• Title/Summary/Keyword: System economic analysis

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Analysis of the Genome Sequence of Strain GiC-126 of Gloeostereum incarnatum with Genetic Linkage Map

  • Jiang, Wan-Zhu;Yao, Fang-Jie;Fang, Ming;Lu, Li-Xin;Zhang, You-Min;Wang, Peng;Meng, Jing-Jing;Lu, Jia;Ma, Xiao-Xu;He, Qi;Shao, Kai-Sheng;Khan, Asif Ali;Wei, Yun-Hui
    • Mycobiology
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    • v.49 no.4
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    • pp.406-420
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    • 2021
  • Gloeostereum incarnatum has edible and medicinal value and was first cultivated and domesticated in China. We sequenced the G. incarnatum monokaryotic strain GiC-126 on an Illumina HiSeq X Ten system and obtained a 34.52-Mb genome assembly sequence that encoded 16,895 predicted genes. We combined the GiC-126 genome with the published genome of G. incarnatum strain CCMJ2665 to construct a genetic linkage map (GiC-126 genome) that had 10 linkage groups (LGs), and the 15 assembly sequences of CCMJ2665 were integrated into 8 LGs. We identified 1912 simple sequence repeat (SSR) loci and detected 700 genes containing 768 SSRs in the genome; 65 and 100 of them were annotated with gene ontology (GO) terms and KEGG pathways, respectively. Carbohydrate-active enzymes (CAZymes) were identified in 20 fungal genomes and annotated; among them, 144 CAZymes were annotated in the GiC-126 genome. The A mating-type locus (MAT-A) of G. incarnatum was located on scaffold885 at 38.9 cM of LG1 and was flanked by two homeodomain (HD1) genes, mip and beta-fg. Fourteen segregation distortion markers were detected in the genetic linkage map, all of which were skewed toward the parent GiC-126. They formed three segregation distortion regions (SDR1-SDR3), and 22 predictive genes were found in scaffold1920 where three segregation distortion markers were located in SDR1. In this study, we corrected and updated the genomic information of G. incarnatum. Our results will provide a theoretical basis for fine gene mapping, functional gene cloning, and genetic breeding the follow-up of G. incarnatum.

Cost Estimation Model for Introduction to Virtual Power Plants in Korea (국내 가상발전소 도입을 위한 비용 추정 모델)

  • Park, Hye-Yeon;Park, Sang-Yoon;Son, Sung-Yong
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.15 no.2
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    • pp.178-188
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    • 2022
  • The introduction of virtual power plants is actively being discussed to solve the problem of grid acceptability caused by the spread of distributed renewable energy, which is the key to achieving carbon neutrality. However, a new business such as virtual power plants is difficult to secure economic feasibility at the initial stage of introduction because it is common that there is no compensation mechanism. Therefore, appropriate support including subsidy is required at the early stage. But, it is generally difficult to obtain the cost model to determine the subsidy level because of the lack of enough data for the new business model. In this study, a survey of domestic experts on the requirements, appropriate scale, and cost required for the introduction of virtual power plants is conducted. First, resource composition scenarios are designed from the survey results to consider the impact of the resource composition on the cost. Then, the cost estimation model is obtained using the individual cost estimation data for their resource compositions using logistic regression analysis. In the case study, appropriate initial subsidy levels are analyzed and compared for the virtual power plants on the scale of 20-500MW. The results show that mid-to-large resource composition cases show 29-51% lower cost than small-to-large resource composition cases.

Forecasting Korean CPI Inflation (우리나라 소비자물가상승률 예측)

  • Kang, Kyu Ho;Kim, Jungsung;Shin, Serim
    • Economic Analysis
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    • v.27 no.4
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    • pp.1-42
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    • 2021
  • The outlook for Korea's consumer price inflation rate has a profound impact not only on the Bank of Korea's operation of the inflation target system but also on the overall economy, including the bond market and private consumption and investment. This study presents the prediction results of consumer price inflation in Korea for the next three years. To this end, first, model selection is performed based on the out-of-sample predictive power of autoregressive distributed lag (ADL) models, AR models, small-scale vector autoregressive (VAR) models, and large-scale VAR models. Since there are many potential predictors of inflation, a Bayesian variable selection technique was introduced for 12 macro variables, and a precise tuning process was performed to improve predictive power. In the case of the VAR model, the Minnesota prior distribution was applied to solve the dimensional curse problem. Looking at the results of long-term and short-term out-of-sample predictions for the last five years, the ADL model was generally superior to other competing models in both point and distribution prediction. As a result of forecasting through the combination of predictions from the above models, the inflation rate is expected to maintain the current level of around 2% until the second half of 2022, and is expected to drop to around 1% from the first half of 2023.

Comparative Analysis of Trade-Labor Linkage in FTAs of the US and EU (미국과 EU의 FTA에 나타난 무역-노동기준 연계에 관한 비교 분석)

  • Kang, Yoo-Duk;Ko, Bo-Min
    • Korea Trade Review
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    • v.41 no.3
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    • pp.1-25
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    • 2016
  • This study reviews international discussions about the trade-labor linkage and examines the labor chapters of FTAs enforced by the US and the EU from a comparative perspective. Since early 1990s, starting from the NAFTA, the US has included forceable labor provisions in its FTAs and this trend continues to the TPP which was concluded in October 2015. On the other hand, the EU's labor provisions in its FTAs have been composed of promotional elements on labor rights based on cooperations and dialogues. These different features of labor provisions in the US and European FTAs are mainly due to the motives of the FTAs of the US and the EU respectively as well as their domestic situations with regards to domestic law and institutional set-ups. The coordination of labor provisions involves a long-term institutional as well as regulatory convergence which triggers not only economic but also social changes, compared to a relatively short-term effect of tariff elimination. For Korea which has been a FTA partner country both with the US and the EU, it is significant to keep the different characteristics in the labor provisions in mind, particularly in the process of its implementation. Concerning the implementation of Korea-US FTA, it might be problematic if Korean law and its regulatory practice on labor-management relations do not comply with that of the US. The Korea-EU FTA case can also have an indirect impact on Korea's labor laws since it stipulates in its provisions that both parties should have discussions not only within each government but also with the civil communities including NGOs. Thus, Korea should pay more attention to the true meaning in labor provisions of both FTAs in order to promote its firms to be equipped with the right labor-management system in their operations abroad.

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How do people verify identity in the Metaverse: Through exploring the user's avatar (메타버스 내 아바타 정체성 확인에 영향을 미치는 요인에 관한 연구)

  • Kihyun Kim;Seongwon Lee;Kil-Soo Suh
    • Journal of Intelligence and Information Systems
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    • v.29 no.2
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    • pp.189-217
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    • 2023
  • The metaverse is a virtual world where individuals engage in social, economic, and cultural activities using avatars, which represent an alternate version of oneself within the virtual realm. While the metaverse has garnered global attention recently, research exploring the identity manifested through avatars within the metaverse remains limited. This study investigates the influence of four IT artifact characteristics related to avatar usage in the metaverse-avatar representation, avatar copresence, avatar profiling, and avatar-space interaction-on perceived avatar identity verification. A survey was conducted with 196 experienced users of the Zepeto platform, and hypotheses were tested using structural equation modeling. The analysis results indicate that the use of IT artifacts enabling avatar representation, avatar copresence, and avatar-space interaction has a positive impact on perceived avatar identity verification. This achieved self-verification indirectly influences the satisfaction and subsequent intention to continue using the metaverse. This study contributes to the academic field by empirically verifying the metaverse technological factors that influence the projected identity onto avatars within the metaverse. Furthermore, it is expected to provide effective guidelines for metaverse platform companies in designing and implementing the metaverse.

Consideration of the Employment Effect of Food Service in Korea through an Input-output Table (산업연관표를 통한 우리나라 외식산업의 고용효과 고찰)

  • Hwang, Seong-hyuk;Choi, Yong-Hwe;Han, Kyu-Chul
    • The Korean Journal of Franchise Management
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    • v.2 no.1
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    • pp.46-60
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    • 2011
  • Under the crisis of global economy, a creation of employment became an important economic issue in Korea. Recently, the structure of Korea economy has been shifted to technology intensive industry. So, Korea economy has been placed on growth without job. Food service industry to overcome this situation has begun to receive attention as a good alternative. Therefore, this study analyzed the effect of the food service industry up on the national employment in Korea using input-output table. Food service industry has a high influence on related industries that are within a food system in respect to job creation. These results show that it is important to provide support policies by government to develop a food service industry.

A Study on Factor Influencing the Nutrition Quotient for Elderly(NQ-E) of Elderly Living Alone (노인 1인 가구의 노인영양지수(NQ-E)에 영향을 미치는 요인에 관한 연구)

  • Kim, Kawon;Hur, Junsoo
    • 한국노년학
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    • v.39 no.4
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    • pp.741-762
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    • 2019
  • The purpose of this study is to identify the Nutrition Quotient for Elderly(NQ-E) of the elderly living in the community and to investigate the characteristics of living conditions affecting the nutritional status of the elderly. The subjects of the survey were 1,970 elderly single elderly households aged 65 and over in the nationwide through convenience sampling method. A survey cooperative system was established with Comprehensive Support Center for Elderly Living Alone, and the 25 social welfare institutions. 385 Life Managers for Elderly Living Alone participated as a survey agent. As a result, NQ-E was 51.14 points, which is the lowest level in the NQ-E, and the explanatory power was 20.1% in multiple regression analysis. Significant variables were age, sex, subjective health status, low number of medication, non-smoker, non-alcoholic, satisfactory economic status, academic status, and the interaction with family and neighbors. Based on this result, this study explains that comprehensive measures of nutritional management for the elderly living alone needs to be sought.

Improvement on Psychological Stability of the Elderly by Using Companion Robot (반려동물형 로봇을 이용한 고령자 심리 안정의 향상 방안)

  • Lee, Jong-Sik;Lee, Kang-Nyeon
    • Journal of the Korea Knowledge Information Technology Society
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    • v.13 no.3
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    • pp.327-339
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    • 2018
  • This study is on the elderly people's use and experience of pet robots (companion robots). Applying companion robots for the elderly's daily lives can enhance their quality of life. Leisure is main activity of the elderly who are out of work. Therefore, the quality and diversity of leisure can affect the quality of their life. Companion Robots could provide them with more advanced and interesting experiences. Around the world, population aging becomes one of the most important trends in each country. The social and economic burden of aging is serious challenge on sustainability of the world, including S. Korea. The authors examine use of Companion Robots for elderly (from 50 years old to 90 years old). In this experiment, the authors study and measure many factors including system quality, interface quality, displeasure, enjoyment, willingness to reuse, perception on new technology. In regression analysis, intimacy(t=-2.006, p<.05) is significant factor on displeasure of Companion Robot. In another regression, displeasure of Companion Robot (independent variable) is significant factor on enjoyment(t=-3.327, p<.01) and willingness to reuse(t=-2.636, p<.01). Therefore, when elderly one feels less displeasure of Companion Robot, he/she feels more enjoyment and willingness to reuse. As a result, the elderly who don't familiar to new technology could improve quality of life and leisure activity by using companion robot.

Research on optimal safety ship-route based on artificial intelligence analysis using marine environment prediction (해양환경 예측정보를 활용한 인공지능 분석 기반의 최적 안전항로 연구)

  • Dae-yaoung Eeom;Bang-hee Lee
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2023.05a
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    • pp.100-103
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    • 2023
  • Recently, development of maritime autonomoust surface ships and eco-friendly ships, production and evaluation research considering various marine environments is needed in the field of optimal routes as the demand for accurate and detailed real-time marine environment prediction information expands. An algorithm that can calculate the optimal route while reducing the risk of the marine environment and uncertainty in energy consumption in smart ships was developed in 2 stages. In the first stage, a profile was created by combining marine environmental information with ship location and status information within the Automatic Ship Identification System(AIS). In the second stage, a model was developed that could define the marine environment energy map using the configured profile results, A regression equation was generated by applying Random Forest among machine learning techniques to reflect about 600,000 data. The Random Forest coefficient of determination (R2) was 0.89, showing very high reliability. The Dijikstra shortest path algorithm was applied to the marine environment prediction at June 1 to 3, 2021, and to calculate the optimal safety route and express it on the map. The route calculated by the random forest regression model was streamlined, and the route was derived considering the state of the marine environment prediction information. The concept of route calculation based on real-time marine environment prediction information in this study is expected to be able to calculate a realistic and safe route that reflects the movement tendency of ships, and to be expanded to a range of economic, safety, and eco-friendliness evaluation models in the future.

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A Study on the Application of the Price Prediction of Construction Materials through the Improvement of Data Refactor Techniques (Data Refactor 기법의 개선을 통한 건설원자재 가격 예측 적용성 연구)

  • Lee, Woo-Yang;Lee, Dong-Eun;Kim, Byung-Soo
    • Korean Journal of Construction Engineering and Management
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    • v.24 no.6
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    • pp.66-73
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    • 2023
  • The construction industry suffers losses due to failures in demand forecasting due to price fluctuations in construction raw materials, increased user costs due to project cost changes, and lack of forecasting system. Accordingly, it is necessary to improve the accuracy of construction raw material price forecasting. This study aims to predict the price of construction raw materials and verify applicability through the improvement of the Data Refactor technique. In order to improve the accuracy of price prediction of construction raw materials, the existing data refactor classification of low and high frequency and ARIMAX utilization method was improved to frequency-oriented and ARIMA method utilization, so that short-term (3 months in the future) six items such as construction raw materials lumber and cement were improved. ), mid-term (6 months in the future), and long-term (12 months in the future) price forecasts. As a result of the analysis, the predicted value based on the improved Data Refactor technique reduced the error and expanded the variability. Therefore, it is expected that the budget can be managed effectively by predicting the price of construction raw materials more accurately through the Data Refactor technique proposed in this study.