• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.723-726
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• 2019

사람은 한 장소를 방문할 때 순환 패턴이 있으며, 이 패턴에 여러 싸이클의 경향이 있다. 요즘은 스마트폰 및 기타 휴대용 장치로 개인 이동성 데이터를 수집하는 것이 가능하다. 이러한 장치는 다양한 위치 데이터를 수집하고 여러가지 방법으로 분석할 수 있게 해준다. 위치 수집기를 기반으로 지구 위치 데이터에서 추출된 사람의 이동성 모델을 수립하고, 위치 클러스터를 방문자의 순환 패턴을 조사할 수 있다. 수년 동안 수집된 개인의 이동성 모델을 토대로 클러스터 재방문 시간을 계산 후 분석하여 그래프로 시각화하였다. 시간 순서의 위치 클러스터와 방문 클러스터에 대한 위치 데이터는 1 분 단위로 측정된다. 전체 데이터 방문 횟수는 15 분마다 정규화하고, 자원 봉사자의 다양한 지리적 위치 데이터 셋에 대해 방문의 순환 패턴은 자기 상관, 자기 공분산 및 재방문 시간으로 살펴볼 수 있다.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.10
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• pp.277-284
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• 2021

Recently, the smart home environment is expected to be a platform that collects, integrates, and utilizes various data through convergence with wireless information and communication technology. In fact, the number of smart devices with various sensors is increasing inside smart homes. The amount of data that needs to be processed by the increased number of smart devices is also increasing, and big data processing systems are actively being introduced to handle it effectively. However, traditional big data processing systems have all requests directed to cluster drivers before they are allocated to distributed nodes, leading to reduced cluster-wide performance sharing as cluster drivers managing segmentation tasks become bottlenecks. In particular, there is a greater delay rate on smart home devices that constantly request small data processing. Thus, in this paper, we design a Apriori-based big data system for effective data processing in smart home environments where frequent requests occur at the same time. According to the performance evaluation results of the proposed system, the data processing time was reduced by up to 38.6% from at least 19.2% compared to the existing system. The reason for this result is related to the type of data being measured. Because the amount of data collected in a smart home environment is large, the use of cache servers plays a major role in data processing, and association analysis with Apriori algorithms stores highly relevant sensor data in the cache.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04d
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• pp.548-550
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• 2003

EJB(Enterprise Java Bean) 컨테이너에서 대규모의 요청을 위해서는 여러 개의 EJB 컨테이너를 클러스터링 환경으로 구동시키는 것이 필요하다. EJB를 사용하는 클라이언트로는 JSPP나 에플리케이션 클라이언트, 혹은 또 다른 빈이 될 수 있다 이러한 클라이언트가 사용하는 EJB의 스텁을 클러스터 환경에 적합하도록 구현함으로써 트랜잭션 지역화, 장애 발생시 다른 서버로의 메소드 호출 전환, 동일 가상 머신을 탐지한 메소드 호출 최적화 등의 다양한 기능을 수행할 수 있다. 본 논문에서는 이러한 스마트 스텁의 필요성 및 구현에 대해 논의한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.525-527
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• 2013

최근 IT 기업들이 자동차에 IT도입에 열을 올리고 있으며, 그 중에서도 미터 클러스터는 운전자의 편의성을 고려하여 많은 연구와 관심이 증대되고 있다. 자동차 계기판은 전자기기의 발전과 더불어 아날로그 계기판, 디지털 계기판, 이 둘을 함께 사용한 하이브리드 계기판, 그리고 보다 상세한 정보를 이미지와 함께 제공해 주는 스마트 하이브리드 계기판으로 발전하고 있다. 기존의 미터 클러스터는 단순히 차량의 제한된 정보를 표시하며, 운전자의 운전 상태에 따른 시인성이 부족하며, 차량의 상태, 그리고 운행지역의 주변 환경적 정보의 부족으로 인해 운전자의 안정성이 고려되지 못한 부분이 많아 운전자의 안전 운전에 도움이 되지 못하는 부분이 많다. 따라서 본 논문에서는 차량의 상태, 운행 환경정보 등의 통합 된 정보를 LCD 디스플레이 기반에서 운전자의 시인성과 안정성 우선으로 하는 레이아웃을 연구하고자 한다.

• Smart Media Journal
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• v.4 no.4
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• pp.18-23
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• 2015

In this paper, we propose a method for detecting the number of clusters. This method can improve the performance of a gaussian mixture model function in conventional markov random field method by using the tensor voting. The key point of the proposed method is that extracts the number of the center through the continuity of saliency map of the input data of the tensor voting token. At first, we separate the foreground and background region candidate in a given natural images. After that, we extract the appropriate cluster number for each separate candidate regions by applying the tensor voting. We can make accurate modeling a gaussian mixture model by using a detected number of cluster. We can return the result of natural binary text image by calculating the unary term and the pairwise term of markov random field. After the experiment, we can confirm that the proposed method returns the optimal cluster number and text binarization results are improved.

• Journal of the Korean Regional Science Association
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• v.38 no.3
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• pp.19-39
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• 2022

The aim of this study is to compare and analyze structural characteristics of smart city industry focused on Korea and Spain. Structural characteristics of industries were compared focusing on share, penetration, impact path and network clustering of smart industries. Research data used input-output tables established by Korea and Spain in 1995 and 2015, and industries were reclassified into 8 and 25 industries. The analysis model is the Smart SPIN Model. The key finding as follows: It was analyzed that there are differences in the structure and characteristics of the smart city industry between Korea and Spain. Firstly, It is analyzed that Korea has a larger share and penetration rate of IT manufacturing than Spain. On the other hands, Spain has a higher share and penetration rate in the IT service and knowledge service sectors than Korea. Secondly, Korea had many production paths for the IT service and the knowledge service. On the other hands, Spain included more production paths in the IT manufacturing sector. Thirdly, as a result of network analysis, Korea's smart industry has a characteristic that it is difficult to develop independently because it is dependent on traditional industries. In Spain, most of the smart industries were included in one industrial cluster, and it was analyzed to have an independent form. In conclusion, It was found that Korea has the industrial characteristics of a smart city based on IT manufacturing. Spain has the characteristics of smart city industry based on IT service and knowledge service. The results of this study are expected to provide basic data on the direction of smart city promotion and the establishment of smart city policies in Korea.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.229-234
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• 2014

As association between sensor networks that collect environmental information by using numberous sensor nodes and smartphones that are equipped with various sensors, many applications understanding users' context have been developed to interact users and their environments. Collected data should be stored with XML formatted metadata containing semantic information to share the collected data. In case of distance based clustering schemes, the efficiency of data collection decreases because metadata files are extended and changed as the purpose of each system developer. In this paper, we proposed a clustering scheme considering the structural similarity of metadata to reduce clustering construction time and improve the similarity of metadata among member nodes in a cluster.

• Smart Media Journal
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• v.6 no.4
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• pp.24-31
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• 2017

In wireless sensor networks, sensor nodes are deployed in a remote, harsh environment. When the power of the sensor node is consumed in such a network, the sensor nodes become useless together with the deterioration of the quality and performance of the sensor network which may save human life. Although many clustering protocols have been proposed to improve the energy consumption and extend the life of the sensor network, most of the previous studies have shown that the overhead of the cluster head is quite large. It is important to design a routing protocol that minimizes the energy consumption of each node and maximizes the network lifetime because of the power limitations of the sensor nodes and the overhead of the cluster heads. Therefore, in this paper, we propose an efficient clustering scheme that reduces the burden of cluster heads, minimizes energy consumption, and uses algorithms that maximize network lifetime. Simulation results show that the proposed clustering scheme improves the energy balance and prolongs the network life when compared with similar techniques.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.17-25
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• 2018

Recently, with the development of ICT technology and the rapid spread of smart devices, a huge amount of information is being generated. The recommendation system has helped the informant to judge the information from the information overload, and it has become a solution for the information provider to increase the profit of the company and the publicity effect of the company. Recommendation systems can be implemented in various approaches, but social information is presented as a way to improve performance. However, no research has been done to utilize trust cluster information among users in the recommendation system. In this paper, we propose a method to improve the performance of the recommendation system by using the influence between the intra-cluster objects and the information between the trustor-trustee in the cluster generated in the online review. Experiments using the proposed method and real data have confirmed that the prediction accuracy is improved than the existing methods.

• Electronics and Telecommunications Trends
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• v.36 no.5
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• pp.62-73
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• 2021

A stable protein source is required to support the rapidly increasing global population, and fishery products are a particularly important part of the required protein supply. However, due to continued overfishing, fishery resources are depleted, and the number of fish caught by fishing boats has stagnated. Consequently, the aquaculture industry is becoming increasingly important. Internationally, smart aquaculture technology that minimizes labor and environmental pollution has been established through technological developments supported by large investments in automation and water treatment technology over the last several decades. In the case of Korea, the aquaculture industry has not yet emerged as a labor-intensive primary industry. However, in recent years various attempts have been made to apply ICT technology to aquaculture to overcome these problems. In this study, domestic and foreign technologies and patent trends for smart aquaculture are analyzed. In addition, the current status of the smart aquaculture cluster business that the Ministry of Oceans and Fisheries has been promoting since 2019 to utilize ICT technology in aquaculture is introduced.