• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.273-280
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• 2020

Automatic Static Analysis Tools help developers to quickly find potential defects in source code with less effort. However, the tools reports a large number of false positive warnings which do not have to fix. In our study, we proposed an artificial neural network-based warning classification method using topic models of source code blocks. We collect revisions for fixing bugs from software change management (SCM) system and extract code blocks modified by developers. In deep learning stage, topic distribution values of the code blocks and the binary data that present the warning removal in the blocks are used as input and target data in an simple artificial neural network, respectively. In our experimental results, our warning classification model based on neural network shows very high performance to predict label of warnings such as true or false positive.

• Convergence Security Journal
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• v.20 no.3
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• pp.115-123
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• 2020

Cyber Attack have evolved more and more in recent years. One of the best countermeasure to counter this advanced and sophisticated cyber threat is to predict cyber attacks in advance. It requires a lot of information and effort to predict cyber threats. If we use Open Source Intelligence(OSINT), the core of recent information acquisition, we can predict cyber threats more accurately. In order to predict cyber threats using OSINT, it is necessary to establish a Database(DB) for cyber attacks from OSINT and to select factors that can evaluate cyber threats from the established DB. We are based on previous researches that built a cyber attack DB using data mining and analyzed the importance of core factors among accumulated DG factors by AHP technique. In this research, we present a method for quantifying cyber threats and propose a cyber threats prediction model based on artificial neural networks.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.59-68
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• 2023

Currently, yellow phosphor of Y3Al5O12:Ce3+ (YAG:Ce) fluorescent material is applied to a 450~480nm blue LED light source to implement a white LED device and it has a simple structure, can obtain sufficient luminance, and is economical. However, in this method, in terms of spectrum analysis, it is difficult to mass-produce white LEDs having the same color coordinates due to color separation cause by the wide wavelength gap between blue and yellow band. There is a disadvantage that it is difficult to control optical properties such as color stability and color rendering. In addition, this method does not emit purple light in the range of 380 to 420nm, so it is white without purple color that can not implement the spectrum of the entire visible light spectrum as like sunlight. Because of this, it is difficult to implement a color rendering index(CRI) of 90 or higher, and natural light characteristics such as sunlight can not be expected. For this, need for a method of implementing sunlight with one LED by using a method of combining phosphors with one light source, rather than a method of combining red, blue, and yellow LEDs. Using this method, the characteristics of an artificial sunlight LED device with a spectrum similar to that of sunlight were demonstrated by implementing LED devices of various color temperatures with high color rendering by injecting phosphors into a 405nm deep blue LED light source. In order to find the spectrum closest to sunlight, different combinations of phosphors were repeatedly fabricated and tested. In addition, reliability and mass productivity were verified through temperature and humidity tests and ink penetration tests.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.38-44
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• 2003

Artificial blasts, defined as seismo-acoustic events, were discriminated from natural earthquakes in the Korean Peninsula by the seismo-acoustic analysis. Total 197 seismo-acoustic events corresponding to 9 percent of seismic events in 2002 were analyzed and classified as artificial surface blasts. Events distribution pattern of the seismo-acoustic events in 2002 was similar to the previous result in 1999-2001, except for two regions. Newly determined seismo-acoustic events were added to the previous artificial blast database. To extend infrasound detection capability, new small-scale infrasound array(TJIAR) was installed in KIGAM. Preliminary analysis for the small array was conducted to discriminate artificial blasts in the southwestern part of the Korean Peninsula. The small array discriminated S seismo-acoustic events during short period analysis. And two infrasound arrays(TJIAR and CHNAR) were used to determine approximate sound source location by cross bearing method.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.56-62
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• 2019

Recently, research using artificial neural networks has further expanded the field of neural network optimization and automatic structuring from improving inference accuracy. The performance of the machine learning algorithm depends on how the hyperparameters are configured. Open-source hyperparameter optimization software can be an important step forward in improving the performance of machine learning algorithms. In this paper, we review open-source hyperparameter optimization softwares.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 1995.03a
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• pp.108-108
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• 1995

There are always some difficulties to discriminate artificial exlposions from micro-earthquakes, furthermore more difficulties to identify and determine decoupled explosions and/or multiple explosions from micro-earthquakes. In this study we use the synthetic seismogram of the in homogeneous models between the source and the observation station in order to find the source effect of the geological environment. We have found some source characteristics of the air-filled and/or water-filled cavity that we can hardly see P-n and S- waves arrivals and that the high frequency coda waves are well observed compared to the coupled explosions or earthquakes.

• Journal of the Earthquake Engineering Society of Korea
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• v.24 no.1
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• pp.9-17
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• 2020

The stochastic point-source model has been widely used in generating artificial ground motions, which can be used to develop a ground motion prediction equation and to evaluate the seismic risk of structures. This model mainly consists of three different functions representing source, path, and site effects. The path effect is used to emulate decay in ground motion in accordance with distance from the source. In the stochastic point-source model, the path attenuation effect is taken into account by using the geometrical attenuation effect and the inelastic attenuation effect. The aim of this study is to develop accurate equations of ground motion attenuation in the Korean peninsula. In this study, attenuation was estimated and validated by using a stochastic point source model and observed ground motion recordings for the Korean peninsula.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.60 no.1
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• pp.87-99
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• 2024

This study deals with the application of an artificial neural network (ANN) model to predict power consumption for utilizing seawater source heat pumps of recirculating aquaculture system. An integrated dynamic simulation model was constructed using the TRNSYS program to obtain input and output data for the ANN model to predict the power consumption of the recirculating aquaculture system with a heat pump system. Data obtained from the TRNSYS program were analyzed using linear regression, and converted into optimal data necessary for the ANN model through normalization. To optimize the ANN-based power consumption prediction model, the hyper parameters of ANN were determined using the Bayesian optimization. ANN simulation results showed that ANN models with optimized hyper parameters exhibited acceptably high predictive accuracy conforming to ASHRAE standards.

• Journal of the Korean Society for Nondestructive Testing
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• v.5 no.2
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• pp.22-33
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• 1986

The application and development of on-line monitoring technology of AE to surveillance of crack propagation will contribute to the structural integrity of reactor pressure vessel and piping system. This research has been performed in order to obtain the evaluation technology for source location of AE and the analysis for the AE signal of the welded specimen. AE is detected by 4-channels AE system during pressurization in small pressure vessels. The cracking of artificial defects can be accurately located and categorized in real time. The welded specimens have more events rate and higher amplitude than the weldless less specimens, and the events rate have a peak around the yield point and just before the failure under tensile test.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.06a
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• pp.9-10
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• 2007

In this paper, we investigated the effect of solar cell breakage on maximum output power of PV module. The test result using artificial light source didn't give any change in output power in case of crack near electrical ribbon. Also, there was a reduction in output power in case of increasing of crack area far from electrical ribbon. But, this experiment is under artificial light source test method. So, when such a PV module is outdoor for a long time, there would be problems on electrical output power and durability because of thermal aging phenomenon of solar cell breakage.