检索结果-内蒙古大学图书馆

Research and Design of Square Kilometer Array Astronomical Data Management Model Based on Fabric 13

学校读者我要写书评

暂无评论

Research and Design of Square Kilometer Array Astronomical D...

2020 IEEE Congress on Cybermatics: 13th IEEE International Conferences on Internet of Things, iThings 2020, 16th IEEE International Conference on Green computing and Communications, GreenCom 2020, 13th IEEE International Conference on Cyber, Physical and Social computing, CPSCom 2020 and 6th IEEE International Conference on Smart Data, SmartData 2020

作者： Fu, Jinhua Xu, Jie Zhang, Shulin Zhang, Chen State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou University of Light Industry Zhengzhou China Zhengzhou University of Light Industry Zhengzhou China Qinghai University Department of Computer Technology and Applications Xining China

ISBN: (纸本)9781728176475

At present, how to safely share data among different participants has become a huge challenge. The reliable traceability of SKA data is a powerful technical tool for controlling its security and sharing. In order to solve the problem of high management cost and low data credibility of traditional centralized big data management system, SKA data management and credible traceability model design based on Hyperledger Fabric were studied. In this paper, the overall framework and architecture of SKA data management are studied and designed, and the key technologies such as big data storage scheme, big data transmission, big data processing, blockchain metadata storage, alliance chain member allocation, traceability query, contribution mechanism and data sharing are discussed. Distributed architecture, Hyperledger Fabric alliance chain technology, database technology, Golang network programming, Rust asynchronous programming, Java Web and *** are comprehensively adopted. The functions of SKA data transmission, processing, storage, traceability query and data sharing are designed. The functions of transmission, processing, storage, management, sharing and credible traceability of SKA data management system are realized, which provides a reference for the design and implementation of SKA data management system based on blockchain. © 2020 IEEE.

关键词： Metadata

On the Impact of Flaky Tests in Automated Program Repair

学校读者我要写书评

暂无评论

On the Impact of Flaky Tests in Automated Program Repair

IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Yihao Qin Shangwen Wang Kui Liu Xiaoguang Mao Tegawendé F. Bissyandé National University of Defense Technology Changsha China Nanjing University of Aeronautics and Astronautics Nanjing China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China University of Luxembourg Luxembourg

ISBN: (纸本)9781728196305;9781728196312

The literature of Automated Program Repair is largely dominated by approaches that leverage test suites not only to expose bugs but also to validate the generated patches. Unfortunately, beyond the widely-discussed concern that test suites are an imperfect oracle because they can be incomplete, they can include tests that are flaky. A flaky test is one that can be passed or failed by a program in a non-deterministic way. Such tests are generally carefully removed from the repair benchmarks. In practice, however, flaky tests are available test suite of software repositories. To the best of our knowledge, no study has discussed this threat to validity for evaluation of program repair. In this work, we highlight this threat and further investigate the impact of flaky tests by reverting their removal from the Defects4J benchmark. Our study aims to characterize the impact of flaky tests for localizing bugs and the eventual influence on the repair performance. Among other insights, we find that (1) although flaky tests are few (≈0.3%) of total tests, they affect experiments related to a large proportion (98.9%) of Defects4J real-world faults; (2) most flaky tests (98%) actually provide deterministic results under specific environment configurations (with the jdk version influencing the results); (3) flaky tests drastically hinder the effectiveness of spectrum-based fault localization (e.g., the rankings of 90 bugs drop down while none of the bugs obtains better location results compared with results achieved without flaky tests); and (4) the repairability of APR tools is greatly affected by the presence of flaky tests (e.g., 10 state of the art APR tools can now fix significantly fewer bugs than when the benchmark is manually curated to remove flaky tests). Given that the detection of flaky tests is still nascent, we call for the program repair community to relax the artificial assumption that the test suite is free from flaky tests. One direction that we propose is to co

关键词： Location awareness Degradation Conferences Computer bugs Maintenance engineering Tools Benchmark testing

Adaptive Wavelet Filters as Practical Texture Feature Amplifiers for Parkinson’s Disease Screening in OCT

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Zhang, Xiaoqing Shi, Hanfeng Li, Xiangyu Ye, Haili Xu, Tao Li, Na Hu, Yan Lv, Fan Chen, Jiangfan Liu, Jiang Center for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Research Institute of Trustworthy Autonomous Systems Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China State Key Laboratory of Ophthalmology Optometry and Vision Science Wenzhou Medical University Wenzhou China Centre for Computational Science and Mathematical Modelling Coventry University Coventry United Kingdom School of Computer Science University of Nottingham Ningbo China Ningbo315100 China School of Ophthalmology and Optometry Wenzhou Medical University Wenzhou325035 China Department of Electronic and Information Engineering Changchun University Changchun130022 China

Parkinson’s disease (PD) is a prevalent neurodegenerative disorder globally. The eye’s retina is an extension of the brain and has great potential in PD screening. Recent studies have suggested that texture features extracted from retinal layers can be adopted as biomarkers for PD diagnosis under optical coherence tomography (OCT) images. Frequency domain learning techniques can enhance the feature representations of deep neural networks (DNNs) by decomposing frequency components involving rich texture features. Additionally, previous works have not exploited texture features for automated PD screening in OCT. Motivated by the above analysis, we propose a novel Adaptive Wavelet Filter (AWF) that serves as the Practical Texture Feature Amplifier to fully leverage the merits of texture features to boost the PD screening performance of DNNs with the aid of frequency domain learning. Specifically, AWF first enhances texture feature representation diversities via channel mixer, then emphasizes informative texture feature representations with the well-designed adaptive wavelet filtering token mixer. By combining the AWFs with the DNN stem, AWFNet is constructed for automated PD screening. Additionally, we introduce a novel Balanced Confidence (BC) Loss by mining the potential of sample-wise predicted probabilities of all classes and class frequency prior, to further boost the PD screening performance and trustworthiness of AWFNet. The extensive experiments manifest the superiority of our AWFNet and BC over state-of-the-art methods in terms of PD screening performance and trustworthiness. © 2025, CC BY-NC-SA.

关键词： Neurodegenerative diseases

DISCO Might Not Be Funky: Random Intelligent Reflective Surface Configurations That Attack

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Huang, Huan Dai, Lipeng Zhang, Hongliang Zhang, Chongfu Tian, Zhongxing Cai, Yi Swindlehurst, A. Lee Han, Zhu The School of Electronic and Information Engineering Soochow University Suzhou215006 China The School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China The State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China The Center for Pervasive Communications and Computing University of California IrvineCA92697 United States The University of Houston HoustonTX77004 United States

Emerging intelligent reflective surfaces (IRSs) significantly improve system performance, but also pose a significant risk for physical layer security (PLS). Unlike the extensive research on legitimate IRS-enhanced communications, in this article we present an adversarial IRS-based fully-passive jammer (FPJ). We describe typical application scenarios for Disco IRS (DIRS)-based FPJ, where an illegitimate IRS with random, time-varying reflection properties acts like a "disco ball" to randomly change the propagation environment. We introduce the principles of DIRS-based FPJ and overview existing investigations of the technology, including a design example employing one-bit phase shifters. The DIRS-based FPJ can be implemented without either jamming power or channel state information (CSI) for the legitimate users (LUs). It does not suffer from the energy constraints of traditional active jammers, nor does it require any knowledge of the LU channels. In addition to the proposed jamming attack, we also propose an anti-jamming strategy that requires only statistical rather than instantaneous CSI. Furthermore, we present a data frame structure that enables the legitimate access point (AP) to estimate the DIRS-jammed channels’ statistical characteristics in the presence of the DIRS jamming. Typical cases are discussed to show the impact of the DIRS-based FPJ and the feasibility of the anti-jamming precoder (AJP). Moreover, we outline future research directions and challenges for the DIRS-based FPJ and its anti-jamming precoding to stimulate this line of research and pave the way for practical applications. Copyright © 2023, The Authors. All rights reserved.

关键词： Channel state information

IBM Small-Scale Superconducting Quantum Computer Not Gate Error Test

学校读者我要写书评

暂无评论

Journal of Physics: Conference Series 2022年第1期2209卷

作者： Ming He Xiaonan Liu Junchao Wang Jiale An State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou Henan 450001 China

Quantum NOT gates play an important role in the process of quantum information conversion. However, when the X-gate operation is executed on a real quantum computer, there is a large deviation between the actual operation result and the theory, which will lead to inaccurate results when the quantum algorithm containing the X-gate operation is executed. In order to facilitate users to understand the error fluctuations of the X gate in time before executing the quantum algorithm containing the X gate operation on the IBM quantum cloud platform, this paper proposes a method to measure the X gate error. By measuring the X-gate error of four small-scale superconducting quantum computers on the back end of the IBM quantum cloud platform, analyze the degree of fluctuation of the actual measurement value of the quantum device; at the same time, under different execution times shots, the influence of the X-gate test is analyzed. The test results show that the measured value of each qubit of different quantum devices fluctuates to different degrees; the execution times of shots are different, and the test results of X-gate error will be affected to different degrees. This test method helps users select the optimal performance of the qubits before executing quantum algorithms with X gate on IBM's small-scale quantum computers.

关键词：

Observation of giant nonlinear valley Hall effect

学校读者我要写书评

暂无评论

arXiv 2025年

作者： He, Pan Zhang, Min Cao, Jin Li, Jingru Liu, Hao Zhai, Jinfeng Wang, Ruibo Xiao, Cong Yang, Shengyuan A. Shen, Jian State Key Laboratory of Surface Physics Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China Hefei National Laboratory Hefei230088 China Institute of Applied Physics and Materials Engineering Faculty of Science and Technology University of Macau China Fudan University Shanghai200433 China Department of Physics Fudan University Shanghai China Shanghai Research Center for Quantum Sciences Shanghai China Zhangjiang Fudan International Innovation Center Fudan University Shanghai201210 China Collaborative Innovation Center of Advanced Microstructures Nanjing210093 China

The valley Hall effect (VHE) holds great promise for valleytronic applications by leveraging the valley degree of freedom. To date, research on VHE has focused on its linear response to an applied current, leaving nonlinear valley responses undetected and nonlinear valleytronic devices undeveloped. Here, we report the experimental observation of a nonlinear VHE in a graphene-hBN moiré superlattice, evidenced by the generation of second-harmonic nonlocal voltages under AC currents. Remarkably, the nonlinear VHE has magnitude surpassing the linear VHE and is highly tunable via a gate voltage, which exhibits a pair of opposite peaks on the two sides of a Dirac gap. The nonlinear signal shows quadratic scaling with driving current and quartic scaling with local resistance, setting it apart from the linear counterpart. These experimental features are consistent with the theoretical picture of nonlocal transport mediated by nonlinear VHE and linear inverse VHE. We further reveal a nonlinear inverse VHE by observing the third- and fourth-harmonic nonlocal voltages. The nonlinear VHE provides a novel mechanism for valley manipulation and enables a novel valleytronic device—the valley rectifier—that converts AC charge current into DC valley current. Copyright © 2025, The Authors. All rights reserved.

关键词： Degrees of freedom (mechanics)

CRNet:3D Face Reconstruction with Contour Map Regression Network

学校读者我要写书评

暂无评论

CRNet:3D Face Reconstruction with Contour Map Regression Net...

International Conference on Computer and Communications (ICCC)

作者： Tongxin Wei Qingbao Li Jinjin Liu School of Software Zhengzhou University Zhengzhou State Key Laboratory of Mathematical Engineering and Advanced Computing

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

2D face images represent faces with incomplete information. 3D face reconstruction from a single 2D image is a challenging problem with application value. The single feature extraction method distorts the generated 3D face image. In this paper, we use contour-based face segmentation method to reconstruct 3D face image. We focus on the edge and contour information of the face when using contour lines to segment the face. Different from the global 3D face reconstruction method, we combine the global and local face information to carry out 3D face reconstruction. Our method: First of all, we do contour segmentation for human faces and extract the features of the segmented images. Second, we learn the local binary features of each keypoint in a complete face image, then combine the features and use linear regression to detect the keypoints. Thirdly, we use Convolutional Neural Networks to learn the regression 3D Morphable Model coefficient and significantly improve the quality and efficiency of reconstruction. We regressed the coefficients of the 3D deformable model from 2D images to present face alignment for 3D face reconstruction. We carry out feature mapping between 2D face and 3D face image, and monitor and verify 3D face model through mapping relationship. Our method can not only reconstruct face images from all angles, but also reduce face deformities. We made face images fit better under different expressions and postures.

关键词： Image segmentation Solid modeling Three-dimensional displays Two dimensional displays Feature extraction Faces Image reconstruction

A new network intrusion detection system based on blockchain

学校读者我要写书评

暂无评论

International Journal of Performability engineering 2019年第12期15卷 3187-3195页

作者： Fu, Jinhua Xu, Mixue Huang, Yongzhong Tao, Hongwei State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou450001 China School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou450002 China

With the increasing application of computers and networks, several network security problems have emerged, and thus network intrusion detection systems have become the focus of network security research. In order to achieve the purpose of intrusion detection and protection, the traditional network intrusion detection system extracts features from the data of the network data stream according to the feature recognition algorithm and compares the extracted features with those in the training set to recognize the behavior. However, if a user wants to effectively detect malicious behaviors in the network, a large feature library is needed, and it cannot be shared with other users, which makes the quality of single user detection lower than the highest detection quality of the whole network. Blockchain, which is a new network system of decentralization, de-trust, tamper-proof, anti-counterfeiting, and traceability, plays an important role in the transmission and sharing of high-value data. In this paper, a new network intrusion detection system is designed based on blockchain, which can enable users to share feature libraries over the whole network by means of P2P network transmission. Meanwhile, its network structure and consensus algorithm are presented, and its security and performance are analyzed. Analysis results show that this system has lower false negative rates. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Intrusion detection

Hypermultiplexed Integrated-Photonics-based Tensor Optical Processor

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Ou, Shaoyuan Xue, Kaiwen Zhou, Lian Lee, Chun-Ho Sludds, Alexander Hamerly, Ryan Zhang, Ke Feng, Hanke Kopparapu, Reshma Zhong, Eric Wang, Cheng Englund, Dirk Yu, Mengjie Chen, Zaijun Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States Research Laboratory of Electronics MIT CambridgeMA02139 United States PHI Laboratories NTT Research Inc. 940 Stewart Drive SunnyvaleCA94085 United States Department of Electrical Engineering State Key Laboratory of Terahertz and Millimeter Waves City University of Hong Kong Kowloon Hong Kong School of Advanced Computing University of Southern California Los AngelesCA90089 United States Opticore Inc. Los AngelesCA90007 United States

The escalating data volume and complexity resulting from the rapid expansion of artificial intelligence (AI), internet of things (IoT) and 5G/6G mobile networks is creating an urgent need for energy-efficient, scalable computing hardware. Here we demonstrate a hypermultiplexed integrated-photonics-based tensor optical processor (HITOP) that can perform trillions of operations per second (TOPS) at the energy efficiency of 40 TOPS/W. Space-time-wavelength three-dimensional (3D) optical parallelism enables O(N2) operations per clock-cycle using O(N) modulator devices. The system is built with wafer-fabricated III/V micron-scale lasers and high-speed thin-film Lithium-Niobate electro-optics for encoding at 10s femtojoule/symbol. Lasing threshold incorporates analog inline rectifier (ReLu) nonlinearity for low-latency activation. The system scalability is verified with machine learning models of 405,000 parameters. A combination of high clockrates, energy-efficient processing and programmability unlocks the potential of light for large-scale AI accelerators in applications ranging from training of large AI models to real-time decision making in edge deployment. © 2024, CC0.

关键词： Photonic integrated circuits