• Journal of Korea Ship Safrty Technology Authority
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• v.5
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• pp.55-71
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• 2000

국내외적인 어업환경 변화 및 1997년 7월 수입자유화조치 이후 우리나라 수산물 소비행태변화에 따라 전체어업에 종사하고 있는 어선의 조업패턴과 수요량도 크게 변모하고 있다. 이와 같은 변화된 여건하에서 국내 연안어업의 실태와 어선건조물량의 분포 및 어업기술 연구개발사례 등을 살펴보고 어선의 수급에 대한 전망과 조업방법의 자동화 방향을 추정하였다.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.285-301
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• 2023

Due to the increasing demand and importance of non-face-to-face education, open online learning platforms are getting interests both domestically and internationally. These platforms exhibit different characteristics from online courses by universities and other educational institutions. In particular, students engaged in these platforms can receive more learner autonomy, and the development of tools to assist learning is required. From the past, researchers have attempted to utilize process mining to understand realistic study behaviors and derive learning patterns. However, it has a deficiency to employ it to the open online learning platforms. Moreover, existing research has primarily focused on the process model perspective, including process model discovery, but lacks a method for the process pattern and instance perspectives. In this study, we propose a method to identify learning patterns within an open online learning platform using process mining techniques. To achieve this, we suggest three different viewpoints, e.g., model-level, variant-level, and instance-level, to comprehend the learning patterns, and various techniques are employed, such as process discovery, conformance checking, autoencoder-based clustering, and predictive approaches. To validate this method, we collected a learning log of machine learning-related courses on a domestic open education platform. The results unveiled a spaghetti-like process model that can be differentiated into a standard learning pattern and three abnormal patterns. Furthermore, as a result of deriving a pattern classification model, our model achieved a high accuracy of 0.86 when predicting the pattern of instances based on the initial 30% of the entire flow. This study contributes to systematically analyze learners' patterns using process mining.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.53-63
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• 2003

The Origin-Destination(OD) matrix is very important in describing transport movements in a region. The OD matrix can be estimated using traffic counts on links in the transport network and other available information. This information on the travel is often contained in a target OD matrix and traffic counts in links. To estimate an OD matrix from traffic counts, they are the major input data which obviously affects the accuracy of the OD matrix estimated, Generally, the quality of an estimated OD matrix depends much on the reliability of the input data, and the number and locations of traffic counting points in the network. Any Process regarding the traffic counts such as the amount and their location has to be carefully studied. The objective of this study is to select of the optimal location of traffic counting points for the OD matrix estimation. The model was tested in nationwide network. The network consists of 224 zones, 3,125 nodes and 6,725 links except to inner city road links. The OD matrix applied for selection of traffic counting points was estimated to 3-constrained entropy maximizing model. The results of this study follow that : the selected alternative to the best optimal counting points of six alternatives is the alternative using common links of OD matrix and vehicle-km and traffic density(13.0% of 6,725 links), however the worst alternative is alternative of all available traffic counting points(44.9% of 6,725 links) in the network. Finally, it should be concluded that the accuracy of reproduced OD matrix using traffic counts related much to the number of traffic counting points and locations.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.109-118
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• 2020

In recent years, the needs of consumers for personality and personalized clothing are increasing. Knitting machines, which produce clothing by the user at low cost, are a good way to meet consumer demand. However, the user is having difficulty in using the knitting machine pattern program, which is a software program, independently of the operation of the knitting machine. Therefore, this study conducted a literature review prior to the empirical research and evaluated the usability by selecting three kinds of frequently used knitting machine pattern programs as research subjects. Based on the nine usability evaluation principles derived from expert group discussions, the study found that the needs of users for nine evaluation principles: visibility, conciseness, operability, consistency, accuracy, flexibility, intuition, error recognition, and supplementary explanation (The purpose of this study is to identify the direction and alternatives of usability improvement for the interface of the knitting machine pattern program.

• Proceedings of the Materials Research Society of Korea Conference
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• 2009.05a
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• pp.12.2-12.2
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• 2009

전자 디스플레이 산업의 중요성과 미래사회에서 요구되는 정보기기로써 유연한 기판을 사용한 소자에 대한 수요가 급격히 증가하고 있으며, 이들 산업에 응용되기 위해서는 저비용, 고생산 공정이 요구되고 있다. 이를 위해 인쇄전자 기술에 대한 연구가 활발히 진행되고 있다. 특히, 금속배선은 모든 소자의 기본이면서 낮은 저항과 높은 신뢰성을 동시에 요구하고 있어 인쇄전자 기술이 해결해야 할 가장 어려운 난제 중의 하나이다. 따라서 본 연구에서는 낮은 저항과 높은 신뢰성을 만족시킬 수 있는 새로운 금속배선 공정으로서 폴리이미드 필름을 초발수 처리한 후 친수 패턴을 하여 전도성 잉크에 함침함으로서 친수 패턴을 따라 금속배선이 이루어 지도록 하는 방법을 제안하고자 한다. 폴리이미드 필름의 표면을 플라즈마 처리하여 표면에 나노돌기를 형성시키고 불소기를 함유한 코팅층을 형성시킴으로써 물에 대한 접촉각이 $150^{\circ}$이상이 되도록 초발수 처리할 수 있었다. 초발수 처리된 폴리이미드 기판에 쉐도우 마스크를 사용하여 UV조사함으로써 조사된 부분만 친수성을 가지는 패턴을 형성하였다. 이렇게 친수 패턴이 제작된 초발수 폴리이미드 유연기판을 실버잉크에 함침함으로써 선폭 $200{\mu}m$를 가지는 금속배선을 형성시켰다. 형성된 금속배선의 단면 형상을 측정하였으며, 열처리를 통하여 비저항이 $30{\mu}{\Omega}$-cm를 얻을 수 있었다. 통상 1회의 함침으로는 금속배선의 두께가 150nm정도로 금속배선으로 사용하기에는 얇아 배선의 두께를 증가시키기 위하여 수 회 함침을 시도하여 $2{\mu}m$의 두께로 증가시킬 수 있었다. 이때 선폭과 선간 간격은 크게 변하지 않고 두께만 증가시킬 수 있었다. 이는 금속배선을 형성한 후에도 폴리이미드 유연기판의 초발수성은 그대로 유지되어 여러번 함침할 때 잉크가 이미 형성된 배선에만 묻게 되어 두께는 증가하나 선폭과 선간 간격은 증가하지 않는 것으로 판단된다. 사용한 실버잉크는 실버의 함량은 10~20wt%인 수계 잉크였다.

• Journal of Korean Society of Water and Wastewater
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• v.25 no.4
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• pp.581-589
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• 2011

Generally, treated water or raw water is transported into storage reservoirs which are receiving facilities of local governments from multi-regional water supply systems. A water supply control and operation center is operated not only to manage the water facilities more economically and efficiently but also to mitigate the shortage of water resources due to the increase in water consumption. To achieve the goal, important information such as the flow-rate in the systems, water levels of storage reservoirs or tanks, and pump-operation schedule should be considered based on the resonable water demand forecasting. However, it is difficult to acquire the pattern of water demand used in local government, since the operating information is not shared between multi-regional and local water systems. The pattern of water demand is irregular and unpredictable. Also, additional changes such as an abrupt accident and frequent changes of electric power rates could occur. Consequently, it is not easy to forecast accurate water demands. Therefore, it is necessary to introduce a short-term water demands forecasting and to develop an application of the forecasting models. In this study, the forecasting simulator for water demand is developed based on mathematical and neural network methods as linear and non-linear models to implement the optimal water demands forecasting. It is shown that MLP(Multi-Layered Perceptron) and ANFIS(Adaptive Neuro-Fuzzy Inference System) can be applied to obtain better forecasting results in multi-regional water supply systems with a large scale and local water supply systems with small or medium scale than conventional methods, respectively.

• Journal of the Economic Geographical Society of Korea
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• v.5 no.1
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• pp.69-87
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• 2002

This study examines the spatial diffusion and locational charateristics of convenience stores in Daegu which had increased rapidly in the 1990s. The first convenience store (CVS) was introduced in the zone of transition of (Namgu district) adjacent to the city center or CBD in 1992. Thereafter they diffused into CBD and residential areas, but they have centered around places where their steady purchasing population was distributed. As a result, the spatial distribution of CVSs in Daegu shows a very uneven pattern concentrated in areas with many high school, in commercial and business areas, and apartment residential areas. It seems that this pattern is derived from two basic locational factors. Primarily, the location of CVSs in Daegu is very closely related with the spatial distribution of the demand population which will be clients for CVSs. Secondarily, it is also affected by the accessibility of streets which the demand population utilizes easily.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.107-120
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• 2023

The public bicycle of Seoul, Ttareungyi, was launched at October 2015 to reduce traffic and carbon emissions in downtown Seoul and now, 2023 Oct, the cumulative number of user is upto 4 million and the number of bike is about 43,000 with about 2700 stations. However, super growth of Ttareungyi has caused the several problems, especially demand/supply mismatch, and thus the Seoul citizen has been complained about out of stock. In this point, this study conducted a real time demand forecasting model to prevent stock out bike at stations. To develop the model, the research team gathered the rental·return transaction data of 20,000 bikes in whole 1600 stations for 2019 year and then analyzed bike usage, user behavior, bike stations, and so on. The forecasting model using machine learning is developed to predict the amount of rental/return on each bike station every hour through daily learning with the recent 90 days data with the weather information. The model is validated with MAE and RMSE of bike stations, and tested as a prototype service on the Seoul Bike Management System(Mobile App) for the relocation team of Seoul City.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.472-479
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• 2024

Half of the world's total population lives in cities, continuous urbanization is progressing, and the urban population is expected to exceed two-thirds of the total population by 2050. To resolve this phenomenon, the Korean government is focusing on building a new urban air mobility (UAM) industrial ecosystem. Airlines are also part of the UAM industry ecosystem and are preparing to improve efficiency in safe operations, passenger safety, aircraft operation efficiency, and punctuality. This study performs demand forecasting using time series data on the number of daily passengers on Korean Air's Gimpo to Jeju route from 2019 to 2023. For this purpose, statistical and machine learning models such as SARIMA, Prophet, CatBoost, and Random Forest are applied. Methods for effectively capturing passenger demand patterns were evaluated through various models, and the machine learning-based Random Forest model showed the best prediction results. The research results will present an optimal model for accurate demand forecasting in the aviation industry and provide basic information needed for operational planning and resource allocation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3508-3517
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• 2013

District is not only a place that every urban activities are executing but also basic unit that are forming urban structure. Therefore this study tried to make land use-transportation model through analyzing $CO_2$ exhausting volumes by assuming 270 scenarios those are postulated various land use patterns and transport policies in District. As results, this study shows best District Unit Design technique is the policy that develop equally all blocks or only outer blocks and introduction of car free zone to inner 2 way streets. Most important policy in order to reduce $CO_2$ gas is to introduce Transportation Demand Management especially in case of hyper high density development. In case of low density development, policy of car free streets in 2 ways roads is efficiency for reducing $CO_2$ gas. And suggested land use-transportation model will be good for choosing alternatives those are able to reduce $CO_2$ in District Unit.