Multi-Walled Carbon Nanotubes/Polyacrylonitrile Composite as Novel Semi-Permeable Mixed Matrix Membrane in Reverse Osmosis Water Treatment Process

novel and simple method is introduced for rapid and highly efficient water treatment by reverse osmosis (RO) method using multi-walled carbon nanotubes (MWCNTs) / polyacrylonitrile (PAN) polymer as a flexible, highly efficient, reusable and semi-permeable mixed matrix membrane (MMM). For this purpose, MWCNTs were directly synthesized and on-line purified by chemical vapor deposition (CVD) process, followed by directing the MWCNT bundles towards an ultrasonic bath, in which PAN polymer was simultaneously suspended inside a solid porous silica support in water at temperature to ~70 οC. Fabrication process of MMM was finally completed by hot isostatic pressing (HIP) process. In accordance with the analytical figures of merit, the efficiency of fabricated MMM was ~97%. The rate of water treatment process was also evaluated to 6.35 L min-1. The results reveal that, the CNT-based MMM is suitable for rapid treatment of different forms of industrial, sea, drinking and well water samples.

Suspended Matter Model on Alsat-1 Image by MLP Network and Mathematical Morphology: Prototypes by K-Means

In this article, we propose a methodology for the characterization of the suspended matter along Algiers-s bay. An approach by multi layers perceptron (MLP) with training by back propagation of the gradient optimized by the algorithm of Levenberg Marquardt (LM) is used. The accent was put on the choice of the components of the base of training where a comparative study made for four methods: Random and three alternatives of classification by K-Means. The samples are taken from suspended matter image, obtained by analytical model based on polynomial regression by taking account of in situ measurements. The mask which selects the zone of interest (water in our case) was carried out by using a multi spectral classification by ISODATA algorithm. To improve the result of classification, a cleaning of this mask was carried out using the tools of mathematical morphology. The results of this study presented in the forms of curves, tables and of images show the founded good of our methodology.

Applying Wavelet Entropy Principle in Fault Classification

The ability to detect and classify the type of fault plays a great role in the protection of power system. This procedure is required to be precise with no time consumption. In this paper detection of fault type has been implemented using wavelet analysis together with wavelet entropy principle. The simulation of power system is carried out using PSCAD/EMTDC. Different types of faults were studied obtaining various current waveforms. These current waveforms were decomposed using wavelet analysis into different approximation and details. The wavelet entropy of such decompositions is analyzed reaching a successful methodology for fault classification. The suggested approach is tested using different fault types and proven successful identification for the type of fault.

Complex Wavelet Transform Based Image Denoising and Zooming Under the LMMSE Framework

This paper proposes a dual tree complex wavelet transform (DT-CWT) based directional interpolation scheme for noisy images. The problems of denoising and interpolation are modelled as to estimate the noiseless and missing samples under the same framework of optimal estimation. Initially, DT-CWT is used to decompose an input low-resolution noisy image into low and high frequency subbands. The high-frequency subband images are interpolated by linear minimum mean square estimation (LMMSE) based interpolation, which preserves the edges of the interpolated images. For each noisy LR image sample, we compute multiple estimates of it along different directions and then fuse those directional estimates for a more accurate denoised LR image. The estimation parameters calculated in the denoising processing can be readily used to interpolate the missing samples. The inverse DT-CWT is applied on the denoised input and interpolated high frequency subband images to obtain the high resolution image. Compared with the conventional schemes that perform denoising and interpolation in tandem, the proposed DT-CWT based noisy image interpolation method can reduce many noise-caused interpolation artifacts and preserve well the image edge structures. The visual and quantitative results show that the proposed technique outperforms many of the existing denoising and interpolation methods.

Wavelet based Image Registration Technique for Matching Dental x-rays

Image registration plays an important role in the diagnosis of dental pathologies such as dental caries, alveolar bone loss and periapical lesions etc. This paper presents a new wavelet based algorithm for registering noisy and poor contrast dental x-rays. Proposed algorithm has two stages. First stage is a preprocessing stage, removes the noise from the x-ray images. Gaussian filter has been used. Second stage is a geometric transformation stage. Proposed work uses two levels of affine transformation. Wavelet coefficients are correlated instead of gray values. Algorithm has been applied on number of pre and post RCT (Root canal treatment) periapical radiographs. Root Mean Square Error (RMSE) and Correlation coefficients (CC) are used for quantitative evaluation. Proposed technique outperforms conventional Multiresolution strategy based image registration technique and manual registration technique.

A Finite Precision Block Floating Point Treatment to Direct Form, Cascaded and Parallel FIR Digital Filters

This paper proposes an efficient finite precision block floating point (BFP) treatment to the fixed coefficient finite impulse response (FIR) digital filter. The treatment includes effective implementation of all the three forms of the conventional FIR filters, namely, direct form, cascaded and par- allel, and a roundoff error analysis of them in the BFP format. An effective block formatting algorithm together with an adaptive scaling factor is pro- posed to make the realizations more simple from hardware view point. To this end, a generic relation between the tap weight vector length and the input block length is deduced. The implementation scheme also emphasises on a simple block exponent update technique to prevent overflow even during the block to block transition phase. The roundoff noise is also investigated along the analogous lines, taking into consideration these implementational issues. The simulation results show that the BFP roundoff errors depend on the sig- nal level almost in the same way as floating point roundoff noise, resulting in approximately constant signal to noise ratio over a relatively large dynamic range.

Effects of Sea Water Level Fluctuations on Seismic Response of Jacket Type Offshore Platforms

To understand the seismic behavior of the offshore structures, the dynamic interaction of the water-structure-soil should be assessed. In this regard the role of the water dynamic properties in magnifying or reducing of the effects of earthquake induced motions on offshore structures haven't been investigated in precise manner in available literature. In this paper the sea water level fluctuations effects on the seismic behavior of a sample of offshore structures has been investigated by emphasizing on the water-structure interaction phenomenon. For this purpose a two dimensional finite element model of offshore structures as well as surrounded water has been developed using ANSYS software. The effect of soil interaction with embedded pile foundation has been imposed by using a series of nonlinear springs in horizontal and vertical directions in soil-piles contact points. In the model, the earthquake induced motions have been applied on springs and consequently the motions propagated upward to the structure and surrounded water. As a result of numerical study, the horizontal deformations of the offshore deck as well as internal force and buckling coefficient in structural elements have been recorded and controlled with and without water presence. In part of study a parametric study has been accomplished on sea water level fluctuations and effect of this parameter has been studied on the aforementioned numerical results.

A Mesh Free Moving Node Method To Analyze Flow Through Spirals of Orbiting Scroll Pump

The scroll pump belongs to the category of positive displacement pump can be used for continuous pumping of gases at low pressure apart from general vacuum application. The shape of volume occupied by the gas moves and deforms continuously as the spiral orbits. To capture flow features in such domain where mesh deformation varies with time in a complicated manner, mesh less solver was found to be very useful. Least Squares Kinetic Upwind Method (LSKUM) is a kinetic theory based mesh free Euler solver working on arbitrary distribution of points. Here upwind is enforced in molecular level based on kinetic flux vector splitting scheme (KFVS). In the present study we extended the LSKUM to moving node viscous flow application. This new code LSKUM-NS-MN for moving node viscous flow is validated for standard airfoil pitching test case. Simulation performed for flow through scroll pump using LSKUM-NS-MN code agrees well with the experimental pumping speed data.

Numerical Method Based On Initial Value-Finite Differences for Free Vibration of Stepped Thickness Plates

The main objective of the present paper is to derive an easy numerical technique for the analysis of the free vibration through the stepped regions of plates. Based on the utilities of the step by step integration initial values IV and Finite differences FD methods, the present improved Initial Value Finite Differences (IVFD) technique is achieved. The first initial conditions are formulated in convenient forms for the step by step integrations while the upper and lower edge conditions are expressed in finite difference modes. Also compatibility conditions are created due to the sudden variation of plate thickness. The present method (IVFD) is applied to solve the fourth order partial differential equation of motion for stepped plate across two different panels under the sudden step compatibility in addition to different types of end conditions. The obtained results are examined and the validity of the present method is proved showing excellent efficiency and rapid convergence.

A Servo Control System Using the Loop Shaping Design Procedure

This paper describes an expanded system for a servo system design by using the Loop Shaping Design Procedure (LSDP). LSDP is one of the H∞ design procedure. By conducting Loop Shaping with a compensator and robust stabilization to satisfy the index function, we get the feedback controller that makes the control system stable. In this paper, we propose an expanded system for a servo system design and apply to the DC motor. The proposed method performs well in the DC motor positioning control. It has no steady-state error in the disturbance response and it has robust stability.

Performance Analysis of MC-SS for the Indoor BPLC Systems

power-line networks are promise infrastructure for broadband services provision to end users. However, the network performance is affected by stochastic channel changing which is due to load impedances, number of branches and branched line lengths. It has been proposed that multi-carrier modulations techniques such as orthogonal frequency division multiplexing (OFDM), Multi-Carrier Spread Spectrum (MC-SS), wavelet OFDM can be used in such environment. This paper investigates the performance of different indoor topologies of power-line networks that uses MC-SS modulation scheme.It is observed that when a branch is added in the link between sending and receiving end of an indoor channel an average of 2.5dB power loss is found. In additional, when the branch is added at a node an average of 1dB power loss is found. Additionally when the terminal impedances of the branch change from line characteristic impedance to impedance either higher or lower values the channel performances were tremendously improved. For example changing terminal load from characteristic impedance (85 .) to 5 . the signal to noise ratio (SNR) required to attain the same performances were decreased from 37dB to 24dB respectively. Also, changing the terminal load from channel characteristic impedance (85 .) to very higher impedance (1600 .) the SNR required to maintain the same performances were decreased from 37dB to 23dB. The result concludes that MC-SS performs better compared with OFDM techniques in all aspects and especially when the channel is terminated in either higher or lower impedances.

A Distributed Weighted Cluster Based Routing Protocol for Manets

Mobile ad-hoc networks (MANETs) are a form of wireless networks which do not require a base station for providing network connectivity. Mobile ad-hoc networks have many characteristics which distinguish them from other wireless networks which make routing in such networks a challenging task. Cluster based routing is one of the routing schemes for MANETs in which various clusters of mobile nodes are formed with each cluster having its own clusterhead which is responsible for routing among clusters. In this paper we have proposed and implemented a distributed weighted clustering algorithm for MANETs. This approach is based on combined weight metric that takes into account several system parameters like the node degree, transmission range, energy and mobility of the nodes. We have evaluated the performance of proposed scheme through simulation in various network situations. Simulation results show that proposed scheme outperforms the original distributed weighted clustering algorithm (DWCA).

A Discrete Filtering Algorithm for Impulse Wave Parameter Estimation

This paper presents a new method for estimating the mean curve of impulse voltage waveforms that are recorded during impulse tests. In practice, these waveforms are distorted by noise, oscillations and overshoot. The problem is formulated as an estimation problem. Estimation of the current signal parameters is achieved using a fast and accurate technique. The method is based on discrete dynamic filtering algorithm (DDF). The main advantage of the proposed technique is its ability in producing the estimates in a very short time and at a very high degree of accuracy. The algorithm uses sets of digital samples of the recorded impulse waveform. The proposed technique has been tested using simulated data of practical waveforms. Effects of number of samples and data window size are studied. Results are reported and discussed.

Transfer Function of Piezoelectric Material

The study of piezoelectric material in the past was in T-Domain form; however, no one has studied piezoelectric material in the S-Domain form. This paper will present the piezoelectric material in the transfer function or S-Domain model. S-Domain is a well known mathematical model, used for analyzing the stability of the material and determining the stability limits. By using S-Domain in testing stability of piezoelectric material, it will provide a new tool for the scientific world to study this material in various forms.

Neural Network-Based Control Strategies Applied to a Fed-Batch Crystallization Process

This paper is focused on issues of process modeling and two model based control strategies of a fed-batch sugar crystallization process applying the concept of artificial neural networks (ANNs). The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. Two control alternatives are considered – model predictive control (MPC) and feedback linearizing control (FLC). Adequate ANN process models are first built as part of the controller structures. MPC algorithm outperforms the FLC approach with respect to satisfactory reference tracking and smooth control action. However, the MPC is computationally much more involved since it requires an online numerical optimization, while for the FLC an analytical control solution was determined.

The Urban Development Boundary as a Planning Tool for Sustainable Urban Form: The South African Situation

It is the living conditions in the cities that determine the future of our livelihood. “To change life, we must first change space"- Henri Lefebvre. Sustainable development is a utopian aspiration for South African cities (especially the case study of the Gauteng City Region), which are currently characterized by unplanned growth and increasing urban sprawl. While the reasons for poor environmental quality and living conditions are undoubtedly diverse and complex, having political, economical and social dimensions, it is argued that the prevailing approach to layout planning in South Africa is part of the problem. This article seeks a solution to the problem of sustainability, from a spatial planning perspective. The spatial planning tool, the urban development boundary, is introduced as the concept that will ensure empty talk being translated into a sustainable vision. The urban development boundary is a spatial planning tool that can be used and implemented to direct urban growth towards a more sustainable form. The urban development boundary aims to ensure planned urban areas, in contrast to the current unplanned areas characterized by urban sprawl and insufficient infrastructure. However, the success of the urban development boundary concept is subject to effective implementation measures, as well as adequate and efficient management. The concept of sustainable development can function as a driving force underlying societal change and transformation, but the interface between spatial planning and environmental management needs to be established (as this is the core aspects underlying sustainable development), and authorities needs to understand and implement this interface consecutively. This interface can, however, realize in terms of the objectives of the planning tool – the urban development boundary. The case study, the Gauteng City Region, is depicted as a site of economic growth and innovation, but there is a lack of good urban and regional governance, impacting on the design (layout) and function of urban areas and land use, as current authorities make uninformed decisions in terms of development applications, leading to unsustainable urban forms and unsustainable nodes. Place and space concepts are thus critical matters applicable to planning of the Gauteng City Region. The urban development boundary are thus explored as a planning tool to guide decision-making, and create a sustainable urban form, leading to better environmental and living conditions, and continuous sustainability.

The Role of Faith-based Organizations in Building Democratic Process: Achieving Universal Primary Education in Sierra Leone

This paper aims to argue that religion and Faith-based Organizations (FBOs) contribute to building democratic process through the provision of education in Sierra Leone. Sierra Leone experienced a civil war from 1991 to 2002 and about 70 percent of the population lives in poverty. While the government has been in the process of rebuilding the nation, many forms of Civil Society Organizations (CSOs), including FBOs, have played a significant role in promoting social development. Education plays an important role in supporting people-s democratic movements through knowledge acquisition, spiritual enlightenment and empowerment. This paper discusses religious tolerance in Sierra Leone and how FBOs have contributed to the provision of primary education in Sierra Leone. This study is based on the author-s field research, which involved interviews with teachers and development stakeholders, notably government officials, Non-governmental Organizations (NGOs) and FBOs, as well as questionnaires completed by pupils, parents and teachers.

A Study of the Effectiveness of the Routing Decision Support Algorithm

Multi criteria decision making (MCDM) methods like analytic hierarchy process, ELECTRE and multi-attribute utility theory are critically studied. They have irregularities in terms of the reliability of ranking of the best alternatives. The Routing Decision Support (RDS) algorithm is trying to improve some of their deficiencies. This paper gives a mathematical verification that the RDS algorithm conforms to the test criteria for an effective MCDM method when a linear preference function is considered.

Some Rotational Flows of an Incompressible Fluid of Variable Viscosity

The Navier Stokes Equations (NSE) for an incompressible fluid of variable viscosity in the presence of an unknown external force in Von-Mises system x,\ are transformed, and some new exact solutions for a class of flows characterized by equation y f x a\b for an arbitrary state equation are determined, where f x is a function, \ the stream function, a z 0 and b are the arbitrary constants. In three, out of four cases, the function f x is arbitrary, and the solutions are the solutions of the flow equations for all the flows characterized by the equationy f x a\b. Streamline patterns for some forms of f x in unbounded and bounded regions are given.

Multi Task Scheme to Monitor Multivariate Environments Using Artificial Neural Network

When an assignable cause(s) manifests itself to a multivariate process and the process shifts to an out-of-control condition, a root-cause analysis should be initiated by quality engineers to identify and eliminate the assignable cause(s) affected the process. A root-cause analysis in a multivariate process is more complex compared to a univariate process. In the case of a process involved several correlated variables an effective root-cause analysis can be only experienced when it is possible to identify the required knowledge including the out-of-control condition, the change point, and the variable(s) responsible to the out-of-control condition, all simultaneously. Although literature addresses different schemes to monitor multivariate processes, one can find few scientific reports focused on all the required knowledge. To the best of the author’s knowledge this is the first time that a multi task model based on artificial neural network (ANN) is reported to monitor all the required knowledge at the same time for a multivariate process with more than two correlated quality characteristics. The performance of the proposed scheme is evaluated numerically when different step shifts affect the mean vector. Average run length is used to investigate the performance of the proposed multi task model. The simulated results indicate the multi task scheme performs all the required knowledge effectively.