• 기술혁신학회지
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• 제11권4호
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• pp.592-612
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• 2008

새로운 기술혁신의 돌파구로서 발생되고 발전해온 기술의 융합현상은 21세기 지식기반경제체제와 더불어 더욱 활발하게 진행되고 있다. 그러나 기술의 융합과 융합기술에 대한 이해와 활용성 제고 방안은 아직 도입기로서 더 많은 개념정리 및 분류체계 등의 연구가 필요한 실정이다. 그동안 부처별로 기존의 관련 기술 분류가 산발적이어서 중복투자에 대한 우려가 높았고, 상대적으로 기술의 융합이나 융합기술에 대해서는 적용이 미진한 측면이 많았으므로 기존개념의 정리와 기술융합 분야에 대한 새롭고 정확한 세부 분류체계가 필요하게 되었다. 본 연구에서는 기술의 융합현상을 동적인 흐름으로 파악하고 기술 융합형태에 따른 특성을 분석하여 종합적인 관점에서 기술의 융합특성별 새로운 분류체계를 제안하고자 한다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 춘계학술대회 논문집
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• pp.1375-1381
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• 2007

Optimization system for convergence point control is required for train control system, this paper introduces the way of enhanced optimization for convergence point with data of intelligence full prediction system. Also the result of the intelligence full prediction system is useful for train control system at the convergence point and passenger will take more accurate information from the prediction system.

• International journal of advanced smart convergence
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• 제12권4호
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• pp.190-201
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• 2023

Securing transportation safety infrastructure technology for Lv.4 connected autonomous driving is very important for the spread of autonomous vehicles, and the safe operation of level 4 autonomous vehicles in adverse weather has limitations due to the development of vehicle-only technology. We developed the radar-enabled AI convergence transportation entities detection system. This system is mounted on fixed and mobile supports on the road, and provides excellent autonomous driving situation recognition/determination results by converging transportation entities information collected from various monitoring sensors such as 60GHz radar and EO/IR based on artificial intelligence. By installing such a radar-enabled AI convergence transportation entities detection system on an autonomous road, it is possible to increase driving efficiency and ensure safety in adverse weather. To secure competitive technologies in the global market, the development of four key technologies such as ① AI-enabled transportation situation recognition/determination algorithm, ② 60GHz radar development technology, ③ multi-sensor data convergence technology, and ④ AI data framework technology is required.

• 디지털융복합연구
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• 제13권8호
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• pp.245-251
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• 2015

디지털 사이니지 시스템이 윈도우 OS에 장착 된 PC에서 작동 될 경우, 구현 가격이 매우 높다. 이러한 문제점을 해소하고자, 최신 스마트폰에 활용되는 ARM Coretex계열의 멀티코어 프로세서가 탑재된 안드로이드 OS 플랫폼 기반의 저전력 저가격의 디지털 사이니지 시스템과, 원격제어기술을 응용하여 어디서나 광고단말기를 원격제어하고 원격콘텐츠를 관리할 수 있는 융복합형 웹서버 기반의 원격 콘텐츠 관리용 서버프로그램을 개발하였다. 구현된 시스템은 디스플레이를 포함한 일체화된 디지털 사이니지 시스템으로, 저전력 모바일 플랫폼을 최적화한 하드웨어 인터페이스로 설계 구현되었고, 상황정보센서를 이용하여 조도, 온도, 날씨, GPS등의 주변상황 정보를 습득한 서비스 융합형 모델을 구현하는 구조로 설계 구현되었다. 또한 콘텐츠 자동생성 모듈은 컨텐츠 사용자에게 전용 저작 도구와 SMIL 기반의 자동으로 가동되도록 프레임 워크에 의해 규정된 컨텐츠를 제공하고, 사용자 정보 데이터베이스에 저장된 사용자 정보를 참조하여 사용자별 맞춤형 SMIL 컨텐츠를 생성해주는 융복합형 기능이 구현되었다. 개발된 디지털 사이니지 시스템은 기존 윈도우 OS 환경 대비 50% 이상의 소비전력 저감과 16포인트 멀티터치 기능을 구현하였고 상용화를 위한 기본 환경시험성능을 모두 만족하였다.

• ETRI Journal
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• 제31권4호
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• pp.365-375
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• 2009

In this paper, a terrestrial digital multimedia broadcasting (T-DMB) multichannel audio broadcasting system based on spatial audio coding is presented. The proposed system provides realistic multichannel audio service via T-DMB with a small increase of data rate as well as backward compatibility with the conventional stereo-based T-DMB player. To reduce the data rate for additional multichannel audio signals, we compress the multichannel audio signals using the sound source location cue coding algorithm, which is an efficient parametric multichannel audio compression technique. For compatibility, we use the dependent property of an elementary stream descriptor, and this property should be ignored in a conventional T-DMB player. To verify the feasibility of the proposed system, we implement the T-DMB multichannel audio encoder and a prototype player. We perform a compatibility test using the T-DMB multichannel audio encoder and conventional T-DMB players. The test demonstrates that the proposed system is compatible with a conventional T-DMB player and that it can provide a promisingly rich audio service.

• 한국전기전자재료학회논문지
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• 제25권5호
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• pp.403-408
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• 2012

In this paper, we propose useful load flow algorithms called FEDL (fast enhanced decoupled load flow). The proposed load flow method can improve the convergence characteristics particularly when the P-Q coupling becomes significant and the power system operating states deviate from the conditions required for stable convergence of the FDL by reflecting in part the effects of the off-diagonal terms in the Jacobian. In our test with IEEE AEP-30 bus system and RTS-96 73-bus system, it converge even when the fast decoupled load flow (FDL) and its variations keeping load flow matrices constant experience convergence problems. Test results show promising performances of the proposed algorithms in their convergence characteristics both in number of iterations and overall convergence speeds.

• Nonlinear Functional Analysis and Applications
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• 제28권1호
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• pp.265-286
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• 2023

In this paper, we introduce and study a generalized Cayley operator associated to H(·, ·)-monotone operator in semi-inner product spaces. Using the notion of graph convergence, we give the equivalence result between graph convergence and convergence of generalized Cayley operator for the H(·, ·)-monotone operator without using the convergence of the associated resolvent operator. To support our claim, we construct a numerical example. As an application, we consider a system of generalized Cayley inclusions involving H(·, ·)-monotone operators and give the existence and uniqueness of the solution for this system. Finally, we propose a perturbed iterative algorithm for finding the approximate solution and discuss the convergence of iterative sequences generated by the perturbed iterative algorithm.

• 한국산업융합학회 논문집
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• 제25권4_2호
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• pp.655-662
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• 2022

Recently, with the increase in the use of UAV(unmanned aerial vehicles), research on horizontal maintenance stations that can take off and land in various environments has been actively conducted. These stations can safely land UAV through multiple DOF(degrees of freedom) or at least 2-DOF-based actuator actuation. Among them, many researchers are dealing with the multi-DOF stewart platform due to its high safety. However, the stewart platform requires high-precision control technology because it requires a lot of torque to actuate according to the load action. Therefore, in this paper, to solve the mentioned problem, a bevel gear-based 2-DOF horizontal maintenance station system is proposed. The proposed system is configured to prevent damage due to air resistance when maintaining ships and to install it in a small space. Also, in terms of system configuration, the bevel gear-based horizontal maintenance system has the main advantage of being able to take off and land UAVs of various sizes through the replacement of station pads. The driving of the system consists of a simple form that can control the motor by adjusting the rotation speed of the motor according to the sea waveform.

• 전기학회논문지
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• 제67권2호
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• pp.301-307
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• 2018

Unmanned Aerial Vehicles (i.e., drone) are gaining a lot of interest from a wide range of application domains such as infrastructure monitoring and parcel delivery service. In those service scenarios, multiple UAVs are involved and should be reliably operated by so-called UAV management system. For that, we propose oneM2M standard based UAV management and control system which is specifically targeted at traffic management of low-altitude UAVs. In this paper, we include oneM2M platform architecture and its implementation for UAV management system in conjunction with UAV interworking procedure.

• 스마트미디어저널
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• 제9권3호
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• pp.80-89
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• 2020

Out - of - distribution (OOD) samples are frequently encountered when deploying a classification model in plenty of real-world machine learning-based applications. Those samples are normally sampling far away from the training distribution, but many classifiers still assign them high reliability to belong to one of the training categories. In this study, we address the problem of removing OOD examples by estimating marginal density estimation using variational autoencoder (VAE). We also investigate other proper methods, such as temperature scaling, Gaussian discrimination analysis, and label smoothing. We use Chonnam National University (CNU) weeds dataset as the in - distribution dataset and CIFAR-10, CalTeach as the OOD datasets. Quantitative results show that the proposed framework can reject the OOD test samples with a suitable threshold.