Informatics Publishing Limited

P. G. Sanghvi ¹, R. B. Brahmbhat ¹, S. Das ¹, S. Devi ¹

Affiliations
1 Department of Chemistry, Faculty of Science, M. S. University of Baroda, Baroda-390 002, IN

Abstract

Polymerization of styrene in microemulsion was carried out using an oil-in-water system and sodium dodecylsulphate surfactant. The oil/surfactant ratio was observed to be 1 : 1.8 at 30°C. However, systems containing more than 5% w/w styrene in microemulsion turned into emulsion. Use of styrene - 2-hydroxyethyImethacrylate (2-HEMA) mixture could overcome this problem where 2-HEMA acts as polymerizable cosurfactant. Various conditions such as type and concentration of initiatiors, temperature were optimized for polymerization of styrene using SDS and 2-HEMA as surfactant and cosurfactant respectively. The products synthesised at optimized conditions were characterized by IR, NMR and dynamic light scattering. The rate of polymerization was also calculated.

Keywords

Polymerization, Styrene, Microemulsion, Polymerizable Cosurfactant, Particle Size.

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S. Devi ¹, N. P. Hemanth Kumar ¹

Affiliations
1 The Oxford College of Engineering, Bommanahalli, Bangalore-68, IN

Abstract

Increasingly developed social sharing websites, like Flickr and You tube, allows users to create, share, annotates and comments Medias. The large-scale user-generated meta-data not only facilitate users in sharing and organizing multimedia content, but provide useful information to improve media retrieval and management. Personalized search serves as one of such examples where the web search experience is improved by generating the returned list according to the modified user search intents. The basic premise is to embed the user preference and query-related search intent into user-specific topic spaces. Since the users’ original annotation is too sparse for topic modeling, it is necessary to enrich users’ annotation pool before user specific topic spaces construction. The proposed framework contains two components: 1) Ranking based Multi-correlation Tensor Factorization model is to perform annotation prediction 2) User-specific Topic Modeling to map the query relevance and user preference into the same user-specific topic space.

Keywords

Personalized Image Search, Social Annotation, Tensor Factorization, Topic Modeling, Query Mapping.

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S. Devi ¹, L. N. Samaga ²

Affiliations
1 NITTE University, Mangalore-575 018, IN
2 KS Hegde Academy of Medical Sciences, NITTE University, Deralakatte, Mangalore - 575 018, IN

Abstract

This study examined the effect of Transcendental Meditation on blood pressure and stress in subjects with Systemic hypertension. The study, which used a True-Experimental design, recruited a sample of 30 subjects from a general outpatient clinic. Fifteen subjects received Transcendental Meditation training. The meditation is taught in a selfadministered program, requiring one hour of training during the first three days, followed by the regular twice daily practice. Each 15-minutes session consists in sitting quietly with closed eyes while applying a specific mental procedure practiced at home daily. The 2, 4 ,6 weeks assessments were made on stress levels, BP levels systolic blood pressure, diastolic blood pressure and Heart Rate. Transcendental Meditation training had an immediate effect, reducing pulse rate 4.02 beats/min, Stress level 0-6 score, systolic blood pressure 0-4 mm Hg, and diastolic blood pressure 0-3 mm Hg. After 2, 4, 6, weeks of Transcendental Meditation training, further decreases in pulse rate (0-6 beats/min), systolic blood pressure (2-9 mm Hg), and diastolic blood pressure (1-7 mm Hg) occurred. Transcendental Meditation significantly lowered patients' perception of stress (P<0.905), and it enhanced their perception of health and wellbeing. Transcendental Meditation is beneficial for patients with systemic hypertension, and nurses can use it to enhance their independent function as well as their quality of life.

Keywords

Transcendental Meditation, Blood Pressure, Stress, Meditation, Relaxation Therapies.

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S. Devi ¹, S. Sridhar ¹

Affiliations
1 Department of Computer Applications, S.A. Engineering College, IN

Abstract

Data mining is the process of examining large databases in order to generate new information. Data mining in health care plays a major role. Healthcare industry generates large amounts of complex data about patients, hospital resources, disease diagnosis, electronic patient records, medical devices etc., Heart disease is a term for a number of different diseases which affects our heart. Common heart diseases are cardiovascular disease, Carotid Artery Disease (CAD), Coronary Heart Disease (CHD), Peripheral Artery Disease (PAD), Chronic Heart Disease (CKD) and stroke.  The objective of this paper is to evaluate different classification technique in heart disease forecasting like Naive Bayes and K-Nearest Neighbor algorithms.

Keywords

Data Mining, Naïve Bayes, K-Nearest Neighbor and Dataset.

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