Optimal Stationary State Estimation Over Multiple Markovian Packet Drop Channels

In this paper, we investigate the state estimation problem over multiple Markovian packet drop channels. In this problem setup, a remote estimator receives measurement data transmitted from multiple sensors over individual channels. By the method of Markovian jump linear systems, an optimal stationary estimator that minimizes the error variance in the steady state is obtained, based on the mean-square (MS) stabilizing solution to the coupled algebraic Riccati equations. An explicit necessary and sufficient condition is derived for the existence of the MS stabilizing solution, which coincides with that of the standard Kalman filter. More importantly, we provide a sufficient condition under which the MS detectability with multiple Markovian packet drop channels can be decoupled, and propose a locally optimal stationary estimator but computationally more tractable. Analytic sufficient and necessary MS detectability conditions are presented for the decoupled subsystems subsequently. Finally, numerical simulations are conducted to illustrate the results on the MS stabilizing solution, the MS detectability, and the performance of the optimal and locally optimal stationary estimators

The Magnetic Properties of 1111-type Diluted Magnetic Semiconductor (La1−x_{1-x}Bax_{x})(Zn1−x_{1-x}Mnx_{x})AsO in the Low Doping Regime

We investigated the magnetic properties of (La$_{1-x}$Ba$_{x}$)(Zn$_{1-x}$Mn$_{x}$)AsO with $x$ varying from 0.005 to 0.05 at an external magnetic field of 1000 Oe. For doping levels of $x$ $\leq$ 0.01, the system remains paramagnetic down to the lowest measurable temperature of 2 K. Only when the doping level increases to $x$ = 0.02 does the ferromagnetic ordering appear. Our analysis indicates that antiferromagnetic exchange interactions dominate for $x$ $\leq$ 0.01, as shown by the negative Weiss temperature fitted from the magnetization data. The Weiss temperature becomes positive, i.e., ferromagnetic coupling starts to dominate, for $x$ $\geq$ 0.02. The Mn-Mn spin interaction parameter $\mid$$2J/k_B$$\mid$ is estimated to be in the order of 10 K for both $x$ $\leq$ 0.01 (antiferromagnetic ordered state) and $x$ $\geq$ 0.02 (ferromagnetic ordered state). Our results unequivocally demonstrate the competition between ferromagnetic and antiferromagnetic exchange interactions in carrier-mediated ferromagnetic systems.Comment: 9 pages, 3 figure

Pedestrian-Aware Supervisory Control System Interactive Optimization of Connected Hybrid Electric Vehicles via Fuzzy Adaptive Cost Map and Bees Algorithm

Electrified vehicles are increasingly being seen as a means of mitigating the pressing concerns of traffic-related pollution. Due to the nature of engine-assisted vehicle exhaust systems, pedestrians in close proximity to these vehicles may experience events where specific emission concentrations are high enough to cause health effects. To minimize pedestrians’ exposure to vehicle emissions and pollutants nearby, we present a pedestrian-aware supervisory control system for connected hybrid electric vehicles by proposing an interactive optimization methodology. This optimization methodology combines a novel fuzzy adaptive cost map and the Bees Algorithm to optimize power-split control parameters. It enables the self-regulation of inter-objective weights of fuel and exhaust emissions based on the real-time pedestrian density information during the optimization process. The evaluation of the vehicle performance by using the proposed methodology is conducted on the realistic trip map involving pedestrian density information collected from the University College Dublin campus. Moreover, two bootstrap sampling techniques and effect of communication quality are both investigated in order to examine the robustness of the improved vehicle system. The results demonstrate that 14.42% mass of exhaust emissions can be reduced for the involved pedestrians, by using the developed fuzzy adaptive cost map

Adjuvant therapy for T3N0 rectal cancer in the total mesorectal excision era- identification of the high risk patients

<p>Abstract</p> <p>Background</p> <p>Adjuvant therapy for T3N0 rectal cancer was controversial with respect to both radiation and the use of a combined regimen of chemotherapy. We evaluated both clinical features and biomarkers and sought to determine risk factors for those patients retrospectively.</p> <p>Methods</p> <p>A total of 122 patients with T3N0 rectal cancer were analyzed in this study from January 2000 to December 2005. Clinicopathologic and biomarkers were used to predict local recurrence (LR), disease-free survival (DFS), and overall survival (OS).</p> <p>Results</p> <p>The median follow-up interval was 45.4 months. Five-year LR, DFS, and OS rates were 10.4%, 68.3%, and 88.7%. Having a lower tumor location and showing low P21 and high CD44v6 expression were identified as risk factors for LR: patients with two or three of these risk factors had a higher 5-year LR rate (19.3%) than did patients with none or one of these risk factors (6.8%) (p = 0.05). A poorer DFS was related to low P21 nor high CD44v6 expression but not to tumor location: the 5-year DFS rates were 79.3% for those with neither, 65.9% for those with either one or the other, and 16.9% for those with both (p = 0.00).</p> <p>Conclusions</p> <p>The prognostic model including tumor location, P21 and CD44v6 expressions could help to distinguish these patients with high risk T3N0 patients and determine whether adjuvant therapy was beneficial.</p

Pedestrian-aware supervisory control system interactive optimization of connected hybrid electric vehicles via fuzzy adaptive cost map and bees algorithm

Electrified vehicles are increasingly being seen as a means of mitigating the pressing concerns of traffic-related pollution. Due to the nature of engine-assisted vehicle exhaust systems, pedestrians in close proximity to these vehicles may experience events where specific emission concentrations are high enough to cause health effects. To minimize pedestrians’ exposure to vehicle emissions and pollutants nearby, we present a pedestrian-aware supervisory control system for connected hybrid electric vehicles by proposing an interactive optimization methodology. This optimization methodology combines a novel fuzzy adaptive cost map and the Bees Algorithm to optimize power-split control parameters. It enables the self-regulation of inter-objective weights of fuel and exhaust emissions based on the real-time pedestrian density information during the optimization process. The evaluation of the vehicle performance by using the proposed methodology is conducted on the realistic trip map involving pedestrian density information collected from the University College Dublin campus. Moreover, two bootstrap sampling techniques and effect of communication quality are both investigated in order to examine the robustness of the improved vehicle system. The results demonstrate that 14.42% mass of exhaust emissions can be reduced for the involved pedestrians, by using the developed fuzzy adaptive cost map

A novel power-bearing approach and asymptotically optimum estimator for target motion analysis

The problem of target motion analysis (TMA) has been extensively investigated based on bearing-only (BO), Doppler-bearing (DB), and other measurement data. For radio frequency (RF) emitters, signal powers follow the well-known path loss law that can be utilized to aid localization and tracking of targets in BO-TMA, leading to the novel power-bearing (PB) approach as proposed in this paper. We begin our study with the standard error-invariable (EIV) model to which the total least-squares (TLS) solution is known to be the maximum likelihood estimate (MLE), if errors are normal and i.i.d. (identically and independently distributed). However the EIV model arising from the TMA problem has a special structure in that its error matrix is diagonal. Although the TLS algorithm is not an MLE for such a class of EIV models, we will show that it is an asymptotic MLE under some mild condition. The results are then applied to develop the novel PB-TMA approach that is shown to be effective via a simulation example. Cramér-Rao lower bound (CRLB) is employed to demonstrate the performance improvements of PB-TMA over the BO-TMA. Our work shows the promise of PB-TMA for RF signals. ©2010 IEEE

Inner-outer factorization for strictly proper transfer matrices

This note considers inner-outer factorization for strictly proper transfer matrices. We provide characterizations to the solution of this particular factorization problem, and develop a computational algorithm to solve it. A numerical example is used to illustrate the proposed theory and algorithm

An Equalization Approach to Feedback Stabilization over Fading Channels

This paper proposes an equalization approach to mean-square (MS) feedback stabilization for multi-input/multi-output (MIMO) discrete-time systems over fading channels. An orthogonal encode/decode matrix pair is placed at the two ends of the fading channel, thereby equalizing the complementary sensitivity in the MS sense. By adopting the notion of the MS stability in an input-output setting, and using the signal-to-noise ratio (SNR) and encode/decode matrix as additional design parameters, we are able to convert the networked stabilization over fading channels into an equivalent constrained H2 optimal control, and derive the MS stabilizability conditions over linear time-invariant controllers. Our results recover the existing MS stabilizability condition under the state feedback. For output feedback control, we provide a characterization of the minimum network resource for the SNR required to stabilize the networked control system over the fading channel, and develop the synthesis algorithms for design of the orthogonal coding matrix and output feedback controller in different scenarios. Our results show that the MS stabilization problem as formulated in this paper admits the closed-form solution for MIMO plants with unstable block zeros, and is mathematically tractable for more general MIMO plants. Two numerical examples are worked out to illustrate our results