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Comparison of Artificial Neural Network and Box- Jenkins Models to Predict the Number of Patients with Hypertension in Kalar
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    Artificial Neural Network (ANN) is widely used in many complex applications. Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.  The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model  and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Jenkins models on a data set for predict. Comparisons between the models has been performed using Criterion indicator Akaike information Criterion, mean square of error,  root mean square of error, and mean absolute percentage error, concluding that the prediction for patients with hypertension by using artificial neural networks model is the best.

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of The College Of Languages (jcl)
بررسیِ حرکت¬شناختیِ افعالِ متنِ "ما زِ بالاییم و بالا می رویم" مولانا Kinetic Study of Mewlana Jalaluddin Rumi's "Mazi Balaeem we Bala Mi Roeem" Text's Verbs
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چکیده­ی بحث

       به نظر می­آید که عالم هستی ، بر مسأله­ی « حرکت» استوار دارد ، و روح ، همیشه دنبال دگرگونی و تکامل و برتری می­گردد. حرکت ، همه­ی چیزها در عالم إمکان را  در بر می­گیرد. حرکت در بنیادهای فکر مولانا جای مهمی دارد .اشعار مولانا مقدار زیادی از پویایی و حرکت برخوردارست، و از آنجایی که فعل ، عنصر تکانبخش جمله ، و کانون دلالت است ، ترجیح دادیم - علاوه بر دیگر عنا

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Publication Date
Fri Jan 31 2025
Journal Name
Joiv : International Journal On Informatics Visualization
RC5 Performance Enhancement Based on Parallel Computing
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This study aims to enhance the RC5 algorithm to improve encryption and decryption speeds in devices with limited power and memory resources. These resource-constrained applications, which range in size from wearables and smart cards to microscopic sensors, frequently function in settings where traditional cryptographic techniques because of their high computational overhead and memory requirements are impracticable. The Enhanced RC5 (ERC5) algorithm integrates the PKCS#7 padding method to effectively adapt to various data sizes. Empirical investigation reveals significant improvements in encryption speed with ERC5, ranging from 50.90% to 64.18% for audio files and 46.97% to 56.84% for image files, depending on file size. A substanti

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

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Publication Date
Sat Dec 30 2023
Journal Name
Modern Sport
تأثير منهج تعليمي وفق أنموذج بايبي على تعلم بعض مهارات الكرة الطائرة للطالبات بكلية التربية البدنية وعلوم الرياضة
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أن أهمية البحث تكمن في أعداد منهج تعليمي مقترح وفق أنموذج بايبي وتعلم مهارتي الاعداد وأستقبال الارسال بالكرة الطائرة للطالبات وتكمن أهمية أنموذج بايبي بالمساعدة على توظيف المعلومات في المواقف المختلفة،وان مشكلة البحث جاءت بعد أطلاع الباحثات على الدراسات والمصادر السابقة لاحظت بأن هناك ضعف في الاداء المهاري في مهارتي الاعداد وأستقبال الارسال بالكرة الطائرة من قبل الطالبات لذلك أرتأت الباحثات الى التع

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Publication Date
Sun Apr 04 2010
Journal Name
Journal Of Educational And Psychological Researches
بناء مقياس معنى الحياة كما تدركه طالبة الجامعة على وفق Multidimensional Item Response Model
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The undimensionality hypothesis which is item response theory depend it is unable in some of measurement situations because there are many dimensions which are affect of the response, so as the researches reached to expand this hypothesis to construct a new one which is multidimensional, and many of theories are pointed to the concept of meaning of life is multidimensionality, so this research aimed to construct the scale of meaning of life as the student's perception according with Multidimensional Item Response Model and this research adopt Wong's theory 1998 which point to the meaning of life consist of (7) dimensions. The research tool contains (49) items distributed at dimensions of meaning of life. Sample of statistical ana

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Publication Date
Tue Jan 01 2013
Journal Name
Advances In Physics Theories And Applications
Adsorption Study of Symmetrical Schiff Base Ligand 4,4’-[hydrazine-1,2-diylidenebis(methan-1-yl-1-ylidene) bis (2-methoxyphenol)] on Granulated Initiated Calcined Iraqi Montmorillonite via Columnar Method.
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The adsorption ability of Iraqi initiated calcined granulated montmorillonite to adsorb Symmetrical Schiff Base Ligand 4,4’-[hydrazine-1, 2-diylidenebis (methan-1-yl-1-ylidene)) bis (2-methoxyphenol)] derived from condensation reaction of hydrazine hydrate and 4-hydroxy-3-methoxybenzaldehyde, from aqueous solutions has been investigated through columnar method.The ligand (H2L) adsorption found to be dependent on adsorbent dosage, initial concentration and contact time.All columnar experiments were carried out at three different pH values (5.5, 7and 8) using buffer solutions at flow rate of (3 drops/ min.),at room temperature (25±2)°C. The experimental isotherm data were analyzed using Langmuir, Freundlich and Temkin equations. The monol

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Publication Date
Wed Jul 05 2017
Journal Name
Chemical Engineering Communications
Microwave-assisted preparation of mesoporous-activated carbon from coconut (<i>Cocos nucifera</i>) leaf by H<sub>3</sub>PO<sub>4</sub>activation for methylene blue adsorption
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Publication Date
Wed Jul 12 2023
Journal Name
Energies
Finite Time Disturbance Observer Based on Air Conditioning System Control Scheme
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A novel robust finite time disturbance observer (RFTDO) based on an independent output-finite time composite control (FTCC) scheme is proposed for an air conditioning-system temperature and humidity regulation. The variable air volume (VAV) of the system is represented by two first-order mathematical models for the temperature and humidity dynamics. In the temperature loop dynamics, a RFTDO temperature (RFTDO-T) and an FTCC temperature (FTCC-T) are designed to estimate and reject the lumped disturbances of the temperature subsystem. In the humidity loop, a robust output of the FTCC humidity (FTCC-H) and RFTDO humidity (RFTDO-H) are also designed to estimate and reject the lumped disturbances of the humidity subsystem. Based on Lyapunov theo

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Face Identification Using Back-Propagation Adaptive Multiwavenet
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Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a

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