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2021 IEEE Transactions on Emerging Topics in Computing  
Frost Surrogate Applications for Early Design Stage Multicore Contention Modeling by G. Fernandez, J. Abella, G. Bernat, and F.J.  ...  AraujoA Platform-Aware Model-Driven Embedded Software Engineering Process Based on Annotated Analysis Models by P. Parra, O.R. Polo, J. Fernandez, A. Da Silva, S. Sanchez, and A. Martinez Bagatin, S.  ... 
doi:10.1109/tetc.2021.3061783 fatcat:tvkzgywrnfftnnu3pgrhgpzlda

Guest Editorial: IEEE Transactions on Emerging Topics in Computing Special Issue on Advanced Command, Control and On-Board Data Processing for Space Avionic Systems

Gianluca Furano, Marco Ottavi
2021 IEEE Transactions on Emerging Topics in Computing  
Similarly, the development of complex software systems for Space is the focus of "Surrogate Applications for Early Design Stage Multicore Contention Modeling".  ...  The paper introduces a method to optimally allocate software development time between early design phases and late design phases by proposing surrogate applications and a framework to generate them.  ... 
doi:10.1109/tetc.2021.3053795 fatcat:4ufehampnfc2lkfanfvzeu4piu

Unravelling the mechanisms that determine the uptake and metabolism of magnetic single and multicore nanoparticles in a Xenopus laevis model

M. Marín-Barba, H. Gavilán, L. Gutiérrez, E. Lozano-Velasco, I. Rodríguez-Ramiro, G. N. Wheeler, C. J. Morris, M. P. Morales, A. Ruiz
2018 Nanoscale  
Nanoparticles' structure (single or multicore) and their surface chemistry determine how the embryos absorb and activate the iron metabolic pathway.  ...  Here we report for the first-time toxicity and metabolization of single-core and multicore nanoparticles using a combination of in vitro cell culture models and an in vivo X. laevis embryo model.  ...  SC-DMSA and MC-Cit, respectively), an important requirement for biomedical applications.  ... 
doi:10.1039/c7nr06020c pmid:29242877 fatcat:75ilw7s2i5bbbjdrthgcx6avry

Applied inference

Benjamin C. Lee, David Brooks
2010 ACM Transactions on Architecture and Code Optimization (TACO)  
Collectively these studies demonstrate regression models' ability to expose trends and identify optima in diverse design regions, motivating the application of such models in statistical inference for  ...  These compromises are potential core designs in a heterogeneous multicore architecture.  ...  are not feasible early in the design process.  ... 
doi:10.1145/1839667.1839670 fatcat:4rwuf5ehqjeitheo6n5e6ecbbm

DNA methylome of human neonatal umbilical cord: Enrichment of differentially methylated regions compared to umbilical cord blood DNA at transcription factor genes involved in body patterning and effects of maternal folate deficiency or children's sex

Kenichi Sakurai, Keiko Shioda, Akifumi Eguchi, Masahiro Watanabe, Hidenori Miyaso, Chisato Mori, Toshi Shioda, Osman El-Maarri
2019 PLoS ONE  
Here, we propose umbilical cord tissue (UC), which accumulates substances delivered to fetuses during gestation, as an alternative surrogate for epigenetic studies on fetuses.  ...  Our study suggests that UC is useful as an alternative surrogate for studying environmental effects on DNA methylation in human fetuses, compensating CB by providing additional information about epigenetic  ...  Hiromi Tanabe and Ms Tomomi Kokufuta for their technical supports. We also thank Professor Hideoki Fukuoka (Waseda University) for his contribution towards planning and conducting C-MACH.  ... 
doi:10.1371/journal.pone.0214307 pmid:31063509 pmcid:PMC6504184 fatcat:urygmwosdbhd3nhct64urtplcq

Contents

2019 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring)  
L1 and L2 GPS Applications . . . . . . . . . . . . . . . . . . . . . . . . . . 1196 Statistical Design Centering of Microwave Circuits Using Modified Trust Region Optimization and Space Mapping Surrogates  ...  of Carrier Oscillations along B-DNA Aperiodic and Periodic Polymers . . . . . . . . . . . . 831 A Miniaturized Design of Shared-aperture Antenna with High Aperture Reuse Ratio for 5G Applications .  ... 
doi:10.1109/piers-spring46901.2019.9017748 fatcat:lmmr7cnm7nelbbz3f6arofik4q

Assessing the Efficacy of Nano- and Micro-Sized Magnetic Particles as Contrast Agents for MRI Cell Tracking

Arthur Taylor, Anne Herrmann, Diana Moss, Violaine Sée, Karen Davies, Steve R. Williams, Patricia Murray, Masaya Yamamoto
2014 PLoS ONE  
tracking in vivo was tested using a chick embryo model.  ...  Importantly, our data suggest that larger particles might confer advantages for longer-term imaging.  ...  Acknowledgments The authors would like to acknowledge Ian Prior (University of Liverpool) for access to electron microscopy facilities and Michael Barrow (University of Liverpool) for support with zeta  ... 
doi:10.1371/journal.pone.0100259 pmid:24959883 pmcid:PMC4069012 fatcat:m3yj4d4iq5hkvnq47umuva3lue

Cloud-Based Augmentation for Mobile Devices: Motivation, Taxonomies, and Open Challenges

Saeid Abolfazli, Zohreh Sanaei, Ejaz Ahmed, Abdullah Gani, Rajkumar Buyya
2014 IEEE Communications Surveys and Tutorials  
mobile applications.  ...  CMA is the state-of-the-art mobile augmentation model that employs resource-rich clouds to increase, enhance, and optimize computing capabilities of mobile devices aiming at execution of resource-intensive  ...  Unlike elastic application model [33] , the design and implementation of components in µCloud is statically performed in early development phase.  ... 
doi:10.1109/surv.2013.070813.00285 fatcat:77v7cyzdwrbonll45npxl4loxa

Cloud-Based Augmentation for Mobile Devices: Motivation, Taxonomies, and Open Challenges

Saeid Abolfazli, Zohreh Sanaei, Ejaz Ahmad, Abdullah Gani, Rajkumar Buyya
2014 Figshare  
mobile applications.  ...  CMA is the state-of-the-art mobile augmentation model that employs resource-rich clouds to increase, enhance, and optimize computing capabilities of mobile devices aiming at execution of resource-intensive  ...  Unlike Elastic Application model, the design and implementation of components in µCloud is statically performed in early development phase.  ... 
doi:10.6084/m9.figshare.1038330 fatcat:y3ybv3eujjbu3o45pbh3tgid4u

Breaking the memory wall in MonetDB

Peter A. Boncz, Martin L. Kersten, Stefan Manegold
2008 Communications of the ACM  
Recently there is interest in the use of Flash memory for database storage as well as query parallelization for multicore CPUs.  ...  Database technology, as still employed in the majority of today's commercial systems, was designed for hardware of the 1970-1980s and application characteristics that existed at the time.  ... 
doi:10.1145/1409360.1409380 fatcat:ioi2qrcty5ho5ji5kwbvx3nub4

Large-scale data mining using genetics-based machine learning

Jaume Bacardit, Xavier Llorà
2013 Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery  
This capacity goes beyond the innate massive parallelism of evolutionary computation methods by the proposal of a variety of mechanisms specifically tailored for machine learning tasks, including knowledge  ...  Meandre uses a decentralized scheduling policy designed to maximize the use of multicore architectures.  ...  Finally, recently Franco et al. 17 have proposed models for the initialization stage of the BioHEL 3 GBML system.  ... 
doi:10.1002/widm.1078 fatcat:3av5ue3zvranth3z7pvipcyz44

Heterogeneity in Mobile Cloud Computing: Taxonomy and Open Challenges

Zohreh Sanaei, Saeid Abolfazli, Abdullah Gani, Rajkumar Buyya
2014 IEEE Communications Surveys and Tutorials  
Multidimensional heterogeneity in MCC results in application and code fragmentation problems that impede development of cross-platform mobile applications which is mathematically described.  ...  In the burgeoning heterogeneous MCC domain, the comprehension and settlement of fundamental problems in the early development stages leads to the success of MCC.  ...  To develop CMH applications, developers should design the application for the cloud as well as the mobile side.  ... 
doi:10.1109/surv.2013.050113.00090 fatcat:rlayt7itnvacrjdn26r7hnhxzu

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI [article]

Jiangchao Yao, Shengyu Zhang, Yang Yao, Feng Wang, Jianxin Ma, Jianwei Zhang, Yunfei Chu, Luo Ji, Kunyang Jia, Tao Shen, Anpeng Wu, Fengda Zhang (+6 others)
2022 arXiv   pre-print
Specifically, we are the first to set up the collaborative learning mechanism for cloud and edge modeling with a thorough review of the architectures that enable such mechanism.  ...  In this survey, we conduct a systematic review for both cloud and edge AI.  ...  However, it remains unclear whether early exiting is equally applicable to generative models such as GPT-3 and text generation tasks.  ... 
arXiv:2111.06061v3 fatcat:5rq6s5s4cvcidblidgahwynp34

Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges [article]

Bernd Bischl, Martin Binder, Michel Lang, Tobias Pielok, Jakob Richter, Stefan Coors, Janek Thomas, Theresa Ullmann, Marc Becker, Anne-Laure Boulesteix, Difan Deng, Marius Lindauer
2021 arXiv   pre-print
., based on resampling error estimation for supervised machine learning, can be employed.  ...  This work is accompanied by an appendix that contains information on specific software packages in R and Python, as well as information and recommended hyperparameter search spaces for specific learning  ...  Lars Kothoff (University of Wyoming) for their valuable feedback on the manuscript.  ... 
arXiv:2107.05847v3 fatcat:u7zae4vaqffutfm7uvwrda5yp4

Nanomedicine Ex Machina: Between Model-Informed Development and Artificial Intelligence

Mônica Villa Nova, Tzu Ping Lin, Saeed Shanehsazzadeh, Kinjal Jain, Samuel Cheng Yong Ng, Richard Wacker, Karim Chichakly, Matthias G. Wacker
2022 Frontiers in Digital Health  
In our review, we present an overview of modeling and artificial intelligence applications in the development and manufacture of nanomedicines.  ...  Today, a growing number of computational aids and simulations are shaping model-informed drug development.  ...  In this context, the concentration of the drug in the blood plasma serves as a surrogate for bioavailability (3).  ... 
doi:10.3389/fdgth.2022.799341 pmid:35252958 pmcid:PMC8894322 fatcat:rollhkjugfg75nss43bqjtopfq
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