Optimal Sleep-Wake Policies for an Energy Harvesting Sensor Node

We study a sensor node with an energy harvesting source. In any slot,the sensor node is in one of two modes: Wake or Sleep. The generated energy is stored in a buffer. The sensor node senses a random field and generates a packet when it is awake. These packets are stored in a queue and transmitted in the wake mode using the energy available in the energy buffer. We obtain energy management policies which minimize a linear combination of the mean queue length and the mean data loss rate. Then, we obtain two easily implementable suboptimal policies and compare their performance to that of the optimal policy. Next, we extend the Throughput Optimal policy developed in our previous work to sensors with two modes. Via this policy, we can increase the through put substantially and stabilize the data queue by allowing the node to sleep in some slots and to drop some generated packets. This policy requires minimal statistical knowledge of the system. We also modify this policy to decrease the switching costs.

Characterization of compact ICP ion source for focused ion beam applications

A compact, high brightness 13.56 MHz inductively coupled plasma ion source without any axial or radial multicusp magnetic fields is designed for the production of a focused ion beam. Argon ion current of density more than 30 mA/cm(2) at 4 kV potential is extracted from this ion source and is characterized by measuring the ion energy spread and brightness. Ion energy spread is measured by a variable-focusing retarding field energy analyzer that minimizes the errors due t divergence of ion beam inside the analyzer. Brightness of the ion beam is determined from the emittance measured by a fully automated and locally developed electrostatic sweep scanner. By optimizing various ion source parameters such as RF power, gas pressure and Faraday shield, ion beams with energy spread of less than 5 eV and brightness of 7100 Am(-2)sr(-1)eV(-1) have been produced. Here, we briefly report the details of the ion source, measurement and optimization of energy spread and brightness of the ion beam. (C) 2010 Elsevier B.V. All rights reserved.

Joint Power Control, Scheduling and Routing for Multihop Energy Harvesting Sensor Networks

We study wireless multihop energy harvesting sensor networks employed for random field estimation. The sensors sense the random field and generate data that is to be sent to a fusion node for estimation. Each sensor has an energy harvesting source and can operate in two modes: Wake and Sleep. We consider the problem of obtaining jointly optimal power control, routing and scheduling policies that ensure a fair utilization of network resources. This problem has a high computational complexity. Therefore, we develop a computationally efficient suboptimal approach to obtain good solutions to this problem. We study the optimal solution and performance of the suboptimal approach through some numerical examples.

Synthesis and electrical properties of the (PVA)(0.7)(Kl)(0.3)center dot xH(2)SO(4) (0 <= x <= 5) polymer electrolytes and their performance in a primary Zn/MnO2 battery

Solid acid polymer electrolytes (SAPE) were synthesised using polyvinyl alcohol, potassium iodide and sulphuric acid in different molar ratios by solution cast technique. The temperature dependent nature of electrical conductivity and the impedance of the polymer electrolytes were determined along with the associated activation energy. The electrical conductivity at room temperature was found to be strongly depended on the amorphous nature of the polymers and H2SO4 concentration. The ac (100 Hz to 10 MHz) and dc conductivities of the polymer electrolytes with different H2SO4 concentrations were analyzed. A maximum dc conductivity of 1.05 x 10(-3) S cm(-1) has been achieved at ambient temperature for electrolytes containing 5 M H2SO4. The frequency and temperature dependent dielectric and electrical modulus properties of the SAPE were studied. The charge transport in the present polymer electrolyte was obtained using Wagner's polarization technique, which demonstrated the charge transport to be mainly due to ions. Using these solid acid polymer electrolytes novel Zn/SAPE/MnO2 solid state batteries were fabricated and their discharge capacity was calculated. An open circuit voltage of 1.758V was obtained for 5 M H2SO4 based Zn/SAPE/MnO2 battery. (C) 2010 Elsevier Ltd. All rights reserved.

Cooperative Spectrum Sensing Algorithms For OFDM Systems with Frequency Selective Channels

This paper considers the problem of spectrum sensing in cognitive radio networks when the primary user employs Orthogonal Frequency Division Multiplexing (OFDM). We specifically consider the scenario when the channel between the primary and a secondary user is frequency selective. We develop cooperative sequential detection algorithms based on energy detectors. We modify the detectors to mitigate the effects of some common model uncertainties such as timing and frequency offset, IQ-imbalance and uncertainty in noise and transmit power. The performance of the proposed algorithms are studied via simulations. We show that the performance of the energy detector is not affected by the frequency selective channel. We also provide a theoretical analysis for some of our algorithms.

Molecular assemblies for solar energy conversion - Biomimetic approach

Excitation energy migration followed by electron transfer forms the main components of natural photosynthesis. An understanding of these aspects is essential to reenact the primary processes in laboratory under conditions that are precisely repeatable. Here we describe the state of understanding of the natural process and several model systems designed to harvest solar energy and conversion to useful form of chemical energy. The molecular assemblies constituting the model systems offer a great advantage in terms of better comprehension of the mechanistic aspects and yield valuable information on the design of molecular photonic devices.

Source localization in a partially known shallow?water channel

The source localization in shallow water is beset with problems arising from the presence of a large number of correlated multipaths. Nevertheless, given a complete knowledge of the water channel it is definitely possible to localize a source. A complete knowledge of the channel, however, is rarely available under most practical conditions. A new approach is proposed wherein the bottom reflection coefficients are not required; hence the bottom conditions need not be known. Further, because of the use of signal subspace for localization, the proposed approach is robust against the background noise (-20 dB) and channel depth uncertainty (10 lambda). All these nice features of the proposed approach are possible only when the array size is large (>40 sensors). (C) 1995 Acoustical Society of America.

Delay and energy optimal two-hop relaying in delay tolerant networks

We study the trade-off between delivery delay and energy consumption in delay tolerant mobile wireless networks that use two-hop relaying. The source may not have perfect knowledge of the delivery status at every instant. We formulate the problem as a stochastic control problem with partial information, and study structural properties of the optimal policy. We also propose a simple suboptimal policy. We then compare the performance of the suboptimal policy against that of the optimal control with perfect information. These are bounds on the performance of the proposed policy with partial information. Several other related open loop policies are also compared with these bounds.

DNA Free Energy-Based Promoter Prediction and Comparative Analysis of Arabidopsis and Rice Genomes

The cis-regulatory regions on DNA serve as binding sites for proteins such as transcription factors and RNA polymerase. The combinatorial interaction of these proteins plays a crucial role in transcription initiation, which is an important point of control in the regulation of gene expression. We present here an analysis of the performance of an in silico method for predicting cis-regulatory regions in the plant genomes of Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) on the basis of free energy of DNA melting. For protein-coding genes, we achieve recall and precision of 96% and 42% for Arabidopsis and 97% and 31% for rice, respectively. For noncoding RNA genes, the program gives recall and precision of 94% and 75% for Arabidopsis and 95% and 90% for rice, respectively. Moreover, 96% of the false-positive predictions were located in noncoding regions of primary transcripts, out of which 20% were found in the first intron alone, indicating possible regulatory roles. The predictions for orthologous genes from the two genomes showed a good correlation with respect to prediction scores and promoter organization. Comparison of our results with an existing program for promoter prediction in plant genomes indicates that our method shows improved prediction capability.

Photoelectron spectroscopy beamline on Indus-1 synchrotron radiation source

We describe here a photoelectron spectroscopy beamline installed on Indus-1 storage ring. Initially we give a brief description of optical and mechanical layout of beam-line. The beamline optics was designed to cover energy range from 10 eV to 200 eV and it consists of a pre-focusing mirror, a toroidal grating monochromator and a post-focusing mirror. We then discuss indigenously developed ultra high vacuum compatible work station to carry out angle integrated photoemission experiments. The beamline has been successfully commissioned and photoemission measurements on a variety of standard samples are presented.

Impact of Energy Expenditure Rate Constraints on the performance of Multihop Wireless Mesh Networks

In this article we study the problem of joint congestion control, routing and MAC layer scheduling in multi-hop wireless mesh network, where the nodes in the network are subjected to maximum energy expenditure rates. We model link contention in the wireless network using the contention graph and we model energy expenditure rate constraint of nodes using the energy expenditure rate matrix. We formulate the problem as an aggregate utility maximization problem and apply duality theory in order to decompose the problem into two sub-problems namely, network layer routing and congestion control problem and MAC layer scheduling problem. The source adjusts its rate based on the cost of the least cost path to the destination where the cost of the path includes not only the prices of the links in it but also the prices associated with the nodes on the path. The MAC layer scheduling of the links is carried out based on the prices of the links. We study the e�ects of energy expenditure rate constraints of the nodes on the optimal throughput of the network.

Energy-insensitive Guidance of Solid Motor Propelled Long Range Flight Vehicles Using MPSP and Dynamic Inversion

A energy-insensitive explicit guidance design is proposed in this paper by appending newlydeveloped nonlinear model predictive static programming technique with dynamic inversion, which render a closed form solution of the necessary guidance command update. The closed form nature of the proposed optimal guidance scheme suppressed the computational difficulties, and facilitate realtime solution. The guidance law is successfully verified in a solid motor propelled long range flight vehicle, for which developing an effective guidance law is more difficult as compared to a liquid engine propelled vehicle, mainly because of the absence of thrust cutoff facility. The scheme guides the vehicle appropriately so that it completes the mission within a tight error bound assuming that the starting point of the second stage to be a deterministic point beyond the atmosphere. The simulation results demonstrate its ability to intercept the target, even with an uncertainty of greater than 10% in the burnout time

Geographic Resources Decision Support System – an Open Source GIS

Fully structured and matured open source spatial and temporal analysis technology seems to be the official carrier of the future for planning of the natural resources especially in the developing nations. This technology has gained enormous momentum because of technical superiority, affordability and ability to join expertise from all sections of the society. Sustainable development of a region depends on the integrated planning approaches adopted in decision making which requires timely and accurate spatial data. With the increased developmental programmes, the need for appropriate decision support system has increased in order to analyse and visualise the decisions associated with spatial and temporal aspects of natural resources. In this regard Geographic Information System (GIS) along with remote sensing data support the applications that involve spatial and temporal analysis on digital thematic maps and the remotely sensed images. Open source GIS would help in wide scale applications involving decisions at various hierarchical levels (for example from village panchayat to planning commission) on economic viability, social acceptance apart from technical feasibility. GRASS (Geographic Resources Analysis Support System, http://wgbis.ces.iisc.ernet.in/grass) is an open source GIS that works on Linux platform (freeware), but most of the applications are in command line argument, necessitating a user friendly and cost effective graphical user interface (GUI). Keeping these aspects in mind, Geographic Resources Decision Support System (GRDSS) has been developed with functionality such as raster, topological vector, image processing, statistical analysis, geographical analysis, graphics production, etc. This operates through a GUI developed in Tcltk (Tool command language / Tool kit) under Linux as well as with a shell in X-Windows. GRDSS include options such as Import /Export of different data formats, Display, Digital Image processing, Map editing, Raster Analysis, Vector Analysis, Point Analysis, Spatial Query, which are required for regional planning such as watershed Analysis, Landscape Analysis etc. This is customised to Indian context with an option to extract individual band from the IRS (Indian Remote Sensing Satellites) data, which is in BIL (Band Interleaved by Lines) format. The integration of PostgreSQL (a freeware) in GRDSS aids as an efficient database management system.

Biomonitoring of Lotic habitats through Diatoms

Freshwater ecosystems vary in size and composition and contain a wide range of organisms which interact with each other and with the environment. These interactions are between organisms and the environment as nutrient cycling, biomass formation and transfer, maintenance of internal environment and interactions with the external environment. The range of organisms present in aquatic communities decides the generation and transfer function of biomass, which defines and characterises the system. These organisms have distinct roles as they occupy particular trophic levels, forming an interconnected system in a food chain. Availability of resources and competition would primarily determine the balance of individual species within the food web, which in turn influences the variety and proportions of the different organisms, with important implications for the overall functioning of the system. This dynamic and diverse relationship decides the physical, chemical and biological elements across spatial and temporal scales in the aquatic ecosystem, which can be recorded by regular inventorying and monitoring to maintain the integrity and conserve the ecosystem. Regular environmental monitoring, particularly water quality monitoring allows us to detect, assess and manage the overall impacts on the rivers. The appreciation of water quality is in constant flux. Water quality assessments derived through the biotic indices, i.e. assessments based on observations of the resident floral and faunal communities has gained importance in recent years. Biological evaluations provide a description of the water quality that is often not achievable from elemental analyses alone. A biological indicator (or bioindicator) is a taxon or taxa selected based on its sensitivity to a particular attribute, and then assessed to make inferences about that attribute. In other words, they are a substitute for directly measuring abiotic features or other biota. Bioindicators are evaluated through presence or absence, condition, relative abundance, reproductive success, community structure (i.e. composition and diversity), community function (i.e. trophic structure), or any combination thereof.Biological communities reflect the overall ecological integrity by integrating various stresses, thus providing a broad measure of their synergistic impacts. Aquatic communities, both plants and animals, integrate and reflect the effects of chemical and physical disturbances that occur over extended periods of time. Monitoring procedures based on the biota measure the health of a river and the ability of aquatic ecosystems to support life as opposed to simply characterising the chemical and physical components of a particular system. This is the central purpose of assessing the biological condition of aquatic communities of a river.Diatoms (Bacillariophyceae), blue green algae (Cyanophyceae), green algae (Chlorophyceae), and red algae (Rhodphyceae) are the main groups of algae in flowing water. These organisms are widely used as biological indicators of environmental health in the aquatic ecosystem because algae occupy the most basic level in the transfer of energy through natural aquatic systems. The distribution of algae in an aquatic ecosystem is directly related to the fundamental factors such as physical, chemical and biological constituents. Soft algae (all the algal groups except diatoms) have also been used as indicators of biological integrity, but they may have less efficiency than diatoms in this respect due to their highly variable morphology. The diatoms (Bacillariophyceae) comprise a ubiquitous, highly successful and distinctive group of unicellular algae with the most obvious distinguishing characteristic feature being siliceous cell walls (frustules). The photosynthetic organisms living within its photic zone are responsible for about one-half of global primary productivity. The most successful organisms are thought to be photosynthetic prokaryotes (cyanobacteria and prochlorophytes) and a class of eukaryotic unicellular algae known as diatoms. Diatoms are likely to have arisen around 240 million years ago following an endosymbiotic event between a red eukaryotic alga and a heterotrophic flagellate related to the Oomycetes.The importance of algae to riverine ecology is easily appreciated when one considers that they are primary producers that convert inorganic nutrients into biologically active organic compounds while providing physical habitat for other organisms. As primary producers, algae transform solar energy into food from which many invertebrates obtain their energy. Algae also transform inorganic nutrients, such as atmospheric nitrogen into organic forms such as ammonia and amino acids that can be used by other organisms. Algae stabilises the substrate and creates mats that form structural habitats for fish and invertebrates. Algae are a source of organic matter and provide habitat for other organisms such as non-photosynthetic bacteria, protists, invertebrates, and fish. Algae's crucial role in stream ecosystems and their excellent indicator properties make them an important component of environmental studies to assess the effects of human activities on stream health. Diatoms are used as biological indicators for a number of reasons: 1. They occur in all types of aquatic ecosystems. 2. They collectively show a broad range of tolerance along a gradient of aquatic productivity, individual species have specific water chemistry requirements. 3. They have one of the shortest generation times of all biological indicators (~2 weeks). They reproduce and respond rapidly to environmental change and provide early measures of both pollution impacts and habitat restoration. 4. It takes two to three weeks before changes are reflected to a measurable extent in the assemblage composition.

Distributed Source Coding for Sensor Data Model and Estimation of Cluster Head Errors Using Bayesian and K-Near Neighborhood Classifiers in Deployment of Dense Wireless Sensor Networks

The lifetime calculation of large dense sensor networks with fixed energy resources and the remaining residual energy have shown that for a constant energy resource in a sensor network the fault rate at the cluster head is network size invariant when using the network layer with no MAC losses.Even after increasing the battery capacities in the nodes the total lifetime does not increase after a max limit of 8 times. As this is a serious limitation lots of research has been done at the MAC layer which allows to adapt to the specific connectivity, traffic and channel polling needs for sensor networks. There have been lots of MAC protocols which allow to control the channel polling of new radios which are available to sensor nodes to communicate. This further reduces the communication overhead by idling and sleep scheduling thus extending the lifetime of the monitoring application. We address the two issues which effects the distributed characteristics and performance of connected MAC nodes. (1) To determine the theoretical minimum rate based on joint coding for a correlated data source at the singlehop, (2a) to estimate cluster head errors using Bayesian rule for routing using persistence clustering when node densities are the same and stored using prior probability at the network layer, (2b) to estimate the upper bound of routing errors when using passive clustering were the node densities at the multi-hop MACS are unknown and not stored at the multi-hop nodes a priori. In this paper we evaluate many MAC based sensor network protocols and study the effects on sensor network lifetime. A renewable energy MAC routing protocol is designed when the probabilities of active nodes are not known a priori. From theoretical derivations we show that for a Bayesian rule with known class densities of omega1, omega2 with expected error P* is bounded by max error rate of P=2P* for single-hop. We study the effects of energy losses using cross-layer simulation of - large sensor network MACS setup, the error rate which effect finding sufficient node densities to have reliable multi-hop communications due to unknown node densities. The simulation results show that even though the lifetime is comparable the expected Bayesian posterior probability error bound is close or higher than Pges2P*.