Lithium-ion battery State of Charge (SoC) estimation for Electric Vehicle (EV) applications must be robust and as accurate possible to maximize utilization ensure safe operation over a wide range operating conditions. SoC commonly utilizes filters such the Extended Kalman Filter (EKF) which rely on models, usually in form Equivalent Circuit Models (ECM). At low temperatures response current dra...

Abstract Background Combination therapy with an immunomodulator (IMM) and anti-TNF agent (specifically infliximab) is recommended in Crohn’s disease (CD) ulcerative colitis (UC) patients to improve efficacy reduce immunogenicity. Combo increases the risk of adverse events therefore attempts are made de-escalate clinical practice. There scarce data about relapse rates after discontinuation eithe...

Tracking the left ventricular (LV) endocardial boundary and motion from cardiac magnetic resonance (MR) images is difficult because of low contrast and photometric similarities between the heart wall and papillary muscles within the LV cavity. This study investigates the problem via Graph Cut Distribution Matching (GCDM) and Interacting Multiple Model (IMM) smoothing. GCDM yields initial frame ...

To date, there has been a lack of efficient and practical distributedand shared-memory parallelizations of the data association problem for multitarget tracking. Filling this gap is one of the primary focuses of the present work. We begin by describing our data association algorithm in terms of an Interacting Multiple Model (IMM) state estimator embedded into an optimization framework, namely, ...

Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization i...

In this paper, we present an interesting filtering algorithm to perform accurate estimation in jump Markov nonlinear systems, in case of multi-target tracking. With this paper, we aim to contribute in solving the problem of modelbased body motion estimation by using data coming from visual sensors. The Interacting Multiple Model (IMM) algorithm is specially designed to track accurately targets ...

OBJECTIVES To compare 1-year clinical efficacy of (1) initial triple disease-modifying antirheumatic drug therapy (iTDT) with initial methotrexate (MTX) monotherapy (iMM) and (2) different glucocorticoid (GC) bridging therapies: oral versus a single intramuscular injection in early rheumatoid arthritis. METHODS In a single-blinded randomised clinical trial patients were randomised into three ...

This paper addresses the problem of tracking multiple moving targets by recursively estimating the joint multitarget probability density (JMPD). Estimation of the JMPD is done in a Bayesian framework, providing a method of tracking multiple targets which allows nonlinear target motion, nonlinear measurement to state coupling, and non-Gaussian target state densities. We utilize a particle filter...

Tracking maneuvering targets introduce two major directions to improve the Multiple Model (MM) approach: Develop a better MM algorithm and design a better model set. The Interacting Multiple Model (IMM) estimator is a suboptimal hybrid filter that has been shown to be one of the most cost-effective hybrid state estimation schemes. The main feature of this algorithm is the ability to estimate th...