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Wellbore Instability Analysis to Determine the Failure Criteria for Deep Well/H Oilfield
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Publication Date
Tue Jun 22 2021
Journal Name
Expert Systems
Hybrid intelligent technology for plant health using the fusion of evolutionary optimization and deep neural networks
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Publication Date
Thu Aug 01 2024
Journal Name
Journal Of King Saud University - Engineering Sciences
Impact of long-term depletion on horizontal wellbore stability in tight reservoirs-including changes in petrophysical and geomechanical properties
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Publication Date
Tue Jul 01 2014
Journal Name
Journal Of The Faculty Of Medicine Baghdad
The Monosynaptic H-reflex excitability in post-Stroke patients.
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Backgrond: One of the major causes of impaired movements post-stroke is the abnormal phasing of paralytic muscles. Many studies suggested that inappropriate muscle phasing may be associated with enhanced transmission in the monosynaptic Group Ia afferent pathway in the affected limb of post-stroke patients and Group Ia reflexes are abnormally elevated and fail to decrease in amplitude during locomotion.

Objectives: This study was conducted to identify the changes in the Soleus muscle H-reflex excitability at rest in the affected lower limb of post-stroke patients as compared to the contra lateral side and of normal controls.

Patients and methods: The excitability of the m

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Tue Aug 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
FDPHI: Fast Deep Packet Header Inspection for Data Traffic Classification and Management
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Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

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Publication Date
Sun Jul 31 2022
Journal Name
Iraqi Journal Of Science
Deep Learning and Machine Learning via a Genetic Algorithm to Classify Breast Cancer DNA Data
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       This paper uses Artificial Intelligence (AI) based algorithm analysis to classify breast cancer Deoxyribonucleic (DNA). Main idea is to focus on application of machine and deep learning techniques. Furthermore, a genetic algorithm is used to diagnose gene expression to reduce the number of misclassified cancers. After patients' genetic data are entered, processing operations that require filling the missing values using different techniques are used. The best data for the classification process are chosen by combining each technique using the genetic algorithm and comparing them  in terms of accuracy.

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Use of Multi-Response Logistic Regression to Determine the Factors Affecting the Radiation Values of Light-Curing Units in Private Dental Clinics in Erbil
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     This study aims to determine the exposure of dentists to radiation resulting from the use of light therapy units and to assess their risk and impact on dental clinics.  This study was conducted in private dental clinics in the city of Erbil in northern Iraq. Surveys were conducted to collect information about light-curing units. The results were analysed using the multi-response logistic regression to determine the factors affecting the radiation values of light-curing units. The results of the study showed that five major variables have a major effect by radiation.  This is shown with a value of P ≤ 0.05. Typical treatment times with radiant light, with a typical number of daily restorations, may exceed the risk limits for

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Publication Date
Sat Jan 01 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
H - He-essential-supplemented modules
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