Performance evaluation of neural network algorithms for multisensor data fusion in an airborne track while scan radar

This paper deals with the solution to the problem of multisensor data fusion for a single target scenario as detected by an airborne track-while-scan radar. The details of a neural network implementation, various training algorithms based on standard backpropagation, and the results of training and testing the neural network are presented. The promising capabilities of RPROP algorithm for multisensor data fusion for various parameters are shown in comparison to other adaptive techniques

Performance evaluation of nonthermal plasma reactors for NO oxidation in diesel engine exhaust gas treatment

The discharge plasma-chemical hybrid process for NO/sub x/ removal from the due gas emissions is an extremely effective and economical approach in comparison with the conventional selective catalytic reduction system. In this paper we bring out a relative comparison of several discharge plasma reactors from the point of NO removal efficiency. The reactors were either energized by AC or by repetitive pulses. Ferroelectric pellets were used to study the effect of pellet assisted discharges on gas cleaning. Diesel engine exhaust, at different loads, is used to approximately simulate the due gas composition. Investigations were carried out at room temperature with respect to the variation of reaction products against the discharge power. Main emphasis is laid on the oxidation of NO to NO/sub 2/, without reducing NOx concentration (i.e., minimum reaction byproducts), with least power consumption. The produced NO/sub 2/ will be totally converted to N/sub 2/ and Na/sub 2/SO/sub 4/ using Na/sub 2/SO/sub 3/. The AC packed bed reactor and pelletless pulsed corona reactor showed better performance, with minimum reaction products for a given power, when the NO concentration was low (/spl sim/100 ppm). At high engine loads (NO>300 ppm) there was not much decrease in NO/sub x/ reduction and more or less all the reactors performed equally. The paper discusses these observations in detail.

Fuzzy data envelopment analysis for performance evaluation of an irrigation system

Sixteen irrigation subsystems of the Mahi Bajaj Sagar Project, Rajasthan, India, are evaluated and selection of the most suitable/best is made using data envelopment analysis (DEA) in both deterministic and fuzzy environments. Seven performance-related indicators, namely, land development works (LDW), timely supply of inputs (TSI), conjunctive use of water resources (CUW), participation of farmers (PF), environmental conservation (EC), economic impact (EI) and crop productivity (CPR) are considered. Of the seven, LDW, TSI, CUW, PF and EC are considered inputs, whereas CPR and EI are considered outputs for DEA modelling purposes. Spearman rank correlation coefficient values are also computed for various scenarios. It is concluded that DEA in both deterministic and fuzzy environments is useful for the present problem. However, the outcome of fuzzy DEA may be explored for further analysis due to its simple, effective data and discrimination handling procedure. It is inferred that the present study can be explored for similar situations with suitable modifications.

Performance evaluation of chemistry transport models over India

Using continuous and near-real time measurements of the mass concentrations of black carbon (BC) aerosols near the surface, for a period of 1 year (from January to December 2006) from a network of eight observatories spread over different environments of India, a space-time synthesis is generated. The strong seasonal variations observed, with a winter high and summer low, are attributed to the combined effects of changes in synoptic air mass types, modulated strongly by the atmospheric boundary layer dynamics. Spatial distribution shows much higher BC concentration over the Indo-Gangetic Plain (IGP) than the peninsular Indian stations. These were examined against the simulations using two chemical transport models, GOCART (Goddard Global Ozone Chemistry Aerosol Radiation and Transport) and CHIMERE for the first time over Indian region. Both the model simulations significantly deviated from the measurements at all the stations; more so during the winter and pre-monsoon seasons and over mega cities. However, the CHIMERE model simulations show better agreement compared with the measurements. Notwithstanding this, both the models captured the temporal variations; at seasonal and subseasonal timescales and the natural variabilities (intra-seasonal oscillations) fairly well, especially at the off-equatorial stations. It is hypothesized that an improvement in the atmospheric boundary layer (ABL) parameterization scheme for tropical environment might lead to better results with GOCART.

Hybrid Energy Harvesting Wireless Systems: Performance Evaluation and Benchmarking

Energy harvesting sensor (EHS) nodes provide an attractive and green solution to the problem of limited lifetime of wireless sensor networks (WSNs). Unlike a conventional node that uses a non-rechargeable battery and dies once it runs out of energy, an EHS node can harvest energy from the environment and replenish its rechargeable battery. We consider hybrid WSNs that comprise of both EHS and conventional nodes; these arise when legacy WSNs are upgraded or due to EHS deployment cost issues. We compare conventional and hybrid WSNs on the basis of a new and insightful performance metric called k-outage duration, which captures the inability of the nodes to transmit data either due to lack of sufficient battery energy or wireless fading. The metric overcomes the problem of defining lifetime in networks with EHS nodes, which never die but are occasionally unable to transmit due to lack of sufficient battery energy. It also accounts for the effect of wireless channel fading on the ability of the WSN to transmit data. We develop two novel, tight, and computationally simple bounds for evaluating the k-outage duration. Our results show that increasing the number of EHS nodes has a markedly different effect on the k-outage duration than increasing the number of conventional nodes.

Performance Evaluation of OBS Networks with INI Signaling Technique

In this paper, we evaluate the performance of a burst retransmission method for an optical burst switched network with intermediate-node-initiation (INI) signaling technique. The proposed method tries to reduce the burst contention probability at the intermediate core nodes. We develop an analytical model to get the burst contention probability and burst loss probability for an optical burst switched network with intermediate-node-initiation signaling technique. The proposed method uses the optical burst retransmission method. We simulate the performance of the optical burst retransmission. Simulation results show that at low traffic loads the loss probability is low compared to the conventional burst retransmission in the OBS network. Result also show that the retransmission method for OBS network with intermediate-node-initiation signaling technique significantly reduces the burst loss probability.

A Communication-Theoretic Framework for 2-DMR Channel Modeling: Performance Evaluation of Coding and Signal Processing Methods

We develop a communication theoretic framework for modeling 2-D magnetic recording channels. Using the model, we define the signal-to-noise ratio (SNR) for the channel considering several physical parameters, such as the channel bit density, code rate, bit aspect ratio, and noise parameters. We analyze the problem of optimizing the bit aspect ratio for maximizing SNR. The read channel architecture comprises a novel 2-D joint self-iterating equalizer and detection system with noise prediction capability. We evaluate the system performance based on our channel model through simulations. The coded performance with the 2-D equalizer detector indicates similar to 5.5 dB of SNR gain over uncoded data.

Performance evaluation of typical approximation algorithms for nonconvex l(p)-minimization in diffuse optical tomography

The sparse estimation methods that utilize the l(p)-norm, with p being between 0 and 1, have shown better utility in providing optimal solutions to the inverse problem in diffuse optical tomography. These l(p)-norm-based regularizations make the optimization function nonconvex, and algorithms that implement l(p)-norm minimization utilize approximations to the original l(p)-norm function. In this work, three such typical methods for implementing the l(p)-norm were considered, namely, iteratively reweighted l(1)-minimization (IRL1), iteratively reweighted least squares (IRLS), and the iteratively thresholding method (ITM). These methods were deployed for performing diffuse optical tomographic image reconstruction, and a systematic comparison with the help of three numerical and gelatin phantom cases was executed. The results indicate that these three methods in the implementation of l(p)-minimization yields similar results, with IRL1 fairing marginally in cases considered here in terms of shape recovery and quantitative accuracy of the reconstructed diffuse optical tomographic images. (C) 2014 Optical Society of America

Performance evaluation of AR4 Climate Models in simulating daily precipitation over the Indian region using skill scores

The ability of Coupled General Circulation Models (CGCMs) participating in the Intergovernmental Panel for Climate Change's fourth assessment report (IPCC AR4) for the 20th century climate (20C3M scenario) to simulate the daily precipitation over the Indian region is explored. The skill is evaluated on a 2.5A degrees x 2.5A degrees grid square compared with the Indian Meteorological Department's (IMD) gridded dataset, and every GCM is ranked for each of these grids based on its skill score. Skill scores (SSs) are estimated from the probability density functions (PDFs) obtained from observed IMD datasets and GCM simulations. The methodology takes into account (high) extreme precipitation events simulated by GCMs. The results are analyzed and presented for three categories and six zones. The three categories are the monsoon season (JJASO - June to October), non-monsoon season (JFMAMND - January to May, November, December) and for the entire year (''Annual''). The six precipitation zones are peninsular, west central, northwest, northeast, central northeast India, and the hilly region. Sensitivity analysis was performed for three spatial scales, 2.5A degrees grid square, zones, and all of India, in the three categories. The models were ranked based on the SS. The category JFMAMND had a higher SS than the JJASO category. The northwest zone had higher SSs, whereas the peninsular and hilly regions had lower SS. No single GCM can be identified as the best for all categories and zones. Some models consistently outperformed the model ensemble, and one model had particularly poor performance. Results show that most models underestimated the daily precipitation rates in the 0-1 mm/day range and overestimated it in the 1-15 mm/day range.

Performance Evaluation of Underground Mine Communication and Monitoring Devices: Case Studies

Communication and environmental monitoring play a major role in underground mining both from production and safety point of view. However, underground mining communication as well as monitoring devices encounter several challenges because of the nature of underground features and characteristics. Lack of real time information from underground workings may hamper production and create serious safety risks. Proper communication and monitoring devices are inevitable requirements for better production and improved safety. Communication and environmental monitoring devices are basic element of underground mine infrastructure. This paper describes the performance of communication and monitoring devices being used in underground mines. An attempt has been made to assess the safety risks by these devices which may dictate future research directions.

Performance evaluation of a two-stage silica gel plus water adsorption based cooling-cum-desalination system

The first objective of this paper is to show that a single-stage adsorption based cooling-cum-desalination system cannot be used if air cooled heat rejection is used under tropical conditions. This objective is achieved by operating a silica gel + water adsorption chiller first in a single-stage mode and then in a 2-stage mode with 2 beds/stage in each case. The second objective is to improve upon the simulation results obtained earlier by way of empirically describing the thermal wave phenomena during switching of operation of beds between adsorption and desorption and vice versa. Performance indicators, namely, cooling capacity, coefficient of performance and desalinated water output are extracted for various evaporator pressures and half cycle times. The improved simulation model is found to interpret experimental results more closely than the earlier one. Reasons for decline in performance indicators between theoretical and actual scenarios are appraised. (C) 2015 Elsevier Ltd and IIR. All rights reserved.

Experimental characterisation and performance evaluation of a coaxial current transformer for measurement of insulated gate bipolar transistor switching current

Measurement of device current during switching characterisation of an insulated gate bipolar transistor (IGBT) requires a current sensor with low insertion impedance and high bandwidth. This study presents an experimental procedure for evaluating the performance of a coaxial current transformer (CCT), designed for the above purpose. A prototype CCT, which can be mounted directly on a power terminal of a 1200 V/50 A half-bridge IGBT module, is characterised experimentally. The measured characteristics include insertion impedance, gain and phase of the CCT at different frequencies. The bounds of linearity within which the CCT can operate without saturation are determined theoretically, and are also verified experimentally. The experimental study on linearity of the CCT requires a high-amplitude current source. A proportional-resonant (PR) controller-based current-controlled half-bridge inverter is developed for this purpose. A systematic procedure for selection of PR controller parameters is also reported in this study. This set-up is helpful to determine the limit of linearity and also to measure the frequency response of the CCT at realistic amplitudes of current in the low-frequency range.

Performance evaluation of mobile agent based resource management protocol for MANETs

The nodes with dynamicity, and management without administrator are key features of mobile ad hoc networks (1VIANETs). Increasing resource requirements of nodes running different applications, scarcity of resources, and node mobility in MANETs are the important issues to be considered in allocation of resources. Moreover, management of limited resources for optimal allocation is a crucial task. In our proposed work we discuss a design of resource allocation protocol and its performance evaluation. The proposed protocol uses both static and mobile agents. The protocol does the distribution and parallelization of message propagation (mobile agent with information) in an efficient way to achieve scalability and speed up message delivery to the nodes in the sectors of the zones of a MANET. The protocol functionality has been simulated using Java Agent Development Environment (JADE) Framework for agent generation, migration and communication. A mobile agent migrates from central resource rich node with message and navigate autonomously in the zone of network until the boundary node. With the performance evaluation, it has been concluded that the proposed protocol consumes much less time to allocate the required resources to the nodes under requirement, utilize less network resources and increase the network scalability. (C) 2015 Elsevier B.V. All rights reserved.