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18th International Conference on Green, Pervasive, and Cloud Computing, GPC 2023

作者： Yang, Zhongliao Huang, Huichang Liu, Zeyi Dong, Chen Xu, Li College of Computer and Data Science Fuzhou University Fuzhou350116 China College of Computer and Cyber Security Fujian Normal University Fuzhou350007 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China

ISBN: (纸本)9789819998951

Continuous-Flow Microfluidic Biochip (CFMB), with their integrated features, bring traditional biochemical experiments on a single chip to accomplish complex operations and reactions through precise control, efficient reactions and emerging ways of saving reagents. In the field of intelligent digital healthcare, CFMB have attracted a lot of attention. However, traditional manual design schemes can no longer meet the needs of increasingly complex chip architecture design. Therefore, this paper proposes an automated design method for resource binding and module placement of CFMB based on a list scheduling algorithm and an improved Simulated Annealing algorithm. Through the resource binding and scheduling design based on the list scheduling algorithm, an effective scheduling strategy is generated, which effectively improves the biochip execution efficiency. In addition, the improved Simulated Annealing algorithm solves the module placement problem in the biochip in a limited physical space. Compared with some benchmark algorithms, the experimental results demonstrate the effectiveness of the method in the biochip design process and provide a practical framework for further development of CFMB in the field of intelligent digital healthcare. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Biochips

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Genetic-A* Algorithm-Based Routing for Continuous-Flow Microfluidic Biochip in intelligent Digital Healthcare 18th

Genetic-A* Algorithm-Based Routing for Continuous-Flow Micr...

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18th International Conference on Green, Pervasive, and Cloud Computing, GPC 2023

作者： Huang, Huichang Yang, Zhongliao Zhong, Jiayuan Xu, Li Dong, Chen Bao, Ruishen College of Computer and Data Science Fuzhou University Fuzhou350116 China College of Computer and Cyber Security Fujian Normal University Fuzhou350007 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China

ISBN: (纸本)9789819998951

In the field of intelligent digital healthcare, Continuous-flow microfluidic biochip (CFMB) has become a research direction of widespread concern. CFMB integrates a large number of microvalves and large-scale microchannel networks into a single chip, enabling efficient execution of various biochemical protocols. However, as the scale of the chip increases, the routing task for CFMB becomes increasingly complex, and traditional manual routing is no longer sufficient to meet the requirements. Therefore, this paper proposes an automatic routing framework for CFMB based on Genetic algorithm (GA) and A* algorithms. Specifically, we adopt a two-stage A* algorithm to design the routing between modules, using the routing results obtained from the A* algorithm as the basis for evaluating the quality of solutions in the GA algorithm. Then, the GA algorithm is used to search for the optimal approximate solution in the solution space. Experimental results show that this method can reduce routing length and minimize routing crossings, thereby improving the parallel transmission speed of reagents on CFMB. This approach provides a feasible solution for large-scale automated routing of CFMB in the field of intelligent digital healthcare. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Genetic algorithms

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Federated Hybrid-Supervised Learning for Universal Medical Image Segmentation

Federated Hybrid-Supervised Learning for Universal Medical I...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zheng, Shenhai Wen, Sian Li, Congyu Chen, Qing Li, Laquan College of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Cyberspace Big Data Intelligent Security Ministry of Education Chongqing China School of Science Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (纸本)9798350368741

Federated Learning (FL) is an advanced technology that tackles the challenge of blocked data arising from privacy concerns, enabling the training of deep learning models without the need for data sharing. However, FL faces difficulties with heterogeneous data and limited annotations in medical image segmentation. Motivated by this discovery, this study proposes a novel hybrid-supervised federated learning method (FedSLAG) that explores various types of annotations in medical imaging. To focus more on weakly-supervised and unsupervised scenarios within hybrid-supervised learning, a federated Gaussian enhancement module was proposed for heterogeneous sparse annotations (points and scribbles). The feature extraction module combines the features of multiple weakly-supervised clients and establishes the correlation of similar pixels, thus making up for the deficiency of scarce annotations and the insufficient feature extraction capability of a single machine. Then, a two-stage broadcast mechanism based on supervision sparsity was proposed to alleviate optimization deviation in local models. Experiments on breast tumor and skin lesion segmentation tasks demonstrate significant efficiency gains as well as highly competitive segmentation accuracy in many hybrid-supervised situations. Our codes are available at: https://***/TrivenDev/FedSLAG. © 2025 IEEE.

关键词： federated learning hybrid-supervised learning medical image segmentation

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Simulating Bluetooth virus propagation on the real map via infectious attenuation algorithm and discrete dynamical system

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Iran Journal of Computer Science 2024年第4期7卷 755-776页

作者： Zhu, Qingyi Wan, Wentao Gan, Chengquan Fan, Ziqi Yang, Lu-Xing School of Cyber Security and Information Law Chongqing University of Posts and Telecommunications Chongqing 400065 China School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China Key Laboratory of Cyberspace Big Data Intelligent Security Ministry of Education Chongqing 400065 China School of Information Technology Deakin University Melbourne 3125 VIC Australia

In recent years, mobile smart devices have gained popularity globally due to their convenience and efficiency. However, this popularity has also attracted the attention of virus creators, resulting in a significant cost to users. Current research on virus propagation primarily focuses on developing anti-virus software and macroscopic modeling. Software development often lags behind and only begins when viruses become a significant threat. In contrast, macroscopic modeling frequently deviates from reality as real networks do not completely conform to the characteristics of scale-free or small-world networks. Furthermore, special factors such as device mobility and signal attenuation must be considered when studying Bluetooth-transmitted viruses. Traditional research methods have shown limited performance in this field. To address these issues, this paper proposes a method that describes the propagation behavior of Bluetooth viruses in smart devices by utilizing an Infectious Attenuation Algorithm (IAA) and real maps. This method incorporates population density, map contours, and user security awareness to construct a unique discrete system. More importantly, we integrate this system into the map of Deyuan Street in Chengdu City and create a visualization system using the Simulation of Urban Mobility (SUMO) simulation software. In this system, the proposed IAA simulates the decay of virus infectivity based on the distance between devices and the attenuation of signal power between them. Our research approach considers the two core elements of infectivity attenuation and maps, making it more realistic and overcoming the lag in software development. Additionally, the introduction of SUMO for visualization simulation enhances the practical significance of our experiments. Finally, we propose feasible prevention strategies based on comparative experiments, data analysis, and theoretical analysis. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2

关键词： Bluetooth virus Discrete dynamical system Infectious attenuation algorithm Population density Real map security awareness SUMO simulation

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TailClip: Mitigating Tail Latency in Cloud Gaming via Smart Video Frame Generation

TailClip: Mitigating Tail Latency in Cloud Gaming via Smart ...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Qianyun Gong Kunheng Jiang Jingjing Wen Xinjing Yuan Jianxin Shi Lingjun Pu Institute of Systems and Networks College of Computer Science Nankai University Tianjin China Key Laboratory of Data and Intelligent System Security Ministry of Education Nankai University Tianjin China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Latency is one of the most significant issues in cloud gaming, among which tail latency, mainly attributed to dynamic network environments (i.e., transmission) and limited device computing capacity (e.g., decoding), has attracted increasing attention. To mitigate the tail latency, different from existing researches considering resource adaptation such as bitrate adaptation, we propose TailClip, whose novel idea is to enable video frame generation at the client if the tail latency is about to happen. TailClip consists of two innovative components: a Deep Reinforcement Learning (DRL) driven tail latency trigger that jointly decides a series of subsequent frame generation regarding multidimensional features of historical tail latency; a lightweight frame generation model derived by adaptive pruning in terms of device computing capacity at runtime. Extensive evaluations indicate the superior performance of TailClip. For example, it can remove the high-latency frames (i.e., over 100 ms) by 77% with an acceptable video quality (i.e., 0.45 dB reduction on average).

关键词： Performance evaluation Runtime Computational modeling Tail Cloud gaming Streaming media Deep reinforcement learning

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Design and Force Control Analysis of a Novel Waist Massage Instrument

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Recent Patents on Mechanical Engineering 2023年第4期16卷 296-307页

作者： Xie, Shenglong Liu, Zijing Zhang, Liangan Wan, Yanjian Key Laboratory of Intelligent Manufacturing Quality Big Data Tracking and Analysis of Zhejiang Province China Jiliang University Zhejiang Hangzhou310018 China Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Anhui University of Technology Anhui Ma’anshan243032 China School of Mechanical Engineering Anhui University of Technology Anhui Ma’anshan243000 China

Background: There is a shortage of rehabilitation doctors and treatment equipment for patients with lumbar spondylosis. Therefore, a waist massage instrument (WMI) is designed to help patients alle-viate lumbar pain. Objective: The objective of this study is to design a new WMI with the advantages of simple structure, lightweight, and function of effective force control, and to verify its function of palmar push, palmar press, and palmar vibration based on the on-off control, PID control, and fuzzy-PID control. Methods: Firstly, the movement characteristics of the Chinese massage manipulation are analyzed to clarify the design principle of the massage instrument. Then, a new WMI composed of massage head, vibration exciter, and actuator is designed to simulate the three massage manipulations. Next, the electric control system and control methods of on-off, PID, and fuzzy-PID controllers are introduced to realize the force control of WMI. Finally, the force control experiments of WMI are carried out to verify the function of the palmar press, palmar push, and palmar vibration based on the on-off control, PID control, and fuzzy-PID control, respectively. Results: The experimental results indicate that the proposed WMI can implement the massage manipulations of palmar push, palmar press, and palmar vibration well, and has good force control ability after using fuzzy-PID control. Conclusion: The newly designed WMI is effective in providing palmar push, palmar press, and palmar vibration massage manipulations for patients with lumbar spondylosis, and the fuzzy-PID controller im-proves the force control ability of the instrument. The WMI has the potential to be used as an effective treatment for lumbar pain. © 2023 Bentham Science Publishers.

关键词： Three term control systems

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Multi-Granular Genetic Algorithm Based Task Allocation for Heterogeneous UAVs

Multi-Granular Genetic Algorithm Based Task Allocation for H...

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International Conference on Big data and Information Analytics (BigDIA)

作者： Jiajia Cao Guoyin Wang Qun Liu Haihuan Jiang Key Laboratory of Cyberspace Big Data Intelligent Security Ministry of Education Chongqing University of Posts and Telecommunications Chongqing China National Center for Applied Mathematics in Chongqing Chongqing Normal University Chongqing China Key Laboratory of Cyberspace Big Data Intelligent Security Ministry of Education

ISBN: (数字)9798350354621

ISBN: (纸本)9798350354638

The unmanned aerial vehicles (UAVs) cooperative multi-task allocation systems have been widely used in recent years in areas such as land aerial photography, transportation of materials in disaster areas and so on. With the increase of the complex relationship between the mission and the UAV, it is difficult for genetic algorithm to find the global optimal solution in the search process. This paper proposes a new Multi-Granular Genetic Algorithm (MGGA) to solve the UAV cooperative multi-task allocation problem (CMTAP), accounting for multiple constraints in real scenarios. To enhance the quality of the initial population of genetic algorithm, a data preprocessing method via a typical clustering algorithm is proposed at first. Aiming to improve the solution speed of the standard genetic algorithm, MGGA incorporates the concept of Multi-Granular Cognition and combines granular-ball computing with the genetic algorithm to solve the CMTAP. Finally, through simulation experiments in different scenarios, the algorithm is proved to have better optimization ability and convergence effect.

关键词： Computational modeling data preprocessing Clustering algorithms Transportation system recovery Autonomous aerial vehicles Multitasking Resource management Standards Genetic algorithms

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Flexible and self-powered blinking and eyeball movements sensing based on electrospun lead-free piezoelectric nanofibers

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Science China Materials 2024年第12期67卷 3948-3955页

作者： Lei Jiang Xu Mei Tingting Shao Xinran Yang Wuyang Long Meilin Wan Yijing Fan Juan Xiong Xianghui Zhang Yongming Hu Haoshuang Gu Zhao Wang Hubei Key Laboratory of Micro&Nano Electric Materials and Devices School of MicroelectronicsHubei UniversityWuhan 430062China Key Laboratory of Intelligent Sensing System and Security Ministry of EducationHubei UniversityWuhan 430062China School of Chemistry and Environmental Engineering Wuhan University of BioengineeringWuhan 430415China

Potassium sodium niobate(KNN)-based nanofibers could combine piezoelectric properties with exceptional flexibility and biocompatibility,making them highly promising for flexible sensors in electronic skin and wearable ***,the suboptimal piezoelectric performance limits their sensitivity in detecting minute human body motions,such as blinking and eye ***,Li and Ta-doped KNN nanofibers were fabricated via an electro-spinning ***-doping with 6%Li at the A-site and 30%Ta at the B-site induces lattice distortion and an orthorhombic(O)to tetragonal(T)phase transition in the electrospun nanofibers,resulting in a significantly enhanced piezoelectric response,with an average d_(33)*value reaching 110.7 pm/*** outstanding piezoelectric response gives rise to a remarkable sensitivity(0.3365 V/(N cm^(2)))in a self-powered flexible pressure sensor based on the doped KNN nanofibers,encapsulated in a polydimethylsiloxane *** sensors,when attached to the temple regions,can detect tiny facial motions induced by blinking,enabling the distinction of abnormal blinking patterns associated with mental fatigue and excessive eye ***,they support real-time,continuous,and unobtrusive eyeball tracking,highlighting their potential as critical components in human-computer interaction and artificial intelligence applications.

关键词： flexible sensors eye movement sensing piezoelectric nanofibers potassium sodium niobate electrospinning

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GNEA: A Novel GCN-based Network Embedding Algorithm for Semantic Social Network 10

GNEA: A Novel GCN-based Network Embedding Algorithm for Sema...

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10th International Symposium on system security, Safety, and Reliability, ISSSR 2024

作者： Zhao, Jinbo He, Jinling Du, Yuanhan Tang, Ming Xu, Xiaolong Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing China State Grid Jiangsu Electric Power Company Limited Nanjing China Nanjing University of Posts and Telecommunications School of Computer Science Nanjing China

ISBN: (纸本)9798350362930

With the development of semantic social networks, social networks become more complex and their size expands rapidly, which brings significant challenges to social network analysis. Network Embedding can transform the network from a high-dimensional adjacency matrix to a low-dimensional one, which has excellent foreground in link prediction, vertex classification, and graph visualization. Nowadays, most algorithms are proposed for static networks with little consideration of the dynamic changes in the network. However, most real-world networks change over time. Directly applying static network embedding algorithms to dynamic networks will result in poor stability, flexibility, and efficiency. Because of these shortcomings, we propose a graph convolution-based dynamic network representation learning algorithm (GNEA), which combines Graph Convolutional Network (GCN) with Long Short-Term Memory (LSTM) to train the time series networks. GCN is applied to extract features in the network, and LSTM is utilized to capture temporal information. GNEA can not only perform characterization learning on the network but also obtain more abundant information during the dynamic evolution of the network. GNEA is compared with several typical algorithms on the datasets Stochastic Block Model (SBM), Autonomous systems (AS), and Digital Bibliography and Library Project (DBLP). The results prove that GNEA has good performance in MAP and precision@k. © 2024 IEEE.

关键词： Complex networks

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4D foetal cardiac ultrasound image detection based on deep learning with weakly supervised localisation for rapid diagnosis of evolving hypoplastic left heart syndrome

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CAAI Transactions on Intelligence Technology 2024年第6期9卷 1485-1499页

作者： Gang Wang Weisheng Li Mingliang Zhou Haobo Zhu Guang Yang Choon Hwai Yap Chongqing Key Laborotory of Image Rocognition Chongqing University of Posts and TelecommunicationsChongqingChina School of Computing and Data Engineering NingboTech UniversityNingboChina Department of Bioengineering Imperial College LondonLondonUK Key Laboratory of Cyberspace Big Data Intelligent Security(Chongqing University of Posts and Telecommunications) Ministry of EducationChongqingChina School of Computer Science Chongqing UniversityChongqingChina University of Oxford OxfordUK Cardiovascular Research Centre Royal Brompton HospitalLondonUK National Heart and Lung Institute Imperial College LondonLondonUK

Hypoplastic left heart syndrome(HLHS)is a rare,complex,and incredibly foetal congenital heart *** decrease neonatal mortality,evolving HLHS(eHLHS)in pregnant women should be critically diagnosed as soon as ***,diagnosis is currently heavily dependent on skilled medical professionals using foetal cardiac ultrasound images,making it difficult to rapidly and easily examine for this ***,the authors propose a cost-effective deep learning framework for rapid diagnosis of eHLHS(RDeH),which we have named ***,the framework implements a coarseto-fine two-stage detection approach,with a structure classification network for 4D human foetal cardiac ultrasound images from various spatial and temporal domains,and a fine detection module with weakly-supervised localisation for high-precision nidus localisation and physician *** experiments extensively compare the authors’network with other state-of-the-art methods on a 4D human foetal cardiac ultrasound image dataset and show two main benefits:(1)it achieved superior average accuracy of 99.37%on three categories of foetal ultrasound images from different cases;(2)it demonstrates visually fine detection performance with weakly supervised *** framework could be used to accelerate the diagnosis of eHLHS,and hence significantly lessen reliance on experienced medical physicians.

关键词： 4D deep learning fetal cardiac ultrasound hypoplastic left heart syndrome weakly-supervised learning

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