A Numerical Study of a Droplet Impinging on a Liquid Surface

The Navier–Stokes equations for unsteady, incompressible, viscous fluids in the axisymmetric coordinate system are solved using a control volume method. The volume-of-fluid (VOF) technique is used to track the free-surface of the liquid. Model predictions are in good agreement with experimental measurements. It is found that the dynamic processes after impact are sensitive to the initial droplet velocity and the liquid pool depth. The time evolution of the crown height and diameter are obtained by numerical simulation. The critical We number for splashing (Wecr) is studied for Oh (Ohnesorge) numbers in the range of 0.01~0.1; the results compares well with those of the experiments.

Flow Modeling and Runner Design Optimization in Turgo Water Turbines

The incorporation of computational fluid dynamics in the design of modern hydraulic turbines appears to be necessary in order to improve their efficiency and cost-effectiveness beyond the traditional design practices. A numerical optimization methodology is developed and applied in the present work to a Turgo water turbine. The fluid is simulated by a Lagrangian mesh-free approach that can provide detailed information on the energy transfer and enhance the understanding of the complex, unsteady flow field, at very small computing cost. The runner blades are initially shaped according to hydrodynamics theory, and parameterized using Bezier polynomials and interpolation techniques. The use of a limited number of free design variables allows for various modifications of the standard blade shape, while stochastic optimization using evolutionary algorithms is implemented to find the best blade that maximizes the attainable hydraulic efficiency of the runner. The obtained optimal runner design achieves considerably higher efficiency than the standard one, and its numerically predicted performance is comparable to a real Turgo turbine, verifying the reliability and the prospects of the new methodology.

Kinematic and Dynamic Analysis of a Lower Limb Exoskeleton

This paper will provide the kinematic and dynamic analysis of a lower limb exoskeleton. The forward and inverse kinematics of proposed exoskeleton is performed using Denevit and Hartenberg method. The torques required for the actuators will be calculated using Lagrangian formulation technique. This research can be used to design the control of the proposed exoskeleton.

Direct Sequence Spread Spectrum Technique with Residue Number System

In this paper, a residue number arithmetic is used in direct sequence spread spectrum system, this system is evaluated and the bit error probability of this system is compared to that of non residue number system. The effect of channel bandwidth, PN sequences, multipath effect and modulation scheme are studied. A Matlab program is developed to measure the signal-to-noise ratio (SNR), and the bit error probability for the various schemes.

Model Reduction of Linear Systems by Conventional and Evolutionary Techniques

Reduction of Single Input Single Output (SISO) continuous systems into Reduced Order Model (ROM), using a conventional and an evolutionary technique is presented in this paper. In the conventional technique, the mixed advantages of Mihailov stability criterion and continued fraction expansions (CFE) technique is employed where the reduced denominator polynomial is derived using Mihailov stability criterion and the numerator is obtained by matching the quotients of the Cauer second form of Continued fraction expansions. In the evolutionary technique method Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example.

The Water Level Detection Algorithm Using the Accumulated Histogram with Band Pass Filter

In this paper, we propose the robust water level detection method based on the accumulated histogram under small changed image which is acquired from water level surveillance camera. In general surveillance system, this is detecting and recognizing invasion from searching area which is in big change on the sequential images. However, in case of a water level detection system, these general surveillance techniques are not suitable due to small change on the water surface. Therefore the algorithm introduces the accumulated histogram which is emphasizing change of water surface in sequential images. Accumulated histogram is based on the current image frame. The histogram is cumulating differences between previous images and current image. But, these differences are also appeared in the land region. The band pass filter is able to remove noises in the accumulated histogram Finally, this algorithm clearly separates water and land regions. After these works, the algorithm converts from the water level value on the image space to the real water level on the real space using calibration table. The detected water level is sent to the host computer with current image. To evaluate the proposed algorithm, we use test images from various situations.

Color Image Segmentation Using Kekre-s Algorithm for Vector Quantization

In this paper we propose segmentation approach based on Vector Quantization technique. Here we have used Kekre-s fast codebook generation algorithm for segmenting low-altitude aerial image. This is used as a preprocessing step to form segmented homogeneous regions. Further to merge adjacent regions color similarity and volume difference criteria is used. Experiments performed with real aerial images of varied nature demonstrate that this approach does not result in over segmentation or under segmentation. The vector quantization seems to give far better results as compared to conventional on-the-fly watershed algorithm.

Hole Configuration Effect on Turbine Blade Cooling

In this paper a numerical technique is used to predict the metal temperature of a gas turbine vane. The Rising combustor exit temperatures in gas turbine engines necessitate active cooling for the downstream turbine section to avoid thermal failure. This study is performed the solution of external flow, internal convection, and conduction within the metal vane. Also the trade-off between the cooling performances in four different hole shapes and configurations is performed. At first one of the commonly used cooling hole geometry is investigated; cylindrical holes and then two other configurations are simulated. The average temperature magnitude in mid-plan section of each configuration is obtained and finally the lower temperature value is selected such as best arrangement.

Fault Detection of Drinking Water Treatment Process Using PCA and Hotelling's T2 Chart

This paper deals with the application of Principal Component Analysis (PCA) and the Hotelling-s T2 Chart, using data collected from a drinking water treatment process. PCA is applied primarily for the dimensional reduction of the collected data. The Hotelling-s T2 control chart was used for the fault detection of the process. The data was taken from a United Utilities Multistage Water Treatment Works downloaded from an Integrated Program Management (IPM) dashboard system. The analysis of the results show that Multivariate Statistical Process Control (MSPC) techniques such as PCA, and control charts such as Hotelling-s T2, can be effectively applied for the early fault detection of continuous multivariable processes such as Drinking Water Treatment. The software package SIMCA-P was used to develop the MSPC models and Hotelling-s T2 Chart from the collected data.

Mobile Robot Navigation Using Local Model Networks

Developing techniques for mobile robot navigation constitutes one of the major trends in the current research on mobile robotics. This paper develops a local model network (LMN) for mobile robot navigation. The LMN represents the mobile robot by a set of locally valid submodels that are Multi-Layer Perceptrons (MLPs). Training these submodels employs Back Propagation (BP) algorithm. The paper proposes the fuzzy C-means (FCM) in this scheme to divide the input space to sub regions, and then a submodel (MLP) is identified to represent a particular region. The submodels then are combined in a unified structure. In run time phase, Radial Basis Functions (RBFs) are employed as windows for the activated submodels. This proposed structure overcomes the problem of changing operating regions of mobile robots. Read data are used in all experiments. Results for mobile robot navigation using the proposed LMN reflect the soundness of the proposed scheme.

Eukaryotic Gene Prediction by an Investigation of Nonlinear Dynamical Modeling Techniques on EIIP Coded Sequences

Many digital signal processing, techniques have been used to automatically distinguish protein coding regions (exons) from non-coding regions (introns) in DNA sequences. In this work, we have characterized these sequences according to their nonlinear dynamical features such as moment invariants, correlation dimension, and largest Lyapunov exponent estimates. We have applied our model to a number of real sequences encoded into a time series using EIIP sequence indicators. In order to discriminate between coding and non coding DNA regions, the phase space trajectory was first reconstructed for coding and non-coding regions. Nonlinear dynamical features are extracted from those regions and used to investigate a difference between them. Our results indicate that the nonlinear dynamical characteristics have yielded significant differences between coding (CR) and non-coding regions (NCR) in DNA sequences. Finally, the classifier is tested on real genes where coding and non-coding regions are well known.

Influence of Thermo-fluid-dynamic Parameters on Fluidics in an Expanding Thermal Plasma Deposition Chamber

Technology of thin film deposition is of interest in many engineering fields, from electronic manufacturing to corrosion protective coating. A typical deposition process, like that developed at the University of Eindhoven, considers the deposition of a thin, amorphous film of C:H or of Si:H on the substrate, using the Expanding Thermal arc Plasma technique. In this paper a computing procedure is proposed to simulate the flow field in a deposition chamber similar to that at the University of Eindhoven and a sensitivity analysis is carried out in terms of: precursor mass flow rate, electrical power, supplied to the torch and fluid-dynamic characteristics of the plasma jet, using different nozzles. To this purpose a deposition chamber similar in shape, dimensions and operating parameters to the above mentioned chamber is considered. Furthermore, a method is proposed for a very preliminary evaluation of the film thickness distribution on the substrate. The computing procedure relies on two codes working in tandem; the output from the first code is the input to the second one. The first code simulates the flow field in the torch, where Argon is ionized according to the Saha-s equation, and in the nozzle. The second code simulates the flow field in the chamber. Due to high rarefaction level, this is a (commercial) Direct Simulation Monte Carlo code. Gas is a mixture of 21 chemical species and 24 chemical reactions from Argon plasma and Acetylene are implemented in both codes. The effects of the above mentioned operating parameters are evaluated and discussed by 2-D maps and profiles of some important thermo-fluid-dynamic parameters, as per Mach number, velocity and temperature. Intensity, position and extension of the shock wave are evaluated and the influence of the above mentioned test conditions on the film thickness and uniformity of distribution are also evaluated.

Data Hiding in Images in Discrete Wavelet Domain Using PMM

Over last two decades, due to hostilities of environment over the internet the concerns about confidentiality of information have increased at phenomenal rate. Therefore to safeguard the information from attacks, number of data/information hiding methods have evolved mostly in spatial and transformation domain.In spatial domain data hiding techniques,the information is embedded directly on the image plane itself. In transform domain data hiding techniques the image is first changed from spatial domain to some other domain and then the secret information is embedded so that the secret information remains more secure from any attack. Information hiding algorithms in time domain or spatial domain have high capacity and relatively lower robustness. In contrast, the algorithms in transform domain, such as DCT, DWT have certain robustness against some multimedia processing.In this work the authors propose a novel steganographic method for hiding information in the transform domain of the gray scale image.The proposed approach works by converting the gray level image in transform domain using discrete integer wavelet technique through lifting scheme.This approach performs a 2-D lifting wavelet decomposition through Haar lifted wavelet of the cover image and computes the approximation coefficients matrix CA and detail coefficients matrices CH, CV, and CD.Next step is to apply the PMM technique in those coefficients to form the stego image. The aim of this paper is to propose a high-capacity image steganography technique that uses pixel mapping method in integer wavelet domain with acceptable levels of imperceptibility and distortion in the cover image and high level of overall security. This solution is independent of the nature of the data to be hidden and produces a stego image with minimum degradation.

Modeling Biology Inspired Reactive Agents Using X-machines

Recent advances in both the testing and verification of software based on formal specifications of the system to be built have reached a point where the ideas can be applied in a powerful way in the design of agent-based systems. The software engineering research has highlighted a number of important issues: the importance of the type of modeling technique used; the careful design of the model to enable powerful testing techniques to be used; the automated verification of the behavioural properties of the system; the need to provide a mechanism for translating the formal models into executable software in a simple and transparent way. This paper introduces the use of the X-machine formalism as a tool for modeling biology inspired agents proposing the use of the techniques built around X-machine models for the construction of effective, and reliable agent-based software systems.

EFL Learners- Perceptions of Computer-Mediated Communication (CMC) to Facilitate Communication in a Foreign Language

This study explores perceptions of English as a Foreign Language (EFL) learners on using computer mediated communication technology in their learner of English. The data consists of observations of both synchronous and asynchronous communication participants engaged in for over a period of 4 months, which included online, and offline communication protocols, open-ended interviews and reflection papers composed by participants. Content analysis of interview data and the written documents listed above, as well as, member check and triangulation techniques are the major data analysis strategies. The findings suggest that participants generally do not benefit from computer-mediated communication in terms of its effect in learning a foreign language. Participants regarded the nature of CMC as artificial, or pseudo communication that did not aid their authentic communicational skills in English. The results of this study sheds lights on insufficient and inconclusive findings, which most quantitative CMC studies previously generated.

Construction Of Decentralized Lifetime Maximizing Tree for Data Aggregation in Wireless Sensor Networks

To meet the demands of wireless sensor networks (WSNs) where data are usually aggregated at a single source prior to transmitting to any distant user, there is a need to establish a tree structure inside any given event region. In this paper , a novel technique to create one such tree is proposed .This tree preserves the energy and maximizes the lifetime of event sources while they are constantly transmitting for data aggregation. The term Decentralized Lifetime Maximizing Tree (DLMT) is used to denote this tree. DLMT features in nodes with higher energy tend to be chosen as data aggregating parents so that the time to detect the first broken tree link can be extended and less energy is involved in tree maintenance. By constructing the tree in such a way, the protocol is able to reduce the frequency of tree reconstruction, minimize the amount of data loss ,minimize the delay during data collection and preserves the energy.

The Mechanistic Deconvolutive Image Sensor Model for an Arbitrary Pan–Tilt Plane of View

This paper presents a generalized form of the mechanistic deconvolution technique (GMD) to modeling image sensors applicable in various pan–tilt planes of view. The mechanistic deconvolution technique (UMD) is modified with the given angles of a pan–tilt plane of view to formulate constraint parameters and characterize distortion effects, and thereby, determine the corrected image data. This, as a result, does not require experimental setup or calibration. Due to the mechanistic nature of the sensor model, the necessity for the sensor image plane to be orthogonal to its z-axis is eliminated, and it reduces the dependency on image data. An experiment was constructed to evaluate the accuracy of a model created by GMD and its insensitivity to changes in sensor properties and in pan and tilt angles. This was compared with a pre-calibrated model and a model created by UMD using two sensors with different specifications. It achieved similar accuracy with one-seventh the number of iterations and attained lower mean error by a factor of 2.4 when compared to the pre-calibrated and UMD model respectively. The model has also shown itself to be robust and, in comparison to pre-calibrated and UMD model, improved the accuracy significantly.

Multi-Criteria Spatial Analysis for the Localization of Production Structures. Analytic Hierarchy Process and Geographical Information Systems in the Case of Expanding an Industrial Area

Among the numerous economic evaluation techniques currently available, Multi-criteria Spatial Analysis lends itself to solving localization problems of property complexes and, in particular, production plants. The methodology involves the use of Geographical Information Systems (GIS) and the mapping overlay technique, which overlaps the different information layers of a territory in order to obtain an overview of the parameters that characterize it. This first phase is used to detect possible settlement surfaces of a new agglomeration, subsequently selected through Analytic Hierarchy Process (AHP), so as to choose the best alternative. The result ensures the synthesis of a multidimensional profile that expresses both the quantitative and qualitative effects. Each criterion can be given a different weight.

Loop Back Connected Component Labeling Algorithm and Its Implementation in Detecting Face

In this study, a Loop Back Algorithm for component connected labeling for detecting objects in a digital image is presented. The approach is using loop back connected component labeling algorithm that helps the system to distinguish the object detected according to their label. Deferent than whole window scanning technique, this technique reduces the searching time for locating the object by focusing on the suspected object based on certain features defined. In this study, the approach was also implemented for a face detection system. Face detection system is becoming interesting research since there are many devices or systems that require detecting the face for certain purposes. The input can be from still image or videos, therefore the sub process of this system has to be simple, efficient and accurate to give a good result.

Differences in Students` Satisfaction with Distance Learning Studies

Rapid growth of distance learning resulted in importance to conduct research on students- satisfaction with distance learning because differences in students- satisfaction might influence educational opportunities for learning in a relevant Web-based environment. In line with this, this paper deals with satisfaction of students with distance module at Faculty of organizational sciences (FOS) in Serbia as well as some factors affecting differences in their satisfaction . We have conducted a research on a population of 68 first-year students of distance learning studies at FOS. Using statistical techniques, we have found out that there is no significant difference in students- satisfaction with distance learning module between men and women. In the same way, we also concluded that there is a difference in satisfaction with distance learning module regarding to student-s perception of opportunity to gain knowledge as the classic students.