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The tracking of targets in road situation represents a challenge for both the measurement to track association and the positional estimation algorithms. Previous simulation have shown that the data association method based on evidence theory has a good performance, compared with the Nearest Neighbor (NN) and cheap JPDAF method, moreover it has proved that the Interacting Multiple Models (IMM) m...
This study is devoted to overcome the underflow problem and poorly cost-effective limitation of model-set adaptive IMM algorithm. Cause of underflow problem in NovelIMM is addressed firstly, based on which an underflow prevented selection probabilities (UPSP) algorithm is presented to solve this problem. This paper then presents a fast model-set adaptive (FAIMM) IMM algorithm based on steady st...
Robust and adaptive vehicle state estimation tracking algorithms have become a very important part within the autonomous driving field. The family of interacting multiple model (IMM) filters has shown to provide effective accurate in systems whose behavior patterns change significantly over time. main reason for improved performance IMM compared single approaches is mode mixing, which constantl...
The increasing incidence of antimicrobial resistance represents a global threat. As result, surveillance programmes monitoring consumption and in animals have been implemented several countries throughout the world. However, such depend on accurate detailed collection data consumption. For this reason, aim longitudinal study was to compare consistency between three different methods. Antimicrob...
For mass application positioning demands, the current single sensor cannot provide reliable and accurate positioning. Herein, we present batch inverse covariance intersection (BICI) BICI with interacting multiple model (BICI-IMM) multi-sensor fusion methods, which are based on form of sequential (SICI) method. Meanwhile, it is proved that robust. Compared SICI, BICI-IMM reduces estimation error...
This study aims to solve the non-linear fifth-order induction motor model (FO-IMM) using Gudermannian neural networks (GNN) along with optimization procedures of global search as a genetic algorithm together quick local process active-set technique (GNN-GA-AST). The GNN are executed discretize FO-IMM prompt fitness function in procedure mean square error. exactness GNN-GA-AST is observed by com...
Insect resistance to Bacillus thuringiensis: alterations in the indianmeal moth larval gut proteome.
Insect resistance to the Cry toxins of Bacillus thuringiensis (Bt) has been examined previously using a number of traditional biochemical and molecular techniques. In this study, we utilized a proteomic approach involving two-dimensional differential gel electrophoresis, mass spectrometry, and function-based activity profiling to examine changes in the gut proteins from the larvae of an Indianm...
BACKGROUND Methotrexate (MTX) use as an alternative to thiopurines in the treatment of Crohn's disease (CD) in children is increasing. This study was undertaken to assess safety and efficacy of MTX in children with CD. METHODS Patients treated with MTX with a minimum of 1-year follow-up were identified in the Pediatric IBD Collaborative Research Group Registry, a prospective inception cohort ...
Interactive multimedia (IMM) navigation systems rely on two key non-graphical components, a schematic or architectural framework and an associated programming solution. Two primary framework types are recognized – branching (structured) and referential (unstructured) – although most navigation systems include elements of both. Programmed solutions to navigational frameworks typically display va...
Internal marketing has been applied to organizational employees to foster their shared understanding. This study proposes a multilevel model to depict the causal relationships of market orientation behavior (MOB) with internal marketing, knowledge integration, relationship quality, relational bond (RB), and organizational citizenship behavior (OCB). A total of 471 valid responses from employees...
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