Search Results - (( a distribution free algorithm ) OR ( pre evaluation based algorithm ))
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1
EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method
Published 2018“…The accuracy of ESL depends on all the stages of data processing including: head model reconstruction, signal pre-processing and inverse solution. Therefore, a standardized algorithm with less supervision is desired to utilize ESL for pre-surgical evaluation. …”
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Thesis -
2
Mobile Crowd Steering Evacuation Model via Agent Based Simulation by Applying the Social Force Model
Published 2025“…The evaluation states that the existing agent-based steering model computes the complete set of collision-free paths with the least travel time among agents to make path decisions based on updated information. …”
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3
Optimizing Cloud Storage Costs: Introducing the Pre-Evaluation-Based Cost Optimization (PECSCO) Mechanism
Published 2025“…The core of the algorithm utilizes a Genetic Algorithm (GA) to find the optimal position for the first evaluator by minimizing the total distance between this evaluator and all CCTV nodes, aiming for surveillance efficiency. …”
Conference paper -
4
Self-Schedule and Self-Distributive MAC Scheduling Algorithms for Next-Generation Sensor Networks
Published 2015“…According to the proposed algorithms, each node maps a conflict-free time slot for itself up to 2-hop neighboring nodes. …”
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5
An Improved Distributed Scheduling Algorithm for Wireless Sensor Networks
Published 2012“…Simulation results show that the IDSA significantly outperforms a representative distributed random slot assignment algorithm (DRAND).…”
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6
Distance vector-hop range-free location algorithm for wireless sensor network
Published 2015“…Distance Vector-Hop (DV-Hop) algorithm has become the focus of studies for range-free localization algorithms. …”
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7
Effects of Different Superpixel Algorithms on Interactive Segmentations
Published 2022“…In this study, five different types of superpixels ranging from watershed, density, graph, clustering and energy optimization categories are evaluated. The superpixels generated by these five algorithms will be used on two interactive image segmentation algorithms: i) Maximal Similarity based Region Merging (MSRM) and ii) Graph-Based Manifold Ranking (GBMR) with single and multiple strokes on various images from the Berkeley image dataset. …”
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8
Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…Evaluation was made based on various evaluation metrics related to outlier detection and clustering quality. …”
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9
Effects of Different Superpixel Algorithms on Interactive Segmentations
Published 2022“…In this study, five different types of superpixels ranging from watershed, density, graph, clustering and energy optimization categories are evaluated. The superpixels generated by these five algorithms will be used on two interactive image segmentation algorithms: i) Maximal Similarity based Region Merging (MSRM) and ii) Graph-Based Manifold Ranking (GBMR) with single and multiple strokes on various images from the Berkeley image dataset. …”
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10
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…To validate this algorithm, the modified word vectors are compared with original LLM-generated word vectors to evaluate their reflection of the intended context. …”
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11
Distributive and self-sustainable scheduling algorithm for wireless sensor networks
Published 2013“…In this paper, we propose a distributive and self-sustainable scheduling algorithm (DSSA). …”
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12
Distributive and self-sustainable scheduling algorithm for wireless sensor networks
Published 2013“…In this paper, we propose a distributive and self-sustainable scheduling algorithm (DSSA). …”
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13
Distributive and self-sustainable scheduling algorithm for wireless sensor networks
Published 2013“…In this paper, we propose a distributive and self-sustainable scheduling algorithm (DSSA). …”
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14
Block based low complexity iterative QR precoder structure for Massive MIMO
Published 2021“…Meanwhile, we maximize the sum rate and also consider the restrictions on the computational complexity at the base station. In this thesis, we also study and evaluate different conventional linear pre-coding schemes as well as how they relate to optimal structure of the solution which maximize the system performances. …”
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15
Case Slicing Technique for Feature Selection
Published 2004“…This technique with k = 10 has been used in this thesis to evaluate the proposed approach. CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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16
Evaluation of sparsifying algorithms for speech signals
Published 2012“…Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) will be compared and evaluated based on Gini Index. Sparsity properties and measures will be reviewed in this paper. …”
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Performance evaluation of automatic number plate recognition on android smartphone platform
Published 2017“…For comparison purpose, the template matching based OCR will be compared to ANN based OCR. Performance of the proposed algorithm was evaluated on the developed Malaysian number plates’ image database captured by smartphone’s camera. …”
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19
Non-regularized reconstruction of magnetic moment distribution of magnetic nanoparticles using barnacles mating optimizer
Published 2023“…A simulated magnetization curve of unimodal moment distributions from 1 mT to 1 T is used to minimize a model-free magnetic moment distribution. …”
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20
A New Pre-Processing Technique For Computational Of Stereo Matching Algorithm
Published 2021“…Weighted Median (WM) filter is that applied to secure the final disparity map for noise reduction and smoothening to the disparity map. Based on Middlebury Standard Benchmarking Dataset, the proposed algorithm has 23.35% accuracy for nonocc error and 31.65% accuracy for all error, which yields a better accuracy compared to some works in the evaluation dataset.…”
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