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Enhancement of LBP-based face identification system by adopting preprocessing techniques
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Face Identification system is an active research area in these years. However, the accuracy and its dependency in real life systems are still questionable. Earlier research in face identification systems demonstrated that LBP based face recognition systems are preferred than others and give adequate accuracy. It is robust against illumination changes and considered as a high-speed algorithm. Performance metrics for such systems are calculated from time delay and accuracy. This paper introduces an improved face recognition system that is build using C++ programming language with the help of OpenCV library. Accuracy can be increased if a filter or combinations of filters are applied to the images. The accuracy increases from 95.5% (without applying any filter) to 98.5% when applying a combination of Bilateral filter, Histogram Equalization and Tan and Triggs Algorithm. Finally, the results show degradation in accuracy and increasing in recognition time if images database get bigger.

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Publication Date
Sun Jul 01 2012
Journal Name
Journal Of Endodontics
Synthesis and Preliminary Evaluation of a Polyolefin-based Core for Carrier-based Root Canal Obturation
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Introduction: Carrier-based gutta-percha is an effective method of root canal obturation creating a 3-dimensional filling; however, retrieval of the plastic carrier is relatively difficult, particularly with smaller sizes. The purpose of this study was to develop composite carriers consisting of polyethylene (PE), hydroxyapatite (HA), and strontium oxide (SrO) for carrier-based root canal obturation. Methods: Composite fibers of HA, PE, and SrO were fabricated in the shape of a carrier for delivering gutta-percha (GP) using a melt-extrusion process. The fibers were characterized using infrared spectroscopy and the thermal properties determined using differential scanning calorimetry. The elastic modulus and tensile strength tests were dete

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Publication Date
Tue Dec 15 2020
Journal Name
Al-academy
Synthetic Sculpture Techniques in Outputs of Students of the Department of Art Education: أشراق علي خلف العزاوي
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The research studies the synthetic sculpture techniques in the outputs of the students of the department of art education in terms of the shape, texture, content and technique, and employing this style by the students of the department of art education on the college of fine arts, university of Diyala. The research consists of four chapters: the first chapter: the research problem summarized by looking for the synthetic sculpture and its importance in the treatment the industrial wastes in our social life, according to modern synthetic techniques, in the American and European sculpture. This technique has been employed in more than one contemporary artistic direction and style.
This study is considered important for the students of t

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Publication Date
Mon Nov 01 2021
Journal Name
Proceedings Of First International Conference On Mathematical Modeling And Computational Science: Icmmcs 2020
Study the Stability for Ordinary Differential Equations Using New Techniques via Numerical Methods
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Nonlinear differential equation stability is a very important feature of applied mathematics, as it has a wide variety of applications in both practical and physical life problems. The major object of the manuscript is to discuss and apply several techniques using modify the Krasovskii's method and the modify variable gradient method which are used to check the stability for some kinds of linear or nonlinear differential equations. Lyapunov function is constructed using the variable gradient method and Krasovskii’s method to estimate the stability of nonlinear systems. If the function of Lyapunov is positive, it implies that the nonlinear system is asymptotically stable. For the nonlinear systems, stability is still difficult even though

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Publication Date
Mon Feb 19 2018
Journal Name
Al-academy
Directing Techniques to Process the Radio Drama Script ( Khata'a Play as a Sample)
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     The radio drama is considered to be one of the arts that is discovered after a long period of theater's discovery. Initially , it was the broad framework of the theater's work when radio was broadcasting the shows on the huge theaters. This beginning encouraged many of the radio specialists to correlate plays with radio and make a novice and distinctive type of art. Thus, radio drama made its first step including the following   ( plays, short and long series drama as well as other types of radio arts). Because of the above mentioned , the researcher is stimulating  to study directing techniques to process the radio drama script ( Khata'a play as a sample).

The first chapter deals with the

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Publication Date
Sun Jan 01 2017
Journal Name
Research Journal Of Pharmacy And Technology
Estimating the plain and negative tendonography techniques for evaluating injured tendon in rabbit
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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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Scopus (14)
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Publication Date
Thu Mar 02 2023
Journal Name
Applied Sciences
Machine Learning Techniques to Detect a DDoS Attack in SDN: A Systematic Review
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The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Determination of Doxycycline Hyclate by Batch and Reverse Flow Injection Analysis Based on the Oxidative Coupling Reaction with 3-Methyl-2-benzothiazolinone Hydrazone hydrochloride (MBTH)
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New, simple and sensitive batch and reverse FIA spectrophotometric methods for the determination of doxycycline hyclate in pure form and in pharmaceutical preparations were proposed. These methods based on oxidative coupling reaction between doxycycline hyclate and 3-methylbenzothiazolinone-2-hydrazone hydrochloride (MBTH) in the presence ammonium ceric sulfate in acidic medium, to form green water-soluble dye that is stable and has a maximum absorbance at 626 nm. A calibration graph shows that a Beer's law is obeyed over the concentration range of 1-80 and 0.5-110 ?g.mL-1 of DCH for the batch and rFIA respectively with detection limit of 0.325 ?g.mL-1 of DCH for r-FIA methods. All different chemicals and physical experimental paramete

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Publication Date
Thu Dec 01 2011
Journal Name
International Review Of Physics (e-journal) (irephy)
Red shift band enhancement of the nanostructure ZnO100-xAlx thin films as a function of Al concentration for optoelectronic applications
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Publication Date
Fri Oct 01 2021
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
The Use of Logistic Regression Model in Estimating the Probability of Being Affected By Breast Cancer Based On the Levels of Interleukins and Cancer Marker CA15-3
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Breast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased o

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