Revisiting Johnson and Jackson boundary conditions for granular flows

In this article, we revisit Johnson and Jackson boundary conditions for granular flows. The oblique collision between a particle and a flat wall is analyzed by adopting the classic rigid‐body theory and a more realistic semianalytical model. Based on the kinetic granular theory, the input parameter for the partial‐slip boundary conditions, specularity coefficient, which is not measurable in experiments, is then interpreted as a function of the particle‐wall restitution coefficient, the frictional coefficient, and the normalized slip velocity at the wall. An analytical expression for the specularity coefficient is suggested for a flat, frictional surface with a low frictional coefficient. The procedure for determining the specularity coefficient for a more general problem is outlined, and a working approximation is provided. Published 2011 American Institute of Chemical Engineers, 2012     

Perovskite Formation and Dielectric Responses in PZN Modified PMF-PZT Ceramics

PMF-PZN-PZT （0.01Pb（Mol/3Fe2/3）O3-xPb（Znl/3Nb2/3）O3-（O.99-x）P（Zro53Tio 47）03 piezoelectric ceramics）, where x = 0.00 0.01, 0.03, 0.05 and 0.07 were prepared by a conventional mixed-oxide method. The results show that the pure peroveskit phase forms in these ceramics. X-ray diffraction analysis indicated that the phase of the material is a MPB （morphotropic phase boundary） structure. The effects of PZN content on the crystal structure and electrical properties were investigated, optimal dielectric properties were achieved at composition x = 0.07 ceramics by calcination at 800 ℃ and sintering at 1,180 ℃, with a curie temperature of approximately 430 ℃. These results clearly show the significance of PZN in controlling the electrical responses of the PMF-PZN-PZT system.     

A physically based diode model for circuit simulation

A physically based power PiN diode model is presented. Eigen value internal approximation method is used to solve the ambipolar diffusion equation. This model is implemented in SIMPLORER circuit simulator using VHDL‐AMS language. The proposed model can be used in both circuit simulators and the optimization of a given power PiN diode. Good agreement is obtained by comparing the results of the suggested model with experimental data. Copyright © 2013 John Wiley & Sons, Ltd.     

Constrained model predictive control for time-varying delay systems: Application to an active car suspension

This study investigates the problem of robust model predictive control (RMPC) for active suspension systems with time-varying delays and input constraints. The uncertainty is of convex polytopic type. Based on the Lyapunov-Krasovskii functional method, sufficient stability conditions of the time-varying delays systems are derived by linear matrix inequalities (LMIs) terms. At each time set, a feasible state feedback is obtained by minimizing an upper bound of the ‘worst-case’ quadratic objective function over an infinite horizon subject to constraints on inputs. Finally, a quarter-vehicle model is exploited to demonstrate the effectiveness of the proposed method.     

Maintainability defects detection and correction: a multi-objective approach

Software defects often lead to bugs, runtime errors and software maintenance difficulties. They should be systematically prevented, found, removed or fixed all along the software lifecycle. However, detecting and fixing these defects is still, to some extent, a difficult, time-consuming and manual process. In this paper, we propose a two-step automated approach to detect and then to correct various types of maintainability defects in source code. Using Genetic Programming, our approach allows automatic generation of rules to detect defects, thus relieving the designer from a fastidious manual rule definition task. Then, we correct the detected defects while minimizing the correction effort. A correction solution is defined as the combination of refactoring operations that should maximize as much as possible the number of corrected defects with minimal code modification effort. We use the Non-dominated Sorting Genetic Algorithm (NSGA-II) to find the best compromise. For six open source projects, we succeeded in detecting the majority of known defects, and the proposed corrections fixed most of them with minimal effort.     

A Nonparametric Approach to Design Fixed-order Controllers for Systems with Constrained Input

International Journal of Control, Automation and Systems - This paper presents an approach for designing fixed-structure controllers for input-constrained linear systems using frequency domain...     

Pansharpening multispectral remote sensing data by multiplicative joint nonnegative matrix factorization

Pansharpening aims at combining observable panchromatic and multispectral images to generate an unobservable image with the high spatial resolution of the former and the spectral diversity of the latter. In this paper a new fusion method is proposed. This method, related to linear spectral unmixing (LSU) techniques and based on non-negative matrix factorization (NMF), optimizes, by new iterative–multiplicative update rules, a joint criterion that exploits a spatial degradation model between the two images. The proposed Multiplicative Joint Non-negative Matrix Factorization (MJNMF) approach is applied to synthetic and real data, and its effectiveness in spatial and spectral domains is evaluated with commonly used performance criteria. Experimental results show that the proposed method yields good spectral and spatial fidelities of the pansharpened data. Also, it outperforms those tested from the literature.     

Deep mining port scans from darknet

TCP/UDP port scanning or sweeping is one of the most common technique used by attackers to discover accessible and potentially vulnerable hosts and applications. Although extracting and distinguishing different port scanning strategies is a challenging task, the identification of dependencies among probed ports is primordial for profiling attacker behaviors, with a final goal of better mitigating them. In this paper, we propose an approach that allows to track port scanning behavior patterns among multiple probed ports and identify intrinsic properties of observed group of ports. Our method is fully automated based on graph modeling and data mining techniques, including text mining. It provides to security analysts and operators relevant information about services that are jointly targeted by attackers. This is helpful to assess the strategy of the attacker by understanding the types of applications or environment he or she targets. We applied our method to data collected through a large Internet telescope (or darknet).     

Quantifying the uncertainty introduced by discretization and time‐averaging in two‐fluid model predictions

The two‐fluid model (TFM) has become a tool for the design and troubleshooting of industrial fluidized bed reactors. To use TFM for scale up with confidence, the uncertainty in its predictions must be quantified. Here, we study two sources of uncertainty: discretization and time‐averaging. First, we show that successive grid refinement may not yield grid‐independent transient quantities, including cross‐section–averaged quantities. Successive grid refinement would yield grid‐independent time‐averaged quantities on sufficiently fine grids. Then a Richardson extrapolation can be used to estimate the discretization error, and the grid convergence index gives an estimate of the uncertainty. Richardson extrapolation may not work for industrial‐scale simulations that use coarse grids. We present an alternative method for coarse grids and assess its ability to estimate the discretization error. Second, we assess two methods (autocorrelation and binning) and find that the autocorrelation method is more reliable for estimating the uncertainty introduced by time‐averaging TFM data. © 2017 American Institute of Chemical Engineers AIChE J, 63: 5343–5360, 2017     

Interval force/position modeling and control of a microgripper composed of two collaborative piezoelectric actuators and its automation

This paper deals with the modeling and control of a microgripper devoted to micromanipulation and microassembly applications and tasks. Based on two collaborative piezoelectric actuators, the microgripper is typified by a high sensitivity to the environment, in particular a high sensitivity to the properties of the manipulated objects. This sensitivity makes the behavior of the microgripper variable and uncertain versus the environment and consequently makes the tasks lose performances. A possible way to overstep that problem is to model the microgripper behavior and its dependency with the environment as perfect as possible and then calculate a controller from this. However, such model is complex to handle and the yielded controllers are often very complex for implementation. In this paper, we propose to use interval models to describe the behavior of the piezoelectric actuators that compose the microgripper. Then a controllers synthesis consisting in combining interval techniques and classical control theory is proposed. Both the position and the force raised in the microgripper are considered. The main advantages of the proposed technique are: 1) ease and natural way to model the uncertainties, 2) the robustness of the synthesized controllers, 3) and the derivation of low order controllers that are easier for implementation relative to those of classical robust control techniques. Finally, the paper presents the application of the controlled microgripper to an automated pick-transport-andplace task of micro-objects. This automated task demonstrates the efficiency of the control technique in micromanipulation and microassembly applications.