An Enhanced Situational Awareness of AUV's Mission by Multirate Neural Control

This paper focuses on a critical component of the situational awareness (SA), the neural control of depth flight of an autonomous underwater vehicle (AUV). Constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. With the SA strategy, we proposed a multirate neural control of an AUV trajectory using neural network model reference controller for a nontrivial mid-small size AUV "r2D4" stochastic model. This control system has been demonstrated and evaluated by simulation of diving maneuvers using software package Simulink. From the simulation results it can be seen that the chosen AUV model is stable in the presence of high noise, and also can be concluded that the fast SA of similar AUV systems with economy in energy of batteries can be asserted during the underwater missions in search-and-rescue operations.

Environmental Interference Cancellation of Speech with the Radial Basis Function Networks: An Experimental Comparison

In this paper, we use Radial Basis Function Networks (RBFN) for solving the problem of environmental interference cancellation of speech signal. We show that the Second Order Thin- Plate Spline (SOTPS) kernel cancels the interferences effectively. For make comparison, we test our experiments on two conventional most used RBFN kernels: the Gaussian and First order TPS (FOTPS) basis functions. The speech signals used here were taken from the OGI Multi-Language Telephone Speech Corpus database and were corrupted with six type of environmental noise from NOISEX-92 database. Experimental results show that the SOTPS kernel can considerably outperform the Gaussian and FOTPS functions on speech interference cancellation problem.

Agent Decision using Granular Computing in Traffic System

In recent years multi-agent systems have emerged as one of the interesting architectures facilitating distributed collaboration and distributed problem solving. Each node (agent) of the network might pursue its own agenda, exploit its environment, develop its own problem solving strategy and establish required communication strategies. Within each node of the network, one could encounter a diversity of problem-solving approaches. Quite commonly the agents can realize their processing at the level of information granules that is the most suitable from their local points of view. Information granules can come at various levels of granularity. Each agent could exploit a certain formalism of information granulation engaging a machinery of fuzzy sets, interval analysis, rough sets, just to name a few dominant technologies of granular computing. Having this in mind, arises a fundamental issue of forming effective interaction linkages between the agents so that they fully broadcast their findings and benefit from interacting with others.

Exploiting Global Self Similarity for Head-Shoulder Detection

People detection from images has a variety of applications such as video surveillance and driver assistance system, but is still a challenging task and more difficult in crowded environments such as shopping malls in which occlusion of lower parts of human body often occurs. Lack of the full-body information requires more effective features than common features such as HOG. In this paper, new features are introduced that exploits global self-symmetry (GSS) characteristic in head-shoulder patterns. The features encode the similarity or difference of color histograms and oriented gradient histograms between two vertically symmetric blocks. The domain-specific features are rapid to compute from the integral images in Viola-Jones cascade-of-rejecters framework. The proposed features are evaluated with our own head-shoulder dataset that, in part, consists of a well-known INRIA pedestrian dataset. Experimental results show that the GSS features are effective in reduction of false alarmsmarginally and the gradient GSS features are preferred more often than the color GSS ones in the feature selection.

Compensation Method Eliminating Voltage Distortions in PWM Inverter

The switching lag-time and the voltage drop across the power devices cause serious waveform distortions and fundamental voltage drop in pulse width-modulated inverter output. These phenomenons are conspicuous when both the output frequency and voltage are low. To estimate the output voltage from the PWM reference signal it is essential to take account of these imperfections and to correct them. In this paper, on-line compensation method is presented. It needs three simple blocs to add at the ideal reference voltages. This method does not require any additional hardware circuit and off- line experimental measurement. The paper includes experimental results to demonstrate the validity of the proposed method. It is applied, finally, in case of indirect vector controlled induction machine and implemented using dSpace card.

Bin Bloom Filter Using Heuristic Optimization Techniques for Spam Detection

Bloom filter is a probabilistic and memory efficient data structure designed to answer rapidly whether an element is present in a set. It tells that the element is definitely not in the set but its presence is with certain probability. The trade-off to use Bloom filter is a certain configurable risk of false positives. The odds of a false positive can be made very low if the number of hash function is sufficiently large. For spam detection, weight is attached to each set of elements. The spam weight for a word is a measure used to rate the e-mail. Each word is assigned to a Bloom filter based on its weight. The proposed work introduces an enhanced concept in Bloom filter called Bin Bloom Filter (BBF). The performance of BBF over conventional Bloom filter is evaluated under various optimization techniques. Real time data set and synthetic data sets are used for experimental analysis and the results are demonstrated for bin sizes 4, 5, 6 and 7. Finally analyzing the results, it is found that the BBF which uses heuristic techniques performs better than the traditional Bloom filter in spam detection.

An Assessment of Technological Competencies on Professional Service Firms Business Performance

This study was initiated with a three prong objective. One, to identify the relationship between Technological Competencies factors (Technical Capability, Firm Innovativeness and E-Business Practices and professional service firms- business performance. To investigate the predictors of professional service firms business performance and finally to evaluate the predictors of business performance according to the type of professional service firms, a survey questionnaire was deployed to collect empirical data. The questionnaire was distributed to the owners of the professional small medium size enterprises services in the Accounting, Legal, Engineering and Architecture sectors. Analysis showed that all three Technology Competency factors have moderate effect on business performance. In addition, the regression models indicate that technical capability is the most highly influential that could determine business performance, followed by e-business practices and firm innovativeness. Subsequently, the main predictor of business performance for all types of firms is Technical capability.

Simulation Modeling of Manufacturing Systems for the Serial Route and the Parallel One

In the paper we discuss the influence of the route flexibility degree, the open rate of operations and the production type coefficient on makespan. The flexible job-open shop scheduling problem FJOSP (an extension of the classical job shop scheduling) is analyzed. For the analysis of the production process we used a hybrid heuristic of the GRASP (greedy randomized adaptive search procedure) with simulated annealing algorithm. Experiments with different levels of factors have been considered and compared. The GRASP+SA algorithm has been tested and illustrated with results for the serial route and the parallel one.

Separation of Manganese and Cadmium from Cobalt Electrolyte Solution by Solvent Extraction

Impurity metals such as manganese and cadmium from high-tenor cobalt electrolyte solution were selectively removed by solvent extraction method using Co-D2EHPA after converting the functional group of D2EHPA with Co2+ ions. The process parameters such as pH, organic concentration, O/A ratio, kinetics etc. were investigated and the experiments were conducted by batch tests in the laboratory bench scale. Results showed that a significant amount of manganese and cadmium can be extracted using Co-D2EHPA for the optimum processing of cobalt electrolyte solution at equilibrium pH about 3.5. The McCabe-Thiele diagram, constructed from the extraction studies showed that 100% impurities can be extracted through four stages for manganese and three stages for cadmium using O/A ratio of 0.65 and 1.0, respectively. From the stripping study, it was found that 100% manganese and cadmium can be stripped from the loaded organic using 0.4 M H2SO4 in a single contact. The loading capacity of Co-D2EHPA by manganese and cadmium were also investigated with different O/A ratio as well as with number of stages of contact of aqueous and organic phases. Valuable information was obtained for the designing of an impurities removal process for the production of pure cobalt with less trouble in the electrowinning circuit.

Absorption of Volatile Organic Compounds into Polydimethylsiloxane: Phase Equilibrium Computation at Infinite Dilution

Group contribution methods such as the UNIFAC are very useful to researchers and engineers involved in synthesis, feasibility studies, design and optimization of separation processes. They can be applied successfully to predict phase equilibrium and excess properties in the development of chemical and separation processes. The main focus of this work was to investigate the possibility of absorbing selected volatile organic compounds (VOCs) into polydimethylsiloxane (PDMS) using three selected UNIFAC group contribution methods. Absorption followed by subsequent stripping is the predominant available abatement technology of VOCs from flue gases prior to their release into the atmosphere. The original, modified and effective UNIFAC models were used in this work. The thirteen selected VOCs that have been considered in this research are: pentane, hexane, heptanes, trimethylamine, toluene, xylene, cyclohexane, butyl acetate, diethyl acetate, chloroform, acetone, ethyl methyl ketone and isobutyl methyl ketone. The computation was done for solute VOC concentration of 8.55x10-8 which is well in the infinite dilution region. The results obtained in this study compare very well with those published in literature obtained through both measurements and predictions. The phase equilibrium obtained in this study show that PDMS is a good absorbent for the removal of VOCs from contaminated air streams through physical absorption.

High Order Accurate Runge Kutta Nodal Discontinuous Galerkin Method for Numerical Solution of Linear Convection Equation

This paper deals with a high-order accurate Runge Kutta Discontinuous Galerkin (RKDG) method for the numerical solution of the wave equation, which is one of the simple case of a linear hyperbolic partial differential equation. Nodal DG method is used for a finite element space discretization in 'x' by discontinuous approximations. This method combines mainly two key ideas which are based on the finite volume and finite element methods. The physics of wave propagation being accounted for by means of Riemann problems and accuracy is obtained by means of high-order polynomial approximations within the elements. High order accurate Low Storage Explicit Runge Kutta (LSERK) method is used for temporal discretization in 't' that allows the method to be nonlinearly stable regardless of its accuracy. The resulting RKDG methods are stable and high-order accurate. The L1 ,L2 and L∞ error norm analysis shows that the scheme is highly accurate and effective. Hence, the method is well suited to achieve high order accurate solution for the scalar wave equation and other hyperbolic equations.

Compton Scattering of Annihilation Photons as a Short Range Quantum Key Distribution Mechanism

The angular distribution of Compton scattering of two quanta originating in the annihilation of a positron with an electron is investigated as a quantum key distribution (QKD) mechanism in the gamma spectral range. The geometry of coincident Compton scattering is observed on the two sides as a way to obtain partially correlated readings on the quantum channel. We derive the noise probability density function of a conceptually equivalent prepare and measure quantum channel in order to evaluate the limits of the concept in terms of the device secrecy capacity and estimate it at roughly 1.9 bits per 1 000 annihilation events. The high error rate is well above the tolerable error rates of the common reconciliation protocols; therefore, the proposed key agreement protocol by public discussion requires key reconciliation using classical error-correcting codes. We constructed a prototype device based on the readily available monolithic detectors in the least complex setup.

An Application of SMED Methodology

Single Minute Exchange of Dies (SMED) mainly focuses on recognition of internal and external activities. It is concerned particularly with transferring internal activities into external ones in as many numbers as possible, by also minimizing the internal ones. The validity of the method and procedures are verified by an application a Styrofoam manufacturing process where setup times are critical for time reduction. Significant time savings have been achieved with minimum investment. Further, the issues related with employer safety and ergonomics principles during die exchange are noted.

Dry Sliding Wear Behavior of Epoxy-Rubber Dust Composites

Composite pins of rubber dust collected from tyre retreading centres of trucks, cars and buses etc.and epoxy with weight percentages of 10. 15, and 20 % of rubber (weight fractions of 9, 13 and 17 % respectively) have been prepared in house with the help of a split wooden mould. The pins were tested in a pin-on-disc wear monitor to determine the co-efficient of friction and weight losses with varying speeds, loads and time. The wear volume and wear rates have also been found out for all these three specimens.. It is observed that all the specimens have exhibited very low coefficient of friction and low wear rates under dry sliding condition. Out of the above three samples tested, the specimen with 10 % rubber dust by weight has shown lowest wear rates. However a peculiar result i.e decreasing trend has been obtained with 20% reinforcement of rubber in epoxy while rubbed against steel at varying speeds. This might have occurred due to high surface finish of the disc and formation of a thin transfer layer from the composite

MIMO Antenna Selections using CSI from Reciprocal Channel

It is well known that the channel capacity of Multiple- Input-Multiple-Output (MIMO) system increases as the number of antenna pairs between transmitter and receiver increases but it suffers from multiple expensive RF chains. To reduce the cost of RF chains, Antenna Selection (AS) method can offer a good tradeoff between expense and performance. In a transmitting AS system, Channel State Information (CSI) feedback is necessarily required to choose the best subset of antennas in which the effects of delays and errors occurred in feedback channels are the most dominant factors degrading the performance of the AS method. This paper presents the concept of AS method using CSI from channel reciprocity instead of feedback method. Reciprocity technique can easily archive CSI by utilizing a reverse channel where the forward and reverse channels are symmetrically considered in time, frequency and location. In this work, the capacity performance of MIMO system when using AS method at transmitter with reciprocity channels is investigated by own developing Testbed. The obtained results show that reciprocity technique offers capacity close to a system with a perfect CSI and gains a higher capacity than a system without AS method from 0.9 to 2.2 bps/Hz at SNR 10 dB.

Hybrid Neural Network Methods for Lithology Identification in the Algerian Sahara

In this paper, we combine a probabilistic neural method with radial-bias functions in order to construct the lithofacies of the wells DF01, DF02 and DF03 situated in the Triassic province of Algeria (Sahara). Lithofacies is a crucial problem in reservoir characterization. Our objective is to facilitate the experts' work in geological domain and to allow them to obtain quickly the structure and the nature of lands around the drilling. This study intends to design a tool that helps automatic deduction from numerical data. We used a probabilistic formalism to enhance the classification process initiated by a Self-Organized Map procedure. Our system gives lithofacies, from well-log data, of the concerned reservoir wells in an aspect easy to read by a geology expert who identifies the potential for oil production at a given source and so forms the basis for estimating the financial returns and economic benefits.

Classification of Prostate Cell Nuclei using Artificial Neural Network Methods

The purpose of this paper is to assess the value of neural networks for classification of cancer and noncancer prostate cells. Gauss Markov Random Fields, Fourier entropy and wavelet average deviation features are calculated from 80 noncancer and 80 cancer prostate cell nuclei. For classification, artificial neural network techniques which are multilayer perceptron, radial basis function and learning vector quantization are used. Two methods are utilized for multilayer perceptron. First method has single hidden layer and between 3-15 nodes, second method has two hidden layer and each layer has between 3-15 nodes. Overall classification rate of 86.88% is achieved.

Gender Differences in Entrepreneurship: Situation, Characteristics, Motivation and Entrepreneurial Behavior of Women Entrepreneurs in Switzerland

Entrepreneurs are important for national labour markets and economies in that they contribute significantly to economic growth as well as provide the majority of jobs and create new ones. According to the Global Entrepreneurship Monitor’s “Report on Women and Entrepreneurship”, investment in women’s entrepreneurship is an important way to exponentially increase the impact of new venture creation finding ways to empower women’s participation and success in entrepreneurship are critical for more sustainable and successful economic development. Our results confirm that they are still differences between men and women entrepreneurs The reasons seems to be the lack of specific business skills, the less extensive social network, and the lack of identification patterns among women. Those differences can be explained by the fact that women still have fewer opportunities to make a career. If this is correct, we can predict an increasing proportion of women among entrepreneurs in the next years. Concerning the development of a favorable environment for developing and enhancing women entrepreneurship activities, our results show the insertion in a network and the role of a model doubtless represent elements determining in the choice to launch an entrepreneurship activity, as well as a precious resource for the success of her company.

Preparation of Size Controlled Silver on Carbon from E-waste by Chemical and Electro-Kinetic Processes

Preparation of size controlled nano-particles of silver catalyst on carbon substrate from e-waste has been investigated. Chemical route was developed by extraction of the metals available in nitric acid followed by treatment with hydrofluoric acid. Silver metal particles deposited with an average size 4-10 nm. A stabilizer concentration of 10- 40 g/l was used. The average size of the prepared silver decreased with increase of the anode current density. Size uniformity of the silver nano-particles was improved distinctly at higher current density no more than 20mA... Grain size increased with EK time whereby aggregation of particles was observed after 6 h of reaction.. The chemical method involves adsorption of silver nitrate on the carbon substrate. Adsorbed silver ions were directly reduced to metal particles using hydrazine hydrate. Another alternative method is by treatment with ammonia followed by heating the carbon loaded-silver hydroxide at 980°C. The product was characterized with the help of XRD, XRF, ICP, SEM and TEM techniques.

Doping of Conveyor Belt Materials with Nanostructured Fillers to Adapt Innovative Performance Characteristics

The “conveyor belt" as a product represents a complex high performance component with a wide range of different applications. Further development of these highly complex components demands an integration of new technologies and new enhanced materials. In this context nanostructured fillers appear to have a more promising effect on the performance of the conveyor belt composite than conventional micro-scaled fillers. Within the project “DotTrans" nanostructured fillers, for example silicon dioxide, are used to optimize performance parameters of conveyor belt systems. The objective of the project includes operating parameters like energy consumption or friction characteristics as well as adaptive parameters like cut or wear resistance.