• Journal of Biosystems Engineering
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• 제28권2호
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• pp.117-126
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• 2003

This study was conducted to develop precision control system fur cold storage facility that could offer safe storage environment for green grocery. For that reason of neuro-fuzzy control system with learning ability algorithm and single chip neuro-fuzzy micro controller was developed for cold storage facility. Dynamic characteristics and hunting of neuro-fuzzy control system were far superior to on-off and fuzzy control system. Dynamic characteristics of temperature were faster than on-off control system by 1,555 seconds(123% faster) and fuzzy control system by 460 seconds(36.4% faster). When system was arrived at steady state. hunting was ${\pm}$0.5$^{\circ}C$ in on-off control system, ${\pm}$0.4$^{\circ}C$ in fuzzy control system, and ${\pm}$0.3$^{\circ}C$ in neuro-fuzzy control system. Hunting of humidity and wind velocity was also controlled precisely by 70 to 72.5% and 1m/s For storage experiment with onion, characteristics of neuro-fuzzy control system were tested. Dynamic characteristics of neuro-fuzzy control system made cold storage facility conducted precooling ability and minimized hunting.

• 한국과학교육학회지
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• 제14권2호
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• pp.184-191
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• 1994

In this study, a part of high school science instructional materials is evaluated by Instructional Quality Profile(IQP) based on the Merrill's Component Display Theory(CDT). The CDT is based on the Gagne assumption of different conditions of learning for different outcomes. The IQP enables the user to check both the consistency and adequacy of existing cognitive instruction. The IQP can be used to predict student performance, and also to design and develop new insturctional materials. The instructional components are classified according to 5 task levels; An Use-Generalities on Newly Encountered Examples(UGeg), A Remember-Paraphrased -Generalities (RpG), A Remember-Verbatim-Generalities (RvG), A Remember-Paraphrased -Examples (Rpeg), A Remember-Verbatim-Examples(Rveg). And the instructional presentations are classified according to 4 levels: Explain Generalities(EG), Explain examples(Eeg), Inquiry Generalities(IG), Inquiry examples(Ieg). The instructional presentations are determined by instructional components of a related test item, and indexes of the presentation adequacy are calculated by the instructional presentations. The indexes of this study(0.17 - 0.44) were very low and it indicates that the instructional presentations were not adequate to the instructional components of the related text item.

• 한국경영과학회지
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• 제40권4호
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• pp.1-18
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• 2015

This paper proposes relational capability as a main driver of constructing inter-organizational collaboration networks. Based on social network theory and relational view literature, three components of relational capability are constructed and implemented by an agent-based model. The components include organizational capability, structural capability, and trust between a partner and a focal firm. These three components are updated by two micro mechanisms: structural mechanism and relational mechanism. Structural mechanism is a feedback loop in which the relational capability increases structural capability and vice versa. Relational mechanism is a learning-by-doing process in which a focal firm experiences success or failure of collaboration and the experience increases or decreases cumulative trust in a partner firm. Result of agent-based simulation shows that a collaboration network emerges through interactions of firm's relational capabilities and the characteristics of emerged networks vary with the contribution of structural capability and trust to relational capability. Specifically, in case structural capability contributes more to relational capability, the average degree centrality and collaboration proportion increases as time passes and enters into an equilibrium state. In that case, almost every firms participated in the network collaborates each other so that the emerged network becomes highly cohesive. In case trust contributes more to relational capability, the results are reversed. In an equilibrium state, the balance of contribution between structural capability and trust makes an emerged network larger and maximizes average degree centrality of the network.

• The Journal of Asian Finance, Economics and Business
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• 제8권2호
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• pp.195-200
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• 2021

In recent years, Vietnam's economic growth rate has been attributed to the growth of many well-managed industries within Southeast Asia. Among them is the civil construction industry. Construction projects typically take a long time to complete and require a huge budget. Many socio-economic variables and factors affect total construction project costs due to market fluctuations. In recent years, crucial socioeconomic development indicators of construction reached a fairly high growth rate. Also, most infrastructure and construction projects have a high degree of complexity and uncertainty. This makes it challenging to predict the accurate project price. These challenges raise the need to recognize significant factors that influence the construction price index of civil buildings in Vietnam, both micro and macro. Therefore, this paper presents critical factors that affect the construction price index using the fuzzy extent analysis process in an uncertain environment. This proposed quantitative model is expected to reflect the uncertainty in the process of evaluating and ranking the influencing factors of the construction price index in Vietnam. The research results would also allow project stakeholders to be more informed of the factors affecting the construction price index in the context of Vietnam's civil construction industry. They also enable construction contractors to estimate project costs and bid rates better, enhancing their project and risk management performance.

• The Journal of Asian Finance, Economics and Business
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• 제8권4호
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• pp.289-306
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• 2021

This paper aims to investigate how and to what extent FDI impacts the relative demand for skilled labor within firms in the case of developing countries. The analysis uses a sizeable micro-level dataset for Malaysian manufacturing industries using the System-GMM estimators to control the estimations' endogeneity problems. For this purpose, the study uses foreign equity share at the firm level to investigate foreign ownership effects at the firm level and the Horizontal FDI index by Smarzynska Javorcik (2004) to analyze FDI intra-industry linkages influence on the structure of labor demand for Malaysian domestic firms. Our findings indicate that foreign ownership increases the skilled demand within Malaysian manufacturing through the learning process, exclusively for small- and medium-sized firms (SMEs). Conversely for foreign-owned firms, changes in their skilled-labor share do not associate with changes in firm-level foreign equity share. We conclude that foreign ownership per se is not the major contributing factor for skill upgrading in Malaysian manufacturing firms. Furthermore, the competitive pressures caused by foreign firms' presence within the same industry - namely horizontal FDI - has a significant negative spillover effect on the level of skilled-labor share for domestic firms in the Malaysian manufacturing sector within periods of the understudies.

• International Journal of Computer Science & Network Security
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• 제21권11호
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• pp.73-80
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• 2021

Nowadays microblogs have become the most popular platforms to obtain and spread information. Twitter is one of the most used platforms to share everyday life event. However, rumors and misinformation on Arabic social media platforms has become pervasive which can create inestimable harm to society. Therefore, it is imperative to tackle and study this issue to distinguish the verified information from the unverified ones. There is an increasing interest in rumor detection on microblogs recently, however, it is mostly applied on English language while the work on Arabic language is still ongoing research topic and need more efforts. In this paper, we propose a combined Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) to detect rumors on Twitter dataset. Various experiments were conducted to choose the best hyper-parameters tuning to achieve the best results. Moreover, different neural network models are used to evaluate performance and compare results. Experiments show that the CNN-LSTM model achieved the best accuracy 0.95 and an F1-score of 0.94 which outperform the state-of-the-art methods.

• Clinical and Experimental Reproductive Medicine
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• 제49권4호
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• pp.225-238
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• 2022

The ultimate goal of human assisted reproductive technology is to achieve a healthy pregnancy and birth, ideally from the selection and transfer of a single competent embryo. Recently, techniques for efficiently evaluating the state and quality of preimplantation embryos using time-lapse imaging systems have been applied. Artificial intelligence programs based on deep learning technology and big data analysis of time-lapse monitoring system during in vitro culture of preimplantation embryos have also been rapidly developed. In addition, several molecular markers of the secretome have been successfully analyzed in spent embryo culture media, which could easily be obtained during in vitro embryo culture. It is also possible to analyze small amounts of cell-free nucleic acids, mitochondrial nucleic acids, miRNA, and long non-coding RNA derived from embryos using real-time polymerase chain reaction (PCR) or digital PCR, as well as next-generation sequencing. Various efforts are being made to use non-invasive evaluation of embryo quality (NiEEQ) to select the embryo with the best developmental competence. However, each NiEEQ method has some limitations that should be evaluated case by case. Therefore, an integrated analysis strategy fusing several NiEEQ methods should be urgently developed and confirmed by proper clinical trials.

• 유통과학연구
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• 제20권4호
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• pp.85-94
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• 2022

Purpose: Previous research has found that organizational performance pressures and barriers have an effect on the long-term viability of Micro, Small, and Medium Enterprises (MSMEs). Furthermore, MSMEs' intellectual capital and strategic orientation, according to recent research findings, have an impact on this. The goal of this study is to see how intellectual capital and strategic orientation affect MSMEs' performance. Research design, data and methodology: The performance of MSMEs is the dependent variable, with intellectual capital, market orientation, learning orientation, and technical orientation as independent factors. With a sample size of 113 respondents, this research focused on information technology-based MSMEs in Indonesia's Solo Raya area. Data was analyzed use Confirmatory Factor Analysis for the reliability test and path analysis SEM. Results: The interaction between intellectual capital and strategic orientation in respect to MSMEs' performance reveals that innovation capability serves as a partial mediator in the relationship between intellectual capital and technical orientation and organization performance. Conclusions: In general, intellectual capital and strategic orientation have a positive substantial influence on innovation, according to the findings. Furthermore, they have a considerable favorable influence on the performance of MSMEs. It's just that intellectual capital has no discernible impact on knowledge sharing.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.353-354
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• 2021

본 연구에서는 스캐너, 현미경, 레이저를 이용한 입도분석 방법의 한계를 극복하고 비용을 줄이기 위해 초고화소 DSLR 카메라와 MACRO 렌즈를 이용하여 미세광물에 대해 최대한 고품질의 샘플링을 수행 한다. 이를 이용하여 표품 광물 입자들을 촬영한 디지털 사진을 분석하여 모래알 수준(수 mm ~ 0.063 mm)의 광물 입자들에 대한 크기 및 형태 등을 구분한다. 또한 광물입자의 3차원 영상 제작을 위한 여러 촬영기법들을 모색하여, 학습자료 및 광물분류를 위한 영상 제작을 시도하였다.

• 비파괴검사학회지
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• 제31권4호
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• pp.351-359
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• 2011

최근 토목, 기계 및 항공 분야에서 구조물의 안전성 및 적정 성능 수준 확보를 위하여 구조물의 결함 및 노후화에 의한 성능저하 등을 상시적으로 모니터링하기 위한 관심이 높아지고 있다. 실제 구조물에서는 내부 미세 균열에서부터 국부 좌굴, 볼트 풀림, 피로 균열 등과 같이 다양한 형태의 손상이 복합적으로 발생 가능한데, 복합 손상을 단일 모드 계측 시스템으로부터 진단하기는 매우 어렵다. 따라서 본 연구에서는 이러한 복합 손상을 효율적으로 진단하기 위하여 선행 연구에서 제안된 압전센서를 이용한 자가 계측 회로 기반의 다중 모드 계측 시스템을 적용하였다. 자가 계측 회로 기반 다중 모드 계측 시스템은 크게 두 가지 형태의 신호를 계측한다. 첫 번째 모드는 임피던스 계측으로부터 특정 주파수 대역의 구조 응답을 계측하며, 두 번째 모드는 유도 초음파 계측으로부터 단일 중심 주파수에 해당하는 구조 응답을 계측한다. 복합 손상을 손상 유형별로 분류하기 위하여 E/M 임피던스와 유도 초음파의 계측으로부터 추출한 특성을 이용하여 2차원 손상지수를 계산하고 이를 지도학습 기반 패턴인식 기법 중 확률론적 신경망 기법에 적용한다. 제안된 기법의 적용성 검토를 배관 구조물에 인위적으로 다중 손상을 생성시켜 실험을 수행하였다.