Design and Control Strategy of Diffused Air Aeration System

During the past decade, pond aeration systems have been developed which will sustain large quantities of fish and invertebrate biomass. Dissolved Oxygen (DO) is considered to be among the most important water quality parameters in fish culture. Fishponds in aquaculture farms are usually located in remote areas where grid lines are at far distance. Aeration of ponds is required to prevent mortality and to intensify production, especially when feeding is practical, and in warm regions. To increase pond production it is necessary to control dissolved oxygen. Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. This paper presents a new design of diffused aeration system using fuel cell as a power source. Also fuzzy logic control Technique (FLC) is used for controlling the speed of air flow rate from the blower to air piping connected to the pond by adjusting blower speed. MATLAB SIMULINK results show high performance of fuzzy logic control (FLC).

Analysis of Periodic Solution of Delay Fuzzy BAM Neural Networks

In this paper, by employing a new Lyapunov functional and an elementary inequality analysis technique, some sufficient conditions are derived to ensure the existence and uniqueness of periodic oscillatory solution for fuzzy bi-directional memory (BAM) neural networks with time-varying delays, and all other solutions of the fuzzy BAM neural networks converge the uniqueness periodic solution. These criteria are presented in terms of system parameters and have important leading significance in the design and applications of neural networks. Moreover an example is given to illustrate the effectiveness and feasible of results obtained.

Variable Step-Size Affine Projection Algorithm With a Weighted and Regularized Projection Matrix

This paper presents a forgetting factor scheme for variable step-size affine projection algorithms (APA). The proposed scheme uses a forgetting processed input matrix as the projection matrix of pseudo-inverse to estimate system deviation. This method introduces temporal weights into the projection matrix, which is typically a better model of the real error's behavior than homogeneous temporal weights. The regularization overcomes the ill-conditioning introduced by both the forgetting process and the increasing size of the input matrix. This algorithm is tested by independent trials with coloured input signals and various parameter combinations. Results show that the proposed algorithm is superior in terms of convergence rate and misadjustment compared to existing algorithms. As a special case, a variable step size NLMS with forgetting factor is also presented in this paper.

Mechanical Properties of Fibre Reinforced Concrete - A Comparative Experimental Study

This paper in essence presents comparative experimental data on the mechanical performance of steel and synthetic fibre-reinforced concrete under compression, tensile split and flexure. URW1050 steel fibre and HPP45 synthetic fibre, both with the same concrete design mix, have been used to make cube specimens for a compression test, cylinders for a tensile split test and beam specimens for a flexural test. The experimental data demonstrated steel fibre reinforced concrete to be stronger in flexure at early stages, whilst both fibre reinforced concrete types displayed comparatively the same performance in compression, tensile splitting and 28-day flexural strength. In terms of post-crack controlHPP45 was preferable.

Understanding Work Integrated Learning in ICT: A Systems Perspective

Information and communication technology (ICT) is essential to the operation of business, and create many employment opportunities. High volumes of students graduate in ICT however students struggle to find job placement. A discrepancy exists between graduate skills and industry skill requirements. To address the need for ICT skills required, universities must create programs to meet the demands of a changing ICT industry. This requires a partnership between industry, universities and other stakeholders. This situation may be viewed as a critical systems thinking problem situation as there are various role players each with their own needs and requirements. Jackson states a typical critical systems methods has a pluralistic nature. This paper explores the applicability and suitability of Maslow and Dooyeweerd to guide understanding and make recommendations for change in ICT WIL, to foster an all-inclusive understanding of the situation by stakeholders. The above methods provide tools for understanding softer issues beyond the skills required. The study findings suggest that besides skills requirements, a deeper understanding and empowering students from being a student to a professional need to be understood and addressed.

Socio-Demographic Status and Arrack Drinking Patterns among Muslim, Hindu, Santal and Oraon Communities in Rasulpur Union,Bangladesh: A Cross-Cultural Perspective

Arrack is one of the forms of alcoholic beverage or liquor which is produced from palm or date juice and commonly consumed by the lower social class of all religious/ethnic communities in the north-western villages of Bangladesh. The purpose of the study was to compare arrack drinking patterns associated with socio-demographic status among the Muslim, Hindu, Santal, and Oraon communities in the Rasulpur union of Bangladesh. A total of 391 respondents (Muslim n-109, Hindu n-103, Santal n-89, Oraon n-90) selected by cluster random sampling were interviewed by ADP (Arrack Drinking Pattern) questionnaire. The results of Pearson Chi-Squire test revealed that arrack drinking patterns were significantly differed among the Muslim, Hindu, Santal, and Oraon communities- drinkers. In addition, the results of Spearman-s bivariate correlation coefficients also revealed that sociodemographic characteristics of the communities- drinkers were the significantly positive and negative associations with the arrack drinking patterns in the Rasulpur union, Bangladesh. The study suggests that further cross-cultural researches should be conducted on the consequences of arrack drinking patterns on the communities- drinkers.

Multilevel Classifiers in Recognition of Handwritten Kannada Numerals

The recognition of handwritten numeral is an important area of research for its applications in post office, banks and other organizations. This paper presents automatic recognition of handwritten Kannada numerals based on structural features. Five different types of features, namely, profile based 10-segment string, water reservoir; vertical and horizontal strokes, end points and average boundary length from the minimal bounding box are used in the recognition of numeral. The effect of each feature and their combination in the numeral classification is analyzed using nearest neighbor classifiers. It is common to combine multiple categories of features into a single feature vector for the classification. Instead, separate classifiers can be used to classify based on each visual feature individually and the final classification can be obtained based on the combination of separate base classification results. One popular approach is to combine the classifier results into a feature vector and leaving the decision to next level classifier. This method is extended to extract a better information, possibility distribution, from the base classifiers in resolving the conflicts among the classification results. Here, we use fuzzy k Nearest Neighbor (fuzzy k-NN) as base classifier for individual feature sets, the results of which together forms the feature vector for the final k Nearest Neighbor (k-NN) classifier. Testing is done, using different features, individually and in combination, on a database containing 1600 samples of different numerals and the results are compared with the results of different existing methods.

Recognition of Noisy Words Using the Time Delay Neural Networks Approach

This paper presents a recognition system for isolated words like robot commands. It’s carried out by Time Delay Neural Networks; TDNN. To teleoperate a robot for specific tasks as turn, close, etc… In industrial environment and taking into account the noise coming from the machine. The choice of TDNN is based on its generalization in terms of accuracy, in more it acts as a filter that allows the passage of certain desirable frequency characteristics of speech; the goal is to determine the parameters of this filter for making an adaptable system to the variability of speech signal and to noise especially, for this the back propagation technique was used in learning phase. The approach was applied on commands pronounced in two languages separately: The French and Arabic. The results for two test bases of 300 spoken words for each one are 87%, 97.6% in neutral environment and 77.67%, 92.67% when the white Gaussian noisy was added with a SNR of 35 dB.

Investigation of Buoyant Parameters of k-ε Turbulence Model in Gravity Stratified Flows

Different variants for buoyancy-affected terms in k-ε turbulence model have been utilized to predict the flow parameters more accurately, and investigate applicability of alternative k-ε turbulence buoyant closures in numerical simulation of a horizontal gravity current. The additional non-isotropic turbulent stress due to buoyancy has been considered in production term, based on Algebraic Stress Model (ASM). In order to account for turbulent scalar fluxes, general gradient diffusion hypothesis has been used along with Boussinesq gradient diffusion hypothesis with a variable turbulent Schmidt number and additional empirical constant c3ε.To simulate buoyant flow domain a 2D vertical numerical model (WISE, Width Integrated Stratified Environments), based on Reynolds- Averaged Navier-Stokes (RANS) equations, has been deployed and the model has been further developed for different k-ε turbulence closures. Results are compared against measured laboratory values of a saline gravity current to explore the efficient turbulence model.

Robust Statistics Based Algorithm to Remove Salt and Pepper Noise in Images

In this paper, a robust statistics based filter to remove salt and pepper noise in digital images is presented. The function of the algorithm is to detect the corrupted pixels first since the impulse noise only affect certain pixels in the image and the remaining pixels are uncorrupted. The corrupted pixels are replaced by an estimated value using the proposed robust statistics based filter. The proposed method perform well in removing low to medium density impulse noise with detail preservation upto a noise density of 70% compared to standard median filter, weighted median filter, recursive weighted median filter, progressive switching median filter, signal dependent rank ordered mean filter, adaptive median filter and recently proposed decision based algorithm. The visual and quantitative results show the proposed algorithm outperforms in restoring the original image with superior preservation of edges and better suppression of impulse noise

The Application of Adaptive Tabu Search Algorithm and Averaging Model to the Optimal Controller Design of Buck Converters

The paper presents the applications of artificial intelligence technique called adaptive tabu search to design the controller of a buck converter. The averaging model derived from the DQ and generalized state-space averaging methods is applied to simulate the system during a searching process. The simulations using such averaging model require the faster computational time compared with that of the full topology model from the software packages. The reported model is suitable for the work in the paper in which the repeating calculation is needed for searching the best solution. The results will show that the proposed design technique can provide the better output waveforms compared with those designed from the classical method.

Numerical Modeling of Natural Convection on Various Configuration of Rectangular Fin Arrays on Vertical Base Plates

In this research, the laminar heat transfer of natural convection on vertical surfaces has been investigated. Most of the studies on natural convection have been considered constantly whereas velocity and temperature domain, do not change with time, transient one are used a lot. Governing equations are solved using a finite volume approach. The convective terms are discretized using the power-law scheme, whereas for diffusive terms the central difference is employed. Coupling between the velocity and pressure is made with SIMPLE algorithm. The resultant system of discretized linear algebraic equations is solved with an alternating direction implicit scheme. Then a configuration of rectangular fins is put in different ways on the surface and heat transfer of natural convection on these surfaces without sliding is studied and finally optimization is done.

Nonlinear Conduction in Pure and Doped ZnO Varistors

We report here structural, mechanical and I-V characteristics of Zn1-xMxO ceramic samples with various x and M. It is found that the considered dopants does not influence the wellknown peaks related to wurtzite structure of ZnO ceramics, while the shape and size of grains are clearly affected. Average crystalline diameters, deduced from XRD are between 42 nm and 54 nm, which are 70 times lower than those obtained from SEM micrographs. Interestingly, the potential barrier could be formed by adding Cu up to 0.20, and it is completely deformed by 0.025 Ni additions. The breakdown field could be enhanced up to 4138 V/cm by 0.025 Cu additions, followed by a decrease with further increase of Cu . On the other hand a gradual decrease in VHN is reported for both dopants and their values are higher in Ni samples as compared to Cu samples. The electrical conductivity is generally improved by Ni, while addition of Cu improved it only in the over doped region (≥ 0.10). These results are discussed in terms of the difference of valency and ferromagnetic ordering for both dopants as compared to undoped sample.

The Activity of Mergers and Acquisitions in Romania in the 2000-2010 Decade, First Stage: Toward the Maturity of the Market (2000-2004)

The paper investigates the main issues concerning the activity of mergers and acquisitions in Romania in the period 2000- 2004. As in the first decade after the failure of the socialist economy the market of M&A was living its infancy based exclusively on privatization transactions, after 2000 the market entered in a stage of maturity. We are investigated both the registered evolutions in terms of number and value of transactions, and some sectoral issues, concerning the most important industries affected by the M&A process.

Development of Quasi-Two-Dimensional Nb2O5 for Functional Electrodes of Advanced Electrochemical Systems

In recent times there has been a growing interest in the development of quasi-two-dimensional niobium pentoxide (Nb2O5) as a semiconductor for the potential electronic applications such as capacitors, filtration, dye-sensitised solar cells and gas sensing platforms. Therefore once the purpose is established, Nb2O5 can be prepared in a number of nano- and sub-micron-structural morphologies that include rods, wires, belts and tubes. In this study films of Nb2O5 were prepared on gold plated silicon substrate using spin-coating technique and subsequently by mechanical exfoliation. The reason this method was employed was to achieve layers of less than 15nm in thickness. The sintering temperature of the specimen was 800oC. The morphology and structural characteristics of the films were analyzed by Atomic Force Microscopy (AFM), Raman Spectroscopy, X-ray Photoelectron Spectroscopy (XPS).

Inefficiency of Data Storing in Physical Memory

Memory forensic is important in digital investigation. The forensic is based on the data stored in physical memory that involve memory management and processing time. However, the current forensic tools do not consider the efficiency in terms of storage management and the processing time. This paper shows the high redundancy of data found in the physical memory that cause inefficiency in processing time and memory management. The experiment is done using Borland C compiler on Windows XP with 512 MB of physical memory.

Influences of Si and C- Doping on the Al-27 and N-14 Quardrupole Coupling Constants in AlN Nanotubes: A DFT Study

A computational study at the level density functional theory (DFT) was carried out to investigate the influences of Si and C-doping on the 14N and 27Al quadrupole coupling constant in the (10, 0) zigzag single ? walled Aluminum-Nitride nanotube (AlNNT). To this aim, a 1.16nm, length of AlNNT consisting of 40 Al atoms and 40 N atoms were selected where the end atoms are capped by hydrogen atom. To follow the purpose, three Si atoms and three C atoms were doped instead of three Al atoms and three N atoms as a central ring in the surface of the Si and C-doped AlNNT. At first both of systems optimized at the level of BLYP method and 6-31G (d) basis set and after that, the NQR parameters were calculated at the level BLYP method and 6-311+G** basis set in two optimized forms. The calculate CQ values for both optimized AlNNT systems, raw and Si and C-doped, reveal different electronic environments in the mentioned systems. It was also demonstrated that the end nuclei have the largest CQ values in both considered AlNNT systems. All the calculations were carried out using Gaussian 98 package of program.

Selection the Optimum Cooling Scheme for Generators based on the Electro-Thermal Analysis

Optimal selection of electrical insulations in electrical machinery insures reliability during operation. From the insulation studies of view for electrical machines, stator is the most important part. This fact reveals the requirement for inspection of the electrical machine insulation along with the electro-thermal stresses. In the first step of the study, a part of the whole structure of machine in which covers the general characteristics of the machine is chosen, then based on the electromagnetic analysis (finite element method), the machine operation is simulated. In the simulation results, the temperature distribution of the total structure is presented simultaneously by using electro-thermal analysis. The results of electro-thermal analysis can be used for designing an optimal cooling system. In order to design, review and comparing the cooling systems, four wiring structures in the slots of Stator are presented. The structures are compared to each other in terms of electrical, thermal distribution and remaining life of insulation by using Finite Element analysis. According to the steps of the study, an optimization algorithm has been presented for selection of appropriate structure.

Influence of Fibre Content on Crack Propagation Rate in Fibre-Reinforced Concrete Beams

Experimental study on the influence of fibre content on crack behaviour and propagation in synthetic-fibre reinforced beams has been reported in this paper. The tensile behaviour of metallic fibre concrete is evaluated in terms of residual flexural tensile strength values determined from the load-crack mouth opening displacement curve or load-deflection curve obtained by applying a centre-point load on a simply supported notched prism. The results achieved demonstrate that an increase in fibre content has an almost negligible effect on compressive and tensile splitting properties, causes a marginal increment in flexural tensile strength and increasesthe Re3 value.

Scale-Space Volume Descriptors for Automatic 3D Facial Feature Extraction

An automatic method for the extraction of feature points for face based applications is proposed. The system is based upon volumetric feature descriptors, which in this paper has been extended to incorporate scale space. The method is robust to noise and has the ability to extract local and holistic features simultaneously from faces stored in a database. Extracted features are stable over a range of faces, with results indicating that in terms of intra-ID variability, the technique has the ability to outperform manual landmarking.