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Institution

University of Minnesota

EducationMinneapolis, Minnesota, United States
About: University of Minnesota is a education organization based out in Minneapolis, Minnesota, United States. It is known for research contribution in the topics: Population & Transplantation. The organization has 117432 authors who have published 257986 publications receiving 11944239 citations. The organization is also known as: University of Minnesota, Twin Cities & University of Minnesota-Twin Cities.


Papers
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Journal ArticleDOI
01 Dec 1995
TL;DR: In this article, the authors present a two-dimensional framework for research in information technology, based on broad types of design and natural science research activities: build, evaluate, theorize, and justify.
Abstract: Research in IT must address the design tasks faced by practitioners. Real problems must be properly conceptualized and represented, appropriate techniques for their solution must be constructed, and solutions must be implemented and evaluated using appropriate criteria. If significant progress is to be made, IT research must also develop an understanding of how and why IT systems work or do not work. Such an understanding must tie together natural laws governing IT systems with natural laws governing the environments in which they operate. This paper presents a two dimensional framework for research in information technology. The first dimension is based on broad types of design and natural science research activities: build, evaluate, theorize, and justify. The second dimension is based on broad types of outputs produced by design research: representational constructs, models, methods, and instantiations. We argue that both design science and natural science activities are needed to insure that IT research is both relevant and effective.

3,433 citations

Journal ArticleDOI
11 Aug 2016-Nature
TL;DR: Using multi-modal magnetic resonance images from the Human Connectome Project and an objective semi-automated neuroanatomical approach, 180 areas per hemisphere are delineated bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults.
Abstract: Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century-old objective in neuroscience. Using multi-modal magnetic resonance images from the Human Connectome Project (HCP) and an objective semi-automated neuroanatomical approach, we delineated 180 areas per hemisphere bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults. We characterized 97 new areas and 83 areas previously reported using post-mortem microscopy or other specialized study-specific approaches. To enable automated delineation and identification of these areas in new HCP subjects and in future studies, we trained a machine-learning classifier to recognize the multi-modal 'fingerprint' of each cortical area. This classifier detected the presence of 96.6% of the cortical areas in new subjects, replicated the group parcellation, and could correctly locate areas in individuals with atypical parcellations. The freely available parcellation and classifier will enable substantially improved neuroanatomical precision for studies of the structural and functional organization of human cerebral cortex and its variation across individuals and in development, aging, and disease.

3,414 citations

Journal ArticleDOI
TL;DR: The Multi-Ethnic Study of Atherosclerosis was initiated in July 2000 to investigate the prevalence, correlates, and progression of subclinical cardiovascular disease (CVD) in a population-based sample of 6,500 men and women aged 45-84 years for identification and characterization of CVD events.
Abstract: The Multi-Ethnic Study of Atherosclerosis was initiated in July 2000 to investigate the prevalence, correlates, and progression of subclinical cardiovascular disease (CVD) in a population-based sample of 6,500 men and women aged 45-84 years. The cohort will be selected from six US field centers. Approximately 38% of the cohort will be White, 28% African-American, 23% Hispanic, and 11% Asian (of Chinese descent). Baseline measurements will include measurement of coronary calcium using computed tomography; measurement of ventricular mass and function using cardiac magnetic resonance imaging; measurement of flow-mediated brachial artery endothelial vasodilation, carotid intimal-medial wall thickness, and distensibility of the carotid arteries using ultrasonography; measurement of peripheral vascular disease using ankle and brachial blood pressures; electrocardiography; and assessments of microalbuminuria, standard CVD risk factors, sociodemographic factors, life habits, and psychosocial factors. Blood samples will be assayed for putative biochemical risk factors and stored for use in nested case-control studies. DNA will be extracted and lymphocytes will be immortalized for genetic studies. Measurement of selected subclinical disease indicators and risk factors will be repeated for the study of progression over 7 years. Participants will be followed through 2008 for identification and characterization of CVD events, including acute myocardial infarction and other coronary heart disease, stroke, peripheral vascular disease, and congestive heart failure; therapeutic interventions for CVD; and mortality.

3,367 citations

Journal ArticleDOI
TL;DR: In this paper, a framework for the analysis of a large class of discontinuous Galerkin methods for second-order elliptic problems is provided, which allows for the understanding and comparison of most of the discontinuous methods that have been proposed over the past three decades.
Abstract: We provide a framework for the analysis of a large class of discontinuous methods for second-order elliptic problems. It allows for the understanding and comparison of most of the discontinuous Galerkin methods that have been proposed over the past three decades for the numerical treatment of elliptic problems.

3,293 citations

Journal ArticleDOI
TL;DR: Data from three experiments supported the hypothesis that an individual's perception of a particular system's ease of use is anchored to her or his general computer self-efficacy at all times, and objective usability has an impact on ease-of- use perceptions about a specific system only after direct experience with the system.
Abstract: The Technology Acceptance Model (TAM) has been widely used to predict user acceptance and use based on perceived ease of use and usefulness. However, in order to design effective training interventions to improve user acceptance, it is necessary to better understand the antecedents and determinants of key acceptance constructs. In this research, we focus on understanding the determinants of perceived ease of use. Data from three experiments spanning 108 subjects and six different systems supported our hypothesis that an individual's perception of a particular system's ease of use is anchored to her or his general computer self-efficacy at all times, and objective usability has an impact on ease of use perceptions about a specific system only after direct experience with the system. In addition to being an important research issue in user acceptance research, understanding antecedents of perceived ease of use is also important from a practical standpoint since several systems in which millions of dollars are invested are rejected because of poor user interfaces. Moreover, the actual underlying problem might be low computer self-efficacy of the target user group. In such cases, training interventions aimed at improving computer self-efficacy of users may be more effective than improved interface design for increasing user acceptance.

3,288 citations


Authors

Showing all 118112 results

NameH-indexPapersCitations
Walter C. Willett3342399413322
David J. Hunter2131836207050
David Miller2032573204840
Mark I. McCarthy2001028187898
Dennis W. Dickson1911243148488
David H. Weinberg183700171424
Eric Boerwinkle1831321170971
John C. Morris1831441168413
Aaron R. Folsom1811118134044
H. S. Chen1792401178529
Jie Zhang1784857221720
Jasvinder A. Singh1762382223370
Feng Zhang1721278181865
Gang Chen1673372149819
Hongfang Liu1662356156290
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023200
20221,177
202111,903
202011,807
201910,984
201810,367