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International Conference on Machine Learning and Applications (ICMLA)

作者： Tijana Markovic Vladan Devedzic Fang Zhou Zoran Obradovic School of Innovation Design and Engineering Malardalen University Vasteras Sweden Faculty of Organizational Sciences University of Belgrade Belgrade Serbia School of Data Science and Engineering East China Normal University Shanghai China Center for Data Analytics and Biomedical Informatics Temple University Philadelphia USA

The Gaussian Conditional Random Fields (GCRF) algorithm and its extensions are used for machine learning regression problems in which the attributes of objects and the correlation between objects should be considered when making predictions. These algorithms can be applied in different domains where problems can be seen as graphs, but their implementation requires complex calculations and good programming skills. This paper presents an open source software package that includes a tool with graphical user interface (GCRFs tool) and Java library (GCRFs library). GCRFs tool is software that integrates various GCRF-based algorithms and supports training and testing of those algorithms on real-world datasets. The main goal of GCRFs tool is to provide a straightforward and user-friendly graphical user interface that will simplify the use of GCRF-based algorithms. GCRFs Java library contains basic classes for GCRF concepts and can be used by researchers who have experience in Java programming. Also, this paper presents the results of a pilot usability evaluation of the GCRFs tool, where the software was evaluated with expert and non-expert users. This evaluation gave us detailed insight into the experiences and opinions of the users and helped us outline priorities for future development.

关键词： Training Java Machine learning algorithms software packages software algorithms Programming Prediction algorithms

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algorithms and LAPACK-based software for subspace identification

Algorithms and LAPACK-based software for subspace identifica...

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IEEE International Symposium on Computer Aided Control System Design (CACSD)

作者： V. Sima Research Institute for Informatics Bucharest Romania

Basic algorithms and LAPACK-based Fortran software for multivariable system identification by subspace techniques are briefly described. Deterministic and combined deterministic-stochastic identification problems are dealt with using two approaches. A state space model is computed from input-output data sequences. Multiple data sequences collected by possibly independent identification experiments can be handled. Sequential processing of large data sets is provided as an option. Illustrative numerical examples are included.

关键词： software algorithms State-space methods Mathematical model MATLAB Least squares approximation Linear algebra Singular value decomposition Parallel processing Informatics MIMO

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Two New algorithms for software Watermarking by Register Allocation and their Empirical Evaluation

Two New Algorithms for Software Watermarking by Register All...

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International Conference on Information Technology: New Generations (ITNG)

作者： Hakun Lee Keiichi Kaneko Graduate School of Engineering Tokyo University of Agriculture슠and슠Technology Koganei Tokyo Japan

ISBN: (纸本)9781424437702

QP and QPS algorithms embed a message into a program by adding extra edges to an interference graph that represents dependency among the variables in the program. QP algorithm has a drawback that the embedded watermarks are not always extractable from the watermarked programs. Though QPS algorithm can avoid extraction failure by introducing extra constraints on edge addition, the lengths of the embeddable messages are extremely shortened. In this paper we propose CC (color change) and CP (color permutation) algorithms. The proposing algorithms provide more capacity for embeddable information than the fore-mentioned two algorithms while they also offer assurance of extraction of embedded messages. CC and CP algorithms only change the colors of nodes in an interference graph without changing its structure. CC algorithm is effective when the number of the nodes in the interference graph is large enough where as CP algorithm is effective when the number of the colors needed for interference graph coloring is large enough.

关键词： software algorithms Watermarking Quadratic programming Registers Data mining Embedded software Interference constraints Humans Computer crime Information technology

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Improving software Reuse Prediction Using Feature Selection algorithms

Improving Software Reuse Prediction Using Feature Selection ...

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International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)

作者： Mariam Amin Mustafa Hammad University of Bahrain Sakheer Bahrain

ISBN: (数字)9781728196732

ISBN: (纸本)9781728196749

software engineering is witnessing a market struggle in delivering functional products due to time constraints. software developers are reusing already existing components instead of developing the whole software from scratch. Predicting successful reuse can help before any reuse attempt. In this paper, feature selection was utilized to extract the most relevant attributes from a public dataset. Results showed that feature selection improved software reuse experience prediction.

关键词： software Feature extraction Prediction algorithms software reusability Organizations software algorithms Training

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software solution for optimal planning of sales persons work based on Depth-First Search and Breadth-First Search algorithms

Software solution for optimal planning of sales persons work...

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Proceedings of the International Convention MIPRO

作者： E. Žunić A. Djedović B. Žunić Info studo Ltd Sarajevo Bosnia and Herzegovina Goethe-Institut Sarajevo Bosnia and Herzegovina

This paper presents and describes the practical usage of Depth-First Search and Breadth-First Search algorithms in the planning and optimization of sales persons work. Experiments for optimal implementation of these two algorithms for planning purposes are made through a specially developed MATLAB simulator. The application consists of two parts: Web application and Mobile application. Web application is developed using the Application Development Framework Technology (ADF), while for the development of the mobile version of application, Oracle ADF Mobile is used. Both applications are interactive with Google Maps, and based on the selected input parameters (such as the origin and destination of sales persons, the way of planning, any possible obstacles, etc.) they visually show the results, indicators and analysis. The commercial version of the software, eSalesmanPlan, which uses the aforementioned algorithms, is used in several companies in Bosnia and Herzegovina. All indicators point to significant savings both in human as well as financial resources and it will be also presented.

关键词： software algorithms Planning software Search problems Programming Data structures Robots

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A New Approach to software Effort Estimation Using Different Artificial Neural Network Architectures and Taguchi Orthogonal Arrays

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IEEE ACCESS 2021年 9卷 26926-26936页

作者： Rankovic, Nevena Rankovic, Dragica Ivanovic, Mirjana Lazic, Ljubomir Union Univ Sch Comp Belgrade 11000 Serbia Univ Novi Sad Fac Sci Novi Sad 21000 Serbia

In this article, two different architectures of Artificial Neural Networks (ANN) are proposed as an efficient tool for predicting and estimating software effort. Artificial Neural Networks, as a branch of machine learning, are used in estimation because they tend towards fast learning and giving better and more accurate results. The search/optimization embraced here is motivated by the Taguchi method based on Orthogonal Arrays (an extraordinary set of Latin Squares), which demonstrated to be an effective apparatus in a robust design. This article aims to minimize the magnitude relative error (MRE) in effort estimation by using Taguchi's Orthogonal Arrays, as well as to find the simplest possible architecture of an artificial Neural Network for optimized learning. A descending gradient (GA) criterion has also been introduced to know when to stop performing iterations. Given the importance of estimating software projects, our work aims to cover as many different values of actual efficiency of a wide range of projects as possible by division into clusters and a certain coding method, in addition to the mentioned tools. In this way, the risk of error estimation can be reduced, to increase the rate of completed software projects.

关键词： software Neural networks Estimation Computer architecture software algorithms Numerical models Convergence software effort estimation Taguchi method artificial neural networks design orthogonal array-based experiments clustering COCOMO81 COCOMO2000 NASA project dataset Kemerer dataset

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Automatic Convergence in WIPL-D software Using Python Scripting algorithms

Automatic Convergence in WIPL-D Software Using Python Script...

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Electrical, Electronic and Computing Engineering (IcETRAN), International Conference on

作者： Branislav Ninkovic Jasmin Music WIPL-D d.o.o. Belgrade Serbia

ISBN: (数字)9798350386998

ISBN: (纸本)9798350387001

Electromagnetic simulation software is indispensable in the daily work of RCS and antenna engineers. One of the crucial aspects that should be considered when using the results obtained by simulations is their accuracy. Accuracy is usually tested by automatic or manual convergence study. We observe WIPL-D software, a full 3D electromagnetic solver. This tool does not offer an automatic testing mechanism, thus we develop two such mechanisms using Python. WIPL-D released Python scripting library that we use to implement our algorithms. Two proposed algorithms are tested on a realistic scatterer project. Finally, we compared the efficiency of the two approaches.

关键词： Accuracy Three-dimensional displays software algorithms Scattering Manuals software Electromagnetics

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High-performance algorithms and software for systems and control computations

High-performance algorithms and software for systems and con...

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IEEE International Symposium on Computer Aided Control System Design (CACSD)

作者： V. Sima S. van Huffel Research Institute for Informatics Bucharest Romania ESAT Katholieke Universiteit Leuven Leuven Belgium

For large-scale problems, it is extremely important to achieve the best computational efficiency, by exploiting any special structure, and by using the potential of modern high-performance computer architectures. Therefore, developing robust, and efficient algorithms for control systems analysis and design is an objective of primary importance. Improved versions of some basic algorithms for computer-aided control systems design have been recently developed. These algorithms have been incorporated in the latest version of the Fortran 77 subroutine library SLICOT. This paper comments on some of these algorithmic improvements. Several functional capabilities of SLICOT Library routines are briefly mentioned. Performance results for some components of the library, in comparison with equivalent computations performed by some MATLAB functions, included in the MATLAB nucleus or in the MATLAB control toolbox, are presented.

关键词： software algorithms software systems Control systems Libraries MATLAB Large-scale systems Computational efficiency Computer architecture Robust control Control system analysis

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IntruDetector: a software platform for testing network intrusion detection algorithms

IntruDetector: a software platform for testing network intru...

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Annual Computer Security Applications Conference

作者： Tao Wan Xue Dong Yang Department of Computer Science University of Regina Regina SAS Canada

ISBN: (纸本)0769514057

An intrusion detection system (IDS), that monitors passively specific computing resources, and reports anomalous or intrusive activities, is becoming an important component in the security system of information infrastructure. algorithms for detecting intrusions are under rapid development, but far from being mature. One interesting and difficult issue is how to study and test a new intrusion detection algorithm against a variety of (perhaps simulated) intrusive activities under realistic background traffic. A flexible and general-purpose platform for testing intrusion detection algorithms is clearly desirable. This paper presents such a software platform, called IntruDetector. With this platform, detection algorithms can be tested directly in a real environment with a wide range of intrusive activities. The data of normal system activities are directly collected from the live environment, and are mixed with intrusive activities that are simulated by hybrid simulation. The main properties of this approach are: (1) the background traffic is realistic; (2) it allows flexible simulation of various types of intrusions; and (3) normal system operation will not be disrupted by virtually simulated destructive intrusions during testing.

关键词： software testing Intrusion detection software algorithms Algorithm design and analysis System testing Traffic control Face detection Detection algorithms Data security Performance analysis

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software for evaluating image reconstruction algorithms

Software for evaluating image reconstruction algorithms

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： J.A. Browne G.T. Herman Medical Image Processing Group Department of Radiology University of Pennsylvania Philadelphia PA USA

The proliferation of image reconstruction algorithms imposes a need for an efficient and objective evaluation procedure for comparing the efficacy of different algorithms for a particular medical task. In assessing the relative task-oriented performance of reconstruction algorithms, it is desirable to assign statistical significance to claims of superiority of one algorithm over another. However, very often the achievement of statistical significance demands a large number of observations. Performing such an evaluation on mathematical phantoms requires a means of running the competing algorithms on projection data obtained from a large number of randomly generated phantoms. Thereafter, various numerical measures of agreement between the reconstructed images and the original phantoms may be used to reach a conclusion which has some statistical substance. Here, the authors illustrate the software SuperSNARK which automates an evaluation methodology for assigning statistical significance to the observed differences in performance of two or more image reconstruction algorithms. In particular, the authors compare the relative efficacy of the maximum likelihood expectation maximization algorithm and the filtered backprojection method for performing three specific imaging tasks in positron emission tomography.< >

关键词： Image reconstruction software algorithms Reconstruction algorithms Humans Imaging phantoms Performance evaluation Positron emission tomography Biomedical image processing Radiology Biomedical imaging

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