On Adaptive Optimization of Filter Performance Based on Markov Representation for Output Prediction Error

This paper addresses the problem of how one can improve the performance of a non-optimal filter. First the theoretical question on dynamical representation for a given time correlated random process is studied. It will be demonstrated that for a wide class of random processes, having a canonical form, there exists a dynamical system equivalent in the sense that its output has the same covariance function. It is shown that the dynamical approach is more effective for simulating and estimating a Markov and non- Markovian random processes, computationally is less demanding, especially with increasing of the dimension of simulated processes. Numerical examples and estimation problems in low dimensional systems are given to illustrate the advantages of the approach. A very useful application of the proposed approach is shown for the problem of state estimation in very high dimensional systems. Here a modified filter for data assimilation in an oceanic numerical model is presented which is proved to be very efficient due to introducing a simple Markovian structure for the output prediction error process and adaptive tuning some parameters of the Markov equation.

Studying on ARINC653 Partition Run-time Scheduling and Simulation

Avionics software is safe-critical embedded software and its architecture is evolving from traditional federated architectures to Integrated Modular Avionics (IMA) to improve resource usability. ARINC 653 (Avionics Application Standard Software Interface) is a software specification for space and time partitioning in Safety-critical avionics Real-time operating systems. Arinc653 uses two-level scheduling strategies, but current modeling tools only apply to simple problems of Arinc653 two-level scheduling, which only contain time property. In avionics industry, we are always manually allocating tasks and calculating the timing table of a real-time system to ensure it-s running as we design. In this paper we represent an automatically generating strategy which applies to the two scheduling problems with dependent constraints in Arinc653 partition run-time environment. It provides the functionality of automatic generation from the task and partition models to scheduling policy through allocating the tasks to the partitions while following the constraints, and then we design a simulating mechanism to check whether our policy is schedulable or not

Rotation Invariant Fusion of Partial Image Parts in Vista Creation using Missing View Regeneration

The automatic construction of large, high-resolution image vistas (mosaics) is an active area of research in the fields of photogrammetry [1,2], computer vision [1,4], medical image processing [4], computer graphics [3] and biometrics [8]. Image stitching is one of the possible options to get image mosaics. Vista Creation in image processing is used to construct an image with a large field of view than that could be obtained with a single photograph. It refers to transforming and stitching multiple images into a new aggregate image without any visible seam or distortion in the overlapping areas. Vista creation process aligns two partial images over each other and blends them together. Image mosaics allow one to compensate for differences in viewing geometry. Thus they can be used to simplify tasks by simulating the condition in which the scene is viewed from a fixed position with single camera. While obtaining partial images the geometric anomalies like rotation, scaling are bound to happen. To nullify effect of rotation of partial images on process of vista creation, we are proposing rotation invariant vista creation algorithm in this paper. Rotation of partial image parts in the proposed method of vista creation may introduce some missing region in the vista. To correct this error, that is to fill the missing region further we have used image inpainting method on the created vista. This missing view regeneration method also overcomes the problem of missing view [31] in vista due to cropping, irregular boundaries of partial image parts and errors in digitization [35]. The method of missing view regeneration generates the missing view of vista using the information present in vista itself.

The Estimate Rate of Permanent Flow of a Liquid Simulating Blood by Doppler Effect

To improve the characterization of blood flows, we propose a method which makes it possible to use the spectral analysis of the Doppler signals. Our calculation induces a reasonable approximation, the error made on estimated speed reflects the fact that speed depends on the flow conditions as well as on measurement parameters like the bore and the volume flow rate. The estimate of the Doppler signal frequency enables us to determine the maximum Doppler frequencie Fd max as well as the maximum flow speed. The results show that the difference between the estimated frequencies ( Fde ) and the Doppler frequencies ( Fd ) is small, this variation tends to zero for important θ angles and it is proportional to the diameter D. The description of the speed of friction and the coefficient of friction justify the error rate obtained.

MIMO Performances in Tunnel Environment: Interpretation from the Channel Characteristics

The objective of this contribution is to study the performances in terms of bit error rate, of space-time code algorithms applied to MIMO communication in tunnels. Indeed, the channel characteristics in a tunnel are quite different than those of urban or indoor environment, due to the guiding effect of the tunnel. Therefore, MIMO channel matrices have been measured in a straight tunnel, in a frequency band around 3GHz. Correlation between array elements and properties of the MIMO matrices are first studied as a function of the distance between the transmitter and the receiver. Then, owing to a software tool simulating the link, predicted values of bit error rate are given for VLAST, OSTBC and QSTBC algorithms applied to a MIMO configuration with 2 or 4 array elements. Results are interpreted from the analysis of the channel properties.

Object-Oriented Simulation of Simulating Anticipatory Systems

The present paper is oriented to problems of simulation of anticipatory systems, namely those that use simulation models for the aid of anticipation. A certain analogy between use of simulation and imagining will be applied to make the explication more comprehensible. The paper will be completed by notes of problems and by some existing applications. The problems consist in the fact that simulation of the mentioned anticipatory systems end is simulation of simulating systems, i.e. in computer models handling two or more modeled time axes that should be mapped to real time flow in a nondescent manner. Languages oriented to objects, processes and blocks can be used to surmount the problems.

Applying Similarity Theory and Hilbert Huang Transform for Estimating the Differences of Pig-s Blood Pressure Signals between Situations of Intestinal Artery Blocking and Unblocking

A mammal-s body can be seen as a blood vessel with complex tunnels. When heart pumps blood periodically, blood runs through blood vessels and rebounds from walls of blood vessels. Blood pressure signals can be measured with complex but periodic patterns. When an artery is clamped during a surgical operation, the spectrum of blood pressure signals will be different from that of normal situation. In this investigation, intestinal artery clamping operations were conducted to a pig for simulating the situation of intestinal blocking during a surgical operation. Similarity theory is a convenient and easy tool to prove that patterns of blood pressure signals of intestinal artery blocking and unblocking are surely different. And, the algorithm of Hilbert Huang Transform can be applied to extract the character parameters of blood pressure pattern. In conclusion, the patterns of blood pressure signals of two different situations, intestinal artery blocking and unblocking, can be distinguished by these character parameters defined in this paper.

Numerical Simulation of Convection Heat Transfer in a Lid-Driven Cavity with an Open Side

In this manuscript, the LBM is applied for simulating of Mixed Convection in a Lid-Driven cavity with an open side. The cavity horizontal walls are insulated while the west Lid-driven wall is maintained at a uniform temperature higher than the ambient. Prandtl number (Pr) is fixed to 0.71 (air) while Reynolds number (Re) , Richardson number (Ri) and aspect ratio (A) of the cavity are changed in the range of 50-150 , of 0.1-10 and of 1-4 , respectively. The numerical code is validated for the standard square cavity, and then the results of an open ended cavity are presented. Result shows by increasing of aspect ratio, the average Nusselt number (Nu) on lid- driven wall decreases and with same Reynolds number (Re) by increasing of aspect ratio (A), Richardson number plays more important role in heat transfer rate.

Simulating Pathogen Transport with in a Naturally Ventilated Hospital Ward

Understanding how airborne pathogens are transported through hospital wards is essential for determining the infection risk to patients and healthcare workers. This study utilizes Computational Fluid Dynamics (CFD) simulations to explore possible pathogen transport within a six-bed partitioned Nightingalestyle hospital ward. Grid independence of a ward model was addressed using the Grid Convergence Index (GCI) from solutions obtained using three fullystructured grids. Pathogens were simulated using source terms in conjunction with a scalar transport equation and a RANS turbulence model. Errors were found to be less than 4% in the calculation of air velocities but an average of 13% was seen in the scalar field. A parametric study of variations in the pathogen release point illustrated that its distribution is strongly influenced by the local velocity field and the degree of air mixing present.

The Optimal Placement of Capacitor in Order to Reduce Losses and the Profile of Distribution Network Voltage with GA, SA

Most of the losses in a power system relate to the distribution sector which always has been considered. From the important factors which contribute to increase losses in the distribution system is the existence of radioactive flows. The most common way to compensate the radioactive power in the system is the power to use parallel capacitors. In addition to reducing the losses, the advantages of capacitor placement are the reduction of the losses in the release peak of network capacity and improving the voltage profile. The point which should be considered in capacitor placement is the optimal placement and specification of the amount of the capacitor in order to maximize the advantages of capacitor placement. In this paper, a new technique has been offered for the placement and the specification of the amount of the constant capacitors in the radius distribution network on the basis of Genetic Algorithm (GA). The existing optimal methods for capacitor placement are mostly including those which reduce the losses and voltage profile simultaneously. But the retaliation cost and load changes have not been considered as influential UN the target function .In this article, a holistic approach has been considered for the optimal response to this problem which includes all the parameters in the distribution network: The price of the phase voltage and load changes. So, a vast inquiry is required for all the possible responses. So, in this article, we use Genetic Algorithm (GA) as the most powerful method for optimal inquiry.

A Traffic Simulation Package Based on Travel Demand

In this paper we propose a new traffic simulation package, TDMSim, which supports both macroscopic and microscopic simulation on free-flowing and regulated traffic systems. Both simulators are based on travel demands, which specify the numbers of vehicles departing from origins to arrive at different destinations. The microscopic simulator implements the carfollowing model given the pre-defined routes of the vehicles but also supports the rerouting of vehicles. We also propose a macroscopic simulator which is built in integration with the microscopic simulator to allow the simulation to be scaled for larger networks without sacrificing the precision achievable through the microscopic simulator. The macroscopic simulator also enables the reuse of previous simulation results when simulating traffic on the same networks at later time. Validations have been conducted to show the correctness of both simulators.

Simulating Gradient Contour and Mesh of a Scalar Field

This research paper is based upon the simulation of gradient of mathematical functions and scalar fields using MATLAB. Scalar fields, their gradient, contours and mesh/surfaces are simulated using different related MATLAB tools and commands for convenient presentation and understanding. Different mathematical functions and scalar fields are examined here by taking their gradient, visualizing results in 3D with different color shadings and using other necessary relevant commands. In this way the outputs of required functions help us to analyze and understand in a better way as compared to just theoretical study of gradient.

A Neural Model of Object Naming

One astonishing capability of humans is to recognize thousands of different objects visually, and to learn the semantic association between those objects and words referring to them. This work is an attempt to build a computational model of such capacity,simulating the process by which infants learn how to recognize objects and words through exposure to visual stimuli and vocal sounds.One of the main fact shaping the brain of a newborn is that lights and colors come from entities of the world. Gradually the visual system learn which light sensations belong to same entities, despite large changes in appearance. This experience is common between humans and several other mammals, like non-human primates. But humans only can recognize a huge variety of objects, most manufactured by himself, and make use of sounds to identify and categorize them. The aim of this model is to reproduce these processes in a biologically plausible way, by reconstructing the essential hierarchy of cortical circuits on the visual and auditory neural paths.

Involving Action Potential Morphology on a New Cellular Automata Model of Cardiac Action Potential Propagation

Computer modeling has played a unique role in understanding electrocardiography. Modeling and simulating cardiac action potential propagation is suitable for studying normal and pathological cardiac activation. This paper presents a 2-D Cellular Automata model for simulating action potential propagation in cardiac tissue. We demonstrate a novel algorithm in order to use minimum neighbors. This algorithm uses the summation of the excitability attributes of excited neighboring cells. We try to eliminate flat edges in the result patterns by inserting probability to the model. We also preserve the real shape of action potential by using linear curve fitting of one well known electrophysiological model.

Lattice Boltzmann Simulation of Binary Mixture Diffusion Using Modern Graphics Processors

A highly optimized implementation of binary mixture diffusion with no initial bulk velocity on graphics processors is presented. The lattice Boltzmann model is employed for simulating the binary diffusion of oxygen and nitrogen into each other with different initial concentration distributions. Simulations have been performed using the latest proposed lattice Boltzmann model that satisfies both the indifferentiability principle and the H-theorem for multi-component gas mixtures. Contemporary numerical optimization techniques such as memory alignment and increasing the multiprocessor occupancy are exploited along with some novel optimization strategies to enhance the computational performance on graphics processors using the C for CUDA programming language. Speedup of more than two orders of magnitude over single-core processors is achieved on a variety of Graphical Processing Unit (GPU) devices ranging from conventional graphics cards to advanced, high-end GPUs, while the numerical results are in excellent agreement with the available analytical and numerical data in the literature.

Material Density Mapping on Deformable 3D Models of Human Organs

Organ motion, especially respiratory motion, is a technical challenge to radiation therapy planning and dosimetry. This motion induces displacements and deformation of the organ tissues within the irradiated region which need to be taken into account when simulating dose distribution during treatment. Finite element modeling (FEM) can provide a great insight into the mechanical behavior of the organs, since they are based on the biomechanical material properties, complex geometry of organs, and anatomical boundary conditions. In this paper we present an original approach that offers the possibility to combine image-based biomechanical models with particle transport simulations. We propose a new method to map material density information issued from CT images to deformable tetrahedral meshes. Based on the principle of mass conservation our method can correlate density variation of organ tissues with geometrical deformations during the different phases of the respiratory cycle. The first results are particularly encouraging, as local error quantification of density mapping on organ geometry and density variation with organ motion are performed to evaluate and validate our approach.

Virtual or Virtually U: Educational Institutions in Second Life

Educational institutions are increasingly exploring the affordances of 3D virtual worlds for instruction and research, but few studies have been done to document current practices and uses of this emerging technology. This observational survey examines the virtual presences of 170 accredited educational institutions found in one such 3D virtual world called Second Life®, created by San- Francisco based Linden Lab®. The study focuses on what educational institutions look like in this virtual environment, the types of spaces educational institutions are creating or simulating, and what types of activities are being conducted.

Development of a Neural Network based Algorithm for Multi-Scale Roughness Parameters and Soil Moisture Retrieval

The overall objective of this paper is to retrieve soil surfaces parameters namely, roughness and soil moisture related to the dielectric constant by inverting the radar backscattered signal from natural soil surfaces. Because the classical description of roughness using statistical parameters like the correlation length doesn't lead to satisfactory results to predict radar backscattering, we used a multi-scale roughness description using the wavelet transform and the Mallat algorithm. In this description, the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each having a spatial scale. A second step in this study consisted in adapting a direct model simulating radar backscattering namely the small perturbation model to this multi-scale surface description. We investigated the impact of this description on radar backscattering through a sensitivity analysis of backscattering coefficient to the multi-scale roughness parameters. To perform the inversion of the small perturbation multi-scale scattering model (MLS SPM) we used a multi-layer neural network architecture trained by backpropagation learning rule. The inversion leads to satisfactory results with a relative uncertainty of 8%.

Simulation of Irregular Waves by CFD

Wave generation methodology has been developed and validated by simulating wave in CFD. In this analysis, Flap type wave maker has been modeled numerically with wave basin to generate waves for marine experimental analysis. Irregular waves are arrived from the wave spectrum, and this wave has been simulated in CFD. Generated irregular wave has been compared with an analytical wave. Simulated wave has been processed for FFT analysis, and the wave spectrum is validated with original wave spectrum.

Automatic Discrimimation of the Modes of Permanent Flow of a Liquid Simulating Blood

In order to be able to automatically differentiate between two modes of permanent flow of a liquid simulating blood, it was imperative to put together a data bank. Thus, the acquisition of the various amplitude spectra of the Doppler signal of this liquid in laminar flow and other spectra in turbulent flow enabled us to establish an automatic difference between the two modes. According to the number of parameters and their nature, a comparative study allowed us to choose the best classifier.