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  1. 1
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  2. 2
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  3. 3
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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  4. 4
    An Improved Algorithm for Prediction of Young's Modulus of Wood Plastic Composites

    An Improved Algorithm for Prediction of Young's Modulus of Wood Plastic Composites by Gupta, Ritu, Norrozila, Sulaiman, Gupta, Arun

    Published 2013
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  5. 5
    Real-time algorithmic music composition application.

    Real-time algorithmic music composition application. by Yap, Alisa Yi Hui

    Published 2022
    “…Due to time constraints, the development of this system uses a form of RAD development model, namely the phased development model. …”
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    Final Year Project / Dissertation / Thesis
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  6. 6
    Inelastic analysis of composite sections

    Inelastic analysis of composite sections by Thanoon, Waleed Abdulmalik, M. Hamed, Ahmed M., Noorzaei, Jamaloddin, Jaafar, Mohd Saleh, Al-Silayvani, Bayar J.

    Published 2004
    “…This paper describes the development of a numerical algorithm used for the inelastic analysis of composite sections subjected to combined axial force and bending moment. …”
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  7. 7
    Enhancement of Single and Composite Images Based on Contourlet Transform Approach

    Enhancement of Single and Composite Images Based on Contourlet Transform Approach by Melkamu, Hunegnaw Asmare

    Published 2009
    “…Image enhancement is an imperative step in almost every image processing algorithms. Numerous image enhancement algorithms have been developed for gray scale images despite their absence in many applications lately. …”
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  8. 8
    Finding an effective classification technique to develop a software team composition model

    Finding an effective classification technique to develop a software team composition model by Gilal, Abdul Rehman, Jaafar, Jafreezal, Capretz, Luiz Fernando, Omar, Mazni, Basri, Shuib, Abdul Aziz, Izzatdin

    Published 2017
    “…Ineffective software team composition has become recognized as a prominent aspect of software project failures.Reports from results extracted from different theoretical personality models have produced contradicting fits, validity challenges, and missing guidance during software development personnel selection.It is also believed that the technique/s used while developing a model can impact the overall results.Thus, this study aims to: 1) discover an effective classification technique to solve the problem, and 2) develop a model for composition of the software development team.The model developed was composed of three predictors: team role, personality types, and gender variables; it also contained one outcome: team performance variable.The techniques used for model development were logistic regression, decision tree, and Rough Sets Theory (RST).Higher prediction accuracy and reduced patte rn complexity were the two parameters forselecting the effective technique.Based on the results, the Johnson Algorithm (JA) of RST appeared to be an effective technique for a team composition model.The study has proposed a set of 24 decision rules for finding effective team members.These rules involve gender classification to highlight the appropriate personality profile for software developers.In the end, this study concludes that selecting an appropriate classification technique is one of the most important factors in developing effective models.…”
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  9. 9
    Finding an effective classification technique to develop a software team composition model

    Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

    Published 2018
    “…Based on the results, the Johnson algorithm (JA) of RST appeared to be an effective technique for a team composition model. …”
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  10. 10
    Finding an effective classification technique to develop a software team composition model

    Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

    Published 2018
    “…Based on the results, the Johnson algorithm (JA) of RST appeared to be an effective technique for a team composition model. …”
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  11. 11
    DEVELOPMENT OF COMPOSITIONAL MODEL FOR PREDICTING VISCOSITY OF CRUDE OILS USING POLYNOMIAL NEURAL NETWORKS (PNN) INDUCED BY GROUP METHOD OF DATA HANDLING (GMDH)

    DEVELOPMENT OF COMPOSITIONAL MODEL FOR PREDICTING VISCOSITY OF CRUDE OILS USING POLYNOMIAL NEURAL NETWORKS (PNN) INDUCED BY GROUP METHOD OF DATA HANDLING (GMDH) by Wen Pin, Yong

    Published 2011
    “…GMDH is an inductive algorithm for computer-based mathematical modeling using neural network with active neurons that optimizes model coefficients for predetermine mathematical equation and selects the optimal model complexity. …”
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    Final Year Project
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  12. 12
    Tool wear prediction models during end milling of glass fibre-reinforced polymer composites

    Tool wear prediction models during end milling of glass fibre-reinforced polymer composites by Azwan Iskandar, Azmi, Lin, Richard J.T., Bhattacharyya, Debes

    Published 2013
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  13. 13
    Modeling approach of cloud 4D printing service composition optimization based on non-dominated sorting genetic algorithm III

    Modeling approach of cloud 4D printing service composition optimization based on non-dominated sorting genetic algorithm III by Liu, Jiajia, Zainudin, Edi Syams, As'arry, Azizan, Ismail, Mohd Idris Shah

    Published 2024
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  14. 14
    Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam

    Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam by Toghroli, Ali, Suhatril, Meldi, Ibrahim, Zainah, Safa, Maryam, Shariati, Mahdi, Shamshirband, Shahaboddin

    Published 2018
    “…Moreover, achieved results indicated that the developed ELM models can be used with confidence for further work on formulating novel model predictive strategy in shear strength and ductility of steel concrete composite. …”
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  15. 15
    A study of progressive damage detection in thin-walled composite structures using an embedded fiber Bragg grating – acoustic emission hybrid system

    A study of progressive damage detection in thin-walled composite structures using an embedded fiber Bragg grating – acoustic emission hybrid system by Mohd Hafizi, Zohari

    Published 2019
    “…Finally, a signal processing algorithm was developed to locate flaws / damages and also identify the condition of a thin composite structures. …”
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    Research Report
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  16. 16
    A comparative study on various ANN optimization algorithms for magnetorheological elastomer carbonyl iron particle concentration estimation

    A comparative study on various ANN optimization algorithms for magnetorheological elastomer carbonyl iron particle concentration estimation by Kasma Diana, Saharuddin, Mohd Hatta, Mohammed Ariff, Bahiuddin, Irfan, Nurhazimah, Nazmi, Mohd Azizi, Abdul Rahman, Mohd Ibrahim, Shapiai, Fauzan, Ahmad, Sarah Atifah, Saruchi

    Published 2024
    “…Various optimization algorithms have been employed such as Adam, RMSprop, SGD, AdaGrad, and Nadam throughout the modelling process. …”
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  17. 17
    A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market

    A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market by Mohd. Ridzuan Ab. Khalil, Azuraliza Abu Bakar

    Published 2023
    “…This study aims to develop a univariate and multivariate stock market forecasting model using three deep learning algorithms and compare the performance of those models. …”
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  18. 18
    Statistical modeling of the electromechanical behaviour of BI-2223 composite wires

    Statistical modeling of the electromechanical behaviour of BI-2223 composite wires by Muhammad Faris Fuaad

    Published 2024
    text::Final Year Project
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  19. 19
    Artificial neural networks for burst pressure strength of corroded subsea pipelines repaired with composite fiber-reinforced polymer patches / Mohd Fakri Muda

    Artificial neural networks for burst pressure strength of corroded subsea pipelines repaired with composite fiber-reinforced polymer patches / Mohd Fakri Muda by Muda, Mohd Fakri

    Published 2023
    “…Developing an effective prediction model that utilizes Artificial Neural Networks (ANN) to correlate with the repaired assessment method, particularly composite FRP, can potentially overcome these limitations. …”
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  20. 20
    Development of a predictive model for estimating the specific heat capacity of metallic oxides/ethylene glycol-based nanofluids using support vector regression

    Development of a predictive model for estimating the specific heat capacity of metallic oxides/ethylene glycol-based nanofluids using support vector regression by Olanrewaju, Alade A., Abd Rahman, Mohd Amiruddin, Aliyu, Bagudu, Abbas, Zulkifly, Yaakob, Yazid, A. Saleh, Tawfik

    Published 2019
    “…So far, two correlations have been developed to estimate the The accuracies of these models are still subject to further improvement for many nanofluid compositions. …”
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