检索结果-内蒙古大学图书馆

Advanced Functional Materials 2018年第18期28卷

作者： Thanh Nho Do Hung Phan Thuc‐Quyen Nguyen Yon Visell Department of Electrical Computer Engineering Media Arts and Technology Program California NanoSystems Institute University of California Santa Barbara CA 93106 USA Department of Chemistry and Biochemistry University of California Santa Barbara CA 93106 USA

Stochastic geometry model for multi-channel fog radio access networks

学校读者我要写书评

暂无评论

Stochastic geometry model for multi-channel fog radio access...

International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

作者： Mostafa Emara Hesham ElSawy Sameh Sorour Samir Al-Ghadhban Mohamed-Slim Alouini Tareq Y. Al-Naffouri Department of Electrical Engineering King Fahd University of Petroleum and Minerals (KFUPM) Saudi Arabia King Abdullah University of Science and Technology Thuwal SA Department of Electrical and Computer Engineering University of Idaho USA CEMSE Division EE program King Abdullah University of Science and Technology (KAUST) Saudi Arabia

ISBN: (纸本)9781509047109

Cache-enabled base station (BS) densification, denoted as a fog radio access network (F-RAN), is foreseen as a key component of 5G cellular networks. F-RAN enables storing popular files at the network edge (i.e., BS caches), which empowers local communication and alleviates traffic congestions at the core/backhaul network. The hitting probability, which is the probability of successfully transmitting popular files request from the network edge, is a fundamental key performance indicator (KPI) for F-RAN. This paper develops a scheduling aware mathematical framework, based on stochastic geometry, to characterize the hitting probability of F-RAN in a multi-channel environment. To this end, we assess and compare the performance of two caching distribution schemes, namely, uniform caching and Zipf caching. The numerical results show that the commonly used single channel environment leads to pessimistic assessment for the hitting probability of F-RAN. Furthermore, the numerical results manifest the superiority of the Zipf caching scheme and quantify the hitting probability gains in terms of the number of channels and cache size.

关键词： Stochastic processes Mathematical model Geometry Interference Cellular networks Numerical models Conferences

Liquid crystal colloids

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Smalyukh, Ivan I. Department of Physics Department of Electrical Computer and Energy Engineering Soft Materials Research Center and Materials Science and Engineering Program University of Colorado BoulderCO80309 United States Renewable and Sustainable Energy Institute National Renewable Energy Laboratory University of Colorado BoulderCO80309 United States

Colloids are abundant in nature, science and technology, with examples ranging from milk to quantum dots and the "colloidal atom" paradigm. Similarly, liquid crystal ordering is important in contexts ranging from biological membranes to laboratory models of cosmic strings and liquid crystal displays in consumer devices. Some of the most exciting recent developments in both of these soft matter fields emerge at their interface, in the fast-growing research arena of liquid crystal colloids. Mesoscale self-assembly in such systems may lead to artificial materials and structures with emergent physical behavior arising from patterning of molecular order and nano- or micro-particles into precisely controlled configurations. Liquid crystal colloids show an exceptional promise of new discovery that may impinge on the composite material fabrication, low-dimensional topology, photonics, and so on. Starting from physical underpinnings, I review the state of art in this fast-growing field, with a focus on its scientific and technological potential. Copyright © 2017, The Authors. All rights reserved.

关键词： Self assembly

A variable step-size MPPT for sensorless current model predictive control for photovoltaic systems

学校读者我要写书评

暂无评论

A variable step-size MPPT for sensorless current model predi...

2016 IEEE Energy Conversion Congress and Exposition, ECCE 2016

作者： Metry, Morcos Shadmand, Mohammad B. Balog, Robert S. Rub, Haitham Abu Renewable Energy and Advanced Power Electronics Research Laboratory Department of Electrical and Computer Engineering Texas AandM University College StationTX77843 United States Electrical and Computer Engineering Program Texas AandM University at Qatar Qatar Foundation Doha23874 Qatar

ISBN: (纸本)9781509007370

Variability of the solar energy resources requires highly effective maximum power point tracking (MPPT) to ensure maximum energy harvesting from the photovoltaic (PV) modules. To accomplish this, a MPPT controller typically requires accurate knowledge of the voltage and current from the PV module, and must converge quickly with minimal hunting around the maximum power point (MPP). Conventional MPPT techniques use fixed step-size perturbation which need to be optimized for one of two objectives: reducing the convergence settling time, or reducing the steady state ripple. Also, the required sensors increase system cost and can cause reliability issues, particularly for the current sensors which can exhibit thermal drift and degrade over time. This paper presents a highly efficient, variable-step sensorless current MPPT controller using an observer-based model derived from the principles of model predictive control (MPC) to adaptively determine the perturbation step-size. The proposed variable step, sensorless current, model predictive control maximum power point tracking (VS-SC-MPC-MPPT) continuously adjusts the perturbation step size using the predicted dynamic model to enable fast convergence and small limit cycle, without the need of expensive measuring devices. The performance of the VS-SC-MPC-MPPT in this paper is compared to previously developed MPC-MPPT methods. The provided investigation aims to demonstrate higher system efficacy with lower cost. The feasibility of the proposed controller is verified though computer simulation and real time simulation using dSPACE DS1007. © 2016 IEEE.

关键词： Model predictive control

Kernel method for detecting higher order interactions in multi-view data: An application to imaging, genetics, and epigenetics

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Alam, M. Ashad Lin, Hui-Yi Calhoun, Vince Wang, Yu-Ping Department of Biomedical Engineering Tulane University New OrleansLA70118 United States Biostatistics Program Louisiana State University Health Sciences Center New OrleansLA70112 United States Department of Electrical and Computer Engineering University of New Mexico AlbuquerqueNM87131 United States

Technological advances are enabling us to collect multiple types of data at an increasing depth and resolution while decreasing the labor needed to compile and analyze it. A central goal of multimodal data integration is to understand the interaction effects of different features. Understanding the complex interaction among multimodal datasets, however, is challenging. In this study, we tested the interaction effect of multimodal datasets using a novel method called the kernel method for detecting higher order interactions among biologically relevant mulitview data. Using a semiparametric method on a reproducing kernel Hilbert space (RKHS), we used a standard mixed-effects linear model and derived a score-based variance component statistic that tests for higher order interactions between multi-view data. The proposed method offers an intangible framework for the identification of higher order interaction effects (e.g., three way interaction) between genetics, brain imaging, and epigenetic data. Extensive numerical simulation studies were first conducted to evaluate the performance of this method. Finally, this method was evaluated using data from the Mind Clinical Imaging Consortium (MCIC) including single nucleotide polymorphism (SNP) data, functional magnetic resonance imaging (fMRI) scans, and deoxyribonucleic acid (DNA) methylation data, respectfully, in schizophrenia patients and healthy controls. We treated each gene-derived SNPs, region of interest (ROI) and gene-derivedDNA methylation as a single testing unit, which are combined into triplets for evaluation. In addition, cardiovascular disease risk factors such as age, gender, and body mass index were assessed as covariates on hippocampal volume and compared between triplets. Our method identified 13-triplets (p-values ≤ 0.001) that included 6 gene-derived SNPs, 10 ROIs, and 6 gene-derived DNA methylations that correlated with changes in hippocampal volume, suggesting that these triplets may be important in

关键词： Alkylation

Genetic variant analysis of boys with Autism: A pilot study on linking facial phenotype to genotype

学校读者我要写书评

暂无评论

Genetic variant analysis of boys with Autism: A pilot study ...

2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017

作者： Obafemi-Ajayi, Tayo Settles, Luke Su, Yuqing Germeroth, Cynthia Olbricht, Gayla R. Wunsch, Donald C. Takahashi, T. Nicole Miles, Judith Engineering Program Missouri State University Springfield MO United States Mathematics and Statistics Dept. Missouri University of Science and Technology RollaMO United States Information Technology Missouri University of Science and Technology RollaMO United States Electrical and Computer Eng. Dept. Missouri University of Science and Technology RollaMO United States Thompson Center for Autism and Neurodevelopmental Disorders ColumbiaMO United States

ISBN: (纸本)9781509030491

This work examines the validity of facial phenotypes as Autism Spectrum Disorders (ASD) biomarkers in boys with essential autism. A family-based association analysis framework is presented that uses previously identified facially-delineated (FD) clusters to examine relationship between FD clusters and known ASD genes. The hypothesis is that there are certain genetic variants, single nucleotide polymorphisms (SNP), specific to the FD clusters. Although statistical significance was not established, the results identified some candidate SNPs unique to each of the FD clusters that could indicate an underlying etiological difference. Further, recommendations are provided for larger-scale studies that could utilize the analysis framework presented. © 2017 IEEE.

关键词： Biomarkers

Modeling preference time in middle distance triathlons

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Fister, Iztok Iglesias, Andres Deb, Suash Fister, Dušan Jr, Iztok Fister University of Maribor Faculty of Electrical Engineering and Computer Science Smetanova 17 Maribor2000 Slovenia University of Cantabria Avda. de los Castros s/n Santander39005 Spain IT & Educational Consultant Ranchi Jharkhand India Decision Sciences and Modelling Program Victoria University Melbourne Australia University of Maribor Faculty of Mechanical Engineering Smetanova 17 Maribor2000 Slovenia University of Maribor Faculty of Electrical Engineering and Computer Science Smetanova 17 Maribor2000 Slovenia

Modeling preference time in triathlons means predicting the intermediate times of particular sports disciplines by a given overall finish time in a specific triathlon course for the athlete with the known personal best result. This is a hard task for athletes and sport trainers due to a lot of different factors that need to be taken into account, e.g., athlete's abilities, health, mental preparations and even their current sports form. So far, this process was calculated manually without any specific software tools or using the artificial intelligence. This paper presents the new solution for modeling preference time in middle distance triathlons based on particle swarm optimization algorithm and archive of existing sports results. Initial results are presented, which suggest the usefulness of proposed approach, while remarks for future improvements and use are also emphasized. Copyright © 2017, The Authors. All rights reserved.

关键词： Sports

Single shot ultrafast all optical magnetization switching of ferromagnetic Co/Pt multilayers

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Gorchon, Jon Lambert, Charles-Henri Yang, Yang Pattabi, Akshay Wilson, Richard B. Salahuddin, Sayeef Bokor, Jeffrey Lawrence Berkeley National Laboratory 1 Cyclotron Road BerkeleyCA94720 United States Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA94720 United States Department of Materials Science and Engineering University of California BerkeleyCA94720 United States Department of Mechanical Engineering Materials Science and Engineering Program University of California RiversideCA92521 United States

A single femto-second optical pulse can fully reverse the magnetization of a film within picoseconds. Such fast operation hugely increases the range of application of magnetic devices. However, so far, this type of ultrafast switching has been restricted to ferri-magnetic GdFeCo films. In contrast, all optical switching of ferro-magnetic films require multiple pulses, thereby being slower and less energy efficient. Here, we demonstrate magnetization switching induced by a single laser pulse in various ferromagnetic Co/Pt multilayers grown on GdFeCo, by exploiting the exchange coupling between the two magnetic films. Table-top depth-sensitive time-resolved magneto-optical experiments show that the Co/Pt magnetization switches within 7 picoseconds. This coupling approach will allow ultrafast control of a variety of magnetic films, critical for applications. Copyright © 2017, The Authors. All rights reserved.

关键词： Ferromagnetic materials

A Bayesian mixture model for clustering on the stiefel manifold

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Sengupta, Subhajit Pal, Subhadip Mitra, Riten Guo, Ying Banerjee, Arunava Ji, Yuan Program for Computational Genomics and Medicine NorthShore University HealthSystem Department of Bioinformatics and Biostatistics University of Louisville Department of Biostatistics and Bioinformatics Emory University Department of Computer and Information Science and Engineering University of Florida Department of Public Health Sciences University of Chicago

Analysis of a Bayesian mixture model for the Matrix Langevin distribution on the Stiefel manifold is presented. The model exploits a particular parametrization of the Matrix Langevin distribution, various aspects of which are elaborated on. A general, and novel, family of conjugate priors, and an efficient Markov chain Monte Carlo (MCMC) sampling scheme for the corresponding posteriors is then developed for the mixture model. Theoretical properties of the prior and posterior distributions, including posterior consistency, are explored in detail. Extensive simulation experiments are presented to validate the efficacy of the framework. Real-world examples, including a large scale neuroimaging dataset, are analyzed to demonstrate the computational tractability of the approach. Copyright © 2017, The Authors. All rights reserved.

关键词： Mixtures

Wildlife-microbiome interactions and disease: exploring opportunities for disease mitigation across ecological scales

学校读者我要写书评

暂无评论

Drug Discovery Today: Disease Models 2018年 28卷 105-115页

作者： Williams, Candace L. Caraballo-Rodríguez, Andrés Mauricio Allaband, Celeste Zarrinpar, Amir Knight, Rob Gauglitz, Julia M. Institute for Conservation Research San Diego Zoo Global United States Collaborative Mass Spectrometry Innovation Center Skaggs School of Pharmacy and Pharmaceutical Sciences University of California La Jolla San Diego 92307 CA United States Biomedical Sciences Graduate Program University of California La Jolla San Diego 92307 CA United States Department of Medicine University of California La Jolla San Diego 92307 CA United States Veterans Affairs San Diego Healthcare System San Diego California University of California La Jolla San Diego 92307 CA United States Department of Pediatrics University of California La Jolla San Diego 92037 CA United States Department of Bioengineering University of California La Jolla San Diego 92093 CA United States Department of Computer Science and Engineering University of California La Jolla San Diego 92093 CA United States Center for Microbiome Innovation University of California La Jolla San Diego 92307 CA United States

Captive wildlife are a unique set of animals, whose diverse host–microbe symbioses are underexplored. Compared to their wild counterparts they are particularly susceptible to a variety of diseases, many of which have explicit or purported links to the microbiome. In this perspective, we will examine how the microbiome influences gastrointestinal disorders, metabolic dysregulation, reproduction, and disease susceptibility in captive wildlife. Investigation of wildlife, and specifically captive wildlife, affords a unique opportunity to gain understanding of the broad diversity of the associated microbiota and learn from nature's molecular and microbial responses to disease. Studies like these could lead to the discovery of new interventions, ranging from dietary changes to the use of microbes or their natural products as treatment. Intervention strategies can lead to the discovery of medically relevant small molecules and the development of a novel platform for N-of-1 targeted medical investigations. © 2019 Elsevier Ltd

关键词：