• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.2
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• pp.167-174
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• 2014

In this paper, we address a task allocation problem for a robot team that performs a search and attack mission. The robots are limited in sensing and communication capabilities, and carry different types of resources that are used to attack a target. The environment is uncertain and dynamic where no prior information about targets is given and dynamic events unpredictably happen. The goal of robot team is to collect total utilities as much as possible by destroying targets in a mission horizon. To solve the problem, we propose a distributed task allocation framework incorporated with effective resource management based on resource welfare. The framework we propose enables the robot team to retain more robots available by balancing resources among robots, and respond smoothly to dynamic events, which results in system performance improvement.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.62.1-62.1
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• 2019

Current large observational projects perform both static and dynamic sky surveys. The Thirty-Minute Target of Opportunity (TMT) is the project focusing on the dynamic sky survey using Korea Microlensing Telescope Network (KMTNet) that is the best observing system to investigate the dynamic sky. TMT aims to perform and experiment on following components : 1) to select transient or variable sources having hour to day scale cadences for future science cases, 2) to optimize the observation strategy for these objects, 3) to provide automated photometric pipelines for the time series data, and 4) to test the data release environment for all astronomers. In the near future, it is expected that a huge number of events will be alerted through large area surveys such as LSST. Therefore, the TMT project will provide opportunities to prepare the future large survey era as well as to understand the nature of interesting astronomical events.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.592-599
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• 2020

This paper proposes a Convolutional Recurrent Neural Net (CRNN) structure that can simultaneously reflect both static and dynamic characteristics of seismic waveforms for various earthquake events classification. Addressing various earthquake events, including not only micro-earthquakes and artificial-earthquakes but also macro-earthquakes, requires both effective feature extraction and a classifier that can discriminate seismic waveform under noisy environment. First, we extract the static characteristics of seismic waveform through an attention-based convolution layer. Then, the extracted feature-map is sequentially injected as input to a multi-input single-output Long Short-Term Memory (LSTM) network structure to extract the dynamic characteristic for various seismic event classifications. Subsequently, we perform earthquake events classification through two fully connected layers and softmax function. Representative experimental results using domestic and foreign earthquake database show that the proposed model provides an effective structure for various earthquake events classification.

• The Journal of the Acoustical Society of Korea
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• v.23 no.4E
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• pp.112-119
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• 2004

This paper presents a method for the automatic recognition of pitch accents with no prior knowledge about the phonetic content of the signal (no knowledge of word or phoneme boundaries or of phoneme labels). The recognition algorithm used in this paper is a time-delay recurrent neural network (TDRNN). A TDRNN is a neural network classier with two different representations of dynamic context: delayed input nodes allow the representation of an explicit trajectory F0(t), while recurrent nodes provide long-term context information that can be used to normalize the input F0 trajectory. Performance of the TDRNN is compared to the performance of a MLP (multi-layer perceptron) and an HMM (Hidden Markov Model) on the same task. The TDRNN shows the correct recognition of $91.9{\%}\;of\;pitch\;events\;and\;91.0{\%}$ of pitch non-events, for an average accuracy of $91.5{\%}$ over both pitch events and non-events. The MLP with contextual input exhibits $85.8{\%},\;85.5{\%},\;and\;85.6{\%}$ recognition accuracy respectively, while the HMM shows the correct recognition of $36.8{\%}\;of\;pitch\;events\;and\;87.3{\%}$ of pitch non-events, for an average accuracy of $62.2{\%}$ over both pitch events and non-events. These results suggest that the TDRNN architecture is useful for the automatic recognition of pitch accents.

• Earthquakes and Structures
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• v.8 no.4
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• pp.859-887
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• 2015

Structural health monitoring (SHM) has gained in popularity in recent years since it can assess the performance and condition of instrumented structures in real time and provide valuable information to the asset's manager and owner. Operational modal analysis plays an important role in SHM and it involves the determination of natural frequencies, damping ratios and mode shapes of a constructed structure based on measured dynamic data. This paper presents the operational modal analysis and seismic response characterization of the Tsing Ma Suspension Bridge of 2,160 m long subjected to different earthquake events. Three kinds of events, i.e., short-distance, middle-distance and long-distance earthquakes are taken into account. A fast Bayesian modal identification method is used to carry out the operational modal analysis. The modal properties of the bridge are identified and compared by use of the field monitoring data acquired before and after the earthquake for each type of the events. Research emphasis is given on identifying the predominant modes of the seismic responses in the deck during short-distance, middle-distance and long-distance earthquakes, respectively, and characterizing the response pattern of various structural portions (deck, towers, main cables, etc.) under different types of earthquakes. Since the bridge is over 2,000 m long, the seismic wave would arrive at the tower/anchorage basements of the two side spans at different time instants. The behaviors of structural dynamic responses on the Tsing Yi side span and on the Ma Wan side span under each type of the earthquake events are compared. The results obtained from this study would be beneficial to the seismic design of future long-span bridges to be built around Hong Kong (e.g., the Hong Kong-Zhuhai-Macau Bridge).

• Child Studies in Asia-Pacific Contexts
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• v.2 no.2
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• pp.77-90
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• 2012

The present study investigated infants' ability to form a category of a support relation (i.e., "on") when the objects depicting the relation were perceptually simple versus more complex. Twenty Korean infants of 14 months were habituated to dynamic support events with objects that were either simple or more complex in appearance. They were then tested with events that differed from the habituation events in the specific objects, spatial relation, or both. Infants formed a support category whether familiarized to simple or complex objects, looking significantly longer at test events with a novel than familiar relation. The results indicate that at 14 months of age, object features do not impact infants' ability to form a categorical representation of support.

• Journal of Astronomy and Space Sciences
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• v.25 no.2
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• pp.113-128
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• 2008

Solar wind dynamic pressure enhancements are known to cause various types of disturbances to the magnetosphere. In particular, dynamic pressure enhancements may affect the evolution of magnetic storms when they occur during storm times. In this paper, we have investigated the statistical significance and features of dynamic pressure enhancements during magnetic storm times. For the investigation, we have used a total of 91 geomagnetic storms for 2001-2003, for which the Dst minimum $(Dst_{min})$ is below -50 nT. Also, we have imposed a set of selection criteria for a pressure enhancement to be considered an event: The main selection criterion is that the pressure increases by ${\geq}50%\;or\;{\geq}3nPa$ within 30 min and remains to be elevated for 10 min or longer. For our statistical analysis, we define the storm time to be the interval from the main Dst decrease, through $Dst_{min}$, to the point where the Dst index recovers by 50%. Our main results are summarized as follows. $(i){\sim}$ 81% of the studied storms indicate at least one event of pressure enhancements. When averaged over all the 91 storms, the occurrence rate is ${\sim}$ 4.5 pressure enhancement events per storm and ${\sim}$ 0.15 pressure enhancement events per hour. (ii) The occurrence rate of the pressure enhancements is about three times higher for CME-driven storm times than for CIR-driven storm times. (iii) Only 21.1% of the pressure enhancements show a clear association with an interplanetary shock. (iv) A large number of the pressure enhancement events are accompanied with a simultaneous change of IMF $B_y$ and/or $B_z$: For example, 73.5% of the pressure enhancement events are associated with an IMF change of either $|{\Delta}B_z|>2nT\;or\;|{\Delta}B_y|>2nT$. This last finding suggests that one should consider possible interplay effects between the simultaneous pressure and IMF changes in many situations.

• Journal of Korea Multimedia Society
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• v.7 no.6
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• pp.767-780
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• 2004

Interaction requires dynamic relationship between objects. In ubiquitous computing environment, interaction between human and the environment is implied. Tactile interaction has so far been less addressed, while tactile sensation should be an important topic in the field of multimedia study. This paper describes development of a novel PVDF (Polyvinylidene Fluoride) dynamic tactile sensor and associated experiments. PVDF dynamic tactile sensors detect touch events applied to the sensor skin by low frequency components of the signal. Rubber skin-covered sensing material was mounted on the bones. Robust performance with low noise was figured out in our robotic experiment. Whereas most conventional sensors are interested in measurement, our dynamic tactile sensor is sensitive to change of state, which could be a key for economic understanding of happenings in the dynamic world. We note that dynamic sensing uses motion as a part of sensing modality We suggest that dynamic sensing be understood in technological terms in the perspective of interactive media and ubiquitous computing.

• ETRI Journal
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• v.39 no.5
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• pp.683-694
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• 2017

Several studies have focused on multimedia transmission over wireless sensor networks (WSNs). In this paper, we propose a comprehensive and robust model to transmit images over cognitive radio WSNs (CRWSNs). We estimate the spectrum sensing frequency and evaluate its impact on the peak signal-to-noise ratio (PSNR). To enhance the PSNR, we attempt to maximize the number of pixels delivered to the receiver. To increase the probability of successful image transmission within the maximum allowed time, we minimize the average number of packets remaining in the send buffer. We use both single- and multi-channel transmissions by focusing on critical transmission events, namely hand-off (HO), No-HO, and timeout events. We deploy our advanced updating method, the dynamic parameter updating procedure, to guarantee the dynamic adaptation of model parameters to the events. In addition, we introduce our ranking method, named minimum remaining packet best channel selection, to enable us to rank and select the best channel to improve the system performance. Finally, we show the capability of our proposed image scrambling and filtering approach to achieve noticeable PSNR improvement.

• Journal of the Korean Statistical Society
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• v.27 no.3
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• pp.279-288
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• 1998

We propose a multiprocess dynamic Poisson model for the analysis of Poisson process with the covariates. The algorithm for the recursive estimation of the parameter vector modeling time-varying effects of covariates is suggested. Also the algorithm for forecasting of numbers of events at the next time point based on the information gathered until the current time is suggested.