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A Study of the Efficient Planning of Governance for Building Biomass Circulation Estate (바이오매스 순환단지조성을 위한 거버넌스 구축방안 연구)

  • Kwon, Goo-Jung;Lee, Su-Young;Hwang, Jae-Hyun
    • Korean Journal of Organic Agriculture
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    • v.22 no.4
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    • pp.561-579
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    • 2014
  • This research estimates the necessity of a better governance plan on the purpose of fulfillment energy recovery by building resource recycling system for biomass resources and waste resources that derive from agricultural and mountain village areas. The utilization of new renewable energy technology which uses waste and biomass sources diverse as variety of resources, collecting method, operator etc. and is structurally complicated the formation of policy is also very difficult. There is failure because of the problems which occurs from the policy led by government. Biomass Town Development Project should be made through the central government and the local government integrated support system and should be formed a consultative group in order to process the project mutually with these two department including the experts from the related areas. This consultative group, while government organizations carry out the hub function of strategic knowledge management, should carry out the control tower function to be able to be net working transfer the information with the cooperation of private and government so vitalize the communication area among the related actors. And to be able to increase the participation rate of the local people the consistent and various educations should be given so a smooth business promotion progress will be desired through the change of perception and coactive participation of people.

CFD APPLICATION TO THE REGULATORY ASSESSMENT OF FAC-CAUSED CANDU FEEDER PIPE WALL THINNING ISSUE

  • Kang, Dong-Gu;Jo, Jong-Chull
    • Nuclear Engineering and Technology
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    • v.40 no.1
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    • pp.37-48
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    • 2008
  • Flow fields inside feeder pipes have been simulated numerically using a CFD (computational fluid dynamics) code to calculate the shear stress distribution, which is the most important factor in predicting the local regions of feeder pipes highly susceptible to FAC (flow-accelerated corrosion)-induced wall thinning. The CFD approach, with schemes used in this study, to simulate the flow situations inside the CANDU feeder pipes has been verified as it showed a good agreement between the investigation results for the failed feedwater pipe at Surry unit 2 plant in the U.S. and the CFD calculation. Sensitivity studies of the three geometrical parameters, such as angle of the first and second bends, length of the first span between the grayloc hub and the first bend, and length of the second span between the first and the second bends have been performed. CFD analysis reveals that the local regions of feeder pipes of Wolsung unit 1 in Korea, on which wall thickness measurements have been performed so far, are not coincident with the worst regions predicted by the present CFD analysis located in the connection region of straight and bend pipe near the inlet part of the bend intrados. Finally, based on the results of the present CFD analysis, a guide to the selection of the weakest local positions where the measurement of wall thickness should be performed with higher priority has been provided.

Identification of potential candidate genes for lip and oral cavity cancer using network analysis

  • Mathavan, Sarmilah;Kue, Chin Siang;Kumar, Suresh
    • Genomics & Informatics
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    • v.19 no.1
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    • pp.4.1-4.9
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    • 2021
  • Lip and oral cavity cancer, which can occur in any part of the mouth, is the 11th most common type of cancer worldwide. The major obstacles to patients' survival are the poor prognosis, lack of specific biomarkers, and expensive therapeutic alternatives. This study aimed to identify the main genes and pathways associated with lip and oral cavity carcinoma using network analysis and to analyze its molecular mechanism and prognostic significance further. In this study, 472 genes causing lip and oral cavity carcinoma were retrieved from the DisGeNET database. A protein-protein interaction network was developed for network analysis using the STRING database. VEGFA, IL6, MAPK3, INS, TNF, MAPK8, MMP9, CXCL8, EGF, and PTGS2 were recognized as network hub genes using the maximum clique centrality algorithm available in cytoHubba, and nine potential drug candidates (ranibizumab, siltuximab, sulindac, pomalidomide, dexrazoxane, endostatin, pamidronic acid, cetuximab, and apricoxib) for lip and oral cavity cancer were identified from the DGIdb database. Gene enrichment analysis was also performed to identify the gene ontology categorization of cellular components, biological processes, molecular functions, and biological pathways. The genes identified in this study could furnish a new understanding of the underlying molecular mechanisms of carcinogenesis and provide more reliable biomarkers for early diagnosis, prognostication, and treatment of lip and oral cavity cancer.

Exploring Machine Learning Classifiers for Breast Cancer Classification

  • Inayatul Haq;Tehseen Mazhar;Hinna Hafeez;Najib Ullah;Fatma Mallek;Habib Hamam
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.4
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    • pp.860-880
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    • 2024
  • Breast cancer is a major health concern affecting women and men globally. Early detection and accurate classification of breast cancer are vital for effective treatment and survival of patients. This study addresses the challenge of accurately classifying breast tumors using machine learning classifiers such as MLP, AdaBoostM1, logit Boost, Bayes Net, and the J48 decision tree. The research uses a dataset available publicly on GitHub to assess the classifiers' performance and differentiate between the occurrence and non-occurrence of breast cancer. The study compares the 10-fold and 5-fold cross-validation effectiveness, showing that 10-fold cross-validation provides superior results. Also, it examines the impact of varying split percentages, with a 66% split yielding the best performance. This shows the importance of selecting appropriate validation techniques for machine learning-based breast tumor classification. The results also indicate that the J48 decision tree method is the most accurate classifier, providing valuable insights for developing predictive models for cancer diagnosis and advancing computational medical research.

JarBot: Automated Java Libraries Suggestion in JAR Archives Format for a given Software Architecture

  • P. Pirapuraj;Indika Perera
    • International Journal of Computer Science & Network Security
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    • v.24 no.5
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    • pp.191-197
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    • 2024
  • Software reuse gives the meaning for rapid software development and the quality of the software. Most of the Java components/libraries open-source are available only in Java Archive (JAR) file format. When a software design enters into the development process, the developer needs to select necessary JAR files manually via analyzing the given software architecture and related JAR files. This paper proposes an automated approach, JarBot, to suggest all the necessary JAR files for given software architecture in the development process. All related JAR files will be downloaded from the internet based on the extracted information from the given software architecture (class diagram). Class names, method names, and attribute names will be extracted from the downloaded JAR files and matched with the information extracted from the given software architecture to identify the most relevant JAR files. For the result and evaluation of the proposed system, 05 software design was developed for 05 well-completed software project from GitHub. The proposed system suggested more than 95% of the JAR files among expected JAR files for the given 05 software design. The result indicated that the proposed system is suggesting almost all the necessary JAR files.

Economic Analyses on the Satellite Broadband Internet Services for High Speed Trains (고속철도에서의 위성 광대역 인터넷서비스 경제성 분석)

  • Ahn, Jae-Kyoung;Song, Mi-Ja
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.11B
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    • pp.997-1004
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    • 2006
  • There is a growing demand to access the broadband internet while on the very fast move. In order to meet these users needs, much research has been made for providing the broadband internet and HDTV services via satellite broadband internet systems even at top train speeds above 200km/h. In this paper, economic analyses on the satellite broadband internet services for KTX are to be reviewed. Broadband internet to trains in Europe are investigated, and Boeing cases for planes are also examined. In the first step, system configuration which is composed of a hub, terminals, satellite, and gap fillers for the tunnel areas has been proposed. A terminal includes a ultra-fast high gain antenna installed on the roof of the train, and APs inside the coaches. Secondly, cost estimation on the capital expenditures as well as operating expenditures has been performed in the proposed configuration. From the european and Boeing cases, demand and tariff are postulated, consequently, service revenues are derived on the scenario basis. Thirdly, estimated costs and derived revenues make up net present value and internal rate of return in each scenario. Finally, conclusions and contribution of this study are presented.

A Study on the Land Cover Classification and Cross Validation of AI-based Aerial Photograph

  • Lee, Seong-Hyeok;Myeong, Soojeong;Yoon, Donghyeon;Lee, Moung-Jin
    • Korean Journal of Remote Sensing
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    • v.38 no.4
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    • pp.395-409
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    • 2022
  • The purpose of this study is to evaluate the classification performance and applicability when land cover datasets constructed for AI training are cross validation to other areas. For study areas, Gyeongsang-do and Jeolla-do in South Korea were selected as cross validation areas, and training datasets were obtained from AI-Hub. The obtained datasets were applied to the U-Net algorithm, a semantic segmentation algorithm, for each region, and the accuracy was evaluated by applying them to the same and other test areas. There was a difference of about 13-15% in overall classification accuracy between the same and other areas. For rice field, fields and buildings, higher accuracy was shown in the Jeolla-do test areas. For roads, higher accuracy was shown in the Gyeongsang-do test areas. In terms of the difference in accuracy by weight, the result of applying the weights of Gyeongsang-do showed high accuracy for forests, while that of applying the weights of Jeolla-do showed high accuracy for dry fields. The result of land cover classification, it was found that there is a difference in classification performance of existing datasets depending on area. When constructing land cover map for AI training, it is expected that higher quality datasets can be constructed by reflecting the characteristics of various areas. This study is highly scalable from two perspectives. First, it is to apply satellite images to AI study and to the field of land cover. Second, it is expanded based on satellite images and it is possible to use a large scale area and difficult to access.

A study on the carbon trading and maritime finance ecosystem for the maritime industry in the era of sustainability transition (지속가능전환 시기를 맞은 해양산업의 탄소거래 및 해양금융 생태계 구축 연구)

  • Ahn, Soon-Goo;Yun, Hee-Sung
    • Journal of Korea Port Economic Association
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    • v.39 no.4
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    • pp.107-125
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    • 2023
  • The pace of sustainability transition within the maritime industry has been accelerating. This shift primarily necessitates changes in the industry's heavy reliance on fossil fuel-driven ecosystems. Additionally, numerous sustainability laws and regulations, such as the EU's CBAM and IMO's EEXI, have been implemented. This transition is poised to amplify the competitive edge of firms equipped with greater resources, as it introduces substantial operational burdens due to expensive eco-friendly fuel adoption and regulatory compliance. To diverge from the traditional competitive landscape, this paper aims to explore innovative maritime finance models enabling domestic firms to gain competitive advantages on a global scale. Employing analogical reasoning and modeling as a research method, this paper demonstrates that maritime firms can leverage the sustainability transition by aligning sustainable maritime operations with ETS (Emission Trading Schemes). Expanding on this novel approach, the paper delves into potential connections between CCM (Compliance Carbon Market), VCM (Voluntary Carbon Market), and digital asset exchanges. This newly proposed digital/net-zero maritime ecosystem holds the potential to significantly impact the shipping, shipbuilding, and ship finance industries, positioning Busan as a sustainable maritime finance hub. This study holds significance as pioneering research that may stimulate subsequent case-based studies and offer strategic guidance to market participants and policymakers as the maritime industry moves towards a net-zero transition

Transcriptome Analysis of Longissimus Tissue in Fetal Growth Stages of Hanwoo (Korean Native Cattle) with Focus on Muscle Growth and Development (한우 태아기 6, 9개월령 등심 조직의 전사체 분석을 통한 근생성 및 지방생성 관여 유전자 발굴)

  • Jeong, Taejoon;Chung, Ki-Yong;Park, Woncheol;Son, Ju-Hwan;Park, Jong-Eun;Chai, Han-Ha;Kwon, Eung-Gi;Ahn, Jun-Sang;Park, Mi-Rim;Lee, Jiwoong;Lim, Dajeong
    • Journal of Life Science
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    • v.30 no.1
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    • pp.45-57
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    • 2020
  • The prenatal period in livestock animals is crucial for meat production because net increase in the number of muscle fibers is finished before birth. However, there is no study on the growth and development mechanism of muscles in Hanwoo during this period. Therefore, to find candidate genes involved in muscle growth and development during this period in Hanwoo, mRNA expression data of longissimus in Hanwoo at 6 and 9 months post-conceptional age (MPA) were analyzed. We independently identified differentially expressed genes (DEGs) using DESeq2 and edgeR which are R software packages, and considered the overlaps of the results as final-DEGs to use in downstream analysis. The DEGs were classified into several modules using WGCNA then the modules' functions were analyzed to identify modules which involved in myogenesis and adipogenesis. Finally, the hub genes which had the highest WGCNA module membership among the top 10% genes of the STRING network maximal clique centrality were identified. 913(6 MPA specific DEGs) and 233(9 MPA specific DEGs) DEGs were figured out, and these were classified into five and two modules, respectively. Two of the identified modules'(one was in 6, and another was in 9 MPA specific modules) functions was found to be related to myogenesis and adipogenesis. One of the hub genes belonging to the 6 MPA specific module was axin1 (AXIN1) which is known as an inhibitor of Wnt signaling pathway, another was succinate-CoA ligase ADP-forming beta subunit (SUCLA2) which is known as a crucial component of citrate cycle.