Search Results - (( program learning task algorithm ) OR ( java application sensor algorithm ))
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1
Case Slicing Technique for Feature Selection
Published 2004“…The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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Thesis -
2
Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension
Published 2015“…It is found that the interrelated tasks in the programming process, with its various abstractions, and timing in delivering the feedback, need to be addressed with the equal attention in learning to program. …”
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3
Computational Thinking (Algorithms) Through Unplugged Programming Activities: Exploring Upper Primary Students’ Learning Experiences
Published 2021“…A total of 31 students from a rural primary school were exposed to the learning about the algorithm concept (an aspect of CT skills) via UPA learning materials. …”
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4
A preliminary study of difficulties in learning java programming for secondary school
Published 2020“…One of the problems is students have difficulty in certain subtopics of programming. Coding to a specific task by using much complex algorithm is not an easy task as student needs to understand and know how to use it to solve a problem. …”
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5
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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6
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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7
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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Computational Thinking Through Unplugged Programming Activities : Exploring Students’ Learning Experiences
Published 2019“…CT skills can be taught via computing activities that involve different types of programming tasks or via Unplugged Programming Activities (UPA) that do not involve the use of digital devices to represent and deliver programming concepts. …”
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9
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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A new domain specific scripting language for automated machine learning pipeline
Published 2019“…This paper concerns on two difficulties faced by non-expertsâ�� users in the utilization of machine learning; design of the model and the programming task for implementation. …”
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Current applications of machine learning in dentistry
Published 2022“…Machine learning (ML), a subset of AI was described as an algorithm with the ability to "learn" by identifying patterns in a large dataset (Rowe, 2019). …”
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Book Chapter -
13
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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Artificial Intelligence (AI) in the art and design industry / Fahmi Samsudin
Published 2023“…It encompasses different types, such as rule-based AI using if-then statements for decision-making, machine learning which employs algorithms to analyze and learn from data, and deep learning utilizing artificial neural networks to learn from extensive datasets. …”
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An efficient and effective case classification method based on slicing
Published 2006“…The algorithms are: Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5). …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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A multi-depot vehicle routing problem with stochastic road capacity and reduced two-stage stochastic integer linear programming models for rollout algorithm
Published 2021“…A matheuristic approach based on a reduced two-stage Stochastic Integer Linear Programming (SILP) model is presented. The proposed approach is suitable for obtaining a policy constructed dynamically on the go during the rollout algorithm. …”
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Kernel methods and support vector machines for handwriting recognition
Published 2023“…Finding the solution hyperplane involves using quadratic programming which is computationally intensive. Algorithms for practical implementation such as sequential minimization optimization (SMO) and its improvements are discussed. …”
Conference paper -
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Design Of Robot Motion Planning Algorithm For Wall Following Robot
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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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