• Journal of Korea Multimedia Society
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• v.22 no.9
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• pp.1069-1079
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• 2019

In this study, we developed a $PM_{10}$ forecasting model using DNN and Membership Function, and improved the forecasting performance. The model predicts the $PM_{10}$ concentrations of the next 3 days in the Seoul area by using the weather and air quality observation data and forecast data. The best model(RM14)'s accuracy (82%, 76%, 69%) and false alarm rate(FAR:14%,33%,44%) are good. Probability of detection (POD: 79%, 50%, 53%), however, are not good performance. These are due to the lack of training data for high concentration $PM_{10}$ compared to low concentration. In addition, the model dose not reflect seasonal factors closely related to the generation of high concentration $PM_{10}$. To improve this, we propose Julian date membership function as inputs of the $PM_{10}$ forecasting model. The function express a given date in 12 factors to reflect seasonal characteristics closely related to high concentration $PM_{10}$. As a result, the accuracy (79%, 70%, 66%) and FAR (24%, 48%, 46%) are slightly reduced in performance, but the POD (79%, 75%, 71%) are up to 25% improved compared with those of the RM14 model. Hence, this shows that the proposed Julian forecast model is effective for high concentration $PM_{10}$ forecasts.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.186-194
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• 2018

The aim of this study was to examine the effects of an after-school basketball training program of 12 weeks on physical abilities (grip strength, endurance, and flexibility) and learning-related factors (cognition strength, cognition speed, concentration, and mental workload) in middle school students. Middle school students (Males, N=20) were recruited for use in this study and were randomly divided into either a basketball training group (n = 10, BT) or a non-exercise control group (n = 10, CON). Two-way repeated measures ANOVA with post-hoc testing was used for data analysis. Results found endurance and flexibility in the BT group were significantly increased, but not in the CON group. In addition, cognition strength, speed, and concentration in the BT group increased and mental workload in the BT group slightly decreased. In contrast, the CON group showed a significant increase in mental workload. Our findings show that participation in after-school physical education activities (e.g., basketball training program) positively improves physical abilities and increases brain functions for learning.

• Journal of Soil and Groundwater Environment
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• v.25 no.3
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• pp.74-83
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• 2020

Since fine dust (PM₁₀) has a significant influence on soil and groundwater composition during dry and wet deposition processes, it is of a vital importance to understand the fate and transport of aerosol in geological environments. Fine dust is formed after the chemical reaction of several precursors, typically observed in short intervals within a few hours. In this study, deep learning approach was applied to predict the fate of fine dust in an urban area. Deep learning training was performed by combining convolutional neural network (CNN) and recurrent neural network (RNN) techniques. The PM₁₀ concentration after 1 hour was predicted based on three-hour data by setting SO₂, CO, O₃, NO₂, and PM₁₀ as training data. The obtained coefficient of determination value, R², was 0.8973 between predicted and measured values for the entire concentration range of PM₁₀, suggesting deep learning method can be developed into a reliable and viable tool for prediction of fine dust concentration.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.3
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• pp.422-428
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• 1999

The mineral status of native goats and forage species, namely; Cynodon plectostachyus, Pennisetum purpureum. Eleusine indica, Cynodon dactylon, Calopogonium muconoides, Centrosema pubescens, Leucaena leococephala, and Mimosa pudica in lahar affected areas of Concepcion, Tarlac, Philippines were determined. Forage and blood samples were collected six times in 1996-97, and analyzed for calcium, phosphorus, magnesium, sulfur, copper, iron, molybdenum, selenium, and zinc. Forage calcium and sulfur are non-limiting. Most species had low phosphorus, copper and selenium, while some had magnesium and zinc levels lower than the critical limit because of low mineral content and high percolation rate of lahar deposits. Iron and molybdenum were in excess. The effect of seasonal variation was observed only in copper, sulfur and iron. Average blood mineral concentration of the animals was above critical limit, but there were no significant differences between seasons. All the animals had plasma phosphorus and magnesium above critical level; but 20 % had low copper, zinc and selenium especially in dry season possibly due to insufficient amount of these elements and excessive molybdenum and iron in most forage. Conversely, calcium in forage was high; but 40 % of the animals had low plasma calcium concentration. Although no clinical signs of mineral deficiencies were observed, supplemental feeding would be important since the condition of the pasture in lahar-laden areas is not expected to improve in the next five years. Intensified use of L. leucocephala with better mineral profile would be ideal.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.67-73
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• 2023

Under the influence of COVID-19, as a measure of social distancing for about two years and one month, non-face-to-face services using ICT element technology are expanding not only to the education sector but to all fields. In particular, as educational programs using the Metaverse platform spread to various fields, educators, and learners have more learning experiences using Edutech, but problems through non-face-to-face learning such as reduced immersion or concentration in education are raising In this paper, to overcome the problems raised through non-face-to-face learning and develop metaverse immersive media digital contents to improve the educational environment, we utilize VR (Virtual Reality) based on an immersive metaverse to provide education / Training contents and the educational environment was established. In this paper, we presented a system to increase immersion and concentration in educational contents in a virtual environment using HMD (Head Mounted Display) for learners who are put into military education/training. Immersion was further improved.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.330-336
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• 2023

Rapid urbanization is rapidly progressing around the world, and urban problems such as traffic congestion, environmental pollution, and noise pollution are emerging, due to this urban concentration phenomenon, logistics and transportation costs are increasing. Urban Air Mobility(UAM) is a three-dimensional futuristic urban transportation that is expected to become an important transportation axis of smart cities as a service(MaaS) linked to roads, railways, and personal transportation. However, as of July 2023, research on airspace systems, Bertieport design, navigation, and communication for UAM operation is actively being conducted, but little research has been conducted on the concept of pilot education and training and education and training programs. Therefore, this paper aims to present a suitable plan for the domestic pilot training system through SWOT analysis of vertical takeoff and landing(VTOL) pilot education and training programs in the United States and Europe.

• International Journal of Industrial Entomology and Biomaterials
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• v.5 no.2
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• pp.171-174
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• 2002

Two systemic fungicides, SF1 (Bavistin, a carbandazim fungicide 50% WP, Rallis India ltd., India) and SF2 (Bayleton 25% WP-Triadiamefon, a Triazole compound, Rallis India Ltd., India) were screened for control of muscardine disease in silkworm, Bombyx mori. One and two percent of SF1 and 0.05 and 0.1 % of SF2 in aqueous solution were found to be effective in in vivo condition for the control of the disease. These fungicides, on feeding through mulberry leaves continuously for two days to 4$^{th}$ and 5$^{th}$ instar silkworm larvae inoculated topically with conidia of Beauveria bassiana (4$\times$10$^{6}$ conidia/ml) resulted in reduction in mortality due to muscardine by over 90% as against 100% mortality in inoculated control. SF1 at 1% reduced the mortality by 90% in 4$^{th}$ instar and 91% in final instar silkworm while at 2%, the reduction was 92% and 96%, respectively. SF2 at 0.05 and 0.1 % concentration reduced the mortality by 82 and 88% during 4$^{th}$ instar and by 88 and 92% during 5$^{th}$ instar, respectively.

• International Journal of Industrial Entomology and Biomaterials
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• v.3 no.2
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• pp.187-190
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• 2001

Inheritance pattern of resistance to Bombyx mori nuclear polyhedrosis virus (BmNPV) was studied in an Indian silkworm stock TX by single back-cross test method. The resistant parent ［TX］, susceptible parent ［HM］, their Fl, F2, and Fl progeny back-crossed to TX [BC(R)] and HM [BC(S)] were inoculated per os with a fixed concentration of BmNPV($0.5{\times}10^{th} PIB/ml$) on the first day of second stadium. The cumulative mortality was recorded until day $10^{\times}$ post-inoculation. The results show that the resistance to BmNPV in TX fellow mono Mendelian inheritance pattern. The resistance dominated over the susceptibility at Fl. At F2, the resistant and susceptible offspring segregated in 3:1 ratio whereas at BC(S), the resistant and susceptible offspring segregated in 1:1 ratio. The response of BC(R) was more or less like the resistant parent TX which confirms the involvement of a major dominant gene conferring resistance to BmNPV in TX. The possible mechanism of inheritance of resistance in TX is discussed.

• Journal of Korea Multimedia Society
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• v.14 no.9
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• pp.1202-1209
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• 2011

Neuro feedback training using ElectroEncephalo Grams (EEGs) is commonly utilized in the treatment of Alzheimer's disease, and Attention Deficit Hyperactivity Disorder (ADHD). Recently, BCI (Brain-computer Interface) contents have developed, not for the purpose of treatment, but for concentration improvement or brain relaxation training. However, as each user has different wave forms, it is hard to develop contents controlled by such different wave. Therefore, an EEG process that allows the ability to transform the variety of wave forms into one standard signal and use it without taking a user's characteristic of EEG into account, is required. In this paper, a framework that can reduce users' characteristics by normalizing and converting measured EEGs is proposed for contents. This framework also contains the process that controls different brainwave measuring devices. In experiment a handling process applying the proposed framework to the developed BCI contents is introduced.

• Environmental Engineering Research
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• v.25 no.4
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• pp.515-521
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• 2020

Nowadays, due to various pollution sources, it is essential for environmental scientists to monitor water quality. Phytoplanktons form the end of the food chain in water bodies and are one of the most important biological indicators in water pollution studies. Chlorophyll-A, a green pigment, is found in all phytoplankton. Chlorophyll-A concentration indicates phytoplankton biomass directly. Therefore, Chlorophyll-A is an indirect indicator of pollutants, including phosphorus and nitrogen, and their refinement and control are important. The present study, Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images were used to estimate the chlorophyll-A concentration in southern coastal waters in the Caspian Sea. For this purpose, Multi-layer perceptron neural networks (NNs) were applied which contained three and four feed-forward layers. The best three-layer NN has 15 neurons in its hidden layer and the best four-layer one has 5 in each. The three- and four- layer networks both resulted in similar root mean square errors (RMSE), 0.1($\frac{{\mu}g}{l}$), however, the four-layer NNs proved superior in terms of R² and also required less training data. Accordingly, a four-layer feed-forward NN with 5 neurons in each hidden layer, is the best network structure for estimating Chlorophyll-A concentration in the southern coastal waters of the Caspian Sea.