• 산업융합연구
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• 제14권2호
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• pp.15-23
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• 2016

Korea is aging rapidly and unprecedentedly in the world, and the social burden is prospected to be increased rapidly. New business start-up in blue ocean area is boomed in Korea, because sedulousness of people and high household saving rate which are basis of the economic development are getting lower, and propensity of the consumption and debt in household are getting higher. This article is refers that what is success factors of new business start-up in blue ocean through investigating the theoretical concept and the success cases. As a result, the success factors of new business start-up are categorized as environmental factors, strategical factors, organizational factors, personal factors, and factors of growing-up stages. In order not only to identify the success factors, but also to avoid failure, it is important that the basic principle should be followed ; Specifying the objectives, Balancing the fund, Meeting good biz-partners, Analysis of the market and Advice of the experts.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2010년도 추계학술발표대회
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• pp.1399-1401
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• 2010

본 연구는 새만금과 새만금 주변에서 Geosensor 스트림 데이터 측정을 위해 대기관련 센서들로 3개의 클러스터를 구성하고, 수질관련 센서들로 하나의 클러스터를 구성하여 Geosensor 네트워크를 구축하였다. 각 클러스터로부터 5분 단위로 수집된 센서 스트림 데이터를 시스템에 전송하고, 시스템에서는 수신된 스트림 데이터를 분석 및 처리하여 DB에 저장한다. 본 연구에서는 Geosensor 데이터 가공 처리 및 저장, Geosensor 관리, 상황정보 관리, Geosensor 스트림 데이터와 GIS 연동 기능을 포함한 시스템을 개발하고자 한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.997-1000
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• 2021

본 연구는 버스환승정보센터의 디지털기기에 마이크로 인터렉션을 적용하여 UI를 설계한다. UI를 설계하면서 디지털기기에 사용이 어려운 고령자의 특성을 물리적, 인지적 기준으로 분류하고 문제점을 파악하여 지금까지 연구되어온 타이포그래픽, 컬러 등의 그래픽적 요소가 아닌 마이크로인터렉션 효과를 적용하여 고령자에게 디지털기기의 사용성을 높이기 위한 UI를 설계하였다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.972-975
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• 2021

최근 한국 여름 기후의 열대화 현상이 급속화 됨에 따라 잦은 장마와 태풍으로 인해 방제 약품이 씻겨나가 방제가 제대로 안되는 경우가 많아졌다. 이는 식물과 작물들이 병해에 약해지는 계기를 만들었다. 따라서 본 논문에서는 그 중 실내 농사가 어려운 감귤에 중점을 잡고 감귤에서 주로 나타나는 흑점 영상 인식에 대한 모델을 제안하였다. HSV 공간으로의 변환과 LBP 기법을 통해 간단하지만 인식률을 높일 수 있는 방안을 마련하고자 했다. 자원과 계산을 효율적으로 사용하기 위해 모델을 간략화 하였으며 추후 스마트팜의 연구에 도움이 될 수 있을 것이라 기대한다.

• 한국BIM학회 논문집
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• 제8권3호
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• pp.12-19
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• 2018

The research aims to find implications of machine learning and urban big data as a way to construct the flexible transportation network system of smart city by responding the urban context changes. This research deals with a problem that existing a bus headway model is difficult to respond urban situations in real-time. Therefore, utilizing the urban big data and machine learning prototyping tool in weathers, traffics, and bus statues, this research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data is gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is implemented by the machine learning tool (RapidMiner Studio) and conducted several tests for bus delays prediction according to specific circumstances. As a result, possibilities of transportation system are discussed for promoting the urban efficiency and the citizens' convenience by responding to urban conditions.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.440-448
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• 2019

The Internet of Things (IoT) is one of the main enablers for situation awareness needed in accomplishing smart cities. IoT devices, especially for monitoring purposes, have stringent timing requirements which may not be met by cloud computing. This deficiency of cloud computing can be overcome by fog computing for which fog nodes are placed close to IoT devices. Because of low capabilities of fog nodes compared to cloud data centers, fog nodes may not be deployed with all the services required by IoT devices. Thus, in this article, we focus on the issue of fog service placement and present the recent research trends in this issue. Most of the literature on fog service placement deals with determining an appropriate fog node satisfying the various requirements like delay from the perspective of one or more service requests. In this article, we aim to effectively place fog services in accordance with the pre-obtained service demands, which may have been collected during the prior time interval, instead of on-demand service placement for one or more service requests. The concept of the logical fog network is newly presented for the sake of the scalability of fog service placement in a large-scale smart city. The logical fog network is formed in a tree topology rooted at the cloud data center. Based on the logical fog network, a service placement approach is proposed so that services can be placed on fog nodes in a resource-effective way.

• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.1138-1148
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• 2021

In this study, we developed a 'shared-use mobility'-mounted local particulate matter monitoring terminal technology to measure the actual particulate matter concentration around me. As a mobile terminal device in the form of an IoT sensor platform, it is designed to be separated into a control module and a sensor module to minimize interference between sensors and to consider the optimal observation position of each sensor. As a result of the field test, it was confirmed that particulate matter was locally different depending on time and space even within the same area. In addition, it was confirmed that the concentration of particulate matter in the relevant section differed by up to 100 times compared to the surrounding area due to specific sources of particulate matter such as unpaved roads. In addition, we positively reviewed the applicability of the service in the real-time metaverse environment using this result. Through technological advancement and application of multiple shared-use mobilities, we expect to be able to provide new services for practical smart city air environment monitoring, such as localized particulate matter information, air pollution event information, and identification of causes of particulate matter.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.216-216
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• 2015

Frequent hydro-meteorological events caused by global climate change and human exacerbate activities, make the water resource problem more complicated. The increasing speed urbanization brings a significant impact on the city flood control and security, water supply safety, water ecological security, water environment safety and the water engineering security in China, and puts forward higher requirements to urban water integrated management, undoubtedly which become the biggest obstacle for water ecological civilization construction, thus urgent requiring an advanced methods to enhance the effectiveness of the water integrated management. The other fields of smart ideas point out a development path for water resource development. The construction demand of smart water resource is expounded in the paper, combining the philosophy of modern Internet of things with the application of cloud computing technology. The concept of smart water resource is analyzed, the connotation characteristics of smart water resource is extracted, and the general model of smart water resource is refined. Then, the frame structure of smart water resource is put forward. The connotation and the overall framework of the smart water resource represent a higher level of water resource informationization development and provide a comprehensive scientific and technological support to transform water resource management from an extensive, passive, static, branch and traditional management to a fine, active, dynamic, collaborative and modern management.

• 방송공학회논문지
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• 제24권7호
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• pp.1266-1275
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• 2019

With increasing criminal rates and number of CCTVs, much attention has been paid to intelligent surveillance system on the horizon. Object detection and tracking algorithms have been developed to reduce false alarms and accurately help security agents immediately response to undesirable changes in video clips such as crimes and accidents. Many studies have proposed a variety of algorithms to improve accuracy of detecting and tracking objects outside tunnels. The proposed methods might not work well in a tunnel because of low illuminance significantly susceptible to tail and warning lights of driving vehicles. The detection performance has rarely been tested against the tunnel environment. This study investigated a feasibility of object detection and tracking in an actual tunnel environment by utilizing YOLOv3 and Kernelized Correlation Filter. We tested 40 actual video clips to differentiate pedestrians and motorcycles to evaluate the performance of our algorithm. The experimental results showed significant difference in detection between pedestrians and motorcycles without false positive rates. Our findings are expected to provide a stepping stone of developing efficient detection algorithms suitable for tunnel environment and encouraging other researchers to glean reliable tracking data for smarter and safer City.

• 한국인터넷방송통신학회논문지
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• 제20권4호
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• pp.93-99
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• 2020

드론 기술의 발전으로 감시, 재난사고 예방 및 구호 등 공공임무 수행에도 지능화된 드론 활용이 급속히 늘어날 것으로 본다. 드론이 스마트 안전도시 플랫폼에 구축에 사용되기 위해서는 목표물 탐지 및 추적기술, 드론비행 시에 비행 조정 및 장애물 회피기능, 착륙지점 탐지 및 제어 기능 등의 주요 기술 구현이 필요하다. 드론 시스템 은 기술적 파급효과가 크고 신기술 분야의 산업화를 촉진한다. 본 논문에서는 이와 같은 드론 개발을 위하여 객체지향 분석/설계 방법을 이용한 요구사항 분석 및 플로우차트, 화면 설계 등을 보여여줌으로 효과적인 드론 시스템의 소프트웨어 분석 및 설계 방법을 제시하고자 한다.