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finding » findings (Expand Search)
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Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm
Published 2022“…The antecedent part parameters (Gaussian membership function parameters) are encoded as a population of artificial swarm of grasshoppers and optimized using its algorithm. …”
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT
Published 2023“…<p dir="ltr">In mobile edge computing (MEC), it is difficult to recognise an optimum solution that can perform in limited energy by selecting the best communication path and components. This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”
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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
Published 2024“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”
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Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV
Published 2013Get full text
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The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions
Published 2022“…To this end, we carefully identify the types of DRL algorithms utilized in each related work, the elements of these algorithms, and the main findings of each related work. …”
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Learning-Based Spectrum Sensing and Access for Cognitive Radio Systems
Published 2015Get full text
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Competitive learning/reflected residual vector quantization for coding angiogram images
Published 2003“…Medical images need to be compressed for the purpose of storage/transmission of a large volume of medical data. Reflected residual vector quantization (RRVQ) has emerged recently as one of the computationally cheap compression algorithms. …”
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QoS-driven multicast tree generation using tabu search
Published 2020“…The problem to be solved is to find a minimum cost multicast treee where each source to destination path is contrained by a delay bound. …”
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Optimal Routing Protocol in Multimedia Wireless Sensor Networks
Published 2011Get full text
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31
Design and analysis of entropy-constrained reflected residual vector quantization
Published 2002“…Residual vector quantization (RVQ) is a vector quantization (VQ) paradigm which imposes structural constraints on the encoder in order to reduce the encoding search burden and memory storage requirements of an unconstrained VQ. …”
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Evacuation of a highly congested urban city
Published 2017“…The algorithm uses Dijkstras algorithm to find the shortest path(s) and a modified greedy algorithm to assign maximum flows to selected paths given a specific schedule per time interval. …”
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A survey and comparison of wormhole routing techniques in a meshnetworks
Published 1997“…These multiprocessing systems consist of processing elements or nodes which are connected together by interconnection networks in various topologies. …”
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SDODV. (c2018)
Published 2018“…Experimental results prove that SDODV out-performs shortest path and reduces the energy consumption.…”
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Optical recognition of electrical circuit drawings
Published 1997Get full text
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Efficient Seismic Volume Compression using the Lifting Scheme
Published 2000“…In addition, the lifting scheme offers: 1) a dramatic reduction of the required auxiliary memory, 2) an efficient combination with parallel rendering algorithms to perform arbitrary surface and volume rendering for interactive visualization, and 3) an easy integration in the parallel I/O seismic data loading routines. …”
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Multidimensional Gains for Stochastic Approximation
Published 2019“…Necessary and sufficient conditions for M≥ N algorithms are presented pertaining to algorithm stability and convergence of the estimate error covariance matrix. …”
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On the disk dimension of planar graphs
Published 2011“…More significantly, we devise a direct and highly practical linear-time algorithm to decide whether an arbitrary graph has fixed disk dimension k or less. …”
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PERF solutions for distributed query optimization. (c1999)
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masterThesis -
40
A Geometric-Primitives-Based Compression Scheme for Testing Systems-on-a-Chip
Published 2001“…In this paper, it is assumed that an embedded core will be used to execute the decompression algorithm and decompress the test data.…”
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