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Yahoo!

CompanyLondon, United Kingdom
About: Yahoo! is a company organization based out in London, United Kingdom. It is known for research contribution in the topics: Population & Web search query. The organization has 26749 authors who have published 29915 publications receiving 732583 citations. The organization is also known as: Yahoo! Inc. & Maudwen-Yahoo! Inc.


Papers
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Journal ArticleDOI
TL;DR: The mechanism underlying MOS-based gas sensor devices, the advances that have been made towards MOS nanostructured materials and the progress towards low-power nano- and microheaters are described, and an ideal nanogas sensor is attempted by combining the best nanomaterial strategy with the best heater implementation.
Abstract: Nanosized gas sensor elements are potentially faster, require lower power, come with a lower limit of detection, operate at lower temperatures, obviate the need for expensive catalysts, are more heat shock resistant and might even come at a lower cost than their macro-counterparts. In the last two decades, there have been important developments in two key areas that might make this promise a reality. First is the development of a variety of very good performing nanostructured metal oxide semiconductors (MOSs), the most commonly used materials for gas sensing; and second are advances in very low power loss miniaturized heater elements. Advanced nano- or micro-nanogas sensors have attracted much attention owing to a variety of possible applications. In this article, we first discuss the mechanism underlying MOS-based gas sensor devices, then we describe the advances that have been made towards MOS nanostructured materials and the progress towards low-power nano- and microheaters. Finally, we attempt to design an ideal nanogas sensor by combining the best nanomaterial strategy with the best heater implementation. In this regard, we end with a discussion of a suspended carbon nanowire-based gas sensor design and the advantages it might offer compared with other more conventional gas sensor devices.

137 citations

Book ChapterDOI
23 Sep 2013
TL;DR: This paper summarizes the goals, organization, and results of the second RepLab competitive evaluation campaign for Online Reputation Management Systems RepLab 2013, which consists of more than 140,000 tweets annotated by a group of trained annotators supervised and monitored by reputation experts.
Abstract: This paper summarizes the goals, organization, and results of the second RepLab competitive evaluation campaign for Online Reputation Management Systems RepLab 2013. RepLab focused on the process of monitoring the reputation of companies and individuals, and asked participant systems to annotate different types of information on tweets containing the names of several companies: first tweets had to be classified as related or unrelated to the entity; relevant tweets had to be classified according to their polarity for reputation Does the content of the tweet have positive or negative implications for the reputation of the entity?, clustered in coherent topics, and clusters had to be ranked according to their priority potential reputation problems had to come first. The gold standard consists of more than 140,000 tweets annotated by a group of trained annotators supervised and monitored by reputation experts.

137 citations

Patent
Matthias Eichstaedt1, Ashvinkumar P. Patel, Qi Lu, Udi Manber1, Kristine Rudkin 
12 Jul 2000
TL;DR: In this article, a search engine that forms a compact representation of a plurality of user queries to efficiently find desired information in an information network is presented, where the search engine comprises a profile processor having logic to receive the queries from the users and a search module.
Abstract: A search engine that forms a compact representation of a plurality of user queries to efficiently find desired information in an information network (100). The search engine (102) comprises a profile processor having logic to receive the queries from the users (110) and a search module. The search module is coupled to the profile processor and has logic to receive the information content, to combine the user queries into a master query, and to match the master query with the information content to determine matching content. The search engine also includes logic to analyze the matching content to determine if any of the queries has been satisfied.

137 citations

Journal ArticleDOI
TL;DR: LLLT was an effective adjunctive treatment that appeared to promote healing following gingivectomy and adj unctive use of low-level laser therapy (LLLT), and clinical evaluation showed better repair for the laser group, mainly after the third day.
Abstract: Objective: The purpose of this study was to investigate gingival healing after gingivectomy and adjunctive use of low-level laser therapy (LLLT). Background Data:LLLT has been used in animal experiments to examine the influence of laser radiation on the wound healing process since the 1960s. However, clinical trials in dentistry are scarce, and most of them refer to treatment after extraction of the third molars, with only a few reports in the area of periodontics. Methods: Twenty patients with periodontal disease were selected, and treatment was planned for gingivectomy to bilateral maxillary and mandibular premolar teeth. After surgery, one side was submitted to LLLT using a 685-nm wavelength, output power of 50 mW, and energy density of 4 J/cm2. The other side was used as the control and did not receive laser irradiation. Healing was evaluated, clinically and biometrically, immediately post-surgery and at days 3, 7, 14, 21, 28, and 35. Results were submitted to statistical analysis. Results: Biometrica...

137 citations

Journal ArticleDOI
TL;DR: In this article, the effects of sample thickness on the drying characteristics, drying time and energy quality of dried product were also determined, and the experimental data was compared with values predicted by the Page model, and by the Henderson and Pabis model, good agreement being obtained with Page model.

136 citations


Authors

Showing all 26766 results

NameH-indexPapersCitations
Ashok Kumar1515654164086
Alexander J. Smola122434110222
Howard I. Maibach116182160765
Sanjay Jain10388146880
Amirhossein Sahebkar100130746132
Marc Davis9941250243
Wenjun Zhang9697638530
Jian Xu94136652057
Fortunato Ciardiello9469547352
Tong Zhang9341436519
Michael E. J. Lean9241130939
Ashish K. Jha8750330020
Xin Zhang87171440102
Theunis Piersma8663234201
George Varghese8425328598
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20232
202247
20211,088
20201,074
20191,568
20181,352