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Institution

Purdue University

EducationWest Lafayette, Indiana, United States
About: Purdue University is a education organization based out in West Lafayette, Indiana, United States. It is known for research contribution in the topics: Population & Context (language use). The organization has 73219 authors who have published 163563 publications receiving 5775236 citations. The organization is also known as: Purdue & Purdue-West Lafayette.


Papers
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Journal ArticleDOI
TL;DR: In this paper, a review of the literature on structural model evaluation is presented, focusing on the use of fit indices, the influential work of James, Mulaik, and Brett, and recent developments in model evaluation presented since James et al.

925 citations

Proceedings ArticleDOI
01 Jan 2018
TL;DR: A trojaning attack on neuron networks that can be successfully triggered without affecting its test accuracy for normal input data, and it only takes a small amount of time to attack a complex neuron network model.
Abstract: With the fast spread of machine learning techniques, sharing and adopting public machine learning models become very popular. This gives attackers many new opportunities. In this paper, we propose a trojaning attack on neuron networks. As the models are not intuitive for human to understand, the attack features stealthiness. Deploying trojaned models can cause various severe consequences including endangering human lives (in applications like auto driving). We first inverse the neuron network to generate a general trojan trigger, and then retrain the model with external datasets to inject malicious behaviors to the model. The malicious behaviors are only activated by inputs stamped with the trojan trigger. In our attack, we do not need to tamper with the original training process, which usually takes weeks to months. Instead, it takes minutes to hours to apply our attack. Also, we do not require the datasets that are used to train the model. In practice, the datasets are usually not shared due to privacy or copyright concerns. We use five different applications to demonstrate the power of our attack, and perform a deep analysis on the possible factors that affect the attack. The results show that our attack is highly effective and efficient. The trojaned behaviors can be successfully triggered (with nearly 100% possibility) without affecting its test accuracy for normal input data. Also, it only takes a small amount of time to attack a complex neuron network model. In the end, we also discuss possible defense against such attacks.

924 citations

Journal ArticleDOI
31 May 1996-Science
TL;DR: Data from double-ended aryl dithiols used to tether nanometer-sized gold clusters deposited from a cluster beam are in good agreement with semiclassical predictions for correlated single-electron tunneling and permit estimation of the electrical resistance of a single XYL molecule.
Abstract: Double-ended aryl dithiols [α,α′-xylyldithiol (XYL) and 4,4′-biphenyldithiol] formed self-assembled monolayers (SAMs) on gold(111) substrates and were used to tether nanometer-sized gold clusters deposited from a cluster beam. An ultrahigh-vacuum scanning tunneling microscope was used to image these nanostructures and to measure their current-voltage characteristics as a function of the separation between the probe tip and the metal cluster. At room temperature, when the tip was positioned over a cluster bonded to the XYL SAM, the current-voltage data showed “Coulomb staircase” behavior. These data are in good agreement with semiclassical predictions for correlated single-electron tunneling and permit estimation of the electrical resistance of a single XYL molecule (∼18 ± 12 megohms).

924 citations

Journal ArticleDOI
TL;DR: A review of the evolution of methodological applications and available data in highway-accident research can be found in this article, where fruitful directions for future methodological developments are identified and the role that new data sources will play in defining these directions is discussed.

923 citations

Journal ArticleDOI
TL;DR: In this article, advances in the strategies for the visible light activation, origin of visible light activity, and electronic structure of various visible-light active TiO 2 photocatalysts are discussed in detail.
Abstract: The remarkable achievement by Fujishima and Honda (1972) in the photo-electrochemical water splitting results in the extensive use of TiO 2 nanomaterials for environmental purification and energy storage/conversion applications. Though there are many advantages for the TiO 2 compared to other semiconductor photocatalysts, its band gap of 3.2 eV restrains application to the UV-region of the electromagnetic spectrum ( λ ≤ 387.5 nm). As a result, development of visible-light active titanium dioxide is one of the key challenges in the field of semiconductor photocatalysis. In this review, advances in the strategies for the visible light activation, origin of visible-light activity, and electronic structure of various visible-light active TiO 2 photocatalysts are discussed in detail. It has also been shown that if appropriate models are used, the theoretical insights can successfully be employed to develop novel catalysts to enhance the photocatalytic performance in the visible region. Recent developments in theory and experiments in visible-light induced water splitting, degradation of environmental pollutants, water and air purification and antibacterial applications are also reviewed. Various strategies to identify appropriate dopants for improved visible-light absorption and electron–hole separation to enhance the photocatalytic activity are discussed in detail, and a number of recommendations are also presented.

921 citations


Authors

Showing all 73693 results

NameH-indexPapersCitations
Yi Cui2201015199725
Yi Chen2174342293080
David Miller2032573204840
Hongjie Dai197570182579
Chris Sander178713233287
Richard A. Gibbs172889249708
Richard H. Friend1691182140032
Charles M. Lieber165521132811
Jian-Kang Zhu161550105551
David W. Johnson1602714140778
Robert Stone1601756167901
Tobin J. Marks1591621111604
Joseph Wang158128298799
Ed Diener153401186491
Wei Zheng1511929120209
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023194
2022834
20217,499
20207,699
20197,294
20186,840