• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1835-1843
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• 2003

This paper introduces the development of the caliper system for a geometry PIG (Pipeline Inspection Gauge). The objective of the caliper system is to detect and measure dents, wrinkles, and ovalities affect the pipe structural integrity. The developed caliper system consists of a finger arm, an anisotropic permanent magnet, a back yoke, pins, pinholes and a linear hall effect sensor. The angle displacement of the finger arm is measured by the change of the magnetic field in sensing module. Therefore the sensitivity of the caliper system mainly depends on the magnitude of the magnetic field inside the sensing module. In this research, the ring shaped anisotropic permanent magnet and linear hall effect sensors were used to produce and measure the magnetic field. The structure of the permanent magnet, the back yoke and pinhole positions were optimized that the magnitude of the magnetic field range between a high of 0.1020 Tesla and a low of zero by using three dimensional nonlinear finite element methods. A simulator was fabricated to prove the effectiveness of the developed caliper system and the computational scheme using the finite element method. The experimental results show that the developed caliper system is quite efficient for the geometry PIG with good performance.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.557-564
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• 2014

In this study, we present an algorithm that conducts an unique naming process for the bridge object through the solid object identification focused on 3D straight bridge model. For the recognition of 3D objects, the numerical algorithm utilizes centroid point, and solid object on the local coordination system. It classifies the object feature set by classifying the objects and members based on the bridge direction. By doing so, unique names, which contain the information about span, members and order of the object, were determined and the suitability of this naming algorithm was examined through a truss bridge model and a bridge model with different coordinate systems. Also, the naming process based on the object feature set was carried out for the real 3D bridge model and then was applied to the module on local server and mobile device for real bridge inspection work. From the comparison of the developed naming algorithm based on object identification and the conventional one based on field inspection, it was shown that the conventional field inspection work can be effectively improved.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.5
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• pp.203-208
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• 2016

Information system audit is the requirement to configure the information system successfully. However, there is a problem with reduction of efficiency in the audit work when the system capacity is growing up. In the subsidiary field of information system audit, there is the same problem. In this paper, we will focus on the database audit, and implement an SQL audit tool in order to improve the performance of a database. During the designing phase of the SQL audit tool which aim to improve the performance of a database, we have analyzed the requirements of SQL audit work. Based on the aforementioned them, the process of the SQL audit tool has been designed with SQL audit features in accordance with information audit process. During the implementation phase, we have implemented 3 main function modules according to the output of the design phase. The main modules we implemented are the audit job definition module, audit job executing module and result reporting module. With the implemented tool, it applied to an Electric Power Corporation project in China and compared with other tools that are able to use SQL audit. In this paper, the implemented SQL audit tool is able to perform the general SQL audit work and to reduce the cost of the audit work for database performance and to raise the accuracy of result and to apply the extended inspection rule which need to use SQL parsing.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.2
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• pp.122-129
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• 2009

Recently much attention has been paid to a guided wave due to its effective applicability to long range and fast inspection of structures. In guided wave based NDE, the appropriate selection of wave modes is one of important factors since the test performance is highly dependent on which mode of guided waves is employed. As far as plate-like structures are concerned, so far, SH guided wave has not been frequently applied compared to Lamb waves, which is mostly caused by the lack of proper and convenient transducers to generate and measure the SH waves. In this investigation, a new small-sized SH guided wave transducer based on magnetostriction is proposed. The present transducer was designed to be modular and be used with shear couplant to avoid the inconvenience of the existing magnetostrictive patch transducers, which comprises the ferromagnetic patch tightly bonded to a structure. The wave transduction mechanism and the detailed configuration of the present transducer are presented. Experimental verification is also conducted on test specimens and the results confirm the good performance of the present transducer module.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.468-472
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• 2004

In this paper a VLSI design for the automatic magnetizing system has been presented. This is the design of a peripheral controller, which magnetizes CRTs and computers monitors and controls the automatic inspection system. We implemented a programmable peripheral interface(PPI) circuit of the control and protocol module for the magnetizer controller by using a O.8um CMOS SOG(Sea of Gate) technology of ETRI. Most of the PPI functions has been confirmed. In the conventional method, the propagation/ramp delay model was used to predict the delay of cells, but used to model on only a single cell. Later, a modified "apos;Linear delay predict model"apos; was suggested in the LODECAP(LOgic Design Capture) by adding some factors to the prior model. But this has not a full model on the delay chain. In this paper a new "apos;delay predict equationapos;" for the design of the timing control block in PPI system has been suggested. We have described the detail method on a design of delay chain block according to the extracted equation and applied this method to the timing control block design.

• Journal of Convergence for Information Technology
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• v.7 no.1
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• pp.35-42
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• 2017

In this paper, we propose to implement an integrated monitoring system using log data to reduce the load of analysis task of information security officer and to detect information leak in advance. To do this, we developed a transmission module between different model DBMS that transmits large amount of log data generated by the individual security system (MSSQL) to the integrated monitoring system (ORACLE), and the transmitted log data is digitized by individual and individual and researches about the continuous inspection and measures against malicious users when the information leakage symptom is detected by using the numerical data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3435-3440
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• 2010

Unlike the electric method capable of checking only product defect, the real time optical metrology is suggested for measuring and visualizing vibration with respect to position of surface acoustic wave in RF device. The measuring limits and conditions for surface acoustic wave is given, and the interference and diffraction due to RF signal are analyzed by optical interpretation. A single mode laser and a 105MHz-center-frequency repeater filter were employed for experiments and theoretical analysis. In this paper, the optical metrology providing visual energy distribution and real time inspection for surface acoustic wave is proposed for development of high quality multi-service and multi-frequency RF module.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.1-7
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• 2020

With the increase in cyber attacks, automated IDS using machine learning is being studied. According to recent research, the IDS using the recursive learning model shows high detection performance. However, the simple application of the recursive model may be difficult to reflect the associated session characteristics, as the overlapping session environment may degrade the performance. In this paper, we designed the session management module and applied it to LSTM (Long Short-Term Memory) recursive model. For the experiment, the CSE-CIC-IDS 2018 dataset is used and increased the normal session ratio to reduce the association of mal-session. The results show that the proposed model is able to maintain high detection performance even in the environment where session relevance is difficult to find.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.149-156
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• 2003

Recently, the importance of plant maintenance(PM) was highly raised to provide efficient plant operation which highly affects the productivity. For this reason, a number of engineering methodologies, such as riskbased inspection(RBI), fitness for service guidelines(FFS), plant lifecycle management(PLM), have been applied to improve the plant operation efficiency. Also, a network-based business operation system, which is called ERP(Enterprise Resource Planning), has been introduced in the field of plant maintenance. However, there was no attempt to connect engineering methodologies to the ERP PM system. In this paper, a knowledge-based information system for the plant operation of steel making company has been proposed. This system, which is named as K-VRS(Knowledge-based Virtual Reality System), provides a connection between ERP plant maintenance module and knowledge-based engineering methodologies, and thus, enables network-based highly effective plant maintenance process. The developed system is expected to play a great role for more efficient and safer plant maintenance.