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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field
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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Proximal linearized method for sparse equity portfolio optimization with minimum transaction cost
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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Identification of the continuous-time Hammerstein models with sparse measurement data using improved marine predators algorithm
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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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
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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Provider independent cryptographic tools
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Monograph -
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Speech compression using compressive sensing on a multicore system
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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Counting roots of the Polynomial systems by using mixed volume of the Newton polytopes / Nur Suhailah Norazhar, Nur Ain Sofiya Zainuri and Nor Suhada Mohd Rosdi
Published 2024“…These sparse matrices are then used to generate the determinant by using Maple 2015. …”
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Student Project -
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Semi-supervised learning for feature selection and classification of data / 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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Prime-based method for interactive mining of frequent patterns
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
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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Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification
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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Real-Time Video Processing Using Native Programming on Android Platform
Published 2012“…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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Conference or Workshop Item -
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Void avoidance opportunistic routing density rank based for underwater sensor networks
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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Minimum regularized covariance determinant and principal component analysis-based method for the identification of high leverage points in high dimensional sparse data
Published 2022“…The RMD-MRCD-PCA is developed by incorporating the Principal Component Analysis (PCA) in the MRCD algorithm whereby this robust approach shrinks the covariance matrix to make it invertible and thus, can be employed to compute the RMD for high dimensional data. …”
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