• Journal of Biomedical Engineering Research
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• v.32 no.4
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• pp.312-318
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• 2011

The purpose of study was to evaluate effects for repetitive use of thumb according to two different input types (button and touch) of mobile phones. A total of eight young and healthy subjects (6 males and 2 females: $24.63{\pm}8.04$ years) volunteered, and force measurement on thumb using film type pressure sensor was carried out for an hour. Before the experiment De Quervain's syndrome test were performed to check the left and right muscles related with thumb motion and after measuring the pressing force fatigue feeling survey achieved. For a statistical analysis, 1-to-5 ranking scale was used to score the fatigue feeling. From the result of pressure measurement, forces acting on thumb in button type were 3.36 times (the right thumb) and 3.16 times (the left thumb) for the touch type. And the result of survey, fatigue by using the button type of mobile phone was largely triggered than by using touch type. The abductor pollicis brevis and the flexor pollicis brevis were found as common part of fatigue for repetitively using thumb during texting messages. In the further study, some quantitative fatigue comparisons for various input motions are required to analyze repetitive strain injury syndrome.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.2
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• pp.99-104
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• 2013

With diversity of mobile services (e.g., messenger, and social network service) on smartphone, the demand of text input using a soft keyboard is increasing. However, studies on subjective and physiological responses of users for various touch locations are lacking. The present study investigated the ergonomic effects according to touch locations of a soft keyboard on smartphone. The experiment of the present study measured perceived discomfort using Borg's CR-10 scale and electromyography (EMG) on forearm (abductor pollicis longus, and extensor digitorum communis) and thumb (abductor pollicis brevis, and first dorsal interossei) muscles. Perceived discomfort was significantly varied from 0.7 (extremely weak discomfort) to 2.5 (weak discomfort) depending on touch locations. %MVC according to touch locations was only significant at abductor pollicis brevis which varied from 10% to 23%. The experimental results of the present study can be utilized in the ergonomic design of a soft keyboard.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.323-330
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• 2008

In this paper, we propose a new fingerprint sensing method that can reduce orientation error. General fingerprint input methods need finger to be put on the surface of a sensor. It can cause of rotation problem and it affects the recognition result significantly. This improved input method can minimize the rotation of a finger by holding double-sided sensor with both thumb and index finger at the same time. Whenever fingerprint is impressed, it has nearly the same orientation because sensors are located between two fingers. As a result, we can get a better performance in fingerprint recognition system, but it may need more hardware cost.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1103-1108
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• 2016

The development of a variety of sensor technology, users smart phone, the use of motion recognition apparatus such as a console game machines is increasing. It tends to user needs motion recognition-based input device are increasing. Existing motion recognition mouse is equipped with a modified form of the mouse button on the outside and serves as a wheel mouse left and right buttons. Existing motion recognition mouse is to manufacture a small, there is a difficulty to operate the button. It is to apply the motion recognition technology the motion recognition technology is used only pointing the cursor there is a limit. In this paper, use of MEMS-based motion recognition sensor, the body of the two-point operation data by recognizing the operation of the (thumb and forefinger) and generating a control signal, followed by studies on the generated control signal to a wireless transmitting computer input device.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.791-793
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• 2016

In the development of various types of sensor technology, the general users smartphone, the environment is increased, which can be seen in contact with the movement recognition device, such as a console game machine (Nintendo Wii), an increase in the user needs of the action recognition-based input device there is a tendency to have. Mouse existing behavior recognition, attached to the outside, is mounted in the form of mouse button is deformed, the left mouse was the role of the right button and a wheel, an acceleration sensor (or a gyro sensor) inside to, plays the role of a mouse cursor, is to manufacture a compact, there is a difficulty in operating the button, to apply a motion recognition technology is used to operate recognition technology only pointing cursor is limited. Therefore, in this paper, using a MEMS-based motion-les Koguni tion sensor (Motion Recognition Sensor), to recognize the behavior of the two points of the human body (thumb and forefinger), to generate the motion data, and this to the foundation, compared to the pre-determined matching table (moving and mouse button events cursor), and generates a control signal by determining, were studied the generated control signal input device of the computer wirelessly transmitting.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.