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Factors Affecting the Students' Choice of a Major at King Abdulaziz University
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The present study aimed at examining the factors that affect the choice of A major among a sample of BA fe(male) students at the levels 3-8 in King Abdulaziz University (KAU), in Jeddah, Saudi Arabia. To meet this objective, a descriptive survey method was used together with a questionnaire that consisted of 4 axes to answer the central question: What are the factors affecting the choice of a major at the university? Results have shown that the item that measured the students’ ability to choose the major ranked (First); it was concerned with the effect on the students' choice of his/her major in the university. On the last position and with respect to this effect came the professional tendencies and desires. Results have also shown that there were other differences of a statistical significance in favor of a literary major on the four axes of the questionnaire. Besides, there were no differences between the two sexes regarding the choice of a university major. The study has recommended the need for boosting the role of students' awareness, and  holding workshops and cultural courses after joining college, as well as introducing majors, their fields and the application of a professional tendency scale in the preparatory stage in the university.

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Topology-Based Modularity and Modularity Density for Detecting Protein Complexes: A Comparative Study
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     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

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Publication Date
Tue Dec 01 2020
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
A Haptic feedback system based on leap motion controller for prosthetic hand application
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Leap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F

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Publication Date
Fri Jan 01 2016
Journal Name
Machine Learning And Data Mining In Pattern Recognition
A New Strategy for Case-Based Reasoning Retrieval Using Classification Based on Association
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Publication Date
Sun Oct 07 2018
Journal Name
Al-kindy College Medical Journal
Risedronate as a therapeutic trial post-hysterectomy in premenopausal women to prevent osteoporosis
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Background: Osteoporosis is a skeletal defect manifested by a reduction of bone strength as a result of reduced bone mass to the extent that there is a higher risk of fracture even on minor trauma. Hysterectomy in a premenopausal woman is a well known cause of ovarian failure resulting in an increased risk of osteoporosis.

Objective : To clarify bisphosphonate's preventive effect on osteopenia and osteoporosis in premenopausal women after hysterectomy.

Type of the study: Cross –sectional study.

Method:  84 premenopausal females post hysterectomy aged between 40 – 50 years, were enrolled in this randomized controlled double blinded trail a

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Publication Date
Sat Oct 18 2025
Journal Name
Pattern Recognition And Artificial Intelligence
Utilizing Energy-Efficient Deep Learning Technique for Age Estimation Through a Hybrid Methodology
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This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

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Publication Date
Tue Jun 30 2015
Journal Name
Al-kindy College Medical Journal
Familial Pulmonary Alveolar Microlithiasis: A Rare Case Report with Emphasis on Imaging Findings
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ABSTRACT Pulmonary alveolar microlithiasis is rare infiltrative pulmonary disease characterized by intra-alveoli deposition of microliths. We present a familial case of an adult female with complaint of progressive shortness of breath on exertion. Chest radiograph showed innumerable tiny dense nodules, diffusely involving both lungs mainly the lower zones. High-resolution CT scan illustrated widespread intra-alveolar microliths, diffuse ground-glass attenuation areas and septal thickening predominantly in the basal regions. Chest radiograph is all that is needed for the diagnosis of this case but CT scan was done to demonstrate the extent and severity of this disease

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Publication Date
Tue Nov 01 2016
Journal Name
2016 International Conference On Advanced Mechatronic Systems (icamechs)
Hierarchical sliding mode control applied to a single-link flexible joint robot manipulator
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Trajectory tracking and vibration suppression are essential objectives in a flexible joint manipulator control. The flexible joint manipulator is an under-actuated system, in which the number of control actions is less than the degree of freedom to be controlled. It is very challenging to control the underactuated nonlinear system with two degree of freedom. This paper presents a hierarchical sliding mode control (HSMC) for a rotary flexible joint manipulator (RFJM). Firstly, the rotary flexible joint manipulator is modeled by two subsystems. Secondly, the sliding surfaces for both subsystems are constructed. Finally, the control action is designed based on the Lyapunov function. Computer simulation results demonstrate the effectiveness of

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Publication Date
Tue Oct 01 2019
Journal Name
Biochemical & Cellular Archives
A RE-SATURATION IMPACT ON SOIL RETENTION CURVE FOR FIVE DIFFERENT TEXTURED SOILS
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Soil water retention curves (SWRCs) are crucial for characterizing soil moisture dynamics and are particularly relevant in the context of irrigation management. A study was carried out to obtain the SWRC, inflection point, S index, pore size distribution curve, macro porosity, and air capacity from samples submitted to saturation and re-saturation processes. Five different-texture disturbed soil samples Sandy Loam, Loam, Sandy Clay Loam, Silt Loam, and Clay were collected. After obtaining SWRC, each air-dried soil samples were submitted to particle size distribution and clay dispersed in water analyses to verify the soil lost clay. The experimental design was completely randomized with three replications using two processes of SWRC (saturat

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
Quadrupole Moment & Deformation Parameter for Even-Even 38Sr (A=76-102) Nuclide
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Publication Date
Thu Jun 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A missing data imputation method based on salp swarm algorithm for diabetes disease
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

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