Multi-sensor Transmission Management for Remote State Estimation under Coordination

This paper considers the remote state estimation in a cyber-physical system (CPS) using multiple sensors. The measurements of each sensor are transmitted to a remote estimator over a shared channel, where simultaneous transmissions from other sensors are regarded as interference signals. In such a competitive environment, each sensor needs to choose its transmission power for sending data packets taking into account of other sensors’ behavior. To model this interactive decision-making process among the sensors, we introduce a multi-player non-cooperative game framework. To overcome the inefficiency arising from the Nash equilibrium (NE) solution, we propose a correlation policy, along with the notion of correlation equilibrium (CE). An analytical comparison of the game value between the NE and the CE is provided, with/without the power expenditure constraints for each sensor. Also, numerical simulations demonstrate the comparison results

Optimal unbiased linear sensor fusion over multiple lossy channels with collective observability

In this paper, we consider optimal linear sensor fusion for obtaining a remote state estimate of a linear process based on the sensor data transmitted over lossy channels. There is no local observability guarantee for any of the sensors. It is assumed that the state of the linear process is collectively observable. We transform the problem of finding the optimal linear sensor fusion coefficients as a convex optimization problem which can be efficiently solved. Moreover, the closed-form expression is also derived for the optimal coefficients. Simulation results are presented to illustrate the performance of the developed algorithm.The work by Y. Wu and L. Shi is supported by a Hong Kong RGC General Research Fund, Hong Kong Special Administrative Region 16204218. The work of Y. Li was supported by National Natural Science Foundation of China, China (61890924, 61991404), and Liao Ning Revitalization Talents Program (XLYC1907087)

A multi-channel transmission schedule for remote state estimation under DoS attacks

This paper considers a cyber-physical system (CPS) under denial-of-service (DoS) attacks. The measurements of a sensor are transmitted to a remote estimator over a multi-channel network, which may be congested by a malicious attacker. Among these multiple communication paths with different characteristics and properties at each time step, the sensor needs to choose a single channel for sending data packets while reducing the probability of being attacked. In the meanwhile, the attacker needs to decide the target channel to jam under an energy budget constraint. To model this interactive decision-making process between the two sides, we formulate a two-player zero-sum stochastic game framework. A Nash Q-learning algorithm is proposed to tackle the computation complexity when solving the optimal strategies for both players. Numerical examples are provided to illustrate the obtained results

Comparison of Statistical Learning and Predictive Models on Breast Cancer Data and King County Housing Data

In this study, we evaluate the predictive performance of popular statistical learning methods, such as discriminant analysis, random forests, support vector machines, and neural networks via real data analysis. Two datasets, Breast Cancer Diagnosis in Wisconsin and House Sales in King County, are analyzed respectively to obtain the best models for prediction. Linear and Quadratic Discriminant Analysis are used in WDBC data set. Linear Regression and Elastic Net are used in KC house data set. Random Forest, Gradient Boosting Method, Support Vector Machines, and Neural Network are used in both datasets. Individual models and stacking of models are trained based on accuracy or R-squared from repeated cross-validation of training sets. The final models are evaluated by using test sets

Study on the strata displacement law of overlapping shield tunnels with different overlapping angles

Based on the overlapping tunnel of Tel Aviv Red Line Light Rail Project in Israel, this study established a three-dimensional numerical model by using Rhino6 and FLAC3D software on the basis of analysis of on-site monitoring data, to investigate the ground settlement and stratum displacement laws of shield overlapping tunnel at different overlapping angles.Results show that when the two tunnels gradually transit from horizontal to overlapping state, with the increase of overlapping angle of the two tunnels, the accumulated settlement at the measuring points in the middle of the two tunnels increases, but the accumulated settlement is not only affected by overlapping angle, but also closely related to the stratum traversing situation.Under the stratum condition of the project, when the overlapping angle is 60°, the accumulated surface settlement reaches the maximum because both tunnels pass through the loose reservoir K1 stratum.When the overlapping angle of the rear-built tunnel is less than 45° after excavation, the width of the settlement trough increases.When the overlapping angle is larger than 45° and smaller than 60°, the width of the settlement trough remains unchanged.The width of settlement trough decreases when the overlapping angle is larger than 60°.When the overlapping angle reaches 90°, the settlement trough is symmetrical on both sides.After excavation of tunnels on both sides, when the overlapping angle of the tunnels reaches 75°, the strata on both sides change the direction of movement.This research offer reference for the design and construction of overlapping tunnels

Effect of cold rolling on microstructure and mechanical property of a novel (Fe50Mn30Co10Cr10)97C2Mo1 high entropy alloy

Effect of cold rolling on microstructural evolution and mechanical properties of a novel (Fe50Mn30Co10Cr10)97C2Mo1 high entropy alloy has been investigated via electron microscopy and tensile testing. The results show that the alloy is mainly deformed via dislocation and twinning due to its low stacking fault energy. With increasing thickness reduction, the dislocation density first increases, up to a maximum of ∼29.3 × 1014 m−2 at CR 60 %, then reduces, to 21.1 × 1014 m−2 at CR 90 %. The width and spacing of the deformation twins gradually decrease with an increase of thickness reduction. TEM examination also reveals that shear bands produce in CR 40 % sample, and that its volume fraction gradually increases with increasing thickness reduction. Such microstructural evolution with cold rolling, gives rise to a quick enhancement of yield strength of the alloy (1926 MPa for CR 90 % vs. 239 MPa for the as-homogenized sample) whereas a clear loss in ductility. However, the cold-rolled samples at low to medium strains show a good combination of strength and ductility, e.g., CR 20 % sample has a yield strength of 800 MPa (, which is 3.3 times higher than that of as-homogenized HEA) and an elongation of 30 %, while 1300 MPa yield strength and 15 % elongation for CR 40 % sample

Dynamic Evolution Modeling of a Lake-Terminating Glacier in the Western Himalayas Using a Two-Dimensional Higher-Order Flowline Model

To better understand the future evolution of Jiemayangzong Glacier (JMYZG), the headstream of the Yarlung Zangbo River, we simulated its future ice thickness evolution using a two-dimensional higher-order numerical flowline model. Due to the sparsity of in situ observational data, we used a combination of field observations and inversion models of velocity and ice thickness to initialize the model parameters. We validated the parametrizations of the calving scheme by comparing the modeled and observed glacier terminus retreats. To estimate the response of JMYZG to climate change, the ice flow model was forced with different climate scenarios. We found that the JMYZG will retreat under different climate scenarios. By 2100, the volume loss of JMYZG will be approximately 34%, 67% and 81% under SSP1-2.6, SSP3-7.0 and SSP5-8.5, respectively

Dynamic Evolution Modeling of a Lake-Terminating Glacier in the Western Himalayas Using a Two-Dimensional Higher-Order Flowline Model

To better understand the future evolution of Jiemayangzong Glacier (JMYZG), the headstream of the Yarlung Zangbo River, we simulated its future ice thickness evolution using a two-dimensional higher-order numerical flowline model. Due to the sparsity of in situ observational data, we used a combination of field observations and inversion models of velocity and ice thickness to initialize the model parameters. We validated the parametrizations of the calving scheme by comparing the modeled and observed glacier terminus retreats. To estimate the response of JMYZG to climate change, the ice flow model was forced with different climate scenarios. We found that the JMYZG will retreat under different climate scenarios. By 2100, the volume loss of JMYZG will be approximately 34%, 67% and 81% under SSP1-2.6, SSP3-7.0 and SSP5-8.5, respectively

A Label-Free, Mix-and-Detect ssDNA-Binding Assay Based on Cationic Conjugated Polymers

The accurate, simple, and efficient measurement of the concentration of single-stranded DNA (ssDNA) is important for many analytical applications, such as DNA adsorption, biosensor design, and disease diagnosis, but it is still a challenge. Herein, we studied a cationic conjugated polymer (CCP)-based ssDNA assay taking advantage of the obvious fluorescence change of CCPs upon binding ssDNA. Poly(3-(3′-N,N,N-triethylamino-1′-propyloxy)-4-methyl-2,5-thiophene hydrochloride) (PMNT) achieved an apparent dissociation constant (Kd) of 57 ± 4 nM for ssDNA, indicating a very high binding affinity between PMNT and ssDNA. This allowed us to develop a CCP-based ssDNA biosensor with a detection limit of 0.6 nM, similar to the fluorescence-dye-based method using SYBR Green I and SYBR Gold. Our CCP-based biosensor produced smaller differences among ssDNA samples with different base compositions. In addition, the existence of double-stranded DNA (dsDNA) at different concentrations did not interfere with the fluorescence of PMNT, indicating that our CCP-based biosensor was more suitable for the measurement of ssDNA. Compared with fluorescence-intensity-based quantification, our CCP system allowed ratiometric quantification, which made the calibration easier and more robust. We then applied our method to the quantification of ssDNA on AuNPs using both unmodified and thiolated ssDNA, and the accurate quantification of ssDNA was achieved without any fluorophore modification. This method provides an alternative approach for the measurement of ssDNA