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Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
The Extent of the Practice of Iraqi Banks to Manage Profits Using the (LLp it) Model and Its Reflection on the Tax Base, A Case Study of A Sample of Iraqi Private Banks Listed in The Iraqi Stock Exchange
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The research aims to identify the extent to which Iraqi private banks practice profit management motivated by reducing the taxable base by increasing the provision for loan losses by relying on the LLP it model, which consists of a main independent variable (net profit before tax) and independent sub-variables (bank size, total debts to total equity, loans granted to total obligations) under the name of the variables governing the banking business. (Colmgrove-Smirnov) was used to test the normal distribution of data for all banks during the period 2017-2020, and then find the correlation between the main independent variable sub and the dependent variable by means of the correlation coefficient person, and then using the multiple

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Publication Date
Sun Jul 01 2012
Journal Name
Journal Of Techniques مجلة التقني
A STUDY OF SOME TECHNICAL AND ECONOMICAL PARAMETERS FOR MACHINERY UNIT (NEW HOLLAND &DISC PLOW) BY USING THREE DIFFERENT TILT ANGLES دراسة بعض المؤشرات الفنية والأقتصادية للوحدة الميكنية (الجرار نيوهولاند مع المحراث القرصي الثلاثي القلاب) بأستخدام زوايا ميل مختلفة للأقراص
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Publication Date
Sun Jan 02 2022
Journal Name
Journal Of The College Of Languages (jcl)
Comparison between Ghassan Kanafani's Novel " Ma tabaqa lakom" and William Faulkner's "The Sound and the Fury" from the Perspective of the American School (the methodology of the novelistic theme and style): مقایسة دو رمان "ماتبقّي لكم"کنفانی و " خشم و هياهو"ی فاکنر بر اساس مكتب آمريكا (بررسی روش شناختی محتوایی و سبکی )
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     Being the meeting points of the world different languages and out of a scholarly perspective, comparative literature represents a cultural leap as well as an artistic and intellectual development or a global literary movement of both prose and poetry. Such homogenous literary structure requires a systematic and coherent study of the literary output of the people different cultures and civilizations. It also represents the theoretical approach of the present study that debates a systematic comparison between Ghassan Kanafani’s All That's Left to You and William Faulkner’s. The Sound and the Fury.  Within the perspective of the descriptive analysis approach, the present paper discusses th

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Publication Date
Wed May 04 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature
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The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

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Publication Date
Sun Dec 04 2011
Journal Name
Baghdad Science Journal
Modifying Hebbian Network for Text Cipher
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The objective of this work is to design and implement a cryptography system that enables the sender to send message through any channel (even if this channel is insecure) and the receiver to decrypt the received message without allowing any intruder to break the system and extracting the secret information. This work modernize the feedforward neural network, so the secret message will be encrypted by unsupervised neural network method to get the cipher text that can be decrypted using the same network to get the original text. The security of any cipher system depends on the security of the related keys (that are used by the encryption and the decryption processes) and their corresponding lengths. In this work, the key is the final weights

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Publication Date
Tue Jan 01 2013
Journal Name
Photonics & Lasers In Medicine
The assessment of pathological changes in cerebral blood flow in hypertensive rats with stress-induced intracranial hemorrhage using Doppler OCT: Particularities of arterial and venous alterations/Die Beurteilung von pathologischen Veränderungen der Hirndurchblutung bei hypertensiven Ratten mit Stress-induzierten intrakraniellen Blutungen mittels Doppler-OCT: Besonderheiten von arteriellen und venösen Veränderungen
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Abstract<p>Hemorrhagic insult is a major source of morbidity and mortality in both adults and newborn babies in the developed countries. The mechanisms underlying the non-traumatic rupture of cerebral vessels are not fully clear, but there is strong evidence that stress, which is associated with an increase in arterial blood pressure, plays a crucial role in the development of acute intracranial hemorrhage (ICH), and alterations in cerebral blood flow (CBF) may contribute to the pathogenesis of ICH. The problem is that there are no effective diagnostic methods that allow for a prognosis of risk to be made for the development of ICH. Therefore, quantitative assessment of CBF may significantly advance the underst</p> ... Show More
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Publication Date
Tue Dec 01 2020
Journal Name
Results In Physics
Alpha clustering preformation probability in even-even and odd-A<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e3355" altimg="si39.svg"><mml:msup><mml:mrow /><mml:mrow><mml:mn>270</mml:mn><mml:mo>−</mml:mo><mml:mn>317</mml:mn></mml:mrow></mml:msup></mml:math>(116 and 117) using cluster formation model and the mass formulae : KTUY05 and WS4
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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Permeability Determination of Tertiary Reservoir/Ajeel Oil Field
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This paper discusses the method for determining the permeability values of Tertiary Reservoir in Ajeel field (Jeribe, dhiban, Euphrates) units and this study is very important to determine the permeability values that it is needed to detect the economic value of oil in Tertiary Formation. This study based on core data from nine wells and log data from twelve wells. The wells are AJ-1, AJ-4, AJ-6, AJ-7, AJ-10, AJ-12, AJ-13, AJ-14, AJ-15, AJ-22, AJ-25, and AJ-54, but we have chosen three wells (AJ4, AJ6, and AJ10) to study in this paper. Three methods are used for this work and this study indicates that one of the best way of obtaining permeability is the Neural network method because the values of permeability obtained be

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Publication Date
Thu Oct 01 2015
Journal Name
International Journal Of Modern Trends In Engineering And Research (ijmter)
Effect of changing hidden neurons and activation function on Back Propagation (BP) Speed
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The Back-Propagation (BP) is the best known and widely used learning algorithm in training multiple neural network. A vast variety of improvements to BP algorithm have been proposed since ninety’s. in this paper, the effects of changing the number of hidden neurons and activation equation are investigated. According to the simulation results, the convergence speed have been improved and become much faster by the previous two modifications on the BP algorithm.

Publication Date
Wed Oct 21 2015
Journal Name
Integrated Journal Of Engineering Research And Technology
A HYBRID CUCKOO SEARCH AND BACK-PROPAGATION ALGORITHMS WITH DYNAMIC LEARNING RATE TO SPEED UP THE CONVERGENCE (SUBPL) ALGORITHM
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BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.