• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.799-808
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• 2008

The analysis of vehicular loads reflecting the domestic traffic circumstances is necessary for the development of adequate design live load models in the analysis and design of cable-supported bridges or the development of fatigue load models to predict the remaining lifespan of the bridges. This study intends to develop an ANN(artificial neural network)-based Bridge WIM system and Influence line-based Bridge WIM system for obtaining information concerning the loads conditions of vehicles crossing bridge structures by exploiting the signals measured by strain gauges installed at the bottom surface of the bridge superstructure. This study relies on experimental data corresponding to the travelling of hundreds of random vehicles rather than on theoretical data generated through numerical simulations to secure data sets for the training and test of the ANN. In addition, data acquired from 3 types of vehicles weighed statically at measurement station and then crossing the bridge repeatedly are also exploited to examine the accuracy of the trained ANN. The results obtained through the proposed ANN-based analysis method, the influence line analysis method considering the local behavior of the bridge are compared for an example cable-stayed bridge. In view of the results related to the cable-stayed bridge, the cross beam ANN analysis method appears to provide more remarkable load analysis results than the cross beam influence line method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.709-721
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• 2008

This paper is to test the applicability of ModKIMSTORM (Modified KIneMatic Wave STOrm Runoff Model) by applying it to Namgangdam watershed of $2,293km^2$. Model inputs (DEM, land use, soil related information) were prepared in 500 m spatial resolution. Using five typhoon events (Saomi in 2000, Rusa in 2002, Maemi in 2003, Megi in 2004 and Ewiniar in 2006) and two storm events (May of 2003 and July of 2004), the model was calibrated and verified by comparing the simulated streamflow with the observed one at the outlet of the watershed. The Pearson's coefficient of determination $R^2$, Nash and Sutcliffe model efficiency E, the deviation of runoff volumes $D_v$, relative error of the peak runoff rate $EQ_p$, and absolute error of the time to peak runoff $ET_p$ showed the average value of 0.984, 0.981, 3.63%, 0.003, and 0.48 hr for 4 storms calibration and 0.937, 0.895, 8.08%, 0.138, and 0.73 hr for 3 storms verification respectively. Among the model parameters, the stream Manning's roughness coefficient was the most sensitive for peak runoff and the initial soil moisture content was highly sensitive for runoff volume fitting. We could look into the behavior of hyrologic components from the spatial results during the storm periods and get some clue for the watershed management by storms.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6B
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• pp.597-603
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• 2006

The purpose of this study is to improve the short term rainfall forecast skill using neural network model that can deal with the non-linear behavior between satellite data and ground observation, and minimize the flood damage. To overcome the geographical limitation of Korean peninsula and get the long forecast lead time of 3 to 6 hour, the developed rainfall forecast model took satellite imageries and wide range AWS data. The architecture of neural network model is a multi-layer neural network which consists of one input layer, one hidden layer, and one output layer. Neural network is trained using a momentum back propagation algorithm. Flood was estimated using rainfall forecasts. We developed a dynamic flood inundation model which is associated with 1-dimensional flood routing model. Therefore the model can forecast flood aspect in a protected lowland by levee failure of river. In the case of multiple levee breaks at main stream and tributaries, the developed flood inundation model can estimate flood level in a river and inundation level and area in a protected lowland simultaneously.

• Journal of Korea Entertainment Industry Association
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• v.13 no.5
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• pp.15-24
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• 2019

The purpose of the study is to present implications for the management performance and improvement of enterprises through the study of the simplicity of meals, individual values, inhuman relationships, attitude formation, awareness and solitary eating behaviors. The research method was investigated by the judgment sampling method. The collected effective samples were validated using a confirmed factorial analysis to ensure the validity of the discriminatory validity and the internal validity of the convergent validity. First of all, the company should provide information to the people who eat alone to A recognize the simplicity of their meals. Second, we should ensure that the individual values of the Honbab people can be formed through various promotional strategies that can lead to the formation of attitudes. Third, companies should pursue diverse event strategies that can lead to the formation of attitudes of the people of the Honbab family. Fourth, event development such as the provision of a very special service for customers only will have to be conducted when visiting the stores of the Honbap people. Finally, companies should focus on promoting the convenience, convenience, and time-consuming advantages of eating alone through a variety of marketing, and strive to increase their customers.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.389-399
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• 2023

Recently, there has been a growing focus on the Entrepreneurial Intention of Chinese College Students as a key driver of motivational behavior. However, previous research has provided limited analysis on the actual impact of Social Support on the Entrepreneurial Intention of Chinese College Students. The purpose of this study is to enhance the Entrepreneurial Intention of Chinese College Students and to ascertain the mediating effect of Career Adaptability in the relationship between Social Support and Entrepreneurial Intention. Zhejiang Province, the top-ranked province in private economy in China, possesses a strong economic development momentum and an innovative entrepreneurial atmosphere. Therefore, this study selected 194 third and fourth-year undergraduate students from universities in Zhejiang Province as participants and collected data through a survey utilizing measures of Social Support, Career Adaptability, and Entrepreneurial Intention. The collected data was analyzed for correlations between the measured variables using SPSS 26 and Stata 17 SEM Builder for quantification and validation. The results of the study revealed that, firstly, while Social Support did not have a direct impact on Entrepreneurial Intention, it was found to have an indirect influence on Entrepreneurial Intention through Career Adaptability and its various sub-variables. Secondly, Social Support among College Students was found to have a positive impact on Career Adaptability. Thirdly, Career Adaptability among College Students was found to have a positive impact on Entrepreneurial Intention. Based on these analytical findings, this study provides theoretical and practical implications as well as fundamental information for entrepreneurship education and Career Adaptability at the university level.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.167-175
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• 2024

Due to the Fourth Industrial Revolution, ICT(Information and Communication Technology) industry is becoming more important and sophisticated than ever. In B2B based ICT industry demand forecasting by analyzing the previous customer data is so important. RFM, one of customer relationship management models is a marketing technique that evaluates Recency, Frequency and Monetary value to predict customers behavior. RFM model has been studied focusing on the B2C based industry. On the other hand there is a lack of research on B2B based technology industry. Therefore this study applied it to B2B based high technology industry and considered T(technology collaboration) value, which are identified as important factors in the technology industry. To present an improved model for market performance in B2B technology industry, an empirical study was conducted on comparing the accuracy of the traditional RFM model and the improved RFM-T model. The objective of this study is to contribute to market performance by presenting an improved model in B2B based high technology industry.

• Journal of Digital Convergence
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• v.22 no.1
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• pp.1-14
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• 2024

In order to improve the effectiveness of carbon neutrality in Jeju Special Self-Governing Province, this study identifies the current state of social environmental education through literature research, excluding school environmental education being implemented in elementary, middle, and high schools in the province, and identifies shortcomings or problems. The purpose is to establish a plan to systematically and integratedly operate social environmental education, and the derived plan can be used as a guide to change environmental awareness and induce eco-friendly behavior to improve the effectiveness of carbon neutrality. As a result of the study, Jeju Special Self-Governing Province established a consultative body with environmental education institutions, organizations and expert groups operating dispersed throughout the province through the substantial operation and support of the environmental education center currently being entrusted, to identify the current status and develop content necessary for establishing environmental education policies, establishing a platform to enable information sharing, role division, regular communication, empathy, and policy feedback, and on-site environmental education centered on the field to stimulate emotions and personalize environmental problems so that environmental problems can be properly recognized. Emphasizing the necessity.

• Proceedings of the Materials Research Society of Korea Conference
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• 2011.05a
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• pp.5-5
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• 2011

The research and development of hybrid electric vehicle (HEV), plug-in hybrid electric vehicle (PHEV) and electric vehicle (EV) are intensified due to the energy crisis and environmental concerns. In order to meet the challenging requirements of powering HEV, PHEV and EV, the current lithium battery technology needs to be significantly improved in terms of the cost, safety, power and energy density, as well as the calendar and cycle life. One new technology being developed is the utilization of composite cathode by mixing two different types of insertion compounds [e.g., spinel $LiMn_2O_4$ and layered $LiMO_2$ (M=Ni, Co, and Mn)]. Recently, some studies on mixing two different types of cathode materials to make a composite cathode have been reported, which were aimed at reducing cost and improving self-discharge. Numata et al. reported that when stored in a sealed can together with electrolyte at $80^{\circ}C$ for 10 days, the concentrations of both HF and $Mn^{2+}$ were lower in the can containing $LiMn_2O_4$ blended with $LiNi_{0.8}Co_{0.2}O_2$ than that containing $LiMn_2O_4$ only. That reports clearly showed that this blending technique can prevent the decline in capacity caused by cycling or storage at elevated temperatures. However, not much work has been reported on the charge-discharge characteristics and related structural phase transitions for these composite cathodes. In this presentation, we will report our in situ x-ray diffraction studies on this mixed composite cathode material during charge-discharge cycling. The mixed cathodes were incorporated into in situ XRD cells with a Li foil anode, a Celgard separator, and a 1M $LiPF_6$ electrolyte in a 1 : 1 EC : DMC solvent (LP 30 from EM Industries, Inc.). For in situ XRD cell, Mylar windows were used as has been described in detail elsewhere. All of these in situ XRD spectra were collected on beam line X18A at National Synchrotron Light Source (NSLS) at Brookhaven National Laboratory using two different detectors. One is a conventional scintillation detector with data collection at 0.02 degree in two theta angle for each step. The other is a wide angle position sensitive detector (PSD). The wavelengths used were 1.1950 ${\AA}$ for the scintillation detector and 0.9999 A for the PSD. The newly installed PSD at beam line X18A of NSLS can collect XRD patterns as short as a few minutes covering $90^{\circ}$ of two theta angles simultaneously with good signal to noise ratio. It significantly reduced the data collection time for each scan, giving us a great advantage in studying the phase transition in real time. The two theta angles of all the XRD spectra presented in this paper have been recalculated and converted to corresponding angles for ${\lambda}=1.54\;{\AA}$, which is the wavelength of conventional x-ray tube source with Cu-$k{\alpha}$ radiation, for easy comparison with data in other literatures. The structural changes of the composite cathode made by mixing spinel $LiMn_2O_4$ and layered $Li-Ni_{1/3}Co_{1/3}Mn_{1/3}O_2$ in 1 : 1 wt% in both Li-half and Li-ion cells during charge/discharge are studied by in situ XRD. During the first charge up to ~5.2 V vs. $Li/Li^+$, the in situ XRD spectra for the composite cathode in the Li-half cell track the structural changes of each component. At the early stage of charge, the lithium extraction takes place in the $LiNi_{1/3}Co_{1/3}Mn_{1/3}O_2$ component only. When the cell voltage reaches at ~4.0 V vs. $Li/Li^+$, lithium extraction from the spinel $LiMn_2O_4$ component starts and becomes the major contributor for the cell capacity due to the higher rate capability of $LiMn_2O_4$. When the voltage passed 4.3 V, the major structural changes are from the $LiNi_{1/3}Co_{1/3}Mn_{1/3}O_2$ component, while the $LiMn_2O_4$ component is almost unchanged. In the Li-ion cell using a MCMB anode and a composite cathode cycled between 2.5 V and 4.2 V, the structural changes are dominated by the spinel $LiMn_2O_4$ component, with much less changes in the layered $LiNi_{1/3}Co_{1/3}Mn_{1/3}O_2$ component, comparing with the Li-half cell results. These results give us valuable information about the structural changes relating to the contributions of each individual component to the cell capacity at certain charge/discharge state, which are helpful in designing and optimizing the composite cathode using spinel- and layered-type materials for Li-ion battery research. More detailed discussion will be presented at the meeting.

• Journal of Nutrition and Health
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• v.42 no.6
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• pp.559-566
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• 2009

Effective nutrition educations for prevention of chronic diseases for the general population are of great importance these days. The purpose of this study was to evaluate the feasibility of nutrition education for cardiovascular risk factor reduction by e-mail education in male workers. The participants were divided into three groups by age; 28-39 age group, 40-49 age group, and 50-59 age group who got regular checkups for anthropometry and biochemistry. The 1 year program consisted of 15 topics containing information about metabolic syndrome (MS) and healthy eating behavior (intake of salt, fat and alcohol). Seven hundred thirty nine participants volunteered for the study [28-39 age group, n = 240; body mass index (BMI) = 24.9 $\pm$ 2.7 kg/m$^2$: 40' group, n = 276; BMI = 24.8 $\pm$ 2.6 kg/m$^2$: 50' group, n = 223; BMI = 24.9 $\pm$ 2.7 kg/m$^2$]. Percentage body fat (p < 0.05) and percentage of abdominal fat (p < 0.05), total cholesterol (p < 0.05), systolic blood pressure (p < 0.05), and diastolic blood pressure (p < 0.05) were significantly decreased in all participants after the 1 year program. The total number of participants who had MS was decreased from 216 to 199 and especially the incidence of MS was decreased 27% in the group of subjects who were under the age 39. The e-mail worksite nutrition education program shows a substantial contribution to the development of effective CVD and chronic disease control and lifestyle nutrition educations that are applicable to and attractive for the large population at risk.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.