• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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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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• v.33 no.1
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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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.2
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• pp.335-343
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• 2014

It is more important to ensure the credibility of internet media which influence the public opinion. However, there are vague suspicions in public from the examples of manipulation of online reviews with anonymity. In this study, we explore the possibility of manipulating public opinion in online web sites. We investigate the characteristics of comments posted by users on web sites and compare each comments by using the cosine similarity function. Our result shows followings. First, we found a correlation between the similarities of comments and the article ranks in the web sites. Second, it is possible to identify abnormal user activities indicating excessive multiple posting, double posting and astroturf activities.

• Journal of Distribution Science
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• v.12 no.4
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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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.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.17 no.3
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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.

• Proceedings of the PSK Conference
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• 2003.10b
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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)

• The Journal of Internal Korean Medicine
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• v.24 no.1
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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.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1233-1242
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• 2017

Various attempts have been made to prevent crime risk. One of the cases where outdoor pedestrians are attacked by criminals is the abnormal health condition. When a mental or mental condition that can not sustain normal walking due to drunkenness is exposed, the case of being a crime is revealed through crime case analysis. In this study, we propose a method for estimating the state of an individual that can be detected in outdoor activities. In order to avoid the inconvenience of installing a separate terminal for event information transmission of sensors and sensors, it is possible to estimate an abnormal state by using a 3-axis acceleration sensor built in a smart phone. The state of the user can be estimated by analyzing the momentum of the user and analyzing it with the passage of time. It is possible to distinguish the flow of time at regular intervals, to recognize the activity patterns in each time band, and to distinguish between normal and abnormal. In this study, we have evaluated the total amount of kinetic energy and kinetic energy in each direction of the acceleration sensor and the Fourier transformed value of the total energy amount to distinguish the abnormal state.

• Journal of Internet Computing and Services
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• v.23 no.2
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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.