• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.17 no.2
• /
• pp.71-76
• /
• 1981

In order to make a numerical modeling for the one dimensional unsteady flow which expressed by Saint Venant partial differential equations, Preissmann's implicit scheme was used, and it's stability and accuracy was mentioned. By introducing recurrence relations make it possible to use double sweep algorithm. Effective parameters to the result were the values of the $\Delta$t/$\Delta$x, $\theta$ and the chezy coefficient. In oder to get numerical solutions with enough accuracy, $\Delta$t/$\Delta$x should not be far from the value of 1, and the criteria of the $\theta$ was 0.6<$\theta$<1.0 for the stability without condition. This model should be calibrated by real field data, and expected to be developed for the simulation of the river system and to the long wave analysis for one dimensional coastal zone problem.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.5
• /
• pp.649-654
• /
• 2005

In this paper, we describe an implementation of real-time face recognition system under ubiquitous computing environments. First, face image is captured by PDA with CMOS camera and then this image with user n and name is transmitted via WLAN(Wireless LAN) to the server and finally PDA receives verification result from the server The proposed system consists of server and client parts. Server uses PCA and LDA algorithm which calculates eigenvector and eigenvalue matrices using the face images from the PDA at enrollment process. And then, it sends recognition result using Euclidean distance at verification process. Here, captured image is first compressed by the wave- let transform and sent as JPG format for real-time processing. Implemented system makes an improvement of the speed and performance by comparing Euclidean distance with previously calculated eigenvector and eignevalue matrices in the learning process.

• Korean Journal of Remote Sensing
• /
• v.13 no.2
• /
• pp.151-163
• /
• 1997

In this paper, an algorithm for retrieving soil moisture from measurement of microwave reflection at the end of a coaxial canble is presented. Because the wave reflection from the boundary between air and soil layers depends on the dielectric constant of the soil layer, the dielectric constant can be obtained from measured reflection coefficient. At first, an equivalent circuit for the coaxial probe contaced on the soil surface was chosen with two unknown circuit elements. Then, the unknown circuit elements are obtained experrmentally by measuring the reflection constants of 20 soil samples, and consequently, an empirical formula for computing the dielectric constant from the reflection coefficient is obtained. The dielectric constant is mainly influenced by the soil moisture, and the soil moisture can be computed from the dielecfic constant using an existing empirical formula. HP Network Analyzer 8510C was used to measure the magnitude and the phase of the reflection coeffcient at 4.65 GHz, and the measured data set were used to obtain an empirical formula for computing the dielectric constant. The empirical formula obtained in this study was proven by other soil samples.

• Journal of Advanced Navigation Technology
• /
• v.23 no.5
• /
• pp.380-385
• /
• 2019

This paper is concerned with departure passengers' dwell time analysis using real system data. Previous researches emphasize the importance of dwell time analysis from perspective of airport terminal planning and non-aeronautical revenue. However, short-term airport operation using passengers' dwell time is considered impossible due to absence of passengers' behavior data. Recently, in accordance with the wave of smart airport, world leading airports are systematically collecting passenger data. So there is high possibility of analyzing passengers' dwell time with the data stacked in the airport database. We conducted dwell time analysis using data from Incheon Int'l airport. In order to handle passenger data, we adapted clustering algorithm which is one of data mining techniques. As a clustering result, passengers are divided into 3 clusters. One is the cluster for passengers whose dwell time is relatively short and who tend to spend longer time in the airside. Another is the cluster for passengers who have near 3 hours dwell time. The other is the cluster for passengers whose total dwell time is extremely long.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.281-281
• /
• 2019

수리모형실험은 수로 내에서 장시간 파랑을 발생시킬 경우, 수로 내에 반사 파랑의 성분이 누적될 수 있어 상당한 계측 오차를 발생시킬 우려가 있어 수리모형실험 결과의 검증이 필요하다. 일반적으로 수리모형실험 결과의 검증을 위해서는 동일 실험을 무수히 반복하여 불확실성을 제거하거나 다양한 수리실험실에서 수리모형실험을 수행하고 결과를 분석하여 불확실성을 제거할 수 있다. 그러나 이는 엄청난 시간과 노력은 물론 막대한 실험비용이 소요되기 때문에 경제적으로 효용성이 매우 낮아 현실적으로 수행이 어렵다. 이에 비해 수치모형실험은 상대적으로 저렴한 비용으로 수행할 수 있으며, 다수의 실험을 수행하지 않아도 불확실성을 제거할 수 있어 수리모형실험의 검증에 효율적이다. 일반적으로 난류 거동을 동반하는 복잡한 구조물 주변의 흐름 해석에는 3차원 CFD 모형이 필요하다. 특히, 병렬연산이 가능한 CFD 모형을 활용하면 수리모형실험에서도 재현이 쉽지 않은 다양한 조건에 따른 복잡한 흐름을 해석할 수 있어 효용성이 점점 증가하고 있다. 그러나 복잡한 구조물이 존재하게 되면 구조물에 재현에 막대한 격자구조가 필요하여 현실적으로 적용이 쉽지 않다. 이에 대한 대안으로 복잡한 구조물을 비교적 큰 격자에서 재현할 수 있는 가상경계법을 활용하는 연구가 활발히 진행되고 있다. 가상경계법은 Navier-Stokes 방정식에서 유체 내에 존재하는 고체를 모멘텀 이론으로 대체하여 고려하는 기법으로 수치모델링 수행 시 매질을 유체만으로 구성할 수 있어 안정적으로 적용할 수 있는 것으로 알려져 있다. 본 과업에서는 다양한 분야에서 널리 활용되고 있는 3차원 CFD 모형인 OpenFOAM®기반으로 파랑해석에 필요한 경계조건을 계산할 수 있는 olaFlow를 활용하여 복잡한 구조물을 지나는 파랑해석을 수행하기 위해 가상경계법을 olaFlow에 도입한 수치 알고리즘을 개발하였다. 개발한 수치알고리즘을 활용하여 복잡한 구조를 수치모델에서 재현하였으며, 수치모델에 적용된 수치 알고리즘의 안정성에 대해 고찰하였다.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_3
• /
• pp.1349-1359
• /
• 2021

Acquisition of precise position and velocity information of GNSS-INS (Global Navigation Satellite System; Inertial Navigation System) sensors in obtaining SAR SLC (Single Look Complex) images from raw data using BPA (Backprojection Algorithm) was regarded decisive. Several studies on BPA were accompanied by Kalman Filter for sensor noise oppression, but often implemented once where insufficient information was given to determine whether the filtering was effectively applied. Multiple operation of Kalman Filter on GNSS-INS sensor was presented in order to assess the effective order of sensor noise calibration. FMCW (Frequency Modulated Continuous Wave)-SAR raw data was collected from twice airborne experiments whose GNSS-INS information was practically and repeatedly filtered via Kalman Filter. It was driven that the FMCW-SAR raw data with diverse path information could derive different order of Kalman Filter with optimum operation of BPA image restoration.

• Journal of Platform Technology
• /
• v.9 no.1
• /
• pp.32-39
• /
• 2021

Existing environmental measuring devices mainly focus on electromagnetic wave and eco-friendly product certification and durability test, and sensor reliability verification and verification of measurement data are conducted mainly through sensor performance evaluation through type approval and registration, acceptance test, initial calibration, and periodic test. This platform has established an ICT-based environmental monitoring sensor reliability verification system that supports not only performance evaluation for each target sensor, but also a verification system for sensor data reliability. A sensor board to collect sensor data for environmental information was produced, and a sensor and data reliability evaluation and verification service system was standardized. In addition, to evaluate and verify the reliability of sensor data based on ICT, a sensor data platform monitoring prototype using LoRa communication was produced, and the test was conducted in smart cities. To analyze the data received through the system, an optimization algorithm was developed using machine learning. Through this, a sensor big data analysis system is established for reliability verification, and the foundation for an integrated evaluation and verification system is provide.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.10
• /
• pp.1341-1347
• /
• 2020

Legacy studies for classifying arrhythmia have been studied in order to improve the accuracy of classification, Neural Network, Fuzzy, Machine Learning, etc. In particular, deep learning is most frequently used for arrhythmia classification using error backpropagation algorithm by solving the limit of hidden layer number, which is a problem of neural network. In order to apply a deep learning model to an ECG signal, it is necessary to select an optimal model and parameters. In this paper, we propose parameter extraction based on AR and arrhythmia classification through a deep learning. For this purpose, the R-wave is detected in the ECG signal from which noise has been removed, QRS and RR interval is modelled. And then, the weights were learned by supervised learning method through deep learning and the model was evaluated by the verification data. The classification rate of PVC is evaluated through MIT-BIH arrhythmia database. The achieved scores indicate arrhythmia classification rate of over 97%.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.34 no.2
• /
• pp.136-141
• /
• 2021

Heating cables, widely used in office buildings, factories, streets and railways, deteriorate in electrical insulation during operation. The insulation deterioration of heating cables leads to electric discharges that can cause electrical fires. With this background, this paper dealt with a condition monitoring technique for heating cables by the analysis of discharge signals to prevent electrical fires. Insulation deterioration was simulated using an arc generator specified in UL1699 under AC operation, and the characteristic and propagation of discharge signals were analyzed on a 100 meter-long heating cable. Discharge signals produced by insulation deterioration were detected as a voltage pulse because they are as small as a few mV and they are attenuated through propagation path. The frequency spectrum of discharge signals mainly existed in the range from 70 kHz to 110 kHz, and the maximum attenuation of the signal was 84.8% at 100 meters away from the discharge point. Based on the experimental results, a monitoring device, which is composed of a high pass filter with the cut-off frequency of 70 kHz, a comparator, a wave shaper and a microprocessor, was designed and fabricated. Also, an algorithm was designed to discriminate the discharge signal in the presence of noise, compared with the pulse repetition period and the number of pulse counts per 100ms. In the experiment, the result showed that the prototype monitoring device could detect and discriminate the discharge signals produced at every discharge point on a heating cable.

• The Journal of Korean Institute of Information Technology
• /
• v.17 no.6
• /
• pp.103-114
• /
• 2019

Moving-target detection using frequency-modulated continuous-wave (FMCW) radar systems has recently attracted attention. Detection tasks are more challenging with noise resulting from signals reflected from strong static objects or small moving objects(clutter) within radar range. Robust Principal Component Analysis (RPCA) approach for FMCW radar to detect moving objects in noisy environments is employed in this paper. In detail, compensation and calibration are first applied to raw input signals. Then, RPCA via Gradient Descents (RPCA-GD) is adopted to model the low-rank noisy background. A novel update algorithm for RPCA is proposed to reduce the computation cost. Finally, moving-targets are localized using an Automatic Multiscale-based Peak Detection (AMPD) method. All processing steps are based on a sliding window approach. The proposed scheme shows impressive results in both processing time and accuracy in comparison to other RPCA-based approaches on various experimental scenarios.