检索结果-南通市图书馆

What can we learn from quality assurance badges in open-source software?

science China(Information sciences) 2024年第4期67卷 146-163页

作者： Feng LI Yiling LOU Xin TAN Zhenpeng CHEN Jinhao DONG Yang LI Xuanzhi WANG Dan HAO Lu ZHANG MoE Key Lab of HCST School of Computer SciencePeking University department of computer science Purdue University School of computer science & Engineering Beihang University(BUAA) department of computer science University College London(UCL)

In the development of open-source software(OSS), many developers use badges to give an overview of the software and share some key features/metrics conveniently. Among various badges, quality assurance(QA) badges make up a large proportion and are the most prevalent because QA is of vital importance in software development, and ineffective QA may lead to anomalies or defects. In this paper, we focus on QA badges in open-source projects, which present quality assurance information directly and instantly,and aim to produce some interesting findings and provide practical implications. We collect and analyze 100000 projects written in popular programming languages from GitHub and conduct a comprehensive empirical study both inside and outside QA badges. Inside QA badges, we build a category classification for all QA badges based on the properties they focus on, which shows the types of QA badges developers use. Then,we analyze the frequency of the properties that QA badges focus on, and property combinations, too, which present their use status. We find that QA badges focus on various properties while developers give different preferences to different properties. The use status also differs between different programming languages. For example, projects written in C focus on Security to a great extent. Our findings also provide implications for developers and badge providers. Outside QA badges, we conduct a correlation analysis between QA badges and some software metrics that have potential relationships with code quality, contribution quality, and popularity. We find that QA badges have statistically significant correlations with various software metrics.

关键词： quality assurance badge open-source software code quality empirical study

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

CToMP: a cycle-task-oriented memory protection scheme for unmanned systems

引用

science China(Information sciences) 2024年第6期67卷 399-417页

作者： Chengyan MA Ning XI Di LU Yebo FENG Jianfeng MA School of Cyber Engineering Xidian University School of computer science and Technology Xidian University department of computer and Information science University of Oregon

Memory corruption attacks(MCAs) refer to malicious behaviors of system intruders that modify the contents of a memory location to disrupt the normal operation of computing systems, causing leakage of sensitive data or perturbations to ongoing processes. Unlike general-purpose systems, unmanned systems cannot deploy complete security protection schemes, due to their limitations in size, cost and performance.MCAs in unmanned systems are particularly difficult to defend against. Furthermore, MCAs have diverse and unpredictable attack interfaces in unmanned systems, severely impacting digital and physical sectors. In this paper, we first generalize, model and taxonomize MCAs found in unmanned systems currently, laying the foundation for designing a portable and general defense approach. According to different attack mechanisms,we found that MCAs are mainly categorized into two types — return2libc and return2shellcode. To tackle return2libc attacks, we model the erratic operation of unmanned systems with cycles and then propose a cycle-task-oriented memory protection(CToMP) approach to protect control flows from tampering. To defend against return2shellcode attacks, we introduce a secure process stack with a randomized memory address by leveraging the memory pool to prevent Shellcode from being executed. Moreover, we discuss the mechanism by which CTo MP resists the return-oriented programming(ROP) attack, a novel variant of return2libc attacks. Finally, we implement CTo MP on CUAV V5+ with Ardupilot and Crazyflie. The evaluation and security analysis results demonstrate that the proposed approach CTo MP is resilient to various MCAs in unmanned systems with low footprints and system overhead.

关键词： unmanned system memory corruption attack memory protection system security randomized memory address

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Controllable multi-domain semantic artwork synthesis

引用

Computational Visual Media 2024年第2期10卷 355-373页

作者： Yuantian Huang Satoshi Iizuka Edgar Simo-Serra Kazuhiro Fukui department of computer science University of TsukubaTsukuba 305-8577Japan department of computer science and Engineering Waseda UniversityTokyo 169-8050Japan

We present a novel framework for the multidomain synthesis of artworks from semantic layouts.One of the main limitations of this challenging task is the lack of publicly available segmentation datasets for art synthesis.To address this problem,we propose a dataset called ArtSem that contains 40,000 images of artwork from four different domains,with their corresponding semantic label maps.We first extracted semantic maps from landscape photography and used a conditional generative adversarial network(GAN)-based approach for generating high-quality artwork from semantic maps without requiring paired training data.Furthermore,we propose an artwork-synthesis model using domain-dependent variational encoders for high-quality multi-domain synthesis.Subsequently,the model was improved and complemented with a simple but effective normalization method based on jointly normalizing semantics and style,which we call spatially style-adaptive normalization(SSTAN).Compared to the previous methods,which only take semantic layout as the input,our model jointly learns style and semantic information representation,improving the generation quality of artistic images.These results indicate that our model learned to separate the domains in the latent space.Thus,we can perform fine-grained control of the synthesized artwork by identifying hyperplanes that separate the different domains.Moreover,by combining the proposed dataset and approach,we generated user-controllable artworks of higher quality than that of existing approaches,as corroborated by quantitative metrics and a user study.

关键词： semantic artwork synthesis generative adversarial network(GAN) datasets non-photorealistic rendering

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Deep Convolutional Neural Networks for Accurate Classification of Gastrointestinal Tract Syndromes

引用

computers, Materials & Continua 2024年第1期78卷 1207-1225页

作者： Zahid Farooq Khan Muhammad Ramzan Mudassar Raza Muhammad Attique Khan Khalid Iqbal Taerang Kim Jae-Hyuk Cha department of computer science COMSATS University IslamabadWah CampusWah47040Pakistan department of computer science and Mathematics Lebanese American UniversityBeirut13-5053Lebanon department of computer science HITEC UniversityTaxila47080Pakistan department of computer science COMSATS University IslamabadAttock CampusAttock43600Pakistan department of computer science Hanyang UniversitySeoul04763Korea

Accurate detection and classification of artifacts within the gastrointestinal(GI)tract frames remain a significant challenge in medical image processing.Medical science combined with artificial intelligence is advancing to automate the diagnosis and treatment of numerous diseases.Key to this is the development of robust algorithms for image classification and detection,crucial in designing sophisticated systems for diagnosis and treatment.This study makes a small contribution to endoscopic image classification.The proposed approach involves multiple operations,including extracting deep features from endoscopy images using pre-trained neural networks such as Darknet-53 and Xception.Additionally,feature optimization utilizes the binary dragonfly algorithm(BDA),with the fusion of the obtained feature vectors.The fused feature set is input into the ensemble subspace k nearest neighbors(ESKNN)classifier.The Kvasir-V2 benchmark dataset,and the COMSATS university Islamabad(CUI)Wah private dataset,featuring three classes of endoscopic stomach images were used.Performance assessments considered various feature selection techniques,including genetic algorithm(GA),particle swarm optimization(PSO),salp swarm algorithm(SSA),sine cosine algorithm(SCA),and grey wolf optimizer(GWO).The proposed model excels,achieving an overall classification accuracy of 98.25% on the Kvasir-V2 benchmark and 99.90% on the CUI Wah private dataset.This approach holds promise for developing an automated computer-aided system for classifying GI tract syndromes through endoscopy images.

关键词： Feature fusion Darknet-53 Xception binary dragonfly algorithm ensemble

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Improving Video Watermarking through Galois Field GF(2^(4)) Multiplication Tables with Diverse Irreducible Polynomials and Adaptive Techniques

引用

computers, Materials & Continua 2024年第1期78卷 1423-1442页

作者： Yasmin Alaa Hassan Abdul Monem S.Rahma department of computer science College of ScienceUniversity of BaghdadBaghdadIraq department of computer science College of ScienceAl-Maarif University CollegeAl-AnbarIraq

Video watermarking plays a crucial role in protecting intellectual property rights and ensuring content authenticity.This study delves into the integration of Galois Field(GF)multiplication tables,especially GF(2^(4)),and their interaction with distinct irreducible polynomials.The primary aim is to enhance watermarking techniques for achieving imperceptibility,robustness,and efficient execution time.The research employs scene selection and adaptive thresholding techniques to streamline the watermarking process.Scene selection is used strategically to embed watermarks in the most vital frames of the video,while adaptive thresholding methods ensure that the watermarking process adheres to imperceptibility criteria,maintaining the video's visual quality.Concurrently,careful consideration is given to execution time,crucial in real-world scenarios,to balance efficiency and efficacy.The Peak Signal-to-Noise Ratio(PSNR)serves as a pivotal metric to gauge the watermark's imperceptibility and video quality.The study explores various irreducible polynomials,navigating the trade-offs between computational efficiency and watermark imperceptibility.In parallel,the study pays careful attention to the execution time,a paramount consideration in real-world scenarios,to strike a balance between efficiency and efficacy.This comprehensive analysis provides valuable insights into the interplay of GF multiplication tables,diverse irreducible polynomials,scene selection,adaptive thresholding,imperceptibility,and execution time.The evaluation of the proposed algorithm's robustness was conducted using PSNR and NC metrics,and it was subjected to assessment under the impact of five distinct attack scenarios.These findings contribute to the development of watermarking strategies that balance imperceptibility,robustness,and processing efficiency,enhancing the field's practicality and effectiveness.

关键词： Video watermarking galois field irreducible polynomial multiplication table scene selection adaptive thresholding

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

An Encoding-Decoding Framework Based on CNN for circ RNA-RBP Binding Sites Prediction

引用

Chinese Journal of Electronics 2024年第1期33卷 256-263页

作者： Yajing GUO Xiujuan LEI Yi PAN School of computer science Shaanxi Normal University Faculty of computer science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences department of computer science Georgia State University

Predicting RNA binding protein(RBP) binding sites on circular RNAs(circ RNAs) is a fundamental step to understand their interaction mechanism. Numerous computational methods are developed to solve this problem, but they cannot fully learn the features. Therefore, we propose circ-CNNED, a convolutional neural network(CNN)-based encoding and decoding framework. We first adopt two encoding methods to obtain two original matrices. We preprocess them using CNN before fusion. To capture the feature dependencies, we utilize temporal convolutional network(TCN) and CNN to construct encoding and decoding blocks, respectively. Then we introduce global expectation pooling to learn latent information and enhance the robustness of circ-CNNED. We perform circ-CNNED across 37 datasets to evaluate its effect. The comparison and ablation experiments demonstrate that our method is superior. In addition, motif enrichment analysis on four datasets helps us to explore the reason for performance improvement of circ-CNNED.

关键词： Circular RNAs (circRNAs) RNA binding proteins Convolutional neural network Temporal convolutional network Encoder-decoder network

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

SHA: QoS-Aware Software and Hardware Auto-Tuning for Database Systems

引用

Journal of computer science & Technology 2024年第2期39卷 369-383页

作者：李进陈全唐晓新过敏意 department of computer science Shanghai Jiao Tong UniversityShanghai 200240China department of computer science and Technology Shanghai University of Finance and EconomicsShanghai 200433China

While databases are widely-used in commercial user-facing services that have stringent quality-of-service(QoS)requirement,it is crucial to ensure their good performance and minimize the hardware usage at the same time.Our investigation shows that the optimal DBMS(database management system)software configuration varies for different user request patterns(i.e.,workloads)and hardware configurations.It is challenging to identify the optimal software and hardware configurations for a database workload,because DBMSs have hundreds of tunable knobs,the effect of tuning a knob depends on other knobs,and the dependency relationship changes under different hardware configurations.In this paper,we propose SHA,a software and hardware auto-tuning system for DBMSs.SHA is comprised of a scaling-based performance predictor,a reinforcement learning(RL)based software tuner,and a QoS-aware resource reallocator.The performance predictor predicts its optimal performance with different hardware configurations and identifies the minimum amount of resources for satisfying its performance requirement.The software tuner fine-tunes the DBMS software knobs to optimize the performance of the workload.The resource reallocator assigns the saved resources to other applications to improve resource utilization without incurring QoS violation of the database workload.Experimental results show that SHA improves the performance of database workloads by 9.9%on average compared with a state-of-the-art solution when the hardware configuration is fixed,and improves 43.2%of resource utilization while ensuring the QoS.

关键词： auto-tuning database configuration joint tuning utilization quality-of-service(QoS)

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Federated Learning Security and Privacy-Preserving Algorithm and Experiments Research Under Internet of Things Critical Infrastructure

引用

Tsinghua science and Technology 2024年第2期29卷 400-414页

作者： Nasir Ahmad Jalali Hongsong Chen department of computer science University of Science and Technology Beijing(USTB)Beijing 100083China

The widespread use of the Internet of Things(IoTs)and the rapid development of artificial intelligence technologies have enabled applications to cross commercial and industrial band settings.Within such systems,all participants related to commercial and industrial systems must communicate and generate data.However,due to the small storage capacities of IoT devices,they are required to store and transfer the generated data to third-party entity called“cloud”,which creates one single point to store their data.However,as the number of participants increases,the size of generated data also increases.Therefore,such a centralized mechanism for data collection and exchange between participants is likely to face numerous challenges in terms of security,privacy,and performance.To address these challenges,Federated Learning(FL)has been proposed as a reasonable decentralizing approach,in which clients no longer need to transfer and store real data in the central server.Instead,they only share updated training models that are trained over their private datasets.At the same time,FL enables clients in distributed systems to share their machine learning models collaboratively without their training data,thus reducing data privacy and security challeges.However,slow model training and the execution of additional unnecessary communication rounds may hinder FL applications from operating properly in a distributed system.Furthermore,these unnecessary communication rounds make the system vulnerable to security and privacy issues,because irrelevant model updates are sent between clients and servers.Thus,in this work,we propose an algorithm for fully homomorphic encryption called Cheon-Kim-Kim-Song(CKKS)to encrypt model parameters for their local information privacy-preserving function.The proposed solution uses the impetus term to speed up model convergence during the model training process.Furthermore,it establishes a secure communication channel between IoT devices and the server.We also use a lightweight secure transport protocol

关键词： Federated Learning(FL) Internet of Things(IoTs) lightweight Transport Layer Security(iTLS) Cheon-Kim-Kim-Song(CKKS)

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Leveraging User-Generated Comments and Fused BiLSTM Models to Detect and Predict Issues with Mobile Apps

引用

computers, Materials & Continua 2024年第4期79卷 735-759页

作者： Wael M.S.Yafooz Abdullah Alsaeedi department of computer science College of Computer Science and EngineeringTaibah UniversityMedina42353Saudi Arabia

In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user comments.However, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.

关键词： Mobile apps issues play store user comments deep learning LSTM bidirectional LSTM

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Weighted Forwarding in Graph Convolution Networks for Recommendation Information Systems

引用

computers, Materials & Continua 2024年第2期78卷 1897-1914页

作者： Sang-min Lee Namgi Kim department of computer science Kyonggi UniversitySuwonKorea

Recommendation Information Systems(RIS)are pivotal in helping users in swiftly locating desired content from the vast amount of information available on the Internet.Graph Convolution Network(GCN)algorithms have been employed to implement the RIS efficiently.However,the GCN algorithm faces limitations in terms of performance enhancement owing to the due to the embedding value-vanishing problem that occurs during the learning process.To address this issue,we propose a Weighted Forwarding method using the GCN(WF-GCN)algorithm.The proposed method involves multiplying the embedding results with different weights for each hop layer during graph learning.By applying the WF-GCN algorithm,which adjusts weights for each hop layer before forwarding to the next,nodes with many neighbors achieve higher embedding values.This approach facilitates the learning of more hop layers within the GCN framework.The efficacy of the WF-GCN was demonstrated through its application to various datasets.In the MovieLens dataset,the implementation of WF-GCN in LightGCN resulted in significant performance improvements,with recall and NDCG increasing by up to+163.64%and+132.04%,respectively.Similarly,in the Last.FM dataset,LightGCN using WF-GCN enhanced with WF-GCN showed substantial improvements,with the recall and NDCG metrics rising by up to+174.40%and+169.95%,respectively.Furthermore,the application of WF-GCN to Self-supervised Graph Learning(SGL)and Simple Graph Contrastive Learning(SimGCL)also demonstrated notable enhancements in both recall and NDCG across these datasets.

关键词： Deep learning graph neural network graph convolution network graph convolution network model learning method recommender information systems

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

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：