The adaptive patched cubature filter and its implementation

There are numerous contexts where one wishes to describe the state of a randomly evolving system. Effective solutions combine models that quantify the underlying uncertainty with available observational data to form scientifically reasonable estimates for the uncertainty in the system state. Stochastic differential equations are often used to mathematically model the underlying system. The Kusuoka-Lyons-Victoir (KLV) approach is a higher order particle method for approximating the weak solution of a stochastic differential equation that uses a weighted set of scenarios to approximate the evolving probability distribution to a high order of accuracy. The algorithm can be performed by integrating along a number of carefully selected bounded variation paths. The iterated application of the KLV method has a tendency for the number of particles to increase. This can be addressed and, together with local dynamic recombination, which simplifies the support of discrete measure without harming the accuracy of the approximation, the KLV method becomes eligible to solve the filtering problem in contexts where one desires to maintain an accurate description of the ever-evolving conditioned measure. In addition to the alternate application of the KLV method and recombination, we make use of the smooth nature of the likelihood function and high order accuracy of the approximations to lead some of the particles immediately to the next observation time and to build into the algorithm a form of automatic high order adaptive importance sampling.Comment: to appear in Communications in Mathematical Sciences. arXiv admin note: substantial text overlap with arXiv:1311.675

Data Assimilation by Conditioning on Future Observations

Conventional recursive filtering approaches, designed for quantifying the state of an evolving uncertain dynamical system with intermittent observations, use a sequence of (i) an uncertainty propagation step followed by (ii) a step where the associated data is assimilated using Bayes' rule. In this paper we switch the order of the steps to: (i) one step ahead data assimilation followed by (ii) uncertainty propagation. This route leads to a class of filtering algorithms named \emph{smoothing filters}. For a system driven by random noise, our proposed methods require the probability distribution of the driving noise after the assimilation to be biased by a nonzero mean. The system noise, conditioned on future observations, in turn pushes forward the filtering solution in time closer to the true state and indeed helps to find a more accurate approximate solution for the state estimation problem

PADA: Power-aware development assistant for mobile sensing applications

� 2016 ACM. We propose PADA, a new power evaluation tool to measure and optimize power use of mobile sensing applications. Our motivational study with 53 professional developers shows they face huge challenges in meeting power requirements. The key challenges are from the significant time and effort for repetitive power measurements since the power use of sensing applications needs to be evaluated under various real-world usage scenarios and sensing parameters. PADA enables developers to obtain enriched power information under diverse usage scenarios in development environments without deploying and testing applications on real phones in real-life situations. We conducted two user studies with 19 developers to evaluate the usability of PADA. We show that developers benefit from using PADA in the implementation and power tuning of mobile sensing applications.N

Empath-D: VR-based empathetic app design for accessibility

Singapore National Research Foundation under IDM Futures Funding Initiative; Ministry of Education, Singapore under its Academic Research Funding Tier

Effect of total intravenous versus inhalation anesthesia on long-term oncological outcomes in patients undergoing curative resection for early-stage non-small cell lung cancer: a retrospective cohort study

Background Propofol-based total intravenous anesthesia (TIVA) improves long-term outcomes after cancer surgery compared with inhalation anesthesia. However, its effect on patients undergoing non-small cell lung cancer (NSCLC) surgery remains unclear. We aimed to compare the oncological outcomes of TIVA and inhalation anesthesia after curative resection of early-stage NSCLC. Methods We analyzed the medical records of patients diagnosed with stage I or II NSCLC who underwent curative resection at a tertiary university hospital between January 2010 and December 2017. The primary outcomes were recurrence-free survival (RFS) and overall survival (OS) according to anesthesia type. Results We included 1,508 patients with stage I/II NSCLC. The patients were divided into the TIVA (n = 980) and Inhalation (n = 528) groups. The two groups were well-balanced in terms of baseline clinical characteristics. The TIVA group demonstrated significantly improved RFS (7.7 years, 95% CI [7.37, 8.02]) compared with the Inhalation group (6.8 years, 95% CI [6.30, 7.22], P = 0.003). Similarly, TIVA was superior to inhalation agents with respect to OS (median OS; 8.4 years, 95% CI [8.08, 8.69] vs. 7.3 years, 95% CI [6.81, 7.71]; P < 0.001). Multivariable Cox regression analysis revealed that TIVA was an independent prognostic factor related to recurrence (hazard ratio [HR]: 1.24, 95% CI [1.04, 1.47], P = 0.014) and OS (HR: 1.39, 95% CI [1.12, 1.72], P = 0.002). Conclusions Propofol-based TIVA was associated with better RFS and OS than inhalation anesthesia in patients with stage I/II NSCLC who underwent curative resection

Determinants of positive orientations of adolescents in Korean multicultural families based on the socio-ecological model

The number of multicultural adolescents has been increasing globally, and their psychological well-being has received keen attention. The present study aimed to identify the factors affecting the positive orientations (i.e., self-esteem, optimism, and life satisfaction) of Korean adolescents from multicultural families based on the socio-ecological model.This study comprised a cross-sectional survey that used data from the Multicultural Adolescents Panel Study by the National Youth Policy Institute in South Korea. In total, 1260 adolescents from Korean multicultural families participated. To assess how the factors contributed to positive orientations, we performed a hierarchical linear regression analysis.Of the individual-level factors, gender, appearance satisfaction, social withdrawal, bicultural and multicultural attitudes, and academic achievement satisfaction affected the positive orientations of the adolescents. Among the relationship-level factors, their family support, relationships with their friends, and relationships with their teachers influenced their positive orientations; in particular, family support was the most influential factor.The study identified influential factors on the positive orientations among multicultural adolescents. These findings can help healthcare, educational, and social service professionals develop programs to enhance the positive orientations of adolescents from multicultural families