• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.2
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• pp.315-327
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• 2017

Security threats such as unauthorized access and data tampering can occur during the virtual machine migration process. In particular, since virtual machine migration requires users to transfer important data and infrastructure information, it is relatively risky to other cloud services in case of security threats. For this reason, there is a need for dynamic authentication for virtual machine migration. Therefore, this paper proposes an OTP-based dynamic authentication framework to improve the vulnerabilities of the existing authentication mechanism for virtual machine migration. It consists of a virtual machine migration request module and an operation module. The request module includes an OTP-based user authentication process and a migration request process to a data center when a user requests a migration. The operation module includes a secure key exchange process between the data centers using SPEKE and a TOTP-based mutual authentication process between the data center and the physical server.

• Korean Journal of Applied Biomechanics
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• v.32 no.1
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• pp.1-8
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• 2022

Objective: This study proposes a methodology to analyze important variables that have a significant impact on the putting direction prediction using a machine learning-based putting direction prediction model trained with IMU sensor data. Method: Putting data were collected using an IMU sensor measuring 12 variables from 6 adult males in their 20s at K University who had no golf experience. The data was preprocessed so that it could be applied to machine learning, and a model was built using five machine learning algorithms. Finally, by comparing the performance of the built models, the model with the highest performance was selected as the proposed model, and then 12 variables of the IMU sensor were applied one by one to analyze important variables affecting the learning performance. Results: As a result of comparing the performance of five machine learning algorithms (K-NN, Naive Bayes, Decision Tree, Random Forest, and Light GBM), the prediction accuracy of the Light GBM-based prediction model was higher than that of other algorithms. Using the Light GBM algorithm, which had excellent performance, an experiment was performed to rank the importance of variables that affect the direction prediction of the model. Conclusion: Among the five machine learning algorithms, the algorithm that best predicts the putting direction was the Light GBM algorithm. When the model predicted the putting direction, the variable that had the greatest influence was the left-right inclination (Roll).

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.267-277
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• 2024

This paper explores the use of machine learning in game production to create goal-oriented, realistic animations for skeleton monsters. The purpose of this research is to enhance realism by implementing intelligent movements in monsters within game development. To achieve this, we designed and implemented a learning model for skeleton monsters using reinforcement learning algorithms. During the machine learning process, various reward conditions were established, including the monster's speed, direction, leg movements, and goal contact. The use of configurable joints introduced physical constraints. The experimental method validated performance through seven statistical graphs generated using machine learning methods. The results demonstrated that the developed model allows skeleton monsters to move to their target points efficiently and with natural animation. This paper has implemented a method for creating game monster animations using machine learning, which can be applied in various gaming environments in the future. The year 2024 is expected to bring expanded innovation in the gaming industry. Currently, advancements in technology such as virtual reality, AI, and cloud computing are redefining the sector, providing new experiences and various opportunities. Innovative content optimized for this period is needed to offer new gaming experiences. A high level of interaction and realism, along with the immersion and fun it induces, must be established as the foundation for the environment in which these can be implemented. Recent advancements in AI technology are significantly impacting the gaming industry. By applying many elements necessary for game development, AI can efficiently optimize the game production environment. Through this research, We demonstrate that the application of machine learning to Unity and game engines in game development can contribute to creating more dynamic and realistic game environments. To ensure that VR gaming does not end as a mere craze, we propose new methods in this study to enhance realism and immersion, thereby increasing enjoyment for continuous user engagement.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2001.02a
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• pp.310-315
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• 2001

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.445-450
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• 1989

In this study, a variety of method to diagnose a fault of rotatory machine is suggested. Apprehending the physical meaning of each techniques, computer simulation is performed. The result from this computer simulation and the signal of the faulted ball bearing is studied from all its aspect. It is found that this conditioning monitor system is effective.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.2
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• pp.208-213
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• 2012

In this paper, the radial error of a rotary table at five-axis machine tool is evaluated by utilizing ISO 230-2 and estimation method using double ball-bar. The geometric error of a rotary table is defined as position dependent geometric errors or position independent geometric errors according to their physical character. Then estimation method of geometric errors using double ball-bar is simply summarized including measurement path, parametric modeling and least squares approach. To estimate representative radial error, offset error, set-up error which affect to the double ball-bar data, mean value of measured data including CCW/CW-direction are used at estimation process. Radial errors are separated from measured data and used for evaluation with ISO 230-2. Finally, suggested evaluation method is applied to a rotary table at five-axis machine tool and its result is analyzed to improve the accuracy of the rotary table.

• Advances in robotics research
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• v.1 no.2
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• pp.155-169
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• 2014

Study results in the last decades show that amount and quality of physical exercises, then the active participation, and now the cognitive involvement of patient in rehabilitation training are known of crux to enhance recovery outcome of motor dysfunction patients after stroke. Rehabilitation robots mainly have been developing along this direction to satisfy requirements of recovery therapy, or focusing on one or more of the above three points. Therefore, neuro-machine interaction based active rehabilitation robot has been proposed for assisting paralyzed limb performing designed tasks, which utilizes motor related EEG, UCSDI (Ultrasound Current Source Density Imaging), EMG for rehabilitation robot control and feeds back the multi-sensory interaction information such as visual, auditory, force, haptic sensation to the patient simultaneously. This neuro-controlled and perceptual rehabilitation robot will bring great benefits to post-stroke patients. In order to develop such kind of robot, some key technologies such as noninvasive precise detection of neural signal and realistic sensation feedback need to be solved. There are still some grand challenges in solving the fundamental questions to develop and optimize such kind of neuro-machine interaction based active rehabilitation robot.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.6
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• pp.491-499
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• 2007

The variation of a load characteristic in the motor drive is one of the most important consideration. Because the current flowing into the motor generally varies according to the load variation, it needs to design the motor drive circuit properly in accordance with the load variation. However, the load variation of the drum washing machine is irregular and large due to the water flow and reverse load torque. Therefore, to design the motor drive circuit considering this load pattern, simulation results shows the load pattern modeling of the drum washing machine based on the physical analysis in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.2
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• pp.480-497
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• 2012

As a new business concept, machine-to-machine (M2M) communications are born from original telemetry technology with the intrinsic features of automatic data transmissions and measurement from remote sources typically by cable or radio. M2M includes a number of technologies that need to be combined in a compatible manner to enable its deployment over a broad market of consumer electronics. In order to provide better understanding for this emerging concept, the correlations among M2M, wireless sensor networks, cyber-physical systems (CPS), and internet of things are first analyzed in this paper. Then, the basic M2M architecture is introduced and the key elements of the architecture are presented. Furthermore, the progress of global M2M standardization is reviewed, and some representative applications (i.e., smart home, smart grid and health care) are given to show that the M2M technologies are gradually utilized to benefit people's life. Finally, a novel M2M system integrating intelligent road with unmanned vehicle is proposed in the form of CPS, and an example of cyber-transportation systems for improving road safety and efficiency are introduced.

• Journal of The Korean Society of Integrative Medicine
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• v.1 no.4
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• pp.67-74
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• 2013

Purpose : The purpose of this study was to investigate the effect of horseback riding exercise for BMI(body mass index) and waist circumference in the obese women. Method : 20 subjects in Y-equestrian were randomly divided two group, horseback machine exercise(HME) group and horseback-riding exercise(HRE) group. Each group carried out 30 minutes exercise two times a week for 8 weeks. BMI were measured for body composition, and evaluation of waist circumference. Result : The results were as follows, the BMI(body mass index) between horseback machine exercise and horseback-riding exercise groups in post-test, were significantly different in measures(p<.05). And there were significant in two group after exercise(p<.05). The waist circumference between horseback machine exercise and horseback-riding exercise groups in post-test, were significantly different in measures(p<.05). And there were significant in two group after exercise(p<.05). Conclusion : These finding revealed that horseback-riding exercise was effective on BMI and waist circumrerence of obese women so that these exercise can be new altematives exercise for obesity management in the obese women.