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New Approach of Generating Ground-Truth for Local Surveillance Dataset Tested with Benchmark Background Subtraction Models
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     Background subtraction is the dominant approach in the domain of moving object detection. Lots of research has been done to design or improve background subtraction models. However, there are a few well-known and state-of-the-art models that can be applied as a benchmark. Generally, these models are applied to different dataset benchmarks. Most of the time, choosing an appropriate dataset is challenging due to the lack of dataset availability and the tedious process of creating ground-truth frames for the sake of quantitative evaluation. Therefore, in this article, we collected local video scenes of a street and river taken by a stationary camera, focusing on dynamic background challenges. We presented a new technique for creating ground-truth frames using modeling, composing, tracking, and rendering each frame. Eventually, we applied three promising algorithms used in this domain: GMM, KNN, and ViBe, to our local dataset. Results obtained by quantitative evaluations revealed the effectiveness of our new technique for generating the ground-truth scenes to be benchmarked with the original scenes using a number of statistical metrics.

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Publication Date
Mon Feb 21 2022
Journal Name
Applied Sciences
The Behavior of Hybrid Fiber-Reinforced Concrete Elements: A New Stress-Strain Model Using an Evolutionary Approach
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Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti

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Publication Date
Thu Jan 01 2015
Journal Name
Mj Journal On Applied Mathematics
Mathematical models for estimation the concentration of heavy metals in soil
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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Performance Analysis of different Machine Learning Models for Intrusion Detection Systems
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

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Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Science
Evaluation of the Surveillance and Epidemiological Aspects of Cutaneous Leishmaniasis in Babylon Province, Iraq
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Leishmaniasis diseases constitute an important public health problem in both tropical and subtropical areas. The aim of this study is to evaluate the epidemiological situation of cutaneous leishmaniasis (CL) in Babylon province, Iraq. The current work included the recording of 142 new cases of CL infection in Babylon province for the period from November 2019 to February 2020. Male infection was represented by 87 cases (61.27%), while females composed 55 samples (38.73%), with a significant difference (p<0.05) between the two groups. The age group of 5-14 years was found to have the highest recorded CL cases  (56; 39.44%), while the age group of less than one year had the lowest  cases  (1; 0.70%), with the differences

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Application of 2D Electrical Resistivity Method and Ground Penetration Rader for Detection of the Archaeological Remains in Kish Site, Babylon, Iraq
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     The 2D electrical resistivity imaging (ERI) is a non-destructive method with good efficiency to detect shallow subsurface features. The archeological subsurface features were investigated with this method in most cases with the assistance of other methods such as GPR method. Eleven 2D ERI profiles were carried out to investigate the subsurface archeological features in the Kish site in the Babylon area. The 2D electrical resistivity survey was achieved with ABEM Terrameter-LS2 Device and 30 electrodes with 1-meter spacing between the adjacent electrodes along each profile. The length of the profile is 29 meters and the spacing between the adjacent profiles is 3 meters. The software RES2DINV was used to obtain the final inverted

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Publication Date
Sun Feb 28 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Intelligent System for Parasitized Malaria Infection Detection Using Local Descriptors
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Malaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based f

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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The Use of Particle Swarm Algorithm to Solve Queuing Models with Practical Application
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This paper includes the application of Queuing theory with of Particle swarm algorithm or is called (Intelligence swarm) to solve the problem of The queues and developed for General commission for taxes /branch Karkh center in the service stage of the Department of calculators composed of six  employees , and it was chosen queuing model is a single-service channel  M / M / 1 according to the nature of the circuit work mentioned above and it will be divided according to the letters system for each employee, and  it was composed of data collection times (arrival time , service time, departure time)

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Publication Date
Sat Apr 01 2017
Journal Name
Iosr Journal Of Computer Engineering (iosr-jce)
A New Approach to DNA, RNA, and Protein Motifs Templates Visualization and Analysis via Compilation Technique
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Motifs template is the input for many bioinformatics systems such codons finding, transcription, transaction, sequential pattern miner, and bioinformatics databases analysis. The size of motifs arranged from one base up to several Mega bases, therefore, the typing errors increase according to the size of motifs. In addition, when the structures motifs are submitted to bioinformatics systems, the specifications of motifs components are required, i.e. the simple motifs, gaps, and the lower bound and upper bound of each gap. The motifs can be of DNA, RNA, or Protein. In this research, a motif parser and visualization module is designed depending on a proposed a context free grammar, CFG, and colors human recognition system. GFC describes the m

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Publication Date
Mon Apr 17 2023
Journal Name
Wireless Communications And Mobile Computing
A Double Clustering Approach for Color Image Segmentation
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One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first

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Publication Date
Mon Dec 31 2018
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Laminectomy versus interlaminar approach for Lumbar disc herniation
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Background: Low back pain is the most common health problem in men and women between the ages of 20 and 50 years. The lumbar disc prolapse has a major role in this condition. Treatment is either conservative or surgical. The most common surgical interventions are either laminectomy or interlaminar approach.

Objective: To determine which is the best surgical approach for the patient according to his/her type of disc herniation.

Patients and methods: A comparative clinical study conducted in the Neurosciences Hospital, Baghdad, Iraq from January 2016 to January 2018. In this paper we evaluated the clinical outcome following both approaches

Results:

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