• Proceedings of the Korea Water Resources Association Conference
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• 1997.05a
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• pp.409-413
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• 1997

• KIEAE Journal
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• v.9 no.3
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• pp.61-68
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• 2009

Gwangju Metropolitan Government & Ministry of Environment have signed a model city in response to Climate Change agreement. The agreement calls for Gwangju to cut greenhouse gas emissions 10% below 2005 levels by 2015. Gwangju has seen this agreement as an opportunity to cut pollution and conserve the environment as well as to reinvigorate local economy. According to policy of Gwangju, Gwangju held design competition for Gwangju City Arboretum on march, 2009. The purpose of design competition was to give a wide publicity to Gwangju as Hub City of Asian Culture and construct carbon-neutral arboretum in accordance with the policy of 'Low-Carbon and Green Growth'. First of all, a design concept of arboretum is 'winding, round, overlay 'to reflect the landscape of Nam-do which is surrounded by mountains and river flows through the village. Second, the arboretum has five different places with these themes - Forest of Festivals, Health, Nature, Nostalgia, Education and Future. Each place has a symbolic theme park and different flow planning respectively. Third, the most critical point is that the arboretum is a carbon-neutral park. Gwangju arboretum will soon be developed in metropolitan sanitary landfill and constructed as the O2 arboretum based on low carbon strategy. Fourth, the O2 arboretum suggests specialized issue : 'Energy Saving', 'Recycling System', 'Green Network', 'Water System(rainwater maintenance and wetland development)'. Besides, main buildings(greenhouse, visitor center, Nam-do experience exhibition hall, and forest museum) is designed in consideration of harmony with topography character, surroundings. Also, planting will be a multilayer plant based on native landscape trees in consideration of function and the growth characteristics.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.13-30
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• 2023

Since the COVID-19 vaccine became available, people have been sharing their opinions on social media about getting vaccinated, causing discussions of the vaccine to trend on Twitter alongside certain events, making the website a rich data source. This paper explores people's perceptions regarding the COVID-19 vaccine during certain events and how these events influenced public opinion about the vaccine. The data consisted of tweets sent during seven important events that were gathered within 14 days of the first announcement of each event. These data represent people's reactions to these events without including irrelevant tweets. The study targeted tweets sent in Arabic from users located in Saudi Arabia. The data were classified as positive, negative, or neutral in tone. Four classifiers were used-support vector machine (SVM), naïve Bayes (NB), logistic regression (LOGR), and random forest (RF)-in addition to a deep learning model using BiLSTM. The results showed that the SVM achieved the highest accuracy, at 91%. Overall perceptions about the COVID-19 vaccine were 54% negative, 36% neutral, and 10% positive.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.151-156
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• 2008

This paper presents the stability analysis and design for a sampled-data fuzzy control system with neutral type of time delay, which is formed by a nonlinear plant and a sampled-data fuzzy controller connected in a closed loop. The sampling activity and neutral type of time delay will complicate the system dynamics and make the stability analysis much more difficult than that for a pure continuous-time fuzzy control system. Based on the fuzzy-model-based control approach, LMI(linear matrix inequality)-based stability conditions are derived to guarantee the nonlinear networked system stability. An application example will be given to show the merits and design a procedure of the proposed approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1925-1932
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• 2016

One of the major challenges in the design of wireless sensor network (WSN) is to reduce the energy consumption of sensor nodes for prolonging the network lifetime. In the sensor network, communication is the most energy consuming event. Therefore, most of the energy saving techniques conserve energy by adjusting different parameters of the trans-receiver. Among them, one of the promising methods is the transmission power control (TPC). In this paper, we investigated the effects of the link quality based TPC scheme employed to the IEEE 802.15.4 standard for energy saving. The simulation results demonstrated that the link quality based TPC scheme works effectively in conserving energy as compared to the conventional IEEE 802.15.4.

• Journal of the Korean institute of surface engineering
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• v.17 no.2
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• pp.29-40
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• 1984

The structure of rapidly solidified Al-Si-based alloys and its relationship to subsequent anodic film growth in near neutral and acid solutions have been investigated. Solidification of the alloys proceeds via pre-dendritic nuclei, associated with rugosity of the casting surface, from which cellular-type growth, comprised of aluminium-rich material surrounded by silicon-containing material, emanates. Observation of ultramicrotomed sections of the alloys and their anodic films reveals the local oxidation of the silicon-rich phase and its incorporation into the anodic alumina film, formed in near neutral solutions. Such incorporation occurs but resultant isolation of the silicon-rich phase is not possible for anodizing in phosphoric acid, and a three-dimensional network of the oxidized silicon-containing phase, with continuing development of porous anodic alumina, is observed.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.78.3-78.3
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• 2019

We develop a novel technique that can constrain the evolutionary track of the epoch of reionization (EoR) by applying the convolutional neural network (CNN) to the 21-cm differential brightness temperature. We use 21cmFAST, a fast semi-numerical cosmological 21-cm signal simulator, to produce mock 21-cm map between z=6-13. We design a CNN architecture that predicts the volume-averaged neutral hydrogen fraction from the given 21-cm map. The estimated neutral fraction has a good agreement with its truth value even after smoothing the 21-cm map with somewhat realistic choices of beam size and the frequency bandwidth of the Square Kilometre Array (SKA). Our technique could be further utilized to denoise the 21-cm map or constrain the properties of the radiation sources.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.66.2-66.2
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• 2020

We propose a deep learning analysis technique with a convolutional neural network (CNN) to predict the evolutionary track of the Epoch of Reionization (EoR) from the 21-cm differential brightness temperature tomography images. We use 21cmFAST, a fast semi-numerical cosmological 21-cm signal simulator, to produce mock 21-cm maps between z = 6 ~ 13. We then apply two observational effects, such as instrumental noise and limit of (spatial and depth) resolution somewhat suitable for realistic choices of the Square Kilometre Array (SKA), into the 21-cm maps. We design our deep learning model with CNN to predict the sliced-averaged neutral hydrogen fraction from the given 21-cm map. The estimated neutral fraction from our CNN model has great agreement with the true value even after coarsely smoothing with broad beam size and frequency bandwidth and heavily covered by noise with narrow beam size and frequency bandwidth. Our results show that the deep learning analyzing method has the potential to reconstruct the EoR history efficiently from the 21-cm tomography surveys in future.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.4
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• pp.419-425
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• 2020

DC distribution system has been evaluated as an excellent one in comparison with existing AC distribution network because it needs fewer power conversion stages and the full capacity of the equipment can be used without consideration for power factor. Recently, research and development on the implementation of DC distribution networks have been progressed globally based on the rapid advancement in power-electronics technology, and the technological developments from the viewpoint of infrastructure are also in progress. However, to configure a distribution network which is a distribution line for DC, more accurate and rapid introduction of analysis technology is needed for the monitoring, control and operation of the system, which ensure the system run flexible and efficiently. However, in case of a bipolar DC distribution network, there are two buses acting as slack buses, so the Jacobian matrix cannot be configured. Without solving this problem, DC distribution network cannot be operated when the network is unbalanced. Therefore, this paper presented a comprehensive method of analysis with consideration of operating elements which are directly connected between neutral electric potential caused by the unbalanced of load in DC distribution network with bipolar structure.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.79-85
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• 2001

We obtain a solution of inverse kinematic of 3 axis manipulator by using a self-organizing neral network(SONN) with a fuzzy compensator. The self-organizing neural network using the gaussian potential function as the activation function has one hidden layer in the first learning time. The network obtains the optimal number of node by increasing the number of hidden layer node through the learning, and the fuzzy compensator has the optimal loaming rate of neutral network. In this results, we can confirmed that the learning rate is improved and the rapid convergence to the steady-state.