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Effective Solution of University Course Timetabling using Particle Swarm Optimizer based Hyper Heuristic approach
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The university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed approach generates solutions into two phases (initial and improvement). A new LLH named “least possible rooms left” has been developed and proposed to schedule events. Both datasets of international timetabling competition (ITC) i.e., ITC 2002 and ITC 2007 are used to evaluate the proposed method. Experimental results indicate that the proposed low-level heuristic helps to schedule events at the initial stage. When compared with other LLH’s, the proposed LLH schedule more events for 14 and 15 data instances out of 24 and 20 data instances of ITC 2002 and ITC 2007, respectively. The experimental study shows that HH PSO gets a lower soft constraint violation rate on seven and six data instances of ITC 2007 and ITC 2002, respectively. This research has concluded the proposed LLH can get a feasible solution if prioritized.

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Publication Date
Wed Jun 07 2023
Journal Name
Journal Of Educational And Psychological Researches
Multiple Intelligence Test Item Selection-Based on Howard Gardner's MI Model Using a Generalized Partial Estimation Model: Ministry of Education \ Karkh First Directorate of Education
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The aim of the research is to examine the multiple intelligence test item selection based on Howard Gardner's MI model using the Generalized Partial Estimation Form, generalized intelligence. The researcher adopted the scale of multiple intelligences by Kardner, it consists of (102) items with eight sub-scales. The sample consisted of (550) students from Baghdad universities, Technology University, al-Mustansiriyah university, and Iraqi University for the academic year (2019/2020). It was verified assumptions theory response to a single (one-dimensional, local autonomy, the curve of individual characteristics, speed factor and application), and analysis of the data according to specimen partial appreciation of the generalized, and limits

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Publication Date
Wed Mar 30 2022
Journal Name
College Of Islamic Sciences
The grammatical approach to explain Bant Souad's poem (Explanation of Ibn Hisham as a model) a . M . Dr. Abdul Hamid Hamad shehatha Mustansiriya University Faculty of Basic Education the department of Arabic language
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This study is concerned with shedding light on the grammatical method of Ibn Hisham Al-Ansari (761 AH), in his explanation of Bant Souad’s poem by the poet Kaab bin Zuhair, and I included a brief description of Ibn Hisham’s life with a number of explanations of this poem, then clarified the most important features of this method The grammar represented by his reliance on hearing and presenting it to analogy with mention of types of analogy, as well as his attribution of opinions to their owners with weighting, selection and balancing, and his attention to reasoning and a number of grammatical ailments, and his approach is also distinguished by following the method of fractal.

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Publication Date
Wed Mar 02 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effects of Using Educational Moodle Platform to Develop Instructors’ Skills in Designing Electronic Tests at Dhofar University
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With the premise that effective use of online instructional practices is of vital importance in classrooms, the current study aimed to examine the effects of using Moodle applications to develop instructors’ skills in designing electronic tests at Dhofar University. The sample of this study consisted of (25) instructors participated in the experimental group. The researchers implemented a quasi-experimental design with one group pre- and post-test; in addition, an observation card was implemented to measure the target skills related to test design. The research instruments were subjected to validity and reliability measures to ensure valid and reliable data and results. The study results showed that those instructors who participated i

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Human Face Recognition Based on Local Ternary Pattern and Singular Value Decomposition
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There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Moving Objects Detection Based on Frequency Domain: image processing
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In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

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Publication Date
Fri Dec 01 2023
Journal Name
مجلة العلوم و التكنولوجية للنشاطات البدنية و الرياضية
The effect of the think, pair, and share strategy of using educational movies on learning jumping opened legs and closed legs skills on vault in artistic gymnastics for women
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The research aimed at identifying the effect of the think, pair, and share strategy by using educational movies on learning jumping opened legs and closed legs skills on vault in artistic gymnastics for women. It also aimed at identifying the group that learned better the skills understudy. The researcher used the experimental method on second-grade College of Physical Education and Sport Sciences female students. Twelve female students were selected from each of the two sections to form the subjects of the study. The main program was applied for eight weeks with one learning session per week. The data was collected and treated using SPSS to conclude that the think, pair, and share strategy and the traditional program have positive effects

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Tourism Companies Assessment via Social Media Using Sentiment Analysis
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In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor

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Publication Date
Fri Sep 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Fuzzy Control of the Robotic Hands Catching Force Using Muscle Wires Actuator
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The aim of this research is controlling the amount of the robotic hand catching force using the artificial muscle wire as an actuator to achieve the desired response of the robotic hand in order to catch different things without destroying or dropping them; where the process is to be similar to that of human hand catching way. The proper selection of the amount of the catching force is achieved through out simulation using the fuzzy control technique. The mechanism of the arrangement of the muscle wires is proposed to achieve good force selections. The results indicate the feasibility of using this proposed technique which mimics human reasoning where as the weight of the caught peace increases, the force increases also with approximatel

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Simulation and Modelling of Electricity Usage Control and Monitoring System using ThingSpeak
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Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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