124,065 research outputs found
Lee, Jae Woon (June )
No full textDr Jae Woon (June) Lee has been working, teaching and researching in the field of aviation law and policy since 2004, and is a renowned aviation law expert. His main research and teaching interests are aviation law and competition law.
Prof. Lee has seven years of legal affairs experience in the airline industry, advising the company on issues relating to company liability, government regulation and competition law matters. He has also acted as legal advisor to the Ministry of Foreign Affairs of the Republic of Korea on aviation law issues and regularly attended the International Civil Aviation Organization (ICAO) Legal Committee as a Korean delegate.
Prof. Lee has published on various aviation legal issues in both major air law journals and other leading journals of trade law, company law, competition law, and public international law. He serves on the editorial board of the Annals of Air and Space Law.
Prof. Lee has served as a consultant/expert to government and international agencies, including the European Union Aviation Safety Agency, International Air Transport Association and the Hong Kong Competition Commission. He frequently presents at academic and aviation industry conferences and regularly comments in the media.https://commons.erau.edu/aviasian-bios-2021/1010/thumbnail.jp
Transferable silicon nanowire arrays embedded in flexible polymer for color tuning with metal insulator metal structure
No full textYeong Jae Kim Young Jin Yoo Gil Ju Lee Dong Eun Yoo Dong Wook Lee, Vantari Siva, Hansung Song, Il Suk Kang, Young Min Song
Here, we present the transferable color-tuning structures. These structures are comprised of a polymer embedded silicon nanowire arrays (Si NWAs) stacked on a metal/insulator/metal (MIM) cavity. Upon stacking the Si NWAs on the MIM cavity, these cyan, magenta and yellow colors can be tuned to a color gamut by varying parameters of the Si NWAs such as diameter, height and periods. The fine tuning of these colors were explained on the basis of the measured reflectance spectra, which was further supported by the theoretical simulations
An experimental analysis of limitations of MapReduce for iterative algorithms on Spark
No full textMapReduce is the most popular framework for distributed processing. Recently, the scalability of data mining and machine learning algorithms has significantly improved with help from MapReduce. However, MapReduce does not handle iterative algorithms very efficiently. The problem is that many data mining and machine learning algorithms are iterative by nature. In order to overcome the limitations of MapReduce, many advanced distributed systems have been developed, including HaLoop, iMapReduce, Twister, and Spark. In this paper, we identify and categorize the limitations of MapReduce in handling iterative algorithms, and then, experimentally investigate the consequences of these limitations by using the most flexible and stable distributed system, Spark. According to our experiment results, the network I/O overhead was the primary factor that affected system performance the most. The disk I/O overhead also affected system performance, but it was less significant than the network I/O overhead. For the synchronization overhead, it affected system performance only when the static data was not cached.
Jae Yeon Lee
No full textTitres : Ideal Swimming Pool (c) Jae Yeon Lee. Image reproduite avec l'aimable autorisation de l'artiste. Tous droits réservés Artiste : Jae Yeon Lee Nationalité/pays : Corée du sud Année : 2012 Technique : broderie Concept : Ce projet souligne la nature irréaliste de l'espace en présentant une piscine comme un lieu idéal. Cette œuvre utilise la broderie pour créer une piscine. Ce travail se concentre sur le matériau, le fil, et ses effets. Elle représente également l'eau et ..
DF-TAR: A Deep Fusion Network for Citywide Traffic Accident Risk Prediction with Dangerous Driving Behavior
No full textBecause traffic accidents cause huge social and economic losses, it is of prime importance to precisely predict the traffic accident risk for reducing future accidents. In this paper, we propose a Deep Fusion network for citywide Traffic Accident Risk prediction (DF-TAR) with dangerous driving statistics that contain the frequencies of various dangerous driving offences in each region. Our unique contribution is to exploit these statistics, obtained by processing the data from in-vehicle sensors, for modeling the traffic accident risk. Toward this goal, we first examine the correlation between dangerous driving offences and traffic accidents, and the analysis shows a strong correlation between them in terms of both location and time. Specifically, quick start (0.83), rapid acceleration (0.76), and sharp turn (0.76) are the top three offences that have the highest average correlation scores. We then train the DF-TAR model using the dangerous driving statistics as well as external environmental features. By extensive experiments on various frameworks, the DF-TAR model is shown to improve the accuracy of the baseline models by up to 54% by virtue of the integration of dangerous driving into the modeling of traffic accident risk. © 2021 ACM
Replication data for: The Cross-Sectional Distribution of Price Stickiness Implied by Aggregate Data
No full textCarvalho, Carlos, Dam, Niels Arne, and Lee, Jae Won, (2020) "The Cross-Sectional Distribution of Price Stickiness Implied by Aggregate Data." Review of Economics and Statistics 102:1, 162-179
Replication data for: The Cross-Sectional Distribution of Price Stickiness Implied by Aggregate Data
No full textCarvalho, Carlos, Dam, Niels Arne, and Lee, Jae Won, (2020) "The Cross-Sectional Distribution of Price Stickiness Implied by Aggregate Data." Review of Economics and Statistics 102:1, 162-179
Jae Won Lee, Internal Distance(s) Mid - Career Retrospective
No full textCatalog of an exhibition held at the Oakland University Art Gallery, January 10 – February 22, 2009. Contains essay by Dick Goody.Excerpt from essay by Dick Goody: There is something universal in the act of contemplating nature; there is something contextual too. For example, imagine walking down a path and homing in on a particularly attractive leaf; now, pick up the leaf and weigh its beauty. But also consider all the other things that come to mind. The work of Jae Won Lee focuses on the formalistic beauty of nature. All the other things that come to mind, which inform her work, she consigns obliquely away to be separately archived
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