QoS Constrained Optimal Sink and Relay Placement in Planned Wireless Sensor Networks

We are given a set of sensors at given locations, a set of potential locations for placing base stations (BSs, or sinks), and another set of potential locations for placing wireless relay nodes. There is a cost for placing a BS and a cost for placing a relay. The problem we consider is to select a set of BS locations, a set of relay locations, and an association of sensor nodes with the selected BS locations, so that number of hops in the path from each sensor to its BS is bounded by hmax, and among all such feasible networks, the cost of the selected network is the minimum. The hop count bound suffices to ensure a certain probability of the data being delivered to the BS within a given maximum delay under a light traffic model. We observe that the problem is NP-Hard, and is hard to even approximate within a constant factor. For this problem, we propose a polynomial time approximation algorithm (SmartSelect) based on a relay placement algorithm proposed in our earlier work, along with a modification of the greedy algorithm for weighted set cover. We have analyzed the worst case approximation guarantee for this algorithm. We have also proposed a polynomial time heuristic to improve upon the solution provided by SmartSelect. Our numerical results demonstrate that the algorithms provide good quality solutions using very little computation time in various randomly generated network scenarios

Probabilistic partitioning methods to find significant patterns in ChIP-Seq data

Motivation: We have witnessed an enormous increase in ChIP-Seq data for histone modifications in the past few years. Discovering significant patterns in these data is an important problem for understanding biological mechanisms. Results: We propose probabilistic partitioning methods to discover significant patterns in ChIP-Seq data. Our methods take into account signal magnitude, shape, strand orientation and shifts. We compare our methods with some current methods and demonstrate significant improvements, especially with sparse data. Besides pattern discovery and classification, probabilistic partitioning can serve other purposes in ChIP-Seq data analysis. Specifically, we exemplify its merits in the context of peak finding and partitioning of nucleosome positioning patterns in human promoters. Availability and implementation: The software and code are available in the supplementary material. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

A COMPARATIVE STUDY ON THE IN-VITRO ANTIMICROBIAL ACTIVITY OF THE ROOTS OF FOUR THOTTEA SPECIES

Objective: The main objective of the present study was to investigate the antimicrobial activity of the methanol extract of the roots of four Thottea species. Methods: The root extracts of four Thottea species were subjected to antimicrobial assay by Minimum Inhibitory Concentration (MIC) and Agar Disc diffusion Assay against various medically important pathogens. Results: It is evident from the study that. Significant antibacterial activity was recorded by Thottea sivarajanii and highest activity was recorded against Pseudomonas aeruginosa and Staphylococcus epidermis (64 µg/ml). Out of the four extracts tested for antifungal activity, Thottea barberi and Thottea ponmudiana recorded significant antifungal activity and the highest activity was recorded by T. barberi against Trichophyton rubrum (16µg/ml). Conclusion: Results offer a scientific basis for the traditional use of Thottea species in the treatment of microbial infections, showing that the plant extract has an enormous potential as a prospective alternative drug against microbial pathogens. The present study lays the basis for future studies, to validate the possible use of Thottea species as a candidate in the treatment of microbial infections

Seasonal Variation of Atmospheric Aerosols over Prominent Hotspot Regions in South India by Employing MODIS Data

Mounting the amount of aerosols in the atmosphere is a subject of deep concern all over the globe. This elevated level of aerosol concentrations has proven direct impact on the radiative forcing (Gadhavi and Jayaraman A, 2004) and subsequent climate change. Thus it becomes imperative to study the inter-annual and seasonal variations of aerosols with the aid of remote sensing method by employing MODIS data. This paper pertains to the study of seasonal variations of Aerosol Optical Depths over three different locations which are lying along the same latitude in South India. The five year (2005-2009) observation is presented and it reveals that aerosol abundance has strong dependence on the geography, environment and local climate at a specific region. The variation of aerosol abundance is found to be higher at the coastal region than the region surrounded by land mass

Mucormycosis in a surgical defect masquerading as osteomyelitis: a case report and review of literature

Mucormycosis is a rare, highly lethal opportunistic fungal disease affecting immune compromised and diabetic patients. Mucormycosis is considered as the 3rd most common invasive mycosis after candidiasis and  aspergillosis in debilitating patients. It is caused by the filamentous fungi of the class zygomycetes. The infection usually begins in the nose due to inhalation of fungal spores. This fatal fungal disease needs a prompt and early definitive diagnosis, aggressive surgical therapy and high dose anti-fungal therapy. Here, we present a case report of Mucormycosis in a 64 year elderly diabetic male patient who was previously operated for myiasis and also the extensive review of the literature of the mucormycosis.Key words: Diabetes mellitus hyphae, myiasis, PAS stain, zygomycosi

Efficient ML Models for Practical Secure Inference

ML-as-a-service continues to grow, and so does the need for very strong privacy guarantees. Secure inference has emerged as a potential solution, wherein cryptographic primitives allow inference without revealing users' inputs to a model provider or model's weights to a user. For instance, the model provider could be a diagnostics company that has trained a state-of-the-art DenseNet-121 model for interpreting a chest X-ray and the user could be a patient at a hospital. While secure inference is in principle feasible for this setting, there are no existing techniques that make it practical at scale. The CrypTFlow2 framework provides a potential solution with its ability to automatically and correctly translate clear-text inference to secure inference for arbitrary models. However, the resultant secure inference from CrypTFlow2 is impractically expensive: Almost 3TB of communication is required to interpret a single X-ray on DenseNet-121. In this paper, we address this outstanding challenge of inefficiency of secure inference with three contributions. First, we show that the primary bottlenecks in secure inference are large linear layers which can be optimized with the choice of network backbone and the use of operators developed for efficient clear-text inference. This finding and emphasis deviates from many recent works which focus on optimizing non-linear activation layers when performing secure inference of smaller networks. Second, based on analysis of a bottle-necked convolution layer, we design a X-operator which is a more efficient drop-in replacement. Third, we show that the fast Winograd convolution algorithm further improves efficiency of secure inference. In combination, these three optimizations prove to be highly effective for the problem of X-ray interpretation trained on the CheXpert dataset.Comment: 10 pages include references, 4 figure

Design and development of solar assisted electric cart

Paper presented to the 3rd Southern African Solar Energy Conference, South Africa, 11-13 May, 2015.A cart is a vehicle designed for transport, using two wheels and normally pulled by one or a pair of draught animals. A solar vehicle is an electric vehicle which supplies all or most of its required power by converting solar radiation into electricity with the help of solar cells. The aim of this work is to design and develop a solar assisted electric cart that can be used for carrying loads and transporting people by villagers and farmers and also to reduce animal drudgery. As an initial investigation, the physical data of conventional cart used by farmers are collected based on which the motor and various parts of vehicle namely; Chain drive, Shaft, Suspension, Brakes etc. are selected for final development of cart. The FEM analysis is carried out to study the stress and displacements of the cart in order to ensure the safety. The basic performance of cart is evaluated in terms of its range, acceleration and maximum achievable speed. The final weight of cart so designed is 620 kg and load carrying capacityis found to be 800 kg. The achievable acceleration of cart is calculated as 1.2 m/s2with maximum achievable speed of 15km/h with a power rating of about 1.5kW out of which about 11.4% power is derived from solar radiation. The range of the cart is calculated as 44.75 km which seems to be reasonable for rural areas.dc201