• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1117-1125
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• 2014

In a longitudinal study, subjects can experience same type of events repeatedly. Also, there may exist intermittent dropouts resulting in repeated observation gaps during which no recurrent events are observed. Furthermore, when such observation gaps have incomplete forms caused by the unknown termination times of observation gaps, ordinary approaches result in biased estimates. In this study, we investigate the effect of ignoring observation gaps and propose methods to overcome this problem. For estimating the distribution of unknown termination times, an interval-censored mechanism is applied and two cases are considered. Simulation studies are carried out to evaluate the performance of the proposed method. Conviction data of young drivers with several suspensions are analyzed to illustrate the suggested approach.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.8
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• pp.1179-1185
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• 2012

This paper presents a new approach for the detection of seismic events using accumulated changes on time-frequency domain and variable threshold. To detect seismic P-wave arrivals with rapidness and accuracy, it is that the changes on the time and the frequency domains are simultaneously used. Their changes are parameters appropriated to reflect characteristics of earthquakes over moderate magnitude(${\geq}$ magnitude 4.0) and microearthquakes. In addition, adaptively controlled threshold values can prevent false P-wave detections due to low SNR. We tested our method on real earthquakes those have various magnitudes. The proposed algorithm gives a good detection performance and it is also comparable to STA/LTA algorithm in computational complexity. Computer simulation results shows that the proposed algorithm is superior to the conventional popular algorithm (STA/LTA) in the seismic P-wave detection.

• Journal of the Korean Society of Safety
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• v.13 no.3
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• pp.80-87
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• 1998

This paper presents a study on the development of discharge model and computer program for assessing the risk of electrostatic discharge(ESD) of charged human body This ESD event is modelled as a two-body problem using spherical conductors, simulating the approach of a charged conductor (human body) to a second conductor (electronic equipment). The charge/discharge process for the model is formulated as a matrix of equations by Maxwell's method. Body potentials, energies and the charge transfer during a discharge are calculated. The developed program, based on the suggested scheme in this paper, is applied to a sample system. The results provide a better understanding of ESD event and demonstrate the usefulness of two-body model in practical applications.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.616-629
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• 2015

A mobile terminal will expect a number of handoffs within its call duration. In the event of a mobile call, when a mobile node moves from one cell to another, it should connect to another access point within its range. In case there is a lack of support of its own network, it must changeover to another base station. In the event of moving on to another network, quality of service parameters need to be considered. In our study we have used the Markov decision process approach for a seamless handoff as it gives the optimum results for selecting a network when compared to other multiple attribute decision making processes. We have used the network cost function for selecting the network for handoff and the connection reward function, which is based on the values of the quality of service parameters. We have also examined the constant bit rate and transmission control protocol packet delivery ratio. We used the policy iteration algorithm for determining the optimal policy. Our enhanced handoff algorithm outperforms other previous multiple attribute decision making methods.

• Earthquakes and Structures
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• v.16 no.3
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• pp.311-320
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• 2019

Obelisks are historical monuments. There are several obelisks dating from ancient Egyptian period, located around various parts of the world. The city of Istanbul is a home to the Obelisk of Theodosius at the Hippodrome. Due to the expectation of a large event in the near future, the evaluation of seismic response of the Obelisk gets importance. Therefore, in this study structural dynamic behavior of the Obelisk was investigated using discrete element approach. Nonlinear dynamic analyses were performed using real and synthetic time series. Real and synthetic ground motions analyzed from this study seems consistent with the earthquake hazard levels that would be expected at the site of the Obelisk in the occurrence of an event of moment magnitude above 7.0 near Istanbul. Results are evaluated in terms of variation of displacement, relative displacement of adjacent blocks, normal stress and shear stress in time.

• International journal of steel structures
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• v.18 no.4
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• pp.1470-1481
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• 2018

Building-level response to post-earthquake fire hazards in steel buildings has been assessed using primarily two-dimensional analyses of the lateral force resisting system. This approach may not adequately consider potential vulnerabilities in the gravity framing system. For this reason, three-dimensional (3D) finite element models of a 10-story case study building with perimeter moment resisting frames were developed to analyze post-earthquake fire events and better understand building response. Earthquakes are simulated using ground motion time histories, while Eurocode parametric time-temperature curves are used to represent compartment fires. Incremental dynamic analysis and incremental fire analysis procedures capture a range of hazard intensities. Findings show that the structural response due to earthquake and fire hazards are somewhat decoupled from one another. Regardless of the level of plastic hinging present in the moment framing system due to a seismic event, gravity column failure is the initiating failure mode in a fire event.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.199-207
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• 2023

Trend Impact Analysis is a prominent hybrid method has been used in future studies with a modified surprise- free forecast. It considers experts' perceptions about how future events may change the surprise-free forecast. It is an advanced forecasting tool used in futures studies for identifying, understanding and analyzing the consequences of unprecedented events on future trends. In this paper, we propose an advanced mechanism to generate more justifiable estimates to the probability of occurrence of an unprecedented event as a function of time with different degrees of severity using adaptive neuro-fuzzy inference system (ANFIS). The key idea of the paper is to enhance the generic process of reasoning with fuzzy logic and neural network by adding the additional step of attributes simulation, as unprecedented events do not occur all of a sudden but rather their occurrence is affected by change in the values of a set of attributes. An ANFIS approach is used to identify the occurrence and severity of an event, depending on the values of its trigger attributes.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.3
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• pp.141-149
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• 2024

This paper proposes a configuration automation technique to minimize service interruption time in the event of a corporate network access layer switch failure. The automation is achieved without the need for a separate external system, as the network setting information is stored in a container inside the switch, enabling rapid recovery without requiring separate storage. This approach ensures the continuity of network services and demonstrates the efficiency of configuration automation. The proposed technique improves corporate network stability by providing a quick response in the event of a failure.

• Journal of KIISE
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• v.43 no.4
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• pp.470-479
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• 2016

As the number of various types of media data such as UCC (User Created Contents) increases, research is actively being carried out in many different fields so as to provide meaningful media services. Amidst these studies, a semantic web-based media classification approach has been proposed; however, it encounters some limitations in video classification because of its underlying ontology derived from meta-information such as video tag and title. In this paper, we define recognized objects in a video and activity that is composed of video objects in a shot, and introduce a reasoning approach based on description logic. We define sequential rules for a sequence of shots in a video and describe how to classify it. For processing the large amount of increasing media data, we utilize Spark streaming, and a distributed in-memory big data processing framework, and describe how to classify media data in parallel. To evaluate the efficiency of the proposed approach, we conducted an experiment using a large amount of media ontology extracted from Youtube videos.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.224-227
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• 2015

Data transmission via the car driver's tethered smart phone may have a volume-dependent billing in case car driver' phone transmits data in real-time to the remote data center. The on-board diagnosis data generated are temporary stored locally to mobile remote diagnosis application on the car driver's phone, and then transmit to the data center later when car driver connects to the Internet. To increase the easiest of using the remote vehicle application without blocking other tasks to be executing on the cloud, node.js stands as a suitable candidate for handling tasks of data storage on the cloud via mobile network. We demonstrate the effectiveness of the proposed architecture by simulating a preliminary case study of an android application responsible of real time analysis by using a vehicle-to- smart phones applications interface approach that considers the smart phones to act as a remote user which passes driver inputs and delivers output from external applications. In this paper, we propose a study on development of Remote Vehicle fault diagnostic system features web server architecture based event loop approach using node.js platform, and wireless communication to handle vehicle diagnostics data to a data center.