• Journal of Korea Port Economic Association
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• v.26 no.1
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• pp.259-276
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• 2010

This study shows how Incheon will advance into roadmap as multi-transport hub in Northeast Asia hereafter and be proposed an urgent tasks and roles to construct a multi-transportation system for Incheon, which has both an international airport and port. The multi-transportation point of view of inter-major cities competitiveness of total scores was proposed 1. Shanghai(64.8 points), 2 in Hongkong(64.5), 3 in Incheon(62.9), and 4 in Busan(60.4) and Incheon was estimated to have enough competitiveness to be the international multi-transport hub in Northeast Asia. Sea & Air transportation revealed the most important multi-transportation in the Incheon region. In conclusion, this research suggests a development plan for multi-transportation in Incheon. Firstly, it proposes construction of sea & air transportation distribution center and agreement that simplifies logistic process between Incheon and Tianjin, secondly, suggests to activate project for the purpose of creating a better sea-land transportation system between Incheon and Shanghai.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.213-220
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• 2013

This research paper examined to the influencing factors to adopt national policies of international organization's environment. For this a multivariate regression model has been used to examine cross-national differences in environmental policy adoption. The data analysis was conducted by regression analysis, the indexed point of international environmental agreements were ratified by each nation on the measure of independent variables for a sample of 130 countries in all parts of the world. From analysis results, overall, the regression analysis illustrates that the regression model generally fits our predictions for independent variables. The finding has revealed that external determinants are stronger than internal ones in explaining the level of national environmental policy adoption in relation to international environmental cooperation. Namely, All international environmental organizations, international nongovernmental organizations, and regional multinational institutes proved to function in a positive way in influencing number nations to have a favorable attitude toward international environmental policies. The findings of this study will provide helpful information on how to improve the efficacy of the Korean environmental policy system.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.25-31
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• 2022

This study aims to investigate the degree of influence of LMS on online classes conducted after COVID-19 at C University in Gyeongsangnam-do, and to examine the relationship between overall class satisfaction and LMS satisfaction variables. C University started the project to construct 'Next-generation Smart LMS' and operated it from the first semester of 2021. As a result of conducting a survey about overall class satisfaction and LMS satisfaction consisting of five variables with 140 learners who have experienced online classes at C University. The learners showed high satisfaction not only in overall classes but also LMS. As a result of regression analysis of LMS satisfaction and overall class satisfaction, it was found that the functional convenience of LMS and interaction with instructors had a significant effect on overall class satisfaction. This study has limitations in that it was conducted only at one college and a limited number of variables were measured.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.393-404
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• 2022

This study attempted to examine the effect of education and training on organizational performance based on HCCP research through the systematic review of previous studies. For this, 29 papers used HCCP data were selected and analyzed, and the research results are as follows. First, the research results showed that education and training had a positive effect on non-financial performance such as organizational commitment and job satisfaction, and financial performance such as sales and operating profit. Second, in order for education and training to affect organizational performance, job satisfaction, organizational culture, and education transfer were found to be important factors. Third, for effective transfer of education and training, it is necessary to establish a system that can be applied to the field after education and training, finally, it suggested the need for research to be conducted to reveal the practical effectiveness of education and training by measuring the degree to which education and training contributed to financial performance more closely.

• Journal of dental hygiene science
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• v.12 no.6
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• pp.644-651
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• 2012

This study purports to measure the level of work friendship in dental clinic and examines the friendship's effect on the organizational effectiveness. Data were collected from workers who worked in dental clinic located in Seoul and Gyeonggi areas by self-administered questionnaires from early in October till lately in September, 2009 through direct interview and e-mail. Among 250 questionnaires, 240 responses were returned, and 17 copies with an inaccurate answer were excluded. Finally 223 responses were analyzed through SPSS program. The study revealed that the work friendship in dental clinic has enormous influence on job satisfaction, occupational commitment, intent to leave, stress etc. The results imply that the managers of the dental clinics need to create an organizational climate which emphasizes on a good relationship among members and have them take part in various committees or informal activities.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.

• Progress in Medical Physics
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• v.20 no.3
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• pp.132-138
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• 2009

Studies on target motion in 4-dimensional radiotherapy are being world-widely conducted to enhance treatment record and protection of normal organs. Prediction of tumor motion might be very useful and/or essential for especially free-breathing system during radiation delivery such as respiratory gating system and tumor tracking system. Neural network is powerful to express a time series with nonlinearity because its prediction algorithm is not governed by statistic formula but finds a rule of data expression. This study intended to assess applicability of neural network method to predict tumor motion in 4-dimensional radiotherapy. Scaled Conjugate Gradient algorithm was employed as a learning algorithm. Considering reparation data for 10 patients, prediction by the neural network algorithms was compared with the measurement by the real-time position management (RPM) system. The results showed that the neural network algorithm has the excellent accuracy of maximum absolute error smaller than 3 mm, except for the cases in which the maximum amplitude of respiration is over the range of respiration used in the learning process of neural network. It indicates the insufficient learning of the neural network for extrapolation. The problem could be solved by acquiring a full range of respiration before learning procedure. Further works are programmed to verify a feasibility of practical application for 4-dimensional treatment system, including prediction performance according to various system latency and irregular patterns of respiration.

• The Journal of Korean Academy of Prosthodontics
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• v.47 no.1
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• pp.1-11
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• 2009

Statement of problem: There are two methods of color choice for the esthetic restoration. One is visual shade matching which draws a comparison between shade guide and teeth in dentist's own eye and the other is using a digital shade analysis system recently introduced. Although the visual shade matching has a lot of problems, decision of color by this visual shade matching and the ways of expression for the decided color are still applicable to clinical dentistry. Purpose: This study is designed to investigate shade guides used in the dental clinics and laboratories have the same value using ShadeEye-$NCC^{(R)}$ dental chroma meter (Shofu Inc., Kyoto, Japan) using shade guide are evaluated. Material and methods: At the first experiment, eight Vita Lumin Vacuum shade guides (Vident Inc., California, USA) were collected from the dental clinics. A1 and B1 shade tabs are chosen and the colors are analyzed five times each in both tooth and porcelain modes by digital shade analysis system, ShadeEye-$NCC^{(R)}$. In the second experiment, twelve Vita shade guides using practically in the dental clinics and laboratories were collected and also A1 and B1 shade tabs are chosen and the colors of A1 and B1 are analyzed one time each in both tooth and porcelain modes by ShadeEye-$NCC^{(R)}$. Results and conclusion: There were significant differences among eight shade guides in terms of shade (chroma), value and hue in both of A1 and B1 (P<.05). Shade guides using in present both dental clinics and laboratories did not show significant differences, except A1 in the porcelain mode, it showed significant differences (P<.05) in the shade even though the shade tab has the same name.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Journal of Korean Society of Transportation
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• v.30 no.5
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• pp.91-100
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• 2012

Although Korea's coastal areas increasingly experience marine accident due to frequent ship encounters, increased vessel traffic and large vessel, there is a no specific model to evaluate the navigating vessel's risk for the given situation. The maritime transport environmental assessment is necessary due to the amended marine traffic law. However, marine safety diagnosis is now evaluated by foreign models. In this paper, therefore, we suggest a domestic model catering to and reflecting the characteristics of Korea's costal areas as well as those of vessel navigator's risk. We can evaluate subjective risks using this model, and can establish the model output as maritime risk exposure assessment system. We have performed analyses of variance and multiple comparison to identify the factor affecting subjective risks. As a result, measurable subjective risks of maritime traffic accident based on our suggested model can be expressed using the maritime risk exposure assessment system with geographic information system.