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Worst-Case Misidentification Control in Sequential change Diagnosis Using the Min-CuSum

IEEE TRANSACTIONS ON INFORMATION THEORY 2024年第11期70卷 8364-8377页

作者： Warner, Austin Fellouris, Georgios Univ Illinois Dept Stat Urbana IL 61801 USA

The problem of sequential change diagnosis is considered, where a sequence of independent random elements is accessed sequentially, there is an abrupt change in its distribution at some unknown time, and there are two main operational goals: to quickly detect the change, and to accurately identify upon stopping the post-change distribution among a finite set of alternatives. The focus is on the min-CuSum algorithm, which raises an alarm as soon as a CuSum statistic that corresponds to one of the post-change alternatives exceeds a certain threshold. We obtain, under certain assumptions, non-asymptotic upper bounds on its conditional probability of misidentification given that a false alarm did not occur. When, in particular, the data are generated over independent channels and the change can occur in only one of them, its worst-case-with respect to the change point-conditional probability of misidentification given that there was not a false alarm is shown to decay exponentially fast in the threshold. As a corollary, in this setup, the min-CuSum is shown to asymptotically minimize Lorden's detection delay criterion, simultaneously for every post-change scenario, within the class of schemes that satisfy prescribed bounds on both the false alarm rate and the worst-case conditional probability of misidentification, in a regime where the latter does not go to zero faster than the former. Finally, these theoretical results are also illustrated in simulation studies.

关键词： Delays Monitoring change detection algorithms Vectors Time measurement Target tracking Stochastic processes CuSum Lorden's criterion sequential change detection sequential change diagnosis identification

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Wipe scene change detector for use with video compression algorithms and MPEG-7

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 1998年第1期44卷 43-51页

作者： Alattar, AM King Fahd Univ Petr & Minerals Dept Elect Engn Dhahran 31261 Saudi Arabia

The use of wipes in video production to smooth the transition between two consecutive scenes complicates subsequent video compression, video editing, and video database indexing. It is important to detect the wipe region in order to improve the quality of the compressed video or to allow automatic parsing of the video for the purpose of editing and data base indexing. In this paper, a model is developed for the wipe region and is used to derive the statistical characteristics of the frames in the wipe region. A wipe detector that exploits the linear change in the means and the variances of the frames in the wipe region is developed. The developed wipe detector is implemented and tested with video sequences containing wipes of different types and lengths. Simulation results indicate that wipe regions are well represented by the developed wipe model, and that the developed wipe detector is robust to wipe type and length.

关键词： Layout Detectors Video compression change detection algorithms MPEG 7 Standard Video sequences Databases Indexing Image coding Production

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Spatially-Aware Temporal Anomaly Mapping of Gamma Spectra

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IEEE TRANSACTIONS ON NUCLEAR SCIENCE 2014年第3期61卷 1284-1289页

作者： Reinhart, Alex Athey, Alex Biegalski, Steven Carnegie Mellon Univ Dept Stat Pittsburgh PA 15213 USA Univ Texas Austin Appl Res Labs Austin TX 78713 USA Univ Texas Austin Nucl Engn Teaching Lab Austin TX 78712 USA

For security, environmental, and regulatory purposes it is useful to continuously monitor wide areas for unexpected changes in radioactivity. We report on a temporal anomaly detection algorithm which uses mobile detectors to build a spatial map of background spectra, allowing sensitive detection of any anomalies through many days or months of monitoring. We adapt previously-developed anomaly detection methods, which compare spectral shape rather than count rate, to function with limited background data, allowing sensitive detection of small changes in spectral shape from day to day. To demonstrate this technique we collected daily observations over the period of six weeks on a 0.33 square mile research campus and performed source injection simulations.

关键词： change detection algorithms gamma-ray detection radiation monitoring spectral analysis

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Designed inputs for detection and isolation of failures in the state transition matrices of dynamic systems

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IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY 1997年第2期5卷 149-162页

作者： Riggins, RN Ribbens, WB USAF INST TECHNOLDEPT ELECT & COMP ENGNWRIGHT PATTERSON AFBOH 45433 UNIV MICHIGAN DEPT ELECT ENGN & COMP SCIANN ARBORMI 48109

A new failure detection and isolation algorithm is presented for linear time-invariant deterministic systems, In particular, the technique exploits the system inputs to distinguish between a change in the state transition matrix and actuator failures, including output equivalent events, It is assumed that a failure has been detected previously by some other method, such as by a failure detection filter, Previous methods that attempted to isolate changes in the state transition matrix did not use the input in any way and required explicit knowledge of the changed parameter values (e.g., the multiple model method), The designed input method presented in this paper requires only the knowledge of the null spares of the changed parameter matrices, not of the explicit values of the changed parameters, This feature allows the failure detection and isolation (FDI) algorithm based on designed inputs to isolate partially unknown changes in the state transition matrix, a distinct advantage over other methods in terms of computational efficiency, Detailed design procedures are accompanied by an example that illustrates the input design method, The example uses designed inputs to distinguish between changes in the state transition parameters of an AFTI/F-16 model from nearly output equivalent actuator calibration errors.

关键词： Fault detection Control systems Design methodology Actuators Algorithm design and analysis Filters Isolation technology change detection algorithms Null space Computational efficiency

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Model-Free Fault detection and Isolation in Large-Scale Cyber-Physical Systems

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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE 2017年第1期1卷 61-71页

作者： Alippi, Cesare Ntalampiras, Stavros Roveri, Manuel Politecn Milan Dipartimento Elettron Informaz & Bioingn I-20133 Milan Italy Univ Svizzera Italiana CH-6900 Lugano Switzerland

Detecting and isolating faults in cyber-physical systems (CPSs), e.g., critical infrastructures, smart buildings/cities, and the Internet-of-things, are tasks that do generally scale badly with the CPS size. This work introduces a model-free fault detection and diagnosis system (FDDS) designed, having in mind seal-ability issues, so as to be able to detect and isolate faults in CPSs characterised by a large number of sensors. Following the model-free approach, the proposed FDDS learns the nominal fault-free conditions of the large-scale CPS autonomously by exploiting the temporal and spatial relationships existing among sensor data. The novelties in this paper reside in 1) a clustering method proposed to partition the large-scale CPS into groups of highly correlated sensors in order to grant scalability of the proposed FDDS, and 2) the design of model- and fault-free mechanisms to detect and isolate multiple sensor faults, and disambiguate between sensor faults and time variance of the physical phenomenon the cyber layer of CPS inspects.

关键词： change detection algorithms clustering methods cyber-physical systems hidden Markov models

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Industrially Applicable System Regression Test Prioritization in Production Automation

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2018年第4期15卷 1839-1851页

作者： Ulewicz, Sebastian Vogel-Heuser, Birgit Tech Univ Munich Inst Automat & Informat Syst D-85748 Garching Germany

When changes are performed on an automated production system (aPS), new faults can be accidentally introduced into the system, which are called regressions. A common method for finding these faults is regression testing. In most cases, this regression testing process is performed under high time pressure and onsite in a very uncomfortable environment. Until now, there has been no automated support for finding and prioritizing system test cases regarding the fully integrated aPS that are suitable for finding regressions. Thus, the testing technician has to rely on personal intuition and experience, possibly choosing an inappropriate order of test cases, finding regressions at a very late stage of the test run. Using a suitable prioritization, this iterative process of finding and fixing regressions can be streamlined and a lot of time can be saved by executing test cases likely to identify new regressions earlier. Thus, an approach is presented in this paper that uses previously acquired runtime data from past test executions and performs a change identification and impact analysis to prioritize test cases that have a high probability to unveil regressions caused by side effects of a system change. The approach was developed in cooperation with reputable industrial partners active in the field of aPS engineering, ensuring a development in line with industrial requirements. An industrial case study and an expert evaluation were performed, showing promising results.

关键词： change detection algorithms IEC 61131-3 manufacturing automation software quality system testing

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CONSTRAINT OPTIMUM WELL-LOG SIGNAL SEGMENTATION

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1989年第5期27卷 633-641页

作者： MOGHADDAMJOO, A Department of Electrical Engineering and Computer Science University of Wisconsin Milwaukee Milwaukee WI USA

A special classification algorithm is proposed that can be applied to a preprocessed (or the original noisy) well-log signal for segmentation. Knowledge of the number of segments or any other constraint, if existent, along with a criterion function can be used to complete the algorithm. The preprocessing routine consists of a running window change-detection algorithm which detects all the potential candidates for the location of changes in the signal. This routing can be applied in way that significantly overestimates the number of changes. These points of change along with other estimated parameters are used by the classification algorithm to find the global best-segmentation that agrees with the a priori knowledge of the number of segments (or any other constraint) and satisfies a criterion function. The resultant optimum classification algorithm is recursive and computationally efficient. The performance of the overall algorithm is demonstrated by several examples.< >

关键词： Signal processing algorithms change detection algorithms Signal processing Graphics Routing Parameter estimation Performance analysis Algorithm design and analysis Parametric statistics Gaussian distribution

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A Combined Data-Driven and Model-Based Residual Selection Algorithm for Fault detection and Isolation

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IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY 2019年第2期27卷 616-630页

作者： Jung, Daniel Sundstrom, Christofer Linkoping Univ Dept Elect Engn S-58183 Linkoping Sweden Ohio State Univ Ctr Automot Res Columbus OH 43210 USA

Selecting residual generators for detecting and isolating faults in a system is an important step when designing model-based diagnosis systems. However, finding a suitable set of residual generators to fulfill performance requirements is complicated by model uncertainties and measurement noise that have negative impact on fault detection performance. The main contribution is an algorithm for residual selection that combines model-based and data-driven methods to find a set of residual generators that maximizes fault detection and isolation performance. Based on the solution from the residual selection algorithm, a generalized diagnosis system design is proposed where test quantities are designed using multivariate residual information to improve detection performance. To illustrate the usefulness of the proposed residual selection algorithm, it is applied to find a set of residual generators to monitor the air path through an internal combustion engine.

关键词： Automotive applications change detection algorithms fault detection fault diagnosis machine learning

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Conceptual Framework for Software change

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IT PROFESSIONAL 2024年第2期26卷 57-66页

作者： Saied, Mohamed Elfatatry, Ahmed Mohammed Guirguis, Shawkat Kamal Alexandria Univ Inst Grad Studies & Res Dept Informat Technol Alexandria 21526 Egypt Alexandria Univ Inst Grad Studies & Res software Engn field Alexandria 21526 Egypt Alexandria Univ Inst Grad Studies & Res Dept Informat Technol software Engn Alexandria 21526 Egypt Alexandria Univ Inst Grad Studies & Res Dept Informat Technol Comp Sci & informat Alexandria 21526 Egypt

Ever since the invention of software, change has been a destabilizing factor. Although many new software changes are being applied, the terminologies used to describe them are often inconsistent. This restricts practitioners to designing and evaluating their changes. This article aims to develop a conceptual framework of software change based on six main dimensions regarding the source, essence, and consequences of software change. To evaluate the proposed framework, benchmarking is applied against selected 11 previous studies.

关键词： Software systems Codes Cloud computing Software engineering Computer architecture Source coding Software maintenance change detection algorithms Software development management

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HiTempo: a platform for time-series analysis of remote-sensing satellite data in a high-performance computing environment

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2012年第15期33卷 4720-4740页

作者： Van den Bergh, Frans Wessels, Konrad J. Miteff, Simeon Van Zyl, Terence L. Gazendam, Albert D. Bachoo, Asheer K. CSIR Meraka Inst Remote Sensing Res Unit ZA-0001 Pretoria South Africa CSIR Meraka Inst High Performance Comp Res Grp ZA-0001 Pretoria South Africa CSIR Signal Proc Res Grp ZA-0001 Pretoria South Africa

Course resolution earth observation satellites offer large data sets with daily observations at global scales. These data sets represent a rich resource that, because of the high acquisition rate, allows the application of time-series analysis methods. To research the application of these time-series analysis methods to large data sets, it is necessary to turn to high-performance computing (HPC) resources and software designs. This article presents an overview of the development of the HiTempo platform, which was designed to facilitate research into time-series analysis of hyper-temporal sequences of satellite image data. The platform is designed to facilitate the exhaustive evaluation and comparison of algorithms, while ensuring that experiments are reproducible. Early results obtained using applications built within the platform are presented. A sample model-based change detection algorithm based on the extended Kalman filter has been shown to achieve a 97% detection success rate on simulated data sets constructed from MODIS time series. This algorithm has also been parallelized to illustrate that an entire sequence of MODIS tiles (415 tiles over 9 years) can be processed in under 19 minutes using 32 processors.

关键词： acquisition rate Representation of data High Performance Computing Tile Platform time series analysis Extended Kalman filters Dataset change detection algorithms Satellite Imagery

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