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25 articles for “partitioning algorithm”
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Survey on Item Set Mining Algorithms
Abstract: In this paper, we have a tendency to gift a literature survey of existing frequent item set mining algorithms. The idea of frequent item set mining is additionally mentioned briefly. The working procedure of some fashionable frequent item set mining techniques is given. Conjointly the deserves and demerits of each method are described. It’s found that the frequent item set mining remains a burning analysis topic. Cite this Article:Aakash Sahu. …
Published in Journal of Advances in Shell Programming · Vol. 2, Issue 1, 2015 · pp. 7–10 Read article
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3D-IC Partitioning and TSV Sharing Optimization Algorithm
Abstract: Recent technologies are in need of shorter vertical interconnects, thus forcing the integration technology from 2D to 3D. Because more than 50% of dynamic power consumption is due to interconnects. As a solution, 3D integration consists of stacking integrated circuits and connecting them with short vertical interconnects. TSV is used to vertically connect the hardware components in different dies stacked in 3D ICs. But in floor planning TSVs are very …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 3, Issue 2, 2016 · pp. 6–10 Read article
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Multiple Fragment Information Gathering Using Accumulating Framework
Abstract: The approach of use mobile sink, has been adopted in wireless sensor networks ( WSN) and wireless sensor and actor network( WSAN) to achieve advanced efficiency in terms of gathering data from sensors. Mobility-assisted data collection brings in new opportunity to improve the energy efficiency sensor nodes. However, mobile sink also introduces new challenges such as large data collection tansy. A lot of research efforts have been devoted to reduce …
Published in Journal of Web Engineering & Technology · Vol. 2, Issue 3, 2015 · pp. 14–18 Read article
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Customer Segmentation for Enhancing Customer Centric Business
Abstract: Customer segmentation is grouping customers based on similarities so companies can approach each group for marketing effectively and appropriately. Customer segmentation is important for enhancing customer centric business for gaining retention among customers by campaigning them using better marketing strategies, causing more institutional benefit. This paper segments customers by analyzing their characteristics based on both demographic and behavioral attributes using K-Means clustering algorithm and Self-Organizing Maps (SOM). K-Means is a …
Published in E-Commerce for Future & Trends · Vol. 8, Issue 1, 2021 · pp. 17–31 Read article
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Advancements in K-Means Clustering: Boosting Algorithm Performance through Innovations
Abstract: K-Means clustering is a widely used unsupervised learning algorithm for partitioning a dataset into distinct clusters. Despite its popularity and simplicity, K-Means has several limitations, such as sensitivity to initial centroids, convergence to local minima, and inefficiency with large datasets. This paper reviews recent advancements aimed at addressing these challenges and enhancing the performance of the K-Means algorithm. Innovations include improved initialization methods, such as K-Means++, which significantly reduce the …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 30–37 Read article
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Homogeneous Video Transcoding Functions for High-Efficiency Video Coding
Abstract: High-efficiency video coding (HEVC) is the successor of H.264/AVC and it gives the higher compression ratio and high quality video than H.264. But, HEVC increases the computational complexity of video coding due to its flexible quad tree partitioning structure. Transcoding algorithms are very much required to associate the HEVC standard into real applications. Homogeneous video transcoding is used for conversion between the same video formats. A higher quality video at …
Published in Current Trends in Signal Processing · Vol. 7, Issue 2, 2017 · pp. 32–36 Read article
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A Clustering Based CPU Scheduling Algorithm for Real Time Systems
Abstract: CPU scheduling is a fundamental function of operating system. The performance and efficiency of multitasking operating systems mainly depend upon the uses of CPU scheduling algorithm. When an operating system wants to execute a process, it does not know the execution time it needs. After running, the exact execution time of that process would appear. Here we present a new scheduling approach using the Partitioning Around Medoid (PAM) clustering algorithm …
Published in Current Trends in Information Technology · Vol. 1, Issue 1, 2011 Read article
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Hardware Design using Flexible Hk-Means
Abstract: High performance hardware is required to meet the necessities of consumer electronics. Color quantization and image partition are an inevitable part for different applications, and HKMeans is the main algorithm that is used for color quantization and image partition owing to its low cost, less computational time and the hardware area required. The computational time and the hardware area increases as the quantization number increases. Hierarchical K-means or HK-Means is …
Published in Journal of Electronic Design Technology · Vol. 6, Issue 1, 2015 · pp. 30–35 Read article
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A Multi-Quadrant, Integrated and Secure Model of Multiple Watermarking
Abstract: Watermarking safeguards the copyright of digital images with its original owner. A watermarking model is projected by conjoining three distinct multiple watermarking approaches. The secure model is obtained by integrating multiple watermarking with the latest secure cryptographic algorithms. The proposed model will improve copyright protection, achieve large embedding capacity and provide a stronger association amongst image and watermark for integrity and authentication. The multiple watermarking model partitions the cover image …
Published in Journal of Open Source Developments · Vol. 1, Issue 2, 2014 · pp. 15–28 Read article
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Optimizing Data Processing Efficiency in Big Data: Advanced MapReduce Algorithm Innovations
Abstract: The exponential growth of big data in recent years has created an urgent need for innovative and efficient processing frameworks capable of managing and analyzing massive and complex datasets. Among these, MapReduce has gained prominence as a powerful tool for distributed data processing due to its simplicity and scalability. However, traditional MapReduce frameworks often encounter significant limitations in terms of efficiency, scalability, and resource optimization, particularly when handling large-scale and …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
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Modified Listless Set Partitioning in Hierarchical Trees (MLS) for Memory Constrained Image Coding Applications
Abstract: SPIHT image coding algorithm is a very effective state-of-art technique for compression of wavelet transformed images. However, the use of three continuously growing linked lists, limit its applications to achieve high quality images in memory constrained environments.The No List SPIHT (NLS) is an attempt to implement SPIHT algorithm without lists, but it uses 4 bits per coefficient state markers to keep track of significant/insignificant information of pixels/sets. This paper presents …
Published in Current Trends in Signal Processing · Vol. 2, Issue 1-3, 2012 · pp. 56–66 Read article
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Analysis of Image Coders
Abstract: AbstractIn this paper we work on the performance analysis of well-known image compression algorithm i.e., wavelet based image compression which is Set Partition in Hierarchical Tree (SPIHT) and also no list SPIHT (NLS). As SPIHT uses three variable lists which require large hardware implementation and hence extra cost and high encoding and decoding time is required but NLS use marker instead of list which are placed on lower nodes of …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 3, Issue 3, 2016 · pp. 26–30 Read article
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A Survey on Different Clustering Algorithms with Their Major Features
Abstract: Data mining techniques make it possible to search large amounts of data for characteristic rules and patterns. Clustering is used to organize data for efficient retrieval. The aim is to create homogeneous subgroups of examples. The individuals in the same subgroup are similar; the individuals in different subgroups are as different as possible. One of the problems in clustering is the identification of clusters in given data. A popular technique …
Published in Journal of Web Engineering & Technology · Vol. 1, Issue 3, 2014 · pp. 19–24 Read article
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Improved Vision Based Algorithm for Deep Web Data Extraction
Abstract: Several systems and languages have been proposed for solving web-data management problems, but none of existing system addresses all the problems from a unified perspective. Most of the existing link analysis algorithms treat a web page as a single node in the web graph. However, in most cases, a web page contains multiple semantics and hence the web page might not be considered as the atomic node. New web content, …
Published in Journal of Web Engineering & Technology · Vol. 2, Issue 2, 2015 · pp. 28–37 Read article
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A Memory Efficient No List SPECK (NSK) Wavelet Image Coder for Memory-constrained Applications
Abstract: In this paper, a fast and memory-efficient listless version of set-partitioned embedded block (SPECK) image coder is proposed. Due to the use of linked lists, the original SPECK algorithm requires large run-time memory, making it unsuitable for memory-constrained applications. The proposed coder replaces linked list with small fixed size static memory, to keep track of blocks in set partitioning only and use only two markers to facilitate coding. Replacement of …
Published in Journal of Remote Sensing & GIS · Vol. 3, Issue 3, 2012 · pp. 1–16 Read article
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Implementation of MRPrePost Parallel Algorithm based on Hadoop Platform for Large-Data Mining
Abstract: AbstractThe volume, velocity and variety of the data have increased several folds in the past few years. The conventional algorithms and techniques used to mine such huge data are found to be less efficient because these algorithms consider only the large threshold value due to which the number of candidates can be reduced, but this will lead mining association rules production to be inaccurate due to low utilization of data. …
Published in Recent Trends in Parallel Computing · Vol. 4, Issue 2, 2017 · pp. 10–20 Read article
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Enhanced Security for Autonomous Mobile Mesh Networks Using Crypto Algorithm
Abstract: Mobile ad hoc networks (MANETs) are ideal for situations where a fixed infrastructure is unavailable or infeasible. Today’s MANETs, however, may suffer from network partitioning. This limitation makes MANETs unsuitable for applications such as crisis management and battlefield communications, in which team members might need to work in groups scattered in the application terrain. In such applications, inter-group communication is crucial to the team collaboration. To address this weakness introduce …
Published in Recent Trends in Programming languages · Vol. 3, Issue 1, 2016 · pp. 17–24 Read article
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Development and Performance Evaluation of Efficient Low-Complexity SPIHT Image Coder
Abstract: Wavelet transform is one of the advanced, effective and computationally fast methods for image data as well as video compression. The wavelet based image compression is particularly a nonreversible method that has been growing computationally more complicated as they getting more accurate and reliable. In this work we have developed an image compression technique based on main concepts related to partial ordering of the coefficients of image matrix elements by …
Published in Journal of Advanced Database Management & Systems · Vol. 2, Issue 3, 2015 · pp. 5–10 Read article
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Learning-based Edge Detection for Video Sequences
Abstract: The advancing fields in video technology like that of 3D TV and Free Viewpoint Video essentially requires more information to transmit in addition with the 2D color maps. This information is the depth maps of the accompanying scenes from the videos sequences in order to facilitate rendering of arbitrary viewpoints within it. Soft computing approaches such as consisting of fuzzy logic, neural or evolutionary computation are the emerging fields with …
Published in Recent Trends in Parallel Computing · Vol. 2, Issue 3, 2015 · pp. 1–19 Read article
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Privacy Preserving of Vertically Partitioned Data Using Elliptical Curve Cryptography
Abstract: Data mining's privacy problems have become a big problem as a result of financial considerations. This work investigates the topic regarding the issue of privacy-preserving global association rule analysis over several parties in vertically partitioned data to efficiently prevent hidden trends and perform computations across the parties while respecting the privacy of their data. After that, it suggests using Shamir's method of secret sharing to support distributed mining of association …
Published in Journal of Advanced Database Management & Systems · Vol. 9, Issue 3, 2022 · pp. 31–38 Read article