• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.113-119
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• 2019

The key features of 5G mobile communications recently commercialized can be represented by High Data Rate, Connection Density and Low Latency, of which the features most distinct from the existing 4G will be low Latency, which will be the foundation for various new service offerings. AR and self-driving technologies are being considered as services that utilize these features, and 5G Network Latency is also being discussed in related standards. However, it is true that the discussion of E2E Latency from a service perspective is much lacking. The final goal to achieve low Latency at 5G is to achieve 1ms of air interface based on RTD, which can be done through Ultra-reliable Low Latency Communications (URLLC) through Rel-16 in early 20 years, and further network parity through Mobile Edge Computing (MEC) is also being studied. In addition to 5G network-related factors, the overall 5G E2E Latency also includes link/equipment Latency on the path between the 5G network and the IDC server for service delivery, and the Processing Latency for service processing within the mobile app and server. Meanwhile, it is also necessary to study detailed service requirements by separating Latency for initial setup of service and Latency for continuous service. In this paper, the following three factors were reviewed for initial setup of service. First, the experiment and analysis presented the impact on Latency on the Latency in the case of 1 Data Lake Setup, 2 CRDX On/Off for efficient power, and finally 3H/O on Latency. Through this, we expect Low Latency to contribute to the service requirements and planning associated with Latency in the initial setup of the required services.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.523-529
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• 2020

Power distribution management system is essential for the efficient management and operation of power distribution networks. The power distribution system is a system that manages the distribution network based on IT, and has been evolving along with the development of the power industry. The current power distribution system is designed to operate at a relatively low network transmission speed based on the independent operation of the main equipment. However, due to distributed resources such as photovoltaic or energy storage devices, which are rapidly increasing in popularity in recent years, the operation of future distribution environments is becoming more complex, and various information needs to be collected in real time. In this study, the requirements of the next-generation power distribution system were derived to overcome the limitations of the existing power distribution system, and based on this, the communication network system and performance requirements for the distribution system were defined. In order to verify the performance of the designed system, a software-based terminal device simulator was developed because it takes excessive time and cost to introduce a large-scale system such as a power distribution system. Using the simulator, a test environment similar to the actual operation was established, and the number of terminal devices was increased up to 1,000. The proposed system was shown to satisfy the requirements to support the functions of the next-generation power distribution system, recording less than 10 % of the communication network bandwidth.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.1
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• pp.56-69
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• 2021

In this paper, the PV system with a link to the commercial system needs some advantages like small capacity, high power factor, high reliability, low harmonic output, maximum power operation of solar cell, and low cost, etc. as well as the properties of inverter. To transfer the PV energy of photovoltaic power generation system to the system and load, it requires PCS in both directions. The purpose of this paper is to confirm the stable power supply through the load leveling by presenting the PCS considering ESS of photovoltaic power generation. In order to achieve these purpose, 5 step process of operation mode algorithm were used according to the solar insolation amount and load capacity and the controller for charging/ discharging control was designed. For bidirectional and effective energy transfer, the bidirectional converter and battery at DC-link stage were connected and the DC-link voltage and inverter output voltage through the interactive inverter were controlled. In order to prove the validity of the suggested system, the simulation using PSIM was performed and were reviewed for its validity and stability. The 3[kW] PCS was manufactured and its test was conducted in order to check this situation. In addition, the system characteristics suggested through the test results was verified and the PCS system presented in this study was excellent and stronger than that of before system.

• 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.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.168-174
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• 2022

In a wave power generation system, the overtopping system is known as an overtopping wave energy converter (OWEC). The performance of an OWEC is affected by wave characteristics such as height and period because its power generation system is sensitive to those characteristics; these, as well as wave direction, depend on the sea. As these characteristics vary, it is hard for the OWEC to produce power in a stable manner. Therefore, it is necessary to find an appropriate shape for an OWEC, according to the characteristics of the sea it is in. This research verified the effect of the design of the OWEC ramp on the hydraulic efficiency using the smoothed particle hydrodynamics (SPH) particle method. A total of 10 models were designed and used in simulations performed by selecting the design parameters of the ramp and changing the attack angle based on those parameters. The hydraulic efficiency was calculated based on the rate of discharged water obtained from the analysis result. The effect of each variable on the overtopping performance according to the shape of the ramp was then confirmed. In this study, we present suggestions for determining the direction for an appropriately shaped OWEC ramp, based on a specific sea area.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.55-62
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• 2022

The perovskite solar cell is an active part of research in renewable energy fields such as solar energy, wind, hydroelectric power, marine energy, bioenergy, and hydrogen energy to replace fossil fuels such as oil, coal, and natural gas, which will gradually disappear as power demand increases due to the increase in use of the Internet of Things and Virtual environments due to the 4th industrial revolution. The perovskite solar cell is a solar cell device using an organic-inorganic hybrid material having a perovskite structure, and has advantages of replacing existing silicon solar cells with high efficiency, low cost solutions, and low temperature processes. In order to optimize the light absorption layer thin film predicted by the existing empirical method, reliability must be verified through device characteristics evaluation. However, since it costs a lot to evaluate the characteristics of the light-absorbing layer thin film device, the number of tests is limited. In order to solve this problem, the development and applicability of a clear and valid model using machine learning or artificial intelligence model as an auxiliary means for optimizing the light absorption layer thin film are considered infinite. In this study, to estimate the light absorption layer thin-film optimization of perovskite solar cells, the regression models of the support vector machine's linear kernel, R.B.F kernel, polynomial kernel, and sigmoid kernel were compared to verify the accuracy difference for each kernel function.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.554-562
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• 2022

Humans technological advancements have resulted in the depletion of whale resources. Accordingly, the International Whaling Commission was established to preserve whale resources and ensure the orderly development of the whaling industry. After a commercial whaling moratorium came into effect, the international trade of whale meat and related products was banned. However, There is a systematic activity through illegal remodeling ships because whales incidentally caught may be distributed in Korea and have a significant economic benefit. Although suspected illegal whaling is actively cracked down, but it is still insufficient to prevent illegal whaling and distribution. To prevent this, stereoscopic crackdowns utilizing air forces and patrol ships are effective, and it is necessary to quickly separate the captured ship and crew to prevent the destruction of evidence. For the transparent distribution of whale meat, it is necessary to advance related technologies such as whale species identification and individual identification of forensic science institutions based on whale DNA database of the National Institute of Fisheries Science. Accordingly, the Korea Coast Guard Research Center is directly conducting research on related national R&D project. To increase the efficiency of identifying whale-related evidence at crime scene, a rapid test kit that responds specifically to whale bloodstrains is developing and evidence transport packs are manufacturing and distributing, while identification technologies are also being advanced.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.936-939
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• 2022

As air combat system technologies developed in recent years, the development of air defense systems is required. In the operating concept of the anti-aircraft defense system, selecting an appropriate armament for the target is one of the system's capabilities in efficiently responding to threats using limited anti-aircraft power. Much of the flying threat identification relies on the operator's visual identification. However, there are many limitations in visually discriminating a flying object maneuvering high speed from a distance. In addition, as the demand for unmanned and intelligent weapon systems on the modern battlefield increases, it is essential to develop a technology that automatically identifies and classifies the aircraft instead of the operator's visual identification. Although some examples of weapon system identification with deep learning-based models by collecting video data for tanks and warships have been presented, aerial vehicle identification is still lacking. Therefore, in this paper, we present a model for classifying fighters, helicopters, and drones using a convolutional neural network model and analyze the performance of the presented model.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.31-38
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• 2022

An electrocardiogram(ECG) is a recoding of electrical signals of the heart's cyclic activity and an important body information for diagnosing myocardial rhythm. Large amount of information are generated continuously and a significant period of cumulative signal is required for the purpose of diagnosing a specific disease. Therefore, research on compression including clinically acceptable lossy technique has been developed to reduce the amount of information significantly. Recently, wearable smart heart monitoring devices that can transmit electrocardiogram(ECG) are being developed. The use of electrocardiogram, an important personal information for healthcare service, is rapidly increasing. However, devices generally have limited capability and power consumption for user convenience, and it is often difficult to apply the existing compression method directly. It is essential to develop techniques that can process and transmit a large volume of signals in limited resources. A method for compressing and transmitting the ECG signals efficiently by using the cumulative average (template) of the unit waveform is proposed in the paper. The ECG is coded lovelessly using template matching. It is analyzed that the proposed method is superior to the existing compression methods at high compression ratio, and its complexity is not relatively high. And it is also possible to apply compression methods to template matching values.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.339-346
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• 2022

Recently, the resource depletion and climate change problem caused by the massive usage of fossil fuels for electric power generation has become a critical issue worldwide. According to this issue, interest in renewable energy resources that can replace fossil fuels is increasing. Especially, photovoltaic power has gaining much attention because there is no risk of resource exhaustion compared to other energy resources and there are low restrictions on installation of photovoltaic system. In order to use the power generated by the photovoltaic system efficiently, a more accurate photovoltaic power forecasting model is required. So far, even though many machine learning and deep learning-based photovoltaic power forecasting models have been proposed, they showed limited success in terms of interpretability. Deep learning-based forecasting models have the disadvantage of being difficult to explain how the forecasting results are derived. To solve this problem, many studies are being conducted on explainable artificial intelligence technique. The reliability of the model can be secured if it is possible to interpret how the model derives the results. Also, the model can be improved to increase the forecasting accuracy based on the analysis results. Therefore, in this paper, we propose an explainable photovoltaic power forecasting scheme based on BiLSTM (Bidirectional Long Short-Term Memory) and SHAP (SHapley Additive exPlanations).