Clustering
22 articles · search the full text for this term
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Efficient Clustering Techniques for Data Stream Mining
Abstract: Data mining mainly works on a massive database for storing heavy amount of data. It is generally essential for extracting the meaning insights from the massive, continuously growing database. The traditional method often struggles with sheer volume and the dynamic nature of the modern data. Data stream mining allows for the real-time analysis, means insights are generated as the data arrives, and not after the long batch process. This continuous …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 26–32 Read article
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A Survey on Intrusion Detection in Wireless Sensor Network
Abstract: The Wireless Sensor Networks (WSNs) consist of sensor and vehicle infrastructure deployed either on land or in the sea over a selected acoustic field. Such networks are launched in the execution of joint tasks that include monitoring the environmental conditions and collecting measured data. WSNs operate based on an interactive communication among different nodes and ground stations, which provides for real-time data transmission and analysis. This research work gives a …
Published in Journal Of Network security · Vol. 13, Issue 2, 2025 · pp. 51–56 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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Comparative Analysis of MCNN and RCNN for Speech Emotion Recognition Using Gender Information
Abstract: Speech emotion recognition is a speech processing task and a computer-based approach designed to identify and classify the emotions conveyed in audio signals. The aim of this system is to evaluate a speaker's emotional state, such as happiness, anger, sadness, or frustration, by analyzing their speech patterns, which include prosodic features like pitch, frequency, and rhythm. Speech emotion recognition is used in various real-life scenarios that include Customer Service, Healthcare, …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 1, 2025 · pp. 1–10 Read article
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An Innovative Fuzzy-Enhanced Black Widow Spider Optimization for Energy-Efficient Cluster Communication Through the Selection of the Ideal Cluster Head
Abstract: This paper presents a novel approach to enhance energy efficiency in cluster-based wireless sensor networks (WSNs) by integrating fuzzy logic with the black widow spider optimization (BWSO) algorithm. The focus of the suggested fuzzy-enhanced BWSO approach is on cluster head selection, which is essential for lowering energy consumption and enhancing network performance. The program uses fuzzy logic to assess a number of factors, including network density, node proximity, and energy …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 28–34 Read article
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A Machine Learning-based Analysis of Climate Change
Abstract: Climatic variations are a pressing global challenge that demands immediate and comprehensive attention. A wealth of articles has been published on climate change mitigation and adaptation, yet there remains a need for innovative methods to explore the complexities of climatic variations and to devise more efficient and effective strategies for adjustment and alleviation. With technological advancements, machine learning (ML) and deep learning (DL) approaches have derived significant popularity across various …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 1–10 Read article
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Improving Node Efficiency in Wireless Sensor Networks Using Advanced Clustering and Routing Techniques
Abstract: Many Internet of Things (IoT) applications, such as disaster relief, smart buildings, smart farming, and healthcare monitoring, have made use of wireless sensor networks (WSN). It is one of the alternatives to address different IoT difficulties in different contexts. One of the main problems with sensor networks is power efficiency. WSN operated on the Client-Server (CS) architecture in the past, however researchers suggested Mobile Agent (MA) based WSN to increase …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 2, 2024 · pp. 35–64 Read article
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User Engagement in Mobile Applications: Modeling and Predicting
Abstract: The mobile ecosystem is expanding rapidly, making app developers highly competitive. To keep users engaged, apps can anticipate when they might disengage, allowing developers to implement intervention tactics. This work demonstrates that it is possible to accurately forecast user disengagement using numerical models. The framework includes Cox proportional hazards, negative binomial, random forest, boosted-tree, and optimized agglomerative hierarchical clustering models. A 12-month observation dataset from a trash recycling app development …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 10, Issue 3, 2023 · pp. 1–7 Read article
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An Application of Recommendation Systems to Cluster-based Pattern Recognition
Abstract: Information overload is a common problem faced by internet users; so, the recommendation system is becoming increasingly important to this service. Collective filtering is used by recommendation systems to offer recommendations to individuals or for products based on their shared interests. Data or people should be grouped into clusters so that they have more in common with those in the same cluster and stand out from those in other clusters. …
Published in Recent Trends in Parallel Computing · Vol. 10, Issue 2, 2023 · pp. 28–36 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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Maths and Artificial Intelligence: Parallel Yet Intersecting Approach in School Curriculum
Abstract: Understanding students' level of math and working with them in handling their doubts, queries, deciding how they want to approach math, not only as a subject, but a way of interpreting it, thinking, living it, in a less stressed, anxiety and unnecessary troubles around it, which are generally there. We are studying uses of Artificial Intelligence (AI) in diagnosis of current standing of level of math in students and then …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 1, 2023 · pp. 24–30 Read article
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A Review Paper Based on Methodologies and Applications of Data Mining
Abstract: Data mining is like extracting record from a heap of data. Understanding database concepts is vital for data mining. Knowledge Discovery in Databases (KDD) is used to discover crucial data-related information. Our motive is being inundated with exceptional types of information science statistics, environmental records, financial records, and mathematical records. Summarizing the information manually is not possible because of the notable data boom inside the age of community and records …
Published in Recent Trends in Parallel Computing · Vol. 9, Issue 3, 2022 · pp. 8–15 Read article
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A Novel Clustering Techniques Evaluation using Monte Carlo Simulation
Abstract: In Machine Learning clustering is one the most significant method. Today, we have data in rich from many sources but in order to get meaningful information from it is very boring task. Machine learning clustering algorithms to create cluster to decode the meaningful information from the data, this analysis approach has gained much popularity in recent years. This paper explores evaluation performance of frequently used existing clustering techniques such as …
Published in Research & Reviews : Journal of Statistics · Vol. 10, Issue 3, 2021 · pp. 1–23 Read article
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Centrifugal Casting of Nano Crystalline TiB2 Reinforcement Particulate Reinforcement in Al-Alloy Matrix
Abstract: A method of producing Nano size TiB2 particles within an aluminium matrix is the in situ reaction synthesis method, using KBF4 and K2TiF6 potassium based bearing fluxes. The advantages of this in situ reactive process are a small particle size and good particle/matrix interfacial bonding. However, this method is limited to producing low particulate volume percentage material (˂6 vol%). To overcome this limitation, centrifugal casting has been investigated. A series …
Published in Journal of Materials & Metallurgical Engineering · Vol. 3, Issue 3, 2013 · pp. 7–13 Read article
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Survey on Intrusion Detection Using Data Mining Methods
Abstract: The present emerging information growth has made numerous challenges in the data mining. Data mining is the procedure of removing valid, before known, and comprehensive data sets for the future decision making. With the better technology through WWW, the streaming information comes into the picture with its challenges. The data, which alters with time and updates its value, is known as streaming information. As most of the data is streaming …
Published in Journal of Advanced Database Management & Systems · Vol. 3, Issue 2, 2016 · pp. 33–43 Read article
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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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Palm Recognition Using Hybrid Algorithm
Abstract: Biometric system is becoming more popular and increasingly important, since they provide more reliable and accurate means of identification. Now a days biometrics system is used almost everywhere for identification. In Japan, banks have used the palm vein authentication technology for customer identification since July 2004. In addition, Fujitsu has integrated the technology into the access control of electronic door lock systems. Their system has a false acceptance rate of …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 3, 2015 · pp. 12–19 Read article
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Image Segmentation Using Credibility Critical Values
Abstract: In this paper, a method of creating fuzzy data matrix (a matrix whose elements are fuzzy variables) representing an image is proposed. Further, a study on image segmentation carried out on the basis of such a matrix is carried out. This work considers three methods of crisp conversion available in credibility theory. Their performances have been evaluated under k-means clustering and rough k-means clustering with the help of a mammogram …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 2, 2015 · pp. 46–55 Read article
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Enhanced Incremental DB Scan Algorithm using Map-Reduce
Abstract: Distributed data mining is more efficient, scalable and its performance is better than the central data mining techniques. Incremental DBSCAN algorithm is better than the other method DBSCAN. Incremental DBSCAN can give better performance in distributed environment in terms of run time complexity using Hadoop platform. The proposed system uses spatial dataset i.e. dataset are distributed among different sites. Initially, clusters are generated at each site using DBSCAN algorithm. Then …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 3, Issue 2, 2015 · pp. 1–6 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