• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.673-682
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• 2009

XML data are widely used for data representation and exchange on the Web and the data type is an continuous stream in ubiquitous environment. Therefore there are some mining researches related to the extracting of frequent structures and the efficient query processing of XML stream data. In this paper, we propose a mining method to extract frequent structures of XML stream data in recent window based on the sliding window. XML stream data are modeled as a tree set, called XFP_tree and we quickly extract the frequent structures over recent XML data in the XFP_tree.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1996.10a
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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.

• Proceedings of the Korea Concrete Institute Conference
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• 1998.04b
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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.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.3
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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.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.421-426
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• 2001

A formal development method is used to develop software rigorously and systematically. In a formal development method, we specify system by a formal specification language and gradually develop the system more concretely until we can implement the system. VDM is one of formal specification languages. VDM uses mathematical data structures such as sets, sequences, and maps to specify the system, but most programming languages do not have such data structures. Therefore, these data structures should be converted. We can convert mathematical data structures in VDM to a linked list, a data structure in a programming language. In this article, we propose a method to convert a set, a sequence, and a map in VDM to a linked list in a programming language and prove the correctness of this conversion mathematically.

• Smart Structures and Systems
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• v.29 no.1
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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.

• Journal of the Korea institute for structural maintenance and inspection
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• v.3 no.4
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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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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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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• v.18 no.4
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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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• v.7 no.3
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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.