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A Genetic Algorithm for Task Allocation Problem in the Internet of Things
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In the last few years, the Internet of Things (IoT) is gaining remarkable attention in both academic and industrial worlds. The main goal of the IoT is laying on describing everyday objects with different capabilities in an interconnected fashion to the Internet to share resources and to carry out the assigned tasks. Most of the IoT objects are heterogeneous in terms of the amount of energy, processing ability, memory storage, etc. However, one of the most important challenges facing the IoT networks is the energy-efficient task allocation. An efficient task allocation protocol in the IoT network should ensure the fair and efficient distribution of resources for all objects to collaborate dynamically with limited energy. The canonical definition for network lifetime in the IoT is to increase the period of cooperation between objects to carry out all the assigned tasks. The main contribution in this paper is to address the problem of task allocation in the IoT as an optimization problem with a lifetime-aware model. A genetic algorithm is proposed as a task allocation protocol. For the proposed algorithm, a problem-tailored individual representation and a modified uniform crossover are designed. Further, the individual initialization and perturbation operators (crossover and mutation) are designed so as to remedy the infeasibility of any solution located or reached by the proposed genetic algorithm. The results showed reasonable performance for the proposed genetic-based task allocation protocol. Further, the results prove the necessity for designing problem-specific operators instead of adopting the canonical counterparts.

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Publication Date
Mon Oct 06 2014
Journal Name
Journal Of Educational And Psychological Researches
The Effect of the Problem Based Learning on EFL Learners’ Achievement
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The present study discusses the problem based learning in Iraqi classroom. This method aims to involve all learners in collaborative activities and it is learner-centered method. To fulfill the aims and verify the hypothesis which reads as follow” It is hypothesized that there is no statistically significant differences between the achievements of Experimental group and control group”. Thirty learners are selected to be the sample of present study.Mann-Whitney Test for two independent samples is used to analysis the results. The analysis shows that experimental group’s members who are taught according to problem based learning gets higher scores than the control group’s members who are taught according to traditional method. This

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Publication Date
Wed May 09 2012
Journal Name
Fuzzy Inference System - Theory And Applications
Some Studies on Noise and Its Effects on Industrial/Cognitive Task Performance and Modeling
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Publication Date
Thu Feb 23 2023
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
A Training Program According to Interactive Teaching Strategies and its Impact on Achievement and Creative Problem Solving for Fourth-Grade Preparatory Students in Chemistry
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The aim of the research is to know the effect of a training program based on interactive teaching strategies on achievement and creative problem solving among fourth-grade students in chemistry of the directorate of education Rusafa first, the sample was divided into two groups, one experimental and numbering (29) students and the other control group numbering (30) students. The experimental group underwent the training program in the first semester of the year (2021-2022) and the control one studied according to the usual method. Two tools were built, the first being an academic achievement test consisting of (40) multiple-choice items, and the second a test of creative problem-solving skills in a chemistry subject and consisting o

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Publication Date
Sat Nov 01 2014
Journal Name
Journal Of Next Generation Information Technology
The effect of the smoothing filter on an image encrypted by the blowfish algorithm then hiding it in a BMP image
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order to increase the level of security, as this system encrypts the secret image before sending it through the internet to the recipient (by the Blowfish method). As The Blowfish method is known for its efficient security; nevertheless, the encrypting time is long. In this research we try to apply the smoothing filter on the secret image which decreases its size and consequently the encrypting and decrypting time are decreased. The secret image is hidden after encrypting it into another image called the cover image, by the use of one of these two methods" Two-LSB" or" Hiding most bits in blue pixels". Eventually we compare the results of the two methods to determine which one is better to be used according to the PSNR measurs

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Publication Date
Mon Mar 01 2010
Journal Name
Journal Of Computer Science
Dropping down the Maximum Item Set: Improving the Stylometric Authorship Attribution Algorithm in the Text Mining for Authorship Investigation
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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
Parallel Particle Swarm Optimization Algorithm for Identifying Complex Communities in Biological Networks
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    Identification of complex communities in biological networks is a critical and ongoing challenge since lots of network-related problems correspond to the subgraph isomorphism problem known in the literature as NP-hard. Several optimization algorithms have been dedicated and applied to solve this problem. The main challenge regarding the application of optimization algorithms, specifically to handle large-scale complex networks, is their relatively long execution time. Thus, this paper proposes a parallel extension of the PSO algorithm to detect communities in complex biological networks. The main contribution of this study is summarized in three- fold; Firstly, a modified PSO algorithm with a local search operator is proposed

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Multifactor Algorithm for Test Case Selection and Ordering
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Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls sh

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Publication Date
Fri Apr 20 2012
Journal Name
International Journal Of Computer And Information Engineering
An Optimal Algorithm for HTML Page Building Process
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An Optimal Algorithm for HTML Page Building Process

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Publication Date
Thu Sep 26 2019
Journal Name
Processes
Fine-Tuning Meta-Heuristic Algorithm for Global Optimization
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This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t

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Publication Date
Thu Dec 01 2011
Journal Name
2011 Developments In E-systems Engineering
Enhanced Computation Time for Fast Block Matching Algorithm
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