Effect of Peeling Blades and Abrasives on Mechanical Peeling of Cynanchum wilfordii Hemsley (박피(剝皮)날 및 연마재(硏磨材)가 백하수오(白何首烏) 기계박피(機械剝皮)에 미치는 영향(影響))
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- Korean Journal of Acupuncture
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- v.18 no.1
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- pp.165-170
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- 2001
A rapid increasing in cultivation area due to favorable price temporarily and decreasing in consumer's demands caused by economic depressions recently, lead the price of Cynanchum wilfordii Hemsley to decline sharply. Thus, it may give rises to weakening of cultivation bases in Cynanchum wilfordii Hemsley. To investigate optimal mechanical peeling conditions of Cynanchum wilfordii Hemsley, protruded rubber, plastic pad, diamond shape's steel and palstic brush were introduced as blades and artificial stone, sand and small pebble were done as abrasives. The main results obtained were summarized as follows; 1. It took 2 minutes per 1kg in mechanical peeling of Cynanchum wilfordii Hemsley's raw root whereas 36 minutes in manual peeling and values of lightness showed more higher in manual peeling than in mechanical peeling. 2. Yield in combination of diamond shape's steel blade and sand abrasive showed the lowest at 89.9% among treatments and peeling rates in combination of diamond shape's steel blade and small pebble showed the highest at 71.3% in mechanical peeling. 3. Lightness, one of the most important factors in determining quality of Cynanchum wilfordii Hemsley, showed the highest in combination of diamond shape's steel blade and small pebble brasive at 61.90 in mechanical peeling. 4. As the speed of rotation gets faster, yields tend to lower in mechanical peeling. Peeling rates and lightness showed the highest at 66.8%, 57.96 respectively among treatments at 30 r.p.m. in mechanical peeling.
It is very important to forecast freight volume accurately to establish major port policies and future operation plans. Thus, related studies are being conducted because of this importance. In this paper, stepwise regression analysis and artificial neural network model were analyzed to compare the predictive power of each model on Gwangyang Port, the largest domestic port for coal and iron ore transportation. Data of a total of 121 months J anuary 2009-J anuary 2019 were used. Factors affecting coal and iron ore trade volume were selected and classified into supply-related factors and market/economy-related factors. In the stepwise regression analysis, the tonnage of ships entering the port, coal price, and dollar exchange rate were selected as the final variables in case of the Gwangyang Port coal volume forecasting model. In the iron ore volume forecasting model, the tonnage of ships entering the port and the price of iron ore were selected as the final variables. In the analysis using the artificial neural network model, trial-and-error method that various Hyper-parameters affecting the performance of the model were selected to identify the most optimal model used. The analysis results showed that the artificial neural network model had better predictive performance than the stepwise regression analysis. The model which showed the most excellent performance was the Gwangyang Port Coal Volume Forecasting Artificial Neural Network Model. In comparing forecasted values by various predictive models and actually measured values, the artificial neural network model showed closer values to the actual highest point and the lowest point than the stepwise regression analysis.
This study analyzed the risk spillover of BDI on shipping company stock prices through the Copula-CoVaR method based on daily data from January 4, 2010, to October 31, 2022. The main empirical analysis results and policy implications are as follows. First, copula results showed that there was a weak dependence between BDI and shipping company stock prices, and PAN, KOR, and YEN were selected as the most fitting model for dynamic Student-t copula, HMM was selected as the rotated Gumbel copula, and KSS was selected as the best model. Second, in the results of CoVaR, it was confirmed that the upside (downside) CoVaR was significantly different from the upside (downside) VaR in all shipping companies. This means that BDI has a significant risk spillover on shipping companies. In addition, as for the risk spillover, the downside risk is generally lower than the upside risk, so the downside and upside risk spillover were found to be asymmetrical. Therefore, policymakers should strengthen external risk supervision and establish differentiated policies suitable for domestic conditions to prevent systematic risks from BDI shocks. And investors should reflect external risks from BDI fluctuations in their investment decisions and construct optimal investment portfolios to avoid risks. On the other hand, investors propose that the investment portfolio should be adjusted in consideration of the asymmetric characteristics of up and down risks when making investment decisions.
Brand switching data frequently used in market structure analysis is adequate to analyze non- durable goods, because it can capture competition between specific two brands. But brand switching data sometimes can not be used to analyze goods like automobiles having long term duration because one of main assumptions that consumer preference toward brand attributes is not changed against time can be violated. Therefore a new type of data which can precisely capture competition among durable goods is needed. Another problem of using brand switching data collected from actual purchase behavior is short of explanation why consumers consider different set of brands. Considering above problems, main purpose of this study is to analyze market structure for durable goods with consideration set. The author uses exploratory approach and latent class clustering to identify market structure based on heterogeneous consideration set among consumers. Then the relationship between some factors and consideration set formation is analyzed. Some benefits and two demographic variables - age and income - are selected as factors based on consumer behavior theory. The author analyzed USA automotive market with top 11 brands using exploratory approach and latent class clustering. 2,500 respondents are randomly selected from the total sample and used for analysis. Six models concerning market structure are established to test. Model 1 means non-structured market and model 6 means market structure composed of six sub-markets. It is exploratory approach because any hypothetical market structure is not defined. The result showed that model 1 is insufficient to fit data. It implies that USA automotive market is a structured market. Model 3 with three market structures is significant and identified as the optimal market structure in USA automotive market. Three sub markets are named as USA brands, Asian Brands, and European Brands. And it implies that country of origin effect may exist in USA automotive market. Comparison between modal classification by derived market structures and probabilistic classification by research model was conducted to test how model 3 can correctly classify respondents. The model classify 97% of respondents exactly. The result of this study is different from those of previous research. Previous research used confirmatory approach. Car type and price were chosen as criteria for market structuring and car type-price structure was revealed as the optimal structure for USA automotive market. But this research used exploratory approach without hypothetical market structures. It is not concluded yet which approach is superior. For confirmatory approach, hypothetical market structures should be established exhaustively, because the optimal market structure is selected among hypothetical structures. On the other hand, exploratory approach has a potential problem that validity for derived optimal market structure is somewhat difficult to verify. There also exist market boundary difference between this research and previous research. While previous research analyzed seven car brands, this research analyzed eleven car brands. Both researches seemed to represent entire car market, because cumulative market shares for analyzed brands exceeds 50%. But market boundary difference might affect the different results. Though both researches showed different results, it is obvious that country of origin effect among brands should be considered as important criteria to analyze USA automotive market structure. This research tried to explain heterogeneity of consideration sets among consumers using benefits and two demographic factors, sex and income. Benefit works as a key variable for consumer decision process, and also works as an important criterion in market segmentation. Three factors - trust/safety, image/fun to drive, and economy - are identified among nine benefit related measure. Then the relationship between market structures and independent variables is analyzed using multinomial regression. Independent variables are three benefit factors and two demographic factors. The result showed that all independent variables can be used to explain why there exist different market structures in USA automotive market. For example, a male consumer who perceives all benefits important and has lower income tends to consider domestic brands more than European brands. And the result also showed benefits, sex, and income have an effect to consideration set formation. Though it is generally perceived that a consumer who has higher income is likely to purchase a high priced car, it is notable that American consumers perceived benefits of domestic brands much positive regardless of income. Male consumers especially showed higher loyalty for domestic brands. Managerial implications of this research are as follow. Though implication may be confined to the USA automotive market, the effect of sex on automotive buying behavior should be analyzed. The automotive market is traditionally conceived as male consumers oriented market. But the proportion of female consumers has grown over the years in the automotive market. It is natural outcome that Volvo and Hyundai motors recently developed new cars which are targeted for women market. Secondly, the model used in this research can be applied easier than that of previous researches. Exploratory approach has many advantages except difficulty to apply for practice, because it tends to accompany with complicated model and to require various types of data. The data needed for the model in this research are a few items such as purchased brands, consideration set, some benefits, and some demographic factors and easy to collect from consumers.
Internet commerce has been growing at a rapid pace for the last decade. Many firms try to reach wider consumer markets by adding the Internet channel to the existing traditional channels. Despite the various benefits of the Internet channel, a significant number of firms failed in managing the new type of channel. Previous studies could not cleary explain these conflicting results associated with the Internet channel. One of the major reasons is most of the previous studies conducted analyses under a specific market condition and claimed that as the impact of Internet channel introduction. Therefore, their results are strongly influenced by the specific market settings. However, firms face various market conditions in the real worlddensity and disutility of using the Internet. The purpose of this study is to investigate the impact of various market environments on a firm's optimal channel strategy by employing a flexible game theory model. We capture various market conditions with consumer density and disutility of using the Internet.
From the economic point of view the fishing port is the complex of installations on land, organized to serve the fishing fleet and its cargo, and is the main link in the production chain of all components of the fishing industry, with the aim of achieving the planned targets with the minimum cost. Fishing port investment decisions have had significant impact on the development aims of Korean fisheries. Fishing port investments in Korea are made mostly by public or semipublic port authorities. Such investments should be judged not purely on the basis of financial profitability but rather on the extent to which they serve the development aims of the fishing industry. This makes the economic appraisal process more complex and presents certain problems in correctly quantifying the economic costs and benefits of the fishing port projects. This study concentrates more on the theoretical economic appraisal models than on the purely financial aspects of fishing port investments and points out the difference between the two approaches. In the result, there is clearly an element of judgment as to whether or not a shadow price needs to be used in estimating economic benefits and costs. From this viewpoint, some attempts are made to provide definitions of the possible economic benefits and costs, and methods for estimating and evaluating them in Part III and IV. Especially queueing theory is applied in the calculation of economic benefits. When a project is contemplated and analysis shows it to Lave a positive NPV, one question that arises is whether it should be implemented now or delayed. In this paper, the first year rate of return method is regarded as a more concise way of solving the timing of investment, At the end of Part IV, risk analysis of fishing port investments is considered. It can be handled in a number of ways, ranging from informal judgment to complex statistical analyses involving large-scale computer models, This paper recommends that evaluators of fishing port investments use the sensitivity analysis indicating exactly how much NPV will change in response to a given change in an input variable, other things held constant. Decisions regarding the amount of capacity to provide must be made in fishing port investments. Providing too much service would involve excessive capital costs. On the other hand, not providing enough service capacity would cause the waiting line of fishing vessels to become excessively long at times. Therefore, in Part V, the optimal number of berths and berth productivity in fishing port are defined as follows: Minimize E(TC) ＝ E(WC)＋E(SC) The minimum of this function is the solution and that is the optimal number of berth and berth productivity in fishing port.
The wine industry requires practical methods for objectively measuring the composition of both red wine grapes on the vine to determine optimal harvest time; and of freshly harvested grapes for efficient allocation to vinery process streams for particular red wine products, and to determine payment of contract grapegrowers. To be practical for industry application these methods must be rapid, inexpensive and accurate. In most cases this restricts the analyses available to measurement of TSS (total soluble solids, predominantly sugars) by refractometry and pH by electropotentiometry. These two parameters, however, do not provide a comprehensive compositional characterization for the purpose of winemaking. The concentration of anthocyanin pigment in red wine grapes is an accepted indicator of potential wine quality and price. However, routine analysis for total anthocyanins is not considered as a practical option by the wider wine industry because of the high cost and slow turnaround time of this multi-step wet chemical laboratory analysis. Recent work by this
The interest in biodiesel is increasing rapidly. As a result, the price of vegetable oil that is used as a raw material for biodiesel is skyrocketing. Studies of biodiesel using animal waste as a means of solving these problems are underway. Biodiesel produced from animal fat contains considerably more saturated fatty acids than that produced from vegetable oil. In addition, it has a high cetane number and a high heating value. On the other hand, the fluidity decreases at lower temperatures because of the large amount of saturated fatty acids. For the biodiesel production, waste chicken oil and soybean oil were first purified. The raw materials were mixed at various ratios from 1:9 to 9:1. The methanol / oil molar ratio was also changed from 7 mol to 15 mol. The entire reaction time was one hour. The results showed that the optimal mixing ratio of soybean oil to waste chicken oil was 3:7, and the optimal methanol / oil molar ratio was 13. Moreover, the BD yield was 90.2%, the FAME content was 96.6%, and the LAME content was 4.1%. This result satisfied the Korea Industrial Standard (KSM2413).
It is important to estimate the optimal construction cost at the early stage of the project. In this regard, conceptual cost estimate is an important factor for estimate optimal construction cost. However, domestic conceptual cost estimate are only used as cost per unit area according to the building type, and it's accuracy is not high. Hence, the purpose of this study is to calculate the approximate quantity and cost for reinforcing bars, concrete, and formwork by presenting a regression formula based on the total floor area of the common work items in the frame work. In order to verify the accuracy and validity of the regression formula presented in this study, a comparative analysis was performed by applying the regression formula and the traditional approximate quantity take-off method to real cases. As a result, the estimated error rate of the traditional method was -102~+55%, and exceeded the estimated conceptual cost estimate accuracy range of -50~+100% suggested by AACE(American Association of Cost Engineering). On the other hand, the error rate of the regression formula method presented in this study was -6.4~+11.62%. This can be used not only for conceptual cost estimate range of accuracy, but also for detailed estimates. However, it is necessary to analyze the factors that affect the unit price as well as quantity in order to calculate the appropriate cost.
The university facility is made up of multiple buildings and has many maintenance items. In addition, administrative constraints need to be handled within a limited period. Most maintenance work is small scale and multi-work construction, such as waterproofing, needs to be organized. The facility manager makes annual unit price contract with a maintenance company and carries out the maintenance work. On the other hand, delay and rework is occurring because existing maintenance work performed without scheduling based on the manpower input. This study proposed a scheduling model that can support the facility manager to manage maintenance works of multiple university facilities at the program level. The model consists of three stages in order. In object analysis, details of the maintenance items were analyzed and the quantity is calculated based on the quantity takeoff sheet. In resource analysis, the craftsmen and construction period of detailed works are derived for the effective input of craftsmen. In scheduling, the priority of each work and the optimal manpower input are derived. The optimal schedule is selected according to the goodness of fit. The applicability and effectiveness of the prototype was evaluated through a case study and interviews with case participants. The model was found to be an effective tool to support the scheduling of maintenance works for the facility manager.
shows the channel structures analyzed in this study. Before the Internet channel is introduced, a monopoly manufacturer sells its products through an independent physical store. From this structure, the manufacturer could introduce its own Internet channel (MI). The independent physical store could also introduce its own Internet channel and coordinate it with the existing physical store (RI). An independent Internet retailer such as Amazon could enter this market (II). In this case, two types of independent retailers compete with each other. In this model, consumers are uniformly distributed on the two dimensional space. Consumer heterogeneity is captured by a consumer's geographical location (ci) and his disutility of using the Internet channel ( shows various market conditions captured by the two consumer heterogeneities. (a) illustrates a market with symmetric consumer distributions. The model captures explicitly the asymmetric distributions of consumer disutility in a market as well. In a market like that is represented in (c), the average consumer disutility of using an Internet store is relatively smaller than that of using a physical store. For example, this case represents the market in which 1) the product is suitable for Internet transactions (e.g., books) or 2) the level of E-Commerce readiness is high such as in Denmark or Finland. On the other hand, the average consumer disutility when using an Internet store is relatively greater than that of using a physical store in a market like summarizes the various scenarios of consumer distributions analyzed in this study. The range for disutility of using the Internet (
summarizes the analysis results. As the average travel cost in a market decreases while the average disutility of Internet use remains the same, average retail price, total quantity sold, physical store profit, monopoly manufacturer profit, and thus, total channel profit increase. On the other hand, the quantity sold through the Internet and the profit of the Internet store decrease with a decreasing average travel cost relative to the average disutility of Internet use. We find that a channel that has an advantage over the other kind of channel serves a larger portion of the market. In a market with a high average travel cost, in which the Internet store has a relative advantage over the physical store, for example, the Internet store becomes a mass-retailer serving a larger portion of the market. This result implies that the Internet becomes a more significant distribution channel in those markets characterized by greater geographical dispersion of buyers, or as consumers become more proficient in Internet usage. The results indicate that the degree of price discrimination also varies depending on the distribution of consumer disutility in a market. The manufacturer in a market in which the average travel cost is higher than the average disutility of using the Internet has a stronger incentive for price discrimination than the manufacturer in a market where the average travel cost is relatively lower. We also find that the manufacturer has a stronger incentive to maintain a high price level when the average travel cost in a market is relatively low. Additionally, the retail competition effect due to Internet channel introduction strengthens as average travel cost in a market decreases. This result indicates that a manufacturer's channel power relative to that of the independent physical retailer becomes stronger with a decreasing average travel cost. This implication is counter-intuitive, because it is widely believed that the negative impact of Internet channel introduction on a competing physical retailer is more significant in a market like Russia, where consumers are more geographically dispersed, than in a market like Hong Kong, that has a condensed geographic distribution of consumers.
The Study on the Economic Appraisal of Fishing Port Investments
(어항투자사업의 경제성 평가에 관한 연구)
Effects of variety, region and season on near infrared reflectance spectroscopic analysis of quality parameters in red wine grapes
The Effect of Soybean Oil and Waste Chicken Oil Mixing Ratio on Biodiesel Characteristics
(대두유와 폐계유의 혼합비가 바이오디젤 특성에 미치는 영향)
Conceptual Cost Estimate Method of Public Office Building Structural Frame Work by Regression Analysis
(회귀분석을 통한 공공청사 골조 공사의 개산견적 방안)
Program-level Maintenance Scheduling Support Model for Multiple University Facilities
(프로그램레벨 다수 대학시설물 유지보수 일정계획 지원 모델)
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