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Institution

Hewlett-Packard

CompanyPalo Alto, California, United States
About: Hewlett-Packard is a company organization based out in Palo Alto, California, United States. It is known for research contribution in the topics: Signal & Substrate (printing). The organization has 34663 authors who have published 59808 publications receiving 1467218 citations. The organization is also known as: Hewlett Packard & Hewlett-Packard Company.


Papers
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Journal ArticleDOI
TL;DR: In this installment of Trend Wars, the authors discuss cloud computing and OpenNebula with Ignacio M. Llorente and Rubén S. Montero, who are the principal investigator and the chief architect, respectively, of the open source Open nebula project.
Abstract: In this installment of Trend Wars, we discuss cloud computing and OpenNebula with Ignacio M. Llorente and Ruben S. Montero, who are the principal investigator and the chief architect, respectively, of the open source OpenNebula project.

268 citations

Proceedings ArticleDOI
24 Oct 1999
TL;DR: This method first locates candidate text regions directly in the DCT compressed domain, and then reconstructs the candidate regions for further refinement in the spatial domain, so that only a small amount of decoding is required.
Abstract: We present a method to automatically locate captions in MPEG video. Caption text regions are segmented from the background using their distinguishing texture characteristics. This method first locates candidate text regions directly in the DCT compressed domain, and then reconstructs the candidate regions for further refinement in the spatial domain. Therefore, only a small amount of decoding is required. The proposed algorithm achieves about 4.0% false reject rate and less than 5.7% false positive rate on a variety of MPEG compressed video containing more than 42,000 frames.

268 citations

Journal ArticleDOI
TL;DR: This study proposes and experimentally demonstrates an artificial nociceptor based on a diffusive memristor with critical dynamics for the first time, and builds an artificial sensory alarm system to experimentally demonstrate the feasibility and simplicity of integrating such novel artificial nOCICEptor devices in artificial intelligence systems, such as humanoid robots.
Abstract: A nociceptor is a critical and special receptor of a sensory neuron that is able to detect noxious stimulus and provide a rapid warning to the central nervous system to start the motor response in the human body and humanoid robotics. It differs from other common sensory receptors with its key features and functions, including the “no adaptation” and “sensitization” phenomena. In this study, we propose and experimentally demonstrate an artificial nociceptor based on a diffusive memristor with critical dynamics for the first time. Using this artificial nociceptor, we further built an artificial sensory alarm system to experimentally demonstrate the feasibility and simplicity of integrating such novel artificial nociceptor devices in artificial intelligence systems, such as humanoid robots. The development of humanoid robots with artificial intelligence calls for smart solutions for tactile sensing systems that respond to dynamic changes in the environment. Here, Yoon et al. emulate non-adaption and sensitization function of a nociceptor—a sensory neuron—using diffusive oxide-based memristors.

267 citations

Journal ArticleDOI
TL;DR: In this article, the authors investigated the capacity investment decision of a supplier who solicits private forecast information from a manufacturer and found that the underlying reason for cooperation is trust and trustworthiness.
Abstract: This paper investigates the capacity investment decision of a supplier who solicits private forecast information from a manufacturer. To ensure abundant supply, the manufacturer has an incentive to inflate her forecast in a costless, nonbinding, and nonverifiable type of communication known as “cheap talk.” According to standard game theory, parties do not cooperate and the only equilibrium is uninformative---the manufacturer's report is independent of her forecast and the supplier does not use the report to determine capacity. However, we observe in controlled laboratory experiments that parties cooperate even in the absence of reputation-building mechanisms and complex contracts. We argue that the underlying reason for cooperation is trust and trustworthiness. The extant literature on forecast sharing and supply chain coordination implicitly assumes that supply chain members either absolutely trust each other and cooperate when sharing forecast information, or do not trust each other at all. Contrary to this all-or-nothing view, we determine that a continuum exists between these two extremes. In addition, we determine (i) when trust is important in forecast information sharing, (ii) how trust is affected by changes in the supply chain environment, and (iii) how trust affects related operational decisions. To explain and better understand the observed behavioral regularities, we also develop an analytical model of trust to incorporate both pecuniary and nonpecuniary incentives in the game-theoretic analysis of cheap-talk forecast communication. The model identifies and quantifies how trust and trustworthiness induce effective cheap-talk forecast sharing under the wholesale price contract. We also determine the impact of repeated interactions and information feedback on trust and cooperation in forecast sharing. We conclude with a discussion on the implications of our results for developing effective forecast management policies. This paper was accepted by Ananth Iyer, operations and supply chain management.

267 citations

Patent
20 Aug 1992
TL;DR: In this paper, a programmable machine system and a method for managing electronic data access among multiple different relational databases in a network distributed database environment is presented, where the machine is programmed so that it can construct cost-effective access strategies for any of the participating databases absent any DBMS-specific cost models.
Abstract: A programmable machine system and method for managing electronic data access among multiple different relational databases in a network distributed database environment. The machine is programmed so that it can construct cost-effective access strategies for any of the participating databases absent any DBMS-specific cost models. The system provides query optimization across different database management systems in a network distributed database environment based on a calibrating database relying only on typical relational database statistics and cost data is developed by running queries in the various databases against the calibrating database. A logical cost model is constructed using the resulting cost data and is used to estimate the cost of a given query based on logical characteristics of the DBMS, the relations, and the query itself. The cost of a complex query is estimated using primitive queries. Optimal query access strategies are thereby designed and used to control execution of the queries across relational databases controlled by two or more different database management systems.

267 citations


Authors

Showing all 34676 results

NameH-indexPapersCitations
Andrew White1491494113874
Stephen R. Forrest1481041111816
Rafi Ahmed14663393190
Leonidas J. Guibas12469179200
Chenming Hu119129657264
Robert E. Tarjan11440067305
Hong-Jiang Zhang11246149068
Ching-Ping Wong106112842835
Guillermo Sapiro10466770128
James R. Heath10342558548
Arun Majumdar10245952464
Luca Benini101145347862
R. Stanley Williams10060546448
David M. Blei98378111547
Wei-Ying Ma9746440914
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
202223
2021240
20201,028
20191,269
2018964