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A New Approach to DNA, RNA, and Protein Motifs Templates Visualization and Analysis via Compilation Technique

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 motif structure to parse the motifs, detect, debug the errors, and analyze the motifs template to its components. Many experiments are accomplished using motifs templates of various sizes arranged from 10 Kbase to 10 Mbase, various numbers of gaps arranged from 15 gaps to 15000 gaps, and different numbers of errors arranged from 100 errors to 1820 errors. The proposed systems, in all these experiments, exhibited linear behavior in parsing phase and visualization phase that indicates its scalability to motifs template sizes.

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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
Identify and Diagnose the Causes of Financial Funding using the Root Cause Analysis Technique

The analysis of the root cause techniques is a reasonable option to be made to assess the root causes of the funding of construction projects. There are a variety of issues related to financing in construction industries in Iraq. The root,cause analysis is the impact of security and social conditions on financial funding. Variety tools of root cause analysis have originated from literature, as common methods for the detection of root causes. The purpose of this study was to identify and diagnose causes that lead to obstruction of financial funding in the construction projects in the republic of Iraq from the contractors' point of view and their interaction with a number of variables. The study diagnosed nine causes of fi

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Publication Date
Thu Mar 29 2018
Journal Name
Construction Research Congress 2018
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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
New and Existing Approaches Reviewing of Big Data Analysis with Hadoop Tools

Everybody is connected with social media like (Facebook, Twitter, LinkedIn, Instagram…etc.) that generate a large quantity of data and which traditional applications are inadequate to process. Social media are regarded as an important platform for sharing information, opinion, and knowledge of many subscribers. These basic media attribute Big data also to many issues, such as data collection, storage, moving, updating, reviewing, posting, scanning, visualization, Data protection, etc. To deal with all these problems, this is a need for an adequate system that not just prepares the details, but also provides meaningful analysis to take advantage of the difficult situations, relevant to business, proper decision, Health, social media, sc

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Machine Learning Approach for New COVID-19 Cases Using Recurrent Neural Networks and Long-Short Term Memory

     This research aims to predict new COVID-19 cases in Bandung, Indonesia. The system implemented two types of deep learning methods to predict this. They were the recurrent neural networks (RNN) and long-short-term memory (LSTM) algorithms. The data used in this study were the numbers of confirmed COVID-19 cases in Bandung from March 2020 to December 2020. Pre-processing of the data was carried out, namely data splitting and scaling, to get optimal results. During model training, the hyperparameter tuning stage was carried out on the sequence length and the number of layers. The results showed that RNN gave a better performance. The test used the RMSE, MAE, and R2 evaluation methods, with the best numbers being  0.66975075, 0.470

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Publication Date
Sun Oct 01 2006
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Non Enhanced Helical Ct Scan In Visualization Of Normal Appendix

Purpose: To evaluate the frequency of visualization, thickness, and anatomical features of the normal appendix at nonenhanced helical computed tomography (CT).
Materials and methods : Two radiologists prospectively iterpreted, in consensus, the abdominal CT scans of 140 patients who were examined for renal colic assessment. They
were blinded to patients' surgical history regarding a previous appendectomy. No contrast material was used. The frequency of visualization, and the two – wall thickness of normal
appendix were recorded, as well as the anatomical features of the appendix and the effect of adequasy of intraperitoneal fat on identification of the appendix.
Results : The prevalence of appendectomy w

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Publication Date
Sun Mar 04 2018
Journal Name
Baghdad Science Journal
Using Texture Analysis Image Processing Technique to Study the Effect of Microwave Plasma on the Living Tissue

The present study is a hybrid method of studying the effect of plasma on the living tissue by using the image processing technique. This research explains the effect of microwave plasma on the DNA cell using the comet score application, texture analysis image processing and the effect of microwave plasma on the liver using texture analysis image processing. The study was applied on the mice cells. The exposure to the plasma is done by dividing the mice for four groups, each group includes four mice (control group, 20, 50, 90 second exposure to microwave plasma). The exposure to microwave plasma was done with voltage 175v and gas flow on 2 with room temperature; the statistical features are obtained from the comet score images and the textur

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Publication Date
Mon Sep 07 2020
Journal Name
Environmental Science And Pollution Research
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Publication Date
Mon Sep 18 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Protein bound fucos, protein bound hexose and total calcium in sera of patient with thyroid dysfunction and control

Protein bound fucose (PBF), protein  bound hexose (PBHex), and total calcium {T.Ca) were 'determined in sera of (40) hy-p.ertnyroidism , (40)  hypothyroidism patients and (40) controL The resultsr vealed  a significant decrease in the kwel of PBF,  PBHex and T.Ca in sera of patients with .hyperthyroidism  compared  to control; Inc se Qf PBF. there nQ difference in its level betwe.en patients with hypothyroidism and  control  group.  While there  is a significant increment in  PBHex leveli:n both hyper and hypothyroidism With respect to that of control Result  indicates, that total calcium levels were i.n  the nomml range for all p tients groups. Patient  compa

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Publication Date
Sat Oct 01 2022
Journal Name
The Egyptian Journal Of Hospital Medicine
Metallothionein Protein Concentration in The Liver Tissue of Albino Mice Exposed to Cadmium and Zinc Chloride

Background Cadmium (Cd), one of the most abundant heavy metals, is extremely toxic to both humans and animals. hIt is well known that zinc (Zn) administration reduces Cd-induced toxicity and that metallothioneins can have a protective effect in biological systems to mitigate Cd toxicity. Objective The aim of the current study to determine if Zn administration affected the induction of MT-1 and MT-2 in the liver tissue in mice exposed to Cd. Materials and methods Metallothionein protein (MT) level in the tissue of male mice were detected using the anion -exchang high-performance liquid chromatography coupled (HPLC)assay and immunohistochemical staining. Results Single treatment to zinc or cadmium increase the level of MT in the liver, but zi

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Publication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

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