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AATT+: Effectively manifesting concurrency bugs in Android apps

science of computer programming 2018年 163卷 1-18页

作者： Wang, Jue Jiang, Yanyan Xu, Chang Li, Qiwei Gu, Tianxiao Ma, Jun Ma, Xiaoxing Lu, Jian State Key Lab for Novel Software Technology Nanjing University Nanjing China Department of Computer Science and Technology Nanjing University Nanjing China

Smartphones are indispensable in people's daily activities, and smartphone apps tend to be increasingly concurrent due to the wide use of multi-core devices and technologies. Due to this tendency, developers are increasingly unable to tackle the complexity of concurrent apps and to avoid subtle concurrency bugs. To better address this issue, we propose a novel approach to detecting concurrency bugs in Android apps based on the fact that one can generate simultaneous input events and their schedules for an app, which would easily trigger concurrency bugs in an app. We conduct systematic state space exploration to find potentially conflicting resource accesses in an Android app. The app is then automatically pressure-tested by guided event and schedule generation. We implemented our prototype tool named AATT+ and evaluated it with two sets of real-world Android apps. Benchmarking using 15 Android apps with previously known concurrency bugs, AATT+ and existing concurrency-unaware techniques detected 10 and 1 bugs, respectively. Evaluated with another set of 17 popular Android apps, AATT+ detected 11 concurrency bugs and 7 of them were previously unknown, achieving an over 80% higher detection rate than existing concurrency-unaware techniques. © 2018 Elsevier B.V.

关键词： Smartphones

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RTL Satisfiability Solving Using an ATPG based Approach

RTL Satisfiability Solving Using an ATPG based Approach

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2005 6th International Conference on ASIC

作者： Minchuan Chen Weimin Wu Jinian Bian EDA lab Department of Computer Science & TechnologyTsinghua University

ISBN: (纸本)0780392108

We present a special approach to solving Satisfiability problem in RTL(register transfer level) circuit,which contains both Boolean logics and word-level arithmetics. In our approach,an ATPG(automatic test pattern generation) based Satisfiability solver is implemented on RTL netlist *** expert tool for circuits,our ATPG engine employs fast constraint propagation,where all the signals are treated as *** the undecided signals,we render a depth-first *** huge search space is cut down by some *** results on ITC benchmarks demonstrate the feasibility and efficiency of our techniques.

关键词： RTL Satisfiability Solving Using an ATPG based Approach

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Brain-computer Interface Meets Information Retrieval: Perspective on Next-generation Information System 1

Brain-Computer Interface Meets Information Retrieval: Perspe...

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1st International Workshop on Brain-computer Interfaces (BCI) for Multimedia Understanding, BCIMM 2024, co-located with ACM Multimedia 2024

作者： Ye, Ziyi Ai, Qingyao Liu, Yiqun Department of Computer Science and Technology Tsinghua University Quancheng Lab. Beijing China Department of Computer Science and Technology Tsinghua University Zhongguancun Lab. Beijing China Quancheng Lab. Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9798400711893

Information retrieval (IR) applications, such as search engines, ChatGPT, and recommender systems, have become essential tools for acquiring knowledge, making decisions, and solving problems. These systems have transformed the web into an external memory for humans, changing the way we think and learn from information. Despite advances in IR technology, the interaction paradigm between humans and information systems has remained largely unchanged for decades. Recently, with the development of neuroscience and biomedical engineering, it is possible to build a direct communication pathway between a computing device and the human brain via Brain-computer Interfaces (BCIs). In this paper, we provide an overview of the application of BCIs in IR-related research. We identify three main opportunities for integrating active or passive BCIs into information systems: enhancing system control, improving user modeling, and enabling proactive system design. Additionally, we discuss example applications and challenges based on the proposed conceptual framework of BCIs for IR, and propose a research agenda for incorporating BCIs into IR systems. © 2024 Copyright held by the owner/author(s).

关键词： Recommender systems

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Explore the structure of social tags by subsumption relations

Explore the structure of social tags by subsumption relation...

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23rd International Conference on Computational Linguistics, Coling 2010

作者： Si, Xiance Liu, Zhiyuan Sun, Maosong Department of Computer Science and Technology State Key Lab on Intelligent Technology and Systems National Lab for Information Science and Technology China

Thanks to its simplicity, social tagging system has accumulated huge amount of user contributed tags. However, user contributed tags lack explicit hierarchical structure, while many tag-based applications would benefit if such a structure presents. In this work, we explore the structure of tags with a directed and easy-to-evaluate relation, named as the subsumption relation. We propose three methods to discover the subsumption relation between tags. Specifically, the tagged document's content is used to find the relations, which leads to better result. Besides relation discovery, we also propose a greedy algorithm to eliminate the redundant relations by constructing a Layered Directed Acyclic Graph (Layered- DAG) of tags. We perform quantitative evaluations on two real world data sets. The results show that our methods outperform hierarchical clustering-based approach. Empirical study of the constructed Layered-DAG and error analysis are also provided.

关键词： Directed graphs

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computer System Reliability Allocation Method and Supporting Tool

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Wuhan University Journal of Natural sciences 2001年第Z1期6卷 505-510页

作者： Ben Ke\|rong 1, Yan Jiong 2, Wang Ji 2 1 department of computer science, Naval University of Engineering, Wuhan 430033, China Software Engineering Key lab.,Wuhan University,Wuhan 430072, China 2 department of computer science, National Universit Department of Computer Science Naval University of Engineering Wuhan China Software Engineering Key Lab. Wuhan University Wuhan China Department of Computer Science National University of Defence Technology Changsha China

This paper presents a computer system reliability allocation method that is based on the theory of statistic and Markovian chain,which can be used to allocate reliability to subsystem, to hybrid system and software mo... 详细信息

关键词： software Reliability reliability allocation method supporting tool

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Learning with privileged information using Bayesian networks

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Frontiers of computer science 2015年第2期9卷 185-199页

作者： Shangfei WANG Menghua HE Yachen ZHU Shan HE Yue LIU Qiang JI School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Key Lab of Computing and Communicating Software of Anhui Province Hefei 230027 China School of Mathematical Sciences University of Science and Technology of China Hefei 230027 China Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY 12180-3590 USA

For many supervised learning applications, addi- tional information, besides the labels, is often available dur- ing training, but not available during testing. Such additional information, referred to the privileged information, can be exploited during training to construct a better classifier. In this paper, we propose a Bayesian network （BN） approach for learning with privileged information. We propose to in- corporate the privileged information through a three-node BN. We further mathematically evaluate different topologies of the three-node BN and identify those structures, through which the privileged information can benefit the classifica- tion. Experimental results on handwritten digit recognition, spontaneous versus posed expression recognition, and gender recognition demonstrate the effectiveness of our approach.

关键词： Bayesian network privileged information clas-sification maximum likelihood estimation

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Next-Generation Human Activity Recognition Using Locality Constrained Linear Coding Combined With Machine Learning (NG-HAR-LCML)

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Healthcare technology Letters 2025年第1期12卷

作者： Shabbir, Maryam Ahmad, Fahad Alanazi, Saad Awadh Khan, Muhammad Hassan Li, Jianqiang Mahmood, Tariq Naseem, Shahid Anwar, Muhammad Department of Computer Sciences Bahria University Punjab Lahore Pakistan Department of Computer Science Faculty of Computing & Information Technology University of the Punjab Lahore Pakistan School of Computing Faculty of Technology University of Portsmouth Portsmouth United Kingdom University of Portsmouth Portsmouth United Kingdom Department of Computer Science College of Computer and Information Sciences Jouf University Aljouf Sakaka Saudi Arabia The School of Software Engineering Beijing University of Technology Beijing China Lab CCIS Prince Sultan University Riyadh Saudi Arabia Department of Information Sciences University of Education Vehari Pakistan Faculty of Information Sciences Division Science &Technology University of Education Lahore Pakistan

Accurate Human Activity Recognition (HAR) is a critical challenge with wide-ranging applications in healthcare, assistive technologies, and human-computer interaction. Traditional feature extraction methods often struggle to capture the complex spatial and temporal dynamics of human movements, leading to suboptimal classification performance. To address this limitation, this study introduces a novel encoding approach using Locality-Constrained Linear Coding (LLC) to enhance the discriminative power of hand-crafted features extracted from low-cost wearable sensors—an accelerometer and a gyroscope. The proposed LLC-based encoding scheme enables robust feature representation, improving the accuracy of HAR models. The encoded features are classified using a diverse set of Machine Learning (ML) and Deep Learning (DL) algorithms, including Support Vector Machine (SVM), Logistic Regression (LR), Naive Bayes (NB), K-Nearest Neighbours (KNN), AdaBoost, Gradient Boosting Machine (GBM), and Deep Belief Network (DBN). Extensive quantitative evaluations demonstrate that LLC significantly outperforms conventional feature encoding techniques, leading to improved classification accuracy. Among the tested models, DBN achieves a state-of-the-art accuracy of 99%, highlighting its superiority for HAR tasks. The contributions of this research are threefold: (1) it establishes the necessity of an advanced encoding scheme (LLC) for feature enhancement in HAR, (2) it provides a rigorous comparative analysis of multiple ML and DL classifiers, and (3) it introduces a scalable and cost-effective HAR framework suitable for real-world applications. Performance is comprehensively assessed using robust evaluation metrics such as Area Under the Curve (AUC), Classification Accuracy (CA), F1 Score, Precision, Recall, and Matthews Correlation Coefficient (MCC). The findings of this study offer new insights into feature encoding for HAR, setting a foundation for future advancements in sensor-based act

关键词： Support vector machines

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VMckpt:lightweight and live virtual machine checkpointing

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science China(Information sciences) 2012年第12期55卷 2865-2880页

作者： LIU HaiKun 1,JIN Hai 1,LIAO XiaoFei 1,MA Bo 1 & XU ChengZhong 2 1 Services Computing technology and System lab,Cluster and Grid Computing lab,School of computer science and technology,Huazhong University of science and technology,Wuhan 430074,China 2 department of Electrical and computer Engineering,Wayne State University,Detroit,MI 48202,USA 1. Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China2. Department of Electrical and Computer Engineering Wayne State University Detroit MI [48202 USA

Recent advance of virtualization technology provides a new approach to check-point/restart at the virtual machine(VM) *** contrast to traditional process-level checkpointing,checkpointing at the virtualization layer brings up several advantages,such as compatibility,transparence,flexibility and ***,because the virtualization layer has little semantic knowledge about the operation system and the applications running atop,VM-layer checkpointing requires saving the entire operating system state rather than a single *** overhead may render the approach *** reduce the size of VM checkpoint,in this paper we propose a page eviction scheme and an incremental checkpointing mechanism to avoid saving unnecessary VM pages in the *** keep the system online transparently,we propose a live checkpointing mechanism by saving the memory image in a copy-on-write(COW) *** implement the performance optimization mechanisms in a prototype system,called *** results with a group of representative applications show that our page eviction scheme and incremental checkpointing can significantly reduce the checkpoint file size by up to 87% and shorten the total checkpointing/restart time by a factor of up to 71%,in comparison with the Xens default checkpointing *** observed application downtimes due to checkpointing can be reduced to as small as 300 ms.

关键词： checkpoint/restart copy-on-write page eviction virtual machine

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Using artificial intelligence to predict the next deceptive movement based on video sequence analysis: A case study on a professional cricket player's movements

Journal of Engineering Research (Kuwait)

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Journal of Engineering Research (Kuwait) 2025年

作者： Mutawa, A.M. Rajesh Kumar, Korupalli V. K, Hemachandran Murugappan, M. Computer Engineering Department College of Engineering and Petroleum Kuwait University Safat 5969 13060 Kuwait CoE Sports Analytics and Management and AI Research Centre School of Business Woxsen University Hyderabad India Intelligent Signal Processing (ISP) Research Lab Department of Electronics and Communication Engineering Kuwait College of Science and Technology Block 4 Doha 13133 Kuwait Department of Electronics and Communication Engineering School of Engineering Vels Institute of Sciences Technology and Advanced Studies Tamilnadu Chennai India Center of Excellence for Unmanned Aerial Systems (CoEUAS) Universiti Malaysia Perlis Perlis 02600 Malaysia

This research develops an artificial intelligence-based model to predict the next deceptive movement of athletes by analyzing video sequences of previous movements. Utilizing advanced deep neural network models, we analyze deceptive movements to forecast the next move, with a practical application on the deceptive movements of a professional cricket player. The model employs machine learning techniques such as Random Forest (RF), Decision Trees (DT), and K-Nearest Neighbor (KNN) to enhance prediction accuracy. Achieving up to 70 % accuracy, this model rivals human capability, as even highly skilled players can easily fall for deceptive actions. The ability to predict deceptive movements sets humans apart from many intelligent creatures, allowing athletes to avoid predictable actions and gain an edge in various sports. This study applies this concept to cricket, leveraging video data to improve training methods. The results highlight the potential of artificial intelligence in revolutionizing training and performance optimization in sports. © 2025 The Authors

关键词： Artificial intelligence Cricket Deceptive movements Machine learning Performance optimization

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A flexible capacitive photoreceptor for the biomimetic retina

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Light(science & Applications) 2022年第1期11卷 38-49页

作者： Mani Teja Vijjapu Mohammed E.Fouda Agamyrat Agambayev Chun Hong Kang Chun-Ho Lin Boon S.Ooi Jr-Hau He Ahmed M.Eltawil Khaled N.Salama Sensors lab Advanced Membranes and Porous Materials CenterComputerElectrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Communication and Computing Systems Lab ComputerElectrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Department of Electrical Engineering and Computer Science University of California-IrvineIrvineCA 92612USA Department of Electrical Computer and Energy EngineeringArizona State UniversityTempeAZUSA Computer Electrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Department of Materials Science and Engineering City University of Hong KongHong Kong SARChina

Neuromorphic vision sensors have been extremely beneficial in developing energy-efficient intelligent systems for robotics and privacy-preserving security *** is a dire need for devices to mimic the retina's photoreceptors that encode the light illumination into a sequence of spikes to develop such ***,we develop a hybrid perovskite-based flexible photoreceptor whose capacitance changes proportionally to the light intensity mimicking the retina's rod cells,paving the way for developing an efficient artificial retina *** proposed device constitutes a hybrid nanocomposite of perovskites(methyl-ammonium lead bromide)and the ferroelectric terpolymer(polyvinylidene fluoride trifluoroethylene-chlorofluoroethylene).A metal-insulator-metal type capacitor with the prepared composite exhibits the unique and photosensitive capacitive behavior at various light intensities in the visible light *** proposed photoreceptor mimics the spectral sensitivity curve of human photopic *** hybrid nanocomposite is stable in ambient air for 129 weeks,with no observable degradation of the composite due to the encapsulation of hybrid perovskites in the hydrophobic *** functionality of the proposed photoreceptor to recognize handwritten digits(MNIST)dataset using an unsupervised trained spiking neural network with 72.05%recognition accuracy is *** demonstration proves the potential of the proposed sensor for neuromorphic vision applications.

关键词： perovskite illumination preserving

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