• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.78-78
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• 2021

영상유속분석법은 비접촉식으로 유속을 측정하는 방법으로 특히 홍수시 하천의 표면유속을 안전하게 계측할 수 있어서 경제적이고 안전한 하천유속 측정 방법 중 하나이다. STIV는 영상의 휘도 정보를 시간 방향으로 나열하여 작성된 STI(Space-Time Image)에 나타나는 패턴의 기울기를 이용하여 유속을 산정하는 방법이다. 특히 STIV(Space-Time Image Velocimetry)는 기존 입자군의 상호상관법에 기초한 입자영상유속계와 달리 표식자의 유무와 상관없이 유속을 측정할 수 있어 적용성과 안정성이 확보된다. 하지만 영상의 상태가 불량한 경우 정확한 유속 측정이 난해하며 야간에는 별도의 조명 추가 및 태풍과 같은 악기상에서는 빗방울이 카메라에 맺히거나 수면의 진동, 구조물의 진동에 의한 영상의 상태가 불량하게 되어 측정 정도가 떨어진다. 이처럼 영상을 이용한 유속 계측에 있어 다양한 연구 및 기술개발이 요구되는 시점이다. 따라서 본 연구에서는 영상을 이용한 정확한 유속측정을 위해 STIV와 인공지능을 융합하여 정확한 유속 평가를 목적으로 한다. 우선 기존 STI에 의한 기울기 추정방법을 확장하여 딥러닝(CNN)에 의한 기울기 추정방법을 도입하였다. CNN은 일반적으로 이미지의 특성을 추출하는데 유용한 방법으로서 STI의 2차원 Fourier변환 이미지를 사용하여 패턴의 기울기를 감지하도록 학습하였고 적용 결과 기울기에 대한 인식율은 매우 양호하였으며 이를 이용한 실제 관측 영상에 적용한 결과 유속에 대한 정밀도도 매우 양호하게 나타났다. 또한 딥러닝을 적용한 STIV는 노이즈(진동, 화면 불량 등)가 있는 영상에서도 안정적으로 유속을 산정할 수 있으며 전파유속계를 이용한 실제 하천의 표면유속 관측치와 비교 검토 결과 매우 양호하게 유속을 평가하고 있는 것으로 나타났다.

• Journal of Korea Water Resources Association
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• v.47 no.6
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• pp.537-546
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• 2014

Surface image velocimetry was introduced as an efficient and sage alternative to conventional river flow measurement methods during floods. The conventional surface image velocimetry uses a pair of images to estimate velocity fields using cross-correlation analysis. This method is appropriate to analyzing images taken with a short time interval. It, however, has some drawbacks; it takes a while to analyze images for the verage velocity of long time intervals and is prone to include errors or uncertainties due to flow characteristics and/or image taking conditions. Methods using spatio-temporal images, called STIV, were developed to overcome the drawbacks of conventional surface image velocimetry. The grayscale-gradient tensor method, one of various STIVs, has shown to be effectively reducing the analysis time and is fairly insusceptible to any measurement noise. It, unfortunately, can only be applied to the main flow direction. This means that it can not measure any two-dimensional flow field, e.g. flow in the vicinity of river structures and flow around river bends. The present study aimed to develop a new method of analyzing spatio-temporal images in two-dimension using cross-correlation analysis. Unlike the conventional STIV, the developed method can be used to measure two-dimensional flow substantially. The method also has very high spatial resolution and reduces the analysis time. A verification test using artificial images with lid-driven cavity flow showed that the maximum error of the method is less than 10 % and the average error is less than 5 %. This means that the developed scheme seems to be fairly accurate, even for two-dimensional flow.

• Journal of Korea Water Resources Association
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• v.49 no.6
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• pp.469-480
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• 2016

The present study aims to develop a real-time surface image velocimeter (SIV) using an Android smartphone. It can measure river surface velocity by using its built-in sensors and processors. At first the SIV system figures out the location of the site using the GPS of the phone. It also measures the angles (pitch and roll) of the device by using its orientation sensors to determine the coordinate transform from the real world coordinates to image coordinates. The only parameter to be entered is the height of the phone from the water surface. After setting, the camera of the phone takes a series of images. With the help of OpenCV, and open source computer vision library, we split the frames of the video and analyzed the image frames to get the water surface velocity field. The image processing algorithm, similar to the traditional STIV (Spatio-Temporal Image Velocimeter), was based on a correlation analysis of spatio-temporal images. The SIV system can measure instantaneous velocity field (1 second averaged velocity field) once every 11 seconds. Averaging this instantaneous velocity measurement for sufficient amount of time, we can get an average velocity field. A series of tests performed in an experimental flume showed that the measurement system developed was greatly effective and convenient. The measured results by the system showed a maximum error of 13.9 % and average error less than 10 %, when we compared with the measurements by a traditional propeller velocimeter.

• Journal of Korean Philosophical Society
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• v.116
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• pp.225-256
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• 2010

The two school $M{\bar{a}}dhyamika$ and $Yog{\bar{a}}c{\bar{a}}ra$ act as a representative of $Mah{\bar{a}}y{\bar{a}}na$ Buddhism in India. But the two school disputed with each other insisting ${\acute{s}}{\bar{u}}nyat{\bar{a}}-v{\bar{a}}da$ and $vij{\tilde{n}}aptim{\bar{a}}trav{\bar{a}}da$ separately. To introduce the disputation shortly is as follow. $N{\bar{a}}g{\bar{a}}rjuna$ explained the world and truth by two truth theories(二諦說) which carry out truth of a word and the dimension(spiritual enlightenment) which is absolute(ultimate) to it being lokasaṁvṛtisatya(世俗諦) about the truth which can be expressed verbally, and which is phenomenon-like (everyday) at paramaarthasatya(勝義諦). By the way, lokasaṁvṛtisatya and paramaarthasatya are actually distinction of the recognition which is not an ontological distinction. That is, lokasaṁvṛti(世俗) is paramaartha(勝義) as it is the time of seeing by the eyes of those who have realized. The two truth theories of $N{\bar{a}}g{\bar{a}}rjuna$ was developed logical more precisely by his successors. With an everyday language, the position of Candrakīrti(月稱) that it cannot be expressed as the position of $Bh{\bar{a}}vaviveka$(淸辨) that paramaarthasatya can be expressed logically is opposed to each other, and dissociates by $Sv{\bar{a}}tantrika$(自立論證派) and $P{\bar{a}}rsagika$(歸謬論證派). Confrontation of $Sv{\bar{a}}tantrika$ and $P{\bar{a}}rsagika$ is the dispute about the ability of s which is the highest truth to be proved logically. The $P{\bar{a}}rsaga$ of Candrakirti thinks that people exist truly, and is because it claims not existing in the world where a favorite thing is actually actual. However, $Bh{\bar{a}}vaviveka$ proved Sunyata(空性)을 positively based on the reliance to language and logic. Also the mokṣa of $M{\bar{a}}dhyamika$ is not recovery of original condition of $vij{\tilde{n}}apti$ which is pure in itself as $Yog{\bar{a}}c{\bar{a}}ra$ saying, as well as obtaining a thing which is dravya-sat as $Sarv{\bar{a}}stiv{\bar{a}}din$ saying. The mokṣa of $M{\bar{a}}dhyamika$ means a condition of liberated from karma and pains through extinction of $prapa{\tilde{n}}ca$ and discrimination by realizing the real aspect of all dharma which is said by pratītyasamutpāda, $praj{\tilde{n}}apti$, niḥsvabhāva, ${\acute{s}}{\bar{u}}nya$, $madhyam{\bar{a}}pratipad$.

• Journal of Korean Philosophical Society
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• v.117
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• pp.35-55
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• 2011

This article purports to clarify the doctrinal characteristics of the $Yog{\bar{a}}c{\bar{a}}ra$ school's hermeneutic interpretations of the "theory of the three turns of the Dharma Cakra" in the Saṃdbinirmocana-sūtra through early Indian $Yog{\bar{a}}c{\bar{a}}ra$ treatises such as the $Yog{\bar{a}}c{\bar{a}}rabb{\bar{u}}mi-vy{\bar{a}}kby{\bar{a}}$ and the. $Vy{\bar{a}}khy{\bar{a}}yukti$. It will probe how these interpretations apply co the theory of two truths or that of three natures($trisvabh{\bar{a}}va$) among the main doctrines of the $Yog{\bar{a}}c{\bar{a}}ra$ school. Especially, the peculiar characteristic of the "theory of the three turns of the Dharma Cakra" is such chat the thought of ${\acute{s}}{\bar{u}}nyat{\bar{a}}$ in the lineage of $Praj{\bar{n}}{\bar{a}}p{\bar{a}}ramita-s{\bar{u}}tras$ is regarded as incomplete, as the early school of Madhyamaka represented by $N{\bar{a}}g{\bar{a}}rjuna$ is conceived of as belonging to the second period of turn. Speaking of the further details of the "theory of the three turns of the Dharma Cakra", the $Yog{\bar{a}}c{\bar{a}}ra$ school subdivides the realm of saṃvṛti satya in $N{\bar{a}}g{\bar{a}}rjuna^{\prime}s$ theory of two truths; that is, it divides the saṃvṛti into merely linguistic existence and actual existence, and the thus-created structure of the theory of three natures on the basis of ocher-dependent nature(paratantra-$svabh{\bar{a}}va$) makes it possible to establish the doctrinal system of the thought of ${\acute{s}}{\bar{u}}nyat{\bar{a}}$ that is not subject to "nihilism or ${\acute{s}}{\bar{u}}nyat{\bar{a}}$ attached to evil." In effect, the above hermeneutic interpretation of the "theory of the three turns of the Dharma Cakra" is inherited into the structure of the $abh{\bar{u}}taparikalpa$ in the $Madhy{\bar{a}}nta-vibh{\bar{a}}ga$ so that, as seen in the commentary of Sthiramati, it is ascertained to apply to later doctrines through its secure establishment. To summarize its characteristics succinctly, firstly the $abh{\bar{u}}taparikalpa$ newly established as a saṃvṛti-satya is set up as the other-dependent nature, which is seen to have been set up particularly in order to sublate both the $Sarv{\bar{a}}stiv{\bar{a}}da^{\prime}s$ realist "view of being" and the Madhyamaka's "view of ${\acute{s}}{\bar{u}}nyat{\bar{a}}$" that impairs the ocher-dependent nature as a samvṛti-satya. In other words, according to the five kinds of views suggested in Sthiramati's commentary, the three natures are seen to be presented as the fundamental truth in order to unify all the doctrinal systems available ever since the beginning of Buddhism. Then, the theory of three natures is established principally on the basis of the $abh{\bar{u}}taparikalpa$, while the two truths of the $Yog{\bar{a}}c{\bar{a}}ra$ school are clearly ascertained to have been embedded in the structure of the $abh{\bar{u}}taparikalpa$. In fact, this might be understood to reflect the unique ontological view of reality or truth in the $Yog{\bar{a}}c{\bar{a}}ra$ School.