• Steel and Composite Structures
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• v.21 no.6
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• pp.1183-1210
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• 2016

Viscoelastic sandwich structures (VSSs) are widely used in mechanical equipment, but in the service process, they always suffer from aging which affect the whole performance of equipment. Therefore, aging state recognition of VSSs is significant to monitor structural state and ensure the reliability of equipment. However, non-stationary vibration response signals and weak state change characteristics make this task challenging. This paper proposes a novel method for this task based on adaptive second generation wavelet packet transform (ASGWPT) and multiwavelet support vector machine (MWSVM). For obtaining sensitive feature parameters to different structural aging states, the ASGWPT, its wavelet function can adaptively match the frequency spectrum characteristics of inspected vibration response signal, is developed to process the vibration response signals for energy feature extraction. With the aim to improve the classification performance of SVM, based on the kernel method of SVM and multiwavelet theory, multiwavelet kernel functions are constructed, and then MWSVM is developed to classify the different aging states. In order to demonstrate the effectiveness of the proposed method, different aging states of a VSS are created through the hot oxygen accelerated aging of viscoelastic material. The application results show that the proposed method can accurately and automatically recognize the different structural aging states and act as a promising approach to aging state recognition of VSSs. Furthermore, the capability of ASGWPT in processing the vibration response signals for feature extraction is validated by the comparisons with conventional second generation wavelet packet transform, and the performance of MWSVM in classifying the structural aging states is validated by the comparisons with traditional wavelet support vector machine.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.11 no.11
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• pp.1035-1042
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• 1998

After the 1990's, a computer-aided partial discharge(PD) measurement system was referred in part of aging diagnosis using digital signal processing as the new technology has been studied. The PD patterns and relevant information for pattern recognition are discussed in PD research area, because discharge quantity(q), the number of discharge pulse(n) and the applied boltage phase($\varphi$) was combined with the system information of the aging state. This paper investigates the discharge phase and quantity, as well as the number of discharge(n) with regard to discharge signals generated in power cable. therefore, according to characteristic analysis on the distribution of $\varphi$, q and n, it is able to apply in the aging analysis of power cable which visual observation is impossible and distribution change of discharge signals offers much information for risk degree on aging progress of insulation materials.

• Proceedings of the KIEE Conference
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• 2003.07c
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• pp.1726-1728
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• 2003

The aging diagnosis method using partial discharge measurement detects discharge signals that critical cause of failure in insulation material operated a long time and can diagnose aging state of insulation materials with an aging analysis algorithm. The HFPD measurement method is a technique to analyze aging state of high voltage insulation materials and detect higher frequency signals than conventional PD measurement method therefore it takes less noise effect and could execute active line measurement. It is possible to analyze main discharge phenomena and obtain access to aging progress occurred in insulation materials through accumulation of HFPD signals during determined interval and expression of fractal dimension using statistical process of accumulated signals. The HFPD signals that occurred in each applied voltages are measured during 180 cycles and accumulated to the same phase of one cycle. These patterns that made by previous method are normalized with logarithm function and than inputted to neural networks. The aging diagnosis of insulation material was possible and the recognition ratio of neural network appeared very high.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.7
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• pp.1380-1385
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• 2009

This paper was studied about the aging judgment method by ultraviolet rays image to happen in electric power equipment using ultraviolet rays camera. We established the aging judgment method as follows; 20% within of risk factor of insulation state of electrical facility that ultraviolet rays image does not show is "good or recognition". 30$^{\sim}$50% within of risk factor is "check", 50$^{\sim}$60% within of risk factor is "inspection" and 60% above of risk factor is "replacement". This method will be utilized for the inspection about electrical facilities.

• Proceedings of the KIEE Conference
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• 2002.07c
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• pp.1698-1700
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• 2002

Recently, the HFPD measurement methods that detect high frequency bandwidth of frequency components of partial discharge pulses are proposed and many studies are carried out. The HFPD measurement method is able to detect partial discharge signal in active line, therefore this method has a merit that can does condition monitoring of power equipments and measure growth state of partial discharge erosion with on-line and real time. In this study, the radiated HFPD signals are detected by antenna and aging diagnosis is executed with a neural network algorithm. As a result of this study, the aging diagnosis of insulation material using neural networks is possible.

• Proceedings of the KIEE Conference
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• 2004.11a
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• pp.251-254
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• 2004

The aging diagnosis technique using partial discharge detection method detects partial discharge signals cause of power equipment failuer and able to forecast the aging state of insulation system through analysis algorithm, in this paper accumulates HFPD signal during constant scheduled cycles to build HFPD pattern and then analyzes HFPD pattern using statistical parameters and ${\Delta}F$ pattern. The 3D pattern is composed of detected signal frequency, amplitude and repeated number and the FRPDA(frequency resolved partial discharge analysis) technique is used in 3D pattern construction. The ${\Delta}F$ pattern shows variation characteristics of amplitude gradient of consecutive HFPD signal Pulses and able to classify discharge types-internal discharge, surface discharge and coronal discharge etc. Fractal mathematics applied to ${\Delta}F$ pattern quantification and neural networks is used in aging diagnostic algorithm.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.61-69
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• 2017

The purpose of this study is to suggest a foundational design direction for seniors, according to paradigm shift in aging society. This paper researched on current state of the aging society through literature study and defined the theoretical concept that set the foundation of the study. Secondly, for building an age-friendly city, relevant studies on seven cities were selected and their regional design guidelines were analyzed. As a result, essential design elements for building the aging-friendly city were defined as safety, recognition, and accessibility. A detailed design guideline that applies the three elements with understanding on seniors is required to construct the environment for a senior-friendly city. Ultimately, the result of this study is expected to be in practical use as a fundamental resource for age-friendly city design.

• Korean Journal of Pharmacognosy
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• v.51 no.4
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• pp.310-316
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• 2020

Kyung-Ok-Go (KOK) is a traditional prescription used for debilitating natural aging and post-illness debilitation. KOK has been used in a variety of ways because it strengthens immunity, prevents illness, and helps recovery in case of illness. In particular, recent research has revealed that KOK helps improve memory and cognition. Therefore, in this study, we investigated whether KOK was effective in improving memory decline and depression-state observed during menopause. In the present study, we employed ovariectomized mouse as an animal model for measuring menopausal syndrome. The administration of KOK for 8 weeks, the object recognition memory and working memory were improved in novel object recognition test and Y-maze test. And in the forced swimming test, the immobility time were decreased. Additionally, the expression level of mature brain derived neurotropic factor (mBDNF) was increased by KOK administration in ovariectomized mouse hippocampus. These results suggested that KOK could improve cognitive decline and depression during menopausal period, and it might be come from enhancing expression level of mBDNF in hippocampus.

• International Journal of Contents
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• v.16 no.1
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• pp.75-86
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• 2020

As the elderly population is becoming an aging society, the elderly are experiencing many problems. Social security costs for the elderly are increasing and the un-linked social phenomenon is emerging. Thus, the social infrastructure and welfare system established in the past economic growth period are in danger of not functioning properly. People socially isolated or with chronic diseases among the elderly are exposed to various accidents. Thus, an active healthcare management service is imperative. Additionally, in the event of a dangerous situation, the system must have ways to notify guardians (family or medical personnel) regarding appropriate action. Thus, in this paper, we propose the smartphone-based healthcare and emergency response service platform. The proposed service platform aggregates movement of relevant data in real-time using a smartphone. Based on aggregated data, it will always recognize the user's movements and current state using the human motion recognition mechanism. Thus, the proposed service platform provides real-time status monitoring, activity reports, a health calendar, location-based hospital information, emergency situation detection, and cloud messaging server-based efficient notification to several subscribers such as family, guardians, and medical personnel. Through this service, users or guardians can augment the level of care for the elderly through the reports. Also, if an emergency situation is detected, the system immediately informs guardians so as to minimize the risk through immediate response.

• Physical Therapy Korea
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• v.30 no.4
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• pp.306-313
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• 2023

Background: As social problems due to the acceleration of the aging era and the increase in the elderly population are becoming serious, virtual reality (VR)-based healthcare is emerging as an approach for preventing and managing health issues. Objects: This study used validity and reliability analyses to examine the clinical efficacy that is, the clinical value and usability of a novel VR cognitive evaluation system index that we developed. Methods: We developed a VR cognitive evaluation system based on motion recognition analysis evaluation for individuals aged 65 to 85. After conducting the Korean version of the Mini-Mental State Exam (K-MMSE) cognitive evaluation, the evaluation score was verified through correlation analysis in the VR cognitive evaluation system. To verify the construct validity of the two groups, the Global Deterioration Scale (GDS) grades were categorized into a normal cognitive group (GDS grade 1) and a cognitive impairment group (GDS grades 2 and 3). The data were measured twice to determine the reliability between the two measurements and assess the stability and clinical value of the evaluation system. Results: Our evaluation system had a high correlation of 0.85 with the widely used K-MMSE cognitive evaluation. The system had strong criterion-related validity at the 95% confidence interval. Compared to the average score of GDS grade 1 in the VR cognitive evaluation system, the average score of GDS grades 2 and 3 in the VR cognitive evaluation system was statistically significantly lower while also having strong construct validity at the 95% confidence interval. To measure the reliability of the VR cognitive evaluation system, tests-retests were conducted using the intraclass correlation coefficient (3,1), which equaled 0.923 and was statistically significant. Conclusion: The VR cognitive evaluation system we developed is a valid and reliable clinical tool to distinguish between normal cognitive status and mild cognitive impairment.