• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.7 s.100
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• pp.821-828
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• 2005

In our life, we have used many digital appliances. They help us to improve the quality of life but sometimes give us unsatisfactory result. Because they produce specific noise. Especially vacuum cleaner produce much noise that is very annoying. So we need to study what sound metrics affect human sensibility. In this paper, we develop sound quality index for vacuum cleaner using the sound quality metrics defined in psychoacoustics. First, we carry out the subjective evaluation of vacuum cleaner sound to verify what vacuum sound feels good to human. And then artificial neural network estimated the complexity and the nonlinear characteristics of the relations between subjective evaluation and sound metrics. Finally the ANN is trained repeatedly to have a good performance for sound qualify index of the vacuum cleaner. As a result, the sound quality index of vacuum cleaner has a correlation of $93.5\%$ between the subjective evaluation and ANN. So, there exist three factors that Is loudness, sharpness, roughness which affect the sound quality of vacuum cleaner.

• Journal of Communications and Networks
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• v.11 no.1
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• pp.42-46
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• 2009

Superimposed training (SIT) design for estimating of time-varying multipath channels is investigated for mobile orthogonal frequency division multiplexing (OFDM) systems. The design of optimum SIT consists of two parts: The optimal SIT sequence is derived by minimizing the channel estimates' mean square error (MSE); the optimal power allocation between training and information data is developed by maximizing the averaged signal to interference plus noise ratio (SINR) under the condition of equal powered paths. The theoretical analysis is verified by simulations. For the metric of the averaged SINR against signal to noise ratio (SNR), the theoretical result matches the simulation result perfectly. In contrast to an interpolated frequency-multiplexing training (FMT) scheme or an SIT scheme with random pilot sequence, the SIT scheme with proposed optimal sequence achieves higher SINR. The analytical solution of the optimal power allocation is demonstrated by the simulation as well.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.785-790
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• 2014

The purpose of this study is to identify the significant sound quality metric and compose the sound quality index of motor driven roller blind which is part of vehicle sunroof. Before subjective evaluation, sound characteristics of roller blind was analyzed and set the target operating sound for subjective evaluation. Thus, transfer sound of roller blind which has the characteristics of sound modulation was used for subjective evaluation. Linear regression was carried out by chosen Zwicker's metrics which are pointed by comments of jurors. Loudness and sharpness related metrics are prime metrics in sound quality index we composed. Effect of roller blind assay when it is attached to real vehicle was identified to evaluate the validity of index.

• The Journal of the Acoustical Society of Korea
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• v.40 no.2
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• pp.176-182
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• 2021

This paper evaluates and compares the performance of the Deep Nerual Network (DNN)-based speech enhancement models according to various loss functions. We used a complex network that can consider the phase information of speech as a baseline model. As the loss function, we consider two types of basic loss functions; the Mean Squared Error (MSE) and the Scale-Invariant Source-to-Noise Ratio (SI-SNR), and two types of perceptual-based loss functions, including the Perceptual Metric for Speech Quality Evaluation (PMSQE) and the Log Mel Spectra (LMS). The performance comparison was performed through objective evaluation and listening tests with outputs obtained using various combinations of the loss functions. Test results show that when a perceptual-based loss function was combined with MSE or SI-SNR, the overall performance is improved, and the perceptual-based loss functions, even exhibiting lower objective scores showed better performance in the listening test.

• The Journal of the Acoustical Society of Korea
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• v.35 no.6
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• pp.427-435
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• 2016

Array Gain (AG) is a metric to measure the performance of an array of acoustic sensors. AG is affected by the configuration of array, frequency and array element spacing, and the directivity of the ambient noise. In this paper, an algorithm to calculate AG based on the spatial coherence is used, and the results are verified through sea-going experiment. The method using the spatial coherence can be used to consider the arbitrary shape of an array and directionality of ambient noise. In the sea-going experiment, the towed source was used to transmit the Continuous Wave (CW), and was received at the horizontal line array on the seabed. The ambient noise was measured between the source transmission. The experimental AG was calculated from the SNR (Signal to Noise Ratio) of single sensor and an array of sensors. Finally, the predicted AG is shown to agree with the experimental value of AG.

• The Journal of the Acoustical Society of Korea
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• v.29 no.4
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• pp.258-264
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• 2010

In this paper, we propose an objective quality feature which is based on the human auditory system to measure vacuum cleaner noise. It is observed that some frequency bands are more sensitive to the human auditory system. Therefore, we divided the audible frequency range of vacuum cleaner noise into a number of frequency bands and the average energy of these bands was calculated. Among a number of average energies, an average energy of a frequency band was selected as the proposed feature. In order to test the performance of the proposed feature, fourteen vacuum cleaners were chosen and the noise was recorded in an anechoic-chamber. Then we performed subjective tests to obtain subjective scores of the noise data using the PCM (paired comparison method) and ACR (absolute category rating) subjective methods. The proposed objective quality feature shows high correlation with the subjective scores.

• International Journal of Quality Innovation
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• v.10 no.1
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• pp.115-126
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• 2009

Video transmission effectiveness in the Ad Hoc network is becoming important recently, if different routing protocols are applied. Some researchers conclude that the reactive protocols are better for file transfer protocol (FTP) and constant bit rate (CBR) or hypertext transfer protocol (HTTP) transmission in an Ad Hoc wireless network but the performance report of video transmission is not much. This study adopts Qualnet (Network Simulator) as a simulation tool for environmental designing and performance testing, and employs an experimental design with eight groups. Our experiment shows that: (1) The performance of AODV (reactive) protocol is better than DSDV, ZRP and DSR when the transmission load has only one video stream; (2) Proactive (DSDV) and Hybrid protocols (ZRP) are better for a smaller Ad Hoc network when it transmits a video stream with some applications (VoIP, FTP and CBR). We conclude that packet loss rate is sensitive to the quality of video transmission and it has negative relationship with Peak Signal-to-Noise Ratio (PSNR) value. In addition, our experiment also shows that PSNR is a simple Metric for the performance evaluation of video transmission.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1351-1372
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• 2022

A self-organizing multiple unmanned aerial vehicles (multi-UAVs) deployment based on virtual forces has a difficulty in ensuring the quality-of-experience (QoE) of users because of the difference between the assumed center for users in a hotspot and an actual center for users in the hotspot. This discrepancy is aggravated in a non-uniform and mobile user distribution. To address this problem, we propose a new density based virtual force (D-VF) multi-UAVs deployment algorithm which employs a mean opinion score (MOS) as a metric of QoE. Because MOS is based on signal-to-noise ratio (SNR), a sum of users' MOS is a good metric not only to secure a wide service area but to enhance the link quality between multi-UAVs and users. The proposed algorithm improves users' QoE by combining virtual forces with a random search force for the exploration of finding multi-UAVs' positions which maximize the sum of users' MOS. In simulation results, the proposed deployment algorithm shows the convergence of the multi-UAVs into the position of maximizing MOS. Therefore, the proposed algorithm outperforms the conventional virtual force-based deployment scheme in terms of QoE for non-uniform user distribution scenarios.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.44-51
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• 2009

This paper addresses a face verification method using the nonlinear composite filter. This face verification process can be simple and speedy because it does not require any reprocessing such as face detection, alignment or cropping. The optimum nonlinear composite filter is derived by minimizing the output energy due to additive noise and an input scene while maintaining the outputs of training images constant. The filter is equipped with the discrimination capability and the robustness to additive noise by minimizing the outputs of the input scene and the noise, respectively. We build the nonlinear composite filter with two training images and compare the filter with the conventional synthetic discriminant function (SDF) filter. The receiver operating characteristics (ROC) curves are presented as a metric for the performance evaluation. According to the experimental results the optimum nonlinear composite filter is shown to be a robust scheme for face verification in low resolution and noise environments.

• Journal of Broadcast Engineering
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• v.20 no.2
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• pp.204-214
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• 2015

Depth map upsampling is an approach to increase the spatial resolution of depth maps obtained from a depth camera. Depth map quality is closely related to 3D perception of stereoscopic image, multi-view image and holography. In general, the performance of upsampled depth map is evaluated by PSNR (Peak Signal to Noise Ratio). On the other hand, time-consuming 3D subjective tests requiring human subjects are carried out for examining the 3D perception as well as visual fatigue for 3D contents. Therefore, if an objective metric is closely correlated with a subjective test, the latter can be replaced by the objective metric. For this, this paper proposes a best metric by investigating the relationship between diverse objective metrics and 3D subjective tests. Diverse reference and no-reference metrics are adopted to evaluate the performance of upsampled depth maps. The subjective test is performed based on DSCQS test. From the utilization and analysis of three kinds of correlations, we validated that SSIM and Edge-PSNR can replace the subjective test.