• 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.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2222-2224
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• 2002

Induction motors are critical components of many industrial machines and are frequently integrated in commercial equipment. The heavy economical losses and the deterioration of system reliability might be caused by the failure of induction motors in industrial field. Based on the reliability and cost competitiveness of driving system (motors), the faults detection and diagnosis of system is considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis (MCSA) method are emphasized. In this paper, MCSA method are used for induction motor fault diagnosis. This method analyzes the motors supply current. since this diagnoses faults of the motor. The diagnostic algorithm is based on the artificial neural network, and the diagnosis system is programmed by using LabVIEW and MATLAB.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.11 no.2
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• pp.92-96
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• 2006

NLPCA(Nonlinear Principal Component Analysis) is a novel technique for multivariate data analysis, similar to the well-known method of principal component analysis. NLPCA operates by a feedforward neural network called AANN(Auto Associative Neural Network) which performs the identity mapping. In this work, a sensor fault detection system based on NLPCA is presented. To verify its applicability, simulation study on the data supplied from risk management system is executed.

• KIISE Transactions on Computing Practices
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• v.20 no.12
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• pp.632-639
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• 2014

In this paper, we propose a PC's self-monitoring system for protecting illegal outflow of important personal files, which are managed in the Windows environment PC. This paper is based on the idea that it should be a read (access) file operation in order to outflow files through the network. To compare the information (name, some content) obtained from all operations of the reading of the 'Windows File System Driver' and captured transmission packets of mini port of 'Windows NDIS (Network Driver Interface Specification) Driver', and, if two pieces of information match, this system will determine the transmission to user. In this paper, tentatively, we developed a function to gather file information about file read operation and developed a function for transmission packet capture. This demonstration implementation showed that the proposed process has validity and the proposed process verified that it does not significantly affect the PC's performance.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.53-62
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• 2011

With the steady growth of mobile technology and applications, demand for more storage in mobile devices has also increased. A lightweight block-level protocol, Internet Advanced Technology Attachment (iATA), has been developed to deliver a cost-effective storage network solution for mobile devices to obtain more storage. This paper seeks to contribute to designing and implementing Load Balancing (LB), Network Monitoring (NM) and Write Replication (WR) modules to improve the protocol's scalability and data availability. LB and NM modules are invoked to collect system resources states and current network status at each associate node (server machine). A dynamic weight factor is calculated based on the collected information and sent to a referral server. The referral server is responsible to analyze and allocate the most ideal node with the least weight to serve the client. With this approach, the client can avoid connecting to a heavily loaded node that may cause delays in subsequent in-band I/O operations. Write replication is applied to the remaining nodes through a WR module by utilizing the Unison file synchronization program. A client initially connected to node IP A for write operations will have no hindrances in executing the relevant read operations at node IP B in new connections. In the worst case scenario of a node crashing, data remain recoverable from other functioning nodes. We have conducted several benchmark tests and our results are evaluated and verified in a later section.

• Smart Structures and Systems
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• v.29 no.1
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• pp.129-140
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• 2022

The effectiveness of system identification, damage detection, condition assessment and other structural analyses relies heavily on the accuracy and reliability of the measured data in structural health monitoring (SHM) systems. However, data anomalies often occur in SHM systems, leading to inaccurate and untrustworthy analysis results. Therefore, anomalies in the raw data should be detected and cleansed before further analysis. Previous studies on data anomaly detection mainly focused on just single type of data anomaly for denoising or removing outliers, meanwhile, the existing methods of detecting multiple data anomalies are usually time consuming. For these reasons, recognising multiple anomaly patterns for real-time alarm and analysis in field monitoring remains a challenge. Aiming to achieve an efficient and accurate detection for multi-type data anomalies for field SHM, this study proposes a pattern-recognition-based data anomaly detection method that mainly consists of three steps: the feature extraction from the long time-series data samples, the training of a pattern recognition neural network (PRNN) using the features and finally the detection of data anomalies. The feature extraction step remarkably reduces the time cost of the network training, making the detection process very fast. The performance of the proposed method is verified on the basis of the SHM data of two practical long-span bridges. Results indicate that the proposed method recognises multiple data anomalies with very high accuracy and low calculation cost, demonstrating its applicability in field monitoring.

• Korean Journal of Construction Engineering and Management
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• v.11 no.6
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• pp.122-130
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• 2010

Seventy percent of Korea's national territory is covered with mountains, and the land is frequently exposed to typhoons and localized torrential downpours, particularly in July through September. For this reason, slope failure is one of the most frequent types of natural disasters in Korea. To prevent the damage caused by slope failure, the Korean government, academia and industry have strived together to develop and install a wired system for monitoring slope failures. However, conventional wired monitoring systems have been reported to have limitations, such as possible system errors caused by lightning, and the difficulties of restoration and management of the systems. To solve these problems, this research suggests a USN-based monitoring system for slope failures. First, the trend of slope measurement and USN technology was analyzed, and then the current status of damage caused by slope failures in Korea was reviewed. Next, a USN-based monitoring scenario for slope failures, incorporating both USN and slope monitoring technique, was developed. Finally, sensors were decided based on the developed scenario. It is expected that the results of this study will be utilized as fundamental data for the development of monitoring prototype systems for slope failures in the future. The development of the USN-based monitoring system for slope failures and its application in the field will also ultimately contribute to the prevention of slope failures and the minimization of related damage.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.113-120
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• 2022

Information technologies in higher education are the basis for solving the tasks set by monitoring the quality of higher education. The directions of aplying information technologies which are used the most nowadays have been listed. The issues that should be addressed by monitoring the quality of higher education with the use of information technology have been listed. The functional basis for building a monitoring system is the cyclical stages: Observation; Orientation; Decision; Action. The monitoring system's considered cyclicity ensures that the concept of independent functioning of the monitoring system's subsystems is implemented.. It also ensures real-time task execution and information availability for all levels of the system's hierarchy of vertical and horizontal links, with the ability to restrict access. The educational branch uses information and computer technologies to monitor research results, which are realized in: scientific, reference, and educational output; electronic resources; state standards of education; analytical materials; materials for state reports; expert inferences on current issues of education and science; normative legal documents; state and sectoral programs; conference recommendations; informational, bibliographic, abstract, review publications; digests. The quality of Ukrainian scientists' scientific work is measured using a variety of bibliographic markers. The most common is the citation index. In order to carry out high-quality systematization of information and computer monitoring technologies, the classification has been carried out on the basis of certain features: (processual support for implementation by publishing, distributing and using the results of research work). The advantages and disadvantages of using web-based resources and services as information technology tools have been discussed. A set of indicators disclosed in the article evaluates the effectiveness of any means or method of observation and control over the object of monitoring. The use of information technology for monitoring and evaluating higher education is feasible and widespread in Ukrainian education, and it encourages the adoption of e-learning. The functional elements that stand out in the information-analytical monitoring system have been disclosed.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.5
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• pp.746-755
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• 2009

Recently, NMEA2000 became the de facto standard of the communication protocol for the instrument level network in vessels, and it is anticipated that most of the vessels will be equipped with the sensors and actuators based on this protocol. The conventional serial communication specifications such as RS-232, RS-485, or even NMEA0183 are single-talker/multiple-listener and interconnection among multiple sensors and/or actuators usually results in a bundle of wires. On the other hand, NMEA2000 is a true bus type(multiple-talker/multiple-listener) protocol and theoretically up to 256 instruments can be hot-plugged. With the advent of the protocol, it is necessary to consider a new type of monitoring system for the instruments in vessels: In most traditional serial communication environments, a dedicated monitor or user interface was necessary for each sensor or actuator as it was simply not easy to collect data in a single place. With NMEA2000, the collection of various types of information is simple. An embedded system can be employed to combine, to arrange and to display informations from various types of devices. Assuming that the actuators and sensors on a vessel are interconnected by NMEA2000 standard, we devise a tentative interactive vessel monitoring system in which the following 4 kinds of informations are collected and delivered: the navigation, engine, weather and tanks informations.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.351-356
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• 2014

Generally, although securing the condition and location of container freights or normal freights, which load a fresh goods, has been a very important issue in the cold-chain system implementations, it has not gotten out of the traditional methods in the related business world yet. To solve this problem, we propose the designing method and architecture which can be used to implement a smart cold-chain monitoring automation systems. The proposed system architecture is based on the oneM2M standards, and it has 3 layers and entities, which can be implemented to S/W and H/W, network services layer and entity, common services layer and entity, application layer and entity. Based on this architecture, we will not only expect an innovative retrenchment of distribution cost, but also automatically secure the freight condition and location.