• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.55-78
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• 2021

Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.

• Journal of Practical Agriculture & Fisheries Research
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• v.24 no.3
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• pp.15-24
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• 2022

In 2000, a total of 23,794ha of forest was lost due to the East Coast forest fire, and about 70% of the damaged area was concentrated in Samcheok. In 2001, artificial restoration and natural restoration were implemented in the damaged area. This study was conducted to understand the current vegetation structure 21 years after the restoration of forest fire damage in the Samcheok, Gumbong Mountain area. As a result of classifying the vegetation community, it was divided into three communities: Quercus variabilis-Pinus densiflora community, Pinus densiflora-Quercus mongolica community, and Pinus thunbergii community. Quercus variabilis, Pinus densiflora, and Pinus thunbergii planted in the artificial restoration site were found to continue to grow as dominant species in the local vegetation after restoration. As for the species diversity index of the community, the Quercus variabilis-Pinus densiflora community dominated by deciduous broad-leaf trees showed the highest, and the coniferous forest Pinus thunbergii community showed the lowest. Vegetation in areas affected by forest fires is greatly affected by reforestation tree species, and 21 years later, it has shown a tendency to recover to the forest type before forest fire. In order to establish DataBase for effective restoration and to prepare monitoring data, it is necessary to construct data through continuous vegetation survey on the areas affected by forest fires.

• Economic and Environmental Geology
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• v.56 no.2
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• pp.125-138
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• 2023

Most of previous cesium (Cs) sorbents have limitations on the treatment in the large-scale water system having low Cs concentration and high ion strength. In this study, the new Cs sorbent that is eco-friendly and has a high Cs removal efficiency was developed by improving the coal mine drainage treated sludge (hereafter 'CMDS') with the addition of Na and S. The sludge produced through the treatment process for the mine drainage originating from the abandoned coal mine was used as the primary material for developing the new Cs sorbent because of its high Ca and Fe contents. The CMDS was improved by adding Na and S during the heat treatment process (hereafter 'Na-S-CMDS' for the developed sorbent in this study). Laboratory experiments and the sorption model studies were performed to evaluate the Cs sorption capacity and to understand the Cs sorption mechanisms of the Na-S-CMDS. The physicochemical and mineralogical properties of the Na-S-CMDS were also investigated through various analyses, such as XRF, XRD, SEM/EDS, XPS, etc. From results of batch sorption experiments, the Na-S-CMDS showed the fast sorption rate (in equilibrium within few hours) and the very high Cs removal efficiency (> 90.0%) even at the low Cs concentration in solution (< 0.5 mg/L). The experimental results were well fitted to the Langmuir isotherm model, suggesting the mostly monolayer coverage sorption of the Cs on the Na-S-CMDS. The Cs sorption kinetic model studies supported that the Cs sorption tendency of the Na-S-CMDS was similar to the pseudo-second-order model curve and more complicated chemical sorption process could occur rather than the simple physical adsorption. Results of XRF and XRD analyses for the Na-S-CMDS after the Cs sorption showed that the Na content clearly decreased in the Na-S-CMDS and the erdite (NaFeS₂·2(H₂O)) was disappeared, suggesting that the active ion exchange between Na⁺ and Cs⁺ occurred on the Na-S-CMDS during the Cs sorption process. From results of the XPS analysis, the strong interaction between Cs and S in Na-S-CMDS was investigated and the high Cs sorption capacity was resulted from the binding between Cs and S (or S-complex). Results from this study supported that the Na-S-CMDS has an outstanding potential to remove the Cs from radioactive contaminated water systems such as seawater and groundwater, which have high ion strength but low Cs concentration.

• Journal of agricultural medicine and community health
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• v.49 no.3
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• pp.257-270
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• 2024

Objective: This study aimed to empirically evaluate the effectiveness of chronic disease management services utilizing ICT for patients with chronic illnesses. Methods: From May to December, 2023, 452 people who were diagnosed with hypertension and diabetes at 9 participating public health centers were provided with customized health care services for 24 weeks, and 15 performance indicators were analyzed to evaluate their effectiveness. Results: Health behavior indicators and health risk factors decreased before and after participation in the project, blood pressure control rate, hypertension and diabetes management rate, medication compliance, weight, BMI, BP, WC, FBG, and HDL-cholesterol improved(p<0.001). Service factors that influence the improvement of health behaviors included the number of activity monitor transmissions(p=0.049), confirmed concentrated consultations on physical activity(p=0.003) and nutrition(p=0.005), and the adherence to medication missions for hypertension(p=0.020). As for service factors influencing chronic disease management, the improvement in blood pressure regulation rate was due to the number of times the blood pressure monitor was linked(p=0.004), and the number of confirmed intensive consultations on physical activity(p=0.026), and nutrition(p=0.049); the improvement in hypertension control rate was due to the number of times the activity monitor and blood pressure monitor were linked(p<0.001), and the number of hypertension medication missions carried out (p=0.004); and the improvement in diabetes control rate was due to the number of times the blood pressure monitor(p=0.022) and blood sugar system were linked(p=0.017). Conclusion: Although this study has limitations as a comparative study before and after the service, it has proved that chronic disease management using ICT has a positive effect on improvement of health behavior indicator, reduction of health risk factors, hypertension, diabetes management index, weight, BMI, TG, BP, FBG improvement.

• Korean Journal of Childcare and Education
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• v.10 no.3
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• pp.5-29
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• 2014

The purpose of this study was to find out various problem behaviors of children who were not diagnosed with any disability, but instead, engaged in problem behaviors. This study also intended to review the difficulties of children with problem behaviors, their teachers' difficulties and needs, to suggest support for child care and education teachers. This study conducted semi-structured qualitative interviews with eight child care and education teachers. The interviews were transcribed into text and analyzed by contents. The results of this study are as follows. Problem behaviors of children described by teachers were classified into external and internal types. In addition, children with problem behaviors had experienced difficulties in maintaining relationships with their teachers, peers and parents. Many teachers were not successful to provide appropriate support for preschoolers who demonstrated problem behaviors in classrooms or some teachers provided individualized support. Teachers adapted the behavioral and the psychological approaches to problem behaviors of preschoolers. However, teachers reported difficulties with children with problem behavior and brought up the following issues on teaching children with problem behaviors; managing troubled matters happening in the class, difficulty in controlling teacher's emotions on problem behaviors, the lack of time, the integrated child care time without teacher in charge of child, the interruption in activity progress, the lack of a special way to deal with problem behaviors, and difficulty in cooperation with families through parents-teacher counseling sessions. Teachers counseled with parents who had a child with problem behaviors and revealed that parents reacted to problem behaviors in various ways such as embarrassment, acceptance, ignorance, or avoidance. Most teachers received assistance and support for teaching children with problem behaviors, from families, local communities and in-service training. Lastly, teachers with preschoolers with problem behaviors needed the support of experts on managing behavior problems, assistant teaching personnel, education for parents and teachers, respects for teachers, psychological counseling or play therapy from professional service agencies, diagnosis service at child care and education centers which children attended, and support networking with agencies. Teachers also required the family support of medical diagnosis and psychological counseling and financial support from the government.

• Journal of Korean Home Economics Education Association
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• v.26 no.4
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• pp.115-128
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• 2014

The purpose of this study was to investigate home economics teachers' perception of cultural diversity education, to provide an efficient educational material for the multicultural education in teacher education and teacher retraining. 160 Home economics teachers answered the survey questionnaires. To analyze the data, SPSS 19.0 for Windows was used to conduct frequency analysis, factorial analysis, credibility analysis, t-test, one-way ANOVA, and Duncan's multiple comparison. The results of this study were as follows. Four dimensions of cultural diversity education were derived by factor analysis: cultural equality, diversity implementation, diversity value, comfort with diversity. As for their awareness about cultural diversity education, it was in the order of cultural equality, followed by diversity implementation, diversity value, and comfort with diversity. The groups were significantly different according to demographic variables. As for the whole awareness about cultural diversity education and the diversity implementation, group of age 40 teachers recognized more highly than other groups. Furthermore, teachers outside Jeonbuk area recognized more highly the cultural equality, diversity implementation, diversity value than those in Jeonbuk, which is the 3rd high area in the nation of multicultural family proportion. As for cultural equality and diversity implementation, teachers over 15 years of experience, recognized more highly than other groups. Those with the teacher certification in the college of education, recognized more highly the cultural equality, diversity value, comfort with diversity than teachers from the other colleges. Teachers who need multicultural education, recognized more highly cultural equality, diversity implementation, awareness of diversity than those who don't. These results imply that in home economics education, there must be more systematic studies on school field education and related educational programs in order to revitalize multicultural education. And for teachers with highly recognizing cultural diversity to conduct a systematic multicultural education more efficiently, there should be both systematic pre-service education programs at college level and in-service education programs for the teachers in terms of cultural diversity education.

• Korean Journal of Environmental Agriculture
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• v.34 no.2
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• pp.134-138
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• 2015

BACKGROUND: In recent years, several researchers have focused on odour control methods to remove the harmful chemicals from chemical accidents and incidents. The present work deals with the system development of the hazardous. METHODS AND RESULTS: For on-site removal of hazardous gaseous materials from chemical accidents, mobile vortex wet scrubber was designed with water vortex process to absorb the gas into the water. The efficiency of the mobile vortex wet scrubber was evaluated using water spray and 25% ammonia solution. The inlet air velocity (gas flow rate) was according to the damper angle installed within the hood and with increase of gas flow rate, consequently the absorption efficiency was markedly decreased. In particular, when 25% ammonia solution was exposed to the hood inlet for 30 min, the water pH within the scrubber was changed from 7 to 12. Interestingly, although the removal efficiency of ammonia gas exhibited approximately 80% for 5 min, its efficiency in 10 min showed the greatest decrease with 18%. Therefore, our results suggest that the ammonia gas may be absorbed with the driving force of scrubbing water in water vortex process of this scrubber. CONCLUSION: When chemical accidents are occurred, the designed compact scrubber may be utilized as effective tool regarding removal of ammonia gas and other volatile organic compounds in the scene of an accident.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.4
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• pp.81-97
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• 2019

The purpose of this study is to examine what people in Korea recognize the cultural symbolism and the planting patterns of 'Guǐmok', pagoda tree(Sophora japonica). The species planted in the 'Guǐjeong' was empirically investigated and analyzed to determine which species of pagoda tree or Zelkova tree(Zelkova serrata) was taken through literature surveys, field surveys, and interviews with persons. This 'Guǐjeong' was combined to track how the culture of the 'Guǐmok' planting introduced in China was ultimately accepted and transformed in Korea. In this study, we tried to analyze the meaning implicit in the mystery while checking the distribution of the mystery and the form of the mystery, the name of the pavilion and its relevance to the contrast medium. Essentially, the trees that govern the characterization of the nectar plant, regardless of the region, are considered to be a pagoda tree, which is considered an internal factor in which the pagoda tree culture was not completely transformed into a zelkova tree. It was recognized throughout the Joseon Dynasty that the species representing 'Prime ministers(三公)' was judged from all the Joseon Dynasty periods, based on the builder of Guǐjeong's Aho(雅號) and Dangho(堂號). It was confirmed that the tree was very likely to be planted in place of the painting tree. But now is selectively zelkova tree is in accordance with the preparation of planting site conditions and areas on behalf of the Change is very high probability that is planted. Cultural variables that led to the cultural transformation of the 'Guǐmok' seem to have been deeply involved in the geographical space of China and Korea, Confucian practices of the Choson society, comings and goings and letter bridge, and network strength with China through the book spread. In addition, the culture of 'Guǐmok' is presumed to have led to cultural custom of the upper class, not the whole class, in the Yeongnam region, it can be said that the independent adaptation to act to recognize 'Guǐmok' as a pagoda tree, that is a Sophora japonica, has occurred very strongly. The difference between the cultural areas of Yeongnam and non-Yeongnam is also considered to be an internal factor that has played a major role in the cultural transformation of planting of 'Guǐmok'.

• Clean Technology
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• v.25 no.4
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• pp.316-323
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• 2019

In order to enhance combustion efficiency and reduce atmosphere pollutants, it is essential to measure carbon monoxide (CO) concentration precisely in combustion exhaust. CO is the important gas species regarding pollutant emission and incomplete combustion because it can trade off with NOx and increase rapidly when incomplete combustion occurs. In the case of a steel annealing system, CO is generated intentionally to maintain the deoxidation atmosphere. However, it is difficult to measure the CO concentration in a combustion environment in real-time, because of unsteady combustion reactions and harsh environment. Tunable Diode Laser Absorption Spectroscopy (TDLAS), which is an optical measurement method, is highly attractive for measuring the concentration of certain gas species, temperature, velocity, and pressure in a combustion environment. TDLAS has several advantages such as sensitive, non-invasive, and fast response, and in-situ measurement capability. In this study, a combustion system is designed to control the equivalence ratio. Also, the combustion exhaust gases are produced in a Liquefied Petroleum Gas (LPG)/air flame. Measurement of CO concentration according to the change of equivalence ratio is confirmed through TDLAS method and compared with the simulation based on Voigt function. In order to measure the CO concentration without interference from other combustion products, a near-infrared laser at 4300.6 cm^-1 was selected.