MEMS based pressure sensor with triple modular redundancy

In this paper, the design and development of micro electro mechanical systems (MEMS) based pressure sensor with triple modular redundancy (TMR) for space applications has been presented. In order to minimize the mass of the system and also to avoid the uncertainty in the pressure measurement of the three independent hardware, an integrated approach with TMR is adopted. Sequential steps of TMR logic followed and the test results obtained are included.

Three-Dimensional Site Characterization Model Using Artificial Neural Networks

This research is designed to develop a new technique for site characterization in a three-dimensional domain. Site characterization is a fundamental task in geotechnical engineering practice, as well as a very challenging process, with the ultimate goal of estimating soil properties based on limited tests at any half-space subsurface point in a site.In this research, the sandy site at the Texas A&M University's National Geotechnical Experimentation Site is selected as an example to develop the new technique for site characterization, which is based on Artificial Neural Networks (ANN) technology. In this study, a sequential approach is used to demonstrate the applicability of ANN to site characterization. To verify its robustness, the proposed new technique is compared with other commonly used approaches for site characterization. In addition, an artificial site is created, wherein soil property values at any half-space point are assumed, and thus the predicted values can compare directly with their corresponding actual values, as a means of validation. Since the three-dimensional model has the capability of estimating the soil property at any location in a site, it could have many potential applications, especially in such case, wherein the soil properties within a zone are of interest rather than at a single point. Examples of soil properties of zonal interest include soil type classification and liquefaction potential evaluation. In this regard, the present study also addresses this type of applications based on a site located in Taiwan, which experienced liquefaction during the 1999 Chi-Chi, Taiwan, Earthquake.

Efficient space-time codes from cyclic division algebras

An overview of space-time code construction based on cyclic division algebras (CDA) is presented. Applications of such space-time codes to the construction of codes optimal under the diversity-multiplexing gain (D-MG) tradeoff, to the construction of the so-called perfect space-time codes, to the construction of optimal space-time codes for the ARQ channel as well as to the construction of codes optimal for the cooperative relay network channel are discussed. We also present a construction of optimal codes based on CDA for a class of orthogonal amplify and forward (OAF) protocols for the cooperative relay network

Substrate nitridation induced modulations in transport properties of wurtzite GaN/p-Si (100) heterojunctions grown by molecular beam epitaxy

Phase pure wurtzite GaN films were grown on Si (100) substrates by introducing a silicon nitride layer followed by low temperature GaN growth as buffer layers. GaN films grown directly on Si (100) were found to be phase mixtured, containing both cubic (beta) and hexagonal (alpha) modifications. The x-ray diffraction (XRD), scanning electron microscopy (SEM), photoluminescence (PL) spectroscopy studies reveal that the significant enhancement in the structural as well as in the optical properties of GaN films grown with silicon nitride buffer layer grown at 800 degrees C when compared to the samples grown in the absence of silicon nitride buffer layer and with silicon nitride buffer layer grown at 600 degrees C. Core-level photoelectron spectroscopy of Si(x)N(y) layers reveals the sources for superior qualities of GaN epilayers grown with the high temperature substrate nitridation process. The discussion has been carried out on the typical inverted rectification behavior exhibited by n-GaN/p-Si heterojunctions. Considerable modulation in the transport mechanism was observed with the nitridation conditions. The heterojunction fabricated with the sample of substrate nitridation at high temperature exhibited superior rectifying nature with reduced trap concentrations. Lowest ideality factors (similar to 1.5) were observed in the heterojunctions grown with high temperature substrate nitridation which is attributed to the recombination tunneling at the space charge region transport mechanism at lower voltages and at higher voltages space charge limited current conduction is the dominating transport mechanism. Whereas, thermally generated carrier tunneling and recombination tunneling are the dominating transport mechanisms in the heterojunctions grown without substrate nitridation and low temperature substrate nitridation, respectively. (C) 2011 American Institute of Physics. [doi:10.1063/1.3658867]

A general construction of space-time trellis codes for PSK signal sets

The diversity order and coding gain are crucial for the performance of a multiple antenna communication system. It is known that space-time trellis codes (STTC) can be used to achieve these objectives. In particular, we can use STTCs to obtain large coding gains. Many attempts have been made to construct STTCs which achieve full-diversity and good coding gains, though a general method of construction does not exist. Delay diversity code (rate-1) is known to achieve full-diversity, for any number of transmit antennas and any signal set, but does not give a good coding gain. A product distance code based delay diversity scheme (Tarokh, V. et al., IEEE Trans. Inform. Theory, vol.44, p.744-65, 1998) enables one to improve the coding gain and construct STTCs for any given number of states using coding in conjunction with delay diversity; it was stated as an open problem. We achieve such a construction. We assume a shift register based model to construct an STTC for any state complexity. We derive a sufficient condition for this STTC to achieve full-diversity, based on the delay diversity scheme. This condition provides a framework to do coding in conjunction with delay diversity for any signal constellation. Using this condition, we provide a formal rate-1 STTC construction scheme for PSK signal sets, for any number of transmit antennas and any given number of states, which achieves full-diversity and gives a good coding gain.

Fast Direct Torque Control of an Open-End Induction Motor Drive Using 12-Sided Polygonal Voltage Space Vectors

A torque control scheme, based on a direct torque control (DTC) algorithm using a 12-sided polygonal voltage space vector, is proposed for a variable speed control of an open-end induction motor drive. The conventional DTC scheme uses a stator flux vector for the sector identification and then the switching vector to control stator flux and torque. However, the proposed DTC scheme selects switching vectors based on the sector information of the estimated fundamental stator voltage vector and its relative position with respect to the stator flux vector. The fundamental stator voltage estimation is based on the steady-state model of IM and the synchronous frequency of operation is derived from the computed stator flux using a low-pass filter technique. The proposed DTC scheme utilizes the exact positions of the fundamental stator voltage vector and stator flux vector to select the optimal switching vector for fast control of torque with small variation of stator flux within the hysteresis band. The present DTC scheme allows full load torque control with fast transient response to very low speeds of operation, with reduced switching frequency variation. Extensive experimental results are presented to show the fast torque control for speed of operation from zero to rated.

Algebraic Approaches to Space-Time Code Construction for Multiple-Antenna Communication

A major challenge in wireless communications is overcoming the deleterious effects of fading, a phenomenon largely responsible for the seemingly inevitable dropped call. Multiple-antennas communication systems, commonly referred to as MIMO systems, employ multiple antennas at both transmitter and receiver, thereby creating a multitude of signalling pathways between transmitter and receiver. These multiple pathways give the signal a diversity advantage with which to combat fading. Apart from helping overcome the effects of fading, MIMO systems can also be shown to provide a manyfold increase in the amount of information that can be transmitted from transmitter to receiver. Not surprisingly,MIMO has played, and continues to play, a key role in the advancement of wireless communication.Space-time codes are a reference to a signalling format in which information about the message is dispersed across both the spatial (or antenna) and time dimension. Algebraic techniques drawing from algebraic structures such as rings, fields and algebras, have been extensively employed in the construction of optimal space-time codes that enable the potential of MIMO communication to be realized, some of which have found their way into the IEEE wireless communication standards. In this tutorial article, reflecting the authors’interests in this area, we survey some of these techniques.

Interaction Signatures Stabilizing the NAD(P)-Binding Rossmann Fold: A Structure Network Approach

The fidelity of the folding pathways being encoded in the amino acid sequence is met with challenge in instances where proteins with no sequence homology, performing different functions and no apparent evolutionary linkage, adopt a similar fold. The problem stated otherwise is that a limited fold space is available to a repertoire of diverse sequences. The key question is what factors lead to the formation of a fold from diverse sequences. Here, with the NAD(P)-binding Rossmann fold domains as a case study and using the concepts of network theory, we have unveiled the consensus structural features that drive the formation of this fold. We have proposed a graph theoretic formalism to capture the structural details in terms of the conserved atomic interactions in global milieu, and hence extract the essential topological features from diverse sequences. A unified mathematical representation of the different structures together with a judicious concoction of several network parameters enabled us to probe into the structural features driving the adoption of the NAD(P)-binding Rossmann fold. The atomic interactions at key positions seem to be better conserved in proteins, as compared to the residues participating in these interactions. We propose a ``spatial motif'' and several ``fold specific hot spots'' that form the signature structural blueprints of the NAD(P)-binding Rossmann fold domain. Excellent agreement of our data with previous experimental and theoretical studies validates the robustness and validity of the approach. Additionally, comparison of our results with statistical coupling analysis (SCA) provides further support. The methodology proposed here is general and can be applied to similar problems of interest.

A sequential dual method for structural SVMs

In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to compu- tational biology or computer vision and have been tackled using algorithms, referred to as structured output learning algorithms. We consider the problem of structured classifi- cation. In the last few years, large margin classifiers like sup-port vector machines (SVMs) have shown much promise for structured output learning. The related optimization prob -lem is a convex quadratic program (QP) with a large num-ber of constraints, which makes the problem intractable for large data sets. This paper proposes a fast sequential dual method (SDM) for structural SVMs. The method makes re-peated passes over the training set and optimizes the dual variables associated with one example at a time. The use of additional heuristics makes the proposed method more efficient. We present an extensive empirical evaluation of the proposed method on several sequence learning problems.Our experiments on large data sets demonstrate that the proposed method is an order of magnitude faster than state of the art methods like cutting-plane method and stochastic gradient descent method (SGD). Further, SDM reaches steady state generalization performance faster than the SGD method. The proposed SDM is thus a useful alternative for large scale structured output learning.

Proactive control of sequential saccades in the human supplementary eye field

Our ability to regulate behavior based on past experience has thus far been examined using single movements. However, natural behavior typically involves a sequence of movements. Here, we examined the effect of previous trial type on the concurrent planning of sequential saccades using a unique paradigm. The task consisted of two trial types: no-shift trials, which implicitly encouraged the concurrent preparation of the second saccade in a subsequent trial; and target-shift trials, which implicitly discouraged the same in the next trial. Using the intersaccadic interval as an index of concurrent planning, we found evidence for context-based preparation of sequential saccades. We also used functional MRI-guided, single-pulse, transcranial magnetic stimulation on human subjects to test the role of the supplementary eye field (SEF) in the proactive control of sequential eye movements. Results showed that (i) stimulating the SEF in the previous trial disrupted the previous trial type-based preparation of the second saccade in the nonstimulated current trial, (ii) stimulating the SEF in the current trial rectified the disruptive effect caused by stimulation in the previous trial, and (iii) stimulating the SEF facilitated the preparation of second saccades based on previous trial type even when the previous trial was not stimulated. Taken together, we show how the human SEF is causally involved in proactive preparation of sequential saccades.

Scalable sequential alternating proximal methods for sparse structural SVMs and CRFs

Structural Support Vector Machines (SSVMs) and Conditional Random Fields (CRFs) are popular discriminative methods used for classifying structured and complex objects like parse trees, image segments and part-of-speech tags. The datasets involved are very large dimensional, and the models designed using typical training algorithms for SSVMs and CRFs are non-sparse. This non-sparse nature of models results in slow inference. Thus, there is a need to devise new algorithms for sparse SSVM and CRF classifier design. Use of elastic net and L1-regularizer has already been explored for solving primal CRF and SSVM problems, respectively, to design sparse classifiers. In this work, we focus on dual elastic net regularized SSVM and CRF. By exploiting the weakly coupled structure of these convex programming problems, we propose a new sequential alternating proximal (SAP) algorithm to solve these dual problems. This algorithm works by sequentially visiting each training set example and solving a simple subproblem restricted to a small subset of variables associated with that example. Numerical experiments on various benchmark sequence labeling datasets demonstrate that the proposed algorithm scales well. Further, the classifiers designed are sparser than those designed by solving the respective primal problems and demonstrate comparable generalization performance. Thus, the proposed SAP algorithm is a useful alternative for sparse SSVM and CRF classifier design.

Divvying up an incubator: How parasitic and mutualistic fig wasps use space within their nursery microcosm

Differential occupancy of space can lead to species coexistence. The fig-fig wasp pollination system hosts species-specific pollinating and parasitic wasps that develop within galls in a nursery comprising a closed inflorescence, the syconium. This microcosm affords excellent opportunities for investigating spatial partitioning since it harbours a closed community in which all wasp species are dependent on securing safe sites inside the syconium for their developing offspring while differing in life history, egg deposition strategies and oviposition times relative to nursery development. We determined ontogenetic changes in oviposition sites available to the seven-member fig wasp community of Ficus racemosa comprising pollinators, gallers and parasitoids. We used species distribution models (SDMs) for the first time at a microcosm scale to predict patterns of spatial occurrence of nursery occupants. SDMs gave high true-positive and low false-positive site occupancy rates for most occupants indicating species specificity in oviposition sites. The nursery microcosm itself changed with syconium development and sequential egg-laying by different wasp species. The number of sites occupied by offspring of the different wasp species was negatively related to the risk of syconium abortion by the plant host following oviposition. Since unpollinated syconia are usually aborted, parasitic wasps ovipositing into nurseries at the same time as the pollinator targeted many sites, suggesting response to lower risk of syconium abortion owing to reduced risk of pollination failure compared to those species ovipositing before pollination. Wasp life history and oviposition time relative to nursery development contributed to the co-existence of nursery occupants.

On the stability of the L-p-norm of the Riemannian curvature tensor

We consider the Riemannian functional defined on the space of Riemannian metrics with unit volume on a closed smooth manifold M where R(g) and dv (g) denote the corresponding Riemannian curvature tensor and volume form and p a (0, a). First we prove that the Riemannian metrics with non-zero constant sectional curvature are strictly stable for for certain values of p. Then we conclude that they are strict local minimizers for for those values of p. Finally generalizing this result we prove that product of space forms of same type and dimension are strict local minimizer for for certain values of p.

On the Bounds of Certain Maximal Linear Codes in a Projective Space

The set of all subspaces of F-q(n) is denoted by P-q(n). The subspace distance d(S)(X, Y) = dim(X) + dim(Y)-2dim(X boolean AND Y) defined on P-q(n) turns it into a natural coding space for error correction in random network coding. A subset of P-q(n) is called a code and the subspaces that belong to the code are called codewords. Motivated by classical coding theory, a linear coding structure can be imposed on a subset of P-q(n). Braun et al. conjectured that the largest cardinality of a linear code, that contains F-q(n), is 2(n). In this paper, we prove this conjecture and characterize the maximal linear codes that contain F-q(n).