• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.2
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• pp.123-130
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• 2016

This paper describes the design and implementation scheme of HTS(Helmet Tracking System) providing coincident LOS(Line of Sight) between aircraft and HMD(Helmet Mounted Display) which displays flight and mission information on Pilot helmet. The functionality and performance of HMD system depends on the performance of helmet tracking system. The target of HTS system design is to meet real-time performance and reliability by predicting non-periodic latency and high accuracy performance. To prove an availability of a proposed approach, a robust hybrid scheme with a fusion optical and inertial tracking system are tested through a implemented test-bed. Experimental results show real-time and reliable tracking control in spite of external errors.

• Journal of Advanced Marine Engineering and Technology
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• v.35 no.2
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• pp.189-195
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• 2011

In this paper, prediction and comparison on COP(coefficient of performance) of R744-R404A cascade refrigeration system are presented to offer the basic design data for the operating parameters of the system. The operating parameters considered in this study include subcooling and superheating degree, compressor efficiency, and condensing and evaporating temperature in the R404A high- and R744 low-temperature cycle, respectively. The main results were summarized as follows : The prediction for performance of R744-R404A cascade refrigeration system have been proposed through multiple regression analysis and compared with other researcher's correlations. As a result, prediction proposed in the study shows disagreement with existing equations. Therefore, it is necessary to propose the more accurate correlation predicting the COP of R744-R404A cascade refrigeration system through an addition experiments.

• Journal of Energy Engineering
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• v.3 no.1
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• pp.28-35
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• 1994

가스터빈 사이클의 성능 및 NOx 배출물 생성량 예측을 위한 모사 프로그램을 개발하였다. 압축기 및 터빈은 등엔트로피 과정으로, 연소기는 Thermal NOx 생성을 수반하는 연소모형으로서 가정하였다. 또한 터빈 냉각을 위한 추출공기량과 냉각방식이 성능에 미치는 적절한 상관 관계식을 도입하여 평가하였다. 본 성능평가 모델을 이용하여 예측된 결과와 실험결과간의 비교를 통하여 모델의 타당성을 검증하였고, 증기 분사량, 터빈 냉각변수 및 압축비 변화에 따른 예측결과를 통하여 가스터빈 시스템 최적 운전 및 설계기준을 제시하였다.

• Archives of Metallurgy and Materials
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• v.66 no.3
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• pp.689-693
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• 2021

In this study, we propose a cooling structure manufactured using a specialized three-dimensional (3D) printing design method. A cooling performance test system with complex geometry that used a thermoelectric module was manufactured using metal 3D printing. A test model was constructed by applying additive manufacturing simulation and computational fluid analysis techniques, and the correlation between each element and cooling efficiency was examined. In this study, the evaluation was conducted using a thermoelectric module base cooling efficiency measurement system. The contents were compared and analyzed by predicting the manufacturing possibility and cooling efficiency, through additive manufacturing simulation and computational fluid analysis techniques, respectively.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.698-701
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• 2007

DAHAN, the first 1 MWe Solar Power Tower system locates north to Beijing where nearby The Great Wall is now under construction with cooperation between China and Korea. Results in predicting the preliminary performance of this central receiver system are presented in this paper. Operating cycles under some typical weather condition days are simulated and commented. These results can be used to assess the impact of alternative plant designs or operating strategies on annual energy production, with the final objective being to optimize the design of central receiver power plants. Two subsystems are considered in the system simulation: the solar field and the power block. Mathematic models are used to represent physical phenomena and relationships so that the characteristics of physical processes involving these phenomena can be predicted. Decisions regarding the best position for locating heliostats relative to the receiver and how high to place the receiver above the field constitute a multifaceted problem. Four different kinds of field layout are designed and analyzed by the use of ray tracing and mathematical simulation techniques to determine the overall optical performance ${\eta}_{field}$ and the spillage ${\eta}_{spill}$.The power block including a Rankine cycle is analyzed by conventional energy balance methods.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.707-720
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• 2021

To improve the accuracy of the recommendation system, multi-criteria recommendation systems have been widely researched. However, it is highly complicated to extract the preferred features of users and items from the data. To this end, subjective indicators, which indicate a user's priorities for personalized recommendations, should be derived. In this study, we propose a method for generating recommendation candidates by predicting multi-criteria ratings from reviews and using them to derive user priorities. Using a deep learning model based on convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM), multi-criteria prediction ratings were derived from reviews. These ratings were then aggregated to form a linear regression model to predict the overall rating. This model not only predicts the overall rating but also uses the training weights from the layers of the model as the user's priority. Based on this, a new score matrix for recommendation is derived by calculating the similarity between the user and the item according to the criteria, and an item suitable for the user is proposed. The experiment was conducted by collecting the actual "TripAdvisor" dataset. For performance evaluation, the proposed method was compared with a general recommendation system based on singular value decomposition. The results of the experiments demonstrate the high performance of the proposed method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.7
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• pp.527-534
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• 2018

The endurance of the multi-copter is one of the important variables that determine the mission performance. Therefore, accurate endurance should be defined as essential for performing effective missions. In this paper, we present the results of the study on the flight performance of the aircraft, especially the hovering of the drone(multi-copter). Unlike conventional aircraft, which consider aerodynamic performance by the fuselage, the multi-copter is mostly determined by the propulsion system. Therefore, the research method classifies the various parts constituting the drone system into functions, analyzes the performance of the unit parts and obtains the experimental data by sorting out the specifications and functions at the component level and mathematical formulation, The results of this study are as follows. In addition, the 5kg class quad copter was used to predict and verify the voltage change with endurance through analysis of in situ flight. By predicting endurance under various conditions, it can help design/build the right Multi-copter for mission.

• Journal of the Korea Institute of Building Construction
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• v.11 no.5
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• pp.459-467
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• 2011

The work of constructing apartment housing involves various fields of industry that are linked to each other, and is based on a design document prepared by multiple technicians and architects. Consequently, design errors, material flaws or faulty construction works can cause defects, which sometimes overlap with each other. Construction companies should repair any defects found in a completed building within a specified period of time, and to do this, should establish a business plan by efficiently predicting the cost of defect repair. As it is very difficult for companies to accurately predict the occurrence of defects, historical performance data is used as a base. For domestic apartment housing units, data on the cost of defect repair is insufficient, so there are hardly any methods that can be used to make precise predictions. Therefore, the intent of this study is to develop a model that can predict the cost of defect repair by supply type and area, based on historical performance data with ten years worth of post-completion.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.385-391
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• 2005

As the Internet real-time multimedia applications increases, the bandwidth available to TCP connections is oppressed by the UDP traffic, result in the performance of overall system is extremely deteriorated. Therefore, developing a new transmission protocol is necessary. The TCP-friendly algorithm is an example satisfying this necessity. The TCP-Friendly Rate Control (TFRC) is an UDP-based protocol that controls the transmission rate that is based on the available round trip time (RTT) and the packet loss rate (PLR). In the data transmission processing, transmission rate is determined based on the conditions of the previous transmission period. If the one-step ahead predicted values of the control factors are available, the performance will be improved significantly. This paper proposes a prediction model of transmission rate control factors that will be used in the transmission rate control, which improves the performance of the networks. The model developed through this research is predicting one-step ahead variables of RTT and PLR. A multiplayer perceptron neural network is used as the prediction model and Levenberg-Marquardt algorithm is used for the training. The values of RTT and PLR were collected using TFRC protocol in the real system. The obtained prediction model is validated using new data set and the results show that the obtained model predicts the factors accurately.

• Atmosphere
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• v.31 no.1
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• pp.73-83
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• 2021

Numerical weather prediction (NWP) models play an essential role in predicting weather factors, but using them is challenging due to various factors. To overcome the difficulties of NWP models, deep learning models have been deployed in weather forecasting by several recent studies. This study adapts long short-term memory (LSTM), which demonstrates remarkable performance in time-series prediction. The combination of LSTM model input of meteorological features and activation functions have a significant impact on the performance therefore, the results from 5 combinations of input features and 4 activation functions are analyzed in 9 Automated Surface Observing System (ASOS) stations corresponding to cities/islands/mountains. The optimized LSTM model produces better performance within eight forecast hours than Local Data Assimilation and Prediction System (LDAPS) operated by Korean meteorological administration. Therefore, this study illustrates that this LSTM model can be usefully applied to very short-term weather forecasting, and further studies about CNN-LSTM model with 2-D spatial convolution neural network (CNN) coupled in LSTM are required for improvement.