부정 탐지를 위한 이상치 분석 활용방안 연구

김동성(Dongsung Kim),김기태(Kitae Kim),김종우(Jongwoo Kim),박성기(Steve Park) 한국지능정보시스템학회 2014 지능정보연구 Vol.20 No.3

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

Discourse Structure and Syntax-Semantics Interface

Dongsung Kim 담화·인지언어학회 2003 담화·인지언어학회 학술대회 발표논문집 Vol.- No.-

A Retrospective Clinical Evaluation of an Artificial Intelligence Screening Method for Early Detection of STEMI in the Emergency Department

Kim Dongsung,Hwang Ji Eun,Cho Youngjin,Cho Hyoung-Won,Lee Wonjae,Lee Ji Hyun,Oh Il-Young,Baek Sumin,Lee Eunkyoung,Kim Joonghee 대한의학회 2022 Journal of Korean medical science Vol.37 No.10

Background: Rapid revascularization is the key to better patient outcomes in ST-elevation myocardial infarction (STEMI). Direct activation of cardiac catheterization laboratory (CCL) using artificial intelligence (AI) interpretation of initial electrocardiography (ECG) might help reduce door-to-balloon (D2B) time. To prove that this approach is feasible and beneficial, we assessed the non-inferiority of such a process over conventional evaluation and estimated its clinical benefits, including a reduction in D2B time, medical cost, and 1-year mortality. Methods: This is a single-center retrospective study of emergency department (ED) patients suspected of having STEMI from January 2021 to June 2021. Quantitative ECG (QCG™), a comprehensive cardiovascular evaluation system, was used for screening. The non-inferiority of the AI-driven CCL activation over joint clinical evaluation by emergency physicians and cardiologists was tested using a 5% non-inferiority margin. Results: Eighty patients (STEMI, 54 patients [67.5%]) were analyzed. The area under the curve of QCG score was 0.947. Binned at 50 (binary QCG), the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 98.1% (95% confidence interval [CI], 94.6%, 100.0%), 76.9% (95% CI, 60.7%, 93.1%), 89.8% (95% CI, 82.1%, 97.5%) and 95.2% (95% CI, 86.1%, 100.0%), respectively. The difference in sensitivity and specificity between binary QCG and the joint clinical decision was 3.7% (95% CI, −3.5%, 10.9%) and 19.2% (95% CI, −4.7%, 43.1%), respectively, confirming the non-inferiority. The estimated median reduction in D2B time, evaluation cost, and the relative risk of 1-year mortality were 11.0 minutes (interquartile range [IQR], 7.3–20.0 minutes), 26,902.2 KRW (22.78 USD) per STEMI patient, and 12.39% (IQR, 7.51–22.54%), respectively. Conclusion: AI-assisted CCL activation using initial ECG is feasible. If such a policy is implemented, it would be reasonable to expect some reduction in D2B time, medical cost, and 1-year mortality.

Study on statistical breakdown delay time in argon gas using a W-band millimeter-wave gyrotron

Kim, Dongsung,Kim, Sung Gug,Sawant, Ashwini,Yu, Dongho,Choe, MunSeok,Choi, EunMi American Institute of Physics 2016 Physics of plasmas Vol.23 No.4

Use of colloidal iron as a tracer to measure the ingestion rates of free-living marine nematodes

Kim, Dongsung,Shirayama, Yoshihisa Springer-Verlag 2010 Journal of oceanography Vol.66 No.2

High-Throughput Screening for Novel Inhibitors of Protein-Tyrosine Phosphatase-1B

Kim WonBae,Lee Inki,Son MiWon,Jung MiYoung,Shin ChangYell,Kim DongSung,Kim SoonHoe,Yoo MooHi 大韓藥學會 2002 大韓藥學會 總會 및 學術大會 Vol.2002 No.2

DA 11004, a synthetic IDPc inhibitor, inhibits the high fat high sucrose diet-induced obesity in C57BL/6 mice

Kim WonBae,Jeong MiYoung,Shin ChangYell,Sohn JinBup,Lee InKi,Son Miwon,Bae CheolJun,Byun JongSoo,Kim DongSung,Huh TaeLin,Yoo Moohi,Kim SoonHae 大韓藥學會 2003 大韓藥學會 總會 및 學術大會 Vol.2003 No.1

Mitochondrial Genetic Variation of Pen Shell, Atrina pectinata in Korea and Japan

Kim, Dongsung,Rho, Hyun Soo,Jung, Jongwoo The Korean Society of Systematic Zoology 2017 Animal Systematics, Evolution and Diversity Vol.33 No.3

In the northwestern Pacific region, the pen shell (Atrina pectinata) is a widely distributed bivalve and economically important in fisheries. Recently, stock of this species has been greatly reduced due to overexploitation and marine pollution, which arouses interest in conservation. Studies on genetic and taxonomic entities of pen shells have not been tried in Korea, which makes difficult to take measures for effective conservation of this marine resource. In this study, we investigated mitochondrial genetic polymorphism of pen shells collected from 4 locations in Korea and Japan using cytochrome c oxidase I (COI) gene sequences. A total of 39 haplotypes were identified among 86 individuals of pen shell. Although only 5 haplotypes were shared, no significant genetic differentiation was observed between Korean and Japanese populations. These results suggest that pen shell populations of these regions share an ancestral population which might have experienced expansion during the Pleistocene, but gene flow must have been highly restricted after expansion.

Mitochondrial Genetic Variation of Pen Shell, Atrina pectinata in Korea and Japan

Dongsung Kim,Hyun Soo Rho,Jongwoo Jung 한국동물분류학회 2017 Animal Systematics, Evolution and Diversity Vol.33 No.3

In the northwestern Pacific region, the pen shell (Atrina pectinata) is a widely distributed bivalve and economically important in fisheries. Recently, stock of this species has been greatly reduced due to overexploitation and marine pollution, which arouses interest in conservation. Studies on genetic and taxonomic entities of pen shells have not been tried in Korea, which makes difficult to take measures for effective conservation of this marine resource. In this study, we investigated mitochondrial genetic polymorphism of pen shells collected from 4 locations in Korea and Japan using cytochrome c oxidase I (COI) gene sequences. A total of 39 haplotypes were identified among 86 individuals of pen shell. Although only 5 haplotypes were shared, no significant genetic differentiation was observed between Korean and Japanese populations. These results suggest that pen shell populations of these regions share an ancestral population which might have experienced expansion during the Pleistocene, but gene flow must have been highly restricted after expansion.

연관 규칙 마이닝을 이용한 영작문 형태-통사 오류 자동 탐지

김동성(Dongsung Kim) 한국정보과학회 2011 정보과학회논문지 : 소프트웨어 및 응용 Vol.38 No.3

본 연구에서는 일련의 연구에서 수집된 영작문 오류 유형의 정제된 자료를 토대로 연관 규칙을 생성하고, 학습을 통해서 효용성이 검증된 연관 규칙을 활용해서 영작문 데이터의 형태?통사 오류를 자동으로 탐지한다. 영작문 데이터에서 형태?통사 오류를 찾아내는 작업은 많은 시간과 자원이 소요되는 작업이므로 자동화가 필수적이다. 기존의 연구들이 통계적 모델을 활용한 어휘적 오류에 치중하거나 언어 이론적 틀에 근거한 통사 처리에 집중하는 반면에, 본 연구는 데이터 마이닝을 통해서 정제된 데이터에서 연관 규칙을 생성하고 이를 검증한 후 형태·통사 오류를 감지한다. 이전 연구들에서는 이론적 틀에 맞추어진 규칙 생성이나 언어 모델 생성을 위한 대량의 코퍼스 데이터와 같은 다량의 지식 베이스 생성이 필수적인데, 본 연구는 적은 양의 정제된 데이터를 활용한다. 영작문 오류 유형의 형태?통사 연관 규칙을 생성하기 위해서 Apriori 알고리즘을 활용하였다. 알고리즘을 통해서 생성된 연관 규칙 중 잘못된 규칙이 생성될 가능성이 있으므로, 상관성 검정, 코사인 유사도와 같은 규칙 효용성의 통계적 검증을 활용해서 타당한 규칙만을 학습하고 축적된 연관 규칙들을 영작문 오류를 자동으로 탐지하는 실험에 활용하였다. 연구 결과로 형태?통사적 문법 오류를 정확하게 탐지함을 알 수 있다. Since manual error detection of morpho-syntactic errors of English writing requires lots of time and resources, automation of error detection is essential in both Computer-Assisted Language Learning and English learning studies. This approach aims at automatic detection of morpho-syntactic errors of English writing using association rule mining, which needs three steps of procedures. As the first step, we generate association rules based on the refined data. Second, we statistically verify the generated rules. Third, we testify the verified rules on the test data. Previous studies have focused on either word errors based on the language models using large corpora, or the systems very specific to the complex grammatical theories. Meanwhile, this study uses relatively small amount of data. We used the Apriori algorithm for the rule mining task. Since rules generated by the algorithm can contains lots of noise to be reduced, we apply statistical machine learning methods using correlation coefficient and cosine similarity. This process sifts valid mal-rules for the automatic detection tasks from lots of noise.