• Safety and Health at Work
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• 제7권3호
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• pp.185-193
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• 2016

Background: Management and workers in small and medium-sized enterprises (SMEs) often find it hard to comprehend the requirements related to controlling risks due to exposure to substances. An intervention study was set up in order to support 45 SMEs in improving the management of the risks of occupational exposure to chemicals, and in using the control banding tool and exposure model Stoffenmanager in this process. Methods: A 2-year intervention study was carried out, in which a mix of individual and collective training and support was offered, and baseline and effect measurements were carried out by means of structured interviews, in order to measure progress made. A seven-phase implementation evolutionary ladder was used for this purpose. Success and failure factors were identified by means of company visits and structured interviews. Results: Most companies clearly moved upwards on the implementation evolutionary ladder; 76% of the companies by at least one phase, and 62% by at least two phases. Success and failure factors were described. Conclusion: Active training and coaching helped the participating companies to improve their chemical risk management, and to avoid making mistakes when using and applying Stoffenmanager. The use of validated tools embedded in a community platform appears to support companies to organize and structure their chemical risk management in a business-wise manner, but much depends upon motivated occupational health and safety (OHS) professionals, management support, and willingness to invest time and means.

• Smart Structures and Systems
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• 제3권4호
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• pp.455-474
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• 2007

A flexibility-based distributed computing strategy (DCS) for structural health monitoring (SHM) has recently been proposed which is suitable for implementation on a network of densely distributed smart sensors. This approach uses a hierarchical strategy in which adjacent smart sensors are grouped together to form sensor communities. A flexibility-based damage detection method is employed to evaluate the condition of the local elements within the communities by utilizing only locally measured information. The damage detection results in these communities are then communicated with the surrounding communities and sent back to a central station. Structural health monitoring can be done without relying on central data acquisition and processing. The main purpose of this paper is to experimentally verify this flexibility-based DCS approach using wired sensors; such verification is essential prior to implementation on a smart sensor platform. The damage locating vector method that forms foundation of the DCS approach is briefly reviewed, followed by an overview of the DCS approach. This flexibility-based approach is then experimentally verified employing a 5.6 m long three-dimensional truss structure. To simulate damage in the structure, the original truss members are replaced by ones with a reduced cross section. Both single and multiple damage scenarios are studied. Experimental results show that the DCS approach can successfully detect the damage at local elements using only locally measured information.

• Environmental Analysis Health and Toxicology
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• 제17권3호
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• pp.245-252
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• 2002

Airborne pollutants in the subway facilities can be potentially harmful to the health of passengers. This study was designed to examine whether the suspended particulates have mutagenic or carcinogenic effect on the plant cell systems. Total suspended particulates were collected with a high volume air sampler, in the entrance, the waiting room, and the platform of each subway station. The biological end -points in this experiment were the pink mutations in stamen hairs and micronuclei in the pollen mother cells of Tradescantia. The exudates were collected by shaking the filter papers from the sampler in distilled water for 24 hours. All the plant cuttings exposed to the exudates resulted in positive responses. The micronucleus assay proved more reliable and sensitive to the test than the stamen hair assay. The results indicate that the air particulates can give an adverse effect on the health of subway passengers.

• Journal of Nutrition and Health
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• 제55권1호
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• pp.1-9
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• 2022

In the past few decades, great progress has been made on understanding the interaction between nutrition and health status. But despite this wealth of knowledge, health problems related to nutrition continue to increase. This leads us to postulate that the continuing trend may result from a lack of consideration for intra-individual biological variation on dietary responses. Precision nutrition utilizes personal information such as age, gender, lifestyle, diet intake, environmental exposure, genetic variants, microbiome, and epigenetics to provide better dietary advices and interventions. Recent technological advances in the artificial intelligence, big data analytics, cloud computing, and machine learning, have made it possible to process data on a scale and in ways that were previously impossible. A big data platform is built by collecting numerous parameters such as meal features, medical metadata, lifestyle variation, genome diversity and microbiome composition. Sophisticated techniques based on machine learning algorithm can be used to integrate and interpret multiple factors and provide dietary guidance at a personalized or stratified level. The development of a suitable machine learning algorithm would make it possible to suggest a personalized diet or functional food based on analysis of intra-individual metabolic variation. This novel precision nutrition might become one of the most exciting and promising approaches of improving health conditions, especially in the context of non-communicable disease prevention.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.728-735
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• 2022

Roofers get exposed to increased risk of knee musculoskeletal disorders (MSDs) at different phases of a sloped shingle installation task. As different phases are associated with different risk levels, this study explored the application of machine learning for automated classification of seven phases in a shingle installation task using knee kinematics and roof slope information. An optical motion capture system was used to collect knee kinematics data from nine subjects who mimicked shingle installation on a slope-adjustable wooden platform. Four features were used in building a phase classification model. They were three knee joint rotation angles (i.e., flexion, abduction-adduction, and internal-external rotation) of the subjects, and the roof slope at which they operated. Three ensemble machine learning algorithms (i.e., random forests, decision trees, and k-nearest neighbors) were used for training and prediction. The simulations indicate that the k-nearest neighbor classifier provided the best performance, with an overall accuracy of 92.62%, demonstrating the considerable potential of machine learning methods in detecting shingle installation phases from workers knee joint rotation and roof slope information. This knowledge, with further investigation, may facilitate knee MSD risk identification among roofers and intervention development.

• 한국지능시스템학회논문지
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• 제21권4호
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• pp.456-462
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• 2011

최근 미국의 경기부양 법안이 통과됨에 따라 전 세계적으로 의료 산업분야에서의 EHR 시스템에 대한 관심이 증대되고 있다. 이 법안은 다양한 의료표준을 통해 상호 운용성을 보장하는 EHR 시스템을 도입하는 의원이나 병원에 인센티브를 제공하는 프로그램을 제시하고 있다. 이러한 인센티브 프로그램으로 인해 많은 EHR 시스템이 개발되었고, 또한 많은 의원이나 병원이 CCHIT에서 인증한 EHR 시스템을 도입하고 있다. 미국 의료 산업의 변화에 발맞추어 국내의 일부 기업에서도 국내병원에 EMR 시스템을 구축한 경험을 바탕으로 미국 의료 시장에 진출하려고 노력하고 있다. 그러나 미국과 한국의 의료 환경이 상이하여 개발한 시스템의 개선이 불가피하다. 따라서 본 논문에서는 의료표준화 기술에 기반하여 서로 다른 의료정보 시스템 간의 상호 운용성을 보장하는 통합형 EHR 플랫폼을 설계하고 개발한다. 개발한 플랫폼에서는 전송 표준 및 방법, 용어 표준 및 활용, 의사 결정을 위한 지식 관리 등의 다양한 기반 기술을 통합하여 완성된 하나의 시스템을 구현하였고, 의료정보의 표준화를 위한 표준용어체계와 의료정보의 교환을 위한 HL7 인터페이스 엔진을 탑재하여 의료 데이터의 전자적 처리가 가능하도록 하였다. 개발한 플랫폼에 기반하여 미국 개원의의 외래 진료를 지원하기 위한 EHR 시스템인 SeniCare를 개발하고, CMS에서 제시한 "의미 있는 사용"의 조건의 부합 여부를 확인함으로써 개발한 플랫폼의 효용성을 검증한다.

• 성인간호학회지
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• 제27권4호
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• pp.459-471
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• 2015

Purpose: The purpose of this study was to develop a smartphone application and evaluate it's effectiveness and usability for promoting bone health in Korean young adult women. Methods: A smartphone application was developed covering exercise, nutrition, and health habits related to bone health. A pilot testing was conducted using a one-group pre/posttest design. A total of 22 female college students with low bone mass participated in the 8-week use of a pilot testing. Results: The "Strong bone Fit body (SbFb)" application was developed using Android platform. In the pilot testing, bone mineral density, serum CTX, and 25 (OH)Vit.D were significantly decreased. There is no significant change in serum osteocalcin and calcium. Serum phosphorus concentration, nutrient intakes (fiber, VitB6, and pantotenic acid), and all bone composition profiles were significantly increased. Bone-health knowledge was significantly increased but no change in health belief and self-efficacy. Conclusion: The results of this pilot testing suggest the effectiveness of the SbFb application to enhance and promote self-managing abilities for bone health. It can provide continuous feedback and high-quality bone health information. However, some contents and working methods of the application need to be modified and its effectiveness on bone health requires further investigations.

• 한국치위생학회지
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• 제23권1호
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• pp.43-53
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• 2023

Objectives: We developed an integrated cognitive function improvement program comprising cognitive, emotional, and physical domains, and remotely applied it to middle-aged adults to investigate its effects on oral health, cognitive function, and mental health improvement. Methods: The experimental group underwent the program remotely, using the Zoom platform. A total of 24 participants were recruited and divided into 12 experimental and 12 control groups. The program comprised cognitive, emotional, and physical activities. The sessions lasted 90 min and were performed twice a week for 6 weeks from April to May 2022. Results: Cognitive function, arousal, physical, and mental stress were significantly improved in the experimental group after the intervention than at the baseline (p<0.05). Regarding oral health, tongue plaque decreased 1.34-fold (p<0.01) and saliva increased 1.04-fold (p<0.05) in the experimental group after the intervention than at the baseline. Moreover, the experimental group showed significant improvements in tongue plaque and saliva than the control group (p<0.05 for tongue plaque and p<0.01 for saliva). Regarding mental health, social support significantly increased 11.67-fold (p<0.05) in the experimental group than at the baseline. The experimental group also showed significantly improved social support than the control group (p<0.01). Conclusions: The non-face-to-face integrated cognitive function improvement program for middle-aged adults improved their cognitive function and oral and mental health. Based on these findings, this program may be a useful health program tool for middle-aged individuals.

• 한국환경보건학회지
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• 제15권2호
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• pp.1-9
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• 1989

A pilot study was conducted in order to measure indoor and outdoor formaldehyde levels during August 3 - 22, 1988 in several underground spaces in Seoul. Formaldehyde concentrations were monitored during 1 week in selected sampling areas (subway station, underground shopping center, underpass, tunnel, underground parking lot) using passive formaldehyde monitors. In order to investigate a relationship between respiratory prevalence and levels of formaldehyde, each subject was asked to answer respiratory questions. The mean formaldehyde concentrations were 60.1 ppb in subway station, 122.2 ppb in underground shopping stores, 72.1 ppb in underpasses, 39.7 ppb in tunnel, and 75.9 ppb in underground parking lots, respectively. The mean indoor formaldehyde concentrations in underground environments varied from 28.6 ppb to 118.7 ppb. Generally, the mean formaldehyde concentrations in ticketing office in subway stations appeared higher than those level measured in platform. The mean formaldehyde concentrations of underground shopping center in Gangnam Terminal were higher than any other areas and it exceeded 100 ppb of the American Ambient Air Quality Standards of formaldehyde. Prevalence rates of respiratory symptoms of dwellers seemed to be related to higher indoor formaldehyde levels.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.496-507
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• 2001

An expert system for the diagnosis and indication of hypertension is implemented through HTML-based backward inference. HTML-based backward inference is performed using the hypertext function of HTML, and many HTML files, which are hyperlinked to each other based on the backward rules, should be prepared beforehand. The development and maintenance of the HTML files are conducted automatically using the decision graph. Still, the drawing and input of the decision graph is a time consuming and tedious job if it is done manually. So, automatic generator of the decision graph for the diagnosis and indication of hypertension was implemented. The HTML-based backward inference ensures accessibility, multimedia facilities, fast response, stability, easiness, and platform independency of the expert system. So, this research reveals that HTML-based inference approach can be used for many Web-based intelligent site with fast and stable performance.