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jeasiq-1776
Estimating the reliability function of Kumaraswamy distribution data
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The aim of this study is to estimate the parameters and reliability function for kumaraswamy distribution of this two positive parameter  (a,b > 0), which is a continuous probability that has many characterstics with the beta distribution with extra advantages.

The shape of the function for this distribution and the most important characterstics are explained and estimated the two parameter (a,b) and the reliability function for this distribution by using the maximum likelihood method (MLE) and Bayes methods. simulation experiments are conducts to explain the behaviour of the estimation methods for different sizes depending on the mean squared error criterion the results show that the Bayes is better than the ML.

 

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Publication Date
Fri Apr 01 2016
Journal Name
Gis Research Uk 24th Annual Conference
Comparing Open Source Map Data in Areas Lacking Authoritative Mapping
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One wide-ranging category of open source data is that referring to geospatial information web sites. Despite the advantages of such open source data, including ease of access and cost free data, there is a potential issue of its quality. This article tests the horizontal positional accuracy and possible integration of four web-derived geospatial datasets: OpenStreetMap (OSM), Google Map, Google Earth and Wikimapia. The evaluation was achieved by combining the tested information with reference field survey data for fifty road intersections in Baghdad, Iraq. The results indicate that the free geospatial data can be used to enhance authoritative maps especially small scale maps.

Publication Date
Thu Nov 01 2012
Journal Name
2012 International Conference On Advanced Computer Science Applications And Technologies (acsat)
Data Missing Solution Using Rough Set theory and Swarm Intelligence
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This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
ESTIMATED NON-PARAMETRIC AND SEMI-PARAMETRIC MODEL FOR LONGITUDINAL DATA
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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Improved Firefly Algorithm with Variable Neighborhood Search for Data Clustering
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Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

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Publication Date
Fri Nov 01 2019
Journal Name
2019 1st International Informatics And Software Engineering Conference (ubmyk)
Radial Basis Function (RBF) Based on Multistage Autoencoders for Intrusion Detection system (IDS)
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In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete

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Publication Date
Fri May 01 2020
Journal Name
Systematic Reviews In Pharmacy
Methotrexate effect on obestatin, progranulin and kidney function in RA Iraqi males patients
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Methotrxate (MTX) has become the standard of care and first-line therapy for patients who have RA and consider as a gold standard of treatment for RA. The role of MTX in the treatment of RA has now been well established. The use of MTX treatment of RA inhibits proliferation of the lymphocytes, reduces signs and symptoms this disease, reduces progression damage of the joints and improves quality of life outcome. Progranulin (PGRN) acts a role in autoimmune inflammatory, has important function in several processes including immune response. Present study has conducted to find the effect of MTX drugs as a therapeutic target for RA patients because of its ability to bind with tumor necrosis factor receptor (TNFR), with progranulin, obestatin an

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Publication Date
Mon Apr 09 2018
Journal Name
Al-khwarizmi Engineering Journal
Creating Through Points in Linear Function with Parabolic Blends Path by Optimization Method
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The linear segment with parabolic blend (LSPB) trajectory deviates from the specified waypoints. It is restricted to that the acceleration must be sufficiently high. In this work, it is proposed to engage modified LSPB trajectory with particle swarm optimization (PSO) so as to create through points on the trajectory. The assumption of normal LSPB method that parabolic part is centered in time around waypoints is replaced by proposed coefficients for calculating the time duration of the linear part. These coefficients are functions of velocities between through points. The velocities are obtained by PSO so as to force the LSPB trajectory passing exactly through the specified path points. Also, relations for velocity correction and exact v

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Publication Date
Tue Aug 06 2013
Journal Name
Robotica
Function approximation technique-based adaptive virtual decomposition control for a serial-chain manipulator
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SUMMARY<p>The virtual decomposition control (VDC) is an efficient tool suitable to deal with the full-dynamics-based control problem of complex robots. However, the regressor-based adaptive control used by VDC to control every subsystem and to estimate the unknown parameters demands specific knowledge about the system physics. Therefore, in this paper, we focus on reorganizing the equation of the VDC for a serial chain manipulator using the adaptive function approximation technique (FAT) without needing specific system physics. The dynamic matrices of the dynamic equation of every subsystem (e.g. link and joint) are approximated by orthogonal functions due to the minimum approximation errors produced. The contr</p> ... Show More
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Publication Date
Mon Mar 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
تقدير معلمتي التوزيع الاسي العام باستخدام اسلوب المحاكاة
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The main aim of this paper is to study how the different estimators of the two unknown parameters (shape and scale parameter) of a generalized exponential distribution behave for different sample sizes and for different parameter values. In particular, 

. Maximum Likelihood, Percentile and Ordinary Least Square estimators had been implemented for different sample sizes (small, medium, and large) and assumed several contrasts initial values for the two parameters. Two indicators of performance Mean Square Error and Mean Percentile Error were used and the comparisons were carried out between different methods of estimation  by using monte carlo simulation techniq

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Estimation of parameters of two-dimensional sinusoidal signal model by employing Deferential Evaluation algorithm and the use of Sequential approach in estimation
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Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model  in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling  the Symmetric gray scale texture image and estimating by using

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