• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.281-286
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• 2023

This study analyzed the causal relationship between housing sales prices and jeonse prices in Seoul, specifically in the Gangnam and Gangbuk neighborhoods. The time-invariant Granger causality test showed bidirectional causality between the sales price and the jeonse price in Seoul and Gangbuk, but no bidirectional causality was found in Gangnam. However, the time-varying Granger causality test showed a Granger causal relationship between the housing jeonse price and the sales price for the entire period after 1993 in all three areas. Notably, the causal effect of jeonse prices on sales prices has been continuous in Gangnam since 2010. These analysis results suggest that an increase in liquidity supply to the jeonse market could increase volatility throughout the housing market, given the strong influence between the sales and jeonse markets in both directions.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.281-281
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• 2022

바닥에서 생성되는 난류는 순간적으로 강한 모멘텀을 바닥에 전달함과 동시에 바닥에 있는 입자를 움직이게 한다. 경계층 내 난류 운동에 대한 분석은 다양한 유사 이송 문제를 이해하기 위해 필수적이며 이에 따라 많은 선행 연구들은 실험실 실험을 통해 해당 연구를 수행하였다. 본 연구에서는 선행 연구에서 사용하지 못했던 진보된 실험 방법을 활용하여 바닥 경계층 내의 난류 운동에 대해 확인하고 해당 운동에 의해 관성 입자의 움직임이 어떻게 발생하는지에 대하여 물리적으로 설명하고자 한다. 다양한 흐름 조건에서 3가지의 입경 크기를 가지는 모래 입자를 가지고 실험을 수행하였으며, 실험 조건별 고해상도 유속장 및 관성 입자의 움직임은 3차원 입자 영상 유속계 (Particle Image Velocimetry; 이하 PIV)와 입자 추적 유속계 (Particle Tracking Velocimetry; 이하 PTV)를 동시에 적용하여 파악하였다. 취득된 3차원 유속장과 입자 궤적을 기반으로 실험 조건별 흐름 및 입자 거동 특성에 대해 분석하였으며, 관성 입자의 움직임을 발생시키는 3차원 난류 운동은 측정된 유속장에서 산정한 Q-criterion 값을 기반으로 도식화하였다. 측정값 내에는 난류 운동에 대한 정보와 더불어 잡음이 포함되어 있으므로 이를 제거하고자 적합 직교 분해 (Proper Orthogonal Decomposition; 이하 POD) 방법을 적용하였다. 그리고 POD로 추출한 유속장을 통해 바닥면 부근에 존재하는 헤어핀 와류 운동 혹은 와류 묶음과 같은 난류 고유 구조를 파악하였다. 해당 와류 운동들의 3차원 난류 특성을 확인하고자 비등방성 불변 지도(anisotropy invariant map)를 활용하였으며 경계층 내부에서 난류의 형태가 흐름 방향으로 늘어진 럭비공 형태임을 확인하였다. 마지막으로, 입자의 움직임을 발생시키는 난류 이벤트를 결정하고자 사방구 분석 (Quadrant analysis) 기법을 적용하였으며 흐름 조건별로 입자를 움직이게 하는 난류 이벤트는 달라짐을 확인하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.301-307
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• 2024

This study introduces a novel cascade fusion architecture aimed at enhancing thermal images across various scale conditions. The processing of thermal images at multiple scales has been challenging due to the limitations of existing methods that are designed for specific scales. To overcome these limitations, this paper proposes a unified framework that utilizes cascade feature fusion to effectively learn multi-scale representations. Confidence maps from different image scales are fused in a cascaded manner, enabling scale-invariant learning. The architecture comprises end-to-end trained convolutional neural networks to enhance image quality by reinforcing mutual scale dependencies. Experimental results indicate that the proposed technique outperforms existing methods in multi-scale thermal image enhancement. Performance evaluation results are provided, demonstrating consistent improvements in image quality metrics. The cascade fusion design facilitates robust generalization across scales and efficient learning of cross-scale representations.

• The Journal of the Acoustical Society of Korea
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• v.26 no.8
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• pp.375-380
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• 2007

A reverberation chamber should be designed and constructed so as to satisfy its purposes and available space. However, it is somewhat difficult to meet the intended design requirements due to various errors from construction process. So, the post-construction measurement of its volume and surface areas is very essential to check the actual volume and volume uncertainty of a reverberation chamber These values should be carefully calculated and accurately estimated since they are used not only to evaluate the acoustic characteristics of building materials but also to calculate uncertainties for other acoustic characteristics. In this work, the method for the calculation and uncertainty estimation of the volume of a reverberation chamber is presented. To this end, the coordinates of all corners was measured with Total Station after construction. The results showed that the calculated volume of the measured reverberation chamber differs by 5 % from the design specification. The expanded volume uncertainty was also estimated to be about 2 % of the total calculated volume.

• The Journal of the Acoustical Society of Korea
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• v.26 no.8
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• pp.415-425
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• 2007

This paper proposes a method of underwater source localization using the wideband interference patterns matching. By matching two interference patterns in the spectrogram, it is estimated a ratio of the range from source to sensor5, and then this ratio is applied to the Apollonius circle. The Apollonius circle is defined as the locus of all points whose distances from two fixed points are in a constant value so that it is possible to represent the locus of potential source location. The Apollonius circle alone, however still keeps the ambiguity against the correct source location. Therefore another equation is necessary to estimate the unique locus of the source location. By estimating time differences of signal arrivals between source and sensors, the hyperbola equation is used to get the cross point of the two equations, where the point being assumed to be the source position. Simulations are performed to get performances of the proposed algorithm. Also, comparisons with real sea experiment data are made to prove applicability of the algorithm in real environment. The results show that the proposed algorithm successfully estimates the source position within an error bound of 10%.

• The Journal of the Acoustical Society of Korea
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• v.27 no.3
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• pp.154-162
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• 2008

Signals in an underwater channel get distorted by multipath propagation. In this paper, pre-coding method is suggested which helps comprehending the signals with minimum equalization. The signals are transformed based on the knowledge of the impulse response of the channel. Proposed pre-coding method is tested by simulations based on the ray theory and through water tank experiments. In weak multipath environment, in case of an SNR of about 20 dB, BER is $10^{-3}{\sim}10^{-4}$, while in strong multipath environment, similar BER is achieved with SNR of about 30 dB. In order for the pre-coding method to be used for underwater vehicles, channel prediction method utilizing the waveguide invariant is suggested and tested.

• The Journal of the Acoustical Society of Korea
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• v.26 no.8
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• pp.403-408
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• 2007

In a large corpus-based speech synthesizer, a break, which is a parameter influencing the naturalness and intelligibility, is used as an important feature during a unit selection process. Japanese is a language having intonations, which ate indicated by the relative differences in pitch heights and the APs(Accentual Phrases) are placed according to the changes of the accents while a break occurs on a boundary of the APs. Although a break can be predicted by using J-ToBI(Japanese-Tones and Break Indices), which is a rule-based or statistical approach, it is very difficult to predict a break exactly due to the flexibility. Therefore, in this paper, a method is to conduct a unit search by dividing breaks into two types, such as a fixed break and a flexible break, in order to use the advantages of a large-scale corpus, which includes various types of prosodies. As a result of an experiment, the proposed unit selection method contributed itself to enhance the naturalness of synthesized speeches.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.144-159
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• 2014

Techniques for making a single panoramic image using multiple pictures are widely studied in many areas such as computer vision, computer graphics, etc. The panorama image can be applied to various fields like virtual reality, robot vision areas which require wide-angled shots as an useful way to overcome the limitations such as picture-angle, resolutions, and internal informations of an image taken from a single camera. It is so much meaningful in a point that a panoramic image usually provides better immersion feeling than a plain image. Although there are many ways to build a panoramic image, most of them are using the way of extracting feature points and matching points of each images for making a single panoramic image. In addition, those methods use the RANSAC(RANdom SAmple Consensus) algorithm with matching points and the Homography matrix to transform the image. The SURF(Speeded Up Robust Features) algorithm which is used in this paper to extract featuring points uses an image's black and white informations and local spatial informations. The SURF is widely being used since it is very much robust at detecting image's size, view-point changes, and additionally, faster than the SIFT(Scale Invariant Features Transform) algorithm. The SURF has a shortcoming of making an error which results in decreasing the RANSAC algorithm's performance speed when extracting image's feature points. As a result, this may increase the CPU usage occupation rate. The error of detecting matching points may role as a critical reason for disqualifying panoramic image's accuracy and lucidity. In this paper, in order to minimize errors of extracting matching points, we used $3{\times}3$ region's RGB pixel values around the matching points' coordinates to perform intermediate filtering process for removing wrong matching points. We have also presented analysis and evaluation results relating to enhanced working speed for producing a panorama image, CPU usage rate, extracted matching points' decreasing rate and accuracy.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1057-1068
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• 2022

This paper compares the combination performance of feature point-based matching algorithms as a study to confirm the matching possibility between image taken by a user and a virtual texture image with the goal of developing mobile-based real-time image positioning technology. The feature based matching algorithm includes process of extracting features, calculating descriptors, matching features from both images, and finally eliminating mismatched features. At this time, for matching algorithm combination, we combined the process of extracting features and the process of calculating descriptors in the same or different matching algorithm respectively. V-World 3D desktop was used for the virtual indoor texture image. Currently, V-World 3D desktop is reinforced with details such as vertical and horizontal protrusions and dents. In addition, levels with real image textures. Using this, we constructed dataset with virtual indoor texture data as a reference image, and real image shooting at the same location as a target image. After constructing dataset, matching success rate and matching processing time were measured, and based on this, matching algorithm combination was determined for matching real image with virtual image. In this study, based on the characteristics of each matching technique, the matching algorithm was combined and applied to the constructed dataset to confirm the applicability, and performance comparison was also performed when the rotation was additionally considered. As a result of study, it was confirmed that the combination of Scale Invariant Feature Transform (SIFT)'s feature and descriptor detection had the highest matching success rate, but matching processing time was longest. And in the case of Features from Accelerated Segment Test (FAST)'s feature detector and Oriented FAST and Rotated BRIEF (ORB)'s descriptor calculation, the matching success rate was similar to that of SIFT-SIFT combination, while matching processing time was short. Furthermore, in case of FAST-ORB, it was confirmed that the matching performance was superior even when 10° rotation was applied to the dataset. Therefore, it was confirmed that the matching algorithm of FAST-ORB combination could be suitable for matching between virtual texture image and real image.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.