• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3194-3210
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• 2022

Wall obstruction is the main factor leading to the non-line of sight (NLoS) error of indoor localization based on received signal strength indicator (RSSI). Modeling and correcting the path loss of the signals through the wall will improve the accuracy of RSSI localization. Based on electromagnetic wave propagation theory, the reflection and transmission process of wireless signals propagation through the wall is analyzed. The path loss of signals through wall is deduced based on power loss and RSSI definition, and the theoretical model of path loss of signals through wall is proposed. In view of electromagnetic characteristic parameters of the theoretical model usually cannot be accurately obtained, the statistical model of NLoS error caused by the signals through the wall is presented based on the log-distance path loss model to solve the parameters. Combining the statistical model and theoretical model, a hybrid model of path loss of signals through wall is proposed. Based on the empirical values of electromagnetic characteristic parameters of the concrete wall, the effect of each electromagnetic characteristic parameters on path loss is analyzed, and the theoretical model of regional path loss of signals through the wall is established. The statistical model and hybrid model of regional path loss of signals through wall are established by RSSI observation experiments, respectively. The hybrid model can solve the problem of path loss when the material of wall is unknown. The results show that the hybrid model can better express the actual trend of the regional path loss and maintain the pass loss continuity of adjacent areas. The validity of the hybrid model is verified by inverse computation of the RSSI of the extended region, and the calculated RSSI is basically consistent with the measured RSSI. The hybrid model can be used to forecast regional path loss of signals through the wall.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9A
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• pp.1306-1312
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• 2000

The quality loss of a X-band transmitter has been derived by means of MC simulation. The transmitter as a payload of LEO(Low Earth Orbit) satellite is capable of the down transmission the image data of hundreds Mbps generated from the Electro-Optical Instrument in real time. The parameters such as data asymmetry amplitude unbalance,phase unbalance, wave shaping and channel interference are included in the quality loss simulation Assuming that normally distributed gaussian noise is simply added to the channel, the quality loss of 0.7 dB has been obtained through this simulation based on a 95% confidence interval. The obtained quality loss can be applied to the link budgets as an additional loss item.

• Journal of international Conference on Electrical Machines and Systems
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• v.1 no.2
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• pp.10-17
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• 2012

This paper presents an improved iron loss model, for the computation of the no load iron loss in the stator core of the in-wheel permanent magnet synchronous motors (PMSM), for the cases of with and without stator skew. 2-D analytical model is used for the computation of tooth and yoke flux densities of the in-wheel PMSM. The no load iron loss computed by the improved iron loss model, for the cases of with and without skew is compared with the finite element method (FEM) and the results show good consistency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.72-74
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• 2021

The deep learning process currently utilized in various fields consists of data preparation, data preprocessing, model generation, model learning, and model evaluation. In the process of model learning, the loss function compares the value of the model with the actual value and outputs the difference. In this paper, we analyze various loss functions used in the deep learning model for biomarker extraction, which measure the degree of loss of neural network output values, and try to find the best loss function through experiments.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.169-175
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• 1998

There is a shared multibuffer method which can preventing HOL blocking in ATM switch. However, the system still has a problem that reduces the performance of the system because of the cell loss. Therefore, in this paper, preventing of cell loss in non-contentional shared multibuffer switch is suggested. To prevent cell loss, a structure is suggested that a cell can be loss in a certain slot time is stored in the dedicated temporary memory so the cell can be transferred in the next slot time. The simulation result of the structure, this suggested system superior performance than the exited system in cell loss rate and throughput.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.203-207
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• 2005

A loss system where two types of customers arrive in accordance with two independent Poisson processes is considered. An efficient recursive formula is developed for calculating the loss probability when the number of servers is large. Some practical examples regarding the performance evaluation of telecommunications networks are discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1743-1758
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• 2023

Automatic modulation classification is a critical algorithm for non-cooperative communication systems. This paper addresses the challenging problem of closed-set and open-set signal modulation classification in complex channels. We propose a novel approach that incorporates a self-learning filter and center-loss in Deep Residual Shrinking Networks (DRSN) for closed-set modulation classification, and the Opendistance method for open-set modulation classification. Our approach achieves better performance than existing methods in both closed-set and open-set recognition. In closed-set recognition, the self-learning filter and center-loss combination improves recognition performance, with a maximum accuracy of over 92.18%. In open-set recognition, the use of a self-learning filter and center-loss provide an effective feature vector for open-set recognition, and the Opendistance method outperforms SoftMax and OpenMax in F1 scores and mean average accuracy under high openness. Overall, our proposed approach demonstrates promising results for automatic modulation classification, providing better performance in non-cooperative communication systems.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1566-1574
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• 2017

When the inter-turn short circuit (ITSC) fault occurs, the distortion of the magnetic field is serious. The motor loss variations of each part are obvious, and the motor temperature field is also affected. In order to obtain the influence of the ITSC fault on the motor temperature distribution, firstly, the normal and the fault finite element models of the permanent magnet synchronous motor (PMSM) were established. The magnetic density distribution and the eddy current density distribution were analyzed, and the mechanism of loss change was revealed. The effects of different forms and degrees of the fault on the loss were obtained. Based on the loss analysis, the motor temperature field calculation model was established, and the motor temperature change considering the loop current was analyzed. The influence of the fault on the motor temperature distribution was revealed. The sensitivity factors that limit the motor continuous operation were obtained. Finally, the correctness of the simulation was verified by experiments. The conclusions obtained are of great significance for the fault and high temperature demagnetization of the permanent magnet analysis.

• Journal of Audiology & Otology
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• v.24 no.4
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• pp.174-179
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• 2020

Background and Objectives: The integration of auditory-visual speech information improves speech perception; however, if the auditory system input is disrupted due to hearing loss, auditory and visual inputs cannot be fully integrated. Additionally, temporal coincidence of auditory and visual input is a significantly important factor in integrating the input of these two senses. Time delayed acoustic pathway caused by the signal passing through digital signal processing. Therefore, this study aimed to investigate the effects of hearing loss and hearing aid digital delay circuit on sound-induced flash illusion. Subjects and Methods: A total of 13 adults with normal hearing, 13 with mild to moderate hearing loss, and 13 with moderate to severe hearing loss were enrolled in this study. Subsequently, the sound-induced flash illusion test was conducted, and the results were analyzed. Results: The results showed that hearing aid digital delay and hearing loss had no detrimental effect on sound-induced flash illusion. Conclusions: Transmission velocity and neural transduction rate of the auditory inputs decreased in patients with hearing loss. Hence, the integrating auditory and visual sensory cannot be combined completely. Although the transmission rate of the auditory sense input was approximately normal when the hearing aid was prescribed. Thus, it can be concluded that the processing delay in the hearing aid circuit is insufficient to disrupt the integration of auditory and visual information.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.174-183
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• 2018

In the industrial fields, the process capability index has been using to evaluate the variation of quality in the process. The traditional process capability indices such as $C_p$, $C_{pk}$, $C_{pm}$ and $C^+_{pm}$ have been applied in the industrial fields. These traditional process capability indices are mainly applied in the univariate analysis. However, the main streams in the recent industry are the multivariate manufacturing process and the multiple quality characteristics are corrected each other. Therefore, the multivariate statistical method should be used in the process capability analysis. The multivariate process indices need to be enhanced with more useful information and extensive application in the recent industrial fields. Hence, the purpose of the study is to develop a more effective multivariate process index ($MC_{pI}$) using the multivariate inverted normal loss function. The multivariate inverted normal loss function has the flexibility for the any type of the symmetrical and asymmetrical loss functions as well as the economic information. Especially, the proposed modeling method for the multivariate inverted normal loss function (MINLF) and the expected loss from MINLF in this paper can be applied to the any type of the symmetrical and asymmetrical loss functions. And this modeling method can be easily expanded from a bivariate case to a multivariate case.