Search Results - (( learning interaction tests algorithm ) OR ( java implication based algorithm ))

Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

“…The analysis of learning problems shows the unavailability of interactive learning media that can support various learning styles of students in programming algorithm materials. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

“…Combinatorial interaction testing is a practical approach aims to detect defects due to unwanted and faulty interactions. …”
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Machine learning model for performance prediction in mobile network management / Muhammad Hazim Wahid by Wahid, Muhammad Hazim

“…The methodology includes drive test measurement for data collection, exploratory data analysis, data preparation, and applying machine learning algorithms to predict mobile network performance. …”
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Interactive framework for dynamic modelling and active vibration control of flexible structures by Mat Darus, Intan Zaurah, Mohd. Hashim, Siti Zaiton, Tokhi, M. O.

“…The design and implementation of the interactive learning system incorporating the simulation algorithms, modelling and control strategies, are developed using MATLAB. …”
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The impact of virtual reality on programming algorithm courses on student learning outcomes by Dewi, Ika Parma, Ambiyar, Effendi, Hansi, Giatman, Muhammad, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

“…Therefore, learning with VR effectively improves student learning outcomes on programming algorithm materials. …”
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Pairwise Test Suite Generation Using Adaptive Teaching Learning-Based Optimization Algorithm with Remedial Operator by Fakhrud, Din, Kamal Z., Zamli

“…Being a NP-complete problem, pairwise test suite generation problem has been addressed using several meta-heuristic algorithms including the Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm in the literature. …”
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An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications. by S. Ahmed, Bestoun, Enoiu, Eduard, Afzal, Wasif, Kamal Z., Zamli

“…Addressing this issue, we propose to integrate the memory into EMCQ for combinatorial t-wise test suite generation using reinforcement learning based on the Q-learning mechanism, called Q-EMCQ. …”
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User interface and interactivity design guidelines of algorithm visualization on mobile platform by Supli, Ahmad Affandi

“…Moreover, the evaluation of the effectiveness of the AVOMP prototype from 35 participants through laboratory experiments based on the bloom taxonomy test shows that there is a significant difference between students learning sorting algorithms using the manual approach (Pre-Test) and the AVOMP app (Post-Test). …”
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Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…In the future, different types of deep learning algorithms need to be applied, and different datasets can be tested with different hyper-parameters to produce more accurate ASD classifications.…”
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Fuzzy adaptive teaching learning-based optimization strategy for pairwise testing by Din, Fakhrud, Kamal Z., Zamli

“…Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm is an improved form of Teaching Learning-based Optimization (TLBO) algorithm. …”
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Integrating of web 2.0 technologies for interactive courseware : data structure and algorithm as case study by Mohd Nurhafeezi, Nordin

“…Besides that, the research also aims to develop a prototype for Interactive Courseware using Web 2.0 by integrating Web 2.0 technologies and services and lastly to evaluate the effectiveness and the usability of the project by comparing the pre-test and post-test result and surnmative evaluation respectively. …”
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An interactive C++ programming courseware (SIFOO) / Mazliana Hasnan … [et al.] by Hasnan, Mazliana, Othman, Zainab, Mohamad, Norizan, Abdullah, Zamlina

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Hyper-heuristic strategy for input-output-based interaction testing by Din, Fakhrud, Kamal Zuhairi, Zamli

“…However, existing t-way strategies for input-output-based relationship (IOR) interaction testing mostly adopt greedy algorithms which often generate poor quality test data. …”
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

“…The use of meta-heuristic algorithms as the basis for t-way (where t indicates the interaction strength) and mixed strength testing strategies is common in recent literature. …”
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Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function by Tan, Min Keng

“…The dynamic environment causing the need of dynamic modelling for better dynamic optimisation will be catered via a specifically formulated interactive fitness function. The interactive metamodel is extracted using Q-Learning (QL) via online observing and learning of the outflow-inflow traffic characteristics. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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A comparative study of interactive segmentation with different number of strokes on complex images by Kok, Luong Goh, Giap, Weng Ng, Muzaffar Hamzah, Soo, See Chai

“…The most common user input type in interactive segmentation is using strokes. The different number of strokes are utilized in each different interactive segmentation algorithms. …”
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A Comparative Study of Interactive Segmentation with Different Number of Strokes on Complex Images by Goh, Kok Luong, Ng, Giap Weng, Muzaffar, Hamzah, Chai, Soo See

“…The most common user input type in interactive segmentation is using strokes. The different number of strokes are utilized in each different interactive segmentation algorithms. …”
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Identifying Cyberspace Users� Tendency in Blog Writing Using Machine Learning Algorithms by AbuSalim, S.W.G., Mostafa, S.A., Mustapha, A., Ibrahim, R., Wahab, M.H.A.

“…The algorithms are Decision Tree (c4.5), Linear Regression (LR), and Decision Forest (DF) with a 10-fold cross-validation method for training and testing. …”
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Development of deep reinforcement learning based resource allocation techniques in cloud radio access network by Amjad, Iqbal

“…A step towards long network performance optimization is theterm use of deep reinforcement learning (DRL), which can learn the best policy via interaction with the environment. …”
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