• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2008.04a
• /
• pp.241-246
• /
• 2008

Design of a high-speed railway line requires collaboration of heterogeneous application systems and of engineers with different background. Object-based 3D models with metadata can be a shared information model for the effective collaborative design. In this paper, railway infrastructure information model is proposed to enable integrated and inter-operable works throughout the life-cycle of the railway infrastructures, from planning to maintenance. In order to develop the model, object-based 3-D models were built for a 10km railway among Korea high-speed railway lines. The model has basically three information layers for designers, contractors and an owner, respectively. Prestressed concrete box-girders are the most common superstructure of bridges. The design information layer has metadata on requirements, design codes, geometry, analysis and so on. The construction layer has data on drawings, real data for material and products, schedules and so on. The maintenance layer for the owner has the final geometry, material data, products and their suppliers and so on. These information has its own data architecture which is derived from similar concept of product breakdown structure(PBS) and work breakdown structure(WBS). The constructed RIIM for the infrastructures of the high-speed railway was successfully applied to various areas such as design check, structural analysis, automated estimation, construction simulation, virtual viewing, and digital mock-up. The integrated information model can realize virtual construction system for railway lines and dramatically increase the productivity of the whole engineering process.

• The Journal of Society for e-Business Studies
• /
• v.3 no.1
• /
• pp.43-67
• /
• 1998

Logistics is by no means a new subject area. The concept of logistics goes way become more complex as technology advances, and logistics requirements have increased accordingly. In 1964, when ILS philosophy formally came into being, ILS was defined in general terms and did not describe what actions an ILS program should accomplish. ILS philosophy have been developed from 1964 through 1980. In 1982, United States Department of Defense formulated a new concept, CALS. CALS is the strategy that the US defense development to management the transition to integration and automated interchange in defense system engineering, manufacturing, and logistic support. Its goal is to use the inherent features of digitized data to revolutionize the function of data -gathering, data storage and data - transfer techologies associared with the development of defense systems. The Result will be systems that are cheaper, more reliable, and easier to maintain. To define CALS's character, the purpose of this papers compare two concepts - CALS and ILS. The elements of CALS consist of standads and EDI. The elements of ILS include LCC(Life Cycle Cost), LSA(Logistics Support Analysis), LSAR(Logistics Support Analysis Rcord), Aquisition Cycle.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.26 no.7
• /
• pp.759-766
• /
• 2020

In recent years, the maritime traffic environment has been changing in various ways, and the traffic volume has been increasing constantly. Accordingly, the requirements for maritime traffic analysis have become diversified. To this end, traffic characteristics must first be analyzed using vessel trajectory data. However, as the conventional method is mostly manual, it requires a considerable amount of time and effort, and errors may occur during data processing. In addition, ensuring the reliability of the analysis results is difficult, because this method considers the subjective opinion of analysts. Therefore, in this paper, we propose an automated method of traffic network generation for maritime traffic analysis. In the experiment, spatiotemporal features are analyzed using data collected at Mokpo Harbor over six months. The proposed method can automatically generate a traffic network reflecting the traffic characteristics of the experimental area. In addition, it can be applied to a large amount of trajectory data. Finally, as the spatiotemporal characteristics can be analyzed using the traffic network, the proposed method is expected to be used in various maritime traffic analyses.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.24 no.4
• /
• pp.341-353
• /
• 2022

Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.25 no.3
• /
• pp.59-73
• /
• 2022

Currently, the conflict between use and conservation of the ocean is intensifying in the ocean, so it is essential to introduce an effective method to define and manage it in advance for each core value of ocean. Accordingly, although the ocean is divided into nine marine use zone and managed through marine spatial planning, the analysis of the sea areas where mutually exclusive activities overlap in the ocean is insufficient. In this study, an automated model was developed to derive a sea areas where the core values of the ocean conflict. In order to analyze marine activities, available data on marine activity were collected, and data necessity for the analysis of mutually exclusive marine activities were derived. After classifying the derived data into legal and characteristic data, a conflict matrix was prepared through pairwise comparison between data to designate priorities when overlapping occurs. Based on the designated priorities, an automation model was developed, and sea areas where marine activities conflicted were derived, visualized, and area calculated. Using this, it is judged that the efficiency of decision-making can be improved by clearly deriving the sea areas where major issues occur in establishing the marine spatial planning.

• Genomics & Informatics
• /
• v.9 no.1
• /
• pp.19-27
• /
• 2011

Gene Expression Omnibus (GEO) has kept the largest amount of gene-expression microarray data that have grown exponentially. Microarray data in GEO have been generated in many different formats and often lack standardized annotation and documentation. It is hard to know if preprocessing has been applied to a dataset or not and in what way. Standard-based integration of heterogeneous data formats and metadata is necessary for comprehensive data query, analysis and mining. We attempted to integrate the heterogeneous microarray data in GEO based on Minimum Information About a Microarray Experiment (MIAME) standard. We unified the data fields of GEO Data table and mapped the attributes of GEO metadata into MIAME elements. We also discriminated non-preprocessed raw datasets from others and processed ones by using a two-step classification method. Most of the procedures were developed as semi-automated algorithms with some degree of text mining techniques. We localized 2,967 Platforms, 4,867 Series and 103,590 Samples with covering 279 organisms, integrated them into a standard-based relational schema and developed a comprehensive query interface to extract. Our tool, GEOQuest is available at http://www.snubi.org/software/GEOQuest/.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.27 no.1
• /
• pp.41-46
• /
• 2023

Recently, big data analysis can use various techniques according to the development of machine learning. Big data collected in reality lacks an automated refining technique for the same or similar terms based on semantic analysis of the relationship between words. Since most of the big data is described in general sentences, it is difficult to understand the meaning and terms of the sentences. To solve these problems, it is necessary to understand the morphological analysis and meaning of sentences. Accordingly, NLP, a technique for analyzing natural language, can understand the word's relationship and sentences. Among the NLP techniques, the transformer has been proposed as a way to solve the disadvantages of RNN by using self-attention composed of an encoder-decoder structure of seq2seq. In this paper, transformers are used as a way to form associations between words in order to understand the words and phrases of sentences extracted from big data.

• Archives of Pharmacal Research
• /
• v.12 no.4
• /
• pp.289-294
• /
• 1989

A computer program which can differentiate compounds whose absorbance spectra are very similar was developed. The program. [SPECMAN PLUS], written in Pascal provides automated spectral comparison techniques, utilizing the values of Root Mean of Squares (RMS) of differences. This comparison routine of the program can deal with spectra of compounds different concentrations and different spectral recording resolutions. In addition, the program was designed applicable to any spectral data of digital form. The program was applied to the UV spectra of 13 pencillins and 5 cephalosporins, whose absorbance spectra are so similar. As a result, all compounds examined could be differentiated from each other.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1460-1463
• /
• 2005

In this paper, analysis of magnetic marker for autonomous vehicle guidance system using 3-axis magnetic sensor propose. Position sensing is an important an estimation system of vehicle position and orientation on magnetic lane, which is a parameter of the steering controller for automated lane following is described. To verify that the magnetic dipole model could be applied to a magnetic unit paved in roadway, the analysis of the data 3-axis magnetic field measured experimentally.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.5 no.6
• /
• pp.499-503
• /
• 2004

In the actual system development site, the various specifications are drawn up into each phase, namely analysis, design, development and implementation, beginning with the analysis of user requirements and data involved. The part of the specifications are continuously drawn up by using automated tool, but all specification are not automatically drawn up. Therefore, many inconsistent items occur between the specifications. In this paper, we propose the method which detects the error which is included in the specifications, and we are going to design and implement a specification error detection system based on this.