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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

“…In this paper, we propose a sparse equity portfolio optimization model that aims at minimizing transaction cost by avoiding small investments while promoting diversification to help mitigate the volatility in the portfolio. …”
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Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field by Toh, Cheng Chuan

“…Blind Source Separation (BSS) refers to the statistical technique of separating a mixture of underlying source signals.BSS denotes as a phenomena and separation on mixed heart-lung sound is one of its example.The challenge of this research is to separate the separate lung sound and heart sound from mixed heart-lung sound.A clear lung sound for diagnosis purpose able to be obtained after separating the mixed heart-lung sound.In biomedical field,lung information is precious due to it has been provided for respiratory diagnosis.However,the interference of heart sound towards lung sound will generate ambiguity and it will lead to drop down the accuracy of diagnosis.Thus,a clean lung sound is needed to increases the accuracy of diagnosis.One of the ways for non-invasive respiratory diagnosis for obtaining lung information is through extracting lung sound from mixed heart-lung sound by using Two-Dimensional Nonnegative Matrix Factorization (NMF2D) algorithm.This method is based on cocktail party effect in which it refers to human brain able to selectively listen to target among a cacophony of conversations and background noise and this considered as a difficult task to machine.Therefore, duplication on cocktail party effect into machine is used to separate the mixed heart-lung sound.This research presents a novel approach NMF2D algorithm in which a suitable model for signal mixture that accommodated the reverberations and nonlinearity of the signals.The objectives of this research are focusing on investigating the useful signal analysis algorithms,defining a new technique of signal separability,designing and developing novel methods for BSS. …”
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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

“…Subsequently, we applied RAMPA-TCF to identify the parameters of one numerical example and a twin-rotor system (TRS) under various sparse measurement data cases. …”
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

“…However, finding the most appropriate deep learning algorithm for a medical classification problem along with its optimal parameters becomes a difficult task. …”
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Image denoising using combined higher order non-convex total variation with overlapping group sparsity by Adam, Tarmizi, Paramesran, Raveendran

“…In this paper, we address this problem by proposing a combined non-convex higher order total variation with overlapping group sparse regularizer. …”
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Multi-Hop Selective Constructive Interference Flooding Protocol For Wireless Sensor Networks by Alhalabi, Huda A. H.

“…The first step of the proposed protocol involves the development of an energy efficient clustering algorithm which is appropriate for WSN with a sparse density topology. …”
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Scene classification for aerial images based on CNN using sparse coding technique by Qayyum, A., Malik, A.S., Saad, N.M., Iqbal, M., Faris Abdullah, M., Rasheed, W., Rashid Abdullah, T.A., Bin Jafaar, M.Y.

“…Recent developments include several approaches and numerous algorithms address the task. …”
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Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

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

“…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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Speech compression using compressive sensing on a multicore system by Gunawan, Teddy Surya, Khalifa, Othman Omran, Shafie, Amir Akramin, Ambikairajah, Eliathamby

“…In this paper, a novel algorithm for speech coding utilizing CS principle is developed. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

“…Thus far, a few efficient interactive mining algorithms have been proposed. …”
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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 by Norazhar, Nur Suhailah, Zainuri, Nur Ain Sofiya, Mohd Rosdi, Nor Suhada

“…Since the study dealing with the sparse polynomial systems with two variables, to derive the sparse matrices, the developed Maple program, “multires.mpl” is used. …”
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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 by Siti Zahariah, Midi, Habshah

“…The main aim of this paper is to propose a novel method (RMD-MRCD-PCA) of identification of High Leverage Points (HLPs) in high-dimensional sparse data. …”
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Scene classification for aerial images based on CNN using sparse coding technique by Qayyum A., Malik A.S., Saad N.M., Iqbal M., Faris Abdullah M., Rasheed W., Rashid Abdullah T.A., Bin Jafaar M.Y.

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

“…In this research, a fully automated system is presented to automatically detect the various states of the epileptic seizure. …”
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Void avoidance opportunistic routing density rank based for underwater sensor networks by Ismail, Nasarudin

“…Finally, the algorithm Void Avoidance Opportunistic Routing Density Rank Based (ORDRB) was developed to deal with the communication void by introducing a simple method to detect a void node and avoid it during the forwarding process. …”
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A Multi-Criteria Recommendation Technique for Personalized Tourism Experiences by Mustafa, Payandenick, Yin Chai, Wang

“…The proposed method also provided more relevant recommendations to users compared to all other tested algorithms. Overall, the proposed method offers a novel and effective solution to the information overload challenge in the tourism industry.…”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm by Yong, Ericsson, Muhammad Aizzat, Zakaria, Mohamad Heerwan, Peeie, M. Izhar, Ishak

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