• 정보처리학회논문지D
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• 제16D권5호
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• pp.673-682
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• 2009

웹상에서 데이터 교환과 표현을 위한 표준으로 XML 데이터가 널리 사용되고 있으며 유비쿼터스 환경에서 XML 데이터의 형태는 연속적이다. 이와 관련하여 XML 스트림 데이터에 대한 빈발 구조 추출 및 효율적인 질의처리를 위한 마이닝 방법들이 연구되고 있다. 이 논문에서는 슬라이딩 윈도우 기반으로 하여 XML 스트림 데이터로부터 최근 윈도우 범위에 속하는 데이터에 대한 빈발 패턴 구조를 추출하기 위한 마이닝방법을 제안한다. 제안된 방법은 XML 스트림 데이터를 트리집합 모델, XFP_tree로 표현하고 이를 이용하여 최근의 데이터에 대한 빈발구조 패턴을 빠르게 추출한다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1996년도 추계학술대회논문집; 한국과학기술회관, 8 Nov. 1996
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• pp.422-430
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• 1996

The automated scanning laser Doppler vibrometer (LDV) has been designed, and built to measure in-plane displacements associated with waves propagating on vibrating structures. Use of optical fibers allows the compact design of a laser probe head which can be scanned over the vibrating structures. An algorithm for automated self-alignment of the laser probe is developed. The system is completely automated for scanning over the structures, focusing two laser beams at each data point until the detected vibration signal is stable, and for recording and transferring the data to a system computer. The automated system allows one to get extensive data of the vibration field over the structures. The system is tested by scanning a piezoelectric cylindrical shell and a plate excited by a continuous signal and by a pulse signal, respectively. Results show that the automated scanning LDV system can be a useful tool to measure the in-plane vibration field and to detect the elastic waves propagating on the vibrating structures.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1998년도 봄 학술발표회논문집(II)
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• pp.447-454
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• 1998

The main object of the study is that axial force-moment relationships for high strength concrete structures using reliability theory(Linear statstical method, Monte Carlo Simulation) including probability conception. And mean stress factors and centroid factors proposed to high strength concrete structures using reliability theory(Linear statstical method, Monte Carlo Simulation). Finally, The established experimental data for axial force-moment relationships are compared to the analytical data(data for Linear statstical method and Monte Carlo Simulation) for axial force-moment relationships in this analytical method.

• 한국농공학회지
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• 제44권3호
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• pp.101-110
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• 2002

Most of the agricultural structures are in shortage of feasible facility management because these structures are small in size and spacially distributed in rural area. Inspection tools based on visual inspections are generally used for agricultural structures in most of the countries, including Korea. It is necessary to survey data of the irrigation structures to maintain records, and to develop the interface program by constructing database of inspection data. This study was conducted to develop a system for safe appraisal and repair works on agricultural irrigation structures. Repair and rehabilitation method can be chosen from an optimum viewpoint if the information between the method and life-cycle management cost of agricultural structures is constructed in the database. In this study, the system assisting onsite field investigation and determining the typical rehabilitation method of typical agricultural structural problems such as fractures and cracks of members was developed.

• 정보처리학회논문지D
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• 제8D권4호
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• pp.421-426
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• 2001

정형적 개발 방법론은 소프트웨어를 정확하고 체계적으로 개발하기 위하여 사용되며 시스템을 정형 명세 언어를 사용하여 맹세하고 이를 구현할 때까지 점진적으로 시스템을 구체화하는 방법으로 개발한다. VDM은 정형 명세 언어의 하나로서 set, sequence, map의 수학적 추상적 자료구조를 사용하여 시스템을 명세하는데 대부분의 프로그래밍 언어는 이런 자료구조를 가지고 있지 않다. 그러므로 이들 자료구조들의 변환이 필요하며 VDM의 수학적 자료구조들은 프로그래밍 언어의 자료구조인 연결 리스트로 변환 할 수 있다. 본 논문에서는 VDM의 set, sequence, map의 자료구조를 프로그래밍 언어의 자료구조인 연결 리스트로 변환하는 방법과 그 변환의 타당성을 수학적으로 증명하였다.

• Smart Structures and Systems
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• 제29권1호
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• pp.237-250
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• 2022

Structural health monitoring (SHM) plays an important role in ensuring the safety and functionality of critical civil infrastructure. In recent years, numerous researchers have conducted studies to develop computer vision and machine learning techniques for SHM purposes, offering the potential to reduce the laborious nature and improve the effectiveness of field inspections. However, high-quality vision data from various types of damaged structures is relatively difficult to obtain, because of the rare occurrence of damaged structures. The lack of data is particularly acute for fatigue crack in steel bridge girder. As a result, the lack of data for training purposes is one of the main issues that hinders wider application of these powerful techniques for SHM. To address this problem, the use of synthetic data is proposed in this article to augment real-world datasets used for training neural networks that can identify fatigue cracks in steel structures. First, random textures representing the surface of steel structures with fatigue cracks are created and mapped onto a 3D graphics model. Subsequently, this model is used to generate synthetic images for various lighting conditions and camera angles. A fully convolutional network is then trained for two cases: (1) using only real-word data, and (2) using both synthetic and real-word data. By employing synthetic data augmentation in the training process, the crack identification performance of the neural network for the test dataset is seen to improve from 35% to 40% and 49% to 62% for intersection over union (IoU) and precision, respectively, demonstrating the efficacy of the proposed approach.

• 한국구조물진단유지관리공학회 논문집
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• 제3권4호
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• pp.199-204
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• 1999

The continuing development of the sensors for the measurement of the safety of structures has been making a turning point in measuring and evaluating the larger civil structural system as well. However, there are still remaining problems to be solved for the extremely large structure because the natural damages of those structures are not so simple to be monitored for the reason of their locational and structural conditions. One of the most significant problems is that a number of cables which connect the measuring system to the analyzer are liable to distort actual data. This paper presents a new monitoring system for large structures by means of a local wireless communication technique which would eliminate the possibility of the distortion of data by noise in cables. This new monitoring system employs the wireless system and the software for data communication, along with the strain sensor and accelerometers which have been already used in the past. It makes it possible for the data, which have been chosen by the central controling system from the various sensors placed in the large civil structures, to be wirelessly delivered and then analyzed and evaluated by decision making system of the structures.

• 디지털산업정보학회논문지
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• 제8권1호
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• pp.55-64
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• 2012

The advantage of direct volume rendering is to visualize structures of interest in the volumetric data. However it is still difficult to simultaneously show interior and exterior structures. Recently, cone beam computed tomography(CBCT) has been used for dental diagnosis. Despite of its usefulness, there is a limitation in the detection of interior structures such as pulp and inferior alveolar nerve canal. In this paper, we propose an efficient volume rendering model for visualizing important interior as well as exterior structures of dental CBCT. It is based on the concept of illustrative volume rendering and enhances boundary and silhouette of structures. Moreover, we present a new method that assigns a different color to structures in the rear so as to distinguish the front ones from the rear ones. This proposed rendering model has been implemented on graphics hardware, so that we can achieve interactive performance. In addition, we can render teeth, pulp and canal without cumbersome segmentation step.

• Geomechanics and Engineering
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• 제18권4호
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• pp.373-389
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• 2019

It is important to study the problem of durability for tunnel structures. As a main influence on the durability of tunnel structures, carbonation-induced corrosion is studied. For the complicated environment of tunnel structures, based on the data samples from real engineering examples, the intelligent method (genetic programming) is used to construct the service life prediction model of tunnel structures. Based on the model, the prediction of service life for tunnel structures in carbonation environments is studied. Using the data samples from some tunnel engineering examples in China under carbonation environment, the proposed method is verified. In addition, the performance of the proposed prediction model is compared with that of the artificial neural network method. Finally, the effect of two main controlling parameters, the population size and sample size, on the performance of the prediction model by genetic programming is analyzed in detail.

• Smart Structures and Systems
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• 제7권3호
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• pp.229-240
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• 2011

Recent developments in Smart Structures with very large scale embedded sensors and actuators have introduced new challenges in terms of data processing and sensor fusion. These smart structures are dynamically classified as a large-scale system with thousands of sensors and actuators that form the musculoskeletal of the structure, analogous to human body. In order to develop structural health monitoring and diagnostics with data provided by thousands of sensors, new sensor informatics has to be developed. The focus of our on-going research is to develop techniques and algorithms that would utilize this musculoskeletal system effectively; thus creating the intelligence for such a large-scale autonomous structure. To achieve this level of intelligence, three major research tasks are being conducted: development of a Bio-Inspired data analysis and information extraction from thousands of sensors; development of an analytical technique for Optimal Sensory System using Structural Observability; and creation of a bio-inspired decision-making and control system. This paper is focused on the results of our effort on the first task, namely development of a Neuro-Morphic Engineering approach, using a neuro-symbolic data manipulation, inspired by the understanding of human information processing architecture, for sensor fusion and structural diagnostics.