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Innovations in t-way test creation based on a hybrid hill climbing-greedy algorithm
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<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. This study presents a hybrid greedy hill climbing algorithm (HGHC) that ensures both effectiveness and near-optimal results for generating a small number of test data. To make certain that the suggested HGHC outperforms the most used techniques in terms of test size. It is compared to others in order to determine its effectiveness. In contrast to recent practices utilized for the production of covering arrays (CAs) and mixed covering arrays (MCAs), this hybrid strategy is superior since allowing it to provide the utmost outcome while reducing the size and limit the loss of unique pairings in the CA/MCA generation.</p>

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Publication Date
Sat Jan 12 2019
Journal Name
Journal Of The College Of Education For Women
Self- Awareness of Emotions and its Relation to the Way of Helping of Kindergardens' Children
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The self-awareness interactions reflects with emotions,assess the child in respect to its relations with the social standards; they are not merely simply reactions , but rather they connect with his moral behavior and other 's thinks. When the self- awareness gets developed with emotions within the child , the latter become highly sensitive, causing him prone to be blamed . AS a result , the children test the self –awareness interactions with emotions and in age 3 years , where the self –awareness interactions with emotion clearly link to the self- assessment. The children in stage of kindergarten could not describe the self-awareness interactions accurately ; they test it under different circumstances in comparison to the youngest o

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Publication Date
Fri Apr 01 2016
Journal Name
Al–bahith Al–a'alami
Indicators of Mental image among Students of the University of Baghdad about Iraqi Political Parties-(a research based on a master thesis)
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Media studies have focused mostly on the issue of the mental image because the image that is formed in the mind has become not only a photo of a human being and having kept for himself. This image has an outside influence which may sometimes up to the formation of the fate of others and it sometimes includes individuals and groups together.
This study comes in the context of identifying the image of Iraqi political parties among Iraqi university students and the nature of the view that students have in their minds about these parties.
Chapter one includes the problem of the research, the importance of the study, the goals and method used. Chapter two is divided into two sections: section one deals with the concept of the mental i

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Publication Date
Mon Feb 21 2022
Journal Name
Applied Sciences
The Behavior of Hybrid Fiber-Reinforced Concrete Elements: A New Stress-Strain Model Using an Evolutionary Approach
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Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti

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Publication Date
Wed Jun 01 2022
Journal Name
Journal Of King Saud University - Computer And Information Sciences
Heuristic initialization of PSO task scheduling algorithm in cloud computing
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Publication Date
Sun Apr 27 2025
Journal Name
Iraqi Journal Of Science
Intrusion Detection Approach Based on DNA Signature
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Publication Date
Fri May 01 2020
Journal Name
Journal Of Physics: Conference Series
Pilgrims tracking and monitoring based on IoT
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Abstract<p>The pilgrimage takes place in several countries around the world. The pilgrimage includes the simultaneous movement of a huge crowd of pilgrims which leads to many challenges for the pilgrimage authorities to track, monitor, and manage the crowd to minimize the chance of overcrowding’s accidents. Therefore, there is a need for an efficient monitoring and tracking system for pilgrims. This paper proposes powerful pilgrims tracking and monitoring system based on three Internet of Things (IoT) technologies; namely: Radio Frequency Identification (RFID), ZigBee, and Internet Protocol version 6 (IPv6). In addition, it requires low-cost, low-power-consumption implementation. The proposed </p> ... Show More
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Publication Date
Mon May 08 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Image Retrieval Based on Coefficient Correlation Index
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Image retrieval is an active research area in image processing, pattern recognition, and
computer vision. In this proposed method, there are two techniques to extract the feature
vector, the first one is applying the transformed algorithm on the whole image and the second
is to divide the image into four blocks and then applying the transform algorithm on each part
of the image. In each technique there are three transform algorithm that have been applied
(DCT, Walsh Transform, and Kekre’s Wavelet Transform) then finding the similarity and
indexing the images, useing the correlation between feature vector of the query image and
images in database. The retrieved method depends on higher indexing number. <

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Skull Stripping Based on the Segmentation Models
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Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

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Publication Date
Sat Aug 03 2024
Journal Name
Proceedings Of Ninth International Congress On Information And Communication Technology
Offline Signature Verification Based on Neural Network
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The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Engineering
Intelligent Dust Monitoring System Based on IoT
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Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

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