• Journal of IKEEE
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• v.25 no.2
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• pp.399-407
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• 2021

This paper proposes the DC-link voltage design method of Type 4 wind turbine that minimizes power loss and satisfies the High Voltage Ride Through(HVRT) function requirements of the transmission system operator. The Type 4 wind turbine used for large-capacity offshore wind turbine consists of the Back-to-Back converter in which the converter linked to the power grid and the inverter linked to the wind turbine share the DC-link. When the grid high voltage fault occurs in the Type 4 wind turbine, if the DC-link voltage is insufficient compared to the fault voltage level, the current controller of the grid-side converter can't operate smoothly due to over modulation. Therefore, to satisfy the HVRT function, the DC-link voltage should be designed based on the voltage level of high voltage fault. However, steady-state switching losses increase further as the DC-link voltage increases. Therefore, the considerations should be included for the loss to be increased when the DC-link voltage is designed significantly. In this paper, the design method for the DC-link voltage considered the fault voltage level and the loss is explained, and the validity of the proposed design method is verified through the HVRT function simulation based on the PSCAD model of the 2MVA Type 4 wind turbine.

• Clean Technology
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• v.27 no.1
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• pp.61-68
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• 2021

Selective catalytic reduction (SCR) is widely used as a method of removing nitrogen oxide in large-capacity thermal power generation systems. Uniform mixing of the injected ammonia and the inlet flue gas is very important to the performance of the denitrification reduction process in the catalyst bed. In the present study, a computational analysis technique was applied to the ammonia injection system design process of a denitrification facility. The applied model is the denitrification facility of an 800 MW class coal-fired power plant currently in operation. The flow field to be solved ranges from the inlet of the ammonia injection system to the end of the catalyst bed. The flow was analyzed in the two-dimensional domain assuming incompressible. The steady-state turbulent flow was solved with the commercial software named ANSYS-Fluent. The nozzle arrangement gap and injection flow rate in the ammonia injection system were chosen as the design parameters. A total of four (4) cases were simulated and compared. The root mean square of the NH3/NO molar ratio at the inlet of the catalyst layer was chosen as the optimization parameter and the design of the experiment was used as the base of the optimization algorithm. The case where the nozzle pitch and flow rate were adjusted at the same time was the best in terms of flow uniformity.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.287-300
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• 2021

The purpose of this study is to verify the influence relationship of digitally converted services on consumers' intention to use since traditional services are being converted to digital services due to technological development and increase in non-face-to-face services. The study consisted of a program development procedure and a program effectiveness verification procedure, and bootstrapping was performed to verify the mediating effect adjusted along with multiple regression analysis. The subjects of this study were 323 university (graduate) students and the general public residing in Korea. Results. First, it was found that the three perceived interaction factors (perceived communication, perceived control, and perceived reactivity) of digital transformed services had a positive effect on perceived usefulness and perceived ease of use, respectively. Second, the relationship of influence of technology acceptance intention was verified. Third, it was confirmed that the effect of the three perceived interaction factors of digital transformed services on intention to use was mediated by perceived usefulness and perceived ease of use. Fourth, the mediating effect mediated by digital disparity was confirmed. As a result, it was confirmed that the three perceived interaction factors of the digitally converted service are important factors in the intention to use the digitally converted service. This suggests that efforts are needed to minimize the digital divide.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.373-380
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• 2022

This paper presents a deep learning based group synchronization that supports networked immersive interactions between remote users. The goal of group synchronization is to enable all participants to synchronously interact with others for increasing user presence Most previous methods focus on NTP-based clock synchronization to enhance time accuracy. Moving average filters are used to control media playout time on the synchronization server. As an example, the exponentially weighted moving average(EWMA) would be able to track and estimate accurate playout time if the changes in input data are not significant. However it needs more time to be stable for any given change over time due to codec and system loads or fluctuations in network status. To tackle this problem, this work proposes the Deep Group Synchronization(DeepGroupSync), a group synchronization based on deep learning that models important features from the data. This model consists of two Gated Recurrent Unit(GRU) layers and one fully-connected layer, which predicts an optimal playout time by utilizing the sequential playout delays. The experiments are conducted with an existing method that uses the EWMA and the proposed method that uses the DeepGroupSync. The results show that the proposed method are more robust against unpredictable or rapid network condition changes than the existing method.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.87-94
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• 2022

Recently, with the development of information and communication infrastructure, the number of Internet access devices is rapidly increasing. Smartphones, laptops, computers, and even IoT devices are receiving information and communication services through Internet access. Since most of the device operating environment consists of web (WEB), it is vulnerable to web cyber attacks using web shells. When the web shell is uploaded to the web server, it is confirmed that the attack frequency is high because the control of the web server can be easily performed. As the damage caused by the web shell occurs a lot, each company is responding to attacks with various security devices such as intrusion prevention systems, firewalls, and web firewalls. In this case, it is difficult to detect, and in order to prevent and cope with web shell attacks due to these characteristics, it is difficult to respond only with the existing system and security software. Therefore, it is an automated defense system through the collection and analysis of web shells based on artificial intelligence machine learning that can cope with new cyber attacks such as detecting unknown web shells in advance by using artificial intelligence machine learning and deep learning techniques in existing security software. We would like to propose about. The machine learning-based web shell defense system model proposed in this paper quickly collects, analyzes, and detects malicious web shells, one of the cyberattacks on the web environment. I think it will be very helpful in designing and building a security system.

• Journal of Korea Water Resources Association
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• v.55 no.2
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• pp.111-120
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• 2022

The concept of soil moisture memory was used as a method for quantifying the function of soil to control water flow, which evaluates the average residence time of precipitation. In order to characterize the soil moisture memory, a new measurement index called stored precipitation fraction (F_p(f)) was used by tracking the increments in soil moisture by the precipitation event. In this study, the temporal and spatial distribution of soil moisture memory was evaluated along with the slope and soil characteristics of the surface (0~5 cm) soil by using satellite- and model-based precipitation and soil moisture in the Korean peninsula, from 2019 to 2020. The spatial deviation of the soil moisture memory was large as the stored precipitation fraction in the soil decreased preferentially along the mountain range at the beginning (after 3 hours), and the deviation decreased overall after 24 hours. The stored precipitation fraction in the soil clearly decreased as the slope increased, and the effect of drainage of water in the soil according to the composition ratio of the soil particle size was also shown. In addition, average soil moisture contributed to the increase and decrease of hydraulic conductivity, and the rate of rainfall transfer to the depths affected the stored precipitation fraction. It is expected that the results of this study will greatly contribute in clarifying the relationship between soil moisture memory and surface characteristics (slope, soil characteristics) and understanding spatio-temporal variation of soil moisture.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.1
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• pp.121-143
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• 2023

This study was conducted with the aim of identifying the current status of the national authority data construction project centered on the National Library of Korea for the effective construction and utilization of national knowledge information resources. It also aimed to reveal the possibility and improvement of the national information system with the international standard identification system, and suggesting future development plans. To this end, this study conducted interviews and questionnaires with members of the Korean National Authority Data Sharing System(KNASS). The survey consisted of items related to the current status and difficulties related to the authority, the use of the KNASS, the recognition and utilization of identifiers, the awareness and utilization of the linkage with ISNI, the Importance-Performance Analysis for activating the KNASS, and the overall satisfaction and improvement direction. As a result of the analysis, it was proposed to develop rules and guidelines related to the authority works, to increase the quantity and quality of authority data, to raise understanding of the importance and establish a efficient work system, to diversify the authority service and develop a utilization model, to link the KNASS with international identifiers, and to share the necessity of the KNASS.

• Journal of the Korea Institute of Building Construction
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• v.22 no.6
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• pp.565-575
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• 2022

Thanks to the latest developments in digital architectural technologies, free-form designs that maximize the creativity of architects have rapidly increased. However, there are a lot of difficulties in forming various free-form curved surfaces. In panelizing to produce free forms, the methods of mesh, developable surface, tessellation and subdivision are applied. The process of applying such panelizing methods when producing free-form panels is complex, time-consuming and requires a vast amount of manpower when extracting production data. Therefore, algorithms are needed to quickly and systematically extract production data that are needed for panel production after a free-form building is designed. In this respect, the purpose of this study is to propose mathematical algorithms for the automatic generation of production data of free-form panels in consideration of the building model, performance of production equipment and pattern information. To accomplish this, mathematical algorithms were suggested upon panelizing, and production data for a CNC machine were extracted by mapping as free-form curved surfaces. The study's findings may contribute to improved productivity and reduced cost by realizing the automatic generation of data for production of free-form concrete panels.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.331-338
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• 2022

Successor representation (SR) is a model of human reinforcement learning (RL) mimicking the underlying mechanism of hippocampal cells constructing cognitive maps. SR utilizes these learned features to adaptively respond to the frequent reward changes. In this paper, we evaluated the performance of SR under the context where changes in latent variables of environments trigger the reward structure changes. For a benchmark test, we adopted SR-Dyna, an integration of SR into goal-driven Dyna RL algorithm in the 2-stage Markov Decision Task (MDT) in which we can intentionally manipulate the latent variables - state transition uncertainty and goal-condition. To precisely investigate the characteristics of SR, we conducted the experiments while controlling each latent variable that affects the changes in reward structure. Evaluation results showed that SR-Dyna could learn to respond to the reward changes in relation to the changes in latent variables, but could not learn rapidly in that situation. This brings about the necessity to build more robust RL models that can rapidly learn to respond to the frequent changes in the environment in which latent variables and reward structure change at the same time.

• Journal of IKEEE
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• v.27 no.3
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• pp.340-344
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• 2023

In this paper, we propose a study on the development of deep learning structure to secure visibility of outdoor LED display board according to weather change. The proposed technique secures the visibility of the outdoor LED display board by automatically adjusting the LED luminance according to the weather change using deep learning using an imaging device. In order to automatically adjust the LED luminance according to weather changes, a deep learning model that can classify the weather is created by learning it using a convolutional network after first going through a preprocessing process for the flattened background part image data. The applied deep learning network reduces the difference between the input value and the output value using the Residual learning function, inducing learning while taking the characteristics of the initial input value. Next, by using a controller that recognizes the weather and adjusts the luminance of the outdoor LED display board according to the weather change, the luminance is changed so that the luminance increases when the surrounding environment becomes bright, so that it can be seen clearly. In addition, when the surrounding environment becomes dark, the visibility is reduced due to scattering of light, so the brightness of the electronic display board is lowered so that it can be seen clearly. By applying the method proposed in this paper, the result of the certified measurement test of the luminance measurement according to the weather change of the LED sign board confirmed that the visibility of the outdoor LED sign board was secured according to the weather change.