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19th CCF Conference on computer Supported Cooperative Work and Social Computing, ChineseCSCW 2024

作者： Ma, Xinhong Zeng, Yehong Qi, Mingyang Si, Yali Chen, Zhen School of Information Science and Engineering Yanshan University Qinhuangdao066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao066004 China Changshu Institute of Technology Jiangsu Changshu215500 China

ISBN: (纸本)9789819623754

In the era of open cloud, cloud API is an important component and key enabling technology to achieve efficient data transmission, artificial intelligence algorithm empowerment, and software development cost reduction and efficiency. With the proliferation of cloud API with similar functionality, quality of service (QoS) becomes essential for differentiating cloud API performance, and QoS-driven prediction for cloud API has emerged as a critical topic for high quality cloud API selection. However, existing methods often inadequately utilize contextual information in resource-constrained scenario, limiting the improvement of cloud API prediction performance. We in this paper propose a geo-enhanced high-order feature interaction network (GHFIN) for cloud API QoS prediction. Firstly, a correlation analysis was conducted on real-world QoS dataset to explore the relationship between QoS data and geospatial context. Then, we design a geo-enhanced strategy that effectively utilizes the hierarchical relationships of geospatial entities (country, province, city, and district) through an offline real-time coordinate conversion module. On this basis, a geo-enhanced cloud API QoS prediction network GHFIN was designed, which aims to learn the high-order feature interactions through layer-wise feature stacking. Experimental results on two real-world QoS datasets illustrate the effectiveness of GHFIN compared to the classic and state-of-the-art methods, and our extensive analysis shows how the geospatial context and high-order feature interaction positively impact the performance of cloud API QoS prediction. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Quality of service

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FaceGCN: Structured Priors Inspired Graph Convolutional Networks for Blind Face Restoration

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IEEE Transactions on Circuits and Systems for Video technology 2025年

作者： Yan, Weidan Shao, Wenze Zhang, Dengyin Xiao, Liang Nanjing University of Posts and Telecommunications School of Internet of Things Nanjing210003 China Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Intelligent Information Processing and Communication Technology Nanjing210003 China Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210094 China

Facial image restoration has gained a tremendous progress since the increasing boom of the deep learning methods. Owing to its nature of strong ill-posedness, different categories of a-priori constraints have been harnessed or embedded in the existing deep architectures. While, as it turns to blind face restoration with more complicated degradations, the challenge becomes greater. In this paper, a further insightful step is taken by exploring the potentials of the graph convolutional networks (GCN) in conjunction with the structured priors for the blind problem. Specifically, a lightweight yet physically more intuitive model termed FaceGCN is proposed. On the one hand, a dynamic generator of facial adjacency matrices is constructed assisted by two self-supervised losses, allowing a sparse, accurate, and adaptive construction of case-specific face graphs with facial feature components as nodes. On the other hand, to model well the joint local-nonlocal correlations among various facial feature components, a kind of novel strip-attention GCN modules is correspondingly developed by splitting facial feature maps into intra- and inter-strips in both horizontal and vertical orientations, respectively. Extensive experimental results show that FaceGCN has achieved comparable or even superior performance to state-of-the-art methods, yet at a considerably less computational cost. © 1991-2012 IEEE.

关键词： Convolution

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Discrete-time Formation Control With Attitude Alignment: A Geometric Approach under Ergodic Products

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IEEE Transactions on Control of Network Systems 2025年

作者： Li, Zhen Tang, Yang Zhang, Wenbing Fan, Yongqing Huang, Tingwen Xi-an University of Posts and Telecommunications School of Automation Xian710121 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Shanghai200237 China Yangzhou University Department of Mathematics Jiangsu225002 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

Assuming agents possess sensing capabilities and dynamics relative to their body coordinate frames, this paper addresses a displacement-based strategy for discrete-time formation control through attitude synchronization. Unlike the Eulerian approximation, the first challenge lies in developing discrete-time models that capture both position and attitude motions, thereby complementing existing continuous-time systems with a discretized version. Then, two leader-following control protocols are designed, incorporating a jointly-connected topology to relax the connectivity requirements. The analysis of these systems often relies on the Lyapunov function, the existence of which may be hard to guarantee. Consequently, geometric properties of several polytopes are explored under the dynamic topologies and time-varying parameters. By extending the ergodicity results to leader-following scenarios, these properties are characterized as positively invariant sets. This invariance, which is independent of the existence of the Lyapunov function or the solvability of its associated criteria, provides a beneficial tool for analyzing time-variant systems. Utilizing this invariance and some mathematical techniques, the desired formation shape can be achieved in the cases where the attitudes of the followers synchronize with the leader. Finally, a numerical simulation validates the results. © 2014 IEEE.

关键词： Lyapunov functions

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Survey of Spectral Amplitude Coding Optical Code Division Multiple Access Families

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Journal of Lightwave technology 2025年

作者： Ullah, Rahat Ullah, Sibghat Ali, Aitizaz Jianxin, Ren Alwageed, Hathal Salamah Yaya, Mao Qi, Zhipeng Yu, Yongyi Imtiaz, Waqas A. Khan, Maqbool School of Physics and Optoelectronics Nanjing University of Information Science and Technology China Jiangsu Key Laboratory for Optoelectronic Detection of Atmosphere and Ocean Nanjing University of Information Science Technology Nanjing210044 China Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection Nanjing University of Information Science Technology Nanjing210044 China School of Electronics Science and Technology Southeast University China School of Technology NSF Group Asia Pacific University Malaysia Saudi Arabia College of Computer Science Jouf University Saudi Arabia Electrical Engineering Department University of Engineering and Technology Peshawar Pakistan Pak-Austra Fachhochschule Haripur Pakistan

Quest for high capacity communication have led the research community to explore a plethora of technologies. Among these, optical code division multiple access (OCDMA) technique stands tall with support for high data rate connectivity in terms of data, reach and the number of subscribers. The development of OCDMA based networks started with the design and implementation of one dimensional (1D) codes, which provides effective correlation properties to reduce the effect of interference due to multiple users (MAI) and phase-induced-intensity-noise (PIIN) in order to provide the required system capacity. Several families of codes have been developed to determine the most suitable combination between code length, weight against the auto- and cross-correlation property respectively. This survey paper will analyze the most commonly used families of codes from spectral amplitude coding (SAC) based OCDMA systems names Double Weight (DW) codes, Diagonal codes , zero cross-correlation (ZCC) codes, and hybrid codes in terms of different performance parameters and identify the most suitable combination of code length (L), code weight (w), and cross-correlation (λC) to be utilized for next generation communication applications that can provide high capacity and cardinality. © 1983-2012 IEEE.

关键词： Passive optical networks

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Plasmon-assisted channel-tunable bistable states in a monolayer MoS2 nanoresonator coupled to a metallic nanoshell

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Optics Express 2025年第11期33卷 23568-23578页

作者： Jian-Bo Li Hong-Mei Gong Yu-Xiang Peng Si Xiao Jin-Bo Hu Lin-Wen Long Department of Physics Hunan Province Key Laboratory of Materials Surface & Interface Science and Technology Central South University of Forestry and Technology Changsha 410004 China jbli_opt@*** jbli_opt@*** School of Optical and Electronic Information & Jiangsu/Suzhou Key Laboratory of Biophotonics & International Joint Metacenter for Advanced Photonics and Electronics Suzhou City University Suzhou 215104 China hmgong@*** School of Physics Hunan Key Laboratory of Super microstructure and Ultrafast Process Central South University Changsha 410083 China sixiao@*** College of Materials and Energy Central South University of Forestry and Technology Changsha 410004 China

We study how to obtain the channel-tunable bistable states in a coupled system consisting of a monolayer MoS 2 nanomechanical resonator (NR) and a metallic nanoshell (MNS) beyond the dipole approximation. The MNS is constructed by a metallic core and a dielectric shell. The calculated results show that the linear absorption spectrum exhibits some new features, such as three-phonon resonance, Rayleigh resonance, and ac-Stark resonance. In a strong exciton-plasmon coupling regime, the absorption peak and amplification peak in the absorption spectrum can be greatly enhanced by adjusting the exciton-phonon coupling strength. Especially, we plot the bistability phase diagrams in the system’s parameter space and highlight the strong dependency of the lower (upper) bistable threshold on the pumping intensity, the MNS-NR distance, and the dielectric shell thickness. The ratio of linear absorption in the upper and lower stable states can reach 42. For a given MNS with a fixed shell thickness, it is easy to achieve single-channel or dual-channel bistable states by only adjusting the exciton-phonon coupling strength via modulation of the length of the MoS 2 nanosheet along the NR axis. The findings obtained here are very useful for extensive applications such as optical memory cells and channel-tunable bistable switches.

关键词： Absorption spectroscopy Light propagation Metal nanoparticles Nonlinear absorption Optical properties Slow light

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Fault Detection of Nonlinear Dynamic Non-Stationary processes Under Stochastic Operating Modes Using Multi-Batch Differentiation Transformation With Kernel CCA

SSRN

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SSRN 2025年

作者： Feng, Liwei Tian, Bin Cui, Zhenhao Zhao, Chenhao Li, Yuan College of Science Shenyang University of Chemical Technology Shenyang110142 China College of Computer Science and Technology Shenyang University of Chemical Technology Shenyang110142 China College of Information Engineering Shenyang University of Chemical Technology Shenyang110142 China Key Laboratory of Intelligent Technology for Chemical Process Industry of Liaoning Province Shenyang110142 China

Nonlinear multi-batch dynamic non-stationary processes under stochastic operating conditions have characteristics such as inter-batch variability, nonlinearity and dynamic non-stationarity. Due to the influence of process characteristics, the traditional single-batch fault detection methods do not extract features in a comprehensive way, the multi-batch methods have large modeling bias, and they are difficult to extract the non-stationary feature information. The methods of Multi-batch Weighted Differentiation (MWD), Multi Standard Score (M-score), and Model Control Limit Averaging (MCLA) are proposed, and they are combined with KCCA to obtain the Multi-batch Difference Transformation with Kernel Canonical Correlation Analysis fault detection method (MDT-KCCA). MDT-KCCA is capable of adapting to the data differences of multi-batch with stochastic operating conditions, and extracting the feature information in dynamic non-stationary processes to establish an effective and stable monitoring model. Numerical simulation and penicillin fermentation monitoring experiments show that MDT-KCCA outperforms many comparative methods. © 2025, The Authors. All rights reserved.

关键词： Batch data processing

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Structural balance and evolution of cooperation in a population with hybrid interactions

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Physical Review E 2025年第4期111卷 044309-044309页

作者： Liming Zhang Lan Zhang Shun Gao Changwei Huang Qionglin Dai Jiangsu Key Laboratory of Educational Intelligent Technology School of Computer Science and Technology Jiangsu Normal University Xuzhou 221116 China School of Information Xi'an University of Finance and Economics Xi'an Shaanxi 710100 China School of Science Beijing University of Posts and Telecommunications Beijing 100876 People's Republic of China Blockchain and Distributed Ledger Technologies Faculty of Business Economics and Informatics University of Zurich Zurich 8050 Switzerland School of Computer Electronics and Information Guangxi University Nanning 530004 People's Republic of China

This study explores the evolution of cooperation in populations with mixed pairwise and three-body interactions, investigating the impact of higher-order interaction density ρ and individual interaction preference α. Our results reveal that sparse higher-order interactions markedly boost cooperation, exhibiting two critical phase transitions as ρ changes. These transitions underscore the delicate equilibrium needed for optimal cooperation, as excessive higher-order interactions can diminish returns. The preference parameter α significantly influences cooperation sustainability, with intermediate values maximizing cooperative outcomes, particularly when the temptation to defect r is not strong. Crucially, our findings demonstrate that hybrid social dilemmas structurally encode emergent cooperation pathways that are unattainable within homogeneous interaction frameworks, emphasizing the importance of modeling mixed interactions to capture real-world complexity. These insights offer valuable guidance for designing systems aimed at promoting cooperative behavior across social, ecological, and artificial domains.

关键词： Anthropogenic

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STGE-Former: Spatial-Temporal Graph-Enhanced Transformer for EEG-Based Major Depressive Disorder Detection

STGE-Former: Spatial-Temporal Graph-Enhanced Transformer for...

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

作者： Yu Chen Chunfeng Yang School of Computer Science and Engineering Southeast University Nanjing China Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Southeast University Ministry of Education China Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing Southeast University

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Applying deep learning techniques to Electroencephalogram (EEG) data has shown great potential in the field of depression detection. However, existing EEG-based depression detection models face challenges: they struggle to capture the complex spatiotemporal dependencies and the complementary nature of spatiotemporal information in EEG data; functional connectivity between brain regions is not sufficiently considered. To address these issues, we propose a new Spatial-Temporal Graph-Enhanced Transformer, named STGE-Former. Raw EEG signals are first mapped to Spatial-Temporal Shared Embeddings, then processed by the Spatial Attention Stream and the Temporal Graph-Enhanced Attention Stream to extract spatiotemporal complementary information, and finally classified through a classification head. Experimental results on the MODMA dataset show that our model outperforms existing methods in the task of EEG-Based MDD Detection. STGE-Former provides a promising approach for automatic depression detection. The code is available at https://***/RockyChen0205/STGE-Former.

关键词： Deep learning Electric potential Signal processing Depression Transformers Brain modeling Electroencephalography Spatiotemporal phenomena Speech processing Faces

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Micro-Expression key Frame Inference

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IEEE Transactions on Affective Computing 2025年

作者： Wang, Su-Jing Miao, Yu-Han Li, Jingting Zhou, Ling Dong, Zizhao Sun, Mengyi Fu, Xiaolan Institute of Psychology Chinese Academy of Sciences Key Laboratory of Behavior Sciences Beijing100101 China University of the Chinese Academy of Sciences Department of Psychology Beijing100049 China Jiangsu University Of Science and Technology School of Computer Science Jiangsu212028 China Macau University of Science and Technology Faculty of Information Technology Macau999078 China Shanghai Jiao Tong University School of Psychology Shanghai200030 China

Micro-expressions (MEs) are brief, involuntary facial movements critical for detecting lies, drawing growing interest in psychology and computer science. However, annotating ME can burden human coders with excessive time commitment and overwhelming information that compromises coding reliability and efficiency. Such difficulties in data annotation also led to the small sample size problem and hindered the development of ME analysis. Specifically, our psychological research highlights the complexities involved in human annotation of key frames. To facilitate the annotating process of ME, we proposed the Micro-Expression key Frame Inference (ME-KFI) problem, aiming to identify MEs' temporal locations from a single frame, reducing manual annotation effort. We propose a Micro-Expression Contrastive Identification Annotation (MECIA) method as a solution to ME-KFI, including three modules: a contrastive module, an identification module, and an annotation module, corresponding to the three steps of manual annotation. The network's outputs infer the key frame of ME clips. MECIA demonstrates superior performance over random baselines on SAMM and CAS(ME)2 databases and maintains comparable recognition accuracy with ground-truth clips. © 2010-2012 IEEE.

关键词： key frame inference micro-expression micro-expression annotation

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A Risk-Averse Just-In-Time Scheme for Learning-Based Operation of Microgrids With Coupled Electricity-Hydrogen-Ammonia Under Uncertainties

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IEEE Transactions on Sustainable Energy 2025年

作者： Li, Longyan Ning, Chao Pan, Guangsheng Zhang, Leiqi Gu, Wei Zhao, Liang Du, Wenli Shahidehpour, Mohammad Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China School of Electrical Engineering Southeast University Nanjing210096 China Zhejiang Key Laboratory of Distributed Generations and Microgrid Technology State Grid Zhejiang Electric Power Research Institute Hangzhou310014 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology China Department of Electrical and Computer Engineering Illinois Institute of Technology ChicagoIL60616 United States

This paper proposes a Risk-Averse Just-In-Time (RAJIT) operation scheme for Ammonia-Hydrogen-based Micro-Grids (AHMGs) to boost electricity-hydrogen-ammonia coupling under uncertainties. First, an off-grid AHMG model is developed, featuring a novel multi-mode ammonia synthesis process and a hydrogen-ammonia dual gas turbine with tunable feed-in ratios. Subsequently, a state-behavior mapping strategy linking hydrogen storage levels with the operation modes of ammonia synthesis is established to prevent cost-ineffective shutdowns. The proposed model substantially improves operational flexibility but results in a challenging nonlinear fractional program. Based upon this model, a data-driven RAJIT scheme is developed for the real-time rolling optimization of AHMGs. Unlike conventional one-size-fits-all schemes using one optimization method throughout, the data-driven RAJIT intelligently switches between cost-effective deterministic optimization and risk-averse online-learning distributionally robust optimization depending on actual risk profiles, thus capitalizing on the respective strengths of these two optimization methods. To facilitate the solution of the resulting nonlinear program, we develop an equivalent-reformulation-based solution methodology by leveraging a constraint-tightening technique. Numerical simulations demonstrate that the proposed scheme guarantees safety and yields an overall cost reduction up to 14.6% compared with several state-of-the-art methods. © 2025 IEEE.

关键词： Ammonia

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