• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.2
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• pp.185-190
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• 2006

The correct estimation of the ionospheric delays is very important for the precise kinematic positioning especially in case of the long baseline. In case of triple frequency system, the ionospheric delays can be estimated from the measurements, but, in case of dual frequency system, the situation is not so simple. The precision of those supplied by the external information source such as IONEX is not sufficient. The high frequency component is neglected, and the precision of the low frequency component is not sufficient for the long baseline positioning. On the other hand, the high frequency component can be estimated from the phase range measurements. If the low frequency components are estimated by using the external information source or pseudo range measurements, a more reasonable estimation of the ionospheric delays may be possible. It has already been discussed by the author that the estimation of the low frequency components by using the external information source is not sufficient but fairly effective. The estimation using the pseudo range measurements is discussed in the present paper. The accuracy is not sufficient at present because of the errors in the pseudo range measurements. It is clarified that the bias errors in the pseudo range measurements are responsible for the poor accuracy of the ionospheric delays. However, if the accuracy of the pseudo range measurements is improved in future, the method would become very promising.

• 한국항공운항학회지
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• 제22권4호
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• pp.25-33
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• 2014

As global warming becoming an environmentally serious issue, more attention is drawn to fuel consumption which is the direct source of green house gas emission. The fuel consumption by aircraft operation is not an exception. Motivated by the societal and environmental context, this paper explains a method for estimation of aircraft fuel consumed during their flights as well as the computational process using real flight track data. Applying so-called 'Total Energy Model' along with aircraft specific parameters provided in EUROCONTROL's Base of Aircraft Data (BADA) to aircraft radar track data, we estimate fuel consumption of individual aircraft flown between Gimpo and Jeju airports. We then assess the estimation accuracy by comparing the estimated fuel consumption with the actual one collected from an airline. The computational results are quite encouraging in that the method is able to estimate the actual fuel consumption within ${\pm}6{\sim}11%$ of error margin. The limitations and possible enhancements of the method are also discussed.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.475-478
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• 2013

To carry out a one-off construction project successfully, effective and accurate early cost estimation is crucial, especially during the conceptual stage where very limited minimum information of construction project is given. As the level of accuracy of the early cost estimation has huge impacts on precise budgeting and cost management of a project, in other words, reducing the risk of a project, cost must be managed with special awareness. In an effort to improve the estimate accuracy of cost during the conceptual stage, this research introduces a Parameter Impact (PI) which can quantify weights of parameters and rank them; and PI development derived from the principle of impulse in physics is explicated. For a case study, 76 public apartment building cases in Korea are analyzed. To examine the validity of the proposed PI, a validation in terms of CBR applicability test and estimate accuracy comparisons using 10-nearest neighbor cases are carried out. The validation results support that the suggested PI can be applied in quantifying the weights of the parameters and CBR method for early cost estimation.

• 한국통신학회논문지
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• 제35권5C호
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• pp.472-478
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• 2010

UWB 표준인 IEEE 802.15.3a 채널의 무선 통신 시스템 환경에서 채널에 적합하고 추정 정확도가 우수한 신호 도착 방향(AOA) 매개변수 추정 기반의 실내 무선 위치인식 알고리즘을 위한 평균가중 AOA 추정기법을 제안한다. AOA 매개 변수 추정을 위한 IEEE 802.15.3a 기반의 초광대역 신호 모형을 설정하고, 종래 추정 기법보다 추정 정확도가 우수한 평균가중 기반의 다중신호 분류 기법들을 제안한다. 컴퓨터 모의실험을 통해, IEEE 802.15.3a 채널이 포함한 실내 무선 위치인식 시스템 환경을 구축하고, 제안한 AOA 추정 방식을 통해 종래 방식 보다 우수한 추정 결과를 보인다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2020년도 추계학술대회
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• pp.252-255
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• 2020

Unsupervised deep learning methods have shown impressive results for the challenging monocular depth estimation task, a field of study that has gained attention in recent years. A common approach for this task is to train a deep convolutional neural network (DCNN) via an image synthesis sub-task, where additional views are utilized during training to minimize a photometric reconstruction error. Previous unsupervised depth estimation networks are trained within a fixed depth estimation range, irrespective of its possible range for a given image, leading to suboptimal estimates. To overcome this suboptimal limitation, we first propose an unsupervised adaptive depth estimation method guided by minimum and maximum (min-max) depth priors for a given input image. The incorporation of min-max depth priors can drastically reduce the depth estimation complexity and produce depth estimates with higher accuracy. Moreover, we propose a novel network architecture for adaptive depth estimation, called the AdaMM-DepthNet, which adopts the min-max depth estimation in its front side. Intensive experimental results demonstrate that the adaptive depth estimation can significantly boost up the accuracy with a fewer number of parameters over the conventional approaches with a fixed minimum and maximum depth range.

• 경영과학
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• 제30권2호
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• pp.1-10
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• 2013

Case studies are made to investigate the relationship between the accuracy of energy production estimation and project feasibility indicators such as rate of return on equity (ROE) and debt service coverage ratio (DSCR) for three wind farm projects. It is found out that 1% improvement in the accuracy of energy production estimation may enhance the ROE by more than 0.5% in the case of P95, thanks to improved financing terms. AHP survey shows that MCP correlation of measured in situ wind data with long term wind speed distribution and hands-on experiences of flow analysis are more important than other factors for more precise annual energy production estimation.

• 제어로봇시스템학회논문지
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• 제22권6호
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• pp.470-476
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• 2016

This paper proposes a practical algorithm for the reduction of measurement errors due to drift in a micro-electromechanical system (MEMS) gyros that are used for a mobile robot. Any drift in a MEMS gyro will cause an unbounded growth of errors in the estimation of heading, which makes it nearly useless in applications that require high accuracy over a long operating time. In proposed method, maneuvers of a cleaning robot are observed through encoders' measurement process and a decision to correct bias drift will be made if necessary. The method used in this paper is called the "heading estimation filter". To evaluate the accuracy of the proposed method, a comparison was made between the estimation of the heading of the cleaning robot and one from a motion capture system.

• 대한조선학회지
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• 제21권3호
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• pp.1-10
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• 1984

The computer programs of effective horsepower estimation of small fishing boat were developed, which was based on the statistical analysis of model test results. From the EHP estimation by these program and experimental model tests of practical fishing boats, the estimation accuracy was verified with maximum deviation of about 10 percent. Also, the EHP estimation accuracy was practically applied to initial design of four small fishing boats, and after the tank tests, the EHP reduction of the order of 15 to 25 percent was confirmed, as compared with existing ships. Moreover, a computer aided design procedure of fishing boat's hull form has been proposed in this study. The practical use of this procedure of fishing boat's hull form has been proposed in this study. The practical use of this procedure was demonstrated with the hull form design results of several fishing boats.

• Journal of Electrical Engineering and Technology
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• 제13권1호
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• pp.430-437
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• 2018

Ultrasonic attenuation is an important parameter in Quantitative Ultrasound and many algorithms have been proposed to improve estimation accuracy and repeatability for multiple independent estimates. In this work, we propose an improved algorithm for estimating ultrasonic attenuation utilizing the optimal frequency compounding technique based on stochastic noise model. We formulate mathematical compounding equations in the AWGN channel model and solve optimization problems to maximize the signal-to-noise ratio for multiple frequency components. Individual estimates are calculated by the reference phantom method which provides very stable results in uniformly attenuating regions. We also propose the guideline to select frequency ranges of reflected RF signals. Simulation results using numerical phantoms show that the proposed optimal frequency compounding method provides improved accuracy while minimizing estimation bias. The estimation variance is reduced by only 16% for the un-compounding case, whereas it is reduced by 68% for the uniformly compounding case. The frequency range corresponding to the half-power for reflected signals also provides robust and efficient estimation performance.

• Journal of information and communication convergence engineering
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• 제13권2호
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• pp.105-112
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• 2015

The estimation of missing sensor values is an important problem in sensor network applications, but the existing approaches have some limitations, such as the limitations of application scope and estimation accuracy. Therefore, in this paper, we propose a new estimation model based on a spatial-temporal correlation analysis (STCAM). STCAM can make full use of spatial and temporal correlations and can recognize whether the sensor parameters have a spatial correlation or a temporal correlation, and whether the missing sensor data are continuous. According to the recognition results, STCAM can choose one of the most suitable algorithms from among linear interpolation algorithm of temporal correlation analysis (TCA-LI), multiple regression algorithm of temporal correlation analysis (TCA-MR), spatial correlation analysis (SCA), spatial-temporal correlation analysis (STCA) to estimate the missing sensor data. STCAM was evaluated over Intel lab dataset and a traffic dataset, and the simulation experiment results show that STCAM has good estimation accuracy.