• Journal of Korea Game Society
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• v.21 no.6
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• pp.87-96
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• 2021

As the industry develops, the technology used for games is also being advanced. In particular, AI technology is used to game automation and intelligence. These game player patterns are widely used in online games such as player matchmaking, generation of friendly or hostile NPCs, and balancing of game worlds. This study proposes a model generation method for game players. For model generation, attributes such as hunting, collection, movement, combat, crisis management, production, and interaction were defined, and patterns were extracted and modeled using decision tree method. To evaluate the proposed method, we used the game log of a commercial game and confirmed the meaningful results.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.104-104
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• 2017

정상적인 부화 여부를 판별하기 위한 1차 검란은 일반적으로 5일~7일 이후에 시행된다. 미부화란을 이보다 더 빠른 시간 안에 검출할 경우 부화에 소요되는 에너지의 감소 효과 및 미부화란을 다른 용도로 활용하는 것을 기대할 수 있다. 시중에서 쉽게 구입할 수 있는 산란계인 하이라인 브라운 품종의 유정란 29개와 인위적인 미부화란을 만들기 위한 동일 품종의 무정란 11개를 사용하였으며 $38^{\circ}C$, 70% 조건의 항온항습기에서 96시간 동안 부화하였다. 스펙트럼 획득 장치의 광원은 녹색영역을 발광하는 LED램프와 일반 할로겐 광원을 별도로 사용하였으며 스펙트로미터는 VIS/NIR 영역인 520~1,180nm영역과 NIR영역인 900~1,700nm영역의 것을 사용하였다. 부화 시작 전과 부화 시작 후 1일 간격으로 각각 1개의 샘플에 대한 1개의 스펙트럼을 측정하였다. 측정 영역은 LED광원을 이용한 경우는 520~1,1800nm, 할로겐광원을 이용한 경우에는 520~1,180nm와 900~1,700nm이었다. 정상 부화여부는 4일차에서 할란하여 확인하였고, 측정 일자별로 PLS-DA분석법을 이용한 판별 모델을 개발하였다. 4일차에서 유정란 29개 중 11개가 정상 부화하였고, 18개는 미부화하였다. 3일차에서 판별 모델의 정확도는 LED광원의 VIS/NIR 영역 스펙트럼을 이용한 경우는 100%, 할로겐 광원의 VIS/NIR 영역 스펙트럼을 이용한 경우는 70%, 할로겐 광원의 NIR영역 스펙트럼을 이용한 경우는 70%였다. 4일차에서 판별 모델의 정확도는 LED광원의 VIS/NIR 영역 스펙트럼을 이용한 경우는 100%, 할로겐 광원의 VIS/NIR 영역 스펙트럼을 이용한 경우는 90%, 할로겐 광원의 NIR영역 스펙트럼을 이용한 경우는 100%였다. 부화 3일차는 정상 부화할 경우 피가 생성되는 시기이다. 피가 형성된 이후의 부화 여부를 판단하는 광원으로는 할로겐램프보다 LED램프를 사용하는 것이 더 적합한 것으로 나타났다.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.6
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• pp.607-611
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• 2001

Ultrasonic inspection system consist of the operator, equipment and procedure. The reliability of results in ultrasonic inspection is affected by its ability. Furthermore, the reliability of nondestructive testing is influenced by the inspection environment, materials and types of defect. Therefore, it is very difficult to estimate the reliability of NDT due to the various factors. In this study, the probability of detection by logistic probability model and Monte Carlo simulation is used for the reliability assessment of ultrasonic inspection. The utility of the NDT reliability assesment is verified by the analysis of the data from round robin test nth these models.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.98-98
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• 2013

태양의 활동영역에서 관측할 수 있는 흑점은 주로 흑점군으로 관측되며, 태양폭발현상의 발생을 예보하기 위한 중요한 관측 대상 중 하나이다. 현재 태양 폭발을 예보하는 모델들은 McIntosh 흑점군 분류법을 사용하며 통계적 모델과 기계학습 모델로 나누어진다. 컴퓨터는 흑점군의 형태학적 특성을 연속적인 값으로 계산하지만 흑점군의 형태적 다양성으로 인해 McIntosh 분류법과 일치하지 않는 경우가 있다. 이러한 이유로 컴퓨터가 계산한 흑점군의 형태학적인 특성을 예보에 직접 적용하는 것이 필요하다. 우리는 흑점군을 검출하기 위해 최소신장트리(Minimum spanning tree : MST)를 이용한 계층적 군집화 기법을 수행하였다. 그래프(Graph)이론에서 최소신장트리는 정점(Vertex)과 간선(Edge)으로 구성된 간선의 가중치의 합이 최소인 트리이다. 우리는 모든 흑점을 정점, 그들의 연결을 간선으로 적용하여 최소신장트리를 작성하였다. 또한 최소신장트리를 활용한 계층적 군집화기법은 초기값에 따른 군집화 결과의 차이가 없기 때문에 흑점군 검출에 있어서 가장 적합한 알고리즘이다. 이를 통해 흑점군의 기본적인 형태학적인 특성(개수, 면적, 면적비 등)을 계산하고 최소신장트리를 통해 가장 면적이 큰 흑점을 중심으로 트리의 깊이(Depth)와 차수(Degree)를 계산하였다. 이 방법을 2003년 SOHO/MDI의 태양 가시광 영상에 적용하여 구한 흑점군의 내부 흑점수와 면적은 NOAA에서 산출한 값들과 각각 90%, 99%의 좋은 상관관계를 가졌다. 우리는 이 연구를 통해 흑점군의 형태학적인 특성과 더불어 예보에 직접적으로 활용할 수 있는 방법을 논의하고자 한다.

• Journal of IKEEE
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• v.10 no.1 s.18
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• pp.40-48
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• 2006

This paper presents a new rooftop surface estimation method from 3D line segments. 3D rooftop surface estimation is based on the hierarchical grouping and initiated by 3D line merging for the disconnected 3D line segments. Merged 3D lines are applied to the detection of rooftop by surface estimating technique. To estimate surfaces we detect L-corner and T-corner points, and find fixed reliable junction points. The hypothesis of the possible rooftop surfaces are estimated as polygonal surfaces by these fixed junction points and building's rooftop models are generated by testing the possible surfaces in terms of assumptions of building surface properties. We carried out experiments by synthetic images on Avenches data set and the experimental results showed that we could reliably build 3D model with 3D surfaces, errors of which came up with 0.4 - 1.3 meter, 2.5 times more accurate than the elevation date from the conventional area-based stereo.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.3
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• pp.72-78
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• 2000

In this study, we propose a model verification algorithm based on DCT and neural network for ATM security system. We construct database about facial images after capturing thirty persons facial images in the same lumination and distance. To simulate model verification, we capture four learning images and test images per a man. After detecting edge in facial images, we detect a characteristic area of square shape using edge distribution in facial images. Characteristic area contains eye bows, eyes, nose, mouth and cheek. We extract characteristic vectors to calculate diagonally coefficients sum after obtaining DCT coefficients about characteristic area. Characteristic vectors is normalized between +1 and -1, and then used for input vectors of neural networks. Not considering passwords, simulations results showed 100% verification rate when facial images were learned and 92% verification rate when facial images weren't learned. But considering passwords, the proposed algorithm showed 100% verification rate in case of two simulations.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.73-81
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• 2011

In this paper, an improved block-based background modeling technique using adaptive parameter estimation that judiciously adjusts the number of model histograms at each frame sequence is proposed. The conventional block-based background modeling method has a fixed number of background model histograms, resulting to false negatives when the image sequence has either rapid illumination changes or swiftly moving objects, and to false positives with motionless objects. In addition, the number of optimal model histogram that changes each type of input image must have found manually. We demonstrate the proposed method is promising through representative performance evaluations including the background modeling in an elevator environment that may have situations with rapid illumination changes, moving objects, and motionless objects.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.561-566
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• 2005

This paper presents a visual tracking algorithm for the golf swing motion analysis by using the information of the pixels of video frames and movement of the golf club to solve the problem fixed center point in model based tracking method. The model based tracking method use the polynomial function for trajectory displaying of upswing and downswing. Therefore it is under the hypothesis of the no movement of the center of gravity so this method is not for the amateurs. we proposed method using the information of pixel and movement, we first detected the motion by using the information of pixel in the frames in golf swing motion. Then we extracted the club head and hand by a properties of club shaft that consist of the parallel line and the moved location of club in up-swing and down-swing. In addition, we can extract the center point of user by tracking center point of the line between center of head and both foots. And we made an experiment with data that movement of center point is big. Finally, we can track the real trajectory of club head, hand and center point by using proposed tracking algorithm.

• 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 Institute of Electronics Engineers of Korea SC
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• v.42 no.2 s.302
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• pp.33-38
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• 2005

In this paper, the sensing unit of a non-invasive blood glucose sensor for home users, using a magneto-resonance absorption method, have been designed and manufactured. The sensor is capable of non-invasively determining blood glucose levels through measuring the 1H spin-lattice relaxation time in human body, The comparison of initial models, with different dimensions and shapes, for the sensing unit has led us to select the materials of the final model, which has adequate size and weight for home use. Through the design optimization using the FEM model, the dimension of final model has been determined to satisfy the required strength and uniformity of the magnetic field in the detecting area.