Adaptive Kalman Estimation in Target Tracking Mixed with Random One-Step Delays, Stochastic-Bias Measurements, and Missing Measurements

The objective of this paper is concerned with the estimation problem for linear discrete-time stochastic systems with mixed uncertainties involving random one-step sensor delay, stochastic-bias measurements, and missing measurements. Three Bernoulli distributed random variables are employed to describe the uncertainties. All the three uncertainties in the measurement have certain probability of occurrence in the target tracking system. And then, an adaptive Kalman estimation is proposed to deal with this problem. The adaptive filter gains can be obtained in terms of solutions to a set of recursive discrete-time Riccati equations. Examples in three scenarios of target tracking are exploited to show the effectiveness of the proposed design approach

Extended Dissipative Filter for Delayed T-S Fuzzy Network of Stochastic System with Packet Loss

This research investigates a time-varying delay-based adaptive event-triggered dissipative filtering problem for the interval type-2 (IT-2) Takagi-Sugeno (T-S) fuzzy networked stochastic system. The concept of extended dissipativity is used to solve the ,  and dissipative performances for (IT-2) T-S fuzzy stochastic systems in a unified manner. Data packet failures and latency difficulties are taken into account while designing fuzzy filters. An adaptive event-triggered mechanism is presented to efficiently control network resources and minimise excessive continuous monitoring while assuring the system’s efficiency with extended dissipativity. A new adaptive event triggering scheme is proposed which depends on the dynamic error rather than pre-determined constant threshold. A new fuzzy stochastic Lyapunov-Krasovskii Functional (LKF) using fuzzy matrices with higher order integrals is built based on the Lyapunov stability principle for mode-dependent filters. Solvability of such LKF leads to the formation of appropriate conditions in the form of linear matrix inequalities, ensuring that the resulting error mechanism is stable. In order to highlight the utility and perfection of the proposed technique, an example is presented

Cooperative Target Localization and Tracking with Incomplete Measurements

This study investigates a problem on target localization and tracking for two cases where either the slant range information of dual stations is lost or the slant range information of one station and the pitch angle information of the other one are missing. The models of cooperative localization with incomplete measurements are presented and the Kalman filtering algorithm is applied for target tracking. For improving tracking precision, a strategy of observers path planning based on the gradient of circular error probability (CEP) is integrated into the Kalman filtering algorithm. Several numerical examples are used to illustrate the tracking performance of the proposed algorithm with the corresponding root mean square error (RMSE) and Cramer-Rao lower bound (CRLB). The Monte Carlo simulation results validate the effectiveness of the presented algorithm

Extended Dissipative Filter for Delayed T-S Fuzzy Network of Stochastic System with Packet Loss

450-459This research investigates a time-varying delay-based adaptive event-triggered dissipative filtering problem for the interval type-2 (IT-2) Takagi-Sugeno (T-S) fuzzy networked stochastic system. The concept of extended dissipativity is used to solve the ∞, ∞ and dissipative performances for (IT-2) T-S fuzzy stochastic systems in a unified manner. Data packet failures and latency difficulties are taken into account while designing fuzzy filters. An adaptive event-triggered mechanism is presented to efficiently control network resources and minimise excessive continuous monitoring while assuring the system’s efficiency with extended dissipativity. A new adaptive event triggering scheme is proposed which depends on the dynamic error rather than pre-determined constant threshold. A new fuzzy stochastic Lyapunov-Krasovskii Functional (LKF) using fuzzy matrices with higher order integrals is built based on the Lyapunov stability principle for mode-dependent filters. Solvability of such LKF leads to the formation of appropriate conditions in the form of linear matrix inequalities, ensuring that the resulting error mechanism is stable. In order to highlight the utility and perfection of the proposed technique, an example is presented

Distributed Asynchronous Fusion Algorithm for Sensor Networks with Packet Losses

This paper is concerned with the problem of distributed estimation fusion over peer-to-peer asynchronous sensor networks with random packet dropouts. A distributed asynchronous fusion algorithm is proposed via the covariance intersection method. First, local estimator is developed in an optimal batch fashion by constructing augmented measurement equations. Then the fusion estimator is designed to fuse local estimates in the neighborhood. Both local estimator and fusion estimator are developed by taking into account the random packet losses. The presented estimation method improves local estimates and reduces the estimate disagreement. Simulation results validate the effectiveness of the proposed distributed asynchronous fusion algorithm

Excited-state localization and energy transfer in pyrene core dendrimers with fluorene/carbazole as the dendrons and acetylene as the linkages

A multi-leveled theoretical investigation combining TD-DFT (B3LYP and CAM-B3LYP) methods and a semi-empirical method was conducted to determine the structure-related spectral properties of T-series dendrimers composed of nearly hundreds of atoms, based on a proposed molecular model. Both one-and two-photon absorption spectra of the dendrimer molecules were well reproduced. The "antenna effect" in the dendrimers molecule was theoretically studied. The process of excitation energy localization from chromophores in the branches to the pyrene core before the fluorescence emission was visualized using contours of the charge different density (CDD) between the electronic states. Conclusions based on the theoretical model were drawn about the observed photophysical properties of T-series dendrimers as follows: (a) increasing the generation of a branch would enhance the absorption of photons with a wavelength below 430 nm; (b) enlarging the conjugation of branches would enhance the coupling among the chromophores and would lower the excitation energy; (c) the existence of inter-molecular coupling among the "antenna" chromophores in conjugated branches and the pyrene core would significantly promote two-photon absorption

Effects of MicroRNA-155 on the Growth of Human Lung Cancer Cell Line 95D in vitro

Background and objective Recent studies suggest that miR-155 is involved in lung tumorgenesis, whereas the precise mechanism has not yet been characterized. The aim of this study is to investigate the effects of over-expression of miR-155 on the growth of human lung cancer 95D cells in vitro and its possible mechanism, and thus to provide experimental evidence for further researching on the role of miR-155 in the pathogenesis and development of lung cancer. Methods miR-155 mimics control and miR-155 mimics were tranfected into human lung cancer 95D cells by FuGENE® HD Transfection Reagent respectively in vitro. The relative expression level of miR-155 in 95D cells was determined using specific probe of real-time PCR after transfection. The proliferation of 95D cells was detected by MTT assay. The cell cycle was analyzed by flow cytometry. The expression of SOS1 protein was measured by Western blot. Results Compared with control groups, the expression level of miR-155 was significantly increased in miR-155 mimics transfected group (P<0.05). The proliferation of miR-155-transfected 95D cells was significantly inhibited (P<0.05). The percentage of G0/G1 phase cells was increased significantly in miR-155-transfected 95D cells, while the percentage of S phase was remarkably reduced (P<0.05). Furthermore, the expression of SOS1 in miR-155-transfected 95D cells was significantly down-regulated (P<0.05). Conclusion miR-155 could significantly inhibit the growth of human lung cancer 95D cells in vitro, which might be closely related to miR-155 induced G0/G1 phase arrest

A Novel Multiobject Tracking Approach in the Presence of Collision and Division

This paper aims to develop a general framework for accurately tracking and quantitatively characterizing multiple cells (objects) when collision and division between cells arise. Through introducing three types of interaction events among cells, namely, independence, collision, and division, the corresponding dynamic models are defined and an augmented interacting multiple model particle filter tracking algorithm is first proposed for spatially adjacent cells with varying size. In addition, to reduce the ambiguity of correspondence between frames, both the estimated cell dynamic parameters and cell size are further utilized to identify cells of interest. The experiments have been conducted on two real cell image sequences characterized with cells collision, division, or number variation, and the resulting dynamic parameters such as instant velocity, turn rate were obtained and analyzed