Analysis of integrated optofluidic lab-on-a-chip sensor based on refractive index and absorbance sensing

The analysis of a fully integrated optofluidic lab-on-a-chip sensor is presented in this paper. This device is comprised of collinear input and output waveguides that are separated by a microfluidic channel. When light is passed through the analyte contained in the fluidic gap, optical power loss occurs owing to absorption of light. Apart from absorption, a mode-mismatch between the input and output waveguides occurs when the light propagates through the fluidic gap. The degree of mode-mismatch and quantum of optical power loss due to absorption of light by the fluid form the basis of our analysis. This sensor can detect changes in refractive index and changes in concentration of species contained in the analyte. The sensitivity to detect minute changes depends on many parameters. The parameters that influence the sensitivity of the sensor are mode spot size, refractive index of the fluid, molar concentration of the species contained in the analyte, width of the fluidic gap, and waveguide geometry. By correlating various parameters, an optimal fluidic gap distance corresponding to a particular mode spot size that achieves the best sensitivity is determined both for refractive index and absorbance-based sensing.

Throughput analysis of primary and secondary networks in a shared IEEE 802.11 system

In this paper, we analyze the coexistence of a primary and a secondary (cognitive) network when both networks use the IEEE 802.11 based distributed coordination function for medium access control. Specifically, we consider the problem of channel capture by a secondary network that uses spectrum sensing to determine the availability of the channel, and its impact on the primary throughput. We integrate the notion of transmission slots in Bianchi's Markov model with the physical time slots, to derive the transmission probability of the secondary network as a function of its scan duration. This is used to obtain analytical expressions for the throughput achievable by the primary and secondary networks. Our analysis considers both saturated and unsaturated networks. By performing a numerical search, the secondary network parameters are selected to maximize its throughput for a given level of protection of the primary network throughput. The theoretical expressions are validated using extensive simulations carried out in the Network Simulator 2. Our results provide critical insights into the performance and robustness of different schemes for medium access by the secondary network. In particular, we find that the channel captures by the secondary network does not significantly impact the primary throughput, and that simply increasing the secondary contention window size is only marginally inferior to silent-period based methods in terms of its throughput performance.

A GIS (geographical information system)-based spatial data mining approach for optimal location and capacity planning of distributed biomass power generation facilities: A case study of Tumkur district, India

This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.

Optimal design of timer-based, distributed selection with unknown number of nodes

The timer-based selection scheme is a popular, simple, and distributed scheme that is used to select the best node from a set of available nodes. In it, each node sets a timer as a function of a local preference number called a metric, and transmits a packet when its timer expires. The scheme ensures that the timer of the best node, which has the highest metric, expires first. However, it fails to select the best node if another node transmits a packet within Delta s of the transmission by the best node. We derive the optimal timer mapping that maximizes the average success probability for the practical scenario in which the number of nodes in the system is unknown but only its probability distribution is known. We show that it has a special discrete structure, and present a recursive characterization to determine it. We benchmark its performance with ad hoc approaches proposed in the literature, and show that it delivers significant gains. New insights about the optimality of some ad hoc approaches are also developed.

Two-axis force sensing and control of a Reorientable scanning probe

This paper presents the design and implementation of a reorientable scanning probe that is capable of two-axis force sensing and control in the 2-D scanning (X-Z) plane. The probe is comprised of three major components, namely a compliant manipulator, laser measurement system, and magnetic actuation system. Control of the position and orientation of the probe tip is realized by means of magnetic actuation combined with a novel structural design. The design of the manipulator's compliance and that of the optical path of the laser measurement system together enable achieving sensitivity to lateral (X) forces that is nearly identical to that of normal (Z) forces. The achieved sensitivity ratio, of about 0.6, is significantly higher than that of conventional scanning probe systems. The theoretical bases for the structural design and the sensitivity of the two-axis force sensing system are presented. Subsequently, fabrication of the manipulator is described and the result of experimental evaluation of the scanning probe's features is discussed. The scanning probe is used to access the vertical and re-entrant features on the two sides of a cylindrical micropipette, which are subsequently scanned by regulating the lateral force of tip-sample interaction.

Modified current space vector based powerline communication method for distributed inverters interfaced smart grids

The following paper presents a Powerline Communication (PLC) Method for grid interfaced inverters, for smart grid application. The PLC method is based on the concept of the composite vector which involves multiple components rotating at different harmonic frequencies. The pulsed information is modulated on the fundamental component of the grid current as a specific repeating sequence of a particular harmonic. The principle of communication is same as that of power flow, thus reducing the complexity. The power flow and information exchange are simultaneously accomplished by the interfacing inverters based on current programmed vector control, thus eliminating the need for dedicated hardware. Simulation results have been shown for inter-inverter communication, both under ideal and distorted conditions, using various harmonic modulating signals.

CO2 sensing at room temperature using carbon nanotubes coated core fiber Bragg grating

The sensing of carbon dioxide (CO2) at room temperature, which has potential applications in environmental monitoring, healthcare, mining, biotechnology, food industry, etc., is a challenge for the scientific community due to the relative inertness of CO2. Here, we propose a novel gas sensor based on clad-etched Fiber Bragg Grating (FBG) with polyallylamine-amino-carbon nanotube coated on the surface of the core for detecting the concentrations of CO2 gas at room temperature, in ppm levels over a wide range (1000 ppm-4000 ppm). The limit of detection observed in polyallylamine-amino-carbon nanotube coated core-FBG has been found to be about 75 ppm. In this approach, when CO2 gas molecules interact with the polyallylamine-amino-carbon nanotube coated FBG, the effective refractive index of the fiber core changes, resulting in a shift in Bragg wavelength. The experimental data show a linear response of Bragg wavelength shift for increase in concentration of CO2 gas. Besides being reproducible and repeatable, the technique is fast, compact, and highly sensitive. (C) 2013 AIP Publishing LLC.

Design and Analysis of an Acknowledgment-Aware Asynchronous MPR MAC Protocol for Distributed WLANs

Multi-packet reception (MPR) promises significant throughput gains in wireless local area networks (WLANs) by allowing nodes to transmit even in the presence of ongoing transmissions in the medium. However, the medium access control (MAC) layer must now be redesigned to facilitate rather than discourage - these overlapping transmissions. We investigate asynchronous MPR MAC protocols, which successfully accomplish this by controlling the node behavior based on the number of ongoing transmissions in the channel. The protocols use the backoff timer mechanism of the distributed coordination function, which makes them practically appealing. We first highlight a unique problem of acknowledgment delays, which arises in asynchronous MPR, and investigate a solution that modifies the medium access rules to reduce these delays and increase system throughput in the single receiver scenario. We develop a general renewal-theoretic fixed-point analysis that leads to expressions for the saturation throughput, packet dropping probability, and average head-of-line packet delay. We also model and analyze the practical scenario in which nodes may incorrectly estimate the number of ongoing transmissions.

Liquefied Petroleum Gas Sensing of Polyaniline-Titanium Dioxide Nanocomposites

Polyaniline/titaniurn dioxide nanocomposites were prepared using alpha-dextrose as surfactant and ammonium persulphate as an oxidant. The PANI/TiO2 nanocomposite is characterized by FTIR, XRD and TEM. The FTIR spectra revel that the presence of characteristic peaks of benzenoid, qunoide rings and metal-oxygen stretching. The XRD studies show the monoclinic structure of the nanocomposites. The TEM study shows that the size of TiO2 is in the order of 9 nm where as the composite size is of the order of 13 nm and further it was observed that the TiO2 particles are intercalated to form a core shell of PANI. The maximum sensing response for LPG is found to be 90% for 30 wt.% of PANI/TiO2 nanocomposites at 400 ppm whereas for Benzene and Toluene it is negligibly small (<= 20%) and for the cyclohexane sensing response it is around 30% for different wt.%.

Fusion of algorithms for compressed sensing

For compressed sensing (CS), we develop a new scheme inspired by data fusion principles. In the proposed fusion based scheme, several CS reconstruction algorithms participate and they are executed in parallel, independently. The final estimate of the underlying sparse signal is derived by fusing the estimates obtained from the participating algorithms. We theoretically analyze this fusion based scheme and derive sufficient conditions for achieving a better reconstruction performance than any participating algorithm. Through simulations, we show that the proposed scheme has two specific advantages: 1) it provides good performance in a low dimensional measurement regime, and 2) it can deal with different statistical natures of the underlying sparse signals. The experimental results on real ECG signals shows that the proposed scheme demands fewer CS measurements for an approximate sparse signal reconstruction.

Cantilever resonator with integrated actuation and sensing fabricated using a single step lithography

Micro- and nano-mechanical resonators have been proposed for a variety of applications ranging from mass sensing to signal processing. Often their actuation and/or detection involve external subsystems that are much larger than the resonator itself. We have designed a simple microcantilever resonator with integrated sensor and actuator, facilitating the integration of large arrays of resonators. This unique design can be manufactured with a low-cost fabrication process, involving just a single step of lithography. The bilayer cantilever of gold and silicon dioxide is used as piezoresistive sensor as well as thermal bimorph actuator. The ac current used for actuation and the dc current used for piezoresistive detection are separated in the frequency-domain using a bias-tee circuit configuration. The resonant response is measured by detecting the second harmonic of the actuation current using a lock-in amplifier.

Identification of fault location in power distribution system with distributed generation using support vector machines

This paper presents a multi-class support vector machine (SVMs) approach for locating and diagnosing faults in electric power distribution feeders with the penetration of Distributed Generations (DGs). The proposed approach is based on the three phase voltage and current measurements which are available at all the sources i.e. substation and at the connection points of DG. To illustrate the proposed methodology, a practical distribution feeder emanating from 132/11kV-grid substation in India with loads and suitable number of DGs at different locations is considered. To show the effectiveness of the proposed methodology, practical situations in distribution systems (DS) such as all types of faults with a wide range of varying fault locations, source short circuit (SSC) levels and fault impedances are considered for studies. The proposed fault location scheme is capable of accurately identify the fault type, location of faulted feeder section and the fault impedance. The results demonstrate the feasibility of applying the proposed method in practical in smart grid distribution automation (DA) for fault diagnosis.

Remote sensing applications in water resources

With the introduction of the earth observing satellites, remote sensing has become an important tool in analyzing the Earth's surface characteristics, and hence in supplying valuable information necessary for the hydrologic analysis. Due to their capability to capture the spatial variations in the hydro-meteorological variables and frequent temporal resolution sufficient to represent the dynamics of the hydrologic processes, remote sensing techniques have significantly changed the water resources assessment and management methodologies. Remote sensing techniques have been widely used to delineate the surface water bodies, estimate meteorological variables like temperature and precipitation, estimate hydrological state variables like soil moisture and land surface characteristics, and to estimate fluxes such as evapotranspiration. Today, near-real time monitoring of flood, drought events, and irrigation management are possible with the help of high resolution satellite data. This paper gives a brief overview of the potential applications of remote sensing in water resources.

Improved modeling of groundwater recharge in agricultural watersheds using a combination of crop model and remote sensing

For improved water management and efficiency of use in agriculture, studies dealing with coupled crop-surface water-groundwater models are needed. Such integrated models of crop and hydrology can provide accurate quantification of spatio-temporal variations of water balance parameters such as soil moisture store, evapotranspiration and recharge in a catchment. Performance of a coupled crop-hydrology model would depend on the availability of a calibrated crop model for various irrigated/rainfed crops and also on an accurate knowledge of soil hydraulic parameters in the catchment at relevant scale. Moreover, such a coupled model should be designed so as to enable the use/assimilation of recent satellite remote sensing products (optical and microwave) in order to model the processes at catchment scales. In this study we present a framework to couple a crop model with a groundwater model for applications to irrigated groundwater agricultural systems. We discuss the calibration of the STICS crop model and present a methodology to estimate the soil hydraulic parameters by inversion of crop model using both ground and satellite based data. Using this methodology we demonstrate the feasibility of estimation of potential recharge due to spatially varying soil/crop matrix.