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- research-articleApril 2024
What makes a real change in software performance? An empirical study on analyzing the factors that affect the triagement of performance change points
Science of Computer Programming (SCPR), Volume 233, Issue Chttps://doi.org/10.1016/j.scico.2023.103068AbstractPerformance tests can be automatically done on each commit version with a continuous integration system. After code changes are pushed to the repository, multiple benchmark tests are run to measure system's performance. Change point detection ...
Highlights
- We use the features from the four dimensions to build a richer set of features.
- Our approach considers the triagement problem whenever a change point is detected, which is a just in time prediction.
- To make the experiments closer ...
- research-articleOctober 2023
Change point estimation in an M / M / 2 queue with heterogeneous servers
Mathematics and Computers in Simulation (MCSC), Volume 212, Issue CPages 182–194https://doi.org/10.1016/j.matcom.2023.04.022AbstractThe change point problem in the inter-arrival time of an M / M / 2 queue with heterogeneous servers is studied here. In this model, it is assumed that the queue is in a steady state and that customers are served by the fastest ...
- research-articleJuly 2023
Anomaly and change point detection for time series with concept drift
AbstractAnomaly detection is one of the most important research contents in time series data analysis, which is widely used in many fields. In real world, the environment is usually dynamically changing, and the distribution of data changes over time, ...
- ArticleMarch 2023
A Tool for Business Processes Diagnostics
Service-Oriented Computing – ICSOC 2022 WorkshopsPages 350–354https://doi.org/10.1007/978-3-031-26507-5_31AbstractRecorded event data of processes inside organizations is a valuable source for providing insights and information using process mining. Most techniques analyze process executions at detailed levels, e.g., process instances, which may result in ...
- research-articleNovember 2022
A high dimensional dissimilarity measure
Computational Statistics & Data Analysis (CSDA), Volume 175, Issue Chttps://doi.org/10.1016/j.csda.2022.107560AbstractA new dissimilarity measure for high-dimensional, low sample size settings to compare high dimensional probability distributions is proposed. The asymptotic behavior of the new dissimilarity index is studied theoretically. Numerical ...
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- research-articleOctober 2022
A deep learning framework for sensor-equipped machine health indicator construction and remaining useful life prediction
Computers and Industrial Engineering (CINE), Volume 172, Issue PAhttps://doi.org/10.1016/j.cie.2022.108559AbstractPrognostic and health management (PHM) effectively reduces the economic loss of sensor-equipped machine downtime caused by under-maintenance and the waste of resources resulted from over-maintenance. The remaining useful life (RUL) ...
Highlights- A deep learning model with change point recognition is used to construct a health indicator.
- research-articleJune 2022
A software reliability growth model for imperfect debugging
Journal of Systems and Software (JSSO), Volume 188, Issue Chttps://doi.org/10.1016/j.jss.2022.111267AbstractIn general, software reliability growth models (SRGMs) are often developed based on the assumptions of perfect debugging, single error type, and consistent testing environment. However, such the assumptions may be unrealistic for ...
Highlights- A software reliability growth model with imperfect debugging is constructed.
- ...
- research-articleSeptember 2021
Explaining social events through community evolution on temporal networks
Applied Mathematics and Computation (APMC), Volume 404, Issue Chttps://doi.org/10.1016/j.amc.2021.126148Highlights- Establish a connection between the evolution of social networks and real social events.
The social network is closely related to people’s lives. And social events are the products of the human subjective initiative during the evolution of networks. Therefore, there is a close correlation between social events and network ...
- research-articleMarch 2021
Most recent changepoint detection in censored panel data
Computational Statistics (CSTAT), Volume 36, Issue 1Pages 515–540https://doi.org/10.1007/s00180-020-01028-5AbstractThis study aims to detect the most recent changepoint in censored panel data by ignoring dependence within and between segments as well as taking into account the serial autocorrelation. A comparison of different methods to detect the most recent ...
- rapid-communicationMarch 2020
A change point estimation problem related to age replacement policies
Operations Research Letters (OPERRL), Volume 48, Issue 2Pages 105–108https://doi.org/10.1016/j.orl.2019.12.005AbstractThe mean time to failure (MTTF) function plays a vital role in the theory of age replacement policies. The point at which the MTTF function changes trend has important implications in the context of cost optimization in such policies. ...
- research-articleJanuary 2020
Robust change point estimation in two-phase linear regression models: An application to metabolic pathway data
Journal of Computational and Applied Mathematics (JCAM), Volume 363, Issue CPages 337–349https://doi.org/10.1016/j.cam.2019.06.020AbstractIn this study, we develop robust versions of the change point estimation methods given by Hudson (1966) and Muggeo (2003) in the two-phase linear regression model. We use a modified maximum likelihood (MML) methodology originated by ...
- research-articleApril 2018
Optimal replacement policies for a shock model with a change point
Computers and Industrial Engineering (CINE), Volume 118, Issue CPages 383–393https://doi.org/10.1016/j.cie.2018.03.005Highlights- A two-stage shock model is proposed to fit the realistic situation.
- The case ...
In this paper, a mixed shock model with a change point is proposed to fit the situation that the failure mechanism changes during the system operation. For the new model, the change point appears when a run of damaging shocks with a ...
- articleMarch 2018
Abrupt change in mean using block bootstrap and avoiding variance estimation
Computational Statistics (CSTAT), Volume 33, Issue 1Pages 413–441https://doi.org/10.1007/s00180-017-0785-4We deal with sequences of weakly dependent observations that are naturally ordered in time. Their constant mean is possibly subject to change at most once at some unknown time point. The aim is to test whether such an unknown change has occurred or not. ...
- research-articleMay 2017
Nonparametric Splitting Algorithm for Detecting Structural Changes in Predictive Relationships
ICCDA '17: Proceedings of the International Conference on Compute and Data AnalysisPages 143–149https://doi.org/10.1145/3093241.3093282The problem of detecting structural changes in a regression study has become crucially important in a wide variety of fields, since data generating processes in a real world are usually unstable. Taking into account the fact that relationships within ...
- research-articleMarch 2017
Fat node leading tree for data stream clustering with density peaks
Knowledge-Based Systems (KNBS), Volume 120, Issue CPages 99–117https://doi.org/10.1016/j.knosys.2016.12.025Detecting clusters of arbitrary shape and constantly delivering the results for newly arrived items are two critical challenges in the study of data stream clustering. However, the existing clustering methods could not deal with these two problems ...
- research-articleMarch 2017
On Discovery of permanent land cover changes using time series segmentation approach
CODS '17: Proceedings of the 4th ACM IKDD Conferences on Data SciencesArticle No.: 15, Pages 1–10https://doi.org/10.1145/3041823.3041832Sustainable land management is one of the crucial aspects that need to be considered in order to protect the resources for future generations. Understanding of land cover changes that occurred during the past decade is necessary to formulate policies and ...
- research-articleMarch 2016
A hybrid method for estimating the process change point using support vector machine and fuzzy statistical clustering
Applied Soft Computing (APSC), Volume 40, Issue CPages 507–516https://doi.org/10.1016/j.asoc.2015.11.021Graphical abstractDisplay Omitted HighlightsA new hybrid method is developed for estimating the process change point in x control chart.An effective sets of features were extracted and the control chart patterns (CCP) are classified using support vector ...
- articleMarch 2016
Bayesian segmental growth mixture Tobit models with skew distributions
Computational Statistics (CSTAT), Volume 31, Issue 1Pages 121–137https://doi.org/10.1007/s00180-015-0620-8This paper presents an extension of the standard Tobit to simultaneously address segmental phases, subpopulation heterogeneity, lower limit of detection, and skewness in outcomes of human immunodeficiency virus (HIV) or acquired immunodeficiency ...
- research-articleSeptember 2015
Monte Carlo comparison of tests of exponentiality against NWBUE alternatives
Mathematics and Computers in Simulation (MCSC), Volume 115, Issue CPages 1–11https://doi.org/10.1016/j.matcom.2015.04.004In this paper we focus on the testing of exponentiality (which essentially captures no aging) against non-monotonic aging captured by the fairly large class of new worse then better than used in expectation (NWBUE) alternatives. Three different tests ...
- articleMarch 2015
A probabilistic artificial neural network-based procedure for variance change point estimation
Soft Computing - A Fusion of Foundations, Methodologies and Applications (SOFC), Volume 19, Issue 3Pages 691–700https://doi.org/10.1007/s00500-014-1293-xControl charts are useful tools of monitoring quality characteristics. One of the problems of employing a control chart is that the time it alarms is not synchronic with the time when assignable cause manifests itself in the process. This makes ...