• Journal of muscle and joint health
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• v.8 no.1
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• pp.5-26
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• 2001

Many studies have reported that regular aquatic exercise can lead to improvement of health for patients suffering from arthritis. In spite of these benefits, the adherence rate has shown as few as 26% of patients with arthritis who had completed the aquatic exercise education program. Moreover, when patients with arthritis begin an aquatic exercise, 47% withdraw within the first 6 month. No study has been found that constructs model to explain aquatic exercise adherence of patients with arthritis. The purpose of this study were to identify the factors influencing exercise adherence and to construct and test a structural model to explain aquatic exercise adherence of patients with arthritis. Hypothesized model was constructed on the basis of Bandura's social cognitive theory and literature review. Exogenous latent variables included in this model are group cohesion and barrier, endogenous latent variables are self-efficacy, outcome expectancy and self-evaluation. Empirical data used was collected through individual interviews with the structural questionnaire on 249 patients with arthritis who had completed the 6-week aquatic exercise education program of Korean Rheumatology Health Professionals Academy. The interviews were performed from September 6, 1999 through October 8, 1999. A model tested by the covariance structural analysis with LISREL 8.12a program and by descriptive statistics and correlation with SAS 6.12 program. The results are summarized as follows: First, hypothesized model showed a good fit to the empirical data. In the modified model added one new path showed a much better fit. Second, group cohesion had a direct, indirect positive effects, self-efficacy and self evaluation had a direct positive effects on exercise adherence. Barrier had a direct, indirect negative effects on exercise adherence. Outcome expectancy had a direct negative effect, indirect positive effects through self-evaluation on exercise adherence, but total effects was not significant. Total effect size of the variables were group cohesion, self-efficacy, barrier and self evaluation in order. All variables accounted for 54% of the total variance of exercise adherence in the model. In conclusion, this model confirmed to be proper in explaining of aquatic exercise adherence. Group cohesion, self-efficacy, outcome expectancy, self-evaluation, barrier contributed to the aquatic exercise adherence of patients with arthritis. The results of this study suggested that improvement of group cohesion, self-efficacy and self-evaluation, motivation of outcome expectancy through self-evaluation, and reduction of the barrier should be included in the strategy of nursing intervention for the aquatic exercise adherence of patients with arthritis.

• Journal of Korean Society of Rural Planning
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• v.5 no.2 s.10
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• pp.56-65
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• 1999

Recently, new concept and paradigm of 'Environmentally-Friendliness' is taking a growing interest in environmental planning and design. This study is to establish the evaluation model for environmentally-friendliness of 'Tourism Farms' in rural areas by LISREL structural equation model. A questionnaire survey was conducted for deputy manager group and expert group. As the Result of LISREL structural equation model, the environmentally-friendliness of tourism farms is composed of three categories. First, conservation of global environment (Low Impact), second, friendliness to surrounding nature(High Contact), and third, environmental health and amenities (Health & Amenity). Five indicators, such as (1)saving of energy and water resource, (2)reduction and reuse of garbage, (3)natural purification of sewage disposal, (4)utilization of natural energy, (5)campaign and education programs of environmentally-friendliness, were affecting the first category, i.e., conservation of global environment(Low Impact). Friendliness to surrounding nature (High Contact) is affected by 3 indicators, (1)contact to nature and diverse green areas, (2)water intimate & contact areas, (3)natural ecology observation by biotope. Finally, the dimension of environmental health and amenity is affected by 3 indicators, (1)nature affinity by farming experience, (2)environmental-friendliness of soil & crops by organic farming, (3) campaign and education programs of environmentally-friendliness. Total coefficient of determination of the structural equation model by LISREL was 0.897, which showed high explanatory power.

• Structural Engineering and Mechanics
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• v.46 no.3
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• pp.433-445
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• 2013

Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.

• Structural Monitoring and Maintenance
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• v.3 no.1
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• pp.51-69
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• 2016

Monitoring the performance and estimating the remaining useful life of aging civil infrastructure in the United States has been identified as a major objective in the civil engineering community. Structural health monitoring has emerged as a central tool to fulfill this objective. This paper presents a review of the major structural monitoring programs that have been recently implemented in the United States, focusing on the integrity and performance assessment of large-scale structural systems. Applications where response data from a monitoring program have been used to detect and correct structural deficiencies are highlighted. These applications include (but are not limited to): i) Post-earthquake damage assessment of buildings and bridges; ii) Monitoring of cables vibration in cable-stayed bridges; iii) Evaluation of the effectiveness of technologies for retrofit and seismic protection, such as base isolation systems; and iv) Structural damage assessment of bridges after impact loads resulting from ship collisions. These and many other applications show that a structural health monitoring program is a powerful tool for structural damage and condition assessment, that can be used as part of a comprehensive decision-making process about possible actions that can be undertaken in a large-scale civil infrastructure system after potentially damaging events.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.439-459
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• 2010

Structural health monitoring (SHM) of civil infrastructure using wireless smart sensor networks (WSSNs) has received significant public attention in recent years. The benefits of WSSNs are that they are low-cost, easy to install, and provide effective data management via on-board computation. This paper reports on the deployment and evaluation of a state-of-the-art WSSN on the new Jindo Bridge, a cable-stayed bridge in South Korea with a 344-m main span and two 70-m side spans. The central components of the WSSN deployment are the Imote2 smart sensor platforms, a custom-designed multimetric sensor boards, base stations, and software provided by the Illinois Structural Health Monitoring Project (ISHMP) Services Toolsuite. In total, 70 sensor nodes and two base stations have been deployed to monitor the bridge using an autonomous SHM application with excessive wind and vibration triggering the system to initiate monitoring. Additionally, the performance of the system is evaluated in terms of hardware durability, software stability, power consumption and energy harvesting capabilities. The Jindo Bridge SHM system constitutes the largest deployment of wireless smart sensors for civil infrastructure monitoring to date. This deployment demonstrates the strong potential of WSSNs for monitoring of large scale civil infrastructure.

• Journal of Korean Academy of Nursing Administration
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• v.6 no.2
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• pp.291-298
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• 2000

Objective : Use of Internet for health related information is rapidly increasing. There is, however, no consensus as to which information is correct and reliable. This study was conducted to develop an evaluation standards for health related information on the Internet for the purpose of delivering correct information to internet users. Methods : A Delphi technique, which involved a panel of 65 experts, was used as the research design for this study. In the first round, the initial evaluation criteria which consisted of 12 items was developed through a literature review by the researcher and the items represented 2 categories, structure and function. In the second round, a semi-structured questionnaire was sent to the experts with the initial evaluation tool and the respondents identified 55 items. In the third round, these 55 items were analyzed for content validity by the experts and a total of 35 items were included in the model; 11 items in the structural area, 24 in the functional area. Conclusions : Development of indicators for the evaluation of internet site for health information is crucial to provide correct and reliable information. For evaluation to be effective further evaluation programs need to be developed so that users can be sure that the information they received is accurate.

• Smart Structures and Systems
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• v.5 no.4
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• pp.381-395
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• 2009

The paper presents a case study in which the structural condition assessment of the East Bay bridge in Gibsonton, Florida is evaluated with the help of remote health monitoring techniques. The bridge is a four-span, continuous, deck-type reinforced concrete structure supported on prestressed pile bents, and is instrumented with smart Fiber Optic Sensors. The sensors used for remote health monitoring are the newly emerged Fabry-Perot (FP), and are both surface-mounted and embedded in the deck. The sensing system can be accessed remotely through fast Digital Subscriber Lines (DSL), which permits the evaluation of the bridge behavior under live traffic loads. The bridge was open to traffic since March 2005, and the collected structural data have been continuously analyzed since. The data revealed an increase in strain readings, which suggests a progression in damage. Recent visual observations also indicated the presence of longitudinal cracks along the bridge length. After the formation of these cracks, the sensors readings were analyzed and used to extrapolate the values of the maximum stresses at the crack location. The data obtained were also compared to initial design values of the bridge under factored gravity and live loads. The study showed that the proposed structural health monitoring technique proved to provide an efficient mean for condition assessment of bridge structures providing it is implemented and analyzed with care.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1031-1053
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• 2016

The health conditions of in-service civil infrastructures can be evaluated by employing structural health monitoring technology. A reliable health evaluation result depends heavily on the quality of the data collected from the structural monitoring sensor network. Hence, the problem of sensor fault diagnosis has gained considerable attention in recent years. In this paper, an innovative sensor fault diagnosis method that focuses on fault detection and isolation stages has been proposed. The dynamic or auto-regressive characteristic is firstly utilized to build a multivariable statistical model that measures the correlations of the currently collected structural responses and the future possible ones in combination with the canonical correlation analysis. Two different fault detection statistics are then defined based on the above multivariable statistical model for deciding whether a fault or failure occurred in the sensor network. After that, two corresponding fault isolation indices are deduced through the contribution analysis methodology to identify the faulty sensor. Case studies, using a benchmark structure developed for bridge health monitoring, are considered in the research and demonstrate the superiority of the new proposed sensor fault diagnosis method over the traditional principal component analysis-based and the dynamic principal component analysis-based methods.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.6
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• pp.483-500
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• 2007

Emerging sensor-based structural health monitoring (SHM) technology can play an important role in inspecting and securing the safety of aging civil infrastructure, a worldwide problem. However, implementation of SHM in civil infrastructure faces a significant challenge due to the lack of suitable sensors and reliable methods for interpreting sensor data. This paper reviews recent efforts and advances made in addressing this challenge, with example sensor hardware and software developed in the author's research center. It is proposed to integrate real-time continuous monitoring using on structure sensors for global structural integrity evaluation with targeted NDE inspection for local damage assessment.

• Health Policy and Management
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• v.9 no.4
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• pp.87-119
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• 1999

The main purpose of this research is to measure and analyze how productive the health centers are and how much inputs(or outputs) in the inefficient health centers should be decreased(or increased) for efficiency. The evaluation of the performance of health centers gives a strong incentive to improve resource allocation in regional health planning. It has been, however, implemented very rarely until now. In this regard, this paper measures the performance of the health centers with a single indicator for multiple-outputs in terms of productivity(technical efficiency), based on Data Envelopment method. The 20 Kyungnam health centers which provide clinic services and specific primary health care services were analyzed. The results show that 50.0% of 20 health centers were productive with respective to overall technical efficiency, 65.0% were productive for pure technical efficiency, and 50.0% for scale efficiency. The inefficient group includes Geoje, Mahsan, Miryang, Sahchun, Tongyoung, Gosung, Nahmhae, Euryang, Hahmahn, Hahbchun health centers. The worst case was identified as Tongyoung health center which represented a 47.5% efficiency, compared with productive health centers. The empirical results for input-output analysis indicates that the low-productive health centers have excessive manpower in administration department, producing low outputs in clinical services and vaccination program. These findings imply that a systemic evaluation of the performance of the Korean health centers and the subsequent structural reform are strongly required.