• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.338-347
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• 2021

In this paper, the beta-ray sensor circuit used in the true random number generator was designed using DB HiTek's 0.18㎛ CMOS process. The CSA circuit proposed a circuit having a function of selecting a PMOS feedback resistor and an NMOS feedback resistor, and a function of selecting a feedback capacitor of 50fF and 100fF. And for the pulse shaper circuit, a CR-RC2 pulse shaper circuit using a non-inverting amplifier was used. Since the OPAMP circuit used in this paper uses single power instead of dual power, we proposed a circuit in which the resistor of the CR circuit and one node of the capacitor of the RC circuit are connected to VCOM instead of GND. And since the output signal of the pulse shaper does not increase monotonically, even if the output signal of the comparator circuit generates multiple consecutive pulses, the monostable multivibrator circuit is used to prevent signal distortion. In addition, the CSA input terminal, VIN, and the beta-ray sensor output terminal are placed on the top and bottom of the silicon chip to reduce capacitive coupling noise between PCB traces.

• Journal of Korea Water Resources Association
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• v.55 no.5
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• pp.345-356
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• 2022

A severe flooding occured at a small urban catchment in Daejeon-si South Korea on July 30, 2020 causing significant loss of property (inundated 78 vehicles and two apartments) and life (one casualty and 56 victims). In this study, a retrospective analysis of the inundation event was implemented using a physically-based urban flood model, H12 with high-resolution data. H12 is an integrated 1-dimensional sewer network and 2-dimensional surface flow model supported by hybrid parallel techniques to efficiently deal with high-resolution data. In addition, we evaluated the impact of the flooding barriers which were installed after the flood disaster. As a result, it was found that the inundation was affected by a combination of multiple components including the shape of the basin, the low terrain of the inundation area located in the downstream part of the basin, and lack of pipe capacity to drain discharge from the upstream during heavy rain. The impact of the flooding barriers was analyzed by modeling with and without barriers on the high-resolution terrain input data. It was evaluated that the flood barriers effectively lower the water depth in the apartment complex. This study demonstrates capability of high-resolution physically-based urban modeling to quantitatively assess the past inundation event and the impact of the reduction measures.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.119-137
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• 2022

Recent recommendation system studies apply various deep learning models to represent user and item interactions better. One of the noteworthy studies is ONCF(Outer product-based Neural Collaborative Filtering) which builds a two-dimensional interaction map via outer product and employs CNN (Convolutional Neural Networks) to learn high-order correlations from the map. However, ONCF has limitations in recommendation performance due to the problems with CNN and the absence of side information. ONCF using CNN has an inductive bias problem that causes poor performances for data with a distribution that does not appear in the training data. This paper proposes to employ a Vision Transformer (ViT) instead of the vanilla CNN used in ONCF. The reason is that ViT showed better results than state-of-the-art CNN in many image classification cases. In addition, we propose a new architecture to reflect side information that ONCF did not consider. Unlike previous studies that reflect side information in a neural network using simple input combination methods, this study uses an independent auxiliary classifier to reflect side information more effectively in the recommender system. ONCF used a single latent vector for user and item, but in this study, a channel is constructed using multiple vectors to enable the model to learn more diverse expressions and to obtain an ensemble effect. The experiments showed our deep learning model improved performance in recommendation compared to ONCF.

• The Journal of the Acoustical Society of Korea
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• v.41 no.6
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• pp.610-620
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• 2022

An acoustic vector sensor can simultaneously receive vector quantities, such as particle velocity and acceleration, as well as acoustic pressure at one location, and thus it can be used as a single input multiple output receiver in underwater acoustic communication systems. On the other hand, vector signals received by a single vector sensor have different channel characteristics due to the azimuth angle between the source and receiver and the difference in propagation angle of multipath in each component, producing different communication performances. In this paper, we propose a channel parameter-based weighting method to improve the performance of an acoustic communication system using a single vector sensor. To verify the proposed method, we used communication data collected from the experiment conducted during the KOREX-17 (Korea Reverberation Experiment). For communication demodulation, block-based time reversal technique which is robust against time-varying channels were utilized. Finally, the communication results showed that the effectiveness of the channel parameter-based weighting method for the underwater communication system using a single vector sensor was verified.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6B
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• pp.597-603
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• 2006

The purpose of this study is to improve the short term rainfall forecast skill using neural network model that can deal with the non-linear behavior between satellite data and ground observation, and minimize the flood damage. To overcome the geographical limitation of Korean peninsula and get the long forecast lead time of 3 to 6 hour, the developed rainfall forecast model took satellite imageries and wide range AWS data. The architecture of neural network model is a multi-layer neural network which consists of one input layer, one hidden layer, and one output layer. Neural network is trained using a momentum back propagation algorithm. Flood was estimated using rainfall forecasts. We developed a dynamic flood inundation model which is associated with 1-dimensional flood routing model. Therefore the model can forecast flood aspect in a protected lowland by levee failure of river. In the case of multiple levee breaks at main stream and tributaries, the developed flood inundation model can estimate flood level in a river and inundation level and area in a protected lowland simultaneously.

• Journal of Korean Society of Archives and Records Management
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• v.24 no.2
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• pp.89-112
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• 2024

Metadata is a crucial component of record management, playing a vital role in properly managing and understanding the record. In cases where automatic metadata assignment is not feasible, manual input by records professionals becomes necessary. This study aims to alleviate the challenges associated with manual entry by proposing a method that harnesses ChatGPT technology for extracting records management metadata elements. To employ ChatGPT technology, a Python program utilizing the LangChain library was developed. This program was designed to analyze PDF documents and extract metadata from records through questions, both with a locally installed instance of ChatGPT and the ChatGPT online service. Multiple PDF documents were subjected to this process to test the effectiveness of metadata extraction. The results revealed that while using LangChain with ChatGPT-3.5 turbo provided a secure environment, it exhibited some limitations in accurately retrieving metadata elements. Conversely, the ChatGPT-4 online service yielded relatively accurate results despite being unable to handle sensitive documents for security reasons. This exploration underscores the potential of utilizing ChatGPT technology to extract metadata in records management. With advancements in ChatGPT-related technologies, safer and more accurate results are expected to be achieved. Leveraging these advantages can significantly enhance the efficiency and productivity of tasks associated with managing records and metadata in archives.

• Journal of dental hygiene science
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• v.24 no.1
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• pp.62-70
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• 2024

Background: This study aimed to evaluate ChatGPT's performance accuracy in responding to questions from the national dental hygienist examination. Moreover, through an analysis of ChatGPT's incorrect responses, this research intended to pinpoint the predominant types of errors. Methods: To evaluate ChatGPT-3.5's performance according to the type of national examination questions, the researchers classified 200 questions of the 49th National Dental Hygienist Examination into recall, interpretation, and solving type questions. The researchers strategically modified the questions to counteract potential misunderstandings from implied meanings or technical terminology in Korea. To assess ChatGPT-3.5's problem-solving capabilities in applying previously acquired knowledge, the questions were first converted to subjective type. If ChatGPT-3.5 generated an incorrect response, an original multiple-choice framework was provided again. Two hundred questions were input into ChatGPT-3.5 and the generated responses were analyzed. After using ChatGPT, the accuracy of each response was evaluated by researchers according to the types of questions, and the types of incorrect responses were categorized (logical, information, and statistical errors). Finally, hallucination was evaluated when ChatGPT provided misleading information by answering something that was not true as if it were true. Results: ChatGPT's responses to the national examination were 45.5% accurate. Accuracy by question type was 60.3% for recall and 13.0% for problem-solving type questions. The accuracy rate for the subjective solving questions was 13.0%, while the accuracy for the objective questions increased to 43.5%. The most common types of incorrect responses were logical errors 65.1% of all. Of the total 102 incorrectly answered questions, 100 were categorized as hallucinations. Conclusion: ChatGPT-3.5 was found to be limited in its ability to provide evidence-based correct responses to the Korean national dental hygiene examination. Therefore, dental hygienists in the education or clinical fields should be careful to use artificial intelligence-generated materials with a critical view.

• Journal of Environmental Health Sciences
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• v.46 no.3
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• pp.285-296
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• 2020

Objective: The objective of this study was to describe the characteristics of exposure to humidifier disinfectants (HDs) and their association with the presence of a person who experienced the adverse health effects in general households in Korea. Methods: During the month of December 2016, a nationwide online survey was conducted on adults over 20 years of age who had experience of using HDs. It provided information on exposure characteristics and the experience of health effects. The final survey respondents consisted of 1,555 people who provided information on themselves and their household members during the use of HD. Exposure characteristics at the household level included average days of HD use per week, average hours of HD use per day, the duration within which one bottle of HD was emptied, average input frequency of HD, amount of HD (cc) per one time used, and active ingredients of HD products (PHMG, CMIT/MIT, PGH, or others). The risk of the presence of a person who experienced adverse health effects in the household was evaluated by estimating odds ratios (ORs) and 95% confidence intervals (CIs) adjusted for monthly income and region using a multiple logistic regression model. Subgroup analyses were conducted for households with a child (≤7 years) and households with a newborn infant during HD use. Results: The level of exposure to HD tended to be higher for households with a child or newborn infant for several variables including average days of HD use per week (P<0.0001) and average hours of HD use per day (P<0.0001). The proportion of households in which there was at least one person who experienced adverse health effects such as rhinitis, asthma, pneumonia, atopy/skin disease, etc. was 20.6% for all households, 25.3% for households with children, and 29.9% for households with newborn infants. The presence of a person who experienced adverse health effects in the household was significantly associated with average hours of HD use per day (P_trend<0.001), duration within which one bottle of HD was emptied (P_trend<0.001), average input frequency of HD (P_trend<0.001), amount of HD per one use (P_trend=0.01), and use of HDs containing PHMG (OR=2.23, 95% CI=1.45-3.43). Similar results were observed in subgroup analyses. Conclusion: Our results suggest that level of exposure to HD tended to be higher for households with a child or newborn infant and that exposure to HD is significantly associated with the presence of a person who experienced adverse health effects in the household.

• Economic and Environmental Geology
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• v.39 no.6 s.181
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• pp.739-752
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• 2006

Deep-sea surface sediments acquired by multiple corer from 69 stations in the Clarion-Clipperton fracture zone of the northeast equatorial Pacific, were examined to understand the correlation of mass physical properties and sedimen-tological processes. The seabed of the middle part ($8-12^{\circ}N$) of the study area is mainly covered by biogenic siliceous sediment compared with pelagic red clays in the northern part ($16-17^{\circ}N$). In the southern part ($5-6^{\circ}N$), water depth is shallower than carbonate compensation depth (CCD). The mass physical properties such as grain size distribution, mean grain size, water content, specific grain density, wet bulk density, void ratio, and porosity of sediments are distinctly different among the three parts of the study area. Surface sediments in northern part are characterized by fine grain size and low water contents possibly due to low primary productivity and high detrital input. Conversely, sediments in the middle part are characterized by coarse grain size and high water contents, which might be caused by high surface productivity and deeper depth than CCD. The sediments show low water contents and high density in the southern part, which can be explained by shallower depth than CCD. Our results suggest that the variations in mass physical properties of sediments are influenced by combined effects including biogenic primary productivity of surface water, water depth, especially with respect to CCD, sedimentation rate, detrital input, and the geochemistry of the bottom water (for example, formation of authigenic clay minerals and dissolution of biogenic grains).

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.344-350
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• 2003

In this paper, we propose a novel sharing method ordering the events occurring between users collaborated with the common telecomputing environment. We realize the sharing method with multimedia data to improve the coworking effect using teleprocessing network. This sharing method advances the efficiency of communicating projects such as remote education, tele-conference, and co-authoring of multimedia contents by offering conveniences of presentation, group authoring, common management, and transient event productions of the users. As for the conventional sharing white board system, all the multimedia contents segments should be authored by the exclusive program, and we cannot use any existing contents or program. Moreover we suffer from the problem that ordering error occurs in the teleprocessing operation because we do not have any line-up technology for the input ordering of commands. Therefore we develop a method of retrieving input and output events from the windows system and the message hooking technology which transmits between programs in the operating system In addition, we realize the allocation technology of the processing results for all sharing users of the distributed computing environment without any error. Our sharing technology should contribute to improve the face-to-face coworking efficiency for multimedia contents authoring, common blackboard system in the area of remote educations, and presentation display in visual conference.