• Journal of the Korean Geosynthetics Society
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• v.20 no.1
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• pp.45-55
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• 2021

In this study, the behavioral characteristics of the fill dam were analyzed during water level fluctuations through a numerical analysis model, and the reservoir safety management plan was prepared. The variation in plastic deviatoric strain, horizontal displacement, stress path, pore water pressure, etc., due to elevation of water level in the upper and lower sides of shell and core were analyzed using numerical analysis software, viz. GTS NX and LIQCA. The analysis results manifest that as the water level in the dam body increases rapidly, the pore water pressure and displacement also increase quickly. It was found that the elevation of the water level causes an increase in pore water pressure in the dam body as well as an increase in the saturation of the dam body and decreased effective stress. It is considered that this type of dam behavior can be the cause of the reduction of strength and stiffness of the dam. Also, it is assumed that the accumulated plastic deviatoric strain due to the deformation of the dam body caused by water infiltration causes an increase in displacement. Based on these experimental results and the results of analyses of the existing reservoir safety diagnosis techniques, an improvement plan for dam safety diagnosis and evaluation criteria was proposed, and these results can be used as primary data while revising dam safety diagnosis guidelines.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.118-125
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• 2021

In this study Orostachys japonica A. Berger used is a medicinal herb that has long been used as a folk remedy for cancer treatment. In this study, the antioxidant efficacy of the ethyl acetate fraction of Orostachys japonica A. Berger was confirmed. The results of the Orostachys japonica A. Berge ethyl acetate fraction of antioxidant activity assays showed Antioxidant effect of Orostachys japonica A. Berger EtOAc fraction extract at 0.10 mg/mL was showed a DPPH radical scavenging rate of 78.54% and ABTS+ radical scavenging rate of 73.48%. Also, the toxicity result of Orostachys japonica A. Berger EtOAc fraction extracts using alternative experimental animal model zebrafish, confirmed a 100% the survival of the zebrafish embryo was shown that there was no coagulation and no hatching delay at all concentrations. also ROS generation induced by UV-B irradiation was confirmed that the fluorescence intensity decreased as a whole in all larvae treated with Orostachys japonica A. Berger EtOAc fraction extracts. In particular, it was confirmed that ROS generation was effectively suppressed by showing a 35.7% reduction rate compared to the positive control at a concentration of 3 ㎍/mL. These results were confirmed that Orostachys japonica A. Berger EtOAc fraction extracts has the possibility of application in the cosmetics field as a natural antioxidant.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.616-625
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• 2021

Deep neural networks are an approximation method that approximates an arbitrary function to a linear model and then repeats additional approximation using a nonlinear active function. In this process, the method of evaluating the performance of approximation uses the loss function. Existing in-depth learning methods implement approximation that takes into account loss functions in the linear approximation process, but non-linear approximation phases that use active functions use non-linear transformation that is not related to reduction of loss functions of loss. This study proposes parametric activation functions that introduce scale parameters that can change the scale of activation functions and location parameters that can change the location of activation functions. By introducing parametric activation functions based on scale and location parameters, the performance of nonlinear approximation using activation functions can be improved. The scale and location parameters in each hidden layer can improve the performance of the deep neural network by determining parameters that minimize the loss function value through the learning process using the primary differential coefficient of the loss function for the parameters in the backpropagation. Through MNIST classification problems and XOR problems, parametric activation functions have been found to have superior performance over existing activation functions.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.356-366
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• 2021

The high-tech industry, a leader in the national economy, has a larger investment cost compared to general buildings, a shorter construction period, and requires continuous investment. Therefore, accurate construction cost prediction and quick decision-making are important factors for efficient cost and process management. Overseas, the construction information classification system has been standardized since 1980 and has been continuously developed, improving construction productivity by systematically collecting and utilizing project life cycle information. At domestic construction sites, attempts have been made to standardize the classification system of construction information, but it is difficult to achieve continuous standardization and systematization due to the absence of a standardization body and differences in cost and process management methods for each construction company. Particular, in the case of the high-tech industry, the standardization and systematization level of the construction information classification system for high-tech facility construction is very low due to problems such as large scale, numerous types of work, complex construction and security. Therefore, the purpose of this study is to construct a construction information classification system suitable for high-tech facility construction through collection, classification, and analysis of related project data constructed in Korea. Based on the WBS (Work Breakdown Structure) and CBS (Cost Breakdown Structure) classified and analyzed through this study, a code system through hierarchical classification was proposed, and the cost model of buildings by linking WBS and CBS was three-dimensionalized and the utilized method was presented. Through this, an information classification system based on inter-relationships can be developed beyond the one-way tree structure, which is a general construction information classification system, and effects such as shortening of construction period and cost reduction will be maximized.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.1
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• pp.13-20
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• 2022

Aircraft weight is an important factor affecting performance and fuel efficiency. In the conceptual design stage of the aircraft, the process of balancing cost and weight is performed using empirical formulas such as fuel consumption cost per weight in estimating element weight. In addition, when an airline operates an aircraft, it promotes fuel efficiency improvement, fuel saving and carbon reduction through weight management activities. The relationship between changes in aircraft weight and changes in fuel consumption is called the cost of weight, and the cost of weight is used to evaluate the effect of adding or reducing weight to an aircraft on fuel consumption. In this study, the problems of the existing cost of weight calculation method are identified, and a new cost of weight calculation method is introduced to solve the problem. Using Breguet's Range Formula and actual flight data of the A350-900 aircraft, two weight costs are calculated based on take-off weight and landing weight. In conclusion, it was suggested that it is reasonable to use the cost of weight based on the take-off weight and the landing weight for other purposes. In particular, the cost of weight based on the landing weight can be used as an empirical formula for estimating element weight and optimizing cost and weight in the conceptual design stage of similar aircraft.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.215-224
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• 2022

This study tried to examine the effect of cost asymmetry on food service companies and what characteristics affect such cost behavior. This study analyses cost behavior for cost of good sold, selling, general and administrative cost over the 2019-2020 period. Also, the rate of change in activity level was measured using change in sales. This study measures the behavior of cost using the research model of [1]. As a result of the analysis, it was found that food service companies exhibited cost asymmetric behavior as their sales level decreased. In addition, the cost asymmetric behavior has been strengthened since the corona virus, and the shorter the operating cycle. Lastly, the shorter the inventory holding period and the collection period of accounts receivable, which are components of the operating cycle, more strengthen asymmetric behavior of costs. These results seem to be meaningful in examining the cost structure and factors that may affect the structure for food service industry. This has approached the cost aspect of the situation faced by service food companies due to COVID-19, and it can be suggested that this pandemic can lead to cost reduction due to a decrease in corporate sales.

• Journal of Korea Water Resources Association
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• v.55 no.3
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• pp.205-215
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• 2022

Amidst the global climate crisis, dam operation policies formulated under the stationary climate assumption could lead to unsatisfactory water management. In this work, we assessed status-quo performance of the Yongdam Dam in Korea under various climatic stresses in flood risk reduction and water supply reliability for 2021-2040. To this end, we employed a decision-centric framework equipped with a stochastic weather generator, a conceptual streamflow model, and a machine-learning reservoir operation rule. By imposing 294 climate perturbations to dam release simulations, we found that the current operation rule of the Yongdam dam could redundantly secure water storage, while inefficiently enhancing the supply reliability. On the other hand, flood risks were likely to increase substantially due to rising mean and variability of daily precipitation. Here, we argue that the current operation rules of the Yongdam Dam seem to be overly focused on securing water storage, and thus need to be adjusted to efficiently improve supply reliability and reduce flood risks in downstream areas.

• Smart Media Journal
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• v.11 no.5
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• pp.9-16
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• 2022

Recently, agricultural sites are automating into digital agricultural smart farms by applying technologies such as big data and Internet of Things (IoT). These smart farms aim to increase production and improve crop quality by measuring the environment of crops, investigating and processing data. Production prediction is an important study in smart farm digital agriculture, which is a high-tech agriculture, and it is necessary to analyze environmental data using big data and further standardized research to manage the quality of growth information data. In this paper, environmental and production data collected from smart farm strawberry farms were analyzed and studied. Based on regression analysis, crop production prediction models were analyzed using Ridge Regression, LightGBM, and XGBoost. Among the three models, the optimal model was XGBoost, and R2 showed 82.5 percent explanatory power. As a result of the study, the correlation between the amount of positive fluid absorption and environmental data was confirmed, and significant results were obtained for the production prediction study. In the future, it is expected to contribute to the prevention of environmental pollution and reduction of sheep through the management of sheep by studying the amount of sheep absorption, such as information on the growing environment of crops and the ingredients of sheep.

• Korean Journal of Construction Engineering and Management
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• v.23 no.4
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• pp.15-25
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• 2022

As the incidence and mortality of serious disasters in the construction industry are the highest, various efforts are being made in Korea to reduce them. Among them, risk assessment is used as data for disaster reduction measures and evaluation of risk factors at the construction stage. However, the existing risk assessment involves the subjectivity of the performer and is vulnerable to the domestic construction site. This study established a DB classification system for risk assessment with the aim of early identification and pre-removal of risks by quantitatively deriving risk factors using BIM in the risk assessment field and presents a methodology for risk assessment using BIM. Through this, prior removal of risks increases the safety of construction workers and reduces additional costs in the field of safety management. In addition, since it can be applied to new construction methods, it improves the understanding of project participants and becomes a tool for communication. This study proposes a framework for deriving quantitative risks based on BIM, and will be used as a base technology in the field of risk assessment using BIM in the future.

• Korean small business review
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• v.42 no.4
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• pp.251-283
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• 2020

The purpose of this study is to provide assistance to the establishment of related policies to improve the level of acceptance and use of smart factories for SMEs in Korea. To this end, the Unified Technology Acceptance Model (UTAUT) was extended to select additional factors that could affect the intention to accept technology, and to demonstrate this. To achieve the research objective, a questionnaire composed of 7-point Likert scales was prepared, and a survey was conducted for manufacturing-related companies. A total of 136 questionnaires were used for statistical processing. As a result of the hypothesis test, performance expectation and social influence had a positive (+) positive effect on voluntary use, but effort expectation and promotion conditions did not have a significant effect. As an extension factor, the network effect and organizational characteristics had a positive (+) effect, and the innovation resistance had a negative effect (-), but the perceived risk had no significant effect. When the size of the company is large, the perceived risk and innovation resistance are low, and the level of influencing factors for veterinary intentions, veterinary intentions, and veterinary behaviors are excluded. Through this study, factors that could have a positive and negative effect on the adoption (reduction) of smart factory-related technologies were identified and factors to be improved and factors to be reduced were suggested. As a result, this study suggests that smart factory-related technologies should be accepted.