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

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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

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Instructional experiences with modeling and analysis using the i∗ framework 1

Instructional experiences with modeling and analysis using t...

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1st International iStar Teaching Workshop, iStarT 2015 - co-located with the 27th International Conference on Advanced Information Systems Engineering, CAiSE 2015

作者： Babar, Zia Nalchigar, Soroosh Lessard, Lysanne Horkoff, Jennifer Yu, Eric Faculty of Information University of Toronto Toronto Canada Department of Computer Science University of Toronto Toronto Canada Telfer School of Management University of Ottawa Ottawa Canada Department of Human Computer Interaction City University London London United Kingdom

First year professional Master's students at the Faculty of Information, University of Toronto are taught how to analyze problem domains us-ing i∗ modeling in the final segment of the introductory course on "Systems Analysis and Process Innovation". Over the past several years, the course in-structors and teaching assistants have had the opportunity to observe and inter-act with the course students on the learning and use of the i∗ framework for modeling and analysis which makes it possible to make general observations regarding student experiences with the i∗ framework in an instructional setting. These observations are broad ranging and cover areas such as pedagogical de-sign, conceptual understanding and proficiency with the i∗ framework, domain modeling and analysis, and tools for i∗ modeling.

关键词： Systems analysis

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Teaching i∗ alongside a contrasting modeling framework 1

Teaching i∗ alongside a contrasting modeling framework

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1st International iStar Teaching Workshop, iStarT 2015 - co-located with the 27th International Conference on Advanced Information Systems Engineering, CAiSE 2015

作者： Yu, Eric Lessard, Lysanne Babar, Zia Nalchigar, Soroosh Horkoff, Jennifer Faculty of Information University of Toronto Toronto Canada Department of Computer Science University of Toronto Toronto Canada Telfer School of Management University of Ottawa Ottawa Canada Department of Human Computer Interaction City University London London United Kingdom

We briefly describe the design of a course on "Systems Analysis and Process Innovation", focusing especially on its project assignments. Students are introduced to process modeling and data modeling, followed by i∗ and Val-ue Network modeling. In their project assignments, students apply these model-ing techniques to real organizational settings to analyze an as-is situation and to explore to-be alternatives. A distinctive feature in the design of the project as-signments is that student teams split into 2 sub-teams in which each sub-team uses a different modeling technique to analyze the same domain setting. After each sub-team has separately completed its own work, the two sub-teams then compare their results for the domain problem setting, and more importantly, contrast the strengths and limitations of the two modeling approaches based on their project experience.

关键词： Students

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Author Correction: Embodiment in a Child-Like Talking Virtual Body Influences Object Size Perception, Self-Identification, and Subsequent Real Speaking

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Scientific reports 2018年第1期8卷 4854页

作者： Ana Tajadura-Jiménez Domna Banakou Nadia Bianchi-Berthouze Mel Slater UCL Interaction Centre (UCLIC) University College London London UK. a.tajadura@ucl.ac.uk. Universidad Loyola Andalucía Department of Psychology Seville Spain. a.tajadura@ucl.ac.uk. Universidad Loyola Andalucía Human Neuroscience Lab Seville Spain. a.tajadura@ucl.ac.uk. Event Lab Department of Clinical Psychology and Psychobiology Faculty of Psychology Barcelona Spain. Institute of Neurosciences University of Barcelona Barcelona Spain. UCL Interaction Centre (UCLIC) University College London London UK. Department of Computer Science University College London London UK. melslater@ub.edu. Event Lab Department of Clinical Psychology and Psychobiology Faculty of Psychology Barcelona Spain. melslater@ub.edu. Institute of Neurosciences University of Barcelona Barcelona Spain. melslater@ub.edu. Institució Catalana de Recerca i Estudis Avançats (ICREA) Barcelona Spain. melslater@ub.edu.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

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On the combination of two visual cognition systems using combinatorial fusion

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Brain Informatics 2015年第1期2卷 21-32页

作者： Batallones, Amy Sanchez, Kilby Mott, Brian Coffran, Cameron Frank Hsu, D. Laboratory of Informatics and Data Mining Department of Computer and Information Science Fordham University New YorkNY United States Program for the Human Environment The Rockefeller University New YorkNY United States

When combining decisions made by two separate visual cognition systems, statistical means such as simple average (M1) and weighted average (M2 and M3), incorporating the confidence level of each of these systems have been used. Although combination using these means can improve each of the individual systems, it is not known when and why this can happen. By extending a visual cognition system to become a scoring system based on each of the statistical means M1, M2, and M3 respectively, the problem of combining visual cognition systems is transformed to the problem of combining multiple scoring systems. In this paper, we examine the combined results in terms of performance and diversity using combinatorial fusion, and study the issue of when and why a combined system can be better than individual systems. A data set from an experiment with twelve trials is analyzed. The findings demonstrated that combination of two visual cognition systems, based on weighted means M2 or M3, can improve each of the individual systems only when both of them have relatively good performance and they are diverse. © 2015, The Author(s).

关键词： Decision making

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Adaptive Thresholding and Reweighting to Improve Domain Transfer Learning for Unbalanced Data with Applications to EEG Imbalance

Adaptive Thresholding and Reweighting to Improve Domain Tran...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Kyung-Min Su W. David Hairston Kay A. Robbins Department of Computer Science University of Texas at San Antonio San Antonio TX USA University of Texas at San Antonio San Antonio TX US Human Research and Engineering Directorate US Army Research Laboratory MD USA

ISBN: (纸本)9781509061686

Domain adaptation methods can be highly sensitive to class balance, particularly the usually unknown balance of the unlabeled test set. In this work, we analyze the effect of imbalance on a well-known algorithm, ARTL (Adaptation Regularization Transfer Learning) and propose four approaches for mitigating the adverse effects of imbalance. These include (1) balancing the training set for pseudo-label calculation, (2) applying adaptive thresholding to pseudo-label calculation, (3) using class reweighting in the optimization objective, and (4) applying adaptive thresholding to the output objective. We tested these methods with the UCI newsgroup dataset and on three types of imbalanced EEG (electroencephalogram) classification problems. We observed significant improvements, particularly for cases of extreme imbalance, which are not well addressed by standard classification techniques.

关键词： Electroencephalography Training Standards Manifolds Classification algorithms Optimization Training data

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Cognitive models of prediction as decision AIDS 14

Cognitive models of prediction as decision AIDS

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14th International Conference on Cognitive Modeling, ICCM 2016

作者： Lebiere, Christian Morrison, Don Abdelzaher, Tarek Hu, Shaohan Gonzalez, Cleotilde Buchler, Norbou Veksler, Vladislav D. Department of Psychology Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213 United States Department of Computer Science University of Illinois at Urbana Champaign 201 N Goodwin Ave UrbanaIL61801 United States Department of Social and Decision Sciences Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213 United States Cognitive Sciences Branch Human Resources and Effectiveness Directorate U.S. Army Research Laboratory Aberdeen Proving GroundMD21005 United States

ISBN: (纸本)9780998508207

We consider the use of cognitive models as both models of human cognitive function and human-compatible decision aids. The domain of application is prediction based on partial information in the context of emergency events where the availability and timeliness of information is limited. The cognitive model is based on the memory retrieval processes of the ACT-R cognitive architecture, most specifically its underpinnings in the rational analysis of cognition. The model is shown to capture well the temporal and spatial characteristics of the data. Finally, we discuss potential issues in the application of cognitive models as decision aids and recommender systems, in particular the ability to introspect in the workings of the model to select data most suitable for the human decision making process. Copyright © TRECVID *** rights reserved.

关键词： Decision making

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Oxidative Species-Induced Excitonic Transport in Tubulin Aromatic Networks: Potential Implications for Neurodegenerative Disease

arXiv

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arXiv 2017年

作者： Kurian, P. Obisesan, T.O. Craddock, T.J.A. National Human Genome Center Howard University College of Medicine WashingtonDC20060 United States Department of Medicine Howard University College of Medicine WashingtonDC20060 United States Computational Physics Laboratory Howard University WashingtonDC20059 United States Georgetown-Howard Universities Center for Clinical and Translational Science Clinical Research Unit Howard University College of Medicine WashingtonDC20060 United States Departments of Psychology & Neuroscience Computer Science and Clinical Immunology Nova Southeastern University Fort LauderdaleFL33314 United States Clinical Systems Biology Group Institute for Neuro-Immune Medicine Nova Southeastern University Fort LauderdaleFL33328 United States

Oxidative stress is a pathological hallmark of neurodegenerative tauopathic disorders such as Alzheimer’s disease and Parkinson’s disease-related dementia, which are characterized by altered forms of the microtubule-associated protein (MAP) tau. MAP tau is a key protein in stabilizing the microtubule architecture that regulates neuron morphology and synaptic strength. When MAP tau is degraded in tauopathic disorders, neuron dysfunction results. The precise role of reactive oxygen species (ROS) in the tauopathic disease process, however, is poorly understood. Classically, mitochondrial dysfunction has been viewed as the major source of oxidative stress and has been shown to precede tau and amyloid pathology in various dementias, but the exact mechanisms are not clear. It is known that the production of ROS by mitochondria can result in ultraweak photon emission (UPE) within cells. While of low intensity, surrounding proteins within the cytosol can still absorb these energetic photons via aromatic amino acids (e.g., tryptophan and tyrosine). One likely absorber of these photons is the microtubule cytoskeleton, as it forms a vast network spanning neurons, is highly co-localized with mitochondria, and shows a high density of aromatic amino acids. Functional microtubule networks may traffic this ROS-generated endogenous photon energy for cellular signaling, or they may serve as dissipaters/conduits of such energy to protect the cell from potentially harmful effects. Experimentally, after in vitro exposure to exogenous photons, microtubules have been shown to reorient and reorganize in a dose-dependent manner with the greatest effect being observed around 280 nm, in the tryptophan and tyrosine absorption range. In this paper, recent modeling efforts based on ambient temperature experiment are presented, showing that tubulin polymers can feasibly absorb and channel these photoexcitations via resonance energy transfer, on the order of dendritic length scales and neuronal fi

关键词： Amino acids

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I feel you-monitoring environmental variables related to asthma in an integrated real-time frame

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BMC Research Notes 2015年第1期8卷 1-4页

作者： Berenguer, Anabela Gonçalves Human Genetics Laboratory University of Madeira Funchal 9000-390 Portugal Department of Computer Science and Engineering University of Oulu PL 4500 Oulu 90014 Finland

The study of asthma and other complex diseases has proven to be a "moving target" for researchers due to its complex aetiology, difficulty in definition, and immeasurable environmental effects. A large number of studies regarding the contribution of both genetic and environmental factors often result in contradictory results, in part due to the highly heterogeneous nature of asthma. Recent literature has focused on the epigenetic signatures of asthma caused by environmental factors, highlighting the importance of environment. However, unlike the genetic techniques, environmental assessment still lacks accuracy. A plausible solution for this problem would be an individual-based environmental exposure assessment, relying on new technologies such as personal real-time environmental sensors. This could prove to enable the assessment of the whole environmental exposure - or exposome - matching in terms of precision the genome that is emphasized in most studies so far. In addition, the measurement of the whole array of biological molecules, in response to the environment action, could help understand the context of the disease. The current perspective comprises a beyond-genetics integrated vision of omics technology coupled with real-time environmental measures targeting to enhance our comprehension of the disease genesis. © 2015 Berenguer.

关键词： Asthma Environment Epigenetics Exposome Genetics Omics Real-time monitoring Sensors

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Consumption intent analysis in Chinese microblog

Consumption intent analysis in Chinese microblog

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2014 International Conference on Information Technology and Application, ITA2014

作者： Mao, Junkang Yao, Tianfang Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781138026773

With the development of Chinese microblog and E-commerce, the messages with opinions and intents expressed by users would have a significant impact on many domains. In this paper, we study on how to identify the consumption intent in Chinese microblog. We use text classification based on NB, SVM and EM-based transfer learning algorithm to identify consumption intent. And we compare NB, SVM and EM algorithm methods. Due to the freedom and irregular of the microblog posts, we consider more about preprocessing microblog raw data, which bring new challenges to the traditional text classification methods. © 2015 Taylor & Francis Group, London.

关键词： Classification (of information)

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