• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.169-170
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• 2019

Lately, as artificial intelligence becomes a source of global competitiveness, the government is strategically fostering artificial intelligence that is the base technology of future new industries such as autonomous vehicles, drones, and robots. Domestic artificial intelligence research and services have been launched mainly in Naver and Kakao, but their size and level are weak compared to overseas. Recently, deep learning has been conducted in recent years while recording innovative performance in various pattern recognition fields including speech recognition and image recognition. In addition, deep running has attracted great interest from industry since its inception, and global information technology companies such as Google, Microsoft, and Samsung have successfully applied deep learning technology to commercial products and are continuing research and development. Therefore, we will look at artificial intelligence which is attracting attention based on previous research.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.53-59
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• 2020

This paper relates to an IoT device system that detects sound source and estimates the sound source location. More specifically, it is a system using a sound source direction detection device that can accurately detect the direction of a sound source by analyzing the difference of arrival time of a sound source signal collected from microphone sensors, and track the generation direction of a sound source using an IoT sensor. As a result of a performance test by generating a sound source, it was confirmed that it operates very accurately within 140dB of the acoustic detection area, within 1 second of response time, and within 1° of directional angle resolution. In the future, based on this design plan, we plan to commercialize it by improving the reliability by reflecting the artificial intelligence algorithm through big data analysis.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.163-172
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• 2020

Recently, concepts of the Fourth Industrial Revolution technologies such as artificial intelligence, big data, and cloud computing have been introduced and the limits of individual or team development policies are being reviewed. Also, a lot of latest technology source codes have been opened to the public, and related studies are being conducted based on them. Meanwhile, the company is applying the strengths of the open source software development methodology to proprietary software development, and publicly announcing support for open source development methodology. In this paper, we introduced several software development methodology such as open source model, inner source model, and the similar DevOps model, which have been actively discussed recently, and compared their characteristics and components. Rather than claiming the excellence of a specific model, we argue that if the software development policy of an individual or affiliated organization is established according to each benefit, they will be able to achieve software quality improvement while satisfying customer requirements.

• Journal of Microbiology and Biotechnology
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• v.12 no.6
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• pp.979-985
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• 2002

The possibility of microalgal nitrogen treatment was tested in wastewaters with a low carbon/nitrogen (C/N) ratio. Chlorella kessleri was cultured in the two different artificial wastewaters with nitrate as a nitrogen source: one contained glucose for an organic carbon source and the other without organic carbon sources. The growth rates of the two cultures were almost identical when the aeration rate was over 1 vvm. These results suggest that microalgae could successfully remove nitrogen from wastewater, as far as the mass transfer of $CO_2$, was not limited. Nitrate was successfully reduced to below 2 mg $NO_3^-$-N/ml from the initial nitrate concentration of 140 mg $NO_3^-$-N/ml in 10 days, even in the wastewater with no organic carbon source. Similar results were obtained when ammonium was used as the sole nitrogen source instead of nitrate. Higher concentrations of nitrogen of 140, 280, 560 and 1,400 mg/ml were also tested and similar amounts of nitrogen were removed by algal cultures without showing any substrate inhibition.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.209-214
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• 2005

In the present age, the quality of MT(magnetotellurics) data highly depends on the level of industrial interference in data. We analyzed the correlation between the spatial distributions of man-made EM noise source and the characteristics of MT data. The noise source analysis shows the correlation between the noise source density and the power spectral density of measured magnetic field in the frequency band of 60 Hz harmonics. In the MT 'dead band', the strong polarization observed on the magnetic field reveals that the severe artificial noises are caused by the adjacent metropolis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2574-2587
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• 2019

Blind Source Separation (BSS) is a technique used to separate supposed independent sources of signals from a given set of observations. In this paper, the High Exploration Particle Swarm Optimization (HEPSO) algorithm, which is an enhancement of the Particle Swarm Optimization (PSO) algorithm, has been used to separate a set of source signals. Compared to PSO algorithm, HEPSO algorithm depends on two additional operators. The first operator is based on the multi-crossover mechanism of the genetic algorithm while the second one relies on the bee colony mechanism. Both operators have been employed to update the velocity and the position of the particles respectively. Thus, they are used to find the optimal separating matrix. The proposed method enhances the overall efficiency of the standard PSO in terms of good exploration and performance. Based on many tests realized on speech and music signals supplied by the BSS demo, experimental results confirm the robustness and the accuracy of the introduced BSS technique.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.342-352
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• 2021

Multicast Routings is a big challenge due to limitations such as node power and bandwidth Mobile Ad-hoc Network (MANET). The path to be chosen from the source to the destination node requires protocols. Multicast protocols support group-oriented operations in a bandwidth-efficient way. While several protocols for multi-cast MANETs have been evolved, security remains a challenging problem. Consequently, MANET is required for high quality of service measures (QoS) such infrastructure and application to be identified. The goal of a MANETs QoS-aware protocol is to discover more optimal pathways between the network source/destination nodes and hence the QoS demands. It works by employing the optimization method to pick the route path with the emphasis on several QoS metrics. In this paper safe routing is guaranteed using the Secured Multicast Routing offered in MANET by utilizing the Ant Colony Optimization (ACO) technique to integrate the QOS-conscious route setup into the route selection. This implies that only the data transmission may select the way to meet the QoS limitations from source to destination. Furthermore, the track reliability is considered when selecting the best path between the source and destination nodes. For the optimization of the best path and its performance, the optimized algorithm called the micro artificial bee colony approach is chosen about the probabilistic ant routing technique.

• The Journal of the Korea Contents Association
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• v.15 no.6
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• pp.267-275
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• 2015

This study has been implemented to check the effect of roughness on the color stability according to the surface treatment of artificial teeth. 20 units of 3 groups with the different surface treatment of artificial teeth have been precipitated in the soy sauce, the red pepper paste, the coffee and the cola, measure equipment was used for Shade-eye(Chroma Meter, Shofu, U.S.A). The value of L*, a*, b* using its average value after measuring 3 times per 1 point by selecting 3 points randomly out of central parts of teeth on a cycle of each 1 day, 1 week, 2 weeks, 3 weeks, 4 weeks after precipitation in terms of precipitated specimens. As a result of Multiple regression analysis, the value of ${\Delta}E*$ of artificial teeth according to the surface treatment showed the significant negative(-) effect in the Group 2(p<0.001) and the red pepper paste had the biggest effect on the color change of artificial teeth out of pollution source.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.187-194
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• 2022

LNG is known as the transitional energy source for the future eco-friendly, attracting enormous market attention due to global eco-friendly regulations, Covid-19 Pandemic, Russia-Ukraine War. In addition, since new LNG suppliers such as the U.S. and Australia are also diversifying, the LNG spot market is expected to grow. On the other hand, research on the LNG transportation market has been marginalized. Therefore, this study attempted to predict short-term LNG 160K spot rates and compared the prediction performance between artificial neural networks and the ARIMA model. As a result of this paper, while it was difficult to determine the superiority and superiority of ARIMA and artificial neural networks, considering the relative free of ANN's contraints, we confirmed the feasibility of ANN in LNG 160K spot rate prediction. This study has academic significance as the first attempt to apply an artificial neural network to forecasting LNG 160K spot rates and are expected to contribute significantly in practice in that they can improve the quality of short-term investment decisions by market participants by increasing the accuracy of short-term prediction.

• Korean Journal of Environmental Agriculture
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• v.41 no.4
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• pp.245-251
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• 2022

BACKGROUND: Selection an suitable light source is essential in the year-round production of horticultural crops in closed production systems such as plant factory with controlled environments. This study was investigated to confirm the effects of artificial light sources on growth of cherry tomato'CF Jelly'(Lycopersicon esculentum var.) under high-pressure sodium lamps (HPS), metal-halide lamps (MH), and LEDs. METHODS AND RESULTS: Light intensity of the light sources was controlled at 220±30 µmol/m²/s with 12 hrs of photoperiod for a day. Flower development was significantly faster in HPS and MH treatments compared to the LEDs. There was no significant difference between the leaf number and leaf shape under the HPS and MH treatments. Reproductive growth of cherry tomato was significantly promoted by the LEDs treatment of blue plus red lights. Fruit yield per plant also increased under the LEDs compared to the others. CONCLUSION(S): Growth, flowering, and fruit setting of the cherry tomato were accomplished by the artificial lights under plant factory conditions. The HPS treatment showed negative effect on fruit quality in terms of blossom-end rot incidence compared to the LEDs or MH treatment. Effect of the LEDs on promotion of fruit weight and yield was also proved. Additional research should be carried out for improving sugar metabolism or decreasing disease in the fruits under plant factory system using only artificial lights.