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arXiv 2024年

作者： Zhang, Yichi Zhang, Yuchen Zhu, Lipeng Xiao, Sa Tang, Wanbin Eldar, Yonina C. Zhang, Rui National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu611731 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot7610001 Israel The Chinese University of Hong Kong Shenzhen China Shenzhen Research Institute of Big Data Shenzhen518172 China

In this correspondence, we propose a movable antenna (MA)-aided multi-user hybrid beamforming scheme with a sub-connected structure, where multiple movable sub-arrays can independently change their positions within different local regions. To maximize the system sum rate, we jointly optimize the digital beamformer, analog beamformer, and positions of subarrays, under the constraints of unit modulus, finite movable regions, and power budget. Due to the non-concave/non-convex objective function/constraints, as well as the highly coupled variables, the formulated problem is challenging to solve. By employing fractional programming, we develop an alternating optimization framework to solve the problem via a combination of Lagrange multipliers, penalty method, and gradient descent. Numerical results reveal that the proposed MA-aided hybrid beamforming scheme significantly improves the sum rate compared to its fixed-position antenna (FPA) counterpart. Moreover, with sufficiently large movable regions, the proposed scheme with sub-connected MA arrays even outperforms the fully-connected FPA array. Copyright © 2024, The Authors. All rights reserved.

关键词： Beamforming

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Multi-Band Compatible Camouflage Enabled by Phase Transition Modulation of Flexible Gst Films

SSRN

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SSRN 2024年

作者： Wang, Jian Wu, Zuoxu Sun, Xiaoyu Tang, Zunqian Wang, Chong Yu, Fangyuan Zhao, Zirui Mao, Jun Zhang, Qian Cao, Feng School of Science Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Harbin Institute of Technology Shenzhen518055 China School of Materials Science and Engineering Institute of Materials Genome & Big Data Harbin Institute of Technology Shenzhen518055 China State Key Laboratory of Advanced Welding and Joining China Fuzhou University China

With the rapid development of detection technology, there is an urgent need for multi-band compatible camouflage technology, particularly in the visible-infrared band. However, the conflicting requirements between camouflage across different bands and surface thermal management pose significant challenges in achieving synchronized control for multiple bands in diverse application environments and targets. Herein, we propose a spectrally selective emitter leveraging phase-change modulation of Ge2Sb2Te5, capable of achieving effective camouflage in both the visible band and two atmospheric windows over a wide temperature range. The designed emitters exhibit colorful appearances, compatible with various background environments, thereby ensuring the visible camouflage. Meanwhile, the emitters demonstrate low emissivity values of 0.1 in the MWIR band and 0.08 in the LWIR band, effectively reducing the infrared emission through atmospheric *** radiative temperatures of the optimized emitters in the MWIR and LWIR bands are reduced by 105 °C and 140 °C relative to the target surface (200 °C), respectively, providing excellent radiative suppression compared to similar studies. Remarkably, the designed emitter still demonstrates robust flexibility, making it suitable for a variety of targets with complex curved surfaces. This work paves the way for designing the flexible visible-infrared compatible camouflage coatings with integrated thermal management functionality. © 2024, The Authors. All rights reserved.

关键词： Germanium alloys

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Mining Repetitive Negative Sequential Patterns with Gap Constraints

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ACM Transactions on Knowledge Discovery from data 2025年第4期19卷

作者： Li, Yan Wang, Zhulin Liu, Jing Guo, Lei Fournier-Viger, Philippe Wu, Youxi Wu, Xindong School of Economics and Management Hebei University of Technology Tianjin China School of Artificial Intelligence Hebei University of Technology Tianjin China State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Hebei Key Laboratory of Big Data Computing Tianjin China Hefei University of Technology Hefei China

Sequential pattern mining (SPM) with gap constraints (or repetitive SPM or tandem repeat discovery in bioinformatics) can find frequent repetitive subsequences satisfying gap constraints, which are called positive sequential patterns with gap constraints (PSPGs). However, classical SPM with gap constraints cannot find the frequent missing items in the PSPGs. To tackle this issue, this article explores negative sequential patterns with gap constraints (NSPGs). We propose an efficient NSPG-Miner algorithm that can mine both frequent PSPGs and NSPGs simultaneously. To effectively reduce candidate patterns, we propose a pattern join strategy with negative patterns which can generate both positive and negative candidate patterns at the same time. To calculate the support (frequency of occurrence) of a pattern in each sequence, we explore a NegPair algorithm that employs a key-value pair array structure to deal with the gap constraints and the negative items simultaneously and can avoid redundant rescanning of the original sequence, thus improving the efficiency of the algorithm. To report the performance of NSPG-Miner, 11 competitive algorithms and 11 datasets are employed. The experimental results not only validate the effectiveness of the strategies adopted by NSPG-Miner but also verify that NSPG-Miner can discover more valuable information than the state-of-the-art algorithms. Copyright © 2025 held by the owner/author(s). Publication rights licensed to ACM.

关键词： sequential pattern mining gap constraint negative sequential pattern key-value pair

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Multimodal Dialogue Emotion Recognition Based on Label Optimization and Coarse-Grained Assisted Fine-Grained

Multimodal Dialogue Emotion Recognition Based on Label Optim...

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

作者： Zhibo Zhang Zhenyu Yang Yan Huang Baojie Xu Wenyue Hu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Multimodal dialogue emotion recognition integrates data from multiple modalities to accurately identify emotional states in conversations. However, differences in expression and information density across modalities complicate the fusion of features. Traditional methods may introduce redundant information from other utterances, reducing the accuracy of emotion recognition. Existing one-hot labels often fail to capture the full range of emotional expressions, leading to biased results. To address these issues, we propose a model that fuses different modalities within the same utterance to avoid redundancy. It employs a progressive classification process, refining emotion recognition from coarse to fine granularity. Additionally, we use emotion polarity probabilities as weights for fine-grained classification and introduce a multimodal information-rich label that considers both the data and their interactions. Experiments on IEMOCAP and MELD datasets demonstrate the model’s effectiveness, significantly improving dialog emotion recognition accuracy. Our code is available at https://***/r/LOCG-188E.

关键词： Emotion recognition Accuracy Fuses Refining Termination of employment Speech recognition Signal processing Speech processing Optimization Faces

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Joint Optimization of Transmit Power and Trajectory for UAV-Enabled data Collection With Dynamic Constraints

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IEEE Transactions on Communications 2025年

作者： Zhang, Hongyun Li, Bin Rong, Yue Zeng, Yong Zhang, Rui School of Aeronautics and Astronautics Sichuan University Sichuan Chengdu610065 China The School of Electrical Engineering Computing and Mathematical Sciences Curtin University GPO Box U1987 PerthWA6845 Australia National Mobile Communications Research Laboratory Southeast University Jiangsu Nanjing210096 China The Purple Mountain Laboratories Nanjing211111 China School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hon g Kong Guangdong Shenzhen518172 China The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

The unmanned aerial vehicle (UAV)-enabled data collection system with a rotary-wing UAV and multiple ground nodes (GNs) is investigated in this paper. The average transmission data rate is maximized through the coordinated optimization of the GNs’ transmit power and the UAV’s trajectory. In particular, the UAV dynamic constraints and physical constraints are imposed. The UAV dynamics, which are governed by a group of differential equations, are usually ignored in existing works. As a consequence, the planned trajectory cannot be fully tracked by the controller in real world applications, which could lead to severe performance degradation. Thus, a control-based method is devised to address this issue. Specifically, by adopting the state-space model from control theory, the data collection problem is established as a dynamic optimization problem subject to state constraints, in which both of the decision variables and constraints are infinite-dimensional in nature. The key idea of the solution method is to convert the infinite-dimensional dynamic program into a finite-dimensional static nonlinear problem. This is achieved by deriving the required gradients of the dynamic optimization problem based on the control parametrization scheme and an exact penalty function method. The effectiveness and superiority of the proposed design are validated via numerical experiments. © 1972-2012 IEEE.

关键词： State space methods

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A Geneformer-Based Model for Identifying Early Gastric Cancer Therapeutic Targets

A Geneformer-Based Model for Identifying Early Gastric Cance...

引用

2025 2nd International Conference on Algorithms, Software engineering and Network Security (ASENS)

作者： Xuan Liu Guohua Li Yanshen Liao Zishao Zhong Hang Wei School of Medical Information Engineering Guangzhou University of Chinese Medicine Guangzhou China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Guangzhou China Syndrome/Department of Gastroenterology State Key Laboratory of Traditional Chinese Medicine The Second Affiliated Hospital of Guangzhou University of Chinese Medicine Guangzhou China Guangdong Provincial Hospital of Chinese Medicine Guangdong Provincial Academy of Chinese Medical Sciences/State Key Laboratory of Dampness Syndrome of Chinese Medicine Guangdong Provincial Key Laboratory of Chinese Medicine for Prevention and Treatment of Refractory Chronic Diseases Guangzhou China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

Gastric cancer is a major global health issue characterized by high incidence and mortality rates. Early gastric cancer has a more favorable prognosis, yet most patients are diagnosed at an advanced stage due to subtle symptoms and limited diagnostic methods. Currently, the screening for therapeutic targets in early gastric cancer primarily relies on CRISPR-Cas9, next-generation sequencing, and advanced bioinformatics analysis, facing challenges such as off-target effects, high costs, complex data interpretation, and the elucidation of causal relationships. In this study, the Geneformer model was pre-trained on a large-scale corpus and fine-tuned on an early gastric cancer dataset to identify early gastric cancer cells. Potential therapeutic targets were identified through simulated gene perturbations and disease treatments, and their effectiveness was validated using KEGG pathway enrichment analysis and biological experimental results. After rigorous quality control and preprocessing of the data, the Geneformer model achieved excellent performance in the cell state annotation task, with an accuracy of 93.47% and an F1 score of 0.9187. Additionally, the model identified 445 potential therapeutic targets for early gastric cancer, such as TFF1, TFF2, and GKN2, which were enriched in gastric cancer-related pathways, with some targets validated by biological experiments. In summary, the proposed methodologies are capable of effectively identifying early gastric cancer cells and discovering potential therapeutic targets.

关键词： Sequential analysis Costs Annotations Biological system modeling Microprocessors Computer architecture data models Bioinformatics Biological cells Cancer

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High-Frequency Stereo Matching Network

High-Frequency Stereo Matching Network

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Haoliang Zhao Huizhou Zhou Yongjun Zhang Jie Chen Yitong Yang Yong Zhao Text Computing & Cognitive Intelligence Engineering Research Center of National Education Ministry State Key Laboratory of Public Big Data College of Computer Science and Technology Institute of Artificial Intelligence Guizhou University Guiyang Guizhou China Ghost-Valley AI Technology Shenzhen Guangdong China School of Physics and Optoelectronic Engineering Guangdong University of Technology Guangzhou China The Key Laboratory of Integrated Microsystems Shenzhen Graduate School Peking University China

In the field of binocular stereo matching, remarkable progress has been made by iterative methods like RAFT-Stereo and CREStereo. However, most of these methods lose information during the iterative process, making it difficult to generate more detailed difference maps that take full advantage of high-frequency information. We propose the Decouple module to alleviate the problem of data coupling and allow features containing subtle details to transfer across the iterations which proves to alleviate the problem significantly in the ablations. To further capture high-frequency details, we propose a Normalization Refinement module that unifies the disparities as a proportion of the disparities over the width of the image, which address the problem of module failure in cross-domain scenarios. Further, with the above improvements, the ResNet-like feature extractor that has not been changed for years becomes a bottleneck. Towards this end, we proposed a multi-scale and multi-stage feature extractor that introduces the channel-wise self-attention mechanism which greatly addresses this bottleneck. Our method (DLNR) ranks 1st on the Middlebury leaderboard, significantly outperforming the next best method by 13.04%. Our method also achieves SOTA performance on the KITTI-2015 benchmark for D1-fg. Code and demos are available at: https://***/David-Zhao-1997/High-frequency-Stereo-Matching-Network.

关键词：

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Biogas Fermentation Monitoring Research Based on Borderline-SMOTE Algorithm and Stacking Ensemble Learning

Biogas Fermentation Monitoring Research Based on Borderline-...

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Information and Communication technology (ICTech), International Conference of

作者： Pengfei Xiu Lijun Fu Yukun Sun Hongliang Wang Xuerao Li Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Liaoning Province Human-Computer Interaction System Engineering Research Center Based on Digital Twin Shenyang China Shandong University Big Data Technology and Cognitive Intelligence Laboratory University of Chinese Academy of Sciences Shenyang China Shenyang Institute of Computing Technology Chinese Academy of Sciences Liaoning Province Human-Computer Interaction System Engineering Research Center Based on Digital Twin Shenyang China

ISBN: (数字)9798350376258

ISBN: (纸本)9798350376265

Anaerobic fermentation is the most important link to gas production, this paper solves the current problem with the help of the current complete machine learning technology, combining perception and intelligent processing, intelligent processing of information, and derive a decision-making basis for its control or management [1]. Aiming at the current problems of the anaerobic fermentation process in biogas engineering, the system design was carried out, and the anaerobic fermentation process of biogas and its main influencing factors were investigated, and the monitoring parameters of the system were selected to be temperature, PH value, liquid level and redox potential [2]. Previous studies are mainly based on a single prediction model, which leads to poor generalization ability of the model. In this study, unbalanced samples are handled by Borderline-SMOTE algorithm. Based on the Stacking integrated learning approach, a common single prediction model is used to construct a combined prediction model. The accuracy, precision, recall, F1 score and area under the ROC curve are used to evaluate the advantages and disadvantages of the combined prediction model over the single prediction model.

关键词： Accuracy Biological system modeling Stacking Process control Production Predictive models Prediction algorithms Biogas Fermentation Monitoring

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An Efficient Benders Decomposition Approach for Optimal Large-Scale Network Slicing

arXiv

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arXiv 2023年

作者： Chen, Wei-Kun Wu, Zheyu Zhang, Rui-Jin Liu, Ya-Feng Dai, Yu-Hong Luo, Zhi-Quan The School of Mathematics and Statistics Beijing Key Laboratory on MCAACI Beijing Institute of Technology Beijing100081 China The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China

This paper considers the network slicing (NS) problem which attempts to map multiple customized virtual network requests to a common shared network infrastructure and allocate network resources to meet diverse service requirements. This paper proposes an efficient customized Benders decomposition algorithm for globally solving the large-scale NP-hard NS problem. The proposed algorithm decomposes the hard NS problem into two relatively easy function placement (FP) and traffic routing (TR) subproblems and iteratively solves them enabling the information feedback between each other, which makes it particularly suitable to solve large-scale problems. Specifically, the FP subproblem is to place service functions into cloud nodes in the network, and solving it can return a function placement strategy based on which the TR subproblem is defined;and the TR subproblem is to find paths connecting two nodes hosting two adjacent functions in the network, and solving it can either verify that the solution of the FP subproblem is an optimal solution of the original problem, or return a valid inequality to the FP subproblem that cuts off the current infeasible solution. The proposed algorithm is guaranteed to find the globally optimal solution of the NS problem. By taking the special structure of the NS problem into consideration, we successfully develop two families of valid inequalities that render the proposed algorithm converge much more quickly and thus much more efficient. Numerical results demonstrate that the proposed valid inequalities effectively accelerate the convergence of the decomposition algorithm, and the proposed algorithm significantly outperforms the existing algorithms in terms of both solution efficiency and quality. Copyright © 2023, The Authors. All rights reserved.

关键词： Resource allocation

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Optical Intelligent Reflecting Surface Assisted MIMO VLC: Channel Modeling and Capacity Characterization

arXiv

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arXiv 2023年

作者： Sun, Shiyuan Mei, Weidong Yang, Fang An, Nan Song, Jian Zhang, Rui The Department of Electronic Engineering Tsinghua University Beijing100084 China The Key Laboratory of Digital TV System of Shenzhen City Research Institute of Tsinghua University in Shenzhen Shenzhen518057 China The Shenzhen International Graduate School Tsinghua University Shenzhen518055 China The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore The Chinese University of Hong Kong Shenzhen China Shenzhen Research Institute of Big Data Shenzhen518172 China

Although the multi-antenna or so-called multiple-input multiple-output (MIMO) transmission has been the enabling technology for the past generations of radio-frequency (RF)-based wireless communication systems, its application to the visible light communication (VLC) still faces a critical challenge as the MIMO spatial multiplexing gain can be hardly attained in VLC channels due to their strong spatial correlation. In this paper, we tackle this problem by deploying the optical intelligent reflecting surface (OIRS) in the environment to boost the capacity of MIMO VLC. Firstly, based on the extremely near-field channel condition in VLC, we propose a new channel model for OIRS-assisted MIMO VLC and reveal its peculiar "no crosstalk" property, where the OIRS reflecting elements can be respectively configured to align with one pair of transmitter and receiver antennas without causing crosstalk to each other. Next, we characterize the OIRS-assisted MIMO VLC capacities under different practical power constraints and then proceed to maximize them by jointly optimizing the OIRS element alignment and transmitter emission power. In particular, for optimizing the OIRS element alignment, we propose two algorithms, namely, location-aided interior-point algorithm and log-det-based alternating optimization algorithm, to balance the performance versus complexity trade-off;while the optimal transmitter emission power is derived in closed form. Numerical results are provided, which validate the capacity improvement of OIRS-assisted MIMO VLC against the VLC without OIRS and demonstrate the superior performance of the proposed algorithms compared to baseline schemes. Copyright © 2023, The Authors. All rights reserved.

关键词： Visible light communication

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