• Journal of Information Technology Applications and Management
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• v.15 no.1
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• pp.271-282
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• 2008

Database administrators are demanded to acquire much knowledges and take great efforts for keeping consistent performance in system. Various principles, methods, and tools have been proposed in many studies and commercial products in order to alleviate such burdens on database administrators, and it has resulted to the automation of DBMS which reduces the intervention of database administrator. This paper suggests a resource selection method that estimates the status of the database system based on the workload characteristics and that recommends tuneable resources. Our method tries to simplify selection information on DBMS status using data-mining techniques, enhance the accuracy of the selection model, and recommend tuneable resource. For evaluating the performance of our method, instances are collected in TPC-C and TPC-W workloads, and accuracy are calculated using 10 cross validation method, comparisons are made between our scheme and the method which uses only the classification procedure without any simplification of informations. It is shown that our method has over 90% accuracy and can perform tuneable resource selection.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.508-510
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• 2005

In this paper, we have studied for the current control method with high accuracy for the high power LED driver that is necessary to the lighting system using LEDs. The control performance of LED driver can be improved with the adjustment of current control boundary by introducing D/A converters for setting high-offset and low-offset. And microprocessor (ATmega128) and D/A converter with 8 bits resolution are used in the proposed driver so that LED's illumination can be remotely controlled by serial communication on the spot or by key input. In the results of performance tests, we confirmed that the proposed control method is superior to the conventional control method using op-amps.

• ETRI Journal
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• v.46 no.2
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• pp.205-217
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• 2024

We propose a bandwidth prediction approach based on deep learning. The approach is intended to accurately predict the bandwidth of various types of mobile networks. We first use a machine learning technique, namely, the gradient boosting algorithm, to recognize the connected mobile network. Second, we apply a handover detection algorithm based on network recognition to account for vertical handover that causes the bandwidth variance. Third, as the communication performance offered by 3G, 4G, and 5G networks varies, we suggest a bidirectional long short-term memory model with time distribution for bandwidth prediction per network. To increase the prediction accuracy, pretraining and fine-tuning are applied for each type of network. We use a dataset collected at University College Cork for network recognition, handover detection, and bandwidth prediction. The performance evaluation indicates that the handover detection algorithm achieves 88.5% accuracy, and the bandwidth prediction model achieves a high accuracy, with a root-mean-square error of only 2.12%.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.3
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• pp.174-181
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• 2012

The spindle unit is a core part in high precision machine tool. Rotation accuracy of spindle unit is needed for high dignity cutting and improving the performance of machine tool. However, there are many factors to effect to rotational error motion(rotation accuracy). This study studied how rotational error motion is variation when unbalance amount is variation. Rotation accuracy of initial spindle unit is decided depending on parts and assembly such as bearing. When it is rotation, vibration and noise is appeared depending on volume of unbalance amount, so it works to decrease unbalance amount. The purpose of the study tests that unbalance amount how much effects to initial rotation condition. The result of the study shows that accuracy of parts and assembly is highly necessary to reach high rotation accuracy and unbalance amount hardly effects to initial rotation accuracy. However, it shorten spindle's life because vibration and noise is increasing by increasing unbalance amount and we can expect situation that rotation accuracy is falling by long time operation.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.3
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• pp.327-334
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• 1988

In this paper, the performance of PRA (pel recurdive algorithm) and BMA(block matching algorithm), which are the most well-known motion estimation techniques, is compared and the effects of the motion estimation accuracy on the motion compensated coding are described. Results of computer simulation on the real images indicate that the TSS (three step search), which is one of the BMA,is slightly better than the PRA in terms of the accuracy however, the required bit rate is 6.6-8.2 Kbps higher that of the PRA because the TSS requires a transmission of motion estimation vectors.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.26-32
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• 1994

The Lloyd-Max algorithm is an iterative scheme for design of the minimum mean square error quantizer. It is very simple in concept and easy to program into a computer. However its convergence and accuracy are primarily dependent upon the accuracy of the initial parameter. In this paper, a new initial parameter which converges to a specific value when the number of output levels becomes large is selected. And an estimator using curve fitting techique is suggested. In addition, performance of the proposed method is shown to be superior to that of the existing methods in accuracy and convergence.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.200-205
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• 1989

The performance of conventional robot arms is inhibited by trade-off between speed and accuracy. Because these systems measure only joint angles, in spite of slow speed, they must rely on a stiff structure in order to attain positioning accuracy. Lightweight links would allow faster motion, but their flexibility would also produce positioning errors. This research is involved with the development and evaluation of an End-point Control System whose major goal is to compensate for link deflections and thus mitigate the speed versus accuracy conflict in conventional manipulator.

• The Korean Journal of Emergency Medical Services
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• v.13 no.3
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• pp.29-40
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• 2009

Objective : This study is an experimental study which is designed to examine the differences between knowledge and self-confidence before and after theory education(CPR PPT material) based on guidelines of CPR and emergency cardiac treatment of American Heart Association(AHA, 2005) and video self-instruction program for the general public by Korean Association of Cardiopulmonary Resuscitation(KACPR), trace CPR performance ability after CPR and AED education and investigate the accuracy of artificial respiration and chest compression, and know the difference in CPR performance abilities including AED. Methods : Subjects of this study include ground crews and staffs at M airport in G province equipped with emergency equipments for CPR according to Art. 47, Sec. 2 of Emergency Medical Law, airport police, rent-a-cops, security guard, quarantine officer, custom officer, and communication, electricity, civil engineering, facility management staff, airport fire fighting staff, air mechanic, traffic controller, and airport management team among airport facility management staffs. They were given explanation of necessity of research and 147 of 220 subjects who gave consent to this research but 73 who were absent from survey were excluded were used as subjects of this study. of 147 subjects, there were 102 men and 45 women. Results : 1) Knowledge score of CPR was $6.18{\pm}0.87$ before instruction and it was increased to $15.12{\pm}1.78$ after instruction, and there was statistically significant difference. 2) Self-confidence score in CPR was $3.16{\pm}0.96$ before instruction and it was increased to $7.05{\pm}0.75$ after instruction, and there was statistically significant difference. 3) Total average score in CPR performance ability after instruction was 7.46 out of 9, performance ability was highest in confirmation of response as 144(97.95%), follwed by request of help as 140(95.25%) and confirmation of respiration as 135(91.83%), and lowest in performing artificial respiration twice(gross elevation of chest) as 97(65.98%). Accuracy of artificial respiration(%) was $28.60{\pm}16.88$ and that of chest compression(%) was $73.10{\pm}22.16$. 4) Performance ability of AED after instruction showed proper performance in power on by 141(95.91%) and attaching pad by 135(91.83%), hand-off for analyzing rhythm showed 'accuracy' in 115(78.23%) and 'non-performance' in 32(21.77%), delivery of shock and hand-off confirmation showed 'accuracy' in 109(74.14%) and 'inaccuracy' in 38(25.86%), and beginning chest compression immediately after AED was done by 105(71.42%).

• KEPCO Journal on Electric Power and Energy
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• v.6 no.4
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• pp.413-418
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• 2020

It is necessary to manage the prediction accuracy of the machine learning model to prevent the decrease in the performance of the grid network condition prediction model due to overfitting of the initial training data and to continuously utilize the prediction model in the field by maintaining the prediction accuracy. In this paper, we propose an automation technique for maintaining the performance of the model, which increases the accuracy and reliability of the prediction model by considering the characteristics of the power grid state data that constantly changes due to various factors, and enables quality maintenance at a level applicable to the field. The proposed technique modeled a series of tasks for maintaining the performance of the power grid condition prediction model through the application of the workflow management technology in the form of a workflow, and then automated it to make the work more efficient. In addition, the reliability of the performance result is secured by evaluating the performance of the prediction model taking into account both the degree of change in the statistical characteristics of the data and the level of generalization of the prediction, which has not been attempted in the existing technology. Through this, the accuracy of the prediction model is maintained at a certain level, and further new development of predictive models with excellent performance is possible. As a result, the proposed technique not only solves the problem of performance degradation of the predictive model, but also improves the field utilization of the condition prediction model in a complex power grid system.

• Journal of Positioning, Navigation, and Timing
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• v.3 no.3
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• pp.117-122
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• 2014

In CDGPS, ambiguity resolution is determined by the performance of a floating solution, and thus, the performance needs to be improved. In the case of precise positioning at a stationary position, the batch method using multiple measurements is used for the accuracy improvement of a position. The position accuracy performance of a floating solution is outstanding, but it has a problem of high computation cost because all measurements are used. In this study, to improve the floating solution performance of the initial static user in CDGPS, a floating solution method using a recursive filter was implemented. A recursive filter estimates the position solution of the current epoch using the position solution of up to the previous epoch and the pseudorange measurement of the current epoch. The computation cost of the floating solution method using a recursive filter was found to be similar to that of the epoch-by-epoch method. Also, based on actual GPS signals, the floating solution performance was found to be similar to that of the batch method. The floating solution using a recursive filter could significantly improve the performance of the prompt initial position and ambiguity resolution of the initial static user.