• Journal of Institute of Control, Robotics and Systems
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• v.12 no.1
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• pp.41-46
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• 2006

Ubiquitous location based services, offer helpful services anytime and anywhere by using real-time location information of objects based on ubiquitous network. Particularly, autonomous mobile robots can be a solution for various applications related to ubiquitous location based services, e.g. in hospitals, for cleaning, at airports or railway stations. However, a meaningful and still unsolved problem for most applications is to develop a robust and cheap positioning system. A typical example of position measurements is dead reckoning that is well known for providing a good short-term accuracy, being inexpensive and allowing very high sampling rates. However, the measurement always has some accumulated errors because the fundamental idea of dead reckoning is the integration of incremental motion information over time. The other hand, a localization system using RFID offers absolute position of robots regardless of elapsed time. We construct an absolute positioning system based on RFID and investigate how localization technique can be enhanced by RFID through experiment to measure the location of a mobile robot. Tags are placed on the floor at 5cm intervals in the shape of square in an arbitrary space and the accuracy of position measurement is investigated . To reduce the error and the variation of error, a weighting function based on Gaussian function is used. Different weighting values are applied to position data of tags since weighting values follow Gaussian function.

• Proceedings of the IEEK Conference
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• 2004.06b
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• pp.565-568
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• 2004

This paper proposes effective method for delay estimation in RLC interconnects. This method is simple, but precise. The results using the proposed method for RLC circuits show that absolute average relative error is within $7\%$ with the exception of first node in comparison with HSPICE results.

• The Journal of Korean Society for Radiation Therapy
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• v.23 no.1
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• pp.51-58
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• 2011

Purpose: In this study, we tried to check the usefulness of two Linear Accelerators, Clinac IX and 21EX (Varian, Palo Alto, CA), which are equipped in Ajou Medical Center. From 2008 to 2010, we evaluated the error range of Absolute Dose based on the daily output, which was measured by CHECKMATE$^{TM}$ (Sun Nuclear, Melbourne, FL). Materials and Methods: For Daily Q.A, photon beams of two linear accelerators, 21EX and IX (6 MV and 10 MV, respectively) were measured daily by using CHECKMATE$^{TM}$ just before the treatment began, while the absolute dose was measured biweekly by using water phantom. We analyzed the data of measured values from the daily Q.A and the absolute dose from 2008 to 2010 for 21EX, and from 2009 to 2010 for IX. We utilized Excel 2007 (Microsoft, USA) to evaluate Average, Standard deviation and Confidence level of the data. Furthermore, in order to check the measured values of CHECKMATE$^{TM}$ and the significance of absolute dose, each error value was compared and analyzed. Results: During the observation period, the output of two equipment's absolute dose increased in process of time and in both 6 MV and 10 MV, there was a similar increasing trend. In addition, the error rate of the measured value of CHECKMATE$^{TM}$ and the value of absolute dose were under 0.34, which means that there is a similarity relationship between the two measured values. After checking that the measured value of CHECKMATE$^{TM}$ increased, We measured the absolute dose to adjust that. When the error range was close to 2~3%, the number of changing the output was four for 21EX and three for IX. Conclusion: As a result of measuring and analyzing the daily output changes for two years by using CHECKMATE$^{TM}$, we could find that there is a significance between the output which we should obey during Q.A, and the measured value of absolute dose within the error tolerance of 2~3%. Thus, the use of CHECKMATE$^{TM}$ can be positively considered for more efficient and reliable daily output verification of linear accelerator. It can also be a good standard for other medical centers to understand the trends of linear accelerator and to refer to for the correction of each output.

• 보존과학연구
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• s.26
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• pp.189-202
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• 2005

This study carried out to understand thermoluminescence dating of ancient tiles at Jinju Janghungri Kilin site. Also radiocarbon dating by the benzene synthesis method and Liquid scintillation counting method were performed for comparison for the agedetermination of charcoal sample at the obtained same site.1st and 2nd glow curve were obtained according to the typical method thermoluminescence. Plateau tests of revealed the proper temperature range to be $300~440^{\circ}C$ Palaeodose average values were formed to the 2.44Gy.Annual dose of ancient tiles was calculated from soil samples and ancient tiles it self by measuring alpha radiation dose, potassium concentrations and water contents respectively. Annual dose average values were calculated to be 7.012mGy/yr.The radiocarbon age(BP year) was converted to calibrated age(AD/BC year) using high precision curve. Radiocarbon ages were calculated to be AD 15~17 .Comparison of samples with their radiocarbon and thermoluminescence ages for revealed the in range the AD 15~17. This result means that the measured absolute ages are in good agreement with each other within the margin of error.

• Fire Science and Engineering
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• v.18 no.2
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• pp.27-33
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• 2004

An accurate knowledge of the AIT(Autoignition temperatures) of chemicals is important in developing appropriate prevention and control measures in industrial fire protection. The AITs describe the minimum temperature to which a substance must be heated, without the application of a flame or spark, which will cause that substance to ignite. The measurement AITs are dependent upon many factors. namely initial temperature. pressure, volume, fuel/air stoichiometry. catalyst material, concentration of vapor, ignition delay time. This study measured the AITs of acids from ignition delay time by using ASTM E659-78 apparatus which was produced in the year 1994. The experiment AITs were a good agreement with the calculated AITs by the proposed equations with a few A.A.P.E.(average absolute percent error) and A.A.D.(average absolute deviation).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.3
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• pp.323-332
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• 2012

An airborne LiDAR system performs several observations on flight routes to collect data of targeted regions accompanying with discrepancies between the collected data strips of adjacent routes. This paper aims to present an automatic error correction technique using modified ICP as a way to remove relative errors from the observed data of strip data between flight routes and to make absolute correction to the control data. A control point data from the existing digital topographic map were created and the modified ICP algorithm was applied to perform the absolute automated correction on the relatively adjusted airborne LiDAR data. Through such process we were able to improve the absolute accuracy between strips within the average point distance of airborne LiDAR data and verified the possibility of automation in the geometric corrections using a large scale digital map.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.153-160
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• 2020

The kinetic energy of the rain drops was predicted in a relation between the rain rate and rain quantity, derived directly from the rain drop size distribution (DSD), which had been measured by a disdrometer located in the eastern state of Alagoas-Brazil. The equation in the form of exponential form suppressed the effects of large drops at low rainfall intensity observed at the beginning and end of the rainfall. The kinetic energy of the raindrop was underestimated in almost rain intensity ranges and was considered acceptable by the performance indicators such as coefficient of determination, average absolute error, percent relative error, mean absolute error, root mean square error, Willmott's concordance index and confidence index.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.161-167
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• 2019

Recently, demand forecasting techniques have been actively studied due to interest in stable power supply with surging power demand, and increase in spread of smart meters that enable real-time power measurement. In this study, we proceeded the deep learning prediction model experiments which learns actual measured power usage data of home and outputs the forecasting result. And we proceeded pre-processing with moving average method. The predicted value made by the model is evaluated with the actual measured data. Through this forecasting, it is possible to lower the power supply reserve ratio and reduce the waste of the unused power. In this paper, we conducted experiments on three types of networks: Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN), and Long Short Term Memory (LSTM) and we evaluate the results of each scheme. Evaluation is conducted with following method: MSE(Mean Squared Error) method and MAE(Mean Absolute Error).

• Advances in Energy Research
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• v.8 no.2
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• pp.95-110
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• 2022

Wind energy can be utilized for the generation of electricity, due to significant wind potential at different parts of the world, some countries have already been generating of electricity through wind. Pakistan is still well behind and has not yet made any appreciable effort for the same. The objective of this work was to add some new strategies to calculate Weibull parameters and assess wind energy potential. A new approach calculates Weibull parameters; we also developed an alternate formula to calculate shape parameters instead of the gamma function. We obtained k (shape parameter) and c (scale parameter) for two-parameter Weibull distribution using five statistical methods for five different cities in Pakistan. Maximum likelihood method, Modified Maximum likelihood Method, Method of Moment, Energy Pattern Method, Empirical Method, and have been to calculate and differentiate the values of (shape parameter) k and (scale parameter) c. The performance of these five methods is estimated using the Goodness-of-Fit Test, including root mean square error, mean absolute bias error, mean absolute percentage error, and chi-square error. The daily 10-minute average values of wind speed data (obtained from energydata.info) of different cities of Pakistan for the year 2016 are used to estimate the Weibull parameters. The study finds that Hyderabad city has the largest wind potential than Karachi, Quetta, Lahore, and Peshawar. Hyderabad and Karachi are two possible sites where wind turbines can produce reasonable electricity.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.4
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• pp.65-74
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• 2005

AnnAGNPS model was applied to a catchment mainly occupied with bushland for modeling non-point source pollution. Since the single event model cannot handle events longer than 24 hours duration, the event-based calibration was carried out using the continuous mode. As event flows affect sediment and nutrient generation and transport, the calibration of the model was performed in three steps: Hydrologic, Sediment and Nutrient calibrations. The results from hydrologic calibration for the catchment indicate a good prediction of the model with average ARE(Absolute Relative Error) of $24.6\%$ fur the runoff volume and $12\%$ for the peak flow. For the sediment calibration, the average ARE was $198.8\%$ indicating acceptable model performance for the sediment prediction. The predicted TN(Total Nitrogen) and TP(Total Phosphorus) were also found to be acceptable as the average ARE for TN and TP were $175.5\%\;and\;126.5\%$, respectively. The AnnAGNPS model was therefore approved to be appropriate to model non-point source pollution in bushland catchments. In general, the model was likely to result in underestimation for the larger events and overestimation fur the smaller events for the water quality predictions. It was also observed that the large errors in the hydrologic prediction also produced high errors in sediment and nutrient prediction. This was probably due to error propagation in which the error in the hydrologic prediction influenced the generation of error in the water quality prediction. Accurate hydrologic calibration should be hence obtained for a reliable water quality prediction.