• Korean Journal of Clinical Pharmacy
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• v.32 no.3
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• pp.226-237
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• 2022

Background: Monoclonal antibodies for the treatment of patients with different types of cancer, such as cetuximab, have been widely used for the past 10 years in oncology. Although drug information package insert contains some representative adverse events which were observed in the clinical trials for drug approval, the overall adverse event patterns on the real-world cetuximab use were less investigated. Also, there have been no published papers that deal with the full spectrums of adverse drug events of cetuximab using national-wide drug safety surveillance systems. Methods: In this study, we detected new adverse event signals of cetuximab in the Korea Adverse Event Reporting System (KAERS) by utilizing proportional reporting ratios, reporting odds ratios, and information components indices. Results: The KAERS database included 869,819 spontaneous adverse event reports, among which 2,116 reports contained cetuximab. We compared the labels of cetuximab among the United States, European Union, Australia, Japan, and Korea to compare the current labeling information and newly detected signals of our study. Some of the signals including hyperkeratosis, tenesmus, folliculitis, esophagitis, neuralgia, disseminated intravascular coagulopathy, and skin/throat tightness were not labeled in the five countries. Conclusion: We identified new signals that were not known at the time of market approval.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.647-652
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• 1998

The YGN Units 3&4 plant conditions during shutdown operation were reviewed to identified the possible even scenarios following the loss of shutdown cooling. The Thermal hydraulic analyses were performed for the five cases of RCS configurations under the worst event scenario, unavailable secondary cooling and no RCS inventory makeup, using the RELAP5/MOD3.2 code to investigate the plant behavior, From the analyses results, times to boil, times to core uncovery and times to core heat up were estimated to determined the containment closure time to prevent the uncontrolled released of fission products to atmosphere, These data provide useful information to the abnormal procedure to cope with event.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.137-142
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• 2019

This paper Various services exist to detect and monitor abnormal event. However, most services focus on fires and gas leaks. so It is impossible to prevent and respond to emergency situations for the elderly and severely disabled people living alone. In this study, AI model is designed and compared to detect abnormal event of heart rate signal which is considered to be the most important among various bio signals. Specifically, electrocardiogram (ECG) data is collected using Physionet's MIT-BIH Arrhythmia Database, an open medical data. The collected data is transformed in different ways. We then compare the trained AI model with the modified and ECG data.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.114-121
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• 2010

Based on a complex event processing technique, an abuse pattern monitoring method is developed to provide an real-time detection. CEP is a technique to find complex event pattern in a massive information system. In this study, the events occurred by game-play are observed to be against the rules using CEP. User abuse patterns are pre-registered in CEP engine. And CEP engine monitors user abuse after aggregating the game data transferred by game logging server.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.869-870
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• 2006

In this study, we proposed an algorithm which can detect the walking event in hemiplegic patient using three axis acceleration signal. Twenty hemiplegic patients were participated in an experiment on a level corridor. To evaluate the accuracy, we compared the time difference between the detected event and signal from FSR-Sensor. Consequently, the mean difference of 46.1ms was obtained and it suggests that the proposed method is effective to detect the walking event in hemiplegic patient. In future, these results could be used to evaluate the walking ability in hemiplegic patient in clinical practice.

• Korean Journal of Computational Design and Engineering
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• v.19 no.1
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• pp.29-40
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• 2014

Conceptual Modeling is the process of abstracting a model from a real or proposed system. It is probably the most important aspect of a simulation study. Relate works show that the elementary developers devoted little time to understanding how the systems actually worked, namely they didn't build appropriate conceptual model. Thus, the result of simulation is inconsistent because it depends on developer's competence. Although many researchers suggested various techniques enabling developer to build conceptual model, there were several limitations. In this study, to overcome the limitations of existing techniques, we proposed COMBINE-DES (COnceptual Model BuildINg framEwork using ontology for Discrete Event Simulation). The COM-BINE-DES supports expediting the conceptual modeling with Solution ontology generated by Domain ontology and Simulation ontology. Moreover, it provides consistent simulation result regardless of repeated modeling.

• Proceedings of the KSMRM Conference
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• 2001.11a
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• pp.111-111
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• 2001

목적： To evaluate the feasibility of the event-related functional MR study using power grip studying the hand motor system 대상 및 방법： Event-related functional MRI was performed on a 1.5T MR unit in seven norm volunteers (man=7, right-handedness=2, left-handedness=5, mean age： 25 years). A single-shot GRE-EPI sequence (TR/TE/flip angle： 1000ms/40ms/90, FOV = 240 mm matrix= 64$\times$64, slice thickness/gap = 5mm/0mm, 7 true axial slices) was used for functiona MR images. A flow-sensitive conventional gradient echo sequence (TR/TE/flip angl 50ms/4ms/60) was used for high-resolution anatomical images. To minimize the gross hea motion, neck-holders (MJ-200, USA) were used. A series of MR images were obtained in axial planes covering motor areas. To exclude motion-corrupted images, all MR images wer surveyed in a movie procedure and evaluated using the estimation of center of mass of ima signal intensities. Power grip task consisted of the powerful grip of all right fingers and hand movement ta used very fast right finger tapping at a speed of 3 per 1 second. All tasks were visual-guid by LCD projector (SHARP, Japan). Two tasks consisted of 134 phases including 7 activatio and 8 rest periods. Active stimulations were performed during 2 seconds and rest period were 15 seconds and total scan time per one task was 2 min 14 sec. Statistical maps we obtained using cross-correlation method. Reference vector was time-shifted by 4 seconds an Gaussian convolution with a FWHM of 4 seconds was applied to it. The threshold in p val for the activation sites was set to be 0.001. All mapping procedures were peformed usin homemade program an IDL (Research Systems Inc., USA) platform. We evaluated the activation patterns of the motor system of power grip compared to hand movement in t event-related functional MRI.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1670-1683
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• 2017

Mitotic event recognition is a crucial and challenging task in biomedical applications. In this paper, we introduce the slow feature analysis and propose a fully-automated mitotic event recognition method for cell populations imaged with time-lapse phase contrast microscopy. The method includes three steps. First, a candidate sequence extraction method is utilized to exclude most of the sequences not containing mitosis. Next, slow feature is learned from the candidate sequences using slow feature analysis. Finally, a hidden conditional random field (HCRF) model is applied for the classification of the sequences. We use a supervised SFA learning strategy to learn the slow feature function because the strategy brings image content and discriminative information together to get a better encoding. Besides, the HCRF model is more suitable to describe the temporal structure of image sequences than nonsequential SVM approaches. In our experiment, the proposed recognition method achieved 0.93 area under curve (AUC) and 91% accuracy on a very challenging phase contrast microscopy dataset named C2C12.

• International Journal of Contents
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• v.16 no.1
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• pp.25-33
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• 2020

We develop a simulation method that affords very high variability of virtual pedagogical situations involving many independent plans, still achieves authoring (or implementation) scalability. While each individual plan would be coherently drawn up by an agent for its respective goal, those independently-made plans might be coincidentally intertwined in their execution. The inevitable non-determinism involved in this multi-event plan encompassing pre-planned and unforeseen events is resolved by (multi-phase) dynamic planning and articulated sequencing of events in contrast to static planning and monolithic authoring in conventional narrative systems. Connections between events are dictated by their associated rules and their actual connections are dynamically determined in execution time by current conditions of background-world. This unified connection scheme across pre-planned and unforeseen events allows a multi-plan, multi-agent situation to be coherently planned and executed in a global scale. To further the variability of a situation, the inter-event coupling is made in a fine level of action along with a limited episteme of each agent involved. We confirm analytically the viability of our approach with respect to the situation variability and authoring scalability, and demonstrate its practicality with an implementation of a composite situation.

• Smart Media Journal
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• v.8 no.4
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• pp.72-79
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• 2019

The automated demand response (DR) program encourages consumers to participate in grid operation by reducing power consumption or deferring electricity usage at peak time automatically. However, successful deployment of the automated DR program sphere needs careful assessment of appliances load profile (ALP). To this end, the recent method estimates frequency, consistency, and peak time consumption parameters of the daily ALP to compute their potential score to be involved in the DR event. Nonetheless, as the daily ALP is subject to varying with respect to the DR time ALP, the existing method could lead to an inappropriate estimation; in such a case, inappropriate appliances would be selected at the automated DR operation that effected a consumer comfort level. To address this challenge, we propose a more proper method, in which all the three parameters are calculated using ALP that overlaps with DR time, not the total daily profile. Furthermore, evaluation of our method using two public residential electricity consumption data sets, i.e., REDD and REFIT, shows that our energy management systems (EMS) could properly match a DR target. A more optimal selection of appliances for the DR event achieves a power consumption decreasing target with minimum comfort level reduction. We believe that our approach could prevent the loss of both utility and consumers. It helps the successful automated DR deployment by maintaining the consumers' willingness to participate in the program.