Search Results - (( developing using sparse algorithm ) OR ( java application mining algorithm ))

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

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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    Article
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    Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field by Toh, Cheng Chuan

    Published 2018
    “…Theoretically,β and α is parameters that used to vary the NMF2D algorithm in order to yield high SDR value. …”
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    Thesis
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    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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    Conference or Workshop Item
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    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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    Final Year Project / Dissertation / Thesis
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    Proximal linearized method for sparse equity portfolio optimization with minimum transaction cost by Sim, Hong Seng, Ling, Wendy Shin Yie, Leong, Wah June, Chen, Chuei Yee

    Published 2023
    “…The efficiency of the algorithm is demonstrated using real stock data and the model is promising in portfolio selection in terms of generating higher expected return while maintaining good level of sparsity, and thus minimizing transaction cost.…”
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    Article
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    Identification of the continuous-time Hammerstein models with sparse measurement data using improved marine predators algorithm by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Zaharuddin, Mohamed

    Published 2024
    “…In contemporary industrial applications, the complexity of systems often makes it challenging to create precise models using first-principle approaches. Consequently, researchers have turned to data-driven modeling, which offers the key advantage of developing a mathematical model of the system entirely from the input–output data captured from an actual plant. …”
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    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

    Published 2022
    “…Then, the feature selection process is performed using sparse fuzzy-c-means (FCM) for selecting significant features to classify medical data. …”
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    Thesis
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    Speech compression using compressive sensing on a multicore system by Gunawan, Teddy Surya, Khalifa, Othman Omran, Shafie, Amir Akramin, Ambikairajah, Eliathamby

    Published 2011
    “…Compressive sensing is a new paradigm of acquiring signals, fundamentally different from uniform rate digitization followed by compression, often used for transmission or storage. In this paper, a novel algorithm for speech coding utilizing CS principle is developed. …”
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    Proceeding Paper
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    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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    Thesis
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    Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

    Published 2010
    “…Since rerunning the mining algorithms from scratch can be very time consuming, researchers have introduced interactive mining to find proper patterns by using the current mining model with various minsup. …”
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    Hardware development of autonomous mobile robot based on actuating lidar by Mohd Romlay, Muhammad Rabani, Mohd Ibrahim, Azhar, Toha, Siti Fauziah, Rashid, Muhammad Mahbubur, Ahmad, Muhammad Syahmi

    Published 2022
    “…As opposed to a point cloud generated from high-end LiDAR sensors where many algorithms have been developed for object detection, sparse LiDAR point clouds still possess large room for improvement. …”
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    Article
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    Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification by Sobhan Sheykhivand, Tohid Yousefi Rezaii, Zohreh Mousavi, Azra Delpak, Ali Farzamnia

    Published 2020
    “…This study is based on sparse representation-based classification (SRC) theory and the proposed dictionary learning using electroencephalogram (EEG) signals. …”
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    Void avoidance opportunistic routing density rank based for underwater sensor networks by Ismail, Nasarudin

    Published 2021
    “…There are three new proposed algorithms introduced to address all three issues which resulted from using the OR approach in UWSNs. …”
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    Thesis