• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.35 no.11
• /
• pp.1036-1042
• /
• 2007

It is rather difficult to improve flight control computer(FLCC) hardware(H/W) development schedule due to lack of commercial off-the-self(COTS) tools or target specific tools. Thus, it is suggested to develop an enhanced process utilizing modeling, simulation and virtual reality tools. This paper presents H/W design process enhancement tool(PET) for FLCC design requirements such as FLCC input/output(I/O) signal flow, I/O fault detection, failure management algorithm, circuit logic, PCB assembly configuration and installation utilizing simulation and visualization in virtual space. New tool will provide simulation capability of various FLCC design configuration including shop replaceable unit(SRU) level assembly/dis-assembly utilizing open flight format 3-D modeling data.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.3
• /
• pp.179-190
• /
• 2020

In this paper, we estimated the Direction of Arrival (DOA) using Conventional BeamForming (CBF), adaptive beamforming and compressive beamforming. Minimum Variance Distortionless Response (MVDR) and Multiple Signal Classification (MUSIC) are used as the adaptive beamforming, and grid-free compressive sensing is applied for the compressive sensing beamforming. Theoretical background and limitations of each technique are introduced, and the performance of each technique is compared through simulation and real experiments. The real experiments are conducted in the presence of reflected signal, transmitting a sound using two speakers and receiving acoustic data through a linear array consisting of eight microphones. Simulation and experimental results show that the adaptive beamforming and the grid-free compressive beamforming have a higher resolution than conventional beamforming when there are uncorrelated signals. On the other hand, the performance of the adaptive beamforming is degraded by the reflected signals whereas the grid-free compressive beamforming still improves the conventional beamforming resolution regardless of reflected signal presence.

• Journal of radiological science and technology
• /
• v.39 no.2
• /
• pp.227-236
• /
• 2016

Dynamic positron emission tomography(dPET) is widely used medical imaging modality that can provide both physiological and functional neuro-image for diagnosing various brain disease. However, dPET images have low spatial-resolution and high noise level during spatio-temporal analysis (three-dimensional spatial information + one-dimensional time information), there by limiting clinical utilization. In order to overcome these issues for the spatio-temporal analysis, a novel computational technique was introduced in this paper. The computational technique based on singular value decomposition classifies multiple independent components. Signal components can be distinguished from the classified independent components. The results show that signal to noise ratio was improved up to 30% compared with the original images. We believe that the proposed computational technique in dPET can be useful tool for various clinical / research applications.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.5
• /
• pp.1063-1070
• /
• 2015

In this paper, we propose a distributed user scheduling with transmit power control based on the amount of generating interference to other base stations (BSs) in multi-cell multi-input multi-output (MIMO) networks. Assuming that the time-division duplexing (TDD) system is used, the interference channel from users to other cell BSs is obtained at each user. In the proposed scheduling, each user first generates a transmit beamforming vector by using singular value decompositon (SVD) over MIMO channels and reduces the transmit power if its generating interference to other BSs is larger than a predetermined threshold. Each BS selects the user with the largest effective channel gains among users, which reflects the adjusted power of users. Simulation results show that the proposed technique significantly outperforms the existing user scheduling algorithms.

• Journal of the Institute of Convergence Signal Processing
• /
• v.4 no.1
• /
• pp.1-8
• /
• 2003

Various methods have been studying to maintain and apply the multimedia inform abruptly increasing over all social fields, in recent years. For retrieval of still images, we is implemented content-based image retrieval system in this paper that make possible to retrieve similar objects from image database after segmenting query object from background if user request query. Query image is processed median filtering to remove noise first and then object edge is detected it by canny edge detection. And query object is segmented from background by using convex hull. Similarity value can be obtained by means of histogram intersection with database image after securing color histogram from segmented image. Also segmented image is processed gray convert and wavelet transform to extract spacial gray distribution and texture feature. After that, Similarity value can be obtained by means of banded autocorrelogram and energy. Final similar image can be retrieved by adding upper similarity values that it make possible to not only robust in background but also better correct object retrieval by using object segmentation method.

• The Journal of the Acoustical Society of Korea
• /
• v.41 no.5
• /
• pp.518-524
• /
• 2022

In this paper, we propose a method for combining convolutional neural networks and attention mechanism to improve the recognition performance of emotional stress from Electroencephalogram (EGG) signals. In the proposed method, EEG signals are decomposed into five frequency domains, and spatial information of EEG features is obtained by applying a convolutional neural network layer to each frequency domain. As a next step, salient frequency information is learned in each frequency band using a gate transformer-based attention mechanism, and complementary frequency information is further learned through inter-frequency mapping to reflect it in the final attention representation. Through an EEG stress recognition experiment involving a DEAP dataset and six subjects, we show that the proposed method is effective in improving EEG-based stress recognition performance compared to the existing methods.

• Journal of the Korean Society of Radiology
• /
• v.13 no.6
• /
• pp.841-846
• /
• 2019

Effect of misalignment on the performance was evaluated for the development of time-of-flight(TOF)-PET detector. A pair of TOF-PET detector consists of Lutetium-yttrium oxyorthosilicate(LYSO) scintillation crystal with a volume of 3 mm × 3 mm × 20 mm and Geiger-mode avalanche photodiodes(GAPD) photo-sensor with a active area of 3.07 mm × 3.07 mm. Analog output signals from TOF-PET detector were sent to the pre-amplifier and then fed into the gain adjust circuit for achievement of gain homogeneity for each detector. The amplified signals were recorded and digitized by data acquisition system based on oscilloscope. The effect of the detector misalignment between LYSO and GAPD was examined for four different alignment offsets of 0.0 mm, 0.5 mm, 1.0 mm and 1.5 mm for a pair of TOF-PET detector. The photopeak position decreased from ~400 mV to ~250 mV with increasing detector misalignment. the energy resolution and time resolution were degraded from 11.6% to 16.2%, and from 477 ps to 632 ps, respectively. This study demonstrated that PET detector performance was degraded considerably depending on the detector misalignment, which would be a critical issue for the development of TOF-PET detector.

• The Journal of the Acoustical Society of Korea
• /
• v.32 no.6
• /
• pp.548-555
• /
• 2013

The localization of sources has a numerous number of applications. To estimate the position of sources, the relative delay between two or more received signals for the direct signal must be determined. Although the generalized cross-correlation method is the most popular technique, an approach based on eigenvalue decomposition (EVD) is also popular one, which utilizes an eigenvector of the minimum eigenvalue. The performance of the eigenvalue decomposition (EVD) based method degrades in the low SNR and the correlated environments, because it is difficult to select a single eigenvector for the minimum eigenvalue. In this paper, we propose a new adaptive algorithm based on Canonical Correlation Analysis (CCA) in order to extend the operation range to the lower SNR and the correlation environments. The proposed algorithm uses the eigenvector corresponding to the maximum eigenvalue in the generalized eigenvalue decomposition (GEVD). The estimated eigenvector contains all the information that we need for time delay estimation. We have performed simulations with uncorrelated and correlated noise for several SNRs, showing that the CCA based algorithm can estimate the time delays more accurately than the adaptive EVD algorithm.

• Spatial Information Research
• /
• v.21 no.6
• /
• pp.57-67
• /
• 2013

GPS based car navigation systems show significant problems in such environment as a tunnel, a road surrounded by high buildings. In this study, we thus propose a method to determine positions and attitudes using only in-vehicle sensory data without a GPS. To check the feasibility of this method, we constructed a system to acquire in-vehicle sensory data and reference data simultaneously. We acquired test data using this system, estimated the trajectory based on the proposed method and evaluated the accuracy of both the sensory data and the trajectory. The speed and angular velocities provided by the in-vehicle sensors include 1.1 km/h and 0.8 deg/s RMS errors, respectively. The estimated trajectory using these data shows 20.8 m RMS errors for a 15 minute drive. In future, if we further combine additional sensors such as a camera and a GPS, we can achieve a high accurate navigation system at a low cost without an expensive high-grade external IMU.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.9
• /
• pp.4133-4137
• /
• 2011

Reliable Multi-Reader RFID identification is one of issues in Multi-Reader RFID realization program in recent. And the Multi-Reader RFID reader has difficulty to obtain reliable data in data capture layer. The reason is that unreliable readings such as a false positive reading and a false negative reading and missed readings can happen by reader collision problems, noise, or the mobility of tagged objects. We introduce performance metrics to solve these reader problems. We propose three solutions the Minimum Overlapped Read Zone (MORZ) with Received Signal Strength Indicator (RSSI), the Spatial-Temporal Division Access (STDA) method, and double bigger size of tags attached on the object. To show the improvement of the proposed methods, we calculate tag's successful read rates in a smart office, which consists of Multi-Reader RFID systems.