• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.273-281
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• 2022

In this paper, we propose a robot sound recognition system that detects various sound events. The proposed system is designed to detect various sound events in real-time by using a microphone on a robot. To get real-time performance, we use a VGG11 model which includes several convolutional neural networks with real-time normalization scheme. The VGG11 model is trained on augmented DB through 24 kinds of various environments (12 reverberation times and 2 signal to noise ratios). Additionally, based on random forest algorithm, a decision logic is also designed to generate event signals for robot applications. This logic can be used for specific classes of acoustic events with better performance than just using outputs of network model. With some experimental results, the performance of proposed sound recognition system is shown on real-time device for robots.

• Journal of Information Processing Systems
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• v.8 no.2
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• pp.213-240
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• 2012

Safety critical systems, real time systems, and event-based systems have a complex set of events and their own interdependency, which makes them difficult to test ma Safety critic Safety critical systems, real time systems, and event-based systems have a complex set of events and their own interdependency, which makes them difficult to test manually. In order to cut down on costs, save time, and increase reliability, the model based testing approach is the best solution. Such an approach does not require applications or codes prior to generating test cases, so it leads to the early detection of faults, which helps in reducing the development time. Several model-based testing approaches have used different UML models but very few works have been reported to show the generation of test cases that use events. Test cases that use events are an apt choice for these types of systems. However, these works have considered events that happen at a user interface level in a system while other events that happen in a system are not considered. Such works have limited applications in testing the GUI of a system. In this paper, a novel model-based testing approach is presented using business events, state events, and control events that have been captured directly from requirement specifications. The proposed approach documents events in event templates and then builds an event-flow model and a fault model for a system. Test coverage criterion and an algorithm are designed using these models to generate event sequence based test scenarios and test cases. Unlike other event based approaches, our approach is able to detect the proposed faults in a system. A prototype tool is developed to automate and evaluate the applicability of the entire process. Results have shown that the proposed approach and supportive tool is able to successfully derive test scenarios and test cases from the requirement specifications of safety critical systems, real time systems, and event based systems.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.12-15
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• 2003

Korea Institute of Geoscience and Mineral Resources(KIGAM) is operating Wonju Korea Seismic Research Station(KSRS), 29 regional seismic research stations and 5 Korea-China joint seismic stations in China. Also KIGAM is operating Korea Earthquake Monitoring System (KEMS) to archive the real-time data stream and to determine event parameters (epicenter, origin time, and magnitude) by the automatic processing and analyst review. To do this, KEMS used KIGAM's regional seismic network and other institute's network in a near real-time base. From Dec. 1, 2001 to Nov. 30, 2002, 3,827 seismic events were analyzed in a automatic processing procedure and finally 3,437 events were analyzed by analyst and archived. But problem is this event catalog includes not only natural earthquake, but also artificial events produced by the blast. More than 80 % events were concentrated in daytime and many events were concentrated in the confirmed blast sites, Pyeongyang, Pocheon, Yeongjong-do, Donghae city, etc. Because these artificial events are a major potential cause of error when estimating the seismicity of a specific region, discrimination procedure has to be developed in the first place.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.57-64
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• 2012

Multiplayer, real-time games are a kind of soft real-time systems because a game server has to respond to requests from many clients within specified time constraints. Client events have different timeliness and consistency requirements according to their nature in the game world. These requirements lead to different priorities on CPU processing. Events can be divided into different groups, depending on their consistency degree and priority. To handle these events with different priority and meet their timing constraints, we propose a priority-based group task scheduling policy in this paper. The number of clients or events requested by each client may be increased temporarily. In the presence of transient overloading, the game server needs to allocate more CPU bandwidth to serve an event with the higher priority level preferentially. The proposed scheduling policy is capable of enhancing real-time performance of the entire system by maximizing the number of events with higher priority completed successfully within their deadlines. The performance of this policy is evaluated through extensive simulation experiments.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.342-348
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• 2017

Precursor analysis is widely used in the nuclear industry to judge the significance of events relevant to safety. However, in case of events that may damage equipment through effects that are not ordinary functional dependencies, the analysis may not always fully appreciate the potential for further evolution of the event. For fires, which are one class of such events, this paper discusses modelling challenges that need to be overcome when performing a probabilistic precursor analysis. The events used to analyze are selected from the Organisation for Economic Cooperation and Development (OECD) Fire Incidents Records Exchange (FIRE) Database.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.669-670
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• 2008

In this paper, we present a real-time system to detect abnormal events on gas pipes, based on the signals which are observed through the audio sensors attached on them. First, features are extracted from these signals so that they are robust to noise and invariant to the distance between a sensor and a spot at which an abnormal event like an attack on the gas pipes occurs. Then, a classifier is constructed to detect abnormal events using neural networks. It is a combination of two neural network models, a Gaussian mixture model and a multi-layer perceptron, for the reduction of miss and false alarms. The former works for miss alarm prevention and the latter for false alarm prevention. The experimental result with real data from the actual gas system shows that the proposed system is effective in detecting the dangerous events in real-time with an accuracy of 92.9%.

• Journal of The Korean Astronomical Society
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• v.26 no.2
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• pp.135-139
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• 1993

Events of eclipses as well as other major astronomical events observable in the eastern sector of Asian continent are computed and checked with astronomical records of antiquity. Particular attention was given to two types of the events recorded in remaining records of Dangun Chosun Period (DCP): (1) concentration of major planets near the constellation of Nu-Sung $(\beta\;Aries)$ and (2) a large ebb-tide. We find them most likely to have occurred in real time. i.e., when the positions of the sun, moon, and planets happen to be aligned in the most appropriate position. For solar eclipses data, however, we find among 10 solar eclipse events recorded, only 6 of them are correct up to months, implying its statistical significance is no less insignificant. We therefore conclude that the remaining history books of DCP indeed contains important astronomical records, thereby the real antiquity of the records of DCP cannot be disproved.

• Journal of Korea Water Resources Association
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• v.45 no.6
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• pp.531-544
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• 2012

This study suggested the parameter estimation method for given rainfall events to be properly expressed by the beta distribution. For this purpose, this study compared the characteristics of probability density function with the parameter proposed considering the cases with and without addition to the rainfall peak, and the cases of using the real hyetograph and the rearranged hyetograph about the rainfall peak. As an example, this study analyzed the independent rainfall events at Seoul in 2010 and the annual maximum independent rainfall events from 1961 to 2010. The results derived are as follows. First, this study confirmed the necessity of additional consideration on rainfall peak to mimic the real hyetograph of rainfall events by the beta distribution. Second, this study confirmed the case of using rearranged hyetograph about the rainfall peak derived a better beta distribution to well mimic the characteristics of real rainfall than the case using the real hyetograph.

• Korean Journal of Child Studies
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• v.24 no.1
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• pp.61-76
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• 2003

This study investigated children's cognition of physically impossible televised events by age and types of tasks. The 67 subjects were 3-, 5-, and 7-year-old children from 1 day care center and 1 elementary school in Seoul. Children's responses were taped and transcribed. Cognition about the events were measured by recognition of impossibility, possibility of replication, and reasons for the possibility of replication of the events. Data were analysed by ANOVA(repeated measure) and $Scheff{\acute{e}}$ test. Children's cognitions about the events varied by age groups. Three-year-old children's recognition of the 3 tasks was different from that of the 5-and 7-year-old children; while 3-year-olds interpreted the events on TV as real, 5- and 7-year-olds considered them to be unreal.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.91-98
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• 2016

We propose a method to train a model that can predict the probability of a crime being committed. CCTV data by matching criminal events are required to train the crime prediction model. However, collecting CCTV data appropriate for training is difficult. Thus, we collected actual criminal records and converted them to an appropriate format using variables by considering a crime prediction environment and the availability of real-time data collection from CCTV. In addition, we identified new specific crime types according to the characteristics of criminal events and trained and tested the prediction model by applying neural network partial least squares for each crime type. Results show a level of predictive accuracy sufficiently significant to demonstrate the applicability of CCTV to real-time crime prediction.