• Proceedings of the KIEE Conference
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• 2002.11d
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• pp.70-72
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• 2002

LPM that is used for head driver is problem of miniaturization of construction and cost. This can be achieved by most suitable shape decision. and suitable selection of control system. Specially, in LPM that Full step is mm$\sim$um unit. the large change of thrust receives much effect by tooth number per pole. tooth width and slot width about change of the air gap length. Therefore, this paper presents LPM that use for suitable head driver to reduce of the structure and the cost. to generate maximum thrust of LPM, and finds the proportion of the tooth pitch to tooth width and the slot width about change of the air gap length through FEM analysis. Also, applying different tooth width and slot width that is given as analysis result. this paper presented model that thrust is improved.

• ETRI Journal
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• v.37 no.4
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• pp.793-803
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• 2015

We propose a novel HMI UI/UX for an in-vehicle infotainment system. Our proposed HMI UI comprises multimodal interfaces that allow a driver to safely and intuitively manipulate an infotainment system while driving. Our analysis of a touchscreen interface-based HMI UI/UX reveals that a driver's use of such an interface while driving can cause the driver to be seriously distracted. Our proposed HMI UI/UX is a novel manipulation mechanism for a vehicle infotainment service. It consists of several interfaces that incorporate a variety of modalities, such as speech recognition, a manipulating device, and hand gesture recognition. In addition, we provide an HMI UI framework designed to be manipulated using a simple method based on four directions and one selection motion. Extensive quantitative and qualitative in-vehicle experiments demonstrate that the proposed HMI UI/UX is an efficient mechanism through which to manipulate an infotainment system while driving.

• IE interfaces
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• v.21 no.1
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• pp.43-50
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• 2008

Understanding consumers' latent desires for product form has now become a critical issue in product design. Accordingly, product development processes is rapidly changing from product-oriented development to user-centered development. Driver visibility is considered as an important element of driving posture packaging in automobile interior design. This study presents a systematic process for driver visibility analysis approached from affective engineering method that provides design variable selection and screening with respect to the image/impression element of the human visibility. Also, the analysis of front visibility, often called the feeling of "openness", in motor vehicle interior design, is selected and practiced a case study using the systematic process proposed in this study. Twenty six participants evaluated the feeling of openness for thirty motor vehicles following the perceived scale of affective design factors. The results showed that variables such as the height of head lining, the height of cluster housing, the gradient of windshield and the volume of A-pillar were the critical design variables which affect the feeling of openness in a motor vehicle.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.256-261
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• 2007

Electroencephalographic(EEG) is used to record activities of human brain in the area of psychology for many years. As technology developed, neural basis of functional areas of emotion processing is revealed gradually. So we measure fundamental areas of human brain that controls emotion of human by using EEG. Hands gestures such as shaking and head gesture such as nodding are often used as human body languages for communication with each other, and their recognition is important that it is a useful communication medium between human and computers. Research methods about gesture recognition are used of computer vision. Many researchers study Emotion Recognition method which uses one of EEG signals and Gestures in the existing research. In this paper, we use together EEG signals and Gestures for Emotion Recognition of human. And we select the driver emotion as a specific target. The experimental result shows that using of both EEG signals and gestures gets high recognition rates better than using EEG signals or gestures. Both EEG signals and gestures use Interactive Feature Selection(IFS) for the feature selection whose method is based on the reinforcement learning.

• Journal of the Korean Applied Science and Technology
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• v.35 no.1
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• pp.273-283
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• 2018

The purpose of this study is to analyze the optimum driver selection according to shaft intensity, shaft length and shaft weight that are determining factors of driver shot. To achieve the above purpose, the subject were participate with handicap zero 10 male pro golfer and mean score 90(handicap about 18) amateur 10 male golfer. The used club limited number 1 driver, we tested 24 driver which is shaft intensity, length, weight, total weight and swing weight. Dependent variable was strike ball speed, flying distance and head speed. The findings can be summarized as follows. First, There is a significantly difference in CPM. Ball speed, head speed and flying distance according to driver shaft intensity were found to be the best when CPM is 230<. Second, There is a significantly difference in shaft length. Ball speed, and head speed according to driver shaft length were found to be the best at 46 inch and flying distance were found to be the best at 45 inch. Third, There is not significantly difference in SW. Ball speed and flying distance according to driver shaft weight were found to be the best with 65g. In the case of head speed, it was the fastest with 50g shaft. Four, total variables were significantly difference between in pro and amateur golfer. In conclusion, there would be differences in individual physical condition but the best result was found with a driver of CPM 230<, shaft length 46inch, and shaft weight 65g.

• Journal of the Korean Institute of Gas
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• v.17 no.3
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• pp.27-32
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• 2013

Natural gas liquefaction process which is operated under cryogenic condition spends large amount of energy. Most of energy in the natural gas liquefaction process is consumed by compressors. Therefore, minimizing energy consumption of compressors is an important issue in process design and operation. Among various natural gas liquefaction processes, propane pre-cooled mixed refrigerant (C3MR) process consists of mixed refrigerant system and pure refrigerant system. In this study, to find the optimal design of pure refrigerant system, pure refrigerant cycle is simulated on different number of pressure levels and the necessary energy of each design is compared. After that, the driver selection model is applied to analyse each processes, which has different number of equipments, in terms of cost. As the result, the design using many equipments spends lower energy. Using this result, this study suggests standard of process design selection by the cost term.

• Proceedings of the ESK Conference
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• 1996.10a
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• pp.185-190
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• 1996

Navigation system is regarded as the interface border line between the Intelligent Transportation Systems (ITS) and the driver as the prospective information provider of the ATIS (Advanced Traveler Information System). Following theory, if the navigation system appropriately designed and utilized, that can maximize the transport efficiency, contribute to improvements of the environments and road safety. To accomplish these dinds of objectives of the navigation system use, human factors plays an important roles specially focused on the driver's safety, performance and system usability. Because the effectiveness of the system depends on the acceptance of the system, and the extent to which the system conforms to driver physical and cognitive limitations and capabilities. Therefore, the ergonomic design vaniables must be seriously selected and reflected in early design step for more effective and appreciate product design. As the first step of this aim, this study selected and categorized the human factors design variables of the navigation system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.329-332
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• 2022

Since IoT devices include various sensors and drivers, application programmers need to understand the structure and characteristics of sensors and actuators. If the manufacturer provides the driver of the sensor or actuator, IoT development can be efficiently carried out, which is called the Plug & Play technique. What matters is that the technique proposed by this research team in the past are not suitable for Arduino or Raspberry-Pi, which are recently used. In this paper, we propose a USB sensor device that can be mounted on a Raspberry-Pi. When the device is plugged into the Raspberry-Pi, the built-in driver is transmitted and played. The configuration of the USB sensor device was presented, and considerations for chip selection for processing sensors and drivers were presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.25-35
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• 2011

Traffic volume increases due to diversification of industry. Also, Automobile ownerships also increase steadily. It is estimated that the registered number of vehicle is expected to be 20 milion in the year 2015. These trends may result in increasing the number of woman drivers and elderly drivers. Therefore, this study aims to identify routes that reflect characteristics of each driver's preferences. A survey was conducted on different routes attributes for variances drivers. Driver types were classified by gender, age, and driving career. Accordingly, a weight for road composition attribute such as number of lanes, number of accidents, slope was estimated by using Swing Weighting technique in Multi-Attribute Utility Theory. In addition, a case study was conducted and identified weights were applied to routes. In result, drivers commonly prefer short route when they considered their routes. Also, male drivers prefer speedy and shorter route than that of female drivers. Elderly drivers prefer safe routes that represent low accidents rate. Moreover driving career under a year drivers prefer safe and easy routes. Therefore, we may conclude that the necessity of diversified route information is essential in the future car navigation system.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.832-837
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• 2007

Electroencephalographic(EEG) is used to record activities of human brain in the area of psychology for many years. As technology develope, neural basis of functional areas of emotion processing is revealed gradually. So we measure fundamental areas of human brain that controls emotion of human by using EEG. Hands gestures such as shaking and head gesture such as nodding are often used as human body languages for communication with each other, and their recognition is important that it is a useful communication medium between human and computers. Research methods about gesture recognition are used of computer vision. Many researchers study Emotion Recognition method which uses one of EEG signals and Gestures in the existing research. In this paper, we use together EEG signals and Gestures for Emotion Recognition of human. And we select the driver emotion as a specific target. The experimental result shows that using of both EEG signals and gestures gets high recognition rates better than using EEG signals or gestures. Both EEG signals and gestures use Interactive Feature Selection(IFS) for the feature selection whose method is based on a reinforcement learning.