• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.59-66
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• 2019

According to the KT telecommunication statistics, people stayed inside their houses on an average of 11.9 hours a day. As well as, according to NSC statistics in the united states, people regardless of age are injured for a variety of reasons in their houses. For purposes of this research, we have investigated an abnormal event detection algorithm to classify infrequently occurring behaviors as accidents, health emergencies, etc. in their daily lives. We propose a fusion method that combines three classification algorithms with vision pattern, audio pattern, and activity pattern to detect unusual user events. The vision pattern algorithm identifies people and objects based on video data collected through home CCTV. The audio and activity pattern algorithms classify user audio and activity behaviors using the data collected from built-in sensors on their smartphones in their houses. We evaluated the proposed individual pattern algorithm and fusion method based on multiple scenarios.

• ETRI Journal
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• v.31 no.4
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• pp.463-465
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• 2009

In this letter, we present an event stream processing system that can evaluate a pattern query for a data sequence with predicates. We propose a pattern query language and develop a pattern query processing system. In our system, we propose novel techniques for run-time aggregation and negation processing and apply our system to stream data generated from vehicles to monitor unusual driving patterns.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.95-103
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• 2019

According to the Statistics Korea in 2017, the 10 leading causes of death contain a cardiac disorder disease, self-injury. In terms of these diseases, urgent assistance is highly required when people do not move for certain period of time. We propose an unusual event detection algorithm to identify abnormal user behaviors using dust, vision and activity sensors in their houses. Vision sensors can detect personalized activity behaviors within the CCTV range in the house in their lives. The pattern algorithm using the dust sensors classifies user movements or dust-generated daily behaviors in indoor areas. The accelerometer sensor in the smartphone is suitable to identify activity behaviors of the mobile users. We evaluated the proposed pattern algorithms and the fusion method in the scenarios.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.4
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• pp.106-111
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• 2013

The heavy snow event occurred on JAN 4, 2010 brought huge disaster such as Gimpo International Airport runway closed, heavy delays of other airport, and property damage of 16 billion won. Though this heavy snow event is involved in the general synoptic scale heavy snow forecast, it recorded too much snow amount and longer duration than expected. To explain this unusual event, we used the conveyor belt theory. By combining the synoptic scale heavy snow forecast and the conveyor belt theory, the characteristics of heavy snow event was well explained.

• Journal of the korean society of oceanography
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• v.39 no.4
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• pp.207-211
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• 2004

We used long time series of hydrographic and biological variables to examine the ecosystem consequences of a rare, anomalous event in the south sea of Korea. The highest zooplankton biomass in 36 years of sampling occurred in April 1997. Zooplankton biomass exceeded 2 times than the long-term mean at 35% of the stations. Copepod abundance was low in April and June and also failed to show a seasonal peak in 1997. Mackerel (Scomber japonicus) catches were very low in spring 1997 and 1999, in spite of a positive correlation between zooplankton biomass and mackerel catches at lags of 0, 12 and 24 months. It was discussed that a high zooplankton biomass with low copepod abundance in April 1997 resulted from unusual high temperature and salps abundance. Water temperatures were ca. $2^{\circ}C$ higher than the long-term mean at the surface. Salps and doliolids (thaliaceans), especially the warm-water species Doliolum nationalis, dominated the zooplankton. An unusual incursion of the Tsushima Warm Current may have transported the thaliaceans into the area and/or produced favorable conditions for a bloom. This study suggested that taxonomic composition of zooplankton was important to decide mackerel catches.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.3
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• pp.169-174
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• 2002

When the long - lasting stationary fronts were pushed northward by the Pacific Highs in late July, mostly clear skies with intermittent showers were a typical weather of August in Korea. However, torrential rains and flash floods are now a seasonal event of August in recent years. Some meteorologists suspect this unusual phenomenon might be connected with the global change and are concerned about the possibility of change in summer climatic pattern in Korea. August of year 2002 must be remembered to be one of the record breaking months with respect to the rainfall events. In this paper, we analyzed the weather and crop data nationwide for August in 2002, and suggest a few countermeasures necessary to overcome the wet and cool summer impacts on agricultural sector.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11A
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• pp.1066-1072
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• 2010

In this paper we proposed a multi event handling surveillance system using multiple PTZ cameras. One event is assigned to each PTZ camera to detect unusual situation. If a new object appears in the scene while a camera is tracking the old one, it can not handle two objects simultaneously. In the second case that the object moves out of the scene during the tracking, the camera loses the object. In the proposed method, the nearby camera takes the role to trace the new one or detect the lost one in each case. The nearby camera can get the new object location information from old camera and set the seamless event link for the object. Our simulation result shows the continuous camera-to-camera object tracking performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.913-919
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• 2011

In this paper, we present a new efficient event detection algorithm for sensor networks with faults. We focus on multi-attributed events, which are sets of data points that correspond to interesting or unusual patterns in the underlying phenomenon that the network monitors. Conventional algorithms cannot detect some events because they treat only their own sensor readings which can be affected easily by environmental or physical problem. Our approach exploits spatio-temporal correlation of sensor readings. Sensor nodes exchange a fault-tolerant code encoded their own readings with neighbors, organize virtual sensor readings which have spatio-temporal correlation, and determine a result for multi-attributed events from them. In the result, our proposed algorithm provides improvement of detecting multi-attributed events and reduces the number of false-negatives due to negative environmental effects.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.95-103
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• 2019

The number of one person households has grown steadily over the recent past and the population of lonely and unnoticed death are also observed. The phenomenon of one person households has been occurred. In the dark side of society, the remarkable number of lonely and unnoticed death are reported among different age-groups. We propose an unusual event detection method which may give a remarkable solution to reduce the number of the death rete for people dying alone and remaining undiscovered for a long period of time. The unusual event detection method we suggested to identify abnormal user behavior in their lives using vision pattern, audio pattern, and dust pattern algorithms. Individually proposed pattern algorithms have disadvantages of not being able to detect when they leave the coverage area. We utilized a fusion method to improve the accuracy performance of each pattern algorithm and evaluated the technique with multiple user behavior patterns in indoor areas.

• Animal cells and systems
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• v.5 no.3
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• pp.253-262
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• 2001

Ligand-receptor clustering event is the most important step in leukocyte adhesion and spreading on endothelial cells. Intercellular adhesion molecule-1 (ICAM-1) has been shown to enhance leukocyte adhesion, but the molecular event during the process of adhesion is unclear. To visualize the dynamics of ICAM-1 movement during adhesion, we have engineered stable Chinese hamster ovary cell lines expressing ICAM-1 fused to a green fluorescent protein (IC1_GFP/CHO) and examined them under the fluorescence microscopy. The transfection of IC1_GFP alone in these cells was sufficient to support the adhesion of K562 cells that express $\alpha$L$\beta$2 (LFA-1) integrin stimulated by CBR LFA-1/2 mAb. This phenomenon was mediated by ICAM-1-LFA-1 interactions, as an mAb that specifically inhibits ICAM-1-LFA-1 interaction (RRl/l) completely abolished the adhesion of LFA-1＊ cells to IC1_ GFP/CHO cells. We found that the characteristic of adhesion was followed almost immediately (~10 min) by the rapid accumulation of ICAM-1 on CHO cells at a tight interface between the two cells. Interestingly, ICI_GFP/CHO cells projected plasma membrane and encircled approximately half surface of LFA-1+ cells, as defined by confocal microscopy. This unusual phenomenon was also confirmed on HUVEC after adhesion of LFA-1＊ cells. Neither cytochalasin D nor 2,3-butanedione 2-monoxime an inhibitor of myosin light chain kinase blocked LFA-1-mediated ICAM-1 clustering, indicating that actin cytoskeleton and myosin-dependent contractility are not necessary for ICAM-1 clustering. Taken together, we suggest that leukocyte adhesion to endothelial cells induces specialized form of ICAM-1 clustering that is distinct from immunological synapse mediated by T cell interaction with antigen presenting cells.