• Journal of the Korean Society of Safety
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• v.31 no.6
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• pp.121-128
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• 2016

Social Media transformed the mass media based information traffic, and it has become a key resource for finding value in enterprises and public institutions. Particularly, in regards to disaster management, the necessity for public participation policy development through the use of social media is emphasized. National Disaster Management Research Institute developed the Social Big Board, which is a system that monitors social Big Data in real time for purposes of implementing social media disaster management. Social Big Board collects a daily average of 36 million tweets in Korean in real time and automatically filters disaster safety related tweets. The filtered tweets are then automatically categorized into 71 disaster safety types. This real time tweet monitoring system provides various information and insights based on the tweets, such as disaster issues, tweet frequency by region, original tweets, etc. The purpose of using this system is to take advantage of the potential benefits of social media in relations to disaster management. It is a first step towards disaster management that communicates with the people that allows us to hear the voice of the people concerning disaster issues and also understand their emotions at the same time. In this paper, Korean language text mining based Social Big Board will be briefly introduced, and disaster issue detection model, which is key algorithms, will be described. Disaster issues are divided into two categories: potential issues, which refers to abnormal signs prior to disaster events, and occurrence issues, which is a notification of disaster events. The detection models of these two categories are defined and the performance of the models are compared and evaluated.

• Safety and Health at Work
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• v.10 no.1
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• pp.54-60
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• 2019

Background: Increasing the establishment of integrated management systems (IMSs) is done with the purpose of leaving traditional management methods and replacing them with modern management methods. Thus, the present study sought to analyze the events and investigate the impact of IMS on health and safety performance indices in an Iranian combined cycle power plants. Methods: This case study was conducted in 2012 in all units of the Yazd Combined Cycle Power Plant on accident victims before and after the implementation of IMS. For data analysis and prediction of indices after the implementation of IMS, descriptive statistics and Kolmogorov-Smirnov test, Chi-square, linear regression, and Cubic tests were conducted using SPSS software. Results: The number of people employed in the power plant in an 8-year period (2004-2011) was 1,189, and 287 cases of work-related accidents were recorded. The highest accident frequency rate and accident severity rate were in 2004 (32.65) and 2008 (209), respectively. Safe T-score reached to below -3 during 2010-2011. In addition, given the regression results, the relation between all predictor variables with outcomes was significant (p < 0.05), except for the variable $X^1$ belonging to the accident severity rate index. Conclusion: The implementation of safety programs especially that of IMS and its annual audits has had a significant impact on reducing accident indices and improving safety within the study period. Accordingly, health and safety management systems are appropriate tools for reducing accident rate, and the use of regression models and accident indices is also a suitable way for monitoring safety performance.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1319-1331
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• 2015

In the Republic of Korea, there's been a culture called 'Hyo' since Koryo Dynasty and this word represents the meaning of paying utmost respects to one's own parents and ancestors whether they are alive or have passed. However, nowadays, most of people live away from their family gravesites so that they do not and cannot take care of them except on the special holidays. For this reason, people could not respond promptly to the incidents occurred at the sites as they receive notifications much later dates most of the time. Thus, in this paper, we propose a low-cost gravesite monitoring system which the users can immediately respond to the disastrous events after being informed of current situations through PLC without delay. For the performance evaluation, the lab and test bed experiments were performed on an actual ship using 200Mbps and 500Mbps products instead of performing an on-site experiment after the system has actually been constructed. The Mountain Region PLC was installed on the power lines and the result showed successful 36.14Mbps communication. Therefore, we expect that this study will contribute in time and cost reduction while constructing the internet infrastructures in mountain regions or building the Smart-graves, tumulus, and charnel houses.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.5
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• pp.94-102
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• 2003

This paper presents active management of feeder automation systems using active database. DAS(Distribution Automation System) has been managed for feeder automation in passive manner. Therefore, feeder automation system has to be managed by operator when feeder overloadings is detected. It may be possible for propagating the feeder overloadings area by operator's mistake. To overcome this defect, the author proposed the feeder automation technique with active manner to obtain feasible feeder reconfiguration. Active database can manage feeder automation system by data driven monitoring of events and by corresponding actions without operator's intervening. To manage feeder automation system with active manner, production rule, active rule manager are designed. And active database system architecture for feeder automation system is proposed. Test results on the KEPCO's 108 bus distribution system show that the performance is efficient and robust.

• Journal of Wetlands Research
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• v.19 no.1
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• pp.80-89
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• 2017

Researches about NPS(Non-point Pollution Source) reduction have been widely carried out in recent years. A pilot channel-type constructed wetland (wet swale) was constructed in Rongyin area to treat stormwater generated from a green house agro-land of 22.7 ha. From 2006 to 2008, monitoring was conducted to evaluate its performance on the removal effect for organic pollutants as well as nutrients. Totally, sampling trips of 17 rainfall events were made and they covered most types of storm events in Korea. The channel-type constructed wetland have average removal efficiencies of 78.3~92.0%, 56.4~66.1%, 28.2~45.5% and 50.6~66.4% for SS, COD, TN and TP, respectively. According to four methods for estimating the removal efficiency, the average efficiencies of TSS, COD, TN and TP are 86.0%, 60.1%, 30.1% and 53.5%, respectively. From 2006 to 2008, annual efficiency improved due to infiltration potential increase. It was found that most of the pollutants removed in this channel type of wetland was particulate solids bound pollutants, which is assumed fact that it lacks of physico-chemical treatment conditions which are commonly observed in the retention type of constructed wetlands.

• Smart Structures and Systems
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• v.32 no.4
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• pp.267-279
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• 2023

Data modelling and interpretation for structural health monitoring (SHM) field data are critical for evaluating structural performance and quantifying the vulnerability of infrastructure systems. In order to improve the data modelling accuracy, and extend the application range from data regression analysis to out-of-sample forecasting analysis, an improved most likely heteroscedastic Gaussian process (iMLHGP) methodology is proposed in this study by the incorporation of the outof-sample forecasting algorithm. The proposed iMLHGP method overcomes this limitation of constant variance of Gaussian process (GP), and can be used for estimating non-stationary typhoon-induced response statistics with high volatility. The first attempt at performing data regression and forecasting analysis on structural responses using the proposed iMLHGP method has been presented by applying it to real-world filed SHM data from an instrumented cable-stay bridge during typhoon events. Uncertainty quantification and correlation analysis were also carried out to investigate the influence of typhoons on bridge strain data. Results show that the iMLHGP method has high accuracy in both regression and out-of-sample forecasting. The iMLHGP framework takes both data heteroscedasticity and accurate analytical processing of noise variance (replace with a point estimation on the most likely value) into account to avoid the intensive computational effort. According to uncertainty quantification and correlation analysis results, the uncertainties of strain measurements are affected by both traffic and wind speed. The overall change of bridge strain is affected by temperature, and the local fluctuation is greatly affected by wind speed in typhoon conditions.

• The KIPS Transactions:PartA
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• v.12A no.1 s.91
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• pp.53-58
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• 2005

The use of computers for control and monitoring of industrial process has expanded greatly in recent years. The computer used in such applications is shared between a certain number of time-critical control and monitor function and non time-critical batch processing job stream. Embedded systems encompass a variety of hardware and software components which perform specific function in host computer. Many embedded system must respond to external events under certain timing constraints. Failure to respond to certain events on time may either seriously degrade system performance or even result in a catastrophe. In the design of real-time embedded system, decisions made at the architectural design phase greatly affect the final implementation and performance of the system. Flexibility indicates how well a particular system architecture can tolerate with respect to satisfying real-time requirements. The degree of flexibility of real-time system architecture indicates the capability of the system to tolerate perturbations in timing related specifications. Given degree of flexibility, one may compare and rank different implementations. A system with a higher degree of flexibility is more desirable. Flexibility is also an important factor in the trade-off studies between cost and performance. In this paper, it is identified the need for flexibility function and shows that the existing real-time analysis result can be effective. This paper motivated the need for a flexibility for the efficient analysis of potential design candidates in the architectural design exploration or real time embedded system.

• Journal of the Korean Institute of Gas
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• v.1 no.1
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• pp.27-32
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• 1997

Continual monitoring of abnormal operating conditions i a key issue in maintaining high product quality and safe operation, since the undetected process abnormality may lead to the undesirable operations, finally producing low quality products, or breakdown of equipment. The statistical projection method recently highlighted has the advantage of easily building reference model with the historical measurement data in the statistically in-control state and not requiring any detailed mathematical model or knowledge-base of process. As the complexity of process increases, however, we have more measurement variables and recycle streams. This situation may not only result in the frequent occurrence of process Perturbation, but make it difficult to pinpoint trouble-making causes or at most assignable source unit due to the confusing candidates. Consequently, an ad hoc skill to monitor and diagnose in plat-wide scale is needed. In this paper, we propose a hierarchical plant-wide monitoring methodology based on hierarchical decomposition and principal component analysis for handling the complexity and interactions among process units. This have the effect of preventing special events in a specific sub-block from propagating to other sub-blocks or at least delaying the transfer of undesired state, and so make it possible to quickly detect and diagnose the process malfunctions. To prove the performance of the proposed methodology, we simulate the Tennessee Eastman benchmark process which is operated continuously with 41 measurement variables of five major units. Simulation results have shown that the proposed methodology offers a fast and reliable monitoring and diagnosis for a large scale chemical plant.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.216-223
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• 2019

Fault detection during production processes is one of the required operational tasks to run production processes both safely and consistently. Unexpected operational events or undetected process faults can have a serious impact on the production systems and subsequently on the final products' quality. In addition, such situations may lead to malfunctions or breakdowns of production processes. To reliably detect such abnormalities, a new one-class classification-based detection scheme has recently been developed The proposed method consists of four steps:1) noise filtering, 2) feature selection, 3) nonlinear representation and 4) outlier detection. The performance of the proposed scheme was demonstrated using the multivariate data obtained from a simulation process. The results have shown that the proposed method produced reliable monitoring results and outperforms any existing methods with an average improvement of 25.4%. The use of proper feature selection in the proposed framework yielded better detection performance.

• Biomedical Engineering Letters
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• v.8 no.4
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• pp.383-392
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• 2018

For prompt gamma ray imaging for biomedical applications and environmental radiation monitoring, we propose herein a multiple-scattering Compton camera (MSCC). MSCC consists of three or more semiconductor layers with good energy resolution, and has potential for simultaneous detection and differentiation of multiple radio-isotopes based on the measured energies, as well as three-dimensional (3D) imaging of the radio-isotope distribution. In this study, we developed an analytic simulator and a 3D image generator for a MSCC, including the physical models of the radiation source emission and detection processes that can be utilized for geometry and performance prediction prior to the construction of a real system. The analytic simulator for a MSCC records coincidence detections of successive interactions in multiple detector layers. In the successive interaction processes, the emission direction of the incident gamma ray, the scattering angle, and the changed traveling path after the Compton scattering interaction in each detector, were determined by a conical surface uniform random number generator (RNG), and by a Klein-Nishina RNG. The 3D image generator has two functions: the recovery of the initial source energy spectrum and the 3D spatial distribution of the source. We evaluated the analytic simulator and image generator with two different energetic point radiation sources (Cs-137 and Co-60) and with an MSCC comprising three detector layers. The recovered initial energies of the incident radiations were well differentiated from the generated MSCC events. Correspondingly, we could obtain a multi-tracer image that combined the two differentiated images. The developed analytic simulator in this study emulated the randomness of the detection process of a multiple-scattering Compton camera, including the inherent degradation factors of the detectors, such as the limited spatial and energy resolutions. The Doppler-broadening effect owing to the momentum distribution of electrons in Compton scattering was not considered in the detection process because most interested isotopes for biomedical and environmental applications have high energies that are less sensitive to Doppler broadening. The analytic simulator and image generator for MSCC can be utilized to determine the optimal geometrical parameters, such as the distances between detectors and detector size, thus affecting the imaging performance of the Compton camera prior to the development of a real system.