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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
Thu Jan 01 2015
Journal Name
Journal Of Madenat Alelem College
Antimicrobial effect of Trigonella foenum graecum Seed Extracts against Tested Bacteria Isolated from Meat and Fish
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A qualitative chemical test was performed on functional groups extracted from fenugreek plant and its extracts (aqueous, alcoholic and volatile oil). Results revealed that fenugreek seeds contain the main functional groups, while extracts are varied accorodihg to their content of functional groups qualitatively and quantitively. Moreover, inhibition activity was tested for extracts of fenugreek seeds (aqueous, alcoholic and volatile oil). against gram negative (Salmonella typhimurium, Escherichia coli and Pseudomonas aeruginosa) and gram positive (Staphylococcus aureus) by the ager well diffusion method. Data have revealed that inhibition activity was different in accoradance with extract solvent and the tested microorgan. Oil extract (15)%

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Probabilistic Inventory Models With Pareto Distribution
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Inventory or inventories are stocks of goods being held for future use or sale. The demand for a product in is the number of units that will need to be removed from inventory for use or sale during a specific period. If the demand for future periods can be predicted with considerable precision, it will be reasonable to use an inventory rule that assumes that all predictions will always be completely accurate. This is the case where we say that demand is deterministic.

The timing of an order can be periodic (placing an order every days) or perpetual (placing an order whenever the inventory declines to units).

in this research we discuss how to  formulating inv

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Virulence surveillance of wheat black stem rust fungus
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General survey for wheat rust diseases in Iraqi fields was done during the seasons of 2010, 2011 and 2012. The survey covered different fields in southern, middle and northern regions. Results of the first season indicated that most of Iraqi cultivars such as Tmmoze2, IPA 99 and Mexipak showed different types of susceptibility to both yellow and leaf rust infection. Disease severity increased when the conditions were favorable for infections with using susceptible cultivars. The severity of leaf rust was less in the north region comparing with the middle and south regions. Most of the introduced cultivars such as Sham6 and Cimmyto showed susceptible reaction to yellow and leaf rust. Yellow rust was in epiphytotic form at the Iraqi-Syrian-Tu

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Publication Date
Fri Jan 01 2016
Journal Name
Statistics And Its Interface
Search for risk haplotype segments with GWAS data by use of finite mixture models
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The region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Hybrid CNN-SMOTE-BGMM Deep Learning Framework for Network Intrusion Detection using Unbalanced Dataset
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This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward

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Publication Date
Sun May 17 2020
Journal Name
Iraqi Journal Of Science
Dynamics and optimal Harvesting strategy for biological models with Beverton –Holt growth
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In this work, the dynamic behavior of discrete models is analyzed with Beverton- Holt function growth . All equilibria are found . The existence and local stability are investigated of all its equilibria.. The optimal harvest strategy is done for the system by using Pontryagin’s maximum principle to solve the optimality problem. Finally numerical simulations are used to solve the optimality problem and to enhance the results of mathematical analysis

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition
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A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Evaluating the phenomenological approach models in predicting the Neutron Induced Deuteron Emission Spectra from Different reactions
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A neutron induced deuteron emission spectra and double differential cross-sections (DDX), in 27Al (n, D) 26Mg, 51V (n, D)50Ti , 54Fe ( n, D)53Mn and 63Cu (n, D) 62Ni reactions, have been investigated using the phenomenological approach model of Kalbach. The pre-equilibrium stage of the compound nucleus formation is considered the main pivot in the discription of cross-section, while the equilibrium (pick up or knock out ) process is analyzed in the framework of the statistical theory of cluster reactions, Feshbach, Kerman, and Koonin (FKK) model. To constrain the applicable parameterization as much as possible and to assess the predictive power of these models, the calculated results have been compared with the experimental data and othe

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Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
Generating dynamic S-BOX based on Particle Swarm Optimization and Chaos Theory for AES
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Data security is a significant requirement in our time. As a result of the rapid development of unsecured computer networks, the personal data should be protected from unauthorized persons and as a result of exposure AES algorithm is subjected to theoretical attacks such as linear attacks, differential attacks, and practical attacks such as brute force attack these types of attacks are mainly directed at the S-BOX and since the S-BOX table in the algorithm is static and no dynamic so this is a major weakness for the S-BOX table, the algorithm should be improved to be impervious to future dialects that attempt to analyse and break the algorithm  in order to remove these weakness points, Will be generated dynamic substitution box (S-B

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