• Korean Journal of Environmental Biology
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• v.41 no.2
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• pp.109-125
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• 2023

This study was conducted to select target fish species as baseline research for accumulation analysis of major hazardous chemicals entering the aquatic ecosystem in Korea and to analyze the impact on fish community. The test bed was selected from a sewage treatment plant, which could directly confirm the impact of the inflow of harmful chemicals, and the Geum River estuary where harmful chemicals introduced into the water system were concentrated. A multivariable metric model was developed to select target candidate fish species for hazardous chemical analysis. Details consisted of seven metrics: (1) commercially useful metric, (2) top-carnivorous species metric, (3) pollution fish indicator metric, (4) tolerance fish metric, (5) common abundant metric, (6) sampling availability (collectability) metric, and (7) widely distributed fish metric. Based on seven metric models for candidate fish species, eight species were selected as target candidates. The co-occurring dominant fish with target candidates was tolerant (50%), indicating that the highest abundance of tolerant species could be used as a water pollution indicator. A multi-metric fish-based model analysis for aquatic ecosystem health evaluation showed that the ecosystem health was diagnosed as "bad conditions". Physicochemical water quality variables also influenced fish feeding and tolerance guild in the testbed. Eight water quality parameters appeared high at the T1 site, indicating a large impact of discharging water from the sewage treatment plant. T2 site showed massive algal bloom, with chlorophyll concentration about 15 times higher compared to the reference site.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.1
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• pp.46-58
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• 2024

Pollinators are organisms that carry out the pollination process of plants and include Hymenoptera, Lepidoptera, Diptera, and Coleoptera. Among them, bees not only pollinate plants but also improve urban green spaces damaged by land use changes, providing a habitat and food for birds and insects. Today, however, the number of pollinating plants is decreasing due to issues such as early flowering due to climate change, fragmentation of green spaces due to urbanization, and pesticide use, which in turn leads to a decline in bee populations. The decline of bee populations directly translates into problems, such as reduced biodiversity in cities and decreased food production. Urban beekeeping has been proposed as a strategy to address the decline of bee populations. However, there is a problem asurban beekeeping strategies are proposed without considering the complex structure of the socio-ecological system consisting of bees foraging and pollination activities and are therefore unsustainable. Therefore, this study aims to analyze the socio-ecological system of honeybees, which are pollinators, structurally using system thinking and propose a green space planning strategy to revitalize urban beekeeping. For this study, previous studies that centered on the social and ecological system of bees in cities were collected and reviewed to establish the system area and derive the main variables for creating a causal loop diagram. Second, the ecological structure of bees' foraging and pollination activities and the structure of bees' ecological system in the city were analyzed, as was the social-ecological system structure of urban beekeeping by creating an individual causal loop diagram. Finally, the socio-ecological system structure of honey bees was analyzed from a holistic perspective through the creation of an integrated causal loop diagram. Citizen participation programs, local government investment, and the creation of urban parks and green spaces in idle spaces were suggestedas green space planning strategies to revitalize urban beekeeping. The results of this study differ from previous studies in that the ecological structure of bees and the social structure of urban beekeeping were analyzed from a holistic perspective using systems thinking to propose strategies, policy recommendations, and implications for introducing sustainable urban beekeeping.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.2
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• pp.51-63
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• 2024

While the government policy to fully adopt BIM in the construction sector is being implemented, the construction and utilization of landscape BIM models are facing challenges due to problems such as limitations in BIM authoring tools, difficulties in modeling natural materials, and a shortage in BIM content including libraries. In particular, plants, fundamental design elements in the field of landscape architecture, must be included in BIM models, yet they are often omitted during the modeling process, or necessary information is not included, which further compromises the quality of the BIM data. This study aimed to contribute to the construction and utilization of landscape BIM models by developing a plant library that complies with BIM standards and is applicable to the landscape industry. The plant library of trees and shrubs was developed in Revit by modeling 3D shapes and collecting attribute items. The geometric information is simplified to express the unique characteristics of each plant species at LOD200, LOD300, and LOD350 levels. The attribute information includes properties on plant species identification, such as species name, specifications, and quantity estimation, as well as ecological attributes and environmental performance information, totaling 24 items. The names of the files were given so that the hierarchy of an object in the landscape field could be revealed and the object name could classify the plant itself. Its usability was examined by building a landscape BIM model of an apartment complex. The result showed that the plant library facilitated the construction process of the landscape BIM model. It was also confirmed that the library was properly operated in the basic utilization of the BIM model, such as 2D documentation, quantity takeoff, and design review. However, the library lacked ground cover, and had limitations in those variables such as the environmental performance of plants because various databases for some materials have not yet been established. Further efforts are needed to develop BIM modeling tools, techniques, and various databases for natural materials. Moreover, entities and systems responsible for creating, managing, distributing, and disseminating BIM libraries must be established.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.384-395
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• 2023

Since transpiration plays a key role in optimal irrigation management, knowledge of the irrigation demand of crops like tomatoes, which are highly susceptible to water stress, is necessary. One way to determine irrigation demand is to measure transpiration, which is affected by environmental factor or growth stage. This study aimed to estimate the transpiration amount of tomatoes and find a suitable model using mathematical and deep learning models using minute-by-minute data. Pearson correlation revealed that observed environmental variables significantly correlate with crop transpiration. Inside air temperature and outside radiation positively correlated with transpiration, while humidity showed a negative correlation. Multiple Linear Regression (MLR), Polynomial Regression model, Artificial Neural Network (ANN), Long short-term Memory (LSTM), and Gated Recurrent Unit (GRU) models were built and compared their accuracies. All models showed potential in estimating transpiration with R² values ranging from 0.770 to 0.948 and RMSE of 0.495 mm/min to 1.038 mm/min in the test dataset. Deep learning models outperformed the mathematical models; the GRU demonstrated the best performance in the test data with 0.948 R² and 0.495 mm/min RMSE. The LSTM and ANN closely followed with R² values of 0.946 and 0.944, respectively, and RMSE of 0.504 m/min and 0.511, respectively. The GRU model exhibited superior performance in short-term forecasts while LSTM for long-term but requires verification using a large dataset. Compared to the FAO56 Penman-Monteith (PM) equation, PM has a lower RMSE of 0.598 mm/min than MLR and Polynomial models degrees 2 and 3 but performed least among all models in capturing variability in transpiration. Therefore, this study recommended GRU and LSTM models for short-term estimation of tomato transpiration in greenhouses.

• Journal of Nutrition and Health
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• v.48 no.6
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• pp.558-570
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• 2015

Purpose: The objective of this study is to investigate the work performances and the factors contributing to the work performance of nutrition teachers and school dieticians according to employment status in Daejeon and Chungcheongnamdo. Methods: A survey was conducted among 415 school dieticians from selected elementary, middle, and high schools in the area. This survey was used for analysis of the general characteristics and the status of working and foodservice environments. The frequency of occurrence was measured using the ${\chi}^2$-test while analysis of differences in work performance of 57 variables grouped according to 12 categories by mean ${\pm}$ SD was performed using student t-test. In addition, a regression analysis was performed to assess the influence of occupational (working and foodservice) environment on work performances. Results: All 14 environmental factors including general characteristics were different between nutrition teachers and school dieticians. In 12 of 57 variables there were significant differences in work performance between the two groups. When compared using average work performance, 5 domains showed significant difference in work performance between the two groups. These 5 domains were other works (T = 6.050), dietary habit guide (T = 4.789), menu (nutrition) management (T = 3.524), foodservice administration and evaluation (T = 2.757), and production and service management (T = 2.588). Overall, the work performances of nutrition teachers were comparably higher than those of school dietitians. A correlation analysis between occupational (working or foodservice) environments and work performances of the two groups showed that the work performances of nutrition teachers were influenced by the number of employees, number of students, meal frequency a day, annual salary, age, foodservice years of school, and school type. Conclusion: Meanwhile, the work performances of school dieticians were influenced by the number of students, number of employees, meal frequency a day, work hour, education level, age, school type, and service years as a dietitian.

• Journal of agricultural medicine and community health
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• v.25 no.1
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• pp.65-83
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• 2000

To know the relationship of general characteristics with activities of daily living(ADL) and instrumental activities of daily living(IADL), we carried out the study on the elderies living in Chollabuk-Do area during 6 months, from June to December in 1999. Study subjects were 281, women and men were 195(69.6%) and 85(30.4%) respectively. Mean ages of women and men were 71.9 and 70.8 respectively. 81.1% elderies has disease and 18.9% were disease free. Disease prevalences of movement joint disease, others, circulatory disease, digestive disease, dental disease, respiratory disease were 50.1%, 25.0%, 10.5%, 9.4%, 8.5%, and 6.3% respectively. The percentages to the use of medical institution in recent were 40.0% for hospital, 16.8% for oriental hospital, 14.5% for public health center, 10.9% for drug store, 10.0% for others, and 7.8% for dental service. The percentages to the improvement of symptom after the use of medical institution were 62.3% for normal, 19.4% for improvement, and 18.2% for non-improvement. The percentages to the health situation were 37.1% for bad, 35.7% for good, and 27.1% for normal. Activities of daily living were 67.1% for 6 scores, 27.9% for 5 scores, 2.1% for 4 scores and ADL of women was lower than the men's. Instrumental activities of daily living were 50.4% for 5 scores, 19.3% for 3 scores, 12.1% for 4 scores and IADL of women was lower than the men's. Frequencies of disability in ADL were 28.9% for incontinence, 6.1% for bathing, 2.9% for meal, 2.5% for walking around house, 1.8% for toilet use, 1.4% for dressing and disability frequencies of women in 6 items of ADL were higher than the men's. The percentages of high, intermediate, low ADL in activities of daily living were 67.1%, 32.5%, 0.4% respectively and decrease of high ADL, increase of intermediate ADL were found with the increasing of age. Frequencies of disability in IADL were 42.9% for payment in and out, 31.8% for payment of written claim, 21.1% for shopping, 16.4% for preparation of meal, and 11.8% for use of bus. All items of women in IADL was higher than the men's but preparation of meal. The percentages of high, intermediate, low IADL in instrumental activities of daily living were 50.4%, 42.5%, 7.1% and decrease of high IADL, increase of intermediate IADL were found with the increasing of age. Mean of ADL with the general characteristics was 5.56 and 2 variables of level of education, health situation were statistically significant. Mean of IADL with the general characteristics was 3.76 and 8 variables of age, sex, level of education, occupation, presence of spouse, duty of living cost, health situation, category of ADL were statistically significant. With the result of stepwise regression, ADL was statistically related with religion, health situation and ADL was statistically related with level of education, living together with family, duty of living cost, health situation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.5
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• pp.53-68
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• 2014

This study is aimed at analyzing the factors that affect the behaviors of employee's investment, such as a decision making process in a variety of views and proving the extent of how those factors influence on their investment. The basic assumption is that the preceding factors that can be determined by the personal investment propensity, a psychological factor asserted by Behavior Financial Theory and financial-economic and social environment. This study uses Hershey's Investment Behavior Model(2007) as the main analysis tool to explain the investment behavior of individuals and deals with personal investment inclination in the psychological perspective of overconfidence, self-control and the risk tolerance propensity and add the financial and economic factors in terms of financial literacy and economic distress. Also the new preceding social environmental factors like social interaction and the effect of reference group are added to make this research to be more precise. This study analyze the adjustment effect of professional invest-consulting service that affect the fluctuation influence between the individual variables(those factors) and subordination variable(the level of investment satisfaction). The study reveals that overconfidence and self-control in direct ways have a positive effect on the level of investment satisfaction in terms of investment behavior and economic distress has a negative effect on the level of investment satisfaction. The adjustment effect provided by financial experts in investment consulting service is affirmed as the critical factor that increase the influence between self-control and the level of investment satisfaction. To conclude, the research reveals that the psychological factors are the main criteria when the workers as employees have to make investment decisions. To make investors be reasonable, a systematic financial education system provided by experts is needed from the early adolescent stages and financial companies should develop the relevant services of consulting service department as a key financial sector and financial investment products and consulting program and marketing tool pertinent to investors ages, vocational traits and their inclinations.

• 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.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.139-160
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• 2017

Technology commercialization creates effective economic value by linking the company's R & D processes and outputs to the market. This technology commercialization is important in that a company can retain and maintain a sustained competitive advantage. In order for a specific technology to be commercialized, it goes through the stage of technical planning, technology research and development, and commercialization. This process involves a lot of time and money. Therefore, the duration and cost of technology commercialization are important decision information for determining the market entry strategy. In addition, it is more important information for a technology investor to rationally evaluate the technology value. In this way, it is very important to scientifically estimate the duration and cost of the technology commercialization. However, research on technology commercialization is insufficient and related methodology are lacking. In this study, we propose an evaluation model that can estimate the duration and cost of R & D technology commercialization for small and medium-sized enterprises. To accomplish this, this study collected the public data of the National Science & Technology Information Service (NTIS) and the survey data provided by the Small and Medium Business Administration. Also this study will develop the estimation model of commercialization duration and cost of R&D performance on using these data based on the market approach, one of the technology valuation methods. Specifically, this study defined the process of commercialization as consisting of development planning, development progress, and commercialization. We collected the data from the NTIS database and the survey of SMEs technical statistics of the Small and Medium Business Administration. We derived the key variables such as stage-wise R&D costs and duration, the factors of the technology itself, the factors of the technology development, and the environmental factors. At first, given data, we estimates the costs and duration in each technology readiness level (basic research, applied research, development research, prototype production, commercialization), for each industry classification. Then, we developed and verified the research model of each industry classification. The results of this study can be summarized as follows. Firstly, it is reflected in the technology valuation model and can be used to estimate the objective economic value of technology. The duration and the cost from the technology development stage to the commercialization stage is a critical factor that has a great influence on the amount of money to discount the future sales from the technology. The results of this study can contribute to more reliable technology valuation because it estimates the commercialization duration and cost scientifically based on past data. Secondly, we have verified models of various fields such as statistical model and data mining model. The statistical model helps us to find the important factors to estimate the duration and cost of technology Commercialization, and the data mining model gives us the rules or algorithms to be applied to an advanced technology valuation system. Finally, this study reaffirms the importance of commercialization costs and durations, which has not been actively studied in previous studies. The results confirm the significant factors to affect the commercialization costs and duration, furthermore the factors are different depending on industry classification. Practically, the results of this study can be reflected in the technology valuation system, which can be provided by national research institutes and R & D staff to provide sophisticated technology valuation. The relevant logic or algorithm of the research result can be implemented independently so that it can be directly reflected in the system, so researchers can use it practically immediately. In conclusion, the results of this study can be a great contribution not only to the theoretical contributions but also to the practical ones.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1309-1320
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• 2015

This study made an attempt to analyse the relationship between operation environment and fleet size per route which represents the level of service for inner-city bus service. Regression analysis method has been adopted as main analysis tool and 98 routes of bus operation status in Ulsan city as of 2013 has also been selected for analysis target. Correlation analysis was performed to identify the relationship between dependent and independent variables. There are three types of model for whole sample, type operation, and bus route operation system. These are the results of the current study. 1. The model developed for whole sample of 98 routes is as follows. Y(Fleet Size)=$-4.532+0.00002877*X_1$(Revenue). This model shows that it is necessary to have more than 140 passengers per day to increase fleet size of each bus route in Ulsan. 2. Models developed by type of operation (which are standard, express, and middle sized) are shown below. Stand Bus : Y(Fleet Size)=$-10.954+0.00004283*X_1$(Revenue). It is identified that more than 153 passengers need to use standard bus to increase fleet size per each standard bus, Middle Sized Bus : Y(Fleet Size)=-0.859+0.00001438*X1(Revenue). For middle sized bus, at least 52 daily passengers are needed to increase number of bus in each route. 3. Models developed for each route operation systems are as belows. Joint Operation Group : Y(Fleet Size)=$-4.786+0.00003028*X_1$(Revenue). Individual Operation Group : Y(Fleet Size)=$-2.339+0.00002030*X_1$(Revenue). These model provide similar result which 140 people is the minimum number of passenger to raise the number of vehicles in each route. This result shows that the route operation systems does not affect the raise number of cars significantly.