• Title/Summary/Keyword: R&D classification

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Development of VR Ship Environment for The Educational Training of Ship Survey (선박 검사 교육훈련을 위한 VR 선박 환경 구축)

  • Kil, WooSung;Son, Myeong-Jo;Lee, Jeong-Youl
    • Journal of the Society of Naval Architects of Korea
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    • v.55 no.4
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    • pp.361-369
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    • 2018
  • The ship surveyor makes a scheme of reasonable ship operation by examining whether the ship has been properly constructed in accordance with the rule of classification societies and international conventions or whether the facilities of the ship in operation meet the standard stipulated by law. Even though the ship surveyors of classification society generally consist of people who have the skill of design or operation of a ship, it takes a long time to train a surveyor to the maturity level. This paper describes the development of survey simulator based on virtual ship environment that enables the surveyor minimize trial and errors to survey the ships. By using VR(Virtual Reality) based survey simulator, surveyors possibly achieve improvement of competence in survey quality by means of safe and immersive training environment. In order to improve the usability and utility of the VR simulator, the ship 3D model has been generated using 3D CAD model for design and production in shipyard. Through this, we suggested the possibility of consistent use of 3D model as the digital twin of a ship.

A Study on the Application of DFMEA for Safety Design of Weapon System (무기체계의 안전 설계를 위한 DFMEA 적용에 관한 연구)

  • Seo, Yang Woo;Oh, Young Il;Kim, Hee Wook;Kim, So Jung
    • Journal of the Korean Society of Systems Engineering
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    • v.18 no.1
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    • pp.46-57
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    • 2022
  • In this paper, we proposed the DFMEA Implementation Method for safety design of Weapon System. First, we presented the process for DFMEA. And then, the case analysis of OOO missile was performed in accordance with the process presented. After defining the system requirements of OOO missile, failure definition scoring criteria was set. In order to clarify the definition of failure, the failure was classified into safety, reliability, maintainability and others. After performing the function analysis, the relationship matrix analysis was performed to identify the failure mode according to the function without omission. After clarifying the failure classification, mode of failure, cause of failure and effect were analyzed to calculate the severity, occurrence and detection values. After the action priority was judged, the recommended action according to the failure classification was identified for the determined action priority. The results of this study can be used as a relevant basis for the design reflection and resource re-allocation of stakeholders.

Performance Assessment of Machine Learning and Deep Learning in Regional Name Identification and Classification in Scientific Documents (머신러닝을 이용한 과학기술 문헌에서의 지역명 식별과 분류방법에 대한 성능 평가)

  • Jung-Woo Lee;Oh-Jin Kwon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.2
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    • pp.389-396
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    • 2024
  • Generative AI has recently been utilized across all fields, achieving expert-level advancements in deep data analysis. However, identifying regional names in scientific literature remains a challenge due to insufficient training data and limited AI application. This study developed a standardized dataset for effectively classifying regional names using address data from Korean institution-affiliated authors listed in the Web of Science. It tested and evaluated the applicability of machine learning and deep learning models in real-world problems. The BERT model showed superior performance, with a precision of 98.41%, recall of 98.2%, and F1 score of 98.31% for metropolitan areas, and a precision of 91.79%, recall of 88.32%, and F1 score of 89.54% for city classifications. These findings offer a valuable data foundation for future research on regional R&D status, researcher mobility, collaboration status, and so on.

An Empirical Study on Classification, Business Type, Organizational Culture on Performance of Korean IT SMEs·Venture (중소·벤처기업의 업종, 영업형태, 조직문화가 기업성과에 미치는 영향에 관한 연구: 삼원분산분석(3-way ANOVA)을 중심으로)

  • Roh, Doo-Hwan;Hwang, Kyung-Ho
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.14 no.2
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    • pp.221-233
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    • 2019
  • In Korea, small and medium sized domestic enterprises(SMEs) play an pivotal role in the national economy, accounting for 99.9% of all enterprises, 87.9% of total employment, and 48.3% of production. and SMEs was driving a real force of the development of national economy in many respects such as innovation, job creation, industrial diversity, balanced regional development. Despite their crucial role in the national development, most of SMEs suffer from a lack of R&D capabilities and equipments as well as funding capacity. Public R&D institutes can provide SMEs with valuable supplementary technological knowledge and help them build technological capacity. so, In order to effectively support SMEs, government and public R&D institutes must be a priority to know about the factors influencing the performance related to technology transfer and technological collaborations. In particular, SMEs are not only taking up a large portion of the national economy, but also their influence in politics and economy so strong that raising the competitiveness of small and medium-sized companies is a national policy goal that must be achieved in order to achieve sustained economic growth. For this reason, it is necessary to look specifically at the relationship between concepts such as the environment, strategy, and organizational culture surrounding the enterprise to enhance the competitiveness of SMEs. The paper analyzes 665 companies to find out which organizational culture affects their performance by classification and type of business of SMEs. This study demonstrated that when SMEs seek consistency in their external environment, strategies, and organizational structure to maintain their continued competitiveness. According to three-way analysis of variance (3-way ANOVA) indicates that classification of industries in SMEs has statistically significant main effects, but the type of business and organizational culture do not have significant effects. However, the company's organizational performance (operating profit) of SMES were found to differ significantly in comparison between groups according to classification standards of industries, and therefore adopted some parts. In addition, an analysis of the effect of interaction between the three independent variables of small and medium-sized enterprises has shown that there are statistically significant interaction effects among classification, types of business, and organizational cultures. The results shows that there is an organizational culture suitable for each industry classification and type of business of an entity, and is expected to be used as a basis for establishing promotion policies related to the incubation and commerciality of small and medium-sized venture companies in the future.

Automatic Classification of Department Types and Analysis of Co-Authorship Network: Focusing on Korean Journals in the Computer Field

  • Byungkyu Kim;Beom-Jong You;Min-Woo Park
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.4
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    • pp.53-63
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    • 2023
  • The utilization of department information in bibliometric analysis using scientific and technological literature is highly advantageous. In this paper, the department information dataset was built through the screening, data refinement, and classification processing of authors' department type belonging to university institutions appearing in academic journals in the field of science and technology published in Korea, and the automatic classification model based on deep learning was developed using the department information dataset as learning data and verification data. In addition, we analyzed the co-authorship structure and network in the field of computer science using the department information dataset and affiliation information of authors from domestic academic journals. The research resulted in a 98.6% accuracy rate for the automatic classification model using Korean department information. Moreover, the co-authorship patterns of Korean researchers in the computer science and engineering field, along with the characteristics and centralities of the co-author network based on institution type, region, institution, and department type, were identified in detail and visually presented on a map.

Identifying Interdisciplinarity of Korean National R&D Using Patent CoIPC Network Analysis (한국 국가 R&D의 학제적 특성 분석 - 특허 공동IPC 연결망 분석의 활용 -)

  • Park, Hyunseok;Seo, Wonchul;Yoon, Janghyeok
    • Journal of the Korean Society for Library and Information Science
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    • v.46 no.4
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    • pp.99-117
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    • 2012
  • This paper proposes a method of using national R&D patents' CoIPC networks to identify interdisciplinary trends of technology areas related to Korean national R&D. While previous research analyzed interdisciplinarity of national R&D with simple bibliometric descriptions, this research uses the network-based indexes to analyze its interdisciplinarity from the viewpoints of interdisciplinary "diversity of coupling" and "strength of coupling". In this research, this proposed method was used to form a R&D CoIPC network from the Korean national R&D patents registered from 2007 to 2010. It is expected that the proposed method can be incorporated into a system for a national R&D trend analysis, and used to identify the issues of technology convergence in national R&D and formulate its related research policies.

Comparison of Loss Function for Multi-Class Classification of Collision Events in Imbalanced Black-Box Video Data (불균형 블랙박스 동영상 데이터에서 충돌 상황의 다중 분류를 위한 손실 함수 비교)

  • Euisang Lee;Seokmin Han
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.24 no.1
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    • pp.49-54
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    • 2024
  • Data imbalance is a common issue encountered in classification problems, stemming from a significant disparity in the number of samples between classes within the dataset. Such data imbalance typically leads to problems in classification models, including overfitting, underfitting, and misinterpretation of performance metrics. Methods to address this issue include resampling, augmentation, regularization techniques, and adjustment of loss functions. In this paper, we focus on loss function adjustment, particularly comparing the performance of various configurations of loss functions (Cross Entropy, Balanced Cross Entropy, two settings of Focal Loss: 𝛼 = 1 and 𝛼 = Balanced, Asymmetric Loss) on Multi-Class black-box video data with imbalance issues. The comparison is conducted using the I3D, and R3D_18 models.

R&D Scoreboard에 의한 연구개발투자와 성과의 연관성 분석

  • 조성표;이연희;박선영;배정희
    • Journal of Technology Innovation
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    • v.10 no.1
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    • pp.98-123
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    • 2002
  • This study develops a Korean R&D Scoreboard which has originated from the R&D Scoreboard in United Kingdom. The Scoreboard contains details of the R&D investment, sales, growth, profits and employee numbers for Korean companies which are extracted from company annual reports and key ratios calculated, with some movements over time. Companies are classified by the Korea Standard Industrial Classification. The Scoreboard contains 190 companies which consist of 100 largest companies and 30 middle-or small-sized firms listed in Korea Stock Exchange (KSE), and 30 ventures and 30 other firms listed in KOSDAQ. The overall company R&D intensity (R&D as a percentage of sales) is 2.1% compared to the international average of 4.2%. Korea has an unusually large R&D percentage of sales in IT hardware (4.9%) and telecommunication (3.7%). R&D intensity is positively correlated with company performance measures such as profitability, sales growth, productivity and market value. For largest companies listed in KSE and ventures listed in KOSDAQ, the ratio of operating profit to sales is greater for high R&D intensity companies. Sales growth is in proportion to R&D intensity for all companies. Plots of value added per employee or sales per employee vs R&D per employee rise together for the sectors studied, especially for the chemical sectors and automobile sectors, demonstrating a correlation with productivity. The average market value of high R&D companies in the KSE has risen more than 1.6 times that of the KOSPI 200 index. Given the correlation between R&D intensity and company performance and given that R&D is a smaller percentage of surplus (profits plus R&D) than international level (both overall and in several sectors), the challenges facing Korean companies are to maintain the leading position in IT hardware and telecommunication, and to increase the intensity of R&D in many medium-intensive R&D sectors where Korea has an average intensity well below international or US levels.

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Production of 3-Hydroxypropionic Acid from Acrylic Acid by Newly Isolated Rhodococcus erythropolis LG12

  • Lee, Sang-Hyun;Park, Si-Jae;Park, Oh-Jin;Cho, Jun-Hyeong;Rhee, Joo-Won
    • Journal of Microbiology and Biotechnology
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    • v.19 no.5
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    • pp.474-481
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    • 2009
  • A novel microorganism, designated as LG12, was isolated from soil based on its ability to use acrylic acid as the sole carbon source. An electron microscopic analysis of its morphological characteristics and phylogenetic classification by 16S rRNA homology showed that the LG12 strain belongs to Rhodococcus erythropolis. R. erythropolis LG12 was able to metabolize a high concentration of acrylic acid (up to 40 g/l). In addition, R. erythropolis LG12 exhibited the highest acrylic acid-degrading activity among the tested microorganisms, including R. rhodochrous, R. equi, R. rubber, Candida rugosa, and Bacillus cereus. The effect of the culture conditions of R. erythropo/is LG12 on the production of 3-hydroxypropionic acid (3HP) from acrylic acid was also examined. To enhance the production of 3HP, acrylic acid-assimilating activity was induced by adding 1 mM acrylic acid to the culture medium when the cell density reached an $OD_{600}$ of 5. Further cultivation of R. erythropo/is LG 12 with 40 g/l of acrylic acid resulted in the production of 17.5 g/l of 3HP with a molar conversion yield of 44% and productivity of 0.22 g/l/h at $30^{\circ}C$ after 72 h.

A Gaussian Mixture Model Based Pattern Classification Algorithm of Forearm Electromyogram (Gaussian Mixture Model 기반 전완 근전도 패턴 분류 알고리즘)

  • Song, Y.R.;Kim, S.J.;Jeong, E.C.;Lee, S.M.
    • Journal of rehabilitation welfare engineering & assistive technology
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    • v.5 no.1
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    • pp.95-101
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    • 2011
  • In this paper, we propose the gaussian mixture model based pattern classification algorithm of forearm electromyogram. We define the motion of 1-degree of freedom as holding and unfolding hand considering a daily life for patient with prosthetic hand. For the extraction of precise features from the EMG signals, we use the difference absolute mean value(DAMV) and the mean absolute value(MAV) to consider amplitude characteristic of EMG signals. We also propose the D_DAMV and D_MAV in order to classify the amplitude characteristic of EMG signals more precisely. In this paper, we implemented a test targeting four adult male and identified the accuracy of EMG pattern classification of two motions which are holding and unfolding hand.