• Convergence Security Journal
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• v.22 no.4
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• pp.35-44
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• 2022

Among the five promotion strategies of Defense Innovation 4.0(DI 4.0), the military structure/operation optimization strategy aims to innovate the military structure based on advanced science&technology(S&T), and to integrate advanced S&T in the field of defense operation such as education&training and human resource development. As the future battlefield expands to AI-based unmanned/robot combat systems, space, cyberspace, and electromagnetic fields, it is necessary to train officers with the capabilities required in these battlefields. It is necessary to develop capabilities from junior officers who will lead the future battlefield to operating core advanced power based on the 4^th industrial revolution S&T. We review the education system of the military in universities and propose a method of redesigning the education system that is compatible with DI 4.0 and can develop technology-intensive capabilities based on advanced S&T. We propose a operation plan of major and extra-programs that can develop the capabilities of junior officers required for the future battlefield, and also suggest ways to support the army's practical training.

• Convergence Security Journal
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• v.21 no.1
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• pp.115-120
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• 2021

An O2O-based real estate brokerage web sites or apps are increasing explosively. As a result, the environment has been changed from the existing offline-based real estate brokerage environment to the online-based environment, and consumers are getting very good feelings in terms of time, cost, and convenience. However, behind the convenience of online-based real estate brokerage services, users often suffer time and money damage due to false information or malicious false information. Therefore, in this study, in order to reduce the damage to consumers that may occur in the O2O-based real estate brokerage service, we designed a false property information filtering system that can determine the authenticity of registered property information using artificial intelligence technology. Through the proposed research method, it was shown that not only the authenticity of the property information registered in the online real estate service can be determined, but also the temporal and financial damage of consumers can be reduced.

• Journal of Korea Game Society
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• v.18 no.4
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• pp.75-82
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• 2018

With the development of information and communication technology, various methods have been tried to provide learners with a fun educational environment through fun and interest. It is a good example to utilize technologies such as games and robots in education for edutainment and game-based learning. In this study, we propose an intelligent rhythm education system using user data collection and analysis for humanoid robot rhythm generation. To do this, the user selects music and inputs rhythm information according to the selected music. The robot utilization data of this user extracts patterns through collection and analysis. Patterns are based on frequency, and FFT similarity comparison method is applied when past data is insufficient. The proposed method is validated through experiments of kindergarten children.

• Annual Conference of KIPS
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• 2022.11a
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• pp.126-128
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• 2022

초고성능컴퓨터를 활용하여 전통적인 병렬처리 기반의 계산과학을 비롯하여 AI, 빅데이터 등의 ICT 기반 연구를 수행할 수 있어야 한다는 수요가 증가하고 있다. 계산과학 연구의 다양성에 맞춰 컴퓨팅 연구환경을 제공하기 위하여 한국과학기술정보연구원(KISTI)에서는 초고성능컴퓨터를 인프라로 활용하는 HPC 클라우드인 KI(KISTI Intelligent) Cloud를 개발하여 서비스하고 있다. 본 논문에서는 KI Cloud의 과금을 위한 기능의 설계 및 구현 현황을 기술하였다. 가상서버(VM) 기반의 서비스와 컨테이너 기반의 서비스의 사용량을 측정하기 위하여 Prometheus로 CPU의 사용량을 수집하여 과금 정책을 적용하고 있는 KI Cloud의 과금 기능에 대해서 살펴보도록 한다.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2268-2277
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• 2017

As constantly increasing wind power penetrates power grid, wind power plants (WPPs) are exerting a direct influence on the traditional power system. Most of WPPs are using variable speed constant frequency (VSCF) wind turbines equipped with doubly fed induction generators (DFIGs) due to their high efficiency over other wind turbine generators (WTGs). Therefore, the analysis of DFIG has attracted considerable attention. Precisely measuring optimum reference speed is basis of utilized maximum wind power in electric power generation. If the measurement of wind speed can be easily taken, the reference of rotation speed can be easily calculated by known system's parameters. However, considering the varying wind speed at different locations of blade, the turbulence and tower shadow also increase the difficulty of its measurement. The aim of this study is to design fuzzy controllers to replace the wind speedometer to track the optimum generator speed based on the errors of generator output power and rotation speed in varying wind speed. Besides, this paper proposes the fuzzy adaptive PID control to replace traditional PID control under rated wind speed in variable-pitch wind turbine, which can detect and analyze important aspects, such as unforeseeable conditions, parameters delay and interference in the control process, and conducts online optimal adjustment of PID parameters to fulfill the requirement of variable pitch control system.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3409-3416
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• 2023

Licensing the next-generation of nuclear reactor designs requires extensive use of Modeling and Simulation (M&S) to investigate system response to many operational conditions, identify possible accidental scenarios and predict their evolution to undesirable consequences that are to be prevented or mitigated via the deployment of adequate safety barriers. Deep Learning (DL) and Artificial Intelligence (AI) can support M&S computationally by providing surrogates of the complex multi-physics high-fidelity models used for design. However, DL and AI are, generally, low-fidelity 'black-box' models that do not assure any structure based on physical laws and constraints, and may, thus, lack interpretability and accuracy of the results. This poses limitations on their credibility and doubts about their adoption for the safety assessment and licensing of novel reactor designs. In this regard, Physics Informed Neural Networks (PINNs) are receiving growing attention for their ability to integrate fundamental physics laws and domain knowledge in the neural networks, thus assuring credible generalization capabilities and credible predictions. This paper presents the use of PINNs as surrogate models for accidental scenarios simulation in Nuclear Power Plants (NPPs). A case study of a Loss of Heat Sink (LOHS) accidental scenario in a Nuclear Battery (NB), a unique class of transportable, plug-and-play microreactors, is considered. A PINN is developed and compared with a Deep Neural Network (DNN). The results show the advantages of PINNs in providing accurate solutions, avoiding overfitting, underfitting and intrinsically ensuring physics-consistent results.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.1-10
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• 2019

The present research aims to identify the issues that occurred when uploading stock photos to the internet-based stock image agencies and to develop technical solutions based on web service technologies. We identify the issues by examination of previous studies and stock photo uploading systems of major three agencies currently in service. As such, we develop web service technology by focusing on the following matters. First, we apply an automatic tag system to ensure convenience. Second, to ensure safety, we apply a technology that easily enables prevention of portrait rights violations and trademark infringements. We also prepare for measures against possible harmfulness. Third, to ensure completeness, we apply a method which resolves upload failure issues that frequently occurred in the past. In particular, the present research is significant as it applies an automatic image analysis system based on Google Cloud Vision API as the artificial intelligence-based image processing technology. In addition, we develop a web service program which improves user access by using SNS-type screen composition.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.29-37
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• 2009

National R&D programs play an important role in the development of a country in this age of the knowledge economy. Since many numbers of R&D programs compete for limited resources such as national R&D budget, the R&D program evaluation problem is a challenging decision-making problem faced by decision makers that deal with R&D management. In this sense, DEA(Data Envelopment Analysis) has been regarded as one of the most widely accepted methods to measure the relative efficiency of productivity of R&D programs. DEA is a methodology to measure and to evaluate the relative efficiency of a homogeneous set of decision-making units(DMUs) in a process which uses multiple inputs to produce multiple outputs. However, the sample of the R&D programs could consist of two or more naturally occurring subsets, thus exhibiting clear signs of heterogeneity such as different objectives. In such situations, the fairness of DEA is limited, for the nature of the relative efficiency of a DMU is likely to be influenced by its membership in a particular subset of the sample. In this study, we propose a methodology AI-DEA(attainment index DEA) allowing for reflecting decision maker's subjective judgement on difference among different subsets of R&D programs which have heterogeneous objectives. This methodology combines AHP and Delphi in order to decide the attainmnet index of each DMU for each outputs, and apply them to DEA model. We illustrate the proposed approach with a pilot evaluation of 13 programs involving 6 different subsets of Korean National R&D programs and compares the results of the original DEA model and AI-DEA model.

• Journal of Drive and Control
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• v.17 no.3
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• pp.1-8
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• 2020

Recently, a special purpose machine with two manipulators and quadruped crawler system has been developed for rapid life-saving and initial restoration work at disaster sites. This special purpose machine provides the driver with various environmental recognition functions for accurate and rapid task determination. In particular, the human detection technology assists the driver in poor working conditions such as low-light, dust, water vapor, fog, rain, etc. to prevent secondary human accidents when moving and working. In this study, a human detection module is developed to be mounted on a special purpose machine. A thermal sensor and CCD camera were used to detect victims and nearby workers in response to the difficult environmental conditions present at disaster sites. The performance of various AI-based life detection algorithm were verified and then applied to the task of detecting various objects with different postures and exposure conditions. In addition, image visibility improvement technology was applied to further improve the accuracy of human detection.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.44 no.3
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• pp.218-228
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• 2008

This paper describes on the real-time tracking of ship's dynamic behavior by AIS information in the coastal waters. The AIS data was received at a land station by using the antenna of AIS receiver mounted on the rooftop of the laboratory, Pukyong National University (PKNU), Busan, Korea, and stored as a NMEA format of serial output sentence of VDM(VHF Data-Link Message) and displayed on the ENC(Electronic Navigational Chart) of a PC-based ECDIS. In this study, the AIS receiver was mainly used to obtain the dynamic information that is necessary to evaluate and track the movement situation of training ship "KAYA" of PKNU in the coastal waters. The change of position with time for the ship turning under the rudder angle of port $30^{\circ}$ was correctly tracked with the turning circle of 940 m in diameter on the ENC of a PC-based ECDIS. Then, the dynamic information of the AIS system was updated every 6.29 seconds under the turning situation for the speed of 10.9 knots and every 21.65 seconds under the situation running at the speed of 11.05 knots on the straight line route of $155^{\circ}$, respectively. In case of AIS target tracking in the inshore zone behind large topographical obstructions, such as mountain and apartment buildings, the update rate of dynamic information was irregularly changed by the existence of land obstacles. However, the position tracking by AIS information under the situation existing no sea obstructions was achieved in real or near real-time and the instant presentation of course alternations for the ship was correctly monitored by using a PC-based ECDIS. From these results, we concluded that the PC-based ECDIS technology and methodology combined with the AIS information can be easily extended and applied to the surveillance and management for the fishing operation of fishing vessels in the coastal zone and in the EEZ fishing grounds.