• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.127-135
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• 2023

This study aimed to develop biomass allometric equations and estimate carbon emission factors, such as the wood density, biomass-expansion factor, and root-to-shoot ratio, for Platanus occidentalis and Metasequoia glyptostroboides planted in urban areas. Twenty M. glyptostroboides and 25 P. occidentalis trees were harvested, and the dry weights and stem volumes of stems, branches, leaves, and roots (>5 mm) were measured. The wood densities of M. glyptostroboides and P. occidentalis were 0.293 ± 0.008 g cm^-3 and 0.509 ± 0.018 g cm^-3, and the biomass-expansion factors were 1.738 ± 0.031 and 1.561 ± 0.035. The root-to-shoot ratios were 0.446 ± 0.009 and 0.402 ± 0.012. The uncertainty tests (coefficient of variation, %) gave 2.8% and 3.5% values for wood density, 1.8% and 2.3% for biomass-expansion factor, and 2.1% and 2.9% for root-to-shoot ratio, respectively. Among the developed allometric equations, Model I using the diameter at breast height (DBH) was suitable. The allometric equations of M. glyptostroboides and P. occidentalis above ground were y = 1.679 (DBH)^1.315 and y = 0.505 (DBH)^1.896, and the allometric equations of the root and total were y = 0.746 (DBH)^1.315, y = 0.301 (DBH)^1.751, y = 2.422 (DBH)^1.316, and y = 0.787 (DBH)^1.858. If the carbon-emission factors of this study and biomass allometric equations of the three developed models are used to estimate the carbon storage and biomass of urban forests, errors caused by not considering the use of fixed factors and the environmental differences can be reduced.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.21-44
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• 2018

In recent years, the rapid development of internet technology and the popularization of smart devices have resulted in massive amounts of text data. Those text data were produced and distributed through various media platforms such as World Wide Web, Internet news feeds, microblog, and social media. However, this enormous amount of easily obtained information is lack of organization. Therefore, this problem has raised the interest of many researchers in order to manage this huge amount of information. Further, this problem also required professionals that are capable of classifying relevant information and hence text classification is introduced. Text classification is a challenging task in modern data analysis, which it needs to assign a text document into one or more predefined categories or classes. In text classification field, there are different kinds of techniques available such as K-Nearest Neighbor, Naïve Bayes Algorithm, Support Vector Machine, Decision Tree, and Artificial Neural Network. However, while dealing with huge amount of text data, model performance and accuracy becomes a challenge. According to the type of words used in the corpus and type of features created for classification, the performance of a text classification model can be varied. Most of the attempts are been made based on proposing a new algorithm or modifying an existing algorithm. This kind of research can be said already reached their certain limitations for further improvements. In this study, aside from proposing a new algorithm or modifying the algorithm, we focus on searching a way to modify the use of data. It is widely known that classifier performance is influenced by the quality of training data upon which this classifier is built. The real world datasets in most of the time contain noise, or in other words noisy data, these can actually affect the decision made by the classifiers built from these data. In this study, we consider that the data from different domains, which is heterogeneous data might have the characteristics of noise which can be utilized in the classification process. In order to build the classifier, machine learning algorithm is performed based on the assumption that the characteristics of training data and target data are the same or very similar to each other. However, in the case of unstructured data such as text, the features are determined according to the vocabularies included in the document. If the viewpoints of the learning data and target data are different, the features may be appearing different between these two data. In this study, we attempt to improve the classification accuracy by strengthening the robustness of the document classifier through artificially injecting the noise into the process of constructing the document classifier. With data coming from various kind of sources, these data are likely formatted differently. These cause difficulties for traditional machine learning algorithms because they are not developed to recognize different type of data representation at one time and to put them together in same generalization. Therefore, in order to utilize heterogeneous data in the learning process of document classifier, we apply semi-supervised learning in our study. However, unlabeled data might have the possibility to degrade the performance of the document classifier. Therefore, we further proposed a method called Rule Selection-Based Ensemble Semi-Supervised Learning Algorithm (RSESLA) to select only the documents that contributing to the accuracy improvement of the classifier. RSESLA creates multiple views by manipulating the features using different types of classification models and different types of heterogeneous data. The most confident classification rules will be selected and applied for the final decision making. In this paper, three different types of real-world data sources were used, which are news, twitter and blogs.

• Journal of the Korean Society of Food Science and Nutrition
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• v.38 no.11
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• pp.1618-1624
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• 2009

This study was conducted to estimate the shelf-life of cooked mung bean sprouts contaminated with Staphylococcus aureus according to storage temperatures after cooking in school foodservice operations. A predictive growth model of S. aureus in cooked mung bean sprouts prepared using a standard recipe was developed at 4 storage temperatures (5, 15, 25, and 35${^{\circ}C}$). To determine the effect of vinegar on the shelf-life of cooked mung bean sprouts, the growth of S. aureus in sprouts prepared using vinegar and the standard recipe were compared. The $R^2$ values of the specific growth rate (SGR) and lag time (LT) determined using the Gompertz model were greater than 0.90 at all temperatures except 5${^{\circ}C}$, which confirmed that it would be appropriate to use these parameters for a secondary model. The secondary model, which indicates changes in LT and SGR values according to storage temperatures, was calculated using response surface models. The compatibility of the developed model was confirmed by calculating $R^2$, Bf, Af and MSE values as statistic parameters. The $R^2$ values of LT and SGR were 0.94 or higher, and the MSE, Bf and Af values were 0.02 and 0.002, 0.97 and 1.03, and 1.31 and 1.10, respectively, with high statistical compatibility. The growth rate of S. aureus was higher when the standard recipe was used than when vinegar was used at all temperatures. Indeed, no growth of S. aureus was observed in mung bean sprouts prepared using vinegar. Based on the model developed, cooked mung bean sprouts prepared using the standard recipe for school foodservice should be stored at 10${^{\circ}C}$ or less. Additionally, sprouts stored at 25 or 35${^{\circ}C}$ should be consumed within 6 or 12 hours after cooking. Finally, the addition of vinegar will prevent the growth of S. aureus in cooked mung bean sprouts.

• Information Systems Review
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• v.18 no.3
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• pp.209-233
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• 2016

Internet companies that utilize social network have increased in number. The introduction of diverse social media services facilitated innovative changes in e-business. Social network service (SNS), which is a domain of social media, is a web-based service designed to strengthen human relations in the Internet and build new social relations. The remarkable growth of social network services and the profit generation and perception of this service are the new growth engines of this digital age. Given this development, many global IT companies views SNS as the most powerful form of social media. Thus, they invest efforts to develop business models using SNS.2) This study verifies the impact of privacy exposure in SNS as a result of privacy invasion. This study examines the purpose of using the SNS and user's awareness of the significance of personal information, which are key factors that affect self-disclosure of personal information. This study utilizes theory of reasoned action (TRA) to provide a theoretical platform that describes the specific behavior and emotional response of individuals. This study presents a research model that considers negative attitude (negatude). In this model, self-disclosure in SNS is considered a TRA. TRA is a subjective norm, a behavioral intention, and a key variable of exposure behavior. A survey was conducted on college students at Y university in Seoul to empirically verify the research model. The students have experiences in using SNS. A total of 198 samples were collected. Path analysis was applied to analyze the relations of factors. The results of path analysis show the statistically insignificant impact of privacy invasion on negatude, subjective norm, behavioral intention, and exposure behavior. The impact of unrecognized privacy invasion was also considered insignificant. The impacts of intention to use SNS on negatude, subjective norm, behavioral intention, and exposure behavior was significant. A significant impact was also found for the significance of personal information on subjective norm, behavioral intention, and exposure behavior, whereas the impact on negatude was insignificant. The impact of subjective norm on behavioral intention was significant. Lastly, the impact of behavioral intention on exposure behavior was insignificant. These findings are significant because the study examined the process of self-disclosure by integrating psychological and social factors based on theoretical discussion.

• Journal of the Korean Geographical Society
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• v.51 no.6
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• pp.779-797
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• 2016

A calibrated hydrological model is a useful tool for quantifying the impacts of the climate variations and land use/land cover changes on sediment load, water quality and runoff. In the rainy season each year, the Xe Bang Fai river basin is provisionally flooded because of typhoons, the frequency and intensity of which are sensitive to ongoing climate change. Severe heavy rainfall has continuously occurred in this basin area, often causing severe floods at downstream of the Xe Bang Fai river basin. The main purpose of this study is to investigate the climate change impact on river discharge using a Soil and Water Assessment Tool (SWAT) model based on future climate change scenarios. In this study, the simulation of hydrological river discharge is used by SWAT model, covering a total area of $10,064km^2$ in the central part of country. The hydrological model (baseline) is calibrated and validated for two periods: 2001-2005 and 2006-2010, respectively. The monthly simulation outcomes during the calibration and validation model are good results with $R^2$ > 0.9 and ENS > 0.9. Because of ongoing climate change, three climate models (IPSL CM5A-MR 2030, GISS E2-R-CC 2030 and GFDL CM3 2030) indicate that the rainfall in this area is likely to increase up to 10% during the summer monsoon season in the near future, year 2030. As a result of these precipitation increases, the SWAT model predicts rainy season (Jul-Aug-Sep) river discharge at the Xebangfai@bridge station will be about $800m^3/s$ larger than the present. This calibrated model is expected to contribute for preventing flood disaster risk and sustainable development of Laos

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.549-559
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• 2014

The rapid expansion of cities led to the shortage of housing in urban areas. The government compensated for this shortage through large scale residential developments that increased the housing supply. The supply of condominium apartments remains above 83% of the entire housing supply, and the proportion of apartments are at a steady increase, at about 50%. Due to the increase, illegally parked cars resulting from the shortage of parking spaces within the apartment complex have become increasingly problematic as they block the transit of emergency vehicles, and heighten the tension among neighboring residents in obtaining a parking space. Especially, the future residents are considered to plan the parking based on the estimated demand for parking. However, the parking unit method utilized to estimate the parking demand accounts for the exclusive use of space, which is believed to be far from the parking demands in reality. The reason for this discrepancy is that, as the number of households decrease, and area of exclusive space is expanded, the planned parking increases. On the other hand, when the number of households increase, and the area of exclusive space is reduced, the planned parking decreases, thus methods to recalculate the parking units based on estimated parking demand is an urgent concern. To estimate the parking units based on condominium apartments, this study first examined the existing research literature, and appointed the field of investigation to collect the necessary data. In addition, field study data and surveys collected and analyzed, in order to identify the problems underlying parking units, and problems regarding the current traffic impact assessment parking unit calculation method were deduced. Through identifying the influential factors on parking demand estimates, and performing a factorial analysis based on the collected data, the variables were selected in relation to the parking demand estimates, to develop the parking unit estimate model. Finally, through comparing and verifying the existing traffic impact assessment parking unit estimate against the newly developed model using collected data, a far more realistic parking unite estimate was suggested, reflecting the characteristics of the residents. The parking unit estimate model developed in this study is anticipated to serve as the guidelines for future parking lot legislature, as wel as the basis to provide a more realistic estimate of parking demands based on the resident characteristics of an apartment complex.

• Economic and Environmental Geology
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• v.47 no.3
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• pp.205-217
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• 2014

As Mt. Backdu is expected to erupt, the social and economic impacts of the eruption on the Korean peninsula as well as on the world become a research topic of interest. If the volcano erupts, South Korea can be directly impacted by volcanic ash, which will bring out secondary damages in various ways. Given that the direct damage is a basis to estimate indirect and secondary damages, this paper was to review a method to estimate direct damages, called catastrophe risk models, and estimate the direct damages of available eruption scenarios of Mt. Baekdu. Based on the results, the damages by volcanic ash will occur mostly around Gangwon province if the Mt. Backdu erupts. Thus the inventory lists and their damage functions of Gangwon provinces were collected. In particular agricultural and forestry products were surveyed based on the land use. Direct damages were estimated using volcanic ash distribution of eruption scenarios, inventory information and their damage functions. In result, a scenario in winter caused the damage of 299.8 billion KRW (20.4% of total agricultural production in 2010) and 28.9 billion KRW (9.0% of total forestry production in 2010) in agriculture and forestry, respectively. The damages in agriculture was larger, and it is due to the damage functions which show the agricultural products are more vulnerable to volcanic ash than forestry products. Also the agricultural production (1,471.7 billion KRW in 2010) are more than 4.5 times the forestry production (322.3 billion KRW in 2010) in Gangwon province. Inje and Gangnung had the most damages in the scenario in winter. Inje had the most damage due to the thick ash deposit (8.5 mm in average) despite the low production. On the other hand, Goseong had a low damage compared to the ash thickness larger than 20mm, owing to the low production. The direct damage estimated through this process can be used to estimate indirect damages.

• Korean Journal of Ecology and Environment
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• v.56 no.1
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• pp.45-56
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• 2023

In stream ecosystem assessment, RIVPACS, which makes a simple but clear evaluation based on macroinvertebrate community, is widely used. In this study, a preliminary study was conducted to develop a RIVPACS-type model suitable for Korean streams nationwide. Reference streams were classified into two types(upstream and downstream), and a prediction model for macroinvertebrates was developed based on each family. A model for upstream was divided into 7 (train): 3 (test), and that for downstream was made using a leave-one-out method. Variables for the models were selected by non-metric multidimensional scaling, and seven variables were chosen, including elevation, slope, annual average temperature, stream width, forest ratio in land use, riffle ratio in hydrological characteristics, and boulder ratio in substrate composition. Stream order classified 3,224 sites as upstream and downstream, and community compositions of sites were predicted. The prediction was conducted for 30 macroinvertebrate families. Expected (E) and observed fauna (O) were compared using an ASPT biotic index, which is computed by dividing the BMWPK score into the number of families in a community. EQR values (i.e. O/E) for ASPT were used to assess stream condition. Lastly, we compared EQR to BMI, an index that is commonly used in the assessment. In the results, the average observed ASPT was 4.82 (±2.04 SD) and the expected one was 6.30 (±0.79 SD), and the expected ASPT was higher than the observed one. In the comparison between EQR and BMI index, EQR generally showed a higher value than the BMI index.

• Women's Health Nursing
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• v.2 no.2
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• pp.298-331
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• 1996

Recent improvements in living standard and development in medical care led to an increased interest in life expectancy and personal health, and also led to a more demand for higher quality of life. Thus, the problem of women's health draw a fresh interest nowadays. Since late-middle aged women experience various physical and socio-psychological changes and tend to have chronic illnesses, these women have to take initiatives for their health control by realizing their own responsibility. The basic elements for a healthy life of these women are understanding of their physical and psychological changes and acceptance of these changes. Health promoting behaviors of an individual or a group are actions toward increasing the level of well-being and self-actualization, and are affected by various variables. In Pender's health promoting model, variables are categorized into cognitive factors(individual perceptions), modifying factors, and variables affecting the likelihood for actions, and the model assumes the health promoting behaviors are affected by cognitive factors which are again affected by demographic factors. Since Pender's model was proposed based on a tool broad conceptual frame, many studies done afterwards have included only a limited number of variables of Pender's model. Furthermore, Pender's model did not precisely explain the possibilities of direct and indirect paths effects. The objectives of this study are to evaluate Pender's model and thus propose a model that explains health promoting behaviors among late-middle aged women in order to facilitate nursing intervention for this group of population. The hypothetical model was developed based on the Pender's health promoting model and the findings from past studies on women's health. Data were collected by self-reported questionnaires from 417 women living in Seoul, between July and November 1994. Questionnaires were developed based on instruments of Walker and others' health promotion lifestyle profile, Wallston and others' multidimensional health locus of control, Maoz's menopausal symptom check list and Speake and others' health self-rating scale. IN addition, items measuring self-efficacy were made by the present author based on past studies. In a pretest, the questionnaire items were reliable with Cronbach's alpha ranging from .786 to .934. The models for health promoting behaviors were tested by using structural equation modelling technique with LISREL 7.20. The results were summarized as follows : 1. The overall fit of the hypothetical model to the data was good (chi-square=4.42, df=5, p=.490, GFI=.995, AGFI=.962, RMSR=.024). 2. Paths of the model were modified by considering both its theoretical implication and statistical significance of the parameter estimates. Compared to the hypothetical model, the revised model has become parsimonious and had a better fit to the data (chi-square =4.55, df=6, p=.602, GFI=.995, AGFI=.967, RMSR=.024). 3. The results of statistical testing were as follows : 1) Family function internal health locus of control, self-efficacy, and education level exerted significant effects on health promoting behaviors(${\gamma}_{43}$=.272, T=3.714; ${\beta}_[41}$=.211, T=2.797; ${\beta}_{42}$=.199, T=2.717; ${\gamma}_{41}$=.136, T=1.986). The effect of economic status, physical menopausal symptoms, and perceived health status on health promoting behavior were insignificant(${\gamma}_{42}$=.095, T=1.456; ${\gamma}_{44}$=.101, T=1.143; ${\gamma}_{43}$=.082, T=.967). 2) Family function had a significance direct effect on internal health locus of control (${\gamma}_{13}$=.307, T=3.784). The direct effect of education level on internal health locus of control was insignificant(${\gamma}_{11}$=-.006, T=-.081). 3) The directs effects of family functions & internal health locus of control on self-efficacy were significant(${\gamma}_{23}$=.208, T=2.607; ${\beta}_{21}$=.191, T=2.2693). But education level and economic status did not exert a significant effect on self-efficacy(${\gamma}_{21}$=.137, T=1.814; ${\beta}_{22}$=.137, T=1.814; ${\gamma}_{22}$=.112, T=1.499). 4) Education level had a direct and positive effect on perceived health status, but physical menopausal symptoms had a negative effect on perceived health status and these effects were all significant(${\gamma}_{31}$=.171, T=2.496; ${\gamma}_{34}$=.524, T=-7.120). Internal health locus and self-efficacy had an insignificant direct effect on perceived health status(${\beta}_{31}$=.028, T=.363; ${\beta}_{32}$=.041, T=.557). 5) All predictive variables of health promoting behaviors explained 51.8% of the total variance in the model. The above findings show that health promoting behaviors are explained by personal, environmental and perceptual factors : family function, internal health locus of control, self-efficacy, and education level had stronger effects on health promoting behaviors than predictors in the model. A significant effect of family function on health promoting behaviors reflects an important role of the Korean late-middle aged women in family relationships. Therefore, health professionals first need to have a proper evaluation of family function in order to reflect the family function style into nursing interventions and development of strategies. These interventions and strategies will enhance internal health locus of control and self-efficacy for promoting health behaviors. Possible strategies include management of health promoting programs, use of a health information booklets, and individual health counseling, which will enhance internal health locus of control and self-efficacy of the late-middle aged women by making them aware of health responsibilities and value for oneself. In this study, an insignificant effect of physical menopausal symptoms and perceived health status on health promoting behaviors implies that they are not motive factors for health promoting behaviors. Further analytic researches are required to clarify the influence of physical menopausal symptoms and perceived health status on health promoting behaviors with-middle aged women.

• Journal of The Korean Association For Science Education
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• v.35 no.2
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• pp.217-229
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• 2015

In this study, we explored the development of scientific model through the social-construction process on "combustion." Students were 8th graders from one middle school class. Each student engaged in small group discussions three times and made a group model on combustion. Discourses between peers and teacher were videotaped, audiotaped, and transcribed. The results show that the small groups constructed an initial concept: 'Conditions of combustion', which they then evaluated and revised the initial concept through combustion experiment. Following the discussions, some small groups evaluated their model and made a revised model. Then, the small groups compared various models and constructed a scientific model through consensus within the small group and as a whole class. Finally, students kept revising their model to 'Burning needs oxygen.' This tells us that the social construction process of scientific model made a meaningful role to build scientific model through diverse discussion between the students and their teacher, although they have had some difficult process to reach the final consensus. The data also showed some group features: the members were open to other's ideas. They analyzed the differences between their own ideas from others and revised their model after the whole class discussion. Lastly, they showed the tendency to make a good use of teacher's guidance. This study implies the importance of having social interaction process for students to understand the scientific model and learn the nature of scientific inquiry in class.