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Proceedings of the 36th International Conference on Neural Information Processing Systems

作者： Weixia Zhang Dingquan Li Xiongkuo Min Guangtao Zhai Guodong Guo Xiaokang Yang Kede Ma MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Network Intelligence Research Department Peng Cheng Laboratory Department of Computer Science and Electrical Engineering West Virginia University Department of Computer Science City University of Hong Kong

ISBN: (纸本)9781713871088

No-reference image quality assessment (NR-IQA) aims to quantify how humans perceive visual distortions of digital images without access to their undistorted references. NR-IQA models are extensively studied in computational vision, and are widely used for performance evaluation and perceptual optimization of man-made vision systems. Here we make one of the first attempts to examine the perceptual robustness of NR-IQA models. Under a Lagrangian formulation, we identify insightful connections of the proposed perceptual attack to previous beautiful ideas in computer vision and machine learning. We test one knowledge- driven and three data-driven NR-IQA methods under four full-reference IQA models (as approximations to human perception of just-noticeable differences). Through carefully designed psychophysical experiments, we find that all four NR- IQA models are vulnerable to the proposed perceptual attack. More interestingly, we observe that the generated counterexamples are not transferable, manifesting themselves as distinct design flows of respective NR-IQA methods.

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Improving the Transmission Rate by A Two-Phase Hybrid Duplex Scheme for Gaussian Relay Channel

Improving the Transmission Rate by A Two-Phase Hybrid Duplex...

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IEEE International Conference on Communications (ICC)

作者： Jianxin Duan Zhengchuan Chen Zhong Tian Min Wang Li Zhen Dapeng O. Wu Tony Q. S. Quek School of Microelectronics and Communication Engineering. Chongquing University Chongqing China Shaanxi Key Laboratory of Information Communication Network and Security Xi'an University of Posts and Telecommunications Xi'an China School of Optoelectronics Engineering Chongqing University of Posts and Telecommunications Chongqing China Department of Computer Science City University of Hong Kong Hong Kong Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Combining half-duplex (HD) and full-duplex (FD) is promising in improving the information transmission rate of relay channels. This work proposes a novel two-phase hybrid duplex scheme for Gaussian relay channel where the relay operates in FD mode for a fraction of time and only transmits information for the rest of time. The achievable rate of the proposed hybrid duplex scheme is characterized in detail. Based on the obtained result, a joint time division and power allocation problem is formulated to maximize the achievable rate. In particular, the formulated problem is solved through a two-step optimization method. Firstly, the optimal relay power allocation is obtained for given time division factors. Then, the achievable rate maximization problem is addressed by finding the optimal time division factors. The closed-form expression for the maximal achievable rate is derived for some specific cases. Numerical results show that the proposed two-phase hybrid duplex scheme significantly improves the achievable rate of Gaussian relay channel compared with existing benchmark schemes.

关键词： Closed-form solutions Half-duplex system Optimization methods Information processing Full-duplex system Benchmark testing Resource management

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A 3D Modeling Method for Scattering on Rough Surfaces at the Terahertz Band

arXiv

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arXiv 2023年

作者： Chen, Ben Guan, Ke He, Danping Xie, Pengxiang Zhong, Zhangdui Dou, Jianwu Mumtaz, Shahid Bazzi, Wael State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen518055 China School of Engineering Nottingham Trent University United Kingdom Electrical and Computer Engineering Department American University in Dubai Dubai United Arab Emirates

The terahertz (THz) band (0.1-10 THz) is widely considered to be a candidate band for the sixth-generation mobile communication technology (6G). However, due to its short wavelength (less than 1 mm), scattering becomes a particularly significant propagation mechanism. In previous studies, we proposed a scattering model to characterize the scattering in THz bands, which can only reconstruct the scattering in the incidence plane. In this paper, a three-dimensional (3D) stochastic model is proposed to characterize the THz scattering on rough surfaces. Then, we reconstruct the scattering on rough surfaces with different shapes and under different incidence angles utilizing the proposed model. Good agreements can be achieved between the proposed model and full-wave simulation results. This stochastic 3D scattering model can be integrated into the standard channel modeling framework to realize more realistic THz channel data for the evaluation of 6G. Copyright © 2023, The Authors. All rights reserved.

关键词： Stochastic systems

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Continuous Prediction of Leg Kinematics during Walking using Inertial Sensors, Smart Glasses, and Embedded Computing

Continuous Prediction of Leg Kinematics during Walking using...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Oleksii Tsepa Roman Burakov Brokoslaw Laschowski Alex Mihailidis Department of Computer Science AGE-WELL Networks of Centres of Excellence program University of Toronto and the Vector Institute for Artificial Intelligence Department of Mathematical Methods of System Analysis Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Department of Computer Science University of Toronto Toronto ON Canada Department of Mathematics National University of Kyiv-Mohyla Academy Kyiv Ukraine Department of Mechanical and Industrial Engineering University of Toronto Toronto ON Canada Toronto Rehabilitation Institute University Health Network Toronto ON Canada Institute of Biomedical Engineering University of Toronto Toronto ON Canada

Unlike traditional hierarchical controllers for robotic leg prostheses and exoskeletons, continuous systems could allow persons with mobility impairments to walk more naturally in real-world environments without requiring high-level switching between locomotion modes. To support these next-generation controllers, we developed a new system called KIFNet (Kinematics and Image Fusing network) that uses lightweight and efficient deep learning models to continuously predict the leg kinematics during walking. We tested different sensor fusion methods to combine kinematics data from inertial sensors and computer vision data from smart glasses and found that adaptive instance normalization achieved the lowest RMSE predictions for knee and ankle joint kinematics. We also deployed our model on an embedded device. Without inference optimization, our model was 20 times faster than the previous state-of-the-art and achieved 20% higher prediction accuracies, and during some locomotor activities like stair descent, decreased RMSE up to 300%. With inference optimization, our best model achieved 125 FPS on an NVIDIA Jetson Nano. These results demonstrate the potential to build fast and accurate deep learning models for continuous prediction of leg kinematics during walking based on sensor fusion and embedded computing, therein providing a foundation for real-time continuous controllers for robotic leg prostheses and exoskeletons.

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Logical Relation Modeling and Mining in Hyperbolic Space for Recommendation

Logical Relation Modeling and Mining in Hyperbolic Space for...

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International Conference on Data engineering

作者： Yanchao Tan Hang Lv Zihao Zhou Wenzhong Guo Bo Xiong Weiming Liu Chaochao Chen Shiping Wang Carl Yang College of Computer and Data Science Fuzhou University Fuzhou China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China Institute for Artificial Intelligence University of Stuttgart Stuttgart Germany College of Computer Science Zhejiang University Hangzhou China Department of Computer Science Emory University Atlanta United States

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

The sparse interactions between users and items have aggravated the difficulty of their representations in recommender systems. Existing methods leverage tags to alleviate the sparsity problem but ignore prevalent logical relations among items and tags (e.g., membership, hierarchy, and exclusion), which can be leveraged to enhance the accuracy of modeling user preferences and conducting recommendations. To this end, we propose to extract logical relations among item tags from existing tag taxonomies and exploit the individual strengths of the Poincaré and the Lorentz models in hyperbolic space for logical relation modeling towards enhanced recommendations. Moreover, we find that the logical relations directly extracted from existing tag taxonomies can be inaccurate and coarse. Therefore, we further devise innovative consistency-based and granularity- based weighting mechanisms based on user behavior patterns for data-driven logical relation mining that can be jointly optimized along with recommendations in an end-to-end fashion. Extensive experiments on four real-world benchmark datasets show drastic performance gains brought by our proposed framework, which constantly achieves an average of 8.25% improvement over state-of-the-art competitors regarding both Recall and NDCG metrics. Insightful case studies further demonstrate that our automatically refined logical relations are highly accurate and interpretable.

关键词： Measurement Accuracy Taxonomy Semantics Predictive models Performance gain Linguistics

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Blind Quality Assessment of 3D Dense Point Clouds with Structure Guided Resampling

arXiv

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arXiv 2022年

作者： Zhou, Wei Yang, Qi Jiang, Qiuping Zhai, Guangtao Lin, Weisi The Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada The Tencent MediaLab Shanghai200030 China The School of Information Science and Engineering Ningbo University Ningbo315211 China The Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai200240 China The School of Computer Science and Engineering Nanyang Technological University 639798 Singapore

Objective quality assessment of 3D point clouds is essential for the development of immersive multimedia systems in real-world applications. Despite the success of perceptual quality evaluation for 2D images and videos, blind/no-reference metrics are still scarce for 3D point clouds with large-scale irregularly distributed 3D points. Therefore, in this paper, we propose an objective point cloud quality index with Structure Guided Resampling (SGR) to automatically evaluate the perceptually visual quality of 3D dense point clouds. The proposed SGR is a general-purpose blind quality assessment method without the assistance of any reference information. Specifically, considering that the human visual system (HVS) is highly sensitive to structure information, we first exploit the unique normal vectors of point clouds to execute regional pre-processing which consists of keypoint resampling and local region construction. Then, we extract three groups of quality-related features, including: 1) geometry density features;2) color naturalness features;3) angular consistency features. Both the cognitive peculiarities of the human brain and naturalness regularity are involved in the designed quality-aware features that can capture the most vital aspects of distorted 3D point clouds. Extensive experiments on several publicly available subjective point cloud quality databases validate that our proposed SGR can compete with state-of-the-art full-reference, reduced-reference, and no-reference quality assessment algorithms. © 2022, CC BY.

关键词： Multimedia systems

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Wearable Devices for Early Warning of Acute Exacerbation in Chronic Obstructive Pulmonary Disease Patients

Wearable Devices for Early Warning of Acute Exacerbation in ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Chun-Chieh Hsiao Cai-Ying Chu Ren-Guey Lee Jer-Hwa Chang Chwan-Lu Tseng Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taoyuan Taiwan R.O.C Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan R.O.C School of Respiratory Therapy College of Medicine Taipei Medical University Department of Internal Medicine Wan Fang Hospital Taipei Medical University Taipei Taiwan R.O.C

Chronic Obstructive Pulmonary Disease (COPD) is one of the leading causes of chronic diseases and deaths worldwide. When acute exacerbation of COPD (AECOPD) occurs, the frequency and severity of malignant attacks are highly correlated with the mortality rate. The purpose of this study is to use wearable devices to collect the physiological parameters of patients for early warning and prevention of complications of possible AECOPD attacks in the future. The subjects used wearable devices to measure Heart Rate Variability (HRV) at home. Physiological data and health assessment scales of 13 COPD patients were collected during the 6-month study period. According to the scale responses, the severity of the condition was classified into mild AE and no AE. If the subject needed emergency medical treatment due to COPD, it was classified as AE. With the scale classification method, a machine-learning Random Forest (RF) algorithm is used to predict the occurrence of AECOPD in the next 7 days, so as to prevent the deterioration of the disease in advance. The results of the study show that the accuracy of the model is more than 92% according to different classification methods, and using the mixed-parameter model as a feature for the prediction can improve the sensitivity of the original warning mechanism. In order to provide predictive results to the nursing staff at any time, the user interface of our system would transmit a warning message to remind the nursing staff to ensure early medical intervention for patients to avoid the occurrence of AECOPD.

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Access Control Policy Based on Friend Circle

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computers, Materials & Continua 2020年第3期62卷 1143-1159页

作者： Qin Liu Tinghuai Ma Fan Xing Yuan Tian Abdullah Al-Dhelaan Mohammed Al-Dhelaan School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China CICAEET Jiangsu Engineering Centre of Network MonitoringNanjing University of Information Science and TechnologyNanjing210044China Computer Science Department College of Computer and Information SciencesKing Saud UniversityRiyadh11362Saudi Arabia

Nowadays,the scale of the user’s personal social network(personal network,a network of the user and their friends,where the user we call“center user”)is becoming larger and more *** is difficult to find a suitable way to manage them *** order to solve this problem,we propose an access control model for social network to protect the privacy of the central users,which achieves the access control accurately and *** on the hybrid friend circle detection algorithm,we consider the aspects of direct judgment,indirect trust judgment and malicious users,a set of multi-angle control method which could be adapted to the social network environment is ***,we propose the solution to the possible conflict of rights in the right control,and assign the rights reasonably in the case of guaranteeing the privacy of the users.

关键词： Social network privacy protection circle of friends access control

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On the Effectiveness of Function-Level Vulnerability Detectors for Inter-Procedural Vulnerabilities

arXiv

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arXiv 2024年

作者： Li, Zhen Wang, Ning Zou, Deqing Li, Yating Zhang, Ruqian Xu, Shouhuai Zhang, Chao Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Department of Computer Science University of Colorado Colorado Springs Colorado SpringsCO United States Institute for Network Sciences and Cyberspace Tsinghua University Beijing China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security Cluster and Grid Computing Lab China JinYinHu Laboratory Wuhan China

Software vulnerabilities are a major cyber threat and it is important to detect them. One important approach to detecting vulnerabilities is to use deep learning while treating a program function as a whole, known as function-level vulnerability detectors. However, the limitation of this approach is not understood. In this paper, we investigate its limitation in detecting one class of vulnerabilities known as inter-procedural vulnerabilities, where the to-be-patched statements and the vulnerability-triggering statements belong to different functions. For this purpose, we create the first Inter-Procedural Vulnerability Dataset (InterPVD) based on C/C++ open-source software, and we propose a tool dubbed VulTrigger for identifying vulnerability-triggering statements across functions. Experimental results show that VulTrigger can effectively identify vulnerability-triggering statements and inter-procedural vulnerabilities. Our findings include: (i) inter-procedural vulnerabilities are prevalent with an average of 2.8 inter-procedural layers;and (ii) function-level vulnerability detectors are much less effective in detecting to-be-patched functions of inter-procedural vulnerabilities than detecting their counterparts of intra-procedural vulnerabilities. Copyright © 2024, The Authors. All rights reserved.

关键词： Open source software

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Safety Guaranteed Power-Delivered-to-Load Maximization for Magnetic Wireless Power Transfer

Safety Guaranteed Power-Delivered-to-Load Maximization for M...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Wangqiu Zhou Xinyu Wang Hao Zhou Shenyao Jiang Zhi Liu Yusheng Ji LINKE Lab School of Computer Science and Technology University of Science and Technology of China CAS Key Laboratory of Wireless-Optical Communications University of Science and Technology of China Deqing Alpha Innovation Institute Huzhou China Department of Computer and Network Engineering The University of Electro-Communications Tokyo Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo Japan

ISBN: (数字)9798350383508

ISBN: (纸本)9798350383515

Electromagnetic radiation (EMR) safety has always been a critical reason for hindering the development of magneticenabled wireless power transfer technology. People focus on the actual received energy at charging devices while paying attention to their health. Thus, we study this significant problem in this paper, and propose a universal safety guaranteed power-delivered-to-load (PDL) maximization scheme (called SafeGuard). Technically, we first utilize the off-the-shelf electromagnetic simulator to perform the EMR distribution analysis to ensure the universality of the method. Then, we innovatively introduce the concept of multiple importance sampling for achieving efficient EMR safety constraint extraction. Finally, we treat the proposed optimization problem as an optimal boundary point search problem from the perspective of space geometry, and devise a brand-new grid-based multi-constraint parallel processing algorithm to efficiently solve it. We implement a system prototype for SafeGuard, and conduct extensive experiments to evaluate it. The results indicate that our SafeGuard can obviously improve the achieved PDL by up to 1.75× compared with the state-of-the-art baseline while guaranteeing EMR safety. Furthermore, SafeGuard can accelerate the solution process by 29.12× compared with the traditional numerical method to satisfy the fast optimization requirement of wireless charging systems.

关键词： Performance evaluation Monte Carlo methods System performance Inductive charging Prototypes Wireless power transfer Parallel processing

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