Kim, Seong-Jong;Kang, Young-June;Park, Nak-Kyu;Lee, Dong-Hwan
Journal of the Korean Society for Precision Engineering
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v.26
no.7
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pp.65-72
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2009
Laser interferometry is widely used as a measuring system in many fields because of its high resolution and its ability to measure a broad area in real-time all at once. In conventional laser interferometry, for example out-of-plane ESPI (Electronic Speckle Pattern Interferometry), in plane ESPI, shearography and holography, it uses PZT or other components as a phase shift instrumentation to extract 3-D deformation data, vibration mode and others. However, in most cases PZT has some disadvantages, which include nonlinear errors and limited time of use. In the present study, a new type of laser interferometry using a laser diode is proposed. Using Laser Diode Sinusoidal Phase Modulating (LD-SPM) interferometry, the phase modulation can be directly modulated by controlling the laser diode injection current thereby eliminating the need for PZT and its components. This makes the interferometry more compact. This paper reports on a new approach to the LD (Laser Diode) Modulating interferometry that involves four-frame phase shift method. This study proposes a four-frame phase mapping algorithm, which was developed to have a guaranteed application, to stabilize the system in the field and to be a user-friendly GUI. In this paper, the theory for LD wavelength modulation and sinusoidal phase modulation of LD modulating interferometry is shown. Using modulating laser and research of measurement algorithm does comparison with existent ESPI measurement algorithm. Algorithm measures using GPIB communication through most LabVIEW 8.2. GPIB communication does alteration through PC. Transformation of measurement object measures through modulating laser algorithm that develops. Comparison of algorithm of modulating laser developed newly with existent PZT algorithm compares transformation price through 3-D. Comparison of 4-frame phase mapping, unwrapping, 3-D is then introduced.
This study is to present alternatives of strategical utilization of e-L/C in respective of transaction cost. Documentary credit is most used for trade importers' credit quality and the guarantee of the purchase price as the form of payment in export and import business dealings. The beneficiary must provide the documents required in a letter of credit in order to claim payment documents from the issuing bank, this leads to certain complexity during the procedure in practice, the preparation and the expenses of significant requirements and additional documents as well as in completing demands from the credit. In a result, there has been issues raised about the aspects of time and cost during the payment process. The outcome of such problems caused by delays in the existing trade procedure is the public to require the use of e-L/C in order to improve problems from the 'Transaction Cost' side. This study provides e-L/C's use to overcome the problems that are appearing from 'Transaction Cost' side as the aspect of time and the cost. In order to do so, we have to identify the problems in the original credit and e-L/C. Thus, provide the propose strategy of e-L/C from the Transaction Cost aspect.
The purpose of this study is to derive the factors for the general consumers to choose the store to buy seafood. Survey on 414 general consumers by questionnaires was conducted to find out the factors for them to choose the stores in the traditional market and large supermarket, and through the analysis on the results the factors for general consumers to choose large supermarkets were derived when they buy seafood and at the same time the degree of its importance was analyzed. The results of the survey showed that the general consumers chose large supermarkets to buy seafood despite the fact that they recognized the seafood prices are lower in the traditional markets than in the large supermarkets. Particularly, the results of analyzing the sixteen criteria for choosing the store in which to buy seafood were grouped into four: the 'assortment of goods and high quality', 'service', 'price and promotion' and 'convenient accessibility.' The results of examining the order of priority based on the four factors showed that the 'assortment of diverse seafood and high quality' was found to be given the first priority, followed by 'convenient accessibility' and 'prices and promotion factors', with 'service' being statistically insignificant. Based on these results, Monroe (1975)'s consumers' store choice process is summarized as follows. Before buying seafood, the consumers who use large supermarkets have the desire for buying seafood and then judge the properties of the store which they will use. In this process, consumers were satisfying their needs in large supermarkets in the criteria of 'assortment of diverse seafood and high quality', convenient accessibility', and 'prices and promotion factors' which were found to be statistically significant in this research. Accordingly, the general consumers choose to buy seafood in large supermarkets rather than in the traditional markets. The general consumers were more satisfied with using large supermarkets than using traditional markets, so after they have initially bought seafood in the large supermarkets, they habitually buy seafood in the large supermarkets without going through Monroe (1975)'s 'eight stage process for the store choice.' When such habitual store choice behavior continues for a long time, it results in becoming structural.
The purpose of this study is to analyze cause-and-effect relationships between patterns of the road network and socio-economic factors such as population, industry, and land use of Seoul during the period of 1970~2000. In this study, Structural Equation Model (SEM) is used to estimate simultaneously the cause-and-effect relationships between many independent variables and dependent variables. For the observed variables, variables related to population, industry, land price, land use, and road variables were included; these variables were classified by exploratory factor analysis. The analysis using the SEM showed that the structure of the model changed around the 1980's. In general, socio-economic factors such as population, industry, and land use affected construction of the road network of the city during the 1970's and the 1980's. Especially, it was analyzed that the industrial development had the greatest impact on formation of the road network. In the 1990's, the effect that the road network exerts on socio-economic factors proved to be more appropriate than the other way round. At that time, the road-related factors had the greatest effect on the land price and industrial development, and that tendency has continued until now.
The possession rate of residential telephones tend to decrease as mobile phones are widely spread. There is also a decrease in the access rate of the qualified respondents due to the low rate of phone book registration and that of house owner's presence at home. Such a change in telephone survey environment calls for another survey-channel which makes good use of new telecommunication services. In this paper, a mobile survey system was designed and performed by the use of SMS (Short Message Service) which is a kind of mobile data communication service. The system draws the sample by using random digit sampling based on 'quota allocation', and sends the SMS to the sample according to the arranged scheduler. Then, the survey-panel which received the SMS connects to the responding server by pressing the 'send' button (which is connected by the callback number), responding to the question. As a result, the responding value is stored in the database and is analyzed in real-time. This system is distinguished from other research methodologies for its simplicity in data collection, its inexpensive research price, and the innovatively low research time.
To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.
Journal of the Korean Regional Science Association
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v.32
no.1
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pp.67-82
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2016
This study aims to test the spatial mismatch hypothesis by exploring the relationship between income and commuting time in Seoul, Korea. For this purpose, we analyze the commuting times of individuals who commute to Seoul, using the data for the metropolitan household survey. We employed a hierarchial linear model(HLM) to capture the effects of both individual attributes and regional attributes, and their interactions. The results show that the commuting time decreases with household income controlling for the regional attributes, and the effect of income increases with the housing price of the location of a commuter's firm. This implies that the spatial mismatch holds for Seoul as follows: Lower personal income and housing affordablility extend individuals' commuting times, and the destinations' characteristics such as housing type and land use also have impacts on commuting time. These results have some policy implications for achieving social equity in terms of spatial structure of the city.
There are growing interests in the introduction of consumer's selective electricity tariff systems in order to enhance demand response in electricity market in Korea. Real time pricing (RTP) and Time of Use (TOU) are typical examples of demand response system through which electricity price is linked to real time demand. This paper adopts an agent-based model to analyze the effects of such demand system on the counsumers' electricity costs. The result shows that real time pricing system is effective to reduce electricity costs of consumers by providing more flexible tariff system, depending on each consumer's demand pattern. This finding could be used as a basis for supporting smart grid system in the presence of responsive demand environment.
Some road charges toll to finance the cost or to manage traffic congestion. With a growth of PPI projects, toll roads would be increase continuously. Tolls have a considerable influence on user's route choice, and sometimes can affect to the departure time and even to mode choice. For modelling toll roads, user's WTP or VOT has an important role and it is general that VOT is equivalent to the wages of workers. The current way of modelling technique yields various toll price elasticity from low to high. When there exist few alternative routes, unrealistic result that all traffic assigned to some shortest path may occur. The toll price elasticity can be influenced by alternative route and congestion level, but some result shows nearly unrealistic patterns. The model to forecast more realistic toll road demand is very essential for estimating toll revenue, choice of optimal toll level & collecting location and establishing toll charge strategy. This paper reviewed some literatures about toll road modelling and tested case study about the assignment technique with different VOT. The case study shows that using different VOT yields more realistic result than the use of single VOT.
This paper tested the lead-lag relationship as well as the symmetric and asymmetric volatility spillover effects between international currency futures markets and cash markets. We use five kinds of currency spot and futures markets such as British pound, Australian and Canadian dollar, Brasilian Real and won/dollar spot and futures markets. daily closing prices covering from September 15, 2003 to July 30, 2009. For this purpose we employed dynamic time series models such as the Granger causality based on VAR and time-varying MA(1)-GJR-GARCH(1, 1)-M. The main empirical results are as follows; First, according to Granger causality test, we find that the bilateral lead-lag relationship between the five countries' currency spot and futures market. The price discover effect from currency futures markets to spot market is relatively stronger than that from currency spot to futures markets. Second, based on the time varying GARCH model, we find that there is a bilateral conditional mean spillover effects between the five currency spot and futures markets. Third, we also find that there is a bilateral asymmetric volatility spillover effects between British pound, Canadian dollar, Brasilian Real and won/dollar spot and futures market. However there is a unilateral asymmetric volatility spillover effect from Australian dollar futures to cash market, not vice versa. From these empirical results we infer that most of currency futures markets have a much better price discovery function than currency cash market and are inefficient to the information.
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