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Exploiting Language Models to Classify Events from Twitter
Vo, Duc-Thuan,Hai, Vo Thuan,Ock, Cheol-Young Hindawi Publishing Corporation 2015 Computational intelligence and neuroscience Vol.2015 No.-
<P>Classifying events is challenging in Twitter because tweets texts have a large amount of temporal data with a lot of noise and various kinds of topics. In this paper, we propose a method to classify events from Twitter. We firstly find the distinguishing terms between tweets in events and measure their similarities with learning language models such as ConceptNet and a latent Dirichlet allocation method for selectional preferences (LDA-SP), which have been widely studied based on large text corpora within computational linguistic relations. The relationship of term words in tweets will be discovered by checking them under each model. We then proposed a method to compute the similarity between tweets based on tweets' features including common term words and relationships among their distinguishing term words. It will be explicit and convenient for applying to k-nearest neighbor techniques for classification. We carefully applied experiments on the Edinburgh Twitter Corpus to show that our method achieves competitive results for classifying events.</P>
STS 304 스테인리스강의 대기중 1050~1200˚C, 1시간 동안의 산화
Thuan Dinh Nguyen,이동복 대한금속·재료학회 2009 대한금속·재료학회지 Vol.47 No.4
The STS304 stainless steel was oxidized isothermally and cyclically at temperatures between 1050 and 1200˚C for 1 hr in air. During isothermal oxidation, it displayed good oxidation resistance at 1050˚C. However, it suffered from breakaway oxidation above 1100˚C, being accompanied with internal oxidation. During cyclic oxidation, it also displayed good oxidation resistance at 1050˚C, but it suffered from massive weight loss above 1125˚C. The oxide scales formed consisted primarily of Fe2O3, Fe3O4 with and without Cr2O3. They were generally non-adherent.
Thuan-Hieu Tran,장우진,김영범,구윤모,김은기,윤주영,김진환 한국생물공학회 2007 Biotechnology and Bioprocess Engineering Vol.12 No.5
The effect of fluidic conditions on the bioluminescent detection of ATP in a microfluidic device was surveyed using home-made detector system. The bioluminescent reaction of ATP was directly affected by the retention time and flow rates of the solutions in this diffusion-based mixing and reaction system due to the laminar flow in the microchannel. ATP and enzyme solutions were separately injected into the microfluidic device at different flow rates through 3 inlet ports. The ATP solution was injected through the middle port, while the enzyme solution was injected in the two remaining ports. When the ratio of ATP to enzyme solution was fixed, the optimum flow rates of enzyme, ATP, and enzyme solution was 3.5, 8.0, and 3.5 μL/min, respectively. The optimal total flow rate was 15 μL/min. The detection limit for the concentration of ATP at optimal conditions was less than 10-7 M.