Process mining methods allow analysts to use logs of historical executions of business processes in order to gain knowledge about the actual behavior of these processes. One of the most widely studied process mining o...
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Process mining methods allow analysts to use logs of historical executions of business processes in order to gain knowledge about the actual behavior of these processes. One of the most widely studied process mining operations is automated process discovery. An event log is taken as input by an automated process discovery method and produces a business process model as output that captures the control-flow relations between tasks that are described by the event log. In this setting, this paper provides a systematic comparative evaluation of existing implementations of automated process discovery methods with domain experts by using a real life event log extracted from an international software engineering company and four quality metrics: understandability, correctness, precision, and usefulness. The evaluation results highlight gaps and unexplored trade-offs in the field and allow researchers to improve the lacks in the automated process discovery methods in terms of usability of process discovery techniques in industry.
Process modeling is one of the most significant tasks software process improvement teams perform. Conventionally modeling is performed by teams composed of domain experts and process engineers and it takes considerabl...
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Process modeling is one of the most significant tasks software process improvement teams perform. Conventionally modeling is performed by teams composed of domain experts and process engineers and it takes considerable effort and time. In recent years there have been studies which use the data extracted from the actual events that took place to determine process models. In this paper we present the results of a case study we conducted to determine the effectiveness of four process discovery and process mining algorithms. After applying process discovery algorithms we compare the results by the actual process and process definitions. We discuss the discrepancies between the actual flow and the process definitions, and the weaknesses and strong aspects of the algorithms.
software clustering is a method for increasing software system understanding and maintenance. software designers, first use MDG graph to model the structure of software system. In MDG, system modules (e.g. files ,clas...
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software clustering is a method for increasing software system understanding and maintenance. software designers, first use MDG graph to model the structure of software system. In MDG, system modules (e.g. files ,classes) are represented as nodes and their relationships (e.g. function calls , inheritance relationships) as directed edges that connect the nodes. Once the MDG created, clustering algorithms are applied and create a partitioned MDG. Graph partitioning is a NP-Complete problem, So many algorithms for solving it has been reported in the literatures. In this paper two approximate algorithms have been proposed. The first algorithm is based on object migration learning automata and the second algorithm is a hybrid evolutionary algorithm obtained from combining object migration learning automata and genetic algorithm. The second algorithm by using learning automata and genetic algorithm accelerates the searching process and also prevents the algorithm from getting stuck in local optimal. Another positive point of the proposed algorithm is high stability. The proposed algorithms have been compared with some of the existing algorithms. Results show that the second algorithm has superiority over the existing methods.
This paper describes a software platform used for the testing of PMU algorithms. The platform is implemented in MATLAB and consists of two parts. The first one permits the insertion of the simulation parameters while ...
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ISBN:
(纸本)9781467304399
This paper describes a software platform used for the testing of PMU algorithms. The platform is implemented in MATLAB and consists of two parts. The first one permits the insertion of the simulation parameters while the second is the actual simulator for the algorithms. The second program contains a waveform generator including modulation and filtering. It also permits the comparison between the results of the PMU algorithm against those of an “ideal PMU”. The platform has been tested for its functionality and is used as a shared tool to quantify the uncertainties of the estimation algorithms developed in the framework of the EMRP project “Smart Grids”.
This work covers the experimental verification of 2 space-time (ST) algorithms on the smart antenna software radio test system (SASRATS) platform . This work also covers the concept and architecture of SASRATS, which ...
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This work covers the experimental verification of 2 space-time (ST) algorithms on the smart antenna software radio test system (SASRATS) platform . This work also covers the concept and architecture of SASRATS, which was designed and developed to facilitate the field testing of ST processing architectures and algorithms. The paper covers the experimental verification of two robust ST algorithms developed by the authors for signal enumeration and channel order estimation. Simulation results are also presented and compared with the experimental results obtained on the SASRATS platform.
The motion estimation (ME) is the most time consuming and power demanding module in a video encoder. In this paper, we provide the first detailed instruction-level simulation results on motion estimation. Firstly, we ...
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The motion estimation (ME) is the most time consuming and power demanding module in a video encoder. In this paper, we provide the first detailed instruction-level simulation results on motion estimation. Firstly, we analyze various aspects of the selected seven typical motion estimation algorithms, such as search speed, instruction frequencies, branch behavior, and power distribution. Then, we propose suitable compiler techniques, hardware techniques and optimal instruction set architecture to speed up and reduce the power consumption of the motion estimation. SimpleScalar and SimplePower are used to simulate the effects of the optimizations on the motion estimation algorithms. Experimental results show that the execution time spent on motion vector search for one frame are averagely reduced by 39% and the power consumption is reduced by 62% by applying these techniques
Quite recently the polynomial design methods found a new great field of application outside the control area: the algebraic approach has been used successfully in signal processing and mobile communications. In contra...
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Quite recently the polynomial design methods found a new great field of application outside the control area: the algebraic approach has been used successfully in signal processing and mobile communications. In contrast to the control systems synthesis, polynomials and polynomial matrices with complex coefficients are often required when designing filters, equalizers, decouplers and other components of mobile phones for instance. Polynomial Toolbox for Matlab admits complex polynomials in most computations, including Diophantine equations and spectral factorizations. As a result, the toolbox appears a suitable tool for rapid prototyping whenever polynomial design routines with complex coefficients are required. The objective of this report is twofold. First, we explain in a clear and popular manner how the complex coefficients arise in technical practice. Based on this motivation, we present important numerical algorithms for complex polynomials and polynomial matrices and their implementation in the Polynomial Toolbox for Matlab. Finally, the power of the Toolbox is illustrated by selected numerical examples involving complex coefficients.
In this paper, we extend the classical result by Huang, Kintala, Kolettis and Fulton (1995), and in addition propose a modified stochastic model to determine the software rejuvenation schedule. More precisely, the sof...
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In this paper, we extend the classical result by Huang, Kintala, Kolettis and Fulton (1995), and in addition propose a modified stochastic model to determine the software rejuvenation schedule. More precisely, the software rejuvenation models are formulated via the semi-Markov processes, and the optimal software rejuvenation schedules which maximize the system availabilities are derived analytically for respective cases. Further, we develop nonparametric statistical algorithms to estimate the optimal software rejuvenation schedules, provided that the statistical complete (unsensored) sample data of failure times is given. In numerical examples, we examine asymptotic properties for the statistical estimation algorithms.
In order to explore optimization effects of RETC software and intelligent algorithms, including genetic algorithm, simulated annealing algorithm and particle swarm optimization, on parameters of Van Genuchten (VG)Equa...
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In order to explore optimization effects of RETC software and intelligent algorithms, including genetic algorithm, simulated annealing algorithm and particle swarm optimization, on parameters of Van Genuchten (VG)Equation for the soil water characteristic curve of urban green space, the soil drying curve of green space was obtained by using the tensiometer method in this study, where RETC software, genetic algorithm, simulated annealing algorithm and particle swarm optimization we reconstructed to solve parameters of VG Equation. The results indicated that the parameter fitting results of VG Equation determined by RETC software and three intelligent algorithms were very close to experimental results with a very high simulation accuracy (R 2 = 0.996) in given conditions, moreover, the fitting effect of intelligent algorithms was better than that of RECT software.
Given article describes algorithms to isolation of malicious software logical and physical objects of the system. As example logical object are used files. As example physical object are used sectors of the hard disk.
Given article describes algorithms to isolation of malicious software logical and physical objects of the system. As example logical object are used files. As example physical object are used sectors of the hard disk.
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