• Journal of Korea Technology Innovation Society
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• v.7 no.3
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• pp.607-640
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• 2004

This article analyzes the venture firm based upon the new framework of Dynamic Firm Capability (DFC) to identify the process mechanism. Research methodology includes the case study involving structured interview and data collection from two leading Korean ICT(Information Communication Technology) firms in the same sector (DVR). IDIS, spun off from the university, has accumulated the innovative capability based on the R&D department. On the other hand, KODICOM has retained the technological trajectory in terms of marketing competence. Underlying hypothesis is that a firm should show a idiosyncratic evolutionary pattern by acquiring different complimentary assets(CA). In addition, effective internal process should be matched with the essential characteristics not only at the firm level but also at the sectoral level. By analyzing those two different firms, we will find the strategic successful factors based upon the evolutionary point of view. It is a key contribution of this paper to study on the process mechanism of ventures, and to explain detailed process mechanism by viewing two different characteristics of the firm at the functional level.

• Korean Journal of Applied Biomechanics
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• v.17 no.3
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• pp.125-131
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• 2007

The purpose of this study was to evaluate the difference in grip force and angular kinematic variables between elite (handicap${\leq}2$) and novice golfers. Three-dimensional motion analysis system with synchronized grip force measurement system was used. The participants consisted of two groups based on their playing ability: 10 elite golfers and 10 novice golfers. Each subject performed 5 putting strokes at the distance of 1, 3, and 5m with randomly selected order. During entire putting phase, elite group showed relatively constant grip force but novice group showed continuously increasing grip force pattern. There existed a clear difference in the trajectory of shoulder line between two groups. As for novice group the rotational center did not converge into one point, for elite group the rotational center converged into precise single point. And there was a clear difference pattern in anterior-posterior directional movement at shoulder between two groups. These difference might be helpful for improving consistent putting skills.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.11
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• pp.152-165
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• 1998

This study proposes the analysis and evaluation method of time series ultrasonic signal using the chaoral post-process system for precision rate enhancement of ultrasonic pattern recognition. Chaos features extracted from time series data for analysis quantitatively weld defects For this purpose, feature extraction objectives in this study are fractal dimension, Lyapunov exponent, shape of strange attrator. Trajectory changes in the strange attractor indicated that even same type of defects carried substantial difference in chaoticity resulting from distance shifts such as nearby 0.5, 1.0 skip distance. Such difference in chaoticity enables the evaluation of unique features of defects in the weld zone. In quantitative chaos fenture extraction, feature values of 0.835 and 0.823 in the case of slag inclusion and 0.609 and 0.573 in the case of crack were suggested on the basis of fractal dimension and Lyapunov exponent. Proposed chaoral post-process system in this study can enhances precision rate of ultrasonic pattern recognition results from defect signals of weld zone, such as slag inclusion and crack.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.103-112
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• 2022

The goal of pattern mining is to identify novel patterns in a database. High utility itemset mining (HUIM) is a research direction for pattern mining. This is different from frequent itemset mining (FIM), which additionally considers the quantity and profit of the commodity. Several algorithms have been used to mine high utility itemsets (HUIs). The original BPSO algorithm lacks local search capabilities in the subsequent stage, resulting in insufficient HUIs to be mined. Compared to the transfer function used in the original PSO algorithm, the V-shaped transfer function more sufficiently reflects the probability between the velocity and position change of the particles. Considering the influence of the acceleration factor on the particle motion mode and trajectory, a nonlinear acceleration strategy was used to enhance the search ability of the particles. Experiments show that the number of mined HUIs is 73% higher than that of the original BPSO algorithm, which indicates better performance of the proposed algorithm.

• ETRI Journal
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• v.31 no.5
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• pp.565-575
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• 2009

This paper concerns the use of support vector regression (SVR), which is based on the kernel method for learning from examples, in identification of walking robots. To handle complex dynamics in humanoid robot and realize stable walking, this paper develops and implements two types of reference natural motions for a humanoid, namely, walking trajectories on a flat floor and on an ascending slope. Next, SVR is applied to model stable walking motions by considering these actual motions. Three kinds of kernels, namely, linear, polynomial, and radial basis function (RBF), are considered, and the results from these kernels are compared and evaluated. The results show that the SVR approach works well, and SVR with the RBF kernel function provides the best performance. Plus, it can be effectively applied to model and control a practical biped walking robot.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.45-51
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• 2000

This study proposes that analysis and evaluation method of time series ultrasonic signal using the chaotic feature extrac-tion for degradation extent. Features extracted from time series data using the chaotic time series signal analyze quantitatively material degradation extent. For this purpose analysis objective in this study if fractal dimension lyapunov exponent and strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical syste, In experiment fractal(correlation) dimensions and lyapunov experiments showed values of mean 3.837-4.211 and 0.054-0.078 in case of degradation material The proposed chaotic feature extraction in this study can enhances ultrasonic pattern recognition results from degrada-tion signals.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.3 no.5
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• pp.350-364
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• 1991

The movements of small particles distributed uniformly in a steady flow in rectangular chambers having inlets and outlets were simulated numerically. Low Reynolds number turbulent model with a two-equation ($k-{\varepsilon}$) which describes the turbulent characteristics was applied to predict the air flow pattern and particles movements under the condition of the various locations and size of ducts. The calculation results show that the prediction of recirculation zone and stagnation point of flow is important to determine the particles behavior according to the design change. These results will be useful in designing the rectangular chambers for collective protection.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.466-479
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• 2006

This paper addresses a formation navigation issue for a group of mobile robots passing through an environment with either static or moving obstacles meanwhile keeping a fixed formation shape. Based on Lyapunov function and graph theory, a NN formation control is proposed, which guarantees to maintain a formation if the formation pattern is $C^k,\;k\geq1$. In the process of navigation, the leader can generate a proper trajectory to lead formation and avoid moving obstacles according to the obtained information. An evolutionary computational technique using particle swarm optimization (PSO) is proposed for motion planning so that the formation is kept as $C^1$ function. The simulation results demonstrate that this algorithm is effective and the experimental studies validate the formation ability of the multiple mobile robots system.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.358-364
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• 2007

Intelligent walking modeling of humanoid robot using learning based neuro-fuzzy system is presented in this paper. Walking pattern, trajectory of the zero moment point (ZMP) in a humanoid robot is used as an important criterion for the balance of the walking robots but its complex dynamics makes robot control difficult. In addition, it is difficult to generate stable and natural walking motion for a robot. To handle these difficulties and explain empirical laws of the humanoid robot, we are modeling practical humanoid robot using neuro-fuzzy system based on the two types of natural motions which are walking trajectories on a t1at floor and on an ascent. Learning based neuro-fuzzy system employed has good learning capability and computational performance. The results from neuro-fuzzy system are compared with previous approach.

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.83-89
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• 2016

Internet of Things (IoT) is widely used for biomechanics in sports activities and AHRS(Attitude and Heading Reference System) is a more cost effective solution than conventional high-grade IMUs (Inertial Measurement Units) that only integrate gyroscopes. In this paper, we attach the AHRS to the snowboard to measure the motion data like Air To Fakie, Caballerial and Free Style. In order to reduce the measurement error, we have adopted the sensors equipped with Kalman filtering and also used Euler angle to quaternion conversion to reduce the Gimbal-lock effect. We have tested and evaluated the accuracy and execution time of the pattern recognition algorithms like PCA, ICA, LDA, SVM to show the recognition possibility of it on the basic motions of Snowboarding from the 9-axis trajectory information which is gathered from AHRS sensor. With the result, PCA, ICA have low accuracy, but SVM have good accuracy to use for recognition of basic motions of Snowboarding.