Deblurring in a noncoherent optical processing system: pupil function synthesis and experimental implementation

The bipolar point spread function (PSF) corresponding to the Wiener filter tor correcting linear-motion-blurred pictures is implemented in a noncoherent optical processor. The following two approaches are taken for this implementation: (1) the PSF is modulated and biased so that the resulting function is non-negative and (2) the PSF is split into its positive and sign-reversed negative parts, and these two parts are dealt with separately. The phase problem associated with arriving at the pupil function from these modified PSFs is solved using both analytical and combined analytical-iterative techniques available in the literature. The designed pupil functions are experimentally implemented, and deblurring in a noncoherent processor is demonstrated. The postprocessing required (i.e., demodulation in the first approach to modulating the PSF and intensity subtraction in the second approach) are carried out either in a coherent processor or with the help of a PC-based vision system. The deblurred outputs are presented.

Mining Land Cover Information Using Multilayer Perceptron and Decision Tree from MODIS Data

Land cover (LC) changes play a major role in global as well as at regional scale patterns of the climate and biogeochemistry of the Earth system. LC information presents critical insights in understanding of Earth surface phenomena, particularly useful when obtained synoptically from remote sensing data. However, for developing countries and those with large geographical extent, regular LC mapping is prohibitive with data from commercial sensors (high cost factor) of limited spatial coverage (low temporal resolution and band swath). In this context, free MODIS data with good spectro-temporal resolution meet the purpose. LC mapping from these data has continuously evolved with advances in classification algorithms. This paper presents a comparative study of two robust data mining techniques, the multilayer perceptron (MLP) and decision tree (DT) on different products of MODIS data corresponding to Kolar district, Karnataka, India. The MODIS classified images when compared at three different spatial scales (at district level, taluk level and pixel level) shows that MLP based classification on minimum noise fraction components on MODIS 36 bands provide the most accurate LC mapping with 86% accuracy, while DT on MODIS 36 bands principal components leads to less accurate classification (69%).

A QFT-based robust SVC controller for improving the dynamic stability of power systems

A new design technique for an SVC-based power system damping controller has been proposed. The controller attempts to place all plant poles within a specified region on the s-plane to guarantee the desired closed loop performance. The use of Horowitz's quantitative feedback theory (QFT) permits the design of a 'fixed gain controller' that maintains its performance in spite of large variations in the plant parameters during its normal course of operation. The required controller parameters are arrived at by solving an optimization problem that incorporates the control specifications. The performance of this robust controller has been evaluated on a single machine infinite bus system equipped with a mid point SVC, and the results are shown to be consistent with the expected performance of the stabilizer. (C) 1998 Elsevier Science S.A. All rights reserved.

Polymer microfabrication by scanning based microstereolithography: Optical design and material functionality

Several research groups have attempted to optimize photopolymerization parameters to increase the throughput of scanning based microstereolithography (MSL) systems through modified beam scanning techniques. Efforts in reducing the curing line width have been implemented through high numerical aperture (NA) optical setups. However, the intensity contour symmetry and the depth of field of focus have led to grossly non-vertical and non-uniform curing profiles. This work tries to review the photopolymerization process in a scanning based MSL system from the aspect of material functionality and optical design. The focus has been to exploit the rich potential of photoreactor scanning system in achieving desired fabrication modalities (minimum curing width, uniform depth profile, and vertical curing profile) even with a reduced NA optical setup and a single movable stage. The present study tries to manipulate to its advantage the effect of optimized lower c] (photoinitiator (PI) concentration) in reducing the minimum curing width to similar to 10-20 mu m even with a higher spot size (similar to 21.36 mu m) through a judiciously chosen ``monomer-PI'' system. Optimization on grounds of increasing E-max (maximum laser exposure energy at surface) by optimizing the scan rate provides enough time for the monomer or resin to get cured across the entire resist thickness (surface to substrate similar to 10-100 mu m), leading to uniform depth profiles along the entire scan lengths. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4750975]

Mapping the apoptosis inducing domain of an immunomodulatory protein: glycodelin A

Glycodelin A (GdA) is a dimeric glycoprotein synthesized by the human endometrium under progesterone regulation. Based on the high sequence similarity with beta-lactoglobulin, it is placed under the lipocalin superfamily. The protein is one of the local immunomodulators present at the feto-maternal interface which affects both the innate as well as the acquired arms of the immune system, thereby bringing about successful establishment and progression of pregnancy. Our previous studies revealed that the domain responsible for the immunosuppressive activity of glycodelin lies on its protein backbone and the glycans modulate the same. This study attempts to further delineate the apoptosis inducing region of GdA. Our results demonstrate that the stretch of amino acid sequence between Met24 to Leu105 is necessary and sufficient to inhibit proliferation of T cells and induce apoptosis in them. Further, within this region the key residues involved in harboring the activity were shown to be present between Asp52 and Ser65.

Solar driven Adsorption Desalination system

Desalination is one of the most traditional processes to generate potable water. With the rise in demand for potable water and paucity of fresh water resources, this process has gained special importance. Conventional thermal desalination processes involves evaporative methods such as multi-stage flash and solar distils, which are found to be energy intensive, whereas reverse osmosis based systems have high operating and maintenance costs. The present work describes the Adsorption Desalination (AD) system, which is an emerging process of thermal desalination cum refrigeration capable of utilizing low grade heat easily obtainable from even non-concentrating type solar collectors. The system employs a combination of flash evaporation and thermal compression to generate cooling and desalinated water. The current study analyses the system dynamics of a 4-bed single stage silica-gel plus water based AD system. A lumped model is developed using conservation of energy and mass coupled with the kinetics of adsorption/desorption process. The constitutive equations for the system components viz. evaporator, adsorber and condenser, are solved and the performance of the system is evaluated for a single stage AD system at various condenser temperatures and cycle times to determine optimum operating conditions required for desalination and cooling. (C) 2013 P. Dutta. Published by Elsevier Ltd.

Girsanov Transformation-Based Reliability Modeling and Testing of Actively Controlled Structures

The problem of estimation of the time-variant reliability of actively controlled structural dynamical systems under stochastic excitations is considered. Monte Carlo simulations, reinforced with Girsanov transformation-based sampling variance reduction, are used to tackle the problem. In this approach, the external excitations are biased by an additional artificial control force. The conflicting objectives of the two control forces-one designed to reduce structural responses and the other to promote limit-state violations (but to reduce sampling variance)-are noted. The control for variance reduction is fashioned after design-point oscillations based on a first-order reliability method. It is shown that for structures that are amenable to laboratory testing, the reliability can be estimated experimentally with reduced testing times by devising a procedure based on the ideas of the Girsanov transformation. Illustrative examples include studies on a building frame with a magnetorheologic damper-based isolation system subject to nonstationary random earthquake excitations. (C) 2014 American Society of Civil Engineers.

Reduction of Permittivity in Epoxy Nanocomposites at Low Nano-filler Loadings

Experimental studies reveal a reduction in the values of permittivity for epoxy nanocomposites; at low filler loadings as compared to neat epoxy over a wide frequency range. This permittivity reduction is attributed to the interaction dynamics between nanoparticles: and epoxy chains at the interface region and interestingly, this interaction has also been found to influence the glass transition temperatures (T-g) of the examined nanocomposite systems. Accordingly, a dual nanolayer interface model for an epoxy based nanocomposite system is analyzed to explain the obtained permittivity characteristics.

A Current Source Inverter Fed Induction Motor Drive with Power Factor Angle Control Using Microprocessor

This paper describes a method of adjusting the stator power factor angle for the control of an induction motor fed from a current source inverter (CSI) based on the concept of space vectors (or park vectors). It is shown that under steady state, if the torque angle is kept constant over the entire operating range, it has the advantage of keeping the slip frequency constant. This can be utilized to dispose of the speed feedback and simplify the control scheme for the drive, such that the stator voltage integral zero crossings alone can be used as a feedback for deciding the triggering instants of the CSI thyristors under stable operation of the system. A closed-loop control strategy is developed for the drive based on this principle, using a microprocessor-based control system and is implemented on a laboratory prototype CSI fed induction motor drive.

Testing and Modeling of MR Damper and Its Application to SDOF Systems Using Integral Backstepping Technique

Magnetorheological dampers are intrinsically nonlinear devices, which make the modeling and design of a suitable control algorithm an interesting and challenging task. To evaluate the potential of magnetorheological (MR) dampers in control applications and to take full advantages of its unique features, a mathematical model to accurately reproduce its dynamic behavior has to be developed and then a proper control strategy has to be taken that is implementable and can fully utilize their capabilities as a semi-active control device. The present paper focuses on both the aspects. First, the paper reports the testing of a magnetorheological damper with an universal testing machine, for a set of frequency, amplitude, and current. A modified Bouc-Wen model considering the amplitude and input current dependence of the damper parameters has been proposed. It has been shown that the damper response can be satisfactorily predicted with this model. Second, a backstepping based nonlinear current monitoring of magnetorheological dampers for semi-active control of structures under earthquakes has been developed. It provides a stable nonlinear magnetorheological damper current monitoring directly based on system feedback such that current change in magnetorheological damper is gradual. Unlike other MR damper control techniques available in literature, the main advantage of the proposed technique lies in its current input prediction directly based on system feedback and smooth update of input current. Furthermore, while developing the proposed semi-active algorithm, the dynamics of the supplied and commanded current to the damper has been considered. The efficiency of the proposed technique has been shown taking a base isolated three story building under a set of seismic excitation. Comparison with widely used clipped-optimal strategy has also been shown.

OFDM-MAC algorithms and their impact on TCP performance in next generation mobile networks

Next generation wireless systems employ Orthogonal frequency division multiplexing (OFDM) physical layer owing to the high data rate transmissions that are possible without increase in bandwidth. While TCP performance has been extensively studied for interaction with link layer ARQ, little attention has been given to the interaction of TCP with MAC layer. In this work, we explore cross-layer interactions in an OFDM based wireless system, specifically focusing on channel-aware resource allocation strategies at the MAC layer and its impact on TCP congestion control. Both efficiency and fairness oriented MAC resource allocation strategies were designed for evaluating the performance of TCP. The former schemes try to exploit the channel diversity to maximize the system throughput, while the latter schemes try to provide a fair resource allocation over sufficiently long time duration. From a TCP goodput standpoint, we show that the class of MAC algorithms that incorporate a fairness metric and consider the backlog outperform the channel diversity exploiting schemes.

Simultaneous measurement of aerodynamic and heat transfer data for large angle blunt cones in hypersonic shock tunnel

Aerodynamic forces and fore-body convective surface heat transfer rates over a 60 degrees apex-angle blunt cone have been simultaneously measured at a nominal Mach number of 5.75 in the hypersonic shock tunnel HST2. An aluminum model incorporating a three-component accelerometer-based balance system for measuring the aerodynamic forces and an array of platinum thin-film gauges deposited on thermally insulating backing material flush mounted on the model surface is used for convective surface heat transfer measurement in the investigations. The measured value of the drag coefficient varies by about +/-6% from the theoretically estimated value based on the modified Newtonian theory, while the axi-symmetric Navier-Stokes computations overpredict the drag coefficient by about 9%. The normalized values of measured heat transfer rates at 0 degrees angle of attack are about 11% higher than the theoretically estimated values. The aerodynamic and the heat transfer data presented here are very valuable for the validation of CFD codes used for the numerical computation of How fields around hypersonic vehicles.

Artificial neural networks and multicriterion analysis for sustainable irrigation planning

The objective of the present paper is to select the best compromise irrigation planning strategy for the case study of Jayakwadi irrigation project, Maharashtra, India. Four-phase methodology is employed. In phase 1, separate linear programming (LP) models are formulated for the three objectives, namely. net economic benefits, agricultural production and labour employment. In phase 2, nondominated (compromise) irrigation planning strategies are generated using the constraint method of multiobjective optimisation. In phase 3, Kohonen neural networks (KNN) based classification algorithm is employed to sort nondominated irrigation planning strategies into smaller groups. In phase 4, multicriterion analysis (MCA) technique, namely, Compromise Programming is applied to rank strategies obtained from phase 3. It is concluded that the above integrated methodology is effective for modeling multiobjective irrigation planning problems and the present approach can be extended to situations where number of irrigation planning strategies are even large in number. (c) 2004 Elsevier Ltd. All rights reserved.

Support vector machine for evaluating seismic-liquefaction potential using shear wave velocity

The use of the shear wave velocity data as a field index for evaluating the liquefaction potential of sands is receiving increased attention because both shear wave velocity and liquefaction resistance are similarly influenced by many of the same factors such as void ratio, state of stress, stress history and geologic age. In this paper, the potential of support vector machine (SVM) based classification approach has been used to assess the liquefaction potential from actual shear wave velocity data. In this approach, an approximate implementation of a structural risk minimization (SRM) induction principle is done, which aims at minimizing a bound on the generalization error of a model rather than minimizing only the mean square error over the data set. Here SVM has been used as a classification tool to predict liquefaction potential of a soil based on shear wave velocity. The dataset consists the information of soil characteristics such as effective vertical stress (sigma'(v0)), soil type, shear wave velocity (V-s) and earthquake parameters such as peak horizontal acceleration (a(max)) and earthquake magnitude (M). Out of the available 186 datasets, 130 are considered for training and remaining 56 are used for testing the model. The study indicated that SVM can successfully model the complex relationship between seismic parameters, soil parameters and the liquefaction potential. In the model based on soil characteristics, the input parameters used are sigma'(v0), soil type. V-s, a(max) and M. In the other model based on shear wave velocity alone uses V-s, a(max) and M as input parameters. In this paper, it has been demonstrated that Vs alone can be used to predict the liquefaction potential of a soil using a support vector machine model. (C) 2010 Elsevier B.V. All rights reserved.

Molecular systematics and conservation of the langurs and leaf monkeys of South Asia

Numerous morphology-based classification schemes have been proposed for langurs and leaf monkeys of South Asia but there is very little agreement between them. An incorrect classification scheme when used as a basis for biogeographic studies can support erroneous hypotheses. Further, lack of taxonomic resolution will also confound conservation efforts, given that conservation biologists use traditional morphology-based-classification schemes to prioritize species for conservation. Here, I have revisited recent molecular phylogenetic studies done on langurs and leaf monkeys of South Asia. Results from these studies are in turn used to derive a rational and scientific basis for prioritizing species for conservation. Molecular data support the classification of langurs of the Indian subcontinent-Hanuman, Nilgiri and purple-faced langurs-in the genus Semnopithecus, whereas Phayre's leaf monkey along with other Southeast Asian leaf monkeys form another distinct clade (Trachypithecus). The phylogenetic position of capped and golden langurs remains unresolved. Molecular data suggest that they are closely related to each other but this group might have evolved through past hybridization between Semnopithecus and Trachypithecus. Additionally, genetic data also support the splitting of the so-called Hanuman langurs into at least three species. The scores for taxonomic uniqueness of langurs and leaf monkeys of South Asia were revised using this molecular phylogeny-based classification. According to the revised scores, Phayres leaf monkey and golden langur are priority species for conservation followed by capped and Nilgiri langurs.