• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.156-162
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• 2007

The parallel beam SPECT system acquires projection data by using collimators in conjunction with photon detectors. The projection data of the parallel beam SPECT system is, however, blurred by the point response function of the collimator that is used to define the range of directions where photons can be detected. By increasing the number of parallel holes per unit area in collimator, one can reduce such blurring effect. This approach also, however, has the blurring problem if the distance between the object and the collimator becomes large. In this paper we consider correction methods for artifacts caused by non-circular orbit of parallel beam SPECT with many parallel holes per detector cell. To do so, we model the relationship between the object and its projection data as a linear system, and propose an iterative reconstruction method including artifacts correction. We compute the projector and the backprojector, which are required in iterative method, as a sum of convolutions with distance-dependent point response functions instead of matrix form, where those functions are analytically computed from a single function. By doing so, we dramatically reduce the computation time and memory required for the generation of the projector and the backprojector. We conducted several simulation studies to compare the performance of the proposed method with that of conventional Fourier method. The result shows that the proposed method outperforms Fourier methods objectively and subjectively.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.256-262
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• 2004

A key component of an autonomous mobile robot is to localize itself and build a map of the environment simultaneously. In this paper, we propose a vision-based localization and mapping algorithm of mobile robot using fisheye lens. To acquire high-level features with scale invariance, a camera with fisheye lens facing toward to ceiling is attached to the robot. These features are used in mP building and localization. As a preprocessing, input image from fisheye lens is calibrated to remove radial distortion and then labeling and convex hull techniques are used to segment ceiling and wall region for the calibrated image. At the initial map building process, features we calculated for each segmented region and stored in map database. Features are continuously calculated for sequential input images and matched to the map. n some features are not matched, those features are added to the map. This map matching and updating process is continued until map building process is finished, Localization is used in map building process and searching the location of the robot on the map. The calculated features at the position of the robot are matched to the existing map to estimate the real position of the robot, and map building database is updated at the same time. By the proposed method, the elapsed time for map building is within 2 minutes for 50㎡ region, the positioning accuracy is ±13cm and the error about the positioning angle of the robot is ±3 degree for localization.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.2
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• pp.67-74
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• 2008

This paper proposes two peak-windowing algorithms for peak-to-average power reduction(PAPR) of orthogonal frequency division multiple access(OFDMA) downlink systems. The Proposed algorithms mitigate the effect of excessive suppression due to successive peaks or relatively high peaks of the signal. First, multi-stage peak windowing algorithm is proposed, which exploits multiple threshold of target PAPR in order to step down the peaks gradually. Secondary, variable-length peak windowing algorithm is proposed, which adapts the window length with respect to the existence of successive peaks within a half of window length. Therefore, the proposed method reduces the distortion of signal amplitude caused by window overlapping. The proposed algorithms outperform the conventional peak windowing with the aid of window-length adaptation or sequential peak power reduction. Simulation results show the efficiency of the proposed algorithms over OFDMA downlink systems, especially WiBro systems.

• Annals of Clinical Neurophysiology
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• v.13 no.2
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• pp.80-86
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• 2011

Background: A dry-type electrode is an alternative to the conventional wet-type electrode, because it can be applied without any skin preparation, such as a conductive electrolyte. However, because a dry-type electrode without electrolyte has high electrode-to-skin impedance, an impedance-converting amplifier is typically used to minimize the distortion of the bioelectric signal. In this study, we developed an active dry electroencephalography (EEG) electrode using an impedance converter, and compared its performance with a conventional Ag/AgCl EEG electrode. Methods: We developed an active dry electrode with an impedance converter using a chopper-stabilized operational amplifier. Two electrodes, a conventional Ag/AgCl electrode and our active electrode, were used to acquire EEG signals simultaneously, and the performance was tested in terms of (1) the electrode impedance, (2) raw data quality, and (3) the robustness of any artifacts. Results: The contact impedance of the developed electrode was lower than that of the Ag/AgCl electrode ($0.3{\pm}0.1$ vs. $2.7{\pm}0.7\;k{\Omega}$, respectively). The EEG signal and power spectrum were similar for both electrodes. Additionally, our electrode had a lower 60-Hz component than the Ag/AgCl electrode (16.64 vs. 24.33 dB, respectively). The change in potential of the developed electrode with a physical stimulus was lower than for the Ag/AgCl electrode ($58.7{\pm}30.6$ vs. $81.0{\pm}19.1\;{\mu}V$, respectively), and the difference was close to statistical significance (P=0.07). Conclusions: Our electrode can be used to replace Ag/AgCl electrodes, when EEG recording is emergently required, such as in emergency rooms or in intensive care units.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.4 s.95
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• pp.380-388
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• 2005

This paper presents analysis results of the effects of RF filter characteristics on the system performance of impulse radio. The impulse radio system transmits modulated pulses having very short time duration and information can be extracted in receiver side based on cross-correlation between received and transmitted pulses. Accordingly, the pulse distortion due to in-band group delay variation can cause serious system performance degradation. In general, RF bandpass filters inevitably cause group delay difference to the signal passing through the filter which is proportional to its skirt characteristic due to its resonance phenomenon. For time as well as frequency domain analysis, small signal scattering parameter $S_{21}$ and its Fourier transform are used to characterize output pulse waveform under the condition that the input and output ports are matched. The output pulse waveform of the filter is predicted based on convolution integral between input pulse and filter transfer function, and resulting BER performances in the BPM and PPM based impulse radio system are calculated.

• Journal of the Korean Society of Radiology
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• v.16 no.3
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• pp.295-302
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• 2022

Sparse-view computed tomography (CT) imaging technique is able to reduce radiation dose, ensure the uniformity of image characteristics among projections and suppress noise. However, the reconstructed images obtained by the sparse-view CT imaging technique suffer from severe artifacts, resulting in the distortion of image quality and internal structures. In this study, we proposed a convolutional neural network (CNN) with wavelet transformation and residual learning for reducing artifacts in sparse-view CT image, and the performance of the trained model was quantitatively analyzed. The CNN consisted of wavelet transformation, convolutional and inverse wavelet transformation layers, and input and output images were configured as sparse-view CT images and residual images, respectively. For training the CNN, the loss function was calculated by using mean squared error (MSE), and the Adam function was used as an optimizer. Result images were obtained by subtracting the residual images, which were predicted by the trained model, from sparse-view CT images. The quantitative accuracy of the result images were measured in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The results showed that the trained model is able to improve the spatial resolution of the result images as well as reduce artifacts in sparse-view CT images effectively. Also, the trained model increased the PSNR and SSIM by 8.18% and 19.71% in comparison to the imaging model trained without wavelet transformation and residual learning, respectively. Therefore, the imaging model proposed in this study can restore the image quality of sparse-view CT image by reducing artifacts, improving spatial resolution and quantitative accuracy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.27-34
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• 2024

The direct and indirect damages caused by fires in underground utility tunnels have a great impact on society as a whole, so efforts are needed to prevent and manage them in advance. To this end, research is ongoing to prevent disasters such as fire flooding by applying digital twin technology to underground utility tunnels. A network is required to transmit the sensed signals from each sensor to the platform. In essence, it is necessary to analyze the application of wireless networks in the underground utility tunnel environments because the tunnel lacks the reception range of external wireless communication systems. Within the underground utility tunnels, electromagnetic interference caused by transmission and distribution cables, and diffuse reflection of signals from internal structures, obstacles, and metallic pipes such as water pipes can cause distortion or size reduction of wireless signals. To ensure real-time connectivity for remote surveillance and monitoring tasks through sensing, it is necessary to measure and analyze the wireless coverage in underground utility tunnels. Therefore, in order to build a wireless network environment in the underground utility tunnels. this study minimized the shaded area and measured the actual cavity environment so that there is no problem in connecting to the wireless environment inside the underground utility tunnels. We analyzed the data transmission rate, signal strength, and signal-to-noise ratio for each section of the terrain of the underground utility tunnels. The obtained results provide an appropriate wireless planning approach for installing wireless networks in underground utility tunnels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.5
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• pp.258-270
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• 2014

In this paper, we investigate channel capacity of two kinds of uplink OFDMA (Orthogonal Frequency Division Multiple Access) schemes, i.e. ZCZ (Zero Correlation Zone) code time-spread OFDMA and sparse SC-FDMA (Single Carrier Frequency Division Mmultiple Access) robust to access timing offset (TO) among multiple users. In order to reflect the practical condition, we consider not only access TO among multiple users but also peak to average power ratio (PAPR) which is one of hot issues of uplink OFDMA. In the case with access TO among multiple users, the amplified signal of users by power control might affect a severe interference to signals of other users. Meanwhile, amplified signal by considering distance between user and base station might be distorted due to the limit of amplifier and thus the performance might degrade. In order to achieve the maximum channel capacity, we investigate the combinations of transmit power so called ASF (adaptive scaling factor) by numerical simulations. We check that the channel capacity of the case with ASF increases compared to the case with considering only distance i.e. ASF=1. From the simulation results, In the case of high signal to noise ratio (SNR), ZCZ code time-spread OFDMA achieves higher channel capacity compared to sparse block SC-FDMA. On the other hand, in the case of low SNR, the sparse block SC-FDMA achieves better performance compared to ZCZ time-spread OFDMA.

• 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.

• Progress in Medical Physics
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• v.26 no.4
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• pp.280-285
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• 2015

In radiation therapy fields, a brachytherapy is a treatment that kills lesion of cells by inserting a radioisotope that keeps emitting radiation into the body. We currently verify the consistency of radiation treatment plan and dose distribution through film/screen system (F/S system), provide therapy after checking dose. When we check dose distribution, F/S systems have radiation signal distortion because there is low resolution by penumbra depending on the condition of film developed. In this study, We fabricated a $HgI_2$ Semiconductor radiation sensor for base study in order that we verify the real dose distribution weather it's same as plans or not in brachytherapy. Also, we attempt to evaluate the feasibility of QA system by utilizing and evaluating the sensor to brachytherapy source. As shown in the result of detected signal with various source-to-detector distance (SDD), we quantitatively verified the real range of treatment which is also equivalent to treatment plans because only the low signal estimated as scatters was measured beyond the range of treatment. And the result of experiment that we access reproducibility on the same condition of ${\gamma}$-ray, we have made sure that the CV (coefficient of variation) is within 1.5 percent so we consider that the $HgI_2$ sensor is available at QA of brachytherapy based on the result.