• 제어로봇시스템학회논문지
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• 제22권9호
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• pp.745-752
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• 2016

We suggest an efficient Simultaneous Localization and 3D Polygon Map Building (SLAM) method with Kinect depth sensor for mobile robots in indoor environments. In this method, Kinect depth data is separated into row planes so that scan line segments are on each row plane. After grouping all scan line segments from all row planes into line groups, a set of 3D Scan polygons are fitted from each line group. A map matching algorithm then figures out pairs of scan polygons and existing map polygons in 3D, and localization is performed to record correct pose of the mobile robot. For 3D map-building, each 3D map polygon is created or updated by merging each matched 3D scan polygon, which considers scan and map edges efficiently. The validity of the proposed 3D SLAM algorithm is revealed via experiments.

• 한국어교육
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• 제23권1호
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• pp.77-100
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• 2012

This study investigates issues in relation to text segmenting, in particular, line breaks in Korean language textbooks. Research on L1 and L2 reading has shown that readers process texts by chunking (grouping words into phrases or meaningful syntactic units) and, therefore, phrase-cued texts are helpful for readers whose syntactic knowledge has not yet been fully developed. In other words, it would be important for language textbooks to avoid awkward syntactic divisions at the end of a line, in particular, those textbooks for beginners and intermediate level learners. According to our analysis of a number of major Korean language textbooks for beginner-level learners, however, many textbooks were found to display line-breaks of awkward syntactic division. Moreover, some textbooks displayed frequent instances where a single word (or eojeol in the case of Korean) is split between different lines. This can hamper not only learners' learning of the rules of spaces between eojeols in Korean, but also learners' development in automatic word recognition, which is an essential part of reading processes. Based on the findings of our textbook analysis and of existing research on reading, this study suggests ways to overcome awkward line-breaks in Korean language textbooks.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1995년도 추계학술대회논문집
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• pp.62-74
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• 1995

This study surveys four characteristics (overall density, local density, grouping, complexity) to effect user's performance on the on-line terminal displays of commercial banks, and makes the new screen by the screen design procedure. The new screen includes to increase the number of groups and to arrange the items on the screen. And then, this study carrys out experiments to compare performance(operating time and error number ) by each screen. The result is described that the operating time decreases about 20% at the new OUT-screen than the existing OUT-screens; about 25% at the new IN-screen.

• 산업공학
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• 제10권2호
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• pp.51-56
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• 1997

This paper concerns with the problem of mixed model assembly sequencing using neural net. In recent years, because of two characteristics of it, massive parallelism and learning capability, neural nets have emerged to solve the problems for which more conventional computational approaches have proven ineffective. This paper proposes a method using neural net that can consider line balancing and grouping problems simultaneously. In order to solve the mixed model assembly sequencing of the motor industry, this paper uses the modified ART1 algorithm.

• Journal of Computational Design and Engineering
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• 제1권2호
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• pp.140-151
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• 2014

Storing, and the loading and unloading of materials at production sites in the manufacturing sector for mass production is a critical problem that affects various aspects: the layout of the factory, line-side space, logistics, workers' work paths and ease of work, automatic procurement of components, and transfer and supply. Traditionally, the nesting problem has been an issue to improve the efficiency of raw materials; further, research into mainly 2D optimization has progressed. Also, recently, research into the expanded usage of 3D models to implement packing optimization has been actively carried out. Nevertheless, packing algorithms using 3D models are not widely used in practice, due to the large decrease in efficiency, owing to the complexity and excessive computational time. In this paper, the problem of efficiently loading and unloading freeform 3D objects into a given container has been solved, by considering the 3D form, ease of loading and unloading, and packing density. For this reason, a Group Packing Approach for workers has been developed, by using analyzed truck packing work patterns and Group Technology, which is to enhance the efficiency of storage in the manufacturing sector. Also, an algorithm for 3D packing has been developed, and implemented in a commercial 3D CAD modeling system. The 3D packing method consists of a grouping algorithm, a sequencing algorithm, an orientating algorithm, and a loading algorithm. These algorithms concern the respective aspects: the packing order, orientation decisions of parts, collision checking among parts and processing, position decisions of parts, efficiency verification, and loading and unloading simulation. Storage optimization and examination of the ease of loading and unloading are possible, and various kinds of engineering analysis, such as work performance analysis, are facilitated through the intelligent 3D packing method developed in this paper, by using the results of the 3D model.

• Journal of Electrical Engineering and Technology
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• 제2권1호
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• pp.123-128
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• 2007

SPWPM traditional software development is surveyed and essential problems are investigated on the basis of system wireless link considerations. This paper presents the current state software planning tools for wireless LAN link optimization. The software directory is based on combination of MatLab and MapInfo software and measurement which gives the best grouping parameters to build up the software development. Among the requirements assumed, the WLAN site selections must be Line-of-sight (LOS) or near line of sight (NLOS) field strength prediction for either point to point or point to multi points. The results obtainable the out put of the program include two-dimensional (2D) and three dimensional (3D) plots for creating the link; design parameters through GUI representing the height and location for each antenna is depending on K-factor of the area and transmit antenna location.

• 한국멀티미디어학회논문지
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• 제11권3호
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• pp.292-300
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• 2008

본 논문에서는 점진적인 화소 확장을 이용하여 영상 내에 존재하는 선분을 찾아내는 선분 추출 알고리즘을 제안한다. 본 논문에서 제안하는 선분 추출 방법에서는 기존의 선분 추출 방법인 허프 변환 기반 방법이나 선분의 그룹화 기반 방법과는 다른 접근법을 사용하였다. 영상이 입력되면 케니 테두리를 구하고, 테두리 화소 중 임의의 점을 선택하여 선분을 근사화 시킨 기본 직선을 만든 후, 선택된 점에서 임의의 반경 내에 있는 테두리 화소들을 선택한다. 직선과의 거리 오차와 기울기 각의 오차를 이용하여 선택된 화소에 가중치를 부여한다. 가중치 합 비교에 의해 선택된 화소들이 떨어져 있는지를 판별한 후, 가중치를 적용한 최소자승법에 의해 선 맞춤을 하여 선분을 구하게 된다. 제안된 알고리즘은 기존에 제안된 방법들과 결과를 비교하였으며, 계산 속도가 빠르면서 실제 존재하는 선분 추출이 가능하다는 것을 실험 결과를 통해 제시한다.

• 전자공학회논문지A
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• 제31A권6호
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• pp.169-176
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• 1994

본 논문에서는 조합회로에 있어서 고장 시뮬레이션의 고속화를 위한 효율적인 병렬 평가 알고리듬을 제안한다. 제안한 알고리듬은 고장소자의 평가 및 전파에 있어서 병렬법, 연역법 그리고 동시법의 장점을 이용하고 있기 때문에 시뮬레이션의 고속화를 실현할 수 있을 뿐만 아니라 다치(multi-valued) 신호를 쉽게 취급할 수 있다. 또한, 동일한 신호선에서 발생하는 액티브(active)고장을 동일한 고장 그룹으로 할당하므로써 병렬연산의 효율을 증가시키기 위한 고장의 그룹화(fault grouping) 방법을 제안한다. 제안한 알고리듬은 C언어로 구현하였으며, ISCAS '85 Benchmark 회로에 대한 실험 결과 종래의 동시법과 비교하여 약 2.6배에서 8.2배 정도의 고속화가 실현되었다.

• 방송공학회논문지
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• 제13권2호
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• pp.236-244
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• 2008

본 논문에서는 칼라 세그멘테이션, 에지 정합, 지각적 그룹핑 등을 사용하여 Lidar 데이터와 광학 영상의 정보 융합에 의한 새로운 구조물 검출 및 복원 알고리듬을 제안한다. 제안하는 알고리듬은 두 가지 단계로 구성된다. 첫 번째로, 항공 Lidar 데이터로부터 초기 구조물 추출 결과와 영상의 칼라 세그멘테이션 결과를 사용하여 coarse building boundary를 추출한다. 두 번째로, coarse building boundary와 에지 정합 및 지각적 그룹핑에 의해 보다 정밀한 구조물 추출 결과인 precise building boundary를 추출한다. 본 논문에서 제안하는 알고리듬은 보다 신뢰성 있는 구조물 검출을 위해, 광학 영상으로부터 칼라 정보를 사용한다. 이를 통해, Lidar에 의해 획득된 붕괴된 형태의 구조물 외곽선을 보완한다. 또한, 인공지물의 특징으로서, 에지의 직선성 및 다면체 형태의 지붕모양을 반영함으로써 신뢰성 있는 구조물을 검출한다. 다중 센서 데이터에 대한 실험은 제안하는 알고리듬이 Lidar 단일 센서 결과에 비해 정밀하고 신뢰성 있는 결과를 보여준다.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• 제5권3호
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• pp.76-85
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• 2024

The purpose of this study is to propose a new method of analysis focusing on interconnections between species rather than traditional biodiversity analysis, which represents ecosystems in terms of species and individual counts such as species diversity and species richness. This new approach aims to enhance our understanding of ecosystem networks. Utilizing data from the 4th National Natural Environment Survey (2014-2018), the following eight taxonomic groups were targeted for our study: herbaceous plants, woody plants, butterflies, Passeriformes birds, mammals, reptiles & amphibians, freshwater fishes, and benthonic macroinvertebrates. A co-occurrence frequency analysis was conducted using nationwide data collected over five years. As a result, in all eight taxonomic groups, the degree value represented by a linear regression trend line showed a slope of 0.8 and the weighted degree value showed an exponential nonlinear curve trend line with a coefficient of determination (R²) exceeding 0.95. The average value of the clustering coefficient was also around 0.8, reminiscent of well-known social phenomena. Creating a combination set from the species list grouped by temporal information such as survey date and spatial information such as coordinates or grids is an easy approach to discern species distributed regionally and locally. Particularly, grouping by species or taxonomic groups to produce data such as co-occurrence frequency between survey points could allow us to discover spatial similarities based on species present. This analysis could overcome limitations of species data. Since there are no restrictions on time or space, data collected over a short period in a small area and long-term national-scale data can be analyzed through appropriate grouping. The co-occurrence frequency analysis enables us to measure how many species are associated with a single species and the frequency of associations among each species, which will greatly help us understand ecosystems that seem too complex to comprehend. Such connectivity data and graphs generated by the co-occurrence frequency analysis of species are expected to provide a wealth of information and insights not only to researchers, but also to those who observe, manage, and live within ecosystems.