• Title/Summary/Keyword: capacity models

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Authentication of Hempseed Oil from Different Commercial Oils Using Simple UV-Vis Spectrophotomety (UV-Vis spectrophotometry법을 이용한 다양한 유지류로부터 헴프씨드 오일의 진위 판별법)

  • Lee, Yun-Jin;Kang, Deok-Gyeong;Kim, Young-Min;Sohn, Ho-Yong
    • Journal of Life Science
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    • v.32 no.5
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    • pp.362-367
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    • 2022
  • Hempseed, a dehulled Cannabis fructus, has high nutraceutical potential. It has plenty of essential amino acids, vitamins, and essential polyunsaturated fatty acids, including α- and γ-linolenic acid. Increased exercise capacity, cognitive function, and ameliorative effects against hypercholesterolemia, neuro-inflammation, thrombus formation, and learning and memory impairment were reported in hemp-seed oil-administered models. Therefore, the market prices of hempseed oil are 45~140-fold higher than the other plant-derived oils, such as soy, corn, olive, canola, or linseed oil. In this study, instead of FTIR (Fourier Transform Infrared Spectroscopy) or FTIR-Raman spectroscopy, a simple UV-Vis spectrophotometry method was developed to authenticate the hempseed oil. Measurements of absorbance at 245, 305, and 415 nm of oils and calculations of 245/415 and 315/415 nm provided that the ratios of 245/415 and 315/415 nm of authentic hempseed oils were 12.9 and 9.6, respectively. The 245/415 and 315/415 nm of soy oil, corn oil, canola oil, and linseed oil were 35.4~61.8 and 29.7~50.8, respectively. This simple UV-Vis spectrophotometry method could also be applied to differentiate hempseed oil from blended oil products in markets.

Dynamic Numerical Modeling of Subsea Railway Tunnel Based on Geotechnical Conditions and Seismic Waves (지반조건과 지진파를 고려한 해저철도 터널의 동적 수치 모델링)

  • Kwak, Chang-Won;Yoo, Mintaek
    • Journal of the Korean Geotechnical Society
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    • v.38 no.11
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    • pp.69-86
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    • 2022
  • The railway is widely used to transport passengers and freight due to its punctuality and large transport capacity. The recent remarkable development in construction technology enables various subsea railway tunnels for continent-continent or continent-island connectivity. In Korea, design and construction experience is primarily based on the successful completion of the Boryeong subsea tunnel (2021) and the Gadeok subsea tunnel (2010). However, frequent earthquakes with diverse magnitudes, globally induced and continuously increased the awareness of seismic risks and the frequency of domestic earthquakes. The effect of an earthquake on the subsea tunnel is very complicated. However, ground conditions and seismic waves are considered the main factors. This study simulated four ground types of 3-dimensional numerical models, such as soil, rock, composite, and fractured zone, to analyze the effect of ground type and seismic wave. A virtual subsea railway shield tunnel considering external water pressure was modeled. Further, three different seismic waves with long-term, short-term, and both periods were studied. The dynamic analyses by finite difference method were performed to investigate the displacement and stress characteristics. Consequently, the long-term period wave exhibited a predominant lateral displacement response in soil and the short-term period wave in rock. The artificial wave, which had both periodic characteristics, demonstrated predominant in the fractured zone. The effect of an earthquake is more noticeable in the stress of the tunnel segment than in displacement because of confining effect of ground and structural elements in the shield tunnel. 

A multi-channel CNN based online review helpfulness prediction model (Multi-channel CNN 기반 온라인 리뷰 유용성 예측 모델 개발에 관한 연구)

  • Li, Xinzhe;Yun, Hyorim;Li, Qinglong;Kim, Jaekyeong
    • Journal of Intelligence and Information Systems
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    • v.28 no.2
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    • pp.171-189
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    • 2022
  • Online reviews play an essential role in the consumer's purchasing decision-making process, and thus, providing helpful and reliable reviews is essential to consumers. Previous online review helpfulness prediction studies mainly predicted review helpfulness based on the consistency of text and rating information of online reviews. However, there is a limitation in that representation capacity or review text and rating interaction. We propose a CNN-RHP model that effectively learns the interaction between review text and rating information to improve the limitations of previous studies. Multi-channel CNNs were applied to extract the semantic representation of the review text. We also converted rating into independent high-dimensional embedding vectors representing the same dimension as the text vector. The consistency between the review text and the rating information is learned based on element-wise operations between the review text and the star rating vector. To evaluate the performance of the proposed CNN-RHP model in this study, we used online reviews collected from Amazom.com. Experimental results show that the CNN-RHP model indicates excellent performance compared to several benchmark models. The results of this study can provide practical implications when providing services related to review helpfulness on online e-commerce platforms.

Inhibition of the Texture Softening of Shrimp Litopenaeus vannamei Pressured at High-temperature in a Retort Using a Mixed Solution of Calcium Chloride and Potato Starch (염화칼슘 및 감자전분의 혼합용액을 활용한 고온가압 처리 새우(Litopenaeus vannamei)살의 물성 연화 억제)

  • Choe, Yu Ri;Park, Ji Hoon;Cho, Hye Jeong;Lee, Jung Suck;Kim, Jin-Soo
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.55 no.6
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    • pp.817-826
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    • 2022
  • This study was conducted to determinean optimal soaking solution for inhibiting the texture softening of shrimp Litopenaeus vannamei pressured at high temperature (S-P/HT) in a retort, and also to optimize concentrations of 0.5% calcium chloride (CC) and 5.0% potato starch (PS) for preparation of a mixed solution (MS) and soaking time (ST) in the MS. On the basis of the results of expressible drip (4.6%), water holding capacity (95.1%), hardness (18.4 N/cm2) and sensory texture (7.2 score), the MS was found to be the optimal soaking solution for inhibition of texture softening under S-P/HT conditions, The concentrations of CC (X1, %), PS (X2, %), and ST (X3, min) were selected as independent variables, and hardness (Y1), springiness (Y2) and sensory texture (Y3) were selected as dependent variables. The optimal conditions of X1, X2, and X3 were 0.51%, 6.34%, and 364 min, respectively. Under the optimal conditions, the experimental values of Y1, Y2 and Y3 were 18.3±0.8 N/cm2, 4.4±0.3 mm and 7.7±0.2, respectively, which did not diffr significantly from the predicted values (P>0.05). In conclusion, the optimized models of X1, X2, and X3 for the preparation of S-P/HT using CC-PS were suitably fitted.

Korean and Multilingual Language Models Study for Cross-Lingual Post-Training (XPT) (Cross-Lingual Post-Training (XPT)을 위한 한국어 및 다국어 언어모델 연구)

  • Son, Suhyune;Park, Chanjun;Lee, Jungseob;Shim, Midan;Lee, Chanhee;Park, Kinam;Lim, Heuiseok
    • Journal of the Korea Convergence Society
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    • v.13 no.3
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    • pp.77-89
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    • 2022
  • It has been proven through many previous researches that the pretrained language model with a large corpus helps improve performance in various natural language processing tasks. However, there is a limit to building a large-capacity corpus for training in a language environment where resources are scarce. Using the Cross-lingual Post-Training (XPT) method, we analyze the method's efficiency in Korean, which is a low resource language. XPT selectively reuses the English pretrained language model parameters, which is a high resource and uses an adaptation layer to learn the relationship between the two languages. This confirmed that only a small amount of the target language dataset in the relationship extraction shows better performance than the target pretrained language model. In addition, we analyze the characteristics of each model on the Korean language model and the Korean multilingual model disclosed by domestic and foreign researchers and companies.

The Effects of Technology Commercialization Capability and Competitive Strategy of Venture Companies on Growth Prospects: Focused on Mediating Effect of Business Model Innovation (벤처기업의 기술사업화역량과 경쟁전략이 성장전망에 미치는 영향: 비즈니스모델 혁신의 매개효과를 중심으로)

  • Ahn, Mun Hyoung
    • Journal of Industrial Convergence
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    • v.20 no.8
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    • pp.1-13
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    • 2022
  • Although the number of venture start-ups has increased significantly, it is difficult to judge the success or failure based on short-term performance alone. The survival of a company cannot be guaranteed if it does not show sustainable growth prospects. As a growth factor for venture companies, the level of technology commercialization capability and competitive strategies are considered important. Recently, the emergence of innovative business models is creating new opportunities and driving the growth of numerous venture start-ups. This study tried to investigate the mediating effect of business model innovation in the relationship between technology commercialization capability, competitive strategy and the growth prospects of venture companies. For this, empirical analysis was conducted using the original data of the Research on the Precision Status of Venture Firms 2021. As a result, production, manufacturing, marketing capability, cost leadership and product differentiation had a positive(+) effect on growth prospects. The mediating effect of business model innovation between all factors except for manufacturing capacity and growth prospects was verified. This study expanded the scope of research by shedding new light on the factors influencing the long-term growth prospects of venture companies and revealing business model innovation as a new mediating variable. In future research, it is necessary to develop an objective measurement tool and to identify differences according to industrial characteristics.

Design of High Efficiency Permanent Magnet Synchronous Generator for Application of Waste Heat Generation ORC System (폐열발전 ORC 시스템 적용을 위한 고효율 영구자석형 동기발전기 설계)

  • Yeong-Jung Kim;Seung-Jin Yang;Chae-Joo Moon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.1
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    • pp.45-52
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    • 2023
  • The power generation method using expensive diesel has operation problems such as high cost diesel generator and a lack of reserved power due to increase of power demand in some islands, requiring expansion of power generation facilities. To solve this problems, it is necessary to improve the efficiency of power generation facilities through an ORC(Organic Rankin Cycle) system application that uses waste heat as a heat source. Therefore, localized application technology of price competitive and highly reliable ORC power generation system is needed, and optimization technology of generators is having great effect, so this study performed two generator designs to get a high-efficiency generator with an optimized 30kW output. The comparison of simulation data for two designed models showed that a generator with SPM factor of 46.2% had an efficiency of 92.1% and a power ouput of about 23.2kW based on 12,000rpm, a generator with SPM factor of 44.46%, had a power output of 27.9kW and efficiency of 93.6% based on above rpm. For the verification of improved design model with SPM factor of 44.46%, the prototype test system with 110kW motor dynamometer was installed and got to the efficiency of 92.08% with conditions of the rated capacity 25kW at 12,000rpm, the test results of prototype generator showed the validity of generator design.

An Evaluation of Development Plans for Rolling Stock Maintenance Shop Using Computer Simulation - Emphasizing CDC and Generator Car - (시뮬레이션 기법을 이용한 철도차량 중정비 공장 설계검증 - 디젤동차 및 발전차 중정비 공장을 중심으로 -)

  • Jeon, Byoung-Hack;Jang, Seong-Yong;Lee, Won-Young;Oh, Jeong-Heon
    • Journal of the Korea Society for Simulation
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    • v.18 no.3
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    • pp.23-34
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    • 2009
  • In the railroad rolling stock depot, long-term maintenance tasks is done regularly every two or four year basis to maintain the functionality of equipments and rolling stock body or for the repair operation of the heavily damaged rolling stocks by fatal accidents. This paper addresses the computer simulation model building for the rolling stock maintenance shop for the CDC(Commuter Diesel Car) and Generator Car planned to be constructed at Daejon Rolling Stock Depot, which will be moved from Yongsan Rolling Stock Depot. We evaluated the processing capacity of two layout design alternatives based on the maintenance process chart through the developed simulation models. The performance measures are the number of processed cars per year, the cycle time, shop utilization, work in process and the average number waiting car for input. The simulation result shows that one design alternative outperforms another design alternative in every aspect and superior design alternative can process total 340 number of trains per year 15% more than the proposed target within the current average cycle time.

Sustained release of alginate hydrogel containing antimicrobial peptide Chol-37(F34-R) in vitro and its effect on wound healing in murine model of Pseudomonas aeruginosa infection

  • Shuaibing Shi;Hefan Dong;Xiaoyou Chen;Siqi Xu;Yue Song;Meiting Li;Zhiling Yan ;Xiaoli Wang ;Mingfu Niu ;Min Zhang;Chengshui Liao
    • Journal of Veterinary Science
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    • v.24 no.3
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    • pp.44.1-44.17
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    • 2023
  • Background: Antibiotic resistance is a significant public health concern around the globe. Antimicrobial peptides exhibit broad-spectrum and efficient antibacterial activity with an added advantage of low drug resistance. The higher water content and 3D network structure of the hydrogels are beneficial for maintaining antimicrobial peptide activity and help to prevent degradation. The antimicrobial peptide released from hydrogels also hasten the local wound healing by promoting epithelial tissue regeneration and granulation tissue formation. Objective: This study aimed at developing sodium alginate based hydrogel loaded with a novel antimicrobial peptide Chol-37(F34-R) and to investigate the characteristics in vitro and in vivo as an alternative antibacterial wound dressing to treat infectious wounds. Methods: Hydrogels were developed and optimized by varying the concentrations of crosslinkers and subjected to various characterization tests like cross-sectional morphology, swelling index, percent water contents, water retention ratio, drug release and antibacterial activity in vitro, and Pseudomonas aeruginosa infected wound mice model in vivo. Results: The results indicated that the hydrogel C proved superior in terms of cross-sectional morphology having uniformly sized interconnected pores, a good swelling index, with the capacity to retain a higher quantity of water. Furthermore, the optimized hydrogel has been found to exert a significant antimicrobial activity against bacteria and was also found to prevent bacterial infiltration into the wound site due to forming an impermeable barrier between the wound bed and external environment. The optimized hydrogel was found to significantly hasten skin regeneration in animal models when compared to other treatments in addition to strong inhibitory effect on the release of pro-inflammatory cytokines (interleukin-1β and tumor necrosis factor-α). Conclusions: Our results suggest that sodium alginate -based hydrogels loaded with Chol-37(F34-R) hold the potential to be used as an alternative to conventional antibiotics in treating infectious skin wounds.

A Study on the Settlement Prediction of Soft Ground Embankment Using Artificial Neural Network (인공신경망을 이용한 연약지반성토의 침하예측 연구)

  • Kim, Dong-Sik;Chae, Young-Su;Kim, Young-Su;Kim, Hyun-Dong
    • Journal of the Korean Geotechnical Society
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    • v.23 no.7
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    • pp.17-25
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    • 2007
  • Various geotechnical problems due to insufficient bearing capacity or excessive settlement are likely to occur when constructing roads or large complexes on soft ground. Accurate predictions of the magnitude of settlement and the consolidation time provide numerous options of ground improvement methods and, thus, enable to save time and expense of the whole project. Asaoka's method is probably the most frequently used one for settlement prediction and the empirical formulae such as Hyperbolic method and Hoshino's method are also often used. To find an elaborate method of predicting the embankment settlement, two recurrent type neural network models, such as Jordan model and Elman-Jordan model, are adopted. The data sets of settlement measured at several domestic sites are analyzed to obtain the most suitable model structures. It was shown from the comparison between predicted and measured settlements that Jordan model provides better predictions than Elman-Jordan model does and that the predictions using CPT results are more accurate than those using SPT results. It is believed that RNN using cone penetration test results can be a highly efficient tool in predicting settlements if enough field data can be obtained.