Search Results - (( using interactive matching algorithm ) OR ( java application optimisation algorithm ))

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    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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    Scan Matching and KNN Classification for Mobile Robot Localisation Algorithm by Addie Irawan, Hashim, Marni Azira, Markom, Abdul Hamid, Adom, Mohd Muslim Tan, E. S.

    Published 2017
    “…The localisation algorithm is developed using scan matching method which is incorporated with K-nearest neighbours (KNN) classification. …”
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    Investigation And Development Of Flattening Algorithms For Curved Latent Fingerprint Images by Chong, Bei Wei

    Published 2015
    “…Boundary of interested area can be acquired using a predefined algorithm or define by user using interactive drawing. …”
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    Sports tournament scheduling using genetic algorithm / Hafeezur Syakir Abdul Motok@Mohd Ridzuan by Abdul Motok@Mohd Ridzuan, Hafeezur Syakir

    Published 2020
    “…The phase in RAD such as planning requirements, user design, rapid construction and cutover is used during development. RAD highlights on user interaction and quick development of the system using prototypes. …”
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    Instance matching framework for heterogeneous semantic web content over linked data environment by Mansir, Abubakar

    Published 2021
    “…This framework adapted the methods used in the benchmark studies with additional components and modifications in some existing components to boost the matching performance. …”
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    Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite by Suali, Anjila J., Nuraminah Ramli, Rozmie Razif Othman, Hasneeza Liza Zakaria, Iszaidy Ismail, Nor Shahida Mohd Jamail, Rimuljo Hendradi, Nurol Husna Che Rose

    Published 2025
    “…Experimental results indicate that WOA outperforms or matches the effectiveness of these strategies in generating smaller test suites, particularly for higher interaction strengths. …”
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    Sequence t-way test generation using the barnacles mating optimizer algorithm by Kamal Z., Zamli, Kader, Md. Abdul

    Published 2021
    “…More precisely, we focus on the generation of test cases due to the ordering of inputs (or sequence) using the newly developed Barnacles Mating Optimizer (BMO) Algorithm. …”
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    PHASE AMBIGUITY REDUCTION IN LASER INTERACTED INTERFEROGRAMS by Yahaya, Asiah, Munajat, Yusof

    Published 2006
    “…Phase measurement of laser interaction is often plagued with ambiguity when analyzed using single interferogram. …”
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    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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    Online food ordering application using Boyer-Moore algorithm / Muhammad Zulhilmie Dzulkifli by Dzulkifli, Muhammad Zulhilmie

    Published 2021
    “…The main goal of this study is to create an online food ordering app using the corresponding Boyer-Moore string matching algorithm. …”
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    Career recommender system in Malaysia using content-based filtering / Muhammad Luqman Shamsul by Shamsul, Muhammad Luqman

    Published 2025
    “…This project focuses on developing a career recommender system tailored to the Malaysian job market using content-based filtering algorithms. The system aims to address challenges in career planning, such as lack of personalized guidance and information overload, by analyzing users' skills, educational background, and preferences. …”
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    SRcS: Smartphone Recommendation System using genetic algorithm / Nursalsabiela Affendy Azam by Affendy Azam, Nursalsabiela

    Published 2020
    “…The technique used is Genetic Algorithm where the user input will be the smartphone specification preferences and budget so these inputs will be processed through Genetic Algorithm and a list of optimum results will be obtained. …”
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    Human Spontaneous Emotion Detection System by Radin Monawir, Radin Puteri Hazimah

    Published 2018
    “…Having smart computerized system which can understand and instantly gives appropriate response to human is the utmost motive in human and computer interaction (HCI) field.It is argued either HCI is considered advance if human could not have natural and comfortable interaction like human to human interaction.Besides,despite of several studies regarding emotion detection system, current system mostly tested in laboratory environment and using mimic emotion.Realizing the current system research lack of real life or genuine emotion input,this research work comes up with the idea of developing a system that able to recognize human emotion through facial expression.Therefore,the aims of this study are threefold which are to enhance the algorithm to detect spontaneous emotion,to develop spontaneous facial expression database and to verify the algorithm performance.This project used Matlab programming language,specifically Viola Jones method for features tracking and extraction,then pattern matching for emotion classification purpose.Mouth feature is used as main features to identify the emotion of the expression.For verification purpose,the mimic and spontaneous database which are obtained from internet,open source database or novel (own) developed databases are used.Basically,the performance of the system is indicated by emotion detection rate and average execution time.At the end of this study,it is found that this system is suitable for recognizing spontaneous facial expression (63.28%) compared to posed facial expression (51.46%).The verification even better for positive emotion with 71.02% detection rate compared to 48.09% for negative emotion detection rate.Finally,overall detection rate of 61.20% is considered good since this system can execute result within 3s and use spontaneous input data which known as highly susceptible to noise.…”
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