• Horticultural Science & Technology
• /
• v.34 no.1
• /
• pp.55-66
• /
• 2016

This study was carried out to investigate the effect of artificial light sources with different light qualities on the growth and flowering characteristics of a herbaceous long-day plant, Petunia ${\times}$ hybrida Hort. Seedlings of petunia cultivar 'Madness Rose' were potted, acclimated for one week, and grown in a phytotron equipped with tube- and bulb-type fluorescent lamps (FL tube and bulb), tube-type white light-emitting diodes (LED tube), halogen lamps (HL), metal halide lamps (MH), and high pressure sodium lamps (HPS) for 10 weeks. The temperature, photoperiod, and photosynthetic photon flux density (PPFD) in the phytotron were $22{\pm}2^{\circ}C$, 16 h, and $25{\pm}2{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, respectively. Light sources combined with HL promoted stem elongation, and plant height and internode length decreased with increasing red to far-red (R:FR) ratio. FL tube + LED tube, HPS, and FL tube promoted branching, whereas plants grown under light sources combined with HL did not have any branches. Days to flowering (from longest to shortest) occurred as follows: FL tube + HL > FL tube + HL > MH > HPS = FL tube + FL bulb > FL tube + LED tube > LED tube > FL tube, indicating that reducing the R:FR ratio of the light sources promoted flowering. Only 20% of plants grown under an FL tube flowered, whereas under all other treatments, 100% of plants flowered. At 10 weeks after treatment, plants grown under HPS and MH had (cumulatively) 12 open flowers, and those grown under FL tube + FL bulb, LED tube, FL tube + LED tube, and HPS treatment had approximately seven flower buds. These results suggest that light sources with low R:FR ratios promote flowering and stem elongation in petunia, but they reduce its ornamental value due to overgrowth and poor branching.

• ETRI Journal
• /
• v.43 no.4
• /
• pp.603-616
• /
• 2021

Over the last few years, autonomous vehicles have progressed very rapidly. The odometry technique that estimates displacement from consecutive sensor inputs is an essential technique for autonomous driving. In this article, we propose a fast, robust, and accurate odometry technique. The proposed technique is light detection and ranging (LiDAR)-based direct odometry, which uses a spherical range image (SRI) that projects a three-dimensional point cloud onto a two-dimensional spherical image plane. Direct odometry is developed in a vision-based method, and a fast execution speed can be expected. However, applying LiDAR data is difficult because of the sparsity. To solve this problem, we propose an SRI generation method and mathematical analysis, two key point sampling methods using SRI to increase precision and robustness, and a fast optimization method. The proposed technique was tested with the KITTI dataset and real environments. Evaluation results yielded a translation error of 0.69%, a rotation error of 0.0031°/m in the KITTI training dataset, and an execution time of 17 ms. The results demonstrated high precision comparable with state-of-the-art and remarkably higher speed than conventional techniques.

• Design & Manufacturing
• /
• v.15 no.3
• /
• pp.1-6
• /
• 2021

An artificial neural network model based on a deep learning algorithm is known to be more accurate than humans in image classification, but there is still a limit in the sense that there needs to be a lot of training data that can be called big data. Therefore, various techniques are being studied to build an artificial neural network model with high precision, even with small data. The transfer learning technique is assessed as an excellent alternative. As a result, the purpose of this study is to develop an artificial neural network system that can classify burr images of light guide plate products with 99% accuracy using transfer learning technique. Specifically, for the light guide plate product, 150 images of the normal product and the burr were taken at various angles, heights, positions, etc., respectively. Then, after the preprocessing of images such as thresholding and image augmentation, for a total of 3,300 images were generated. 2,970 images were separated for training, while the remaining 330 images were separated for model accuracy testing. For the transfer learning, a base model was developed using the NASNet-Large model that pre-trained 14 million ImageNet data. According to the final model accuracy test, the 99% accuracy in the image classification for training and test images was confirmed. Consequently, based on the results of this study, it is expected to help develop an integrated AI production management system by training not only the burr but also various defective images.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.201-206
• /
• 1996

This paper presents a new information processing machine which is called artificial brain(ABrain) and considers the structure of artificial neural networks constructed in a RICOH neurocomputer RN-2000 in the ABrain, in order to track given trajectories which are produced in a micro-computer or a moving light by hand in a recognition and tracking system.

• Journal of Bio-Environment Control
• /
• v.21 no.3
• /
• pp.220-227
• /
• 2012

This study was conducted to analyze the seeding quality of paprika and the growth and early yield after transplanting of paprika nursed under artificial light and natural light. In this study, blue LED, red LED, and white fluorescent lamps (FL) were used as artificial lighting sources. Photoperiod, average photosynthetic photon flux, air temperature, and relative humidity in a closed transplants production system (CTPS) were maintained at 16/8 h, $204{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, 26/$20^{\circ}C$, and 70%, respectively. Leaf length, leaf width, leaf area, top fresh weight and dry weight of paprika seedlings, and chlorophyll content in paprika leaves nursed under LED and fluorescent lamps for 21 days after experiment were significantly affected by light treatments. As compared with the control (white FL), leaf area of paprika grown under blue LED, red LED, and natural light was decreased by 63%, 63%, and 28%, respectively. Top dry weight of paprika grown under blue LED, red LED, and natural light was 64%, 50%, and 22%, respectively, compared with the control. Number of leaves on 18 days after transplanting showed with red LED, blue LED, and natural light by 86%, 84%, and 48%, respectively, compared with the control. On 114 days after transplanting, paprika nursed under blue LED and red LED had relatively short plant height. This result might be caused that the elongation of its internodes was suppressed by the illumination of sole blue or red light. Average number of fruits per plant harvested during 4 weeks after first harvest was 3.5 with red LED, 3.3 with blue LED, 1.0 with natural light, and 2.2 with control, respectively. Early yield of paprika nursed under red LED, blue LED, natural light, and control were 453 g/plant, 403 g/plant, 101 g/plant, and 273 g/plant, respectively. Larger fruit of 136 g was harvested with red LED treatment. Even though the early yield of paprika was greatly increased with artificial lighting, but total yield was almost similar as the harvest period after transplanting in greenhouses was lengthened. From the above results, we could understand that paprika nursed under white FL, blue LED, and red LED showed good growth after transplanting and was early harvested by a week as compared to the natural light. Therefore, the white FL, blue LED, and red LED as the artificial lighting sources in CTPS could be strategically used to enhance the seedling quality, to shorten the harvest time, and to increase the yield of paprika.

• KIEAE Journal
• /
• v.12 no.4
• /
• pp.71-76
• /
• 2012

The light is one of the most important factors in architectural design. Especially, natural light is the valuable source of illumination that can be utilized for better indoor environment. Compared to artificial light, it is a sustainable energy source without the cost of electric energy and offers a more natural feeling to residents stayed in buildings. Natural light also creates light and shadow in building. It enables people to perceive the depth of space. Many architects have tried to suggest various technologies to create optimum indoor environment by using the natural light. Therefore, this paper tried to examine the works of Le Corbusier and to analyze how to control the light in his works and apply it to his design. It will help to know how he created different characteristics to spaces by using natural light.

• Carbon letters
• /
• v.16 no.3
• /
• pp.135-146
• /
• 2015

Graphite can be classified into natural graphite from mines and artificial graphite. Due to its outstanding properties such as light weight, thermal resistance, electrical conductivity, thermal conductivity, chemical stability, and high-temperature strength, artificial graphite is used across various industries in powder form and bulk form. Artificial graphite of powder form is usually used as anode materials for secondary cells, while artificial graphite of bulk form is used in steelmaking electrode bars, nuclear reactor moderators, silicon ingots for semiconductors, and manufacturing equipment. This study defines artificial graphite as bulk graphite, and provides an overview of bulk graphite manufacturing, including isotropic and anisotropic materials, molding methods, and heat treatment.

• Analytical Science and Technology
• /
• v.25 no.3
• /
• pp.197-206
• /
• 2012

Ambers are composed of polymer molecules which contain aromatic moieties such as benzene, naphthalene, phenanthrene and anthracene. They emit fluorescence when irradiated with ultraviolet light, which was used for confirming an amber. The fluorescence of amber, however, tends to decrease as the surface of amber is weathered with light, heat, oxygen for a long time. In this study, the reliability of confirming amber with its fluorescence by measuring the changes of fluorescence after artificial aging. Aging factors were UV light (${\lambda}$=340 nm), oxygen with heat (100%, $90^{\circ}C$) and heat ($90^{\circ}C$) and aging time was for 5, 15, 30 and 60 days, respectively. In the excitation and emission spectra of amber, the intensity decreased and the maximal wavelength was shifted to longer wavelength with artificial aging time. Especially, there was a drastic decrease in the intensity of spectra to 1.7% of initial value after 60 days aging under oxygen with heat. Only in Colombian amber there showed an increase of fluorescence intensity for a certain aging time, which could be explained by the production of aromatic ring in the presence of light and heat. Conclusively, the fluorescence can be lessened by the natural weathering with light, heat and oxygen and it is not accurate to recognize amber just with UV irradiation method.

• Applied Chemistry for Engineering
• /
• v.20 no.6
• /
• pp.681-684
• /
• 2009

The turbidity of flow type samples has a nonlinear relation to brightness of laser scattered light, but the shape of images in laser scattered light is different from each turbidity samples. The turbidity measurement will be easy if it uses a pattern of images in laser scattered light. But the excessive analysis load comes from the turbidity measured by red, green, blue intensity (intensity) of all pixels of images in laser scattered light. Therefore the images in laser scattered light were divided by appropriate block to decrease excessive analysis load. The shape of divided images in laser scattered light was different from each turbidity sample. The real turbidity has a linear relation to turbidity measured by the artificial neural network learned with the intensity of divided images in laser scattered light and turbidity.

• Journal of the Korean Society of Tobacco Science
• /
• v.17 no.1
• /
• pp.5-14
• /
• 1995

Efficient algorithms for the automatic classification of flue-cured tovacco ripeness and grading have been developed The ripeness of the tobacco was classified into 4 levels vased on the color. The lab-built simple RGB color measuring system was utilized for detecting the light reflectance of the tobacco leaves. The measured data were used far training the artificial neural network The performance of the trained network was also tested far the untrained samples. The spectrophotometer was used to detect the light reflectance and absorption of the graded tobacco leaves in the frequency ranges of the visible light The measured data and the statistical analysis was performed to investigate the light characteristics of the graded samples. The measured data were obtained from samples of 5 different grades directly without considering the leaf positions. Those data were used far training the artificial neural network The performance of the trained network was also tested far the untrained samples. The neural network based sensor information processing showed successful results for grading of tobacco leaves.