Towards a Machine Learning Driven Trust Management Heuristic for the Internet of Vehicles by Sarah Ali Siddiqui, Adnan Mahmood, Quan Z. Sheng, Hajime Suzuki, Wei Ni

“…The first matrix (<i>FM1</i>) takes into account all the pairwise individual parameters as individual features, whereas the second matrix (<i>FM2</i>) considers the average of all pairwise computations performed for each individual parameter as one feature. …”
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Time Delay Estimation for Sound Source Localization Using CNN-Based Multi-GCC Feature Fusion by Haitao Liu, Xiuliang Zhang, Penggao Li, Yu Yao, Sheng Zhang, Qian Xiao

“…Furthermore, the proposed model offers the advantages of compact size and efficient computational performance when compared to existing methods. …”
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Path-oriented synchronized transit scheduling using time-dependent data by Lee, Kelvin, Jiang, Yu, Ceder, Avishai, Dauwels, Justin, Su, Rong, Nielsen, Otto Anker

“…It is found that the proposed valid inequalities could outperform them and combining different valid inequalities could further improve computational performance.…”
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Lane detection system for autonomous vehicle using image processing techniques by Mohd Kiblee, Shahizul Eza

“…A completely autonomous vehicle is one in which a computer performs all the tasks that the human driver normally would. …”
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Spectral domain convolutional neural network optimized for computational workload and memory access cost by Rizvi, Shahriyar Masud

“…The strategies involve the reduction of the output feature map (OFM) size, OFM depth, or both under an accuracy constraint to compute performance-optimized CNN inference and training. …”
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Smart EV Charging With Context-Awareness: Enhancing Resource Utilization via Deep Reinforcement Learning by Muddsair Sharif, Huseyin Seker

“…Notably, our proposed methodology, DQN, demonstrated superior computational performance compared to the others. Our results reveal that the proposed system achieves a remarkable, approximately 18&#x0025; enhancement in energy efficiency compared to traditional methods. …”
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Semantic Segmentation Optimized for Low Compute Embedded Devices by Hojun Son, James Weiland

“…We propose a modified Net score that includes frame per seconds to complement traditional metrics mean Intersection of Union (mIoU), the number of multiply-accumulate operations (GFLOPs), and the number of parameters to evaluate mobile computing performance. Our CNN achieved 65.7 FPS on GTX 1080, 76.7&#x0025; mIoU without ImageNet pre-training, while requiring 25 GFLOPs and 4.55M parameters, resulting in a 127.53 modified Net score compared to 119.89 for Deep Dual Resolution Neural Network (DDRNET23&#x005F;slim) and 115.39 for Regseg. …”
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Text Classification Based on Neural Network Fusion by Deageon Kim

“…In recent years, with the increase of data and the improvement of computing performance, the use of deep learning technology to represent and classify texts has attracted great attention. …”
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Endoscopic capsule robot-based diagnosis, navigation and localization in the gastrointestinal tract by Mark Hanscom, David R. Cave

“…Technological advancements in computation performance have led to improvements in image compression and transfer, as well as advancements in sensor detection and alternative methods of capsule localization. …”
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Wafer defect prediction with statistical machine learning by Arnold, Naomi (Naomi Aiko)

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Performance analysis of functional expansion tallies on 2D PWR pin cell by Han, Zhuoran

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Integrated transportation system design optimization by Taylor, Christine P. (Christine Pia), 1979-

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Planning and scheduling of concurrent high-level activities for UUV mission operations by Chang, Larry, S. M. Massachusetts Institute of Technology

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Embedded caching framework for privacy preserving data mining by Zhai, Ke

“…Although various algorithms in data mining have been enhanced to incorporate secure mechanisms for data privacy preservation, their computation performance is far too high to allow them to be practically useful. …”
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Measurements of the Higgs Boson in the H - τ τ decay channel by Howard, JR

“…In addition, two studies on enhancement of computing performance in the ATLAS trigger and data analysis pipeline are presented.…”

Optimal control and reinforcement learning for formula one lap simulation by Hoeppke, C

“…The exponential increase in computational performance has enabled the practical application of these algorithms. …”

Improving resource management with multi-instance broker scheduling algorithm in hierarchical grid computing by Yahaya, Bakri

“…In brief, this research aims to solve resource management issues so as to enhance the grid computing performance. The iHLBA scheduling algorithm was tested and it was found that the main issue was the delay occurring on the job submission. …”
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Split Pool Ligation-based Single-cell Transcriptome sequencing (SPLiT-seq) data processing pipeline comparison by Lucas Kuijpers, Bastian Hornung, Mirjam C. G. N. van den Hout - van Vroonhoven, Wilfred F. J. van IJcken, Frank Grosveld, Eskeatnaf Mulugeta

“…We provide an overview of the tools, their computational performance, functionality and impact on downstream processing of the single-cell data, which vary greatly depending on the tool used. …”
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Dynamic pore-scale modeling of residual fluid configurations in disordered porous media by Gong Yanbin, Sedghi Mohammad, Piri Mohammad

“…A heavily-parallelized implementation of this platform is further advanced to achieve an efficient computational performance. We first conduct primary drainage and imbibition simulations in pore networks representing Bentheimer and Berea sandstones. …”
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Development of a Computationally Efficient Tabulated Chemistry Solver for Internal Combustion Engine Optimization Using Stochastic Reactor Models by Andrea Matrisciano, Tim Franken, Laura Catalina Gonzales Mestre, Anders Borg, Fabian Mauss

“…Concerning computational performances, the newly proposed solver delivers remarkable speed-ups (up to four orders of magnitude) when compared to the online chemistry simulations. …”
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