检索结果-内蒙古大学图书馆

25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multicategory classification of 11 neuromuscular diseases based on microarray data using support vector machine 36

Multicategory classification of 11 neuromuscular diseases ba...

引用

2014 36th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2014

作者： Beom Choi, Soo Park, Jee Soo Chung, Jai Won Yoo, Tae Keun Kim, Deok Won Brain Korea 21 PLUS Project for Medical Science Yonsei University Seoul Korea Republic of Dept. of Medicine Yonsei University College of Medicine Seoul Korea Republic of Graduate Program in Biomedical Engineering Yonsei University Seoul Korea Republic of Dept. of Medical Engineering Yonsei University College of Medicine Seoul Korea Republic of

ISBN: (纸本)9781424479290

We applied multicategory machine learning methods to classify 11 neuromuscular disease groups and one control group based on microarray data. To develop multicategory classification models with optimal parameters and features, we performed a systematic evaluation of three machine learning algorithms and four feature selection methods using three-fold cross validation and a grid search. This study included 114 subjects of 11 neuromuscular diseases and 31 subjects of a control group using microarray data with 22,283 probe sets from the National Center for Biotechnology Information (NCBI). We obtained an accuracy of 100%, relative classifier information (RCI) of 1.0, and a kappa index of 1.0 by applying the models of support vector machines one-versus-one (SVM-OVO), SVM one-versus-rest (OVR), and directed acyclic graph SVM (DAGSVM), using the ratio of genes between categories to within-category sums of squares (BW) feature selection method. Each of these three models selected only four features to categorize the 12 groups, resulting in a time-saving and cost-effective strategy for diagnosing neuromuscular diseases. In addition, a gene symbol, SPP1 was selected as the top-ranked gene by the BW method. We confirmed relationships between the gene (SPP1) and Duchenne muscular dystrophy (DMD) from a previous study. With our models as clinically helpful tools, neuromuscular diseases could be classified quickly using a computer, thereby giving a time-saving, cost-effective, and accurate diagnosis. © 2014 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

引用

BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

来源：评论

学校读者我要写书评

暂无评论

Improved performance of a low-cost PDR system through sensor calibration and analysis

Improved performance of a low-cost PDR system through sensor...

引用

IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Yunki. Kim Donghyuk Lee Kijung. Kim Jangmyung. Lee Dept. of Electrical Engineering Pusan National University Busan Korea Dept. Interdisciplinary Program in Robotics Pusan National University Busan Korea Dept. of Electrical Engineering 'Brain Korea 21 Project’ of Pusan National University Busan Korea

ISBN: (纸本)9781479957378

This paper proposes improvement for performance of a low-cost Pedestrian Dead-Reckoning(PDR) System through calibration and analysis of sensor. It is applied that PDR System for estimating pedestrian's position in the area not being able to be received. also sensor's error is removed by using angle compensation technique and performance of system is improved by analysis of PDR system. Consequently, position of pedestrian is estimated by applying the improved value of sensor and result of angle analysis to PDR system. Experiments were conducted to verify the proposed system. Experimental results within 2% of range error, RMS position error of less than 3% showed superior performance.

关键词： Acceleration Mathematical model Equations Length measurement Temperature sensors Estimation Calibration

来源：评论

学校读者我要写书评

暂无评论

Classification of serous ovarian tumors based on microarray data using multicategory support vector machines 36

Classification of serous ovarian tumors based on microarray ...

引用

2014 36th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2014

作者： Park, Jee Soo Beom Choi, Soo Chung, Jai Won Kim, Sung Woo Kim, Deok Won Dept. of Medicine Yonsei University College of Medicine Seoul Korea Republic of Brain Korea 21 PLUS Project for Medical Science Yonsei University Seoul Korea Republic of Graduate Program in Biomedical Engineering Yonsei University Seoul Korea Republic of Future IT RandD Laboratory LG Electronics Advanced Research Institute Seoul Korea Republic of Dept. of Medical Engineering Yonsei University College of Medicine Seoul Korea Republic of

ISBN: (纸本)9781424479290

Ovarian cancer, the most fatal of reproductive cancers, is the fifth leading cause of death in women in the United States. Serous borderline ovarian tumors (SBOTs) are considered to be earlier or less malignant forms of serous ovarian carcinomas (SOCs). SBOTs are asymptomatic and progression to advanced stages is common. Using DNA microarray technology, we designed multicategory classification models to discriminate ovarian cancer subclasses. To develop multicategory classification models with optimal parameters and features, we systematically evaluated three machine learning algorithms and three feature selection methods using five-fold cross validation and a grid search. The study included 22 subjects with normal ovarian surface epithelial cells, 12 with SBOTs, and 79 with SOCs according to microarray data with 54,675 probe sets obtained from the National Center for Biotechnology Information gene expression omnibus repository. Application of the optimal model of support vector machines one-versus-rest with signal-to-noise as a feature selection method gave an accuracy of 97.3%, relative classifier information of 0.916, and a kappa index of 0.941. In addition, 5 features, including the expression of putative biomarkers SNTN and AOX1, were selected to differentiate between normal, SBOT, and SOC groups. An accurate diagnosis of ovarian tumor subclasses by application of multicategory machine learning would be cost-effective and simple to perform, and would ensure more effective subclass-targeted therapy. © 2014 IEEE.

关键词： Ovarian Neoplasms SYNTHETIC ORGANIC CHEMICALS Machine learning algorithms Support Vector Network Ovarian Serous Tumor selection methods AOX1 gene Microarray DNA microarray technology Subclasses optimal parameter Feature extraction vector computer Ovary Cancer

来源：评论

学校读者我要写书评

暂无评论

Screening for pre-diabetes using support vector machine model 36

Screening for pre-diabetes using support vector machine mode...

引用

2014 36th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2014

作者： Chung, Jai Won Kim, Won Jae Beom Choi, Soo Park, Jee Soo Kim, Deok Won Graduate Program in Biomedical Engineering Yonsei University Seoul Korea Republic of Dept. of Medicine Yonsei University College of Medicine Seoul Korea Republic of Brain Korea 21 PLUS Project for Medical Science Yonsei University Seoul Korea Republic of Department of Medical Engineering Yonsei University College of Medicine Seoul Korea Republic of

ISBN: (纸本)9781424479290

The global prevalence of diabetes is rapidly increasing. Studies support screening and interventions for pre-diabetes, which results in serious complications and diabetes. This study aimed at developing an intelligence-based screening model for pre-diabetes that could assist with decreasing the prevalence of diabetes through early identification and subsequent interventions. Data from the Korean National Health and Nutrition Examination Survey (KNHANES) were used, excluding subjects with diabetes. The KNHANES 2010 data (n = 4,685) were used for training and internal validation, while data from KNHANES 2011 (n = 4,566) were used for external validation. We developed a model to screen for pre-diabetes using support vector machine (SVM), and performed a systematic evaluation of the SVM model using internal and external validation. We compared the performance of the SVM model with that of a screening score model based on logistic regression analysis for pre-diabetes that had been developed previously. Backward elimination logistic regression resulted in associations between pre-diabetes and age, sex, waist circumference, body mass index, alcohol intake, family history of diabetes, and hypertension. The areas under the curves (AUCs) for the SVM model in the internal and external datasets were 0.761 and 0.731, respectively, while the AUCs for the screening score model were 0.734 and 0.712, respectively. The SVM model developed in this study performed better than the screening score model that had been developed previously and may be more effective for pre-diabetes screening. © 2014 IEEE.

关键词： Asymptotic stability Delays Discrete-time systems Numerical stability Stability criteria Time-varying systems

来源：评论

学校读者我要写书评

暂无评论

SU-E-J-274: Responses of Medulloblastoma Cells to Radiation Dosimetric Parameters in Intensity-Modulated Radiation Therapy

引用

Medical Physics 2015年第6PART11期42卷 3330-3330页

作者： J Park S Rogalla D Woo D Lee H Park C Contag T Suh Dept. of Pediatrics Stanford University School of Medicine Stanford CA Molecular Imaging Program at Stanford Stanford CA Bio-X Program Stanford CA Research Institute of Biomedical Engineering The Catholic University of Korea Seoul Korea Proton Therapy Center National Cancer Center Goyang Korea Asan Institute for Life Sciences Asan Medical Center Seoul Korea Dept. of Radiation Oncology Ajou University School of Medicine Suwon Korea Dept. of Biomedical Engineering The Catholic University of Korea Seoul Korea

Purpose: To evaluate radiation responses of the medulloblastoma cell line Daoy in intensity-modulated radiation therapy (IMRT), quantitative variations to variable radiation dosimetic parameters were tracked by bioluminescent images (BLIs). Methods: The luciferase and green fluorescent protein positive Daoy cells were cultured on dishes. The medulloblastoma cells irradiated to different dose rate, interval of fractionated doses, field margin and misalignment, and dose uniformity in IMRT were monitored using bioluminescent images. The cultured cells were placed into a dedicated acrylic phantom to deliver intensity-modulated fluences and calculate accurate predicted dose distribution. The radiation with dose rate from 0.5 Gy/min to 15 Gy/min was irradiated by adjusting monitor unit per minute and source-to-surface distances. The intervals of fractionated dose delivery were changed considering the repair time of double strand breaks (DSB) revealed by straining of *** effect of non-uniform doses on the cells were visualized by registering dose distributions and BLIs. The viability according to dosimetric parameters was correlated with bioluminescent intensities for cross-check of radiation responses. Results: The DSB and cell responses due to the first fractionated dose delivery significantly affected final tumor control rather than other parameters. The missing tumor volumes due to the smaller field margin than the tumor periphery or field misalignment caused relapse of cell responses on BLIs. The dose rate and gradient had effect on initial responses but could not bring out the distinguishable killing effect on cancer cells. Conclusion: Visualized and quantified bioluminescent images were useful to correlate the dose distributions with spatial radiation effects on cells. This would derive the effective combination of dose delivery parameters and fractionation. Radiation responses in particular IMRT configuration could be reflected to image based-dose re-opt

关键词： Dosimetry Intensity modulated radiation therapy Medical imaging Cell cultures Cancer Gamma rays Schottky barriers Gamma ray effects Proteins Radiation monitoring

来源：评论

学校读者我要写书评

暂无评论

Analysis of unsteady flow past a circular cylinder using a harmonic balance method 44

Analysis of unsteady flow past a circular cylinder using a h...

引用

44th AIAA Fluid Dynamics Conference 2014

作者： Clark, Emily B. Ekici, Kivanc Beran, Philip S. The Bredesen Center for Interdisciplinary Research and Graduate Education University of Tennessee Knoxville TN 37996 United States Dept. of Mechanical Aerospace and Biomedical Engineering University of Tennessee Knoxville TN 37996 United States Multidisciplinary Technologies Center Air Vehicles Directorate Air Force Research Laboratory Wright-Patterson AFB OH 45433 United States

ISBN: (数字)9781624102899

ISBN: (纸本)9781624102899

Two-dimensional laminar flow over a circular cylinder was investigated in this work. Two cases were considered in which the cylinder was either in constant rotation or in periodic oscillation. The governing nonlinear Navier-Stokes equations were solved using a finite difference discretization and Newton's method. Three flow solvers were developed for this research: a steady solver, an unsteady time-accurate solver, and an unsteady harmonic balance solver. The purpose of the work was to investigate the effects of a rotating cylinder for lift enhancement, drag reduction, and the suppression of vortex shedding. Suppression of vortex shedding was accomplished for a cylinder in constant rotation, while lift enhancement and drag reduction were achieved for the cylinder in both constant and periodic rotation. Trade-offs were discovered for lift enhancement and drag reduction for the unsteady results. For a cylinder in constant rotation, there was no apparent trade-off for the higher Reynolds number case. Drag reduction and lift enhancement occurred concurrently for Re=200 for all rotation rates. There was a trade-off for Re=100 past a critical rotation rate. The lift enhancement and drag reduction occurred simulationously until the critical rotation rate, but past this value, there was a sharp increase in the mean drag coefficient. The trade-offs were stricter in the periodic rotation case. Drag reduction did not occur at the best frequencies for lift enhancement. On the other hand, drag reduction was the greatest between the lock-on and non lock-on regions, where lift enhancement was lowest.

关键词： Navier Stokes equations

来源：评论

学校读者我要写书评

暂无评论

Multicategory classification of 11 neuromuscular diseases based on microarray data using support vector machine

Multicategory classification of 11 neuromuscular diseases ba...

引用

Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Soo Beom Choi Jee Soo Park Jai Won Chung Tae Keun Yoo Deok Won Kim Brain Korea 21 PLUS Project for Medical Science Yonsei University Dept. of Medicine Yonsei University College of Medicine Graduate Program in Biomedical Engineering Yonsei University Dept. of Medical Engineering Yonsei University College of Medicine

ISBN: (纸本)9781424479276

关键词：

来源：评论

学校读者我要写书评

暂无评论

Wireless power transmission using electromagnetic inductive coupling and lc resonant

引用

Transactions of the Korean Institute of Electrical Engineers 2013年第3期62卷 349-354页

作者： Lee, Seung-Hwan Kimm, Hyoen-Min Kim, Hee-Je Kim, Su-Weon Dept. of Interdisciplinary Program in Robotics Pusan National University Korea Republic of Electrical Engineering Pusan National University Korea Republic of

Wireless power transmission introduced by Tesla has instrumented by many scientists of the world. This technique first was utilized as wireless communications such as radio in long range transmission. And contactless transmission using inductive property was used on white goods. In 2007, MIT' lab introduced that new wireless power transmission by magnetic resonance which has about 50% efficiency and 2M transmission distances, it was a chance to refocus a new possibility of wireless power transmission. In this paper, using LC coupling compensate the short distances of contactless transmission, this simple method could transmit about 30cm distances. Using this approach, it can be solved the short transmission distances, a drawback of Electromagnetic inductive coupling method.

关键词： Natural frequencies

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：