Search Results - (( java implication based algorithm ) OR ( case detection clustering algorithm ))

Cluster detection for spatio-temporal dengue cases at Selangor districts using multi-EigenSpot algorithm by Nor, N.H.M., Daud, H., Ullah, S.

“…This study aims to detect the spatio-temporal clustering or hotspot regions of dengue cases for the districts of Selangor, Malaysia using a nonparametric algorithm (Multi-EigenSpot) to detect dengue clusters. …”
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Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.] by Pusadan, Mohammad Yazdi, Rabbani, Mohammad Abied, Ardiansyah, Rizka, Ngemba, Hajra Rasmita

“…In this study, the method used is K-Means to perform clustering based on area grouping. The implementation of the K-Means Clustering algorithm for detecting the level of spread of COVID-19 data in Indonesia by using the parameter k=3 is quite good with areas in Indonesia that have a high the spread of COVID-19 and the results of the cluster validity test get silhouette values on O = (Total Case, Total Death) and P = (Total Case, Total Death, Total Recovered) have the same cluster value, which is 0.93 which means the cluster quality is very good.…”
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Cluster detection for spatio-temporal dengue cases at Selangor districts using multi-EigenSpot algorithm by Nor, Nurul Hidayah Mohd, Daud, Hanita, Ullah, Sami

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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 results showed the effectiveness of the proposed method for detecting multiple clusters in a spatiotemporal space. …”
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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 results showed the effectiveness of the proposed method for detecting multiple clusters in a spatiotemporal space. …”
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning by Islam, Md Kamrul

“…These results prove the superiority of BOCEDS algorithm over the existing clustering algorithms. …”
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Abnormalities detection in apert syndrome using hierarchical clustering algorithms by Nur Syahirah, Zulkipli, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff

“…There are 12 skull angles and these angles are analysed using hierarchical clustering algorithms for identifying the outliers or abnormalities. …”
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A multi-view clustering algorithm for attributed weighted multi-edge directed networks by Khameneh, Azadeh Zahedi, Kilicman, Adem, Mahad, Zahari

“…This type of directed network, whose nodes are described by a list of attributes and directed links are viewed as directed multi-edge, is a new challenge to graph clustering. This paper proposes a new approach to detecting and evaluating clusters of AWMEDiG based on the maximum clique method. …”
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Arabic Text Clustering Methods And Suggested Solutions For Theme-based Quran Clustering: Analysis Of Literature by Qusay Bsoul, Jaffar Atwan, Rosalina Abdul Salam, Malik Jawarneh

A hybrid framework based on neural network MLP and means clustering for intrusion detection system by Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia

“…Concerning the robustness of K-means method and MLP algorithms benefits, this research is the part of an effort to develop a hybrid information detection system (IDS) which is able to detect high percentage of novel attacks while keep the false alarm at low rate.This paper provides the conceptual view and a general framework of the proposed system.…”
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A hybrid framework based on neural network MLP and K-means clustering for intrusion detection system by Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia

“…Concerning the robustness of K-means method and MLP algorithms benefits, this research is the part of an effort to develop a hybrid information detection system (IDS) which is able to detect high percentage of novel attacks while keep the false alarm at low rate. …”
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Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering by Davari, Atefeh, Marhaban, Mohammad Hamiruce, Mohd Noor, Samsul Bahari, Karimadini, Mohammad, Karimoddini, Ali

“…The algorithm also improves the calculations of shape and width of membership functions by means of clustering in order to improve the accuracy. …”
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Survey on Clustered Routing Protocols Adaptivity for Fire Incidents: Architecture Challenges, Data Losing, and Recommended Solutions by Abbas O.K., Abdullah F., Radzi N.A.M., Salman A.D., Abdulkadir S.J.

“…Many clustered routing algorithms have been developed to address various issues like energy efficiency, network lifetime, and hotspot problems. …”

Optic cup and optic disc segmentation using improved selfish gene algorithm / Norharyati Md Ariff by Md Ariff, Norharyati

“…Image processing techniques were employed to segment and extract the optic cup and optic disc for glaucoma detection purpose. This study performed using a new bio-inspired algorithm; Selfish Gene Algorithm (SFGA) for optic cup and optic disc segmentation. …”
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Multi-user beamforming, fairness and device-to-device channel state information sharing in downlink non-orthogonal multiple access systems by Abdulhussein, Mohanad Mohammed

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Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli by Rosli, Muhammad Helmi

“…Each experiment highlight the advantages and disadvantages of the experimental architecture.The disadvantages from each experiment prompts the design of dynamic parallel partitioning and allocating framework. The case study use for this experiment is Sobel edge detection algorithm. …”
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Segmenting nodules of lung tomography image with level set algorithm and neural network by Chong, Soon Yee, Tan, Min Keng, Yeo, Kiam Beng, Mohd Yusof Ibrahim, Hao, Xiaoxi, Teo, Kenneth Tze Kin

“…Computer aided diagnosis (CAD) plays an important role in medical field which helps radiologists to detect and localise lung nodule. The aim of this research is to develop an image segmentation algorithm for nodule detection in computed tomography (CT) image. …”
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An improved diabetes risk prediction framework : An Indonesian case study by Sutanto, Daniel Hartono

“…However,there is the issue of noisy dataset detected as incomplete data and the outlier class problem that affects sampling bias.Existing frameworks were deemed difficult in identifying the critical risk factors of diabetes;some of which were considerably inaccurate and consume substantial computation time.The purpose of this study is to develop a suitable framework for predicting diabetes risks.From a complete blood test,the framework can predict and classify the output of either having diabetes risk or no diabetes risk.A Diabetes Risk Prediction Framework (DRPF) was developed from the literature review and case studies were afterwards conducted in three private hospitals in Semarang.Analyses were conducted to find a suitable component of the framework—due to lack of comparison and analysis on the combination of feature selection and classification algorithm.DRPF comprises four main sections: pre-processing,outlier detection,risk weighting,and learning. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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