Results 251 to 260 of about 140,191 (290)
Support vector machines for disruption prediction and novelty detection at JET [PDF]
Fusion Engineering and Design, 2007 In the last years there has been a growing interest on black box approaches to disruption prediction. The drawback of these approaches is that the system could deteriorate its performance once it does not get updated.
B Cannas, A Fanni, P Sonato
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Predictability and Disruption of Spontaneous Speech
Language and Speech, 1966Three experiments were conducted to test the general hypothesis that disrupted spontaneous speech is less predictable than fluent speech. Predictability was estimated by means of the Cloze procedure and disruption by Mahl's non- ah speech disturbance ratio. The hypothesis was not confirmed.
S, Feldstein, C, Rogalski, J, Jaffe
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Demystifying Disruption: A New Model for Understanding and Predicting Disruptive Technologies
Marketing Science, 2010The failure of firms in the face of technological change has been a topic of intense research and debate, spawning the theory (among others) of disruptive technologies. However, the theory suffers from circular definitions, inadequate empirical evidence, and lack of a predictive model. We develop a new schema to address these limitations.
Ashish Sood, Gerard J. Tellis
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A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals [PDF]
International Journal of Environmental Research and Public Health, 2016 Endocrine disruptors such as polychlorinated biphenyls (PCBs), diethylstilbestrol (DES) and dichlorodiphenyltrichloroethane (DDT) are agents that interfere with the endocrine system and cause adverse health effects.
Huixiao Hong +2 more
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Disruption of embryonic vascular development in predictive toxicology
Birth Defects Research Part C: Embryo Today: Reviews, 2011AbstractToxicity testing in the 21st century is moving toward using high‐throughput screening assays to rapidly test thousands of chemicals against hundreds of molecular targets and biological pathways, and to provide mechanistic information on chemical effects in human cells and small model organisms.
Thomas B, Knudsen +1 more
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Predicting Structural Disruption of Proteins Caused by Crossover
2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2005We present a machine learning model that predicts a structural disruption score from a protein s primary structure. SCHEMA was introduced by Frances Arnold and colleagues as a method for determining putative recombination sites of a protein on the basis of the full (PDB) description of its structure. The present method provides an alternative to SCHEMA
Bauer, Denis +3 more
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Feature Selection for Prediction of Railway Disruption Length
2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019Disruptions such as accidents, facility failures and power outage occur frequently during daily railway operation, which can disrupt the railway timetable and cause financial cost in terms of lost patronage. Recent study indicates that skilled dispatchers can estimate the disruption length based on the analysis of related features.
Menglin Fan, Wei Zheng
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Bid Prediction for Multi-Robot Exploration with Disrupted Communications
2021 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 2021Teams of autonomous mobile robots have potential to contribute to surveillance as well as search and rescue operations. Larger and more complex disaster scenarios with high operational tempo, such as when delay may mean further loss of life, may benefit from cooperative teams of many robots working together for efficient search operations ...
Bradley Woosley +4 more
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Modeling railway disruption lengths with Copula Bayesian Networks [PDF]
Transportation Research Part C: Emerging Technologies, 2016 Decreasing the uncertainty in the lengths of railway disruptions is a major help to disruption management. To assist the Dutch Operational Control Center Rail (OCCR) during disruptions, we propose the Copula Bayesian Network method to construct a ...
Dorota Kurowicka, Rob M P Goverde
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Prediction and mitigation of disruptions in ASDEX Upgrade
Journal of Nuclear Materials, 2001Abstract Disruptions in tokamaks are instabilities events which can damage the machine components. The avoidance and mitigation of these events is desirable in present machines as well as in Next Step devices (such as ITER). A neural network has been developed to predict the occurrence of disruptions caused by edge cooling mechanisms in ASDEX Upgrade.
G Pautasso +10 more
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