• ETRI Journal
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• v.45 no.2
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• pp.254-266
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• 2023

This paper investigates the effect of hardware impairments (HIs) and imperfect channel state information (ICSI) on a SWIPT-assisted adaptive nonorthogonal multiple access (NOMA)/orthogonal multiple access (OMA) system over independent and nonidentical Rayleigh fading channels. In the NOMA mode, the energy-constrained near users act as a relay to improve the performance for the far users. The OMA transmission mode is adopted to avoid a complete outage when NOMA is infeasible. The best user selection scheme is considered to maximize the energy harvested and avoid error propagation. To characterize the performance of the proposed systems, closed-form and asymptotic expressions of the outage probability for both near and far users are studied. Moreover, exact and approximate expressions of the ergodic rate for near and far users are investigated. Simulation results are provided to verify our theoretical analysis and confirm the superiority of the proposed NOMA/OMA scheme in comparison with the conventional NOMA and OMA protocol with/without HIs and ICSI.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.221-228
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• 2024

As the importance of cardiovascular health is highlighted, research on its correlation with blood pressure, the most important indicator, is being actively conducted. Therefore, extensive clinical data is essential, but the measurement of the central arterial blood pressure waveform must be performed invasively within the artery, so the quantity and quality are limited. This study suggested a mock circulatory robot and artificial aorta to reproduce the blood pressure waveform generated by the overlap of forward and reflected waves. The artificial aorta was fabricated with biomimetic silicone to mimic the physiological structure and vascular stiffness of the human. A pressurizing chamber was implemented to prevent distortion of the blood pressure waveform due to the strain-softening of biomimetic silicone. The reproduced central arterial blood pressure waveforms have similar magnitude, shape, and propagation characteristics to humans. In addition, changes in blood pressure waveform due to aging were also reproduced by replacing an artificial aorta with various stiffness. It can be expanded to construct a biosignal database and health sensor testing platform, a core technology for cardiovascular health-related research.

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3275-3285
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• 2021

A Nuclear Power Plant (NPP) is a complex dynamic system-of-systems with highly nonlinear behaviors. In order to control the plant operation under both normal and abnormal conditions, the different systems in NPPs (e.g., the reactor core components, primary and secondary coolant systems) are usually monitored continuously, resulting in very large amounts of data. This situation makes it possible to integrate relevant qualitative and quantitative knowledge with artificial intelligence techniques to provide faster and more accurate behavior predictions, leading to more rapid decisions, based on actual NPP operation data. Data-driven models (DDM) rely on artificial intelligence to learn autonomously based on patterns in data, and they represent alternatives to physics-based models that typically require significant computational resources and might not fully represent the actual operation conditions of an NPP. In this study, a feed-forward backpropagation artificial neural network (ANN) model was trained to simulate the interaction between the reactor core and the primary and secondary coolant systems in a pressurized water reactor. The transients used for model training included perturbations in reactivity, steam valve coefficient, reactor core inlet temperature, and steam generator inlet temperature. Uncertainties of the plant physical parameters and operating conditions were also incorporated in these transients. Eight training functions were adopted during the training stage to develop the most efficient network. The developed ANN model predictions were subsequently tested successfully considering different new transients. Overall, through prompt prediction of NPP behavior under different transients, the study aims at demonstrating the potential of artificial intelligence to empower rapid emergency response planning and risk mitigation strategies.

• Tunnel and Underground Space
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• v.11 no.3
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• pp.217-224
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• 2001

Rock masses are usually discontinuous in nature due to various geological processes and contain rock joints and bridges. Crack propagation and coalescence processes in rock bridge mainly cause rock failures in slopes, foundations, and tunnels. In this study, we focused on the crack initiation, propagation and coalescence process of rock materials containing two pre-existing open cracks arranged in different geometries. Specimens of 120${\times}$60${\times}$25 mm in size, which were made of Yeoman Marble, were prepared. In the specimens, two artificial cracks were cut with pre-existing crack angle ${\alpha}$, bridge angle ${\beta}$, pre-existing crack length 2c and bridge length 2b. Wing crack initiation stress, wing crack propagation angle, and crack coalescence stress were measured and crack initiation, propagation and coalescence processes were observed during uniaxial compression. Crack coalescence types were classified and analytical study using Ashby and Hallam model (1986) was performed to be compared with the experimental results.

• Journal of Plant Biotechnology
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• v.7 no.3
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• pp.175-181
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• 2005

This work described some essential factors necessary for micro-propagation of banana for mass production of synthetic seeds for germ plasm conservation, and how peroxides activity of conserved tissue was influenced. Shoot tips of field grown plants were used to obtain shoot clusters on shoot proliferation medium (MS medium supplemented with 5 mg/l BAP). Using longitudinally-split shoot tip technique, 18720, 8640, 7488, 2016 plantlets were obtained from one shoot tip of Maghraby, Grand Naine, Balady, and Williams, respectively, in six subculture, one month each, on solid medium. Shoot tips excised from in vitro grown plantlets were encapsulated in calcium-alginate beads and stored at $4^{\circ}C$ for one month on half-strength MS basal medium without growth regulators or sugars. After one month all the viable-conserved synseeds formed shoots when they were transferred to MS basal medium, some of them showed synchronous formation of shoot and root systems in one week. Plants retrieved from encapsulated shoot tips were hardened off and transferred to soil.

• Journal of the Korean Ceramic Society
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• v.54 no.6
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• pp.492-498
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• 2017

A thermal barrier coating (TBC) with self-healing property for cracks was proposed to improve reliability during gas turbine operation, including structural design. Effect of healing agent on crack propagation behavior in TBCs with and without buffer layer was investigated through furnace cyclic test (FCT). Molybdenum disilicide ($MoSi_2$) was used as the healing agent; it was encapsulated using a mixture of tetraethyl orthosilicate and sodium methoxide. Buffer layers with composition ratios of 90 : 10 and 80 : 20 wt%, using yttria stabilized zirconia and $MoSi_2$, respectively, were prepared by air plasma spray process. After generating artificial cracks in TBC samples by using Vickers indentation, FCTs were conducted at $1100^{\circ}C$ for a dwell time of 40 min., followed by natural air cooling for 20 min. at room temperature. The cracks were healed in the buffer layer with the healing agent of $MoSi_2$, and it was found that the thermal reliability of TBC can be enhanced by introducing the buffer layer with healing agent in the top coat.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.2011-2015
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• 2009

In an insulating dielectric liquid such as transformer oil, space charge injection and propagation were analyzed under the Fowler-Nordheim and Richardson-Dushman's thermal emission charge injection conditions for blade-plane electrodes stressed by a step voltage. The governing equations were composed of all five equations such as the Poisson's equation for electric fields, three continuity equations for electrons, negative, and positive ions, and energy balanced equation for temperature distributions. The governing equations for each carrier, the continuity equations, belong to the hyperbolic-type PDE of which the solution has a step change at the space charge front resulting in numerical instabilities. To decrease these instabilities, the governing equations were solved simultaneously by the Finite Element Method (FEM) employing the artificial diffusion scheme as a stabilization technique. Additionally, the terminal current was calculated by using the generalized energy method which is based on the Poynting's theorem, and represents more reliable and stable approach for evaluating discharge current. To verify the proposed method, the discharge phenomena were successfully applied to the blade~plane electrodes, where the radius of blade cap was $50{\mu}m$.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1414-1424
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• 2021

In this paper, the importance of input factors of a DNN (Deep Neural Network) PM_2.5 forecasting model using LRP(Layer-wise Relevance Propagation) is analyzed, and forecasting performance is improved. Input factor importance analysis is performed by dividing the learning data into time and PM_2.5 concentration. As a result, in the low concentration patterns, the importance of weather factors such as temperature, atmospheric pressure, and solar radiation is high, and in the high concentration patterns, the importance of air quality factors such as PM_2.5, CO, and NO₂ is high. As a result of analysis by time, the importance of the measurement factors is high in the case of the forecast for the day, and the importance of the forecast factors increases in the forecast for tomorrow and the day after tomorrow. In addition, date, temperature, humidity, and atmospheric pressure all show high importance regardless of time and concentration. Based on the importance of these factors, the LRP_DNN prediction model is developed. As a result, the ACC(accuracy) and POD(probability of detection) are improved by up to 5%, and the FAR(false alarm rate) is improved by up to 9% compared to the previous DNN model.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.697-700
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• 2003

The SASW method is a promising and effective way of profiling ground stiffness nondestructively. This method has been successfully applied to many geotechnical sites, but significant lateral variability, embedded obstacles, and pavement lead to the low reliability. To improve these problems, the horizontal wave component has been introduced to improve the reliability of the stiffness profile determined by the SASW method. To understand dispersion character of the horizontal component wave propagation in artificial profiles, FEM analysis had been performed. Used models are homogeneous half-space and two layered half- spaced layers.

• Journal of the Korean Society of Propulsion Engineers
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• v.16 no.3
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• pp.9-15
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• 2012

This research simulates the ultrasonic wave propagation in multi-layered media using generalized formular of system response function. We made the artificial defect specimen of a rocket motor and compared with experimental wave forms. The simulation results are coincide with measured waves and we found that the pulse echo method is able to detect unbond defect at liner-propellant interface.