• Journal of Navigation and Port Research
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• v.35 no.6
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• pp.477-482
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• 2011

Solar flares have the 11-year cycle and release a large energy which may produce coronal mass ejections (CME). The NOAA (National Oceanic and Atmospheric Administration) predicted that the sun spot activity will be maximized in 2013-2014. A strong solar flare can cause the disturbance of global positioning system including various communication of TV, radio broadcasting. The actual solar storm in 1989 caused power outages in Canada during 9 hours and about 600 million people had experienced a blackout. Such a solar storm can shorten the GPS satellite's life span about 5 to 10 years which can resulted in economic loss considering the amount of multi-billion won. This paper analyzed the influence of recent X-class solar storm occurred on 15th of February about 10:45 this year that was reached Korea (Bohyun observatory) on 18th of February about 10:30 (01:30 - UTC), and compared with the data before and after a week. The proton data of 18th of February considered that the solar storm reached on earth showed a fluctuation compared to the data before and after a week. The positioning results at Daejeon and Seoul of Korea also showed higher positioning error compared to the data before and after a week results.

• Journal of Navigation and Port Research
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• v.37 no.6
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• pp.575-580
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• 2013

The IMU(Inertial Measurement Unit) which is the expensive equipment has been used as a special limited area, usually in measurement of posture of applying to the areas of ship, submarine, aircraft and military equipment application. However, in the current situation, MEMS AHRS technology can replace the high-priced IMU in MEMS AHRS selected application field. In this paper, wireless hull motion measurement system was suggested for measuring key elements of ship's movement such as rolling, pitching and yawing using gyro, acceleration and magnetic sensors of AHRS. In order to reduce the error such as instantaneous acceleration, effects and vibration of geomagnetic, we have adopted the sensors equipped with Kalman filtering. The Wireless hull motion measurement system using AHRS sensors was tested in actual ship and it could easily be applied in limited installation circumstances of the ship. In the future, this system can be useful in the navigation safety and marine accident analysis by using with ship equipment such as INS or VDR in the maritime.

• Journal of Navigation and Port Research
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• v.44 no.3
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• pp.187-194
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• 2020

It is very important to forecast freight volume accurately to establish major port policies and future operation plans. Thus, related studies are being conducted because of this importance. In this paper, stepwise regression analysis and artificial neural network model were analyzed to compare the predictive power of each model on Gwangyang Port, the largest domestic port for coal and iron ore transportation. Data of a total of 121 months J anuary 2009-J anuary 2019 were used. Factors affecting coal and iron ore trade volume were selected and classified into supply-related factors and market/economy-related factors. In the stepwise regression analysis, the tonnage of ships entering the port, coal price, and dollar exchange rate were selected as the final variables in case of the Gwangyang Port coal volume forecasting model. In the iron ore volume forecasting model, the tonnage of ships entering the port and the price of iron ore were selected as the final variables. In the analysis using the artificial neural network model, trial-and-error method that various Hyper-parameters affecting the performance of the model were selected to identify the most optimal model used. The analysis results showed that the artificial neural network model had better predictive performance than the stepwise regression analysis. The model which showed the most excellent performance was the Gwangyang Port Coal Volume Forecasting Artificial Neural Network Model. In comparing forecasted values by various predictive models and actually measured values, the artificial neural network model showed closer values to the actual highest point and the lowest point than the stepwise regression analysis.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.7
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• pp.319-326
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• 2016

Given the attributes of mobile apps that shorten the time to make purchase decisions while enabling easy purchase cancellations, usability can be regarded to be a highly prioritized quality attribute among the diverse quality attributes that must be provided by mobile apps. With that backdrop, mobile app developers have been making great effort to minimize usability hampering elements that degrade the merchantability of apps in many ways. Most elements that hamper the convenience in use of mobile apps stem from those potential errors that occur when GUIs are designed. In our previous study, we have proposed a technique to analyze the usability of mobile apps using user behavior logs. We proposes a technique to detect usability hampering elements lying dormant in mobile apps' GUI models by expressing user behavior logs with finite state models, combining user behavior models extracted from multiple users, and comparing the combined user behavior model with the expected behavior model on which the designer's intention is reflected. In addition, to reduce the burden of the repeated test operations that have been conducted by existing developers to detect usability errors, the present paper also proposes a mobile usability error detection automation tool that enables automatic application of the proposed technique. The utility of the proposed technique and tool is being discussed through comparison between the GUI issue reports presented by actual open source app developers and the symptoms detected by the proposed technique.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.593-606
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• 2016

Computer simulation is widely used in a variety of computational science and engineering fields, including computational fluid dynamics, nano physics, computational chemistry, structural dynamics, and computer-aided optimal design, to simulate the behavior of a system. As the demand for the accuracy and complexity of the simulation grows, however, the cost of executing the simulation is rapidly increasing. It, therefore, is very important to lower the total execution time of the simulation especially when that simulation makes a huge number of repetitions with varying values of input parameters. In this paper we develop a simulation service system that provides the ability to predict the result of the requested simulation without actual execution for that simulation: by recording and then returning previously obtained or predicted results of that simulation. To achieve the goal of avoiding repetitive simulation, the system provides two main functionalities: (1) storing simulation-result records into database and (2) predicting from the database the result of a requested simulation using statistical machine learning techniques. In our experiments we evaluate the prediction performance of the system using real airfoil simulation result data. Our system on average showed a very low error rate at a minimum of 0.9% for a certain output variable. Using the system any user can receive the predicted outcome of her simulation promptly without actually running it, which would otherwise impose a heavy burden on computing and storage resources.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.383-392
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• 2014

The research for coatings is one of the most popular and active research in the polymer industry. For the coatings, electronics industry, medical and optical fields are growing more important. In particular, the trend is the increasing of the technical requirements for the performance and accuracy of the coatings by the development of automotive and electronic parts. In addition, the industry has a need of more intelligent and automated system in the industry is increasing by introduction of the IoT and big data analysis based on the environmental information and the context information. In this paper, we propose an optimization model for the design of experiments based coating formulation data objects using the Internet technologies and big data analytics. In this paper, the coating formulation was calculated based on the best data analysis is based on the experimental design, modify the operator with respect to the error caused based on the coating formulation used in the actual production site data and the corrected result data. Further optimization model to correct the reference value by leveraging big data analysis and Internet of things technology only existing coating formulation is applied as the reference data using a manufacturing environment and context information retrieval in color and quality, the most important factor in maintaining and was derived. Based on data obtained from an experiment and analysis is improving the accuracy of the combination data and making it possible to give a LOT shorter working hours per data. Also the data shortens the production time due to the reduction in the delivery time per treatment and It can contribute to cost reduction or the like defect rate reduced. Further, it is possible to obtain a standard data in the manufacturing process for the various models.

• Korean Journal of Remote Sensing
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• v.9 no.2
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• pp.51-69
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• 1993

Precipitable Water(PW) are retrieved over the tropical and subtropical Pacific Ocean from TOVS infrared and microwave channel brightness temperature and OLR observations by means of stepwise linear regression. The retrieved TOVS PW fields generated by PW$_{sfc}$(71.1 % of the variance and 0.62 g cm$^{-2}$ standard error over the surface) and PW$_{700500}$(71.7 % and 0.17 g cm$^{-2}$ over the 700 - 500 hPa layer) revealed more evolving synoptic signals over the tropical and subtropical Pacific Ocean. The PW$_{sfc}$ dose not show significantly the TP feature because of the representation of the lower PW for high-level clouds not associated with deep convection. There exists some elusion to trace the TP on the PW$_{sfc}$ field if any supplementary information does not provide. But ECMWF analysis has a general tendency of drying the subtropics and moistening the ITCZ (InterTropical Convergence Zone) and SPCZ(South Pacific Convergence Zone). However, although ECMWF analysis is fairly successful in capturing mean patterms, it is unsuccessful in following active synoptic signal like a tropical plume. Similarly, SMMR-PW does not represent the TP well which consists of the highand middle-level clouds, but PW$_{sfc}$ shows underestimated moistness of TP and does not depict significant signal of TP. In the PW field derived from microwave observations, the TP can not be recognized well. Furthermore, the signature of PW$_{sfc}$ was different from OLR for the TP, which implies the presence of high- and middle-layer thin clouds, but in a closer agreement for deep and active convection areas which contain thick middle- and lower-layer clouds; though OLR represented the cloudiness in the tropics well. In synoptically active regions, it differed from OLR analysis, primarily bacause of actual differences in water vapor and cloud features. The signature of PW$_{sfc}$ was different from OLR for the TP.

• Applied Chemistry for Engineering
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• v.30 no.5
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• pp.606-614
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• 2019

A mixing ratio of the oil in water (O/W) emulsion of palm oil and the non-ionic surfactant (Tween-Span type) possessing different hydrophile-lipophilie balance (HLB) values was evaluated in this work. An optimum condition was determined through analysis of main and interaction effects of each quantitative factor using central composite design model-response surface methodology (CCD-RSM). Quantitative factors used by CCD-RSM were an emulsification time, emulsification speed, HLB value and amount of surfactant. On the other hand, the reaction parameters were the viscosity and mean droplet size of O/W emersion. Optimized conditions obtained from CCD-RSM were the emulsification time of 12.7 min, emulsification speed of 5,551 rpm, HLB value of 8.0 and amount of surfactant of 5.7 wt.%. Ideal experimental results under the optimized experimental condition were the viscosity of 1,551 cP and mean droplet size of 432 nm which satisfy the targeted values. The average error value from our actual experiment for verifying the conclusions was below to 2.5%. Therefore, a high favorable level could be obtained when the CCD-RSM was applied to the optimized palm oil to water emulsification.

• Journal of the Korean Society for Railway
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• v.16 no.3
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• pp.196-201
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• 2013

As there is no failure data for the entire lifecycle of a product, when analyzing reliability measures based on early failure data only, there may be a significant error between the estimated mean life and the real one, because it can be underestimated, or on the other hand, it can be overestimated when analyzing reliability measures based on a large amount of censored data with the failure data. To resolve the issue, this study proposes an optimal sampling estimation procedure that selects the proportion of censored data to estimate the optimal distribution with the idea that the estimated distribution could be approximated as closely as the real life distribution. This would work if we sampled the optimal proportion on the censored data, because failure data has real intrinsic distribution in any situation. We validate the proposed procedure using an actual example. If the proposed method is applied to the maintenance policy of TWC (Train to Wayside Communication) system, then we can establish the optimal maintenance policy. Thus, we expect that it will be effective for improvement of reliability and cost savings.

• Korean Journal of Optics and Photonics
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• v.13 no.5
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• pp.442-448
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• 2002

In the earth telescope for space observation, the adaptive optical (AO) system that immediately compensates atmospheric turbulence is helpful to get high-resolution images. An adaptive optics for earth telescopes is very attractive, since the Earth telescopes can be made at lower costs and have larger optical apertures than space telescopes. Generally. in order to remove the wavefront error produced by atmospheric turbulence, a deformable mirror, whose surface shape changes in a controllable way in response to a drive signal, is used. The characteristics and patterns of actuators are very important for the effective control of a deformable mirror. The mirror surface shape deformed by one actuator is defined as an influence function and the deformable mirror can be effectively modeled and designed using this influence function. In this paper. by simplifying the actual influence function obtained by FEM analyses into the Gaussian function and introducing the coupling coefficient between actuators, the influence function is constructed. The proper coupling coefficient of the target system can be obtained by performance analyses of a deformable mirror for various coupling coefficients. Using the constructed influence function, the deformable mirror with equally spaced triangular and square actuator patterns is analyzed for various spacings and an effective actuator pattern is proposed.