• 대한토목학회논문집
• /
• 제32권2A호
• /
• pp.97-108
• /
• 2012

재킷식 해양구조물인 울돌목 시험조류발전소에 대하여 장기 모니터링을 통하여 구조물 동적 응답을 계측하였으며, 계측된 동적 응답 중 저주파수 거동을 정밀하게 계측할 수 있는 동적 경사 응답을 이용하여 구조물의 고유주파수 및 모드감쇠비를 추정하고, 이와 같은 동특성이 조위와 조류 유속 등 외부 환경에 의하여 어떤 영향을 받는지를 분석하였다. 제한된 수의 응답 계측 자료로부터 구조물의 고유주파수 및 모드감쇠비를 정밀하게 추정하기 위하여 개선된 실험모드해석 방법인 LS-FDD 방법을 제안하였으며, 제안된 실험모드해석 기법을 이용하여 울돌목 시험조류발전소의 동적 경사 응답을 분석하여, 주요 3차모드의 고유주파수와 모드감쇠비를 정밀하게 추정하였다. 추정된 동특성은 시간에 따라 크게 변동하며, 이러한 변동은 조석의 영향을 지배적으로 받고 있음을 시계열 분석 및 주파수 분석을 통하여 알 수 있었다. 또한 울돌목 시험조류발전소에서 관측한 일정 기간의 조위 및 조류 유속 자료를 이용하여, 구조물의 동특성과 조류 자료 사이의 상관관계를 분석하였고, 조위 및 유속 자료만으로 구조물의 동특성을 예측할 수 있는 모델식을 결정하였다.

• Smart Structures and Systems
• /
• 제26권4호
• /
• pp.419-433
• /
• 2020

Investigation of structural integrity has been a critical issue in the field of civil engineering for years. Visual inspection is one of the most available methods to explore deteriorative components in structures. Still, this method is not applicable to invisible damage of structures. Alternatively, system identification methods are capable of tracking modal properties of structures over time. The deviation of these dynamic properties can serve as indicators to access structural integrity. In this study, a modal tracking technique using frequency-domain system identification from seismic responses of structures is proposed. The method first segments the measured signals into overlapped sequential portions and then establishes multiple Hankel matrices. Each Hankel matrix is then converted to the frequency domain, and a temporal-average frequency-domain Hankel matrix can be calculated. This study also proposes the frequency band selection that can divide the frequency-domain Hankel matrix into several portions in accordance with referenced natural frequencies. Once these referenced natural frequencies are unavailable, the first few right singular vectors by the singular value decomposition can offer these references. Finally, the frequency-domain stochastic subspace identification tracks the natural frequencies and mode shapes of structures through quick stabilization diagrams. To evaluate performance of the proposed method, a numerical study is carried out. Moreover, the long-term monitoring strong motion records at a specific site are exploited to assess the tracking performance. As seen in results, the proposed method is capable of tracking modal properties through seismic responses of structures.

• 정보저장시스템학회논문집
• /
• 제3권2호
• /
• pp.94-112
• /
• 2007

Nano-sized inverted domain dots in ferroelectric materials have potential application in ultrahigh-density rewritable data storage systems. Herein, a data storage system is presented based on scanning non-linear dielectric microscopy and a thin film of ferroelectric single-crystal lithium tantalite. Through domain engineering, we succeeded to form an smallest artificial nano-domain single dot of 5.1 nm in diameter and artificial nano-domain dot-array with a memory density of 10.1 Tbit/$inch^2$ and a bit spacing of 8.0 nm, representing the highest memory density for rewritable data storage reported to date. Sub-nanosecond (500psec) domain switching speed also has been achieved. Next, long term retention characteristic of data with inverted domain dots is investigated by conducting heat treatment test. Obtained life time of inverted dot with the radius of 50nm was 16.9 years at $80^{\circ}C$. Finally, actual information storage with low bit error and high memory density was performed. A bit error ratio of less than $1\times10^{-4}$ was achieved at an areal density of 258 Gbit/inch2. Moreover, actual information storage is demonstrated at a density of 1 Tbit/$inch^2$.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2020년도 학술발표회
• /
• pp.101-101
• /
• 2020

Traditional stochastic simulation of hydroclimatological variables often underestimates the variability and correlation structure of larger timescale due to the difficulty in preserving long-term memory. However, the Long Short-Term Memory (LSTM) model illustrates a remarkable long-term memory from the recursive hidden and cell states. The current study, therefore, employed the LSTM model in stochastic generation of hydrologic and climate variables to examine how much the LSTM model can preserve the long-term memory and overcome the drawbacks of conventional time series models such as autoregressive (AR). A trigonometric function and the Rössler system as well as real case studies for hydrological and climatological variables were tested. Results presented that the LSTM model reproduced the variability and correlation structure of the larger timescale as well as the key statistics of the original time domain better than the AR and other traditional models. The hidden and cell states of the LSTM containing the long-memory and oscillation structure following the observations allows better performance compared to the other tested conventional models. This good representation of the long-term variability can be important in water manager since future water resources planning and management is highly related with this long-term variability.

• 정보처리학회논문지D
• /
• 제13D권3호
• /
• pp.309-316
• /
• 2006

본 논문에서는 도메인 온톨로지를 이용하여 XML 형식의 지식 문서를 분류하고 대표 개념을 효과적으로 추출하기 위한 기법을 제시하였다. 먼저, 도메인 온톨로지는 텍스트마이닝 기법과 통계적 기법을 이용하여 생성하였다. 이를 위해 XML 문서의 구조적인 특징을 이용하여 도메인 대표용어 집합을 구성하였다. 그리고 XML 문서를 효과적으로 분류하기 위한 DScore 기법과 지식 문서로부터 개념을 추출하기 위한 TScore 기법을 제시하였다. 본 논문에서 제안한 기법의 효율성을 검증하기 위하여 295편의 컴퓨터 관련 논문을 대상으로 실험하였다. 실험 결과, 본 연구에서 제안한 도메인 대표 용어 집합을 이용한 분류 결과가 기존의 방법보다 우수한 성능을 보였다. 특히 TScore기법에서는 문서에서 출현한 용어의 빈도수는 낮더라도 문서의 개념을 대표할 수 있는 용어를 효과적으로 추출할 수 있음을 보였다. 본 연구는 개념 기반의 검색 기법을 통하여 대량의 지식 문서를 효과적으로 관리하기 위한 지식 관리 모델에 적용할 수 있다.

• 융합보안논문지
• /
• 제23권5호
• /
• pp.65-72
• /
• 2023

본 논문에서는 LSTM(Long Short-Term Memory)을 기반으로 하는 Deep Learning 모델을 구축하여 인간의 습관적 특성을 고려한 악성 도메인 탐지 방법을 제시한다. DGA(Domain Generation Algorithm) 악성 도메인은 인간의 습관적인 실수를 악용하여 심각한 보안 위협을 초래한다. 타이포스쿼팅을 통한 악성 도메인의 변화와 은폐 기술에 신속히 대응하고, 정확하게 탐지하여 보안 위협을 최소화하는 것이 목표이다. LSTM 기반 Deep Learning 모델은 악성코드별 특징을 분석하고 학습하여, 생성된 도메인을 악성 또는 양성으로 자동 분류한다. ROC 곡선과 AUC 정확도를 기준으로 모델의 성능 평가 결과, 99.21% 이상 뛰어난 탐지 정확도를 나타냈다. 이 모델을 활용하여 악성 도메인을 실시간 탐지할 수 있을 뿐만 아니라 다양한 사이버 보안 분야에 응용할 수 있다. 본 논문은 사용자 보호와 사이버 공격으로부터 안전한 사이버 환경 조성을 위한 새로운 접근 방식을 제안하고 탐구한다.

• Journal of Electrical Engineering and Technology
• /
• 제13권4호
• /
• pp.1419-1424
• /
• 2018

Very short-term electric load forecasting is essential for real-time power system operation. In this paper, a very short-term electric load forecasting technique applying the Kalman filter algorithm is proposed. In order to apply the Kalman filter algorithm to electric load forecasting, an electrical load forecasting algorithm is defined as an observation model and a state space model in a time domain. In addition, in order to precisely reflect the noise characteristics of the Kalman filter algorithm, the optimal error covariance matrixes Q and R are selected from several experiments. The proposed algorithm is expected to contribute to stable real-time power system operation by providing a precise electric load forecasting result in the next six hours.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2022년도 추계학술발표대회
• /
• pp.308-310
• /
• 2022

With the rise of the Al wave, task-oriented dialogue systems have become one of the popular research directions in academia and industry. Currently, task-oriented dialogue systems mainly adopt pipelined form, which mainly includes natural language understanding, dialogue state decision making, dialogue state tracking and natural language generation. However, pipelining is prone to error propagation, so many task-oriented dialogue systems in the market are only for single-round dialogues. Usually single- domain dialogues have relatively accurate semantic understanding, while they tend to perform poorly on multi-domain, multi-round dialogue datasets. To solve these issues, we developed a paddle-based multi-domain task-oriented Chinese dialogue system. It is based on NEZHA-base pre-training model and CrossWOZ dataset, and uses intention recognition module, dichotomous slot recognition module and NER recognition module to do DST and generate replies based on rules. Experiments show that the dialogue system not only makes good use of the context, but also effectively addresses long-term dependencies. In our approach, the DST of dialogue tracking state is improved, and our DST can identify multiple slotted key-value pairs involved in the discourse, which eliminates the need for manual tagging and thus greatly saves manpower.

• 한국IT서비스학회지
• /
• 제13권3호
• /
• pp.129-148
• /
• 2014

Generally, the Internet Address Resources Act is intended to protect the public from acts of Internet "cybersquatting", a term used to describe the bad faith, abusive registration of Internet domain names. In determining whether a person has a bad faith intent, a court may consider factors such as, (1) the trademark or other intellectual property rights of the person, if any, in the domain name, (2) the extent to which the domain name consists of the legal name of the person or a name that is otherwise commonly used to identify that person, (3) the person's prior use, if any, of the domain name in connection with the bona fide offering of any goods or services, (4) the person's bona fide noncommercial or fair use of the mark in a site accessible under the domain name, (5) the person's intent to divert consumers from the mark owner's online location to a site accessible under the domain name that could harm the goodwill represented by the mark, either for commercial gain or with the intent to tarnish or disparage the mark, by creating a likelihood of confusion as to the source, sponsorship, affiliation, or endorsement of the site, (6) the person's offer to transfer, sell, or otherwise assign the domain name to the mark owner or any third party for financial gain without having used, or having an intent to use, the domain name in the bona fide offering of any goods or services, or the person's prior conduct indicating a pattern of such conduct.

• IEIE Transactions on Smart Processing and Computing
• /
• 제3권5호
• /
• pp.271-274
• /
• 2014

Bayesian based Multi-Frame Super-Resolution (MF-SR) has been used as a popular and effective SR model. On the other hand, the texture region is not reconstructed sufficiently because it works on the spatial domain. In this study, the MF-SR method was extended to operate on the frequency domain to improve HF information as much as possible. For this, a spatially weighted bilateral total variation model was proposed as a regularization term for a Bayesian estimation. The experimental results showed that the proposed method can recover the texture region more realistically with reduced noise, compared to conventional methods.