Sensor Scheduling for Energy-Efficient Target Tracking in Sensor Networks

In this paper we study the problem of tracking an object moving randomly through a network of wireless sensors. Our objective is to devise strategies for scheduling the sensors to optimize the tradeoff between tracking performance and energy consumption. We cast the scheduling problem as a Partially Observable Markov Decision Process (POMDP), where the control actions correspond to the set of sensors to activate at each time step. Using a bottom-up approach, we consider different sensing, motion and cost models with increasing levels of difficulty. At the first level, the sensing regions of the different sensors do not overlap and the target is only observed within the sensing range of an active sensor. Then, we consider sensors with overlapping sensing range such that the tracking error, and hence the actions of the different sensors, are tightly coupled. Finally, we consider scenarios wherein the target locations and sensors' observations assume values on continuous spaces. Exact solutions are generally intractable even for the simplest models due to the dimensionality of the information and action spaces. Hence, we devise approximate solution techniques, and in some cases derive lower bounds on the optimal tradeoff curves. The generated scheduling policies, albeit suboptimal, often provide close-to-optimal energy-tracking tradeoffs

Sensor Management for Tracking in Sensor Networks

We study the problem of tracking an object moving through a network of wireless sensors. In order to conserve energy, the sensors may be put into a sleep mode with a timer that determines their sleep duration. It is assumed that an asleep sensor cannot be communicated with or woken up, and hence the sleep duration needs to be determined at the time the sensor goes to sleep based on all the information available to the sensor. Having sleeping sensors in the network could result in degraded tracking performance, therefore, there is a tradeoff between energy usage and tracking performance. We design sleeping policies that attempt to optimize this tradeoff and characterize their performance. As an extension to our previous work in this area [1], we consider generalized models for object movement, object sensing, and tracking cost. For discrete state spaces and continuous Gaussian observations, we derive a lower bound on the optimal energy-tracking tradeoff. It is shown that in the low tracking error regime, the generated policies approach the derived lower bound

Social Determinants of Smoke Exposure During Pregnancy: Findings From Waves 1 & 2 of the Population Assessment of Tobacco and Health (PATH) Study

Maternal smoking during pregnancy (MSDP) and secondhand smoke (SHS) exposure are associated with a myriad of negative health effects for both mother and child. However, less is known regarding social determinants for SHS exposure, which may differ from those of maternal smoking during pregnancy (MSDP). To identify social determinants for SHS exposure only, MSDP only, and MSDP and SHS exposure, data were obtained from all pregnant women (18–54 years; N = 726) in waves 1 and 2 of the Population Assessment of Tobacco and Health Study (2014–2015). Multiple logistic regressions were conducted using SAS 9.4. Smoke exposure during pregnancy was common; 23.0% reported SHS exposure only, 6.1% reported MSDP only, and 11.8% reported both SHS exposure and MSDP. Results demonstrate that relationships between smoke exposure during pregnancy and social determinants vary by type of exposure. Women at risk for any smoke exposure during pregnancy include those who are unmarried and allow the use of combustible tobacco products within the home. Those who are at higher risk for SHS exposure include those who are younger in age, and those who are earlier in their pregnancy. Those who are at higher risk for maternal smoking include those with fair/poor mental health status and those who believe that others\u27 view tobacco use more positively. These results suggest the need for implementing more comprehensive policies that promote smoke-free environments. Implementing these strategies have the potential to improve maternal and fetal health outcomes associated with tobacco smoke exposure

Doctoral capstone experience : therapy staff education in the intensive care units

There is a global need for further education for therapy staff within the intensive care units (ICUs). The range of education material and onboarding processes available for therapists in ICUs varies among hospitals and across the nation. This mixed methods quality improvement study aimed to address the education gap for the ICU Boone Hospital therapy staff in Columbia, Missouri. The research question is: Will education addressing ICU machines, lines/tubes, parameters, and safety precautions improve therapy staff comfortability and confidence in the ICU? Participants included the current therapy staff at Boone Hospital including the OTs, OTAs, PTs, PTAs, and SLPs. This question was measured through pre- and post-surveys covering various ICU topics/systems. Data was analyzed by comparing the pre- and post-survey questions specific to each body system as an average. Then aggregate data was used by obtaining an overall percent difference of Q1 and Q2. Q3 was analyzed by pulling three general themes from the pre-surveys and three general themes from the post-surveys. It was concluded that the educational binder improved therapy staff comfortability and confidence in the ICU in the topics of neurological, renal, tubes, and drains. The data was inconclusive for the respiratory, cardiac, and IV sections. Overall, the therapy staff reported an increase in comfort by 31.9% and high confidence also increased by 31.9%. The themes concluded that the binder was beneficial reference guide however, hands on experience and practice was reported as a necessary aspect to feel fully equipped to providing therapy in the ICU.Includes bibliographical references

Increased consumption of fruit and vegetables for the primary prevention of cardiovascular diseases

There is increasing evidence that high consumption of fruit and vegetables is beneficial for cardiovascular disease (CVD) prevention

Variations in central adiposity, cardiovascular fitness, and objectively measured physical activity according to weight status in children (9-11 years)

The purpose of this study was twofold: first, to compare the central adiposity (CA), cardiovascular fitness (CF), and physical activity (PA) in children with different weight status, and second, to determine the associations between moderate to vigorous physical activity (MVPA) and measures of adiposity [CA and body mass index (BMI)] and CF. A sample of 244 children (boys = 120 and girls = 124), 9.7–10.8 years of age (10.3 ± 0.3 years), was measured for stature, body mass, waist circumferences, and 20-m multi-stage fitness test. PA was recorded with ankle mounted accelerometer. BMI groups were used to classify children as underweight (UW), normal weight (NW), and overweight (OW). The prevalence of being OW was 21.7 and 25% in boys and girls, respectively. Only 5.3% of the participants were found to accumulate recommended amount (≥60 min/day) of MVPA. Boys were significantly outperformed girls in terms of CF. Moreover, they were significantly more engaged in moderate and vigorous physical activities than girls. Regardless of gender, results indicated that OW children had significantly higher values in all anthropometric parameters and lower level of CF than their UW and NW counterparts. In girls, OW children were found to accrue less time engaging in MVPA than the children in UW and NW groups. In boys, OW children were found to accrue less time engaging in vigorous activities than UW and NW children. Results also showed that there were no significant differences between UW and NW girls and boys in respect to CF. Besides, UW girls were found to accrue more time engaging in MVPA than NW girls. MVPA was found to be significantly and negatively correlated with BMI and waist circumference and significantly and positively correlated with CF in both boys and girls. These discrepancies and associations highlight the considerable influences of MVPA on weight status and CF in children

Techniques for the Regeneration of Wideband Speech from Narrowband Speech

This paper addresses the problem of reconstructing wideband speech signals from observed narrowband speech signals. The goal of this work is to improve the perceived quality of speech signals which have been transmitted through narrowband channels or degraded during acquisition. We describe a system, based on linear predictive coding, for estimating wideband speech from narrowband. This system employs both previously identified and novel techniques. Experimental results are provided in order to illustrate the system’s ability to improve speech quality. Both objective and subjective criteria are used to evaluate the quality of the processed speech signals

Inverse molecular design from first principles: Tailoring organic chromophore spectra for optoelectronic applications

The discovery of molecules with tailored optoelectronic properties, such as specific frequency and intensity of absorption or emission, is a major challenge in creating next-generation organic light-emitting diodes (OLEDs) and photovoltaics. This raises the following question: How can we predict a potential chemical structure from these properties? Approaches that attempt to tackle this inverse design problem include virtual screening, active machine learning, and genetic algorithms. However, these approaches rely on a molecular database or many electronic structure calculations, and significant computational savings could be achieved if there was prior knowledge of (i) whether the optoelectronic properties of a parent molecule could easily be improved and (ii) what morphing operations on a parent molecule could improve these properties. In this Perspective, we address both of these challenges from first principles. We first adapt the Thomas-Reiche-Kuhn sum rule to organic chromophores and show how this indicates how easily the absorption and emission of a molecule can be improved. We then show how by combining electronic structure theory and intensity borrowing perturbation theory we can predict whether or not the proposed morphing operations will achieve the desired spectral alteration, and thereby derive widely applicable design rules. We go on to provide proof-of-concept illustrations of this approach to optimizing the visible absorption of acenes and the emission of radical OLEDs. We believe that this approach can be integrated into genetic algorithms by biasing morphing operations in favor of those that are likely to be successful, leading to faster molecular discovery and greener chemistry