Path renewal method in filtering based wireless sensor networks.

In applications of wireless sensor networks, there are many security issues. Attackers can create false reports and transmit the reports to the networks. These false reports can lead not only false alarms, but also the depletion of limited energy resources. In order to filter out such false reports during the forwarding process, Ye et al. proposed the statistical en-route filtering (SEF). Several research efforts to enhance the efficiency of SEF have been made. Especially, the path selection method proposed by Sun et al. can improve the detection power of SEF by considering the information on the filtering keys of and distances of upstream paths. However, such selection mechanism could lead to favored paths in heavy traffic, which would result in unbalanced energy consumption. In this paper, we propose a path renewal method to provide load balancing for sensor networks in terms of energy consumption. In our method, a node renews its upstream path to save energy resources if the remaining energy of and the communication traffic of the node exceed some threshold values. We show the effectiveness of the proposed method in terms of balanced energy consumption and filtering power by providing simulation results.

The estimation of cardiovascular risk factors by body mass index and body fat percentage in Korean male adults.

The aim of the study was to assess cardiovascular risk in men with high body fat percentage (BF%) and normal body mass index (BMI) and men with normal BF% and high BMI. This study was a cross-sectional study using data on 5534 Korean male adults. Body mass index, BF%, and waist circumference were measured as adiposity indices. Bioelectrical impedance analysis was used for measuring BF%. Blood pressure, fasting plasma glucose, total cholesterol, triglyceride, and high-density lipoprotein cholesterol were measured routinely. Information regarding alcohol consumption, smoking, exercise, and past/current medical history was obtained by structured questionnaires. Subjects were categorized into 4 groups by means of BMI and BF% (group 1, BMI <25 kg/m(2) and BF% <25%; group 2, BMI <25 kg/m(2) and BF% > or =25%; group 3, BMI > or =25 kg/m(2) and BF% <25%; group 4, BMI > or =25 kg/m(2) and BF% > or =25%). Cardiovascular risk factors (CVRFs) such as high blood pressure, hyperglycemia, and dyslipidemia were estimated in each group. As might be expected, the prevalences of high blood pressure, hyperglycemia, and dyslipidemia were lowest in group 1 and were highest in group 4. Multivariate analyses showed that subjects in group 2 or group 4 had a 1.8 times increased risk of clustering of 2 or more CVRFs compared with subjects in group 1 (P < .001). The adjusted odds ratio (1.15; 95% confidence interval, 0.94-1.40) of subjects in group 3 on clustering of 2 or CVRFs was not significantly increased (P = .180). High BF% was related to increase of cardiovascular risk regardless of the level of BMI in Korean men. However, cardiovascular risk of men with high BMI without high BF% was not significantly increased.