Recent Advancements in System Modelling Applications

Smart grid technology provides good support for power generation from consumer premises using solar/wind. The difficulty associated with operation of such grids are, lack of an operating platform for the coordinated operation of large number of distributed sources and requirement of huge computational and storage facilities. The immense potential of cloud computing technology can be utilized to address these issues. Also the resources in various substations can be shared to reduce the cost of operation. The cloud computing architecture provides a user friendly environment for the reliable operation of smart grids and it supports various smart grids applications. The proposed architecture for data storage has been realized in the open stack cloud environment.

In this paper we study the design, implementation and evaluate the performance of a Kalman filter using FPGA. It is essential to be familiar with minimum mean square error filtering and state space methods. It is important that the set of equations, their relevance to one another and indeed the overall functionality of the algorithm that defines the Kalman filter require complete understanding. The filter will be implemented with field programmable gate arrays (FPGA), to monitor the level fluctuations for a dam/reservoir.

Digital watermarking has been proposed to increase medical image security, confidentiality and integrity. Medical image watermarking is a special subcategory of image watermarking in the sense that the images have special requirements. Particularly, watermarked medical images should not differ perceptually from their original counterparts, because the clinical reading of the images for diagnosis must not be affected. Hence, in this paper, a robust and imperceptible watermarking technique based on discrete wavelet transform (DWT) is proposed for medical images. For extraction, a blind source separation technique, namely, independent component analysis is attempted. Conventional extraction techniques need embedding parameters such as strength, location and information about watermark or original image, whereas, ICA extracts the watermark without the use of these parameters. The quality of watermarked image and extracted watermark are measured in terms of peak signal to noise ratio (PSNR) and normalized correlation (NC) values respectively. Robustness of the proposed scheme is validated against various image processing attacks. The proposed work is attempted on color images also. A true color image is split into red, green and blue components, where watermark is embedded in each plane individually followed by extraction. Performance of the proposed scheme is compared among the color components, and it is recommended that blue plane is the better choice of embedding watermark for medical color images.

The paper develops an autoassociative neural network (AANN) based online handwritten character recognition method for Tamil scripts. The coordinate positions traced during the pen movement in the digital tablet are preprocessed to remove noise, normalize the characters to a uniform height, and rescale the pen positions to result in uniformly spaced x and y positions. The rescaled x and y positions are individually provided as feature vectors to an AANN classifier and trained using the back propagation algorithm. The network training results in the adjusted weights that minimize the error between the input and output and captures the distribution of feature vectors in the input space effectively to create separate x and y models for 156 Tamil characters. The number of rescaled points is varied in order to experiment with various AANN structures and determine the best recognition rate. The confidence scores individually obtained from the x and y models are concatenated to give rise to the weighted xy model through a weighted sum rule. The experimental results reveal a higher recognition rate of 89.74 % for a weighting factor of 0.3 when applied to the scores of 96 rescaled points. The strength of the proposed approach lies in the computational simplicity and the consistency of the results claim its use in real world applications.

The aim behind this paper is to develop, design and implement a autonomous vehicle on real time environment with suitable performance measures. For this purpose, an algorithm using image processing is modeled. The vehicle considered for study is a differentially steered toy car fixed with a web cam. The image data are transferred to the central computer through cables. The vehicle uses image acquisition tools and image processing tools to handle the images and find the obstacle. Two algorithms are being developed based on the above idea along with evaluation of appropriate performance measures.

A novel stochastic optimization approach to solve multilevel thresholding problem in image segmentation using bacterial foraging (BF) technique is presented. The BF algorithm is based on the foraging behavior of

E. Coli

bacteria which is present in the human intestine. The proposed BF algorithm is used to maximize Renyi’s entropy function. The utility of the proposed algorithm is aptly demonstrated by considering several benchmark test images and the results are compared with those obtained from particle swarm optimization (PSO) and genetic algorithm (GA) based methods. The experimental results show that the proposed algorithm could demonstrate enhanced performance in comparison with PSO and GA in terms of solution quality and stability. The computation speed is accelerated and the quality improved through the use of this strategy.

This paper attempts to develop a pioneering mechanism to re-route the data through an alternate path on the occurrence of an exigency in a Wireless Virtual Private Network (WVPN). The fact that Code Division Multiple Access (CDMA) technology facilitates large scale data transmission and is relatively free from interference augur the choice of CDMA nodes to examine the feasibility of a re-routing concept. It is designed to assuage a restricted usage of bandwidth to serve the elaborate needs of the growing traffic. The proposed Cluster based Adhoc On-demand Distance Vector (CAODV) methodology allows the Cluster Head (CH) to perceive a viable swap of the packets in the next possible minimum bandwidth path. The Network Simulator-2 (NS-2) simulation results are compared in terms of its performance metrics with that obtained in a normal environment to highlight the applicability of the projected strategy in the utility world.

Geant4 is a Monte-Carlo simulation tool-kit developed for the virtual study of high energy physics. Hadrontherapy is an open source code, available in this toolkit for application in radiation therapy developed by the MC-INFN group. The aim of this work is to study the passive transport beam line, which is installed at Laboratory Nazionali del Sud (INFN) in Catania, Italy. The theoretical models implemented in the Geant4 code are studied. The physical interpretation of dose distribution curves for proton beam in the calculation of stopping power of proton beam in the calculation of stopping power of proton beam in water medium at different energies are discussed. In the end we study the spectra of secondary particles produced in the interactions for 60 MeV proton beam which is relevant for the study of Radioactive Biological Efficiency (RBE) and Spread Out in Bragg Peak (SOBP).

This work considers a multiobjective optimization problem with max-product fuzzy relational constraints. The utility function based approach is proposed that translates the multidimensional criterion space to single dimensional one. Further, a hybridized genetic algorithm is applied to solve the transformed single objective optimization problem. As the feasible domain has the inherent non-convexity; traditional metaheuristics cannot be applied in their original form. So with a careful study of the feasible domain a specific hybridized genetic algorithm is designed that keeps the new solutions inside the feasible domain and results in a set of solutions offering close approximation of the efficient set and hence, makes the problem decidable.

Water is a basic human need. Three fourth of our earth is surrounded by water. Water is stored in lakes and large tanks for human purposes like drinking, bathing, washing and irrigation. Effective use and operation of this storage is of prime importance. Veeranam tank is the largest tank irrigation system in Tamilnadu which commands two taluks of Kattumannarkoil and Chidambaram comprising of a large number of villages and hamlets which sums upto 120. In addition it has recently supplemented Chennai urban water supply. Optimal operation of the tank is thus need of the hour. Abundant literature is available on Artificial Intelligence techniques and their successful application for prediction, simulation, identification, classification and optimization in the field of water resources management. But literature on operation of tanks is meager. Tanks have been operated on adhoc basis and experience, with not much scientific logic. This paper addresses the need for optimal operation of Veeranam tank irrigation system using the concept of a fuzzy rule-based system for tank operation. The rule-base was built on the basis of the expert’s knowledge and heuristic data. MATLAB Fuzzy logic toolbox was used for simulation in this study. Model was evaluated using various metrics like RMSE, MAE and AI.

With the present market trend, businesses and organisations with large salesforces are experiencing much turnover among their sellers. Movement of salespeople from one company to another is a continual process as long as there is market demand. In the traditional sense, a salesperson’s productivity is directly proportional to the revenue that he or she brings to the company. Importantly, the senior leaders in organisations are interested in knowing the variations in sales productivity as a result of hiring and attrition in the salesforce. In this paper we focus our attention on the characterisation of sales productivity based on four categories. When an existing salesperson leaves, what is the sales productivity over time if replaced by a new hire from a university, an experienced new hire, or a transfer from another division in the company? In addition if an organisation ventures into acquisition, what is the anticipated sales productivity from this? We model the sales productivity of new hires as a linear time-invariant system and estimate productivity profiles with a least-squares deconvolution formulation. By applying business constraints on productivity profiles for regularisation, we are left with a constrained quadratic program to solve. We demonstrate the estimation technique on real-world sales data from a global enterprise, finding productivity profiles under the four different cases listed above.

The consequences of recent stagnation in economy are being experienced globally, with different industry and business segments, and their employees, bearing the brunt of this recession by varying degrees. Several employees have lost their livelihoods—a penalty of the slump they may not even have been directly responsible for. The present economic crisis calls for a systems approach that is not only sustainable but also absorbs the transients caused by global economic events, ensuring that the basic human necessities of all individuals are catered to at all times. The concept of a holistic community living is explored and is compared with the prevalent self-centered culture that breeds volatility and insecurity. It has been shown that integrating individuals together into local community systems is not only economically viable and stable but also leads to other benefits that ensure an improved lifestyle in a supportive environment that is free from petty strife. The practicability of the proposed systems model is supported by examples and proved through a case study on Dayalbagh, verily a Utopia on earth.

This paper presents the comparison of the different Carrier Overlapping Pulse Width Modulation (COPWM) techniques for three phase seven level Z-source diode clamped inverter. Due to switch combination redundancies, there are certain degrees of freedom to generate the multi level AC output voltage. This work presents the use of CFD combination. The Z-source based DCMLI is triggered by the different COPWM techniques having sinusoidal reference and triangular carriers. It is observed that the COPWM-3 technique provides reduced harmonics at its output voltage. The effectiveness of the PWM techniques developed using CFD are demonstrated by simulation using MATLAB/SIMULINK.

Multilevel static power conversion technology imbibes the ability to process high voltage and generate multi-tier voltage waveforms with high spectral quality. This technology is increasingly being used [

1

] in power converters and power conditioning circuits. Multilevel power converter is a general term applied to power converters with topologies capable of synthesizing multi-tier voltage waveforms and processing high voltages, by means of series connections of active devices to offer three or more discrete DC voltage [

2

] levels. Interconnection of power devices to split DC rail increases the voltage handling capability of these converters for the given power devices. Series-parallel DC–DC conversion systems in which multiple standardized converter modules are connected in series or parallel [

3

] at the output and input sides. Multiple connected DC–DC conversion systems attract more attention [

4

] in recent years, and are being to be widely used in various applications [

5

]. DC choppers are used to convert unregulated DC input voltage into a controlled DC output voltage at a desired level. They are widely preferred in the switched mode power supplies, and DC motor drives applications. Besides DC choppers find their role as interfaces between the DC systems [

6

] of different [

7

] voltage levels. The output voltage of PWM based [

8

] DC choppers are varied by varying the duty cycle. Buck converter is a subset of DC–DC converters. It is desired to explore new methodologies, so as to enable DC choppers to elicit better performance of DC Drives.

This work proposes new modulation strategies for three phase cascaded multilevel inverter topology with reduced number of switches and is able to create five level output. The main advantage of the proposed work is to reduce the number of switches when compared to the conventional MLIs. The reduced number of switches reduces the switching losses and improves the efficiency of the inverter. Variable amplitude variable frequency strategy provides output with relatively low distortion and better DC bus utilization is obtained with variable amplitude carrier overlapping phase disposition technique.

This paper presents the comparison of unipolar multicarrier Pulse Width Modulation (PWM) techniques for the Diode Clamped Multi Level Inverter (DCMLI). Due to switch combination redundancies, there are certain degrees of freedom to generate the five levels AC output voltage. The different types of unipolar PWM strategies for the chosen inverter are considered and the effectiveness of the developed strategies is demonstrated by the simulation. The results indicate that the multilevel inverter triggered by the developed sub-harmonic PWM strategy exhibits reduced harmonics. The results are presented and analysed.

This paper deals with the design issues relevant to achieve ZVS for three level converters. It shows the method of designing a three level converter and to achieve ZVS in the wide range of load current and input voltage by employing coupled inductor. This converter overcomes the drawbacks presented by the conventional zero-voltage switching (ZVS) three-level converter, such as high circulating energy, severe parasitic ringing on the rectifier diodes, loss of duty cycle, high conduction loss and limited ZVS load range for the primary switches. This converter employs a coupled inductor to achieve zero-voltage switching of the primary switches in the entire line and load range is described. Because the coupled inductor does not appear as a series inductance in the load current path, it does not cause a loss of duty cycle or severe voltage ringing across the output rectifiers.

This paper proposes a variable common mode injection pulse width modulation (VCMIPWM) scheme for three level neutral point clamped (NPC) inverter. Using suitable PWM control technique the waveform quality of the inverter output can be improved. Optimal harmonic profile may be obtained by having equal zero vectors in a switching cycle. If the expression of common mode injection as calculated for two level inverters is directly applied for three level inverters the dwell times for zero vectors will be unequal and the harmonic performance will be poor. The amount of common mode injection required to have equal zero vectors depends on the magnitude of sinusoidal reference vectors. The amount of common mode injection is calculated for various cases of reference sinusoidal vectors and is injected with the sinusoidal reference vectors to produce modified reference vectors. Simulation has been carried out in MATLAB/SIMULINK for three level inverter with the VCMIPWM and the results are compared with the fixed common mode injection pulse width modulation (FCMIPWM).

The paper develops a fuzzy based methodology to improve the frequency spectrum of the output voltage and almost eliminates the need of a filter in a DC link inverter. The presence of harsh loads attempt to deteriorate the quality of the current drawn from the mains. It therefore orients to simultaneously reshape the input current phasor to a nearly sinusoidal waveform in the sense it drastically reduces the amplitude of the multiple frequency harmonic components of the input AC current. The scheme derives the reference for the PWM pulses through the use of fuzzy principles and arrives at the appropriate width for the pulses to the power switches. The frequency of the carrier is allowed to vary randomly with a view to distinctly decrease the current frequency magnitudes over the operating range. It includes the simulation results obtained using MATLAB to illustrate its potential to extract a variable magnitude output voltage in tune with the change in the modulation index. The regulated output voltage over a range of operating loads and the sinusoidal shape of the supply current substantiate the merits of the strategy and claim its applicability in the utility world.

In the deregulated environment, the economic related problems like generation dispatch, unit commitment, network cost allocation, congestion management, market clearing prices etc. are all associated with the geographical location of the generation companies and the consumers. The number of transmission lines, the distance and the voltage levels are some of the predominant factors in deciding the solution for the above problems for which electrical distance between the utilities is widely used as a tool by the power system researchers. In this paper, a complete analysis has been made on the concept of electrical distance and on the various factors affecting it. A sample five bus system is taken for analysis. The results are quite encouraging and help the researchers to extend the application of electrical distance in various domains.

Power system frequency regulation entitled load frequency control (LFC), as a major function of automatic generation control (AGC), has been one of the important control problems in electric power system design and operation. Normally, for the control of frequency conventional control methodology is used. In the recent years, the soft computing techniques such as artificial neural network (ANN), Fuzzy systems and evolutionary algorithms are used to develop an intelligent load frequency controller. The Performance of a Fuzzy logic controller is limited by its large number of rules and if the rules are large then computation time and requirement of memory is large. This problem is compensated by using Polar Fuzzy logic controller. So a Polar Fuzzy logic controller is proposed for the load frequency control problem. The aim of the Polar Fuzzy Controller is to restore the frequency and tie-line power in a smooth way to its nominal value in the shortest possible time if any load disturbance is applied. System performance is examined and compared with a standard Fuzzy logic controller, and conventional PI controller.

The paper proposes a new mixed method for reducing the order of interval systems i.e., systems having uncertain but bounded parameters. The denominator of the reduced order model is obtained by α table and numerator is derived by applying factor division and Cauer second form. A numerical example has been discussed to illustrate the procedures. The errors between the original higher order and reduced order models have also been highlighted to support the effectiveness of the proposed methods.

Impulse testing of transformers after assembly is a routine procedure carried out for the assessment of their winding insulation. During impulse test insulation failure may result in two classes of winding faults in a transformer namely series faults and shunt faults. Series faults are due to the short between turns in the section and the shunt faults are due to the short between turns in the section and the ground. This paper aims at deriving a technique for the detection and classification of impulse faults in a transformer winding using wavelet transform and a fuzzy Inference system. A specially designed 6.6 kV model layer winding is considered for the study. The entire winding comprising ten sections are divided into three regions namely sections near line end, sections near the neutral end and the sections in the middle of the winding. The neutral currents are recorded with series faults and shunt faults introduced in the sections belonging to the three regions. Continuous wavelet transform is applied on these neutral current records to extract the discriminating features. The features extracted from the wavelet transformed signal are the second most predominant frequency, the time range at which it occurs and the corresponding wavelet coefficient. A fuzzy Inference system is designed and implemented using Matlab software with these three features extracted from the wavelet transformed signal as inputs and generates an output that classifies the fault and no fault conditions. It is observed that the results are satisfactory.

In this study, we discuss about a neural system for three-phase induction-motor speed control and power factor correction. The speed control strategy consists in keeping constant voltage–frequency ratio of the induction-motor supply source. A neural-control system uses speed error and speed-error variation to change both the fundamental voltage amplitude and frequency of a sinusoidal pulse width modulation inverter. The controller performance in relation to reference and load-torque variations is considered. A high-performance single-phase AC to DC rectifier with active power factor correction technique is used for line power factor correction. Single phase supply is converted to three phase and it is fed to three phase induction motor. The proposed approach has many advantages over conventional fuzzy based induction motor speed control such as less settling time, accuracy and improved efficiency. In this approach we obtain power factor correction in single phase source. According to the simulation results, proposed method has achieved better results by suppressing speed overshoot and ripple as compared to the conventional method and able to correct speed error from load-torque variations.

Transformer is an essential device in power systems. Winding deformation due to short circuit is one of the faults that require serious attention. Model based approaches for winding deformation detection have attracted researchers widely. This paper aims at determination of distributed parameters of the lumped element model of a transformer winding using particle swarm intelligence. A specially designed layer winding model is used to carry out the frequency response experiment. Difference between the simulated frequency response and experimental frequency response is defined as the fitness function that is minimized using particle swarm optimization technique.

The explanation related to the concept of Rotating Magnetic Field (RMF) in 3-phase induction motor (IM) and its visualization is a tricky issue in teaching–learning process. The complexity increases with the number of poles. Hence visualization of RMF for a 4-pole Induction motor is attempted via magnetic field distribution pattern(s). The aim of this paper is to explore and utilize the capability of Finite Element Method Magnetics (FEMM) as a tool for demonstrating rotating magnetic field effect produced in the stator of a 3-phase induction motor. In addition to the RMF demo, visual correlation between angular rotations of electrical wave with mechanical degree is reported. Also, the effect of phase sequence reversal is incorporated in the graphical exhibition.

Modelling of integrating and unstable time delay processes using describing function (DF) approximation of a relay with hysteresis is presented in this paper. Modelling of system parameters is necessary for tuning of controllers. In relay based identification methods describing function analysis is generally used to estimate the model parameters because of the general usefulness of the method and it is simple and straightforward. The effect of measurement noise in process modelling is an important issue as noise may change the actual amplitude of limit cycle output and also can fail the system identification test. To reduce the effect of measurement noise, a relay with hysteresis is considered in the proposed identification method. Simulation results are discussed to validate the proposed identification method.

In this paper, the fractional-orders of integrator and differentiator in an optimal PID controller, for a first order plus dead time (FOPDT) model, are varied and a comparative study is made on the closed loop responses. In addition a new model based controller design approach is followed for designing fractional-order controllers for a class of fractional order systems.

The basic requirement for an autopilot is fast response and minimum steady state error for better guidance performance. The highly nonlinear nature of the missile dynamics due to the severe kinematic and inertial coupling of the missile airframe as well as the aerodynamics has been a challenge for an autopilot that is required to have satisfactory performance for all flight conditions in probable engagements. Dynamic inversion is very popular nonlinear controller for this kind of scenario. But the drawback of this controller is that it is sensitive to parameter perturbation. To overcome this problem, neural network has been used to capture the parameter uncertainty on line. The choice of basis function plays the major role in capturing the unknown dynamics. Here in this paper, many basis function has been studied for approximation of unknown dynamics. Cosine basis function has yield the best response compared to any other basis function for capturing the unknown dynamics. Neural network with Cosine basis function has improved the autopilot performance as well as robustness compared to Dynamic inversion without Neural network.

Presently there is a vast interest in unmanned aerial vehicle (UAV) development given its civilian and military applications. One of the main UAV components is autopilot system. Its development invariably demands several lab simulations and field tests. Generally after an UAV crash few parts remain unused. Thus, before embedding an autopilot system, it has to be exhaustively lab tested. With educational and research purposes in autopilot control systems development area, a test platform is herein proposed. It employs Matlab/Simulink to run the autopilot controller under test. The autopilot controller designed on Matlab/Simulink is tested by controlling an aircraft on X-Plane. The inputs given to the aircraft flight control surfaces in the X-Plane are simultaneously sent to the microcontroller which translates these commands into effective servo movement control. Through this platform, designed autopilot systems can be applied into models similar to real aircraft minimizing risks and increasing flexibility for design changes. As study case, tests results from a pitch attitude autopilot system are presented.

Design and Implementation of State estimators for nonlinear, large dimensional system have gain widespread attention in the field of advanced process control. In this paper an Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) based state estimation schemes have been applied to estimate the state variables of Tennessee Eastman Process. The efficacy of the derivative based and derivative free state estimation schemes on the Tennessee Eastman Process have been assessed through simulation studies.

ECG signal classification is widely used for diagnosing many cardiac diseases, which is the main cause of mortality in developed countries. Since most of the clinically useful information in the ECG signal is found in the intervals and amplitudes. The development of accurate and robust methods for automatic ECG signal classification is a subject of major importance. Modeling techniques like Least Square Estimation (LSQ) and Autoregressive (AR) modeling have been performed on the ECG signal. The model coefficients extracted using autoregressive modeling technique was found to be resourceful, so it has been taken for further validation. The ECG data is taken from standard MIT-BIH Arrhythmia database. AR coefficients obtained from the AR modeling are fed to the back-propagation neural network which classifies the ECG signal. In order to train the modeling coefficients with the back-propagation neural network the architecture implemented with 2 input neurons, 2 hidden neurons and 2 output neurons. In this work all neurons uses sigmoid activation function.

Sleep Apnoea is a disorder characterized by abnormal pauses in breathing during sleep. Obstructive Sleep Apnoea is a condition where breathing is interrupted by a physical block to airflow despite respiratory effort. It is based on the fact that heart rate dynamics of a healthy person differs from that of a person suffering from OSA. The heart rate typically shows cyclic increases and decreases associated with the Apnoea phase and resumption of breathing. Identification of the oscillatory dynamics is done using the RR inter beat interval series. Hilbert transformation is applied to the sinus inter beat interval time series to derive the instantaneous amplitudes and frequencies of the series thus monitoring the presence or absence of OSA.

The aim of this paper is to automate the classification of various blood diseases using digital image processing technique in MATLAB software. The analysis of blood smear is a powerful diagnostic tool for the prediction of diseases like Malaria, Elephantiasis, Trypanosomiasis, Sickle cell anaemia and Polycythemia. As they are life threatening diseases and an enormous global health problem, rapid and precise differentiation is necessary in clinical settings. Automation of disease detection in life science laboratories can be done by extracting the statistical features of the blood smear images taken by the digital microscopes and processing it using Digital Image Processing technique in MATLAB software.

In this paper the project titled an automated breathing device for critically ill patients has been discussed. Ambu bag (AB) is a flexible reservoir bag used for artificial ventilation connected by tubing and non-rebreathing valve to a face mask or endo-tracheal tube. It is a hand held device used to provide positive pressure ventilation to a patient who is not breathing or who is breathing inadequately [

1

]. In ambulances and in emergency wards of hospitals manually operated ambu bag is used. Bagging is necessarily regular in medical emergencies when the patient’s breathing is insufficient or has ceased completely and also to provide mechanical ventilation in preference to mouth to mouth resuscitation. The problems involved in this type of manual ambu bag is that sometimes due to the negligence of the caretakers required quantity of oxygen is not carried over to the lungs, secondly even if the caretakers are alert one cannot assure that they expel a constant quantity of oxygen into the patient’s lungs, thirdly this type of mechanism basically is a stress to the caretakers. To overcome this, an automatic mechanism for administering oxygen into the patient’s body has been developed and tested successfully. This automated ambu bag is economically cheap and gives much comfort to the care takers and the required amount of oxygen can be delivered appropriately according to the need of the patient.

The objective of the present study was to investigate the hypolipidemic effect of various extracts of whole plant of

Bauhinia purpurea

in rat fed with high fat diet. The elevated levels of total cholesterol, ester and free cholesterol, phospholipids, triglycerides, low-density lipoprotein, and very low-density lipoprotein due to high fat diet (HFD). The group receiving ethyl acetate extract of

Bauhinia purpurea

at the dose of 250 mg/kg (Group IV) was significantly (

P

< 0.001) reduced the lipid profile and lipoprotein levels. A significant (

p

< 0.001) reduction in HDL-cholesterol was noticed in HFD fed groups (II); however, a significant increased the HDL level was produced by the administration of ethyl acetate extract of

Bauhinia purpurea

. There was a noticed increase in the body weight in HFD fed group (II), which was significantly (

p

< 0.001) reduced by the administration of ethyl acetate extract of

Bauhinia purpurea

. Therefore, it was concluded that the ethyl acetate extract of whole plant of

Bauhinia purpurea

as definite cardio protective effect against hyperlipidemia.

Objective

: To evaluate the immunomodulatory activity of aqueous leaf extract of

Ocimum sanctum

(ALEOS) by in-vitro and in-vivo methods.

Materials and Methods

: Extracts and standard drug were administered orally for 14 days. The immunomodulatory activity were studied in Wistar strain rats by the following parameters like Delayed Type Hypersensitivity (DTH), Humoral Antibody Titre (HAT), Total Leucocyte Count (TLC) and Differential Leucocyte Count (DLC).

Results

: The effect of ALEOS 200 and 400 mg/kg on DTH response is significantly (

P

< 0.05) increased when compared with the control group. In HAT the ALEOS 200 mg/kg showed significant (

P

< 0.05) effect and ALEOS 400 mg/kg, Standard treatment produced highly significant (

P

< 0.01) when compared with control group. ALEOS 200, 400 mg/kg and standard treatment shows highly significant (

P

< 0.01) in TLC when compared with control group. In DLC count ALEOS 200 mg/kg showed significant effect (

P

< 0.05) only but in ALEOS 400 mg/kg and standard treatment shows highly significant (

P

< 0.01) compared with the control group. Physiochemical examination of the extract showed the presence of carbohydrates, glycosides, saponins, phenolics, tannins and alkaloids.

Conclusion

: Based on the results it can be concluded that the plant

Ocimum sanctum

was found to be a better herb for immunomodulatory activity. Further studies are required to understand the mechanism of action at the molecule level to support these findings.

The aim of the present investigation was isolation and characterization of active components derived from whole plant of

Mucuna pruriens

. The plant were extracted with various solvents (pet. ether, ethyl acetate and methanol), methanol was found to be more active among them. The preliminary phytochemical results revealed that phytosterols, flavonoids and amino acids as active constituents in methanolic extract of

Mucuna pruriens

. The methanolic extract of

Mucuna pruriens

was undergone column chromatography with different solvent fractions. Despite, three compounds were isolated from methanolic extract of

Mucuna pruriens

with the compound 1 was eluted with benzene: Chloroform 90:10, v/v and compound 2 were eluted with eluted with ethyl acetate: methanol 80:20, v/v and then compound 3 were eluted with ethyl acetate: methanol, 70:30, v/v. The structures of the two isolated compounds were characterized by using FT-IR, NMR and Mass spectrophotometric methods. Thus, the compound 1 was characterized as acetate of 3β-Hydroxy-5α-Cholanic acid (C

26

H

38

O

3

), the compound 2 was characterized as 3, 5, 7, 4′-Tetrahydroxy-6-methoxyflavone (C

16

H

12

O

7

) and the compound 3 was characterized as Ethyl 2-amino-5-hydroxy-3, 6, 6-trimethyl heptonate (C

12

H

25

NO

3

). Furthermore, pharmacological studies required for the isolated compounds.

Ultrasound imaging is a widely used and safe medical diagnostic technique, due to its noninvasive nature, low cost, real time imaging. However the usefulness of ultrasound imaging is degraded by the presence of signal depended noise known as speckle. Removing speckle noise from the original image is still a challenging research in image processing. Nonlinear techniques have recently assumed significance as they are able to suppress speckle noise which is also called as multiplicative noise to preserve important signal elements such as edges and fine details. Among nonlinear techniques, the fuzzy logic based approaches are important as they are capable of reasoning with vague and uncertain information. This paper presents a fuzzy filter for suppressing noise in polycystic ovary image to show the feasibility of the proposed noise reduction using Fuzzy filter. The better performance of the filter is demonstrated on the basis of MSE and RMSE values calculated from the original and restored images respectively.

It has been well established that microorganisms are virtually an unlimited source of natural products, many of which have potential therapeutic applications. Among the various organisms the filamentous soil bacteria of the genus

Streptomyces

are remarkable and are considered as a potential source of important bioactive compounds. In the present study we have isolated actinomycetes from six locations in Neyveli lignite mine area, Tamilnadu, India and tested for their antagonistic activity. Seven isolates, which possess good antagonistic activity against bacterial and fungal pathogens, were selected and all the isolates represented the genus

Streptomyces

. The isolates have been identified up to the species level as per ISP procedures. The results of the study prove that the lignite mines are very promising zone for potential actinomycetes.

The economic emission dispatch (EED) assumes a lot of significance to meet the clean energy requirements of the society and simultaneously minimizes the cost of generation. The biogeography based optimization (BBO), inspired from the geographical distribution of biological species, has some features that are common to genetic algorithm and particle swam optimization; and searches for optimal solution through the migration and mutation operators. This paper presents an effective BBO strategy for obtaining the robust solution of EED problem. The feasibility of the proposed approach is evaluated through three test systems and the results are presented to highlight its suitability for practical applications.

Flexible AC Transmission System (FACTS) devices have brought in remarkable changes in the field of power system operation and control. Their development and application have made the traditional AC power system with an inherent time lag to respond quickly towards unprecedented changes. As these devices use power electronic switches unlike conventional controllers, they tend to be costlier and hence it is inevitable to consider not only the ratings but also the location for device placement to tap maximum benefit. In this work, the problem of optimal device placement is addressed taking into account the cost of the device also. Hence the objective function is formulated in such a way to take into account the cost of the device, line loadings and load voltage deviations. The problem is solved by applying BBO technique, simulating various load conditions on IEEE 14, 30 and 57 bus systems. The results of the proposed technique are compared with the results obtained through the application of PSO algorithm.

In multi-process embedded system, optimizing the design of hardware and software reliability is fairly hard. In this paper, hardware replication and software re-execution techniques are combined to tolerate transient faults. It helps to reduce the usage of space and time in terms of embedded system design with minimal resource. The probability of information about embedded systems reliability is analyzed using System Fault Tree (SFT). SFT analyzer integrates SFT into an optimization process. An optimization algorithm which is used in this paper is known as Multi-Objective Differential Evolution (MODE), which makes effective design space exploration. It is also used to map the fault-tolerance policy information into chromosomes. The experimental result shows the achievement of maximum reliability in spatial redundancy using minimal resource and minimal fault tolerance.

The chapter develops an artificial neural network (ANN) based strategy to identify the sense of an ambiguous word as part of an information retrieval mechanism in a question answering system. The philosophy echoes to support the broad domain of natural language processing through its trained capabilities and endeavour to resolve the lexical ambiguity. The neural network is designed using the relations between the target word and associated words that appear in the sentence. It evolves a feed forward procedure to allow the weights to be adjusted and arrive at the precise contextual sense of the word. The inputs and weights are assigned in tune with the frequently appearing words in the English literature to train the model. The performance is investigated for a set of words that inherit a similar context with the words used in the training phase and the results claim the emergence of a promising word sense identifying tool.