• The Journal of the Korea institute of electronic communication sciences
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• 제7권2호
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• pp.401-407
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• 2012

This paper analyzes performance of major obstacle avoidance methods. For the analysis, numerical performance indexes are proposed: motion distance to goal point, motion time, distance to obstacles, and smoothness of the motion. Especially, the index of smoothness measures efficiency of the motion using the angular acceleration and jerk of the robot heading. Four major obstacle avoidance methods are compared in terms of the performance indexes. The four methods are artificial potential field(APF) method, elastic force(EF) method, APF with virtual distance, and EF with virtual distance. Through simulation, the four methods are compared and features of the methods are explored.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• 제34권7호
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• pp.63-70
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• 2006

This paper describes research of using area of artificial mark on vision based head tracker system. A head tracker system consists of the translational and rotational motions which are detected by web camera. Results of the motion are taken from image processing and neural network. Because of the characteristics of cockpit, the specific color on the helmet is tracked for translational motion. And rotational motion is tracked via neural network. Ratio of two different colored area on the helmet is used as input of network. Neural network algorithms used, such as back-propagation and RBFN (Radial Basis Function Network). Both back-propagation using a characteristic of feedback and RBFN using a characteristic of statistics have a good performances for the tracking of nonlinear system such as a head motion. Finally, this paper analyzes and compares with tracking performance.

• Journal of the Earthquake Engineering Society of Korea
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• 제15권1호
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• pp.57-63
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• 2011

In this study, a ground motion response spectrum for the seismic risk assessment of low and intermediate level radioactive waste repositories was developed. For the development of the ground motion response spectrum, a probabilistic seismic hazard analysis (PSHA) was performed. Through the performance of a PSHA, a seismic hazard curve which was based on a seismic bed rock was developed. A uniform hazard spectrum was determined by using a developed seismic hazard curve. Artificial seismic motions were developed based on the uniform hazard spectrum. A seismic response analysis was performed on the developed artificial seismic motion. Finally, an evaluation response spectrum for the seismic risk assessment analysis of low and intermediate level radioactive waste repositories was developed.

• Journal of Internet of Things and Convergence
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• 제9권3호
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• pp.13-19
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• 2023

In this paper, we investigated the implementation of a hairstyle recommendation system based on big data and deepfake technology. The proposed hairstyle recommendation system recognizes the facial shapes based on the user's photo (image). Facial shapes are classified into oval, round, and square shapes, and hairstyles that suit each facial shape are synthesized using deepfake technology and provided as videos. Hairstyles are recommended based on big data by applying the latest trends and styles that suit the facial shape. With the image segmentation map and the Motion Supervised Co-Part Segmentation algorithm, it is possible to synthesize elements between images belonging to the same category (such as hair, face, etc.). Next, the synthesized image with the hairstyle and a pre-defined video are applied to the Motion Representations for Articulated Animation algorithm to generate a video animation. The proposed system is expected to be used in various aspects of the beauty industry, including virtual fitting and other related areas. In future research, we plan to study the development of a smart mirror that recommends hairstyles and incorporates features such as Internet of Things (IoT) functionality.

• Journal of the Korean Society for Precision Engineering
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• 제26권4호
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• pp.82-90
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• 2009

Pneumatic cylinder is one of the low cost actuation sources which have been applied in industrial and prosthetic application since it has a high power/weight ratio, a high-tension force and a long durability However, the control problems of pneumatic systems, oscillatory motion and compliance, have prevented their widespread use in advanced robotics. To overcome these shortcomings, a number of newer pneumatic actuators have been developed such as McKibben Muscle, Rubber Actuator and Pneumatic Artificial Muscle (PAM) Manipulators. In this paper, one solution for position control of a robot arm, which is driven by two pneumatic artificial muscles, is presented. However, some limitations still exist, such as a deterioration of the performance of transient response due to the changes in the external load of the robot arm. To overcome this problem, a switching algorithm of the control parameter using a learning vector quantization neural network (LVQNN) is proposed in this paper. This estimates the external load of the pneumatic artificial muscle manipulator. The effectiveness of the proposed control algorithm is demonstrated through experiments with different external working loads.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 한국전산구조공학회 1998년도 가을 학술발표회 논문집
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• pp.439-446
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• 1998

One of the most important roles in the nonlinear dynamic structural analysis is to select a proper ground excitation, which dominates the response of a structure. Because of the lack of recorded accelerograms in Korea, a stochastic model of ground excitation with various dynamic properties rather than recorded accelerograms is necessarily required. If all information is not available at site, the information from other sites with similar features can be used by the procedure of seismic hazard analysis. Eliopoulos and Wen identified the parameters of the ground motion model by the empirical relations or expressions developed by Trifunac and Lee. Because the relations used in the parameter identification are largely empirical, it is required to apply the artificial neural networks instead of the empirical model. Additionally, neural networks have the advantage of the empirical model that it can continuously re-train the new recorded data, so that it can adapt to the change of the enormous data. Based on the redefined traditional processes, three neural-networks-based models (FAS_NN, PSD_NN and INT_NN) are proposed to individually substitute the Fourier amplitude spectrum, the parameter identification of power spectral density function and intensity function. The paper describes the first half of the research for the development of Neural-Networks-based model for the generation of an Artificial earthquake and a Response Spectrum(NNARS).

• The Journal of the Society of Korean Medicine Diagnostics
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• 제16권3호
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• pp.33-40
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• 2012

Objectives: Existing cardiovascular simulators are used to evaluate artificial organs such as artificial hearts, prosthetic valves, and artificial blood vessels, and pulses are typically triggered using artificial hearts. However, the forms of pulse waves vary according to the location of arteries, and for precise assessment of artificial blood vessels, the development of simulators that generate diverse pressure pulse waves is necessary. This study developed a novel cardiovascular simulator that generates different forms of pulse waves. Methods: This simulator consists of a stepping motor, a slider-crank mechanism that transforms the rotation movement of a motor into the straight-line motion of a piston, a piston that generates pulsatile flows, a water tank that supplies fluids, an elastic tube made of silicon, and a device that adjusts the terminal resistance of fluids. Results & Conclusion: This study examined motor rotation and its operation under conditions similar to the physiological conditions of the heart. The simulator developed in this study produced diverse forms of waves, and the generated pressure waves well satisfied physiological conditions.

• Journal of the Microelectronics and Packaging Society
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• 제29권3호
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• pp.1-12
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• 2022

With the rapid development of artificial intelligence technology that gives existing sensors functions similar to human intelligence is drawing attention. Previously, researches were mainly focused on an improvement of fundamental performance indicators as sensors. However, recently, attempts to combine artificial intelligence such as classification and prediction with sensors have been explored. Based on this, intelligent sensor research has been actively reported in almost all kinds of sensing fields such as disease detection, motion detection, and gas sensor. In this paper, we introduce the basic concepts, types, and driving mechanisms of artificial intelligence and review some examples of its use.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.894-903
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• 2008

In this paper, we present an artificial muscle actuator producing rectilinear motion, called the Tube-Spring-Actuator(TSA). The TSA is supposed to be a prospective substitute in areas requiring macro forces such as robotics. It is simply configured from a synthetic elastomer tube with an inserted spring. The design of the TSA is described in detail and its analysis is conducted to investigate the characteristics of the actuator based on the derived model. In addition, the performance of the proposed actuator is tested via experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• 제59권8호
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• pp.1482-1488
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• 2010

Recently to increase the productivity and improve the quality in the industrial process, suppressing the residual vibration in motion control systems becomes the essential problem to solve. One of the methods to suppress the residual vibration is the input shaping technique. It is based on parameters of the system model; however, the parameters are usually difficult to obtain. This paper shows the effects of the residual vibration caused by the variation of the general velocity profile for the system with two vibration modes, and also shows the effects of the input shaping filter based on the parameters of system model. Finally, the simulation results show that the proposed input shaping filter using an artificial immune algorithm is more effective for suppressing residual vibrations than genetic algorithm.