracy, we reveal that this degradation comes from an unreasonable classification gradient magnitude caused by the imbalance, rather than a lack of re-sampling/re-weighting. Motivated by our discovery, we propose a simple yet effective Sampling-Free mechanism to achieve a reasonable classification gradient magnitude by initialization and loss scaling. Unlike heuristic sampling methods with multiple hyperparameters, our Sampling-Free mechanism is fully data diagnostic, without laborious hyperparameters searching. We verify the effectiveness of our method in training anchor-based and anchor-free object detectors, where our method always achieves higher detection accuracy than heuristic sampling methods on COCO and PASCAL VOC datasets. Our Sampling-Free mechanism provides a new perspective to address the foreground-background imbalance. Our code is released at https://***/ChenJoya/sampling-free. Copyright © 2019, The Authors. All rights reserved.

关键词： Object detection

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