• Title/Summary/Keyword: design parameter

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Defect Inspection and Physical-parameter Measurement for Silicon Carbide Large-aperture Optical Satellite Telescope Mirrors Made by the Liquid-silicon Infiltration Method (액상 실리콘 침투법으로 제작된 대구경 위성 망원경용 SiC 반사경의 결함 검사와 물성 계수 측정)

  • Bae, Jong In;Kim, Jeong Won;Lee, Haeng Bok;Kim, Myung-Whun
    • Korean Journal of Optics and Photonics
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    • v.33 no.5
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    • pp.218-229
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    • 2022
  • We have investigated reliable inspection methods for finding the defects generated during the manufacturing process of lightweight, large-aperture satellite telescope mirrors using silicon carbide, and we have measured the basic physical properties of the mirrors. We applied the advanced ceramic material (ACM) method, a combined method using liquid-silicon penetration sintering and chemical vapor deposition for the carbon molded body, to manufacture four SiC mirrors of different sizes and shapes. We have provided the defect standards for the reflectors systematically by classifying the defects according to the size and shape of the mirrors, and have suggested effective nondestructive methods for mirror surface inspection and internal defect detection. In addition, we have analyzed the measurements of 14 physical parameters (including density, modulus of elasticity, specific heat, and heat-transfer coefficient) that are required to design the mirrors and to predict the mechanical and thermal stability of the final products. In particular, we have studied the detailed measurement methods and results for the elastic modulus, thermal expansion coefficient, and flexural strength to improve the reliability of mechanical property tests.

Comparative Evaluation on the Cost Analysis of Software Development Model Based on Weibull Lifetime Distribution (와이블 수명분포에 근거한 소프트웨어 개발모형의 비용 분석에 관한 비교 평가)

  • Bae, Hyo-Jeong
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.3
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    • pp.193-200
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    • 2022
  • In this study, the finite-failure NHPP software reliability model was applied to the software development model based on the Weibull lifetime distribution (Goel-Okumoto, Rayleigh, Type-2 Gumbe), which is widely used in the software reliability field, and then the cost attributes were compared and evaluated. For this study, failure time data detected during normal operation of the software system were collected and used, the most-likelihood estimation (MLE) method was applied to the parameter estimation of the proposed model, and the calculation of the nonlinear equation was solved using the binary method. As a result, first, in the software development model, when the cost of testing per unit time and the cost of removing a single defect increased, the cost increased but the release time did not change, and when the cost of repairing failures detected during normal system operation increased, the cost increased and the release time was also delayed. Second, as a result of comprehensive comparative analysis of the proposed models, it was found that the Type-2 Gumble model was the most efficient model because the development cost was lower and the release time point was relatively faster than the Rayleigh model and the Goel-Okumoto basic model. Third, through this study, the development cost properties of the Weibull distribution model were newly evaluated, and the analyzed data is expected to be utilized as design data that enables software developers to explore the attributes of development cost and release time.

Evaluation of Water Quality Change by Membrane Damage to Pretreatment Process on SDI in Wastewater Reuse (하수재이용에서 전처리 막 손상에 의한 수질변화가 SDI에 미치는 영향평가)

  • Lee, Min Soo;Seo, Dongjoo;Lee, Yong-Soo;Chung, Kun Yong
    • Membrane Journal
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    • v.32 no.4
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    • pp.253-263
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    • 2022
  • This study suggests a guideline for designing unit process of wastewater reuse in terms of a maintenance of the process based on critical parameters to draw a high quality performance of RO unit. Defining the parameters was done by applying membrane integrity test (MIT) in pretreatment process utilizing lab-scale MF. SDI is utilized for judging whether permeate is suitable to RO unit. However, result said TOC concentration matching with particle count analysis is better for judging the permeate condition. When membrane test pressure (Ptest) was measured to derive log removal value in PDT, virgin state of membrane fiber was used to measure dynamic contact angle utilizing surface tension of the membrane fiber. Actually, foulant affects to the state of membrane surface, and it decreases the Ptest value along with time elapsed. Consequently, LRVDIT is also affected by Ptest value. Thus, sensitivity of direct integrity test descends with result of Ptest value change, so Ptest value should be considered not the virgin state of the membrane but its current state. Overall, this study focuses on defining design parameters suitable to MF pretreatment for RO process in wastewater reuse by assessing its impact. Therefore, utilities can acknowledge that the membrane surface condition must be considered when users conduct the direct integrity test so that Ptest and other relative parameter used to calculate LRVDIT are adequately measured.

Damage Analysis of Manganese Crossings for Turnout System of Sleeper Floating Tracks on Urban Transit (도시철도 침목플로팅궤도 분기기 망간크로싱의 손상해석)

  • Choi, Jung-Youl;Yoon, Young-Sun;Ahn, Dae-Hee;Han, Jae-Min;Chung, Jee-Seung
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.5
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    • pp.515-524
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    • 2022
  • The turnout system of the sleeper floating tracks (STEDEF) on urban transit is a Anti-vibration track composed of a wooden sleeper embedded in a concrete bed and a sleeper resilience pad under the sleeper. Therefore, deterioration and changes in spring stiffness of the sleeper resilience pad could be cause changes in sleeper support conditions. The damage amount of manganese crossings that occurred during the current service period of about 21 years was investigated to be about 17% of the total amount of crossings, and it was analyzed that the damage amount increased after 15 years of use (accumulated passing tonnage of about 550 million tons). In this study, parameter analysis (wheel position, sleeper support condition, and dynamic wheel load) was performed using a three-dimensional numerical model that simulated real manganese crossing and wheel profile, to analyze the damage type and cause of manganese crossing that occurred in the actual field. As a result of this study, when the voided sleeper occurred in the sleeper around the nose, the stress generated in the crossing nose exceeded the yield strength according to the dynamic wheel load considering the design track impact factor. In addition, the analysis results were evaluated to be in good agreement with the location of damage that occurred in the actual field. Therefore, in order to minimize the damage of the manganese crossing, it is necessary to keep the sleeper support condition around the nose part constant. In addition, by considering the uniformity of the boundary conditions under the sleepers, it was analyzed that it would be advantageous to to replace the sleeper resilience pad together when replacing the damaged manganese crossing.

Impact of Franchisor Leadership and Franchisee Marketing Efforts on Franchisee Dissatisfaction and Switching Intentions (프랜차이즈 가맹본부 리더십과 가맹점 마케팅 노력이 가맹점 불만족과 전환의도에 미치는 영향)

  • Han, In-Su;Lee, Phil-Soo;Park, Heung-Jin
    • The Korean Journal of Franchise Management
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    • v.7 no.1
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    • pp.31-44
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    • 2016
  • Purpose - This study aims to examine different impacts of franchisor's leadership and franchisee's marketing efforts on franchisee dissatisfaction and switching intentions, and to investigate how franchisee dissatisfaction plays a mediating role in the relationship between these constructs. This study attempted to fill the gap in the literature by treating the franchisee dissatisfaction as a mediator in the relationship between these constructs, identify how franchisor's leadership and franchisee's marketing efforts have effects on franchisee dissatisfaction, in turn, reduce switching intentions, and provide the managerial implications for building a long-term relationship to achieve mutual goals between franchisors and franchisees Research design, data, and methodology - In order to test the hypotheses, the data were collected from franchisees in Seoul and Gyeonggi Province. The franchisee owners were informed about the purpose of this study by the trained interviewers. The respondents received a letter introducing the purpose of this study and another letter that the owners wrote to encourage their active participation. Among the 300 questionnaires distributed, 260 (86.7%) questionnaires were returned. Of those collected questionnaires, 6 uncompleted responses were excluded, and 254 questionnaires with an effective response rate of 84.7% were coded and analyzed using frequency, confirmatory factor analysis, and correlations analysis, and structural equation modeling with SPSS 21.0 and SmartPLS 3.0. Results - The findings of the study are as follows. First, franchisor leadership had a negative effect on franchisee dissatisfaction, but franchisee marketing efforts did not have a significant effect on franchisee dissatisfaction. Second, franchisee dissatisfaction had a positive effect on switching intentions. Third, franchisor leadership had a negative effect on switching intentions, but franchisee marketing efforts did not have a significant effect on switching intentions. Conclusions - This study researched the franchisor's leadership as a single factor of transformational leadership. Thus, it may have limits in measuring leadership. Future studies shall include emotional, loyal, and transactional leadership. In addition, the future studies shall also research the effect of franchisor's leadership and franchisees' marketing efforts on dissatisfaction and switching intentions. For example, the franchisor's relationship-oriented efforts can be a crucial parameter that reduces dissatisfaction and switching intentions.

Predictive Equation of Dynamic Modulus for Hot Mix Asphalt with Granite Aggregates (화강암 골재를 이용한 아스팔트 혼합물의 동탄성 계수 예측방정식)

  • Lee, Kwan-Ho;Kim, Hyun-O;Jang, Min-Seok
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.3D
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    • pp.425-433
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    • 2006
  • The presented work provided a predictive equation for dynamic modulus of hot mix asphalt, which showed higher reliability and more simplicity. Lots of test result by UTM at laboratory has been used to develop the precise predictive equation. Evaluation of dynamic modulus for 13mm and 19mm surface course and 25mm of base course of hot mix asphalt with granite aggregate and two asphalt binders (AP-3 and AP-5) were carried out. Superpave Level 1 Mix Design with gyrator compactor was adopted to determine the optimum asphalt binder content (OAC) and the measured ranges of OAC were between 5.1% and 5.4% for surface HMA, and around 4.2% for base HMA. The dynamic modulus and phase angle were determined by testing on UTM, with 5 different testing temperature (-10, 5, 20, 40, & $55^{\circ}C$) and 5 different loading frequencies (0.05, 0.1, 1, 10, 25 Hz). Using the measured dynamic modulus and phase angle, the input parameters of Sigmoidal function equation to represent the master curve were determined and these will be adopted in FEM analysis for asphalt pavements. The effect of each parameter for equation has been compared. Due to the limitation of laboratory tests, the reliability of predictive equation for dynamic modulus is around 80%.

Seismic Fragility Analysis for Probabilistic Performance Evaluation of PSC Box Girder Bridges (확률론적 내진성능평가를 위한 PSC Box 거더교의 지진취약도 해석)

  • Song, Jong-Keol;Jin, He-Shou;Lee, Tae-Hyung
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.2A
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    • pp.119-130
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    • 2009
  • Seismic fragility curves of a structure represent the probability of exceeding the prescribed structural damage state for a given various levels of ground motion intensity such as peak ground acceleration (PGA), spectral acceleration ($S_a$) and spectral displacement ($S_d$). So those are very essential to evaluate the structural seismic performance and seismic risk. The purpose of this paper is to develop seismic fragility curves for PSC box girder bridges. In order to construct numerical fragility curve of bridge structure using nonlinear time history analysis, a set of ground motions corresponding to design spectrum are artificially generated. Assuming a lognormal distribution, the fragility curve is estimated by using the methodology proposed by Shinozuka et al. PGA is simple and generally used parameter in fragility curve as ground motion intensity. However, the PGA has not good relationship with the inelastic structural behavior. So, $S_a$ and $S_d$ with more direct relationship for structural damage are used in fragility analysis as more useful intensity measures instead of PGA. The numerical fragility curves based on nonlinear time history analysis are compared with those obtained from simple method suggested in HAZUS program.

Optimal Shear Strength Enhancement using Corrugated CFRP Panel for H beam with Slender Web (세장판 복부를 갖는 H형 보의 파형 CFRP 패널을 이용한 최적 전단보강)

  • Ga-Yoon Park;Min-Hyun Seong;Jin-Kook Kim
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.28 no.5
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    • pp.10-19
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    • 2024
  • In this study, FEM analysis was performed with the goal of optimal design of corrugated CFRP panels reinforcing H-shaped beams with slender plate webs. The buckling reinforcement performance of corrugated CFRP panels according to various specifications was evaluated, and in particular, a new reinforcement method was proposed by analyzing the effect of the ratio of vertical reinforcement according to the net height of the abdomen of the H-type beam on the location of the first elastic buckling mode. To minimize the amount of CFRP used, the attachment angle was set to 45 degrees. Furthermore, parameter analysis was performed according to changes in the specifications of the corrugated CFRP panel, and the buckling reinforcement performance of the corrugated CFRP panel was evaluated through the ductility factor. In addition, we attempted to use the material efficiently by simultaneously considering the maximum load and ductility factor along with the volume of the corrugated CFRP panels. It was confirmed that the model with two or three-layer CFRP laminate have a high ductility factor and efficient use of materials, and that the buckling reinforcement performance is predominantly affected by the length and height of the corrugated CFRP panel rather than the width.

Manganese and Iron Interaction: a Mechanism of Manganese-Induced Parkinsonism

  • Zheng, Wei
    • Proceedings of the Korea Environmental Mutagen Society Conference
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    • 2003.10a
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    • pp.34-63
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    • 2003
  • Occupational and environmental exposure to manganese continue to represent a realistic public health problem in both developed and developing countries. Increased utility of MMT as a replacement for lead in gasoline creates a new source of environmental exposure to manganese. It is, therefore, imperative that further attention be directed at molecular neurotoxicology of manganese. A Need for a more complete understanding of manganese functions both in health and disease, and for a better defined role of manganese in iron metabolism is well substantiated. The in-depth studies in this area should provide novel information on the potential public health risk associated with manganese exposure. It will also explore novel mechanism(s) of manganese-induced neurotoxicity from the angle of Mn-Fe interaction at both systemic and cellular levels. More importantly, the result of these studies will offer clues to the etiology of IPD and its associated abnormal iron and energy metabolism. To achieve these goals, however, a number of outstanding questions remain to be resolved. First, one must understand what species of manganese in the biological matrices plays critical role in the induction of neurotoxicity, Mn(II) or Mn(III)? In our own studies with aconitase, Cpx-I, and Cpx-II, manganese was added to the buffers as the divalent salt, i.e., $MnCl_2$. While it is quite reasonable to suggest that the effect on aconitase and/or Cpx-I activites was associated with the divalent species of manganese, the experimental design does not preclude the possibility that a manganese species of higher oxidation state, such as Mn(III), is required for the induction of these effects. The ionic radius of Mn(III) is 65 ppm, which is similar to the ionic size to Fe(III) (65 ppm at the high spin state) in aconitase (Nieboer and Fletcher, 1996; Sneed et al., 1953). Thus it is plausible that the higher oxidation state of manganese optimally fits into the geometric space of aconitase, serving as the active species in this enzymatic reaction. In the current literature, most of the studies on manganese toxicity have used Mn(II) as $MnCl_2$ rather than Mn(III). The obvious advantage of Mn(II) is its good water solubility, which allows effortless preparation in either in vivo or in vitro investigation, whereas almost all of the Mn(III) salt products on the comparison between two valent manganese species nearly infeasible. Thus a more intimate collaboration with physiochemists to develop a better way to study Mn(III) species in biological matrices is pressingly needed. Second, In spite of the special affinity of manganese for mitochondria and its similar chemical properties to iron, there is a sound reason to postulate that manganese may act as an iron surrogate in certain iron-requiring enzymes. It is, therefore, imperative to design the physiochemical studies to determine whether manganese can indeed exchange with iron in proteins, and to understand how manganese interacts with tertiary structure of proteins. The studies on binding properties (such as affinity constant, dissociation parameter, etc.) of manganese and iron to key enzymes associated with iron and energy regulation would add additional information to our knowledge of Mn-Fe neurotoxicity. Third, manganese exposure, either in vivo or in vitro, promotes cellular overload of iron. It is still unclear, however, how exactly manganese interacts with cellular iron regulatory processes and what is the mechanism underlying this cellular iron overload. As discussed above, the binding of IRP-I to TfR mRNA leads to the expression of TfR, thereby increasing cellular iron uptake. The sequence encoding TfR mRNA, in particular IRE fragments, has been well-documented in literature. It is therefore possible to use molecular technique to elaborate whether manganese cytotoxicity influences the mRNA expression of iron regulatory proteins and how manganese exposure alters the binding activity of IPRs to TfR mRNA. Finally, the current manganese investigation has largely focused on the issues ranging from disposition/toxicity study to the characterization of clinical symptoms. Much less has been done regarding the risk assessment of environmenta/occupational exposure. One of the unsolved, pressing puzzles is the lack of reliable biomarker(s) for manganese-induced neurologic lesions in long-term, low-level exposure situation. Lack of such a diagnostic means renders it impossible to assess the human health risk and long-term social impact associated with potentially elevated manganese in environment. The biochemical interaction between manganese and iron, particularly the ensuing subtle changes of certain relevant proteins, provides the opportunity to identify and develop such a specific biomarker for manganese-induced neuronal damage. By learning the molecular mechanism of cytotoxicity, one will be able to find a better way for prediction and treatment of manganese-initiated neurodegenerative diseases.

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Optimization of Support Vector Machines for Financial Forecasting (재무예측을 위한 Support Vector Machine의 최적화)

  • Kim, Kyoung-Jae;Ahn, Hyun-Chul
    • Journal of Intelligence and Information Systems
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    • v.17 no.4
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    • pp.241-254
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    • 2011
  • Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.