• BMB Reports
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• v.45 no.3
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• pp.133-140
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• 2012

Cancers claim millions of lives each year. Early detection that can enable a higher chance of cure is of paramount importance to cancer patients. However, diagnostic tools for many forms of tumors have been lacking. Over the last few years, studies of chimeric RNAs as biomarkers have emerged. Numerous reports using bioinformatics and screening methodologies have described more than 30,000 expressed sequence tags (EST) or cDNA sequences as putative chimeric RNAs. While cancer cells have been well known to contain fusion genes derived from chromosomal translocations, rearrangements or deletions, recent studies suggest that trans-splicing in cells may be another source of chimeric RNA production. Unlike cis-splicing, trans-splicing takes place between two pre-mRNA molecules, which are in most cases derived from two different genes, generating a chimeric non-co-linear RNA. It is possible that trans-splicing occurs in normal cells at high frequencies but the resulting chimeric RNAs exist only at low levels. However the levels of certain RNA chimeras may be elevated in cancers, leading to the formation of fusion genes. In light of the fact that chimeric RNAs have been shown to be overrepresented in various tumors, studies of the mechanisms that produce chimeric RNAs and identification of signature RNA chimeras as biomarkers present an opportunity for the development of diagnoses for early tumor detection.

• Food Science of Animal Resources
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• v.31 no.2
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• pp.147-157
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• 2011

Mycobacterium avium paratuberculosis (MAP), the cause of Johne's disease in animals, may be a causative agent of Crohn's disease (CD) in humans, but the evidence supporting this claim is controversial. Milk, meat, and water could be potential sources of MAP transmission to humans. Thus, if the link between MAP and Crohn's disease is substantiated, the fact that MAP has been detected in retail foods could be a public health concern. The purpose of the present study was to review the link between MAP and CD, the prevalence of MAP in foods, heat inactivation, control of MAP during food processing, and detection methods for MAP. Although MAP positive rates in retail milk in nine countries ranged from 0 to 2.9% by the culture method and from 4.5 to 15.5% by PCR, high temperature short time pasteurization can effectively control MAP. The effectiveness of pasteurization to inactivate MAP depends on the initial concentration of the MAP in raw milk. Development of highly sensitive and specific rapid detection methods for MAP may enhance investigation into the relationship between MAP and CD, the prevention of the spread of MAP, and problem-solving related to food safety. Collaboration and efforts by government agencies, the dairy industry, farmers, veterinarians, and scientists will be required to reduce and prevent MAP in food.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.437-441
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• 2022

문맥 독립 주장 탐지는 논점에 대한 정보가 주어지지 않은 상황에서 문서 내부의 문장들 또는 단일 문장에 대한 주장을 탐지하는 작업이다. 본 논문에서는 GCN 계층을 통해 얻은 구조 정보와 사전 학습된 언어 모델을 통해 얻은 의미 정보를 활용하는 문맥 독립 주장 탐지 모델을 제안한다. 특히 문장의 전체 구조 정보를 나타내는 부모-자식 그래프와 문장의 특정 구조 정보를 나타내는 조부모-조손 그래프를 활용해 추가적인 구조 정보를 활용하여 주장 탐지 성능을 향상시켰다. 제안 모델은 IAM 데이터셋을 사용한 실험에서 기본 RoBERTa base 모델과 비교하여 최대 2.66%p의 성능 향상을 보였다.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.241-250
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• 2022

Due to the COVID-19 pandemic, with increased 'untact' services and with unstable household economy, the bike insurance fraud is expected to surge. Moreover, the fraud methodology gets complicated. However, the fraud detection model for bike insurance is absent. we deal with the issue of skewed class distribution and reflect the criterion of fraud detection expert. We utilize a balanced random-forest algorithm to develop an efficient bike insurance fraud detection model. As a result, while the predictive performance of balanced random-forest model is superior than it of non-balanced model. There is no significant difference between the variables used by the experts and the confirmatory models. The important variables to detect frauds are turned out to be age and gender of driver, correspondence between insured and driver, the amount of self-repairing claim, and the amount of bodily injury liability.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.593-608
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• 2013

According to increasing number of injury claims, the challenge is reducing investigation of cases of injuries by selecting them more delicately, while also increasing the redemption rates and the amount of restitution. In this regards, we developed the fraud detection model for injury claims of self-employed insured by using decision tree after collecting medical claim data from 2006 to 2011 of the National Health Insurance in Korea. As a result of this model, subject types were classified into 18 types. If applying these types to the actual survey compared with if not applying, the redumption collecting rate will be increasing by 12.8%. Also, the effectiveness of this model will be maximize when the number of claims handlers considering their survey volume and management plans are examined thoroughly.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.745-754
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• 2005

This paper proposes an information hiding algorithm using channel coding technique which can be used to detect transmission errors and to protect copyright for MPEG-2 video The watermark signal is generated by applying copyright information of video data to a convolutional encoder, and the signal is embedded into macro blocks in every frame while encoding to MPEG-2 video stream In the decoder, the embedded signal is detected from macro blocks in every frame, and the detected signal is used to localize transmission errors in the video stream. The detected signal can also be used to claim ownership of the video data by decoding it to the copyright Information. In this stage, errors in the detected watermark signal can be corrected by channel decoder. The 3 video sequences which consist of 300 frames each are applied to the proposed MPEG-2 codec. Experimental results show that the proposed method can detect transmission errors in the video stream while decoding and it can also reconstruct copyright information more correctly than the conventional method.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.79-88
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• 2024

The use of the social media has become part of our daily life activities. The social web channels provide the content generation facility to its users who can share their views, opinions and experiences towards certain topics. The researchers are using the social media content for various research areas. Sentiment analysis, one of the most active research areas in last decade, is the process to extract reviews, opinions and sentiments of people. Sentiment analysis is applied in diverse sub-areas such as subjectivity analysis, polarity detection, and emotion detection. Stance classification has emerged as a new and interesting research area as it aims to determine whether the content writer is in favor, against or neutral towards the target topic or issue. Stance classification is significant as it has many research applications like rumor stance classifications, stance classification towards public forums, claim stance classification, neural attention stance classification, online debate stance classification, dialogic properties stance classification etc. This research study explores different feature sets such as lexical, sentiment-specific, dialog-based which have been extracted using the standard datasets in the relevant area. Supervised learning approaches of generative algorithms such as Naïve Bayes and discriminative machine learning algorithms such as Support Vector Machine, Naïve Bayes, Decision Tree and k-Nearest Neighbor have been applied and then ensemble-based algorithms like Random Forest and AdaBoost have been applied. The empirical based results have been evaluated using the standard performance measures of Accuracy, Precision, Recall, and F-measures.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.48.2-48.2
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• 2013

To understand the connection between active galactic nuclei (AGNs) and star formation, we investigated the relation between AGN bolometric and far-infrared (FIR) luminosities, using type-2 AGNs. By matching type-2 AGNs at z < 0.3 selected from the SDSS based on the emission-line diagnostics, against the AKARI/FIS All-Sky Survey Catalogue and the COSMOS PEP (PACS Evolutionary Probe) Survey Catalogue, we obtained a sample of 729 type-2 AGNs detected in the AKARI survey ($90{\mu}m$) and 17 ones detected in the PEP survey ($100{\mu}m$). For AGN bolometric luminosities, we adopted an estimate based on the [OIII] and [OI] line luminosities. We confirmed that there is a correlation between the AGN bolometric and FIR luminosities with a large scatter, which is consistent with previous studies. However, we claim that this correlation suffers from various artificial effects, e.g., FIR detection limits, survey volumes, and so on. We will discuss the limitations of studying the connection between AGN and star formation using currently available facilities.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.11
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• pp.938-941
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• 2012

LED is divided to multichannel in order not to exceed a certain voltage in aspects of electric standard. However, it's not possible to know in accordance with what channel SMPS controls the constant voltage and current. In order to solve this problem, it needs to detect the maximum LED String voltage which is applied to LED control circuit, and it is possible to minimize the voltage drop when a difference of LED string voltage occurs by each channel if LED is controlled by the maximum LED string voltage detected. In addition, it is also possible to maximize the efficiency of LED if change LED voltage by detecting the maximum voltage. Feasibility of this claim was verified through implementation of the circuit.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.413-414
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• 1998

This paper presents a real-time Spatial Decision Support System(SDSS) for security camera image monitoring. Other SDSSs are not real-time systems, i.e., they show the images that are already transformed into data format such as virtual reality. In our system, the image is broadcasted in real-time since the purpose of the security camera needs to do it in real-time. With these real-time images, other systems do not add up anything more; the screen just shows the images from the camera. However in our system, we created a motion detection system so that the supervisor(Judge) of a sec.urity monitoring system does not have to pay attention to it constantly. In other words, we created a judge advising system for the supervisor of the security monitoring system. Most of small objects do not need the supervisor's attention since they could be birds, cats, dogs, etc. if they show up in the screen image. In this new system the system only report the unusual change to the supervisor by calculating the motion and size of objects in the screen. Thus the supervisor can be liberated from the 24-hour concentration duty; instead he/she can be only alerted when the real security threat such as a big moving object like an human intruder appears. Thus this system can be called a real-time Spatial DSS. The utility of this system is proved mathematically by using the concept of entropy. In other words, big objects like human intruders increase the entropy of the screen images significantly therefore the supervisor must be alerted. Thus by proving its utility of the system theoretically, we can claim that our new real-time SDSS is superior to others which do not use our technique.hnique.