• 한국측량학회지
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• 제39권5호
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• pp.289-295
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• 2021

Recently, owing to the development of autonomous vehicles, research on precisely determining the position of a moving object has been actively conducted. Previous research mainly used the fusion of GNSS/IMU (Global Positioning System / Inertial Navigation System) and sensors attached to the vehicle through a Kalman filter. However, in recent years, new technologies have been used to determine the location of a moving object owing to the improvement in computing power and the advent of deep learning. Various techniques using RNN (Recurrent Neural Network), LSTM (Long Short-Term Memory), and NARX (Nonlinear Auto-Regressive eXogenous model) exist for such learning-based positioning methods. The purpose of this study is to compare the precision of existing filter-based sensor fusion technology and the NARX-based method in case of GNSS signal blockages using simulation data. When the filter-based sensor integration technology was used, an average horizontal position error of 112.8 m occurred during 60 seconds of GNSS signal outages. The same experiment was performed 100 times using the NARX. Among them, an improvement in precision was confirmed in approximately 20% of the experimental results. The horizontal position accuracy was 22.65 m, which was confirmed to be better than that of the filter-based fusion technique.

• 디지털융복합연구
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• 제14권10호
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• pp.17-23
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• 2016

중국의 고대 문자인 "갑골문" 상형문자를 디지털과 결합시켜 대중화 시키는 것도 매우 의미 있는 일이라 사료된다. 표의문자 (表意文字) 인 중국 문자는 표음 문자 (表音文字) 인 한글과는 다르게, 보여 지는 시각효과가 크고 또 그 이미지화된 자료를 가지고 의미를 상고해 내는 작업을 함에 있어서 디지털의 기술을 빌려 쓴다면, 앞으로 중문학계는 물론이고 더 나아가 인문학계와 융합하는 문제는 시간문제라는 생각이 든다. 고대(상형) 문자를 컴퓨터과학, 즉 디지털과 결합시킨다는 것은 e-learing 의 기술적인 도입과 결합과도 상관이 있을 것 같은데, 앞으로 디지털 시대를 맞아하여 인문학과 자연과학과의 결합이 절실해 지리라 본다. 이를 위하여 e-learning 과 디지털 교육이 시급하며, 상형문자(표의문자)의 데이터베이스 구축 및 자료화 작업은 교육에 있어서도 매우 유용할 것이라 사료된다.

• Asian review of World Histories
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• 제4권1호
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• pp.3-34
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• 2016

This introduction is both a statement of a research problem and an account of the first research results for its solution. As more historical databases come online and overlap in coverage, we need to discuss the two main issues that prevent 'big' results from emerging so far. Firstly, historical data are seen by computer science people as unstructured, that is, historical records cannot be easily decomposed into unambiguous fields, like in population (birth and death records) and taxation data. Secondly, machine-learning tools developed for structured data cannot be applied as they are for historical research. We propose a complex network, narrative-driven approach to mining historical databases. In such a time-integrated network obtained by overlaying records from historical databases, the nodes are actors, while thelinks are actions. In the case study that we present (the world as seen from Venice, 1205-1533), the actors are governments, while the actions are limited to war, trade, and treaty to keep the case study tractable. We then identify key periods, key events, and hence key actors, key locations through a time-resolved examination of the actions. This tool allows historians to deal with historical data issues (e.g., source provenance identification, event validation, trade-conflict-diplomacy relationships, etc.). On a higher level, this automatic extraction of key narratives from a historical database allows historians to formulate hypotheses on the courses of history, and also allow them to test these hypotheses in other actions or in additional data sets. Our vision is that this narrative-driven analysis of historical data can lead to the development of multiple scale agent-based models, which can be simulated on a computer to generate ensembles of counterfactual histories that would deepen our understanding of how our actual history developed the way it did. The generation of such narratives, automatically and in a scalable way, will revolutionize the practice of history as a discipline, because historical knowledge, that is the treasure of human experiences (i.e. the heritage of the world), will become what might be inherited by machine learning algorithms and used in smart cities to highlight and explain present ties and illustrate potential future scenarios and visionarios.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2022년도 춘계학술대회
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• pp.391-393
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• 2022

최근에는 딥러닝과 빅데이터를 기반으로 한 수요예측 기술이 전자상거래, 물류, 유통 분야의 스마트화를 가속화하고 있다. 특히, 글로벌 운송 네트워크와 현대적인 지능형 물류의 중심인 항만은 4차 산업혁명으로 인한 세계 경제 및 항만 환경의 변화에 발 빠르게 대응하고 있습니다. 항만물동량 예측은 신항만 건설, 항만확장, 터미널 운영 등 다양한 분야에서 중요한 영향을 담당하고 있다. 따라서 본 연구의 목적은 항만 물동량 예측에 자주 쓰이는 시계열 분석과 타 산업에서 좋은 결과를 도출해내고 있는 딥러닝 분석을 비교하여 부산항의 미래 컨테이너 예측에 적합한 예측모델을 제시하는 것이다. 부산항 컨테이너 물동량을 이용하여 학습시키고 그 이후 물동량 예측을 진행하였다. 또한, 상관관계 분석을 통해 물동량 변화와 관련된 외부변수를 선정하여 다변량 딥러닝 예측모델에 적용하였다. 그 결과 부산항 컨테이너 물동량만 이용한 단일변수 예측모델에서 LSTM의 오차가 가장 낮았고, 외부변수를 이용한 다변수 예측모델에서도 LSTM의 성능이 가장 우수하였다.

• 공학교육연구
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• 제20권2호
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• pp.39-49
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• 2017

This research aims to explore the relationships between 'teamwork skills' (often called team activity competence) and 'thinking styles' of engineering students in Korea, and to provide an explanation for the application of team-based environment as well as for the increase of teamwork skills. Teams and team activity are pervasive in today's organization and there has been relatively much research on teamwork skills and its related factors. However, to date, little attention has been paid to the teamwork skills, essential factor in team-based environment and its relationships with thinking styles. This study was conducted with 383 engineering students at P University, and students' teamwork skills as well as thinking styles have been measured before and after team-based learning class (hereafter TBL). Our findings show that firstly, there was a significant increase of teamwork skills between before and after TBL class. Second, team activity competence was found to have a higher correlation with most of creativity generating styles (i.e. legislative, judicial, hierarchical and global styles). Third, hierarchical style was found to influence team activity more than other components, and also legislative, external, global and judicial styles contributed to team-based activity. These findings are expected to provide an explanation for the application of thinking styles in team-based environment and will be useful for the improvement of related courses in engineering school.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.93-102
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• 2021

The world is facing an unprecedented economic, social and political crisis with the spread of COVID-19. The Corona Virus (COVID-19) and its global spread have resulted in declaring a pandemic by the World Health Organization. The deadly pandemic of 21st century has spread its wings across the globe with an exponential increase in the number of cases in many countries. The developing and underdeveloped countries are struggling hard to counter the rapidly growing and widespread challenge of COVID-19 because it has greatly influenced the global economies whereby the underdeveloped countries are more affected by its devastating impacts, especially the life of the low-income population. Information and Communication Technology (ICT) were particularly useful in spreading key emergency information and helping to maintain extensive social distancing. Updated information and testing results were published on national and local government websites. Mobile devices were used to support early testing and contact tracing. The government provided free smartphone apps that flagged infection hotspots with text alerts on testing and local cases. The purpose of this research work is to provide an in depth overview of emerging technologies and recent ICT developments to combat COVID-19 Pandemic. Finally, the author highlights open challenges in order to give future research directions.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.156-156
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• 2022

Explicitly spatially distributed and reliable data on industrial water demand is very much important for both policy makers and researchers in order to carry a region-specific analysis of water resources management. However, such type of data remains scarce particularly in underdeveloped and developing countries. Current research is limited in using different spatially available socio-economic, climate data and geographical data from different sources in accordance to predict industrial water demand at finer resolution. This study proposes a random forest regression (RFR) model to predict the industrial water demand at 0.50× 0.50 spatial resolution by combining various features extracted from multiple data sources. The dataset used here include National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL), Global Power Plant database, AQUASTAT country-wise industrial water use data, Elevation data, Gross Domestic Product (GDP), Road density, Crop land, Population, Precipitation, Temperature, and Aridity. Compared with traditional regression algorithms, RF shows the advantages of high prediction accuracy, not requiring assumptions of a prior probability distribution, and the capacity to analyses variable importance. The final RF model was fitted using the parameter settings of ntree = 300 and mtry = 2. As a result, determinate coefficients value of 0.547 is achieved. The variable importance of the independent variables e.g. night light data, elevation data, GDP and population data used in the training purpose of RF model plays the major role in predicting the industrial water demand.

• 한국초등과학교육학회지:초등과학교육
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• 제25권4호
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• pp.383-395
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• 2006

흔히 학교 교육은 학습자의 관심과 필요와 지나치게 동떨어져 있으며 인간 중심적 접근보다는 과학자 중심의 접근법을 유지하고 있다는 비판을 받고 있다. 실제로 과학이 주로 교실 안에서 교과서에 기초하여 가르쳐지지만, 과학의 학습이 교육과정과 학교의 울타리에 국한될 수는 없다. 먼저, 이 논문은 일련의 비유를 통해 과학 교육의 역사적 발전 과정을 간략히 요약 특징화하고, 이어서 과학 교육의 인간주의적 측면과 상황의 차원을 강조하는 소위 'Hearts-On' 과학교육의 새로운 비유를 제안한다. 둘째로, 본 논문은 내용의 상황(즉, 물리적, 개인적, 사회적, 전 지구적)과 학습의 상황(즉, 교과서적, 실험실적, 교실적, 지역사회적, 전 지구적)의 측면에서 전통적인 학교 과학(특히, 물리)교육이 얼마나 제한되어 있는가를 비판적으로 점검한다. 셋째로, 저자 및 동료들이 최근 수행하고 있는 시도들을 Hearts-On 과학교육의 예로 소개한다. 특히, 일련의 지역 사회-기반 과학 프로그램과 상황 물리 책자(즉, 몸물리, 걸치는 물리, 식탁 물리, 스포츠 물리)의 개발 과정들을 요약한다. 마지막으로, 과학적 인간주의라는 아이디어 가 과학 교육의 상황중심적 접근법과 관련하여 논의된다. 이 논문이 과학 교육을 어떻게 교육과정과 학교라는 울타리를 넘는 보다 인간주의적인 것으로 확장할 수 있는가의 문제를 고민하는 데 도움이 되었으면 한다.

• Journal of Ship and Ocean Technology
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• 제12권4호
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• pp.1-6
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• 2008

Nowadays, the computational capability and graphical power based on PCs increase very rapidly every year. As a result, the complicated engineering or scientific problems that could have only been handled by supercomputers a couple of decades ago can now be routinely run on PCs. Besides, the PCs can be assembled in parallel to increase its computational capability theoretically without limitation. The Web-based interface and communication tools are also being enhanced very rapidly and the real-time distance learning (E-Learning) and project cooperation on web get increasing attention. Using the-state-of-the-art computational method, a number of complicated and computationally intensive problems are being solved by PCs. The results can be well demonstrated on screen by graphics and animation tools. Those examples include the simulations of fully nonlinear waves, their interactions with floating bodies, global-motion analysis of multi-unit floating production system including complicated mooring lines and risers. Several examples will be presented in this regard. Also, Web and java-applet based educational tools have been developed at Texas A&M University for better understanding of waves and wave-body interactions. The background and examples of such Web-based educational tools published in Kim et al. (2003) are briefly introduced here.

• 한국IT서비스학회지
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• 제17권4호
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• pp.119-137
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• 2018

Recently, the start-up firms have been under the spotlight because they can create many jobs and are regarded as the growth engine of a country in the fourth industrial revolution. Moreover, after the global financial debacle, many countries emphasize on an entrepreneurial spirit and venture firms. they also pay attention to the importance of educations to promote the start-up firms. In this work, based on technology acceptance model, we try to identify the main factors of accepting online start-up education system. We first defined this system as the online start-up education system which refers to a system to support learning for knowledge, experiences and overall process of start-up firms' tasks. This system also simulates tasks related with prep-entrepreneur so that can be regarded as a kind of decision support systems. As this system has some characteristics, we confirmed some factors of extended technology acceptance model. In our experiments, we find that the perceived ease of use and trust are main factors of acceptance for the online start-up education systems. These results mean that the system should be made to be easy and trustful for their users. Therefore, we expect that this work will be helpful to researchers and developers who consider start-up education systems and provide a way to activate founding start-up firms.