• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.3
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• pp.223-228
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• 2019

This study analyzes the propagation of the path losses between Jeju-do and Jin-do transceivers located in the coastal areas of Korea using the Advanced Refractive Prediction System(AREPS) simulation software based on the actual coastal weather database. The simulated data is used to construct a duct map according to the altitude and thickness of the trap. The duct map is then divided into several regions depending on the altitude parameters of Tx and Rx, which can be used to effectively estimate the abnormal wave propagation characteristics due to duct occurrence in the Jeju-do coastal area. To validate the proposed duct map, two representative atmospheric index samples of the weather database in May 2018 are selected, and the simulated path losses using these atmospheric indices are compared with the measured data. The simulated path losses for abnormal conditions at the Rx point at Jeju-do are 167.7 dB and 192.3 dB, respectively, which are in good agreement with the measured data of 164.4 dB and 194.9 dB, respectively.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.6
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• pp.59-69
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• 2005

Ad hoc network is the network which can be considered without a pre-constructed infrastructure, and a mobile node can join the network freely. However, the participation of the mobile nodes to the ad hoc network brings up much burden of re-computation for new routes, because it leads to losing the connection frequently. And, also, it causes serious security problem to be broadcasted wrong information by the malicious user. Therefore, it needs authentication against the mobile nodes. To make that Possible, we have two methods: single CA and distributed CA. In the case of CA method, the wireless network can be collapsed owing to expose the CA, but still the distributed CA method is a little more safe than previous one because it needs attacks toward a lot of CAs to collapse the network We can consider Secret Share scheme as the method that constructs the distributed CA system, but it is weak when the network size is too large. In this paper, we suggest hierarchical structure for the authentication method to solve this problem, and we will show the results of simulation for this suggestion.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.222-234
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• 2020

Autonomous vehicles are equipped with a wide rage of sensors such as GPS, RADAR, LIDAR, camera, IMU, etc. and are driven by recognizing and judging various transportation systems at intersections in the city. The accident ratio of the intersection of the autonomous vehicles is 88% of all accidents due to the limitation of prediction and judgment of an area outside the sensing distance. Not only research on non-signalized intersection collision avoidance strategies through V2V and V2I is underway, but also research on safe intersection driving in failure situations is underway, but verification and fragments through simple intersection scenarios Only typical V2V failures are presented. In this paper, we analyzed the architecture of the V2V module, analyzed the causal factors for each V2V module, and defined the failure mode. We presented intersection scenarios for various road conditions and traffic volumes. we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to analyze the risk of autonomous vehicle based on the simulation. We presented ASIL, which is the result of risk analysis, proposed a monitoring concept for each component of the V2V module, and presented monitoring coverage.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.183-191
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• 2021

Non-intrusive load monitoring is a technology that can be used for predicting and classifying the type of appliances through real-time monitoring of user power consumption, and it has recently got interested as a means of energy-saving. In this paper, we propose a system for classifying appliances from user consumption data by combining GAF(Gramian angular field) technique that can be used for converting one-dimensional data to the two-dimensional matrix with convolutional neural networks. We use REDD(residential energy disaggregation dataset) that is the public appliances power data and confirm the classification accuracy of the GASF(Gramian angular summation field) and GADF(Gramian angular difference field). Simulation results show that both models showed 94% accuracy on appliances with binary-state(on/off) and that GASF showed 93.5% accuracy that is 3% higher than GADF on appliances with multi-state. In later studies, we plan to increase the dataset and optimize the model to improve accuracy and speed.

• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.1
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• pp.22-28
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• 2021

Multivariate processes, such as chemical and mechanical process, power plants are operated in a state where several facilities are complexly connected, the fault of a particular system can also have fatal consequences for the entire process. In addition, since process data is measured in an unstable environment, outlier is likely to be include in the data. Therefore, monitoring technology is essential, which can remove outlier from measured data and detect failures in advance. In this paper, data obtained from dynamic and multivariate process models was used to detect fault in various type of processes. The dynamic process is a simulation of a process with autoregressive property, and the multivariate process is a model that describes a situation when a specific sensor fault. Mahalanobis distance was used to remove outlier contained in the data generated by dynamic process model and multivariate process model, and fault detection was performed using ICA. For comparison, we compared performance with and a conventional single ICA method. The proposed fault detection method improves performance by 0.84%p for bias data and 6.82%p for drift data in the dynamic process. In the case of the multivariate process, the performance was improves by 3.78%p, therefore, the proposed method showed better fault detection performance.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.753-762
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• 2020

With an increasing interest in integrating artificial intelligence (AI) into interview processes, the Republic of Korea (ROK) army is trying to lead and analyze AI-powered interview platform. This study is to analyze the AI interview data using a unified non-crossing multiple quantile tree (UNQRT) model. Compared to the UNQRT, the existing models, such as quantile regression and quantile regression tree model (QRT), are inadequate for the analysis of AI interview data. Specially, the linearity assumption of the quantile regression is overly strong for the aforementioned application. While the QRT model seems to be applicable by relaxing the linearity assumption, it suffers from crossing problems among estimated quantile functions and leads to an uninterpretable model. The UNQRT circumvents the crossing problem of quantile functions by simultaneously estimating multiple quantile functions with a non-crossing constraint and is robust from extreme quantiles. Furthermore, the single tree construction from the UNQRT leads to an interpretable model compared to the QRT model. In this study, by using the UNQRT, we explored the relationship between the results of the Army AI interview system and the existing personnel data to derive meaningful results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.477-483
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• 2021

In a military maintenance system, the standard maintenance man-hour of weapon systems is a tool to estimate the maintenance capabilities of maintenance units, provide standards for determining the maintenance needs and workload, and provide basic data for establishing a maintenance plan. The standard maintenance man-hours of major weapon systems have already been derived and used, but the standard maintenance man-hour in a wartime maintenance environment has not been computed. Therefore, the standard wartime maintenance man-hours need to be derived and This study proposes a process and method of computing the maintenance man-hours. In addition, this work suggests the criteria of collecting and screening data that is necessary for estimating the standard maintenance man-hours and introduces a methodology for analyzing the characteristics of maintenance man-hour distribution in the process. The proposed process first designs a model that reflects the wartime maintenance environment, selects statistical techniques, collects maintenance data, analyzes the descriptive statistics, estimates the distribution, and finally presents representative values of maintenance man-hour. Based on the proposed method, the standard wartime maintenance man-hours of the four weapon systems were calculated, and the distribution of the maintenance man-hours was analyzed to follow a lognormal distribution, and the method presented reliable results.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.287-292
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• 2021

Load and resistance factor design is an efficient design approach that provides a system of consistent design solutions. This study aims to determine the load and resistance factors needed for the design of breakwater foundations within a probabilistic framework. In the study, four typical types of Korean breakwaters, namely, rubble mound breakwaters, vertical composite caisson breakwaters, perforated caisson breakwaters, and horizontal composite breakwaters, are investigated. The bearing capacity of breakwater foundations under wave loading conditions is thoroughly examined. Two levels of the target reliability index (RI) of 2.5 and 3.0 are selected to implement the load and resistance factors calibration using Monte Carlo simulations with 100,000 cycles. The normalized resistance factors are found to be lower for the higher target RI as expected. Their ranges are from 0.668 to 0.687 for the target RI of 2.5 and from 0.576 to 0.634 for the target RI of 3.0.

• Journal of Korean Society of Disaster and Security
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• v.15 no.1
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• pp.47-56
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• 2022

Recently, water resources and energy policies such as integrated water management and carbon neutrality are changing rapidly. There is an opinion that the value of hydropower reservoirs related to these policies should be re-evaluated. In the past, they have contributed to flood control in addition to electricity generation, such as operating at a limited water level during the flood season, but loss of power generation is inevitable with this operation. Therefore, this study introduced the concept of resilience to the hydropower generation system to minimize the power loss. A framework for evaluating the power generation performance of them was presented by defining the maximization of electricity sales as performance. Based on the current procedure of multiple operation plan, a scenario was established and simulation was performed using HEC-5. As a result of applying to the framework, it was confirmed that the power generation performance according to each scenario was evaluated as an important factor. And it was confirmed that the performance of flood control and water use could also be evaluated.