• Research in Community and Public Health Nursing
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• v.30 no.1
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• pp.1-10
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• 2019

Purpose: This study tries to analyze the concept of Yangsaeng in the Korean aged, with focus on nursing. Methods: Rodgers' evolutionary approach was used to identify the common definitions, attributes, antecedents, and consequences of the Yangsaeng concept for the aged. Literature search was conducted at the NAL, NDSL, RISS, ProQuest, PubMed, AMED, and MEDLINE databases from 2004 to 2016, using the keywords "Yangsaeng," "health promotion," "health management," "traditional oriental methods," and "traditional oriental nursing."Finally, 20 relevant articles were selected and thoroughly reviewed. Results: The analysis shows that the model of Yangsaeng for the Korean aged is that of personal adaptive-capacity, totality, challenging, and coping resource and includes physical, social and psychological health and wellness. Conclusion: This work provides some implications on the development of nursing intervention related with Yangsaeng for the Korean aged, and suggests the implementation of such intervention in the practice of Yangsaeng for the Korean aged. Therefore, a better understanding of the Korean aged and Yangsaeng within the context of nursing can be achieved.

• International Journal of Advanced Culture Technology
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• v.10 no.3
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• pp.164-173
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• 2022

This study aimed to explore the themes and parameters of environmental health behaviors based on Rogers' protection motivation theory through a systematic mapping review. Using a systematic approach, a literature review was conducted of articles that adopted Rogers' protection motivation theory. A total of 11 articles on protection motivation theory using participants and environmental health as outcomes were identified in a search of CINAHL, Cochrane Library, EMBASE, Eric, PsycARTICLES, PubMed, and RISS between September 1 and September 8, 2021. Themes related to the environment and personal behaviors between 2002 and 2021 were extracted. The parameters based on protection motivation theory were identified through systematic mapping as fear appraisal, rewards of maladaptive response, severity, vulnerability, costs of adaptive response, response efficacy, self-efficacy, and intention. Self-efficacy and response efficacy considerably affected environmental health behaviors. Emotional fear appeal related to environmental hazards motivates an internal process that alters the threat appraisal and their coping appraisal. Environmental behavior perception and intention influenced on environmental health behaviors with small effect sizes. Therefore, a deeper understanding of the severity of environmental health issues could lead to the development of helpful, effective, and intensive interventions to promote healthcare among the vulnerable population.

• Geomechanics and Engineering
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• v.27 no.5
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• pp.511-525
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• 2021

In the design of underground excavation, the shear strength (SS) is a key characteristic. It describes the way the rock material resists the shear stress-induced deformations. In general, the measurement of the parameters related to rock shear strength is done through laboratory experiments, which are costly, damaging, and time-consuming. Add to this the difficulty of preparing core samples of acceptable quality, particularly in case of highly weathered and fractured rock. This study applies rock index test to the indirect measurement of the SS parameters of shale. For this aim, two efficient artificial intelligence methods, namely (1) adaptive neuro-fuzzy inference system (ANFIS) implemented by subtractive clustering method (SCM) and (2) support vector regression (SVR) optimized by Harmony Search (HS) algorithm, are proposed. Note that, it is the first work that predicts the SS parameters of shale through ANFIS-SCM and SVR-HS hybrid models. In modeling processes of ANFIS-SCM and SVR-HS, the results obtained from the rock index tests were set as inputs, while the SS parameters were set as outputs. By reviewing the obtained results, it was found that both ANFIS-SCM and SVR-HS models can provide acceptable predictions for interlocking and friction angle parameters, however, ANFIS-SCM showed a better generalization capability.

• Smart Structures and Systems
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• v.32 no.1
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• pp.61-81
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• 2023

This study presents an ensemble learning based Bayesian model updating approach for structural damage diagnosis. In the developed framework, the structure is initially decomposed into a set of substructures. The autoregressive moving average (ARMAX) model is established first for structural damage localization based structural motion equation. The wavelet packet decomposition is utilized to extract the damage-sensitive node energy in different frequency bands for constructing structural surrogate models. Four methods, including Kriging predictor (KRG), radial basis function neural network (RBFNN), support vector regression (SVR), and multivariate adaptive regression splines (MARS), are selected as candidate structural surrogate models. These models are then resampled by bootstrapping and combined to obtain an ensemble model by probabilistic ensemble. Meanwhile, the maximum entropy principal is adopted to search for new design points for sample space updating, yielding a more robust ensemble model. Through the iterations, a framework of surrogate ensemble learning based model updating with high model construction efficiency and accuracy is proposed. The specificities of the method are discussed and investigated in a case study.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.11
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• pp.63-77
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• 1994

This paper describes the real-time system which, through analyzing a sequence of images, can extract motional information on a moving object and can contol servo equipment to always locate the moving object at the center of an image frame. An image is a vast amount of two-dimensional signal, so it takes a lot of time to analyze the whole quantity of a given image. Especially, the time needed to load pixels from a memory to processor increase exponentially as the size of an image increases. To solve such a problem and track a moving object in real-time, this paper addresses how to selectively search the spatial and time domain. Based on the selective search of spatial and time domain, this paper suggests various types of techniques which are essential in implementing a real-time tracking system. That is, this paper describes how to detect an entrance of a moving object in the field of view of a camera and the direction of the entrance, how to determine the time interval of adjacent images, how to determine nonstationary areas formed by a moving object and calculated velocity and position information of a moving object based on the determined areas, how to control servo equipment to locate the moving object at the center of an image frame, and how to properly adjust time interval(${\Delta}$t) to track an object taking variable speed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.126-134
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• 2017

There have been numerous studies on extracting the R-peak from electrocardiogram (ECG) signals. However, most of the detection methods are complicated to implement in a real-time portable electrocardiograph device and have the disadvantage of requiring a large amount of calculations. R-peak detection requires pre-processing and post-processing related to baseline drift and the removal of noise from the commercial power supply for ECG data. An adaptive filter technique is widely used for R-peak detection, but the R-peak value cannot be detected when the input is lower than a threshold value. Moreover, there is a problem in detecting the P-peak and T-peak values due to the derivation of an erroneous threshold value as a result of noise. We propose a robust R-peak detection algorithm with low complexity and simple computation to solve these problems. The proposed scheme removes the baseline drift in ECG signals using an adaptive filter to solve the problems involved in threshold extraction. We also propose a technique to extract the appropriate threshold value automatically using the minimum and maximum values of the filtered ECG signal. To detect the R-peak from the ECG signal, we propose a threshold neighborhood search technique. Through experiments, we confirmed the improvement of the R-peak detection accuracy of the proposed method and achieved a detection speed that is suitable for a mobile system by reducing the amount of calculation. The experimental results show that the heart rate detection accuracy and sensitivity were very high (about 100%).

• KIISE Transactions on Computing Practices
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• v.20 no.12
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• pp.652-657
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• 2014

Given a starting point, destination point and various Points Of Interest (POIs), which contain a full or partial order, for a user to visit we wish to create, a sequenced route from the starting point to the destination point that includes one member of each POI type in a particular order. This paper proposes a method for finding the approximate shortest route between the start point, destination point and one member of each POI type. There are currently two algorithms that perform this task but they both have weaknesses. One of the algorithms only considers the distance between the visited POI (or starting point) and POI to visit next. The other algorithm chooses candidate points near the straight-line distance between the start point and destination but does not consider the order of visits on the corresponding network path. This paper outlines an algorithm that chooses the candidate points that are nearer to the network path between the start point and destination using network search. The algorithm looks for routes using the candidate points and finds the approximate shortest route by assigning an adaptive priority to the route that visits more POIs in a short amount of time.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.2
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• pp.235-244
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• 2014

This paper describes the subarray channel configuration and calibration method for airborne AESA radar antenna. AESA radar demonstrator was designed and implemented for the digital beam-forming performance test of the 12 channel subarray structure. Magnitude and phase difference can be exist between the manufactured subarray channel. In this paper, calibration method for the subarray difference error was suggested. We measured digital monopulse slope in the subarray channel and verified the channel calibration effect. To verify the subarray channel operation, digital monopulse channel was compared with analog monopulse channel performance. AESA radar demonstrator was tested in the ground far field test range. Emulated single target was generated to test the detection and tracking performance of the demonstrator with the same waveform and search pattern. We verified that the detection and tracking performance of the 12 subarray digital monopulse channel was similar with the conventional analog monopulse channel. Also, ABF(Adaptive Beam-Forming) function for the sidelobe jammer was tested and effective operation was verified.

• Journal of KIISE:Software and Applications
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• v.36 no.2
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• pp.169-177
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• 2009

In this paper, we propose a new shot boundary detection method which is optimized for news video story parsing. This new news shot boundary detection method was designed to satisfy all the following requirements: 1) minimizing the incorrect data in data set for anchor shot detection by improving the recall ratio 2) detecting abrupt cuts and gradual transitions with one single algorithm so as to divide news video into shots with one scan of data set; 3) classifying shots into static or dynamic, therefore, reducing the search space for the subsequent stage of anchor shot detection. The proposed method, based on singular value decomposition with incremental clustering and mercer kernel, has additional desirable features. Applying singular value decomposition, the noise or trivial variations in the video sequence are removed. Therefore, the separability is improved. Mercer kernel improves the possibility of detection of shots which is not separable in input space by mapping data to high dimensional feature space. The experimental results illustrated the superiority of the proposed method with respect to recall criteria and search space reduction for anchor shot detection.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.12
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• pp.85-98
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• 1998

This paper proposes a new design method of neuro-FLC by the Lamarckian co-adaptation scheme that incorporates the backpropagation learning into the GA evolution in an attempt to find optimal design parameters (fuzzy rule base and membership functions) of application-specific FLC. The design parameters are determined by evolution and learning in a way that the evolution performs the global search and makes inter-FLC parameter adjustments in order to obtain both the optimal rule base having high covering value and small number of useful fuzzy rules and the optimal membership functions having small approximation error and good control performance while the learning performs the local search and makes intra-FLC parameter adjustments by interacting each FLC with its environment. The proposed co-adaptive design method produces better approximation ability because it includes the backpropagation learning in every generation of GA evolution, shows better control performance because the used COG defuzzifier computes the crisp value accurately, and requires small workspace because the optimization procedure of fuzzy rule base and membership functions is performed concurrently by an integrated fitness function on the same fuzzy partition. Simulation results show that the Lamarckian co-adapted FLC produces the most superior one among the differently generated FLCs in all aspects such as the number of fuzzy rules, the approximation ability, and the control performance.