• Proceedings of the Korea Information Processing Society Conference
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• 2001.04a
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• pp.515-518
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• 2001

HTTP/1.0은 동일한 서버로부터 각각의 개체에 대하여 개별적인 TCP 연결을 생성하기 때문에 다중의 요구를 비효율적으로 처리한다. 이러한 문제를 해결하기 위한 방안으로 제안된 HTTP/1.1 은 TCP연결을 지속적인 연결(Persistent connection)이라는 개념을 도입하여 하나의 TCP 연결 상에서 다중의 요구(Request)를 처리하도록 하고 있다[9]. 네트워크가 발전됨에 따라 사용자가 늘어나고 다양해지면서 서비스의 차별화 문제가 중요한 문제로 대두되었다[3,5]. 본 논문에서 제시하는 Diff(Differentiated)-HTTP은 웹 서버에 서비스를 요청한 클라이언트들에게 차별화 된 서비스를 제공하기 위해서 사용자를 두 등급, 기본 등급과 우선 순위를 고려한 상위 등급으로 구분한다. 각 등급은 제한 시간(Holding Time)으로 차별화 되고 상위 등급에 속한 클라이언트에게 제한된 시간을 증가시켜 지연을 최소로 함으로써 고품질의 서비스를 제공하는 방안을 제안한다.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.40-41
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• 2021

The construction industry has the highest occupational accidents/injuries among all industries. Korean government installed surveillance camera systems at construction sites to reduce occupational accident rates. Construction safety managers are monitoring potential hazards at the sites through surveillance system; however, the human capability of monitoring surveillance system with their own eyes has critical issues. Therefore, this study proposed to build a deep learning-based safety monitoring system that can obtain information on the recognition, location, identification of workers and heavy equipment in the construction sites by applying multiple-object tracking with instance segmentation. To evaluate the system's performance, we utilized the MS COCO and MOT challenge metrics. These results present that it is optimal for efficiently automating monitoring surveillance system task at construction sites.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10c
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• pp.40-42
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• 2001

캐쉬 일관성 프로토콜의 하나인 MESI 프로토콜은 다중 프로세싱 환경에서 각각의 프로세서와 메모리 사이의 데이터 일관성을 유지하기 위해 캐쉬, 메모리 등의 통신 개체들을 조정하는 일종의 규칙들 중 하나이다. 프로세서의 수가 많아지고 시스템이 복잡해 질 경우 MESI 프로토콜을 정확하게 설계하고 그 동작을 분석하기는 매우 어렵다. 본 연구에서는 정형기법 도구인 ESTEREL을 이용하여 MESI 프로토콜을 설계하고 그 동작의 안정성을 검증하여, 시스템의 정확성과 안정성을 보장하는 방법에 대해 논한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.109-116
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• 2023

In this paper, we study the containment control problem for second-order multi-agent systems, which consists of multiple leaders and followers. The goal is to drive the followers toward the convex hull spanned by the leaders. Thus, the swarm behavior can be obtained by controlling the entire group by the leaders. This paper considers the leaders move at a constant speed and the followers have input saturations. Moreover, we assume that the followers can exchange information with neighbors, and only relative state information is available. Under these assumptions, we propose the Proportional-Integral based distributed control algorithm to solve the containment control problem with moving leaders. Moreover, based on Lasalle's invariance principle, the conditions for the control gains that guarantee the convergence of the followers to the convex hull spanned by the leaders are investigated, and it was shown that it can be designed only using the system parameter. Finally, the simulations are conducted to validate the theoretical result.

• Journal of Cadastre & Land InformatiX
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• v.46 no.1
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• pp.87-100
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• 2016

The acquisition of the forest resource information has depended on a partial sampling method or aerial photographs which demand a lot of effort and time because of the vast areas and the difficult approach. For the acquisition of the forest resource information, there have been the optical remote-sensing and the multi-spectrum image to offer only horizontal distributions of trees, but a new technological approach, such as Airborne LiDAR, is more necessary to acquire directly three dimensional information related to the forest terrains and trees' features. This paper proposes an algorithm for the forest information extraction such as trees' individual numbers and the heights of trees by using LiDAR data. Especially, this proposed algorithm adopts a region growing method for the extraction of the vegetation-point and extracts the forest information using morphological features of trees.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.67-75
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• 2018

Multidimensional scaling (MDS) is an exploratory analysis of multivariate data to represent the dissimilarity among objects in the geometric low-dimensional space. However, a general MDS map only shows the information of objects without any information about variables. In this study, we used MDS based on the algorithm of Torgerson (Theory and Methods of Scaling, Wiley, 1958) to visualize some clusters of objects in categorical data. For this, we convert given data into a multiple indicator matrix. Additionally, we added the information of levels for each categorical variable on the MDS map by applying the partition method of Shin et al. (Korean Journal of Applied Statistics, 28, 1171-1180, 2015). Therefore, we can find information on the similarity among objects as well as find associations among categorical variables using the proposed MDS map.

• Korean journal of applied entomology
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• v.59 no.4
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• pp.295-301
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• 2020

In this study, we aimed to investigate the changes in the catch rate of Monochamus saltuarius, based on sexual maturation by using aggregation-sex pheromone traps. Ovariole development of caught M. saltuarius females was compared to that of the ones not caught using traps. In a mesh cage set up at the Hongneung experimental forest, we placed a multi-funnel trap with or without an aggregation-sex pheromone lure. M. saltuarius adults, which emerged from pine logs, were grouped in four according to the emergence dates (0, 1, 7, and 10 days after emergence [DAE]). We released beetles into the mesh cage to investigate the catch rate using the traps. In each group, a total of 80 beetles (20 beetles × 4 replications) were tested, making it a total of 320 beetles. Among the four groups, M. saltuarius adults in the 7 DAE group were caught more frequently using the traps, especially with a pheromone lure; the other groups showed a low catch rate. A similar number of female and male beetles were caught using the traps. Regarding ovariole development, all the female adults in the 0 and 1 DAE groups were immature, while those in the other two groups were completely developed. Therefore, aggregation-sex pheromone traps might have a limitation in the prevention of pine wilt disease because of the transmission of pine wood nematode during maturation feeding of newly emerged M. saltuarius adults. However, aggregation-sex pheromone traps can be effective for collecting sexually mature M. saltuarius adults, for the investigation of seasonal occurrence of beetles in forests.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.215-219
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• 2018

다중 화자 대화 속 인물 식별이란 여러 등장인물이 나오는 대본에서 '그녀', '아버지' 등 인물을 지칭하는 명사 또는 명사구가 실제 어떤 인물을 나타내는지 파악하는 문제이다. 대본 자연어 데이터만을 입력으로 하는 대화 속 인물 식별 문제는 드라마 대본에 대해서 데이터가 구축 되었고 이를 기반으로 여러 연구가 진행되었다. 그러나, 사람도 다중 화자 대화의 문장만 보고는 인물을 지칭하는 명사 또는 명사구가 실제 어떤 인물인지 파악하기 어려운 경우가 있다. 이에 본 논문에서는 발화가 되는 시점의 영상 장면 정보를 추가적으로 활용하여 인물 식별의 성능을 높이는 방법을 제시한다. 또한 기존 대화 속 인물 식별 연구들은 미리 정의된 인물을 대상으로 분류하는 형태로 접근해왔다. 이는 학습에 사용되지 않았던 인물이 나오는 임의의 다른 드라마 대본이나 대화 등에 바로 적용될 수 없다. 이에 본 논문에서는 영상 정보는 활용하되, 한번 학습하면 임의의 대본에 적용될 수 있도록 사전 인물 정보를 사용하지 않는 상호참조해결 기반의 인물 식별 방법도 제시한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1483-1490
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• 2009

This parer is presented multiple path-planning of unmanned autonomous forklift using modified genetic algorithm and fuzzy inference system. There are a task-level feedback method and a method that path is dynamically replaned in realtime while the autonomous vehicles are moving by means of an optimal algorithm for existing multiple path-planning. However, such methods cause malfunctions and inefficiency in the sense of time and energy, and path-planning should be dynamically replanned in realtime. To solve these problems, we propose multiple path-planning using modified genetic algorithm and fuzzy inference system and show the performance with autonomous vehicles. For experiment, we designed and built two autonomous mobile vehicles that equipped with the same driving control part used in actual autonomous forklift, and test the proposed multiple path-planning algorithm. Experimental result that actual autonomous mobile vehicle, we verified that fast optimized path-planning and efficient collision avoidance are possible.

• Journal of the Korea Institute of Building Construction
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• v.21 no.5
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• pp.397-408
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• 2021

The construction industry has the highest occupational accidents/injuries and has experienced the most fatalities among entire industries. Korean government installed surveillance camera systems at construction sites to reduce occupational accident rates. Construction safety managers are monitoring potential hazards at the sites through surveillance system; however, the human capability of monitoring surveillance system with their own eyes has critical issues. A long-time monitoring surveillance system causes high physical fatigue and has limitations in grasping all accidents in real-time. Therefore, this study aims to build a deep learning-based safety monitoring system that can obtain information on the recognition, location, identification of workers and heavy equipment in the construction sites by applying multiple object tracking with instance segmentation. To evaluate the system's performance, we utilized the Microsoft common objects in context and the multiple object tracking challenge metrics. These results prove that it is optimal for efficiently automating monitoring surveillance system task at construction sites.