• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.9-24
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• 2022

Currently, a vast amount of hydrologic data is accumulated in real-time through automatic water level measuring instruments in agricultural reservoirs. At the same time, false and missing data points are also increasing. The applicability and reliability of quality control of hydrological data must be secured for efficient agricultural water management through calculation of water supply and disaster management. Considering the characteristics of irregularities in hydrological data caused by irrigation water usage and rainfall pattern, the Korea Rural Community Corporation is currently applying the Hampel filter as a water level data quality management method. This method uses window size as a key parameter, and if window size is large, distortion of data may occur and if window size is small, many outliers are not removed which reduces the reliability of the corrected data. Thus, selection of the optimal window size for individual reservoir is required. To ensure reliability, we compared and analyzed the RMSE (Root Mean Square Error) and NSE (Nash-Sutcliffe model efficiency coefficient) of the corrected data and the daily water level of the RIMS (Rural Infrastructure Management System) data, and the automatic outlier detection standards used by the Ministry of Environment. To select the optimal window size, we used the classification performance evaluation index of the error matrix and the rainfall data of the irrigation period, showing the optimal values at 3 h. The efficient reservoir automatic calibration technique can reduce manpower and time required for manual calibration, and is expected to improve the reliability of water level data and the value of water resources.

• Economic and Environmental Geology
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• v.55 no.4
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• pp.353-366
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• 2022

Spatial estimation of geoscience data (geo-data) is challenging due to spatial heterogeneity, data scarcity, and high dimensionality. A novel spatial estimation method is needed to consider the characteristics of geo-data. In this study, we proposed the application of Gaussian Mixture Model (GMM) among machine learning algorithms with multivariate data for robust spatial predictions. The performance of the proposed approach was tested through soil chemical concentration data from a former smelting area. The concentrations of As and Pb determined by ex-situ ICP-AES were the primary variables to be interpolated, while the other metal concentrations by ICP-AES and all data determined by in-situ portable X-ray fluorescence (PXRF) were used as auxiliary variables in GMM and ordinary cokriging (OCK). Among the multidimensional auxiliary variables, important variables were selected using a variable selection method based on the random forest. The results of GMM with important multivariate auxiliary data decreased the root mean-squared error (RMSE) down to 0.11 for As and 0.33 for Pb and increased the correlations (r) up to 0.31 for As and 0.46 for Pb compared to those from ordinary kriging and OCK using univariate or bivariate data. The use of GMM improved the performance of spatial interpretation of anthropogenic metals in soil. The multivariate spatial approach can be applied to understand complex and heterogeneous geological and geochemical features.

• Journal of Korean Elementary Science Education
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• v.40 no.4
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• pp.443-459
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• 2021

In this study, a TPACK-based STEAM program was developed and applied under the theme of excretory organs in the 'Structure and Function of Our Body' of the elementary science curriculum. The program was produced and conducted through curriculum analysis and learning goal detailing, learning environment analysis, teaching·learning method and technology selection, TPACK elements arrangement and teaching·learning material development, application and effectiveness verification. Teacher's TPACK considered in STEAM program design process is content knowledge (appearance and work of excretory organs), pedagogical knowledge (STEAM, problem-based learning, research learning, discussion learning, cooperative learning, scientific writing) and technology knowledge (3D printer and smart device application technology). The program consisted of a total of 8 hours of project learning activities and was applied to 29 students in the fifth grade as an experimental group. A program of the same theme developed mainly from textbooks was applied to 27 students in the fifth grade of a comparison group. As a result of the application of the program, the experimental group showed significant improvement in creative problem-solving ability and scientific attitude compared to the comparison group, and the class satisfaction with the STEAM program was also high. However, there was no significant difference in academic achievement ability.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.345-353
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• 2021

Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO₂. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.81-91
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• 2021

The reasonable decision making procedure for conducting follow-up management of water-friendly riverfront have been proposed in the national streams when the use of the level of usage for facility becomes degraded. It consists of two part usage: the selection of destination and the follow-up strategy with the alternatives. Considering the water-friendly riverfront grade derived from prior research, Grade IV and V were selected as candidates, and if the economic utility became low, it should be selected as candidates for the follow-up management. In addition, the basic plan for follow-up management was reviewed and alternatives suitable for the strategy could be derived considering the need for the operation of water-friendly riverfront in target site. The prior study on the follow-up decision making process of the water-friendly riverfront has not yet been confirmed, but since the life cycle of such facilities become almost expired, systematic procedures are needed to enable the use of administrative procedures for users' convenience and safety.

• Journal of Dairy Science and Biotechnology
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• v.41 no.1
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• pp.9-25
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• 2023

Yogurt fermentation is known to be beneficial because it provides a low pH and harsh environment for foodborne pathogens and improves organoleptic properties. Additionally, organic acids produced through fermentation have a good effect on the viscosity and gelling properties of yogurt. Several potential health benefits of probiotic and generally recognized as safe strains have been suggested. Yogurt is the preferred vehicle for delivering probiotics to health-conscious consumers. Therefore, manufacturers of probiotic beverages must comply with the relevant regulations. The development of probiotic yogurt begins with the selection of strains with safety and functional properties of probiotics. The selected probiotic strain should be technically suitable for viability and improve organoleptic quality while maintaining the number of bacteria above the standard value during processing and storage conditions. In addition, the efficacy of probiotic strains contained in yogurt should be investigated, confirmed, and approved according to well-designed clinical trials. Although various methods are used to detect probiotic strains, the recently widely used next generation sequencing method can be actively utilized. In the future, more research should be conducted with the latest methods to identify probiotic functions and accurately detect probiotic strains.

• Korean Journal of Ecology and Environment
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• v.55 no.4
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• pp.285-293
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• 2022

Sampling gears for collecting fish are diverse, and the community of fish varies according to the selection and characteristics of the sampling gears. The present study compared the characteristics of fish communities in Yedang reservoir using four sampling gears (kick net, cast net, gill net, and fyke net). The kick net and cast net were inefficient in collecting the number of individuals. However, they increased the species diversity of fish inhabiting the waterfront. Although not many individuals were collected, the gill net mainly collected large fish. The largest number of individuals was collected in the fyke net, and the dominance was high due to the high species selectivity. Through Self-Organizing Map (SOM) analysis, large fish were collected in the gill net, whereas small fish were collected in the fyke net. The characteristics and efficiency of the fish differed depending on the sampling gears. It is expected that researchers will need to use it appropriately according to the characteristics of the sampling gears when investigating the fish community.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.317-321
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• 2022

In response to Incheon tap water accident in 2019, the Ministry of Environment has created the "Comprehensive Measures for Water Safety Management" to improve water operation management, provide systematic technical support, and respond to accidents. Accordingly, K-water is making a smart water supply management system for the entire process of tap water. In order to advance the response to water accidents, it is essential to secure the reliability of real-time water operation data such as flow rate, pressure, and water level, and to develop and apply a warning algorithm in advance using big data analysis techniques. In this paper, various statistical techniques are applied using water supply operation data (flow, pressure, water level, etc) to prepare the foundation for the selection of the optimal operating range and advancement of the monitoring and alarm system. In addition, the arrival time is analyzed through cross-correlation analysis of changes in raw water turbidity between the water intake and water treatment plants. The purpose of this paper is to study the model that predicts the raw water turbidity of a water treatment plant by applying raw water turbidity data considering the time delay according to the flow rate change.

• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.1-11
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• 2023

Smart factory environments and digital twin environments are established, and today's factories accumulate vast amounts of production data and are managed in real time as visualized results suitable for user convenience. Production simulation techniques are in the spotlight as a way to prevent delays in delivery and predict factory volatility in situations where production schedule planning becomes difficult due to the diversification of production products. With the development of the digital twin environment, new packages are developed and functions of existing packages are updated, making it difficult for users to make decisions on which packages to use to develop simulations. Therefore, in this study, the concept of Discrete Event Simulation (DES) performed based on discrete events is defined, and the characteristics of various simulation packages were compared and analyzed. To this end, studies that solved real problems using discrete event simulation software for 10 years were analyzed, and three types of software used by the majority were identified. In addition, each package was classified by simulation technique, type of industry, subject of simulation, country of use, etc., and analysis results on the characteristics and usage of DES software were provided. The results of this study provide a basis for selection to companies and users who have difficulty in selecting discrete event simulation package in the future, and it is judged that they will be used as basic data.

• Journal of Korean Library and Information Science Society
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• v.53 no.1
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• pp.171-190
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• 2022

This study aims to examine the current status of managing elementary school libraries in Busan and suggest the ways to improve it with the viewpoint of 'the five laws of library science'. The scope of study was set as the elementary school libraries in Busan, and the operation status of 304 elementary school libraries was analyzed. And for in-depth investigation, D elementary school library was examined as a case. The operation status of elementary school libraries in Busan was analyzed with the analysis elements; existence of school library, placement of teacher librarian, library collection, annual use, budget, and library seats for 6 years from 2016 to 2021. As a result, especially the placement rate of full-time teacher librarians was only 10.5%, indicating that the problem of manpower shortage was serious. As case study, the current state of managing D elementary school library was deeply investigated with perspectives of the first law and the third law of library science among Ranganathan's five laws of library science. With the first law, the investigation was divided into the aspects of open-shelf system, library location, library hours, furniture, and staff. With the third law, the investigation was done as the aspects of shelf arrangement, catalog, extended service, book selection. Especially, books with more than 50 copies for the program of reading one book each semester accounted for 4.8% of the total collection, showing the problem of unbalanced collection. As the result of this study, 'expanding the placement of teacher librarians', 'making better reading environment through remodeling', and 'balanced collection development' were suggested as the ways of developing school libraries.