• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.287-310
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• 2022

Companies' interest in developing AI-based intelligent new products is increasing. Recently, the main concern of companies is to innovate customer experience and create new values by developing new products through the effective use of Artificial intelligence technology. However, due to the nature of products based on radical technologies such as artificial intelligence, intelligent products differ from existing products and development methods, so it is clear that there is a limitation to applying the existing development methodology as it is. This study proposes a new research method based on KANO-TOPSIS for the successful development of AI-based intelligent new products by using car voice assistants as an example. Using the KANO model, select and evaluate functions that customers think are necessary for new products, and use the TOPSIS method to derives priorities by finding the importance of functions that customers need. For the analysis, major categories such as vehicle condition check and function control elements, driving-related elements, characteristics of voice assistant itself, infotainment elements, and daily life support elements were selected and customer demand attributes were subdivided. As a result of the analysis, high recognition accuracy should be considered as a top priority in the development of car voice assistants. Infotainment elements that provide customized content based on driver's biometric information and usage habits showed lower priorities than expected, while functions related to driver safety such as vehicle condition notification, driving assistance, and security, also showed as the functions that should be developed preferentially. This study is meaningful in that it presented a new product development methodology suitable for the characteristics of AI-based intelligent new products with innovative characteristics through an excellent model combining KANO and TOPSIS.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.329-352
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• 2022

It is reported that particulate matter(PM) penetrates the lungs and blood vessels and causes various heart diseases and respiratory diseases such as lung cancer. The subway is a means of transportation used by an average of 10 million people a day, and although it is important to create a clean and comfortable environment, the level of particulate matter pollution is shown to be high. It is because the subways run through an underground tunnel and the particulate matter trapped in the tunnel moves to the underground station due to the train wind. The Ministry of Environment and the Seoul Metropolitan Government are making various efforts to reduce PM concentration by establishing measures to improve air quality at underground stations. The smart air quality management system is a system that manages air quality in advance by collecting air quality data, analyzing and predicting the PM concentration. The prediction model of the PM concentration is an important component of this system. Various studies on time series data prediction are being conducted, but in relation to the PM prediction in subway stations, it is limited to statistical or recurrent neural network-based deep learning model researches. Therefore, in this study, we propose four transformer-based models including spatiotemporal transformers. As a result of performing PM concentration prediction experiments in the waiting rooms of subway stations in Seoul, it was confirmed that the performance of the transformer-based models was superior to that of the existing ARIMA, LSTM, and Seq2Seq models. Among the transformer-based models, the performance of the spatiotemporal transformers was the best. The smart air quality management system operated through data-based prediction becomes more effective and energy efficient as the accuracy of PM prediction improves. The results of this study are expected to contribute to the efficient operation of the smart air quality management system.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.433-440
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• 2023

High dose rate brachytherapy is a cancer treatment that intensively irradiates radiation to tumors by inserting isotopes with high dose rates into the body. For such a treatment, it is necessary to deliver an accurate dose to the tumor tissue through an accurate treatment plan while delivering only a minimum dose to the normal tissue. Therefore, it is very important to check the location accuracy of the source through accurate Quality Assurance (QA) in clinical practice. However, since the source position is determined using a ruler, automatic radiographer, video monitor, etc. in clinical practice, it yields inaccurate results. In this study, a semiconductor dosimeter using CsPbI₂Br and CsPbIBr₂ was fabricated. And, in order to analyze whether it is more suitable for the relative QA dosimeter for brachytherapy device among the two materials, the radiation detection ability of each was compared and evaluated. In order to evaluate the radiation detection ability in brachytherapy, the reproducibility and linearity of the two materials were evaluated in ¹⁹²IR. In the reproducibility evaluation, CsPbI₂Br presented a Relative Standard Deviatio(RSD) of 0.98% and CsPbIBr₂ presented an RSD of 3.45%. In the linearity evaluation, the coefficient of determination (R²) of CsPbI₂Br was presented as 0.9998, and the R² of CsPbIBr₂ was presented as 0.9994. As a result of the evaluation, it was found that CsPbI₂Br was more stable in radiation detection while satisfying the evaluation criteria in the dosimeter manufactured in this experiment. Therefore, CsPbI₂Br material is suitable for application as a relative dosimeter for radiation detection in brachytherapy devices.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.6-7
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• 2021

Vegetation development in rivers is one of the important issues not only in academic fields such as geomorphology, ecology, hydraulics, etc., but also in river management practices. The problem of river vegetation is directly connected to the harmony of conflicting values of flood management and ecosystem conservation. In Korea, since the 2000s, the issue of river vegetation and land formation has been continuously raised under various conditions, such as the regulating rivers downstream of the dams, the small eutrophicated tributary rivers, and the floodplain sites for the four major river projects. In this background, this study proposes a method for classifying the distribution of vegetation in rivers based on remote sensing data, and presents the results of applying this to the Naeseong Stream. The Naeseong Stream is a representative example of the river landscape that has changed due to vegetation development from 2014 to the latest. The remote sensing data used in the study are images of Sentinel 1 and 2 satellites, which is operated by the European Aerospace Administration (ESA), and provided by Google Earth Engine. For the ground truth, manually classified dataset on the surface of the Naeseong Stream in 2016 were used, where the area is divided into eight types including water, sand and herbaceous and woody vegetation. The classification method used a random forest classification technique, one of the machine learning algorithms. 1,000 samples were extracted from 10 pre-selected polygon regions, each half of them were used as training and verification data. The accuracy based on the verification data was found to be 82~85%. The model established through training was also applied to images from 2016 to 2020, and the process of changes in vegetation zones according to the year was presented. The technical limitations and improvement measures of this paper were considered. By providing quantitative information of the vegetation distribution, this technique is expected to be useful in practical management of vegetation such as thinning and rejuvenation of river vegetation as well as technical fields such as flood level calculation and flow-vegetation coupled modeling in rivers.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.253-263
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• 2023

This study explored the discrepancy between the text of a teacher's guide about straight and reflective light and the content knowledge of pre-service elementary teachers. A total of 455 questions and 543 answers generated by 279 pre-service elementary teachers after reading a 'Shadow and Mirror' unit in the teacher's guide were analyzed. The questions were classified according to the types of concepts and discrepancies, and the answers were analyzed for accuracy. The results of analyzing the concepts of questions revealed that the pre-service elementary teachers were most curious about the shadow in the straight concept, the mirror image in the reflection concept, and the light source in other concepts. The questions with a low correct answer rate due to incorrect- or non-answers, such as those concerning the superposition principle of light by reflection, the principle of experimental tools, and images by lenses, were only partially or not included in the teacher's guide. When the questions were classified according to the type of discrepancy, the frequency of questions due to knowledge deficit was higher than that due to knowledge clash. This demonstrates that the concepts that teachers need to know must be supplemented with the contents of the teacher's guide. Discrepancies due to knowledge clashes are often caused by conflicts between what is experienced in everyday life and what is presented in textbooks. Therefore, it is necessary to reduce the discrepancy between the texts of the teacher's guide and the knowledge of pre-service elementary teachers by including the differences between the actual context of everyday life and the context of the textbook in the teacher's guide.

• Korean Journal of Cognitive Science
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• v.34 no.2
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• pp.111-151
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• 2023

It is reported that binge drinkers show cognitive impairment similar to alcohol use disorder patients. A previous studies using neuropsychological tests and brain imaging techniques to investigate the visual perception of alcohol use disorder patients reported that they had global-local visual perception defects. Although the neurological basis for the global-local visual perception deficit in the heavy drinking group has been presented, there are no studies to date that have investigated the global-local visual perception in the heavy drinking group. This study investigated local-biased visual perception in female college students with binge drinking (BD) using event-related potentials (ERPs). Based on the scores of the Korean version of Alcohol Use Disorder Identification Test and the Alcohol Use Questionnaire, participants were assigned into BD (n=25) and non-BD (n=25) groups. Local-global visual processing was assessed using a local-global paradigm, in which large stimuli (global level) composed of small stimuli (local level) were presented. The stimuli presented at global and local levels were either congruent or incongruent. The behavioral results exhibited that the BD and non-BD groups did not differ in terms of accuracy and response time. In terms of ERPs, the BD and non-BD groups did not show difference in N100, P150 and N200 amplitude. However, the BD group showed significantly smaller P300 amplitude than non-BD group especially in the local condition. In addition, a negative correlation between P300 amplitude and binge drinking score was observed, i.e., severer binge drinking smaller P300 amplitude. The P300 is known to reflect cognitive inhibition and attentional allocation. In the global-local paradigm, the local condition required to attend to local target while ignoring global non-target. Therefore, the present results indicate that female college students with BD do not have local-biased visual processing, instead they seem to have difficulties in inhibition of irrelevant stimuli.

• Journal of Korea Water Resources Association
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• v.56 no.1
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• pp.53-62
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• 2023

Recently, due to the influence of climate change, the occurrence of damage to heavy rain is increasing around the world, and the frequency of heavy rain with a large amount of rain in a short period of time is also increasing. Heavy rains generate a large amount of outflow in a short time, causing flooding in the downstream part of the mountainous area before joining the small and medium-sized rivers. In order to reduce damage to downstream areas caused by flooding, it is very important to calculate the outflow of mountainous areas due to torrential rains. However, the sewage network flooding analysis, which is currently conducting the most analysis in Korea, uses the time and area method using the existing data rather than calculating the rainfall outflow in the mountainous area, which is difficult to determine that the soil characteristics of the region are accurately applied. Therefore, if the rainfall is analyzed for mountainous areas that can cause flooding in the downstream area in a short period of time due to large outflows, the accuracy of the analysis of flooding characteristics that can occur in the downstream area can be improved and used as data for evacuating residents and calculating the extent of damage. In order to calculate the rainfall outflow in the mountainous area, the rainfall outflow in the mountainous area was calculated using MIKE SHE among the MIKE series, and the flooding analysis in the downstream area was conducted through MIKE 21 FM (Flood model). Through this study, it was possible to confirm the amount of outflow and the time to reach downstream in the event of rainfall in the mountainous area, and the results of this analysis can be used to protect human and material resources through pre-evacuation in the downstream area in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4C
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• pp.247-254
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• 2006

Online testing method is one of the numerical experiment methods using experimental information for a numerical analysis directly. The method has an advantage in that analysis can be conducted without using an idealized mechanical model, because mechanical properties are updated from element test for a numerical analysis in real time. The online testing method has mainly been used for the geotechnical seismic engineering, whose major target is sand. A testing method that may be applied to a consolidation problem has recently been developed and laboratory and field verifications have been tried. Although related research thus far has mainly used a method to update average reaction for a numerical analysis by positioning an element tests at the center of a consolidation layer, a weakness that accuracy of the analysis can be impaired as the thickness of the consolidation layer becomes more thicker has been pointed out regarding the method. To clarify the effectiveness and possible analysis scope of the online testing method in relation to the consolidation problem, we need to review the results by applying experiment conditions that may completely exclude such a factor. This research reviewed the results of the online consolidation test in terms of reproduction of the consolidation settlement and the dissipation of excess pore water pressure of a clay specimen by comparing the results of an online consolidation test and a separated-type consolidation test carried out under the same conditions. As a result, the online consolidation test reproduced the change of compressibility according effective stress of clay without a huge contradiction. In terms of the dissipation rate of excess pore water pressure, however, the online consolidation test was a little faster. In conclusion, experiment procedure needs to improve in a direction that hydraulic conductivity can be updated in real time so as to more precisely predict the dissipation of excess pore water pressure. Further research or improvement should be carried out with regard to the consolidation settlement after the end of the dissipation of excess pore water pressure.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3A
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• pp.297-307
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• 2010

Recently, maintenance engineering and technology for civil and building structures have begun to draw big attention and actually the number of structures that need to be evaluate on structural safety due to deterioration and performance degradation of structures are rapidly increasing. When stiffness is decreased because of deterioration of structures and member cracks, dynamic characteristics of structures would be changed. And it is important that the damaged areas and extent of the damage are correctly evaluated by analyzing dynamic characteristics from the actual behavior of a structure. In general, typical measurement instruments used for structure monitoring are dynamic instruments. Existing dynamic instruments are not easy to obtain reliable data when the cable connecting measurement sensors and device is long, and have uneconomical for 1 to 1 connection process between each sensor and instrument. Therefore, a method without attaching sensors to measure vibration at a long range is required. The representative applicable non-contact methods to measure the vibration of structures are laser doppler effect, a method using GPS, and image processing technique. The method using laser doppler effect shows relatively high accuracy but uneconomical while the method using GPS requires expensive equipment, and has its signal's own error and limited speed of sampling rate. But the method using image signal is simple and economical, and is proper to get vibration of inaccessible structures and dynamic characteristics. Image signals of camera instead of sensors had been recently used by many researchers. But the existing method, which records a point of a target attached on a structure and then measures vibration using image processing technique, could have relatively the limited objects of measurement. Therefore, this study conducted shaking table test and field load test to verify the validity of the method that can measure multi-point displacement responses of structures using image processing technique.

• The Journal of Korean Philosophical History
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• no.29
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• pp.255-280
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• 2010

Zhang Bo-duan compiled about internal alchemy in Taoism. Although he lived in the mundane world, he wished to seek theory on neidan of Taoism(internal alchemy). After finding enlightenment, he elucidated that the enlightenment was a state of rising above world not needed to leave the world. After ages, he was admired as the founder of Taoism in Southern school and his Oh Jin Peon which contents internal alchemy was considered seriously to have more than 30 people who annotated with it until Ch'ing Empire. At his age of 80, he met the real person who gave him theory on neidan of Taoism(internal alchemy), its preface tells that he organized its main point, and then wrote Oh Jin Peon with it in 1075. Generally Zhang Bo-duan was known to leave three books as Oh Jin Peon, Guem Dan Sa Baek Ja, and Cheung Hwa Bi Mun, most of critics have been studying on the basis of them. However, it is not correct whether all of them is his writings and there is not exact analysis but simple belief about it. I think accuracy and details are indispensible in philosophical approach. The study not having verification about primary data is no more than a visionary projet which soon collapses. So the purpose of this study is adding the detail analysis on it and making its exact basis of philosophical approach. Zhang Bo-duan over his age of 80, became enlightened, in his old age handed down his student the secret as a record and theory on neidan of Taoism(internal alchemy). And not in his living but after his dying his status was soared. Because of his high status in internal alchemy Taoism, it seems that there are more interest in it and some published books which just leave his name. In this study, I accept Oh Jin Peon as a his real writing among unsure his writings and criticize systematically and classify its characteristics. And I demonstrate that Guem Dan Sa Baek Ja, Cheung Hwa Bi Mun couldn't be his real writings, these could be forgeries by posterity, with proposing some basis of the argument.