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387 articles for “clustering”
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Implementation of K-Means clustering algorithm with technical indicators to identify Profitable stocks
Abstract: In the ever-changing world of stock market trading, accurately predicting price movements is key to maximizing profits. Technical analysis, which looks at past price data to predict future trends, provides valuable insights for investors. This paper delves into using machine learning methods, particularly the K-Means clustering algorithm, along with moving average data, to categorize daily trading patterns. By breaking down the market into clusters and examining the main patterns within …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 8–14 Read article
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Improved Performance Using Cluster Based Routing Methods for Wireless Sensor Network
Abstract: Clustering technique in (WSN) wireless sensor networks is skilled planning in order to efficiently handle the sensor network (nexus). LEACH, is in general, used as clustering protocol contained by CH, and also their source nodes which are attached, are irregularly transformed so as to permit effective balance. However, involvement of LEACH so that all source nodes promote their knowledgeable information directly to cluster heads which are connected, influence the energy …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 4, Issue 3, 2017 · pp. 5–11 Read article
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CTCHFA: Discovery of Circulating Tumor Cells in Metastatic Breast Cancer and Nonmetastatic Cancer by using Novel Hybrid Hierarchical Clustering Algorithm in Firefly Distance
Abstract: AbstractBlood testing for circulating tumor cells (CTCs) has emerged as one of the highest fields in cancer research. CTC detection are an early gene marker of reaction to systemic therapy, whereas their molecular characterization has a strong field that can be translated to individualized targeted treatments and spare breast cancer (BC) patients from unnecessary and ineffective therapies. Genomic research regarding CTCs monitoring for BC is limited due to the lack …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 1, 2015 · pp. 9–18 Read article
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Clustering Hierarchy Technique for Energy-Efficient Wireless Sensor Networks
Abstract: WSNs are popular due to advancement of technology in field sensors and wireless communication network sub sequence of their miniaturization. It has number of applications for the remote and hazardous environment where lifetime of a sensing unit and energy consumption are main factors. As nodes are battery operated, optimization of energy for better and maximum lifetime is the main issue. This paper has proposed the clustering based hierarchical type of …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 2, Issue 1, 2015 · pp. 24–29 Read article
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Energy Efficient Clustering Techniques for Heterogeneous Wireless Sensor Networks:A Survey
Abstract: Clustering techniques enhance stability, efficiency and lifetime of wireless sensor networks. But clustering techniques developed for homogeneous wireless sensor networks are unable to take advantage of heterogeneity provided by heterogeneous wireless sensor networks. In this paper, clustering techniques proposed by various researchers for heterogeneous wireless sensor networks to prolong the stability, efficiency and lifetime of the network are surveyed based on heterogeneity parameters like link quality, computational power and energy.Cite …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 3, Issue 1, 2016 · pp. 1–9 Read article
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A Review Paper on Clustering Technique in MANET
Abstract: Mobile ad hoc networks (MANETs) are a distinctive kind of wireless networks that could be quickly deployed without preexisting infrastructures. They are used in exceptional contexts corresponding to collaborative, medical, military, or embedded functions. The clustering method builds upon the proposal of hierarchical or clustered management for MANETs and identifies logical clusters of nodes. Clustering is a major research topic for MANETs considering the fact that clustering makes it possible …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 3, Issue 2, 2016 · pp. 17–25 Read article
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Comparing UWDBCSN Clustering with LNCA for Node Replication Attack
Abstract: AbstractClustering in WSN divides sensor nodes into different clusters. Each node is headed by a cluster head. Instead of direct routing, the communication can take place between cluster heads that increases the lifetime of sensor network. Some security issues in clustering may arise because of the presence of attacker node(s) in the network. Attacker nodes may disrupt the whole cluster by introducing attacks like node replication, denial of service, wormhole, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 4, Issue 2, 2017 · pp. 41–49 Read article
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A New Method to Optimize Initial Cluster Number and Then Apply K-Means Algorithm to Perform Image Segmentation
Abstract: Clustering is described as the task of merely grouping a set of data points, which in our case are represented by image pixels, with the application of one or more algorithms, into super-pixels. The k-means clustering algorithm is used for many day-to-day practical applications where the quality of the obtained clusters depends heavily on the initial selection of centroids. In literature, several methods have already been proposed for the improvement …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 5, Issue 2, 2018 · pp. 18–24 Read article
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Managing and Maintaining Container inside Kubernetes Clusters
Abstract: It is an open-source orchestration tool developed by Google, its historical name is bought after it has been changed to Kubernetes, now it is part of the Cloud Native Computing Foundation. Kubernetes is mostly used for maintaining micro servers and containers. Here, container refers to an existing application that has been containerized using Docker and can only be implemented within Kubernetes. Micro servers are used when there are multiple little …
Published in Recent Trends in Parallel Computing · Vol. 9, Issue 2, 2022 · pp. 6–12 Read article
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Deep Learning for Grape Cluster Segmentation
Abstract: Grape cluster identification and its segmentation for the purpose of vineyard total weight prediction tasks indicate the need for more accurate segmentation atomization. The Grape Cluster Segmentation challenge is supplied as an answer the usage of deep neural community fashions including YOLO v3, Mask RCNN, and U-net. In the sense of a modified U-net model for segmenting grapes using training and testing strategies, this contribution contributes to the validation of …
Published in Recent Trends in Programming languages · Vol. 8, Issue 2, 2021 · pp. 23–32 Read article
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Biological Network Clustering using Distance and Graphical Network Algorithm
Abstract: Clustering is a process of grouping together similar data items together based on certain percentage of similarity or certain amount of threshold value. The study of the protein-protein interaction is an important task as this is necessary in order to identify how the proteins are grouped together and how they interact with each other. This process of studying or identifying the protein-protein interaction so far done anciently is followed by …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 5, Issue 1, 2015 · pp. 6–14 Read article
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Model Based Clustering using Finite Mixture Models of Lognormal Distribution
Abstract: AbstractModel-based clustering consists of fitting a mixture model to data and identifying cluster with its components. This study discusses model-based clustering using a finite mixture of a univariate lognormal distribution with k components. In this study, lognormal mixture models for skewed data and also the estimation of mixing proportion by distance-based clustering have been considered. Parameter estimation is carried out by expectation maximization (EM) algorithm using different initialization approach using …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 3, 2018 · pp. 58–67 Read article
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On-Farm Demonstration of Improved Sorghum (Sorghum bicolor L. Moench) Technologies in Cluster based Large scale Approaches at Gofa Zone, Southern Ethiopia
Abstract: Sorghum is used as a source of food and cash for smallholder farmers in drought phrone areas of Gofa Zone. Farmers produce sorghum traditionally without proper management and input use and as a result yield obtained by farmers was far below the crop potential. Therefore, Arba Minch Agricultural Research Center carried out a cluster-based large-scale demonstration of improved sorghum in Melo-Koza and Zala Districts of the Gofa Zone in Southern …
Published in Research & Reviews : Journal of Botany · Vol. 13, Issue 1, 2024 · pp. 23–30 Read article
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Intrinsic Evaluation of Graph Embeddings: Assessing Clustering and Community Detection Performance
Abstract: This paper presents an intrinsic evaluation of some graph embedding techniques on clustering and community detection tasks. We analyze a diverse set of embedding methods, ranging from traditional techniques such as Laplacian eigenmaps to more recent approaches like graph autoencoders, high-order proximity preserved embedding (HOPE), and graph attention network (GAT), using two widely studied datasets, Cora and CiteSeer. Our evaluation relies on two main metrics: Silhouette score with respect to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 40–48 Read article
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Role of Beowulf Clusters in Next-Generation Military Applications: A Comprehensive Study
Abstract: Beowulf clusters, which utilize cost-effective commodity hardware combined with open-source software for parallel computing, have emerged as a viable and efficient solution for high-performance computing needs. This paper explores their growing relevance and practical applications in modern and future military technologies. Contemporary military operations increasingly rely on rapid data processing, real-time intelligence, high-fidelity simulations, and autonomous decision-making systems. Beowulf clusters offer scalable and adaptable computational power that supports these demands …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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Covariance based Clustering for Digital Image Compression
Abstract: Traditionally clustering is done based on distance between the data points and the cluster centroids. A new type of clustering based on distance between the covariance matrices of the clustered data points was recently introduced. This allows clustering data points according to their spatial distribution model. This paper presents an improved algorithm for the computation of covariance based clustering with application to digital image compression. Karhunen-Loeve Transform is an optimal …
Published in Current Trends in Information Technology · Vol. 8, Issue 1, 2018 · pp. 16–21 Read article
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Gray Wolf Optimization Based Clustering Using Network Parameters for WSN Applications
Abstract: Modern communication systems need to use energy. This is very important for the Internet of things which’s a big network of smart devices that talk to each other. The Internet of Things is becoming very popular because it is useful. This paper is about a way to send data in a Wireless Sensor Network. We made a routing protocol that works well in a simulated environment. Our approach is to …
Published in Journal of Communication Engineering & Systems · Vol. 16, Issue 2, 2026 · pp. 33–42 Read article
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An Empirical Study on Evaluating Graph Based Clustering for HD Data Using Attribute Selection
Abstract: An attribute subset selection can be showed as a process of identifying and eliminating or removing a number of irrelevant and surplus attributes (features) because irrelevant attributes do not give predictive accuracy and the surplus attributes provide the information that is already present in the other attributes. Attribute selection involves identifying a subset of the most useful attributes that produces the similar results as the final set of results. An …
Published in Journal of Advanced Database Management & Systems · Vol. 1, Issue 2, 2014 · pp. 33–40 Read article
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An Improved K-means Clustering Algorithm for Classification of Odor/Gas Sensor Data Using Normalized Cosine Distance Parameter
Abstract: This paper presents a novel approach of K-means Clustering for classification of odors/gases (E-nose) using cosine distance as a distance parameter. A sensor array constituting five sensors is exposed to four different types of gases to extract data. The problem of classifying the data into respective classes in considered as a K-means Clustering task. To quantify the amount of similitude between the data corresponding to same classes; usually euclidean distance …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 2, 2015 · pp. 56–60 Read article
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Asynchronous Check pointing Protocols for Cluster Based MANETs: A Comparative Analysis
Abstract: The recent advancement in the field of wireless networking and mobile computing has led to the development of variety of applications for wireless networks. Mobile Ad Hoc Networks (MANETs) are emerging as one of the major wireless technology in the field of mobile computing. A MANET is a group of mobile devices or nodes that are self-configurable and can communicate using wireless links. The nodes of such a network have …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 2, Issue 3, 2015 · pp. 19–25 Read article