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Vijayakumar V.,Information Institute of Engineering
International Journal of Control | Year: 2017

In this work, we consider a nonlinear resolvent integro-differential evolution inclusions in Hilbert spaces. This paper deals with the approximate controllability for nonlinear resolvent integro-differential inclusions in Hilbert spaces. We use Bohnenblust–Karlin's fixed-point theorem to establish a set of sufficient conditions for the approximate controllability for nonlinear resolvent integro-differential inclusions in Hilbert spaces. Further, we extend the result to study the approximate controllability concept with non-local conditions. An example is presented to demonstrate the obtained theory. © 2017 Informa UK Limited, trading as Taylor & Francis Group

Nirmal Kumar A.,Information Institute of Engineering
Journal of Applied Research and Technology | Year: 2013

In this study, a multilevel inverter was designed and implemented to operate a stand-alone solar photovoltaic system. The proposed system uses pulse-width modulation (PWM) in the multilevel inverter to convert DC voltage from battery storage to supply AC loads. In the PWM method, the effectiveness of eliminating low-order harmonics in the inverter output voltage is studied and compared to that of the sinusoidal PWM method. This work also uses adaptive neuro fuzzy inference (ANFIS) to predict the optimum modulation index and switch angles required for a five level cascaded H-bridge inverter with improved inverter output voltage. The data set for the ANFIS-based analysis was obtained with the Newton-Raphson (NR) method. The proposed predictive method is more convincing than other techniques in providing all possible solutions with any random initial guess and for any number of levels of a multilevel inverter. The simulation results prove that the lower-order harmonics are eliminated using the optimum modulation index and switching angles. An experimental system was implemented to demonstrate the effectiveness of the proposed system.

Gopinath B.,Information Institute of Engineering | Shanthi N.,KS Rangasamy College of Technology
Asian Pacific Journal of Cancer Prevention | Year: 2013

Objective: The aim of this study was to develop an automated computer-aided diagnostic system for diagnosis of thyroid cancer pattern in fine needle aspiration cytology (FNAC) microscopic images with high degree of sensitivity and specificity using statistical texture features and a Support Vector Machine classifier (SVM). Materials and Methods: A training set of 40 benign and 40 malignant FNAC images and a testing set of 10 benign and 20 malignant FNAC images were used to perform the diagnosis of thyroid cancer. Initially, segmentation of region of interest (ROI) was performed by region-based morphology segmentation. The developed diagnostic system utilized statistical texture features derived from the segmented images using a Gabor filter bank at various wavelengths and angles. Finally, the SVM was used as a machine learning algorithm to identify benign and malignant states of thyroid nodules. Results: The SVMachieved a diagnostic accuracy of 96.7% with sensitivity and specificity of 95% and 100%, respectively, at a wavelength of 4 and an angle of 45. Conclusion: The results show that the diagnosis of thyroid cancer in FNAC images can be effectively performed using statistical texture information derived with Gabor filters in association with an SVM.

Gopinath B.,Information Institute of Engineering | Shanthi N.,KS Rangasamy College of Technology
Australasian Physical and Engineering Sciences in Medicine | Year: 2013

An automated computer-aided diagnosis system is developed to classify benign and malignant thyroid nodules using multi-stained fine needle aspiration biopsy (FNAB) cytological images. In the first phase, the image segmentation is performed to remove the background staining information and retain the appropriate foreground cell objects in cytological images using mathematical morphology and watershed transform segmentation methods. Subsequently, statistical features are extracted using two-level discrete wavelet transform (DWT) decomposition, gray level co-occurrence matrix (GLCM) and Gabor filter based methods. The classifiers k-nearest neighbor (k-NN), Elman neural network (ENN) and support vector machine (SVM) are tested for classifying benign and malignant thyroid nodules. The combination of watershed segmentation, GLCM features and k-NN classifier results a lowest diagnostic accuracy of 60 %. The highest diagnostic accuracy of 93.33 % is achieved by ENN classifier trained with the statistical features extracted by Gabor filter bank from the images segmented by morphology and watershed transform segmentation methods. It is also observed that SVM classifier results its highest diagnostic accuracy of 90 % for DWT and Gabor filter based features along with morphology and watershed transform segmentation methods. The experimental results suggest that the developed system with multi-stained thyroid FNAB images would be useful for identifying thyroid cancer irrespective of staining protocol used. © 2013 Australasian College of Physical Scientists and Engineers in Medicine.

Gopinath B.,Information Institute of Engineering | Shanthi N.,KS Rangasamy College of Technology
Journal of Medical and Biological Engineering | Year: 2012

This paper proposes automated segmentation methods for dead cancer cells in the microscopic images of Ehrlich's Lymphoma Ascite (ELA) cancer cells of Swiss albino mice to evaluate the cytotoxic effect of the medicinal plants Cynodon dactylon (C. dactylon) and Terminalia catappa (T. catappa). Microscopic images of untreated ELA cancer cell samples and these treated with extracts of C. dactylon and T. catappa are acquired. The dead cancer cells in the microscopic images are identified and isolated using region-based mathematical morphology and watershed segmentation methods. The dead cancer cells in the output images are counted using run-length encoding method. The microscopic image of the untreated sample has only nine dead cancer cells whereas those of samples treated with the extracts each have 31 dead cancer cells. The percentage of dead ELA cancer cells in the samples increased by 244.45% after treatment with the extracts of C. dactylon and T. catappa, respectively. It is thus concluded that C. dactylon and T. catappa have a significant cytotoxic effect against ELA cancer cells.

Gopal C.,Information Institute of Engineering | Mohanraj M.,Information Institute of Engineering | Chandramohan P.,Professional Group of Institutions | Chandrasekar P.,Professional Group of Institutions
Renewable and Sustainable Energy Reviews | Year: 2013

The research developments with renewable energy source water pumping systems (RESWPSs) are reviewed in this paper. The reported investigations are categorized into five major groups as follows: (i) solar photovoltaic water pumping systems (SPWPSs), (ii) solar thermal water pumping systems (STWPSs), (iii) wind energy water pumping systems (WEWPSs), (iv) biomass water pumping systems (BWPSs) and (v) hybrid renewable energy water pumping systems (HREWPSs). More than a hundred published articles related to RESWPSs are briefly reviewed. Additionally, the limitations with RESWPSs and further research needs are described. This paper concludes that renewable energy sources (RESs) play a vital role in reducing the consumption of conventional energy sources and its environmental impacts for water pumping applications. © 2013 Elsevier Ltd.

Mohanraj M.,Information Institute of Engineering | Jayaraj S.,National Institute of Technology Calicut | Muraleedharan C.,National Institute of Technology Calicut
Renewable and Sustainable Energy Reviews | Year: 2012

In this paper, an attempt has been made to review the applications of artificial neural networks (ANN) for energy and exergy analysis of refrigeration, air conditioning and heat pump (RACHP) systems. The studies reported are categorized into eight groups as follows: (i) vapour compression systems (ii) RACHP systems components, (iii) vapour absorption systems, (iv) prediction of refrigerant properties (v) control of RACHP systems, (vi) phase change characteristics of refrigerants, (vii) heat ventilation air conditioning (HVAC) systems and (viii) other special purpose heating and cooling applications. More than 90 published articles in this area are reviewed. Additionally, the limitations with ANN models are highlighted. This paper concludes that ANN can be successfully applied in the field of RACHP systems with acceptable accuracy. © 2011 Elsevier Ltd. All rights reserved.

Raman N.,Information Institute of Engineering
Asian Journal of Information Technology | Year: 2016

The design of low power multipliers is the basic necessity for the design and the implementation of efficient power aware devices. Multipliers play a major role in digital signal processing applications. In multiplication, reliability is strongly affected by power consumption. Here Vedic multiplier is designed by the principles of Vedic Mathematics which is the ancient Indian system of mathematics. In this study four 4x4 Vedic multipliers are designed based on four different logic full adders such as 28T, TGFA, 14T and 16T. These multipliers and full adders were designed and simulated using microwind 2 electronic design automation tool with 0.12 μm technology. Finally a comparison is made on the performance of full adders and Vedic multipliers based on power consumption and transistor count. © Medwell Journals, 2016.

Mohanraj M.,Information Institute of Engineering
Energy for Sustainable Development | Year: 2013

In this work, the energy performance of a domestic refrigerator has been assessed theoretically with R134a and R430A as alternative refrigerant. The performance has been assessed for three different condensing temperatures, specifically, 40, 50 and 60. °C with a wide range of evaporator temperatures between -. 30 and 0. °C. The performance of the domestic refrigerator was compared in terms of volumetric cooling capacity, coefficient of performance, compressor power consumption and compressor discharge temperature. Total equivalent global warming impact of the refrigerator was assessed for a 15-year life time. The results showed that volumetric cooling capacities of R430A and R134a are similar, so that R134a compressor can be used for R430A without modifications. The coefficient of performance of R430A was found to be higher than that of R134a by about 2.6-7.5% with 1-9% lower compressor power consumption at all operating temperatures. The compressor discharge temperature of R430A was observed to be 3-10. °C higher than that of R134a. Total equivalent global warming impact of R430A was found to be lower than that of R134a by about 7% due to its higher energy efficiency. The results confirmed that R430A is an energy efficient and environment-friendly alternative to R134a in domestic refrigerators. © 2013 Elsevier Ltd.

Akila,Anna University | Maheswari U.,Information Institute of Engineering
Journal of Computer Science | Year: 2013

In this study, we propose a content-based medical image retrieval framework based on binary association rules to augment the results of medical image diagnosis, for supporting clinical decision making. Specifically, this work is employed on scanned Magnetic Resonance brain Images (MRI) and the proposed Content Based Image Retrieval (CBIR) process is for enhancing relevancy rate of retrieved images. The pertinent features of a query brain image are extracted by applying third order moment invariant functions, which are then examined with the selected feature indexes of large medical image database for appropriate image retrieval. Binary association rules are incorporated here for organizing and marking the significant features of database images, regarding a specific criterion. Trigonometric function distance similarity measurement algorithm is applied to improve the accuracy rate of results. Moreover, the performances of classification and retrieval methods are determined in terms of precision and recall rates. Experimental results reveal the efficacy of the adduced methodology as compared to the related works. © 2013 Science Publications.

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