• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.5
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• pp.1-11
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• 2008

Wireless Sensor Networks is applied to improvement of life convenience or service like U-City as well as environment pollution, tunnel and structural health monitoring, storm, and earthquake diagnostic system. To increase the usability of sensor data and applicability, mobile devices and their facilities allow the applications of sensor networks to give mobile users and actuators the results of event detection at anytime and anywhere. In this paper, we present MUSNEMO(Multi-sensor centric Ubiquitous Smart sensor NEtwork using Mobile devices) developed system for providing more efficient and valuable information services with a variety of mobile devices and network camera integrated to WSN. Our system is performed based on IEEE 802.15.4 protocol stack. To validate system usability, we built sensor network environments where were equipped with five application sensors such magnetic, photodiode, microphone, motion and vibration. We also built and tested proposed MUSNEMO to provide a novel model for event detection systems with mobile framework.

• Proceedings of the Korea Society of Environmental Toocicology Conference
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• 2003.10a
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• pp.91-93
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• 2003

It has been estimated that the equivalent of approximately $US 50 billion has been spent on research on the behavior and fate of pesticides in the environment since Rachel Carson published “Silent Spring” in 1962. Much of the resulting knowledge has been summarized explicitly in computer algorithms in a variety of empirical, deterministic, and probabilistic simulation models. These models describe and predict the transport, degradation and resultant concentrations of pesticides in various compartments of the environment during and after application. In many cases the known errors of model predictions are large. For this reason they are typically designed to be “conservative”, i.e., err on the side of over-prediction of concentrations in order to err on the side of safety. These predictions are then compared with toxicity data, from tests of the pesticide on a series of standard representative biota, including terrestrial and aquatic indicator species and higher animals (e.g., wildlife and humans). The models' predictions are good enough in some cases to provide screening of those compounds which are very unlikely to do harm, and to indicate those compounds which must be investigated further. If further investigation is indicated a more detailed (and therefore more complicated) model may be employed to give a better estimate, or field experiments may be required. A model may be used to explore “what if” questions leading to possible alternative pesticide usage patterns which give lower potential environmental concentrations and allowable exposures. We are currently at a maturing stage in this research where the knowledge base of pesticide behavior in the environmental is growing more slowly than in the past. However, innovative uses are being made of the explosion in available computer technology to use models to take ever more advantage of the knowledge we have. In this presentation, current developments in the state of the art as practiced in North America and Europe will be presented. Specifically, we will look at the efforts of the ‘Focus’ consortium in the European Union, and the ‘EMWG’ consortium in North America. These groups have been innovative in developing a process and mechanisms for discussion amongst academic, agriculture, industry and regulatory scientists, for consensus adoption of research advances into risk management methodology.

• Journal of Preventive Medicine and Public Health
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• v.33 no.4
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• pp.459-468
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• 2000

Objectives : To investigate the association between BMI and Mortality. Methods : This study was based on the analysis and assembly of the 'Kangwha Cohort Study', previously conducted by the Department of Preventive Medicine, Yonsei University. A total of 2,696 males and 3,595 females were followed for almost ten years and ten months from March 1985 to January 1996, a total of whom 2,420 died during this period. The Cox's proportional hazards regression model was used to analyze this data. Results : We found a U-shaped relationship between BMI and mortality among the aged men in the Kangwha cohort. The hazard ratio of dying was adjusted for age, marital status, occupation, self cognitive health level, chronic disease, smoking, and alcohol frequency, then sorted by body mass index into the following groups; less than 10.5, 18.5 to less than 21.0, 21.0 to less than 23.5, 23.5 to less than 26.0 and greater than or equal to 26. The corresponding ratios for men were 1.81(1.50-2.19, 95%CI), 1.31(1.14-1.51, 95%CI), 1.0(referent), 1.05(0.87-1.26, 95%CI) and 1.39(1.09-1.76, 95%CI), respectively. And for women, 1.46(1.19-1.78), 1.12(0.95-1.31, 95%CI), 1.0(referent), 1.00(0.84-1.20, 95%CI) and 1.09(0.89-1.34, 95%CI), respectively. Conclusions : The risk of death among aged men in Kangwha increased in the under and overweight groups. The relationship between BMl and mortality has been well studied in Western populations, but little is known about the association between BMI and mortality in our country. So, on the basis of this study, it is apparent that more studies of the relationship between BMI and mortality will be needed for future work.