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Quantifying software security based on stochastic Petri nets

Journal of Computational Information Systems 2010年第9期6卷 3049-3056页

作者： Yang, Nianhua Yu, Huiqun Sun, Hua Qian, Zhilin Department of Computer Science and Engineering East China University of Science and Technology Shanghai 200237 China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai 201112 China

To quantitatively predict software security, a component security model is proposed based on Stochastic Petri Nets (SPNs). An isomorphic Markov Chain (MC) is obtained from the component SPN model. A quantitative security evaluation prediction method is proposed. The prediction value is calculated according to the steady states probability distribution of MC, obtained from a software SPN model. Sensitivity analysis method is proposed. It provides a mean to trace back to the critical components for security enhancing. A case study shows the applicability and feasibility of our method. © 2010 Binary Information Press.

关键词： Sensitivity analysis

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Formal specification and reasoning for situated multi-agent system

Formal specification and reasoning for situated multi-agent ...

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International Conference on computer and Information Science (ACIS)

作者： Zhuang Li Huaikou Miao School of Computer Engineering Science Shanghai University Shanghai China Shanghai Key Laboratory of Computer Software Evaluating&Testing Shanghai China

We present a formal specification to engineer situated multi-agent Systems (situated MAS), which has revealed the need for specifying and reasoning of its global property. This paper shows how MAS is specified with modified Object-Z notation with trace semantic of action system, and how to reason about safety and liveness property in this specification. Independent and joint MAS examples are are used to illustrate specifying and reasoning in specification for situated MAS.

关键词： Noise measurement

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Stock technical analysis system based on real-time stream processing

Stock technical analysis system based on real-time stream pr...

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作者： Ding, Wencheng Wang, Hongya Peng, Nan Xiao, Yingyuan Liu, Zhenyu School of Computer Science and Technology Donghua University Shanghai China School of Computer Science and Engineering Tianjin University of Technology Tianjin China Shanghai Key Laboratory of Computer Software Testing and Evaluation Shanghai China

ISBN: (纸本)9781538636749

Nowadays a large number of applications requires continuous and timely processing of information as it flows from the periphery to the center of the system. Among numerous tools that support these scenarios, the Esper engine is one of the most excellent and practical ones. In this paper, we utilize the Esper engine and a series of financial models to design and implement Stock Technical Analysis System Based on Real-time Stream Processing(STAS). Several general financial models, such as the capital asset pricing model, Candlestick chart, KDJ index and MACD index, are introduced to fulfill the requirements from different users. All these models or indexes are supported by the Esper engine which has a superiority in real-time processing. In this system, users can choose their favorite stocks based on annualized income and visualize these selected stocks in the form of data list, graph and analysis report. © 2017 IEEE.

关键词： Esper Engine Real-time Stream Processing Stock Technical Analysis

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Finding interesting cleaning rules from dirty data

Finding interesting cleaning rules from dirty data

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作者： Peng, Nan Wang, Hongya Ding, Wencheng Xiao, Yingyuan Liu, Zhenyu School of Computer Science and Technology Donghua University Shanghai China School of Computer Science and Engineering Tianjin University of Technology Tianjin China Shanghai Key Laboratory of Computer Software Testing and Evaluation Shanghai China

ISBN: (纸本)9781538636749

Data cleaning is an important problem and data quality rules are the most promising way to address it. Previous researches have focused on constraints, such as functional dependencies (FDs), conditional functional dependencies (CFDs), fixing rules, and editing rules. These rules can be provided by experts, or discovered by mining algorithms and then experts verify. But in the condition of dirty dataset, it is highly unlikely that useful FDs could be discovered. If there are no useful cleaning rules, the user can not capture and correct errors in data. In this paper, we develop a system that is able to find interesting rules from dirty data. There is no hope to mine significant functional dependencies directly by the TANE algorithm because of the existence of errors in data. Thus, we discover approximate functional dependencies as candidate cleaning rules with the improved TANE algorithm. The number of candidate rules is very large, making it expensive for the user verification. Since not all candidate rules make sense in practice, we design two kinds of ranking methods: the support-based ranking and the comprehensive score ordering. Our ranking methods usually put the most useful rules ahead. Experimental results show that our sorting methods can effectively help the user find useful cleaning rules. © 2017 IEEE.

关键词： Data Cleaning Data Quality Rules Functional Dependencies

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Test Sequence Generation Based on Chain Unique Input-Output Sequence in FSM Conformance testing

Test Sequence Generation Based on Chain Unique Input-Output ...

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作者： Weiwei Lin Hongwei Zeng School of Computer Engineering and Science Shanghai UniversityShanghai Key Laboratory of Computer Software Evaluating &Testing School of Computer Engineering and Science Shanghai University

This paper introduces a test method based on chain unique input/output(CUIO) sequence in finite state machine(FSM) conformance testing. For FSMs with UIO for each state, the test sequence based on CUIO can identify all the states and verify all the transitions. For FSMs without UIO for some states, the test sequence based on CUIO can identify as many states and verify as many transitions as possible. Meanwhile, W method is introduced to deal with the unidentified states and the unverified transitions. For FSMs without UIO for each state, the method completely degenerates to W method. It is proved by experiment that the average and maximum reduction rate are 45.5% and 63.2% comparing with UIO ***, the method is always feasible even when UIO method fails.

关键词： Test Sequence Generation Based on Chain Unique Input-Output Sequence in FSM Conformance testing

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Scheduling Real-Time Embedded Systems Based on TCPNIA

Journal of Software

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Journal of software 2011年第3期6卷 340-348页

TCPNIA (Timed Colored Petri Nets with Inhibitor Arcs, TCPNIA) is a model for specifying real-time embedded systems. It integrates features of colored Petri nets, timed Petri nets and inhibitor arcs. The methods for modeling modules of systems using TCPNIA are proposed. A depth-first scheduling algorithm for TCPNIA is proposed. The system level resource's influence to schedulable path is considered. Different data in tokens will change an execution path and call different data operational functions. The influence from data operational functions is considered in the scheduling algorithm. The time requirement upper bound of a schedulable path can be calculated in the algorithm. Tasks' parallel executions have been considered when the time upper bound of the path is calculated. The soundness of the algorithm is proved. The time and space complexities of the algorithm are also analyzed. The compositional conditions and method for composing schedulable path are given. A case study shows the applicability and feasibility of the method. © 2011 ACADEMY PUBLISHER.

关键词： Petri nets

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Surface Defects Detection of Railway Turnouts

Surface Defects Detection of Railway Turnouts

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第三十四届中国控制会议

作者： Li Shen Xiukun Wei Limin Jia State Key Laboratory of Railway Traffic Control and Safety Beijing Jiaotong University Shanghai Key Laboratory of Computer Software Evaluating & Testing(Shanghai Development Center of Computer Software Technology)

ISBN: (纸本)9781467374439

As the turnout is a critical part of railway tracks, its surface defects are directly related to the operation safety. The defects detection of turnout is an effect way to ensure the safety and comfort of urban transit railway. In this paper, the feature extraction of the turnout defects is investigated based on the bogie acceleration measurements. The normal turnout model and faulty turnout model based on SIMPACK are established first, from which the vehicle vibration acceleration is obtained. Then, the acceleration signal is analyzed in time- frequency domain. The results show that the power spectral density(PSD) and all the frequency-domain features are useful for detecting the poor fit defect of the switch point. And the peak and PSD features can be used to detect the curve opposite super-elevation. The proposed method provides alternative for the detection of turnout defects by using in-service vehicle.

关键词： turnout,defects feature,poor fit of switch point,curve opposite super-elevation

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Detection of Rail Squats Based on Hilbert-Huang Transform by Using Bogie Acceleration Measurement

Detection of Rail Squats Based on Hilbert-Huang Transform by...

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第28届中国控制与决策会议

作者： Xiukun Wei Yuxin Liu Xianxian Yin State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Shanghai Key Laboratory of Computer Software Evaluating & Testing(Shanghai Development Center of Computer Software Technology)

ISBN: (纸本)9781467397155

The squat is a type of rolling contact fatigue(RCF) damage,the existence of squats directly impacts the operating condition of urban rail *** current detection methods of the rail squats damage are mainly based on track inspection car and rail flaw *** has some disadvantages,for example,long detection cycle,no real-time detecting and narrow scope,time consuming and *** this paper,a new detection method of squats which based on the in-service vehicles is *** bogie acceleration signal is used to detect the squats on the *** validate the possibility of the proposed *** the help of SIMPACK software,an in-service vehicle-track dynamic model and models of typical squats are built to generate the simulated bogie acceleration signals when the train wheels rolls over the *** simulation signals from the normal rail and the rail with squats are studied by HHT,it is found that0～50Hz and 300 Hz are the feature frequency caused by the squats damages.A unique W-shaped natural vibration mode is decomposed from the acceleration signals which is the feature vibration mode of the squat ***,the above detection method is applied to the field test data of shanghai metro line *** feasibility and reliability of the proposed method are *** proposed method provides an alternative for real application.

关键词： Squats In Service Vehicle Acceleration Signals SIMPACK HHT Field Test

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Instance-Aware Domain Generalization for Face Anti-Spoofing

Instance-Aware Domain Generalization for Face Anti-Spoofing

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Qianyu Zhou Ke-Yue Zhang Taiping Yao Xuequan Lu Ran Yi Shouhong Ding Lizhuang Ma Shanghai Jiao Tong University Shanghai Key Laboratory of Computer Software Evaluating and Testing Youtu Lab Tencent Deakin University

Face anti-spoofing (FAS) based on domain generalization (DG) has been recently studied to improve the generalization on unseen scenarios. Previous methods typically rely on domain labels to align the distribution of each domain for learning domain-invariant representations. However, artificial domain labels are coarse-grained and subjective, which cannot reflect real domain distributions accurately. Besides, such domain-aware methods focus on domain-level alignment, which is not fine-grained enough to ensure that learned representations are insensitive to domain styles. To address these issues, we propose a novel perspective for DG FAS that aligns features on the instance level without the need for domain labels. Specifically, Instance-Aware Domain Generalization framework is proposed to learn the generalizable feature by weakening the features' sensitivity to instance-specific styles. Concretely, we propose Asymmetric Instance Adaptive Whitening to adaptively eliminate the style-sensitive feature correlation, boosting the generalization. Moreover, Dynamic Kernel Generator and Categorical Style Assembly are proposed to first extract the instance-specific features and then generate the style-diversified features with large style shifts, respectively, further facilitating the learning of style-insensitive features. Extensive experiments and analysis demonstrate the superiority of our method over state-of-the-art competitors. Code will be publicly available at this link.

关键词：

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Detection of Railway Track Squats by Using Bogie Acceleration Measurement

Detection of Railway Track Squats by Using Bogie Acceleratio...

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第三十四届中国控制会议

作者： Xianxian Yin Xiukun Wei Limin Jia State Key Laboratory of Railway Traffic Control and Safety Beijing Jiaotong University Shanghai Key Laboratory of Computer Software Evaluating & Testing(Shanghai Development Center of Computer Software Technology)

ISBN: (纸本)9781467374439

The railway track squat is one of the most dangerous track defects, it causes large dynamic contact force at the wheel-rail interface, leading to fast deterioration of the track, bring significant harm to the safety of the passengers. Early detection of such defects is very important for timely maintenance. In this paper, a squats detection method based on bogie acceleration(BA) measurement is presented. A simulation model with acceleration sensors is set up in the SIMPACK simulation environment. Time-frequency analysis and wavelet packet decomposition are applied to analyze these BA data obtained from the simulation model. The effectiveness of the above approach is demonstrated by simulation results.

关键词： squats BA measurement time-frequency domain analysis wavelet packet decomposition

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