• KIPS Transactions on Software and Data Engineering
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• v.1 no.2
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• pp.91-102
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• 2012

Computer aided language learning has become popular. But the level of automation of constructing a Korean learning assistant system is not so high because a practical language learning system needs large scale knowledge resources, which is very hard to acquire. In this paper, we propose a Korean learning assistant system that utilizes easily obtainable knowledge resources like a corpus, web documents and a lexicon. Our system has three modules - problem solving, pronunciation marker and writing assistant. Automatic problem generator uses a corpus and a lexicon to make problems with one correct answer and three distracters, then verifies their suitability by utilizing frequency information from web documents. We analyze pronunciation rules for a pronunciation marker and recommend appropriate words and sentences in real-time by using data extracted from a corpus. In experiment, we evaluate 400 automatically generated problems, which show 89.9% problem suitability and 64.9% example suitability.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.117-124
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• 2008

This paper introduces a novel approach for automated mapping of a map feature that is vinyl green house in high spatial resolution imagery Some map features have their unique spatial patterns. These patterns are normally detected in high spatial resolution remotely sensed data by human recognition system. When spatial patterns can be applied to map feature identification, it will improve image classification accuracy and will be contributed a lot to feature identification. In this study, an automated feature identification approach using spatial aucorrelation is developed, specifically for the vinyl green house that has distinctive spatial pattern in its array. The algorithm aimed to develop the method without any human intervention such as digitizing. The method can investigate the characteristics of repeated spatial pattern of vinyl green house. The repeated spatial pattern comes from the orderly array of vinyl green house. For this, object-based approaches are essential because the pattern is recognized when the shapes that are consists of the groups of pixels are involved. The experimental result shows very effective vinyl house extraction. The targeted three vinyl green houses were exactly identified in the IKONOS image for a part of Jeju area.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.236-242
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• 2019

Recently, scanning projects have been carried out in various construction and construction fields for maintenance purposes. The point cloud generated by the scan results is composed of a number of points representing the object to be scanned. The process of extracting the necessary information, including dimensions, from such scan data is called paradox. The reverse engineering process of modeling a point cloud as BIM involves considerable manual work. Owing to the time-consuming reverse engineering nature of the work, the costs increase exponentially when rework requests are made, such as design changes. Reverse engineering automation technology can help improve these problems. On the other hand, the reverse design product is variable depending on the use, and the kind and detail level of the product may be different. This paper proposes the G2BM (Geometry-to-BIM mapping) rule definition method that automatically maps a BIM object from a primitive geometry to a BIM object. G2BM proposes a process definition and a customization method for reverse engineering BIM objects that consider the use case variability.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.335-344
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• 2021

The purpose of this paper is the development of course data models and learning achievement computation algorithms for enabling the course-embedded assessment(CEA), which is essential of competency-based education in higher education. The previous works related CEA have weakness in the development of the systematic solution for CEA computation. In this paper, we propose data models and algorithms to implement competency-based assessment system. Our data models are composed of a layered architecture of learning outcomes, learning modules and activities, and an associative matrix of learning outcomes and activities. The proposed methods can be applied to the development of the course-embedded assessment system as core modules. We evaluated the effectiveness of our proposed models through applying the models to a practical course, Java Programing. From the result of the experiments we found that our models can be used in the assessment system as a core module.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.115-123
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• 2021

Manufacturing execution system is a factory information system that handles production-related quality data as well as executes production plans of process unit for all resources in the production process on site. As the 4th industrial revolution, which maximizes an automation and connectivity with artificial intelligence, has become a hot topic, manufacturers are showing interest in building a smart factories, but enormous construction costs and unstandardized production processes are obstacles to smart factory construction. Therefore, this paper designs and implements a manufacturing execution system for building a smart factory in a deterioration factory. we propose a Web-based manufacturing execution system aiming at a smart factory at the basic level for steel wire processing. The proposed system will smoothly support interworking with the existing ERP system using REST APIs, and will consider extensibility so that it can be used in various devices and browsers. We will show practicality by implementing the proposed WoT-based manufacturing execution system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.792-798
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• 2021

In this paper, an algorithm for determining the coagulant input rate in the drug-injection tank during the process of the water purification plant was derived through big data analysis and prediction based on artificial intelligence. In addition, analysis of big data technology and AI algorithm application methods and existing academic and technical data were reviewed to analyze and review application cases in similar fields. Through this, the goal was to develop an algorithm for determining the coagulant input rate and to present the optimal input rate through autonomous driving simulator and pilot operation of the coagulant input process. Through this study, the coagulant injection rate, which is an output variable, is determined based on various input variables, and it is developed to simulate the relationship pattern between the input variable and the output variable and apply the learned pattern to the decision-making pattern of water plant operating workers.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.79-86
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• 2023

Construction is one of the oldest fields of providing human living comfort. However, despite the continuous development not only in IT but also in other fields, productivity degradation due to low automation is still serious. In particular, the use of the 4th industrial revolution technologies in construction is just beginning. Blockchain, which is one of the 4th industrial revolution technologies, is a type of a distributed database that is used to replicate, share, and synchronize data spread across different geographical locations, such as multiple sites, countries, or organizations. In this paper, we introduce the block chain and analyze use cases according to seven themes in construction. As a result of the analysis, it is expected to increase the understanding of blockchain in construction and provide usefulness for the development of various services in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.651-657
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• 2023

Railroad alignment improvements and operating speed increase occupy considerable portion in recent railroad market. Developing countries have limitations to construction of new high speed railroads due to the burden of budgets and the lack of demands, and the projects of operating speed increase arepracticallyrecommended. Thisstudy developed the methodologyto provide the railroad alignment design alternatives and the costs by upgrading the "Intelligent Railroad Alignment Design Program (ei-Rail)" which has been used to obtain the alignment plans and construction costs for railroad construction projects. The program provides the cost for alignment improvement, design drafts and the effects of operating speed increase with the input of target improvement speed and the prevailing railroad alignment on the numerical map. It is then expected for the ei-Rail program to be used for the supporting tool for the railroad alignment improvement projects.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.76-76
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• 2020

국가 물관리일원화 이후, 지방하천 관리에 대한 지자체 역할과 권한이 커지고 있으며, 중앙정부의 물관리 수준에 부합하는 데이터관리 체계구축 및 지속적인 품질관리(Quality Control, QC)와 표준화(Standardization) 기술개발이 요구되고 있다. 지자체의 경우 기존의 행정구역별로 분산 관리해오던 물관리 시스템을 유역단위로 전환할 필요가 있으며, 국가하천 구간과 연계한 종합적인 관리가 필요한 실정이다. 서울시의 물관리 시스템은 자치구별로 산재해 있으며, 관리 주체 및 해당 변수에 따라 제공되는 정보가 다르고 하천유역 단위로 분류되어 있지 않다. 따라서, 서울시와 자치구, 중앙정부 및 관련 기관과의 연계성 있는 정보제공을 위한 데이터 플랫폼 구축 기술개발이 필요한 실정이다. 본 연구에서는, 빅데이터, AI 기술을 활용한 물정보의 품질관리 자동화 기술개발과 지속적인 유지관리 및 표준화 정보제공 시스템 구축 기능을 포함하는 서울시 통합물관리 데이터 플랫폼 구축 목표 모델을 제시하였으며, 서울시 물관리 체계와 관련하여 SWAT 분석을 통한 단계별 사업추진 로드맵을 도출하였다. 분석결과, 서울시 통합물관리 플랫폼 구축을 위해서는 유역별 수량-수질 통합 모니터링 및 모델링 기술개발, 빅데이터 기반 물 정보화 플랫폼 구축 기술개발, 지방하천 유역 거버넌스 구축 및 법제도 정비 방안 마련이 요구되며, 관련하여 주요 이슈(3대 핵심전략, 10개 단위과제)를 도출하여 관련 연구과제를 제안하였다. 마지막으로, 서울시 통합물관리 정책 실현을 위해서는 법제도 마련이 시급하며, 서울시 '통합물관리 기본조례' 제정을 통한 기반을 조성할 필요가 있음을 시사하였다. 또한, 다양한 분야 이해관계자 협의체인 '서울시 통합물관리위원회(가칭)'의 거버넌스를 구성하여 운영하는 것이 현실적이며, 한강유역관리 및 지방하천 관리와 관련한 중추적인 역할 수행과 쟁점 논의 등 합리적 합의가 가능할 것으로 기대한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.669-670
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• 2020

현재 4차 산업이 진행됨으로써 대부분의 사물들이 자율화 기능이 더해지는 시대가 오고 있다. 자율화 기술이 발전됨으로써 모든 사람들은 삶을 살아가면서 스스로 문제를 해결해 나갈수 있으며 기존의 생활속도보다 빨라지는 것을 느낄수 있을 것이다. 그래서 마트에서도 쇼핑을하면서 소비자들이 어떻게 쇼핑을 할 때 현재의 수준보다 쇼핑의 질이 높아 질지 고안해보았다. 본 과제물은 소비자들이 쇼핑을할 때 보다 편리하게 일을 처리할수도록 스마트 기능을 카트와 카운터에 추가하였다. 카트에 디스플레이와 바코드 스캐너를 부착함으로써 검색을 통해 소비자들이 원하는 물품의 가격, 위치등의 정보를 알아 낼 수 있고 현재 카트에 담긴 물품의 총 가격을 알 수 있다. 또한, 쇼핑을 마치고 계산을할 때 계산 대기줄이 길어지는 불편함을 해소하기위해 자동계산 기능이 있다. 쇼핑을 마친 소비자가 카트를 카운터로 끌고가면 카트에 저장되어 있는 쇼핑정보가 카운터의 디스플레이에 표시되고 카트와 카운터의 정보가 일치한다면 소비자가 카트에 요금을 충전해 스스로 계산을 수행할수 있다. 이런 자동화, 스마트 기능들은 소비자들의 편리함과 시간을 단축시킬수 있을 것이다.