• 한국공간정보시스템학회:학술대회논문집
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• 2003.11a
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• pp.135-140
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• 2003

차량과 같이 시간의 흐름에 따라 위치를 변경하는 객체를 이동체라 한다. 이동체의 과거 궤적은 시간이 지남에 따라 누적되므로 대용량 정보가 된다. 대용량 궤적 정보를 저장하는 이동체 데이터베이스에서 효율적으로 궤적을 검색하기 위해서는 색인이 필요하다. 특히 궤적을 선택하는 과정과 선택된 궤적의 일부분을 추출하는 과정으로 이루어진 복합 질의를 처리하기 위해서는 궤적 보존을 지원하는 TB-tree와 같은 색인 구조가 적합하다. 그러나 TB-tree와 같이 시간적으로 잘 구성된 색인은 공간적인 겹침이 괴지는 문제가 있고, 반대로 공간적으로 잘 구성된 색인은 시간 도메인의 겹침을 심화시키는 문제점이 있다. 이 논문에서는 시간 도메인 중심의 분할 정책과 공간 도메인 중심의 분할 정책을 분석하여 서로 다른 두 도메인 사이의 관계를 밝힐 수 있는 파라미터를 제안하고, 이를 TB-tree에 적용하여 78-tree의 장점을 유지하면서 영역 질의껜 효과적인 분할 정책을 설계 및 구현한다. 또한 성능평가를 통하여 제안된 분할 정책이 기존의 TB-tree 보다 영역 질의에서 우수함을 보인다.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.157-158
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• 2016

이제는 스마트폰은 현대인의 생활에 있어 없어서는 안되는 필수 용품이 되었다. 수많은 스마트폰용 어플리케이션은 편리하고 다양한 혜택을 제공해 주고 있다. 대학생들에게도 사용하는 많은 어플리케이션이 있지만 그중에서도 교육용 어플리케이션의 사용 실태는 관심의 대상이라고 볼 수 있다. 본 연구에서는 교육용 어플리케이션의 사용에 대한 양적인 조사를 연구 범위로 한다. 조사방법론으로는 대전의 한 대학교의 학생들에게 설문을 통하여 교육용 어플리케이션 사용 여부와 사용 시간, 그리고 어플리케이션 선택 경위를 파악하는 설문방법을 취한다. 먼저 성별과 학년별 스마트폰 종류의 차이가 있는지를 분석하고, 교육용 앱 사용 여부와 사용시간, 그리고 어플리케이션 선택 경위에 있어 스마트폰 종류, 성별에 따른 차이와 학년에 따른 차이를 SPSS 20 통계 패키지를 이용하여 검증한다. 검증 결과는 성별 보유 스마트폰의 종류는 차이가 없으나 학년별로는 신입생보다 재학생들이 아이폰을 사용하는 비율이 월등히 높아 통계적으로 유의한 차이가 있음이 나타났다. 한편 스마트폰 종류별로 교육용 앱의 사용시간에 차이가 있어 안드로이드폰을 사용하는 경우가 아이폰보다 통계적으로 유의하게 긴 시간을 사용하고 있었다. 하지만 성별, 학년별 사용시간은 통계적으로 유의한 차이가 없었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8B
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• pp.657-667
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• 2012

In the MPR selection algorithm of Optimized Link State Routing (OLSR), each node selects own MPRs independently, so most of nodes are selected to MPR at least once. To cope with this problem, the MPR candidate selection algorithm was proposed. The MPR candidate selection algorithm can reduce the number of MPRs, but the efficiencies of route and connectivity decline due to decreased number of MPRs. So, in this paper, we propose the Significant Multi-Point Relay (S-MPR) selection algorithm which can enhance the performance of ad hoc network by improving the MPR selection algorithm of OLSR. In proposed S-MPR selection algorithm, each node selects the most important node to S-MPR to guarantee the connectivity then selects remaining MPRs in MPR candidates. So proposed S-MPR selection algorithm can reduce the overhead of many MPRs without decline of routing performance. To show the performance gain of proposed S-MPR selection algorithm, we simulate the proposed S-MPR selection algorithm by using OPNET.

• The KIPS Transactions:PartC
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• v.14C no.7
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• pp.571-582
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• 2007

Vehicular ad-hoc networks is temporarily established through inter-vehicle communication without any additional infrastructure aids. It requires a immediate message propagation because it mainly deals with critical traffic information such as traffic accidents. The distance-based broadcast scheme is one of the representative broadcast schemes for vehicular ad-hoc network. In this scheme, a node to disseminate messages is selected based on a distance from a source node. However, a message propagation delay will be increased if the relay nodes are not placed at the border of transmission range of the source node. In particular, when the node density is low, the message propagation delay is getting longer. In this paper, we propose a time-window reservation based relay node selection scheme. A node receiving the alert message from the source node has its time-window and randomly selects its waiting time within the given time-window range. A proportional time period of the given time-window is reserved in order to reduce the message propagation delay. The experimental results show that the proposed scheme has shorter message propagation delay than the distance-based broadcast scheme irrespective of node density in VANET. In particular, when the node density is low, the proposed scheme shows about 26% shorter delay and about 46% better performance in terms of compound metric, which is a function of propagation latency and network traffic.

• The KIPS Transactions:PartC
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• v.17C no.6
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• pp.491-498
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• 2010

Wi-Fi based vehicle-to-infrastructure (V2I) communication is an emerging solution to improve the safety, traffic efficiency, and comfort of passengers. However, due to the high mobility of vehicles and the limited coverage of Wi-Fi APs, the V2I system may suffer from frequent handoffs although roadside APs can support cost effective Internet connectivity. Such problem of V2I systems can be overcome with Mobile AP (MAP) platform. The MAPs yield longer service duration by moving along with vehicles, yet they provide a lower link capacities than the roadside APs. In this paper, we propose a new association control mechanism that effectively determines whether the vehicle will select a fixed roadside-AP or a nearby MAP in mobile vehicular network environments. We consider both the achievable link bandwidth and available connection duration as a selection criterion and provide their run-time estimation method. Extensive simulation using real traces show significant performance improvements.

• Journal of KIISE
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• v.42 no.2
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• pp.145-154
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• 2015

This paper proposes an enhanced projection candidate selection algorithm to improve the performance of the existing path prediction algorithm. Various user path prediction algorithms have previously been developed, but those algorithms are inappropriate for a real-time and close user path prediction environment. To resolve this issue, a new prediction algorithm has been proposed, but several problems still remain. In particular, this algorithm should be enhanced to provide much faster processing performance. The major cause of the high processing time of the previous path prediction algorithm is the high time complexity of its projection candidate selection. Therefore, this paper proposes a new path fragment management structure and an improved projection candidate selection algorithm to improve the processing speed of the existing projection candidate selection algorithm. This paper also shows the effectiveness of the algorithm herein proposed through a comparative performance evaluation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.599-604
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• 2010

In this study, the value of travel time was estimated with reflecting the fuel cost according to travel distance. The main objective of this study is whether the addition of the fuel cost as a factor for route choice behavior is appropriate or not, through the stated preference survey. The route choice model was developed using SP survey technique with the consideration of level difference and the value of travel time, toll and fuel costs. Consequently, the fuel cost is identified as a main factor like travel time and toll cost in choosing routes from drivers' viewpoints. Nevertheless, since toll costs are recognized as out-of-pocket expenses whereas fuel costs as periodical expenses, it seems drivers are more sensitive to toll than fuel costs.

• Journal of Digital Convergence
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• v.12 no.5
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• pp.345-351
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• 2014

The purpose of this study was to identify the difference between job satisfaction and organizational commitment by the type of time management behavior in clinical nurses. Total 208 nurses were recruited from clinical settings where located in Seoul and Daejeon, South Korea. Data were collected using self-administered method with structured questionnaire between August 2012 and January 2013. Descriptive statistics, K-mean cluster analysis, one-way ANOVA were performed for data analysis. As results, the type of time management behavior were classified into four types such as unconcern type, accomplishment type, urgency type and selection & concentration type. Among four types, nurses who belonged to be accomplishment and selection & concentration type were tend to have positive behaviors in terms of time managements as they had high scores in job satisfaction. Therefore, further study on whether types of time management are related with organizational culture including commitment and effectiveness should be explored.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.5
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• pp.155-162
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• 2021

n-step TD learning is a combination of Monte Carlo method and one-step TD learning. If appropriate n is selected, n-step TD learning is known as an algorithm that performs better than Monte Carlo method and 1-step TD learning, but it is difficult to select the best values of n. In order to solve the difficulty of selecting the values of n in n-step TD learning, in this paper, using the characteristic that overestimation of Q can improve the performance of initial learning and that all n-step returns have similar values for Q ≈ Q^*, we propose a new learning target, which is composed of the maximum and the mean of all k-step returns for 1 ≤ k ≤ n. Finally, in OpenAI Gym's Atari game environment, we compare the proposed algorithm with n-step TD learning and proved that the proposed algorithm is superior to n-step TD learning algorithm.

• Journal of Global Scholars of Marketing Science
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• v.4
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• pp.1-24
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• 1999

소비시장은 소비자들의 변화에 따라 함께 변천한다. 다가오는 21세기에는 소득수준의 향상과 다원화사회가 이룩되면서 소비자들의 라이프스타일과 소비행태도 새롭게 형성될 전망이다. 이는 21세기 소비자행태와 소비시장변화를 소득수준의 향상과 이에 따른 가치관의 변화, 자유시간의 증대, 신소비계층의 출현 등의 변수를 통해 예측된다. 최근, 사회 경제적으로 이루어지는 급격한 변화 등으로 소비자들의 라이프스타일이 다양화되면서 소비자들의 관광지 선택행동에서 변화를 가져오고 있다. 과거 저가격위주의 관광을 하던 관광자들이 점차 그들의 생활의 질을 추구하기 위해서 좀 더 많은 비용을 지불하고서도 보다 매력적인 관광지를 방문하는 것이 이러한 변화의 한 예라 할 수 있겠다. 관광자가 관광지를 선택하는 과정은 기본적으로 소비자의 점포선택이나 제품에 대한 선택과정과도 동일하다고 볼 수 있다. 왜냐하면 점포선택에 있어서 기본적으로 제기되는 소비자의 라이프스타일 유형이나 관광지선택에 따른 관광자 라이프스타일 유형의 선택속성은 그 구성면에서 유사하기 때문이다. 관광자 행동특성에 따른 라이프스타일 유형연구는, 다양화되어 가는 생활양식에 기인하여 관광지 선택행동의 연구에 기여할 수 있을 것이다.