• 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.

• Current Photovoltaic Research
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• v.7 no.4
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• pp.85-96
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• 2019

Renewable energy is emerging as a reliable alternative source of energy, it is much safer, cleaner than conventional sources and has contributed significantly in this sector. However, there are still some challenges that needed to address this evolving technology. Artificial Intelligence (A. I.) can assess the past, optimize the present, and forecast the future. Therefore, A. I. will resolve most of these problems. Artificial intelligence is complex in nature, but it reduces error and aims to reach a greater degree of precision which make renewables smarter. This paper provides an overview of frequently used A. I. methods in solar energy applications. A sample algorithm is also provided for literature purposes and knowledge transfer.

• Wind and Structures
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• v.5 no.1
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• pp.1-14
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• 2002

Artificial Neural Networks (ANN) have the capability to develop functional relationships between input-output patterns obtained from any source. Thus ANN can be conveniently used to develop a generalised relationship from limited and sometimes inconsistent data, and can therefore also be applied to tackle the data obtained from wind tunnel tests on building models with large number of variables. In this paper ANN model has been developed for predicting wind induced pressures in various zones of a Gable Building from limited test data. The procedure is also extended to a case wherein interference effects on a gable roof building by a similar building are studied. It is found that the Artificial Neural Network modelling is seen to predict successfully, the pressure coefficients for any roof slope that has not been covered by the experimental study. It is seen that ANN modelling can lead to a reduction of the wind tunnel testing effort for interference studies to almost half.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.433-439
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• 2019

Artificial bee colony algorithm is a strong global search algorithm which exhibits excellent exploration ability. The conventional ABC algorithm adopts employed bees, onlooker bees and scouts to cooperate with each other. However, its one dimension and greedy search strategy causes slow convergence speed. To enhance its performance, in this paper, we abandon the greedy selection method and propose an artificial bee colony algorithm with special division and intellective search (ABCIS). For the purpose of higher food source research efficiency, different search strategies are adopted with different employed bees and onlooker bees. Experimental results on a series of benchmarks algorithms demonstrate its effectiveness.

• Mycobiology
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• v.28 no.4
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• pp.165-170
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• 2000

This study was carried out to obtain the basic data for artificial culture of veiled lady mushroom (Dictyophora spp). The optimal conditions for the mycelial growth were $25^{\circ}C$ and pH 5.0 for all isolates except the optimal temperature of $30^{\circ}C$ for D. echinovolvata ASI 32002 and Phallus rugulosus. The optimal medium for Dictyophora spp. was PBA (potato bamboo sawdust extract agar) medium. The strain ASI 32002, D. echinovolvata, grew faster than. D. indusiata ASI 32003 and Phallus rugulosus ASI 25007 on the medium. Carbon sources such as glucose, maltose and inuline were favorable for stimulating a mycelial growth of the two strains of ASI 32002 and ASI 32003. Asparagine and glutamine appeared to be favorable to the strain ASI 32002 and ASI 32003, where as alanine, one of nitrogen source also favorable to the strain ASI 32002. The optimum C/N ratio of the two isolates of ASI 32002 and ASI 32003 was about 25 : 1 when 2% glucose as carbon source was mixed with the basal medium. While, in the case of 4% as carbon source, the optimum C/N ratio was about 30 : 1.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2001.02a
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• pp.160-166
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• 2001

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1998.06b
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• pp.122-128
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• 1998

• Journal of Environmental Science International
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• v.33 no.5
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• pp.305-322
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• 2024

The aim of this study was to investigate the effects of artificial light sources on the germination and seedling vigor of lettuce, aiming to identify the optimal artificial light source for producing high-quality seedlings. Lettuce cultivar of 'Tomalin' and 'Seonpunggold' exhibited the highest seed emergence in the Metal halide(MH) lamp and High-pressure sodium(HPS) lamp treatment group, while the emergence rate parameter, T50, was the fastest in the HPS lamp treatment group. Both cultivars showed good growth characteristics such as number of leaves, root length, and stem diameter under RGB-LED, and their seedling vigor was excellent as well. The plant height was smallest in the Red + Green + Blue LED treatment, but the leaves were round and thick, resulting in higher biomass and dry weight. Single light sources of Red LED and Blue LED led to reduced growth compared with that under the mixed light treatments. Chlorophyll content in lettuce varied with the type of artificial light, with both cultivars exhibiting the highest chlorophyll content in the Red + Green + Blue LED treatment. The most suitable artificial light for lettuce seedling growth was the Red + Green + Blue LED treatment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.89-96
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• 2021

The number of confirmed cases of coronavirus-19 is soaring around the world and has caused numerous deaths. Wearing a mask is very important to prevent infection. Incidents and accidents have occurred due to the recommendation to wear a mask in public places such as buses and subways, and it has emerged as a serious social problem. To solve this problem, this paper proposes an open source-based face mask wearing monitoring system. We used open source software, web-based artificial intelligence tool teachable machine and open source hardware Arduino. It judges whether the mask is worn, and performs commands such as guidance messages and alarms. The learning parameters of the teachable machine were learned with the optimal values of 50 learning times, 32 batch sizes, and 0.001 learning rate, resulting in an accuracy of 1 and a learning error of 0.003. We designed and implemented a mask wearing monitoring system that can perform commands such as guidance messages and alarms by determining whether to wear a mask using a web-based artificial intelligence tool teachable machine and Arduino to prove its validity.