In this paper we present a planar left-handed material pattern on the rectangular patch antenna mounted on the substrate is designed to enhance its horizontal radiation as well as to broaden its working bandwidth. The parametric study is done to study the effect of the ground plane slots width of 0.3, 0.4 and 0.5 mm respectively on the return loss and bandwidth enhancement, the best value of g is 0.4 mm. Enhancement in the bandwidth is achieved by introducing the meta material phenomena instead of the single patch antenna is about 19.2 times with g = 0.4 mm.

Hexavalent chromium removal from aqueous solution via adsorption on granular activated carbon: Adsorption, desorption, modeling and simulation studies

Mina Gholipour and Hassan Hashemipour

Hexavalent chromium is one of the contaminants recognized as a carcinogenic and mutagenic agent. Therefore, it is essential to remove these components from wastewater before disposal. In this study, removal of hexavalent chromium via adsorption on commercial granular activated carbon (GAC) was investigated as a function of adsorbent dosage, initial solution pH, initial Cr(VI) concentrations, contact time and temperature. The batch experiments were conducted at three temperatures (17, 27 and 37°C) and the results showed that Cr(VI) removal kinetics obeys pseudo second order rate equation. Equilibrium studies showed that the experimental data fitted well with Longmuir isotherm adsorption model. Thermodynamic parameters were also determined and results suggest that the adsorption process is a spontaneous and endothermic. reversibility of Cr(VI) adsorption and repeated availability performance of the adsorbent, was investigated by desorption process. In addition, artificial neural network (ANN) was utilized to simulate the experimental data. The results showed that the training step of the network was successful and therefore, the simulation could be applied to predict hexavalent chromium removal with high accuracy.

This paper investigates on the performance comparison of m x n equalizer based maximum likelihood (ML) and minimum mean square error (MMSE) MIMO receiver for wireless channel. The effect of fading and interference effects can be combated with equalizer. This paper also analyses the performance of MMSE equalizer based receiver for MIMO wireless channel. The bit error rate (BER) characteristics for the various transmitting and receiveing antennna are simulated in Matlab tool box and many advantages and disadvantages of the system are described. The simulation carried out in signal processing lab show that the MMSE equalizer based receiver is a good choice for removing some inter symbol interference (ISI) and minimizes the total noise power. However the simulation results show ML equalizer performance better. The simulation tool box used is Matlab V.7.0 and the results were obtained at RF signal processing lab. The results show that the BER decreases as the m x n antenna configurations is increased for both ML and MMSE equalizer based detector. ML equalizer based detector out performs the MMSE receiver in terms of BER characteristics.

A Three - Level Voltage Source Inverter is used increasingly to supply a variable frequency and variable voltage for variable speed applications. A suitable pulse width modulation (PWM) technique is employed to obtain the required output voltage at the line side of the inverter. This paper studies popular multi-level topology, Diode Clamped or Neutral Point Clamped for three-level. Two methods of Sine-triangle (SPWM) and two methods of Space Vector Pulse Width Modulation (SVPWM) are employed to generate the modulation wave. These modulation waves are compared against a triangular carrier to generate the PWM signals for the three phases. In SVPWM methods, a revolving reference voltage vector is provided as voltage reference instead of three phase modulating waves used in SPWM. The magnitude and frequency of the fundamental component in the line side are controlled by the magnitude and frequency, respectively, of the reference vector. Space Vector Modulation Technique has become the important PWM technique for three phase Voltage Source Inverters because of its increased dc bus utilization and reduced harmonic distortion compared to SPWM. The four PWM methods are simulated in MATLAB/SIMULINK software and are compared for THD and Capacitor Balance. Programs are carried out using Embedded Editor functions and matlab editor functions. The simulation study reveals that Space vector PWM utilizes dc bus voltage more effectively, generates less THD and improved capacitor balance when compared to sine PWM.

G. Narsimlu, L. Anand Babu and P. S. S. Rao

Abstract:

The paper considers the effect on the dusty gas otherwise at rest at infinity due to uniform motion of a sphere. The dust particles are assumed to have small relaxation time. Using the potential solution of gas flow at large Reynolds number R, an equation for the concentration of dust near the sphere is derived and solved numerically. It is also shown that particles do not collide with the sphere until the Stokes number is greater than 1/12 if we assume the gas flow unchanged by the presence of the dust particles and also graphically represented concentration of dust about sphere along radius vector.

Effective use of ferrous sulfate and alum as a coagulant in treatment of dairy industry wastewater

Kokila A. Parmar, Sarju Prajapati, Rinku Pate and Yogesh Dabhi

Abstract:

Dairy plants need usually large quantities of clean water. More than 90% of clean water is converted into wastewater demonstrating very high potential risk of environmental pollution. The present study was undertaken to compare, under the same analytical conditions, the efficiency of ferrous sulfate and alum used as coagulant in chemical treatment of raw wastewater collected from dairy plant. Results of visual and physicochemical evaluation of chemically treated wastewater indicated significant improvement of their selected characteristics, however different response to the coagulant treatment was observed within the tested samples. Removal efficiencies for individual parameters varied in the wide range between 20.9 and 97.2%.

Performance of cement grout incorporating sand dust under various temperatures

M. A. Hossain, M. H. Rashid, M. M. Rahman and K. Nahar

The present research studies the addition of sand dust (SD) on the performance of cement grout. Cube specimens of 5 x 5 x 5 cm were made with different mixing temperature and compositions. The mixing temperatures were 15, 30, 45 and 60°C. It was observed that grout mixed at 60°C is not suitable for bonded post tensioned concrete structure because the efflux time of fluidity test is not within the allowable limit. Grout consisting of cement, sand dust and water shows better bond stress and resistance to salt attack than grout consisting of cement and water. On the other hand compressive strength of controlled sample shows higher values than the samples with sand dust. The rate of capillary suction is almost same for all the fresh grout mixed at different temperature and composition.

Speed control of brushless DC motor by using fuzzy logic PI controller

M. V. Ramesh, J. Amarnath and S. Kamakshaiah

Abstract:

This paper presents the fuzzy, PI controller for speed control of BLDC motor. The controller uses three fuzzy logic controllers and three PI controllers. The output of the PI controllers is summed and is given as the input to the current controller. The current controller uses P controller. The mathematical modeling of BLDC motor is also presented. The BLDC motor is fed from the inverter where the rotor position and current controller is the input. The fuzzy logic control is learned continuously and gradually becomes the main effective control. The Simulink software was used to simulate the proposed scheme. The results are obtained for variable load torque.

Experimental study of air flow rate effects on humidification parameters with preheating and dehumidification process changing

Ayad T. Mustafa

Abstract:

The objective of this research is to study experimentally the effect of air flow rate on humidification process parameters. Experimental data are obtained from air conditioning study unit T110D. Results obtained from experimental test, calculations and psychometrics software are discussed. The effect of air flow rate on steam humidification process parameters as a part of air-conditioning processes can be explain in results obtained. Results of the steam humidification process with and without preheating with 5A and 7.5A shows decreasing in dry bulb temperature, humidity ratio, and heat add to moist air with increasing air flow rate, but humidification load, and total energy of moist air increase with increasing air flow rate in the testing tunnel. The steam humidification process with dehumidifying coil shows increase in dry bulb temperature, humidity ratio, humidification load, and heat add to moist air with increasing air flow rate in the testing tunnel, but the total energy decrease as air flow rate increase. These results obtained can be beneficial for controlling comfort air-conditioning processes in buildings.

A mathematical analysis of brewery effluent distribution in Ikpoba River in Benin city, Nigeria

Anthony C. Igboanugo and Chinedu M. Chiejine

Abstract:

A fundamental study was carried out in a lotic ecosystem loaded with brewery effluent and other oxygen-demanding wastes from non-point sources to ascertain the pollutant level and its potential hazardousness to aquatic live and human health in the environment studied. Samples of wastewater and river water which were taken at predetermined points, on different days, in the neighbourhood of the point source, were subjected to laboratory chemical analysis to determine the concentration of effluent parameters namely: BOD, COD, DO, and pH. Differential calculus and statistical models adapted for the analysis proved to be successful in predicting the contaminant distribution in the river thereby making the research result relevant for surface water pollution control.

An expert model for the shell and tube heat exchangers analysis by artificial neural networks

Abstract:

Due to the importance of heat exchangers in chemical and petrochical industries, heat exchangers analysis and heat translate calculations are preceded. The conventional and prevalent methods (such as KERN method and etc) are presented heat translate calculation for the analysis and selection of shell and tube heat exchanger based on the obtained pressure drop and fouling factor after consecutive calculation. Also there are many properties and parameters in prevalent methods. The current work proposed a new method based on the artificial neural network (ANN) for the analysis of Shell and Tube Heat Exchangers. Special parameters for heat exchangers analysis were obtained by neural network and the required experimental data were collected form Kern’s book, TEMA and Perry’s handbook. The work used back- propagation learning algorithm incorporating levenberg - marquardt training method. The accuracy and trend stability of the trained networks were verified according to their ability to predict unseen data. MSE error evaluation was used and the error limitation is 10^-3-10^-6. Parameters can be obtained without using charts, different Tables and complicated equations. During this research, Twenty two networks were utilized for all different properties. The results demonstrated the ANN’s capability to predict the analysis.

Vapour liquid equilibrium (VLE) data prediction for binary systems containing propane

A. R. Moghadassi, M. R. Nikkholgh, S. M. Hosseini, F. Parvizian and A. Sanaeirad

Abstract:

In this research, the ability of multi-layer perceptron neural networks to estimate vapour liquid equilibrium data have been studied. Four binary systems (R1270+R290, CO₂+R290, R125+R290, and R32+R290) have been investigated in the large ranges of temperature and pressure. These systems show different deviations from the Raoult's law. The networks with one hidden layer consist of five neurons are developed as the optimal structure. The networks were trained and then used as one-step tools without any iteration to estimate VLE data. For these binary systems, uncertainties in the ANNs results were not more than 0.126, 0.371, 0.221, and 0.613 %, respectively. In addition, the abilities of ANNs are shown by comparisons with Margules, van Laar, and some other usual correlations. Results show capability of presented networks obviously.

The development of green environment through lean implementation in a garment industry

Ravikumar Marudhamuthu and Marimuthu krishnaswamy

Abstract:

This research addresses the development of green environment through lean principles in an Indian garment export industry. Garment industries are thought to have a collective impact on environmental issues, they lack behind in larger area in terms of environmental activeness and performance. To meet with the challenges of business Environment Company strive to rearrange their production by implementing Lean and green environment. In specific, this research addresses the development of green and Lean in a garment industry. The objective is to explore the link between the Lean and green performance relationship and by evolving and testing various strategies to eliminate waste. This paper briefly describes the application of 5s, Value Stream Mapping (VSM) and Single Minute Exchange of Die (SMED). Existing state of VSM were efficiently constructed in future state VSM to improve the production process by identifying waste and its causes. This also describes how environmental performances are improved by eliminating the wastes. Adoption of lean has lowered the marginal cost of pollution reduction. It is made clear that lean is associated with greater source reduction (pollution prevention). Finally we say that lean is associated with lower emissions. We conclude that more on establishment engages in lean, the lower will be its emissions, in other words; Lean is green.

A novel CAD system for breast cancer segmentation in sonograms

Alamelumangai N. and Devishree J.

Abstract:

Breast cancer has turned out to be the most important health concern in the world over the past years. Early diagnosis is an efficient method to detect and supervise breast cancer. Computer diagnosis system can act as a major function in the early detection of breast cancer and can decrease the death rate among women with breast cancer. This paper provides a better system which detects cancer in early stages. The proposed system involves three phases such as speckle noise reduction, image enhancement and image segmentation. To remove speckle noise, we have used Neuro-Fuzzy based Memetic algorithm. Image enhancement is performed using Hough transform. Later, the enhanced image is segmented using clustering technique called Modified Fuzzy Possibilistic C-Means technique with Repulsion factor to identify the cancer affected region. The experimental result suggests that the proposed system results in better detection of cancer regions when compared to the existing technique.

Vapor liquid equilibrium prediction by PE and ANN for the extraction of un-saturated fatty acid esters by supercritical CO₂

Abdul Mun'em Abbas Karim, Ali Khudhair Mutlag and Mohammed Salah Hameed

Abstract:

The prediction of vapor-liquid equilibrium (VLE) may serve as a cheap alternative method to the experimental measurements of VLE. This is especially true for high pressure where it requires expensive equipment to measure VLE as compared with the low pressure experiments. A program phase equilibria (PE) with Peng-Robinson equation of state (PR-EOS) and artificial neural networks (ANN) technique are applied at high-pressure VLE. Related literature data were used to develop and validate a model capable of predicting VLE for four CO2-fatty acid ester systems. The systems used including oleic acid methyl ester, linoleic acid methyl ester, eicosapentaenoic acid ethyl ester (EPAEE) and docosahexenoic acid ethyl ester (DHAEE) at two different temperatures of 313K and 333K and pressure range (28.6-235.4) bar. The percentage average root square relative deviation (%ARSRD) is used to compare the predicted results by the PE program and artificial neural networks (ANN) favored the ANN model as it gives more representative results to the experimental data.

Abstract:

In the present study a method has been proposed for the behavioral prediction of a person through automated handwriting analysis. The present work identifies the psychological traits in the writing namely size, slant and pressure, baseline, number of breaks, margins, speed of writing and spacing between the words. The handwriting is analyzed through Image Processing in MATLAB. The behavioral pattern of the person is predicted from the above traits of the handwriting. The developed system identifies handwriting closely which may not be possible for a graphologist. It is real time and involves less image preprocessing. The proposed system is calibrated with manual analysis. The results obtained through the system are in good agreement to more than 80 percent of the cases with ideal manual analysis.