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bsj-2405
Scale-Invariant Feature Transform Algorithm with Fast Approximate Nearest Neighbor
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There is a great deal of systems dealing with image processing that are being used and developed on a daily basis. Those systems need the deployment of some basic operations such as detecting the Regions of Interest and matching those regions, in addition to the description of their properties. Those operations play a significant role in decision making which is necessary for the next operations depending on the assigned task. In order to accomplish those tasks, various algorithms have been introduced throughout years. One of the most popular algorithms is the Scale Invariant Feature Transform (SIFT). The efficiency of this algorithm is its performance in the process of detection and property description, and that is due to the fact that it operates on a big number of key-points, the only drawback it has is that it is rather time consuming. In the suggested approach, the system deploys SIFT to perform its basic tasks of matching and description is focused on minimizing the number of key-points which is performed via applying Fast Approximate Nearest Neighbor algorithm, which will reduce the redundancy of matching leading to speeding up the process. The proposed application has been evaluated in terms of two criteria which are time and accuracy, and has accomplished a percentage of accuracy of up to 100%, in addition to speeding up the processes of matching and description.

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Interdisciplinary Mathematics
Analytical solutions for nonlinear differential equations via differential transform technique
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A relatively novel technique differential equations named Differential Transform Technique (DTM) is proposed. The evaluation of this approach is based on an iterative method in series form. Here, First give several basic definitions and properties of DTM, and applied various examples for the proposed method are tested to show the efficiency and accuracy to get the solutions of non-linear pantograph equation with elegantly computed components. In addition to solving the problems efficiently and rapidly, The advantage of the suggested approach is that it produces an analytical approach with fewer terms in a convergent series form.

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Publication Date
Sun Nov 01 2020
Journal Name
2020 2nd Annual International Conference On Information And Sciences (aicis)
An Enhanced Multi-Objective Evolutionary Algorithm with Decomposition for Signed Community Detection Problem
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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Variable Selection Using aModified Gibbs Sampler Algorithm with Application on Rock Strength Dataset
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Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm with Gene Ontology-Aware Crossover Operator for Protein Complex Detection
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     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

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Publication Date
Thu Jul 01 2010
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
NOTES ON SOME ARMORED SCALE INSECTS (HEMIPTERA:DIASPIDIDAE) OF IRAQ
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Sixteen species of Armored Scale insects were recorded from Baghdad city during 2001-2005. Three of these are reported here for the first time Abgrallaspis cyanophylli (Signoret, 1869), Aonidiella citrina (Craw,1870) and Chrysomphalus aonidium (Linnaeus,1758). The other thirteen species were recorded earlier Aonidiella aurantii (Maskell), Aonidiella orientalis (Newstead), Chrysomphalus dictyospermi (Morgan), Diaspidiotus ostreaeformis (Curtis), Diaspidiotu perniciosus (Comctock), Hemiberlesia lataniae (Signoret), Lepidosaphes beckii (Newman), Lepidosaphes conchiformis (Gmelin), Lepidosaphes ulmi (Linnaeus), Mercetaspis halli

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Bayes Analysis for the Scale Parameter of Gompertz Distribution
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In this paper, we investigate the behavior of the bayes estimators, for the scale parameter of the Gompertz distribution under two different loss functions such as, the squared error loss function, the exponential loss function (proposed), based different double prior distributions represented as erlang with inverse levy prior, erlang with non-informative prior, inverse levy with non-informative prior and erlang with chi-square prior.

The simulation method was fulfilled to obtain the results, including the estimated values and the mean square error (MSE) for the scale parameter of the Gompertz distribution, for different cases for the scale parameter of the Gompertz distr

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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Optimum Dimensions of Hydraulic Structures and Foundation Using Genetic Algorithm coupled with Artificial Neural Network
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      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

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Publication Date
Mon Feb 14 2022
Journal Name
Journal Of Educational And Psychological Researches
Developing and Applying the Unrealistic Optimism Scale among Junior High School Students
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The present study aims to develop and apply the unrealistic optimism scale among high school students. The researcher has designed a scale of (38) paragraphs to measure the unrealistic optimism. A sample of (200) male and female students were chosen randomly to collect the needed data. The study found that the unrealistic scale of optimism has good psychometric characteristics. The research sample has a high level of التفاؤل غير الواقعي لدى عينة البحث unrealistic optimism. There is a statistically significant difference between male and female in the unrealistic optimism in favor of the male students. Finally, there is a statistically significant difference between students in the fourth and sixth gra

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Publication Date
Tue Sep 01 2026
Journal Name
Modern Sport
Development and Psychometric Validation With Normative Levels of the Spotlight Effect Scale Among Students of Physical Education and Sport Sciences
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The Spotlight Effect, defined as individuals' tendency to overestimate the extent to which others notice and evaluate them, has important implications for psychological functioning, social interaction, and performance in educational and sport environments. Despite previous studies have addressed the Spotlight Effect theoretically and empirically, no validated instrument has been specifically developed to assess this construct especially among students of Colleges of Physical Education and Sport Sciences. This study aimed to develop and validate a Spotlight Effect Scale and establishing normative levels for its interpretation. The descriptive survey approach was used, involving 555 students from Colleges of Physical Education and Spo

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Publication Date
Thu Jan 01 2015
Journal Name
Iraqi Journal Of Science
Improved Rijndael Algorithm by Encryption S-Box Using NTRU Algorithm
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With the wide developments of computer applications and networks, the security of information has high attention in our common fields of life. The most important issues is how to control and prevent unauthorized access to secure information, therefore this paper presents a combination of two efficient encryption algorithms to satisfy the purpose of information security by adding a new level of encryption in Rijndael-AES algorithm. This paper presents a proposed Rijndael encryption and decryption process with NTRU algorithm, Rijndael algorithm is widely accepted due to its strong encryption, and complex processing as well as its resistance to brute force attack. The proposed modifications are implemented by encryption and decryption Rijndael

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