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  1. 1
    An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma

    An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma by Sani , Danjuma

    Published 2017
    “…Many normal parameter reduction algorithms exist to handle parameter reduction and maintain consistency of decision choices. …”
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    Thesis
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  2. 2
    Pairwise testing tools based on hill climbing algorithm (PTCA)

    Pairwise testing tools based on hill climbing algorithm (PTCA) by Lim, Seng Kee

    Published 2014
    “…The actual implementation of the algorithm which is in Java programming language, the program is implemented on Net Bean 7.0.1. …”
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    Undergraduates Project Papers
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  3. 3
    A novel normal parameter reduction algorithm of soft sets

    A novel normal parameter reduction algorithm of soft sets by Ma, Xiuqin, Norrozila, Sulaiman, Qin, Hongwu, Herawan, Tutut

    Published 2010
    “…In this paper, we propose a novel normal parameter reduction algorithm of soft sets based on the oriented-parameter sum, which can be carried out without parameter important degree and decision partition. …”
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  4. 4
    Application of a New Efficient Normal Parameter Reduction Algorithm of Soft Sets in Online Shopping

    Application of a New Efficient Normal Parameter Reduction Algorithm of Soft Sets in Online Shopping by Ma, Xiuqin, Hongwu, Qin

    Published 2014
    “…A new efficient normal parameter reduction algorithm of soft set in decision making was proposed. …”
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  5. 5
    New Parameter Reduction of Soft Sets

    New Parameter Reduction of Soft Sets by Ma, Xiuqin

    Published 2012
    “…However, the algorithm involves a great amount of computation. In this thesis, a New Efficient Normal Parameter Reduction algorithm (NENPR) of soft sets is proposed based on the new theorems, which have been proved and presented. …”
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  6. 6
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…The circuits have been designed by proteus, the microcontrollers have been programmed by micro C, and the Graphical User Interface (GUI) has been implemented in Java. Few by electronic components such as RFID, multiplexer, XBee, and servo motors have been used to realize the system. …”
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  7. 7
    Modelling of multi-robot system for search and rescue

    Modelling of multi-robot system for search and rescue by Poy, Yi Ler

    Published 2023
    “…In conclusion, this project shows that the MPSO algorithm is capable of generating a better path compared to the normal PSO algorithm in terms of average path length and execution time, making it a promising algorithm for multi-robot path planning in dynamic environments.…”
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    Final Year Project / Dissertation / Thesis
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  8. 8
    Talkout : Protecting mental health application with a lightweight message encryption

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

    Published 2022
    “…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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    Academic Exercise
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  9. 9
    Identification of vocal and voice disorders

    Identification of vocal and voice disorders by Murugesa Pandiyan, Paulraj, Prof. Madya Dr., Sazali, Yaacob, Prof. Dr., Mohd Rizon, Mohammed Juhari, Prof. Dr., Sivanandam, S. N., Muthusamy, Hariharan, Dr.

    Published 2011
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    Working Paper
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  10. 10
    Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms

    Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms by Ahmad Pouradabi, Amir Rastegarnia, Azam Khalili, Ali Farzamnia

    Published 2022
    “…Diffusion normalized least mean square (DNLMS) algorithm has low misadjustment error, but it is slow in convergence. …”
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    Proceedings
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  11. 11
    Design & Development of a Robotic System Using LEGO Mindstorm

    Design & Development of a Robotic System Using LEGO Mindstorm by Abd Manap, Nurulfajar, Md Salim, Sani Irwan, Haron, Nor Zaidi

    Published 2006
    “…The system is capable in operating an off-line programming method, starting from its programming sequences until robotic implementation of the program. During early stages, the research is emphasis more towards designing a robotic system using RoboLab software and C++ programming language. …”
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  12. 12
    The normalized random map of gradient for generating multifocus image fusion

    The normalized random map of gradient for generating multifocus image fusion by Ismail, ., Kamarul Hawari, Ghazali

    Published 2020
    “…This data has a significant role in predict the initial focus regions. The proposed algorithm successes to supersede difficulties of mathematical equations and algorithms. …”
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  13. 13
    Dynamic robust bootstrap method based on LTS estimators

    Dynamic robust bootstrap method based on LTS estimators by Midi, Habshah, Uraibi, Hassan Sami, Al-Talib, Bashar Abdul Aziz Majeed

    Published 2009
    “…In order to make reliable inferences about the parameters of a model, require that the parameter estimates are normally distributed. …”
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  14. 14
    Data Hiding Techniques In Digital Images

    Data Hiding Techniques In Digital Images by Al Thloothi, Salah Ramadan

    Published 2003
    “…After all these studies, one of the algorithms in the masking technique is developed and implemented using JAVA program to embed message into true color image with a good quality and higher capacity. …”
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  15. 15
    Adaptive Traffic Prioritization Algorithm Over Ad Hoc Network Using IEEE 802.11e

    Adaptive Traffic Prioritization Algorithm Over Ad Hoc Network Using IEEE 802.11e by Anuar, Ammar

    Published 2016
    “…Each AC has its own queue and set of EDCA parameter values. Although IEEE 802.11e has been widely implemented in commercial hardware, the EDCA parameters are normally preset with some default values recommended by the standard. …”
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  16. 16
    Multi-floor indoor location estimation system based on wireless local area network

    Multi-floor indoor location estimation system based on wireless local area network by Chua, Tien Han

    Published 2007
    “…Before developing the system, study on characteristics of RSS is conducted to help the design, development and implementation of the proposed system. The proposed system is then designed and developed using Java programming language. …”
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  17. 17
    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah

    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

    Published 2017
    “…Results suggest that the PSO algorithm is viable alternative to other established algorithms for LLS parameter estimation. …”
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  18. 18
    Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan

    Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan by Hassan, Siti Fatimah

    Published 2015
    “…For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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  19. 19
    Smart diagnosis of long bone tumor / Mazni Parimin

    Smart diagnosis of long bone tumor / Mazni Parimin by Parimin, Mazni

    Published 2005
    “…Here, backpropagation training algorithm will be used and network parameters will be set. …”
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    Student Project
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  20. 20
    Statistical approach on grading: mixture modeling

    Statistical approach on grading: mixture modeling by Md. Desa, Zairul Nor Deana

    Published 2006
    “…In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
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