Search Results - (( process reduction clustering algorithm ) OR ( java application testing algorithm ))

Parallelization of noise reduction algorithm for seismic data on a beowulf cluster by Aziz, I. A., Sandran, T., Haron, N. S., Hasan, M. H, Mehat, M.

“…This paper presents the parallelization of a sequential noise reduction algorithm for seismic data processing into a parallel algorithm. …”
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Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction by Alkawsi G., Al-amri R., Baashar Y., Ghorashi S., Alabdulkreem E., Kiong Tiong S.

“…The findings of the experiments are compared to the outcomes of BOCEDS, CEDAS, and MuDi-Stream algorithms. The outcomes indicate that the EWR algorithm outperformed the baseline clustering algorithms. …”

Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

“…Moreover, three improvements of EM for brain MRI segmentation are proposed, which incorporate neighbourhood information in a new manner in the clustering process. In addition, two algorithms for the post-processing of clustering results using user-interaction and the re-evaluation of boundary data in each cluster are presented. …”
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Improved clustering using robust and classical principal component by Hassn, Ahmed Kadom

“…k-means algorithm is a popular data clustering algorithm. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. …”
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Improving the efficiency of clustering algorithm for duplicates detection by Emran, Nurul Akmar, Abdul Rahim, Abdulrazzak Ali Mohamed, Kamal Baharin, Safiza Suhana, Othman, Zahriah, Salem, Awsan Thabet, Abd Aziz, Maslita, Md. Bohari, Nor Mas Aina, Abdullah, Noraswaliza

“…Clustering method is a technique used for comparisons reduction between the candidates records in the duplicate detection process. …”
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Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

“…The effectiveness of the clustering model is the most important challenge. The K-Means clustering algorithm is an effective algorithm for multi-clusters that can be used in VANETs. …”

An evolutionary-based term reduction approach to bilingual clustering of Malay-English corpora by Rayner Alfred, Leow, Ching Leong, Joe Henry Obit

“…The document clustering process groups the unstructured text documents into a predefined set of clusters in order to provide more information to the users. …”
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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Optimised content-social based features for fake news detection in social media using text clustering approach by Yahya, Adnan Hussein Ali

“…In general, the process of fake news detection was conducted in two different phases, the topic detection phase using a graph-based unsupervised clustering method based on HFPA and Markov Clustering Algorithm (MCL) called (HFPA-MCL) and the fake news detection phase using an unsupervised clustering method based on K-means algorithm. …”
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A proposed design for noise reduction algorithm in seismograph on high performance computing using F-K filter by I.A., Aziz, T., Sandran, N.S., Haron, M., Mehat

“…This paper proposes a design of noise reduction algorithm for seismic data on a High Performance Computing (HPC) environment. …”
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Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi by Yazdi, Saeed Reza Aghabozorgi Sahaf

“…Several studies which focus on time-series clustering have been conducted in said areas. Many of these studies focus on the time complexity of time-series clustering in large datasets and utilize dimensionality reduction approaches and conventional clustering algorithms to address the problem. …”
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Energy-efficient data transmission with clustering and compressive sensing in wireless sensor networks / Mukil Alagirisamy by Mukil , Alagirisamy

“…In the extended ECH-DUAL algorithm in addition to dual sink a new cluster head selection method is proposed for unequal clustering. …”
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Customer mobile behavioral segmentation and analysis in telecom using machine learning by Sharaf Addin, Eman Hussein, Admodisastro, Novia Indriaty, Mohd Ashri, Siti Nur Syahirah, Kamaruddin, Azrina, Chew, Yew Chong

“…Secondly was the pre-processing which includes the dimensionality reduction of the dataset using the PCA technique and finding the optimal number of clusters using the Elbow method. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…For floor localisation, the strategy is based on developing the algorithm to determine the floor by utilising fingerprint clustering technique. …”
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Adaptive Feature Selection and Image Classification Using Manifold Learning Techniques by ASHRAF, AMNA, MOHD NAWI, NAZRI, MUHAMMAD AAMIR, MUHAMMAD AAMIR

“…In the first phase, the manifold learning approach is used to improve the ‘feature selection by clustering’. Clustering algorithms such as K-means, spectral clustering, and the Gaussian Mixer Model have been tested with manifold learning approaches for adaptive feature selection. …”
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An assessment of sedimentation in Terengganu River, Malaysia using satellite imagery by Aziz A., Essam Y., Ahmed A.N., Huang Y.F., El-Shafie A.

The classification of hunger behaviour of Lates Calcarifer through the integration of image processing technique and k-Nearest Neighbour learning algorithm by Taha, Zahari, Razman, Mohd Azraan, Abdul Ghani, Ahmad Shahrizan, P.P. Abdul Majeed, Anwar, Musa, Rabiu Muazu, A. Adnan, Fatihah, Sallehudin, Muhammad Firdaus, Mukai, Yukinori

“…The clustered fish behaviour is then classified through k-Nearest Neighbour (k-NN) learning algorithm. …”
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The classification of hunger behaviour of Lates Calcarifer through the integration of image processing technique and k-Nearest Neighbour learning algorithm by Zahari, Taha, M. A. M., Razman, Ahmad Shahrizan, Abdul Ghani, A. P. P., Abdul Majeed, R. M., Musa, F. A., Adnan, M. F., Sallehudin, Y., Mukai

“…The clustered fish behaviour is then classified through k-Nearest Neighbour (k-NN) learning algorithm. …”
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Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement by Kadmin, Ahmad Fauzan

“…Then, a new proposed cost aggregation based on the Hybrid Random Aggregation (HA) was implemented that utilized modified Iterative Non-Local Guided Filter (iNLGF), Simple Linear Iterative Clustering (SLIC), Graph Segmentation (GS) and Extended Restart Random Walk (eRWR) for error reduction. …”
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