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Institution

Carnegie Mellon University

EducationPittsburgh, Pennsylvania, United States
About: Carnegie Mellon University is a education organization based out in Pittsburgh, Pennsylvania, United States. It is known for research contribution in the topics: Population & Robot. The organization has 36317 authors who have published 104359 publications receiving 5975734 citations. The organization is also known as: CMU & Carnegie Mellon.


Papers
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Journal ArticleDOI
TL;DR: The total structure of Au(38)(SC(2)H(4)Ph)(24) nanoparticles determined by single crystal X-ray crystallography is reported, which is based upon a face-fused Au(23) biicosahedral core and capped by three monomeric Au(SR)(2) staples at the waist of the Au( 23) rod.
Abstract: We report the total structure of Au38(SC2H4Ph)24 nanoparticles determined by single crystal X-ray crystallography. This nanoparticle is based upon a face-fused Au23 biicosahedral core, which is further capped by three monomeric Au(SR)2 staples at the waist of the Au23 rod and six dimeric staples with three on the top icosahedron and other three on the bottom icosahedron. The six Au2(SR)3 staples are arranged in a staggered configuration, and the Au38S24 framework has a C3 rotation axis.

921 citations

Journal ArticleDOI
TL;DR: In this article, a systematic investigation of all simple possibilities of having massive neutrinos in SU(2) models of electroweak interactions, without the ad hoc imposition of lepton number conservation, is presented.
Abstract: We make a systematic investigation of all simple possibilities of having massive neutrinos in SU(2)\ifmmode\times\else\texttimes\fi{}U(1) models of electroweak interactions, without the ad hoc imposition of lepton-number conservation. The minimal standard model is enlarged with triplet or singly or doubly charged singlet scalars as well as fermions in singlet and doublet representations. We find that in all cases the neutrino mass eigenstates are Majorana fields. This is so even though right-handed neutrino fields are added to the model. When mass terms of the Dirac type are also present (and if ${\ensuremath{ u}}_{R}'\mathrm{s}$ also have small masses) neutrinos will oscillate into antineutrinos (which, we argue, are most likely "sterile"). General fermion mass terms of both Dirac and Majorana types are studied and the results are included in the Appendix.

920 citations

Book ChapterDOI
11 May 2004
TL;DR: Two new regional shape descriptors are introduced: 3D shape contexts and harmonic shape contexts that outperform the others on cluttered scenes on recognition of vehicles in range scans of scenes using a database of 56 cars.
Abstract: Recognition of three dimensional (3D) objects in noisy and cluttered scenes is a challenging problem in 3D computer vision. One approach that has been successful in past research is the regional shape descriptor. In this paper, we introduce two new regional shape descriptors: 3D shape contexts and harmonic shape contexts. We evaluate the performance of these descriptors on the task of recognizing vehicles in range scans of scenes using a database of 56 cars. We compare the two novel descriptors to an existing descriptor, the spin image, showing that the shape context based descriptors have a higher recognition rate on noisy scenes and that 3D shape contexts outperform the others on cluttered scenes.

919 citations

Proceedings ArticleDOI
05 Nov 2003
TL;DR: This paper is the first on secure information aggregation in sensor networks that can handle a malicious aggregator and sensor nodes, and presents efficient protocols for secure computation of the median and the average of the measurements, for the estimation of the network size, and for finding the minimum and maximum sensor reading.
Abstract: Sensor networks promise viable solutions to many monitoring problems. However, the practical deployment of sensor networks faces many challenges imposed by real-world demands. Sensor nodes often have limited computation and communication resources and battery power. Moreover, in many applications sensors are deployed in open environments, and hence are vulnerable to physical attacks, potentially compromising the sensor's cryptographic keys.One of the basic and indispensable functionalities of sensor networks is the ability to answer queries over the data acquired by the sensors. The resource constraints and security issues make designing mechanisms for information aggregation in large sensor networks particularly challenging.In this paper, we propose a novel framework for secure information aggregation in large sensor networks. In our framework certain nodes in the sensor network, called aggregators, help aggregating information requested by a query, which substantially reduces the communication overhead. By constructing efficient random sampling mechanisms and interactive proofs, we enable the user to verify that the answer given by the aggregator is a good approximation of the true value even when the aggregator and a fraction of the sensor nodes are corrupted. In particular, we present efficient protocols for secure computation of the median and the average of the measurements, for the estimation of the network size, and for finding the minimum and maximum sensor reading. Our protocols require only sublinear communication between the aggregator and the user. To the best of our knowledge, this paper is the first on secure information aggregation in sensor networks that can handle a malicious aggregator and sensor nodes.

918 citations

Journal ArticleDOI
08 Feb 1974-Science
TL;DR: It is shown that, by viewing experimentation in a parameter-estimating paradigm instead of a hypothesis-testing paradigm, one can obtain much more information from experiments—information that, combined with contemporary theoretical models of the cognitive processes, has implications for human performance on tasks quite different from those of the original experiments.
Abstract: I have explored some of the interactions between research on higher mental processes over the past decade or two and laboratory experiments on simpler cognitive processes. I have shown that, by viewing experimentation in a parameter-estimating paradigm instead of a hypothesis-testing paradigm, one can obtain much more information from experiments-information that, combined with contemporary theoretical models of the cognitive processes, has implications for human performance on tasks quite different from those of the original experiments. The work of identifying and measuring the basic parameters of the human information processing system has just begun, but already important information has been gained. The psychological reality of the chunk has been fairly well demonstrated, and the chunk capacity of short-term memory has been shown to be in the range of five to seven. Fixation of information in longterm memory has been shown to take about 5 or 10 seconds per chunk. Some other "magical numbers" have been estimated-for example, visual scanning speeds and times required for simple grammatical transformations-and no doubt others remain to be discovered. But even the two basic constants discussed in this article-short-term memory capacity and rate of fixation in long-term memory-organize, systematize, and explain a wide range of findings, about both simple tasks and more complex cognitive performances that have been reported in the psychological literature over the past 50 years or more.

915 citations


Authors

Showing all 36645 results

NameH-indexPapersCitations
Yi Chen2174342293080
Rakesh K. Jain2001467177727
Robert C. Nichol187851162994
Michael I. Jordan1761016216204
Jasvinder A. Singh1762382223370
J. N. Butler1722525175561
P. Chang1702154151783
Krzysztof Matyjaszewski1691431128585
Yang Yang1642704144071
Geoffrey E. Hinton157414409047
Herbert A. Simon157745194597
Yongsun Kim1562588145619
Terrence J. Sejnowski155845117382
John B. Goodenough1511064113741
Scott Shenker150454118017
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023120
2022499
20214,980
20205,375
20195,420
20184,972