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Institution

Philips

CompanyVantaa, Finland
About: Philips is a company organization based out in Vantaa, Finland. It is known for research contribution in the topics: Signal & Layer (electronics). The organization has 68260 authors who have published 99663 publications receiving 1882329 citations. The organization is also known as: Koninklijke Philips Electronics N.V. & Royal Philips Electronics.


Papers
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Journal ArticleDOI
TL;DR: The price dynamics in a competitive market consisting of spectrum agile network service providers and users, where multiple self interested spectrum providers operating with different technologies and costs compete for potential customers is explored.
Abstract: We explore the price dynamics in a competitive market consisting of spectrum agile network service providers and users. Here, multiple self interested spectrum providers operating with different technologies and costs compete for potential customers. Different buyers or consumers may evaluate the same seller differently depending on their applications, operating technologies and locations. Two different buyer populations, the quality-sensitive and the price-sensitive are investigated, and the resulting collective price dynamics are studied using a combination of analysis and simulations. Various scenarios are considered regarding the nature and accuracy of information available to the sellers. A myopically optimal strategy is studied when full information is available, while a stochastic learning based strategy is considered when the information is limited. Cooperating groups may be formed among the sellers which will in-turn influence the group profit for those participants. Free riding phenomenon is observed under certain circumstances

208 citations

Journal ArticleDOI
Emile H. L. Aarts1
TL;DR: The concept of ambient intelligence is reviewed and its relation with multimedia is elaborated on and the emphasis is on qualitative aspects, highlighting those elements that play a role in realizing ambient intelligence.
Abstract: Ambient intelligence opens up a world of unprecedented experiences. The interaction of people with electronic devices will change as context awareness, natural interfaces, and ubiquitous availability of information come to fruition. Ambient intelligence is going to impose major challenges on multimedia research. Distributed multimedia applications and their processing on embedded static and mobile platforms will play a major role in the development of ambient-intelligent environments. The requirements that ambient-intelligent multimedia applications impose on the mechanisms users apply to interact with media call for paradigms substantially different from contemporary interaction concepts. The complexity of media will continually increase in terms of volume and functionality, thus introducing a need for simplicity and ease of use. Therefore, the massively distributed, integrated use of media will require replacing well-known interaction vehicles, such as remote control and menu-driven search and control, with novel more intuitive, and natural concepts. This article reviews the concept of ambient intelligence and elaborates on its relation with multimedia. (The "Advances in media processing" sidebar gives insight into the developments that have set the stage for this new step forward.) The emphasis is on qualitative aspects, highlighting those elements that play a role in realizing ambient intelligence. Multimedia processing techniques and applications are key to realizing ambient intelligence, and they introduce major challenges to the design and implementation of both media-processing platforms and multimedia applications. Technology will not be the limiting factor in realizing ambient intelligence. The ingredients to let the computers disappear are already available, but the true success of the paradigm will depend on the ability to develop concepts that allow natural interaction with digital environments. We must build these digital environments with the invisible technology of the forthcoming century. The role of intelligent algorithms in this respect is apparent because it is the key enabling factor for realizing natural interaction.

208 citations

Journal ArticleDOI
TL;DR: In this paper, a recently developed approach, called electric properties tomography (EPT), is adapted for and applied to in vivo imaging, which derives the patient's electric conductivity and permittivity from the spatial sensitivity distributions of the applied radiofrequency coils.
Abstract: The electric properties of human tissue can potentially be used as an additional diagnostic parameter, e.g., in tumor diagnosis. In the framework of radiofrequency safety, the electric conductivity of tissue is needed to correctly estimate the local specific absorption rate distribution during MR measurements. In this study, a recently developed approach, called electric properties tomography (EPT) is adapted for and applied to in vivo imaging. It derives the patient's electric conductivity and permittivity from the spatial sensitivity distributions of the applied radiofrequency coils. In contrast to other methods to measure the patient's electric properties, EPT does not apply externally mounted electrodes, currents, or radiofrequency probes, which enhances the practicability of the approach. This work shows that conductivity distributions can be reconstructed from phase images and permittivity distributions can be reconstructed from magnitude images of the radiofrequency transmit field. Corresponding numerical simulations using finite-difference time-domain methods support the feasibility of this phase-based conductivity imaging and magnitude-based permittivity imaging. Using this approximation, three-dimensional in vivo conductivity and permittivity maps of the human brain are obtained in 5 and 13 min, respectively, which can be considered a step toward clinical feasibility for EPT. Magn Reson Med, 2011. © 2011 Wiley-Liss, Inc.

207 citations

Patent
28 Jun 1999
TL;DR: In this article, a frame grab thread is used to acquire frames from an input data stream to be analyzed by a cut detector thread and a filter thread, and a commercial detection thread determines whether a commercial has occurred from data created by the cut detector and the filter thread stored in a memory.
Abstract: A commercial detection apparatus includes a frame grab thread which acquires frames from an input data stream to be analyzed by a cut detector thread and a filter thread. A commercial detection thread determines whether a commercial has occurred from data created by the cut detector thread and the filter thread stored in a memory. A factor used by the commercial detection thread is whether a black frame has occurred. The input data stream is divided into a plurality of regions and then a maximum and minimum value for a section of these regions is determined and compared to one another. If the maximum and minimum values are close enough, and the maximum value is below a threshold, then the frame is deemed to be black. The commercial detection thread also looks at the average cut frame distance, cut rate, changes in the average cut frame distance, the absence of a logo, a commercial signature detection, brand name detection, a series of black frames preceding a high cut rate, similar frames located within a specified period of time before a frame being analyzed and character detection. During playback, the detected commercials are either skipped or substituted with alternate content.

207 citations


Authors

Showing all 68268 results

NameH-indexPapersCitations
Mark Raymond Adams1471187135038
Dario R. Alessi13635474753
Mohammad Khaja Nazeeruddin12964685630
Sanjay Kumar120205282620
Mark W. Dewhirst11679757525
Carl G. Figdor11656652145
Mathias Fink11690051759
David B. Solit11446952340
Giulio Tononi11451158519
Jie Wu112153756708
Claire M. Fraser10835276292
Michael F. Berger10754052426
Nikolaus Schultz106297120240
Rolf Müller10490550027
Warren J. Manning10260638781
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20235
202239
2021898
20201,428
20191,665
20181,378