Self-configuring indoor localization based on low-cost ultrasonic range sensors.

In smart environments, target tracking is an essential service used by numerous applications from activity recognition to personalized infotaintment. The target tracking relies on sensors with known locations to estimate and keep track of the path taken by the target, and hence, it is crucial to have an accurate map of such sensors. However, the need for manually entering their locations after deployment and expecting them to remain fixed, significantly limits the usability of target tracking. To remedy this drawback, we present a self-configuring and device-free localization protocol based on genetic algorithms that autonomously identifies the geographic topology of a network of ultrasonic range sensors as well as automatically detects any change in the established network structure in less than a minute and generates a new map within seconds. The proposed protocol significantly reduces hardware and deployment costs thanks to the use of low-cost off-the-shelf sensors with no manual configuration. Experiments on two real testbeds of different sizes show that the proposed protocol achieves an error of 7.16~17.53 cm in topology mapping, while also tracking a mobile target with an average error of 11.71~18.43 cm and detecting displacements of 1.41~3.16 m in approximately 30 s.

[The relationship between metabolic syndrome and Korean cardiocerebrovascular risk assessment: for male researchers in a workplace].

OBJECTIVES: The prevalence of metabolic syndrome has recently increased. Payments from the Korea Labor Welfare Corporation for compensation for mortality in workers caused by cardiovascular and cerebrovascular diseases have also increased in Korea in recent years. The association of metabolic syndrome and cardiocerebrovascular disease has been investigated by several researchers in recent studies. This study was conducted in an attempt to characterize the relationship between metabolic syndrome and Korean cardiocerebrovascular disease risk assessment, and to provide basic data to group health practices for the prevention of cardiocerebrovascular disease. METHODS: Health examinations were previously conducted for 1526 male researchers at a private laboratory. The prevalence by age and the odds ratio of metabolic syndrome scores into the "cardiocerebrovascular risk group" (sum of low, intermediate, and high risk groups) of the Korean cardiocerebrovascular disease risk assessment were assessed, in an effort to elucidate the associations between metabolic syndrome and cardiocerebrovascular disease risk assessment. RESULTS: The prevalence of metabolic syndrome and inclusion in the cardiocerebrovascular risk group was 11.7% and 22.1% respectively. The severity of metabolic syndrome and cardiocerebrovascular risk assessment showed that individuals in their 40's and 50's were at higher risk than those in their 30's (p<0.001). The age-adjusted odds ratio of metabolic syndrome to cardiocerebrovascular risk group inclusion was 5.6. CONCLUSIONS: An active prevention program for cardiocerebrovascular disease needs to begin in the 40's, as the prevalence of metabolic syndrome and the risk group of cardiocerebrovascular risk assessment peak in the 40's age group. The odds ratio between metabolic syndrome and the cardiocerebrovascular risk group was high, which indicates that metabolic syndrome scores should be utilized as guidelines during the consultation and behavioral modification program for the workplace prevention of cardiocerebrovascular diseases in group health practices.