检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Ge, Xiuting Fang, Chunrong Zhang, Quanjun Wu, Daoyuan Yu, Bowen Zheng, Qirui Guo, An Lin, Shangwei Zhao, Zhihong Liu, Yang Chen, Zhenyu The State Key Laboratory for Novel Software Technology Nanjing University China School of Computer Science and Engineering Nanyang Technological University Singapore

Actionable Warning Identification (AWI) plays a pivotal role in improving the usability of static code analyzers. Currently, Machine Learning (ML)-based AWI approaches, which mainly learn an AWI classifier from labeled warnings, are notably common. However, these approaches still face the problem of restricted performance due to the direct reliance on a limited number of labeled warnings to develop a classifier. Very recently, Pre-Trained Models (PTMs), which have been trained through billions of text/code tokens and demonstrated substantial success applications on various code-related tasks, could potentially circumvent the above problem. Nevertheless, the performance of PTMs on AWI has not been systematically investigated, leaving a gap in understanding their pros and cons. In this paper, we are the first to explore the feasibility of applying various PTMs for AWI. By conducting the extensive evaluation on 10K+ SpotBugs warnings from 10 large-scale and open-source projects, we observe that all studied PTMs are consistently 9.85%∼21.12% better than the state-of-the-art ML-based AWI approaches. Besides, we investigate the impact of three primary aspects (i.e., data preprocessing, model training, and model prediction) in the typical PTM-based AWI workflow. Further, we identify the reasons for current PTMs’ underperformance on AWI. Based on our findings, we provide several practical guidelines to enhance PTM-based AWI in future work. Copyright © 2024, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

FedCA: Federated learning based on classification layer alignment

FedCA: Federated learning based on classification layer alig...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Gang Liu Jing Jia Rui Mao Yan Ji Guangdong Province Key Laboratory of Popular High Performance Computers College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

The issue of data heterogeneity has long been a significant challenge in federated learning, impacting the speed of global model convergence and potentially lowering the overall performance of the global model, thereby impeding its development. In response to this challenge, we propose a classifier head-based method to correct the local model update direction. Unlike most existing calibration methods, our method not only ensures a global model with good performance but also guarantees the performance of a single local model. Concretely, we have introduced a new federated learning framework called FedCA. In this framework, the output of the feature extractor is imported into both a global classifier and a local classifier. The gradients are calculated separately, and then backpropagate into the model. This method ensures the performance of the local model and allows the client to maintain a consistent learning direction. Our experimental results demonstrate the feasibility of this method.

关键词： Training Federated learning Feature extraction Data models Classification algorithms Calibration Convergence

来源：评论

学校读者我要写书评

暂无评论

Exploring Unlabeled Data in Multiple Aspects for Semi-Supervised MRI Segmentation

引用

Health Data Science 2024年第1期4卷 177-190页

作者： Qingyuan He Kun Yan Qipeng Luo Duan Yi Ping Wang Hongbin Han Defeng Liu Radiology Department Peking University Third HospitalBeijingChina Peking University Third Hospital Beijing Key Laboratory of Magnetic Resonance Imaging Devices and TechnologyBeijingChina School of Computer Science Peking UniversityBeijingChina Department of Pain Medicine Peking University Third HospitalBeijingChina School of Software and Microelectronics Peking UniversityBeijingChina National Engineering Research Center for Software Engineering Peking UniversityBeijingChina Key Laboratory of High Conffdence Software Technologies(Peking University) Ministry of EducationBeijingChina Department of Obstetrics and Gynecology Peking University Third HospitalBeijingChina Center for Reproductive Medicine Peking University Third HospitalBeijingChina

Background:MRI segmentation offers crucial insights for automatic *** deep learningbased segmentation methods have attained cutting-edge performance,their efffcacy heavily relies on vast sets of meticulously annotated ***:In this study,we propose a novel semi-supervised MRI segmentation model that is able to explore unlabeled data in multiple aspects based on various semi-supervised learning ***:We compared the performance of our proposed method with other deep learning-based methods on 2 public datasets,and the results demonstrated that we have achieved Dice scores of 90.3%and 89.4%on the LA and ACDC datasets,***:We explored the synergy of various semi-supervised learning technologies for MRI segmentation,and our investigation will inspire research that focuses on designing MRI segmentation models.

关键词： analysis labeled designing

来源：评论

学校读者我要写书评

暂无评论

Makespan and Security-Aware Workflow Scheduling for Cloud Service Cost Minimization Using Firefly Optimizer 22nd

Makespan and Security-Aware Workflow Scheduling for Cloud ...

引用

22nd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2022

作者： Zhou, Chengliang Wang, Tian Li, Liying Sun, Jin Zhou, Junlong School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China National Trusted Embedded Software Engineering Technology Research Center East China Normal University Shanghai200062 China

ISBN: (纸本)9783031226762

As efficient commercial information technology, cloud computing has attracted more and more users to submit their requests to the cloud platform and pay for them based on the amount and quality of services. One of the most important concerns of cloud service providers is to minimize the monetary cost for completing users’ requests while meeting constraints on the quality of services such as makespan and security. To solve this concern, this paper proposes a makespan and security-aware workflow scheduling method based on an improved firefly optimizer that consists of a new solution initialization scheme, a firefly position updating scheme, a firefly-to-solution mapping operator, and two task-to-virtual machine assignment schemes. We carry out extensive simulation experiments on real-world workflows to validate our proposed workflow scheduling method. The results reveal that the monetary cost reduction achieved by our method can be up to 54.0% compared to a baseline and two state-of-the-art approaches. © 2023, Springer Nature Switzerland AG.

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

Detection of Java Basic Thread Misuses Based on Static Event Analysis 23

Detection of Java Basic Thread Misuses Based on Static Event...

引用

Proceedings of the 38th IEEE/ACM International Conference on Automated software engineering

作者： Baoquan Cui Miaomiao Wang Chi Zhang Jiwei Yan Jun Yan Jian Zhang State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Technology Center of Software Engineering Institute of Software Chinese Academy of Sciences Beijing China and University of Chinese Academy of Sciences Beijing China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China and University of Chinese Academy of Sciences Beijing China Technology Center of Software Engineering Institute of Software Chinese Academy of Sciences Beijing China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China and Technology Center of Software Engineering Institute of Software Chinese Academy of Sciences Beijing China and University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350329964

The fundamental asynchronous thread (***) in Java can be easily misused, due to the lack of deep understanding for garbage collection and thread interruption mechanism. For example, a careless implementation of asynchronous thread may cause no response to the interrupt mechanism in time, resulting in unexpected thread-related behaviors, especially resource leak/***, few works aim at these misuses and related works adopt either the dynamic approach which lacks effective inputs or the static path-sensitive approach with high time consumption due to the path explosion, causing false negatives. We have found that the behavior of threads and the interaction between threads and its referencing objects can be abstracted. In this paper, we propose an event analysis approach to detect the defects in Java programs and Android apps, which focuses on the existence or the order of the events to reduce the false negatives. We extract the misuse-related events, containing the thread events and the destroy events of the object referenced by the thread. Then we analyze the events with loop identification, happens-before relationship construction and alias determination. Finally, we implement an automatic tool named Leopard and evaluate it on real world Java programs and Android apps. Experiments show that it is efficient when comparing with the existing approach (misuse: 723 vs 47, time: 60s vs 30min), which also outperforms the existing work in precision. The manual check indicates that Leopard is more efficient and effective than existing work. Besides, 66 issues reported by us have been confirmed and 21 of them have been fixed by developers.

关键词： thread misuse

来源：评论

学校读者我要写书评

暂无评论

Development of a Soft Hand and Wrist Rehabilitation Robot Utilizing Lattice Structure Actuators

Development of a Soft Hand and Wrist Rehabilitation Robot Ut...

引用

World Rehabilitation Robot Convention (WRRC)

作者： Jianwei Lai Aiguo Song Wenbin Zhang Ye Lu Jiajin Wang Ye Li State Key Laboratory of Digital Medical Engineering Jiangsu Key Laboratory of Remote Measurement and Control School of Instrument Science and Engineering Southeast University Nanjing China College of Computer Science and Software Engineering Hohai University Nanjing China

ISBN: (数字)9798350355123

ISBN: (纸本)9798350355130

Soft robots offer promising solutions for rehabilitation due to their inherent attributes such as suppleness, lightweight construction, and safety features. However, prevalent soft actuators face limitations in output force and bending angle, impeding their effective application in rehabilitation. This paper proposes a novel design approach employing a two-layer lattice structure actuator, comprising flexion, guiding, and extension layers. This innovative design facilitates supple and efficient bi-directional rehabilitation training for fingers and wrists. Experimental results demonstrate the efficacy of the proposed dual-layer lattice structure actuator. At an air pressure of 150 kPa, it achieves an end force of 14.88 N, marking a remarkable 906% increase compared to its single-layer counterpart. Additionally, the dual-layer structure exhibits a minimum bending radius of 2.77 cm under 60 kPa, representing a 38.5% reduction relative to the single-layer actuator. Leveraging these actuators, a hand and wrist rehabilitation robot was developed and subjected to a clinical trial involving two healthy subjects. The trial outcomes reveal significant improvements in finger grasping ability and wrist range of motion with the assistance of the rehabilitation robot. These results underscore the practical usability and effectiveness of the soft hand and wrist rehabilitation robot, thereby holding promise for enhancing patient rehabilitation outcomes.

关键词： Wrist Training Actuators Force Lattices Bending Soft robotics Assistive robots Usability Periodic structures

来源：评论

学校读者我要写书评

暂无评论

Activity Diagram Synthesis Using Labelled Graphs and the Genetic Algorithm

引用

Journal of computer Science & Technology 2021年第6期36卷 1388-1406页

作者： Chun-Hui Wang Zhi Jin Wei Zhang Didar Zowghi Hai-Yan Zhao Wen-Pin Jiao Key Laboratory of High Confidence Software Technology(Ministry of Education) Peking University Beijing 100871China Institute of Software School of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China School of Computer Science Inner Mongolia Normal UniversityHohhot 010022China Faculty of Engineering and Information Technology University of TechnologySydney 2007Australia

Many applications need to meet diverse requirements of a large-scale distributed user *** challenges the current requirements engineering ***-based requirements engineering was proposed as an umbrella term for dealing with the requirements development in the context of the large-scale user ***,there are still many *** others,a key issue is how to merge these requirements to produce the synthesized requirements description when a set of requirements descriptions from different participants are *** techniques are needed for supporting the requirements *** are widely used in industry to represent *** paper chooses the activity diagrams and proposes a novel approach for the activity diagram synthesis which adopts the genetic algorithm to repeatedly modify a population of individual solutions toward an optimal *** a result,it can automatically generate a resulting diagram which combines the commonalities as many as possible while leveraging the variabilities of a set of input *** approach is featured by:1)the labelled graph proposed as the representation of the candidate solutions during the iterative evolution;2)the generalized entropy proposed and defined as the measurement of the solutions;3)the genetic algorithm designed for sorting out the high-quality *** cases of different scales are used to evaluate the effectiveness of the *** experimental results show that not only the approach gets high precision and recall but also the resulting diagram satisfies the properties of minimization and information preservation and can support the requirements traceability.

关键词： crowd-based requirements engineering requirements synthesis activity diagram genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

An Approach to Optimize Symbolic Execution in Ethereum Smart Contracts

An Approach to Optimize Symbolic Execution in Ethereum Smart...

引用

IEEE International Conference on software Quality, Reliability and Security Companion (QRS-C)

作者： Yi Liu Lizhi Cai Chenchen Chai Yuan Ma School of Information Science and Engineering East China University of Science and Technology Shanghai China Shanghai Key Laboratory of Computer Software Testing & Evaluating Shanghai Development Center of Computer Software Technology Shanghai China

ISBN: (数字)9798350365658

ISBN: (纸本)9798350365665

As the application of smart contracts in blockchain technology becomes increasingly widespread, their security issues have emerged as a focal point of both research and practice. Although symbolic execution technology has been extensively applied for the detection of security vulnerabilities in smart contracts, its limitations in terms of execution efficiency and code coverage remain significant. In response to these challenges, this study introduces an innovative method named HoneyToken-DetectorRev, which optimizes traditional symbolic execution through program slicing technology, aiming to enhance the efficiency and effectiveness of smart contract security detection. By selecting ten smart contracts from the Ethereum platform, which vary in business logic and complexity, we conducted an empirical analysis of HoneyToken-DetectorRev. The experimental results demonstrate that this method significantly improves the efficiency of smart contract detection without sacrificing precision. This research not only provides an effective technical approach for the security detection of smart contracts but also offers theoretical and practical guidance for further enhancing the security of blockchain applications.

关键词： Codes Smart contracts software quality Inspection Boosting Complexity theory software reliability Security Logic Business

来源：评论

学校读者我要写书评

暂无评论

Attack and Improvement of a Hidden Vector Encryption Scheme 12

Attack and Improvement of a Hidden Vector Encryption Scheme

引用

12th International Conference on Electronics, Communications and Networks, CECNet 2022

作者： Wang, Ke Wang, Zhikun Luo, Song Guan, Zhi Key Laboratory of High Confidence Software Technologies Peking University MoE Beijing China Department of Computer Science and Technology Eecs Peking University Beijing China School of Computer Science and Engineering Chongqing University of Technology Chongqing China National Engineering Research Center for Software Engineering Peking University Beijing China

ISBN: (纸本)9781643683683

Hidden Vector Encryption (HVE) is a new kind of attribute-based encryption in which a vector is hidden in the ciphertext or linked with the secret key. In ESORICS 2014, Phuong et al. proposed an HVE scheme with constant-size ciphertext which is constructed in the prime order setting. In this paper, we show that Phuong et al.'s scheme is not vector-hiding due to public parameters in their scheme leak some information about vectors. Furthermore, an improved HVE scheme is proposed in the prime order setting and its security is proven in the security model. Comparison shows our scheme has more efficient in decryption than current other HVE schemes. © 2022 The authors and IOS Press.

关键词： Vectors

来源：评论

学校读者我要写书评

暂无评论

Approximate k-Nearest Neighbor Query over Spatial Data Federation 28th

Approximate k-Nearest Neighbor Query over Spatial Data Fede...

引用

28th International Conference on Database Systems for Advanced Applications, DASFAA 2023

作者： Zhang, Kaining Tong, Yongxin Shi, Yexuan Zeng, Yuxiang Xu, Yi Chen, Lei Zhou, Zimu Xu, Ke Lv, Weifeng Zheng, Zhiming State Key Laboratory of Software Development Environment Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing School of Computer Science and Engineering and Institute of Artificial Intelligence Beihang University Beijing China Department of Computer Science and Engineering HKUST Hong Kong Guangzhou China City University of Hong Kong Hong Kong

ISBN: (纸本)9783031306365

Approximate nearest neighbor query is a fundamental spatial query widely applied in many real-world applications. In the big data era, there is an increasing demand to scale these queries over a spatial data federation, which consists of multiple data owners, each holding a private, disjoint partition of the entire spatial dataset. However, it is non-trivial to enable approximate k-nearest neighbor query over a spatial data federation. This is because stringent security constraints are often imposed to protect the sensitive, privately owned data partitions, whereas naively extending prior secure query processing solutions leads to high inefficiency (e.g., 100 s per query). In this paper, we propose two novel algorithms for efficient and secure approximate k-nearest neighbor query over a spatial data federation. We theoretically analyze their communication cost and time complexity, and further prove their security guarantees and approximation bounds. Extensive experiments show that our algorithms outperform the state-of-the-art solutions with respect to the query efficiency and often yield a higher accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Nearest neighbor search

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：