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Edge-assisted indexing for highly dynamic and static data in mixed reality connected autonomous vehicles

Intelligent and Converged Networks 2024年第2期5卷 167-179页

作者： Daniel Mawunyo Doe Dawei Chen kyungtae han Haoxin Wang Jiang Xie Zhu han Department of Electrical and Computer Engineering University of HoustonHoustonTX 77004USA InfoTech Labs Toyota Motor North America Research and DevelopmentMountain ViewCA 94043USA Department of Computer Science Georgia State UniversityAtlantaGA 30302USA Department of Electrical and Computer Engineering University of North Carolina at CharlotteCharlotteNC 28223USA

The integration of Mixed Reality(MR)technology into Autonomous Vehicles(AVs)has ushered in a new era for the automotive industry,offering heightened safety,convenience,and passenger ***,the substantial and varied data generated by MR-Connected AVs(MR-CAVs),encompassing both highly dynamic and static information,presents formidable challenges for efficient data management and *** this paper,we formulate our indexing problem as a constrained optimization problem,with the aim of maximizing the utility function that represents the overall performance of our indexing *** optimization problem encompasses multiple decision variables and constraints,rendering it mathematically infeasible to solve ***,we propose a heuristic algorithm to address the combinatorial complexity of the *** heuristic indexing algorithm efficiently divides data into highly dynamic and static categories,distributing the index across Roadside Units(RSUs)and optimizing query *** approach takes advantage of the computational capabilities of edge servers or RSUs to perform indexing operations,thereby shifting the burden away from the vehicles *** algorithm strategically places data in the cache,optimizing cache hit rate and space utilization while reducing *** quantitative evaluation demonstrates the superiority of our proposed scheme,with significant reductions in latency(averaging 27%-49.25%),a 30.75%improvement in throughput,a 22.50%enhancement in cache hit rate,and a 32%-50.75%improvement in space utilization compared to baseline schemes.

关键词： mixed reality autonomous vehicles data indexing edge computing query optimization

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Strong contact coupling of neuronal growth cones with height-controlled vertical silicon nanocolumns

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Nano Research 2018年第5期11卷 2532-2543页

作者： Seong-Min Kim Seyeong Lee Dongyoon Kim Dong-Hee Kang Kisuk Yang Seung-Woo Cho Jin Seok Lee Insung S. Choi kyungtae Kang Myung-han Yoon School of Materials Science and Engineering Gwangju Institute of Science and Technology Gwongju 61005 Republic of Korea Department of Biotechnology Yonsei University 50 Yonsei-ro Seodaemun-gu Seoul 03722 Republic of Korea Department of Chemistry Sookmyung Women's University Seoul 04310 Republic of Korea Center for Cell-Encapsulation Research Department of Chemistry KAIST Daejeon 34141 Republic of Korea Department of Applied Chemistry Kyung Hee University Yongin Gyeonggi 17104 Republic of Korea

In this study, we report that height-controlled vertically etched silicon nano- column arrays （vSNAs） induce strong growth cone-to-substrate coupling and accelerate in vitro neurite development while preserving the essential features of initial neurite formation. Large-scale preparation of vSNAs with flat head morphology enabled the generation of well-controlled topographical stimulation without cellular impalement. A systematic analysis on topography- induced variations on cellular morphology and cytoskeletal dynamics was conducted. In addition, neurite development on the grid-patterned vSNAs exhibited preferential adhesion to the nanostructured region and outgrowth directionality. The arrangement of cytoskeletal proteins and the expression of a focal adhesion complex indicated that a strong coupling existed between the underlying nanocolumns and growth cones. Furthermore, the height-controlled nanocolumn substrates differentially modulated neurite polarization and elongation. Our findings provide an important insight into neuron-nanotopography interactions and their role in cell adhesion and neurite development.

关键词： vertical silicon nanostructures metal-assisted chemical etching primary hippocampal neurons neurite outgrowth cytoskeletal dynamics

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