Mobile tele-echography: user interface design.

Ultrasound imaging allows the evaluation of the degree of emergency of a patient. However, in some instances, a well-trained sonographer is unavailable to perform such echography. To cope with this issue, the Mobile Tele-Echography Using an Ultralight Robot (OTELO) project aims to develop a fully integrated end-to-end mobile tele-echography system using an ultralight remote-controlled robot for population groups that are not served locally by medical experts. This paper focuses on the user interface of the OTELO system, consisting of the following parts: an ultrasound video transmission system providing real-time images of the scanned area, an audio/video conference to communicate with the paramedical assistant and with the patient, and a virtual-reality environment, providing visual and haptic feedback to the expert, while capturing the expert's hand movements. These movements are reproduced by the robot at the patient site while holding the ultrasound probe against the patient skin. In addition, the user interface includes an image processing facility for enhancing the received images and the possibility to include them into a database.     

Access Time Minimization for Distributed Multimedia Applications

The problem of minimizing the access time of a requested multimedia (MM) document on a network based environment is addressed. A generalized version of this problem is formulated and retrieval strategies that minimize the access time of the user-requested MM document from a pool of MM servers are proposed. To this end, we design single-installment and multi-installment MM document retrieval strategies, through which the minimization of access time can be carried out. The main idea is to utilize more than one MM server in downloading the requested document. Each server assumes the responsibility of uploading a predetermined portion of the entire document in a particular order. Single- and multi-installment strategies differ in the number of disjoint document pieces each server sends to the client. We first introduce a directed flow graph (DFG) model to represent the retrieval process and generate a set of recursive equations using this DFG. Then, we derive closed-form solutions for the portions of the MM document downloaded from the various servers and the corresponding access time. We present rigorous analysis for these two strategies and show their performance under MPEG-I and MPEG-II video streams playback rates. Their behavior under different network bandwidths is also examined, revealing in-depth information about their expected performance. We also show that in the case of a multi-installment strategy, the access time can be completely controlled by fine tuning the number of installments. Since the number of installments is software tunable, the adaptive nature of the strategies to different channel bandwidths is also demonstrated. Important trade-off studies with respect to the number of servers involved in the retrieval process and the number of installments are presented. In the case of a heterogeneous network employing a single-installment strategy, we prove that the access time is independent of the server sequence used. Illustrative examples are provided for ease of understanding.     

New partial differential equations governing the joint, response–excitation, probability distributions of nonlinear systems, under general stochastic excitation

In the present work the problem of determining the probabilistic structure of the dynamical response of nonlinear systems subjected to general, external, stochastic excitation is considered. The starting point of our approach is a Hopf-type equation, governing the evolution of the joint, response–excitation, characteristic functional. Exploiting this equation, we derive new linear partial differential equations governing the joint, response–excitation, characteristic (or probability density) function, which can be considered as an extension of the well-known Fokker–Planck–Kolmogorov equation to the case of a general, correlated excitation and, thus, non-Markovian response character. These new equations are supplemented by initial conditions and a marginal compatibility condition (with respect to the known probability distribution of the excitation), which is of non-local character. The validity of this new equation is also checked by showing its equivalence with the infinite system of moment equations. The method is applicable to any differential system, in state-space form, exhibiting polynomial nonlinearities. In this paper the method is illustrated through a detailed analysis of a simple, first-order, scalar equation, with a cubic nonlinearity. It is also shown that various versions of Fokker–Planck–Kolmogorov equation, corresponding to the case of independent-increment excitations, can be derived by using the same approach.

A numerical method for the solution of these new equations is introduced and illustrated through its application to the simple model problem. It is based on the representation of the joint probability density (or characteristic) function by means of a convex superposition of kernel functions, which permits us to satisfy a priori the non-local marginal compatibility condition. On the basis of this representation, the partial differential equation is eventually transformed to a system of ordinary differential equations for the kernel parameters. Extension to general, multidimensional, dynamical systems exhibiting any polynomial nonlinearity will be presented in a forthcoming paper.     

Controlling aggregate thin film surface morphology for improved light trapping using a patterned deposition rate profile

This work focuses on modeling and control of aggregate thin film surface morphology for improved light trapping using a patterned deposition rate profile. The dynamics of the evolution of the thin film surface height profile are modeled by an Edwards–Wilkinson-type equation (a second-order stochastic partial differential equation) in two spatial dimensions. The thin film surface morphology is characterized in terms of aggregate surface roughness and surface slope. These variables are computed with respect to appropriate visible light-relevant characteristic length scales and defined as the root-mean-squares of height deviation and slope of aggregate surface height profiles, respectively. Analytical solutions of the expected aggregate surface roughness and surface slope are obtained by solving the Edwards–Wilkinson equation and are used in the controller design. The model parameters of the Edwards–Wilkinson equation are estimated from kinetic Monte-Carlo simulations using a novel parameter estimation procedure. This parameter dependence on the deposition rate is used in the formulation of the predictive controller to predict the influence of the control action on the surface roughness and slope at the end of the growth process. The cost function of the controller involves penalties on both aggregate surface roughness and mean slope from set-point values as well as constraints on the magnitude and rate of change of the control action. The controller is applied to the two-dimensional Edwards–Wilkinson equation. Simulation results show that the proposed controller successfully regulates aggregate surface roughness and slope to set-point values at the end of the deposition that yield desired levels of thin film reflectance and transmittance.     

Dynamics and control of aggregate thin film surface morphology for improved light trapping: Implementation on a large-lattice kinetic Monte Carlo model

This work demonstrates the use of feedback control, coupled with a suitable actuator design, in manufacturing thin films whose surface morphology is characterized by a desired visible light reflectance/transmittance level. The problem is particularly important in the context of thin film manufacturing for thin film solar cells where it is desirable to produce thin films with precisely tailored light trapping characteristics. Initially, a thin film deposition process involving atom adsorption and surface migration is considered and is modeled using a large-lattice (lattice size=40,000) kinetic Monte Carlo simulation. Subsequently, thin film surface morphology characteristics like roughness and slope are computed with respect to different characteristic length scales ranging from atomic to the ones corresponding to visible light wavelength and it is found that a patterned actuator design is needed to induce thin film surface roughness and slope at visible light wavelength spatial scales, which lead to desired thin film reflectance and transmittance levels. Then, an Edwards–Wilkinson-type equation (a second-order stochastic partial differential equation) is used to model the surface evolution at the visible light wavelength spatial scale and form the basis for the design of a feedback controller whose objective is to manipulate the deposition rate across the spatial domain of the process. The model parameters of the Edwards–Wilkinson equation are estimated from kinetic Monte Carlo simulations and their dependence on the deposition rate is used in the formulation of the predictive controller to predict the influence of the control action on the surface roughness and slope throughout the thin film growth process. Analytical solutions of the expected surface roughness and surface slope at the visible light wavelength spatial scale are obtained by solving the Edwards–Wilkinson equation and are used in the control action calculation. The cost function of the controller involves penalties on both surface roughness and slope from set-point values as well as constraints on the magnitude and rate of change of the control action. The controller is applied to the large-lattice kinetic Monte Carlo simulation. Simulation results demonstrate that the proposed controller and patterned actuator design successfully regulate aggregate surface roughness and slope to set-point values at the end of the deposition that yield desired levels of thin film reflectance and transmittance.     

Modeling and control of protein crystal shape and size in batch crystallization

In this work, the modeling and control of a batch crystallization process used to produce tetragonal hen egg white lysozyme crystals are studied. Two processes are considered, crystal nucleation and growth. Crystal nucleation rates are obtained from previous experiments. The growth of each crystal progresses via kinetic Monte Carlo simulations comprising of adsorption, desorption, and migration on the (110) and (101) faces. The expressions of the rate equations are similar to Durbin and Feher. To control the nucleation and growth of the protein crystals and produce a crystal population with desired shape and size, a model predictive control (MPC) strategy is implemented. Specifically, the steady‐state growth rates for the (110) and (101) faces are computed and their ratio is expressed in terms of the temperature and protein concentration via a nonlinear algebraic equation. The MPC method is shown to successfully regulate both the crystal size and shape distributions to different set‐point values. © 2013 American Institute of Chemical Engineers AIChE J, 59: 2317–2327, 2013     

电力市场条件下的工业负荷管理

讨论了竞争性电力市场的模式以及电价在竞争性电力市场中的波动性;论述了竞争性电力市场中的工业电力终端用户与电力供应商之间可能签订的合同;以某国的工业负荷GISASA为案例,分析了在竞争的电力市场中,电力用户为了避免或减少风险,如何通过合同和合适的产品战略获得电力供应和进行电力负荷管理.     

Parallel algorithms for reducing derivation time of distinguishing experiments for nondeterministic finite state machines

Many approaches have been proposed for deriving tests from finite state machine (FSM) specifications with respect to some established coverage criteria. A fundamental core problem in FSM-based testing relates to the derivation of input sequences that can distinguish states of an FSM specification, aka distinguishing sequences. A major effort in the construction of these sequences is based on the derivation of a successors search-tree labeled by sets of pairs of states of the given machine. We aim at reducing the time associated with such constructions through the use of state-of-the-art parallel technologies. Namely, we propose a parallel algorithm that we implement and evaluate on multicore CPUs and on many-core GPUs. We evaluate two alternative GPU implementations that use the CUDA and Thrust software platforms and a network of workstations based solution. The latter sports a workload partitioning based on Divisible Load Theory. A rigorous set of experiments highlights the differences of the proposed implementations in terms of execution time and speedup.     

Dependence of film surface roughness and slope on surface migration and lattice size in thin film deposition processes

This work focuses on the study of the dependence of film surface roughness and slope on lattice size in thin film deposition processes. Two different models of thin film deposition processes, in both 1D and 2D, are considered: random deposition with surface relaxation model and deposition/migration model. Surface roughness and surface slope are defined as the root-mean-squares of the surface height profile and of the surface slope profile, respectively. Both surface roughness and slope evolve to steady-state values at large times but are subject to different dynamics and scaling properties. A linear and a logarithmic dependence of surface roughness square on lattice size are observed in the 1D and 2D lattice models, respectively, in both the random deposition with surface relaxation model and the deposition/migration model with zero activation energy contribution from each neighboring particle. Furthermore, a stronger lattice-size dependence is found in the deposition/migration model when the migration activation energy contribution from each neighboring particle becomes significant. On the other hand, a weak lattice-size dependence is found for the surface mean slope in all growth models considered, especially at large lattice sizes. Finally, the dynamics of surface roughness and surface slope is studied with respect to different characteristic length scales.     

Optimal pyramidal and subband decompositions for hierarchicalcoding of noisy and quantized images

Optimal hierarchical coding is sought, for progressive or scalable image transmission, by minimizing the variance of the error difference between the original image and its lower resolution renditions. The optimal, according to the above criterion, pyramidal and subband image coders are determined for images subject to corruption by quantization or transmission noise. Given arbitrary analysis filters and assuming adequate knowledge of the noise statistics, optimal synthesis filters are found. The optimal analysis filters are subsequently determined, leading to formulas for globally optimal structures for pyramidal and subband image decompositions. Experimental results illustrate the implementation and performance of the optimal coders.