Search Results - (( java implementation learning algorithm ) OR ( based classification force algorithm ))

Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Enhancing benthic habitat mapping: A review of integrating satellite and side scan sonar data for improved classification accuracy by Yeong, Wei Yi, Chong, Wei Sheng, Ching Hue, Imelus Nius

“…Research on classification methods shows that object-based approaches produce different results depending on field conditions, which are consistently better than pixel-based methods, for both satellite spectral and side-scan sonar data. …”
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Classification models for higher learning scholarship award decisions by Wirawati Dewi Ahmad, Azuraliza Abu Bakar

“…A dataset of successful and unsuccessful applicants was taken and processed as training data and testing data used in the modelling process. Five algorithms were employed to develop a classification model in determining the award of the scholarship, namely J48, SVM, NB, ANN and RT algorithms. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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A wheelchair sitting posture detection system using pressure sensors by Mohamad Yusoff, Muhammad Annuar Alhadi, Azmi, Nur Liyana, Nordin, Nor Hidayati Diyana

“…All the classification algorithms were evaluated by using the k-fold cross validation method. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Improving automatic forced alignment for phoneme segmentation in Quranic recitation by Alqadasi, Ammar Mohammed Ali, Khedher, Akram M Z M, Sunar, Mohd Shahrizal, Hj Salam, Md. Sah, Abdulghafor, Rawad, Khaled, Nashwan Abdo

“…These enhancements encompass the adaptation of an acoustic model tailored for Qur’anic recitation as preprocessing and culminate in the development of an algorithm aimed at refining forced alignment based on the phonetic nuances of the Qur’an. …”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…Specifically, it can go beyond the regular generic description of a plant, integrating the organ-specific features together with the generic features to explicitly force the designed network to focus on the organ regions during species classification. …”
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A review of classification techniques for electromyography signals by Mohd Saad, Norhashimah, Omar, Siti Nashayu, Abdullah, Abdul Rahim, Shair, Ezreen Farina, H.Rashid

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Talkout : Protecting mental health application with a lightweight message encryption by Gavin Teo Juen

“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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CAGDEEP : Mobile malware analysis using force atlas 2 with strong gravity call graph and deep learning by Nur Khairani, Kamarudin, Ahmad Firdaus, Zainal Abidin, Azlee, Zabidi, Mohd Faizal, Ab Razak

“…Afterwards, this study adopts Convolutional Neural Network (CNN) for malware detection and classification algorithm. We compare CAGDeep with a state-of-the-art Android malware detection approach. …”
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Automated classification radiograph of Periodontal bone loss using deep learning by Al Husaini, Mohammed Abdulla Salim, Habaebi, Mohamed Hadi, Yadav, Seema

“…This study highlights the potential of deep learning-based OPG classification systems to assist dental professionals in faster and more accurate detection of periodontal diseases.…”
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Handgrip strength evaluation using neuro fuzzy approach by Seng, W.C., Chitsaz, M.

“…The results indicate that the classification accuracy of normal and pathological patients are 90 and 75 respectively. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition by Burhan, Nuradebah

“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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Digital economy tax compliance model in Malaysia using machine learning approach by Raja Azhan Syah Raja Wahab, Azuraliza Abu Bakar

“…The experimental results show that the ensemble method can improve the single classification model’s accuracy with the highest classification accuracy of 87.94% compared to the best single classification model. …”
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Robust and reliable dual the classification system with error compensation module by Ahmad Nasiruddin, Ab Razak

“…An automatic vehicle classification system (AVC) has been developed in order to mitigate the problem based on the classes defined by Malaysian Highway Authority (MHA). …”
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