• Journal of the Korean Applied Science and Technology
• /
• v.39 no.5
• /
• pp.674-682
• /
• 2022

This study aims to examine the relationship between hyperuricemia and metabolic syndrome, which is a risk to health, and to analyze the effect of hyperuricemia on the body. The analysis data were downloaded and used for the 8th 2nd (2020) data of the National Health and Nutrition Survey, and in this study, 2,320 men and 2,893 women were finally analyzed. For the analysis of the data, Chi-square test and t-test were used for the difference values according to collected general characteristics and hyperuricemia, and the risk of eGFR rise was analyzed by regression analysis, and Pearson correlation was used to confirm the correlation with each variable. Through this study, it was found that hyperuricemia is significantly related to metabolic syndrome, and through this, preemptive management is needed to prevent metabolic syndrome from worsening into vascular diseases including kidney diseases. Therefore, it is proposed to develop a health program suitable for the patient's age through this study.

• Journal of the Korea Safety Management & Science
• /
• v.24 no.4
• /
• pp.49-59
• /
• 2022

Mt. Umyeon is a low-altitude mountain near a residential area, and the actual forest area is not large due to the fact that development for use as a living green space is being completed and in progress across the mountain, so the buffering action for landslides was weak. The unit was located at the top of Mt. Umyeon, and there were reports of contents related to the military unit in some accident areas. Some experts suggested that the landslide that started on the cut side of the unit could be one of the causes of the landslide at Mt. Umyeon. It is presumed that there was a sudden collapse of trees that had fallen due to erosion inside the valley. In the case of the Umyeon landslide, localized torrential rain is the biggest cause, but the fact that it suffered a lot of damage is the result of no preemptive measures. In particular, it can be said that the damage was caused by the concentration of residential and commercial facilities due to the unplanned urban expansion without prior review of the feng shui geography of settlement areas. The important lesson we have learned is that we should recognize nature as living things and live in harmony and coexistence between humans and nature through understanding and cooperation. Adapting to changes in the environment can survive, but if it doesn't, it will be slaughtered. As such, geography influences changes in feng shui. Changes in feng shui have a profound effect on not only humans but also the natural ecosystem.

• Smart Structures and Systems
• /
• v.29 no.1
• /
• pp.181-193
• /
• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Journal of Korean Society of Disaster and Security
• /
• v.16 no.1
• /
• pp.13-22
• /
• 2023

The importance of preemptive flood preparation is growing as the importance of preparing for climate change increases due to record heavy rains in the Seoul metropolitan area in August 2022. Although it is responding to flood control through reservoirs and sediment sites, the government is preparing excellent spill reduction measures through a preliminary consultation system for Low Impact Development (LID). In this study, the depth of flooding was simulated when LID technologies were applied to the Sillim 2-drain region in Dorimcheon Stream basin, an urban stream, using XP-SWMM, a two-dimensional model. In addition, the analysis and applicability of the effect of reducing rainfall runoff for the largest rainfall in a day were reviewed, and it was judged to be effective as a method of reducing flooding in urban areas. Although there is a limitation in which the reduction effect is overestimated, it is thought that the LID technologies can be a significant countermeasure as a countermeasure for small-scale flooded areas where some flooding occurs after structural flooding measures are established.

• The Journal of the Convergence on Culture Technology
• /
• v.6 no.4
• /
• pp.379-384
• /
• 2020

The purpose of this study is to analyze the impact of individual savings banks' financial conditions on their loan portfolio after savings bank restructuring. The analysis results are as follows. First, it was estimated that the relationship between the rate of change in the NPL Ratio and the ratio of household loans has a significant positive value. Second, it was estimated that the interaction effect between the rate of change in the ratio of fixed and below loans and the spread of the deposit-to-deposit rate has a significant negative (-) value with the household loan weight. Third, the relationship between the asset size and the proportion of household loans was estimated to have a significant positive (+) value. In other words, it was analyzed that the financial situation of the savings bank affects the loan portfolio, and it should provide important implications for establishing policies for each financial situation of the savings bank. Depending on the financial situation in the future, there is a need to avoid excessive asset expansion of specific loans and preemptive soundness management.

• Journal of Distribution Science
• /
• v.13 no.2
• /
• pp.75-83
• /
• 2015

Purpose - This study aims to identify the effects of communication cues, anonymity, and social presence on group polarization in computer-mediated communication (CMC) settings. Extant literature has introduced some theoretical backgrounds of social presence and SIDE (Social Identity model of Deindividuation Effects) to explain the effects of communication cues and anonymity. The concept of social presence emphasized the mediating role on communication cues and anonymity. However, most literature did not measure social presence and compare group polarization of all condition groups. This does not sufficiently explain the result of group polarization. Research design, data, and methodology - We believe that the direct impact of anonymity on group polarization can provide a more admissible and clearer explanation for the results. In addition, this study categorizes anonymity into two levels, as anonymity of group and anonymity of self. To justify the anonymity view, a laboratory experiment was conducted. The experiment was conducted in communication cues settings (visual cue; without visual cue) and anonymity settings (identified; anonymous). Each of the four settings has 10 groups consisting of five subjects each (total 200 subjects). The subjects are undergraduates from a large university, majoring in business. All experimental procedures and calculations of choice shift and preference change follow the literature. Results - First, the removal of visual cues does not produce a significant impact on group polarization, which cannot be explained by the social presence view. Second, the anonymous condition does not significantly affect group polarization, which also cannot be explained by the social presence view. However, the anonymous condition directly affects group polarization. Specifically, anonymity of self has a stronger effect on group polarization than anonymity of group. The result explains about the leading factor affecting group polarization. This study examines another view of how computer-mediated communication may be associated with group polarization. The process and outcome data from the experiment reveal that group polarization is not affected by level of social presence, but by level of anonymity. Group discussions conducted with visual cue CMC setting and identified CMC setting result in weaker group polarization. Conversely, group discussions conducted without visual cue CMC setting and anonymous CMC setting lead to stronger group polarization. The results of the study have the following implications. First, they provide clues for business organizations to design the most appropriate media conditions and preemptive social conditions to implement when making group decisions through CMC, to maximize achievements, generate amicable agreements, or actively share information. Second, this study can be useful in analyzing different adverse effects generated through Internet use. Conclusions - This research can help explain discussions and decision-making actions on Internet forums, which have recently increased, as well as providing a foundational basis in newly establishing policies for the forums. Finally, it should be noted that many other factors such as group size, topics, and group history may affect group polarization. These should be examined in future studies.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.4
• /
• pp.611-616
• /
• 2018

With the recent increase in awareness of the diversification of patterns of warfare and security, technological evolution is occurring in the field of autonomous defense robots. As defense science and technology develops with the development of the concept of military utilization focusing on human lives and economic operation, the importance of autonomous robots in the effect-oriented future battlefield is increasing. The major developed countries have developed core technologies, investment strategies, priorities, data securing strategies and infrastructure development related to the field of autonomous defense robots, and research activities such as technology planning and policy strategy for autonomous defense robots in Korea have already begun. In addition, the field of autonomous defense robots encompasses technologies that represent the fourth industrial revolution, such as artificial intelligence, big data, and virtual reality, and so the expectations for this future area of technology are very high. It is difficult to predict the path of technological development due to the increase in the demand for new rather than existing technology. Moreover, the selection and concentration of strategic R&D is required due to resource constraints. It is thought that a preemptive response is needed. This study attempts to derive 6 new technologies that will shape the future of autonomous defense robots and to obtain meaningful results through an empirical study.

• Journal of Distribution Research
• /
• v.15 no.5
• /
• pp.127-153
• /
• 2010

This study explores the locomotives of the growth in the Korean online shopping industry upon the theoretical basis based on the last 10 years' rapid changing environment. This attempt reveals the counter-arguments against preemtive effects based on the observation of reintermediation process in the online industry. We reviewed the NEBIC model proposed by Wheeler(2002) and propose the growth model, double helix framework based on the dynamic capability view. Furthermore the relevance of the proposed framework was validated with the review of last 10 years' sales and market share data in the online shopping industry. Meanwhile we found the limits of online market growth with the open market domination. So future of the online shopping retailers is depending on the development of the channel functions and merchandising on the basis of self-capability. Based on the tentative conclusion, we also suggest implications for the policy makers. Firstly policy facilitating the specialization of the power sellers incubased in the open market is necessary for the sustainable online market growth. And the establishment of the control tower is suggested to coordinate the consistency of the policies and regulations. And the device of the incentive is also proposed to strengthen the open markets' function to facilitate the small and medium online merchants.

• Journal of the Korean Geotechnical Society
• /
• v.34 no.7
• /
• pp.17-27
• /
• 2018

Sinkholes have occurred in various places around the world and concerns about public safety have been raised in recent years. Particularly, a ground subsidence may occur due to a variety of conditions when developing underground spaces. Ground subsidence refers to the sinking of the Earth's surface caused by the loss of the soil constituting ground due to a certain artificial cause in the ground. Ground subsidence is induced by artificial causes such as the leakage of water supply/sewage pipes and groundwater disturbance, and it is different from a sinkhole, where the sinking of the Earth's surface is induced by the cavity formed due to the melting of limestone in the ground with limestone bedrock. In recent underground development in the urban areas of Korea, damages to surrounding buildings have frequently led to many difficulties with civil complaints and compensation issues, and the collapse of some buildings has resulted in the loss of lives and property. Accordingly, the central government has legislated the Special Act on Underground Safety Management, which will take effect from January 1, 2018. This law specifies an underground safety management system for securing underground safety, under which underground safety impact assessment is performed for projects involving underground excavation work that exceeds a certain size, and safety inspection is regularly performed for underground facilities and the surrounding ground. In this study, the contents of the special act on underground safety management are reviewed, and the direction of development of underground safety policy for preparing preemptive underground safety management preparation and response system is suggested.

• The Journal of Bigdata
• /
• v.3 no.2
• /
• pp.19-33
• /
• 2018

Owing to the increase of FTA, food trade, and versatile preferences of consumers, food import has increased at tremendous rate every year. While the inspection check of imported food accounts for about 20% of the total food import, the budget and manpower necessary for the government's import inspection control is reaching its limit. The sudden import food accidents can cause enormous social and economic losses. Therefore, predictive system to forecast the compliance of food import with its preemptive measures will greatly improve the efficiency and effectiveness of import safety control management. There has already been a huge data accumulated from the past. The processed foods account for 75% of the total food import in the import food sector. The analysis of big data and the application of analytical techniques are also used to extract meaningful information from a large amount of data. Unfortunately, not many studies have been done regarding analyzing the import food and its implication with understanding the big data of food import. In this context, this study applied a variety of classification algorithms in the field of machine learning and suggested a data preprocessing method through the generation of new derivative variables to improve the accuracy of the model. In addition, the present study compared the performance of the predictive classification algorithms with the general base classifier. The Gaussian Naïve Bayes prediction model among various base classifiers showed the best performance to detect and predict the nonconformity of imported food. In the future, it is expected that the application of the abnormality detection model using the Gaussian Naïve Bayes. The predictive model will reduce the burdens of the inspection of import food and increase the non-conformity rate, which will have a great effect on the efficiency of the food import safety control and the speed of import customs clearance.