• The Journal of the Acoustical Society of Korea
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• v.36 no.2
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• pp.130-135
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• 2017

In this paper, we propose an interface for interactive sound experience in the virtual concert hall. The proposed interface consists of two systems, called 'virtual acoustic position' and 'virtual active listening'. To provide these systems, we applied an artificial reverberation algorithm, multi-channel source separation and head-related transfer function. The proposed interface was implemented by using Unity. The interface provides the virtual concert hall to user through Oculus Rift, one of the virtual reality headsets. Moreover, we used Leap Motion as a control device to allow a user experience the system with free-hand. And user can experience the sound of the system through headphones.

• Soft Computing and Machine Intelligence
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• v.1 no.1
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• pp.1-10
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• 2021

Analysis and Tracking of bug reports is a challenging field in software repositories mining. It is one of the fundamental ways to explores a large amount of data acquired from defect tracking systems to discover patterns and valuable knowledge about the process of bug triaging. Furthermore, bug data is publically accessible and available of the following systems, such as Bugzilla and JIRA. Moreover, with robust machine learning (ML) techniques, it is quite possible to process and analyze a massive amount of data for extracting underlying patterns, knowledge, and insights. Therefore, it is an interesting area to propose innovative and robust solutions to analyze and track bug reports originating from different open source projects, including Mozilla and Eclipse. This research study presents an ML-based classification model to analyze and track bug defects for enhancing software engineering management (SEM) processes. In this work, Artificial Neural Network (ANN) and Naive Bayesian (NB) classifiers are implemented using open-source bug datasets, such as Mozilla and Eclipse. Furthermore, different evaluation measures are employed to analyze and evaluate the experimental results. Moreover, a comparative analysis is given to compare the experimental results of ANN with NB. The experimental results indicate that the ANN achieved high accuracy compared to the NB. The proposed research study will enhance SEM processes and contribute to the body of knowledge of the data mining field.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1277-1283
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• 2021

It is important for operators of poly-pipelines in petroleum industry to continuously monitor characteristics of transferred fluid such as its type and amount. To achieve this aim, in this study a dual energy gamma attenuation technique in combination with artificial neural network (ANN) is proposed to simultaneously determine type and amount of four different petroleum by-products. The detection system is composed of a dual energy gamma source, including americium-241 and barium-133 radioisotopes, and one 2.54 cm × 2.54 cm sodium iodide detector for recording the transmitted photons. Two signals recorded in transmission detector, namely the counts under photo peak of Americium-241 with energy of 59.5 keV and the counts under photo peak of Barium-133 with energy of 356 keV, were applied to the ANN as the two inputs and volume percentages of petroleum by-products were assigned as the outputs.

• Journal of Power Electronics
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• v.9 no.3
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• pp.403-409
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• 2009

Automatically tuned passive filters can improve power quality to a great extent in power systems. A novel three-phase shunt auto-tuned filter is designed to effectively compensate source current harmonics and to provide reactive power required by the non-linear load, which draws a highly reactive, harmonic-rich current from the supply. An artificial neural network (ANN) based controller selects filter component values in accordance with reactive power requirement and harmonic compensation. Traditional passive filters are permanently connected to the system and draw large amounts of source current even under light load conditions. By using auto-tuned filters, the passive filter components can be controlled according to load variations and, hence, draw only required source currents. The selection is done by the ANN with the help of a properly tuned knowledge base to provide instantaneous compensation using a digital controller.

• Journal of electromagnetic engineering and science
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• v.9 no.4
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• pp.175-181
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• 2009

The measurements were performed to verify experimentally that the voltage arising on a telecommunication line by a power line is due to the induction phenomena because there has been an opinion that the arising voltage on a telecommunication line is not by induction, but by other causality. The voltage appeared on the telecommunication line by way of an electric field or magnetic field generated by the source apparatus that had been artificially made to provide intentional constant high-voltage or current in ELF, that is, 60 Hz as an emulated commercial power.

• The Journal of Engineering Geology
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• v.16 no.2 s.48
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• pp.179-187
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• 2006

Two specimens of mortar containing artificial slit and Geochang granite containing the straight notch were selected to be used in this research. Source mechanism of micro-crack by radiation pattern based on dislocation the-ory was estimated by the first motion of longitudinal wave and spatial distribution between the location of transducers for monitoring acoustic emission and source coordinates determined by the application of the least square method. Result of analysis showed that the orientation of dislocation surfaces due to shear dislocation and tensile dislocation squares considerably with crack direction visually observed. The ultimate goal of this study is to provide fundamental information for source mechanism of micro-crack within materials.

• Journal of Distribution Science
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• v.20 no.11
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• pp.121-129
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• 2022

Purpose: Artificial intelligence is widely used, particularly in the popular neural network theory called Deep learning. The improvement of computing speed and capability expedited the progress of Deep learning applications. The application of Deep learning in education has various effects and possibilities in creating and managing educational content and services that can replace human cognitive activity. Among Deep learning, Deep fake technology is used to combine and synchronize human faces with voices. This paper will show how to develop e-Learning content videos using those technologies and open-source tools. Research design, data, and methodology: This paper proposes 4 step development process, which is presented step by step on the Google Collab environment with source codes. This technology can produce various video styles. The advantage of this technology is that the characters of the video can be extended to any historical figures, celebrities, or even movie heroes producing immersive videos. Results: Prototypes for each case are also designed, developed, presented, and shared on YouTube for each specific case development. Conclusions: The method and process of creating e-learning video contents from the image, video, and audio files using Deep fake open-source technology was successfully implemented.

• Journal of Biosystems Engineering
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• v.24 no.2
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• pp.115-122
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• 1999

Because of their small mass, volume, solid state construction and long life, light-emitting diodes(LEDs) hold promises as a lighting source for intensive plant production system. Spectral characteristics and light intensity of LEDs were tested to investigate their feasibility as artificial lighting sources for growth and morphogenesis control in transplant production system. Blue, green, and red LEDs had a peak-emission wavelength at 442nm, 522nm, and 673nm, respectively. Their half width defined as the difference between upper and lower wavelength in the intensity equivalent to 50% of the maximum intensity showed 26nm, 41nm, and 74nm, respectively. Photosynthetic photon flux(PPE) at the distance of 9cm under the LEDs array was measured as $235{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ for red, $109{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ for green, and $75{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ for blue LEDs. At the same distance, green LEDs had the illuminance of 13,0001x, nine to ten times higher than those of red and blue LEDs. Red, green, and blue LEDs at a distance of 9cm had the irradiance of $46W{\cdot}m^{-2},\;19W{\cdot}m^{-2},\;8W{\cdot}m^{-2}$, respectively. Light intensity of blue, green, and red LEDs increased linearly in proportion to the magnitude of the current applied to the operating circuit. Thus the light intensity of LEDs was controlled by the applied current in operating circuit.

• Journal of Biosystems Engineering
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• v.23 no.6
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• pp.591-598
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• 1998

Light intensity and spectral characteristics of different types of fluorescent lamps were tested to investigate their possibility as the artificial lighting sources for the close illumination applied in the transplant production factory. Photosynthetic photon flux densitiy(PPF), illuminance and irradiance for all lamps decreased logarithmically with an increase of the vertical distance from the lighting source. The fluorescent lamp specially designed plant growth (PG lamp) showed a maximum spectral irradiance at the wavelength of 660nm. However, it showed lower irradiance than that of a standard fluorescent lamp at the range of wavelength between 500 and 600nm. On the other hand, PG lamp showed higher PPF and lower illuminance than those of the standard fluorescent lamp. The maximum peak of spectral characteristics for both of the single and twin three-bind fluorescent lamps was shorn at the wavelength of 545m and the next peaks were shown at the wavelength of 610nm and 435nm, respectively. Since the red fluorescent lamp has a narrower peak at the wavelength of 660nm, it may be useful for the supplementary red lighting. For three of standard, single three-band and twin three-band fluorescent lamps, the values of conversion factor for converting illuminance to PPF fell within the narrow range from 76 to 791x/$\mu$molㆍm$^{-2}$ ㆍs$^{-l}$ . However, for PG lamp, it was 29.71x/$\mu$molㆍm$^{-2}$ ㆍs$^{-1}$. Also, the values of conversion factor for converting PPF to irradiance of fluorescent lamp used in this study ranged between 4.85 and 5.34$\mu$molㆍm$^{-2}$ ㆍs$^{-1}$/Wㆍm$^{-2}$ .

• Journal of the Korea Convergence Society
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• v.11 no.7
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• pp.239-249
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• 2020

The purpose of this study was to verify whether the endorser effect similar to humans can be created in advertising campaigns based on the artificial intelligence endorser. In particular, considering the characteristics of artificial intelligence, a research model was presented by convergence of consumer innovativeness and anthropomorphism. The results of the online survey of 244 respondents showed that expertise of the artificial intelligence endorser has a positive effect on both brand attitude and purchase intention, but not for trustworthiness while it has a positive effect on brand attitude. Also, the effect of consumer innovativeness and anthropomorphism on brand attitude and purchase intention for artificial intelligence was found. The endorser effect was expanded to artificial intelligence, which is an intangible object, and the existing theory and research results were combined to re-verify it. Theoretical and practical implications for artificial intelligence-based products and services were presented.