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Keyword: clusterText Line Segmentation on Myanmar Handwritten Document using Average Linkage Clustering Algorithm
Text line segmentation from document images is a significant challenge in the field of document image analysis. It involves extracting individual text lines from Myanmar handwritten document images to enable text recognition. This task becomes particularly challenging in Myanmar handwritten documents, especially those with irregular or cursive writing styles, due to variations in line spacing,…
Read MoreGraph-based Clustering Algorithms – A Review on Novel Approaches
Classical clustering algorithms often require an a-priori number of expected clusters and the presence of all documents beforehand. From practical point of view, the use of these algorithms especially in more dynamic environments dealing with growing or shrinking corpora therefore is not applicable. Within the last years, graph-based representations of knowledge such as co-occurrence graphs…
Read MoreAn Improved Approach for QoS Based Web Services Selection Using Clustering
With the rising number of web services created to build complex business processes, selecting the appropriate web service from a large number of web services respond to the same client request with the same functionality are developed independently but with different quality of service (QoS) attributes. From this point, there are many approaches to web…
Read MoreA Recommendation Approach in Social Learning Based on K-Means Clustering
E-learning, among the most prominent modes of learning, offers learners the opportunity to attend online courses. To improve the quality of online learning, social learning through social networks promotes interaction and collaboration among learners. As part of the learning process management in these environments, the implementation of recommendation systems facilitates the provision of content adapted…
Read MoreProjection of Wireless Multipath Clusters Using Multi-Dimensional Visualization Techniques
Advances in channel modeling allow wireless communication designers to accurately model and understand the channel’s phenomena within different propagation scenarios. A precise channel model results in the wireless system’s optimized performance while considering trade-offs due to the effects of the channel. The geometric-based stochastic channel model considers different interacting objects affecting the parameters using the…
Read MoreEvaluating the Effectiveness of Query-Document Clustering Using the QDSM Measure
It is well documented that the average length of the queries submitted to Web search engines is rather short, which negatively impacts the engines’ performance, as measured by the precision metric. It is also well known that ambiguous keywords in a query make it hard to identify what exactly search engine users are looking for.…
Read MoreInterface for Visualization of Wireless Propagation Multipath Clustering Outcomes
A graphical user interface (GUI) is presented to visualize the multipaths generated by COST 2100 channel model (C2CM) and the results of clustering the wireless propagation multipaths using Modified Simultaneous Clustering and Model Selection (MSCAMSMA). The usual practice of authors is to show their data and results using figures, tables, and graphs which are already…
Read MoreVariation Between DDC and SCAMSMA for Clustering of Wireless MultipathWaves in Indoor and Semi-Urban Channel Scenarios
The performance of Simultaneous Clustering and Model Selection Matrix Affinity (SCAMSMA) and Deep Divergence-Based Clustering (DDC) in clustering wireless mul- tipaths generated by COST 2100 channel model (C2CM) is compared. Enhancing the accuracy of clustering multipaths is an open area of research which the clustering ap- proaches try to improve. Jaccard index is used as…
Read MoreEvaluation of Disadvantaged Regions in East Java Based-on the 33 Indicators of the Ministry of Villages, Development of Disadvantaged Regions, and Transmigration Using the Ensemble ROCK (Robust Clustering Using Link) Method
East Java province is a large province in Indonesia, in which Surabaya is the second largest metropolitan city after Jakarta. Various problems of development inequality in East Java have caused East Java to be defined as a disadvantaged area in 2015. The determination of disadvantaged regions is carried out every 5 years using 6 criteria…
Read MoreClustering of Mindset towards Self-Regulated Learning of Undergraduate Students at the University of Phayao
The effects of Covid-19 severely affected the Thai higher education model. Therefore, there are three significant objectives in this research: (1) to cluster the mindsets and attitudes toward self-regulated learning styles of undergraduate students at the University of Phayao. (2) to construct a predictive model for recommending an appropriate student learning clusters. (3) to evaluate…
Read MoreCluster Centroid-Based Energy Efficient Routing Protocol for WSN-Assisted IoT
Wireless sensor network is highly resource constrained, where energy efficiency and network lifetime plays a major role for its sustenance. As the sensor nodes are battery operated and deployed in hostile environments, either recharging or replacement of batteries in sensor nodes is not possible after its deployment in inaccessible areas. In such condition, energy is…
Read MoreA Novel Representative k-NN Sampling-based Clustering Approach for an Effective Dimensionality Reduction-based Visualization of Dynamic Data
Visualization plays a crucial role in the exploratory analysis of Big Data. The direct visualization of Big Data is a challenging task and difficult to analyze. Dimensionality Reduction techniques extract the features in the context of visualization. Due to the unsupervised and non-parametric nature, most of the dimensionality reduction techniques are not evaluated quantitatively and…
Read MorePriority Incorporated Zone Based Distributed Clustering Algorithm for Heterogeneous Wireless Sensor Network
Wireless sensor networks (WSNs) are considered to be the currently flourishing scientific domain, thereby found to be applicable in numerous industrial and domestic applications. As per the mathematical results in Pulse-coupled oscillator (PCO), it has been predicted that, numerous iterations are needed for convergence, leading to increased power consumption. Biologically inspired solutions are greatly applicable…
Read MoreSurvey on Semantic Similarity Based on Document Clustering
Clustering is a branch of data mining which involves grouping similar data in a collection known as cluster. Clustering can be used in many fields, one of the important applications is the intelligent text clustering. Text clustering in traditional algorithms was collecting documents based on keyword matching, this means that the documents were clustered without…
Read MoreAn Enhanced Fuzzy Clustering with Cluster Density Immunity
Clustering is one of the well-known unsupervised learning methods that groups data into homogeneous clusters, and has been successfully used in various applications. Fuzzy C-Means(FCM) is one of the representative methods in fuzzy clustering. In FCM, however, cluster centers tend leaning to high density area because the sum of Euclidean distances in FCM forces high…
Read MoreA Comparison of Mean Models and Clustering Techniques for Vertebra Detection and Region Separation from C-Spine X-Rays
In Computer Aided Diagnosis (CAD) tools, vertebra localization and detection are the essential steps for the diagnosis of cervical spine injuries. The accurate localization leads to accurate treatment, which is more challenging in case of poor contrast and noisy radiographs. This paper targets c-spine radiographs for the localization of vertebra using different vertebra templates, vertebra…
Read MoreTheoretical developments for interpreting kernel spectral clustering from alternative viewpoints
To perform an exploration process over complex structured data within unsupervised settings, the so-called kernel spectral clustering (KSC) is one of the most recommended and appealing approaches, given its versatility and elegant formulation. In this work, we explore the relationship between (KSC) and other well-known approaches, namely normalized cut clustering and kernel k-means. To do…
Read MoreOn the Performance of a Clustering-based Task Scheduling in a Heterogeneous System
Recent task scheduling algorithms for a generalized workflow job in heterogeneous system adopt list-based scheduling. In those algorithms, the response time cannot be effectively reduced if the given workflow job is data-intensive. If the workflow job is computationally intensive, an attempt is made to assign tasks to many processors, which can lead to resource starvation.…
Read MoreA novel model for Time-Series Data Clustering Based on piecewise SVD and BIRCH for Stock Data Analysis on Hadoop Platform
With the rapid growth of financial markets, analyzers are paying more attention on predictions. Stock data are time series data, with huge amounts. Feasible solution for handling the increasing amount of data is to use a cluster for parallel processing, and Hadoop parallel computing platform is a typical representative. There are various statistical models for…
Read MoreAnalysis of Learning Development With Sugeno Fuzzy Logic And Clustering
In the first journal, I made this attempt to analyze things that affect the achievement of students in each school of course vary. Because students are one of the goals of achieving the goals of successful educational organizations. The mental influence of students’ emotions and behaviors themselves in relation to learning performance. Fuzzy logic can…
Read MoreReal Time Advanced Clustering System
This paper describes a system to gather information from a stationary camera to identify moving objects. The proposed solution makes only use of motion vectors between adjacent frames, obtained from any algorithm. Starting from them, the system is able to retrieve clusters of moving objects in a scene acquired by an image sensor device. Since…
Read MoreLeveraging Machine Learning for a Comprehensive Assessment of PFAS Nephrotoxicity
Polyfluoroalkyl substances (PFAS) are persistent chemicals that accumulate in the body and environment. Although recent studies have indicated that PFAS may disrupt kidney function, the underlying mechanisms and overall effects on the organ remain unclear. Therefore, this study aims to elucidate the impact of PFAS on kidney health using machine learning techniques. Utilizing a dataset…
Read MoreVisualization of the Effect of Additional Fertilization on Paddy Rice by Time-Series Analysis of Vegetation Indices using UAV and Minimizing the Number of Monitoring Days for its Workload Reduction
This research is an extension of the research (ISEEIE 2023), which dealt with Time-Series Clustering (TSC) of Vegetation Index (VI) for paddy rice. The novelty of this research is “Visualization of growth changes before and after additional fertilization,” “Analyzing the appropriate amount of additional fertilizer,” and “Optimization of monitoring period to minimize the number of…
Read MoreColorized iVAT Images for Labeled Data
A 2-dimensional numerical data set X = {x1,…,xn} with associated category labels {l1,…,ln} can be accurately represented in a 2-dimensional scatterplot where color is used to represent each datum’s label. The colorized scatterplot indicates the presence or absence of spatial clusters in X and any special distribution of labels among those clusters. The same approach…
Read MoreAutomated Hydroponic System using Wireless Sensor Networks
Researchers have associated agriculture and food processing with adverse environmental impacts like; falls in the underground freshwater table, energy consumption, and high carbon emission. These factors have the worst effect on developing countries. Therefore, there is a need for on-demand food production techniques that require minimum resource utilization. For these reasons, scientists are now focusing…
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