• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 한국항해항만학회 2022년도 춘계학술대회
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• pp.383-384
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• 2022

Following the development of technologies such as digital twin, IoT, and AI after the 4th industrial revolution, decision-making problems are being solved based on high-dimensional data analysis. This has recently been applied to the port logistics sector, and a number of studies on big data analysis, deep learning predictions, and simulations have been conducted on container terminals to improve port productivity. These high-dimensional data analysis techniques generally require a large number of data. However, the global port environment has changed due to the COVID-19 pandemic in 2020. It is not appropriate to apply data before the COVID-19 outbreak to the current port environment, and the data after the outbreak was not sufficiently collected to apply it to data analysis such as deep learning. Therefore, this study intends to present a port data augmentation method for data analysis as one of these problem-solving methods. To this end, we generate the container stowage situation of the yard through a generative adversarial neural network model in terms of container terminal operation, and verify similarity through statistical distribution verification between real and augmented data.

• The Journal of the Convergence on Culture Technology
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• 제10권2호
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• pp.537-545
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• 2024

The importance of University Archives Management is increasing. In this study, we researched cases of collecting and managing educational archival contents in universities. Developed archival contents for software practical education, and implemented it to the Capstone Design course and overseas program. The effect of applying the model was analyzed through surveys and interviews. The Capstone Design Survey, involving 349 participants, indicated the highest satisfaction with the University-Industry Cooperation type. The experience of dissemination and enhancement was aggregated as the second highest satisfaction. In the second survey, 62 students who had participated in the overseas program over the span of two years took part. All nine Likert-type questions showed high satisfaction scores of more than 4 points. The top three satisfaction factors-content, program type, and advanced experience-showed high satisfaction scores of 4.85, 4.74, and 4.71, respectively. Through interviews with professors, mentors, and students, it was also confirmed that instructional methods utilizing archival contents are effective. And the model we developed is applicable for convergence education.

• Journal of Navigation and Port Research
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• 제48권1호
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• pp.62-77
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• 2024

In the maritime shipping industry, imbalance between supply and demand has persistently increased, leading to the utilization of blank sailings by major shipping companies worldwide as a key means of flexibly adjusting vessel capacity in response to shipping market conditions. Traditionally, blank sailings have been frequently implemented around the Chinese New Year period. However, due to unique circumstances such as the global pandemic starting in 2020 and trade tensions between the United States and China, shipping companies have recently conducted larger-scale blank sailings compared to the past. As blank sailings directly impact freight transport delays, they can have negative repercussions from perspectives of both businesses and consumers. Therefore, this study employed Poisson regression models and negative binomial regression models to analyze the influence of maritime freight rate determinants on shipping companies' decisions regarding blank sailings, aiming to proactively address potential consequences. Results of the analysis indicated that, in Poisson regression analysis for 2M, significant variables included global container shipping volume, container vessel capacity, container ship scrapping volume, container ship newbuilding index, and OECD inflation. In negative binomial regression analysis, ocean alliance showed significance with global container shipping volume and container ship order volume, the alliance with container ship capacity and interest rates, non-alliance with international oil prices, global supply chain pressure index, container ship capacity, OECD inflation, and total alliance with container ship capacity and interest rates.

• Journal of The Korean Association For Science Education
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• 제44권2호
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• pp.141-153
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• 2024

The 2022 revised science curriculum aims to develop the ability to solve scientific problems arising in daily life and society based on convergent thinking stimulated through participation in research activities using artificial intelligence (AI). Therefore, we developed a science-AI convergence education program that combines the science curriculum with artificial intelligence and employed it in convergence classes for high school students. The aim of the science-AI convergence class was for students to qualitatively understand the movement of a damped pendulum and build an AI model to predict the position of the pendulum using the block coding platform KNIME. Individual in-depth interviews were conducted to understand and interpret the learners' experiences. Based on Giorgi's phenomenological research methodology, we described the learners' learning processes and changes, challenges and limitations of the class. The students collected data and built the AI model. They expected to be able to predict the surrounding phenomena based on their experimental results and perceived the convergence class positively. On the other hand, they still perceived an with the unfamiliarity of platform, difficulty in understanding the principle of AI, and limitations of the teaching method that they had to follow, as well as limitations of the course content. Based on this, we discussed the strengths and limitations of the science-AI convergence class and made suggestions for science-AI convergence education. This study is expected to provide implications for developing science-AI convergence curricula and implementing them in the field.

• Journal of Intelligence and Information Systems
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• 제26권4호
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Korean Journal of Veterinary Research
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• 제41권4호
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• pp.571-578
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• 2001

To evaluate if the apoptotic fragment assay could be used to estimate the dose prediction after radiation exposure, we examined apoptotic mouse crypt cells per 1,000 cells after whole body $^{60}Co$ $\gamma$-rays and 50MeV ($p{\rightarrow}Be^+$) cyclotron fast neutron irradiation in the range of 0.25 to 1 Gy, respectively. The incidence of apoptotic cell death rose steeply at very low doses up to 1 Gy, and radiation at all doses tigger rapid changes in crypt cells in stem cell region. These data suggest that apoptosis may play an important role in homeostasis of damaged radiosensitive target organ by removing damaged cells. The curve of dose-effect relationship for the data of apoptotic fragments was obtained by the linear-quadratic model $y=0.18+(9.728{\pm}0.887)D+(-4.727{\pm}1.033)D^2$ ($r^2=0.984$) after $\gamma$-rays irradiation, while $y=0.18+(5.125{\pm}0.601)D+(-2.652{\pm}0.7000)D^2$ ($r^2=0.970$) after neutrons in mice. The dose-response curves were linear-quadratic, and a significant dose-response relationship was found between the frequency of apoptotic cell and dose. These data show a trend towards increase of the numbers of apoptotic crypt cells with increasing dose. Both the time course and the radiation dose-response curve for high and low linear energy transfer (LET) radiation modalities were similar. The relative biological effectiveness (RBE) value for crypt cells was 2.072. In addition, there were significant peaks on apoptosis induction at 4 and 6h after irradiation, and the morpholoigcal findings of the irradiated groups were typical apoptotic fragments in crypt cells that were hardly observed in the control group. Thus, apoptosis in crypt cells could be a useful in vivo model for studying radio-protective drug sensitivity or screening test, microdosimetric indicator and radiation-induced target organ injury. Since the apoptotic fragment assay is simple, rapid and reproducible in the range of 0.25 to 1 Gy, it will also be a good tool for evaluating the dose response of radiation-induced organ damage in vivo and provide a potentially valuable biodosimetry for the early dose prediction after accidental exposure.

• Journal of the Korean Institute of Landscape Architecture
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• 제46권3호
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• pp.1-13
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• 2018

Landscape Architecture is a minority manpower field that requires wide knowledge and experience. Therefore, the service market is narrower than other fields, and education service for practitioners is lacking. The purpose of this study is to propose e-learning content development methodology that can provide customized landscaping practical education according to the level of education and increase the economic efficiency of the development process. First, in theoretical review, the ADDIE model was modified to select the curriculum development model that pursues efficiency and introduced the concept of reusing learning objects in the SCORM-based model. In particular, to overcome the problems presented in the precious studies, the analysis and design stages have been strengthened and faculty designers with integrated knowledge of Landscape Architecture and ICT have led the overall phase. The actual development process is based on a step by step procedure--analysis of landscaping practitioners needs and environments, etc., teaching and learning procedures and the design of activities considering contents reuse, the first development such as actual shooting and editing, and the second development reusing the first development content--and was done in the order of evaluation and revision of professionalism and satisfaction. As a result of the study, the space-based courses composed of modular learning objects were first developed as 216 courses in 8 subjects, as 208 courses in 3 subjects in total, in which the modularized learning object are crossed and combined in units and difficulty-based courses were second developed in 216 courses with 3 subjects in total. As a result of the evaluation the satisfaction assessment of the overall satisfaction was 4.20 and the average value of the eight measures was 3.97, both being close to 4.0. For the professional assessment, the scores of 8 subjects were very high at 84.8 to 96.4 points. in context, the scores of 5 subjects were equal to from 89.9 to 96.4 points. In conclusion, as the study was conducted based on a clear understanding of the digital characteristics of e-learning contents and general characteristic of the landscaping industry, it was possible to develop a curriculum by developing a course composed of modular learning objects and reusing learning objects by unit. In particular, it has been proven to be effective in conveying professional knowledge and experiences via general procedures and provided an opportunity to overcome some analog problems that may occur in offline education. In the future, further studies need to be done by expanding the content and by focusing on segmented subjects.

• Journal of Dental Rehabilitation and Applied Science
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• 제28권2호
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• pp.147-161
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• 2012

This study is to assess the effect of horizontal misfit of an implant supported 3-unit fixed prosthodontics on the stress development at the marginal cortical bone surrounding implant neck. Two finite element models consisting of a three unit fixed prosthodontics and an implant/bone complex were constructed on a three dimensional basis. The three unit fixed prosthodontics were designed either shorter (d=17.8mm model) or longer (d=18.0mm model) by 0.1mm than the span of two implants placed at the mandibular second premolar and second molar areas 17.9mm apart. Fitting of the fixed prosthodontics onto the implant abutments was simulated by a total of 6 steps, that is to say, 0.1mm displacement per each step, using DEFORM 3D (ver 6.1, SFTC, Columbus, OH, USA) program. Stresses in the fixed prosthodontics and implants were evaluated using von-Mises stress, maximum compressive stress, and radial stress as necessary. The d=17.8mm model assembled successfully on to the implant abutments while d=18.0mm model did not. Regardless if the fixed prosthodontics fitted onto the abutments or not, excessively higher stresses developed during the course of assembly trial and thereafter. On the marginal cortical bone around implants during the assembly, the peak tensile and compressive stresses were as high as 186.9MPa and 114.1MPa, respectively, even after the final sitting of the fixed prosthodontics (for d=17.8mm model). For this case, the area of marginal bone subject to compressive stresses above 55MPa, equivalent of the $4,000{\mu}{\varepsilon}$, i.e. the reported threshold strain to inhibit physiological remodeling of human cortical bone, extended up to 2mm away from implant during the assembly. Horizontal misfit of 0.1mm can produce excessively high stresses on the marginal cortical bone not only during the fixed prosthodontics assembly but also thereafter.

• Tuberculosis and Respiratory Diseases
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• 제45권1호
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• pp.99-106
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• 1998

Background: Bronchial asthma is a complex disease, which is characterized by spontaneous exacerbations of airway obstruction and persistent bronchial hyperresponsiveness. Animal models have fallen short of reproducing the human disease, particularly in mimicking the spontaneous and persistent airflow obstruction that characterized in asthma. In animals, airflow obstruction is usually assessed by measuring airflow resistance during tidal breathing under such invasive technique as tracheostomy and anesthesia. A noninvasive technique for measuring pulmonary function in small animals is needed to evaluate long-term changes in lung function during the course of experimentally produced disease without sacrificing the animal. Purpose: The purpose of this study was to evaluate early bronchoconstrcition after allergen challenge and airway responsiveness (AR) to inhaled methacholine in nonanethetized, unrestrained guinea pigs. Method: Guinea pig model of asthma was sensitized by subcutaneous injection with ovalbumin and challenged by inhalation of aerosolized ovalbumin(1% wt/vol ovlabumin). Airflow obstruction of conscious guinea pig was measured as specific airway resistance (airway resistance $\times$ thoracic gas volume). Airway resistance and thoracic gas volume of conscious guinea pig were assessed by body plethysmography before challenge and at regular intervals for as long as 30 minutes after challenge. AR to aerosolized methacholine of asthma group was compared with that of control group in body plethysmography. Result: Asthma model<> developed in 13 (65%) among 20 guinea pigs, in which early responses occurred in the airways after the exposure to inhalation with ovalbumin. Airway challenge with ovalbumin caused increase in specific airway resistance, which peaked at 6 minutes and amounted to a $231.5{\pm}30.4%$ increase from baseline. AR to aerosolized methacholine of asthma model increased significantly compared with control group. Conclusion: These results have showed a useful animal model to evaluate early bronchoconstrcition after allergen challenge and airway responsiveness in nonanethetized, unrestrained guinea pigs.

• The KIPS Transactions:PartD
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• 제12D권3호
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• pp.417-428
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• 2005

Today, IT organizations perform projects with vision related to marketing and financial profit. The objective of realizing the vision is to improve the project performing ability in terms of QCD. Organizations have made a lot of efforts to achieve this objective through process improvement. Large companies such as IBM, Ford, and GE have made over $80\%$ of success through business process re-engineering using information technology instead of business improvement effect by computers. It is important to collect, analyze and manage the data on performed projects to achieve the objective, but quantitative measurement is difficult as software is invisible and the effect and efficiency caused by process change are not visibly identified. Therefore, it is not easy to extract the strategy of improvement. This paper measures and analyzes the project performance, focusing on organizations' external effectiveness and internal efficiency (Qualify, Delivery, Cycle time, and Waste). Based on the measured project performance scores, an OT (Opportunity Tree) model was designed for optimizing the project performance. The process of design is as follows. First, meta data are derived from projects and analyzed by quantitative GQM(Goal-Question-Metric) questionnaire. Then, the project performance model is designed with the data obtained from the quantitative GQM questionnaire and organization's performance score for each area is calculated. The value is revised by integrating the measured scores by area vision weights from all stakeholders (CEO, middle-class managers, developer, investor, and custom). Through this, routes for improvement are presented and an optimized improvement method is suggested. Existing methods to improve software process have been highly effective in division of processes' but somewhat unsatisfactory in structural function to develop and systemically manage strategies by applying the processes to Projects. The proposed OT model provides a solution to this problem. The OT model is useful to provide an optimal improvement method in line with organization's goals and can reduce risks which may occur in the course of improving process if it is applied with proposed methods. In addition, satisfaction about the improvement strategy can be improved by obtaining input about vision weight from all stakeholders through the qualitative questionnaire and by reflecting it to the calculation. The OT is also useful to optimize the expansion of market and financial performance by controlling the ability of Quality, Delivery, Cycle time, and Waste.