• Journal of Environmental Impact Assessment
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• v.32 no.5
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• pp.363-376
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• 2023

As the risk of biodiversity reduction and extinction becomes serious due to climate change and indiscriminate development, the importance of conservation of the natural environment and ecosystem is increasing. In this situation, Ireviewed that overseas cases of the ecological outlook and evaluation system aimed at providing information on natural resources and ecosystem change. As a results, other countries showed that various research institutes have been carrying on field surveys by classification group, but it was different from us that the investigated data are collected and managed in an integrated manner and repeatedly provided within a short period of time. In addition, it was analyzed that it was highly utilized in policy and environmental impact assessment by providing evaluation-based prediction and outlook information along with basic survey data. Based on this, the limitations of information use in our wildlife surveys and environmental impacts assessments were analyzed, and the estabilishment of a ecology outlook and evaluation system and policy support measures were considered. In addition, based on the proposed outlook and evaluation system preparation plan, a policy direction that can be effectively used in domestic natural ecosystem policies was proposed.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.883-888
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• 2023

Since data centers are places that provide IT services 24 hours a day, 365 days a year, data center power consumption is expected to increase to approximately 10% by 2030, and the introduction of high-density IT equipment will gradually increase. In order to ensure the stable operation of IT equipment, various types of research are required to conserve energy in cooling and improve energy management. This study proposes the following process for energy saving in data centers. We conducted CFD modeling of the data center, proposed an artificial intelligence-based thermal environment prediction model, compared actual measured data, the predicted model, and the CFD results, and finally evaluated the data center's thermal management performance. It can be seen that the predicted values of RCI, RTI, and PUE are also similar according to the normalization used in the normalization method. Therefore, it is judged that the algorithm proposed in this study can be applied and provided as a thermal environment prediction model applied to data centers.

• Journal of the Korea Society for Simulation
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• v.32 no.4
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• pp.1-10
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• 2023

This study examines the response when the shock by underwater explosion is transmitted to a vertical launch air-vehicle mounted on a ship using modeling and simulation, and is about a plan to increase method shock resistance to protect the air vehicle. In order to obtain an accurate mathematical model, a dynamic characteristic test was performed on similar equipment, and through this, the mathematical model could be supplemented. And, using the supplemented mathematical model, the air vehicle simulated the shock response by the underwater explosion specified in the BV043 standard. As a result of the first simulation, it was confirmed that air vehicle could not withstand shock, and air vehicle protection method using a ring spring type shock absorber was studied. In addition to the basic shape of abosber, it was confirmed that the ring spring absober can be used to increase the impact resistance of a shipborn vertical launch vehicle by performing simulations for each case by changing deseign varables.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.151-161
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• 2024

In this paper, we develop 'the Danger Map' of a workplace to identify risk and harmful factors by analyzing images of each process within the manufacturing plant site using artificial intelligence (AI). We proposed a system that automatically derives 'the risk and safety levels' based on the frequency and intensity derived from this Danger Map in accordance with actual field conditions and applies them to similar manufacturing industries. In particular, in the traditional evaluation method of manually evaluating the risk of a workplace using Excel, the risk level for each risk and harmful factor acquired from the video is automatically calculated and evaluated to ensure safety through the system and calculate the safety level, so that the company can take appropriate actions accordingly. and measures were prepared. To automate safety calculation and evaluation, 'Heinrich's law' was used as a model, and a 5X4 point evaluation scale was calculated for risky behavior patterns. To demonstrate this system, we applied it to a casting factory and were able to save 2 people the time and labor required to calculate safety each month.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.609-619
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• 2020

In accordance with a demand for high quality video streaming, it needs high data rate in limited bandwidth and more traffic congestion occurs. In particular, when providing real time video service, packet loss rate and bit error probability increase significantly. To solve these problems, a raptor code, which is one of FEC(Forward Error Correction) techniques, is pervasively used in the application layers as a method for improving real-time service quality. In this paper, we propose a method of determining image transmission parameters based on various deep neural networks to increase transmission efficiency at a similar level of image quality by using raptor codes. The proposed neural network uses the packet loss rate, video encoding rate and data rate as inputs, and outputs raptor FEC parameters and packet sizes. The results of the proposed method present that the throughput is 1.2% higher than that of the existing multimedia transmission technique by optimizing the transmission efficiency at a PSNR(Peak Signal-to-Noise Ratio) level similar to that of the existing technique.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.21-29
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• 2018

In the era of the 4-th industrial revolution, the concept of smart factory is emerging. There are efforts to predict the occurrences of facility errors which have negative effects on the utilization and productivity by using data analysis. Data composed of the situation of a facility error and the type of the error, called the facility error log, is required for the prediction. However, in many manufacturing companies, the types of facility error are not precisely defined and categorized. The worker who operates the facilities writes the type of facility error in the form with unstructured text based on his or her empirical judgement. That makes it impossible to analyze data. Therefore, this paper proposes a framework for constructing a phrase network to support the identification and classification of facility error types by using facility error logs written by operators. Specifically, phrase indicating the types are extracted from text data by using dictionary which classifies terms by their usage. Then, a phrase network is constructed by calculating the similarity between the extracted phrase. The performance of the proposed method was evaluated by using real-world facility error logs. It is expected that the proposed method will contribute to the accurate identification of error types and to the prediction of facility errors.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.161-161
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• 2017

스마트 시설환경의 제어 요소는 난방기, 창 개폐, 수분/양액 밸브 개폐, 환풍기, 제습기 등 직접적으로 시설환경의 조절에 관여하는 인자와 정보 교환을 위한 통신, 사용자 인터페이스 등 간접적으로 제어에 관련된 요소들이 복합적으로 존재한다. PID 제어와 같이 하는 수학적 논리를 바탕으로 한 제어와 전문 관리자의 지식을 기반으로 한 비선형 학습 모델에 의한 제어 등이 공존할 수 있다. 이러한 다양한 요소들을 복합적으로 연동시키기 위해선 기존의 시퀀스 기반 제어 방식에는 한계가 있을 수 있다. 관행의 방식과 같이 시계열 상에서 획득한 충분한 데이터를 이용하여 제어의 양과 시점을 결정하는 방식은 예외 상황에 충분히 대처하기 어려운 단점이 있을 수 있다. 이러한 예외 상황은 자연적인 조건의 변화에 따라 불가피하게 발생하는 경우와 시스템의 오류에 기인하는 경우로 나뉠 수 있다. 본 연구에서는 실시간으로 변하는 시설환경 내의 다양한 환경요소를 실시간으로 분석하고 상응하는 제어를 수행하여 수학적이며 예측 가능한 논리에 의해 준비된 제어시스템을 보완할 방법을 연구하였다. 과거의 고성능 컴퓨팅(HPC; High Performance Computing)은 다수의 컴퓨터를 고속 네트워크로 연동하여 집적적으로 연산능력을 향상시킨 기술로 비용과 규모의 측면에서 많은 투자를 필요로 하는 첨단 고급 기술이었다. 핸드폰과 모바일 장비의 발달로 인해 소형 마이크로프로세서가 발달하여 근래 2 Ghz의 클럭 속도에 이르는 어플리케이션 프로세서(AP: Application Processor)가 등장하기도 하였다. 상대적으로 낮은 성능에도 불구하고 저전력 소모와 플랫폼의 소형화를 장점으로 한 AP를 시설환경의 실시간 제어에 응용하기 위한 방안을 연구하였다. CPU의 클럭, 메모리의 양, 코어의 수량을 다음과 같이 달리한 3가지 시스템을 비교하여 AP를 이용한 마이크로 클러스터링 기술의 성능을 비교하였다.1) 1.5 Ghz, 8 Processors, 32 Cores, 1GByte/Processor, 32Bit Linux(ARMv71). 2) 2.0 Ghz, 4 Processors, 32 Cores, 2GByte/Processor, 32Bit Linux(ARMv71). 3) 1.5 Ghz, 8 Processors, 32 Cores, 2GByte/Processor, 64Bit Linux(Arch64). 병렬 컴퓨팅을 위한 개발 라이브러리로 MPICH(www.mpich.org)와 Open-MP(www.openmp.org)를 이용하였다. 2,500,000,000에 이르는 정수 중 소수를 구하는 연산에 소요된 시간은 1)17초, 2)13초, 3)3초 이었으며, $12800{\times}12800$ 크기의 행렬에 대한 2차원 FFT 연산 소요시간은 각각 1)10초, 2)8초, 3)2초 이었다. 3번 경우는 클럭속도가 3Gh에 이르는 상용 데스크탑의 연산 속도보다 빠르다고 평가할 수 있다. 라이브러리의 따른 결과는 근사적으로 동일하였다. 선행 연구에서 획득한 3차원 계측 데이터를 1초 단위로 3차원 선형 보간법을 수행한 경우 코어의 수를 4개 이하로 한 경우 근소한 차이로 동일한 결과를 보였으나, 코어의 수를 8개 이상으로 한 경우 앞선 결과와 유사한 경향을 보였다. 현장 보급 가능성, 구축비용 및 전력 소모 등을 종합적으로 고려한 AP 활용 마이크로 클러스터링 기술을 지속적으로 연구할 것이다.

• Convergence Security Journal
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• v.18 no.3
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• pp.113-122
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• 2018

The issue of security on the Korean peninsula is facing the greatest upheaval in 2018 with the inter-Korean summit and the US-North Korea summit. North Korea has pursued the parallel policy developing military and economic at the same time. However, North Korea is changing its route to give up nuclear weapons and focus on the economy through summit talks. Since the change in North Korea is similar to that of Libya in the past, it is necessary to analyze why North Korea is trying to abandon its nuclear program and how the process is flowing compared to the case of Libya. The Libya model was constructed and analyzed in terms of international and domestic perpectives and recognition of the situation by leadership. North Korea's nuclear policy was evaluated based on the Libya model. The nuclear development of Libya and North Korea has caused diplomatic and economic pressures from the international community and ultimately led to instability of the regime. Two countries have tried to abandon nuclear program in order to solve the instability of the regime, also gain the economic reward insead. Libya took economic benefits and secured some of the stability of the regime, but the regime collapsed under the wave of democracy due to the influx of foreign capital and ideas. North Korea will seek diplomatic and economic gains with the example of Libya, but will try to limit as much as possible the culture of democracy and the full opening that can be incidental.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.86-94
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• 2019

This paper describes the development of unmanned vehicle remote control system which is configured with steering and accelerating/braking hardware to improve the sense of reality and safety of control. Generally, in these case of the remote control system, a joystick-type device is used for steering and accelerating/braking control of unmanned vehicle in most cases. Other systems have been developing using simple steering wheel, but there is no function of that feedback the feeling of driving situation to users and it mostly doesn't include the accelerating/braking control hardware. The technology of feedback means that a reproducing the feeling of current driving situation through steering and accelerating/braking hardware when driving a vehicle in person. In addition to studying feedback technologies that reduce unfamiliarity in remote control of unmanned vehicles, it is necessary to develop the remote control system with hardware that can improve sense of reality. Therefore, in this study, the reliable remote control system is developed and required system specification is defined for applying force-feedback haptic control technology developed through previous research. The system consists of a steering-wheel module similar to a normal vehicle and an accelerating/braking pedal module with actuators to operate by feedback commands. In addition, the software environment configured by CAN communication to send feedback commands to each modules. To verify the reliability of the remote control system, the force-feedback haptic control algorithms developed through previous research were applied, to assess the behavior of the algorithms in each situation.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.299-306
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• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.