• Asian-Australasian Journal of Animal Sciences
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• v.31 no.12
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• pp.1963-1973
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• 2018

Objective: This study was conducted to evaluate the effect of dietary energy and lipase supplementation on growth performance, nutrient digestibility, serum profiles, intestinal morphology, small intestinal digestive enzyme activities, biochemical index of intestinal development and noxious gas emission in weaning pigs. Methods: A total of 240 weaning pigs ([Yorkshire${\times}$Landrace]${\times}$Duroc) with an average body weight (BW) of $7.3{\pm}0.12kg$ were used in this 28-d experiment. Weaning pigs were randomly allocated to 4 dietary treatments in a $2{\times}2$ factorial arrangement with 2 levels of energy (net energy = 2,470 kcal/kg for low energy diet and 2,545 kcal/kg for basal diet) and 2 levels of lipase (0 and 1.5 U/g of lipase) according to BW and sex. There were 6 replications (pens) per treatment and 10 pigs per pen (5 barrows and 5 gilts). Results: Weaning pigs fed the low energy diet had lower (p<0.05) gain-to-feed ratio (G:F) throughout the experiment, apparent digestibility of dry matter, nitrogen, ether extract, and gross energy during d 0 to 14, average daily gain during d 15 to 28, lipase activity in duodenum and ileum and protein/DNA in jejunum (p<0.05), respectively. Lipase supplementation had no effect on growth performance but affected apparent nutrient digestibility (p<0.05) on d 14 and enhanced lipase activity in the duodenum and ileum and protease activity in duodenum and jejunum of pigs (p<0.05) fed the low energy diet. Lipase reduced serum low-density lipoprotein cholesterol (LDL-C) and triglyceride (TG), $NH_3$ production (p<0.05) from the feces. Conclusion: The low energy diet decreased G:F throughout the experiment and nutrient digestibility during d 0 to 14 as well as lipase activity in duodenum and ileum. Lipase supplementation increased nutrient digestibility during d 0 to 14 and exerted beneficial effects on lipase activity in duodenum and ileum as well as protease activity in duodenum and jejunum, while reduced serum LDL-C, TG and fecal $NH_3$.

• Korean Journal of Clinical Laboratory Science
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• v.52 no.1
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• pp.1-17
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• 2020

Three-dimensional microscopic approaches in histopathology display multiplex properties that present puzzling questions for specimens as related to their comprehensive volumetric information. This information includes spatial distribution of molecules, three-dimensional co-localization, structural formation and whole data set that cannot be determined by two-dimensional section slides due to the inevitable loss of spatial information. Advancement of optical instruments such as two-photon microscopy and high performance objectives with motorized correction collars have narrowed the gap between optical theories and the actual reality of deep tissue imaging. However, the benefits gained by a prolonged working distance, two-photon laser and optimized beam alignment are inevitably diminished because of the light scattering phenomenon that is deeply related to the refractive index mismatch between each cellular component and the surrounding medium. From the first approaches with simple crude refractive index matching techniques to the recent cutting-edge integrated tissue clearing methods, an achievement of transparency without morphological denaturation and eradication of natural and fixation-induced nonspecific autofluorescence out of real signal are key factors to determine the perfection of tissue clearing and the immunofluorescent staining for high contrast images. When performing integrated laboratory workflow of tissue for processing frozen and formalin-fixed tissues, clear lipid-exchanged acrylamide-hybridized rigid imaging/immunostaining/in situ hybridization-compatible tissue hydrogel (CLARITY), an equipment-based tissue clearing method, is compatible with routine procedures in a histopathology laboratory.

• Journal of Korea Technology Innovation Society
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• v.10 no.2
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• pp.284-309
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• 2007

Technology transfer (TT) consortium is an affiliation of two or more public research institutions (PRIs) that participate in a common technology transfer activity or pool their resources together, with the objective of facilitating technology transfer. Based on empirical analysis of five regional TT consortia (2002-2006) operating in Korea, this paper suggests their effectiveness by employing a TT performance index (TTPI) and identifies possible characteristics involved, such as motivations, facilitators, barriers, and challenges. TTPI devised in the paper is a new composite TT performance index to measure how much the TT performance of a PH changed in a designated year compared to a base year. All the performance indicators of TTPI are well-structured based on the unique TT process that is prevalent in Korea. Further, TTPI can bring different size and focus of PRIs to the same scale for comparison by double-normalizing. The paper tests the effectiveness of TT consortium for the escalation of TT performances in member PRIs by highlighting the differences of TTPI's between 2005 and 2001. As a result, the paper found that the escalation of TTPI for member PRIs was greater than that for non-member PRIs. As for the characteristics of TT consortia, their respective factors obtained by TT expert survey were computed with proportion tests of differences (Z tests) to compare two perspectives between intramural and extramural groups. One of key findings is that there is general homogeneity in stakeholder perspectives regarding motivations, facilitators, barriers, and challenges. Some notable responses are as follow; the most probable motivation to join TT consortium is to share or exchange TT competences for enhanced performance. Second, the most probable facilitator is professional capability of consortium-hired personnel. Third, the foremost probable barriers to effective TT consortium are frequent change of consortium director and passive participation of member PRIs. Lastly, both publicizing TT consortia and developing performance metrics are the most important for the improvement of TT consortia. The understanding of the characteristics of TT consortia increases the likelihood of accelerated success, because TT consortia path from formation to termination encompasses many concepts, processes, principles, and factors. Finally, an analysis of the survey data combined with expert interview and observation data led the authors to derive five conditions as being critical to viable TT consortia in Korea at early stage of technology transfer systems. These conditions include policy infrastructure, proactive participation, excellent professionals, personal motivation, and teaming mechanisms. It is expected that the Korean evidence is a starting point to develop and refine the theory of TT consortia and for additional studies in other countries.

• Tuberculosis and Respiratory Diseases
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• v.43 no.4
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• pp.547-557
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• 1996

Background : An excessive accumulation of neutrophils in lung tissue has been known to play an important role in mediating the tissue injury among the adult respiratory distress syndrome, idiopathic pulmonary fibrosis and cystic fibrosis by releasing toxic oxygen radicals and proteolytic enzymes. Therefore, it is important to understand a possible mechanism of neutrophil accumulation in lung tissue. In many species, exposure to hyperoxic stimuli can cause changes of lung tissues very similar to human adult respiratory distress syndrome and neutrophils are also functioning as the main effector cells in hyperoxic lung injury. The purpose of the present study was to examine whether neutrophils function as a key effector cell and to study the nature of possible neutrophil chemotactic factors found in bronchoalveolar lavage fluid from the hyperoxia exposed rats. Methods : We exposed the rats to the more than 95% oxygen for 24, 48, 60 arid 72 hours and bronchoalveolar lavage(BAL) was performed. Neutrophil chemotactic activity was measured from the BAT- fluid of each experimental groups. We also evaluated the molecular weight of neutrophil chemotactic tractors using fast performance liquid chromatography and characterized the substances by dialyzer membrane and heat treatment. Results : 1) The neutrophil proportions in bronchoalveolar lavage fluid began to rise from 48 hours after oxygen exposure, and continued to be significantly increased with exposure times. 2) chemotactic index for neutrophils in lung lavages from rats exposed to hyperoxia was significantly higher in 48 hours group than in control group, and was significantly increased with exposure time. 3) No deaths occured until after 48 hours of exposure. However, mortality rates were increased to 33.3 % in 60 hours group and 81.3 % in 72 fours group. 4) Gel filtration using fast performance liquid chromatography disclosed two peaks of neutrophil chemotactic activity in molecular weight of 104,000 and 12,000 daltons. 5) Chemotactic indices of bronchoalveolar lavage fluid were significantly deceased when bronchoalveolar lavage fluid was treated with heat ($56^{\circ}C$ for 30 min or $100^{\circ}C$ for 10 min) or dialyzed (dialyzer membrane molecular weight cut off : 12,000 daltons). Conclusion : These results suggested that the generation of neutrophil chemotactic factor and subsequent neutrophil influx into the lungs are playing an important roles in hyperoxia-induced acute lung injury. Neutrophil chemotactic factor in the lung lavage fluids consisted of several distinct components having different molecular weight and different physical characteristics.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.6
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• pp.9-21
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• 2003

In this paper, we propose a new submesh allocation scheme which improves the performance of multicomputer systems. The key idea of this allocation scheme is to reduce waiting time of task by minimizing the submesh search time and the submesh a]location delay caused by external fragmentation. This scheme reduces the submesh search time by classifying independent free submeshes according to their types (square, horizontal rectangle, vertical rectangle) and searching a best-fit submesh from the classified free submesh list. If a submesh allocation delay occurs due to external fragmentation, the proposed scheme relocates tasks, executing In allocated submeshes, to another free submeshes and compacts processor fragmentation. This results in reducing the submesh allocation delay. Through simulation, we show that it is more effective to reduce the submesh allocation delay due to external fragmentation than reducing the submesh search time with respect to the waiting time of task. We also show that the proposed strategy improves the performance compared to previous strategies.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.653-662
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• 2011

Land surface temperature (LST) is a one of the key variables of land surface which can be estimated from geostationary meteorological satellite. In this study, we have developed the three sets of LST retrieval algorithm from MTSAT-2 data through the radiative transfer simulations under various atmospheric profiles (TIGR data), satellite zenith angle, spectral emissivity, and surface lapse rate conditions using MODTRAN 4. The three LST algorithms are daytime, nighttime and total LST algorithms. The weighting method based on the solar zenith angle is developed for the consistent retrieval of LST at the early morning and evening time. The spectral emissivity of two thermal infrared channels is estimated by using vegetation coverage method with land cover map and 15-day normalized vegetation index data. In general, the three LST algorithms well estimated the LST without regard to the satellite zenith angle, water vapour amount, and surface lapse rate. However, the daytime LST algorithm shows a large bias especially for the warm LST (> 300 K) at day time conditions. The night LST algorithm shows a relatively large error for the LST (260 ~ 280K) at the night time conditions. The sensitivity analysis showed that the performance of weighting method is clearly improved regardless of the impacting conditions although the improvements of the weighted LST compared to the total LST are quite different according to the atmospheric and surface lapse rate conditions. The validation results of daytime (nighttime) LST with MODIS LST showed that the correlation coefficients, bias and RMSE are about 0.62~0.93 (0.44~0.83), -1.47~1.53 (-1.80~0.17), and 2.25~4.77 (2.15~4.27), respectively. However, the performance of daytime/nighttime LST algorithms is slightly degraded compared to that of the total LST algorithm.

• 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.

• Geomechanics and Engineering
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• v.37 no.5
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• pp.475-498
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• 2024

The prediction of the susceptibility of soil to liquefaction using a limited set of parameters, particularly when dealing with highly unbalanced databases is a challenging problem. The current study focuses on different ensemble learning classification algorithms using highly unbalanced databases of results from in-situ tests; standard penetration test (SPT), shear wave velocity (V_s) test, and cone penetration test (CPT). The input parameters for these datasets consist of earthquake intensity parameters, strong ground motion parameters, and in-situ soil testing parameters. liquefaction index serving as the binary output parameter. After a rigorous comparison with existing literature, extreme gradient boosting (XGBoost), bagging, and random forest (RF) emerge as the most efficient models for liquefaction instance classification across different datasets. Notably, for SPT and V_s-based models, XGBoost exhibits superior performance, followed by Light gradient boosting machine (LightGBM) and Bagging, while for CPT-based models, Bagging ranks highest, followed by Gradient boosting and random forest, with CPT-based models demonstrating lower G_mean(error), rendering them preferable for soil liquefaction susceptibility prediction. Key parameters influencing model performance include internal friction angle of soil (ϕ) and percentage of fines less than 75 µ (F₇₅) for SPT and V_s data and normalized average cone tip resistance (q_c) and peak horizontal ground acceleration (a_max) for CPT data. It was also observed that the addition of V_s measurement to SPT data increased the efficiency of the prediction in comparison to only SPT data. Furthermore, to enhance usability, a graphical user interface (GUI) for seamless classification operations based on provided input parameters was proposed.

• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2595-2609
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• 2024

This paper introduces a base isolation system-tuned mass damper inerter (BIS-TMDI) hybrid system to the AP1000 nuclear power plant (NPP), which reduces seismic damage potential of the NPP structure. The effects of fluid-structure interaction (FSI) caused by the passive containment cooling system water storage tank (PCCWST) on NPP's seismic performance are investigated. The FSI of water tank theoretical model is considered based on the Housner's model, and a series of time history analyses are performed to prove the rationality of the proposed model. Three single-objective optimization strategies are employed to minimize the relative displacement variance and absolute acceleration variance of the upper structure, as well as the filtered energy index (FEI). Furthermore, a multi-objective optimization strategy considering all these three indexes is proposed to obtain optimal parameters of vibration control. The influence of vibration control strategies on the relative deformation and acceleration of the upper structure is explored with various water level ratios. The analytical results indicate that the proposed BIS-TMDI strategy has significantly reduced the NPP structure's seismic response. The effectiveness of the vibration control strategy is influenced by the water level ratio, emphasizing the significance of designing an appropriate water level ratio to reduce NPP structure's seismic response.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.163-179
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• 2010

Recentlythe concept of fast fashion is drawing attention as customer needs are diversified and supply lead time is getting shorter in fashion industry. It is emphasized as one of the critical success factors in the fashion industry how quickly and efficiently to satisfy the customer needs as the competition has intensified. Because the fast fashion is inherently susceptible to trend, it is very important for fashion retailers to make quick decisions regarding items to launch, quantity based on demand prediction, and the time to respond. Also the planning decisions must be executed through the business processes of procurement, production, and logistics in real time. In order to adapt to this trend, the fashion industry urgently needs supports from intelligent quick response(QR) system. However, the traditional functions of QR systems have not been able to completely satisfy such demands of the fast fashion industry. This paper proposes an intelligent quick response system for the fast fashion(IQRS-FF). Presented are models for QR process, QR principles and execution, and QR quantity and timing computation. IQRS-FF models support the decision makers by providing useful information with automated and rule-based algorithms. If the predefined conditions of a rule are satisfied, the actions defined in the rule are automatically taken or informed to the decision makers. In IQRS-FF, QRdecisions are made in two stages: pre-season and in-season. In pre-season, firstly master demand prediction is performed based on the macro level analysis such as local and global economy, fashion trends and competitors. The prediction proceeds to the master production and procurement planning. Checking availability and delivery of materials for production, decision makers must make reservations or request procurements. For the outsourcing materials, they must check the availability and capacity of partners. By the master plans, the performance of the QR during the in-season is greatly enhanced and the decision to select the QR items is made fully considering the availability of materials in warehouse as well as partners' capacity. During in-season, the decision makers must find the right time to QR as the actual sales occur in stores. Then they are to decide items to QRbased not only on the qualitative criteria such as opinions from sales persons but also on the quantitative criteria such as sales volume, the recent sales trend, inventory level, the remaining period, the forecast for the remaining period, and competitors' performance. To calculate QR quantity in IQRS-FF, two calculation methods are designed: QR Index based calculation and attribute similarity based calculation using demographic cluster. In the early period of a new season, the attribute similarity based QR amount calculation is better used because there are not enough historical sales data. By analyzing sales trends of the categories or items that have similar attributes, QR quantity can be computed. On the other hand, in case of having enough information to analyze the sales trends or forecasting, the QR Index based calculation method can be used. Having defined the models for decision making for QR, we design KPIs(Key Performance Indicators) to test the reliability of the models in critical decision makings: the difference of sales volumebetween QR items and non-QR items; the accuracy rate of QR the lead-time spent on QR decision-making. To verify the effectiveness and practicality of the proposed models, a case study has been performed for a representative fashion company which recently developed and launched the IQRS-FF. The case study shows that the average sales rateof QR items increased by 15%, the differences in sales rate between QR items and non-QR items increased by 10%, the QR accuracy was 70%, the lead time for QR dramatically decreased from 120 hours to 8 hours.