• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.12 s.115
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• pp.1156-1163
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• 2006

This paper presents an ultra wideband(UWB) direct conversion mixer for IEEE 802.15.3a applications with simulation and measurement results. Since the direct conversion mixing causes dc-offset and even-order distortion, the proposed mixer adopts an anti-parallel diode pairs(APDPs) to solve these problems. The proposed mixer consists of an in-phase wilkinson power divider over $3.1{\sim}4.8GHz$, a wideband $45^{\circ}$ power divider over $1.5{\sim}2.4GHz$, and miniatured band pass filters(BPFs) for RF-LO isolations. The conversion loss is optimized with impedance matchings between APDPs and wideband components. The measured mixer shows the conversion loss of 13.5 dB, input third-order intercept-point($IIP_3$) of 7 dBm, and 1-dB gam compression point($P_{1dB}$) of -4 dBm. Quadrature(I/Q) outputs have the magnitude difference of about 1 dB and phase difference of ${\pm}3^{\circ}$.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.457-466
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• 1997

We developed a new hearing aid telephone which helps the hearing impaired person to improve the listening ability of telephone speech. Recently, the hearing impaired person and the elderly who has hearing loss have been continuously increased and their desire for participating society as a producer has been increased also. So they strong1y want the hearing aid devices which make compensation fortheir handicap. The hearing aid telephone is one of the basic aid devices that helps the hearing impaired to communicate well with other poeple and to acquire easily useful information through the phone. We analyze the hearing ability of the hearing impaired, design the new model of the hearing aid telephone and test the telephone in three fields-electrical, word perception, user test. Our new tolephone has lour band pass filter channels and the center frequencies of these filters are 500, 1000, 2000, 3000Hz which are considered psychoacoustic factors and telephone line characteristics. The hearing impaired can adjust the total gain characteristics of receiving sound to his hearing ability by setting four volumes in the telelphone. This procedure is called fitting which is a very important factor for the hearing impaired to take meaning of speech. The total gain of this telephone is over 20dB from 250Hz to 3200Hz range. From the results of the tests we certify that our new model is better for the hearing impaired to understand the meaning or telephone speech than the old general models. The next step of developing the hearing aid telephone is to study about compressing sidetone and noise, dividing frequency bands, selecting hearing aid pattern and compensating psychoacoustic loudness. we expect that the advanced hearing aid telephone can be developed by the research about speech perception characteristics of the hearing impaired in engineering and clinical side.

• Korean Journal of Optics and Photonics
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• v.16 no.5
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• pp.469-475
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• 2005

An integrated photonic microwave bandpass filter has been proposed and demonstrated incorporating a coherently coupled microring resonator in low-loss polymers. The proposed device may feature compact site, simple structure, tuning via the thermooptic and electrooptic effect, and flexible integration with other electrical and optical devices. The resonator was designed to have an extremely small bandwidth so that it could be used to selectively pass the optical signal carrying the microwave signal to attain efficient bandpass filtering. We made and tested two resonators with a single ring and double rings, and performed a theoretical fitting of their measured transfer curves to predict the performance of the microwave filters based on them precisely. It was found that as the number of the rings used for the resonator increases, the bandwidth gets smaller, the rolloff sharper, and the band rejection higher. Finally our filter exhibited the center frequency of 10GHz, the 3-dB bandwidth of 1.0GHz, the corresponding quality (Q) factor of 10, and the rejection outside of the passband of more than 25dB.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.