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bsj-10084
Efficient Task Scheduling Approach in Edge-Cloud Continuum based on Flower Pollination and Improved Shuffled Frog Leaping Algorithm
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The rise of edge-cloud continuum computing is a result of the growing significance of edge computing, which has become a complementary or substitute option for traditional cloud services. The convergence of networking and computers presents a notable challenge due to their distinct historical development. Task scheduling is a major challenge in the context of edge-cloud continuum computing. The selection of the execution location of tasks, is crucial in meeting the quality-of-service (QoS) requirements of applications. An efficient scheduling strategy for distributing workloads among virtual machines in the edge-cloud continuum data center is mandatory to ensure the fulfilment of QoS requirements for both customer and service provider. Existing research used metaheuristic algorithm to solve tak scheduling problem, however, must of the existing metaheuristics used suffers from falling into local mina due to their inefficiency to avoid unfeasible region in the solution search space. Therefore, there is a dire need for an efficient metaheuristic algorithm for task scheduling.  This study proposed an FPA-ISFLA task scheduling model using hybrid flower pollination and improved shuffled frog leaping algorithms. The simulation results indicate that the FPA-ISFLA algorithm is superior to the PSO algorithm in terms of makespan time, resource utilization, and execution cost reduction, especially with an increasing number of tasks.

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Publication Date
Wed Jan 02 2019
Journal Name
Journal Of Educational And Psychological Researches
A training program for chemistry teachers based on the knowledge economy and its impact on the productive thinking of their students
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       The current research aims to build a training program for chemistry teachers based on the knowledge economy and its impact on the productive thinking of their students. To achieve the objectives of the research, the following hypothesis was formulated:

   There is no statistically significant difference at (0.05) level of significance between the average grades of the students participating in the training program according to the knowledge economy and the average grades of the students who did not participate in the training program in the test of productive thinking. The study sample consisted of (288) second intermediate grade students divided into (152) for the control group

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Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The research is based on a thesis not discussed: Test the strategy of the General Organization based on the model Wichler and Bakov A case study at the Iraqi Ministry of Interior
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The study aimed at identifying the strategic gaps in the actual reality of the management of public organizations investigated to determine the strategy used based on the study model. The study relied on the variable of the general organization strategy in its dimensions (the general organization strategy, the organization's political strategy and the defense strategy of the organization) The sample of the study was (General Directorate of Traffic, Civil Status Directorate and Civil Defense Directorate), formations affiliated to the Ministry of the Interior, for the importance of the activity carried out by these public organizations by providing them In order to translate the answers into a quantitative expression in the analysi

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Publication Date
Wed Feb 29 2012
Journal Name
Al-khwarizmi Engineering Journal
A New Audio Steganography System Based on Auto-Key Generator
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Stenography is the art of hiding the very presence of communication by embedding secret message into innocuous looking cover document, such as digital image, videos, sound files, and other computer files that contain perceptually irrelevant or redundant information as covers or carriers to hide secret messages.

In this paper, a new Least Significant Bit (LSB) nonsequential embedding technique in wave audio files is introduced. To support the immunity of proposed hiding system, and in order to recover some weak aspect inherent with the pure implementation of stego-systems, some auxiliary processes were suggested and investigated including the use of hidden text jumping process and stream ciphering algorithm. Besides, the suggested

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Assessment of Azotobacter chroococcum’s Ability to Produce Hydrolytic Enzymes and Enhance Growth of Vicia faba
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A. chroococcum isolate was examined for its ability to produce the hydrolytic enzymes chitinase, pectinase, protease, and lipase, in an effort to enhance the growth of fava bean (Vicia faba). Biological experiment was conducted in pots with complete random design (CRD). The experiment includes three treatments: control (plant without treatment) (P), NPK fertilizer (plant + fertilizer) (PF), and A. chroococcum inoculum (plant + A. chroococcum) (PA). These treatments were performed with sterile and non-sterile soil, which were planted with fava beans. At the end of experiment (seven weeks from planting), length and weight of plant shoot and plant root were calculated. The results show that the isolate wa

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Publication Date
Mon Nov 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
The Effect Irrigation Scheduling and Potassium Fertilization on Water Consumption of Potato (Solanum tuberosum L.) Under Modern Irrigation Systems
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A field experiment was conducted in Yusufiya sub-district - Mahmudiya township/Baghdad governorate in silty loam texture soil during the spring season of 2020. The experiment included three treatments with three replicates, as the Randomized Complete Block Design (RCBD) was used according to the arrangement of the split design block. The treatments are in the irrigation system, which included surface drip irrigation (T1) and sprinkler irrigation (T2). Secondly, the Irrigation levels including the irrigation using 0.70 Pan Evaporation Fraction PEF (I1), irrigation using 1.00 PEF (I2), and irrigation using 1.30 PEF (I3). Coupled with, Pota

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Mon Dec 25 2017
Journal Name
Al-khwarizmi Engineering Journal
Comparisons of Mechanical Properties of sub-mm Lead Based and Lead Free Based Solder Using in Manufacturing of Printed Circuits
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Abstract

This study investigates the mechanical compression properties of tin-lead and lead-free alloy spherical balls, using more than 500 samples to identify statistical variability in the properties in each alloy. Isothermal aging was done to study and compare the aging effect on the microstructure and properties.

The results showed significant elastic and plastic anisotropy of tin phase in lead-free tin based solder and that was compared with simulation using a Crystal Plasticity Finite Element (CPEF) method that has the anisotropy of Sn installed. The results and experiments were in good agreement, indicating the range of values expected with anisotropic properties.

Keywords<

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Fri Apr 26 2024
Journal Name
Mathematical Modelling Of Engineering Problems
Solving Tri-criteria: Total Completion Time, Total Earliness, and Maximum Tardiness Using Exact and Heuristic Methods on Single-Machine Scheduling Problems
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Publication Date
Fri Jan 01 2021
Journal Name
Analytical And Bioanalytical Chemistry Research
Mutual Derivatization in the Determination of Dapsone and Thymol Using Cloud Point Extraction Followed by Spectrophotometric Detection
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A procedure for the mutual derivatization and determination of thymol and Dapsone was developed and validated in this study. Dapsone was used as the derivatizing agent for the determination of thymol, and thymol was used as the derivatizing agent for the determination of Dapsone. An optimization study was performed for the derivatization reaction; i.e., the diazonium coupling reaction. Linear regression calibration plots for thymol and Dapsone in the direct reaction were constructed at 460 nm, within the concentration range of 0.3-7 μg ml-1 for thymol and 0.3-4 μg ml-1 for Dapsone, with limits of detection 0.086 and 0.053 μg ml-1, respectively. Corresponding plots for the cloud point extraction of thymol and Dapsone were constructed

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