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In recent years, robots have been increasingly utilized in applications with complex unknown environments, which makes system modeling challenging. In order to meet the demand from such applications, an experience-based learning approach can be used. In this paper, a novel learning algorithm is proposed, which can learn an unknown system model from given(More)
Human adenovirus type 36 (Ad36) as an obesity agent induces adiposity by increasing glucose uptake and promoting chronic inflammation in fat tissues; in contrast, exercise reduces total body fat and inflammation. Our objective was to determine the association between Ad36 and the effects of exercise on inflammation and glycemic control. In the human trials(More)
This study investigated the cross-sectional and longitudinal association between adenovirus 36 (Ad36) and obesity in 79 Korean adolescent boys over 1 year. We analyzed the changes in body composition and metabolic risk factors according to the presence of Ad36 antibodies. Ad36 antibodies in serum were detected using the constant virus-decreasing serum(More)
The relationship between obesity and vaccine efficacy is a serious issue. Previous studies have shown that vaccine efficacy is lower in the obese than in the non-obese. Here, we examined the influence of obesity on the efficacy of influenza vaccination using high fat diet (HFD) and regular fat diet (RFD) mice that were immunized with 2 types of influenza(More)
Adenovirus 36 (Ad36) is known to be associated with human obesity and to trigger inflammation in murine models. However, to date no clinical drugs for treating virus-induced obesity have been developed. Therefore, in this study, the anti-obesity and anti-inflammation effects of mulberry extract on Ad36 were evaluated in mice. The mulberry extract-fed group(More)
This paper presents shadow detection methods for vision-based autonomous driving in an urban environment. Shadows misclassified as objects create problems in autonomous driving applications. Real-time efficient algorithms in dynamic background settings are proposed. Without the static background assumption, which was often used in previous work to develop(More)
Using a scenario of multiple mobile observing platforms (UAVs) measuring weather variables in distributed regions of the Pacific, we are developing algorithms that will lead to improved forecasting of high-impact weather events. We combine technologies from the nonlinear weather prediction and planning/control communities to create a close link between(More)
Pathogenic T helper cells (TH) and macrophages have been implicated in the development of rheumatoid arthritis (RA), which can lead to severe synovial inflammation and bone destruction. A range of therapies have been widely used for RA, including specific monoclonal antibodies and chemical inhibitors against inflammatory cytokines produced by these cells.(More)
In recent years, robots have started being utilized in applications with complex/unknown interaction environment, which makes system/interface modeling to be very challenging. In order to meet the demand from such applications, the experience based learning approach can be a suitable tool. In this paper, a general algorithm for learning based robot control(More)
This work addresses the problem of trajectory planning for UAV sensors taking measurements of a large nonlinear system to improve estimation and prediction of such a system. The lack of perfect knowledge of the global system state typically requires probabilistic state estimation. The goal is therefore to find trajectories such that the measurements along(More)