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3-D Object Recognition using Multi-Wavelet and Neural Network
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This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as compared with matching by minimum distance, gave (94%) and (83%) score by using group (1), (gp) and features respectively, which is much better than the minimum distance. Recognition using (gp) neural network (NN) gave a (94%) and (72%) score by using group (2), (gp) and features respectively, while the minimum distance gave (11%) and (33%) scores. Time consumption through the recognition process using (NN) with (gp) is less than that minimum distance.

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Publication Date
Mon Aug 19 2024
Journal Name
Journal Of Metastable And Nanocrystalline Materials
The Structural, Magnetic, and Electrochemical Properties of Composite PAni/Co<sub>0.2</sub>Mn<sub>0.8</sub>Fe<sub>2</sub>O<sub>4</sub>
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The current work concerns preparing cobalt manganese ferrite (Co0.2Mn0.8Fe2O4) and decorating it with polyaniline (PAni) for supercapacitor applications. The X-ray diffraction findings (XRD) manifested a broad peak of PAni and a cubic structure of cobalt manganese ferrite with crystal sizes between 21 nm. The pictures were taken with a field emission scanning electron microscope (FE-SEM), which evidenced that the PAni has nanofibers (NFs) structures, grain size 33 – 55 nm, according to the method of preparation, where the hydrothermal method was used. The magnetic measurements (VSM) that were conducted at room temperature showed that the samples had definite magnetic properties. Additionally, it was noted that the saturation magnetizatio

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Science
Automatic Number Extraction from Fixed Imaging Distance
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     Developed countries are facing many challenges to convert large areas of existing services to electronic modes, reflecting the current nature of workflow and the equipment utilized for achieving such services. For instance, electricity bill collection still tend to be based on traditional approaches (paper-based and relying on human interaction) making them comparatively time-consuming and prone to human error.

This research aims to recognize numbers in mechanical electricity meters and convert them to digital figures utilizing Optical Character Recognition (OCR) in Matlab. The research utilized the location of red region in color electricity meters image to determine the crop region that contain the meters numbers, then

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Image Compression Techniques on-Board Small Satellites
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      Raw satellite images are considered high in resolution, especially multispectral images captured by remote sensing satellites. Hence, choosing the suitable compression technique for such images should be carefully considered, especially on-board small satellites, due to the limited resources. This paper presents an overview and classification of the major and state-of-the-art compression techniques utilized in most space missions launched during the last few decades, such as the Discrete Cosine Transform (DCT) and the Discrete Wavelet Transform (DWT)-based compression techniques. The pros and cons of the onboard compression methods are presented, giving their specifications and showing the differences among them to provide uni

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Examining sensitivity of financial performance at construction projects prequalification stage
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Construction projects are complicated in nature and require many considerations in contractor selection. One of the complicated interactions is that between performance with the project size, and contractor financial status, and size of projects contracted. At the prequalification stage, the financial ‎requirements restrict the ‎contractors to meet minimum limits in financial criteria such as net worth, working capital and ‎annual turnover, etc. In construction projects, however, there are cases when contractors meet these requirements but show low performance in practice. The model used in the study predicts the performance by training of a neural network. The data used in the study are 72 of the most recent roadw

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Publication Date
Sun Apr 01 2018
Journal Name
Construction And Building Materials
Linear viscous approach to predict rut depth in asphalt mixtures
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Rutting in asphalt mixtures is a very common type of distress. It occurs due to the heavy load applied and slow movement of traffic. Rutting needs to be predicted to avoid major deformation to the pavement. A simple linear viscous method is used in this paper to predict the rutting in asphalt mixtures by using a multi-layer linear computer programme (BISAR). The material properties were derived from the Repeated Load Axial Test (RLAT) and represented by a strain-dependent axial viscosity. The axial viscosity was used in an incremental multi-layer linear viscous analysis to calculate the deformation rate during each increment, and therefore the overall development of rutting. The method has been applied for six mixtures and at different tem

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Publication Date
Mon May 14 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Comparison Between Different Approaches to Overcome the Multicollinearity Problem in Linear Regression Models
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    In the presence of multi-collinearity problem, the parameter estimation method based on the ordinary least squares procedure is unsatisfactory. In 1970, Hoerl and Kennard insert analternative method labeled as estimator of ridge regression.

In such estimator, ridge parameter plays an important role in estimation. Various methods were proposed by many statisticians to select the biasing constant (ridge parameter). Another popular method that is used to deal with the multi-collinearity problem is the principal component method. In this paper,we employ the simulation technique to compare the performance of principal component estimator with some types of ordinary ridge regression estimators based on the value of t

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Crossref
Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Journal Of Science
Intelligent Agent Services in Electronic Libraries
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Global services with an agent or a multi-agent system are a promising and new research area. However, several measures have been proposed to demonstrate the benefits of agent technology by supporting distributed services and applying smart agent technology in web dynamics. This paper is designed to build a Semantic Web on the World Wide Web (WWW) to enhance the productivity of managing electronic library applications, which poses a problem to researchers and students, represnted by the process of exchanging books from e-libraries, where the process is slow or the library needs large system data.

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Scopus Crossref
Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
An Integrated Information Gain with A Black Hole Algorithm for Feature Selection: A Case Study of E-mail Spam Filtering
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     The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,

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Publication Date
Wed Nov 29 2023
Journal Name
International Journal Of Advances In Scientific Research And Engineering (ijasre), Issn:2454-8006, Doi: 10.31695/ijasre
Yolo Versions Architecture: Review
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Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
استعمال انحدار الاسقاطات المتلاحقة و الشبكات العصبية في تجاوز مشكلة البعدية
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المستخلص يهدف هذا البحث الى تجاوز مشكلة البعدية من خلال طرائق الانحدار اللامعلمي والتي تعمل على تقليل جذر متوسط الخطأ التربيعي (RMSE) , أذ تم  استعمال طريقة انحدار الاسقاطات المتلاحقة  (PPR)    ,والتي تعتبر احدى طرائق اختزال الابعاد التي تعمل على تجاوز مشكلة البعدية (curse of dimensionality) , وان طريقة (PPR) من التقنيات الاحصائية التي تهتم بأيجاد الاسقاطات الاكثر أهمية في البيانات المتعددة الابعاد , ومع ايجاد كل اسقاط

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