Performance analysis of self-organized Ad-Hoc sensor networks

This project deals with a Distributed Sensor Network (DSN). The main focus of this thesis is to deliver an OPNET simulation model for working DSN model. After building a model, various performance analysis techniques in terms of different parameters were used to verify the working model. Query Dominant Sets (QDS) are the main idea behind this thesis. The QDS node is in charge of the nodes for a specific region and its job is to assign the query tasks that it gets to the nodes in that region to help maximize the life of the network. If no user queries are being sent, the QDS nodes themselves go to sleep to conserve energy and just listen for special incoming control signals. QDS management (including the selection of QDS and the interaction of QDS nodes and other common nodes) is a challenging issue in DSN platforms. Our algorithm for QDS management attempts to limit the dead spots in the network that tend to disrupt the communication of the whole network. It has two phases and the first phase is the election phase. The second stage is the previously elected QDS nodes distribute the tasks to the other nodes. This algorithm turns out to be distributed which is good for sensor networks. There is no use of any global communication or long-range, high energy data communication, but just local communications. This also helps to save power and energy for long life of the sensors. This algorithm is also very scalable and fault tolerant. We have done significant simulations to verify our QDS concepts. There are some metrics that are used to evaluate our schemes such as the average energy values of all the nodes in the network, minimum energy of all the nodes in the network, total energy consumed in the awake, transmit, and receive states, maximum time spent by any node in electing a new QDS, number of elected QDSs, and so on. Our simulations have shown satisfactory energy-efficiency of our algorithms

Explicit Pre A*-algebra

This manuscript is a study on Birkhoff centre of a Pre-A*-algebra. In fact, it is proved that Birkhoff centre of a Pre A*-algebra is also a Pre A*-algebra and identified that the centre of Birkhoff centre of a Pre A*-algebra is a Boolean algebra.Keywords: Pre A*-algebra, Centre, Birkoff centre, Boolean algebra

Azine Dyes as Iodometric Indicators

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Variation of hydrochemical parameters with reference to geomorphological features in Godavari estuary, India

24-33In this study, seasonal observations of hydrochemical parameters were measured in the estuarine regions of  Gautami Godavari (GGE) and Vasishta Godavari (VGE), which are surrounded by extensive mangrove swamps and closely spaced beach ridge-swale complex, respectively. A significant vertical stratification in the water column showed in the VGE region due to the strong influence of saline water intrusion. NO2- -N was higher and NO3- -N was lower in VGE during the end of the post monsoon season with reference to excretion by phytoplankton and uptake during the process of primary production respectively, which is also supported by higher concentrations of Chlorophyll a. Nutrients (NO3- -N, PO43—P and SiO42--Si) showed conservative behaviour with salinity in GGE, whereas, in the case of VGE absence of this is due to intrusion of saline water was significantly higher

EVALUATION AND PHARMACIST'S INTERVENTION FOR IMPROVING ADHERENCE AMONG RENAL FAILURE PATIENTS

Objective: Management of renal disease may include pharmacotherapy, dialysis, life style modifications, organ transplants and immunosuppressive therapy. Lack of adherence and proper perception towards prescribed renal failure treatment is a major contributor to poor outcome. A prospective, open labeled, interventional, pre-post study which included 60 patients with Chronic Renal Failure (CRF) on Hemodialysis (HD) was conducted over a period of 6 months with an objective to evaluate the degree of adherence, perception towards various treatment recommendations and to study the effect of pharmacist's intervention in improving compliance among patients on HD.Methods: Patients were assessed using the End Stage Renal Disease- Adherence Questionnaire (ESRD-AQ) scored questionnaire, where subjects were evaluated before and after counseling with a follow up period of 45 days and their response was scored.Results: Based on the scored response from 58 subjects who completed the study, overall adherence were grouped into three categories such as good adherence, moderate adherence, poor adherence which at baseline was found to be 69%,24.1%,6.9% of study subjects respectively and was improved to 72.4%,25.9%,1.7% at review.Conclusion: After pharmacist led patient counseling, patient perception towards medications, diet and fluid on showed improvement. On review the data analyzed for adherence parameters were statistically insignificant but clinically comparable with considerable improvement. Common reason cited by study subjects for non-compliance to medications was forgetfulness. From this study it can be concluded that pharmacist's intervention has a positive impact clinically on patient's perception and adherence.Â

Deep MR Brain Image Super-Resolution Using Spatio-Structural Priors

High resolution Magnetic Resonance (MR) images are desired for accurate diagnostics. In practice, image resolution is restricted by factors like hardware and processing constraints. Recently, deep learning methods have been shown to produce compelling state-of-the-art results for image enhancement/super-resolution. Paying particular attention to desired hi-resolution MR image structure, we propose a new regularized network that exploits image priors, namely a low-rank structure and a sharpness prior to enhance deep MR image super-resolution (SR). Our contributions are then incorporating these priors in an analytically tractable fashion \color{black} as well as towards a novel prior guided network architecture that accomplishes the super-resolution task. This is particularly challenging for the low rank prior since the rank is not a differentiable function of the image matrix(and hence the network parameters), an issue we address by pursuing differentiable approximations of the rank. Sharpness is emphasized by the variance of the Laplacian which we show can be implemented by a fixed feedback layer at the output of the network. As a key extension, we modify the fixed feedback (Laplacian) layer by learning a new set of training data driven filters that are optimized for enhanced sharpness. Experiments performed on publicly available MR brain image databases and comparisons against existing state-of-the-art methods show that the proposed prior guided network offers significant practical gains in terms of improved SNR/image quality measures. Because our priors are on output images, the proposed method is versatile and can be combined with a wide variety of existing network architectures to further enhance their performance.Comment: Accepted to IEEE transactions on Image Processin

Phytopharmacology of Chloroxylon swietenia: a review

The nature has provided a complete store house of remedies to use for all ailments for mankind. The knowledge on drugs has accumulated over thousands of years as a result of mans inquisitive nature. Phytomedicines or natural prescriptions, have assumed a basic part in World wellbeing for a large number of years. As per the World Health Organization (WHO), "natural medications incorporate herbs, home grown materials, home grown arrangements and completed home grown items, that contain as dynamic fixings parts of plants, or other plant materials, or blends. Chloroxylon swietenia DC. (Family: Rutaceae) is an important traditional medicinal plant used in the treatment of various ailments like fungal infection of skin, rheumatism, common cold, cough, ophthalmic infection and cataract, wounds and as an astringent. It is a tropical aromatic tree of dry deciduous forests popularly known as East Indian Satin Wood. The findings of this study will facilitate pharmacognostic standardization of the plant material and aid in the preparation of an herbal monograph for the species. Further studies on this plant must be carried out to explore some other important, necessary and unknown benefits. As the plant has multifunctional properties, this review is worthwhile and therefore it presents comprehensive analysed information on the phytochemical and pharmacological aspects of the botanical. Keywords: Chloroxylon swietenia, phytomedicines, pharmacological aspects, anti-feedant, anti-bacterial activity, IUCN, vulnerable species

Variation of hydrochemical parameters with reference to geomorphological features in Godavari estuary, India

In this study, seasonal observations of hydrochemical parameters were measured in the estuarine regions of  Gautami Godavari (GGE) and Vasishta Godavari (VGE), which are surrounded by extensive mangrove swamps and closely spaced beach ridge-swale complex, respectively. A significant vertical stratification in the water column showed in the VGE region due to the strong influence of saline water intrusion. NO2- -N was higher and NO3- -N was lower in VGE during the end of the post monsoon season with reference to excretion by phytoplankton and uptake during the process of primary production respectively, which is also supported by higher concentrations of Chlorophyll a. Nutrients (NO3- -N, PO43—P and SiO42--Si) showed conservative behaviour with salinity in GGE, whereas, in the case of VGE absence of this is due to intrusion of saline water was significantly higher