• 한국정밀공학회지
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• 제14권7호
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• pp.144-153
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• 1997

The inverse kinematics problem of a reclaimer which excavates and transports raw materials in a raw yard is investigated. Because of the geometric feature of the equipment in which scooping buckets are attached around the rotating disk, kinematic redundancy occurs in determining joint variable. Link coordinates are introduced following the Denavit-Hartenbery representation. For a given excavation point the forward kinematics yields 3 equations, however the number of involved joint variables in the equations is four. It is shown that the rotating disk at the end of the boom provides an extra passive degree of freedom. Two approaches are investigated in obtaining inverse kinematics solutions. The first method pre-assigns the height of excavation point which can be determined through path planning. A closed form solution is obtained for the first approach. The second method exploits the orthogonality between the normal vector at the excavation point and the z axis of the end-effector coordinate system. The geometry near the reclaiming point has been approximated as a plane, and the plane equation has been obtained by the least square method considering 8 adjacent points near the point. A closed form solution is not found for the second approach, however a linear approximate solution is provided.

• 한국멀티미디어학회논문지
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• 제5권5호
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• pp.552-561
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• 2002

본 논문은 쾌속조형(rapid prototyping) 시스템에서 사용되며 3D 기하학적 형상을 가지는 STL 파일에 워터마크를 삽입하고 추출하는 방법에 관한 연구이다. 제안된 알고리즘은 3D 형상의 왜곡이 없도록 하기위해, 패싯의 법선 영역과 꼭지점 영역에 워터마크를 삽입한다. 워터마크 비트들은 법선의 위치와 꼭지점의 순서 정보를 이용하여 삽입된다 제안된 알고리즘은 패싯의 저장 순서에 대한 종속성이 없으며, 워터마크의 비가시성 (invisibility)을 충족한다. 제안된 알고리즘으로 3D 기하학적 형상에 워터마크를 삽입하고 추출하는 실험 결과들은 STL로 표현된 3D원형상에 영향을 주지 않고 워터마크의 삽입과 추출이 가능함을 보여준다.

• 로봇학회논문지
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• 제9권1호
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• pp.1-10
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• 2014

In recent years, the research of 3D mapping technique in urban environments obtained by mobile robots equipped with multiple sensors for recognizing the robot's surroundings is being studied actively. However, the map generated by simple integration of multiple sensors data only gives spatial information to robots. To get a semantic knowledge to help an autonomous mobile robot from the map, the robot has to convert low-level map representations to higher-level ones containing semantic knowledge of a scene. Given a 3D point cloud of an urban scene, this research proposes a method to recognize the objects effectively using 3D graph model for autonomous mobile robots. The proposed method is decomposed into three steps: sequential range data acquisition, normal vector estimation and incremental graph-based segmentation. This method guarantees the both real-time performance and accuracy of recognizing the objects in real urban environments. Also, it can provide plentiful data for classifying the objects. To evaluate a performance of proposed method, computation time and recognition rate of objects are analyzed. Experimental results show that the proposed method has efficiently in understanding the semantic knowledge of an urban environment.

• 정보처리학회논문지A
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• 제10A권2호
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• pp.157-164
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• 2003

최근 볼륨 그래픽스가 의료 영상의 해석 도구로서 주목을 받아 오고 있다. 볼륨 그래픽스에서는 가시화를 위하여 복셀로 정의된 물체가 필요하다. 이 때문에 기하학적인 방법으로 정의한 다각형 및 곡면을 복셀 기반의 물체로 변환시키는데 이를 복셀화(voxelization)라고 한다. 기하학적인 물체를 복셀화하면 기하학적 물체 데이터를 샘플링 데이터와 함께 단일화된 방법으로 볼륨 렌더링할 수 있다. 본 논문에서는 큐브의 단면을 이용한 복셀화의 한 기법을 제안한다. 그리고 개인용 컴퓨터 환경에서 이 기법을 구현한 후에 단순한 기하학적인 데이터를 이용해서 평가하여 논리적인 타당성을 조사한다. 이 기법은 변환된 복셀로부터 정확한 법선 벡터를 계산할 수 있고 복셀간에 구멍(hole)이 발생하지 않고 다해상도(multi-resolution) 표현이 가능한 특성을 가지고 있다.

• International Journal of Computer Science & Network Security
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• 제21권6호
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• pp.89-100
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• 2021

Smart Grid Network (SGN) is a next generation electrical power network which digitizes the power distribution grid and achieves smart, efficient, safe and secure operations of the electricity. The backbone of the SGN is information communication technology that enables the SGN to get full control of network station monitoring and analysis. In any network where communication is involved security is essential. It has been observed from several recent incidents that an adversary causes an interruption to the operation of the networks which lead to the electricity theft. In order to reduce the number of electricity theft cases, companies need to develop preventive and protective methods to minimize the losses from this issue. In this paper, we have introduced a machine learning based SVM method that detects malicious nodes in a smart grid network. The algorithm collects data (electricity consumption/electric bill) from the nodes and compares it with previously obtained data. Support Vector Machine (SVM) classifies nodes into Normal or malicious nodes giving the statues of 1 for normal nodes and status of -1 for malicious -abnormal-nodes. Once the malicious nodes have been detected, we have done a trust evaluation based on the nodes history and recorded data. In the simulation, we have observed that our detection rate is almost 98% where the false alarm rate is only 2%. Moreover, a Trust value of 50 was achieved. As a future work, countermeasures based on the trust value will be developed to solve the problem remotely.

• Journal of information and communication convergence engineering
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• 제20권3호
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• pp.219-225
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• 2022

In this study, we propose training a support vector machine (SVM) model on top of deep networks for detecting Covid-19 from chest X-ray images. We started by gathering a real chest X-ray image dataset, including positive Covid-19, normal cases, and other lung diseases not caused by Covid-19. Instead of training deep networks from scratch, we fine-tuned recent pre-trained deep network models, such as DenseNet121, MobileNet v2, Inception v3, Xception, ResNet50, VGG16, and VGG19, to classify chest X-ray images into one of three classes (Covid-19, normal, and other lung). We propose training an SVM model on top of deep networks to perform a nonlinear combination of deep network outputs, improving classification over any single deep network. The empirical test results on the real chest X-ray image dataset show that deep network models, with an exception of ResNet50 with 82.44%, provide an accuracy of at least 92% on the test set. The proposed SVM on top of the deep network achieved the highest accuracy of 96.16%.

• 한국게임학회 논문지
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• 제10권6호
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• pp.169-178
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• 2010

본 논문은 실시간 응용 프로그램에서 사실적인 금속 재질을 렌더링하기 위한 효과적인 기법을 제안한다. 제안된 기법은 금속면의 미세한 흡집을 표현하기 위해 법선 벡터를 섭동(perturbation)하는 방법을 사용한다. 법선 벡터를 섭동하는 일반적인 방법은 범프(bump) 매핑이나 법선(normal) 매핑 등의 방법을 사용하는 것이다. 그러나 이러한 방식은 이방성 반사 특성을 갖는 표면에서는 사실적인 빛의 산란을 보이지 못한다. 금속 특유의 반사를 표현하기 위해서는 미세면 분포 함수를 이용하여 이방성 반사 특성을 모델링하는 것이 일반적이므로 일반적 법선 섭동만으로는 만족스런 결과를 얻지 못한다. 본 논문은 법선 벡터의 섭동과 함께 미세면 분포 함수를 변형하는 기법을 통해 매우 사실적인 금속면 재질 렌더링이 가능한 기법을 제안한 다. 제안된 기법은 쉽게 GPU 프로그램으로 구현되며, 실시간 환경에서 동작한다.

• 정보보호학회논문지
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• 제14권1호
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• pp.35-45
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• 2004

폭발적으로 증가하는 인터넷 환경에서 정보보호는 가장 중요한 고려사항 중의 하나이다. 현재 이에 대한 대응방안으로 IDS, 방화벽, VPN 등 여러 보안 솔루션들이 사용되고 있지만 TCP/IP를 근간으로 하는 인터넷 환경은 기본적으로 프로토콜 자체의 취약성을 가지고 있다. 그 중에서도, TCP/IP 헤더 중 ICMP Payload. Identification(ID), Sequence Number(SEQ), Acknowledge(ACK). Timestamp의 필드 내용을 조작함으로써 특정 정보를 전송할 수 있는 은닉채널이 가능하다고 이미 알려져 있다. 특히 본 논문에서는 TCP/IP 헤더의 여러 필드들 중에서도 IP 헤더의 ID 필드, TCP 헤더의 SEQ 필드를 이용한 은닉채널 탐지에 초점을 맞추었으며, 이러한 은닉채널의 탐지를 위하여, 패턴분류 문제 있어서 우수한 성능을 보이는 것으로 알려져 있는 Support Vector Machine(SVM)을 사용하였다. 본 논문의 실험결과에서는 제안된 탐지방안이 정상 TCP/IP 트래픽으로부터 은닉채널이 포함된 TCP/IP 패킷을 구분할 수 있음을 보여주었다.

• 한국연초학회지
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• 제23권2호
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• pp.109-114
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• 2001

A CAB cDNA vector(pKGCAB), encoding the light harvesting chlorophyll a/b binding protein in Korean ginseng (Panax ginseng C. A. Meyer), was constructed with the CaMV35S promoter of plant expression vector. The chimeric vector was transformed into tobacco(Nicotiana tabacum cv. NC 82) using Agrobacterium tumefaciens LBA 4404 strain, and the transgenic tobacco plant CAB-TP2 was selected. Photosynthetic rates of the CAB-TP2 plant at before-flowering stage were increased about 20% under low irradiance conditions of quantum 100 and 500 $\mu$mol.m$^{-2}$ s$^{-1}$ , however, the rates were similar to those of NC 82 under quantum 1000 and 2000 $\mu$mol.m$^{-2}$ s$^{-1}$ conditions. The plants were germinating under low- or normal irradiance condition and the quantum yield of photosystem III were measured. The differences of the Fv/Em values between conditions were 0.07 and 0.01 in NC 82 and CAB-TP2, respectively. The mature leaves in the position 8-10 of the CAB-TP2 at before-flowering stage revealed l0% higher Fv/Fm values in range of 0.759 to 0.781 and 40% more chlorophyll contents of 70-93mg/$m\ell$ than those of normal NC 82. These data suggest the possibility that the increase in photosynthetic activity of leaves under low light intensity in the canopy of CAB-TP2 transgenic tobacco might lead to increase the quality of lower tobacco leaves.

• Bulletin of the Korean Chemical Society
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• 제31권10호
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• pp.2841-2848
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• 2010

Quasiclassical trajectory (QCT) method has been used to investigate stereodynamics information of the reaction $O(^1D)+H_2{\rightarrow}\;OH$+H on the DK (Dobbyn and Knowles) potential energy surface (PES) at a collision energy of 23.06 kcal/mol, with the initial quantum state of reactant $H_2$ being set for v = 0 (vibration quantum number) and j = 0-5 (rotation quantum number). The PDDCSs (polarization dependent differential cross sections) and the distributions of P($\theta_r$), P($\phi_r$), P($\theta_r$, $\phi_r$) have been presented in this work. The results demonstrate that the products are both forward and backward scattered. As j increases, the backward scattering becomes weaker while the forward scattering becomes slightly stronger. The distribution of P($\theta_r$) indicates that the product rotational angular momentum j' tends to align along the direction perpendicular to the reagent relative velocity vector k, but this kind of product alignment is found to be rather insensitive to j. Furthermore, the distribution of P($\phi_r$) indicates that the rotational angular momentum vector of the OH product is preferentially oriented along the positive direction of y-axis, and such product orientation becomes stronger with increasing j.