• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.5
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• pp.114-119
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• 2000

This study was carried out to obtain fundamental information of growth response of ground cover plants under artificial light quality at indoor. Aglaonema 'Silver Queen', Hedera helix L., Hoya carnosa 'Tricolor' and Saintpaulia ionantha 'Frances' were examined under a 400lux light intensity consisted of Mercury lamp, True-lite lamp, incandescent lamp, dark-room and sunlight indoor condition. A data analysis were performed by GLM, Duncan's multiple range test and mean score with SAS program. Results of experiments are as follows; 1. A plant growth status was better showed under the True-lite lamp than sunlight. 2. A Saintpaulia ionantha flower color was responded in the first place, the deep pinkish red color of Saintpaulia ionantha flower was obtained under Mercury lamp and "True-lite lamp", "sunlight", and incandescent lamp were follow. Flower numbers of Saintpaulia ionantha after 60 days tended to decrease under every artificial light quality. 3. Leaf length and leaf width were increased under True-lite lamp, but most of plants was not significantly affected by artificial light quality. 4. A stem length of Hedera helix was increased the highest rank under sunlight also, one of artificial light, the highest increase rank was showed under incandescent lamp. 5. Chlorophyll content was highly increased under Mercury lamp, but was responded poor under incandescent lamp.

• 한국생물공학회:학술대회논문집
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• 2000.11a
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• pp.553-556
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• 2000

Possibility of biological nitrogen treatment was tested in wastewaters with low C/N ratio. Chlorella kessleri was inoculated at $10^6\;cell/mL$ of initial density in two different artificial wastewaters: one that contained glucose for organic carbon source and the other without carbon source. Nitrate could be successfully reduced below 10 mg $NO_3/mL$ from initial nitrate concentration of 560 mg $NO_3/mL$ in 10 days even in the wastewater without carbon source, This 98% removal of nitrate without extra organic carbon source lights up the future of biological wastewater treatment, where the insufficient ability of nitrogen removal is a major problem.

• Electronics and Telecommunications Trends
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• v.35 no.7
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• pp.36-45
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• 2020

The method and process of research and development (R&D) is changing when we develop artificial intelligence (AI), and the way R&D results are dispersed is also changing. For the R&D process, using and participating in open-source ecosystems has become more important, so we need to be prepared for open source. For product and service development, a combination of AI algorithm, data, and computing power is needed. In this paper, we introduce ETRI AI Strategy #4, "Expanding AI Open Platform." It consists of two key tasks: one to build an AI open source platform (OSP) to create a cooperative AI R&D ecosystem, and another to systematize the "x+AI" open platform (XOP) to disperse AI technologies into the ecosystem.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1359-1363
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• 2017

In this study, the Relux program was simulated for optimum conditions of daylight and artificial light sources(LED) in the glass greenhouse. From the results of daylight simulation, the optimum design conditions for the glass greenhouse were established which were 90[o] installation angle and higher transmittance. In this case of growing lettuce in the glass greenhouse, the control method of the only artificial light source was compared that of daylight and LED. The result of illumination simulation produced a power consumption effect of 37.2[%] in the summer and 51.9[%] in the winter, respectively. From this results, we propose to suggest that we grow the lettuce in the energy saving glass greenhouse.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.10
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• pp.14-22
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• 2011

The artificial lights to be introduced for the plant factories is requiring the artificial light resources with minimizing the energy consumption to reduce the greenhouse gases which is a major cause of global warming, and maximizing the efficiency in photosynthesis effect light-wave range, in which the plants can be greatly grown and developed, and having the signal light-wave range for forming the light types. the best growing and developing environment for the plants has recently realized with utilizing the LED(Lighting Emitting Diode) lamps, as a environment-friendly green lamps, which can elevating the light efficiency with using only the specific light wave range. In this study, to provide the necessary lights for the full artificial light type of the plant factory, the following research/study and experiments has been conducting. experiments of the spectrum for each light sources, and LED, The intensity of illumination, Irradiance, Photosynthesis Photon Flux Density.

• Journal of muscle and joint health
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• v.28 no.3
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• pp.217-222
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• 2021

Background: The reaction of nurses to the advent of artificial intelligence (AI) during the fourth industrial revolution era remains questionable. Understanding Florence Nightingale's achievements may provide valuable lessons that will be helpful to contemporary nurses. Aims: To understand Nightingale's nursing philosophy and methods and provide suggestions for future nursing practice, education, research, and health policy. Source of evidence: Literature. Discussion/Conclusion: Just as Nightingale captured the situation of her time and introduced latest scientific methods, modern nurses need to learn from Nightingale's drastic actions to meet social needs. Nursing can regain a solid humanistic foundation by returning to core values of nursing and humanities, while simultaneously adopting state-of-the-art technologies. Implications for Nursing Policy: AI-driven technologies will advance nursing services and provide greater human-centered and personalized care by eliminating iterative and labor-intensive tasks. Nursing educational policy should support the advancement of nursing curricula to develop AI competencies and specialists within the nursing field.

• The Journal of Information Systems
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• v.28 no.3
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• pp.141-158
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• 2019

Purpose Artificial Intelligence (AI) is a core technology, leading the 4th industrial revolution. This study aims to diagnose the Korean's national competitiveness for AI technologies through patent analyses. Design/methodology/approach In this study, KIWEE and Derwent Innovation databases were used as data source of patents. we extracted 10,510 AI patents data with keywords and classified them into 15 subcategories of AI technology. We executed patent analyses for activity index, patent intensity index, technology strength, and patent family size and diagnosed Korea's national competitiveness in AI industry. Findings The results showed that Korea is less competitive than the United States and Japan in AI industry. However, patent amount has increased since 2010, which is encouraging result. This study has implication on the need for human and R&D investment in AI industry.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.21-40
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• 2019

This paper presents a comprehensive survey of various artificial intelligence (AI) techniques implemented in cognitive radio engine to improve cognition capability in cognitive radio networks (CRNs). AI enables systems to solve problems by emulating human biological processes such as learning, reasoning, decision making, self-adaptation, self-organization, and self-stability. The use of AI techniques is studied in applications related to the major tasks of cognitive radio including spectrum sensing, spectrum sharing, spectrum mobility, and decision making regarding dynamic spectrum access, resource allocation, parameter adaptation, and optimization problem. The aim is to provide a single source as a survey paper to help researchers better understand the various implementations of AI approaches to different cognitive radio designs, as well as to refer interested readers to the recent AI research works done in CRNs.

• Structural Engineering and Mechanics
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• v.78 no.5
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• pp.529-543
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• 2021

Inevitable source-uncertainties in geometry configuration, boundary condition, and material properties may deviate the structural dynamics from its expected responses. This paper aims to examine the influence of these uncertainties on the vibration of functionally graded beams. Finite element procedures are presented for Timoshenko beams and utilized to generate reliable datasets. A prerequisite to the uncertainty quantification of the beam vibration using Monte Carlo simulation is generating large datasets, that require executing the numerical procedure many times leading to high computational cost. Utilizing artificial neural networks to model beam vibration can be a good approach. Initially, the optimal network for each beam configuration can be determined based on numerical performance and probabilistic criteria. Instead of executing thousands of times of the finite element procedure in stochastic analysis, these optimal networks serve as good alternatives to which the convergence of the Monte Carlo simulation, and the sensitivity and probabilistic vibration characteristics of each beam exposed to randomness are investigated. The simple procedure presented here is efficient to quantify the uncertainty of different stochastic behaviors of composite structures.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.312-320
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• 2021

Increase in computational cost and exhaustive search can lead to more complexity and computational energy. Thus, there is need for effective and efficient scheme to reduce the complexity to achieve optimal energy utilization. This will improve the energy efficiency and enhance the proficiency in terms of the resources needed to achieve convergence. This paper primarily focuses on the development of hybrid swarm intelligence scheme for reducing the computational complexity in binary optimization. In order to reduce the complexity, both artificial bee colony (ABC) and particle swarm optimization (PSO) have been employed to effectively minimize the exhaustive search and increase convergence. First, a new approach using ABC and PSO has been proposed and developed to solve the binary optimization problem. Second, the scout for good quality food sources is accomplished through the deployment of PSO in order to optimally search and explore the best source. Extensive experimental simulations conducted have demonstrate that the proposed scheme outperforms the ABC approaches for reducing complexity and energy consumption in terms of convergence, search and error minimization performance measures.