• Journal of Information Processing Systems
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• v.4 no.3
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• pp.113-120
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• 2008

Most enterprises have controlled claim data related to marketing, production, trade and delivery. They can extract the engineering information needed to the reliability of unit from the claim data, and also detect critical and latent reliability problems. Existing method which could detect abnormal quality unit lists in early stage from claim database has three problems: the exclusion of fallacy probability in claim, the false occurrence of claim fallacy alarm caused by not reflecting inventory information and too many excessive considerations of claim change factors. In this paper, we propose a process and methods extracting abnormal quality unit lists to solve three problems of existing method. Proposed one includes data extraction process for reliability measurement, the calculation method of claim fallacy alarm probability, the method for reflecting inventory time in calculating claim reliability and the method for identification of abnormal quality unit lists. This paper also shows that proposed mechanism could be effectively used after analyzing improved effects taken from automotive company's claim data adaptation for two years.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.413-423
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• 2022

The NHIS provides free or highly subsidized healthcare to all people by providing financial fortification. However, the financial sustainability of the scheme is threatened by numerous factors. Therefore, this work sought to provide a solution to process claims intelligently. The provided Petri net model demonstrated successful data flow among the various participant. For efficiency, scalability, and performance two main subsystems were modelled and integrated - data input and claims processing subsystems. We provided smart claims processing algorithm that has a simple and efficient error detection method. The complexity of the main algorithm is good but that of the error detection is excellent when compared to literature. Performance indicates that the model output is reachable from input and the token delivery rate is promising.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.57-66
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• 2022

Claims and disputes are major causes of cost and schedule overruns in the construction business. In order to manage claims and disputes effectively, it is necessary to analyze various types of contract documents punctually and accurately. Since volume of such documents is so vast, analyzing them in a timely manner is practically very challenging. Recently developed approaches such as artificial intelligence (AI), machine learning algorithms, and natural language processing (NLP) have been applied to various topics in the field of construction contract and claim management. Based on the systematic literature review, this paper analyzed the goals, methodologies, and application results of such approaches. AI methods applied to construction contract management are classified into several categories. This study identified possibilities and limitations of the application of such approaches. This study contributes to providing the directions for how such approaches should be applied to contract management for future studies, which will eventually lead to more effective management of claims and disputes.

• Journal of Preventive Medicine and Public Health
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• v.39 no.5
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• pp.433-437
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• 2006

Objectives: The aim of this study is to develop a methodology for estimating a nationwide statistic for hernia operations with using the claim database of the Korea Health Insurance Cooperation (KHIC). Methods: According to the insurance claim procedures, the claim database was divided into the electronic data interchange database (EDI_DB) and the sheet database (Paper_DB). Although the EDI_DB has operation and management codes showing the facts and kinds of operations, the Paper_DB doesn't. Using the hernia matched management code in the EDI_DB, the cases of hernia surgery were extracted. For drawing the potential cases from the Paper_DB, which doesn't have the code, the predictive model was developed using the data mining technique called SEMMA. The claim sheets of the cases that showed a predictive probability of an operation over the threshold, as was decided by the ROC curve, were identified in order to get the positive predictive value as an index of usefulness for the predictive model. Results: Of the claim databases in 2004, 14,386 cases had hernia related management codes with using the EDI system. For fitting the models with applying the data mining technique, logistic regression was chosen rather than the neural network method or the decision tree method. From the Paper_DB, 1,019 cases were extracted as potential cases. Direct review of the sheets of the extracted cases showed that the positive predictive value was 95.3%. Conclusions: The results suggested that applying the data mining technique to the claim database in the KHIC for estimating the nationwide surgical statistics would be useful from the aspect of execution and cost-effectiveness.

• The Transactions of the Korea Information Processing Society
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• v.2 no.6
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• pp.960-968
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• 1995

In this paper we present a reordering scheme that could lead to efficient vectorization of the preconditioners for the large sparse linear systems arising from partial differential equations on the CRAY-2, This reordering scheme is a line version of the conventional red/black ordering. This reordering scheme, coupled with a variant of ILU(Incomplete LU) preconditioning, can overcome the poor rate of convergence of the conventional red/black reordering, if relatively large number of fill-ins were used. We substantiate our claim by conducting various experiments on the CRAY-2 machine. Also, the computation of the Frobenius norm of the error matrices agree with our claim.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.195-200
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• 2019

The purpose of this study is to analyze the characteristics of National Health Insurance claim data and to construct a pilot medical episode data considering it. In this study, the trends of respiratory disease (ICD10: J00-J99) cardiovascular disease (ICD10: I00-I99) from the day of onset of treatment to re-admission after admission were confirmed in Seoul, and the largest decrease was observed when the no-treatment period was 0 day. The data reduction rate when the no-treatment period is 0 day is judged to be due to the monthly separation claim of the health insurance claim data. Also, the result that there is a tendency of monthly separation request according to the type of medical treatment. Through this study, we constructed epidemic data for the pilot medical treatment considering the characteristics of the claim data of health insurance, and based on this, it can be used as a data processing method for calculating basic epidemiological information.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.7-10
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• 2000

Studies of prosody and sentence processing have demonstrated that prosodic phrasing can exhibit strong effects on processing decisions in English. In this paper, we tested Korean sentence fragments containing syntactically ambiguous Adj-N1-N2 strings in a cross-modal naming task. Four accentual phrasing patterns were tested: (a) the default phrasing pattern, in which each word forms an accentual phrase; (b) a phrasing biased toward N1 modification; (c) a phrasing biased toward complex-NP modification; and (d) a phrasing used with adjective focus. Patterns (b) and (c) are disambiguating phrasings; the other two are commonly found with both interpretations and are thus ambiguous. The results showed that the naming time of items produced in the prosody contradicting the semantic grouping is significantly longer than that produced in either default or supporting prosody, We claim that, as in English, prosodic information in Korean is parsed into a well-formed prosodic representation during the early stages of processing. The partially constructed prosodic representation produces incremental effects on syntactic and semantic processing decisions and is retained in memory to influence reanalysis decisions.

• Food Science of Animal Resources
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• v.29 no.5
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• pp.599-611
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• 2009

This article concerns the labeling guideline for health benefits of livestock products. In recent years, livestock products with health benefits have emerged as a key market for livestock product industries. However, the current labeling regulation for functional foods severely prohibits livestock product industries from attaching most of the health benefits claims to the products. Also, manufacturers have some difficulties in labeling the health benefits of certain livestock products because of a lack of guidelines on health benefit claims for livestock products. Therefore, some livestock product industries and scientists have strongly demanded a revision of labeling regulation, Appended Chart No. 14 provided by Article 52 (2) of Enforcement Regulation of the Processing of Livestock Products Act, so they could mark the health benefits on their products. To support the 'revision of labeling regulation', the goals of this article were as follows; 1) to assess the current situation on nutrition labeling and nutrition claims on foods, 2) to determine the current situation on health claim regulatory systems used in foreign countries (CODEX, USA, Japan, EU, and Australia/New Zealand), 3) to assess the current situation on the health claim or health benefit claim regulations for functional foods, conventional foods, and livestock products in Korea, and 4) to determine the need for complement in health benefit claim for livestock products. In conclusion, guidelines for the use of health benefit claims on livestock products should be prepared as soon as possible and the guidelines should be viable and easy for manufacturers and control authorities to understand. Also, nutrient profiles should be developed to identify whether the livestock products are eligible to bear health benefit claims and to help consumers make the right choices.

• The Transactions of the Korea Information Processing Society
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• v.2 no.4
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• pp.443-452
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• 1995

Object-oriented database systems have been proposed as an effective solution for providing the data management facilities of complex applications. Proving this claim and the investigation of related issues such as query processing have been hampered by the absence of a formal object-oriented query model. In this paper, we not only define a query model based on aggregation inheritance but also develop semantic rewriting rules which are applied to equivalence preserving rewrite rules in algebraic expression of a query. Analyzing semantically the query model, the query model can be optimized to logically object-oriented query processing. And algebra expresstions of a query can be optimized by applying equivalence preserving rewrite rules.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1980-1987
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• 2000

In this paper, an efficient watermarking technique in wavelet transform domain is proposed. Watermarking is embedding a digital signal called as 'watermark' into images to claim the ownership. In the proposed method, the image is 1-level wavelet transformed, and then the watermark with a binary stamp is embedded into the baseband. The watermark is embedded by inverting the polarities of he selected coefficient paris. In the inverting process, we can increase image quality by finding means and differences of the selected neighboring coefficient paris, and then adding values, which are inversely proportional to the differences, to th means. The experimental results show that the proposed method has good quality and is robust to various attacks such as the JPEG lossy comparison, noise addition, clipping, blurring, etc.