• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.786-792
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• 2010

This paper presents a real-time lane detection method which can accurately find the lane-mark boundaries in complex road environment. Unlike many existing methods that pay much attention on the post-processing stage to fit lane-mark position among a great deal of outliers, the proposed method aims at removing those outliers as much as possible at feature extraction stage, so that the searching space at post-processing stage can be greatly reduced. To achieve this goal, a grid-based morphology operation is firstly used to generate the regions of interest (ROI) dynamically, in which a directional edge-linking algorithm with directional edge-gap closing is proposed to link edge-pixels into edge-links which lie in the valid directions, these directional edge-links are then grouped into pairs by checking the valid lane-mark width at certain height of the image. Finally, lane-mark colors are checked inside edge-link pairs in the YUV color space, and lane-mark types are estimated employing a Bayesian probability model. Experimental results show that the proposed method is effective in identifying lane-mark edges among heavy clutter edges in complex road environment, and the whole algorithm can achieve an accuracy rate around 92% at an average speed of 10ms/frame at the image size of $320{\times}240$.

• Analytical Science and Technology
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• v.35 no.6
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• pp.256-266
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• 2022

It is important to determine the concentration of long-lived radionuclides (e.g., ¹²⁹I) in nuclear waste to ensure safety when handling it. To analyze nuclides in a solid sample (e.g., concrete and soil), it is essential to effectively separate and purify the nuclides of interest in the sample. This study reports the comprehensive efforts made to validate the analytical procedure for ¹²⁹I detection in solid samples, using a high-temperature combustion furnace. ¹²⁹I volatilized from the sample collected in 0.01 M HNO₃ solution with a reducing agent (e.g., NaHSO₃) and was rapidly measured by ICP-MS. Analytical conditions, such as pyrolysis temperature and types of mobile phase gas, catalyst, and trapping solution, were optimized to obtain a high recovery rate of spiked ¹²⁹I. Finally, the optimized method was applied for the simultaneous analysis of other volatile radionuclides, such as ³H and ¹⁴C. The performance test results for the optimized method confirmed that the LSC (for ³H and ¹⁴C) and ICP-MS (for ¹²⁹I) measurements, with the separation of volatile nuclides using a high-temperature combustion furnace, were reliable.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.572-578
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• 2020

The stock market is affected by unexpected factors, such as politics, society, and natural disasters, as well as by corporate performance and economic conditions. In recent days, artificial intelligence has become popular, and many researchers have tried to conduct experiments with that. Our study proposes an experiment using not only stock-related data but also other various economic data. We acquired a year's worth of data on stock prices, the percentage of foreigners, interest rates, and exchange rates, and combined them in various ways. Thus, our input data became diversified, and we put the combined input data into a nonlinear autoregressive network with exogenous inputs (NARX) model. With the input data in the NARX model, we analyze and compare them to the original data. As a result, the model exhibits a root mean square error (RMSE) of 0.08 as being the most accurate when we set 10 neurons and two delays with a combination of stock prices and exchange rates from the U.S., China, Europe, and Japan. This study is meaningful in that the exchange rate has the greatest influence on stock prices, lowering the error from RMSE 0.589 when only closing data are used.

• Journal of the Microelectronics and Packaging Society
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• v.27 no.4
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• pp.119-125
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• 2020

Transition metal dichalcogenides (TMDCs), two-dimensional atomic layered materials with direct bandgap in the range of 1.1-2.1 eV, have attracted a lot of research interest due to their high response to light and capability to build new types of artificial heterostructures. However, the large-area synthesis of high-quality and uniform TMDC films with vertical-stacked heterostructure still remains challenge. In this study, we have developed a metal-organic chemical vapor deposition (MOCVD) system for TMDCs and conducted a systematic study on the growth of single-layer TMDCs and their heterostructures. In particular, using a bubbler-type organometallic compound sources, the concentration and flow rate of each source can be precisely controlled to obtain uniformly single-layered MoS2 and WS2 films over the centimeter scale. In addition, the MoS2/WS2 vertical heterostructure was achieved by growing WS2 film directly on the MoS2 film, as confirmed by electron microscopy, UV-visible spectrophotometer, Raman spectroscopy, and photoluminescence spectroscopy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.1-10
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• 2021

The interest in underwater acoustic sensor networks (UWASNs), along with the rapid development of underwater industries, has increased. To operate UWASNs efficiently, it is important to adopt well-designed medium access control (MAC) protocols that prevent collisions and allow the sharing of resources between nodes efficiently. On the other hand, underwater channels suffer from a narrow bandwidth, long propagation delay, and low data rate, so existing terrestrial node pairing schemes for non orthogonal multiple access (NOMA) cannot be applied directly to underwater environments. Therefore, a multi-dimensional node pairing scheme is proposed to consider the unique underwater channel in UWASNs. Conventional NOMA schemes have considered the channel quality only in node pairing. Unlike previous schemes, the proposed scheme considers the channel gain and many other features, such as node fairness, traffic load, and the age of data packets to find the best node-pair. In addition, the sender employs a list of candidates for node-pairs rather than path loss to reduce the computational complexity. The simulation results showed that the proposed scheme outperforms the conventional scheme by considering the fairness factor with 23.8% increases in throughput, 28% decreases in latency, and 5.7% improvements in fairness at best.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.459-464
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• 2017

This study aims to provide basic materials for marketing strategies of cosmeceuticals by investigating customers' recognition and satisfaction about cosmeceuticals targeting 161 adult men and women in their 20s to 50s and living in Seoul, Korea and then analyzing what should be improved for customers. According to the survey, many customers prefer cosmeceuticals due to the professionalism recognized by hospitals, the recommendation by doctors and the scientific image, though the recognition about cosmeceuticals is low among customers in their 40s or older because they are unfamiliar with the term. The survey also shows that the satisfaction about cosmeceuticals is very high in that 94.41% out of 49.85% total users said they were willing to repurchase them, while 72.22% out of 50.15% total nonusers said they wanted to purchase them. The greater knowledge about skin, the higher the interest in cosmetics and the aesthetic practice rate. When it comes to comparing cosmeceutical users and nonusers in choosing cosmetic products, the greater knowledge about skin, more nonusers consider brand recognition (r=.222, p<.05) and cosmetic ingredient (r=.245, p<.005); and more users convenience (r=.162, p<.05). Now that total customers' awareness of cosmeceuticals remains low yet, therefore, it is considered necessary to steadily promote them, enhance repurchase factors, and come up with strategies differentiated from ordinary cosmetics.

• Plant Journal
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• v.10 no.2
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• pp.38-47
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• 2014

Renewable Portfolio Standards was introduced into the system in Korea in 2012. Interest in the unutilized and renewable energy sources is increasing. and these being actively investigated. An organic rankine cycle has emerged as an alternative in order to take advantage of bio-gas engine heat of sewage treatment plants whose capacity is 1500 kW. The organic rankine cycle power system was simulated by a simulator which is a commercial program of power plant design and performance analysis. The biogas engine is operated by $460^{\circ}C$ and 2.7 kg/s flow rate in the sewage treatment plant. Working fluids(R-601a, R-123, R-245fa) are selected to use in ORC power system in this temperature range. It was the isopentane that is the best performance among three working fluids. It could be obtained net power of 163.1 kW and efficiency of 13.66% from isopentane in the simulation.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.67-85
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• 2018

Vehicle platooning through wireless communication and automated driving technology has become realized. Platooning is a technique in which several vehicles travel at regular intervals while maintaining a minimum safety distance. Truck platooning is of keen interest because it contributes to preventing truck crashes and reducing vehicle emissions, in addition to the increase in truck flow capacity. However, it should be noted that interactions between vehicle platoons and adjacent manually-driven vehicles (MV) significantly give an impact on the performance of traffic flow. In particular, when vehicles entering from on-ramp attempt to merge into the mainstream of freeway, proper interactions by adjusting platoon size and inter-platoon spacing are required to maximize traffic performance. This study developed a methodology for establishing operational strategies for truck platoonings on freeway on-ramp areas. Average speed and conflict rate were used as measure of effectiveness (MOE) to evaluate operational efficiency and safety. Microscopic traffic simulation experiments using VISSIM were conducted to evaluate the effectiveness of various platooning scenarios. A decision making process for selecting better platoon operations to satisfy operations and safety requirements was proposed. It was revealed that a platoon operating scenario with 50m inter-platoon spacing and the platoon consisting of 6 vehicles outperformed other scenarios. The proposed methodology would effectively support the realization of novel traffic management concepts in the era of automated driving environments.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.99-106
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• 2008

A synthetic aperture radar (SAR) system is of great interest in many fields of civil and military applications because of all-weather and luminance free imaging capability. SAR image quality parameters such as spatial resolution, peak to sidelobe ratio (PSLR), and integrated sidelobe ratio (ISLR) can be normally estimated by modeling of impulse response function (IRF) which is obtained from various system design parameters such as altitude, operational frequency, PRF, etc. In modeling of IRF, however, background clutter environment surrounding the IRF is generally neglected. In this paper, analysis method for SAR mage quality is proposed in the real background clutter environment. First of all, SAR raw data of a point scatterer is generated based on various system parameters. Secondly, the generated raw data can be focused to ideal IRF by range Doppler algorithm (RDA). Finally, background clutter obtained from image of currently operating SAR system is applied to IRF. In addition, image quality is precisely analyzed by zooming and interpolation method for effective extraction of IRF, and then the effect of proposed methodology is presented with several simulation results under the assumption of estimation error of Doppler rate.

• Education of Primary School Mathematics
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• v.26 no.4
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• pp.333-348
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• 2023

Clear analysis and diagnosis of various characteristic factors of individual students is the most important in order to realize individual customized teaching and learning, which is considered the most essential function of math artificial intelligence-based digital textbooks. In this study, analysis factors and tools for individual customized learning diagnosis and construction models for data collection and analysis were derived from mathematical AI digital textbooks. To this end, according to the Ministry of Education's recent plan to apply AI digital textbooks, the demand for AI digital textbooks in mathematics, personalized learning and prior research on data for it, and factors for learner analysis in mathematics digital platforms were reviewed. As a result of the study, the researcher summarized the factors for learning analysis as factors for learning readiness, process and performance, achievement, weakness, and propensity analysis as factors for learning duration, problem solving time, concentration, math learning habits, and emotional analysis as factors for confidence, interest, anxiety, learning motivation, value perception, and attitude analysis as factors for learning analysis. In addition, the researcher proposed noon data on the problem, learning progress rate, screen recording data on student activities, event data, eye tracking device, and self-response questionnaires as data collection tools for these factors. Finally, a data collection model was proposed that time-series these factors before, during, and after learning.