Sensor Fusion Based Discrete Kalman Filter for Outdoor Robot Navigation

The objective of the presented work is to implement the Kalman Filter into an application that reduces the influence of the environmental changes over the robot expected to navigate over a terrain of varying friction properties. The Discrete Kalman Filter is used to estimate the robot position, project the estimated current state ahead at time through time update and adjust the projected estimated state by an actual measurement at that time via the measurement update using the data coming from the infrared sensors, ultrasonic sensors and the visual sensor respectively. The navigation test has been performed in a real world environment and has been found to be robust.

Stability Analysis of Impulsive Stochastic Fuzzy Cellular Neural Networks with Time-varying Delays and Reaction-diffusion Terms

In this paper, the problem of stability analysis for a class of impulsive stochastic fuzzy neural networks with timevarying delays and reaction-diffusion is considered. By utilizing suitable Lyapunov-Krasovskii funcational, the inequality technique and stochastic analysis technique, some sufficient conditions ensuring global exponential stability of equilibrium point for impulsive stochastic fuzzy cellular neural networks with time-varying delays and diffusion are obtained. In particular, the estimate of the exponential convergence rate is also provided, which depends on system parameters, diffusion effect and impulsive disturbed intention. It is believed that these results are significant and useful for the design and applications of fuzzy neural networks. An example is given to show the effectiveness of the obtained results.

Anodic Growth of Highly Ordered Titanium Oxide Nanotube Arrays: Effects of Critical Anodization Factors on their Photocatalytic Activity

Highly ordered arrays of TiO2 nanotubes (TiNTs) were grown vertically on Ti foil by electrochemical anodization. We controlled the lengths of these TiNTs from 2.4 to 26.8 ¶üÇóμm while varying the water contents (1, 3, and 6 wt%) of the electrolyte in ethylene glycol in the presence of 0.5 wt% NH4F with anodization for various applied voltages (20–80 V), periods (10–240 min) and temperatures (10–30 oC). For vertically aligned TiNT arrays, not only the increase in their tube lengths, but also their geometric (wall thickness and surface roughness) and crystalline structure lead to a significant influence on photocatalytic activity. The length optimization for methylene blue (MB) photodegradation was 18 μm. Further extending the TiNT length yielded lower photocatalytic activity presumably related to the limited MB diffusion and light-penetration depth into the TiNT arrays. The results indicated that a maximum MB photodegradation rate was obtained for the discrete anatase TiO2 nanotubes with thick and rough walls.

Simultaneous Treatment and Catalytic Gasification of Olive Mill Wastewater under Supercritical Conditions

Recently, a growing interest has emerged on the development of new and efficient energy sources, due to the inevitable extinction of the nonrenewable energy reserves. One of these alternative sources which has a great potential and sustainability to meet up the energy demand is biomass energy. This significant energy source can be utilized with various energy conversion technologies, one of which is biomass gasification in supercritical water. Water, being the most important solvent in nature, has very important characteristics as a reaction solvent under supercritical circumstances. At temperatures above its critical point (374.8oC and 22.1 MPa), water becomes more acidic and its diffusivity increases. Working with water at high temperatures increases the thermal reaction rate, which in consequence leads to a better dissolving of the organic matters and a fast reaction with oxygen. Hence, supercritical water offers a control mechanism depending on solubility, excellent transport properties based on its high diffusion ability and new reaction possibilities for hydrolysis or oxidation. In this study the gasification of a real biomass, namely olive mill wastewater (OMW), in supercritical water is investigated with the use of Pt/Al2O3 and Ni/Al2O3 catalysts. OMW is a by-product obtained during olive oil production, which has a complex nature characterized by a high content of organic compounds and polyphenols. These properties impose OMW a significant pollution potential, but at the same time, the high content of organics makes OMW a desirable biomass candidate for energy production. All of the catalytic gasification experiments were made with five different reaction temperatures (400, 450, 500, 550 and 600°C), under a constant pressure of 25 MPa. For the experiments conducted with Ni/Al2O3 catalyst, the effect of five reaction times (30, 60, 90, 120 and 150 s) was investigated. However, procuring that similar gasification efficiencies could be obtained at shorter times, the experiments were made by using different reaction times (10, 15, 20, 25 and 30 s) for the case of Pt/Al2O3 catalyst. Through these experiments, the effects of temperature, time and catalyst type on the gasification yields and treatment efficiencies were investigated.

Modeling and Simulation for Physical Vapor Deposition: Multiscale Model

In this paper we present modeling and simulation for physical vapor deposition for metallic bipolar plates. In the models we discuss the application of different models to simulate the transport of chemical reactions of the gas species in the gas chamber. The so called sputter process is an extremely sensitive process to deposit thin layers to metallic plates. We have taken into account lower order models to obtain first results with respect to the gas fluxes and the kinetics in the chamber. The model equations can be treated analytically in some circumstances and complicated multi-dimensional models are solved numerically with a software-package (UG unstructed grids, see [1]). Because of multi-scaling and multi-physical behavior of the models, we discuss adapted schemes to solve more accurate in the different domains and scales. The results are discussed with physical experiments to give a valid model for the assumed growth of thin layers.

Septic B-spline Collocation Method for Solving One-dimensional Hyperbolic Telegraph Equation

Recently, it is found that telegraph equation is more suitable than ordinary diffusion equation in modelling reaction diffusion for such branches of sciences. In this paper, a numerical solution for the one-dimensional hyperbolic telegraph equation by using the collocation method using the septic splines is proposed. The scheme works in a similar fashion as finite difference methods. Test problems are used to validate our scheme by calculate L2-norm and L∞-norm. The accuracy of the presented method is demonstrated by two test problems. The numerical results are found to be in good agreement with the exact solutions.

Acceleration Analysis of a Rotating Body

The velocity of a moving point in a general path is the vector quantity, which has both magnitude and direction. The magnitude or the direction of the velocity vector can change over time as a result of acceleration that the time rate of velocity changes. Acceleration analysis is important because inertial forces and inertial torques are proportional to rectilinear and angular accelerations accordingly. The loads must be determined in advance to ensure that a machine is adequately designed to handle these dynamic loads. For planar motion, the vector direction of acceleration is commonly separated into two elements: tangential and centripetal or radial components of a point on a rotating body. All textbooks in physics, kinematics and dynamics of machinery consider the magnitude of a radial acceleration at condition when a point rotates with a constant angular velocity and it means without acceleration. The magnitude of the tangential acceleration considered on a basis of acceleration for a rotating point. Such condition of presentation of magnitudes for two components of acceleration logically and mathematically is not correct and may cause further confusion in calculation. This paper presents new analytical expressions of the radial and absolute accelerations of a rotating point with acceleration and covers the gap in theoretical study of acceleration analysis.

Microstructure and Corrosion Behavior of Laser Welded Magnesium Alloys with Silver Nanoparticles

Magnesium alloys have gained increased attention in recent years in automotive, electronics, and medical industry. This because of magnesium alloys have better properties than aluminum alloys and steels in respects of their low density and high strength to weight ratio. However, the main problems of magnesium alloy welding are the crack formation and the appearance of porosity during the solidification. This paper proposes a unique technique to weld two thin sheets of AZ31B magnesium alloy using a paste containing Ag nanoparticles. The paste containing Ag nanoparticles of 5 nm in average diameter and an organic solvent was used to coat the surface of AZ31B thin sheet. The coated sheet was heated at 100 °C for 60 s to evaporate the solvent. The dried sheet was set as a lower AZ31B sheet on the jig, and then lap fillet welding was carried out by using a pulsed Nd:YAG laser in a closed box filled with argon gas. The characteristics of the microstructure and the corrosion behavior of the joints were analyzed by opticalmicroscopy (OM), energy dispersive spectrometry (EDS), electron probe micro-analyzer (EPMA), scanning electron microscopy (SEM), and immersion corrosion test. The experimental results show that the wrought AZ31B magnesium alloy can be joined successfully using Ag nanoparticles. Ag nanoparticles insert promote grain refinement, narrower the HAZ width and wider bond width compared to weld without and insert. Corrosion rate of welded AZ31B with Ag nanoparticles reduced up to 44 % compared to base metal. The improvement of corrosion resistance of welded AZ31B with Ag nanoparticles due to finer grains and large grain boundaries area which consist of high Al content. β-phase Mg17Al12 could serve as effective barrier and suppressed further propagation of corrosion. Furthermore, Ag distribution in fusion zone provide much more finer grains and may stabilize the magnesium solid solution making it less soluble or less anodic in aqueous

Stochastic Simulation of Reaction-Diffusion Systems

Reactiondiffusion systems are mathematical models that describe how the concentration of one or more substances distributed in space changes under the influence of local chemical reactions in which the substances are converted into each other, and diffusion which causes the substances to spread out in space. The classical representation of a reaction-diffusion system is given by semi-linear parabolic partial differential equations, whose general form is ÔêétX(x, t) = DΔX(x, t), where X(x, t) is the state vector, D is the matrix of the diffusion coefficients and Δ is the Laplace operator. If the solute move in an homogeneous system in thermal equilibrium, the diffusion coefficients are constants that do not depend on the local concentration of solvent and of solutes and on local temperature of the medium. In this paper a new stochastic reaction-diffusion model in which the diffusion coefficients are function of the local concentration, viscosity and frictional forces of solvent and solute is presented. Such a model provides a more realistic description of the molecular kinetics in non-homogenoeus and highly structured media as the intra- and inter-cellular spaces. The movement of a molecule A from a region i to a region j of the space is described as a first order reaction Ai k- → Aj , where the rate constant k depends on the diffusion coefficient. Representing the diffusional motion as a chemical reaction allows to assimilate a reaction-diffusion system to a pure reaction system and to simulate it with Gillespie-inspired stochastic simulation algorithms. The stochastic time evolution of the system is given by the occurrence of diffusion events and chemical reaction events. At each time step an event (reaction or diffusion) is selected from a probability distribution of waiting times determined by the specific speed of reaction and diffusion events. Redi is the software tool, developed to implement the model of reaction-diffusion kinetics and dynamics. It is a free software, that can be downloaded from http://www.cosbi.eu. To demonstrate the validity of the new reaction-diffusion model, the simulation results of the chaperone-assisted protein folding in cytoplasm obtained with Redi are reported. This case study is redrawing the attention of the scientific community due to current interests on protein aggregation as a potential cause for neurodegenerative diseases.

Time and Distance Dependence of Protons Energy Loss for Laser (pw-ps) Fusion Driven Ion Acceleration

The anomalous generation of plasma blocks by interaction of petawatt-picosecond laser pulses permits side-on ignition of uncompressed solid fusion fuel following an improved application of the hydrodynamic Chu-model for deuterium-tritium. The new possibility of side-on laser ignition depends on accelerated ions and produced ions beams of high energy particles by the nonlinear ponderomotive force of the laser pulse in the plasma block, a re-evaluation of the early hydrodynamic analysis for ignition of inertial fusion by including inhibition factor, collective effect of stopping power of alpha particles and the energy loss rate reabsorption to plasma by the protons of plasma blocks being reduced by about a factor 40.

Analysis of Feature Space for a 2d/3d Vision based Emotion Recognition Method

In modern human computer interaction systems (HCI), emotion recognition is becoming an imperative characteristic. The quest for effective and reliable emotion recognition in HCI has resulted in a need for better face detection, feature extraction and classification. In this paper we present results of feature space analysis after briefly explaining our fully automatic vision based emotion recognition method. We demonstrate the compactness of the feature space and show how the 2d/3d based method achieves superior features for the purpose of emotion classification. Also it is exposed that through feature normalization a widely person independent feature space is created. As a consequence, the classifier architecture has only a minor influence on the classification result. This is particularly elucidated with the help of confusion matrices. For this purpose advanced classification algorithms, such as Support Vector Machines and Artificial Neural Networks are employed, as well as the simple k- Nearest Neighbor classifier.

Robot Map Building from Sonar and Laser Information using DSmT with Discounting Theory

In this paper, a new method of information fusion – DSmT (Dezert and Smarandache Theory) is introduced to apply to managing and dealing with the uncertain information from robot map building. Here we build grid map form sonar sensors and laser range finder (LRF). The uncertainty mainly comes from sonar sensors and LRF. Aiming to the uncertainty in static environment, we propose Classic DSm (DSmC) model for sonar sensors and laser range finder, and construct the general basic belief assignment function (gbbaf) respectively. Generally speaking, the evidence sources are unreliable in physical system, so we must consider the discounting theory before we apply DSmT. At last, Pioneer II mobile robot serves as a simulation experimental platform. We build 3D grid map of belief layout, then mainly compare the effect of building map using DSmT and DST. Through this simulation experiment, it proves that DSmT is very successful and valid, especially in dealing with highly conflicting information. In short, this study not only finds a new method for building map under static environment, but also supplies with a theory foundation for us to further apply Hybrid DSmT (DSmH) to dynamic unknown environment and multi-robots- building map together.

Artificial Neural Networks and Multi-Class Support Vector Machines for Classifying Magnetic Measurements in Tokamak Reactors

This paper is mainly concerned with the application of a novel technique of data interpretation for classifying measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artificial Neural Networks and Multi-Class Support Vector Machines have been exploited to classify magnetic variables useful to determine shape and position of the plasma with a reduced computational complexity. The proposed technique is used to analyze simulated databases of plasma equilibria based on ITER geometry configuration. As well as demonstrating the successful recovery of scalar equilibrium parameters, we show that the technique can yield practical advantages compared with earlier methods.

Belief Theory-Based Classifiers Comparison for Static Human Body Postures Recognition in Video

This paper presents various classifiers results from a system that can automatically recognize four different static human body postures in video sequences. The considered postures are standing, sitting, squatting, and lying. The three classifiers considered are a naïve one and two based on the belief theory. The belief theory-based classifiers use either a classic or restricted plausibility criterion to make a decision after data fusion. The data come from the people 2D segmentation and from their face localization. Measurements consist in distances relative to a reference posture. The efficiency and the limits of the different classifiers on the recognition system are highlighted thanks to the analysis of a great number of results. This system allows real-time processing.

Maxwell-Cattaneo Regularization of Heat Equation

This work focuses on analysis of classical heat transfer equation regularized with Maxwell-Cattaneo transfer law. Computer simulations are performed in MATLAB environment. Numerical experiments are first developed on classical Fourier equation, then Maxwell-Cattaneo law is considered. Corresponding equation is regularized with a balancing diffusion term to stabilize discretizing scheme with adjusted time and space numerical steps. Several cases including a convective term in model equations are discussed, and results are given. It is shown that limiting conditions on regularizing parameters have to be satisfied in convective case for Maxwell-Cattaneo regularization to give physically acceptable solutions. In all valid cases, uniform convergence to solution of initial heat equation with Fourier law is observed, even in nonlinear case.

Acceptance and Commitment Therapy for Work Stress: Variation in Perceived Group Process and Outcomes

Employees commonly encounter unpredictable and unavoidable work related stressors. Exposure to such stressors can evoke negative appraisals and associated adverse mental, physical, and behavioral responses. Because Acceptance and Commitment Therapy (ACT) emphasizes acceptance of unavoidable stressors and diffusion from negative appraisals, it may be particularly beneficial for work stress. Forty-five workers were randomly assigned to an ACT intervention for work stress (n = 21) or a waitlist control group (n = 24). The intervention consisted of two 3-hour sessions spaced one week apart. An examination of group process and outcomes was conducted using the Revised Sessions Rating Scale. Results indicated that the ACT participants reported that they perceived the intervention to be supportive, task focused, and without adverse therapist behaviors (e.g., feelings of being criticized or discounted). Additionally, the second session (values clarification and commitment to action) was perceived to be more supportive and task focused than the first session (mindfulness, defusion). Process ratings were correlated with outcomes. Results indicated that perceptions of therapy supportiveness and task focus were associated with reduced psychological distress and improved perceived physical health.

GPS INS Integration Application in Flight Management System

Flight management system (FMS) is a specialized computer system that automates a wide variety of in-flight tasks, reducing the workload on the flight crew to the point that modern aircraft no longer carry flight engineers or navigators. The primary function of FMS is to perform the in-flight management of the flight plan using various sensors (such as GPS and INS often backed up by radio navigation) to determine the aircraft's position. From the cockpit FMS is normally controlled through a Control Display Unit (CDU) which incorporates a small screen and keyboard or touch screen. This paper investigates the performance of GPS/ INS integration techniques in which the data fusion process is done using Kalman filtering. This will include the importance of sensors calibration as well as the alignment of the strap down inertial navigation system. The limitations of the inertial navigation systems are investigated in order to understand why INS sometimes is integrated with other navigation aids and not just operating in standalone mode. Finally, both the loosely coupled and tightly coupled configurations are analyzed for several types of situations and operational conditions.

Creating the Color Panoramic View using Medley of Grayscale and Color Partial Images

Panoramic view generation has always offered novel and distinct challenges in the field of image processing. Panoramic view generation is nothing but construction of bigger view mosaic image from set of partial images of the desired view. The paper presents a solution to one of the problems of image seascape formation where some of the partial images are color and others are grayscale. The simplest solution could be to convert all image parts into grayscale images and fusing them to get grayscale image panorama. But in the multihued world, obtaining the colored seascape will always be preferred. This could be achieved by picking colors from the color parts and squirting them in grayscale parts of the seascape. So firstly the grayscale image parts should be colored with help of color image parts and then these parts should be fused to construct the seascape image. The problem of coloring grayscale images has no exact solution. In the proposed technique of panoramic view generation, the job of transferring color traits from reference color image to grayscale image is done by palette based method. In this technique, the color palette is prepared using pixel windows of some degrees taken from color image parts. Then the grayscale image part is divided into pixel windows with same degrees. For every window of grayscale image part the palette is searched and equivalent color values are found, which could be used to color grayscale window. For palette preparation we have used RGB color space and Kekre-s LUV color space. Kekre-s LUV color space gives better quality of coloring. The searching time through color palette is improved over the exhaustive search using Kekre-s fast search technique. After coloring the grayscale image pieces the next job is fusion of all these pieces to obtain panoramic view. For similarity estimation between partial images correlation coefficient is used.

Numerical Modeling of Benzene Transport in Andosol and Sand: Adequacy of Diffusion and Equilibrium Adsorption Equations

Prediction of benzene transport in soil and volatilization from soil to the atmosphere is important for the preservation of human health and management of contaminated soils. The adequacy of a simple numerical model, assuming two-phase diffusion and equilibrium of liquid/solid adsorption, was investigated by experimental data of benzene concentration in a flux chamber (with headspace) where Andosol and sand were filled. Adsorption experiment for liquid phase was performed to determine an adsorption coefficient. Furthermore, adequacy of vapor phase adsorption was also studied through two runs of experiment using sand with different water content. The results show that the model adequately predicted benzene transport and volatilization from Andosol and sand with water content of 14.0%. In addition, the experiment additionally revealed that vapor phase adsorption should be considered in diffusion model for sand with very low water content.

Thermophoretic Deposition of Nanoparticles Due Toa Permeable Rotating Disk: Effects of Partial Slip, Magnetic Field, Thermal Radiation, Thermal-Diffusion, and Diffusion-Thermo

The present contribution deals with the thermophoretic deposition of nanoparticles over a rapidly rotating permeable disk in the presence of partial slip, magnetic field, thermal radiation, thermal-diffusion, and diffusion-thermo effects. The governing nonlinear partial differential equations such as continuity, momentum, energy and concentration are transformed into nonlinear ordinary differential equations using similarity analysis, and the solutions are obtained through the very efficient computer algebra software MATLAB. Graphical results for non-dimensional concentration and temperature profiles including thermophoretic deposition velocity and Stanton number (thermophoretic deposition flux) in tabular forms are presented for a range of values of the parameters characterizing the flow field. It is observed that slip mechanism, thermal-diffusion, diffusion-thermo, magnetic field and radiation significantly control the thermophoretic particles deposition rate. The obtained results may be useful to many industrial and engineering applications.