• Journal of the Ergonomics Society of Korea
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• v.33 no.5
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• pp.407-422
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• 2014

Objective: The purpose of the study is to develop quantitative usability evaluation criteria for senior-friendly autonomous transportation robot. Background: The Republic of Korea has become the most rapidly aging society, and is anticipated to enter the post-aged society in 2026. To raise the quality of life of a senior with limited mobility and to reduce the burden of caregivers, many high-tech assistive products with information technologies are developed nowadays. The senior-friendly autonomous transportation robot is one person robot vehicle to move a senior to the destination for hospitals, nursing homes or silver town complex. With built-in navigation system and environmental monitoring censors, it automatically seeks the path to the destination and avoids collision to obstacles and pedestrians on the way. Due to the early stage of the product, few usability studies in this field have been done, mostly on general service robots to assist seniors, power wheelchairs and delivery robots. ISO and KS standards for the service robots are focused on safety. Method: Based on the reference usability index, the early draft of the usability evaluation questionnaires was developed. After small group tests and interviews, the experts modified the initial draft to the Usability Evaluation Criteria for Senior-Friendly Autonomous Transportation Robot (UEC-SFATR). Result: UEC-SFATR consisted of 4 subscales - Safety, Controllability, Efficiency and Satisfaction. All of the 4 subscales of UEC-SFATR were passed the reliability criteria by 4 groups of seniors, divided by gender and familiarity of smart-devices. Conclusion: UEC-SFATR covers wider area of user experiences of the SFATR and is a good measurement tool to help both the users and developers of the robot. Application: This study provides guide to the future product development and product competitiveness evaluation by quantifying user experiences for the SFATR.

• Steel and Composite Structures
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• v.16 no.1
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• pp.21-44
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• 2014

The aim of this study is to determine the dynamic characteristics of long reinforced concrete highway bridges with post-tension tendons using analytical and experimental methods. It is known that the deck length and height of bridges are affected the dynamic characteristics considerably. For this purpose, Berta Bridge constructed in deep valley, in Artvin, Turkey, is selected as an application. The Bridge has two piers with height of 109.245 m and 85.193 m, and the total length of deck is 340.0 m. Analytical and experimental studies are carried out on Berta Bridge which was built in accordance with the balanced cantilever method. Finite Element Method (FEM) and Operational Modal Analysis (OMA) which considers ambient vibration data were used in analytical and experimental studies, respectively. Finite element model of the bridge is created by using SAP2000 program to obtain analytical dynamic characteristics such as the natural frequencies and mode shapes. The ambient vibration tests are performed using Operational Modal Analysis under wind and human loads. Enhanced Frequency Domain Decomposition (EFDD) and Stochastic Subspace Identification (SSI) methods are used to obtain experimental dynamic characteristics like natural frequencies, mode shapes and damping ratios. At the end of the study, analytical and experimental dynamic characteristic are compared with each other and the finite element model of the bridge was updated considering the material properties and boundary conditions. It is emphasized that Operational Modal Analysis method based on the ambient vibrations can be used safely to determine the dynamic characteristics, to update the finite element models, and to monitor the structural health of long reinforced concrete highway bridges constructed with the balanced cantilever method.

• Journal of the Korean Dietetic Association
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• v.30 no.2
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• pp.140-151
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• 2024

This study evaluated the effectiveness of an obesity program developed to solve 'obesity', which was selected as the top priority for urgent improvement among the dietary problems of elementary school students in Busan. The program aimed to practice four health rules every day (sleep early, eat two vegetables with each meal, reduce sugary snacks, and exercise for 30 minutes every day). The participants were trained to practice the four rules online in real time every day for three weeks, and their performance in nutrition education tasks was monitored using Padlet. The anthropometric measurements showed no change in the overall average weight before and after participating in the program, but all students grew in height (z=-6.978, P<0.001), and the number of obese students decreased significantly (z=-3.317, P<0.001). This obesity program was effective in improving height growth and obesity in elementary school students. In terms of dietary changes, after participating in the program, the frequency of vegetable consumption increased significantly (z=-4.849, P<0.001), the frequency of sweet snack consumption decreased significantly (z=-4.298, P<0.001), and the bedtime improved (z=-1.000). Therefore, the non-face-to-face, self-directed obesity program developed in this study is expected to reduce the workload of nutrition teachers carrying a heavy workload such as meal service and nutrition classes, and can be used as an efficient nutrition counseling program.

• Journal of Environmental Health Sciences
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• v.50 no.2
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• pp.125-137
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• 2024

Background: The Korea Risk Information Surveillance System (K-RISS) was developed to enable the early detection of food and drug safety-related issues. Its goal is to deliver real-time risk indicators generated from ongoing food and drug risk monitoring. However, the existing K-RISS system suffers under several limitations. Objectives: This study aims to augment K-RISS with more detailed indicators and establish a severity standard that takes into account structural changes in the daily time series of K-RISS values. Methods: First, a Delphi survey was conducted to derive the required weights. Second, a control chart, commonly used in statistical process controls, was utilized to detect outliers and establish caution, attention, and serious levels for K-RISS values. Furthermore, Bai and Perron's method was employed to determine structural changes in K-RISS time series. Results: The study incorporated 'closeness to life' and 'sustainability' indicators into K-RISS. It obtained the necessary weights through a survey of experts for integrating variables, combining indicators by data source, and aggregating sub K-RISS values. We defined caution, attention, and serious levels for both average and maximum values of daily K-RISS. Furthermore, when structural changes were detected, leading to significant variations in daily K-RISS values according to different periods, the study systematically verified these changes and derived respective severity levels for each period. Conclusions: This study enhances the existing K-RISS system and introduces more advanced indicators. K-RISS is now more comprehensively equipped to serve as a risk warning index. The study has paved the way for an objective determination of whether the food safety risk index surpasses predefined thresholds through the application of severity levels.

• The Korean Journal of Nuclear Medicine
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• v.38 no.1
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• pp.62-73
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• 2004

Purpose: The herpes simplex virus type 1 thymidine kinase gene(HSV1-tk) is an attractive candidate as a reporter gene in noninvasive reporter gene monitoring system. The HSV1-tk gene was chosen as a reporter gene, because it has been extensively studied, and there are appropriate reporter probes, substrates of HSV1-tk gene product, to apply for HSV1-tk gene imaging. We used radiolabeled 5-iodovinyl-2'-deoxyuridine (IVDU) and 5-iodovinyl-2'-fluoro-2'-deoxyuridine (IVFRU) as reporter probes for HSV1-tk gene monitoring system. Materials and Methods: We prepared HSV1-tk gene transduced Morris hepatoma cell line using retroviral vector, MOLTEN containing HSV1-tk gene. And we confirmed the HSV1-tk gene expression by Northern blotting and Western blotting. We compared in vitro uptakes of radioiodinated IVDU and IVFRU to monitor HSV1-tk gene expression in Morris hepatoma cell line (MCA) and HSV1-tk gene tranduced MCA (MCA-tk) cells until 480 minutes. We also peformed correlation analysis between percentage of HSV1-tk gene tranduced MCA cell % (MCA-tk%) and uptakes of radiolabeled IVDU or IVFRU. Results: MCA-tk cell expressed HSV1-tk mRNA and HSV1-TK protein. Two compounds showed minimal uptake in MCA, but increased uptake was observed in MCA-tk. IVDU showed 4-fold higher accumulation than IVFRU at 480 min in MCA-tk (p<0.01). Both IVDU and IVFRU uptake were linearly correlated ($R^2>0.96$) with increasing MCA-tk%. Conclusion: The radiolabeld IVDU and IVFRU showed higher specific accumulation in retrovirally HSV1-tk gene transfected Morris hepatoma cell line. Both IVDU and IVFRU could be used as good substrates for evaluation of HSV1-tk gene expression.

• Environmental Analysis Health and Toxicology
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• v.20 no.4 s.51
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• pp.311-325
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• 2005

A chemical ranking and scoring system, CRS - Korea, has recently been developed and proposed to use to prioritize on a screening level the toxic chemicals for monitoring and risk assessment. As CRS-Korea requires rigorous assessments prior to its wide application, an assessment was conducted in this study by examining the contribution of individual parameter score to the final chemical score or ranking. The sensitivity of the system to the default values for various parameters of missing data was also tested. The chemical ranking/score was round to depend primarily on the score of a single parameter, i. e., the chemical release, while toxicity scores show little correlation with the priority Further analysis indicated that the dominating effect of the chemical release results from i) its multiplicative relationship with the other two exposure parameters (biodegradation and persistent) and ii) the fact that a maximum score of 10 was assigned to the chemical release parameter while 5 was assigned for all others. AE the fraction of the data that are missing exceeded $70\%$ for various toxicity parameters at compared to less than $10\%$ for exposure parameters, the sensitivity of the ranking to the default value was not significant (rank correlation coefficient = 0.98) for toxicity parameters. Bated on this assessment, an improved CRS system (CRS - Korea II) was proposed in which the impact of the chemical release was properly adjusted by changing the multiplicative relationship to additive one and the maximum score to 5. Chemical priority was derived for each of 16 provinces by using CRS-Korea II. The chemical priority was found to significantly vary among the provinces. It was concluded that not only the national chemical priority but the local chemical priority should be taken into account in setting the nationwide chemical monitoring and risk assessment strategy.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.95-104
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• 2020

In this paper, we propose the real time indoor air quality monitoring and controlling platform on cloud using IoT sensor data such as PM10, PM2.5, CO2, VOCs, temperature, and humidity which has direct or indirect impact to indoor air quality. The system is connected to air ventilator to manage and optimize the indoor air quality. The proposed system has three main parts; First, IoT data collection service to measure, and collect indoor air quality in real time from IoT sensor network, Second, Big data processing pipeline to process and store the collected data on cloud platform and Finally, Big data analysis and visualization service to give real time insight of indoor air quality on mobile and web application. For the implication of the proposed system, IoT sensor kits are installed on three different public day care center where the indoor pollution can cause serious impact to the health and education of growing kids. Analyzed results are visualized on mobile and web application. The impact of ventilation system to indoor air quality is tested statistically and the result shows the proper optimization of indoor air quality.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.5
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• pp.436-441
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• 2009

A fiber optic sensor is prospective to be applied to structural health monitoring. Especially, a fiber Bragg grating(FBG) sensor is one of the most popular sensors for the structural health monitoring. The FBG sensor has several demodulation systems for tracking the shift of the Bragg wavelength. The dynamic bandwidth is dependent on the demodulation system. In this paper, the sensing mechanism is that the slope of the optical spectrum of FBG could be used as its sensitivity when the tunable laser shot the monochromatic laser wavelength at the highest slope point. In this technique, the high sensitivity is guaranteed even though the sensing range is limited. In an example of the application, the composite plate embedding a FBG sensor was manufactured by using an autoclave method and the above sensing mechanism was applied to the composite plate. Firstly, the natural frequencies of the plate were successfully measured by the FBG sensor during the impact hammer test. Secondly, a high-power speaker was used to force the plate to be vibrated at the specific frequency that was one of the natural frequencies. During the shaking, the FBG sensor measures the dynamic characteristics and ESPI was also used to measure the mode shape. From the two dynamic tests, the availability of the FBG sensor system and the ESPI was proven as a technique for measuring the dynamic characteristics of composite structure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.611-617
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• 2018

The application of health monitoring, including a fault detection technique, is needed to secure the structural safety of large structures. A 2-step crack identification method for detecting the crack location and size of the beam structure is presented. First, a crack occurrence region was estimated using the modified Laplacian operator for the strain mode shape obtained from the distributed local strain data. The crack location and size were then identified based on the natural frequencies obtained from the acceleration data and the neural network technique for the pre-estimated crack occurrence region. The natural frequencies of a cracked beam were calculated based on an equivalent bending stiffness induced by the energy method, and used to generate the training patterns of the neural network. An experimental study was carried out on an aluminum cantilever beam to verify the present method for crack identification. Cracks were produced on the beam, and free vibration tests were performed. A crack occurrence region was estimated using the modified Laplacian operator for the strain mode shape, and the crack location and size were assessed using the natural frequencies and neural network technique. The identified crack occurrence region agrees well with the exact one, and the accuracy of the estimation results for the crack location and size could be enhanced considerably for 3 damage cases. The presented method could be applied effectively to the structural health monitoring of large structures.

• Structural Monitoring and Maintenance
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• v.2 no.1
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• pp.77-93
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• 2015

The idea of using measured dynamic characteristics for damage detection is attractive because it allows for a global evaluation of the structural health and condition. However, vibration-based damage detection for complex structures such as long-span cable-supported bridges still remains a challenge. As a suspension or cable-stayed bridge involves in general thousands of structural components, the conventional damage detection methods based on model updating and/or parameter identification might result in ill-conditioning and non-uniqueness in the solution of inverse problems. Alternatively, methods that utilize, to the utmost extent, information from forward problems and avoid direct solution to inverse problems would be more suitable for vibration-based damage detection of long-span cable-supported bridges. The auto-associative neural network (ANN) technique and the probabilistic neural network (PNN) technique, that both eschew inverse problems, have been proposed for identifying and locating damage in suspension and cable-stayed bridges. Without the help of a structural model, ANNs with appropriate configuration can be trained using only the measured modal frequencies from healthy structure under varying environmental conditions, and a new set of modal frequency data acquired from an unknown state of the structure is then fed into the trained ANNs for damage presence identification. With the help of a structural model, PNNs can be configured using the relative changes of modal frequencies before and after damage by assuming damage at different locations, and then the measured modal frequencies from the structure can be presented to locate the damage. However, such formulated ANNs and PNNs may still be incompetent to identify damage occurring at the deck members of a cable-supported bridge because of very low modal sensitivity to the damage. The present study endeavors to enhance the damage identification capability of ANNs and PNNs when being applied for identification of damage incurred at deck members. Effort is first made to construct combined modal parameters which are synthesized from measured modal frequencies and modal shape components to train ANNs for damage alarming. With the purpose of improving identification accuracy, effort is then made to configure PNNs for damage localization by adapting the smoothing parameter in the Bayesian classifier to different values for different pattern classes. The performance of the ANNs with their input being modal frequencies and the combined modal parameters respectively and the PNNs with constant and adaptive smoothing parameters respectively is evaluated through simulation studies of identifying damage inflicted on different deck members of the double-deck suspension Tsing Ma Bridge.