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21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Wang, Guijuan Lin, Cheng-Kuan Fan, Jianxi Cheng, Baolei Liu, Zhao School of Computer Science and Technology Soochow University Suzhou215006 China College of Mathematics and Computer Science Fuzhou University Fuzhou350108 China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Jiangsu Province Nanjing210003 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China

ISBN: (纸本)9781728120584

The generalized hypercube is an excellent interconnection network since it includes many interconnection topologies and it can be used to construct many data center networks. Considering the probability that, in general, all neighbors of one vertex becoming faulty at the same time is extremely low, we assume that each vertex has at least one fault-free neighbor. An r-dimensional generalized hypercube is denoted by G(m-r, m-r-1,⋅, m-1). In this paper, we proposed an efficient algorithm which can construct at least κ^1(G) disjoint paths based on any two adjacent vertices in G(m-r, m-r-1, m-1) in O(rm) time where κ^1(G) is the 1-restricted connectivity of G(m-r, m-r-1, m-1). The maximum length of these disjoint paths is bounded by 7. © 2019 IEEE.

关键词： Fault tolerance

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A Balanced Cost Fault-Tolerant Scheduling Algorithm in Heterogeneous Real-Time Systems 22

A Balanced Cost Fault-Tolerant Scheduling Algorithm in Heter...

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22nd IEEE International Conference on High Performance Computing and Communications, 18th IEEE International Conference on Smart City and 6th IEEE International Conference on Data Science and Systems, HPCC-SmartCity-DSS 2020

作者： Liu, Jing Zhang, Yifu Liu, Yang Yang, Pei Chen, Cen Zhu, Ziqi Zeng, Zeng Wuhan University of Science and Technology College of Computer Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan China Institute for Infocomm Research Singapore Singapore

ISBN: (纸本)9781728176499

High reliability is required for many safety-critical and real-Time applications. It is difficult to avoid permanent faults during the executing process of tasks. Once such faults are not processed in time, real-Time tasks cannot be completed within the specified time, which may lead to catastrophic consequences. In order to deal with the problem of permanent fault tolerance in heterogeneous real-Time systems, in this paper, we propose a balanced cost fault-Tolerant scheduling algorithm. First, the algorithm uses the task computation time and the average communication time of its successor nodes as the ranking factors when calculating task priority, so that the priority of the task with larger average communication time improved;second, a task cost table is established, and tasks are allocated to appropriate processors according to the values in the task cost table in processor allocation stage. Experimental results show that the proposed algorithm can effectively improve the system reliability and reduce the completion time. © 2020 IEEE.

关键词： Real time systems

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End-to-End Model for Offline Handwritten Mongolian Word Recognition 8th

End-to-End Model for Offline Handwritten Mongolian Word Reco...

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8th CCF International Conference on Natural Language processing and Chinese Computing, NLPCC 2019

作者： Wei, Hongxi Liu, Cong Zhang, Hui Bao, Feilong Gao, Guanglai School of Computer Science Inner Mongolia University Hohhot010021 China Provincial Key Laboratory of Mongolian Information Processing Technology Hohhot China

ISBN: (纸本)9783030322359

This paper proposed an end-to-end model for recognizing offline handwritten Mongolian words. To be specific, a sequence to sequence architecture with attention mechanism is used to perform the task of generating a target sequence from a source sequence. The proposed model consists of two LSTMs and one attention network. The first LSTM is an encoder which consumes a frame sequence of one word image. The second LSTM is a decoder which can generate a sequence of letters. The attention network is added between encoder and decoder, which allow the decoder to focus on different positions in a sequence of frames during the procedure of decoding. In this study, we have attempted two schemes for generating frames from word images. In the first scheme, frames are generated with overlapping. Each adjacent two frames overlap half a frame. In the second scheme, frames are generated without overlapping. In addition, the height of the frame is also taken into consideration in our study. By comparison, the better scheme for generating frames has been determined. Experimental results demonstrate that the proposed end-to-end model outperforms the state-of-the-art method. © 2019, Springer Nature Switzerland AG.

关键词： Decoding

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Neural Network-Based Prescription of Chinese Herbal Medicines

Neural Network-Based Prescription of Chinese Herbal Medicine...

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IEEE International Symposium on information (IT) in Medicine and Education, ITME

作者： Wen Zhao Weikai Lu Chang'en Zhou Zuoyong Li Haoyi Fan Xuejuan Lin Zhaoyang Yang Candong Li School of Traditional Chinese Medicine Fujian University of Traditional Chinese Medicine Fuzhou China School of Electronic Electrical Engineering and Physics Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China School of Computer Science and Technology Harbin University of Science and Technology Harbin China

ISBN: (纸本)9781728194202

Objective: To develop a neural network model that recommends traditional Chinese medicine (TCM) herbal prescriptions. Methods: We constructed a new dataset of diagnosis and treatment knowledge from the Treatise on Febrile Diseases. Based on TCM's logical principles of “syndrome differentiation” and “state recognition”, a back-propagation neural network model is proposed that simulates clinical diagnosis and treatment. Results: The proposed model is a four-layer BP neural network. Experiments on the constructed dataset show that the proposed method achieved the best precision, recall, and F1-scores. Conclusion: The proposed method provides much more accurate herbal prescription recommendations than logistic regression.

关键词： Neural networks Education Clinical diagnosis information technology Logistics Diseases

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Reproducibility Assessment of Magnetic Resonance Spectroscopy of Pregenual Anterior Cingulate Cortex across Sessions and Vendors via the Cloud Computing Platform CloudBrain-MRS

arXiv

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arXiv 2025年

作者： Chen, Runhan Lin, Meijin Chen, Jianshu Lin, Liangjie Wang, Jiazheng Li, Xiaoqing Wang, Jianhua Huang, Xu Qian, Ling Liu, Shaoxing Long, Yuan Guo, Di Qu, Xiaobo Han, Haiwei National Institute for Data Science in Health and Medicine Xiamen University Xiamen361102 China College of Ocean & Earth Sciences Xiamen University Xiamen361102 China Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Xiamen University Xiamen361102 China Department of Electronic Science Xiamen University Xiamen361102 China Clinical and Technical Support Philips Healthcare Beijing100016 China School of Economics and Management Xiamen University of Technology Xiamen361024 China Department of Radiology The First Hospital Affiliated to Xiamen University Xiamen361003 China Software Technology Company Limited Suzhou215163 China School of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China

Given the need to elucidate the mechanisms underlying illnesses and their treatment, as well as the lack of harmonization of acquisition and post-processing protocols among different magnetic resonance system vendors, this work is to determine if metabolite concentrations obtained from different sessions, machine models and even different vendors of 3 T scanners can be highly reproducible and be pooled for diagnostic analysis, which is very valuable for the research of rare diseases. Participants underwent magnetic resonance imaging (MRI) scanning once on two separate days within one week (one session per day, each session including two proton magnetic resonance spectroscopy (1H-MRS) scans with no more than a 5-minute interval between scans (no off-bed activity)) on each machine. were analyzed for reliability of within- and between sessions using the coefficient of variation (CV) and intraclass correlation coefficient (ICC), and for reproducibility of across the machines using correlation coefficient. As for within- and between- session, all CV values for a group of all the first or second scans of a session, or for a session were almost below 20%, and most of the ICCs for metabolites range from moderate (0.4≤ICC © 2025, CC BY.

关键词： Magnetic resonance imaging

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Predicting the pathological status of mammographic microcalcifications through a radiomics approach

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Intelligent Medicine 2021年第3期1卷 95-103页

作者： Min Li Liyu Zhu Guangquan Zhou Jianan He Yanni Jiang Yang Chen School of Biological Science and Medical Engineering Southeast UniversityNanjingJiangsu 210096China Department of Radiology the First Affiliated Hospital of Nanjing Medical UniversityNanjingJiangsu 210029China Department of Radiology the Second Affiliated Hospital of Nantong UniversityNantongJiangsu 226001China The State Key Laboratory of Bioelectronics Southeast UniversityNanjingJiangsu 210096China Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing School of Computer Science and EngineeringSoutheast UniversityNanjingJiangsu 210096China The Laboratory of Image Science and Technology Key Laboratory of Ministry of EducationSchool of Computer Science and EngineeringSoutheast UniversityNanjingJiangsu 210096China

Objective The study aimed to develop a machine learning(ML)-coupled interpretable radiomics signature to predict the pathological status of non-palpable suspicious breast microcalcifications(MCs).Methods We enrolled 463 digital mammographical view images from 260 consecutive patients detected with non-palpable MCs and BI-RADS scored at 4(training cohort,n=428;independent testing cohort,n=35)in the First Affiliated Hospital of Nanjing Medical university between September 2010 and January ***,837 textures and 9 shape features were subsequently extracted from each view and finally selected by an XGBoostembedded recursive feature elimination technique(RFE),followed by four machine learning-based classifiers to build the radiomics *** Ten radiomic features constituted a malignancy-related signature for breast MCs as logistic regression(LR)and support vector machine(SVM)yielded better positive predictive value(PPV)/sensitivity(SE),0.904(95%CI,0.865–0.949)/0.946(95%CI,0.929–0.977)and 0.891(95%CI,0.822–0.939)/0.939(95%CI,0.907–0.973)respectively,outperforming their negative predictive value(NPV)/specificity(SP)from 10-fold crossvalidation(10FCV)of the training *** optimal prognostic model was obtained by SVM with an area under the curve(AUC)of 0.906(95%CI,0.834–0.969)and accuracy(ACC)0.787(95%CI,0.680–0.855)from 10FCV against AUC 0.810(95%CI,0.760–0.960)and ACC 0.800 from the testing *** The proposed radiomics signature dependens on a set of ML-based advanced computational algorithms and is expected to identify pathologically cancerous cases from mammographically undecipherable MCs and thus offer prospective clinical diagnostic guidance.

关键词： Nonpalpable microcalcifications Radiomics Machine learning

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Principled design of translation, scale, and rotation invariant variation operators for metaheuristics

arXiv

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arXiv 2021年

作者： Tian, Ye Zhang, Xingyi He, Cheng Tan, Kay Chen Jin, Yaochu Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei230601 China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China Guangdong Provincial Key Laboratory of Braininspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Department of Computing The Hong Kong Polytechnic University Hong Kong Department of Computer Science University of Surrey Guildford SurreyGU2 7XH United Kingdom

In the past three decades, a large number of metaheuristics have been proposed and shown high performance in solving complex optimization problems. While most variation operators in existing metaheuristics are empirically designed, this paper aims to design new operators automatically, which are expected to be search space independent and thus exhibit robust performance on different problems. For this purpose, this work first investigates the influence of translation invariance, scale invariance, and rotation invariance on the search behavior and performance of some representative operators. Then, we deduce the generic form of translation, scale, and rotation invariant operators. Afterwards, a principled approach is proposed for the automated design of operators, which searches for highperformance operators based on the deduced generic form. The experimental results demonstrate that the operators generated by the proposed approach outperform state-of-theart ones on a variety of problems with complex landscapes and up to 1000 decision variables. © 2021, CC BY.

关键词： Heuristic algorithms

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Automated segmentation of intraretinal cystoid macular edema based on Gaussian mixture model

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Journal of Innovative Optical Health Sciences 2020年第1期3卷 35-47页

作者： Jinghong Wu Sijie Niu Qiang Chen Wen Fan Songtao Yuan Dengwang Li Shandong Key Laboratory of Medical Physics and Image Processing&Shandong Provincial Engineering and Technical Center of Light Manipulations School of Physics and Electronics Shandong Normal University Jinan 250358P.R.China School of Information Science and Engineering University of Jinan Jinan 250022P.R.China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing 210094 P.R.China Department of Ophthalmology the First Affiliated Hospital with Nanjing Medical University Nanjing 210094P.R.China

We introduce a method based on Gaussian mixture model(GMM)clustering and level-set to automatically detect intraretina fluid on diabetic retinopathy(DR)from spectral domain optical coherence tomography(SD-OCT)images in this ***,each B-scan is segmented using GMM *** original chustering results are refined using location and thickness ***,the spatial information among every consecutive five B-scans is used to search potential ***,the improved level-set method is used to obtain the accurate *** high sensitivity and accuracy demonstrated here show its potential for detection of fluid.

关键词： Gaussian mixture model level-set spectral domain optical coherence tomography(SD-OCT) segmentation

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Beamforming Design and Association Scheme for Multi-RIS Multi-User mmWave Systems Through Graph Neural Networks

arXiv

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arXiv 2025年

作者： Liu, Mengbing Huang, Chongwen Alhammadi, Ahmed Di Renzo, Marco Debbah, Mérouane Yuen, Chau School of Electrical and Electronics Engineering Nanyang Technological University 639798 Singapore College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China Zhejiang Provincial Key Laboratory of Multi-Modal Communication Networks and Intelligent Information Processing Hangzhou310027 China Technology Innovation Institute Masdar City Abu Dhabi United Arab Emirates Université Paris-Saclay CNRS CentraleSupélec Laboratoire des Signaux et Systèmes 3 Rue Joliot-Curie Gif-sur-Yvette91192 France King’s College London Centre for Telecommunications Research Department of Engineering LondonWC2R 2LS United Kingdom KU 6G Research Center Department of Computer and Information Engineering Khalifa University Abu Dhabi127788 United Arab Emirates CentraleSupelec University Paris-Saclay Gif-sur-Yvette91192 France

Reconfigurable intelligent surface (RIS) is emerging as a promising technology for next-generation wireless communication networks, offering a variety of merits such as the ability to tailor the communication environment. Moreover, deploying multiple RISs helps mitigate severe signal blocking between the base station (BS) and users, providing a practical and efficient solution to enhance the service coverage. However, fully reaping the potential of a multi-RIS aided communication system requires solving a non-convex optimization problem. This challenge motivates the adoption of learning-based methods for determining the optimal policy. In this paper, we introduce a novel heterogeneous graph neural network (GNN) to effectively leverage the graph topology of a wireless communication environment. Specifically, we design an association scheme that selects a suitable RIS for each user. Then, we maximize the weighted sum rate (WSR) of all the users by iteratively optimizing the RIS association scheme, and beamforming designs until the considered heterogeneous GNN converges. Based on the proposed approach, each user is associated with the best RIS, which is shown to significantly improve the system capacity in multi-RIS multiuser millimeter wave (mmWave) communications. Specifically, simulation results demonstrate that the proposed heterogeneous GNN closely approaches the performance of the high-complexity alternating optimization (AO) algorithm in the considered multi-RIS aided communication system, and it outperforms other benchmark schemes. Moreover, the performance improvement achieved through the RIS association scheme is shown to be of the order of 30%. Copyright © 2025, The Authors. All rights reserved.

关键词： Beamforming

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An Improved Whale Optimization Algorithm and Its Application to Power Generation in Cascade Reservoir 16th

An Improved Whale Optimization Algorithm and Its Application...

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16th International Conference on Intelligent information Hiding and Multimedia Signal processing, IIH-MSP 2020 in conjunction with the 13th International Conference on Frontiers of information technology, Applications and Tools, FITAT 2020

作者： Lü, Ji-Xiang Yan, Li-Jun Pan, Tien-Szu Chu, Shu-Chuan Pan, Jeng-Shyang He, Xian-Kang Chang, Kuo-Chi School of Information Science and Engineering Fujian University of Technology Fuzhou350108 China Shenzhen Institute of Information Technology Shenzhen518172 China Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung82445 Taiwan College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China College of Science and Engineering Flinders University Sturt Rd Bedford ParkSA5042 Australia Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350108 China College of Mechanical & Electrical Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (纸本)9789813364196

Nowadays, there is a very popular artificial intelligence algorithm called whale optimization algorithm (WOA). WOA is obtained through the special bubble net foraging process of humpback whales. It has a special search mechanism, and is very helpful to solve some complex optimization problems and large scale. An improved WOA is implemented to optimize the cascade reservoir power generation. Firstly, by introducing nonlinear time-varying adaptive weights, the WOA performance in the local optimization and global exploration stages is improved;secondly, the differential mutation perturbation factor is introduced in the shrinking and surrounding stage of the whale algorithm to prevent premature convergence. In addition, the logarithmic spiral search method of whale individuals has been improved so that the ability to solve the algorithm traversal can be found. Experimental results show that it has a great improvement in accuracy and convergence compared with the original WOA in the optimal dispatch model of cascade reservoir power generation. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Optimization

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