• Proceedings of the KSME Conference
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• 2004.11a
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• pp.459-464
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• 2004

The rifle impact of human body affected by the posture of human for rifling. The interaction human-rifle system influence the firing accuracy. In this paper, impact analysis of human model for shooting posture is carried out. ADAMS code and LifeMOD is used in impact analysis of human model and modeling of the human body, respectively. On the shooting, human model is affected by rifle impact during the 0.001 second. Performed simulation time for shooting is 0.1 second. Applied constraint condition to human-rifle system is rotating and spherical condition. As the results, the displacement of rifle and transfer path analysis of impact of human model is presented.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2947-2950
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• 2007

A 3D human ventricular model is proposed to simulate an integrative analysis of heart physiology and blood hemodynamics. This consists of the models of electrophysiology of human cells, electric wave propagation of tissue, heart solid mechanics, and 3D blood hemodynamics. The 3D geometry of human heart is discretized to a finite element mesh for the simulation of electric wave propagation and mechanics of heart. In cellular level, excitations by action potential are simulated using the existing human model. Then the contraction mechanics of a whole cell is incorporated to the excitation model. The excitation propagation to ventricular cells are transiently computed in the 3D cardiac tissue using a mono-domain method of electric wave propagation in cardiac tissue. Blood hemodynamics in heart is also considered and incorporated with muscle contraction. We use a PISO type finite element method to simulate the blood hemodynmaics in the human ventricular model.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.113-116
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• 2000

Human face recognition and 3D human face reconstruction has been studied in this paper. To find the facial feature points, find edge from input image and analysis the accumulated histogram of edge information. This paper use a Generic Face Model to display the 3D human face model which was implement with OpenGL and generated with 500 polygons. For reality of 3D human face model, we propose Group matching mapping method between facial feature points and the one of Generic Face Model. The personalized 3D human face model which resembles real human face can be generated automatically in less than 5 seconds on Pentium PC.

• Journal of Navigation and Port Research
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• v.29 no.2
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• pp.135-140
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• 2005

In this paper, we propose a human model for analysing the human work pattern or human fault, where a gantry crane simulator is used to survey the property cf human operation From the input and output cf gantry crane response, we make a human operation model by using conventional ARX identification method To identify the human model, we assume the eight inputs and two outputs. By using the achieved input/output data, we estimate the parameters of ARX for the human work model. To verify the proposed method, we compared the real data with the modeled data, where three kinds of work trajectory path are used.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.186-192
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• 2009

In this paper, we represent the recognition method for human frontal upper body pose. In HCI(Human Computer Interaction) and HRI(Human Robot Interaction) when a interaction is established the human has usually frontal direction to the robot or computer and use hand gestures then we decide to focus on human frontal upper-body pose, The two main difficulties are firstly human pose is consist of many parts which cause high DOF(Degree Of Freedom) then the modeling of human pose is difficult. Secondly the matching between image features and modeling information is difficult. Then using Pictorial Model we model the human main poses which are mainly took the space of frontal upper-body poses and we recognize the main poses by making main pose database. using determined main pose we used the model parameters for particle filter which predicts the posterior distribution for pose parameters and can determine more specific pose by updating model parameters from the particle having the maximum likelihood. Therefore based on recognizing main poses and tracking the specific pose we recognize the human frontal upper body poses.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.722-725
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• 2023

대규모 언어 모델(LLM)은 대규모의 데이터를 학습하여 얻은 지식을 기반으로 텍스트와 다양한 콘텐츠를 인식하고 요약, 번역, 예측, 생성할 수 있는 딥러닝 알고리즘이다. 초기 공개된 LLM은 영어 기반 모델로 비영어권에서는 높은 성능을 기대할 수 없었으며, 이에 한국, 중국 등 자체적 LLM 연구개발이 활성화되고 있다. 본 논문에서는 언어가 LLM의 성능에 영향을 미치는가에 대하여 한국어 기반 LLM과 영어 기반 LLM으로 KoBEST의 4가지 Task에 대하여 성능비교를 하였다. 그 결과 한국어에 대한 사전 지식을 추가하는 것이 LLM의 성능에 영향을 미치는 것을 확인할 수 있었다.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.201-209
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• 2003

Virtual human models are widely used to save time and expense in vehicle safety studies. A human model is an essential tool to visualize and simulate a vehicle driver in virtual environments. This research is focused on creation and application of a human model fer virtual reality. The Korean anthropometric data published are selected to determine basic human model dimensions. These data are applied to GEBOD, a human body data generation program, which computes the body segment geometry, mass properties, joints locations and mechanical properties. The human model was constituted using MADYMO based on data from GEBOD. Frontal crash and bump passing test were simulated and the driver's motion data calculated were transmitted into the virtual environment. The human model was organized into scene graphs and its motion was visualized by virtual reality techniques including OpenGL Performer. The human model can be controlled by an arm master to test driver's behavior in the virtual environment.

• Korean Journal of Computational Design and Engineering
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• v.14 no.6
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• pp.364-373
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• 2009

In this paper, we suggest the method for constructing parameterized human body model which has any required body sizes from 3D scan data. Because of well developed 3D scan technology, we can get more detailed human body model data which allow to generate precise human model. In this field, there are a lot of research is performed with 3D scan data. But previous researches have some limitations to make human body model. They need too much time to perform hole-filling process or calculate parameterization of model. Even more they missed out verification process. To solve these problems, we used several methods. We first choose proper 125 3D scan data from 5th Korean body size survey of Size Korea according to age, height and weight. We also did post process, feature point setting, RBF interpolation and align, to parameterize human model. Then principal component analysis is adapted to the result of post processed data to obtain dominant shape parameters. These steps allow to reduce process time without loss of accuracy. Finally, we compare these results and statistical data of Size Korea to verify our parameterized human model.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.3
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• pp.254-259
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• 2016

Recently, DC distribution systems have become a hot issue because of the increase in digital loads and DC generation systems according to the expansion of renewable energy technologies. To obtain the practical usage of DC electricity, safety should be guaranteed. The main concerns for safety are twofold: one side is human protection against electric shocks, and the other is facility protection from short faults. "Effects of current on human beings and livestock" (IEC 60479) defines a human body impedance model in electric shock conditions that consists of resistive components and capacitive components. Although the human body impedance model properly works in AC electricity, it does not well match with the electric shock behavior in DC electricity. In this study, the contradiction of the human body impedance model defined by IEC 60479 in case of DC electricity is shown through experiments for the human body. From the analysis of experimental results, a novel unified human body impedance model in electric shock conditions is proposed. This model consists of resistive components, capacitive components, and an inductance component. The proposed human impedance model matches well for AC and DC electricity environments in simulation and experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.977-989
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• 1999

The purpose of this study is to analyze how the human body having more muscles than its degree-of-freedom modulates an effective stiffness using redundant actuation, and to apply this concept to the design and control of advanced machines which requires adaptable spring. To investigate the adaptable stiffness phenomenon due to redundant actuation in the human body, this paper derives a general stiffness model of the Human body. In particular, for a planar 1 DOF human arm model, a planar 2 DOF human arm model, a spherical 3 DOF shoulder model, a 4 DOF human arm model, and a 7 DOF human arm model, the required nonlinear geometry ad the number of required actuator for successful modulation of the effective stiffness are analyzed along with a load distribution method for modulation of the required stiffness of such systems. Secondly, the concept of motion frequency modulation is introduced to show the usefulness of adaptive stiffness modulation. The motion frequency modulation represents a control of stiffness and / or inertia properties of systems. To show the effectiveness of the proposed algorithm, simulations are performed for 2 DOF anthropomorphic robot.