ORNEV: Optimized Recharging of Wireless Sensor Networks using Virtual Base Stations

Several recharging methodologies and frameworks have been proposed for recharging wireless sensor networks. In this paper we study these propositions and device a method that would enhance the recharging capability of the framework and keep the network up and running without the energy getting depleted. We explore a new dimension where we use the SenCars used for charging a node to transmit data just like a node in the WSN. The SenCar acts like a virtual base station for a node that carries high traffic that it will be charging. This cuts down transmission of data through nodes that connects the high traffic node with the base station thereby moving them to sleep mode. This SenCar then directly transmits traffic information from the node it is charging to the base station using cellular technology. DOI: 10.17762/ijritcc2321-8169.150712

A Survey on the Various Frameworks Available for Re-Energizing Wireless Senor Networks

Wireless Sensor Networks (WSNs) are finding its applications in different scenarios in our day to day life. However a major problem that our current technology faces these days is the lack of technical knowledge of how these networks can be kept up and functioning to an efficient level. The power consumption and replenishment of these sensors that are deployed in the environment to be monitored has been a challenging factor since decades. Researches on the improvements in the efficiency in the power consumption of WSNs have been going on for quite a while. Premature energy depletion and outdated recharging strategies are some of the major research areas that require improvement in WSNs. In this paper we enumerate the existing technologies and new proposals on the different frameworks that have been designed to enhance the efficiency in recharging Sensors deployed in WSNs. DOI: 10.17762/ijritcc2321-8169.150311

Extracting the Groupwise Core Structural Connectivity Network: Bridging Statistical and Graph-Theoretical Approaches

Finding the common structural brain connectivity network for a given population is an open problem, crucial for current neuro-science. Recent evidence suggests there's a tightly connected network shared between humans. Obtaining this network will, among many advantages , allow us to focus cognitive and clinical analyses on common connections, thus increasing their statistical power. In turn, knowledge about the common network will facilitate novel analyses to understand the structure-function relationship in the brain. In this work, we present a new algorithm for computing the core structural connectivity network of a subject sample combining graph theory and statistics. Our algorithm works in accordance with novel evidence on brain topology. We analyze the problem theoretically and prove its complexity. Using 309 subjects, we show its advantages when used as a feature selection for connectivity analysis on populations, outperforming the current approaches

A Prediction based Energy-Efficient Tracking Method in Sensor Networks

I. INTRODUCTION Recently, an increasing interest in deploying wireless sensor networks (WSNs) for real-life applications. OTSN is mainly used to track certain objects in a monitored area and to report their position to the application's users. Object tracking, which is also called target tracking, is a major field of research in WSNs and has many real-life applications such as wild life monitoring, security applications for buildings and compounds to avoid interference or trespassing, and international border monitoring for prohibited crossings. Additionally, object tracking is measured one of the most challenging applications in WSNs due to its application requirements, which place a heavy load on the network resources, mainly energy consumption. The main task of an object tracking sensor network (OTSN) is to track a moving object and to report its latest location in the monitored area to the application in an acceptable timely manner, and this dynamic process of sensing and reporting keeps the network's resources under heavy pressure. However, there has been a very limited focus on the energy lost by the computing components, which are referred to as microcontroller unit (MCU) and the sensing components OTSN is considered as one of the most energy-consuming applications of WSNs. Due to this fact, there is a necessity to develop energy-efficient techniques that adhere to the application requirements of an objecttracking system, which reduce the total energy consumption of the OTSN while maintaining a tolerable missing rate level

Travelling on Graphs with Small Highway Dimension

We study the Travelling Salesperson (TSP) and the Steiner Tree problem (STP) in graphs of low highway dimension. This graph parameter was introduced by Abraham et al. [SODA 2010] as a model for transportation networks, on which TSP and STP naturally occur for various applications in logistics. It was previously shown [Feldmann et al. ICALP 2015] that these problems admit a quasi-polynomial time approximation scheme (QPTAS) on graphs of constant highway dimension. We demonstrate that a significant improvement is possible in the special case when the highway dimension is 1, for which we present a fully-polynomial time approximation scheme (FPTAS). We also prove that STP is weakly NP-hard for these restricted graphs. For TSP we show NP-hardness for graphs of highway dimension 6, which answers an open problem posed in [Feldmann et al. ICALP 2015]

Direct observation of growth and collapse of a Bose-Einstein condensate with attractive interactions

The dynamical behavior of Bose-Einstein condensation (BEC) in a gas with attractive interactions is striking. Quantum theory predicts that BEC of a spatially homogeneous gas with attractive interactions is precluded by a conventional phase transition into either a liquid or solid. When confined to a trap, however, such a condensate can form provided that its occupation number does not exceed a limiting value. The stability limit is determined by a balance between self-attraction and a repulsion arising from position-momentum uncertainty under conditions of spatial confinement. Near the stability limit, self-attraction can overwhelm the repulsion, causing the condensate to collapse. Growth of the condensate, therefore, is punctuated by intermittent collapses, which are triggered either by macroscopic quantum tunneling or thermal fluctuation. Previous observation of growth and collapse has been hampered by the stochastic nature of these mechanisms. Here we reduce the stochasticity by controlling the initial number of condensate atoms using a two-photon transition to a diatomic molecular state. This enables us to obtain the first direct observation of the growth of a condensate with attractive interactions and its subsequent collapse.Comment: 10 PDF pages, 5 figures (2 color), 19 references, to appear in Nature Dec. 7 200

Effect of Silver Plasmonic Layer on Cu2O/In2S3 Solar Cell

Solar cell with the structure Cu/Cu2O/In2S3/Ag@NP/Ag was fabricated where the In2S3-window layer and the plasmonic Ag nano particle thin film layer were deposited using injection chemical spray pyrolysis technique. Quantum efficiency measurement of these solar cells showed improved performance in the blue region of the visible spectrum compared to their counterparts. The films with Ag nano particles exhibited surface plasmon resonance peak at 432 nm which could be assigned to plasmon resonance of Ag nano-particles. The open circuit voltage of the best solar cell is 0.65 V, with short circuit current density of 1.2 mA/cm2, fill factor 22% and efficiency 0.17 %. We conclude that the in-coupling of light by the metallic nanoparticle thin film layer into the underlying semiconductor layer resulted in improvement in electrical performance of these solar cells containing the plasmonic Ag nano particles

Long-term Variability Properties and Periodicity Analysis for Blazars

In this paper, the compiled long-term optical and infrared measurements of some blazars are used to analyze the variation properties and the optical data are used to search for periodicity evidence in the lightcurve by means of the Jurkevich technique and the discrete correlation function (DCF) method. Following periods are found: 4.52-year for 3C 66A; 1.56 and 2.95 years for AO 0235+164; 14.4, 18.6 years for PKS 0735+178; 17.85 and 24.7 years for PKS 0754+100; 5.53 and 11.75 for OJ 287. 4.45, and 6.89 years for PKS 1215; 9 and 14.84 years for PKS 1219+285; 2.0, 13.5 and 22.5 for 3C273; 7.1 year for 3C279; 6.07 for PKS 1308+326; 3.0 and 16.5 years for PKS 1418+546; 2.0 and 9.35 years for PKS 1514-241; 18.18 for PKS 1807+698; 4.16 and 7.0 for 2155-304; 14 and 20 years for BL Lacertae. Some explanations have been discussed.Comment: 10 pages, 2 table, no figure, a proceeding paper for Pacific Rim Conference on Stellar Astrophysics, Aug. 1999, HongKong, Chin

Benign cervical multi-nodular goiter presenting with acute airway obstruction: a case report

<p>Abstract</p> <p>Introduction</p> <p>Benign cervical goiters rarely cause acute airway obstruction.</p> <p>Case presentation</p> <p>We report the case of a 64-year-old woman of African descent who presented with acute shortness of breath. She required immediate intubation and later a total thyroidectomy for a benign cervical multi-nodular goiter with no retrosternal tracheal compression.</p> <p>Conclusion</p> <p>Benign multi-nodular goiters are commonly left untreated once euthyroid. Peak inspiratory flow rates should be measured via spirometry in all goiters to assess the degree of tracheal compression. Once tracheal compression is identified, an elective total thyroidectomy should be performed to prevent morbidity and mortality from acute airway obstruction.</p