• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1993.10a
• /
• pp.149-154
• /
• 1993

In heavy grinding that is on of the high efficient grinding method, meaningful deformation is generated by high temperature. So, after machining, geomeric error generated od the workpiece. The most important factor on the geometric error is temperature difference between upper layer and lower layer (T $_{d}$) . Relations between Td and grinding condition and maximum geometric error and grinding condition are obtained by experiment. This relations are used in fuzzy algorithm for improvement geometric accuracy. The main results are follows : (1) The linear relation between maximum geometric error and grinding condition is ovtained by experiment. (2) The linear relation between maximum temperature difference between upper layer and lower layer and grinding condition is ovtained by experiment. (3) Control peth of wheel for improvement geometric accuracy is obtained by using the fuzzy algorithm.m.

• Journal of IKEEE
• /
• v.23 no.4
• /
• pp.1465-1468
• /
• 2019

The image noise improvement algorithm proposed in this paper extracts the boundary line by using the window of the binarized image to detect the gesture motion. Boundary line blurring is prevented by improving Gaussian noise generated during video output. To improve gesture recognition in low-light environments, an image noise enhancement algorithm has been designed to provide an output image close to the base image. Analyzing the experimental results, we found almost 10% improvement in the results compared to the results of the existing Median filter.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.11
• /
• pp.2192-2199
• /
• 2009

This paper proposes a novel tracking algorithm for efficiency improvement of photovoltaic(PV) system using sensor method. PV system of sensor method is exactly impossible to track a sun position when insolation is low or rapidly changed by the clouds and fogs. Also, in this case, tracking device is occurred energy consumption by unnecessary operating. This statement of reason, real power of PV system is not increased than fixed PV system in specified location. Therefore, this paper proposes a novel tracking algorithm considered insolation for efficiency improvement of PV system using sensor method. And this paper analyzes the generation volume and proves the validity of proposed algorithm as compared with the conventional PV tracking system using sensor method.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1994.06c
• /
• pp.358-363
• /
• 1994

This paper presents the improvement of the SCHMM using discrete VQ and One-Pass algorithm for keywords recognition in Korean continuous speech. The SCHMM using discrete VQ is a simple model that is composed of a variable mixture gaussian probability density function with dynamic mixture number. One-Pass algorithm is improved such that recognition rates are enhanced by fathoming any undesirable semisyllable with the low likelihood and the high duration penalty, and computation time is reduced by testing only the frame which is dissimilar to the previously testd frame. In recognition experiments for speaker-dependent case, the improved One-Pass algorithm has shown recognition rates as high as 99.7% and has reduced compution time by about 30% compared with the currently abailable one-pass algorithm.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.15 no.5
• /
• pp.243-249
• /
• 2020

Event detection in wireless sensor networks is a key requirement in many applications. Acoustic sensors are one of the most frequently used sensors for event detection in sensor networks, but they are sensitive and difficult to handle because they vary greatly depending on the environment and target characteristics of the sensor field. In this paper, we propose a learning-based improvement of CFAR algorithm for increasing node-level event detection performance in acoustic sensor networks, and verify the effectiveness of the designed algorithm by comparing and evaluating the event detection performance with other algorithms. Our experimental results demonstrate the superiority of the proposed algorithm by increasing the detection accuracy by more than 45.16% by significantly reducing false positives by 7.97 times while slightly increasing the false negative compared to the existing algorithm.

• Proceedings of the KIEE Conference
• /
• 2015.07a
• /
• pp.416-417
• /
• 2015

In this study, the parameters of the lightning flashover rate calculation algorithm in South Korea, USA, Japan are investigated for the suitable algorithm for South Korea. Each parameters used in each calculation algorithms have a obvious difference by the environment of the area and transmission lines, because they have different environmental parameters respectively. In this paper, the environmental parameters are weighted according to the change of outputs by different inputs, environmental parameters. In addition, the methods of the selection CRIEPI algorithm and the application EPRI, CRIEPI parameters for improvement the KEPRI algorithm are proposed.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.7A
• /
• pp.978-985
• /
• 2000

Blind equalizers recover the transmitted data using statistical characteristics of the signal alone. Among many alternatives, steepest gradient descent type algorithms such as the CMA and Sato algorithm are most widely utilized in practice. In this paper we propose a dual-mode NCMA algorithm, which combines the advantages of the dual mode CMA and Normalized CMA (NCMA) with the dual mode phase recovery algorithm. In addition, we perform computer simulations to demonstrate the performance improvement of the proposed algorithm with a QAM system. Simulation results show that the presented algorithm has a faster convergence speed and smaller steady-state residual error than the CMA and dual-mode CMA.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.25 no.5
• /
• pp.73-78
• /
• 2011

We developed a noise reduction algorithm for the measurement accuracy improvement of a fiber-optic distributed temperaure sensor system. The denoising technique is based on the wavelet transform. The proposed algorithm was applied to a FBG sensor output with the Gaussian line-fitting algorithm to minimize the output noise which originated from the intensity noise of the laser light source and the instability of signal porcessing. We confirmed the feasibility of the denoising algorithm by comparing the measurement results with those obtained with the Gaussian line-fitting algorithm only.

• Nuclear Engineering and Technology
• /
• v.56 no.7
• /
• pp.2659-2665
• /
• 2024

This study proposes an algorithm that combines a Kalman Filter method with effective decay constant correction to improve the accuracy of predicting radiation dose rate distribution during emergencies. The algorithm addresses the limitations of relying solely on measurement data by incorporating calculation data and refining the estimations. The effectiveness of algorithm was assessed using hypothetical test scenarios, which demonstrated a significant improvement in the accuracy of dose rate prediction compared to the model predictions. The estimates generated by the algorithm showed a good agreement with the measured data, and the discrepancies tend to decrease over time. Furthermore, the application of the effective decay constant correction accelerated the reduction of prediction errors. In conclusion, it was confirmed that the combined use of the Kalman filter method and effective decay constant correction is an effective approach to improve the accuracy of dose rate prediction.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.3
• /
• pp.1356-1362
• /
• 2015

The location of PV systems in distribution system has been increased as one of countermeasure for global environmental issues. As the operation efficiency of PV systems is getting decreased year by year due to the aging phenomenon and maintenance problems, the optimal algorithm for state diagnosis in PV systems is required in order to improve operation performance in PV systems. The existing output prediction algorithms considering various parameters and conditions of PV modules could have complicated calculation process and then their results may have a possibility of significant prediction error. To solve these problems, this paper proposes an optimal prediction algorithm of PV system by using least square methods of linear regression analysis. And also, this paper presents a performance evaluation algorithm in PV modules based on the proposed optimal prediction algorithm of PV system. The simulation results show that the proposed algorithm is a practical tool of the state diagnosis for performance improvement in PV systems.