Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4

Search results for: S. Arumugam

4 Calcification Classification in Mammograms Using Decision Trees

Authors: S. Usha, S. Arumugam

Abstract:

Cancer affects people globally with breast cancer being a leading killer. Breast cancer is due to the uncontrollable multiplication of cells resulting in a tumour or neoplasm. Tumours are called ‘benign’ when cancerous cells do not ravage other body tissues and ‘malignant’ if they do so. As mammography is an effective breast cancer detection tool at an early stage which is the most treatable stage it is the primary imaging modality for screening and diagnosis of this cancer type. This paper presents an automatic mammogram classification technique using wavelet and Gabor filter. Correlation feature selection is used to reduce the feature set and selected features are classified using different decision trees.

Keywords: Breast Cancer, Mammogram, Symlet Wavelets, Gabor Filters, Decision Trees

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3 Innovative Techniques for Characterization of Nonwoven Insulation Materials Embedded with Aerogel

Authors: Mohanapriya Venkataraman, Rajesh Mishra, Jakub Weiner, Adnan Mazari, Jiri Militky, Veera Kumar Arumugam

Abstract:

The major objective of this study is to understand the potential of a newly fabricated equipment to study the thermal properties of nonwoven textile fabrics treated with aerogel at subzero temperatures. Thermal conductivity was calculated by using the empirical relation Fourier’s law, The relationship between the thermal conductivity and thermal resistance of the samples were studied at various environmental temperatures (which was set in the clima temperature system between +25oC to -25oC). The newly fabricated equipment was found to be a suitable for measuring at subzero temperatures. This field of measurements is being developed and will be the subject of further research which will be more suitable for measurement of the various thermal characteristics.

Keywords: Thermal Measurements, Aerogel, Nonwoven, Hot plate Heading.

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2 Antioxidant Capacity and Total Phenolic Content of Aqueous Acetone and Ethanol Extract of Edible Parts of Moringa oleifera and Sesbania grandiflora

Authors: Perumal Siddhuraju, Arumugam Abirami, Gunasekaran Nagarani, Marimuthu Sangeethapriya

Abstract:

Aqueous ethanol and aqueous acetone extracts of Moringa oleifera (outer pericarp of immature fruit and flower) and Sesbania grandiflora white variety (flower and leaf) were examined for radical scavenging capacities and antioxidant activities. Ethanol extract of S. grandiflora (flower and leaf) and acetone extract of M. oleifera (outer pericarp of immature fruit and flower) contained relatively higher levels of total dietary phenolics than the other extracts. The antioxidant potential of the extracts were assessed by employing different in vitro assays such as reducing power assay, DPPH˙, ABTS˙+ and ˙OH radical scavenging capacities, antihemolytic assay by hydrogen peroxide induced method and metal chelating ability. Though all the extracts exhibited dose dependent reducing power activity, acetone extract of all the samples were found to have more hydrogen donating ability in DPPH˙ (2.3% - 65.03%) and hydroxyl radical scavenging systems (21.6% - 77.4%) than the ethanol extracts. The potential of multiple antioxidant activity was evident as it possessed antihemolytic activity (43.2 % to 68.0 %) and metal ion chelating potency (45.16 - 104.26 mg EDTA/g sample). The result indicate that acetone extract of M. oleifera (OPIF and flower) and S. grandiflora (flower and leaf) endowed with polyphenols, could be utilized as natural antioxidants/nutraceuticals.

Keywords: Antioxidant activity, Moringa oleifera, Polyphenolics, Sesbania grandiflora, Underutilized vegetables.

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1 Novel Hybrid Approaches For Real Coded Genetic Algorithm to Compute the Optimal Control of a Single Stage Hybrid Manufacturing Systems

Authors: M. Senthil Arumugam, M.V.C. Rao

Abstract:

This paper presents a novel two-phase hybrid optimization algorithm with hybrid genetic operators to solve the optimal control problem of a single stage hybrid manufacturing system. The proposed hybrid real coded genetic algorithm (HRCGA) is developed in such a way that a simple real coded GA acts as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method is next employed to do fine tuning. The hybrid genetic operators involved in the proposed algorithm improve both the quality of the solution and convergence speed. The phase–1 uses conventional real coded genetic algorithm (RCGA), while optimisation by direct search and systematic reduction of the size of search region is employed in the phase – 2. A typical numerical example of an optimal control problem with the number of jobs varying from 10 to 50 is included to illustrate the efficacy of the proposed algorithm. Several statistical analyses are done to compare the validity of the proposed algorithm with the conventional RCGA and PSO techniques. Hypothesis t – test and analysis of variance (ANOVA) test are also carried out to validate the effectiveness of the proposed algorithm. The results clearly demonstrate that the proposed algorithm not only improves the quality but also is more efficient in converging to the optimal value faster. They can outperform the conventional real coded GA (RCGA) and the efficient particle swarm optimisation (PSO) algorithm in quality of the optimal solution and also in terms of convergence to the actual optimum value.

Keywords: Hybrid systems, optimal control, real coded genetic algorithm (RCGA), Particle swarm optimization (PSO), Hybrid real coded GA (HRCGA), and Hybrid genetic operators.

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