• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.256-264
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• 2020

Industrial Wireless Sensor Networks (IWSNs) is exploited to achieve various objectives such as improving productivity and reducing cost in the diversity of industrial application, and it has requirements such as low-delay and high reliability packet transmission. To accomplish the requirement, the network manager performs graph construction and resource allocation about network topology, and determines the transmission cycle and path of each node in advance. However, this network management scheme cannot treat mobile devices that cause continuous topology changes because graph reconstruction and resource reallocation should be performed as network topology changes. That is, despite the growing need of mobile devices in many industries, existing scheme cannot adequately respond to path failure caused by movement of mobile device and packet loss in the process of path recovery. To solve this problem, a network management scheme is required to prevent packet loss caused by mobile devices. Thus, we analyse the location and movement cycle of mobile devices over time using machine learning for predicting the mobility pattern. In the proposed scheme, the network manager could prevent the problems caused by mobile devices through performing graph construction and resource allocation for the predicted network topology based on the movement pattern. Performance evaluation results show a prediction rate of about 86% compared with actual movement pattern, and a higher packet delivery ratio and a lower resource share compared to existing scheme.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.19-19
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• 2023

최근 기후변화에 의해 단기간에 많은 양의 집중호우가 발생하여 도시지역의 침수 피해가 증가하고 있다. 이에 도시지역의 홍수 피해 해결을 위해 도심지 홍수 발생 시 홍수정도 및 상황을 파악할 수 있는 장비가 개발되었으나, 실용화 단계까지는 진행이 미흡한 상황이다. 또한 기존 도시지역 홍수 현상 및 원인을 분석하기 위해 수치모형을 활용하고 있으나, 우수관망의 노후화 및 초기 강우패턴 적용에 대한 정확한 해석결과의 어려워 활용성이 낮다. 또한 홍수정도와 발생상황 인지를 위한 계측 장비의 개발 연구는 지속적으로 진행되고 있으나, 계측 장비의 높은 가격으로 전국적으로 설치 할 수 없는 상황으로 이를 대응하기 위한 별도의 방안 마련이 필요한 실정이다. 이를 위해 본 과제에서는 고성능·저비용 계측센서를 개발하여 실용화 가능성을 높이고, 전국에 산재되어있는 CCTV(교통상황, 방법용 등)의 영상을 활용한 침수상황 인지 기술 개발, 계측 데이터와 모니터링 데이터의 활용을 위한 빅데이터 개방 플랫폼을 구축하여, 상습 침수지역에 대해 실시간 감시가 가능한 계측 시스템의 정형 데이터와 CCTV 및 영상 등 모니터링 장비의 비정형 데이터의 분석 기술을 결합한 새로운 도심지 홍수 감시 기술의 개발을 목표로 한다. 이를 위해 본 연구 1차년도에 지표면 침수심 계측센서와 우수관망 월류심 계측센서를 개발하였으며, 2차년도에는개발된 계측센서의 현장실증을 통해 데이터를 수집한다. 수집된 계측센서 데이터와 비정형(CCTV 영상) 데이터의 AI학습을 통해 분석된 침수심, 침수범위, 침수면적 데이터는 도심지 홍수 정보 프로그램을 통해 표출되며, 최종적으로는 현장 상황을 쉽게 파악 가능한 3D 레이어의 형식으로 표출하고자 한다. 추후 도심지 홍수 정보 프로그램을 통해 표출되는 3D 레이어는 환경부가 추진하는 DT(Digital Twin) 연계 인공지능(AI) 홍수예보 사업과의 연계 시 도심지 홍수 지도 구축을 위한 자료로 활용될 수 있을 것으로 판단된다.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.583-589
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• 2012

This Paper contained Managing the Memory With Virtual Server, building Database for Broadcast and statistics, architecture Can Easily Build up Each Analysis algorism and How to Broadcast Analysis outcome for Inteligent Vessel Navigation Analysis System. Also concrete Algorism and formula for each navigation analysis that we studed(Collision, Patten, Traffic separation, Danger Area So on).

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.107-109
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• 2016

최근 클라우드 컴퓨팅 기술의 발전은 기존에 어려웠던 응용연구 분야의 실험 환경 구축을 용이하게 함으로써 새로운 협업연구 패러다임을 가져오고 있다. 본 논문에서는 고성능 연구망 기반의 협업연구 환경을 구축하기 위해 필요한 데이터 공유 및 전송에 관한 서비스 제공 방안을 제안한다. 이러한 서비스 모델은 연구망의 특성을 반영하고, 접근 패턴이 다른 사용자들을 동시에 수용할 수 있도록 구성된다. 이를 토대로, 최근 오픈소스 소프트웨어로 활발히 이용되는 서비스 구성 요소들을 분류 및 선택하여 실험 테스트베드를 구성하고, 활용 시나리오별 데이터 전송 실험을 수행함으로써 제안 서비스의 활용 가능성을 확인하였다.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.35-42
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• 2017

In this paper, a building disaster notification system with MEC (Mobile Edge Computing) technology is proposed, which informs people in a building about the disaster. The overview of MEC is presented, and the structure and characteristics of network using MEC are described. In addition, the characteristics of a enterprise integration pattern based Apache Camel is described, and how to implement MEC with Apache Camel is presented. Finally, an implementation method of building disaster notification system with Apache Camel based MEC is proposed to quickly recognize disasters through sensors and to rapidly evacuate people from buildings.

• School Mathematics
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• v.19 no.1
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• pp.117-135
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• 2017

Even though patterns and correspondence serve a fundamental basis of function for elementary students, there has been lack of research in this field. This study explored prior studies to extract the key instructional elements on how to teach patterns and correspondence. This study then analyzed the unit of 'patterns and correspondence' in the mathematics textbooks in terms of four key instructional elements (i.e., relation to real-life contexts, diversity of pattern tasks, exploration for a correspondence relationship, and teaching variables). The results of this study showed that topics dealing with patterns and correspondence were represented with relation to real-life contexts but diversity of pattern tasks and exploration for a correspondence relationship were needed to be further considered in the textbooks. Another noticeable result was that teaching variables was not explicitly addressed in the textbooks. Based on these results, this study provides textbook writers with implications on what to further consider in dealing with patterns and correspondence.

• Journal of Internet Computing and Services
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• v.10 no.2
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• pp.1-13
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• 2009

Intrusion detection is a process that identifies the attacks and responds to the malicious intrusion actions for the protection of the computer and the network resources. Due to the fast development of the Internet, the types of intrusions become more complex recently and need immediate and correct responses because the frequent occurrences of a new intrusion type rise rapidly. Therefore, to solve these problems of the intrusion detection systems, we propose a sequential pattern miner for analysis of the alert data in order to support intelligent and automatic detection of the intrusion. Sequential pattern mining is one of the methods to find the patterns among the extracted items that are frequent in the fixed sequences. We apply the prefixSpan algorithm to find out the alert sequences. This method can be used to predict the actions of the sequential patterns and to create the rules of the intrusions. In this paper, we propose an extended prefixSpan algorithm which is designed to consider the specific characteristics of the alert data. The extended sequential pattern miner will be used as a part of alert data analyzer of intrusion detection systems. By using the created rules from the sequential pattern miner, the HA(high-level alert analyzer) of PEP(policy enforcement point), usually called IDS, performs the prediction of the sequence behaviors and changing patterns that were not visibly checked.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.6
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• pp.77-90
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• 2015

An increasing number of vehicles is causing various traffic problems such as chronic congestion of highways and air pollution. Local governments have been managing traffic by constructing systems such as Intelligent Transport Systems (ITS) and Advanced Traffic Management Systems (ATMS) to relieve such problems, but construction of an infrastructure-based traffic system is insufficient in resolving chronic traffic problems. A more sophisticated system with enhanced operational management capabilities added to the existing facilities is necessary at this point. As traffic patterns of the urban traffic flow is time-specific due to the different vehicle populations throughout the time of the day, a local network-wide signal operation plan that can manage such situation-specific traffic patterns is deemed to be necessary. Therefore, this study is conducted for the purpose of establishment of a plan for contextual signal control management through signal optimization at the network level after setting the Frame Signal in accordance to the traffic patterns gathered from the short-term traffic forecast data as a means to mitigate the problems with existing standardized signal operations.

• The Korean Journal of Applied Statistics
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• v.36 no.5
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• pp.473-488
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• 2023

Gangwon-do is one of Korea's most popular tourist destinations, with varying tourism demands and trends across its subregions. It is crucial to identify the characteristics of tourism in each area and compare the tourism patterns over time to devise policies that revitalize tourism in each local government and promote balanced development across regions. In this paper, we classify the regions in Gangwon-do based on tourism data from the last four years and analyze the tourism pattern of each region using the non-Euclidean additive model proposed by Jeon et al. (2021). The model incorporates the proportions of visitors by age groups and the proportions of navigation searches by destination types as two covariates, and the proportions of tourism expenditure types as a response variable. We estimate the model using the smooth-backfitting method and coordinate-wise bandwidth selection. The results are visualized in ternary plots, and changes in tourism patterns over time are analyzed by comparing the ratios of prediction errors to fitting errors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.462-471
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• 2018

Even though software (SW) education has not been considered part of the current national kindergarten curriculum, in practice there is growing interest in adopting it. Teachers would be expected to play a key role in the successful introduction and implementation of new educational changes, such as SW education. In preparation for its adoption in ECE, it would be useful to determine ECE teachers' perception and attitudes toward early childhood software education. For this study, 219 ECE teachers' level of concern toward SW education was surveyed using the Stages of Concern Questionnaire. It was found that the teachers' level of concern was the highest at stage 0-Unconcerned and that they had high levels of stage management, personal and informational concern. Thus, a non-user pattern was mostly indicated. However, compared to the typical non-user pattern, the pattern aspect close to critical non-user ever appeared to some extent. In addition, a significant difference in the level of concern was shown at all stages depending on the awareness of the necessity for SW education. The teachers with SW training experience showed a higher intensity only at stage 0. There was a statistically significant difference in stages 0 and 6 depending on the future implementation decision. These results will be utilized as a resource in building an ECE teachers' support system according to their level of concern about SW education.