• Journal of Korean Academy of Nursing
• /
• v.48 no.2
• /
• pp.143-153
• /
• 2018

Purpose: The purpose of this study was to identify factors predicting behavioral and psychological symptoms of dementia (BPSD) in persons with dementia. Factors including the patient, caregiver, and environment based on the multi-dimensional behavioral model were tested. Methods: The subjects of the study were 139 pairs of persons with dementia and their caregivers selected from four geriatric long-term care facilities located in S city, G province, Korea. Data analysis included descriptive statistics, inverse normal transformations, Pearson correlation coefficients, Spearman's correlation coefficients and hierarchical multiple regression with the SPSS Statistics 22.0 for Windows program. Results: Mean score for BPSD was 40.16. Depression (${\beta}=.42$, p<.001), exposure to noise in the evening noise (${\beta}=-.20$, p=.014), and gender (${\beta}=.17$, p=.042) were factors predicting BPSD in long-term care facilities, which explained 25.2% of the variance in the model. Conclusion: To decrease BPSD in persons with dementia, integrated nursing interventions should consider factors of the patient, caregiver, and environment.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.21 no.4
• /
• pp.291-298
• /
• 2011

According to the developments of automobile industry, the technology to enhance noise, vibration and harshness(NVH) performance has been studying in a point of view of ride comfort and quietness. Especially the use of computer aided engineering(CAE) simulation tools such as finite element(FE) analysis allows engineers to efficiently evaluate NVH performance. This paper presents the method to bulid FE models for full vehicle including engine, transmission. suspension and steering system, also to evaluate vibration performance of full vehicle. The full vehicle model, which is discussed, is correlated with the result of the frequency response measurement in the case of the car shake performance for high speed driving.

• Journal of KSNVE
• /
• v.10 no.6
• /
• pp.1009-1016
• /
• 2000

This paper describes the procedure of increasing the efficiency of experimental modal analysis and updating the quality of FE model using the scaled commercial vehicle frame. In this study, it was found that the experimental modal analysis could be more efficient when the measurements were made on the areas with high kinetic energies. Such areas could be located with the aid of FE modal analysis. Also, the number of measurement points could be decided by considering the dynamic characteristics of full FE model. The correlation of FE model and experimental modal analysis was assessed by the differences between the natural frequencies and MAC matrix, which is based on normal modes. These differences of modal parameters were reduced through the sensitivity and optimization analysis of which objective function consisted of the errors of natural frequencies and the diagonal terms of MAC matrix.

• Journal of the Korean Statistical Society
• /
• v.31 no.2
• /
• pp.199-212
• /
• 2002

This article introduces transfer function model (TFM) with conditional heteroscedasticity where ARCH concept is built into the traditional TFM of Box and Jenkins (1976). Model building strategies such as identification, estimation and diagnostics of the model are discussed and are illustrated via empirical study including simulated data and real data as well. Comparisons with the classical TFM are also made.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2011.10a
• /
• pp.191-195
• /
• 2011

The airframe ground vibration tests were conducted on the KC-100 aircraft according to the regulation requirement, KAS 23.629(a)(2) and the modal characteristics for the target modes were measured. To make FE model tuning, a design sensitivity approach with engineering judgment was implemented using MSC/Nastran and Attune, a genetic algorithm based parameter optimization software. Based on the comparison between initial prediction and test results, design variables such as beam cross-sectional properties and spring stiffnesses were devised. As the results, the correlation of the FE model to the GVT results was made appropriately, meeting the goal of matching the target frequencies within 5%.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10b
• /
• pp.164-169
• /
• 1992

Classical methods for estimating transfer function models have not always been successful. A statistic approach to the identification of transfer function models which is corrupted by disturbances or noise is presented. The estimated impulse response is obtained from the autocorrelation function and cross correlation function between the measured input and output. Several data analysis tools such as R- , S- and GPAC array for the estimated impulse response give us pretty clear information on the order of transfer function models.

• Journal of Internet of Things and Convergence
• /
• v.8 no.2
• /
• pp.79-84
• /
• 2022

This paper presents an enhancement method of document restoration capability which is robust for security, loss, and contamination, It is based on two methods, that is, encryption and DnCNN(DeNoise Convolution Neural Network). In order to implement this encryption method, a mathematical model is applied as a spatial frequency transfer function used in optics of 2D image information. Then a method is proposed with optical interference patterns as encryption using spatial frequency transfer functions and using mathematical variables of spatial frequency transfer functions as ciphers. In addition, by applying the DnCNN method which is bsed on deep learning technique, the restoration capability is enhanced by removing noise. With an experimental evaluation, with 65% information loss, by applying Pre-Training DnCNN Deep Learning, the peak signal-to-noise ratio (PSNR) shows 11% or more superior in compared to that of the spatial frequency transfer function only. In addition, it is confirmed that the characteristic of CC(Correlation Coefficient) is enhanced by 16% or more.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.22 no.7
• /
• pp.605-618
• /
• 2012

In this study, the possibility of decision error is investigated to identify and improve the reliability of participants in the process of conducting the sound quality analysis for laser printers. So far, there is not a way to identify and express the possibility of individual participant quantitatively. Thus, the decision error model is proposed which is based on the expectation value between the perceived sounds. Through the experimental verification on the laser printers, it was found that the possibility of decision error is affected according to the normalized difference. The possibility of decision error has inversely proportional to the normalized difference between the perceived sounds. When the normalized difference becomes small value, the uncertainly between decisions is inversely increase, and then it is difficult to obtain the proper result in the process of the jury evaluation for laser printers. For this reason, in this study, the proposed decision error model is added in the previous step of the correlation verification. Comparing to the conventional process only using the correlation based method, after the reliability of each participant is verified, the correlation with the mean response of participants is verified. It was found that the participants who were recognized as having unusual preferences are actually identified as having the reliability problem. Based on the results of this study, the proposed decision error model will be helpful to identify and improve the reliability of participants in the following study for the sound quality analysis.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.24 no.3
• /
• pp.253-260
• /
• 2014

conducted. In-situ measurements were conducted to investigate the noise characteristics in high-speed trains such as KTX and KTX-Sancheon. Binaural microphones and spherical microphone were adopted to record and evaluate the spectral characteristics and noise incidence characteristics at the seats in the passenger cars. Environmental elements were also recorded during the noise measurements using a camcorder and GPS application. In addition, auditory tests were conducted to investigate annoyance of interior noise of high-speed trains. Based on the objective measure and subjective responses on interior noise, statistical analysis such as correlation and regression analyses were carried out. From the results perception models for evaluating the interior noise of high-speed train were derived.

• Journal of information and communication convergence engineering
• /
• v.16 no.1
• /
• pp.38-42
• /
• 2018

In this paper, we consider measurement allocation problem in a spatially correlated sensor field. Our goal is to determine the probability of each sensor's being measured based on its contribution to the estimation reliability; it is desirable that a sensor improving the estimation reliability is measured more frequently. We consider a spatial correlation model of a sensor field reflecting transmission power limit, noise in measurement and transmission channel, and channel attenuation. Then the estimation reliability is defined distortion error between event source and its estimation at sink. Motivated by the correlation nature, we model the measurement allocation problem into a cooperative game, and then quantify each sensor's contribution using Shapley value. Against the intractability in the computation of exact Shapley value, we deploy a randomized method that enables to compute the approximate Shapley value within a reasonable time. Besides, we envisage a measurement scheduling achieving the balance between network lifetime and estimation reliability.