• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2019년도 춘계학술발표대회
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• pp.542-544
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• 2019

Changes in a person's health affect one's lifestyle and work activities. According to the World Health Organization (WHO), abnormal activity is growing faster in people aged 60 or more than any other age group in almost every country. This trend steadily continues and expected to increase further in the near future. Abnormal activity put these people at high risk of expected incidents since most of these people live alone. Human abnormal activity analysis is a challenging, useful and interesting problem among the researchers and its particularly crucial task in life and health care areas. In this paper, we discuss the problem of abnormal activities of old people lives alone at home. We propose Convolutional Neural Network (CNN) based model to detect the abnormal behaviors of elderlies by utilizing six simulated action data from daily life actions.

• Mycobiology
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• 제33권1호
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• pp.30-34
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• 2005

This study investigated the biochemical changes of abnormal fruiting bodies grown under artificial environmental conditions in P. ostreatus. Abnormal mushroom growth during cultivation damages the production of good quality mushroom. This study showed that different environmental conditions produced morphological changes in the fruiting bodies of P. ostreatus. The fruiting bodies with morphological changes were collected and examined for differences in biochemical properties, enzyme activities, and carbohydrates composition. The enzyme activities assay showed that glucanase and chitinase activities decreased when the temperature was below or above the optimum cultivation temperature for P. ostreatus. The biochemical compositions of the abnormal mushroom were significantly different from the normal fruiting bodies. It was suggested that the changes in the biochemical composition of abnormal mushroom were caused by the unfavorable environmental conditions during mushroom cultivation.

• 정보보호학회논문지
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• 제24권2호
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• pp.335-343
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• 2014

인터넷의 발달로 대중의 여론에 영향을 주는 인터넷 매체의 신뢰성이 중요해지는 반면 최근의 익명성을 이용한 리뷰 조작 등의 사례는 대중들에게 막연한 의구심을 들게 한다. 본 연구에서는 이러한 사이버 여론 조작과 관련된 현상이 인터넷 게시판 등 웹사이트에도 존재하는지 여부를 수치적으로 살펴보기 위하여 댓글의 요소를 분석하고 내용을 코사인 유사도를 이용하여 비교하였다. 분석 결과 첫째, 댓글 내용의 유사성은 댓글 순위에 의한 게시글의 랭킹과 상관관계가 있었으며 분석 대상 2개 웹사이트에 대해서는 14.1%와 2.6%가 유사한 댓글로 구성되어 있었다. 둘째, 사이버 여론 조작에 일반적으로 이용되는 기법인 과다한 중복 게시 행위와 실제로는 동일인이지만 여러 명으로 위장한 것으로 추정되는 사용자를 파악 할 수 있었다.

• 유통과학연구
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• 제12권4호
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• pp.85-92
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• 2014

Purpose - This study conducted empirical research on non-financial corporations listed on the stock exchange from 2001 to 2010, focusing on the effects of corporate governance on real earnings management of corporations. In particular, this study examined primarily the impact of the largest shareholder who could use earnings management to pursue his own self-interest, and foreign investors who played a checking role against the largest shareholders. The study also reviewed the relationship between corporate governance and earnings management while also considering corporate growth. Research design, data, and methodology - As for the measurements of real earnings management, abnormal operating cash flow and abnormal production cost were utilized. As for the independent variables, share ratio of the largest shareholder and affiliate person (M) and share ratio of foreign investors (FT) were leveraged. This study excluded those organizations that had changed their fiscal years, those that had not submitted an audit report, corporations under supervision, delisted corporations, corporations that had changed their business type, and so on, from the non-financial corporations out of the publicly traded corporations whose fiscal year ended in December from 2001 to 2010 in addition, KIS values were utilized for the corporate financial data in the study. To verify whether management structure and growth had an impact on real earnings management of a corporation through empirical analysis, a multiple regression analysis model was applied. Result - First, as a result of the analysis, the share ratio (M) of the largest shareholder and affiliate person was found to have a significant positive correlation with abnormal cash flow from operations(ACF) and abnormal production cost (APD). When controlling the growth, the share ratio (M) of the largest shareholder and affiliate person was found to have an insignificant correlation with abnormal cash flow from operations(ACF) but a significant correlation with abnormal production cost (APD). Second, foreign ownership (FT) was found to have a significant positive correlation with abnormal cash flow from operations(ACF) and abnormal production cost (APD) at the confidence level of 1 percent when not including the growth dummy. When controlling the growth, foreign ownership (FT) was found to have a significant negative correlation with abnormal cash flow from operations (ACF) and with abnormal production cost (APD). Conclusion - The results imply that the largest shareholder is closely related to earnings management through real activities regardless of corporate growth. It is also possible to determine from these results that foreign investors are related to earnings management through real activities when not considering corporate growth, but that they would reduce earnings management in the case of considering the growth. Thus, this study verified along with the existing studies that foreign investors were conducting the control function on controlling shareholders.

• 산업경영시스템학회지
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• 제44권4호
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• pp.169-176
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• 2021

Maritime monitoring requirements have been beyond human operators capabilities due to the broadness of the coverage area and the variety of monitoring activities, e.g. illegal migration, or security threats by foreign warships. Abnormal vessel movement can be defined as an unreasonable movement deviation from the usual trajectory, speed, or other traffic parameters. Detection of the abnormal vessel movement requires the operators not only to pay short-term attention but also to have long-term trajectory trace ability. Recent advances in deep learning have shown the potential of deep learning techniques to discover hidden and more complex relations that often lie in low dimensional latent spaces. In this paper, we propose a deep autoencoder-based clustering model for automatic detection of vessel movement anomaly to assist monitoring operators to take actions on the vessel for more investigation. We first generate gridded trajectory images by mapping the raw vessel trajectories into two dimensional matrix. Based on the gridded image input, we test the proposed model along with the other deep autoencoder-based models for the abnormal trajectory data generated through rotation and speed variation from normal trajectories. We show that the proposed model improves detection accuracy for the generated abnormal trajectories compared to the other models.

• 한국항공운항학회지
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• 제17권3호
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• pp.32-39
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• 2009

Due to the lack of navigable airspace caused by worldwide air traffic increases, air traffic control(ATC) services are becoming more complex, which results in the increase of aircraft accidents. To cope with these challenges, major aviation institutes abroad are actively conducting research regarding the human factors affecting controllers but as of late, no such specialized activities have been found in Korea. Due to the dynamic attributes of ATC operations, management of controller's situation awareness(SA) and workload, and knowledge on the impact of abnormal aircraft to controllers are very important. Furthermore, using actual flight data of each country will lead to valuable results, because individually, it has different airspace characteristics and air traffic volumes. This study assumed that air traffic difficulties would affect the controller's SA and workload. To testify the above hypothesis, the abnormal air traffic situations are simulated by using ATC simulator. The findings indicated that the effect of traffic situations containing abnormal aircraft on the controller's SA and workload, it led to demand increase and supply decrease in SA, and increased mental demand, temporal demand, effort and mean workload score in the workload.

• 대한약학회:학술대회논문집
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• 대한약학회 2003년도 Proceedings of the Convention of the Pharmaceutical Society of Korea Vol.2-2
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• pp.154.2-154.2
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• 2003

Mammalian cell cycles are tightly regulated by cyclins, cyclin dependent kinase (CDK), Retinoblatoma (Rb) protein, and cellular CDK inhibitors (CDKI). Cyelin dependent kinases (CDK) are key enzymes regulating eukaryotic cell cycle. And also it is recognized that the abnormal increase of CDK activities is one of the common events in human cancer and CDK inhibitors have therapeutic values in cancer treatment. Until now it is known that over 10 different CKDs participate in cell cycle regulation. (omitted)

• 대한한방내과학회지
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• 제24권1호
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• pp.144-150
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• 2003

Back pains include pain in one or both side costa portion and lateral abdomen. There are different kinds of flank-related disease such as intercostal nerve pain, chronic gastritis, duodenitis, herpes zoster, pepticulcer, cholecystitis, cholelithiasis and so on. Back pain arises from pathological abnormal activities. On the other hand psychogenic pains are caused by psychogenic factors without pathological abnormal activities. This is similar to KiWol back pain, which resulted from psychogenic factors like stress, anxiety, anger and etc. In oriental medicine, KiWol is the state of depression of Ki, and Shihosogansan used to treat the back pain diagnosed as stagnation of the liver Ki. So, we decided to apply Shihosogansan to a patient who suffered from back pain diagnosed as stagnation of the liver Ki. Therefore the patient treated with Shihosogansan and improved in consciousness symptoms, so we report it for the better treatment.

• 한국전자통신학회논문지
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• 제12권6호
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• pp.1233-1242
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• 2017

범죄 위험을 예방하기 위한 다양한 시도가 이루어지고 있다. 옥외활동 하는 보행자들이 범죄자들의 공격을 받는 경우 중의 하나는 비정상적인 건강상태이다. 술에 만취하여 정상 보행을 지속하지 못하는 심신미약 상태가 노출되었을 때, 범행 대상이 되는 경우가 범죄 사례 분석을 통하여 나타나고 있다. 본 연구에서는 옥외활동에서 감지할 수 있는 개인의 상태 추정 방안을 제안한다. 센서와 센서의 이벤트 정보전송을 위하여 별도의 단말기를 장착하는 불편을 피하기 위하여 스마트폰에 내장되어 있는 3축 가속도 센서를 이용하여 비정상적인 상태를 추정할 수 있는데, 3축 가속도를 통하여 측정한 각 축으로의 운동량을 산출하고 시간의 흐름에 따라 분석함으로써 사용자의 상태를 추정할 수 있다. 시간의 흐름을 일정한 간격으로 구분하고 각 시간대역에서의 활동 패턴을 인지하고 정상과 비정상을 구분할 수 있다. 본 연구에서는 비정상 상태를 구분하기 위하여 가속도 센서의 각 방향으로의 운동량과 운동에너지 총량을 계산한 것과 에너지 총량을 푸리에 변환한 값을 비교하여 평가하였다.

• 인터넷정보학회논문지
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• 제23권2호
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• pp.37-44
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• 2022

With the outbreak of COVID-19, non-face-to-face activities such as remote learning and telecommuting have increased rapidly. As a result, the number of people staying at home and the number of hours spent inside the house have also increased since the pandemic. Our team had previously worked on methods for detecting abnormal conditions in a person's health in various circumstances within the house by converging single sensor-based algorithms. In our previous research, we installed IoT sensors indoors to detect people emergency situations requiring aids, the scope of detection was limited to indoor space due to the limitation in sensors. In this study, we have come up with a system that integrates our previous study with a new method for detecting abnormal conditions in outdoor environments using outdoor security cameras and wearable devices. The proposed system enables users to be notified of emergency situations in both indoor and outdoor areas and respond to them as quickly as possible.