• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1714-1719
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• 2003

Antilock Brake System (ABS) is indispensable safety equipment for vehicles today. In order to develop new ABS ECU suitable for pneumatic brake system of a bus, a Hardware In-the-Loop Simulation (HILS) System was developed. In this HILS, the pneumatic brake system of a bus and antilock brake component were used as hardware. For the computer simulation, the 14-Degree of Freedom (DOF) bus dynamic model was constructed using the Matlab/Simulink software package. This model was compiled and downloaded in the simulation board, where the Power PC processor was used for real-time simulation. Additional commercial package, the ControlDesk was used to monitor the dynamic simulation results and physical signal values. This paper will focus on the procedure and results of evaluating the ECU in the HILS simulation. Two representative cases, wet basalt road and $split-{\mu}$ road, were used to simulate real road conditions. At each simulated road, the vehicle was driven and stopped under the help of the developed ECU. In each simulation, the dynamical behavior of the vehicle was monitored. After enough tests in the laboratory using HILS, the parameter-tuned ECU was equipped in a real bus, which was driven and stopped in the real test field in Korea. And finally, the experiment results of ABS equipped vehicle's dynamic behavior both in HILS test and in test fields were compared.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.4
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• pp.246-255
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• 2010

There exist virtual machine scheduling delays in virtualized environment in which virtual machines share physical resources. Many resource management systems have been proposed to provide better application QoS through monitoring and analyzing application performance and resource utilization of virtual machines. However, those management systems don't consider virtual machine scheduling delays, result in incorrect application performance evaluation and QoS violations In this paper, we propose an application behavior analysis considering the scheduling delays, and a virtual machine priority allocation scheme based on the analysis to improve the application response time by minimizing the overall virtual machine scheduling delays.

• Korean Journal of Cognitive Science
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• v.23 no.3
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• pp.367-388
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• 2012

The centennial of Alan Mathison Turing(23 June 1912 - 7 June 1954) is an appropriate occasion on which to assess his profound influence on the development of cognitive science. His contributions to and attitudes toward that field are discussed from the metamathematical perspective. This essay addresses (i)Turing's mathematical analysis of cognition, (ii)universal Turing machines, (iii)the limitations of universal Turing machines, (iv)oracle Turing machine beyond universal Turing machine, and (v)Turing test for cognitive science. Turing was a ground-breaker, eager to move on to new fields. He actually opened wider the scientific windows to the mind. The results show that first, by means of mathematical logic Turing discovered a new bridge between the mind and the physical world. Second, Turing gave a new formal analysis of operations of the mind. Third, Turing investigated oracle Turing machines and connectionist network machines as new models of minds beyond the limitations of his own universal machines. This paper explores why the cognitive scientist would be ever expecting a new Turing Test on the shoulder of Alan Turing.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1107-1116
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• 2016

Recent astronomical survey observations have produced substantial amounts of data as well as completely changed conventional methods of analyzing astronomical data. Both classical statistical inference and modern machine learning methods have been used in every step of data analysis that range from data calibration to inferences of physical models. We are seeing the growing popularity of using machine learning methods in classical problems of astronomical data analysis due to low-cost data acquisition using cheap large-scale detectors and fast computer networks that enable us to share large volumes of data. It is common to consider the effects of inhomogeneous spatial and temporal coverage in the analysis of big astronomical data. The growing size of the data requires us to use parallel distributed computing environments as well as machine learning algorithms. Distributed data analysis systems have not been adopted widely for the general analysis of massive astronomical data. Gathering adequate training data is expensive in observation and learning data are generally collected from multiple data sources in astronomy; therefore, semi-supervised and ensemble machine learning methods will become important for the analysis of big astronomical data.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.111-117
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• 2020

Recently, with the high interest of machine learning, the need for educational controllers to interface with physical devices has increased. However, existing controllers are limited in terms of high cost and area of utilization for educational purposes. In this paper, motion control controllers using brain waves are proposed for the purpose of students' machine learning applications. The brain motion that occurs when imagining a specific action is measured and sampled, then the sample values were learned through Tensor Flow and the motion was recognized in contents such as games. Movement variation for motion recognition consists of directionality and jump motion. The identification of the recognition behavior is sent to a game produced by an Unreal Engine to operate the character in the game. In addition to brain waves, the implemented controller can be used in various fields depending on the input signal and can be used for educational purposes such as machine learning applications.

• The Journal of Korean Association of Computer Education
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• v.18 no.2
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• pp.83-90
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• 2015

In an virtualization environment, several virtual machines use physical resources together. If a specific virtual machine uses to much of the computing resources, other machines may not be working properly. There are various method to solve this problem. Most representative study is to migrate a specified virtual machines to a different server, a target server. In this study, server load can be transferred to a target server by the remigrate of the load imposed on virtual machine. It is still problematic that virtual machine has to remigrate to a different server. This thesis has proposed the algorithm determining the remigration targets by applying dynamic thresholds to solve those problems. The migration algorithm applies dynamic thresholds according to the following criteria. Firstly, the usage of CPU, network and memory; secondly, decide the set of artificial machine and the target server based on the resources surpassed thresholds; thirdly, determine artificial machines based on the resource usage in the target server.

• Physical Therapy Rehabilitation Science
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• v.11 no.3
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• pp.285-295
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• 2022

Objective: The purpose of this study is to use logistic regression and decision tree analysis to identify the factors that affect the success or failurein the national physical therapy examination; and to build and compare predictive models. Design: Secondary data analysis study Methods: We analyzed 76,727 subjects from the physical therapy national examination data provided by the Korea Health Personnel Licensing Examination Institute. The target variable was pass or fail, and the input variables were gender, age, graduation status, and examination area. Frequency analysis, chi-square test, binary logistic regression, and decision tree analysis were performed on the data. Results: In the logistic regression analysis, subjects in their 20s (Odds ratio, OR=1, reference), expected to graduate (OR=13.616, p<0.001) and from the examination area of Jeju-do (OR=3.135, p<0.001), had a high probability of passing. In the decision tree, the predictive factors for passing result had the greatest influence in the order of graduation status (x²=12366.843, p<0.001) and examination area (x²=312.446, p<0.001). Logistic regression analysis showed a specificity of 39.6% and sensitivity of 95.5%; while decision tree analysis showed a specificity of 45.8% and sensitivity of 94.7%. In classification accuracy, logistic regression and decision tree analysis showed 87.6% and 88.0% prediction, respectively. Conclusions: Both logistic regression and decision tree analysis were adequate to explain the predictive model. Additionally, whether actual test takers passed the national physical therapy examination could be determined, by applying the constructed prediction model and prediction rate.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.746-750
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• 2005

This paper describes image processing techniques that can detect, segment, and analyze the mango's physical properties such as size, shape, surface area, and color from images. First, images of mangoes taken by a digital camera are analyzed and segmented. The segmentation is done based on constructed hue model of the sample mangoes. Some morphological and filtering techniques are then applied to clean noises before fitting spline curve on the mango boundary. From the clean segmented image, the mango projected area can be computed. The shape of the mango is then analyzed using some structuring models. Color is also spatially analyzed and indexed in the database for future classification. To obtain the surface area, the mango is peeled. The scanned image of its peels is then segmented and filtered using similar approach. With calibration parameters, the surface area could then be computed. We employed the system to evaluate physical properties of a mango cultivar called "Nam Dokmai". There were sixty mango samples in three various sizes graded by an experienced farmer's eyes and hands. The results show the techniques could be a good alternative and more feasible method for grading mango comparing to human's manual grading.

• The Journal of Korean Physical Therapy
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• v.14 no.3
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• pp.136-144
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• 2002

The Purpose of this study was to compare the lumbar strength and lumbar flexor/extensor ratio between spondylolisthesis and herniated disc patients. The patients who had a subacute low back pain have been proved to each disease through MRI and we measured the maximal isometric strength of all patients(28) through MedX lumbar extension machine(Ocala, FL). In all patients, males had higher lumbar extensor strength than that of females. Especially, the spondylolisthesis patients had lower lumbar extensor strength than that of herniated disc patients. The statistical significant(p<.05, p<.01) differences were manifested in $48^{\circ},\;60^{\circ}\;and\;72^{\circ}$ between male groups. Also the statistical significant (p<.05) differences were manifested in $60^{\circ}\;and\;72^{\circ}$between female groups. In the lumbar flexor/ extensor ratio, the males of spondylolisthesis groups represented the functional weakness in the flexed portion of the range of motion, and the females of spondylolisthesis and the all patients of herniated disc represented the functional weakness in the extended portion of the range of motion. In conclusion, we may propose the program such that the spondylolisthesis males must increase the ratio of extended portion exercise, and the spondylolisthesis females and herniated disc patients must increase the ratio of flexed portion exercise.

• Journal of Technologic Dentistry
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• v.35 no.2
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• pp.97-103
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• 2013

Purpose: The purpose of this study was to investigate the effect of addition of fiber glass on the physical properties of silanized fiber mesh and non silanized mesh of denture base resins. Methods: The denture base resins were used in this study heat curing acrylic resins(Vertex Rs, Lucitone 199, $20{\times}80mm$) and fiber glass(SES, Green B&D co., Ltd, $20{\times}80mm$) were used as reinforcement. The specimens were stored in distilled water at $37{\pm}2^{\circ}C$ for 72 hours before test. Bending strength and tensile strength were measured by an universal testing machine(Instron 4301, Instron Corp.). Penetration distribution on fiber was observed by scanning electron microscopy(JSM 840A, Jeol Ltd). Results: The bending strength and modulus were increased by 30% after adding fiber glass on denture base resins. Tensile strength showed significant increasing by adding fiber glass on denture base resins. Conclusion: In this study, Addition of silanized fiber in denture base resins were improved physical properties. we confirmed the fiber glass possibility of the replacement about conventional materials.