• Journal of Engineering Education Research
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• v.20 no.6
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• pp.68-75
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• 2017

This study has a purpose to analyse changes in perception and image about engineering and technology of students who participated in the engineering camp. To achieve this objective, the questions were as follows. 1) What about participants' image difference for engineering before and after participating the engineering camp 2) What about participants' image difference for technology before and after participating the engineering camp. For this study, the program was progressed from Aug in 2017 and the data was collected from 88 students, middle school seniors and high school freshmen. The results of this study were as follows: First, secondary students perceived 'valuable(6.74)', 'meaningful(6.73)', 'rich(6.40)', 'collaborative(6.42)', 'nice(6.22)' as high image rank of the positive response for engineering. On the other hand, 'complex(3.59)', 'labored(3.80)', 'hard(4.66)', 'dangerous(4.48)', 'cold(4.86)' were perceived as low image rank of the negative response for engineering. We can realize that they generally has the image that engineering is valuable, meaningful and nice but also labored, complex and hard. The students who participated in the engineering camp showed the greatest difference in 'complex - simple' and 'dangerous - safe' engineering categories before and after the camp, followed by 'cold - hot', 'labored - easy', and 'hard - soft', respectively. Second, secondary students perceived 'meaningful(6.58)', 'valuable(6.55)', 'wide(6.38)', 'nice(6.37)', 'strong(6.25)' as high image rank of the positive response for technology. On the other hand, 'complex(3.85)', 'labored(3.93)', 'hard(4.62)', 'dangerous(4.72)', 'cold(5.05)' were perceived as low image rank of the negative response for technology. The students who participated in the engineering camp had the big change in 'hard - soft' technology category before and after the camp, followed by 'complex - simple', 'labored - easy', 'theoretical - practical' and 'dangerous - safe', respectively. We can see that the negative images for technology which were complex, labored, dangerous, theoretical was improved with positive image such as simple, easy, safe and practical, after conducting the engineering camp. In conclusion, both image recognitions for engineering and technology have improved after the camp. It means that interesting and entertaining engineering-technology program can boost interests in engineering and technology which felt difficult, so that images about them can be turned out positive. Also, it is possible to reduce avoidance of natural science and engineering subjects, as part of the purpose of training creative talents in science and engineering, so it can be said that the engineering camp is highly meaningful because it can lead students into the field of science and engineering.

• Structural Engineering and Mechanics
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• v.49 no.1
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• pp.111-128
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• 2014

The stochastic response surface method (SRSM) and the response surface method (RSM) are often used for structural reliability analysis, especially for reliability problems with implicit performance functions. This paper aims to compare these two methods in terms of fitting the performance function, accuracy and efficiency in estimating probability of failure as well as statistical moments of system output response. The computational procedures of two response surface methods are briefly introduced first. Then their capabilities are demonstrated and compared in detail through two examples. The results indicate that the probability of failure mainly reflects the accuracy of the response surface function (RSF) fitting the performance function in the vicinity of the design point, while the statistical moments of system output response reflect the accuracy of the RSF fitting the performance function in the entire space. In addition, the performance function can be well fitted by the SRSM with an optimal order polynomial chaos expansion both in the entire physical and in the independent standard normal spaces. However, it can be only well fitted by the RSM in the vicinity of the design point. For reliability problems involving random variables with approximate normal distributions, such as normal, lognormal, and Gumbel Max distributions, both the probability of failure and statistical moments of system output response can be accurately estimated by the SRSM, whereas the RSM can only produce the probability of failure with a reasonable accuracy.

• Journal of Ocean Engineering and Technology
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• v.28 no.4
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• pp.294-305
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• 2014

In offshore structures, fire is one of the most important hazardous events. The concern of fires has recently been reflected in the rules and quantified risk assessment based design practice. Within the framework of quantified risk assessment and the management of offshore installations, therefore, more refined computations of the consequences or hazardous action effects due to fire are required. To mitigate fire risk, passive fire protection(PFP) is widely used on offshore structures. This study presents methods for a nonlinear structural response analysis considering the PFP effects under fires. It is found that a structural response analysis is most likely to use valuable technology for the optimization and design of offshore structures with PFP. Thermal and structural response analyses have been performed using LS-DYNA and FAHTS/USFOS. The results of these structural response analyses are compared with each other.

• Nuclear Engineering and Technology
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• v.38 no.3
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• pp.285-292
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• 2006

Thermoresistant (TR) clones of radiation-induced fibrosarcoma (RIF) cells have been reported to show an adaptive response to 1cGy of low dose radiation, and HSP25 and inducible HSP70 are involved in this process. In this study, to further elucidate the mechanism by which HSP25 and inducible HSP70 regulate the adaptive response, HSP25 or inducible HSP70 overexpressed RIF cells were irradiated with 1cGy and the cell cycle was analyzed. HSP25 or inducible HSP70 overexpressed cells together with TR cells showed increased G1 phase after 1cGy irradiation, while RIF cells did not. $[^3H]-Thymidine$ and BrdU incorporation also indicated that both HSP25 and inducible HSP70 are involved in G1 arrest after 1cGy irradiation. Molecular analysis revealed upregulation of p27Cip/Kip protein in HSP25 and inducible HSP70 overexpressed cells, and cotransfection of p27Cip/Kip antisense abolished the induction of the adaptive response and 1cGy-mediated G1 arrest. The above results indicate that induction of an adaptive response by HSP25 and inducible HSP70 is mediated by upregulation of p27Cip/Kip protein, resulting in low dose radiation-induced G1 arrest.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.2
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• pp.248-255
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• 2013

The objective of this study is to optimize the Metal Injection Molding(MIM) process with design of experiments(DOE) and numerical analysis. To derive the optimal process condition, experiment or numerical analysis was performed under various process conditions. To analyze the interaction among influential factors contributing to the temperature at flow front and response surface in MIM, both central point and axial point were added to the full factorial design with 2 levels and 5 factors and then their impacts on response variable in 43 experimental conditions were analyzed and the significance was evaluated. As a result, sprue, runner, and gate were completely filled in about 0.247 seconds after injection, the front part of the green body was filled in about 0.3344 seconds, the green body except gate, etc changed to almost solid state in about 3.29 seconds, the Packinging pressure was completed in about 6.29 seconds, and the green body inside and outside and sprue, etc became solid in 13.2 seconds. The impact of individual or reciprocal action of factors on the temperature at flow front was analyzed through regular probability, test statistics, main effect, and interaction effect. As a result, of a total of 31 combinations of factors, 9 unit factors and reciprocal actions were significant, and the screening was also possible. A proper regression equation was drawn with regression analysis and response surface design on the response variable of temperature at flow front, and the applicability could be verified.

• Journal of Fisheries and Marine Sciences Education
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• v.24 no.5
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• pp.712-720
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• 2012

Recently, many problems related on shoreline response to spill oil were exposed again on a occasion of M/T Hebei spirit accident even though the weakness on the shoreline response system has been brought up since M/T Sea Prince oil spill accident. Therefore the establishment of shoreline response system that best suits our country is needed through considering the response system of well-developed country. The socioeconomic conflict between the persons concerned on the clean-up endpoints can be sharpened in Korea because the frequency of coastal use of our country is too high compared to other countries. Thus procedural justification, that is, how the clean-up endpoints be established is more important than what type of clean-up endpoints be used. In the present paper, we attempted to suggest a new manner on the decision making system for clean-up endpoints that best suits our country. The decision making system for clean-up endpoints need to be divided into two steps, that is, set-up step of clean-up endpoints criteria and decision step of clean-up endpoints. The decision making organization of local governments play a key role in case of set-up step of clean-up endpoints criteria, while the response command headquarters under Korean coast guard and decision making organization of local governments codecide whether the clean-up endpoints criteria is fits or not.

• IMMUNE NETWORK
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• v.14 no.3
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• pp.128-137
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• 2014

Respiratory viruses can induce acute respiratory disease. Clinical symptoms and manifestations are dependent on interactions between the virus and host immune system. Dendritic cells (DCs), along with alveolar macrophages, constitute the first line of sentinel cells in the innate immune response against respiratory viral infection. DCs play an essential role in regulating the immune response by bridging innate and adaptive immunity. In the steady state, lung DCs can be subdivided into $CD103^+$ conventional DCs (cDCs), $CD11b^+$ cDCs, and plasmacytoid DCs (pDCs). In the inflammatory state, like a respiratory viral infection, monocyte-derived DCs (moDCs) are recruited to the lung. In inflammatory lung, discrimination between moDCs and $CD11b^+$ DCs in the inflamed lung has been a critical challenge in understanding their role in the antiviral response. In particular, $CD103^+$ cDCs migrate from the intraepithelial base to the draining mediastinal lymph nodes to primarily induce the $CD8^+$ T cell response against the invading virus. Lymphoid $CD8{\alpha}^+$ cDCs, which have a developmental relationship with $CD103^+$ cDCs, also play an important role in viral antigen presentation. Moreover, pDCs have been reported to promote an antiviral response by inducing type I interferon production rather than adaptive immunity. However, the role of these cells in respiratory infections remains unclear. These different DC subsets have functional specialization against respiratory viral infection. Under certain viral infection, contextually controlling the balance of these specialized DC subsets is important for an effective immune response and maintenance of homeostasis.

• Wind and Structures
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• v.37 no.3
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• pp.229-243
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• 2023

This study analyzes the response of a tall building with an H-shaped cross-section when subjected to wind loading generated by the same H-shape. As normative standards usually adopt regular geometries for determining the wind loading, this paper shows unpublished results which compares results of the dynamic response of H-shaped buildings with the response of simplified section buildings. Computational Fluid Dynamics (CFD) is employed to determine the steady wind load on the H-shaped building. The CFD models are validated by comparison with wind tunnel test data for the k-ε and k-ω models of turbulence. Transient wind loading is determined using the Synthetic Wind Method. A new methodology is presented that combines Stochastic and CFD methods. In addition, time-history dynamic structural analysis is performed using the HHT method for a period of 60 seconds on finite element models. First, the along-wind response is studied for wind speed variations. The wind speeds of 28, 36, 42, and 50 m/s at 0° case are considered. Subsequently, the dynamic response of the building is studied for wind loads at 0°, 45°, and 90° with a wind speed of 42 m/s, which approximates the point of resonance between gusts of wind and the structure. The response values associated with the first two directions for the H-shaped building are smaller than those for the R-shaped (Equivalent Rectangular Shape) one. However, the displacements of the H-shaped building associated with the latter wind load are larger.

• Korean small business review
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• v.32 no.1
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• pp.65-87
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• 2010

With the advent of knowledge-based society, the revitalization of technological innovation type SMEs, termed "inno-biz" hereafter, has been globally recognized as a government policymakers' primary concern in strengthening national competitiveness, and much effort is being put into establishing polices of boosting the start-ups and innovation capability of SMEs. Especially, in that the inno-biz enables national economy to get vitalized by widening world markets with its superior technology, and thus, taking the initiative of extremely competitive world markets, its growth and development has greater significance. In the case of Korea, the government has been maintaining the policies since the late 1990s of stimulating the growth of SMEs as well as building various infrastructures to foster the start-ups of the SMEs such as venture businesses with high technology. In addition, since the enactment of "Innovation Promotion Law for SMEs" in 2001, the government has been accelerating the policies of prioritizing the growth and development of inno-biz. So, for the sound growth and development of Korean inno-biz, this paper intends to offer effective management strategies for SMEs and suggest proper policies for the government, by researching into the effect of technological innovation capability and technology commercialization capability as the primary business resources on business performance in Korean SMEs in the light of market information orientation. The research is carried out on Korean companies characterized as inno-biz. On the basis of OSLO manual and prior studies, the research categorizes their status. R&D capability, technology accumulation capability and technological innovation system are categorized into technological innovation capability; product development capability, manufacturing capability and marketing capability into technology commercialization capability; and increase in product competitiveness and merits for new technology and/or product development into business performance. Then the effect of each component on business performance is substantially analyzed. In addition, the mediation effect of technological innovation and technology commercialization capability on business performance is observed by the use of the market information orientation as a parameter. The following hypotheses are proposed. H1 : Technology innovation capability will positively influence business performance. H1-1 : R&D capability will positively influence product competitiveness. H1-2 : R&D capability will positively influence merits for new technology and/or product development into business performance. H1-3 : Technology accumulation capability will positively influence product competitiveness. H1-4 : Technology accumulation capability will positively influence merits for new technology and/or product development into business performance. H1-5 : Technological innovation system will positively influence product competitiveness. H1-6 : Technological innovation system will positively influence merits for new technology and/or product development into business performance. H2 : Technology commercializing capability will positively influence business performance. H2-1 : Product development capability will positively influence product competitiveness. H2-2 : Product development capability will positively influence merits for new technology and/or product development into business performance. H2-3 : Manufacturing capability will positively influence product competitiveness. H2-4 : Manufacturing capability will positively influence merits for new technology and/or product development into business performance. H2-5 : Marketing capability will positively influence product competitiveness. H2-6 : Marketing capability will positively influence merits for new technology and/or product development into business performance. H3 : Technology innovation capability will positively influence market information orientation. H3-1 : R&D capability will positively influence information generation. H3-2 : R&D capability will positively influence information diffusion. H3-3 : R&D capability will positively influence information response. H3-4 : Technology accumulation capability will positively influence information generation. H3-5 : Technology accumulation capability will positively influence information diffusion. H3-6 : Technology accumulation capability will positively influence information response. H3-7 : Technological innovation system will positively influence information generation. H3-8 : Technological innovation system will positively influence information diffusion. H3-9 : Technological innovation system will positively influence information response. H4 : Technology commercialization capability will positively influence market information orientation. H4-1 : Product development capability will positively influence information generation. H4-2 : Product development capability will positively influence information diffusion. H4-3 : Product development capability will positively influence information response. H4-4 : Manufacturing capability will positively influence information generation. H4-5 : Manufacturing capability will positively influence information diffusion. H4-6 : Manufacturing capability will positively influence information response. H4-7 : Marketing capability will positively influence information generation. H4-8 : Marketing capability will positively influence information diffusion. H4-9 : Marketing capability will positively influence information response. H5 : Market information orientation will positively influence business performance. H5-1 : Information generation will positively influence product competitiveness. H5-2 : Information generation will positively influence merits for new technology and/or product development into business performance. H5-3 : Information diffusion will positively influence product competitiveness. H5-4 : Information diffusion will positively influence merits for new technology and/or product development into business performance. H5-5 : Information response will positively influence product competitiveness. H5-6 : Information response will positively influence merits for new technology and/or product development into business performance. H6 : Market information orientation will mediate the relationship between technology innovation capability and business performance. H7 : Market information orientation will mediate the relationship between technology commercializing capability and business performance. The followings are the research results : First, as for the effect of technological innovation on business performance, the technology accumulation capability and technological innovating system have a positive effect on increase in product competitiveness and merits for new technology and/or product development, while R&D capability has little effect on business performance. Second, as for the effect of technology commercialization capability on business performance, the effect of manufacturing capability is relatively greater than that of merits for new technology and/or product development. Third, the mediation effect of market information orientation is identified to exist partially in information generation, information diffusion and information response. Judging from these results, the following analysis can be made : On Increase in product competitiveness, directly related to successful technology commercialization of technology, management capability including technological innovation system, manufacturing capability and marketing capability has a relatively strong effect. On merits for new technology and/or product development, on the other hand, capability in technological aspect including R&D capability, technology accumulation capability and product development capability has relatively strong effect. Besides, in the cast of market information orientation, the level of information diffusion within an organization plays and important role in new technology and/or product development. Also, for commercial success like increase in product competitiveness, the level of information response is primarily required. Accordingly, the following policies are suggested : First, as the effect of technological innovation capability and technology commercialization capability on business performance differs among SMEs; in order for SMEs to secure competitiveness, the government has to establish microscopic policies for SMEs which meet their needs and characteristics. Especially, the SMEs lacking in capital and labor are required to map out management strategies of focusing their resources primarily on their strengths. And the government needs to set up policies for SMEs, not from its macro-scaled standpoint, but from the selective and concentrative one that meets the needs and characteristics of respective SMEs. Second, systematic infrastructures are urgently required which lead technological success to commercial success. Namely, as technological merits at respective SME levels do not always guarantee commercial success, the government should make and effort to build systematic infrastructures including encouragement of M&A or technology trade, systematic support for protecting intellectual property, furtherance of business incubating and industrial clusters for strengthening academic-industrial network, and revitalization of technology financing, in order to make successful commercialization from technological success. Finally, the effort to innovate technology, R&D, for example, is essential to future national competitiveness, but its result is often prolonged. So the government needs continuous concern and funding for basic science, in order to maximize technological innovation capability. Indeed the government needs to examine continuously whether technological innovation capability or technological success leads satisfactorily to commercial success in market economic system. It is because, when the transition fails, it should be left to the government.

• Journal of Microbiology and Biotechnology
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• v.17 no.9
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• pp.1437-1444
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• 2007

A response surface model was developed for predicting the growth rates of Staphylococcus aureus in tryptic soy broth (TSB) medium as a function of combined effects of temperature, pH, and NaCl. The TSB containing six different concentrations of NaCl (0, 2, 4, 6, 8, and 10%) was adjusted to an initial of six different pH levels (pH 4, 5, 6, 7, 8, 9, and 10) and incubated at 10, 20, 30, and $40^{\circ}C$. In all experimental variables, the primary growth curves were well ($r^2=0.9000$ to 0.9975) fitted to a Gompertz equation to obtain growth rates. The secondary response surface model for natural logarithm transformations of growth rates as a function of combined effects of temperature, pH, and NaCl was obtained by SAS's general linear analysis. The predicted growth rates of the S. aureus were generally decreased by basic (pH 9-10) or acidic (pH 5-6) conditions and higher NaCl concentrations. The response surface model was identified as an appropriate secondary model for growth rates on the basis of correlation coefficient (r=0.9703), determination coefficient ($r^2=0.9415$), mean square error (MSE=0.0185), bias factor ($B_f=1.0216$), and accuracy factor ($A_f=1.2583$). Therefore, the developed secondary model proved reliable for predictions of the combined effect of temperature, NaCl, and pH on growth rates for S. aureus in TSB medium.