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Determination Optimum Inventory Level for Material Using Genetic Algorithm
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The integration of decision-making will lead to the robust of its decisions, and then determination optimum inventory level to the required materials to produce and reduce the total cost by the cooperation of purchasing department with inventory department and also with other company,s departments. Two models are suggested to determine Optimum Inventory Level (OIL), the first model (OIL-model 1) assumed that the inventory level for materials quantities equal to the required materials, while the second model (OIL-model 2) assumed that the inventory level for materials quantities more than the required materials for the next period.                                                    This study was applied in Wasit Company for Textile Manufacturing in the Textile Factory, where it produces five products, which are printed striped, plain, poplin, dyed poplin and Naba weave.  The products are made from cotton and they are passing through several stages to transfer to the final product. A genetic algorithm is used to determine the optimum quantity of the purchase a cotton and colors for each month and with minimum cost. Where the purchasing and transportation costs were either constant or variable with respect to purchased quantities while holding cost is kept constant. The results showed that the total cost of the first model is minimum than the second model because the holding cost for this model is less from the second model, while the purchasing and transportation costs from two models are equals. The percentage of purchasing cost for cotton is the biggest value, more 99% of purchasing cost for two models.

                        

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Publication Date
Wed Mar 02 2022
Journal Name
Journal Of Educational And Psychological Researches
King Khalid University towards Strategies Compatible with Brain-Based Learning (BBL)
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The study aimed to reveal the level of knowledge and tendencies of high- study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with brain-based learning (BBL). And Then, putting a proposed concept to develop knowledge and tendencies of high-study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with Brain-based learning (BBL). For achieving this goal, a cognitive test and a scale of tendency were prepared to apply harmonious strategies with brain-based learning. The descriptive approach was used because it suits the goals of the study. The study sample consisted of (70) male and female students of postgraduate

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Publication Date
Tue Jun 14 2022
Journal Name
Al-academy
Visual stimulus in the design of interior spaces
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The visual stimulus is the effective force in visual attraction that achieves visual and perceptual co-optation and is important in wooing the recipient, and many procedural processes in the design are interpreted on it as the visual stimulus achieves visual comfort and a sense of pleasure and gives (place) the interior space a transformation in its plastic structure as well as arousing attention through The kinetic rhythm and the formal diversity, which increases the possibility of breaking the routine and traditional constraints of design patterns through the coating and encapsulation of the vertical and horizontal levels . Thus, the research problem was launched based on the following question: What are the stimuli of the visual stimu

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Crossref
Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Science And Research (ijsr)
Optimal Economic Design of Diversion Structures during Construction of a Dam by Particle Swarm Optimization
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Diverting river flow during construction of a main dam involves the construction of cofferdams, and tunnels, channels or other temporary passages. Diversion channels are commonly used in wide valleys where the high flow makes tunnels or culverts uneconomic. The diversion works must form part of the overall project design since it will have a major impact on its cost, as well as on the design, construction program and overall cost of the permanent works. Construction costs contain of excavation, lining of the channel, and construction of upstream and downstream cofferdams. The optimization model was applied to obtain optimalchannel cross section, height of upstream cofferdam, and height of downstream cofferdamwith minimum construction cost

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Publication Date
Sun Mar 04 2018
Journal Name
Iraqi Journal Of Science
Improving Detection Rate of the Network Intrusion Detection System Based on Wrapper Feature Selection Approach
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Regarding the security of computer systems, the intrusion detection systems (IDSs) are essential components for the detection of attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in real time. A major drawback of the IDS is their inability to provide adequate sensitivity and accuracy, coupled with their failure in processing enormous data. The issue of classification time is greatly reduced with the IDS through feature selection. In this paper, a new feature selection algorithm based on Firefly Algorithm (FA) is proposed. In addition, the naïve bayesian classifier is used to discriminate attack behaviour from normal behaviour in the network tra

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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
Feature Extraction in Six Blocks to Detect and Recognize English Numbers
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    The Fuzzy Logic method was implemented to detect and recognize English numbers in this paper. The extracted features within this method make the detection easy and accurate. These features depend on the crossing point of two vertical lines with one horizontal line to be used from the Fuzzy logic method, as shown by the Matlab code in this study. The font types are Times New Roman, Arial, Calabria, Arabic, and Andalus with different font sizes of 10, 16, 22, 28, 36, 42, 50 and 72. These numbers are isolated automatically with the designed algorithm, for which the code is also presented. The number’s image is tested with the Fuzzy algorithm depending on six-block properties only. Groups of regions (High, Medium, and Lo

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Scopus (4)
Scopus Crossref
Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
An Evolutionary-Based Mutation With Functional Annotation to Identify Protein Complexes Within PPI Networks
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     The research deals with an evolutionary-based mutation with functional annotation to identify protein complexes within PPI networks. An important field of research in computational biology is the difficult and fundamental challenge of revealing complexes in protein interaction networks. The complex detection models that have been developed to tackle challenges are mostly dependent on topological properties and rarely use the biological  properties of PPI networks. This research aims to push the evolutionary algorithm to its maximum by employing gene ontology (GO) to communicate across proteins based on biological information similarity for direct genes. The outcomes show that the suggested method can be utilized to improve the

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Scopus (1)
Scopus Crossref
Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
A General Overview on the Categories of Image Features Extraction Techniques: A Survey
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In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

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Crossref
Publication Date
Tue Jan 04 2022
Journal Name
Iraqi Journal Of Science
Spam Filtering Approach based on Weighted Version of Possibilistic c-Means
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A principal problem of any internet user is the increasing number of spam, which became a great problem today. Therefore, spam filtering has become a research fo-cus that attracts the attention of several security researchers and practitioners. Spam filtering can be viewed as a two-class classification problem. To this end, this paper proposes a spam filtering approach based on Possibilistic c-Means (PCM) algorithm and weighted distance coined as (WFCM) that can efficiently distinguish between spam and legitimate email messages. The objective of the formulated fuzzy problem is to construct two fuzzy clusters: spam and email clusters. The weight assignment is set by information gain algorithm. Experimental results on spam based benchmark

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Taxonomy of Memory Usage in Swarm Intelligence-Based Metaheuristics
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Metaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and without memory (memory-less). The absence of memory in some metaheuristics will lead to the loss of the information gained in previous iterations. The metaheuristics tend to divert from promising areas of solutions search spaces which will lead to non-optimal solutions. This paper aims to review memory usage and its effect on the performance of the main SI-based metaheuristics. Investigation has been performed on SI metaheuristics, memory usage and memory-less metaheuristics, memory char

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Crossref (2)
Clarivate Crossref
Publication Date
Fri May 01 2015
Journal Name
Journal Of Engineering
On Gradient Descent Localization in 3-D Wireless Sensor Networks
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Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo

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