Probability of Globality

The objective of global optimization is to find the globally best solution of a model. Nonlinear models are ubiquitous in many applications and their solution often requires a global search approach; i.e. for a function f from a set A ⊂ Rn to the real numbers, an element x0 ∈ A is sought-after, such that ∀ x ∈ A : f(x0) ≤ f(x). Depending on the field of application, the question whether a found solution x0 is not only a local minimum but a global one is very important. This article presents a probabilistic approach to determine the probability of a solution being a global minimum. The approach is independent of the used global search method and only requires a limited, convex parameter domain A as well as a Lipschitz continuous function f whose Lipschitz constant is not needed to be known.

Biometric Technology in Securing the Internet Using Large Neural Network Technology

The article examines the methods of protection of citizens' personal data on the Internet using biometric identity authentication technology. It`s celebrated their potential danger due to the threat of loss of base biometric templates. To eliminate the threat of compromised biometric templates is proposed to use neural networks large and extra-large sizes, which will on the one hand securely (Highly reliable) to authenticate a person by his biometrics, and on the other hand make biometrics a person is not available for observation and understanding. This article also describes in detail the transformation of personal biometric data access code. It`s formed the requirements for biometrics converter code for his work with the images of "Insider," "Stranger", all the "Strangers". It`s analyzed the effect of the dimension of neural networks on the quality of converters mystery of biometrics in access code.

Lattice Boltzmann Method for Turbulent Heat Transfer in Wavy Channel Flows

The hydrodynamic and thermal lattice Boltzmann methods are applied to investigate the turbulent convective heat transfer in the wavy channel flows. In this study, the turbulent phenomena are modeling by large-eddy simulations with the Smagorinsky model. As a benchmark, the laminar and turbulent backward-facing step flows are simulated first. The results give good agreement with other numerical and experimental data. For wavy channel flows, the distribution of Nusselt number and the skin-friction coefficients are calculated to evaluate the heat transfer effect and the drag force. It indicates that the vortices at the trough would affect the magnitude of drag and weaken the heat convection effects on the wavy surface. In turbulent cases, if the amplitude of the wavy boundary is large enough, the secondary vortices would be generated at troughs and contribute to the heat convection. Finally, the effects of different Re on the turbulent transport phenomena are discussed.

Radon in Drinking Water in Novi Sad

Exposure to radon occurs when breathing airborne radon while using water: showering, washing dishes, cooking, and drinking water that contain radon. The results of radon activity measurements in water from public drinking fountain in city of Novi Sad, Serbia is presented in this paper. Radon level in some samples exceeded EPA (Environmental Protection Agency) recommendation for maximum contaminant level (MCL) for radon in drinking water of 11.1 Bq/l.

Simulations of Routing Protocols of Wireless Sensor Networks

Wireless Sensor Network is widely used in electronics. Wireless sensor networks are now used in many applications including military, environmental, healthcare applications, home automation and traffic control. We will study one area of wireless sensor networks, which is the routing protocol. Routing protocols are needed to send data between sensor nodes and the base station. In this paper, we will discuss two routing protocols, such as datacentric and hierarchical routing protocol. We will show the output of the protocols using the NS-2 simulator. This paper will compare the simulation output of the two routing protocol using Nam. We will simulate using Xgraph to find the throughput and delay of the protocol.

Extended Well-Founded Semantics in Bilattices

One of the most used assumptions in logic programming and deductive databases is the so-called Closed World Assumption (CWA), according to which the atoms that cannot be inferred from the programs are considered to be false (i.e. a pessimistic assumption). One of the most successful semantics of conventional logic programs based on the CWA is the well-founded semantics. However, the CWA is not applicable in all circumstances when information is handled. That is, the well-founded semantics, if conventionally defined, would behave inadequately in different cases. The solution we adopt in this paper is to extend the well-founded semantics in order for it to be based also on other assumptions. The basis of (default) negative information in the well-founded semantics is given by the so-called unfounded sets. We extend this concept by considering optimistic, pessimistic, skeptical and paraconsistent assumptions, used to complete missing information from a program. Our semantics, called extended well-founded semantics, expresses also imperfect information considered to be missing/incomplete, uncertain and/or inconsistent, by using bilattices as multivalued logics. We provide a method of computing the extended well-founded semantics and show that Kripke-Kleene semantics is captured by considering a skeptical assumption. We show also that the complexity of the computation of our semantics is polynomial time.

Investigation of Shear Thickening Liquid Protection Fibrous Material

The stab resistance performance of newly developed fabric composites composed of hexagonal paper honeycombs, filled with shear thickening fluid (STF), and woven Kevlar® fabric or UHMPE was investigated in this study. The STF was prepared by dispersing submicron SiO2 particles into polyethylene glycol (PEG). Our results indicate that the STF-Kevlar composite possessed lower penetration depth than that of neat Kevlar. In other words, the STF-Kevlar composite can attain the same energy level in stab-resistance test with fewer layers of Kevlar fabrics than that of the neat Kevlar fabrics. It also indicates that STF can be used for the fabrication of flexible body armors and can provide improved protection against stab threats. We found that the stab resistance of the STF-Kevlar composite increases with the increase of SiO2 concentration in STF. Moreover, the silica particles functionalized with silane coupling agent can further improve the stab resistance.

Optimum Radio Capacity Estimation of a Single-Cell Spread Spectrum MIMO System under Rayleigh Fading Conditions

In this paper, the problem of estimating the optimal radio capacity of a single-cell spread spectrum (SS) multiple-inputmultiple- output (MIMO) system operating in a Rayleigh fading environment is examined. The optimisation between the radio capacity and the theoretically achievable average channel capacity (in the sense of information theory) per user of a MIMO single-cell SS system operating in a Rayleigh fading environment is presented. Then, the spectral efficiency is estimated in terms of the achievable average channel capacity per user, during the operation over a broadcast time-varying link, and leads to a simple novel-closed form expression for the optimal radio capacity value based on the maximization of the achieved spectral efficiency. Numerical results are presented to illustrate the proposed analysis.

Inverse Problem Methodology for the Measurement of the Electromagnetic Parameters Using MLP Neural Network

This paper presents an approach which is based on the use of supervised feed forward neural network, namely multilayer perceptron (MLP) neural network and finite element method (FEM) to solve the inverse problem of parameters identification. The approach is used to identify unknown parameters of ferromagnetic materials. The methodology used in this study consists in the simulation of a large number of parameters in a material under test, using the finite element method (FEM). Both variations in relative magnetic permeability and electrical conductivity of the material under test are considered. Then, the obtained results are used to generate a set of vectors for the training of MLP neural network. Finally, the obtained neural network is used to evaluate a group of new materials, simulated by the FEM, but not belonging to the original dataset. Noisy data, added to the probe measurements is used to enhance the robustness of the method. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.

Development of a Simulator for Explaining Organic Chemical Reactions Based on Qualitative Process Theory

This paper discusses the development of a qualitative simulator (abbreviated QRiOM) for predicting the behaviour of organic chemical reactions. The simulation technique is based on the qualitative process theory (QPT) ontology. The modelling constructs of QPT embody notions of causality which can be used to explain the behaviour of a chemical system. The major theme of this work is that, in a qualitative simulation environment, students are able to articulate his/her knowledge through the inspection of explanations generated by software. The implementation languages are Java and Prolog. The software produces explanation in various forms that stresses on the causal theories in the chemical system which can be effectively used to support learning.

An Incomplete Factorization Preconditioner for LMS Adaptive Filter

In this paper an efficient incomplete factorization preconditioner is proposed for the Least Mean Squares (LMS) adaptive filter. The proposed preconditioner is approximated from a priori knowledge of the factors of input correlation matrix with an incomplete strategy, motivated by the sparsity patter of the upper triangular factor in the QRD-RLS algorithm. The convergence properties of IPLMS algorithm are comparable with those of transform domain LMS(TDLMS) algorithm. Simulation results show efficiency and robustness of the proposed algorithm with reduced computational complexity.

Featured based Segmentation of Color Textured Images using GLCM and Markov Random Field Model

In this paper, we propose a new image segmentation approach for colour textured images. The proposed method for image segmentation consists of two stages. In the first stage, textural features using gray level co-occurrence matrix(GLCM) are computed for regions of interest (ROI) considered for each class. ROI acts as ground truth for the classes. Ohta model (I1, I2, I3) is the colour model used for segmentation. Statistical mean feature at certain inter pixel distance (IPD) of I2 component was considered to be the optimized textural feature for further segmentation. In the second stage, the feature matrix obtained is assumed to be the degraded version of the image labels and modeled as Markov Random Field (MRF) model to model the unknown image labels. The labels are estimated through maximum a posteriori (MAP) estimation criterion using ICM algorithm. The performance of the proposed approach is compared with that of the existing schemes, JSEG and another scheme which uses GLCM and MRF in RGB colour space. The proposed method is found to be outperforming the existing ones in terms of segmentation accuracy with acceptable rate of convergence. The results are validated with synthetic and real textured images.

Experimental Investigation of a Mixture of Methane, Carbon Dioxide and Nitrogen Gas Hydrate Formation in Water-Based Drilling Mud in the Presence or Absence of Thermodynamic Inhibitors

Gas hydrates form when a number of factors co-exist: free water, hydrocarbon gas, cold temperatures and high pressures are typical of the near mud-line conditions in a deepwater drilling operation. Subsequently, when drilling with water based muds, particularly on exploration wells, the risk of hydrate formation associated with a gas influx is high. The consequences of gas hydrate formation while drilling are severe, and as such, every effort should be made to ensure the risk of hydrate formation is either eliminated or significantly reduced. Thermodynamic inhibitors are used to reduce the free water content of a drilling mud, and thus suppress the hydrate formation temperature. Very little experimental work has been performed by oil and gas research companies on the evaluation of gas hydrate formation in a water-based drilling mud. The main objective of this paper is to investigate the experimental gas hydrate formation for a mixture of methane, carbon dioxide & nitrogen in a water-based drilling mud with or without presence of different concentrations of thermodynamic inhibitors including pure salt and a combination of salt with methanol or ethylene glycol at different concentrations in a static loop apparatus. The experiments were performed using a static loop apparatus consisting of a 2.4307 cm inside diameter and 800 cm long pipe. All experiments were conducted at 2200 psia. The temperature in the loop was decreased at a rate of 3.33 °F/h from initial temperature of 80 °F.

Distributed Relay Selection and Channel Choice in Cognitive Radio Network

In this paper, we study the cooperative communications where multiple cognitive radio (CR) transmit-receive pairs competitive maximize their own throughputs. In CR networks, the influences of primary users and the spectrum availability are usually different among CR users. Due to the existence of multiple relay nodes and the different spectrum availability, each CR transmit-receive pair should not only select the relay node but also choose the appropriate channel. For this distributed problem, we propose a game theoretic framework to formulate this problem and we apply a regret-matching learning algorithm which is leading to correlated equilibrium. We further formulate a modified regret-matching learning algorithm which is fully distributed and only use the local information of each CR transmit-receive pair. This modified algorithm is more practical and suitable for the cooperative communications in CR network. Simulation results show the algorithm convergence and the modified learning algorithm can achieve comparable performance to the original regretmatching learning algorithm.

Product Ecodesign Approaches in ISO 14001 Certified Companies

The aim of the study was to investigate whether there is the promotion of product ecodesign measures as a result of adopting ISO 14001 certification in manufacturing companies in the Republic of Slovenia. Companies gave the most of their product development attention to waste and energy reduction during manufacturing process and reduction of material consumption per unit of product. Regarding the importance of different ecodesign criteria reduction of material consumption per unit of product was reported as the most important criterion. Less attention is paid to endof- life issues considering recycling or packaging. Most manufacturing enterprises considered ISO 14001 standard as a very useful tool or at least a useful tool helping them to accelerate and establish product ecodesign activities. Two most frequently considered ecodesign drivers are increased competitive advantage and legal requirements and two most important barriers are high development costs and insufficient market demand.

Active Disturbance Rejection Control for Wind System Based On a DFIG

This paper proposes the study of a robust control of the doubly fed induction generator (DFIG) used in a wind energy production. The proposed control is based on the linear active disturbance rejection control (ADRC) and it is applied to the control currents rotor of the DFIG, the DC bus voltage and active and reactive power exchanged between the DFIG and the network. The system under study and the proposed control are simulated using MATLAB/SIMULINK.

Human Settlement, Land Management and Health in Sub Saharan Cities

An epidemiological cross sectional study was undertaken in Yaoundé in 2002 and updated in 2005. Focused on health within the city, the objectives were to measure diarrheal prevalence and to identify the risk factors associated with them. Results of microbiological examinations have revealed an urban average prevalence rate of 14.5%. Access to basic services in the living environment appears to be an important risk factor for diarrheas. Statistical and spatial analyses conducted have revealed that prevalence of diarrheal diseases vary among the two main types of settlement (informal and planned). More importantly, this study shows that, diarrhea prevalence rates (notably bacterial and parasitic diarrheas) vary according to the sub- category of settlements. The study draws a number of theoretical and policy implications for researchers and policy decision makers.

A New Derivative-Free Quasi-Secant Algorithm For Solving Non-Linear Equations

Most of the nonlinear equation solvers do not converge always or they use the derivatives of the function to approximate the root of such equations. Here, we give a derivative-free algorithm that guarantees the convergence. The proposed two-step method, which is to some extent like the secant method, is accompanied with some numerical examples. The illustrative instances manifest that the rate of convergence in proposed algorithm is more than the quadratically iterative schemes.

Electrophoretic Motion of a Liquid Droplet within an Uncharged Cylindrical Pore

Electrophoretic motion of a liquid droplet within an uncharged cylindrical pore is investigated theoretically in this study. It is found that the boundary effect in terms of the reduction of droplet mobility (droplet velocity per unit strength of the applied electric field) is very significant when the double layer surrounding the droplet is thick, and diminishes as it gets very thin. Moreover, the viscosity ratio of the ambient fluid to the internal one, σ, is a crucial factor in determining its electrophoretic behavior. The boundary effect is less significant as the viscosity ratio gets high. Up to 70% mobility reduction is observed when this ratio is low (σ = 0.01), whereas only 40% reduction when it is high (σ = 100). The results of this study can be utilized in various fields of biotechnology, such as a biosensor or a lab-on-a-chip device.

Effect of Soil Tillage System upon the Soil Properties, Weed Control, Quality and Quantity Yield in Some Arable Crops

The paper presents the influence of the conventional ploughing tillage technology in comparison with the minimum tillage, upon the soil properties, weed control and yield in the case of maize (Zea mays L.), soya-bean (Glycine hispida L.) and winter wheat (Triticum aestivum L.) in a three years crop rotation. A research has been conducted at the University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Romania. The use of minimum soil tillage systems within a three years rotation: maize, soya-bean, wheat favorites the rise of the aggregates hydro stability with 5.6-7.5% on a 0-20 cm depth and 5-11% on 20-30 cm depth. The minimum soil tillage systems – paraplow, chisel or rotary grape – are polyvalent alternatives for basic preparation, germination bed preparation and sowing, for fields and crops with moderate loose requirements being optimized technologies for: soil natural fertility activation and rationalization, reduction of erosion, increasing the accumulation capacity for water and realization of sowing in the optimal period. The soil tillage system influences the productivity elements of cultivated species and finally the productions thus obtained. Thus, related to conventional working system, the productions registered in minimum tillage working represented 89- 97% in maize, 103-112% in soya-bean, 93-99% in winter-wheat. The results of investigations showed that the yield is a conclusion soil tillage systems influence on soil properties, plant density assurance and on weed control. Under minimum tillage systems in the case of winter weat as an option for replacing classic ploughing, the best results in terms of quality indices were obtained from version worked with paraplow, followed by rotary harrow and chisel. At variants worked with paraplow were obtained quality indices close to those of the variant worked with plow, and protein and gluten content was even higher. At Ariesan variety, highest protein content, 12.50% and gluten, 28.6% was obtained for the variant paraplow.