Search Results - (( using gamification learning algorithm ) OR ( basic classification problems algorithm ))

Open access for gamification: a systematic review of literature across disciplines by Zakaria, Noor Syamilah, Saripan, M. Iqbal, Subarimaniam, Neerushah, Ismail, Alyani

“…With the increasing need for developing effective learning methods, gamification has been widely used as a tool to improve the desire and interest in learning. …”
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Self learning module on securing IPV6 deployment / Muhamad Nazif Shahaimi Zaha by Zaha, Muhamad Nazif Shahaimi

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Text classification using Naive Bayes: An experiment to conference paper by Sainin, Mohd Shamrie

“…The basic text classification technique in forum application has been discussed in Sainin (2005a) and Sainin (2005b).The paper explains about the use of the basic naïve Bayes algorithm to classify forum text me ssages into two classes namely clean and bad. …”
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Gamification of Regional Tourism Engagement: Analysis and Design of a Web-Based Information System by Johannes Hamonangan, Siregar, Rufman Iman, Akbar, Augury, El Rayeb, Chaerul, Anwar, Suriati Khartini, Jali, Mohamad Imran, Bandan, Phei Chin, Lim, Abby Lian, Hendrick

“…The system integrates a structured gamification algorithm with a scalable relational database model, built using React.js and Firebase, to ensure responsive and consistent user experiences. …”
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Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar by Abu Bakar, Nordin

“…The knowledge will be stored, used, referred, postulated and reasoned with. Those activities define learning in its own specific domain and context. …”
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Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance by Nor Azlan, Nor Asmaa Alyaa

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Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

“…Those problems lend themselves to the realm of optimization. …”
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Recent Advances in Classification of Brain Tumor from MR Images – State of the Art Review from 2017 to 2021 by Ghazanfar, Latif, Faisal Yousif, Al Anezi, Dayang Nurfatimah, Awang Iskandar, Abul, Bashar, Jaafar, Alghazo

“…The complex nature of the brain tissue makes the problem of locating, segmenting, and ultimately classifying Magnetic Resonance (MR) images a complex problem. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…This reserarch adapted a methodology of computer vision and algorithms that exploit image segmentation, feature extraction and fuzzy classification to guide the research activities. …”
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Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli by Ramli, Muhammad Harith

“…Bat algorithm is chosen for the development of the prototype for segmentation and classification purpose. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

“…The two approaches were applied to image pattern recognition problems. The RSNN was applied to automatic target recognition problem. …”
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Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques by Arif Z.H., Mahmoud M.A., Abdulkareem K.H., Mohammed M.A., Al-Mhiqani M.N., Mutlag A.A., Dama�evi?ius R.

Review of deep convolution neural network in image classification by Al-Saffar, Ahmed Ali Mohammed, Tao, Hai, Mohammed, Ahmed Talab

“…Finally, some problems in the current research are briefly summarized and discussed, and the new direction of future development is forecasted…”
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer by Tehseen Mazhar, Inayatul Haq, Allah Ditta, Syed Agha Hassnain Mohsan, Faisal Rehman, Imran Zafar, Jualang Azlan Gansau, Lucky Poh Wah Goh

“…This article describes the fundamentals of ML-based implementations, as well as future limits and concerns for the production of skin cancer detection and classification systems. We also explored five fields of dermatology using deep learning applications: (1) the classification of diseases by clinical photos, (2) der moto pathology visual classification of cancer, and (3) the measurement of skin diseases by smartphone applications and personal tracking systems. …”
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Systematic review and meta-analysis on the classification metrics of machine learning algorithm based radiomics in hepatocellular carcinoma diagnosis by Mohd Haniff, Nurin Syazwina, Ng, Kwan Hoong, Kamal, Izdihar, Mohd Zain, Norhayati, Abdul Karim, Muhammad Khalis

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Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

A modified reweighted fast consistent and high-breakdown estimator for high-dimensional datasets by A. Baba, Ishaq, Midi, Habshah, June, Leong W., Ibragimov, Gafurjan

“…Outlier detection and classification algorithms play a critical role in statistical analysis. …”
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Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

“…In the development of the “hybrid AI-based” classification models, the proposed model (K1-K2- NN), was basically introduced through combining AI approaches of modified K-NN, genetic algorithm (GA), Fisher’s discriminant ratio (FDR) and class separability criteria (CSC). …”
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Early detection of spots high water saturation for landslide prediction using thermal imaging analysis by Ghazali, K. H., Mohd Falfazli, Mat Jusof, Muhammad, Badaruddin, Jadin, Mohd Shawal

“…The performance of these segmentation algorithms are measured using misclassification error. …”
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Fuzzy C means imputation of missing values with ant colony optimization by Mausor, F.H., Jaafar, J., Mohdtaib, S.

“…This paper proposes a improved method of imputation by employing a new version of Fuzzy c Means (FCM) which hybridized with Evolutionary Algorithm to handle missing values problem. Missing values can be treated by imputing the values. …”
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