• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.152-152
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• 2019

This study demonstrates a novel approach of remotely sensed estimates of stream flow at fifteen hydrological station in the Han River Basin, Korea. Multi-temporal data of the European Space Agency's Sentinel-1 SAR satellite from 19 January, 2015 to 25 August, 2018 is used to develop and validate the flow estimation model for each station. The flow estimation model is based on a power law relationship established between the remotely sensed surface area of water at a selected reach of the stream and the observed discharge. The satellite images were pre-processed for thermal noise, radiometric, speckle and terrain correction. The difference in SAR image brightness caused by the differences in SAR satellite look angle and atmospheric condition are corrected using the histogram matching technique. Selective area filtering is applied to identify the extent of the selected stream reach where the change in water surface area is highly sensitive to the change in stream discharge. Following this, an iterative procedure called the Optimum Threshold Classification Algorithm (OTC) is applied to the multi-temporal selective areas to extract a series of water surface areas. It is observed that the extracted water surface area and the stream discharge are related by the power law equation. A strong correlation coefficient ranging from 0.68 to 0.98 (mean=0.89) was observed for thirteen hydrological stations, while at two stations the relationship was highly affected by the hydraulic structures such as dam. It is further identified that the availability of remotely sensed data for a range of discharge conditions and the geometric properties of the selected stream reach such as the stream width and side slope influence the accuracy of the flow estimation model.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.381-381
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• 2018

우리나라에서는 지속적인 자연재해로 각기 다른 필요성과 목적에 따라 다양한 형태의 홍수 침수 관련 지도가 작성되어 왔다. 연구 성과로 작성된 계획 빈도 및 상위 2개 빈도의 호우피해예상도를 실측 강우와 연계하여 재난관리단계별 대응단계에 활용하기 위해 실시간 피해위험구역을 표출하고자 한다. 본 연구는 실시간으로 피해위험구역을 표출하기 위해 실측 강우와 연계된 호우피해예상도에 공간 보간 알고리즘을 적용하고자 한다. 호우피해예상도란 돌발호우나 태풍으로 인하여 홍수가 발생하면 인명 및 재산피해를 최소화하기 위해 홍수지역을 미리 예측 가능하도록 제작된 지도이다. 지형자료(DEM), 하천 중심선(Stream Centerline), 하천 횡단면(Cross-Section Line), 제방고(Bank), 수문기상 자료(Hydrological Data), 조도계수(Roughness) 등을 사용하여 하천법 제 21조와 하천법시행령 제 17조를 근거로 작성된다. 본 연구에서는 호우피해예상도에 IDW(Inverse Distance Weighted, 역거리가중법) 보간, TIN(Triangulated Irregular Network system, 불규칙삼각망) 보간, Kriging 보간 방법 적용 알고리즘을 제시하고자 하였다. 호우피해예상도에 보간 알고리즘을 적용하기 위해 보간 방법에 따른 적용사례를 분석하였으며 그 결과, 보간 알고리즘을 적용한 호우피해예상도 보간을 통하여 계획빈도 및 상위 2개 빈도 이외의 빈도(하위빈도-계획빈도, 계획빈도-상위빈도 구간)에 대한 호우피해예상도의 피해위험구역 구현 방안을 제시하였다. 호우피해예상도에 IDW, TIN, Kriging 보간 알고리즘을 적용하여 계획빈도 및 상위빈도 이외의 빈도에 대한 피해위험구역을 표출 할 수 있다. 표출된 계획빈도 및 상위빈도 이외의 빈도를 지점확률강우량-빈도에 대한 Matching table을 통하여 실측 강우와 연계 가능하다. 본 연구 결과는 추후 풍수해피해예측시스템에 활용하여 재난관리단계별 예방 및 대응 단계에 활용 할 수 있을 것으로 판단된다.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.187-194
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• 2008

Because the types and severities of most engine faults are various and complex, it is not easy that the conventional model based fault detection approach like the GPA(Gas Path Analysis) method can monitor all engine fault conditions. Therefore this study proposed newly a diagnostic algorithm for isolating and diagnosing effectively the faulted components of the smart UAV propulsion system, which has been developed by KARI(Korea Aerospace Research Institute), using the fuzzy logic and the neural network algorithms. A precise performance model should be needed to perform the model-based diagnostics. The based engine performance model was developed using SIMULINK. For the work and mass flow matching between components of the steady-state simulation, the state-flow library was applied. The proposed steady-state performance model can simulate off-design point performance at various flight conditions and part loads, and in order to evaluate the steady-state performance model their simulation results were compared with manufacturer's performance deck data. According to comparison results, it was confirm that the steady-state model well agreed with the deck data within 3% in all flight envelop. The diagnosis procedure of the proposed diagnostic system has the following steps. Firstly after obtaining database of fault patterns through performance simulation, then secondly the diagnostic system was trained by the FFBP networks. Thirdly after analyzing the trend of the measuring parameters due to fault patterns, then fourthly faulted components were isolated using the fuzzy logic. Finally magnitudes of the detected faults were obtained by the trained neural networks. Because the detected faults have almost same as degradation values of the implanted fault pattern, it was confirmed that the proposed diagnostic system can detect well the engine faults.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.729-738
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• 2019

Recently, we aim to improve the quality of virtual reality contents based on quantitative analysis results of emotions through combination of emotional recognition field and virtual reality field. Emotions are analyzed based on the participant's vital signs. Much research has been done in terms of signal analysis, but the methodology for quantifying emotions has not been fully discussed. In this paper, we propose a normalization function design and expression method to quantify the emotion between various bio - signals. Use the Brute force algorithm to find the optimal parameters of the normalization function and improve the confidence score of the parameters found using the true and false scores defined in this paper. As a result, it is possible to automate the parameter determination of the bio-signal normalization function depending on the experience, and the emotion can be analyzed quantitatively based on this.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.3
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• pp.25-30
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• 2019

Magnetic sensors have the disadvantage that their vector values differ depending on the direction. In this paper, we propose a magnetic vector calibration method for geomagnetic-based indoor localization estimates. The fingerprinting technique used in geomagnetic-based indoor localization the position by matching the magnetic field map and the magnetic sensor value. However, since the moving direction of the current user may be different from the moving direction of the person who creates the magnetic field map at the collection time, the sampled magnetic vector may have different values from the vector values recorded in the field map. This may substantially lower the positioning accuracy. To avoid this problem, the existing studies use only the magnitude of magnetic vector, but this reduces the uniqueness of the fingerprint, which may also degrade the positioning accuracy. In this paper we propose a vector calibration algorithm which can adjust the sampled magnetic vector values to the vector direction of the magnetic field map by using the parametric equation of a circle. This can minimize the inaccuracy caused by the direction mismatch.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.53-60
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• 2021

LOD-based recommender systems usually leverage the data available within LOD datasets, such as DBpedia, in order to recommend items(movies, books, music) to the end users. These systems use a semantic similarity algorithm that calculates the degree of matching between pairs of Linked Data resources. In this paper, we proposed a new approach to measuring semantic distance in an LOD-based recommender system by assigning weights converted from user ratings to links in the LOD graph. The semantic distance measurement model proposed in this paper is based on a processing step in which a graph is personalized to a user through weight calculation and a method of applying these weights to LDSD. The Experimental results showed that the proposed method showed higher accuracy compared to other similar methods, and it contributed to the improvement of similarity by expanding the range of semantic distance measurement of the recommender system. As future work, we aim to analyze the impact on the model using different methods of LOD-based similarity measurement.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.273-284
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• 2018

Purpose: Conventional headland turning typically requires repeated forward and backward movements to move the farming equipment to the next row. This research focuses on developing an upland agricultural robot with an optimized headland turning mechanism that enables a $180^{\circ}$ turning positioning to the next row in one steering motion designed for a two-wheel steering, four-wheel drive agricultural robot named the HADA-bot. The proposed steering mechanism allows for faster turnings at each headland compared to those of the conventional steering system. Methods: The HADA-bot was designed with 1.7-m wide wheel tracks to travel along the furrows of a garlic bed, and a look-ahead path following algorithm was applied using a real-time kinematic global positioning system signal. Pivot turning tests focused primarily on accuracy regarding the turning radius for the next path matching, saving headland turning time, area, and effort. Results: Several test cases were performed by evaluating right and left turns on two different surfaces: concrete and soil, at three speeds: 1, 2, and 3 km/h. From the left and right side pivot turning results, the percentage of lateral deviation is within the acceptable range of 10% even on the soil surface. This U-turn scheme reduces 67% and 54% of the headland turning time, and 36% and 32% of the required headland area compared to a 50 hp tractor (ISEKI, TA5240, Ehime, Japan) and a riding-type cultivator (CFM-1200, Asia Technology, Deagu, Rep. Korea), respectively. Conclusion: The pivot turning trajectory on both soil and concrete surfaces achieved similar results within the typical operating speed range. Overall, these results prove that the pivot turning mechanism is suitable for improving conventional headland turning by reducing both turning radius and turning time.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.32-40
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• 2019

Indoor location estimation studies are needed in various fields. The method of estimating the indoor position can be divided into a method using hardware and a method using no hardware. The use of hardware is more accurate, but has the disadvantage of hardware installation costs. Conversely, the non-hardware method is not costly, but it is less accurate. To estimate the location for AR game, you need to get the solution of the Perspective-N-Point (PnP). To obtain the PnP problem, we need three-dimensional coordinates of the space in which we want to estimate the position and images taken in that space. The position can be estimated through six pairs of two-dimensional coordinates matching the three-dimensional coordinates. To further increase the accuracy of the solution, we proposed the use of an additional non-coplanarity degree to determine which points would increase accuracy. As the non-coplanarity degree increases, the accuracy of the position estimation becomes higher. The advantage of the proposed method is that it can be applied to all existing location estimation methods and that it has higher accuracy than hardware estimation.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.57-64
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• 2021

The domestic semiconductor industry can produce various products that will satisfy customer needs by diversifying assembly parts and increasing compatibility between them. It is necessary to improve the production line as a method to reduce the work-in-process inventory (WIP) in the assembly line, the idle time of the worker, and the idle time of the process. The improvement of the production line is to balance the capabilities of each process as a whole, and to determine the timing of product input or the order of the work process so that the time required between each process is balanced. The purpose of this study is to find the optimal WIP and buffer size through SA (Simulated Annealing) that minimizes lead time while matching the number of two parts in a parallel assembly line with bottleneck process. The WIP level and buffer size obtained by the SA algorithm were applied to the CONWIP and DBR systems, which are the existing production systems, and the simulation was performed by applying them to the new hybrid production system. Here, the Hybrid method is a combination of CONWIP and DBR methods, and it is a production system created by setting new rules. As a result of the Simulation, the result values were derived based on three criteria: lead time, production volume, and work-in-process inventory. Finally, the effect of the hybrid production method was verified through comparative analysis of the result values.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.2
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• pp.29-40
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• 2007

The purpose of this research is to propose a method for scoring the quality of a fingerprint image using the local information derived from the fingerprint image. In previous works for the quality measuring, most of the quality scores are related to the performance of a matching algorithm, and this makes the quality result more subjective. The quality score of a fingerprint image proposed in this work is sensor-independent, source-independent and matcher-independent one, and this concept of fingerprint sample quality results in effective improvement of the system performance. In this research, a new definition of fingerprint image quality and a new method for measuring the quality are proposed. For the experiments, several sub-databases from FVCs are used and the proposed method showed reasonable results for the test database. The proposed method can be used in various systems for the numerous purposes since the quality scores generated by the proposed method are based on the idea that the quality of fingerprint should be sensor-independent, source-independent and matcher-independent.