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387 articles for “clustering”
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An Improved Cluster Head Election Algorithm Using Energy or Weight of Path in MANET
Abstract: Mobile ad hoc network is one of the well-known technologies among wireless networks. Due to mobility and dynamic topology the network suffers from different security and performances issue. Therefore, the clustering algorithms are implemented for improving the scalability and performance of the routing algorithms. The presented work demonstrates a MANET clustering algorithm and their design strategy. The overview of the proposed routing techniques is discussed in this paper.Cite this ArticleKuldeep …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 3, Issue 1, 2016 · pp. 10–16 Read article
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A Technical Survey on Different Clustering Techniques & Fuzzy Logic in Wireless Sensor Network
Abstract: Abstract—The WSN is a distinctive network and WSN includes sensors at enormous scale as well as comprises at least single base station. When building wireless sensor networks, there are critical issues that are appeared such as preserving energy and load balancing. Lifetime of a sensor network is improved by implementing andmitigating energy consumption. Amount of a choice of parameters such as quantity of nodes, strength and range of area as …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 4, Issue 3, 2017 · pp. 1–8 Read article
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Colour Based Segmentation of a Landsat Image Using K-Means Clustering Algorithm
Abstract: AbstractImage segmentation is one of the typical vintage subjects in image processing and it acts as a bulls-eye of the image processing technique. By definition, image segmentation means identifying the similar regions in the image; or in other words, identifying the homogenous pixels in the image and grouping all these pixels based on the homogeneity condition considered. This homogeneity condition can be like, colour, texture, size, compactness etc. It is …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 4, Issue 3, 2017 · pp. 31–38 Read article
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A PCA Based K-Means Clustering Algorithm for Wireless Sensor Nodes
Abstract: This paper presents a novel and improved approach for K-Means Clustering of wireless sensor networks, by using Principal Component Analysis for data reduction on the raw data. A wireless sensor network consisting of 100 nodes is classified into three different clusters using PCA based K-Means Algorithm. Davies-Bouldin Index is used as a parameter to check the effectiveness of the clustering algorithm. Experimental results demonstrate that the PCA based K-Means Algorithm …
Published in Journal of Web Engineering & Technology · Vol. 2, Issue 2, 2015 · pp. 6–10 Read article
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An Enhanced DBSCAN Clustering Mechanism in Big Data
Abstract: Big data is the term for a gathering of data sets so immense and complex that it ends up hard to process utilizing present database administration devices or traditional data handling applications. Today, current data volumes are driven by both unstructured and semi-organized data. In this manner, end-to-end preparing can be blocked by the change between organized data in social frameworks of database administration and unstructured data for examination. In …
Published in Journal of Web Engineering & Technology · Vol. 5, Issue 2, 2018 · pp. 10–15 Read article
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Adaptive Huffman Algorithm for Data Compression Using Text Clustering and Multiple Character Modification
Abstract: Adaptive Huffman algorithm is a popular data compression technique that creates a variable-length binary code for each symbol in a message. However, the original algorithm may not be efficient in compressing text data, particularly when dealing with long sequences of repeated characters. In this study, we propose a novel approach to enhance the compression ratio of the Adaptive Huffman algorithm by utilizing text clustering and multiple character modification. The proposed …
Published in Recent Trends in Programming languages · Vol. 10, Issue 1, 2023 · pp. 30–40 Read article
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Performance Analysis of Clustering Network Using Enhanced DEC Protocol for WSN
Abstract: Each node of a wireless sensor network (WSN) is connected to several other sensors. These sensor nodes can be deployed in dense for monitoring variety and wide range of applications. There are different types of protocols in WSN used to route the packets from source to destination. They are data-centric, hierarchical, and location-based and network flow and quality of service. To manage the energy consumption of WSN, one of the …
Published in Journal Of Network security · Vol. 4, Issue 1, 2016 · pp. 23–31 Read article
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Magnetic Properties of (ZnS)n (n=1-12) Cluster Due to B, C, N and O Doping
Abstract: First principal calculations have been performed using Spin polarized Density Functional Theory (DFT) to study the magnetic properties of B, N, C and O doped (ZnS)n (n = 1 to 12) nanoclusters. All dopants were doped at S site in (ZnS)n clusters. The binding energy of (ZnS)n clusters decrease when doped with B, C and N atoms where as it increases with O doping. The electronic HOMO-LUMO gap of (ZnS)n …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 16, Issue 3, 2014 · pp. 16–22 Read article
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Clustering Categorical Data Using Node Importance Method
Abstract: Normal 0 false false false EN-US X-NONE X-NONE Data clustering is an important technique in data analysis. It can be defined as a given set of data objects, the problem of clustering is to partition data objects into groups in such a way that objects in same group are similar and objects in different groups are dissimilar according to the predefined similarity measurement [Han Jiawei and Kamber Micheline. Data mining: …
Published in Current Trends in Information Technology · Vol. 1, Issue 2-3, 2011 · pp. 8–15 Read article
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Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 Read article
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Selection of Cluster Head in Wireless Sensor Network towards Extending Network Life Time
Abstract: Reduced energy consumption and extended lifetime are basic requirements of Wireless Sensor Network (WSN) with distributed nature and dynamic topological changes. The motes are arranged in clusters and only one mote is chosen as cluster head to synchronize and data routing. The proposed work introduces an innovative approach of choosing cluster head in artificially intelligent wireless sensor network. In the proposed work, the residual energy consumption plays the major role …
Published in Journal of Microcontroller Engineering and Applications · Vol. 3, Issue 3, 2016 · pp. 1–10 Read article
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Scalability Analysis of Semantic Relational Key Terms based Document Clustering Using Parsing Text Calcification
Abstract: Abstract: Document agglomeration, one among the standard info mining ways, is an unsupervised learning worldview wherever agglomeration techniques endeavor to tell apart-inborn groupings of the text documents, with the goal that a meeting of clusters is made during which clusters show high intra-cluster closeness and low bury cluster likeness. The importance of document agglomeration rises out of the big volumes of matter documents created. Albeit varied document agglomeration techniques are …
Published in Recent Trends in Programming languages · Vol. 6, Issue 3, 2019 · pp. 33–40 Read article
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Impact of Cluster Frontline Demonstrations on Blackgram on Enhancement of Income of Farmers in Dhubri District of Assam
Abstract: Blackgram is one of the very important pulse crops in Assam as well as India because of its very important dietary constituent for both human and animals. A study on impact of Cluster Frontline Demonstration (CFLD) on blackgram on enhancement of income of farmers in Dhubri district of Assam was carried out during 2021–22 to know the extent of vertical and horizontal penetration of technologies demonstrated under CFLD programmes and …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 11, Issue 2, 2022 · pp. 7–14 Read article
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Cluster based large scale Demonstration of improved wheat varieties in Silte zone, Southern Ethiopia
Abstract: Cluster Based Large Scale Demonstration of wheat was conducted at Alicho district and Worabe administrative town of Silte zone to increase production and productivity among wheat producer farmers. Once more, kebeles were purposefully chosen from each district based on the potential of the crop for producing wheat. From selected kebales115farmers were benefited from this intervention on 80 hectares of land clustered on three sites in 2021/22 cropping season. Ogolecho and …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 11, Issue 3, 2022 · pp. 41–46 Read article
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An Approach for Travel Pattern Analysis Using HDBSCAN and Apriori Algorithms
Abstract: Most mega-city regions around the world are suffering from an ongoing increase in the number of commuting trips. Understanding commuting patterns is crucial for both public and authority planners. The understanding of travel patterns helps passengers to know about the places and the time where they could get vacant transport and also helps authority planners in laying out a new transport service. The traditional way of understanding travel patterns includes …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 2, 2023 · pp. 1–9 Read article
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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
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Clustering the Data in Search Engines
Abstract: AbstractContents of the internet is rapidly growing day by day. To reach the information we search on the internet, we're using internet search engines, which can return millions of search results depends on the query. Finding the information needed on the search results can be a massive problem. Search result clustering is a useful operation to solve this problem. In this paper, results taken from search engines divided into a …
Published in Journal of Computer Technology & Applications · Vol. 5, Issue 3, 2014 · pp. 1–5 Read article
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A Latest Approach for Crime Rate Prediction and Analysis by Using the Clustering and Machine Learning Algorithm
Abstract: In our daily life, the collection and analysis of crime-related data is uncertain from a security perspective. Crime rate forecasting and analysis is a way of identifying and analyzing crime patterns in crime data contained in a crime database. Our system predicts what criminal activity occurs in everyday life in various parts of the world. Through the utilization of machine learning and data mining algorithms, it is possible to forecast …
Published in Journal Of Network security · Vol. 11, Issue 2, 2023 · pp. 32–42 Read article
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Superpixel Segmentation using DBSCAN Clustering Algorithm
Abstract: AbstractSuperpixel division strategies are generally utilized as a pre-preparing venture to accelerate picture handling tasks. They assemble the pixels of a picture into homogeneous locales while attempting to regard existing shapes. In this paper, we propose a quick superpixels division calculation with contour adherence utilizing the density based spatial clustering of applications with noise (DBSCAN) algorithm. We implement a two-stage processing to decrease the computational costs of superpixel algorithms. First …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 4, Issue 3, 2017 · pp. 26–36 Read article
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Cluster Head and RREQ Based Malicious Behaviour Detecting and Preventing Approach in WSN
Abstract: Wireless sensor network is a type of network which has no communications pattern for communicate between nodes, new nodes easily integrate in network so attacks easily deploy on it. Gray hole is additionally one of the attacks that are tough to notice as a result of it will behave each as normal node and malicious node. For detecting and preventing malicious behavior of node we propose a technique Cluster head …
Published in Journal of Operating Systems Development & Trends · Vol. 2, Issue 3, 2015 · pp. 1–9 Read article