• Proceedings of the IEEK Conference
• /
• 2001.06e
• /
• pp.189-192
• /
• 2001

A new configuration of acoustic echo canceler with stepsize predictor and comparator is proposed in this paper. Conventional acoustic echo cancelers using ES(Exponential Step)algorithm has fast convergence speed, but very weak in interference of environment. The proposed stepsize predictor and comparator improve conventional acoustic echo canceler's defects. The Stepsize predictor generates a stepsize value using residual power of error signal. The stepsize comparator selects the stepsize value that is better performance in a acoustic echo canceler using a stepsize decision factor. The Simulation results show superiority of the proposed acoustic echo canceler in environment interference.

• Proceedings of the KIEE Conference
• /
• 1995.07a
• /
• pp.258-260
• /
• 1995

A novel phase error predictor is proposed for servo system in home-use VCRs. The multirate system in VCRs is converted into a single period sampling system with faster sampling time by using the proposed novel phase error predictor. And the disturbances can be measured much faster. From the experimental results, we can see that the performance of the control system is improved greatly. The phase lock time of the proposed servo system is ten times faster than that of the conventional system.

• Fashion & Textile Research Journal
• /
• v.16 no.3
• /
• pp.378-385
• /
• 2014

This study examined the differences in job related variables, job satisfaction and job performance against demographic characteristics and the impacts of job related variables on job satisfaction and job performance. A questionnaire survey collected data from september $1^{st}$ and $7^{th}$ 2011. A convenience sample was drawn from salespersons working for department stores in Daegu and Pohang. A total of 337 responses were complete and usable questionnaires. Data were tested through factor analysis, t-test, ANOVA, and regression analysis, using SPSS 21.0. The results of this study are as follows: First, six factors were extracted from job related variables (positive reaction of customer, career of salespeople, interpersonal relations, influence of salesperson, customer complaints, overwork). Second, there were significant differences in job related variables, job satisfaction, and job performance according to age, marital status, average monthly income, work period, and job position. Third, regression analysis between job related variables and job satisfaction showed that the most influential predictor of job satisfaction was career of salespeople, followed by interpersonal relations, influence of salesperson, customer complaints, and overwork. The most influential predictor between job related variables and job performance was positive reaction of customer, followed by career of salespeople, interpersonal relations, influence of salesperson, and customer complaints.

• Journal of the Korean Society of Food Culture
• /
• v.39 no.1
• /
• pp.38-52
• /
• 2024

This study investigated relationships between personality types and job satisfaction, and performance among school food service dietitians. An online survey was conducted on 200 school dietitians from March 1 to 31, 2022. Of the personality type factors, extraversion, openness, agreeableness, and conscientiousness were positively correlated with job satisfaction, whereas neuroticism was negatively correlated. Extraversion, openness, agreeableness, and conscientiousness were positively correlated with job performance, whereas neuroticism was negatively correlated. Regression analysis conducted to determine the effects of personality types on job satisfaction revealed conscientiousness predicted satisfaction with items of the job, agreeableness predicted satisfaction with supervisor's supervision, and extraversion predicted satisfaction with colleagues. On the other hand, neuroticism was a negative predictor of satisfaction with the job, supervisor's supervision, colleagues, and work environment items. Analysis of the effects of personality types on job performance established that openness was a positive predictor of satisfaction with roles of the organization and team, and of conscientiousness for the job, innovator, and organizational roles. In contrast, neuroticism negatively predicted satisfaction with job role items. Further studies are required to explore these relationships more closely by incorporating other major factors related to personality characteristics, job satisfaction, and job performance of dietitians working in various fields.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.12
• /
• pp.1806-1814
• /
• 1993

Efficient speech coders using tree coding combined with harmonic scaling are designed at the rate of 4.8 kilobitts/sec (kbps). A time domain harmonic scaling algorithm (TDHS) is used to compress input speech by a factor of two. This process allows the tree coder have 1.5 bits/sample for 4.8 kbps in the case of a 6.4 kHz sampling rate. In the backward adaptive tree coder, there are three components of the code generator, including a hybrid adaptive quantizer, a short-term predictor and a pitch predictor. The robustness of the tree coder is achieved by carefully choosing the input of the short term predictor adaptation. Also, inclusion of a smoother in the pitch predictor improves the error performance of tree coder in the noisy channel. Subjectively, tree coding combined with TDHS provides good quality speech at 4.8 kbps.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.1
• /
• pp.96-102
• /
• 2018

For efficient operating strategy of electric power system, forecasting of daily peak electric load is an important but difficult problem. Therefore a daily peak electric load forecasting system using a neural network and fuzzy system is presented in this paper. First, original peak load data is interpolated in order to overcome the shortage of data for effective prediction. Next, the prediction of peak load using these interpolated data as input is performed in parallel by a neural network predictor and a fuzzy predictor. The neural network predictor shows better performance at drastic change of peak load, while the fuzzy predictor yields better prediction results in gradual changes. Finally, the superior one of two predictors is selected by the rules based on rough sets at every prediction time. To verify the effectiveness of the proposed method, the computer simulation is performed on peak load data in 2015 provided by KPX.

• Journal of Power Electronics
• /
• v.11 no.4
• /
• pp.583-590
• /
• 2011

Three-level NPC inverters have been put into practical use for years especially in high voltage high power grids. This paper researches three-level active power filters (APFs). In this paper a mathematical model in the d-q coordinates is presented for 3-phase 3-wire NPC APFs. The deadbeat control scheme is obtained by using state equations. Canceling the delay of one sampling period and providing the predictive value of the harmonic current is a key problem of the deadbeat control. Based on this deadbeat control, the predictive output current value is obtained by the state observer. The delay of one sampling period is remedied in this digital control system by the state observer. The predictive harmonic command current value is obtained by the repetitive predictor synchronously. The repetitive predictor can achieve a better prediction of the harmonic current with the same sampling frequency, thus improving the overall performance of the system. The experiment results indicate that the steady-state accuracy and the dynamic response are both satisfying when the proposed control scheme is implemented.

• Proceedings of the IEEK Conference
• /
• 2000.07a
• /
• pp.260-263
• /
• 2000

A technique that uses linear prediction to achieve noise reduction in a voice signal which has been mixed with an ambient noise (Signal to Noise (S-N) ratio = about 0dB) is proposed. This noise reduction method which is based on the linear prediction estimates the voice spectrum while ignoring the spectrum of the noise. The performance of the noise reduction method is first examined using the transversal linear predictor filter. However, with this method there is deterioration in the tone quality of the predicted voice due to the low level of the S-N ratio. An additional processing circuit is then proposed so as to adjust the noise reduction circuit with an aim of improving the problem of tone deterioration. Next, we consider a practical application where the effects of round on errors arising from fixed-point computation has to be minimized. This minimization is achieved by using the lattice predictor filter which in comparison to the transversal type, is Down to be less sensitive to the round-off error associated with finite word length operations. Finally, we consider a practical application where noise reduction is necessary. In this noise reduction method, both the voice spectrum and the actual noise spectrum are estimated. Noise reduction is achieved by using the linear predictor filter which includes the control of the predictor filter coefficient’s update.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.3 no.4
• /
• pp.23-27
• /
• 2010

This paper performs emotion classification test to find out the best parameter of electroencyphalogram(EEG) signal. Linear predictor coefficients, band cross-correlation coefficients of fast Fourier transform(FFT) and autoregressive model spectra are used as the parameters of 10-channel EEG signal. A multi-layer neural network is used as the pattern classifier. Four emotions for relaxation, joy, sadness, irritation are induced by four university students of an acting circle. Electrode positions are Fp1, Fp2, F3, F4, T3, T4, P3, P4, O1, O2. As a result, the Linear predictor coefficients showed the best performance.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.43 no.4 s.310
• /
• pp.1-14
• /
• 2006

The indirect branch instruction is a most substantial obstacle in utilizing ILP of modem high performance processors. The target address of an indirect branch has the polymorphic characteristic varied dynamically, so it is very difficult to predict the accurate target address. Therefore the performance of a processor with speculative methodology is reduced significantly due to the many execution cycle delays in occurring the misprediction. We proposed the very accurate and novel indirect branch prediction scheme so called data-dependence based prediction. The predictor results in the prediction accuracy of 98.92% using 1K entries, and. 99.95% using 8K But, all of the proposed indirect predictor including our predictor has a large hardware overhead for restoring expected target addresses as well as tags for alleviating an aliasing. Hence, we propose the scheme minimizing the hardware overhead without sacrificing the prediction accuracy. Our experiment results show that the hardware is reduced about 60% without the performance loss, and about 80% sacrificing only the performance loss of 0.1% in aspect of the tag overhead. Also, in aspect of the overhead of storing target addresses, it can save the hardware about 35% without the performance loss, and about 45% sacrificing only the performance loss of 1.11%.