• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.123-131
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• 2016

Process mining in big data environment utilize a number of data were generated from the business process. It generates lots of knowledge and insights regarding implementation and improvement of the process through the event log of the company's enterprise resource planning (ERP) system. In recent years, various research activities engaged with the audit work of company organizations are trying actively by using the maximum strength of the mining process. However, domestic studies on applicable sales auditing system for the process mining are insufficient under big data environment. Therefore, we propose process-mining methods that can be optimally applied to online and traditional auditing system. In advance, we propose continuous monitoring information system that can early detect and prevent the risk under the big data environment by monitoring risk factors in the organizations of enterprise. The scope of the research of this paper is to design a pre-verification system for risk factor via practical examples in sales auditing. Furthermore, realizations of preventive audit, continuous monitoring for high risk, reduction of fraud, and timely action for violation of rules are enhanced by proposed sales auditing system. According to the simulation results, avoidance of financial risks, reduction of audit period, and improvement of audit quality are represented.

• Journal of Wetlands Research
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• v.24 no.4
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• pp.301-311
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• 2022

The purpose of this study is to analyze the seasonal characteristics of water quality using long-term water quality monitoring data. Seasonal characteristics of water quality were analyzed using monitoring data from 34 tributaries where long-term monitoring was performed in the Nakdong River system, and average data analysis of water quality, coefficient of variation analysis, and trend analysis were performed for seasonal analysis. For seasonal analysis, average data analysis of water quality, coefficient of variation analysis, and trend analysis were performed. As a result of the evaluation of the coefficient of variation, tributaries were larger than main streams, and BOD, T-P, and TOC were larger in autumn and T-N were larger in spring. Trend analysis was analyzed using Mann-Kendall and Sen's Slope. BOD, T-N, and T-P tended to decrease, but TOC had a lot to increase. Through this study, it was possible to evaluate the availability of long-term water quality monitoring data and analyze seasonal characteristics, and to analyze the stabilization period of water quality and changes in pollutant sources for watershed management.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1053-1060
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• 2021

Current water quality monitoring systems in Korea carried based on in-situ grab sample analysis. It is difficult to improve the current water quality monitoring system, i.e. shorter sampling period or increasing sampling points, because the current systems are both cost- and labor-intensive. One possible way to improve the current water quality monitoring system is to adopt a modeling approach. In this study, a modeling technique was introduced to support the current water quality monitoring system, and an artificial neural network model, the computational tool which mimics the biological processes of human brain, was applied to predict water quality of the river. The approach tried to predict concentrations of Total coliform at the outlet of the river and this showed, somewhat, poor estimations since concentrations of Total coliform were rapidly fluctuated. The approach, however, could forecast whether concentrations of Total coliform would exceed the water quality standard or not. As results, modeling approaches is expected to assist the current water quality monitoring system if the approach is applied to judge whether water quality factors could exceed the water quality standards or not and this would help proper water resource managements.

• Journal of the Korean Geosynthetics Society
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• v.21 no.4
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• pp.55-67
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• 2022

In this paper, fundamentals and recent development of the interferometric synthetic aperture radar, known as InSAR, technique for measuring ground deformation through satellite image analysis are presented together with case histories illustrating its applicability to urban ground deformation monitoring. A study area in Korea was selected and processed based on the muti-temporal time series InSAR analysis, namely SBAS (Small Baseline Subset)-InSAR and PS (Persistent Scatterers)-InSAR using Sentinel-1A SAR images acquired from the year 2014 onward available from European Space Agency Copernicus Program. The ground settlement of the study area for the temporal window of 2014-2022 was evaluated from the viewpoint of the applicability of the InSAR technique for urban infrastructure settlement monitoring. The results indicated that the InSAR technique can reasonably monitor long-term settlement of the study area in millimetric scale, and that the time series InSAR technique can effectively measure ground settlement that occurs over a long period of time as the SAR satellite provides images of the Korean Peninsula at regular time intervals while orbiting the earth. It is expected that the InSAR technique based on higher resolution SAR images with small temporal baseline can be a viable alternative to the traditional ground borne monitoring method for ground deformation monitoring in the 4^th industrial era.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.366-375
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• 2022

The monitoring of electricity consumption using Internet of Things (IoT) technology is attracting attention as a technology to reduce operation costs of smart farms. In this study, we propose a method to apply a real-time electrical consumption monitoring system (the e-Gauge system) and utilization of the collected data real-time while a melon-producing smart farm is in operation. For this purpose, the electrical consumption data for the individual smart-farm facilities such as boilers, nutrient distribution systems, automatic controllers, circulation fans, boiler controllers, and other IoT-related utilities were collected during three months of melon cultivation period. By using the monitoring results, the electrical energy consumption pattern was analyzed as an example, and necessary considerations needed to optimally utilize the measurement data were suggested. This paper will be useful in lowering the technological implementation barriers for new researchers to build a electrical consumption monitoring system and reducing trial and errors in the usage of the generated data.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.5
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• pp.437-445
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• 2018

Devices have a lot of small breakdowns rather than big breakdowns. But it often wastes time and increases cost of maintenance, such as calling a service technician for small breakdowns. So, if we use remote control and monitoring service using Internet of Things, we can minimize the time period and cost for the maintenance. However, security is important because remote control and monitoring services contain personal information which when leaked, may be dangerous. There are many types of Internet based monitoring devices that are in use, but it is difficult to expect a high level of security because there are many cases in which the performance is minimal. Therefore, in this paper, we classify remote control and monitoring services based on Internet of Things type and derive encryption requirement for four types. We also compared and analyzed the lightweight cryptographic algorithms that can be expected to use high performance even on the Internet of Things. And it is derived that LED is used as a equipment management type, DESLX as a environment management type, CLEFIA as a healthcare management type and LEA as a security management type are the optimal lightweight cryptographic algorithms for each type.

• Journal of radiological science and technology
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• v.32 no.2
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• pp.141-146
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• 2009

This study analyzed decade-based statistic data which had been collected from the reports of annual radiographic pulmonary tuberculosis screening program initiated by the Korean National Tuberculosis Association (KNTA) for last 5 decades (from 1956 to 2005). We analyzed only the content of annual statistic report to preserve the characteristic of statistic data and the contents of original copy by focusing on the analysis of tuberculosis cases where age and sex were excluded. The results of the disease-based analysis on the tuberculosis cases from cumulative subjects of chest radiography (CXR) from 1956 to 2005 are summarized as follows. 1. The cumulative number of subjects who were examined under annual chest radiography over last 5 decades totaled 54,938,875 persons. 2. The cumulative number of pulmonary tuberculosis cases during same period totaled 958,251 persons (1.74%). 3. The cumulative number of subjects treated during same period totaled 465,082 persons (0.85%). 4. The cumulative number of mild pulmonary tuberculosis cases during same period totaled 229,615 persons (0.42%). 5. The cumulative number of moderate pulmonary tuberculosis cases during same period totaled 144,247 persons (0.26%). 6. The cumulative number of severe pulmonary tuberculosis cases during same period totaled 74,066 persons (0.13%). 7. The cumulative number of exudative pleurisy cases during same period totaled 17,154 persons (0.03%). 8. The cumulative number of subjects under monitoring during same period totaled 493,169 persons (0.90%). 9. The cumulative number of uncertain activity cases during same period totaled 78,214 persons (0.14%). 10. The cumulative number of pseudo-pulmonary tuberculosis cases during same period totaled 272,349 persons (0.50%).

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.27-33
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• 2013

Nowadays, the utilization of renewable energy sources like wind energy is considered one of the most effective means of generating massive amounts of electricity. This is evident in the rapid increase of wind farms all over the world which comprise a huge number of wind turbines. However, the drawback of utilizing wind turbines is that it requires maintenance, which could be a costly operation. To keep the wind turbines in pristine condition so as to reduce downtime, the implementation of CMS (Condition Monitoring System) and FDS (Fault Detection System) is mandatory. The efficiency and accuracy of these systems are crucial in deciding when to carry out a maintenance process. In this paper, a fault detection system based on intelligent clustering method is proposed. Using SCADA data, the clustering model was trained and evaluated for its accuracy through rigorous simulations. Results show that the proposed approach is able to accurately detect the deteriorating condition of a wind turbine as it nears a downtime period.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.1
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• pp.1-8
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• 2004

This study intend to make easy modification, even if there is a new job or structure change, by modularizing program and computerize and automation of production control management used in CIM. under the condition where manager control production on the job-site, for increasing connection with other operation and management on the computer by monitoring center computer, recognizing information by computer is needed, it is possible by converting transaction. So this study goal is to make delivery control and order control fast and accurate by finding dynamic history of machine and production information in enterprise without input production and quality information by themselves with quality information system. So production increase and quality improvement are possible by diminishing manager's and producer's work with the result of the study combining POP and CIM, after that, in e-business and m-business period that every enterprise must pass, customer satisfaction and sales promotion are possible with employee's computerizing minds. these study result also can knowledge process condition with theoretical class and have a power in finding a solution with foundation of theoretical knowledge.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.891-898
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• 2017

Climate changes consistently cause coastal accidents such as coastal flooding, so the studies on monitoring the marine environments are progressing to prevent and reduce the damage from coastal accidents. In this paper, we propose a new method to estimate the sea level which can be applied to the tidal sensors to monitor the variation of sea level. Existing sea level models are very complicated and need a lot of tidal data, so they are not proper for tidal sensors. On the other hand, the proposed algorithm is very simple but precise since we use the measured data from the sensor to estimate the sea level value in short period such as one or two hours. It is shown by experimental results that the proposed method is simple but predicts the sea level accurately.