Search Results - (( regional distribution clustering algorithm ) OR ( _ validation study algorithm ))

Visualization of dengue incidences using expectation maximization (EM) algorithm by Mathur, N., Asirvadam, V.S., Dass, S.C., Gill, B.S.

“…Along with the prediction modeling on data using centroid model and distribution model based on K-means and Expectation Maximization (EM) algorithms respectively. …”
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Tumor Extraction for Brain Magnetic Resonance Imaging Using Modified Gaussian Distribution by Salih Al-Badri, Qussay Abbas

“…Currently testing the validation of the proposed segmentation in a validation study that compares resulting MS lesion as well as gray and white matter tissue structures with Neural Network expert segmentation system. …”
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Scheduled activity energy-aware distributed cluster- based routing algorithm for wireless sensor networks with non-uniform node distribution by Nokhanji, Nooshin

“…Therefore, in this study, a new algorithm called Scheduled-Activity Energy Aware Distributed Clustering (SA-EADC) is proposed. …”
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Comparison between clustering algorithm for rainfall analysis in Kelantan / Wan Nurshazelin Wan Shahidan and Siti Nurasikin Abdullah by Wan Shahidan, Wan Nurshazelin, Abdullah, Siti Nurasikin

“…Comparisons between the clustering algorithms were conducted in this study to identify which clustering algorithm is the most suitable and simple for rainfall distribution. …”
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Clustering of Indonesian forest fires using self organizing maps by Selamat, Ali, Selamat, Md. Hafiz

“…This paper focuses on clustering the locations of Indonesian forest fires and visualizing them into a two-dimensional map using a self-organizing map (SOM) algorithm. …”
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An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan by Ullah, S., Daud, H., Dass, S.C., Hadi, F.-T., Khalil, A.

“…The EigenSpot algorithm has been recently proposed for detecting space-time disease clusters of arbitrary shapes with no restriction on the distribution and quality of the data, and has shown some promising advantages over the state-of-the-art methods. …”
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An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan by Ullah, S., Daud, H., Dass, S.C., Hadi, F.-T., Khalil, A.

“…The EigenSpot algorithm has been recently proposed for detecting space-time disease clusters of arbitrary shapes with no restriction on the distribution and quality of the data, and has shown some promising advantages over the state-of-the-art methods. …”
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Enhancing clustering algorithm with initial centroids in tool wear region recognition by Kasim, Nur Adilla, Nuawi, Mohd Zaki, Abdul Ghani, Jaharah, Ngatiman, Nor Azazi, Che Haron, Che Hassan, Muhammad Rizal

“…The silhouette value average score is 0.8504 (highest score is 0.9207) of how well-distributed the resulting clusters. The clustering system has identified the tool to stop cutting at approximate VB = 0.213 mm before the tool condition enters the failure region of abnormal phase (VB < 0.250 mm).s The proposed system functioned effectively in clustering the data obtained from cutting tests performed within a reasonable range of wear stages. …”
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A coverage path planning approach for autonomous radiation mapping with a mobile robot by Abd Rahman N.A., Sahari K.S.M., Hamid N.A., Hou Y.C.

Communication and computational cost on parallel algorithm of PDE elliptic type by Alias, Norma

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Single Earthquake Bond Pricing Framework With Double Trigger Parameters Based On Multi Regional Seismic Information by Wulan Anggraeni, Sudradjat Supian, Sukono, Nurfadhlina Abdul Halim

Route Optimization based on Clustering and Travelling Salesman Problem by Khadijah, Thahira, Tri Basuki, Kurniawan, Edi Surya, Negara, Ahmad, Haidar Mirza, Misinem, .Misinem

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Using Bimodal Gaussian Mixture Model-Based Algorithm for Background Segmentation in Thermal Fever Mass Screening by Siti Sofiah, Mohd Radzi, Kamarul Hawari, Ghazali, Nazriyah, Che Zan, Faradila, Naim

“…To estimate the bi - modal background-foreground distribution mixture parameters, Expectation-Maximization (EM) algorithm is applied and the images are clustered statistically and linearly. …”
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Research trends among new investigators at ISOQOL: a bibliometric analysis from 2019 to 2023 by Kwon, Jae-Yung, Kaur, Manraj N., Elsman, Ellen B. M., Mehdipour, Ava, Lo, Lori Suet Hang, Ahmed Osman, Ahmed Mohamed Yehia Naguib, Herbelet, Sandrine, Ng, Carrie-Anne, van der Weijst, Lotte

“…Thematic mapping was conducted using clustering algorithms to identify established and emerging research areas. …”
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

“…After that cancer-affected region in the lung is segmented with the help of the proposed Butterfly Optimization Algorithm-based K-Means Clustering (BOAKMC) algorithm. …”
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A hybrid method using haar-like and skin-color algorithm for hand posture detection, recognition and tracking by Bilal, Sara Mohammed Osman Saleh, Akmeliawati, Rini, Salami, Momoh Jimoh Eyiomika, Shafie, Amir Akramin, Bouhabba, El Mehdi

“…The chromatic color distribution of skin can be found within this cluster. …”
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Haemoglobin distribution in ulcers for healing assessment by Malik, Aamir Saeed, Fadzil, A. F. M., Arshad, Leena, Jamil, Adawiyah, Yap, Felix

“…Extracted haemoglobin images indicate areas of haemoglobin distribution reflecting detected regions of granulation tissue. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

“…Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
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Species distribution and molecular variations in drogonflies (order: odonata) within the state of Selangor, Malaysia / Noorhidayah Binti Mamat by Noorhidayah, Mamat

“…Opposite to suborder Zygoptera, they were resolved clustered into 2 clusters, paraphyletic group. The distinct separation between cluster Anisoptera and Zygoptera with confidence level 72% in the NJ analyses while 90% in MP analyses. …”
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Feature extraction and classification :a case study of classifying a simulated digital mammogram images using self-organizing maps (som) by Lau, Leh Teen.

“…This feature extraction technique can be used to find five parameters which are the size, intensity, centroid X, centroid Y and region distribution of segmented regions . Several experiments have been conducted to verify the proposed algorithm and feature extraction results obtained will be used for the training of Neural Network classifier, Self-Organizing Maps (SOM). …”
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