• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.1087-1098
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• 2019

In this study, we developed an integrated urban river data platform that collects, cleans, and provides data for urban river management. The urban river integrated data platform has the function of collecting data provided by various institutions using the Open API service. The collected data is purified through pre-processing and loaded into a database. The collected data can be reviewed and analyzed using a visualization system and provided through the Open API, so that it can be used as individual input data by combining them in the urban river model. In addition, the development system for real-time data was developed to apply real-time data to urban river models. Through this, users will be able to reduce the time and effort required for data collection, pre-processing and input data construction, thereby increasing efficiency and scalability in the development of urban river models and systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.661-664
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• 2017

Recently, during disasters occurrence, dealing with emergencies has been handled well by the early transmission of disaster relating notifications on social media networks (e.g., Twitter or Facebook). Intuitively, with their characteristics (e.g., real-time, mobility) and big communities whose users could be regarded as volunteers, social networks are proved to be a crucial role for disasters response. However, the amount of data transmitted during disasters is an obstacle for filtering informative messages; because the messages are diversity, large and very noise. This large volume of data could be seen as Social Big Data (SBD). In this paper, we proposed a big data platform for collecting and analyzing disasters' data from SBD. Firstly, we designed a collecting module; which could rapidly extract disasters' information from the Twitter; by big data frameworks supporting streaming data on distributed system; such as Kafka and Spark. Secondly, we developed an analyzing module which learned from SBD to distinguish the useful information from the irrelevant one. Finally, we also designed a real-time visualization on the web interface for displaying the results of analysis phase. To show the viability of our platform, we conducted experiments of the collecting and analyzing phases in 10 days for both real-time and historical tweets, which were about disasters happened in South Korea. The results prove that our big data platform could be applied to disaster information based systems, by providing a huge relevant data; which can be used for inferring affected regions and victims in disaster situations, from 21.000 collected tweets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.6
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• pp.2793-2800
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• 2011

The purpose of this research is to develop and optimize a lane departure warning application based on a smartphone which can be applicable as a new platform for various mobile information applications. Recently, a lane detection warning system which is a representative application among safe driving assistant solutions is being commercialized. Due to the necessity of powerful embedded hardware platform and its price, its market is still not growing. In this research, it is proposed to develop and optimize a lane departure warning application on iPhone 3GS. OpenCV is used for efficient image processing, and for lane detection a heuristic algorithm based on Hough Transform is proposed. The application was developed under Macintosh PC platform with Xcode 3.2.4 development tools, downloaded to the iPhone and has been tested on the real paved road. The experimental result has shown that the detection ratio of the straight lane was over 90% and the processing speed was 1.52fps. For the enhancement of the speed, a few optimization methods were introduced and the fastest speed was 3.84fps. Through the improvement of lane detection algorithm, additional optimization works and the adoption of a new powerful platform, it will be successfully commercialized on smartphone application market.

• The Transactions of the Korea Information Processing Society
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• v.5 no.1
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• pp.73-85
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• 1998

Today's Software Systems are becoming bigger, larger and more complex than ever before. To develop largerscale projects, it is required that many experts of different fields participate and cooperate in the same project. So, it is an applied area of CSCW(Computer Supported Cooperative Works} that centers around methodologies and tools that enable cooperative works by geographically distributed people engaged in all aspects of product development. In this paper, we designed a multi-user cooperative works platform, SPACE(Software Platform for distributed Application sharing under Cooperative Environment} as a infrastructure that support to CSCW based system development for telecommunication and information system. SPACE has a fully distributed architecture under Windows 95 environment, has an application sharing mechanism enabling collaborative use of mteractive application adapt to a mixed GUI sharing technology which capture GUI and screen information, and also, an event sharing technology that has a replicated architecture.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.1
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• pp.17-26
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• 2016

IoT means things space networks that form the intelligent relationship such as sensing, networking, information processing about human being, things and service without explicit mutual cooperation of human being. Lately many IoT groups such as AllSeen Alliance, OIC launched a platform for IoT. Self-adaptive is aimed at implementation without the need for decisions of human being during the operation, so that the machine can respond to changes in its own determination. There is a need to apply the concept of self-adaptive to existing IoT and IoT platform. So In this paper, We look for trends of existing IoT, IoT platform and comparisons by applying a self-adaptive concept to IoT, IoT platform. In addition as an example of this paper, we suggest lacking self-adaptive elements to OIC.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1341-1346
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• 2017

In this paper, we designed the open service platform based on integrated type of individual customized service and intelligent information technology with individual's complex attributes and requests. First, the data collection phase is proceed quickly and accurately to repeat extraction, transformation and loading. The generated data from extraction-transformation-loading process module is stored in the distributed data system. The data analysis phase is generated a variety of patterns that used the analysis algorithm in the field. The data processing phase is used distributed parallel processing to improve performance. The data providing should operate independently on device-specific management platform. It provides a type of the Open API.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.8
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• pp.181-188
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• 2020

The fisheries industry is rapidly shifting from a traditional fishery to aquaculture paradigm and it faces various problems such as depletion of fishery resources and aging of fishing villages. We need the establishment of a fisheries big data platform that includes both the data of the central and surrounding industries of the fisheries industry for enhancement of establishment of a fisheries, 6th industrialization of fishing villages, establishment of related technical standards, and discovery of the new industries to overcome this. Data center agencies should collect, link, and pre-processing, and the platform organizer should create a water industry data virtuous circle through the establishment, operation, and data market of big data platforms to help overcome the current crisis, secure smart fisheries hegemony, and use it as a key to value transfer. Through this study, I would like to propose a policy and technical big data platform construction plan to successfully promote it.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2493-2503
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• 1999

The TMN that appears to operate the various communication networks generally and efficiently is developed under the different platform environment such as the different hardware and the different operating system. One of the main problems is that all the agents of the TMN system must be duplicated and maintain the software and the data blocks that perform the identical function. Therefore, the multi-platform cannot be supported in the development of the TMN agent. In order to overcome these problems, the Farming methodology that is based on the Farmer model has been suggested. With the Farming methodology, the software and the data components which are duplicated and stored in each distributed object are saved in the platform independent class repository (PICR) by converting into the format of the independent componentware in the platform, so that the componentwares that are essential for the execution can be loaded and used statically or dynamically from PICR as described in the framework of each distributed object. The distributed TMN agent of the personal communication network is designed and developed by using the Farmer model.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.129-139
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• 2018

The crowdsourcing software development (CSD) is growing rapidly in the open call format in a competitive environment. In CSD, tasks are posted on a web-based CSD platform for CSD workers to compete for the task and win rewards. Task searching and assigning are very important aspects of the CSD environment because tasks posted on different platforms are in hundreds. To search and evaluate a thousand submissions on the platform are very difficult and time-consuming process for both the developer and platform. However, there are many other problems that are affecting CSD quality and reliability of CSD workers to assign the task which include the required knowledge, large participation, time complexity and incentive motivations. In order to attract the right person for the right task, the execution of action plans will help the CSD platform as well the CSD worker for the best matching with their tasks. This study formalized the task assignment method by utilizing different situations in a CSD competition-based environment in artificial intelligence (AI) planning. The results from this study suggested that assigning the task has many challenges whenever there are undefined conditions, especially in a competitive environment. Our main focus is to evaluate the AI automated planning to provide the best possible solution to matching the CSD worker with their personality type.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.882-885
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• 2014

이미지 혹은 영상에 대한 자동 태깅은 해당 콘텐츠에 대한 추가적인 정보를 자동으로 시스템에 제공하는 기술로써 영상 인식, 콘텐츠 매시업, 정보 검색 등 다양한 기술/서비스 분야에서 여러 목적으로 활용되고 있다. 특히, 방송 콘텐츠는 많은 양의 정보를 제한된 영역 및 시간에 축약하여 담고 있기 때문에 영상 처리 기술을 통한 객체 인식이나, 콘텐츠 매시업, 추천 서비스 등의 성능 향상을 위해 자동 혹은 수동 태깅을 통한 정보 제공이 요구된다. 본 논문에서는 블로그를 이용한 프레임 단위의 방송 콘텐츠 태깅 기술을 제안한다. 제안하는 기술은 기존의 콘텐츠 단위의 정보 제공이나, 수동 태깅 된 정보를 제공하는 기술들과 달리, 영상의 각 프레임에 대한 자동 태깅을 목표로 한다. 제안하는 방법은 거리 학습을 통해 영상의 각 프레임이 가지는 특성을 고려한 모델을 구축한 후, 이를 토대로 영상의 프레임들과 블로그의 이미지를 매칭한다. 매칭된 결과를 기반으로 특정 블로그는 영상 내 특정 프레임 구간에 태깅 된다. 제안한 방법은 이미지 매칭 성능을 측정하여 평가하였다. 블로그 이미지에 대해 Top 1 매칭 프레임을 살펴본 결과, 70%의 정확률을 보였다. 소프트 매칭(Top n)의 경우, 최대 90%의 성능을 얻을 수 있음을 실험을 통해 알 수 있었다.