• Journal of Radiation Protection and Research
• /
• v.38 no.1
• /
• pp.29-36
• /
• 2013

The aim of this study was to determine the correlation between exposure index (EI) and dose factors related to radiation dose optimization in digital radiography (DR) system. Two phantoms with built-in regional test object for quantitative assessment of images were used to produce image signals that acquired in chest radiography background. EI and entrane surface dose (ESD) increased proportionally with rise of radiation dose (kVp, mAs) in both DR and CR systems. Especially, DR detector was effective to form good contrast and hence, reached easily to improvement of image quality with minimal dose changes. It made operators possible to expect the accuracy of EI values deeply related to absorbed dose of the detector. The evaluation of images was obtained specially employed calculation of noise to signal ratio (NSR) and contrast to noise ratio (CNR). These measurements were performed for how exposure factors affect image quality. NSR was inversely proportional to kVp and mAs and low NSR represented high signal detection efficiency. Consequently, EI values was the measure of the amount of exposure received by the image receptor and it was proportional to exposure factors. Therefore the EI in a recommended range from manufacturer can offer optimal image quality. Also, continuous monitoring of EI values in the digital radiography can reduce the unnecessary patient dose and help the quality control of the system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.11
• /
• pp.1627-1634
• /
• 2021

This paper introduces a low-power compact ADC circuit for analog Convolutional filter for low-power neural network accelerator SOC. While convolutional neural network accelerators can speed up the learning and inference process, they have drawback of consuming excessive power and occupying large chip area due to large number of multiply-and-accumulate operators when implemented in complex digital circuits. To overcome these drawbacks, we implemented an analog convolutional filter that consists of an analog multiply-and-accumulate arithmetic circuit along with an ADC. This paper is focused on the design optimization of a low-power 8bit SAR ADC for the analog convolutional filter accelerator We demonstrate how to minimize the capacitor-array DAC, an important component of SAR ADC, which is three times smaller than the conventional circuit. The proposed ADC has been fabricated in CMOS 65nm process. It achieves an overall size of 1355.7㎛², power consumption of 2.6㎼ at a frequency of 100MHz, SNDR of 44.19 dB, and ENOB of 7.04bit.

• Journal of the Korean Society of Radiology
• /
• v.17 no.2
• /
• pp.191-199
• /
• 2023

This study aimed to propose minimized radiation doses with an optimized abdomen x-ray image, which realizes a Deep Blind Image Super-Resolution Generative adversarial network (BSRGAN) technique. Entrance surface doses (ESD) measured were collected by changing exposure conditions. In the identical exposures, abdominal images were acquired and were processed with the BSRGAN. The images reconstructed by the BSRGAN were compared to a reference image with 80 kVp and 320 mA, which was evaluated by mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM). In addition, signal profile analysis was employed to validate the effect of the images reconstructed by the BSRGAN. The exposure conditions with the lowest MSE (about 0.285) were shown in 90 kVp, 125 mA and 100 kVp, 100 mA, which decreased the ESD in about 52 to 53% reduction), exhibiting PSNR = 37.694 and SSIM = 0.999. The signal intensity variations in the optimized conditions rather decreased than that of the reference image. This means that the optimized exposure conditions would obtain reasonable image quality with a substantial decrease of the radiation dose, indicating it could sufficiently reflect the concept of As Low As Reasonably Achievable (ALARA) as the principle of radiation protection.

• Journal of Digital Contents Society
• /
• v.18 no.6
• /
• pp.1165-1173
• /
• 2017

Deep learning method, which is one of the most famous machine learning algorithms, has proven its applicability in various applications and is widely used in digital signal processing. However, it is difficult to apply deep learning technology to IoT devices with limited CPU performance and memory capacity, because a large number of training samples requires a lot of memory and computation time. In particular, if the Arduino with a very small memory capacity of 2K to 8K, is used, there are many limitations in implementing the algorithm. In this paper, we propose a method to optimize the ELM algorithm, which is proved to be accurate and efficient in various fields, on Arduino board. Experiments have shown that multi-class learning is possible up to 15-dimensional data on Arduino UNO with memory capacity of 2KB and possible up to 42-dimensional data on Arduino MEGA with memory capacity of 8KB. To evaluate the experiment, we proved the effectiveness of the proposed algorithm using the data sets generated using gaussian mixture modeling and the public UCI data sets.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.48 no.3
• /
• pp.28-35
• /
• 2011

Cooperative ARQ scheme is effective for better QoS guarantee for the next generation mobile communication systems where multimedia data transmission highly increases. In this paper, we propose a cooperative ARQ strategy in ad hoc cognitive relays for mobile multimedia communication for supporting instantaneous cooperation in MANET environment. In the proposed strategy, to support real time, delay-sensitive services, whenever a frame is transmitted from the source, each relay actively senses the SINR of the signal transmitted from the source, and determine whether to propose retransmission or not before the destination transmits feedback signal. To minimize the false retransmission decision or needless retransmission, we propose an adaptive sensing threshold optimization algorithm to maintain suboptimal sensing thresholds for each relay. By computer simulation, it is shown that the proposed cooperative ARQ retransmission scheme outperforms the conventional schemes with respect to frame transmission delay and frame loss probability in real time multimedia data transmission system.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.39 no.7
• /
• pp.37-45
• /
• 2002

In this paper, the microwave characteristics of traveling-wave electroabsorption coplanar waveguide modulator have been analyzed and optimized precisely by using the 3-dimensional finite-difference time-domain method (FDTD). Microwave characteristics are affected by the thickness of intrinsic layer, the width of meas, and the distance between signal electrode and ground electrode on traveling-wave type structure. In case that intrinsic layers are composed of InAsP/InGaP (1.3Q), the optimized distance between signal electrode and ground electrode, the optimized intrinsic region thickness and the width of waveguide are founded to be $3{\mu}m,\;039{\mu}m\;and\;2{\mu}m$, respectively, to minimize microwave loss and to obtain velocity and impedance matched structure. By using the FDTD, we could design the traveling-wave electroabsorption modulator more precisely.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.10
• /
• pp.4814-4834
• /
• 2018

This paper presents an architecture for wireless sensor networks (WSNs) with blind source separation (BSS) applied to retrieve the received mixing signals of the sink nodes first. The little-to-no need of prior knowledge about the source signals of the sink nodes in the BSS method is obviously advantageous for WSNs. The optimization problem of the BSS of multiple independent source signals with complex and noncircular distributions from observed sensor nodes is considered and addressed. This paper applies Castella's reference-based scheme to Novey's negentropy-based algorithms, and then proposes a novel fast fixed-point (FastICA) algorithm, defined as the reference-signal negentropy complex FastICA (RSNT-cFastICA) for complex-valued noncircular-distribution source signals. The proposed method for the sink nodes is substantially more efficient than Novey's quasi-Newton algorithm in terms of computational speed under large numbers of samples, can effectively improve the power consumption effeciency of the sink nodes, and is significantly beneficial for WSNs and wireless communication networks (WCNs). The effectiveness and performance of the proposed method are validated and compared with three related BSS algorithms through theoretical analysis and simulations.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.12 no.2
• /
• pp.1-11
• /
• 2013

This research proposed integrated expressway traffic management strategy using ramp metering and toll mainline metering. This research suggested a traffic signal optimization model for integrated operation of ramp and mainline metering based on Demand-Capacity Model that is used to optimize allowable input volume for ramp metering in FREQ model. The objective function of this model is sectional throughput volume maximization, and this model can calculate optimal signal timings for mainline metering and ramp metering. This study conducted an effectiveness analysis of integrated metering strategy using PARAMICS and its API. It targeted Seoul's Outer Ring Expressway between Gimpo and Siheung toll gate. As a simulation result, integrated operation of mainline and ramp metering provided more smooth traffic flow, and throughput volume of mainline increased to 14% in congested section. In addition, a queue of 400 meter was formed at metering point of toll gate. This research checked that integrated traffic management strategy facilitates more efficient traffic operation of mainline and ramp from diffused traffic congestion.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.10
• /
• pp.2367-2372
• /
• 2015

One of various low-density parity-check(LDPC) codes that has been adopted in many communication standards due to its error correction ability is a quasi-cyclic LDPC(QC-LDPC) code, which leads to comparable decoder complexity. One of the main blocks in the QC-LCDC code decoder is a multi-size circular shifter(MSCS) that can perform various size rotation. The MSCS can be implemented with many structures, one of which is based on Banes network. The Benes network structure can perform the normal MSCS operation efficiently, but it cannot use the properties coming from specifications like rotation sizes. This paper proposesd a scheme where the Benes network structure can use the rotation size property with the modification of the control signal generation. The proposed scheme is applied to the MSCS of IEEE 802.16e WiMAX QC-LDPC decoder to reduce the number of MUXes and the critical path delay.

• Journal of the Institute of Convergence Signal Processing
• /
• v.13 no.1
• /
• pp.12-18
• /
• 2012

Stereo correspondence is the central problem of stereo vision. In this paper, we propose a stereo matching scheme based on a genetic algorithm using a multi-resolution method and AD-Census. The proposed approach considers the matching environment as an optimization problem and finds the disparity by using a genetic algorithm And adaptive chronosome structure using edge pixels and crossover mechanism are employed in this technique. A cost function is composes of certain constraints whice are commonly used in stereo matching. AD-Census measure is applied to reduce disparity error. To increase the efficiency of process, we apply image pyramid method to stereo matching and calculate the initial disparity map at the coarsest resolution. Then initial disparity map is propagated to the next finer resolution, interpolated and performed disparity refinement using local feature vector. We valid our method not only reduces the search time for correspondence compared with conventional GA-based method but also ensures the validity of matching.