In this study, the newest technology available to reduce GHG emissions, which can be applicable in energy industries of the future that has large reduction obligations by energy target management and large intensity of GHG emissions, has been investigated by searching the technical characteristics of each technology. The newest technology to reduce GHG emissions in the field of power generation and energy can be mainly classified into the improvement of efficiency, CCS, and gas combined-cycle technology. In order to improve the reliability of the GHG emission factor obtained from the investigation process, it has been compared to the technology-specific GHG emission factor derived from the estimated amount of emissions. Then the GHG abatement measures, using the derived estimation of factor, by using the newest technology to reduce GHG emissions have been predicted. As a result, the GHG reduction rate by technology of CCS development has been expected to be the largest more than 30%, and the abatement rate by technology of coal gasified fuel cell and pressurized fluidized-bed thermal power generation has been showed more than 20%. If the effective introduction of the newest technology and the study of its characteristics is continued, and properly applied for future GHG emissions, it can be prospected that the national GHG reduction targets can be achieved in cost-efficient way.
Kim, Min-Seung;Jang, Yong-Ju;Lee, Chan-Ho;Choi, Ji-Hye;Lee, Jeong-Hee;Ahn, Min-Ho;Sung, Tae-Eung
The Journal of the Korea Contents Association
/
v.21
no.10
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pp.90-102
/
2021
Technology evaluation is to assess the ability of technology commercialization entities to generate profits by using the subject technology, and domestic technology evaluation agencies have established and implemented their own evaluation systems. In particular, the recently developed technology evaluation model in the fields of marine and fishery does not sufficiently reflect the poor environment for technology development compared to other industries, so it does not pass the level of T4 rating, which is considered appropriate for investment. This is recognized as a challenge that occurs when the common evaluation indicators and evaluation scales used in other industries, and when the scoring system for T1 to T10 grading is similarly or identically utilized. Therefore, through this study, we intend to secure the appropriateness and reliability of the results of the comprehensive rating calculation by developing technology evaluation models and indicators that well explain the nine marine and fisheries industry classification systems. Based on KED and technology evaluation case data, AHP-based index weighting and Monte Carlo simulation-based rating system are applied and the results of case studies are verified. Through the proposed model, we aim to enhance the usability of R&D and commercialization support programs based on fast, convenient and objective evaluation results by applying to upcoming technology evaluation cases.
With the development of science and technology in recent years, various types of unstructured buildings have begun to be implemented by combining traditional architectural styles with digital tools, which are significantly different from conventional formal buildings. Designers will use various methods or digital tools to complete the unstructured and freer architectural forms when building an unstructured building. Based on this background, the need for research on the criteria for evaluating the characteristics of unstructured architectural forms is raised. First, the text was reconstructed by considering and integrating the elements of the unstructured exterior form based on prior research, with the external form of the unstructured building as the main research object. Second, the purpose of this study was to classify various types of unstructured forms and to provide important basic data for designing digital processes of unstructured architectural forms.Third, from 2000 to 2020, the text focused on the study of unstructured buildings and conducted in-depth analysis of the characteristics of their form expressions. While providing a case basis for the study of related fields, distribution laws and presence values related to the characteristics of unstructured buildings were sought. In addition, the analysis was conducted in combination with the distribution of functional use of buildings, and this study is differentiated from the existing research in that the atypical form is applied to the buildings by use, and the application trend of this type is understood to enhance understanding of the atypical form of buildings.
Kim, Jin-Tae;Lee, Jong-Pil;Lee, Soo-Bin;Kim, Dong-Min
The Korean Journal of Nuclear Medicine Technology
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v.25
no.1
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pp.41-43
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2021
Purpose In nuclear medicine blood tests, hemolysis samples are considered as inappropriate sample and are recommended not to be used for blood test. So, the lab are required to collect the blood again in the blood collection room However, The effect of hemolyzed samples on radioimmunoassay has not studied yet. This study was designed to evaluate effects of hemolysis on radioimmunoassay. Materials and Methods The kit manuals of 23 test items were reviewed to confirm whether hemolyzed samples were used. The subjects were 19 general applicants(male : 9, female : 13) and the samples were collected by each two SST tubes, one tube was obtained by centrifugation normally, and the other was obtained hemolyzed sample by centrifugation after external shock. It has been known that highly hemolyzed samples can affect the test results, so the test was performed using the severe hemolyzed sample. The test was performed for each test item using 23 normal serum and hemolysis serum, and SPSS19 program was used for statistical comparison of the test result. Results There was no significant difference between normal serum and hemolysis serum in 21 of 23 test items, but the results of insulin and C-peptide were significantly different(P<0.05). Conclusion It has been known that hemolysis in blood samples can affect the results of biochemical and hematological test, However, hemolysis effect is relatively low. Similarly, this study showed that hemolysis had not much effect on most of immunological radioimmunoassay except for some tests. Therefore, it is thought that the demand for re-collection due to hemolysis will be reduced in the laboratory, which will improve the work process of the laboratory.
It is expected that the integrated control service of the public sector will be increased for the safety of citizens in the future. Therefore, In this study, we analyzed the classification of CCTV control center and the characteristics of interior design. The survey was conducted at eight control centers in Seoul that were constructed since 2007 and analyzed according to the criteria of general matters, services, spatial basic information, spatial structure, and internal structure. The results of the survey are summarized as follows. Based on the results of the study, the Integrated Control Center is a space where the ratio of the physical environment is not high but performs important tasks for the citizens of the city, which are operated 24 hours a day, and security and security. It is characterized by the efficient space allocation for the treatment, the design of the moving line, and the connection according to the urgent work flow. The results of this study are expected to be used as basic data for other integrated control center environment.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2021.10a
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pp.189-192
/
2021
YouTube, the world's largest video sharing platform, is loved by many users in that it provides numerous videos and makes it easy to get helpful information. However, the ratio of like/hate for each video varies according to the subject or upload time, even though they are in the same channel; thus, previous studies try to understand the reason by inspecting some numerical statistics such as the ratio and view count. They can help know how each video is preferred, but there is an explicit limitation to identifying the cause of such preference. Therefore, this study aims to determine the reason that affects the preference through matching between topic words extracted from comments in each video and non-sympathetic types defined in advance. Among the top 10 channels in the field of 'pets' and 'cooking', where outliers occur a lot, the top 10 videos (the threshold of pet: 4.000, the threshold of cooking: 0.723) with the highest ratio were selected. 11,110 comments collected totally, and topics were extracted and matched with non-sympathetic types. The experimental results confirmed that it is possible to predict whether the rate of like/hate would be high or which non-sympathetic type would be by analyzing the comments.
Na-Eun Kim;Dae-Hyun Kim;Yean-Jung Kim;Hyeon-Tae Kim
Journal of Bio-Environment Control
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v.32
no.3
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pp.190-196
/
2023
This study was carried out to collect gas emitted from agricultural heaters using kerosene and to identify the emission concentration of carbon dioxide according to the age of agricultural heating machine. As a result of the linear regression analysis, the carbon dioxide emissions according to the year of agricultural heating machine are R2 = 0.84, which follows y = 26.99x+721.98. Distributed analysis was classified into three groups according to the age of agricultural heating machine. As a result of the distributed analysis, it was 2.196×10-13, which was smaller than the 0.05 probability set for the analysis, which means that there is a difference in at least one group. As a result, the age of the agriculture machine was divided into three groups and the difference between groups was tested. A statistical analysis result was derived that there was a difference in the emission concentration of carbon dioxide according to the age of agricultural heating machine. It is thought that it can be used to investigate greenhouse gas emissions by investigating the amount of carbon dioxide generated by agricultural heaters in the agricultural field of Korea.
Hyeon-Moon Chang;Seon-Ju Kim;Chae-Woon Kim;Ji-Il Seo;Kyung-Ho Lee
The Journal of Bigdata
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v.7
no.2
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pp.153-172
/
2022
Online shopping has transformed and rapidly grown the entire market at the forefront of wholesale and retail services as an effective solution to issues such as digital transformation and social distancing policy (COVID-19 pandemic). Small business owners, who form the majority at the center of the online shopping industry, are constantly collecting policy changes and market trend information to overcome these problems and use them for marketing and other sales activities in order to overcome these problems and continue to grow. Objective and refined information that is more closely related to the business is also needed. Therefore, in this paper, through the collection and analysis of big data information, which is the core technology of digital transformation, key variables are set in product classification, sales trends, consumer preferences, and review information of online shopping malls, and a method of using them for competitor comparison analysis and business sustainability evaluation has been prepared and we would like to propose it as a service. If small and medium-sized businesses can benchmark competitors or excellent businesses based on big data and identify market trends and consumer tendencies, they will clearly recognize their level and position in business and voluntarily strive to secure higher competitiveness. In addition, if the sustainable growth of the online shopping mall operator can be confirmed as an indicator, more efficient policy establishment and risk management can be expected because it has an improved measurement method.
Journal of the Korean Society for Library and Information Science
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v.58
no.1
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pp.395-415
/
2024
In the development of a university library's collection, the concept of patron-driven acquisition refers to a collection strategy that addresses users' direct information needs. In this study, an analysis of ten years' worth of book requests by user types was conducted to understand the topic preferences for efficient collection devleopment in the university library. In collection development, identifying subject areas of users' requested books is necessary for librarians to identify key areas of collection development and establish balanced collection development policies. To identify the major subject areas for each user group, KDC (Korean Decimal Classification) subject classifications were used, and network analysis techniques were applied to investigate the relationships between book topics in detail. The analysis revealed that "social sciences" emerged as the major topic across all user groups. However, in the analysis of sub-topics, "medicine" and "psychology" were distinctively identified as the major subject areas for graduate students, setting them apart from other user groups. The result of the network analysis further indicated that undergraduate students showed unique topics such as civil service, job placement, and career, which were not observed as major topic clusters in other user groups. On the other hand, graduate students tended to concentrate on a few specialized subjects, forming distinct topic clusters in the analysis.
Machine learning techniques utilizing neural networks have been employed in various fields such as disease gene discovery and diagnosis, drug development, and prediction of drug-induced liver injury. Disease features can be investigated by molecular information of DNA. In this study, we developed a neural network to predict the length of DNA and the number of DNA species in mixture solution which are representative molecular information of DNA. In order to address the time-consuming limitations of gel electrophoresis as conventional analysis, we analyzed the dynamic data of a microfluidic concentrating device. The dynamic data were reconstructed into a spatiotemporal map, which reduced the computational cost required for training and prediction. We employed a convolutional neural network to enhance the accuracy to analyze the spatiotemporal map. As a result, we successfully performed single DNA length prediction as single-variable regression, simultaneous prediction of multiple DNA lengths as multivariable regression, and prediction of the number of DNA species in mixture as binary classification. Additionally, based on the composition of training data, we proposed a solution to resolve the problem of prediction bias. By utilizing this study, it would be effectively performed that medical diagnosis using optical measurement such as liquid biopsy of cell-free DNA, cancer diagnosis, etc.
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