Institution
Washington State University
Education•Pullman, Washington, United States•
About: Washington State University is a education organization based out in Pullman, Washington, United States. It is known for research contribution in the topics: Population & Gene. The organization has 26947 authors who have published 57736 publications receiving 2341509 citations. The organization is also known as: WSU & Wazzu.
Topics: Population, Gene, Catalysis, Context (language use), Poison control
Papers published on a yearly basis
Papers
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TL;DR: This survey discusses clear motivations and advantages of multi-sensor data fusion and particularly focuses on physical activity recognition, aiming at providing a systematic categorization and common comparison framework of the literature, by identifying distinctive properties and parameters affecting data fusion design choices at different levels.
680 citations
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TL;DR: This article focused on recognizing simple human activities, which can be exploited to great societal benefits, especially in real-life, human centric applications such as elder care and healthcare.
Abstract: In principle, activity recognition can be exploited to great societal benefits, especially in real-life, human centric applications such as elder care and healthcare. This article focused on recognizing simple human activities. Recognizing complex activities remains a challenging and active area of research and the nature of human activities poses different challenges. Human activity understanding encompasses activity recognition and activity pattern discovery. The first focuses on accurate detection of human activities based on a predefined activity model. An activity pattern discovery researcher builds a pervasive system first and then analyzes the sensor data to discover activity patterns.
679 citations
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19 Nov 2003TL;DR: It is shown that random objects (particularly random matrices) have "predictable" structures in the spectral domain and it develops a random matrix-based spectral filtering technique to retrieve original data from the dataset distorted by adding random values.
Abstract: Privacy is becoming an increasingly important issue in many data mining applications. This has triggered the development of many privacy-preserving data mining techniques. A large fraction of them use randomized data distortion techniques to mask the data for preserving the privacy of sensitive data. This methodology attempts to hide the sensitive data by randomly modifying the data values often using additive noise. We question the utility of the random value distortion technique in privacy preservation. We note that random objects (particularly random matrices) have "predictable" structures in the spectral domain and it develops a random matrix-based spectral filtering technique to retrieve original data from the dataset distorted by adding random values. We present the theoretical foundation of this filtering method and extensive experimental results to demonstrate that in many cases random data distortion preserve very little data privacy. We also point out possible avenues for the development of new privacy-preserving data mining techniques like exploiting multiplicative and colored noise for preserving privacy in data mining applications.
676 citations
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TL;DR: Interruptions were found to improve decision-making performance on simple tasks and to lower performance on complex tasks, and the frequency of interruptions and the dissimilarity of content between the primary and interruption tasks was found to exacerbate this effect.
Abstract: Interruptions are a common aspect of the work environment of most organizations. Yet little is known about how interruptions and their characteristics, such as frequency of occurrence, influence decision-making performance of individuals. Consequently, this paper reports the results of two experiments investigating the influence of interruptions on individual decision making. Interruptions were found to improve decision-making performance on simple tasks and to lower performance on complex tasks. For complex tasks, the frequency of interruptions and the dissimilarity of content between the primary and interruption tasks was found to exacerbate this effect. The implications of these results for future research and practice are discussed.
672 citations
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Arizona State University1, Pace University2, Texas State University3, DePaul University4, Universidad del Norte, Colombia5, University of Kentucky6, Washington State University7, Oklahoma State University–Stillwater8, Northern Illinois University9, Japan Advanced Institute of Science and Technology10, Rutgers University11
TL;DR: In this article, the authors present a research agenda for the emerging area of transformative service research, which lies at the intersection of service research and consumer research and focuses on well-being outcomes related to service and services.
672 citations
Authors
Showing all 27183 results
Name | H-index | Papers | Citations |
---|---|---|---|
Anil K. Jain | 183 | 1016 | 192151 |
Martin Karplus | 163 | 831 | 138492 |
Herbert A. Simon | 157 | 745 | 194597 |
Suvadeep Bose | 154 | 960 | 129071 |
Rajesh Kumar | 149 | 4439 | 140830 |
Kevin Murphy | 146 | 728 | 120475 |
Jonathan D. G. Jones | 129 | 417 | 80908 |
Douglas E. Soltis | 127 | 612 | 67161 |
Peter W. Kalivas | 123 | 428 | 52445 |
Chris Somerville | 122 | 284 | 45742 |
Pamela S. Soltis | 120 | 543 | 61080 |
Yuehe Lin | 118 | 641 | 55399 |
Howard I. Maibach | 116 | 1821 | 60765 |
Jizhong Zhou | 115 | 766 | 48708 |
Farshid Guilak | 110 | 480 | 41327 |