• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2705-2711
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• 2011

The recent development in multimedia technology such as audio technology needs high quality audio system. Especially, Real Audio Technology is to be developed to play realistic sound. To meet this demands, researches on 3-Dimensional Audio which provides realistic audio effect in virtual reality and augmented reality are conducted. In this paper, how to provide realistic audio effect by using better audio technologies in augmented reality was investigated. In the study, the movements of the 3-Dimensional model on the markers were used to provide the sense of reality in virtual and real world. Namely, the sound was modified according to the movement of the model. The change in distance and angle of the model affected the sound volume and the pitch.

• Structural Engineering and Mechanics
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• v.67 no.6
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• pp.617-628
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• 2018

This paper deals with the maximization of the critical buckling load of simply supported antisymmetric angle-ply plates resting on Pasternak foundation subjected to compressive loads using teaching learning based optimization method (TLBO). The first order shear deformation theory is used to obtain governing equations of the laminated plate. In the present optimization problem, the objective function is to maximize the buckling load factor and the design variables are the fibre orientation angles in the layers. Computer programming is developed in the MATLAB environment to estimate optimum stacking sequences of laminated plates. A comparison also has been performed between the TLBO, genetic algorithm (GA) and differential evolution algorithm (DE). Some examples are solved to show the applicability and usefulness of the TLBO for maximizing the buckling load of the plate via finding optimum stacking sequences of the plate. Additionally, the influences of different number of layers, plate aspect ratios, foundation parameters and load ratios on the optimal solutions are investigated.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.5
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• pp.550-557
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• 1999

This paper describes a road-following controller using the proposed neural network for autonomous vehicle. Road-following with visual sensor like camera requires intelligent control algorithm because analysis of relation from road image to steering control is complex. The proposed neural network, relative similarity modular network(RSMN), is composed of some learning networks and a partitioniing network. The partitioning network divides input space into multiple sections by similarity of input data. Because divided section has simlar input patterns, RSMN can learn nonlinear relation such as road-following with visual control easily. Visual control uses two criteria on road image from camera; one is position of vanishing point of road, the other is slope of vanishing line of road. The controller using neural network has input of two criteria and output of steering angle. To confirm performance of the proposed neural network controller, a software is developed to simulate vehicle dynamics, camera image generation, visual control, and road-following. Also, prototype autonomous electric vehicle is developed, and usefulness of the controller is verified by physical driving test.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.97-102
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• 2013

Objective: The aim of this study was to develop an automated computer-aided diagnostic system for diagnosis of thyroid cancer pattern in fine needle aspiration cytology (FNAC) microscopic images with high degree of sensitivity and specificity using statistical texture features and a Support Vector Machine classifier (SVM). Materials and Methods: A training set of 40 benign and 40 malignant FNAC images and a testing set of 10 benign and 20 malignant FNAC images were used to perform the diagnosis of thyroid cancer. Initially, segmentation of region of interest (ROI) was performed by region-based morphology segmentation. The developed diagnostic system utilized statistical texture features derived from the segmented images using a Gabor filter bank at various wavelengths and angles. Finally, the SVM was used as a machine learning algorithm to identify benign and malignant states of thyroid nodules. Results: The SVMachieved a diagnostic accuracy of 96.7% with sensitivity and specificity of 95% and 100%, respectively, at a wavelength of 4 and an angle of 45. Conclusion: The results show that the diagnosis of thyroid cancer in FNAC images can be effectively performed using statistical texture information derived with Gabor filters in association with an SVM.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.50-59
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• 1998

This paper presents stabilization and adaptive control of flexible single link robot manipulator system by self-recurrent neural networks that is one of the neural networks and is effective in nonlinear control. The architecture of neural networks is a modified model of self-recurrent structure which has a hidden layer. The self-recurrent neural networks can be used to approximate any continuous function to any desired degree of accuracy and the weights are updated by feedback-error learning algorithm. When a flexible manipulator is rotated by a motor through the fixed end, transverse vibration may occur. The motor toroque should be controlled in such a way that the motor rotates by a specified angle, while simultaneously stabilizing vibration of the flexible manipuators so that it is arresed as soon as possible at the end of rotation. Accurate vibration control of lightweight manipulator during the large changes in configuration common to robotic tasks requires dynamic models that describe both the rigid body motions, as well as the flexural vibrations. Therefore, a dynamic models for a flexible single link robot manipulator is derived, and then a comparative analysis was made with linear controller through an simulation and experiment. The results are proesented to illustrate thd advantages and imporved performance of the proposed adaptive control ove the conventional linear controller.

• Korean Journal of Applied Biomechanics
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• v.22 no.1
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• pp.1-7
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• 2012

The purpose of this study was to investigate the pattern change of throwing in baseball after 15 weeks of participation in baseball class, by examining ball speed, trunk and upper body angles. The comparison was with 6 university students that haven't had any experience in baseball. 8 infra red cameras and 2 force platforms were used to collect the data. First, there was an increase in the speed of the ball after the class. Second, there was no significant difference in the allocated phases during the throw before and after class. Third, the release point was lower and more in front. Forth, there was an increase in the knee flexion at the left foot landing and release point. Finally, there was an increase in the maximum shoulder external rotation and pelvis angle. It is recommended that the coordination between the segments should be investigated to improve our understanding of the learning of throwing in future research.

• Korean Journal of Applied Biomechanics
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• v.24 no.3
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• pp.209-216
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• 2014

The purpose of this study was to explore the effect of 8 weeks after school classes of track sports on students' start motion through kinematic variables. 30 students in D National university of education participated for this study. These students divided into two groups, 17 students for experimental group and 13 students for control group. The two groups participated in general athletic class as common class, and the experimental group participated in after school class additionally. The general class taught track and jump skill for 3 hours a week, and the after school class taught only athletic running skill for 30 minutes a week. Pre and post test assessed to assess students' kinematic changes. Findings indicated that velocity and step rate were increased, and contact time, step length, displacement of center of mass were decreased in the experimental group. In the control group, early velocity, knee/hip angle velocity were increased, and contact time, step length, displacement of center of mass were decreased. In conclusion, the students who only participated in general class, could not maintain athletic skills obtained from the class. However, students who participated in both general and after school class accomplish athletic start skill. This is because Continuous learning effect helped students keep the skill and did not lose the skill. Thus, in order for students to learn specific sport skills, joining after school class with general class together is recommended.

• Journal of the Korean Society of Physical Medicine
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• v.15 no.4
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• pp.1-9
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• 2020

PURPOSE: The current generation has shortened hamstrings due to a sedentary lifestyle, resulting in reduced flexibility of the hamstring and dysfunction. This study was undertaken to compare effects of three different release exercises on hamstring flexibility, in participants with short hamstrings. METHODS: Totally, 20 subjects having short hamstrings were involved in this study. The inclusion criterion for study participation was active knee extension test (AKET) less than 60°. All participants were subjected to 3 methods: hamstring foam roller release (HFRR), sitting self myofascial release (sitting SMR), and standing self myofascial release (Standing SMR). All participants randomly performed all three methods to avoid bias caused by learning or fatigue. Passive knee extension test (PKET), AKET, finger to floor distance test (FTFT), and pelvic tilting angle test (PTAT) were measured pre- and post-exercises. RESULTS: The PKET, AKET and FTFT were significantly increased after HFRR, sitting SMR, and standing SMR exercise (p < .05). However, PTAT was not significantly increased after the three exercises (p > .05). Furthermore, no significant differences were observed between PKET, AKET, FTFT and PTAT subsequent to HFRR, sitting SMR, and standing SMR (p > .05). CONCLUSION: Our results indicate that HFRR, sitting SMR and standing SMR were immediately effective in improving hamstring flexibility in participants with short hamstrings.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.6
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• pp.797-803
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• 2014

In this paper, 3D face recognition system is designed by using polynomial based on RBFNNs. In case of 2D face recognition, the recognition performance reduced by the external environmental factors such as illumination and facial pose. In order to compensate for these shortcomings of 2D face recognition, 3D face recognition. In the preprocessing part, according to the change of each position angle the obtained 3D face image shapes are changed into front image shapes through pose compensation. the depth data of face image shape by using Multiple Point Signature is extracted. Overall face depth information is obtained by using two or more reference points. The direct use of the extracted data an high-dimensional data leads to the deterioration of learning speed as well as recognition performance. We exploit principle component analysis(PCA) algorithm to conduct the dimension reduction of high-dimensional data. Parameter optimization is carried out with the aid of PSO for effective training and recognition. The proposed pattern classifier is experimented with and evaluated by using dataset obtained in IC & CI Lab.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.56-62
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• 2008

This paper proposes the use of decision tree classification for the measuring pattern recognition from industrial Computed Radiography(CR) images used in nondestructive evaluation(NDE) of steel-tubes. It appears that NDE problems are naturally desired to have machine learning techniques identify patterns and their classification. The attributes of decision tree are taken from NDE test procedure. Geometric features, such as radiative angle, gradient and distance, are estimated from the analysis of input image data. These factors are used to make it easy and accurate to classify an input object to one of the pre-specified classes on decision tree. This algerian is to simplify the characterization of NDE results and to facilitate the determination of features. The experimental results verify the usefulness of proposed algorithm.