• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.5
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• pp.660-666
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• 2012

The weapon system is getting more and more expensive, complex and smarter. Therefore, efficiently and effectively, it is important to operate the weapon system. OMS/MP is a document to quantify operational factors like as environment, mission, mode etc. It is important data to perform RAM analysis in early weapon development phase and operate better a weapon system. This paper present a process and framework of OMS/MP for a naval ship with a deep analysis of relevant domestic and abroad case studies. It propose OMS/MP analysis framework based on wartime scenario and mission area analysis. This result will contribute not only improvement for the availability of a naval ship but also enhancement of RAM analysis process.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.4
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• pp.763-770
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• 2024

Currently, land-based fish farms utilizing seawater have introduced and are utilizing various equipment such as real-time water quality monitoring systems, facility automation systems, and automated dissolved oxygen supply devices. Furthermore, data collected from various equipment in these fish farms produce structured and unstructured big data related to water quality environment, facility operations, and workplace visual information. The big data generated in the operational environment of fish farms aims to improve operational and production efficiency through the development and application of various methods. This study aims to develop a system for effectively analyzing and visualizing big data produced from land-based fish farms. It proposes a data visualization process suitable for use in a fish farm big data analysis system, develops big data visualization tools, and compares the results. Additionally, it presents intuitive visualization models for exploring and comparing big data with time-series characteristics.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.221-232
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• 2023

Recently, due to the expansion of the logistics industry, demand for logistics automation equipment is increasing. The modern logistics industry is a high-tech industry that combines various technologies. In general, as various technologies are grafted, the complexity of the system increases, and the occurrence rate of defects and failures also increases. As such, it is time for a predictive maintenance model specialized for logistics automation equipment. In this paper, in order to secure the operational reliability of the ICT/Cold-Chain Unmanned Storage, a predictive maintenance system was implemented based on the LSTM model. In this paper, a server for data management, such as collection and monitoring, and an analysis server that notifies the monitoring server through data-based failure and defect analysis are separately distinguished. The predictive maintenance platform presented in this paper works by collecting data and receiving data based on RabbitMQ, loading data in an InMemory method using Redis, and managing snapshot data DB in real time. The predictive maintenance platform can contribute to securing reliability by identifying potential failures and defects that may occur in the operation of the ICT/Cold-Chain Unmanned Storage in the future.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.299-310
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• 2022

Environmental protection has been infused into the development of numerous fields by the Chinese government. The government's implementation of green development has also shifted its focus to green transformation and governance of highpolluting companies. In the context of green and sustainable development, this study employs DEA data envelopment analysis to compare the operating efficiency of listed firms that implemented Green Mergers and Acquisitions (M&A) in China in 2018. The conclusions of this study are as follows: First, China's green M&A enterprises are unevenly dispersed among the country's east, middle, and western regions. Second, compared to before the implementation of Green M&A, operational efficiency has improved in most industries. Third, the difference in Green M&A across industries is generally favorable, showing that most organizations have improved their operational performance as a result of Green M&A implementation. In 2018, however, the gap in operating efficiency is more negative. Fourth, whereas the eastern and western areas' operational efficiency has improved as a result of Green M&A, the central region's has not. Based on this conclusion, this study makes recommendations for China's future sustainable development of heavily polluted firms.

• Environmental Engineering Research
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• v.19 no.1
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• pp.31-36
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• 2014

In this study, the influence of the control and operational parameters within a sewage treatment plant were reviewed by performing multiple regression analysis on the effluent quality of the sewage treatment. The data used for this review are based on the actual data from a sewage treatment plant using the media process within the year 2012. The prediction models of chemical oxygen demand ($COD_{Mn}$) and total nitrogen (T-N) within the effluent of the 2nd settling tank based on the multiple regression analysis yielded the prediction accuracy measurements of 0.93 and 0.84, respectively; and it was concluded that the model was accurately predicting the variances of the actual observed values. If the data on the energy spent on each operating condition can be collected, then the operating parameter that conserves energy without violating the effluent quality standards of COD and T-N can be determined using the regression model and the standardized regression coefficients. These results can provide appropriate operation guidelines to conserve energy to the operators at sewage treatment plants that consume a lot of energy.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.7-14
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• 2011

This paper discusses operational technique and effectiveness of Variable Speed Limits system that is implemented to control the traffic-flow on the Naebu Expressway. As the first step of the analysis, traffic data collected from vehicle detectors are corrected and smoothed. Applying a pattern analysis technique to the traffic data, the weekday traffic is classified into four different groups, and median of each group is calculated. Using three state variables, i.e., diverted traffic volume, average density and average speed, the conditions of roadway segments are determined. Computational outputs resulted from the application of the proposed model to the scenarios show that implementation of Variable Speed Limits system improved both safety and efficiency of the expressway. For the operational strategy, this paper also presents the change rate of the speed limit, and the effective duration of the speed limit according to the entering traffic volume.

• The Journal of Fisheries Business Administration
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• v.53 no.1
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• pp.1-16
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• 2022

This paper aims to propose a new systematic approach to analyze the factor productivity and to investigate those characteristics of factor productivity in operational and managerial perspectives. The Cobb-Douglas production function is adopted to estimate the labor and capital productivity. In estimating those productivities the data of The Research on the Actual Condition of Coastal Fisheries (RACF), especially those of Jeon-Nam Province are used. The statistical analysis of RACF data shows that the characteristics are a little bit different between labor and capital of the operational equipment in the coastal fisheries. The Cobb-Douglas type production function is useful in estimating the factor productivity, especially in case of 'coastal Stow-net fishery' even though the limited data is used. However, in case of 'trap fishery,' the Cobb-Douglas production function appears to have some limitations in estimation. This implies that estimating the factor productivities in fisheries employing broad perspectives and various methods are needed.

• Journal of the Korean earth science society
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• v.39 no.4
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• pp.388-400
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• 2018

The purpose of this study was to explore the nine components of computational thinking (CT) practices and their operational definitions from the view of science education and to develop a CT practice framework that is going to be used as a planning and assessing tool for CT practice, as it is required for students to equip with in order to become creative problem solvers in $21^{st}$ century. We employed this framework into the earlier developed STEAM programs to see how it was valid and reliable. We first reviewed theoretical articles about CT from computer science and technology education field. We then proposed 9 components of CT as defined in technology education but modified operational definitions in each component from the perspective of science education. This preliminary CTPF (computational thinking practice framework) from the viewpoint of science education consisting of 9 components including data collection, data analysis, data representation, decomposing, abstraction, algorithm and procedures, automation, simulation, and parallelization. We discussed each component with operational definition to check if those components were useful in and applicable for science programs. We employed this CTPF into two different topics of STEAM programs to see if those components were observable with operational definitions. The profile of CT components within the selected STEAM programs for this study showed one sequential spectrum covering from data collection to simulation as the grade level went higher. The first three data related CT components were dominating at elementary level, all components of CT except parallelization were found at middle school level, and finally more frequencies in every component of CT except parallelization were also found at high school level than middle school level. On the basis of the result of CT usage in STEAM programs, we included 'generalization' in CTPF of science education instead of 'parallelization' which was not found. The implication about teacher education was made based on the CTPF in terms of science education.

• Journal of the Korean Data and Information Science Society
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• v.22 no.2
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• pp.207-215
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• 2011

This Risk analysis on information related assets is conducted primarily according to the standards the Korea Information and Telecommunications Technology Association (TTA) or the International Organization for Standardization (ISO). The process is made of asset analysis, threat analysis, vulnerability analysis, and response plan analysis. The risk for information related assets belongs to the operational risks suggested by BIS (Bank for International Settlements) and the information related losses can be estimated in terms of BIS' suggestion. In this paper it is proposed that how to apply the method proposed by BIS to estimate the loss of information assets.

• Journal of the Korea Institute of Military Science and Technology
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• v.5 no.3
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• pp.11-22
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• 2002

In this paper, a statistical meaning that the 1% frequency value which is used as a basis for the temperature specification generation for weapon systems is similar to $3{\sigma}$ frequency value of a year is presented, and the theoretical reference for temperature specification generation is made. The new method which extracts the 1% frequency value from general weather data, not depending on long term temperature hour data, is established, and the temperature analysis result of East Asia is also presented by using this method. On the basis of these result, operational temperature for the weapon systems to be used in the area of East Asia is recommended.