• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.911-917
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• 2023

In today's world, we find ourselves facing energy crises due to factors such as war and climate crises. To prepare for these energy crises, many researchers continue to study systems related to energy monitoring and conservation, such as energy management systems, energy monitoring, and energy conservation. In line with these efforts, nations are making it mandatory for energy-consuming facilities to implement these systems. However, these facilities, limited by space and energy constraints, are exploring ways to improve. This research explores the operation of a data collection system using low-performance embedded devices. In this context, it proves that an optimized version of RocksDB, a Key-Value store, outperforms traditional databases when it comes to time-series data. Furthermore, a comprehensive database evaluation tool was employed to assess various databases, including optimized RocksDB and regular RocksDB. In addition, heterogeneous databases and evaluations are conducted using a UD Benchmark tool to evaluate them. As a result, we were able to see that on devices with low performance, the time required was up to 11 times shorter than that of other databases.

• International Journal of Railway
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• v.2 no.2
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• pp.50-59
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• 2009

Numerous train operating companies provide training by means of driving simulators. A detailed analysis in the course of the rail research project 2TRAIN has shown that the simulation technology, the purposes of training and the overall concept of simulator-based training are rather diverse (Schmitz & Maag, 2008). A joint factor however are weak assessment capabilities and the fact that the simulator training is often not embedded into the overall competence management. This fact hinders an optimal use of the simulators. Therefore, 2TRAIN aims at the development of enhanced training and assessment tools. Taking into account that several simulators are already in use, the focus lays on the extension of existing simulation technology instead of developing entirely new systems. This extension comprises (1) a common data simulation interface (CDSI), (2) a rule-based expert system (ExSys), (3) a virtual instructor (VI), and (4) an _assessment database (AssDB). The foundation of this technical development is an assessment concept (PERMA concept) that is based on performance markers. The first part of the paper presents this assessment concept and a process model for the two major steps of driver performance assessment, i.e. (1) the specification of exercise and assessment and (2) the assessment algorithm and execution of the assessment. The second part describes the rationale and the functionalities of the simulator add-on tools. Finally, recommendations for further technical improvement and appropriate usage are given. based on the results of a pilot study.

• Corrosion Science and Technology
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• v.18 no.6
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• pp.253-257
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• 2019

A deep learning based real-time painting surface inspection algorithm is proposed herein, designed for developing an autonomous inspection drone. The painting surface inspection is usually conducted manually. However, the manual inspection has a limitation in obtaining accurate data for correct judgement on the surface because of human error and deviation of individual inspection experiences. The best method to replace manual surface inspection is the vision-based inspection method with a camera, using various image processing algorithms. Nevertheless, the visual inspection is difficult to apply to surface inspection due to diverse appearances of material, hue, and lightning effects. To overcome technical limitations, a deep learning-based pattern recognition algorithm is proposed, which is specialized for painting surface inspections. The proposed algorithm functions in real time on the embedded board mounted on an autonomous inspection drone. The inspection results data are stored in the database and used for training the deep learning algorithm to improve performance. The various experiments for pre-inspection of painting processes are performed to verify real-time performance of the proposed deep learning algorithm.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.321-324
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• 2005

In these days, the management and visualization of 3D geo-spatial information is regarded as one of an important issue in GiS and remote sensing fields. 3D GIS is considered with the database issues such as handling and managing of 3D geometry/topology attributes, whereas 3D visualization is basically concerned with 3D computer graphics. This study focused on the design and implementation for the OpenGL API-based rendering system for the complex types of 3D geo-spatial features. In this approach 3D features can be separately processed with the functions of authoring and manipulation of terrain segments, building segments, road segments, and other geo-based things with texture mapping. Using this implementation, it is possible to the generation of an integrated scene with these complex types of 3D features. This integrated rendering system based on the feature-based 3D-GIS model can be extended and effectively applied to urban environment analysis, 3D virtual simulation and fly-by navigation in urban planning. Furthermore, we expect that 3D-GIS visualization application based on OpenGL API can be easily extended into a real-time mobile 3D-GIS system, soon after the release of OpenGLIES which stands for OpenGL for embedded system, though this topic is beyond the scope of this implementation.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1244-1248
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• 2010

The previous study of Digital Broadcasting Recommendation system is based on user explicit profiling information. But user profile is always changing and the exact extraction of user profile is very important in recommendation system like Digital TV using many user interactions. This paper is studied of realtime user profiles aggregation through user remote controller input and matching this profiles with contents meta-data like contents genre information, event information, content viewing time. It is not used commercial database system and network communication solution considering embedded system hardware restriction. And it is considered people want different content genre based on watching time. From the results of this paper, there are improvement of user satisfaction of contents recommendation.

• Journal of KIISE
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• v.42 no.6
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• pp.764-768
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• 2015

Requirement of effective image handling methods such as image retrieval has been increasing with the rising production and consumption of multimedia data. In this paper, a method of constructing more effective descriptor is proposed for robust keypoint based image retrieval. The proposed method uses information embedded in the first order and second order derivative images, in addition to the scale space image, for the descriptor construction. The performance of multi-image descriptor is evaluated in terms of the similarities in keypoints with a public domain image database that contains various image transformations. The proposed descriptor shows significant improvement in keypoint matching with minor increase of the length.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.182-188
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• 2007

모바일 음악 재생 장치의 보급이 활성화 되면서 모바일 환경에서 음악을 즐기고자 하는 욕구가 확대되었다. 모바일 음악 재생 장치의 저장 공간이 확대되어 한번에 많은 곡을 보유하게 되었지만, 실제적으로 많은 곡 중에서 자신이 원하는 곡을 쉽게 찾을 수 있는 방법이 존재하지 않고 있다. 이런 문제들을 해결하기 위해 해당 음악 고유의 Metadata를 활용하여 쉽게 찾고자 하는 경향이 있지만, 현재까지는 단순한 사용자 인터페이스만 제공하고 있다. 각각의 음악은 음악 고유의 Context도 가지게 되며, 사용자의 음악 감상 로그에 의해 생성되는 개인화 Context 및 같은 음악을 즐기는 다른 사용자들에 의해 생성되는 Social Context등으로 하나의 음악과 관련된 Context가 증가되는 추세에 있다. 이와 같이 추가되는 Context들은 음악을 탐색하는데 있어 효과적인 수단이 제공되어야 하지만 모바일 음악 재생장치에 있는 음악 탐색 프로그램은 새롭게 추가되는 Context 에 의한 효과적으로 대응하지 못하고 있다. 이러한 문제점을 해결하기 위해서 모바일 장치에 Embedded Database Engine을 장착하여 동적 트리 생성/탐색을 통한 Context 기반 연관 음악 탐색 방법을 제안하게 되었다. 본 논문에서는 새롭게 고안된 음악 탐색 방법에 대하여 3가지 사항에 대해서 제시하였다. 첫째, 새로운 Context추가에 대한 동적 메뉴 추가 방법을 제시하였다. 둘째, 실제로 새롭게 추가된 사용자 인터페이스에 대해서 알아보았으며, 마지막으로 제시된 방법이 얼마나 효과적인가를 계산하여 일반화 하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.3
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• pp.236-241
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• 1996

This paper presents a new eddy current testing system for inspecting tubes of steam generator in nuclear power plant. The proposed system adopted embedded expert system concept to automate tasks of the inspection such as inspection planning and flaw signal interpretation, and integrated all the tasks into a client/server type computing architecture using database management system. Therefore, human factor errors occurred during inspection could be minimized and the inspection data could be transferred in real-time. As a result, we can increase the level of inspection confidence and the productivity of a personal inspector. A prototype of the proposed system has been developed for 5 years and the test operation has been performed in domestic nuclear power plants.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.349-359
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• 2017

During the past 25 years, in the context of probabilistic safety assessment, efforts have been directed towards establishment of comprehensive pipe failure event databases as a foundation for exploratory research to better understand how to effectively organize a piping reliability analysis task. The focused pipe failure database development efforts have progressed well with the development of piping reliability analysis frameworks that utilize the full body of service experience data, fracture mechanics analysis insights, expert elicitation results that are rolled into an integrated and risk-informed approach to the estimation of piping reliability parameters with full recognition of the embedded uncertainties. The discussion in this paper builds on a major collection of operating experience data (more than 11,000 pipe failure records) and the associated lessons learned from data analysis and data applications spanning three decades. The piping reliability analysis lessons learned have been obtained from the derivation of pipe leak and rupture frequencies for corrosion resistant piping in a raw water environment, loss-of-coolant-accident frequencies given degradation mitigation, high-energy pipe break analysis, moderate-energy pipe break analysis, and numerous plant-specific applications of a statistical piping reliability model framework. Conclusions are presented regarding the feasibility of determining and incorporating aging effects into probabilistic safety assessment models.

• The Journal of the Acoustical Society of Korea
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• v.24 no.2E
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• pp.46-53
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• 2005

Agency for Defense Development (ADD) developed the Submarine Acoustic Information Management System (SAIMS Version 1.0) capable of interfacing some submarine sensors in operation and predicting detection environments for sonars. The major design concepts are as follows: 1) A proper acoustic model is examined and optimized to cover wide spectra of frequency ranges for both active and passive sonars. 2) Interfacing the submarine sensors to an electric navigation chart, the system attempts to maximize the applicability of the information produced. 3) The state-of-the-art database in large area is built and managed on the system. 4) An algorithm, which is able to estimate a full sound speed profile from the limited oceanographic data, is developed and employed on the system. This paper briefly describes design concepts and algorithms embedded in the SAIMS. The applicability of the SAIMS was verified through three sea experiments in October 2003-February 2004.