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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…Among Information Technology graduates, Java programming assignments is an essential part of learning programming as it trains the student to solve programming assignments so that they can improve their programming skills that is useful in their professional life after graduation. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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Object-Oriented Programming semantics representation utilizing agents
Published 2011“…Learning programming from source code examples is a common behavior among novices. …”
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Cognitive benefits of employing multiple AI voices as specialist virtual tutors in a multimedia learning environment
Published 2025“…To address this gap, we draw on multimedia learning and cognitive models to investigate the effects of using multiple AI voices as specialist virtual tutors for distinct programming algorithm subtopics on cognitive load and learning outcomes. …”
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ProCAss: An intelligent assessment for computer programming corpus
Published 2005“…Then, the ability of LSA algorithm in grading computer program corpus will be evaluated.The grading process will not limited on certain programming languages, but on any programming languages.…”
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Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging
Published 2022“…Nonetheless, a robust DCNN model was achieved as there is no sign of the model’s over-or under-ftting upon the learning process. Conclusions: The application of digital imaging and deep learning techniques used by the DP-AC and convolutions neural network algorithms to segment and identify premolars provides promising results for semi-automated forensic dental staging in the future…”
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STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION
Published 2021“…In this paper, we proposed profound learning strategy to address three primary assignments developing in the zone of skin lesion picture preparation, i.e., dermoscopic highlight, extraction and detection. …”
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Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering
Published 2022“…Objective: Fuzzy clustering algorithm is a partition method used to assign objects from a data set to a cluster by marking the average location. …”
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A framework for a multi-layered security of an automated programming code assessment tool
Published 2024journal::journal article -
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis
Published 2025“…These re suggest that machine learning driven approaches can effectively support academic administrations in making informed staffing decisions, balancing full time and part time lecturer assignments, and optimizing cost structures without compromising teaching quality. …”
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Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad
Published 2022“…The semi-automated dental staging system developed in this study is based on the Malay children’s population and uses a brain-inspired learning algorithm termed "deep learning". The methodology is comprised of four major steps: image preprocessing, which adheres to the inclusion criteria for panoramic dental radiographs, segmentation, and classification of mandibular premolars according to Demirjian's staging system using the Dynamic Programming-Active Contour (DP-AC) method and Deep Convolutional Neural Network (DCNN), respectively, and statistical analysis. …”
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Propositional satisfiability method in rough classification modeling for data mining
Published 2002“…Two models, Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) to represent the minimal reduct computation problem were proposed. …”
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