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Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach
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Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model based on the Spike Neural Network (SNN) called IoT-Traffic Classification (IoT-TCSNN) to classify IoT devices traffic. The model consists of four phases: data preprocessing, feature extraction, classier and evaluation. The proposed model performance is evaluated according to evaluation metrics: accuracy, precision, recall and F1-score and energy usage in comparison with two models: ML based Support Vector Machine IoT-TCSVM and ML based Deep Neural Network (IoT-TCDNN). The evaluations result has been shown that IoT-TCSNN consumes less energy in contrast to IoT-TCDNN and IoT-TCSVM. Also, it gives high accuracy in comparison with IoT-TCSVM.

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Publication Date
Tue Jan 30 2024
Journal Name
International Journal Of Engineering Pedagogy (ijep)
E-learning in the Cloud Computing Environment: Features, Architecture, Challenges and Solutions
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The need to constantly and consistently improve the quality and quantity of the educational system is essential. E-learning has emerged from the rapid cycle of change and the expansion of new technologies. Advances in information technology have increased network bandwidth, data access speed, and reduced data storage costs. In recent years, the implementation of cloud computing in educational settings has garnered the interest of major companies, leading to substantial investments in this area. Cloud computing improves engineering education by providing an environment that can be accessed from anywhere and allowing access to educational resources on demand. Cloud computing is a term used to describe the provision of hosting services

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Publication Date
Fri Feb 04 2022
Journal Name
Neuroquantology
Detecting Damaged Buildings on Post-Hurricane Satellite Imagery based on Transfer Learning
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In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Tue Sep 28 2021
Journal Name
Journal Of The College Of Education For Women
The Role of Binary Settings in John Updike’s Short Stories: A Structuralist Approach: مؤيد انوية ججو الجماني
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John Updike’s use of setting in his fiction has elicited different and even conflicting reactions from critics, varying from symbolic interpretations of setting to a sense of confusion at his use of time and place in his stories.  The present study is an attempt at examining John Updike’s treatment of binary settings in Pigeon Feathers and Other Stories (1962) to reveal theme, characters’ motives and conflicts.  Analyzing Updike’s stories from a structuralist’s perspective reveals his employment of two different places and times in the individual stories as a means of reflecting the psychological state of the characters, as in “The Persistence of Desire”, or expressing conflicting views on social and political is

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Publication Date
Sun Sep 01 2024
Journal Name
Journal Of Radiation Research And Applied Sciences
Bioaccumulation and translocation of radionuclides heavy metals in Cynodon dactylon: A phytoremediation approach in Al-Dora refinery
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Publication Date
Mon Mar 02 2020
Journal Name
Journal Of Applied Research In Higher Education
Proposal of a guide for talent evaluation and management based on a qualitative and three-staged approach
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Purpose

The key objective of the study is to understand the best processes that are currently used in managing talent in Australian higher education (AHE) and design a quantitative measurement of talent management processes (TMPs) for the higher education (HE) sector.

Design/methodology/approach

The three qualitative multi-method studies that are commonly used in empirical studies, namely, brainstorming, focus group discussions and semi-structured individual interviews were considered. Twenty-three individuals from six Australian universities parti

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Publication Date
Tue Mar 01 2022
Journal Name
Eurasian Journalof History, Geography And Economics
Effect of Oil Prices Fluctuations on Agricultural Gross Domestic Product in Iraq: Autoregressive Distributed Lag (ARDL) Approach
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The research dealt with the analysis of the relations between the GDP of the agricultural sector in Iraq, oil prices, the exchange rate and the GDP both on the short term and long term. The research adopted data analysis for the period from 1980-2019 using the ARDL model. the results indicate the existence of long-term relationships between oil prices and the prices of each agricultural commodity at a significance level of 5%. Also, oil prices have a negative consequence on agricultural production in Iraq, and the Iraqi economy is a rentier economy that depends mainly on oil as a source of income and budget financing.

Publication Date
Thu Apr 01 2021
Journal Name
Journal Of Alloys And Compounds
A holistic approach to optical characterizations of vacuum deposited Cu2ZnSnS4 thin film coatings for solar absorbing layers
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Publication Date
Mon Jun 23 2025
Journal Name
Islamic Communication Journal
Negotiating the meaning of female genital mutilation and cutting: A symbolic interactionist approach among religious university students
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The meanings attributed to Female Genital Mutilation/Cutting (FGM/C) are shaped through complex negotiations within religious and socio-cultural frameworks, including those observed in Indonesia. Using a combined qualitative and quantitative (mixed methods)-ethnographic and survey approach, data from 109 students of religious tertiary institutions in East Kalimantan on their perspectives on FGM/C practices can be more comprehensively explored. The results of the study, which were analysed using the three principles of symbolic interactionism, showed that 72.5 per cent of religious college student families still practice FGM/C and 53.2 per cent stated that FGM/C practices are beneficial for women.  However, they are also willing, if

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
A Mathematical Approach for Computing the Linear Equivalence of a Periodic Key-Stream Sequence Using Fourier Transform
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A mathematical method with a new algorithm with the aid of Matlab language is proposed to compute the linear equivalence (or the recursion length) of the pseudo-random key-stream periodic sequences using Fourier transform. The proposed method enables the computation of the linear equivalence to determine the degree of the complexity of any binary or real periodic sequences produced from linear or nonlinear key-stream generators. The procedure can be used with comparatively greater computational ease and efficiency. The results of this algorithm are compared with Berlekamp-Massey (BM) method and good results are obtained where the results of the Fourier transform are more accurate than those of (BM) method for computing the linear equivalenc

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