Call for papers Journal of Control Theory and Applications Special issue on Approximate dynamic programming and reinforcement learning

Approximate dynamic programming (ADP) is a general and effective approach for solving optimal control and estimation problems by adapting to uncertain and nonconvex environments over time.

THE APPLICATION OF COMPATIBLE STRESS ITERATIVE METHOD IN DYNAMIC FINITE ELEMENT ANALYSIS OF HIGH VELOCITY IMPACT

There is a common difficulty in elastic-plastic impact codes such as EPIC[2,3] NONSAP[4], etc.. Most of these codes use the simple linear functions usually taken from static problem to represent the displacement components. In such finite element formulation, the stress components are constant in each element and they are discontinuous in any two neighboring elements. Therefore, the bases of using the virtual work principle in such elements are unreliable. In this paper, we introduce a new method, namely, the compatible stress iterative method, to eliminate the above-said difficulty. The calculated examples show that the calculation using the new method in dynamic finite element analysis of high velocity impact is valid and stable, and the element stiffness can be somewhat reduced.

Hybrid Security Assessment Methodology for Web Applications

This study presents a methodology to evaluate and prevent security vulnerabilities issues for web applications.The analysis process is based on the use of techniques and tools that allow to perform security assessments of white box and black box,to carry out the security validation of a web application in an agile and precise way.The objective of the methodology is to take advantage of the synergies of semi-automatic static and dynamic security analysis tools and manual checks.Each one of the phases contemplated in the methodology is supported by security analysis tools of different degrees of coverage,so that the results generated in one phase are used as feed for the following phases in order to get an optimized global security analysis result.The methodology can be used as part of other more general methodologies that do not cover how to use static and dynamic analysis tools in the implementation and testing phases of a Secure Software Development Life Cycle(SSDLC).A practical application of the methodology to analyze the security of a real web application demonstrates its effectiveness by obtaining a better optimized vulnerability detection result against the true and false positive metrics.Dynamic analysis with manual checking is used to audit the results,24.6 per cent of security vulnerabilities reported by the static analysis has been checked and it allows to study which vulnerabilities can be directly exploited externally.This phase is very important because it permits that each reported vulnerability can be checked by a dynamic second tool to confirm whether a vulnerability is true or false positive and it allows to study which vulnerabilities can be directly exploited externally.Dynamic analysis finds six(6)additional critical vulnerabilities.Access control analysis finds other five(5)important vulnerabilities such as Insufficient Protected Passwords or Weak Password Policy and Excessive Authentication Attacks,two vulnerabilities that permit brute force attacks.

Observation and modeling of tide- and wind-induced surface currents in Galway Bay

A high-frequency radar system has been deployed in Galway Bay, a semi-enclosed bay on the west coast of Ireland. The system provides surface currents with fine spatial resolution every hour. Prior to its use for model validation, the accuracy of the radar data was verified through comparison with measurements from acoustic Doppler current profilers （ADCPs） and a good correlation between time series of surface current speeds and directions obtained from radar data and ADCP data. Since Galway Bay is located on the coast of the Atlantic Ocean, it is subject to relatively windy conditions, and surface currents are therefore strongly wind-driven. With a view to assimilating the radar data for forecasting purposes, a three-dimensional numerical model of Galway Bay, the Environmental Fluid Dynamics Code （EFDC）, was developed based on a terrain-following vertical （sigma） coordinate system. This study shows that the performance and accuracy of the numerical model, particularly with regard to tide- and wind-induced surface currents, are sensitive to the vertical layer structure. Results of five models with different layer structures are presented and compared with radar measurements. A variable vertical structure with thin layers at the bottom and the surface and thicker layers in the middle of the water column was found to be the optimal layer structure for reproduction of tideand wind-induced surface currents. This structure ensures that wind shear can properly propagate from the surface layer to the sub-surface layers, thereby ensuring that wind forcing is not overdamped by tidal forcing. The vertical layer structure affects not only the velocities at the surface layer but also the velocities further down in the water column.

Extraction and application of the low dimensional dynamical component from underwater acoustic target radiating noise

Signal processing in phase space based on nonlinear dynamics theory is a new method for underwater acoustic signal processing. One key problem when analyzing actual acoustic signal in phase space is how to reduce the noise and lower the embedding dimen- sion. In this paper, local-geometric-projection method is applied to obtain fow dimensional element from various target radiating noise and the derived phase portraits show obviously low dimensional attractors. Furthermore, attractor dimension and cross prediction error are used for classification. It concludes that combining these features representing the geometric and dynamical properties respectively shows effects in target classification.

Comparison of selected algorithms for scheduling workflow applications with dynamically changing service availability

This paper compares the quality and execution times of several algorithms for scheduling service based workflow applications with changeable service availability and parameters. A workflow is defined as an acyclic directed graph with nodes corresponding to tasks and edges to dependencies between tasks. For each task, one out of several available services needs to be chosen and scheduled to minimize the workflow execution time and keep the cost of service within the budget. During the execution of a workflow, some services may become unavailable, new ones may appear, and costs and execution times may change with a certain probability. Rescheduling is needed to obtain a better schedule. A solution is proposed on how integer linear programming can be used to solve this problem to obtain optimal solutions for smaller problems or suboptimal solutions for larger ones. It is compared side-by-side with GAIN, divide-and-conquer, and genetic algorithms for various probabilities of service unavailability or change in service parameters. The algorithms are implemented and subsequently tested in a real BeesyCluster environment.

ENGINEERING APPLICATION OF COMPUTATIONAL FLUID DYNAMICS——THE STATE OF ART

The state of art and future prospects are described for the application of the computational fluid dynamics to engineering purposes.2D and 3D simulations are presented for a flow about a pair of bridges,a flow about a cylin- der in waves,a flow about an airplane and a ship,a flow past a sphere,a two layers flow and a flow in a wall boundary layer,The choice of grid system and of turbulence modei is discussed.

Bidirectional Feedback Dynamic Particle Filter with Big Data for the Particle Degeneracy Problem

Particle Filter （PF） is a data assimilation method to solve recursive state estimation problem which does not depend on the assumption of Gaussian noise, and is able to be applied for various systems even with non-linear and non-Gaussian noise. However, while applying PF in dynamic systems, PF undergoes particle degeneracy, sample impoverishment, and problems of high computational complexity. Rapidly developing sensing technologies are providing highly convenient availability of real-time big traffic data from the system under study like never before. Moreover, some sensors can even receive control commands to adjust their monitoring parameters. To address these problems, a bidirectional dynamic data-driven improvement framework for PF （B3DPF） is proposed. The B3DPF enhances feedback between the simulation model and the big traffic data collected by the sensors, which means the execution strategies （sensor data management, parameters used in the weight computation, resampling） of B3DPF can be optimized based on the simulation results and the types and dimensions of traffic data injected into B3DPF can be adjusted dynamically. The first experiment indicates that the B3DPF overcomes particle degeneracy and sample impoverishment problems and accurately estimates the state at a faster speed than the normal PF. More importantly, the new method has higher accuracy for multidimensional random systems. In the rest of experiments, the proposed framework is applied to estimate the traffic state on a real road network and obtains satisfactory results. More experiments can be designed to validate the universal properties of B3DPF.