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bsj-1094
Design and Implementation for optical fiber communication system using frequency shift coding
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In this research, optical communication coding systems are designed and constructed by utilizing Frequency Shift Code (FSC) technique. Calculations of the system quality represented by signal to noise ratio (S/N), Bit Error Rate (BER),and Power budget are done. In FSC system, the data of Nonreturn- to–zero (NRZ ) with bit rate at 190 kb/s was entered into FSC encoder circuit in transmitter unit. This data modulates the laser source HFCT-5205 with wavelength at 1310 nm by Intensity Modulation (IM) method, then this data is transferred through Single Mode (SM) optical fiber. The recovery of the NRZ is achieved using decoder circuit in receiver unit. The calculations of BER and S/N for FSC system at maximum fiber length at 61.2 km equal to 2.30551×10-12, 47.88526 dB respectively. The power budget for FSC system was calculated to be 29 dB. Results show that the BER increases when the received optical power decreases the due to increase of the optical fiber length61.2 km. while S/N decreases. The optical power budget increases as the transmitted optical power increases.

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Publication Date
Sun Mar 01 2009
Journal Name
Al-khwarizmi Engineering Journal
The Optimum Conditions for Production of Soya Peptone by Acidic Hydrolysis of Soya Proteins
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     This study was carried out to obtain the optimum conditions necessary for the process of soya protein hydrolysis by using hydrochloric acid (as a chemical catalyst) instead of the papain enzyme (as a biological catalyst), for the production of soya peptone. These conditions are implemented to test the effect of the variables of the process of hydrolysis on the nature and quality of the product.

        The production of soya peptone was studied for their importance in the process of preparing and producing the culture media used in medical and microbiological laboratories.

      The process of production of soya peptone includes four main

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Publication Date
Thu Dec 31 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Analyzing the reality of the Iraqi market for securities in light of financial globalization
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The Iraqi market for securities in light of financial globalization faces real challenges at the local and international levels, which were reflected in their shadows on the overall economic reality, which imposed the necessity of making fundamental changes in terms of form and content, and from here stems the research problem in the ability of the Iraqi stock market to adapt to the transformations Financial imposed by financial globalization in light of the weakness of the economic structure and its position in the global economy. The research starts from the hypothesis that the Iraqi market for securities in light of financial globalization has an important and significant role in the economic field, through its role in stimula

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Publication Date
Wed Feb 16 2022
Journal Name
Iraqi Journal Of Science
Studying the Suitability of Roads for Transporting Wind Turbines to Proposed Wind Farm Location
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The aim of most researchers is to complete full projects for establishing renewable sources stations. The project depend on many variables, which is called criteria, that’s makes the project workable or not. The criterion which studied in this paper is roads suitability for transporting turbines from the loading ports to construction site. One of the important factors which must provide paved roads for transportation and within standard. Southern Um-Qasr port is the best choice to receive wind turbine equipments. The nods down to the construction region will face 0 turns, 2 bridges that crosses over and 23 bridges that passes underneath.

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Publication Date
Sun Sep 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Fuzzy Analytical Hierarchy Process for Embedded Risk Reduction in Selecting the Right Planning Decision
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The aim of this work is to provide an efficient selection technique as a part of planning process to guide the decision makers to decide the preferences of one supplier over another for purchasing lab instruments in education domain. Fuzzy Analytical Hierarchy Process has used as a multi-criteria decision process, as an industrial engineering tool with certain emphasis on the qualitative aspects required to the decision makers. While the concept of degree of possibility for each criterion is used to reach its relative weights, a specific methodology created to reach the final objective decision of supplier selection. A questionnaire form was developed and distributed to five universities located in Baghdad province with a total

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Publication Date
Tue Sep 29 2020
Journal Name
Iraqi Journal Of Science
Smart Doctor: Performance of Supervised ART-I Artificial Neural Network for Breast Cancer Diagnoses
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Wisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.

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Publication Date
Thu May 04 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Approximate Solution for Two Machine Flow Shop Scheduling Problem to Minimize the Total Earliness
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This paper proposes a new algorithm (F2SE) and algorithm (Alg(n – 1)) for solving the
two-machine flow shop problem with the objective of minimizing total earliness. This
complexity result leads us to use an enumeration solution approach for the algorithm (F2SE)
and (DM) is more effective than algorithm Alg( n – 1) to obtain approximate solution.

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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparative Study for the Early Detection of the most Important Factors Leading to Preeclampsia
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The aim of this research is to determine the most important and main factors that lead to Preeclampsia. It is also about finding suitable solutions to eradicate these factors and avoid them in order to prevent getting Preeclampsia. To achieve this, a case study sample of (40) patients from Medical City - Oncology Teaching Hospital was used to collect data by a questionnaire which contained (17) reasons to be investigated. The statistical package (SPSS) was used to compare the results of the data analysis through two methods (Radial Bases Function Network) and (Factorial Analysis). Important results were obtained, the two methods determined the same factors that could represent the direct reason which causes Preecla

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Adopting statistical methods for controlling the quality of drinking water to achieve customer satisfaction
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The current research aims to adopt production quality decisions as the most important decisions , because they are accompanied by customer satisfaction through monitoring the quality of drinking water in iraq which reach through the pipeline network associated with water treatment projects of Tigris and Euphrates rivers. One of the indicators of quality control was the drawing of the C-chart by specifying the central line and the upper and lower limit of the control and the diagnosis of whether the production system as a whole within the scope of quality control or not and determine the strength and significance of the correlation between the quantities of water And actual needs for customers , the research has reached a number o

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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Publication Date
Tue Aug 01 2023
Journal Name
Journal Of Ecological Engineering
Assessment of the Pressure Driven Membrane for the Potential Removal of Aniline from Wastewater
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