• The Bulletin of The Korean Astronomical Society
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• v.35 no.1
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• pp.48.1-48.1
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• 2010

Four of nine exoplanets found by microlensing were detected by the resonant caustic, which represents the merging of the planetary and central caustics at the position when the projected separation of a host star and a bounded planet is s~1. One of the resonant caustic lensing events, OGLE-2005-BLG-169, was a caustic-crossing high-magnification event with A_max ~800 and the source star was much smaller than the caustic, nevertheless the perturbation was not obviously apparent on the light curve of the event. In this paper, we investigate the perturbation pattern of the resonant caustic to understand why the perturbations induced by the caustic do not leave strong traces on the light curves of high-magnification events despite a small source/caustic size ratio. From this study, we find that the regions with small magnification excess around the center of the resonant caustic are rather widely formed, and the event passing the small-excess region produces a high-magnification event with a weak perturbation that is small relative to the amplification caused by the star and thus does not noticeably appear on the light curve of the event. We also find that the positive excess of the inside edge of the resonant caustic and the negative excess inside the caustic become stronger and wider as q increases, and thus the resonant caustic-crossing high-magnification events with the weak perturbation occur in the range of q $\leq$ 10-4. We determine the probability of the occurrence of events with the small excess $|\varepsilon|{\leq}3%$ in high-magnification events induced by a resonant caustic. As a result, we find that for the Earth-mass planets with a separation of ~2.5 AU the resonant caustic high-magnification events with the weak perturbation can occur with a significant frequen.

• ETRI Journal
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• v.39 no.6
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• pp.832-840
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• 2017

Recently, deep recurrent neural networks have achieved great success in various machine learning tasks, and have also been applied for sound event detection. The detection of temporally overlapping sound events in realistic environments is much more challenging than in monophonic detection problems. In this paper, we present an approach to improve the accuracy of polyphonic sound event detection in multichannel audio based on gated recurrent neural networks in combination with auditory spectral features. In the proposed method, human hearing perception-based spatial and spectral-domain noise-reduced harmonic features are extracted from multichannel audio and used as high-resolution spectral inputs to train gated recurrent neural networks. This provides a fast and stable convergence rate compared to long short-term memory recurrent neural networks. Our evaluation reveals that the proposed method outperforms the conventional approaches.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.989-997
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• 2018

Massive event stream brings us great challenges in its volume, velocity, variety, value and veracity. Picking up some valuable information from it often faces with long detection time, high memory consumption and low detection efficiency. Aiming to solve the problems above, an efficient complex event detection method based on NFA_HTS (Nondeterministic Finite Automaton_Hash Table Structure) is proposed in this paper. The achievement of this paper lies that we successfully use NFA_HTS to realize the detection of complex event from massive RFID event stream. Specially, in our scheme, after using NFA to capture the related RFID primitive events, we use HTS to store and process the large matched results, as a result, our scheme can effectively solve the problems above existed in current methods by reducing lots of search, storage and computation operations on the basis of taking advantage of the quick classification and storage technologies of hash table structure. The simulation results show that our proposed NFA_HTS scheme in this paper outperforms some general processing methods in reducing detection time, lowering memory consumption and improving event throughput.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.538-555
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• 2015

Event detection based on using features from a static grid can give poor results from the viewpoint of two main aspects: the position of the camera and the position of the event that is occurring in the scene. The former causes problems when training and test events are at different distances from the camera to the actual position of the event. The latter can be a source of problems when training events take place in any position in the scene, and the test events take place in a position different from the training events. Both issues degrade the accuracy of the static grid method. Therefore, this work proposes a method called a dynamic grid for event detection, which can tackle both aspects of the problem. In our experiment, we used the dynamic grid method to detect four types of event patterns: implosion, explosion, two-way, and one-way using a Multimedia Analysis and Discovery (MAD) pedestrian dataset. The experimental results show that the proposed method can detect the four types of event patterns with high accuracy. Additionally, the performance of the proposed method is better than the static grid method and the proposed method achieves higher accuracy than the previous method regarding the aforementioned aspects.

• Journal of environmental and Sanitary engineering
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• v.24 no.4
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• pp.102-111
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• 2009

In this study, Particulate carbon were determined from 1990 to 1995. The annual variation were investigated. The sampling was carried out using high volume air sampler. Average concentrations of EC and OC during the yellow sand event were $25.70{\mu}g/m^3$ and $13.91{\mu}g/m^3$, respectively, $22.10{\mu}g/m^3$ and $10.33{\mu}g/m^3$ during the non-yellow sand event. TC concentration of TSP were 10.7% during the yellow sand event and 20.6% during the non-yellow sand event. Average concentration rate of EC and OC of TC were 64.9% and 35.1%, respectively during the yellow sand event, 67.6% and 32.4% during the non-yellow sand event.

• Journal of Korean Neurosurgical Society
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• v.63 no.5
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• pp.598-606
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• 2020

Objective : The purpose of this study was to evaluate the impact of time interval between index event and stenting on the periprocedural risk of stenting for symptomatic carotid stenosis and to determine the optimal timing of stenting. Methods : This retrospective study included 491 (322 symptomatic [65.6%] and 169 asymptomatic [34.4%]) patients undergoing carotid stenting. The symptomatic patients were categorized into Day 0-3, 4-7, 8-10, 11-14, 15-21, and >21 groups according to the time interval between index event and stenting. Periprocedural (≤30 days) risk for clinical (any neurological deterioration) and radiological (new infarction on postprocedural diffusion-weighted imaging) events of stenting in each time interval versus asymptomatic stenosis was calculated with logistic regression analysis adjusted for confounders, and provided as odds ratio (OR) and 95% confidence interval (CI). Results : Overall clinical event rate (4.3%) of stenting for symptomatic carotid stenosis was higher than that for asymptomatic stenosis (1.2%; OR, 3.979 [95% CI, 1.093-14.489]; p=0.036). Stenting in Day 0-3 (13.2%; OR, 10.997 [95% CI, 2.333-51.826]; p=0.002) and Day 4-7 (8.3%; OR, 6.775 [95% CI, 1.382-33.227]; p=0.018) was associated with high risk for clinical events. However, the clinical event rates in stenting after 7 days from index event (Day 8-10, 1.8%; Day 11-14, 2.5%; Day 15-21, 0%; Day >21, 2.9%) were not different from that in stenting for asymptomatic stenosis. Overall radiological event rate (55.6%) in symptomatic stenosis was also higher than that in asymptomatic stenosis (35.5%; OR, 2.274 [95% CI, 1.553-3.352]; p<0.001). The high risk for radiological events was maintained in all time intervals (Day 0-3 : 55.3%; OR, 2.224 [95% CI, 1.103-4.627]; p=0.026; Day 4-7 : 58.3%; OR, 2.543 [95% CI, 1.329-4.949]; p=0.005; Day 8-10 : 53.6%; OR, 2.096 [95% CI, 1.138-3.889]; p=0.018; Day 11-14 : 57.5%; OR, 2.458 [95% CI, 1.225-5.021]; p=0.012; Day 15-21 : 55.6%; OR, 2.271 [95% CI, 1.099-4.764]; p=0.028; Day >21 : 54.8%; OR, 2.203 [95% CI, 1.342-3.641]; p=0.002). Conclusion : This study showed that as stenting was delayed, the periprocedural risk for clinical events decreased. The clinical event risk was high only in stenting within 7 days and comparable with that for asymptomatic stenosis in stenting after 7 days from index event, although the radiological event risk was not affected by stenting timing. Therefore, our results suggest that delayed stenting after 7 days from symptom onset is a safe strategy for symptomatic stenosis.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.927-938
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• 2023

The blanket plays an important role in fusion reactor and stands extremely high thermal and electromagnetic loads during operation situation and plasma disruption event, brings the need for precise thermal and electromagnetic analysis. Since the thermal field and EM field interact with each other nonlinearly, we develop a method of electromagnetic-thermal two-way coupling by using finite element software COMSOL. The coupling analyses of blanket under steady state and MD event are implemented and the results are analyzed. For steady state, the influences of coupling effects are relatively small but still recommended to be considered for a high precision analysis. The influence of thermal field on EM field can't be ignored under MD events. The variation of force density could cause a significant change in stress in certain parts of blanket. The influence of Joule heat during MD event is negligible, yet the potential temperature rise caused by induced current after MD event still needs to be researched.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.622-627
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• 1996

Detailed analysis of Feedwater Line Break (FLB) event for the fuel failure point of view are lack because the event was characterized as the increase in reactor coolant system (RCS) pressure. Up to now, the potential of the rapid system heatup case has been emphasized and comprehensively studied. The cooldown effects of FLB event is considered to be bounded by the Steam Line Break (SLB) event since the cooldown effect of SLB event is larger than that of the FLB event. This analysis provides a new possible path which can cause the fuel failure. The new path means that the fuel failure can occur under the heatup scenario because the Pressurizer Safety Valves (PSVs) open before the reactor trips. The 1000 MWe typical C-E plant FLB event assuming Loss of Offsite Power (LOOP) at the turbine trip has been analyzed as an example and the results show less than 1% of the fuel failure. The result is well within the acceptance criteria. In addition to that, a study was accomplished to prevent the fuel failure for the heatup scenario case as an example. It is found that giving the proper pressure gap between High Pressurizer Pressure Trip (HPPT) analysis setpoint and the minimum PSV opening pressure could prevent the fuel failure.

• Journal of Distribution Science
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• v.21 no.3
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• pp.93-100
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• 2023

Purpose: The purpose of this paper is to confirm whether stocks belonging to the distribution industry in Korea have reversals, following large daily stock price changes accompanied by large trading volumes. Research design, data, and methodology: We examined whether there were reversals after the event date when large-scale stock price changes appeared for the entire sample of distribution-related companies listed on the Korea Composite Stock Price Index from January 2004 to July 2022. In addition, we reviewed whether the reversals differed depending on abnormal trading volume on the event date. Using multiple regression analysis, we tested whether high trading volume had a significant effect on the cumulative rate of return after the event date. Results: Reversals were confirmed after the stock price shock in the Korean distribution industry and the return after the event date varied depending on the size of the trading volume on the event day. In addition, even after considering both company-specific and event-specific factors, the trading volume on the event day was found to have significant explanatory power on the cumulative rate of return after the event date. Conclusions: Reversals identified in this paper can be used as a useful tool for establishing a trading strategy.

• Genomics & Informatics
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• v.17 no.4
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• pp.41.1-41.12
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• 2019

Survival analysis mainly deals with the time to event, including death, onset of disease, and bankruptcy. The common characteristic of survival analysis is that it contains "censored" data, in which the time to event cannot be completely observed, but instead represents the lower bound of the time to event. Only the occurrence of either time to event or censoring time is observed. Many traditional statistical methods have been effectively used for analyzing survival data with censored observations. However, with the development of high-throughput technologies for producing "omics" data, more advanced statistical methods, such as regularization, should be required to construct the predictive survival model with high-dimensional genomic data. Furthermore, machine learning approaches have been adapted for survival analysis, to fit nonlinear and complex interaction effects between predictors, and achieve more accurate prediction of individual survival probability. Presently, since most clinicians and medical researchers can easily assess statistical programs for analyzing survival data, a review article is helpful for understanding statistical methods used in survival analysis. We review traditional survival methods and regularization methods, with various penalty functions, for the analysis of high-dimensional genomics, and describe machine learning techniques that have been adapted to survival analysis.