• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1479-1495
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• 2012

Spectrum scarcity seems to be the most challenging issue to be solved in new wireless telecommunication services. It is shown that spectrum unavailability is mainly due to spectrum inefficient utilization and inappropriate physical layer execution rather than spectrum shortage. Daily increasing demand for new wireless services with higher data rate and QoS level makes the upgrade of the physical layer modulation techniques inevitable. Orthogonal Frequency Division Multiple Access (OFDMA) which utilizes multicarrier modulation to provide higher data rates with the capability of flexible resource allocation, although has widely been used in current wireless systems and standards, seems not to be the best candidate for cognitive radio systems. Filter Bank based Multi-Carrier (FBMC) is an evolutionary scheme with some advantages over the widely-used OFDM multicarrier technique. In this paper, we focus on the total throughput improvement of a cognitive radio network using FBMC modulation. Along with this modulation scheme, we propose a novel uplink radio resource allocation algorithm in which fairness issue is also considered. Moreover, the average throughput of the proposed FBMC based cognitive radio is compared to a conventional OFDM system in order to illustrate the efficiency of using FBMC in future cognitive radio systems. Simulation results show that in comparison with the state of the art two algorithms (namely, Shaat and Wang) our proposed algorithm achieves higher throughputs and a better fairness for cognitive radio applications.

• Journal of The Korean Astronomical Society
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• v.37 no.4
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• pp.143-149
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• 2004

We present photometric results for four new variable stars discovered in the vicinity of the ZZ Ceti-type pulsating white dwarf BR Cam. Observations were performed on 5 nights in November 2003 using the 1.8m telescope at Bohyunsan Optical Astronomy Observatory with no filter, on 3 nights in December 2003 using the 0.61m telescope at Sobaeksan Optical Astronomy Observatory with V, I filters, and on 3 nights in October 2004 using the 1.0m telescope at Mt. Lemmon Optical Astronomy Observatory with V, I filters. We estimated their periods from the phase-match technique for one eclipsing binary and the multiple frequency analysis for three pulsating stars. By considering the light curve shape, period and amplitude difference between two passbands, we classified the objects by their variability types as follows: V1 (USNO-A2.0 1425-05691757) is a W UMa-type eclipsing binary with an orbital period of $0^d.4641$; V2 (USNO-A2.0 1425-05703335) is a multi-periodic $\delta$ Set-type pulsating star with a dominant period of $0^d.0649$; V3 (USNO-A2.0 1425-05699659) is also a $\delta$ Set-type pulsating star with a period of $0^d.1408$; and V 4 (USNO-A2.0 1425-05707705) is a RR Lyr-type pulsating star with a period of $0^d.2643$.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.53-60
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• 2009

The vision-based driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. The facial feature tracking is the primary technique issue in it. Current facial tracking technology faces three challenges: (1) detection failure of some or all of features due to a variety of lighting conditions and head motions; (2) multiple and non-rigid object tracking; and (3) features occlusion when the head is in oblique angles. In this paper, we propose a new active approach. First, the active IR sensor is used to robustly detect pupils under variable lighting conditions. The detected pupils are then used to predict the head motion. Furthermore, face movement is assumed to be locally smooth so that a facial feature can be tracked with a Kalman filter. The simultaneous use of the pupil constraint and the Kalman filtering greatly increases the prediction accuracy for each feature position. Feature detection is accomplished in the Gabor space with respect to the vicinity of predicted location. Local graphs consisting of identified features are extracted and used to capture the spatial relationship among detected features. Finally, a graph-based reliability propagation is proposed to tackle the occlusion problem and verify the tracking results. The experimental results show validity of our active approach to real-life facial tracking under variable lighting conditions, head orientations, and facial expressions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.603-607
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• 2004

The vision-based driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. The facial feature tracking is the primary technique issue in it. Current facial tracking technology faces three challenges: (1) detection failure of some or all of features due to a variety of lighting conditions and head motions; (2) multiple and non-rigid object tracking and (3) features occlusion when the head is in oblique angles. In this paper, we propose a new active approach. First, the active IR sensor is used to robustly detect pupils under variable lighting conditions. The detected pupils are then used to predict the head motion. Furthermore, face movement is assumed to be locally smooth so that a facial feature can be tracked with a Kalman filter. The simultaneous use of the pupil constraint and the Kalman filtering greatly increases the prediction accuracy for each feature position. Feature detection is accomplished in the Gabor space with respect to the vicinity of predicted location. Local graphs consisting of identified features are extracted and used to capture the spatial relationship among detected features. Finally, a graph-based reliability propagation is proposed to tackle the occlusion problem and verify the tracking results. The experimental results show validity of our active approach to real-life facial tracking under variable lighting conditions, head orientations, and facial expressions.

• Smart Structures and Systems
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• v.32 no.5
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• pp.281-295
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• 2023

The purpose of this study is to demonstrate and verify the application of phase-control absolute-acceleration-feedback active tuned mass dampers (PCA-ATMD) to multiple-degree-of-freedom (MDOF) building structures. In addition, servo speed control technique has been developed as a replacement for force control in order to mitigate the negative effects caused by friction and inertia. The essence of the proposed PCA-ATMD is to achieve a 90° phase lag for a structure by implementing the desired control force so that the PCA-ATMD can receive the maximum power flow with which to effectively mitigate the structural vibration. An MDOF building structure with a PCA-ATMD and a real-time filter forming a complete system is modeled using a state-space representation and is presented in detail. The feedback measurement for the phase control algorithm of the MDOF structure is compact, with only the absolute acceleration of one structural floor and ATMD's velocity relative to the structure required. A discrete-time direct output-feedback optimization method is introduced to the PCA-ATMD to ensure that the control system is optimized and stable. Numerical simulation and shaking table experiments are conducted on a three-story steel shear building structure to verify the performance of the PCA-ATMD. The results indicate that the absolute acceleration of the structure is well suppressed whether considering peak or root-mean-square responses. The experiment also demonstrates that the control of the PCA-ATMD can be decentralized, so that it is convenient to apply and maintain to real high-rise building structures.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.47-59
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• 2000

The purpose of this study is to develop travel-time estimation model using neural networks and prediction model using neural networks and kalman-filtering technique. The data used in this study are travel speed collected from inductive loop vehicle detection systems(VDS) and travel time collected from the toll collection system (TCS) between Seoul and Osan toll Plaza on the Seoul-Pusan Expressway. Two models, one for travel-time estimation and the other for travel-time Prediction were developed. Application cases of each model were divided into two cases, so-called, a single-region and a multiple-region. because of the different characteristics of travel behavior shown on each region. For the evaluation of the travel time estimation and Prediction models, two Parameters. i.e. mode and mean were compared using five-minute interval data sets. The test results show that mode was superior to mean in representing the relationship between speed and travel time. It is, however shown that mean value gives better results in case of insufficient data. It should be noted that the estimation and the Prediction of travel times based on the VDS data have been improved by using neural networks, because the waiting time at exit toll gates can be included for the estimation of travel time based on the VDS data by considering differences between VDS and TCS travel time Patterns in the models. In conclusion, the results show that the developed models decrease estimation and prediction errors. As a result of comparing the developed model with the existing model using the observed data, the equality coefficients of the developed model was average 88% and the existing model was average 68%. Thus, the developed model was improved minimum 17% and maximum 23% rather then existing model .

• Journal of The Korean Astronomical Society
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• v.49 no.1
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• pp.25-35
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• 2016

Multiple color selection techniques are successful in identifying quasars from wide-field broadband imaging survey data. Among the quasars that have been discovered so far, however, there is a redshift gap at 5 ≲ z ≲ 5.7 due to the limitations of filter sets in previous studies. In this work, we present a new selection technique of high redshift quasars using a sequence of medium-band filters: nine filters with central wavelengths from 625 to 1025 nm and bandwidths of 50 nm. Photometry with these medium-bands traces the spectral energy distribution (SED) of a source, similar to spectroscopy with resolution R ~ 15. By conducting medium-band observations of high redshift quasars at 4.7 ≤ z ≤ 6.0 and brown dwarfs (the main contaminants in high redshift quasar selection) using the SED camera for QUasars in EArly uNiverse (SQUEAN) on the 2.1-m telescope at the McDonald Observatory, we show that these medium-band filters are superior to multi-color broad-band color section in separating high redshift quasars from brown dwarfs. In addition, we show that redshifts of high redshift quasars can be determined to an accuracy of Δz/(1 + z) = 0.002 - 0.026. The selection technique can be extended to z ~ 7, suggesting that the medium-band observation can be powerful in identifying quasars even at the re-ionization epoch.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.595-602
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• 2013

WiFi fingerprinting is well known as an effective localization technique used for indoor environments. However, this technique requires a large amount of pre-built fingerprint maps over the entire space. Moreover, due to environmental changes, these maps have to be newly built or updated periodically by experts. As a way to avoid this problem, crowd-sourced fingerprint mapping attracts many interests from researchers. This approach supports many volunteer users to share their WiFi fingerprints collected at a specific environment. Therefore, crowd-sourced fingerprinting can automatically update fingerprint maps up-to-date. In most previous systems, however, individual users were asked to enter their positions manually to build their local fingerprint maps. Moreover, the systems do not have any principled mechanism to keep fingerprint maps clean by detecting and filtering out erroneous fingerprints collected from multiple users. In this paper, we present the design of a crowd-sourced fingerprint mapping and localization(CMAL) system. The proposed system can not only automatically build and/or update WiFi fingerprint maps from fingerprint collections provided by multiple smartphone users, but also simultaneously track their positions using the up-to-date maps. The CMAL system consists of multiple clients to work on individual smartphones to collect fingerprints and a central server to maintain a database of fingerprint maps. Each client contains a particle filter-based WiFi SLAM engine, tracking the smartphone user's position and building each local fingerprint map. The server of our system adopts a Gaussian interpolation-based error filtering algorithm to maintain the integrity of fingerprint maps. Through various experiments, we show the high performance of our system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.1
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• pp.1-10
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• 2001

In this paper, a multistage parallel interference canceller (MPIC) and a partial multistage parallel interference canceller (PMPIC) are employed as a technique for improving the performance of the asynchronous DS-CDMA systems. The degree of the effect of the timing errors and phase errors on the interference cancellation capability of two types of cancellers is theoretically analyzed and the computer simulation is performed to confirm the analytical results. From the results, the large performance improvement is obtained by employing MPIC and PMPIC with perfect synchronization over the conventional matched filter, and the performance improvement obtained by MPIC and PMPIC is very close to each other as the number of the stage of MPIC and PMPIC increases. When the timing errors and phase errors are considered (in the case of imperfect synchronization), the performance improvement reduces as the performance degradation at the first stage (no cancellation) has a bad effect on the decision statistics at each stage. However MPIC and PMPIC have the strong interference cancellation capability in spite of imperfect synchronization as the number of the stage increases. An interference canceller, which has the strong interference cancellation capability as well as lower complexity for the implementation, is needed for practical systems with timing errors and phase errors because the perfect synchronization is impossible. Therefore, the excellent tradeoff between complexity and performance offered by PMPIC makes it an attractive approach for practical systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.307-314
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• 2011

A new predistortion technique for dynamic spectrum allocation systems such as cognitive radio (CR) is proposed. The system model considered in this paper occupies a small band at a time, but the center frequency can be changed in the wide range of frequency. In this scenario. the front-end filter may not eliminate the harmonics of the power amplifier (PA) output. The proposed PD reduces the spectral regrowth of the fundamental signal at the carrier frequency (${\omega}_0$) and removes the harmonics ($2{\omega}_0$, $3{\omega}_0$, ...) at the same time. The proposed PD structure is composed of multiple predistorters (PDs) centered at integer multiples of ${\omega}_0$. The PD at ${\omega}_0$ is for removing spectral regrowth of the fundamental signal, and the others are for harmonic reduction. In the proposed PD structure, parameters of PDs are found jointly. Simulation results show that the spectral regrowth can be reduced by 20dB, and the 2nd and 3rd harmonics can be reduced down to -70dB from the power of the fundamental signal.