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Answering reachability queries with ordered label constraints over labeled graphs

Frontiers of computer Science 2024年第1期18卷 105-117页

作者： Daoliang HE Pingpeng YUAN Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science&TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Reachability query plays a vital role in many graph analysis *** researches proposed many methods to efficiently answer reachability queries between vertex *** many real graphs are labeled graph,it highly demands Label-Constrained Reachability(LCR)query inwhich constraint includes a set of labels besides vertex *** researches proposed several methods for answering some LCR queries which require appearance of some labels specified in constraints in the *** that constraint may be a label set,query constraint may be ordered labels,namely OLCR(Ordered-Label-Constrained Reachability)queries which retrieve paths matching a sequence of ***,no solutions are available for ***,we propose DHL,a novel bloom filter based indexing technique for answering OLCR *** can be used to check reachability between vertex *** the answers are not no,then constrained DFS is ***,we employ DHL followed by performing constrained DFS to answer OLCR *** show that DHL has a bounded false positive rate,and it's powerful in saving indexing time and *** experiments on 10 real-life graphs and 12 synthetic graphs demonstrate that DHL achieves about 4.8-22.5 times smaller index space and 4.6-114 times less index construction time than two state-of-art techniques for LCR queries,while achieving comparable query response *** results also show that our algorithm can answer OLCR queries effectively.

关键词： graph ordered-label-constrained reachability partial index bloom filter query processing

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From parallel Plants to Smart Plants:Intelligent Control and Management for Plant Growth

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IEEE/CAA Journal of Automatica Sinica 2017年第2期4卷 161-166页

作者： Mengzhen Kang Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences (SKL-MCCSCASIA) Qingdao Academy of Intelligent Industries Beijing Engineering Research Center of Intelligent Systems and Technology IEEE State Key Laboratory of Management and Control for Complex Systems (SKL-MCCS) Institute of AutomationChinese Academy of Sciences (CASIA) School of Computer and Control Engineering University of Chinese Academy of Sciences Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology

Precision management of agricultural systems, aiming at optimizing profitability, productivity and sustainability, comprises a set of technologies including sensors, information systems, and informed management, etc. Expert systems are expected to aid farmers in plant management or environment control, but they are mostly based on the offline and static information, deviated from the actual situation. parallel management, achieved by virtual/artificial agricultural system, computational experiment and parallel execution, provides a generic framework of solution for online decision support. In this paper, we present the three steps toward the parallel management of plant: growth description U+0028 the crop model U+0029, prediction, and prescription. This approach can update the expert system by adding learning ability and the adaption of knowledge database according to the descriptive and predictive model. The possibilities of passing the knowledge of experienced farmers to younger generation, as well as the application to the parallel breeding of plant through such system, are discussed. © 2017 Chinese Association of Automation.

关键词： Agriculture Artificial intelligence Decision support systems Expert systems Sustainable development

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Deep learning based dual stage model for accurate nasogastric tube positioning in chest radiographs

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Scientific Reports 2025年第1期15卷 1-9页

作者： Park, Inseo Moon, Gwiseong Hong, Ji Young Heo, Jeongwon Ko, Hongseok Lee, Doohee Kim, Yoon Kim, Woo Jin Choi, Hyun-Soo Moon, Kyoung Min Department of Research and Development ZIOVISION Co. Ltd. Kangwon Chuncheon 24341 South Korea Division of Pulmonary and Critical Care Medicine Department of Medicine Chuncheon Sacred Heart Hospital Hallym University Medical Center Chuncheon 24253 South Korea Department of Internal Medicine Kangwon National University Chuncheon 24341 South Korea Department of Radiology Kangwon National University Hospital Chuncheon 24341 South Korea Department of Computer Science and Engineering College of IT Kangwon National University Chuncheon 24341 South Korea Department of Computer Science and Engineering Seoul National University of Science and Technology Seoul 01811 South Korea Division of Pulmonary and Allergy Medicine Department of Internal Medicine Chung-Ang University Hospital Seoul 06973 South Korea Department of Radiology Seoul National University Hospital Seoul 03080 South Korea

Accurate placement of nasogastric tubes (NGTs) is crucial for ensuring patient safety and effective treatment. Traditional methods relying on manual inspection are susceptible to human error, highlighting the need for innovative solutions. This study introduces a deep-learning model that enhances the detection and analysis of NGT positioning in chest radiographs. By integrating advanced segmentation and classification techniques, the model leverages the nnU-Net framework for segmenting critical regions and the ResNet50 architecture, pre-trained with MedCLIP, for classifying NGT placement. Trained on 1799 chest radiographs, the model demonstrates remarkable performance, achieving a Dice Similarity Coefficient of 65.35% for segmentation and an Area Under the Curve of 99.72% for classification. These results underscore its ability to accurately distinguish between correct and incorrect placements, outperforming traditional approaches. This method not only enhances diagnostic precision but also has the potential to streamline clinical workflows and improve patient care. A functional prototype of the model is accessible at https://***. © The Author(s) 2025.

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Advanced feature fusion of radiomics and deep learning for accurate detection of wrist fractures on X-ray images

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BMC Musculoskeletal Disorders 2025年第1期26卷 1-22页

作者： Saadh, Mohamed J. Hussain, Qusay Mohammed Albadr, Rafid Jihad Doshi, Hardik Rekha, M.M. Kundlas, Mayank Pal, Amrita Rizaev, Jasur Taher, Waam Mohammed Alwan, Mariem Jawad, Mahmod Jasem Al-Nuaimi, Ali M. Ali Farhood, Bagher Faculty of Pharmacy Middle East University Amman 11831 Jordan College of Pharmacy Alnoor University Mosul Iraq Ahl Al Bayt University Kerbala Iraq Department of Computer Engineering Faculty of Engineering & Technology Marwadi University Research Center Marwadi University Gujarat Rajkot 360003 India Department of Chemistry and Biochemistry School of Sciences JAIN (Deemed to Be University) Karnataka Bangalore India Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura 140401 India Department of Chemistry Sathyabama Institute of Science and Technology Tamil Nadu Chennai India Department of Public Health and Healthcare Management Rector Samarkand State Medical University 18 Amir Temur Street Samarkand Uzbekistan College of Nursing National University of Science and Technology Dhi Qar Iraq Pharmacy College Al-Farahidi University Baghdad Iraq Department of Pharmacy Al-Zahrawi University College Karbala Iraq Gilgamesh Ahliya University Baghdad Iraq Department of Medical Physics and Radiology Faculty of Paramedical Sciences Kashan University of Medical Sciences Kashan Iran

Objective: The aim of this study was to develop a hybrid diagnostic framework integrating radiomic and deep features for accurate and reproducible detection and classification of wrist fractures using X-ray images. Materials and Methods: A total of 3,537 X-ray images, including 1,871 fracture and 1,666 non-fracture cases, were collected from three healthcare centers. Radiomic features were extracted using the PyRadiomics library, and deep features were derived from the bottleneck layer of an autoencoder. Both feature modalities underwent reliability assessment via Intraclass Correlation Coefficient (ICC) and cosine similarity. Feature selection methods, including ANOVA, Mutual Information (MI), Principal Component Analysis (PCA), and Recursive Feature Elimination (RFE), were applied to optimize the feature set. Classifiers such as XGBoost, CatBoost, Random Forest, and a Voting Classifier were used to evaluate diagnostic performance. The dataset was divided into training (70%) and testing (30%) sets, and metrics such as accuracy, sensitivity, and AUC-ROC were used for evaluation. Results: The combined radiomic and deep feature approach consistently outperformed standalone methods. The Voting Classifier paired with MI achieved the highest performance, with a test accuracy of 95%, sensitivity of 94%, and AUC-ROC of 96%. The end-to-end model achieved competitive results with an accuracy of 93% and AUC-ROC of 94%. SHAP analysis and t-SNE visualizations confirmed the interpretability and robustness of the selected features. Conclusions: This hybrid framework demonstrates the potential for integrating radiomic and deep features to enhance diagnostic performance for wrist and forearm fractures, providing a reliable and interpretable solution suitable for clinical applications. © The Author(s) 2025.

关键词： Attention Mechanisms Classification Deep Learning Diagnostic Framework Feature Fusion Feature Selection Forearm Fractures Radiomics Wrist Fractures X-ray Imaging

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Porting and optimizing VASP on the SW26010 18th

Porting and optimizing VASP on the SW26010

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18th International Conference on Algorithms and Architectures for parallel Processing - ICA3PP 2018 Collocated Workshops: ICA3PP 2018 Workshop on Intelligent Algorithms for Large-scale Complex Optimization Problems, IALCOP 2018, ICA3PP 2018 Workshop on Security and Privacy in Data Processing, SPDP 2018

作者： Li, Leisheng Sun, Qiao Liu, Xin Wu, Changmao Zhao, Haitao Zhang, Changyou Laboratory of Parallel Software and Computational Science Institute of Software Chinese Academy of Sciences Beijing China National Research Centre of Parallel Computer Engineering and Technology WuxiJiangsu China

ISBN: (纸本)9783030052331

VASP (Vienna Ab initio Simulation Package) is a prevalent first-principle software framework. It is so widely used that its runtime usually dominates the usage of current supercomputers. The porting and optimization of VASP to the Sunway TaihuLight supercomputer, a newly heterogeneous many-core platform based on SW26010 CPU, becomes of great importance. In this paper, we focus on the challenges in porting and optimizing VASP on the SW26010 CPU. Optimizations on three types of time-consuming kernels, which include matrix operations, FFT, and certain domain-specific computing primitives, are carried out base on thorough performance profiling. The experimental results are shown by the case of RELAX, where speedup of 2.90x and 4.48x is sustained respectively for both of the iterative diagonalization methods in VASP, RMM-DIIS (RMM) and block Davidson (DAV). © Springer Nature Switzerland AG 2018.

关键词： Density functional theory

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Pinching-Antenna Systems (PASS)-enabled Secure Wireless Communications

arXiv

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arXiv 2025年

作者： Zhu, Guangyu Mu, Xidong Guo, Li Xu, Shibiao Liu, Yuanwei Al-Dhahir, Naofal Key Laboratory of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications Beijing100876 China School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China National Engineering Research Center for Mobile Internet Security Technology Beijing University of Posts and Telecommunications Beijing100876 China Queen’s University Belfast BelfastBT3 9DT United Kingdom Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Department of Electrical and Computer Engineering The University of Texas at Dallas RichardsonTX75080 United States

A novel pinching-antenna systems (PASS)-enabled secure wireless communication framework is proposed. By dynamically adjusting the positions of dielectric particles, namely pinching antennas (PAs), along the waveguides, PASS introduces a novel concept of pinching beamforming to enhance the performance of physical layer security. A fundamental PASS-enabled secure communication system is considered with one legitimate user and one eavesdropper. Both single-waveguide and multiple-waveguide scenarios are studied. 1) For the single-waveguide scenario, the secrecy rate (SR) maximization is formulated to optimize the pinching beamforming. A PA-wise successive tuning (PAST) algorithm is proposed, which ensures constructive signal superposition at the legitimate user while inducing a destructive legitimate signal at the eavesdropper. 2) For the multiple-waveguide scenario, artificial noise (AN) is employed to further improve secrecy performance. A pair of practical transmission architectures are developed: waveguide division (WD) and waveguide multiplexing (WM). The key difference lies in whether each waveguide carries a single type of signal or a mixture of signals with baseband beamforming. For the SR maximization problem under the WD case, a two-stage algorithm is developed, where the pinching beamforming is designed with the PAST algorithm and the baseband power allocation among AN and legitimate signals is solved using successive convex approximation (SCA). For the WM case, an alternating optimization algorithm is developed, where the baseband beamforming is optimized with SCA and the pinching beamforming is designed employing particle swarm optimization. Numerical results demonstrate that i) PASS can significantly improve the secrecy performance over conventional antenna systems in both scenarios;ii) the proposed PAST algorithm for the single-waveguide scenario is efficient, especially when the number of PAs is even or large;iii) WM provides higher and more stable perfo

关键词： Particle swarm optimization (PSO)

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Accelerating restore and garbage collection in deduplication-based backup systems via exploiting historical information

Accelerating restore and garbage collection in deduplication...

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2014 USENIX Annual Technical Conference, USENIX ATC 2014

作者： Fu, Min Feng, Dan Hua, Yu He, Xubin Chen, Zuoning Xia, Wen Huang, Fangting Liu, Qing Wuhan National Lab for Optoelectronics China School of Computer Huazhong University of Science and Technology Wuhan China Dept. of Electrical and Computer Engineering Virginia Commonwealth University VA United States National Engineering Research Center for Parallel Computer Beijing China

ISBN: (纸本)9781931971102

In deduplication-based backup systems, the chunks of each backup are physically scattered after deduplication, which causes a challenging fragmentation problem. The fragmentation decreases restore performance, and results in invalid chunks becoming physically scattered in different containers after users delete backups. Existing solutions attempt to rewrite duplicate but fragmented chunks to improve the restore performance, and reclaim invalid chunks by identifying and merging valid but fragmented chunks into new containers. However, they cannot accurately identify fragmented chunks due to their limited rewrite buffer. Moreover, the identification of valid chunks is cumbersome and the merging operation is the most time-consuming phase in garbage collection. Our key observation that fragmented chunks remain fragmented in subsequent backups motivates us to propose a History-Aware Rewriting algorithm (HAR). HAR exploits historical information of backup systems to more accurately identify and rewrite fragmented chunks. Since the valid chunks are aggregated in compact containers by HAR, the merging operation is no longer required. To reduce the metadata overhead of the garbage collection, we further propose a Container-Marker Algorithm (CMA) to identify valid containers instead of valid chunks. Our extensive experimental results from real-world datasets show HAR significantly improves the restore performance by 2.6X-17X at a cost of only rewriting 0.45-1.99% data. CMA reduces the metadata overhead for the garbage collection by about 90X. © Proceedings of the 2014 USENIX Annual Technical Conference, USENIX ATC 2014. All rights reserved.

关键词： Containers

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Social Energy:Mining Energy From the Society

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IEEE/CAA Journal of Automatica Sinica 2017年第3期4卷 466-482页

作者： Jun Jason Zhang David Wenzhong Gao Yingchen Zhang Xiao Wang Xiangyang Zhao Dongliang Duan Xiaoxiao Dai Jun Hao Fei-Yue Wang Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer ScienceUniversity of Denver IEEE National Renewable Energy Laboratory Qingdao Academy of Intelligent Industries(QAII) QingdaoShandongChinaand SKL-MCCSCASIA School of Automation Science and Electrical Engineering Beihang University Department of Electrical and Computer Engineering College of Engineering and Applied ScienceUniversity of Wyoming State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences(SKL-MCCSCASIA) Research Center of Computational Experiments and Parallel Systems National University of Defense Technology

The inherent nature of energy,i.e.,physicality,sociality and informatization,implies the inevitable and intensive interaction between energy systems and social *** this perspective,we define "social energy" as a complex sociotechnical system of energy systems,social systems and the derived artificial virtual systems which characterize the intense intersystem and intra-system *** recent advancement in intelligent technology,including artificial intelligence and machine learning technologies,sensing and communication in Internet of Things technologies,and massive high performance computing and extreme-scale data analytics technologies,enables the possibility of substantial advancement in socio-technical system optimization,scheduling,control and *** this paper,we provide a discussion on the nature of energy,and then propose the concept and intention of social energy systems for electrical power.A general methodology of establishing and investigating social energy is proposed,which is based on the ACP approach,i.e., "artificial systems"(A), "computational experiments"(C) and "parallel execution"(P),and parallel system methodology.A case study on the University of Denver(DU) campus grid is provided and studied to demonstrate the social energy *** the concluding remarks,we discuss the technical pathway,in both social and nature sciences,to social energy,and our vision on its future.

关键词： ACP distribution locational marginal pricing intelligent operation in power systems parallel control parallel intelligence parallel management social energy socio-technical energy systems

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Cryptanalysis and Improvement of a Chaotic Map-Control-Based and the Plain Image-Related Cryptosystem

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computers, Materials & Continua 2019年第8期61卷 687-699页

作者： Bin Lu Fenlin Liu Xin Ge Zhenyu Li China National Digital Switching System Engineering Technology Research Center ZhengzhouChina Department of Computer Science University of YorkDeramor LaneHeslingtonUK

Due to the characteristics of chaotic systems,different cryptosystems based on chaos have been proposed to satisfy the security of multimedia data.A plain image-related chaotic algorithm is proposed by Luo et *** high speed and *** weaknesses of the cryptosystem are studied in this *** is found that the important secret key information is leaked because an important parameter can be obtained after an inverse operation in the last step of the cryptosystems without secret ***,the value zero is processed improperly in quantification *** on the weaknesses,chosen plaintext attack on the cryptosystem is proposed,by which,an important parameter,equivalent to secret key,can be calculated with a specific chosen plain *** the obtained parameter,the plain image of any ciphered image,encrypted by the cryptosystem,can be ***,an improvement is proposed to solve the problems after modifying the quantification *** is from the experiments that chosen plaintext attack is valid and improved algorithm possesses better performance.

关键词： Multimedia cryptosystem cryptanalysis chaos chosen plaintext attack

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Cluster-preserving sampling algorithm for large-scale graphs

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Science China(Information Sciences) 2023年第1期66卷 60-76页

作者： Jianpeng ZHANG Hongchang CHEN Dingjiu YU Yulong PEI Yingjun DENG National Digital Switching System E&T Research Center Information Engineering University Network Systems Department of the Strategic Support Force School of Computer Science and Technology Eindhoven University of Technology Center for Applied Mathematics Tianjin University

Graph sampling is a very effective method to deal with scalability issues when analyzing largescale graphs. Lots of sampling algorithms have been proposed, and sampling qualities have been quantified using explicit properties(e.g., degree distribution) of the sample. However, the existing sampling techniques are inadequate for the current sampling task: sampling the clustering structure, which is a crucial property of the current networks. In this paper, using different expansion strategies, two novel top-leader sampling methods(i.e., TLS-e and TLS-i) are proposed to obtain representative samples, and they are capable of effectively preserving the clustering structure. The rationale behind them is to select top-leader nodes of most clusters into the sample and then heuristically incorporate peripheral nodes into the sample using specific expansion strategies. Extensive experiments are conducted to investigate how well sampling techniques preserve the clustering structure of graphs. Our empirical results show that the proposed sampling algorithms can preserve the population's clustering structure well and provide feasible solutions to sample the clustering structure from large-scale graphs.

关键词： graph sampling clustering structure top-leader nodes expansion strategies large-scale graphs

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