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joe-1822
Evaluating Roads Network Connectivity for Two Municipalities in Baghdad-Iraq
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The road network serves as a hub for opportunities in production and consumption, resource extraction, and social cohabitation. In turn, this promotes a higher standard of living and the expansion of cities. This research explores the road network's spatial connectedness and its effects on travel and urban form in the Al-Kadhimiya and Al-Adhamiya municipalities. Satellite images and paper maps have been employed to extract information on the existing road network, including their kinds, conditions, density, and lengths. The spatial structure of the road network was then generated using the ArcGIS software environment. The road pattern connectivity was evaluated using graph theory indices. The study demands the abstraction and examination of the topological structure by choosing a few factors associated with the connection of the roads. These involved the cyclomatic number, Eta coefficient, Aggregate Transform Score (ATS), Beta, gamma, and Alpha indices. According to the findings, the Al-Adhamiya roads network is more developed, better linked, and has a higher overall connectivity value than the Al-Kadhimiya network. The two study areas, however, have minimal circuitry and high complexity. Due to the modifications and expansion of land use that the municipalities have seen, the research suggests that the transportation network should be developed to reach greater interconnectedness, particularly in locations outside the city center.

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Publication Date
Tue Jun 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Investigation of Ozone Microbubbles for the Degradation of Methylene Orange Contaminated Wastewater
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   In the present study, semi – batch experiments were conducted to investigate the efficiency of ozone microbubbles (OMBs) in the treatment of aqueous dye solutions methylene orange under different reaction conditions such as  effect of initial solution pH , ozone generation rate and initial MO-concentration. The results showed that the removal of MO by OMBs were very high at the acidic and alkaline media and upon increasing the generation rate of ozone from 0.498 to 0.83 mg/s, the removal efficiency dramatically increased from 75to 100% within 15 min. The rate of oxidation reaction followed a pseudo first- order kinetic model. The results demonstrated that OMBs is efficient in terms of the decline of methylene orange c

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Publication Date
Mon Apr 01 2024
Journal Name
Al-kindy College Medical Journal
Radiological Modalities for the Assessment of Fetal Growth Restriction: A Comprehensive Review
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Fetal growth restriction is a significant contributor to fetal morbidity and mortality. In addition, there are heightened maternal risks associated with surgical operations and their accompanying dangers. Monitoring fetal development is a crucial objective of prenatal care and effective methods for early diagnosis of Fetal growth restriction, allowing prompt management and timely intervention to improve the outcomes. Screening for Fetal growth restriction can be achieved via many modalities; it can be medical, biochemical, or radiological. Some recommended combining more than one for better outcomes. Currently, there is inconsistency about the best method of Fetal growth restriction screening.   In this review, a comprehensive

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Publication Date
Wed Feb 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Diagnose COVID-19 by using hybrid CNN-RNN for Chest X-ray
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<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

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Publication Date
Fri Jul 05 2024
Journal Name
Journal Of Applied Spectroscopy
Spectrophotometric Method Using the Derivative for the Determination of the Drug Losartan
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Publication Date
Sun Mar 30 2025
Journal Name
Studia Universitatis BabeČ™-bolyai Chemia
GREEN SPECTROPHOTOMETRIC METHOD FOR CONCURRENT ESTIMATION OF PIROXICAM AND MEFENAMIC ACID MIXTURE
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Publication Date
Mon Aug 01 2022
Journal Name
Inorganic Chemistry Communications
Study the application of new type green corrosion inhibitors for iron metal
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Density functional theory (DFT) calculations were used to evaluate the capability of Glutamine (Gln) and its derivative chemicals as inhibitors for the anti-corrosive behavior of iron. The current work is devoted to scrutinizing reactivity descriptors (both local and global) of Gln, two states of neutral and protonated. Also, the change of Gln upon the incorporation into dipeptides was investigated. Since the number of reaction centers has increased, an enhancement in dipeptides’ inhibitory effect was observed. Thus, the adsorption of small-scale peptides and glutamine amino acids on Fe surfaces (1 1 1) was performed, and characteristics such as adsorption energies and the configuration with the highest stability and lowest energy were ca

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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Sun Oct 25 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
EFFECT OF EXERCISES USING DIFFERENT RESISTORS IN THE DEVELOPMENT OF THE SPECIAL STRENGTH OF THE ARMS AND THE COMPLETION OF JAVELIN FOR THE ATHLETES OF THE SCHOOL SPECIALIZED ATHLETICS
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Athletics are different from other games as a competition between individuals to show their competence and physical ability to achieve new record numbers in the various activities and various between the boards, jumping and throwing and each type of these activities in particular performance so found the researcher to find the method of training resistors in the development of special power and achievement In the effectiveness of javelin, where the researchers chose the sample of the athletes from the specialized school of athletics to effectively throw the spear at the ages of 15-17 years and carried out the tests of the research, which includes the strength of the speed of the arms and explosive power and The various resistance exercise

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Publication Date
Tue Oct 01 2019
Journal Name
International Journal Of Research In Social Sciences And Humanities
IMPACT OF LEADERSHIP CHARACTERISTICS IN CRISIS MANAGEMENT STRATEGY FOR THE MEMBERS OF THE IRAQI NATIONAL PARALYMPIC COMMITTEE FROM THE POINT OF VIEW OF THE MEMBERS OF THE CENTRAL UNIONS
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Welcome to International Journal of Research in Social Sciences & Humanities (IJRSSH). It is an international refereed journal of Social Sciences, Humanities & Linguistics in English published quarterly, both print and online.

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Publication Date
Wed Aug 27 2025
Journal Name
Baghdad Science Journal
A Clustering Technique Based on the Hard K-Means (H.KM.) Method to Determine the Governorate That Have More Influence for Spreading COVID-19 in the Kingdom of Saudi Arabia
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