• Korean Chemical Engineering Research
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• v.44 no.1
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• pp.65-72
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• 2006

Recent technical advances in the biorecognition engineering and the microparticle fabrication may enable us to develop the single step purification using magnetic particle, because of its simplicity, efficacy, ease of automation, and process economics. In this study, we used commercial magnetic particles from Seradyn, Inc. (Indianapolis, USA). It was ca. 2.8 micron in diameter, consisted of polystyrene core and magnetite coating, and its surface had carboxyl groups. The model, capture protein was IgG and anti-IgG was used as the ligand molecule. We studied the different surfaces ('nude', ester-activated, and anti-IgG coated) for their biorecognition of IgG. At a high pH condition, we could reduce non-specific binding. Also anti-IgG immobilized magnetic particle could capture IgG more selectively. We attempted 'oriented immobilization' of anti-IgG, in which the polysaccharides moiety near the C-terminus was selectively oxidized and linked to the hydrazine-coated MP, to improve the efficacy of biorecognitive binding. Using this method, the IgG capturing ability was improved by ca. 2 fold. From the binary mixture of the IgG-insulin, IgG could be more selectively captured. In summary, the oriented immobilization of oxidized anti-IgG proved to be as effective as the streptavidin-biotin system and yet simpler and cost-effective. This immobilization method can find its applications in protein biochips and biotargeting.

• Journal of the Korean Geographical Society
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• v.29 no.2
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• pp.137-165
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• 1994

Structural adjustment of industry (or industrial restructuring) seems to be inherent in the process of capitalist economic development, which tends to be proceeded with shifts from one stage to another in order to overcome structural crises generated in each stage. The structural adjustment of industry is necessarily accompanied with regional restructuring, since it is not only projected on spece, but also mediated by space. Such a restructuring necessitates industrial and uneven regional devlopment through which capital can seek excessive profits over the rate of socio-spatial average. The industrial restructuring and uneven regional development in the 1980s in Korea can be seen as a process in which capital attempted with a strong support of the govenment to overcome the crises in the end of 1970s and hence to go on rapid economic growth. In this process, capital, especially monopoly capital concentrated into few conglomerates, pursued both extensive expansion and intensive development of industry simultaneously. In results, the Korean economy could eliminate some of peripheral characters and maturate the Fordist accumulation system. The extensive expansion of the Korean industry in the 1980s was stimulated mainly through the enlargement and adjustment of investment for equipment facilities which was planned to exclude or rationalize traditional light industries on some places, and to continue rapid growth of key heavy-chemical industries, especially of fabricated metal industry, on other places. In this process, keeping mainly the existing developmental axis which polarized the Seoul Metroplitan region and the Southeast region in Korea, the enhancing spatial mobiiity of capital and the further differentiating division of labour enforced a tendency of concentration of all types of industry in the Seoul Metropolitan region, and at the same time provoked the diffusion of some industries over Jeolla and Chungchong regions in a considerable extent. The intensive development of industriai structure in the 1980s was pursued through the strategic encouragement of subcontracting small firms mainly which produced assembling components, the technical enhancement and factory (semi-) automation, and the enrichment of service industries for estate management, finance, distribution and retailing which supported and complemented the production of goods. In this process, enabling capital to extend and elaborate its domination over space through the reorganization of regulating systems, the Fordist division of labour generated a socio-spatial hierarchy in the nation-wide scale that characterized: the Seoul Metropolitan region as an overmaturated (or overarching) Fordist region performing the conceptive functions of management, research and development, in which all types of industry (including service industries) tended to be reconcentrated; Kyungsang region as a maturated Fordist region with excutive branches of large conglomerates and with subcontracting firms around them which produced standardized products through the automized production processes in secialized Fordist industries or rationalized traditional industries; and Jeolla and Chungchong regions as newly devloping Fordist regions with newly migrated branches and some subcontracting small firms-in relatively older Fordist industries or partly rationalized traditional industries. From these analyses, it can be argued that the structural adjustment of the Korean industry in the 1980s, which had carried out both through the extensive expansion and the intensive deveiopment, strengthened further uneven regional development process, even though it appears to have reduced apparently the economic and regional disparity by balancing numerically large and small firms and by extending the Fordist industrial space nation-wideiy. And it seems more persuasive to see that the Korean industrial structure in the 1980s maturated the Fordist system of accumulation, but not yet transformed towards the post-Fordist (or the so-called flexible) accumulation system, even though the Korean economy in the 1990s seems to be under a pressure of restructuring towards the latter system.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.