• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1037-1051
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• 2021

Biochemical oxygen demand (BOD) concentration, one of important water quality indicators, is treated as the measuring item for the ecological chapter in lakes and rivers. This investigation employed novel two-stage hybrid paradigm (i.e., wavelet-based gated recurrent unit, wavelet-based generalized regression neural networks, and wavelet-based random forests) to predict BOD concentration in the Dosan and Hwangji stations, South Korea. These models were assessed with the corresponding independent models (i.e., gated recurrent unit, generalized regression neural networks, and random forests). Diverse water quality and quantity indicators were implemented for developing independent and two-stage hybrid models based on several input combinations (i.e., Divisions 1-5). The addressed models were evaluated using three statistical indices including the root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), and correlation coefficient (CC). It can be found from results that the two-stage hybrid models cannot always enhance the predictive precision of independent models confidently. Results showed that the DWT-RF5 (RMSE = 0.108 mg/L) model provided more accurate prediction of BOD concentration compared to other optimal models in Dosan station, and the DWT-GRNN4 (RMSE = 0.132 mg/L) model was the best for predicting BOD concentration in Hwangji station, South Korea.

• Industry Promotion Research
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• v.7 no.1
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• pp.17-23
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• 2022

The purpose of this study is to verify the relationship between parents' adult attachment, resilience, and psychological well-being, as it is inferred that infants and toddlers attending daycare centers will be directly or indirectly affected by their parents' adult attachment type. For this study, a total of 247 copies of the SPSS 12.0 statistical program were used for analysis, except for 43 copies where data were omitted after a questionnaire was conducted on 300 parents (150 parents and 150 mothers) of daycare centers located in Gyeonggi Province. Looking at the results of this study, first, it was confirmed that the general characteristics of parental adult attachment, self-recovery elasticity, and psychological well-being stimulate normality statistically. Second, the relationship between adult attachment and self-recovery elasticity was verified as a negative relationship, and it was confirmed that it had a significant effect. Third, it was confirmed that the relationship between adult attachment and psychological well-being was verified as a negative relationship and had a significant effect. As a follow-up study, we propose a phenomenological study of the mediating effect of psychological well-being on the influence of parents' adult attachment on self-recovery elasticity, parental attachment, resilience, and psychological well-being with infants and toddlers.

• Journal of Popular Narrative
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• v.26 no.2
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• pp.157-190
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• 2020

How is the "Yonsei University Incident" of August 1996 remembered from a periphery perspective and a gender perspective? With this question in mind, I reviewed the history of the revolution and the missing memories in the period from 1996 to 2016 in Korean literature. I tried to recover the story of the revolution experienced and remembered by those who were politically invisible or gender-excluded, by centering on novels with strange reminiscences of the student movement in 1996, namely Yoon I-Hyung's "Big Wolf Blue" ("Big Wolf Blue", 2011), Choi Eun-Young's "Responsibility"(2018), Hwang Jung-Eun's Didi's Umbrella (2019) and Park Sang- Young's "A piece of Rockfish Sashimi The Taste of the Universe"(How to Love in Metropolis, 2019). There is a correlation between the perception of the periphery and the name of the "unrememberable" revolution. And this fact tells us that revolution does not mean the same thing to everyone, even when it "passes" through the midst of a revolution that shares the imagination of a better society and the desire to reorganize the system. In other words, it emphasizes that the logic of exclusion and hierarchy was still in operation even at the moment of revolution. It would be said that this review is not only a rethinking of the student movement, but also a reevaluation from the gender perspective of Korean society in the 1990s.

• Journal of Popular Narrative
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• v.27 no.3
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• pp.53-94
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• 2021

This article pays attention to the gender representation of an abominable male abject that reveal class polarization in the movie Parasite. I seeks to read a new aspect of emotional politics in which a precariat man becomes a male patriarch while representing himself with an abhorrent position. Parasite shows a reversal of daughter and son responsible for parents, contrary to the existing family narrative. They teaches the parents' generation how to survive neoliberal that their place is created only when they take away others' place. However, after losing this prospect, Ki-woo confesses to his father that he is sorry first. Ki-taek also attempted to identify Dong-ik with the patriarch, but this male solidarity collapsed by class and committed murder in sudden anger. As a result, Gi-taek goes down to the hateful status of a stinking underground life, and Ki-woo receives a message of ethical reflection from his isolated father. The film gives the father and son the noble status of ethical fighter who fought against the structure of class polarization, especially the ending epilogue and narration emphasizing the ethical responsibility and mutual solidarity between father and son. In this process, the voices of female characters are gradually omitted, blurring gender screening for male characters. Parasite reveals the political reenactment strategy of precariat men in the age of neoliberalism, which is ethical subject by claiming to be a class abject himself. And representing the hate with gender-selecting, it is beautifying the responsible ethics of the patriarch.

• Journal of Korea Entertainment Industry Association
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• v.14 no.6
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• pp.243-250
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• 2020

The purpose of this study was to investigate the effects of the satisfaction of college students majoring in healthcare-related fields with their major and with their clinical practice on their career decision-making level and to investigate the mediating effect of their satisfaction with clinical practice on the relationship between their satisfaction with their major and their career decision-making level. The subjects were 180 college students who had completed clinical practice as part of their healthcare-related majors at C University in A-gun, B-do Province. Their completed questionnaires were collected between March 2 and March 5, 2020; 165 questionnaires were used for the data analysis. Questionnaires with missing or insincere responses were excluded. According to the results of this study, the students showed a mean of 3.99 points in their satisfaction with their major, 3.33 points in their career decision-making level, and 3.71 points in their satisfaction with clinical practice. Statistically significant positive correlations were found between the students' satisfaction with their major, their career decision-making level, and their satisfaction with clinical practice. In addition, their satisfaction with clinical practice produced a partial mediating effect on the relationship between their satisfaction with their major and their career decision-making level, and those with a higher level of satisfaction with their major and with their clinical practice also presented higher career decision-making levels. Therefore, the present study suggests that healthcare-related students' satisfaction with their major and with clinical practice should be enhanced to increase their career decision-making levels.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.105-118
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• 2022

The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.

• Korean Journal of Clinical Laboratory Science
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• v.54 no.3
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• pp.192-200
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• 2022

The association between heavy metals in the blood and obesity has been examined in many studies. However, inconsistencies have been observed in the results from these studies. The present study was conducted using data from 119,181 participants of the Korea National Health and Nutrition Examination Survey (KNHANES) for 11 years in 2005 and between 2008 and 2017. The subjects with missing heavy metal blood tests, health interview data, and health examination data were excluded from the study. The study population comprised 1,844 individuals (972 men, 872 women) who were eligible for inclusion. It was found that obesity and abdominal obesity were associated with an increase in both blood mercury (P<0.001) and alanine aminotransferase (ALT) (P<0.001). After adjusting the confounding factors, those with concurrent high levels of ALT and the highest tertile of mercury showed an increased risk of obesity (odds ratio 4.46, 95%, confidence interval 2.23~8.90, P<0.001) as well as abdominal obesity (odds ratio 5.36, 95%, confidence interval 2.57~11.17, P<0.001). The interrelationship of mercury and ALT with the parameters of body mass index (P for interaction=0.009) and waist circumference (P for interaction=0.012), respectively, have been observed to be significant, suggesting that the reciprocal relationship could contribute to obesity and abdominal obesity.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.49-59
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• 2022

In this paper, we designed a new enzyme function prediction model PSCREM based on a study that compared and evaluated CNN and LSTM/GRU models, which are the most widely used deep learning models in the field of predicting functions and structures using protein sequences in 2020, under the same conditions. Sequence evolution information was used to preserve detailed patterns which would miss in CNN convolution, and the relationship information between amino acids with functional significance was extracted through overlapping RNNs. It was referenced to feature map production. The RNN family of algorithms used in small CNN-RNN models are LSTM algorithms and GRU algorithms, which are usually stacked two to three times over 100 units, but in this paper, small RNNs consisting of 10 and 20 units are overlapped. The model used the PSSM profile, which is transformed from protein sequence data. The experiment proved 86.4% the performance for the problem of predicting the main classes of enzyme number, and it was confirmed that the performance was 84.4% accurate up to the sub-sub classes of enzyme number. Thus, PSCREM better identifies unique patterns related to protein function through overlapped RNN, and Overlapped RNN is proposed as a novel methodology for protein function and structure prediction extraction.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.45-55
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• 2022

BIM models allow building spaces to be instantiated and recognized as unique objects independently of model elements. These instantiated spaces provide the required semantics that can be leveraged for building code checking, energy analysis, and evacuation route analysis. However, theses spaces or rooms need to be designated manually, which in practice, lead to errors and omissions. Thus, most BIM models today does not guarantee the semantic integrity of space designations, limiting their potential applicability. Recent studies have explored ways to automate space allocation in BIM models using artificial intelligence algorithms, but they are limited in their scope and relatively low classification accuracy. This study explored the use of Graph Convolutional Networks, an algorithm exclusively tailored for graph data structures. The goal was to utilize not only geometry information but also the semantic relational data between spaces and elements in the BIM model. Results of the study confirmed that the accuracy was improved by about 8% compared to algorithms that only used geometric distinctions of the individual spaces.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.181-190
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• 2022

In this paper, we use a LiDAR sensor and an image camera to detect a left-turning waiting vehicle in two ways, unlike the existing image-type or loop-type left-turn detection system, and a left-turn traffic signal corresponding to the waiting length of the left-turning lane. A system that can efficiently assign a system is introduced. For the LiDAR signal transmitted and received by the LiDAR sensor, the left-turn waiting vehicle is detected in real time, and the image by the video camera is analyzed in real time or at regular intervals, thereby reducing unnecessary computational processing and enabling real-time sensitive processing. As a result of performing a performance test for 5 hours every day for one week with an intersection simulation using an actual signal processor, a detection rate of 99.9%, which was improved by 3% to 5% compared to the existing method, was recorded. The advantage is that 99.9% of vehicles waiting to turn left are detected by the LiDAR sensor, and even if an intentional omission of detection occurs, an immediate response is possible through self-correction using the video, so the excessive waiting time of vehicles waiting to turn left is controlled by all lanes in the intersection. was able to guide the flow of traffic smoothly. In addition, when applied to an intersection in the outskirts of which left-turning vehicles are rare, service reliability and efficiency can be improved by reducing unnecessary signal costs.