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Artifact-centric process models aim to describe complex processes as a collection of interacting artifacts. Recent development in process mining allow for the discovery of such models. However, the focus is often on the representation of the individual artifacts rather than their interactions. Based on event data we can automatically discover composite state machines representing artifact-centric...
Tremendous amounts of data can be recorded during software execution. This provides valuable information on software runtime analysis. Many crashes and exceptions may occur, and it is a real challenge to understand how software is behaving. Software is usually composed of various components. A component is a nearly independent part of software that full-fills a clear function. Process mining aims...
Measurements of event related potentials in EEG are contaminated by various sources of noise including artifacts and uncorrelated spontaneous brain activities. A major problem faced during the extraction of evoked potentials is the identification and elimination of bad segments of EEG data contaminated by such sources of noise. We present a new method which automatically identifies and eliminates...
Operational processes leave trails in the information systems supporting them. Such event data are the starting point for process mining — an emerging scientific discipline relating modeled and observed behavior. Whereas an event log describes example behavior of the underlying process, a process model aims to describe an abstraction of the same process. Models may be descriptive or normative. Descriptive...
The growing interest in process mining is fueled by the increasing availability of event data. Process mining techniques use event logs to automatically discover process models, check conformance, identify bottlenecks and deviations, suggest improvements, and predict processing times. Lion's share of process mining research has been devoted to analysis techniques. However, the proper handling of problems...
Operational processes leave trails in the information systems supporting them. Such event data are the starting point for process mining - an emerging scientific discipline relating modeled and observed behavior. The relevance of process mining is increasing as more and more event data become available. The increasing volume of such data (“Big Data”) provides both opportunities and challenges for...
Data-mining over software can reveal similar patterns on software code. This can give important insights for the design of hardware cores, especially considering the benefits of the merge of software kernels and their implementation as a single hardware core. However, software codes have characteristics that make inadequate the direct use of typical data mining tools, mainly related to their large...
Defect detection and classification is crucial in ensuring product quality and reliability. Classification provides information on problems related to the detected defects which can then be used to perform yield prediction, fault diagnosis, correcting manufacturing issues and process control. Accurate classification requires good selection of features to help distinguish between different cluster...
Reduction in integrated circuit (IC) half technology, which will no longer be sustainable by traditional fault isolation and failure analysis techniques. There is an urgent need for diagnostic software tools with (which manifest as clusters) observed from manufacturing defects can be traced back to a specific process, equipment or technology, a novel data mining algorithm defects from test data logs...
In this paper we present an approach to solve the problem of diagnosability of bounded Petri net systems. In particular, we first give necessary and sufficient conditions for diagnosability. Then, we present a method to test diagnosability that is based on the analysis of two graphs that depend on the structure of the net, including the faults model, and the initial marking. The first graph is called...
In this paper, we prove that a discrete-time switched linear system is exponentially stabilizable if and only if there exists a stationary hybrid-control law that consists of a homogeneous switching-control law and a piecewise-linear continuous-control law under which the closed-loop system has a piecewise quadratic Lyapunov function. Such a converse control-Lyapunov function theorem justifies many...
In this paper we consider the property of diagnosability for labeled unbounded Petri nets, namely Petri nets where the number of tokens in one or more places can grow indefinitely. We give necessary and sufficient conditions for diagnosability and we present a test to study diagnosability based on the analysis of the coverability graph of a particular net, called verifier net, that is built starting...
In this paper we study fault diagnosis of systems modeled by untimed continuous Petri nets. In particular, we generalize our previous works in this framework where we solved this problem only for special classes of continuous Petri nets, namely state machines and backward conflict free nets. We show that the price to pay for this generalization is that only three diagnosis states can be defined, rather...
As computer systems continue to improve, they also often become larger and more complicated. This may create barriers for individuals with cognitive and learning disabilities, who may find these systems more difficult to use. In this paper, an approach incorporating recent research into interface accessibility for assistive technology is taken to improve the usability of an e-Learning system. By developing...
Image processing plays an important role in computer science, making complex image manipulation more feasible. It can be used either in a general manner or in specific domains such as for medical purposes. With the availability of the internet, image processing applications can be distributed to be available for different people, regardless of their geographical location. Although there are a handful...
A nonlinear binary code with a single carrier M-QAM linear modulation is designed to control certain transitions in the symbol constellation. This concept is employed to develop spectral shaping modulation codes with M-QAM linear modulations so as to reduce out-of-band power. The code is realized as a nonlinear binary convolutional code, and the coded modulation is represented as a Markov chain. The...
Research has provided evidence that type usage in source files is correlated with the risk of failure of software components. Previous studies that investigated the correlation between type usage and component failure assigned equal blame to all the types imported by a component with a failure history, regardless of whether a type is used in the component, or associated to its failures. A failure-prone...
Short term traffic speed and volume prediction is an important component of well developed Intelligent Transportation Systems and Advanced Traveler Information Systems. In this paper, we examine the use of polled Remote Traffic Microwave Sensors as a data source for aggregate traffic predictors. Clock skew and data loss due to network transience pose significant challenges to integrating polled data...
Choosing the optimal terms to represent a search engine query is not trivial, and may involve an iterative process such as relevance feedback, repeated unaided attempts by the user or the automatic suggestion of additional terms, which the user may select or reject. This is particularly true of a multimedia search engine which searches on concepts as well as user-input terms, since the user is unlikely...
Analysis of keystroke dynamics can be useful in protecting personal data because an individual is authenticated not only by password, but also by that individual's keystroke patterns. In this way, intrusion becomes more difficult because the username/password pair, as well as the typing speed and correct keystroke pattern must both be duplicated. The purpose of this paper is to present a keystroke...
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