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Artificial Intelligence Based Deep Bayesian Neural Network (DBNN) Toward Personalized Treatment of Leukemia with Stem Cells
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The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of Deep Bayesian Neural Network (DBNN) for the personalized treatment of leukemia cancer has shown a significant tested accuracy for the model. DBNNs used in this study was able to classify images with accuracy exceeding 98.73%. This study depicts that the DBNN can classify cell cultures only based on unstained light microscope images which allow their further use. Therefore, building a bayesian‐based model to great help during commercial cell culturing, and possibly a first step in the process of creating an automated/semiautomated neural network‐based model for classification of good and bad quality cultures when images of such will be available.

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Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Network Self-Fault Management Based on Multi-Intelligent Agents and Windows Management Instrumentation (WMI)
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This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

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Publication Date
Sat Apr 09 2022
Journal Name
Engineering, Technology & Applied Science Research
A Semi-Empirical Equation based on the Strut-and-Tie Model for the Shear Strength Prediction of Deep Beams with Multiple Large Web Openings
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The behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be u

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Publication Date
Sun May 21 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Analyses of Ridge Regression Prooblems
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   A Bayesian formulation of the ridge regression problem is considerd, which derives from a direct specification of prior informations about parameters of general linear regression model when data suffer from a high degree of multicollinearity.A new approach for deriving the conventional estimator for the ridge parameter proposed by Hoerl and Kennard (1970) as well as  Bayesian estimator  are presented. A numerical example is studied in order to   compare the performance of these estimators.

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Publication Date
Thu Jan 10 2019
Journal Name
Journal Of The College Of Education For Women
Personal intelligence relationship with the management agliation among teachers
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       Personal intelligence is thinking about an other person , understanding him, have sympathy and differentiation between people, and to appreciate their own point of view, with the sensitivity to their motives, behavior, and goals, so this intelligence involves dealing with a person or group of persons effectively and in normal or logical manner.

      Emotions management is to achieve emotional balance by controlling the emotions continuously, self disciplining, keeping away from excitement sources, and dealing with bad situations in constructive way to achieve the psychological stability .  

  • the study aims

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Publication Date
Sun Apr 30 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fast Training Algorithms for Feed Forward Neural Networks
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 The aim of this paper, is to discuss several high performance training algorithms fall into two main categories. The first category uses heuristic techniques, which were developed from an analysis of the performance of the standard gradient descent algorithm. The second category of fast algorithms uses standard numerical optimization techniques such as: quasi-Newton . Other aim is to solve the drawbacks related with these training algorithms and propose an efficient training algorithm for FFNN

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Diversity Operators-based Artificial Fish Swarm Algorithm to Solve Flexible Job Shop Scheduling Problem
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Artificial fish swarm algorithm (AFSA) is one of the critical swarm intelligent algorithms. In this
paper, the authors decide to enhance AFSA via diversity operators (AFSA-DO). The diversity operators will
be producing more diverse solutions for AFSA to obtain reasonable resolutions. AFSA-DO has been used to
solve flexible job shop scheduling problems (FJSSP). However, the FJSSP is a significant problem in the
domain of optimization and operation research. Several research papers dealt with methods of solving this
issue, including forms of intelligence of the swarms. In this paper, a set of FJSSP target samples are tested
employing the improved algorithm to confirm its effectiveness and evaluate its ex

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Behavior of Reinforced Concrete Deep Beams Strengthened with Carbon Fiber Reinforced Polymer Strips
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This research is concerned to investigate the behavior of reinforced concrete (RC) deep beams strengthened with carbon fiber reinforced polymer (CFRP) strips. The experimental part of this research is carried out by testing seven RC deep beams having the same dimensions and steel reinforcement which have been divided into two groups according to the strengthening schemes. Group one was consisted of three deep beams strengthened with vertical U-wrapped CFRP strips. While, Group two was consisted of three deep beams strengthened with inclined CFRP strips oriented by 45o with the longitudinal axis of the beam. The remaining beam is kept unstrengthening as a reference beam. For each group, the variable considered

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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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Publication Date
Wed Oct 07 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Effectiveness of Deep Brain Stimulation in Iraqi Patients with Parkinson Disease
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Publication Date
Sat Feb 25 2017
Journal Name
International Journal On Advanced Science, Engineering And Information Technology
A Novel DNA Sequence Approach for Network Intrusion Detection System Based on Cryptography Encoding Method
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A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh

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