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Quantitative analysis of the economic characteristics of the land transport network
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Highway network could be considered as a function of the developmental level of the region, that it is representing the sensitive nerve of the economic activity and the corner stone for the implementation of development plans and developing the spatial structure. The main theme of this thesis is to show the characteristics of the regional highway network of Anbar and to determine the most important effective spatial characteristics and the dimension of that effect negatively or positively. Further this thesis tries to draw an imagination for the connection between highway network as a spatial phenomenon and the surrounded natural and human variables within the spatial structure of the region. This thesis aiming also to determine the nature of the regional highway of Anbar, how it has been developed, what are its characteristics, types, and patterns that have been came from the spatial differentiation in the region to evaluate it spatially and as an indicator for the socio-economic development in   the study area.                               

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Publication Date
Thu May 10 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Securing Data in Wireless Body Area Network Using Hyper-Chaotic Zhou System
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  E-Health care system is one of the great technology enhancements via using medical devices through sensors worn or implanted in the patient's body. Wireless Body Area Network (WBAN) offers astonishing help through wireless transmission of patient's data using agreed distance in which it keeps patient's status always controlled by regular transmitting of vital data indications to the receiver. Security and privacy is a major concern in terms of data sent from WBAN and biological sensors. Several algorithms have been proposed through many hypotheses in order to find optimum solutions. In this paper, an encrypting algorithm has been proposed via using hyper-chaotic Zhou system where it provides high security, privacy, efficiency and

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
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         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

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Publication Date
Mon Jan 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
ON-Line MRI Image Selection and Tumor Classification using Artificial Neural Network
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When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network
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Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

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Publication Date
Mon Feb 20 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Text Encryption Algorithm Based on Chaotic Neural Network and Random Key Generator
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This work presents a symmetric cryptography coupled with Chaotic NN , the encryption algorithm process the data as a blocks and it consists of multilevel( coding of character, generates array of keys (weights),coding of text and chaotic NN ) , also the decryption process consists of multilevel (generates array of keys (weights),chaotic NN, decoding of text and decoding of character).Chaotic neural network is used as a part of the proposed system with modifying on it ,the keys that are used in chaotic sequence are formed by proposed key generation algorithm .The proposed algorithm appears efficiency during the execution time where it can encryption and decryption long messages by short time and small memory (chaotic NN offer capacity of m

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Publication Date
Wed Mar 01 2017
Journal Name
2017 Annual Conference On New Trends In Information & Communications Technology Applications (ntict)
Automatic Iraqi license plate recognition system using back propagation neural network (BPNN)
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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
EFFECT OF SPRAYING ORGANIC EMULSION (APPETIZER) AND NANO NPK WITH UREA ON SOME GROWTH CHARACTERISTICS OF THREE SYNTHETIC CULTIVARS OF MAIZE: EFFECT OF SPRAYING ORGANIC EMULSION (APPETIZER) AND NANO NPK WITH UREA ON SOME GROWTH CHARACTERISTICS OF THREE SYNTHETIC CULTIVARS OF MAIZE
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A field experiment was carried out at the research station of the College of Agriculture - Wasit University / Kut, during the fall season 2021 in soil with texture (sandy mixture) using the RCBD design in the arrangement of splintered plates and with three replications, to study the effect of spraying different combinations of organic emulsion (Appetizer) and NPK nano fertilizer with urea fertilizer on the growth of synthetic cultivars of yellow corn. The main panels included three synthetic varieties of yellow corn (Fajr1, Sumer and Baghdad3), which symbolized by (V1,V2,V3) in sequence, while the secondary panels included five fertilization treatments in which mineral fertilizer (urea) was used 46% nitrogen with the full recomme

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Publication Date
Mon Jun 30 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Dental caries and salivary physiochemical characteristics among osteoporotic old adult women
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Background: Osteoporosis is a systemic skeletal disorder affects general health in addition to effect on salivary physical and chemical composition which lead to an adverse effect on oral health status. This study was conducted to evaluate the concentration of glycoprotein (osteonectin) in saliva and its effect on dental caries in relation to salivary flow rate and viscosity among osteoporotic women and compared to control group. Materials and Methods: The total sample composed of 60 females aged 60-65 years attending Al-Yarmook Teaching Hospital, 30 females diagnosed with osteoporosis by measuring bone density at the spine and femur with a dual-energy X-ray absorptiometry at T-score of >2.5, and 30 women without osteoporosis with T-score o

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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Physics
Fatigue and Tensile Characteristics for Composite Materials Used in Prosthetic Socket
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In this research, the use of natural materials like wool and cannabis as intermediate reinforcement for prosthetic limbs due to their comfort, affordability, and local availability was discussed. As part of this study on below-the-knee (BK) prosthetic sockets, two sets of samples were made using a vacuum method. These sets were made of natural fiber-reinforced polymer composites with lamination 80:20: group (Y) had 4 perlon, 1 wool 4 perlon, and group (G) had 4 perlon, 1 cannabis 4 perlon. The two groups were compared with a socket made of polypropylene. Tensile testing was used to determine the mechanical characteristics of the socket materials. The Y group has a yield stress of 17 MPs, an ultimate strength of 18.75 MPa, and an elastic

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