• Journal of KIISE:Software and Applications
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• v.29 no.7
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• pp.498-509
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• 2002

As WWW grows at an increasing speed, a classifier targeted at hypertext has become in high demand. While document categorization il quite mature, the issue of utilizing hypertext structure and hyperlinks has been relatively unexplored. In this paper, we propose a practical method for enhancing both the speed and the quality of hypertext categorization using hyerlinks. In comparison against a recently proposed technique that appears to be the only one of the kind, we obtained up to 18.5% of improvement in effectiveness while reducing the processing time dramatically. We attempt to explain through experiments what factors contribute to tile improvement.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.10-13
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• 2015

Google App Engine(GAE)은 플랫폼 서비스 형태(Platform as a Service, PaaS)의 클라우드 인프라이며 GAE를 기반으로 웹어플리케이션을 제작할 수 있도록 다양한 개발 도구를 제공해 준다. 본 논문에서는 Python 및 Go를 이용하여 GAE 상에서 구현한 클라우드 기반의 web application들의 성능을 비교하고자 한다. 각 web application의 주요 기능은 회원가입, 로그인, 채팅 등으로 구성되어 있고 특히, 회원목록이나 채팅 데이터를 처리하기 위하여 GAE에서 제공하는 Google Datastore를 사용하였다. 성능비교를 위하여 Python2.5, Python 2.7 및 Go를 사용하여 통일한 기능의 web application을 구현하였으며 각각의 메뉴에 대하여 서버 로직의 실행과 장고 (Django) 스타일의 HTML 템플릿을 렌더링하는데 걸리는 시간을 구하고 이를 비교 분석하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.285-290
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• 2006

In this paper we propose a novel personalized paper search system using the relevance among user's queried keywords and user's behaviors on a searched paper list. The proposed system builds user's individual relevance network from analyzing the appearance frequencies of keywords in the searched papers. The relevance network is personalized by providing weights to the appearance frequencies of keywords according to users' behaviors on the searched list, such as 'downloading,' 'opening,' and 'no-action.' In the experimental section, we demonstrate our method using 100 users' search information in the University of Suwon.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.127-132
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• 2009

Geographic information with convergence ubiquitous IT technologies becomes much more intelligent. In ubiquitous space, users can make information access easier and the use of geographic information more efficient through the 'Geospatial Web,' as a platform between the real world and the virtual world. Many global IT venders make an effort to develop innovated technologies, such as Geospatial web platforms and engines. This study examines the concept of 'Geospatial Web,' technology trends for intelligent geographic information and standardization activities for ubiquitous geographic information. Finally, to obtain international market competitiveness, the technology development strategies for intelligent geographic information are suggested.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.04a
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• pp.397-400
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• 2011

MDO Optimization for a low pressure axial compressor rotor has been carried out to improve aerodynamic performance and structural stability. Global optimized solution was obtained from an artificial neural network model with genetic algorithm. Optimized rotor model has a high blade loading near hub and near zero incidence flow angle near tip region to reduce the incidence loss and flow separation at trailing edge region. Also the rotor shape is converged to a trapezoid shape to reduce the maximum stress occurred at the root of the blade. Numerical simulation results show that rotor has 87.6% rotor efficiency and safety factor over than 3.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.04a
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• pp.103-108
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• 2011

The turbulent mixing of a kerosene/liquid oxygen coaxial swirl injector under supercritical pressures have been numerically investigated. Kerosene surrogate models are proposed for the kerosene thermodynamic properties. Turbulent numerical model is based on LES(Large Eddy Simulation) with real-fluid transport and thermodynamics over the entire pressure range; Soave modification of Redlich-Kwong equation of state, Chung's model for viscosity/conductivity, and Fuller's theorem for diffusivity to take account Takahashi's compressible effect. The effect of operating pressure on thermodynamic properties and mixing dynamics inside an injector and a combustion chamber are investigated. Power spectral densities of pressure fluctuations in the injector under various chamber pressure are analyzed.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.65-69
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• 2012

An oxygen rich preburner was tested and the responses from the pressure sensors were studied with FFT analysis. Since the limited capability of the static sensor, less than 250 Hz frequency domain was investigated and compared to the results of the dynamic sensors. As a result, 60 Hz harmonics were presented dominant in the combustion pressure and oxygen inlet pressure. While similar harmonics were shown with the dynamic sensor, it indicated that harmonics less than 60 Hz were very minor and the high frequency is more important.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.921-926
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• 2006

The present study has been conducted economic analysis through actual operation of EHP and GHP which are installed at the same building of an university Cost items, such as initial cost, annual energy cost and maintenance cost of each system are considered to analyze LCC and economical efficiency is compared. The initial cost is considered on the basis of actual costs, and annual energy cost is converted into the cost after measuring electricity and gas consumption a day. LCC applied present value method is used to assess economical efficiency of both them. Variables used to LCC analysis are electricity cost escalation rate, natural gas cost escalation rate, interest rate, and service lives and when each of them are 4%, 2%, 8%, and 20 years, results of analysis short that EHP(148,257,306 won) is 8.05%(12,981,990 won) more profitable than GHP(161,239,295 won).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.10
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• pp.883-892
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• 2021

This paper provides a process for developing deep learning-based aerial object detection models that can run in realtime on onboard. To improve object detection performance, we pre-process and augment the training data in the training stage. In addition, we perform transfer learning and apply a weighted cross-entropy method to reduce the variations of detection performance for each class. To improve the inference speed, we have generated inference acceleration engines with quantization. Then, we analyze the real-time performance and detection performance on custom aerial image dataset to verify generalization.

• Electronics and Telecommunications Trends
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• v.34 no.4
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• pp.23-31
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• 2019

Deep learning is a hot topic in both academic and industrial fields. Deep learning applications can be categorized into two areas. The first category involves applications such as Google Alpha Go using interfaces with human operators to run complicated inference engines in high-performance servers. The second category includes embedded applications for mobile Internet-of-Things devices, automotive vehicles, etc. Owing to the characteristics of the deployment environment, applications in the second category should be bounded by certain H/W and S/W restrictions depending on their running environment. For example, image recognition in an autonomous vehicle requires low latency, while that on a mobile device requires low power consumption. In this paper, we describe issues faced by embedded applications and review popular inference engines. We also introduce a project that is being development to satisfy the H/W and S/W requirements.