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ALL-FABNET: Acute Lymphocytic Leukemia Segmentation Using a Flipping Attention Block Decoder-Encoder Network
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Melanoma, a highly malignant form of skin cancer, affects individuals of all genders and is associated with high mortality rates, especially in advanced stages. The use of tele-dermatology has emerged as a proficient diagnostic approach for skin lesions and is particularly beneficial in rural areas with limited access to dermatologists. However, accurately, and efficiently segmenting melanoma remains a challenging task due to the significant diversity observed in the morphology, pigmentation, and dimensions of cutaneous nevi. To address this challenge, we propose a novel approach called DenseUNet-169 with a dilated convolution encoder-decoder for automatic segmentation of RGB dermascopic images. By incorporating dilated convolution, our model improves the receptive field of the kernels without increasing the number of parameters. Additionally, we used a method called Copy and Concatenation Attention Block (CCAB) for robust feature computation. To evaluate the performance of our proposed framework, we utilized the International Skin Imaging Collaboration (ISIC) 2017 dataset. The experimental results demonstrate the reliability and effectiveness of our suggested approach compared to existing methodologies. Our framework achieved a high level of accuracy (98.38%), precision (96.07%), recall (94.32%), dice score (95.07%), and Jaccard score (90.45%), outperforming current techniques.

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Publication Date
Sun Aug 01 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Cascade-Forward Neural Network for Volterra Integral Equation Solution
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The method of solving volterra integral equation by using numerical solution is a simple operation but to require many memory space to compute and save the operation. The importance of this equation appeares new direction to solve the equation by using new methods to avoid obstacles. One of these methods employ neural network for obtaining the solution.

This paper presents a proposed method by using cascade-forward neural network to simulate volterra integral equations solutions. This method depends on training cascade-forward neural network by inputs which represent the mean of volterra integral equations solutions, the target of cascade-forward neural network is to get the desired output of this network. Cascade-forward neural

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Publication Date
Mon Apr 01 2013
Journal Name
International Journal Of Electrical, Electronics And Telecommunication Engineering
Performance Analysis of xPON Network for Different Queuing Models
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Passive optical network (PON) is a point to multipoint, bidirectional, high rate optical network for data communication. Different standards of PONs are being implemented, first of all PON was ATM PON (APON) which evolved in Broadband PON (BPON). The two major types are Ethernet PON (EPON) and Gigabit passive optical network (GPON). PON with these different standards is called xPON. To have an efficient performance for the last two standards of PON, some important issues will considered. In our work we will integrate a network with different queuing models such M/M/1 and M/M/m model. After analyzing IPACT as a DBA scheme for this integrated network, we modulate cycle time, traffic load, throughput, utilization and overall delay

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Generative Adversarial Network for Imitation Learning from Single Demonstration
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Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

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Publication Date
Fri Jun 01 2007
Journal Name
Al-khwarizmi Engineering Journal
Reduction of the error in the hardware neural network
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Specialized hardware implementations of Artificial Neural Networks (ANNs) can offer faster execution than general-purpose microprocessors by taking advantage of reusable modules, parallel processes and specialized computational components. Modern high-density Field Programmable Gate Arrays (FPGAs) offer the required flexibility and fast design-to-implementation time with the possibility of exploiting highly parallel computations like those required by ANNs in hardware. The bounded width of the data in FPGA ANNs will add an additional error to the result of the output. This paper derives the equations of the additional error value that generate from bounded width of the data and proposed a method to reduce the effect of the error to give

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Classification of Rural Road Network in Al-Najaf Governorate
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This study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the f

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Publication Date
Wed Dec 25 2024
Journal Name
Journal Of Baghdad College Of Dentistry
Estimation of some salivary variables and oral health status of patients with chronic myeloid leukemia aged 45-55 years
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Background: Chronic myeloid leukemia is a cancer of the white blood cells characterized by the increased and unregulated growth of predominantly myeloid cells in the bone marrow. This study aimed to determine the effect of chronic myeloid leukemia on Dental caries and Oral health status including Gingivitis, Loss of attachment, Plaque index and Calculus index as well as evaluation of salivary flow rate and salivary interleukins-6 and tumor necrosis factor-?. Material and methods: Study group consisted of (75) subjects, (25) were newly diagnosed with chronic myeloid leukemia, (25) were taking medications (Glevic), and (25) were control subjects, all ag

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Compared of estimating two methods for nonparametric function to cluster data for the white blood cells to leukemia patients
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Abstract:                                        

   We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.

    In this research, I estimate the reliability function of cluster function by using the seemingly unrelate

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Publication Date
Sun Mar 01 2020
Journal Name
Sustainable Chemistry And Pharmacy
A sustainable approach to utilize olive pips for the sorption of lead ions: Numerical modeling with aid of artificial neural network
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Publication Date
Tue Apr 30 2024
Journal Name
International Review Of Electrical Engineering (iree)
Enhancing Efficiency in Distribution Power Networks by Power Factor Controlling of Renewable Energy Generators: a Case Study of Iraqi Wasit Network
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Integrating Renewable Energy (RE) into Distribution Power Networks (DPNs) is a choice for efficient and sustainable electricity. Controlling the power factor of these sources is one of the techniques employed to manage the power loss of the grid. Capacitor banks have been employed to control phantom power, improving voltage and reducing power losses for several decades. The voltage sag and the significant power losses in the Iraqi DPN make it good evidence to be a case study proving the efficiency enhancement by adjusting the RE power factor. Therefore, this paper studies a part of the Iraqi network in a windy and sunny region, the Badra-Zurbatya-11 kV feeder, in the Wasit governorate. A substation of hybrid RE sources is connected to this

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Publication Date
Sun Oct 01 2023
Journal Name
Medical Journal Of Babylon
Prevalence of coronary artery disease in patients with left bundle branch block and its association with risk factors hypertension and diabetes mellitus
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Abstract<sec> <title>Background:

Left bundle branch block (LBBB) is a common finding in electrocardiography, there are many causes of LBBB.

Objectives:

The aim of this study is to discuss the true prevalence of coronary artery disease (CAD) in patients with LBBB and associated risk factors in the form of hypertension and diabetes mellitus.

Materials and Methods:

Patients with LBBB were admitted to the Iraqi heart center for cardiac disea

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