Analyses of Wear Mechanisms Occurring During Machining of the Titanium Alloy Ti- 6Al-2Sn-4Zr-6Mo

Titanium alloys like the modern alloy Ti 6Al 2Sn 4Zr 6Mo (Ti-6246) combine excellent specific mechanical properties and corrosion resistance. On the other hand,due to their material characteristics, machining of these alloys is difficult to perform. The aim of the current study is the analyses of wear mechanisms of coated cemented carbide tools applied in orthogonal cutting experiments of Ti-6246 alloy. Round bars were machined with standard coated tools in dry conditions on a CNC latheusing a wide range of cutting speeds and cutting depths. Tool wear mechanisms were afterwards investigated by means of stereo microscopy, optical microscopy, confocal microscopy and scanning electron microscopy. Wear mechanisms included fracture of the tool tip (total failure) and abrasion. Specific wear features like crater wear, micro cracks and built-up edgeformation appeared depending of the mechanical and thermal conditions generated in the workpiece surface by the cutting action.

Trace Emergence of Ants- Traffic Flow, based upon Exclusion Process

Biological evolution has generated a rich variety of successful solutions; from nature, optimized strategies can be inspired. One interesting example is the ant colonies, which are able to exhibit a collective intelligence, still that their dynamic is simple. The emergence of different patterns depends on the pheromone trail, leaved by the foragers. It serves as positive feedback mechanism for sharing information. In this paper, we use the dynamic of TASEP as a model of interaction at a low level of the collective environment in the ant-s traffic flow. This work consists of modifying the movement rules of particles “ants" belonging to the TASEP model, so that it adopts with the natural movement of ants. Therefore, as to respect the constraints of having no more than one particle per a given site, and in order to avoid collision within a bidirectional circulation, we suggested two strategies: decease strategy and waiting strategy. As a third work stage, this is devoted to the study of these two proposed strategies- stability. As a final work stage, we applied the first strategy to the whole environment, in order to get to the emergence of traffic flow, which is a way of learning.

Biodegradation of PCP by the Rhizobacteria Isolated from Pentachlorophenol-tolerant Crop Species

Pentachlorophenol (PCP) is a polychlorinated aromatic compound that is widespread in industrial effluents and is considered to be a serious pollutant. Among the variety of industrial effluents encountered, effluents from tanning industry are very important and have a serious pollution potential. PCP is also formed unintentionally in effluents of paper and pulp industries. It is highly persistent in soils and is lethal to a wide variety of beneficial microorganisms and insects, human beings and animals. The natural processes that breakdown toxic chemicals in the environment have become the focus of much attention to develop safe and environmentfriendly deactivation technologies. Microbes and plants are among the most important biological agents that remove and degrade waste materials to enable their recycling in the environment. The present investigation was carried out with the aim of developing a microbial system for bioremediation of PCP polluted soils. A number of plant species were evaluated for their ability to tolerate different concentrations of pentachlorophenol (PCP) in the soil. The experiment was conducted for 30 days under pot culture conditions. The toxic effect of PCP on plants was studied by monitoring seed germination, plant growth and biomass. As the concentration of PCP was increased to 50 ppm, the inhibition of seed germination, plant growth and biomass was also increased. Although PCP had a negative effect on all plant species tested, maize and groundnut showed the maximum tolerance to PCP. Other tolerating crops included wheat, safflower, sunflower, and soybean. From the rhizosphere soil of the tolerant seedlings, as many as twenty seven PCP tolerant bacteria were isolated. From soybean, 8; sunflower, 3; safflower 8; maize 2; groundnut and wheat, 3 each isolates were made. They were screened for their PCP degradation potentials. HPLC analyses of PCP degradation revealed that the isolate MAZ-2 degraded PCP completely. The isolate MAZ-1 was the next best isolate with 90 per cent PCP degradation. These strains hold promise to be used in the bioremediation of PCP polluted soils.

Design, Simulation and Experimental Realization of Nonlinear Controller for GSC of DFIG System

In a wind power generator using doubly fed induction generator (DFIG), the three-phase pulse width modulation (PWM) voltage source converter (VSC) is used as grid side converter (GSC) and rotor side converter (RSC). The standard linear control laws proposed for GSC provides not only instablity against comparatively large-signal disturbances, but also the problem of stability due to uncertainty of load and variations in parameters. In this paper, a nonlinear controller is designed for grid side converter (GSC) of a DFIG for wind power application. The nonlinear controller is designed based on the input-output feedback linearization control method. The resulting closed-loop system ensures a sufficient stability region, make robust to variations in circuit parameters and also exhibits good transient response. Computer simulations and experimental results are presented to confirm the effectiveness of the proposed control strategy.

Use of Detectors Technology for Gamma Ray Issued from Radioactive Isotopes and its Impact on Knowledge of Behavior of the Stationary Case of Solid Phase Holdup

For gamma radiation detection, assemblies having scintillation crystals and a photomultiplier tube, also there is a preamplifier connected to the detector because the signals from photomultiplier tube are of small amplitude. After pre-amplification the signals are sent to the amplifier and then to the multichannel analyser. The multichannel analyser sorts all incoming electrical signals according to their amplitudes and sorts the detected photons in channels covering small energy intervals. The energy range of each channel depends on the gain settings of the multichannel analyser and the high voltage across the photomultiplier tube. The exit spectrum data of the two main isotopes studied ,putting data in biomass program ,process it by Matlab program to get the solid holdup image (solid spherical nuclear fuel)

The New Semi-Experimental Method for Simulation of Turbine Flow Meters Rotation in the Transitional Flow

The new semi-experimental method for simulation of the turbine flow meters rotation in the transitional flow has been developed. The method is based on the experimentally established exponential low of changing of dimensionless relative turbine gas meter rotation frequency and meter inertia time constant. For experimental evaluation of the meter time constant special facility has been developed. The facility ensures instant switching of turbine meter under test from one channel to the other channel with different flow rate and measuring the meter response. The developed method can be used for evaluation and predication of the turbine meters response and dynamic error in the transitional flow with any arbitrary law of flow rate changing. The examples of the method application are presented.

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.

Large-Dimensional Shells under Mining Tremors from Various Mining Regions in Poland

In the paper a detailed analysis of the dynamic response of a cooling tower shell to mining tremors originated from two main regions of mining activity in Poland (Upper Silesian Coal Basin and Legnica-Glogow Copper District) was presented. The representative time histories registered in the both regions were used as ground motion data in calculations of the dynamic response of the structure. It was proved that the dynamic response of the shell is strongly dependent not only on the level of vibration amplitudes but on the dominant frequency range of the mining shock typical for the mining region as well. Also a vertical component of vibrations occurred to have considerable influence on the total dynamic response of the shell. Finally, it turned out that non-uniformity of kinematic excitation resulting from spatial variety of ground motion plays a significant role in dynamic analysis of large-dimensional shells under mining shocks.

Computational Analysis of the MembraneTargeting Domains of Plant-specific PRAF Proteins

The PRAF family of proteins is a plant specific family of proteins with distinct domain architecture and various unique sequence/structure traits. We have carried out an extensive search of the Arabidopsis genome using an automated pipeline and manual methods to verify previously known and identify unknown instances of PRAF proteins, characterize their sequence and build 3D structures of their individual domains. Integrating the sequence, structure and whatever little known experimental details for each of these proteins and their domains, we present a comprehensive characterization of the different domains in these proteins and their variant properties.

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.

A Wind Farm Reduced Order Model Using Integral Manifold Theory

Due to the increasing penetration of wind energy, it is necessary to possess design tools that are able to simulate the impact of these installations in utility grids. In order to provide a net contribution to this issue a detailed wind park model has been developed and is briefly presented. However, the computational costs associated with the performance of such a detailed model in describing the behavior of a wind park composed by a considerable number of units may render its practical application very difficult. To overcome this problem integral manifolds theory has been applied to reduce the order of the detailed wind park model, and therefore create the conditions for the development of a dynamic equivalent which is able to retain the relevant dynamics with respect to the existing a.c. system. In this paper integral manifold method has been introduced for order reduction. Simulation results of the proposed method represents that integral manifold method results fit the detailed model results with a higher precision than singular perturbation method.

Multi-view Description of Real-Time Systems- Architecture

Real-time embedded systems should benefit from component-based software engineering to handle complexity and deal with dependability. In these systems, applications should not only be logically correct but also behave within time windows. However, in the current component based software engineering approaches, a few of component models handles time properties in a manner that allows efficient analysis and checking at the architectural level. In this paper, we present a meta-model for component-based software description that integrates timing issues. To achieve a complete functional model of software components, our meta-model focuses on four functional aspects: interface, static behavior, dynamic behavior, and interaction protocol. With each aspect we have explicitly associated a time model. Such a time model can be used to check a component-s design against certain properties and to compute the timing properties of component assemblies.

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.

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.

Recycling Poultry Feathers for Pb Removal from Wastewater: Kinetic and Equilibrium Studies

Chicken feathers were used as biosorbent for Pb removal from aqueous solution. In this paper, the kinetics and equilibrium studies at several pH, temperature, and metal concentration values are reported. For tested conditions, the Pb sorption capacity of this poultry waste ranged from 0.8 to 8.3 mg/g. Optimal conditions for Pb removal by chicken feathers have been identified. Pseudo-first order and pseudo-second order equations were used to analyze the experimental data. In addition, the sorption isotherms were fitted to classical Langmuir and Freundlich models. Finally, thermodynamic parameters for the sorption process have been determined. In summary, the results showed that chicken feathers are an alternative and promising sorbent for the treatment of effluents polluted by Pb ions.

Enhancement of m-FISH Images using Spectral Unmixing

Breast carcinoma is the most common form of cancer in women. Multicolour fluorescent in-situ hybridisation (m-FISH) is a common method for staging breast carcinoma. The interpretation of m-FISH images is complicated due to two effects: (i) Spectral overlap in the emission spectra of fluorochrome marked DNA probes and (ii) tissue autofluorescence. In this paper hyper-spectral images of m-FISH samples are used and spectral unmixing is applied to produce false colour images with higher contrast and better information content than standard RGB images. The spectral unmixing is realised by combinations of: Orthogonal Projection Analysis (OPA), Alterating Least Squares (ALS), Simple-to-use Interactive Self-Modeling Mixture Analysis (SIMPLISMA) and VARIMAX. These are applied on the data to reduce tissue autofluorescence and resolve the spectral overlap in the emission spectra. The results show that spectral unmixing methods reduce the intensity caused by tissue autofluorescence by up to 78% and enhance image contrast by algorithmically reducing the overlap of the emission spectra.

Metallographic Analysis of Laser and Mechanically Formed HSLA Steel

This research was conducted to develop a correlation between microstructure of HSLA steel and the mechanical properties that occur as a result of both laser and mechanical forming processes of the metal. The technique of forming flat metals by applying laser beams is a relatively new concept in the manufacturing industry. However, the effects of laser energy on the stability of metal alloy phases have not yet been elucidated in terms of phase transformations and microhardness. In this work, CO2 laser source was used to irradiate the surface of a flat metal then the microstructure and microhardness of the metal were studied on the formed specimen. The extent to which the microstructure changed depended on the heat inputs of up to 1000 J/cm2 with cooling rates of about 4.8E+02 K/s. Experimental results revealed that the irradiated surface of a HSLA steel had transformed to austenitic structure during the heating process.

New Product-Type Estimators for the Population Mean Using Quartiles of the Auxiliary Variable

In this paper, we suggest new product-type estimators for the population mean of the variable of interest exploiting the first or the third quartile of the auxiliary variable. We obtain mean square error equations and the bias for the estimators. We study the properties of these estimators using simple random sampling (SRS) and ranked set sampling (RSS) methods. It is found that, SRS and RSS produce approximately unbiased estimators of the population mean. However, the RSS estimators are more efficient than those obtained using SRS based on the same number of measured units for all values of the correlation coefficient.

Research on Weakly Hard Real-Time Constraints and Their Boolean Combination to Support Adaptive QoS

Advances in computing applications in recent years have prompted the demand for more flexible scheduling models for QoS demand. Moreover, in practical applications, partly violated temporal constraints can be tolerated if the violation meets certain distribution. So we need extend the traditional Liu and Lanland model to adapt to these circumstances. There are two extensions, which are the (m, k)-firm model and Window-Constrained model. This paper researches on weakly hard real-time constraints and their combination to support QoS. The fact that a practical application can tolerate some violations of temporal constraint under certain distribution is employed to support adaptive QoS on the open real-time system. The experiment results show these approaches are effective compared to traditional scheduling algorithms.