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A Tri-Gene Ontology Migration Operator for Improving the Performance of Meta-heuristics in Complex Detection Problems
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      Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulated under four expressions depending on the type of gene sub-ontology. To demonstrate the performance of the proposed evolutionary based complex detection algorithm, the Saccharomyces Cerevisiae (yeast) PPI network is used in the evaluation. The results reveal that the proposed algorithm achieves more accurate complex structures than the counterpart heuristic algorithms and the canonical evolutionary algorithm based on the topological-aware mutation operator.

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Molecular Identification of Methylorubrum extorquens using PCR-Amplified MxaF Gene Fragments as A Molecular Marker
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  Methylotrophs bacteria are ubiquitous, and they have the ability to consume single carbon (C1) which makes them biological conversion machines. It is the first study to find facultative methylotrophic bacteria in contaminated soils in Iraq. Conventional PCR was employed to amplify MxaF that encodes methanol dehydrogenase enzyme. DNA templates were extracted from bacteria isolated from five contaminated sites in Basra. The gene specific PCR detected Methylorubrum extorquens as the most dominant species in these environments. The ability of M. extorquens to degrade aliphatic hydrocarbons compound was tested at the laboratory. Within 7 days, gas chromatographic (GC) studies of remaining utilize

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Mathematical Modelling of Gene Regulatory Networks
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    This research includes the use of an artificial intelligence algorithm, which is one of the algorithms of biological systems which is the algorithm of genetic regulatory networks (GRNs), which is a dynamic system for a group of variables representing space within time. To construct this biological system, we use (ODEs) and to analyze the stationarity of the model we use Euler's method. And through the factors that affect the process of gene expression in terms of inhibition and activation of the transcription process on DNA, we will use TF transcription factors. The current research aims to use the latest methods of the artificial intelligence algorithm. To apply Gene Regulation Networks (GRNs), we used a progr

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Publication Date
Sun Jan 01 2017
Journal Name
Iec2017 Proceedings Book
Improving TF-IDF with Singular Value Decomposition (SVD) for Feature Extraction on Twitter
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Publication Date
Mon Oct 28 2019
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
Heuristic Initialization And Similarity Integration Based Model for Improving Extractive Multi-Document Summarization
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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 Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
HRA and its Impact on Employees Performance: A Field Research in the Ministry of Education
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          The research aims to determine the impact of Human Resources Accounting (HRA) on employee’s performance. The research’s problem was embodied in the lack of interest in HRA, which was reflected on the performance of employees in the Ministry of Education; the research adopted the descriptive-analytical approach, and the research community included the directors of departments and people at the headquarters of the Ministry of Education. The sample size was (224) individuals from the total community of 533. The questionnaire was adopted as the main tool for collecting data and information, as well as the interviews that were conducted by the researcher. In order to analyze t

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Publication Date
Sat Dec 01 2018
Journal Name
Political Sciences Journal
American strategic performance towards Middle East in the era of president Trump - A future study
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Abstract The strategic performance of the United States depends on dealing with the Middle East countries and its variants on several bases and motives that enabled them to achieve American hegemony and invest its interests at the expense of the region countries. Within this performance, the administration of the United State President Donald Trump presented the Strategic Document on December 18, 2017, which focused on the principle of "America First", to determine the direction of future US strategic performance in the formulation of means of cooperation and intersections or hostility in addition to interests and threats.The future vision of the Arab region and the Middle East as a whole, this strategy is based on the fact that

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Publication Date
Fri Apr 05 2024
Journal Name
Techhub Journal
The effect of suggested exercises on improving the kinesthetic response of soccer goalkeepers
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Publication Date
Fri Apr 05 2024
Journal Name
Techhub Journal
The effect of suggested exercises on improving the kinesthetic response of soccer goalkeepers
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The introduction to the research included a presentation of some physical characteristics and their importance in sports, including the speed of kinesthetic response response and the extent of its usefulness and importance, especially for soccer goalkeepers, as it is the most important element that goalkeepers must have, and it is also the main key to the excellence and development of all physical and kinesthetic response qualities and skills of a goalkeeper. Football. The speed of kinesthetic response response and reaction is one of the requirements of the game of football, as well as all other sports and even in general professional life. Its importance is highlighted for the football goalkeeper, so he must master it perfectly to perform

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Publication Date
Mon Mar 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
A study to determine the most important factors affecting student performance In the secondary school in Diwaniya
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Student performance may influence by several factors in all his study levels such as primary school, intermediate school and even in his college; some of these factors are psychological factors, social factors, and the factors which correlate with student environment.

In this paper we study some of these factors to discover their influence by using canonical correlation analysis to analyze the data. Many conclusions are discovered to help who focuses student performance or to make it pest in future.

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