• 한국측량학회지
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• 제26권5호
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• pp.493-504
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• 2008

SBAS(Space-Based Augmentation System)는 광역보정항법시스템(WADGPS, Wide Area DGPS)으로써 지역 보정항법시스템(LADGPS, Local Area DGPS)의 단점을 보완한 위성항법 보정시스템이다. 이 연구에서는 GPS 측위의 대표적인 방법인 실시간 이동측위(RTK; Real-Time Kinematic), DGPS(Differential GPS) 측위, 단독측위(Standalone)와 SBAS 이동측위를 실시하고 그에 따른 측위 정확도 비교를 통해 SBAS 이동측위의 성능을 분석하였다. 정지측위 결과 산출한 좌표를 참값으로 간주하였고, 각각의 측위방법으로 획득한 관측데이터를 참값과 비교하여 계산한 2차원 평균제곱근(RMS: Root Mean Square)오차와 3차원 RMS 오차를 정확도 비교의 지표로 사용하였다. 그 결과, 각 측위방법에 따른 3차원 RMS 오차는 RTK 측위 13.1cm, DGPS 측위 126.0cm, 이중주파수 단독측위 135.7cm, 단일주파수 단독측위 428.9cm, 그리고 SBAS 측위 109.2cm로 나타났다. 이를 통해 SBAS 측위의 정확도가 DGPS 측위 정확도와 대등한 수준임을 확인할 수 있었다.

• 한국항공우주학회지
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• 제41권9호
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• pp.689-699
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• 2013

전리층 폭풍 시 발생할 수 있는 극심한 전리층 이상현상은 GNSS 보강시스템 사용자의 안전을 위협하는 대표적인 요인이므로 전리층 위협모델을 기반으로 한 지상 모니터링을 통해 적시에 감지 및 경보가 이루어 져야한다. GNSS 관측 데이터를 기반으로 전리층 분석을 수행하고 그 결과로 위협모델을 개발하기 때문에 각 관측소의 데이터 품질은 시스템 성능에 큰 영향을 미칠 수 있다. 전 세계적으로 GNSS 상시관측소 수가 많이 증가함에 따라 품질이 떨어지는 데이터를 산출하는 관측소 또한 증가하였다. 본 연구에서는 GNSS 데이터 품질평가 기법 이용하여 국내 GPS 상시관측소 데이터의 품질을 비교하고 품질이 떨어지는 데이터가 전리층 지연오차 및 기울기 추정치에 미치는 영향을 분석하였다. 품질평가 결과 국내 상시관측소간 데이터 품질에 큰 차이를 보였고 이 품질은 일정기간 유지된다는 것을 확인하였다. 본 연구에서 분석한 결과를 바탕으로 전리층 위협모델 개발을 위한 GNSS 데이터 품질 기준을 제시할 수 있다.

• 한국환경과학회지
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• 제14권11호
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• pp.995-1004
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• 2005

As a research establish reservoir safety operation for small dam systems. This study presents hydrologic analysis conducted in the Duckdong and Bomun dam watershed based on various rainfall data and increase inflow. Especially the Duckdong dam without flood control feature are widely exposed to the risk of flooding, thus it is constructed emergency gate at present. In this study reservoir routing program was simulation for basin runoff estimating using HEC-HMS model, the model simulation the reservoir condition of emergency Sate with and without. At the reservoir analysis results is the Duckdong dam average storage decrease $20\%$ with emergency gate than without emergency gate. Also, the Bomun dam is not affected by the Duckdong flood control augmentation.

• 한국항공운항학회지
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• 제15권2호
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• pp.18-24
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• 2007

The high ionospheric spatial gradient during ionospheric storm is the most concern when applying GNSS(Global Navigation Satellite System) augmentation systems for aircraft precision approach. Since the ionospheric gradient level depends on geographical location as well as the storm, understanding the ionospheric gradient statistics over a specific regional area is necessary for operating the augmentation systems. This paper compares three ionosphere gradient computation methods, direct differentiation between two receivers' ionospheric delay signal for a common satellite, derivation from a grid ionosphere map, and derivation from a plate ionosphere map. The plate map method provides a good indication on the gradient variation behavior over a regional area with limited number of GNSS receivers. The residual analysis for the ionosphere storm detection is discussed as well.

• 설비공학논문집
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• 제6권4호
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• pp.427-438
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• 1994

This experimental study was earned out to examine the heat transfer characteristics of a 2-dimensional impinging air jet on a flat plate with a set of square rods. The objectives of the study were to investigate the flow and heat transfer characteristics caused by the square rods and to find out the optimum rods arrangement. Experiment was carried out first without using the rods to establish the baseline heat transfer performance. Then, rods of different widths and clearances were installed to cause the turbulence on the fluid flow.

• 한국CDE학회논문집
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• 제12권3호
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• pp.171-181
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• 2007

Ubiquitous computing is a vision of our future computing lifestyle in which computer systems seamlessly integrate into our everyday lives, providing services and information in anywhere and anytime fashion. Augmented reality (AR) can naturally complement ubiquitous computing by providing an intuitive and collaborative visualization and simulation interface to a three-dimensional information space embedded within physical reality. This paper presents a service framework and its applications for providing context-aware u-car maintenance services using augmented reality, which can support a rich set of ubiquitous services and collaboration. It realizes bi-augmentation between physical and virtual spaces using augmented reality. It also offers a context processing module to acquire, interpret and disseminate context information. In particular, the context processing module considers user's preferences and security profile for providing private and customer-oriented services. The prototype system has been implemented to support 3D animation, TTS (Text-to-Speech), augmented manual, annotation, and pre- and post-augmentation services in ubiquitous car service environments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1916-1917
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• 2007

Aortic AIx(augmentation index) has been used to measure aortic stiffness and evaluate ventricular load quantitatively. Algorithm for the detection of augmentation point gradually increases the differential order to detect inflection point rather than detects the distinctive point that appears after a specific time. Developed algorithm for AIx is proved to provide more accurate results than the ones developed by previous studies with the deviation from $-11.5{\pm}14.34$ points to $-3.75{\pm}1.26$ points. Results could provide the basis for the measurement of aortic stiffness using easily-measurable radial artery pulse waves, and could be extended to develop a system for early diagnosis of various vascular diseases.

• 한국가시화정보학회지
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• 제19권1호
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• pp.68-73
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• 2021

In this study, the detection of rubber o-ring defects was carried out using k-fold cross validation and Support Vector Machine (SVM) algorithm. The data process was carried out in 3 steps. First, we proceeded with a frame alignment to eliminate unnecessary regions in the learning and secondly, we applied gray-scale changes for computational reduction. Finally, data processing was carried out using image augmentation to prevent data overfitting. After processing data, SVM algorithm was used to obtain normal and defect detection accuracy. In addition, we applied the SVM algorithm through the k-fold cross validation method to compare the classification accuracy. As a result, we obtain results that show better performance by applying the k-fold cross validation method.

• Journal of Multimedia Information System
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• 제8권4호
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• pp.211-220
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• 2021

The process of inspecting SMDs on the PCB boards improves the product quality, performance and reduces frequent issues in this field. However, undesirable scenarios such as assembly failure and device breakdown can occur sometime during the assembly process and result in costly losses and time-consuming. The detection of these components with a model based on deep learning may be effective to reduce some errors during the inspection in the manufacturing process. In this paper, YOLO models were used due to their high speed and good accuracy in classification and target detection. A SMD detection and classification method using YOLO networks based on robust data preprocessing and augmentation techniques to deal with various types of variation such as illumination and geometric changes is proposed. For 9 different components of data provided from a PCB manufacturer company, the experiment results show that YOLOv4 is better with fast detection and classification than YOLOv3.

• Journal of Multimedia Information System
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• 제8권1호
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• pp.31-34
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• 2021

The classical HMM is defined by a parameter triple �� = (��, A, B), where each parameter represents a collection of probability distributions: initial state, state transition and output distributions in order. This paper proposes a new stationary parameter e = (e1, e2, …, eN) where N is the number of states and et = P(|xt = i, y) for describing how an input pattern y ends in state xt = i at time t followed by nothing. It is often said that all is well that ends well. We argue here that all should end well. The paper sets the framework for the theory and presents an efficient inference and training algorithms based on dynamic programming and expectation-maximization. The proposed model is applicable to analyzing any sequential data with two or more finite segmental patterns are concatenated, each forming a context to its neighbors. Experiments on online Hangul handwriting characters have proven the effect of the proposed augmentation in terms of highly intuitive segmentation as well as recognition performance and 13.2% error rate reduction.