• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.11-19
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• 2009

A RAM-based Neural Net(RBNN) which has multi-discriminators is more effective than RBNN with a discriminator. Experience Sensitive Cumulative Neural Network and 3-D Neuro System(3DNS) that accumulate the features point improved the performance of BNN, which were enabled to train additional and repeated patterns and extract a generalized pattern. In recognition process of Neural Net with multi-discriminator, the selection of class was decided by the value of MRD which calculates the accumulated sum of each class. But they had a saturation problem of its memory cells caused by learning volume increment. Therefore, the decision of MRD has a low performance because recognition rate is decreased by saturation. In this paper, we propose the method which improve the MRD ability. The method consists of the optimum MRD and the matching ratio prototype to generalized image, the cumulative filter ratio, the gap of prototype response MRD. We experimented the performance using NIST database of NIST without preprocessor, and compared this model with 3DNS. The proposed MRD method has more performance of recognition rate and more stable system for distortion of input pattern than 3DNS.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3C
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• pp.141-148
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• 2010

Electrical noises like self potential, burst noises and 60-Hz electrical noises are one of the causes to reduce reliability of electrical resistivity survey. Even the PDC-R (Pseudo DC resisitivity) technique, recently developed, is suffering from the problem of low reliability due to electrical noises. That is, both DC-based and AC-based resistivity technique is subject to reliability problem due to electrical noises embedded in urban geotechnical sites. In this research, a new technique to enhance reliability of the PDC-R technique by minimizing influence of electrical noises was proposed. In addition, an automated procedure was also proposed to facilitate data analysis and interpretation of PDC-R measurements. The proposed technique is composed of two steps: 1. to extract information only related with the input current by means of multiple-filter technique, and 2. to undertake a task to sort out signal information only to show stable and reliable characteristics. This automated procedure was verified by a synthetic harmonic wave including DC shift, burst random noises and 60-Hz electrical noises. Also the procedure was applied to site investigation at urban areas for proving its feasibility and accuracy.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.794-801
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• 2023

The high seas, covering the majority of the world's oceans, hold invaluable marine resources crucial for the growth of the marine bio-industry. The High seas bioresources program of South Korea is at the forefront of these global efforts. This study aims to gauge public awareness and quantify the project benefits, offering insights for future policy decisions. The results revealed that the estimated annual average willingness to pay (WTP) was 3,778.8 KRW, equating to approximately 81.54 billion KRW when extrapolated to the entire national population. The implications of the study are twofold: The project benefits, based on WTP, are substantial, amounting to approximately 81.5 billion KRW annually. This provides critical reference material for future policy formulation, given the considerable WTP in comparison to the current investment. Although interest in international sea marine biological resources is growing, public awareness remains relatively low. However, the project plays a crucial role in building essential databases for the marine bio-industry and securing international sea marine biological resources. Public interest and sustained support are pivotal, not only for this project but also for future policy implementation. Strategies to enhance public awareness are essential, and the study results offer valuable input for future policy decisions.

• Journal of Environmental Health Sciences
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• v.49 no.6
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• pp.312-323
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• 2023

Background: Environmental concentrations of substances can be estimated by K-CHESAR based on main, industrial, and use categories (MC/IC/UC) and ECETOC TRA based on environmental or specific environmental categories (ERC or spERC). Objectives: Three different systems for estimating environmental concentrations were compared to figure out their order with possible reasons along with relationship of regional predicted environmental concentrations (PEC_regional) and final PEC_local for various uses of a substance. Methods: Typical uses of the case substance and their corresponding ERCs were selected from the webpage of the European Chemical Agency. Proper MC/IC/UC and spERC were assigned to each ERC. Emission fractions were compared for each assessment code from the available database. PECs were calculated by three estimating systems: K-CHESAR using MC/IC/UC, ECETOC TRA using ERC, and ECETOC TRA using spERC with their default values for input parameters. Percentage of PEC_regional to PEC_local were manually calculated for each use. Results: Emission factors decreased in the order of ERC > MC/IC/UC > spERC. Values of the final PEC_local derived as sum of PEC_regional and Clocal decreased in the order of calculations using ECETOC TRA-ERC>KCHESAR with MC/IC/UC>ECETOC TRA-spERC for all environmental media. Percentages of PEC_{regional,water} to PEC_local,water ranged from 0 to 10.3% in industrial uses calculated with MC/IC/UC and ERC but 96.3 to 100% in wide dispersive uses of ERC and spERC where values of C_local,water are estimated to be very low. Conclusions: ECETOC TRA generated the most refined PNEC values with spERC and the least with ERC, while K-CHESAR with MC/IC/UC generated values between the two results. The ratio of PEC_regional to PEC_local can be a good measure for performing suitable estimation of PNECs according to use.

• Animal Bioscience
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• v.37 no.6
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• pp.1021-1030
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• 2024

Objective: R-loops are DNA:RNA triplex hybrids, and their metabolism is tightly regulated by transcriptional regulation, DNA damage response, and chromatin structure dynamics. R-loop homeostasis is dynamically regulated and closely associated with gene transcription in mouse zygotes. However, the factors responsible for regulating these dynamic changes in the R-loops of fertilized mouse eggs have not yet been investigated. This study examined the functions of candidate factors that interact with R-loops during zygotic gene activation. Methods: In this study, we used publicly available next-generation sequencing datasets, including low-input ribosome profiling analysis and polymerase II chromatin immunoprecipitation-sequencing (ChIP-seq), to identify potential regulators of R-loop dynamics in zygotes. These datasets were downloaded, reanalyzed, and compared with mass spectrometry data to identify candidate factors involved in regulating R-loop dynamics. To validate the functions of these candidate factors, we treated mouse zygotes with chemical inhibitors using in vitro fertilization. Immunofluorescence with an anti-R-loop antibody was then performed to quantify changes in R-loop metabolism. Results: We identified DEAD-box-5 (DDX5) and histone deacetylase-2 (HDAC2) as candidates that potentially regulate R-loop metabolism in oocytes, zygotes and two-cell embryos based on change of their gene translation. Our analysis revealed that the DDX5 inhibition of activity led to decreased R-loop accumulation in pronuclei, indicating its involvement in regulating R-loop dynamics. However, the inhibition of histone deacetylase-2 activity did not significantly affect R-loop levels in pronuclei. Conclusion: These findings suggest that dynamic changes in R-loops during mouse zygote development are likely regulated by RNA helicases, particularly DDX5, in conjunction with transcriptional processes. Our study provides compelling evidence for the involvement of these factors in regulating R-loop dynamics during early embryonic development.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.121-130
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• 2024

In this paper, we propose and design an NCS-based job matching system for individuals with disabilities. This system allows users with disabilities to access it, input basic information (personal and disability-related details), and take a simple test related to job performance. The system then provides NCS job-related information appropriate to their type and degree of disability. To effectively link various NCS-based jobs, it is essential to consider the degree of disability for each type of disability. However, most evaluation tools target specific types of disabilities or assess the vocational abilities of individuals with disabilities in a limited manner, focusing only on cognitive levels or certain physical functions. This makes it challenging to apply these tools to an NCS-based job matching system for individuals with disabilities. Therefore, in this paper, we utilize the ICF coresets for VR to assess the cognitive levels or physical functions required for performing specific jobs. Additionally, we use the NCS vocational competency evaluation tools to determine the levels of vocational competencies required for performing specific jobs. By doing so, we match NCS-based jobs according to the type and degree of disability. The proposed NCS-based job matching system relies on the user's interaction with the system, which may pose challenges for visually impaired individuals or those with intellectual and autism spectrum disabilities who have low literacy levels. Enhancing the accessibility of this system could enable individuals with disabilities to receive recommendations for NCS-based jobs that suit their vocational abilities.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.4
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• pp.333-341
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• 2008

Three embankments are located in the Chunggye Bay, each named as Changpo, Bokkil and Kuil and environmental changes are expected due to freshwater input. To investigate this phenomenon, three sample sites in front of each embankment gate were selected in Nov. 2006(autumn), Feb. 2007(winter), May. 2007(spring) and Aug. 2007(summer). At every point of embankment spot, large cells(micro-size, >$20\;{\mu}m$) of phytoplankton were turned out to be a major cause of algal bloom in Feb. 2007 and nano-size($2-20\;{\mu}m$) phytoplankton became dominant during rainy season. In rainy season, each point of embankment showed low salinity and transparency with higher ammonium and phosphorus concentrations than dry season. However, the number of phytoplankton has decreased and it is expected that freshwater influx has more influence on high turbidity and radical decrease of salinity than nutrient. According to the results of this study, therefore, nutrient could have more influence on growth of phytoplankton in dry season, but high turbidity and radical changes of salinity have more influence in rainy season.

• Journal of the Korean Regional Science Association
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• v.40 no.2
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• pp.75-89
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• 2024

As the problem of lowering the efficiency of urban services in small and medium-sized cities in the non-metropolitan area intensifies, the necessity of developing a railway station area is being emphasized to form a compressed urban space through regional bases. Although major station areas in large cities are being developed in the form of complex, the analysis of the development location characteristics of the small and medium-sized city station areas is insufficient. The purpose of this study is to analyze the characteristics of development project conditions and potential demand in the high-speed rail station areas across the country, identify the differences in locational characteristics according to the type of city, such as 'metropolitan city', 'large city in non-metropolitan city', 'medium and small city in non-metropolitan city', and find out the appropriate development method. As a result of the analysis, it was analyzed that the 'metropolitan area metropolitan area' has high potential demand and poor business conditions. On the other hand, in the case of the non-metropolitan area, it was analyzed that the 'small and medium-sized city station area' has good business conditions and low potential demand characteristics, and the 'large city station area' has intermediate characteristics. This suggests the need for different development methods in the development of metropolitan and small and medium-sized city station areas. The analysis results of this study show that it is desirable to encourage private participation in large-scale metropolitan station areas, which require large-scale input, to maximize potential demand, and to encourage private participation through public-led projects based on favorable business conditions or development based on regional characteristics.

• Information Systems Review
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• v.21 no.1
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• pp.23-38
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• 2019

The social network service (SNS) is one of the important marketing channels, so many companies actively exploit SNSs by posting SNS messages with appropriate content and style for their customers. In this paper, we focused on the psychological distances embedded in the SNS messages and developed a method to measure the psychological distance in SNS message by mixing a traditional content analysis, natural language processing (NLP), and machine learning. Through a traditional content analysis by human coding, the psychological distance was extracted from the SNS message, and these coding results were used for input data for NLP and machine learning. With NLP, word embedding was executed and Bag of Word was created. The Support Vector Machine, one of machine learning techniques was performed to train and test the psychological distance in SNS message. As a result, sensitivity and precision of SVM prediction were significantly low because of the extreme skewness of dataset. We improved the performance of SVM by balancing the ratio of data by upsampling technique and using data coded with the same value in first content analysis. All performance index was more than 70%, which showed that psychological distance can be measured well.

• Journal of The Korean Association For Science Education
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• v.44 no.1
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• pp.119-130
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• 2024

This study explores the possibility of using a generative artificial intelligence, ChatGPT, for student assessment in science subjects. In order to achieve our goal, we developed assessment items, collected students' responses, and input them into ChatGPT to implement the assessment procedures. Subsequently, we shared the assessment results from ChatGPT with science teachers and compared them to the teachers' assessment process to investigate the use of ChatGPT in student assessment. Regarding the results, in terms of setting the scoring rubric, we found the rubric generated by ChatGPT to be generally appropriate. However, the consistency between the scoring results obtained from ChatGPT and those determined by the teachers was relatively low. This inconsistency was more pronounced in items with additional assessment components and a more intricate rubric. In regard to feedback on student responses, there were some instances where the feedback generated was scientifically incorrect or beyond the scope of the curriculum, but there were also some positives, such as the provision of exemplary answers to questions and additional examples that helped students learn further. From these results, the teachers perceived limitations in using ChatGPT to conduct assessment in terms of reliability, which is considered crucial in student assessment, but suggested that it could be used to support assessment. Finally, synthesizing these findings, implications for utilizing ChatGPT in student assessment were suggested.