Space vector based modulation scheme for reducing capacitor RMS current in three-level diode-clamped inverter

The DC capacitor is an important component in a voltage source inverter.The RMS current flowing through the capacitor determines the capacitor size and losses. The losses, in turn, influence the capacitor life. This paper proposes a space vector based modulation strategy for reducing the capacitor RMS current in a three-level diode-clamped inverter. An analytical closed-form expression is derived for the DC capacitor RMS current with the proposed PWM strategy. The analytical expression is validated through simulations and also experimentally. Theoretical and experimental results are presented, comparing the proposed strategy with conventional space vector PWM (CSVPWM). It is shown that the proposed strategy reduces the capacitor RMS current significantly at high modulation indices and high power factors. (C) 2014 Elsevier B.V. All rights reserved.

OFDM-Aided Differential Space-Time Shift Keying Using Iterative Soft Multiple-Symbol Differential Sphere Decoding

Soft-decision multiple-symbol differential sphere decoding (MSDSD) is proposed for orthogonal frequency-division multiplexing (OFDM)-aided differential space-time shift keying (DSTSK)-aided transmission over frequency-selective channels. Specifically, the DSTSK signaling blocks are generated by the channel-encoded source information and the space-time (ST) blocks are appropriately mapped to a number of OFDM subcarriers. After OFDM demodulation, the DSTSK signal is noncoherently detected by our soft-decision MSDSD detector. A novel soft-decision MSDSD detector is designed, and the associated decision rule is derived for the DSTSK scheme. Our simulation results demonstrate that an SNR reduction of 2 dB is achieved by the proposed scheme using an MSDSD window size of N-w = 4 over the conventional soft-decision-aided differential detection benchmarker, while communicating over dispersive channels and dispensing with channel estimation (CE).

CLAP: A web-server for automatic classification of proteins with special reference to multi-domain proteins

Background: The function of a protein can be deciphered with higher accuracy from its structure than from its amino acid sequence. Due to the huge gap in the available protein sequence and structural space, tools that can generate functionally homogeneous clusters using only the sequence information, hold great importance. For this, traditional alignment-based tools work well in most cases and clustering is performed on the basis of sequence similarity. But, in the case of multi-domain proteins, the alignment quality might be poor due to varied lengths of the proteins, domain shuffling or circular permutations. Multi-domain proteins are ubiquitous in nature, hence alignment-free tools, which overcome the shortcomings of alignment-based protein comparison methods, are required. Further, existing tools classify proteins using only domain-level information and hence miss out on the information encoded in the tethered regions or accessory domains. Our method, on the other hand, takes into account the full-length sequence of a protein, consolidating the complete sequence information to understand a given protein better. Results: Our web-server, CLAP (Classification of Proteins), is one such alignment-free software for automatic classification of protein sequences. It utilizes a pattern-matching algorithm that assigns local matching scores (LMS) to residues that are a part of the matched patterns between two sequences being compared. CLAP works on full-length sequences and does not require prior domain definitions. Pilot studies undertaken previously on protein kinases and immunoglobulins have shown that CLAP yields clusters, which have high functional and domain architectural similarity. Moreover, parsing at a statistically determined cut-off resulted in clusters that corroborated with the sub-family level classification of that particular domain family. Conclusions: CLAP is a useful protein-clustering tool, independent of domain assignment, domain order, sequence length and domain diversity. Our method can be used for any set of protein sequences, yielding functionally relevant clusters with high domain architectural homogeneity. The CLAP web server is freely available for academic use at http://nslab.mbu.iisc.ernet.in/clap/.

Electronically nonadiabatic decomposition mechanisms of clusters of zinc and dimethylnitramine

Electronically nonadiabatic decomposition mechanisms of dimethylnitramine (DMNA) in presence of zinc metal clusters are explored. Complete active space self-consistent field (CASSCF) calculation is employed for DMNA-Zn and ONIOM (Our own N-layered integrated molecular orbital and molecular mechanics) methodology is coupled with CASSCF methodology for DMNA-Zn-10 cluster. Present computational results show that DMNA-Zn clusters undergo electronically nonadiabatic reactions, rendering nitro-nitrite isomerization followed by NO elimination. The overall reactions are also found to be highly exothermic in nature. This is the first report on electronically nonadiabatic decomposition pathways of DMNA-Zn-n neutral clusters. (C) 2014 Elsevier B.V. All rights reserved.

A Grassmann path from AdS(3) to flat space

We show that interpreting the inverse AdS(3) radius 1/l as a Grassmann variable results in a formal map from gravity in AdS(3) to gravity in flat space. The underlying reason for this is the fact that ISO(2, 1) is the Inonu-Wigner contraction of SO(2, 2). We show how this works for the Chern-Simons actions, demonstrate how the general (Banados) solution in AdS(3) maps to the general flat space solution, and how the Killing vectors, charges and the Virasoro algebra in the Brown-Henneaux case map to the corresponding quantities in the BMS3 case. Our results straightforwardly generalize to the higher spin case: the recently constructed flat space higher spin theories emerge automatically in this approach from their AdS counterparts. We conclude with a discussion of singularity resolution in the BMS gauge as an application.

Monitoring urbanization and its implications in a mega city from space: Spatiotemporal patterns and its indicators

Rapid and invasive urbanization has been associated with depletion of natural resources (vegetation and water resources), which in turn deteriorates the landscape structure and conditions in the local environment. Rapid increase in population due to the migration from rural areas is one of the critical issues of the urban growth. Urbanisation in India is drastically changing the land cover and often resulting in the sprawl. The sprawl regions often lack basic amenities such as treated water supply, sanitation, etc. This necessitates regular monitoring and understanding of the rate of urban development in order to ensure the sustenance of natural resources. Urban sprawl is the extent of urbanization which leads to the development of urban forms with the destruction of ecology and natural landforms. The rate of change of land use and extent of urban sprawl can be efficiently visualized and modelled with the help of geo-informatics. The knowledge of urban area, especially the growth magnitude, shape geometry, and spatial pattern is essential to understand the growth and characteristics of urbanization process. Urban pattern, shape and growth can be quantified using spatial metrics. This communication quantifies the urbanisation and associated growth pattern in Delhi. Spatial data of four decades were analysed to understand land over and land use dynamics. Further the region was divided into 4 zones and into circles of 1 km incrementing radius to understand and quantify the local spatial changes. Results of the landscape metrics indicate that the urban center was highly aggregated and the outskirts and the buffer regions were in the verge of aggregating urban patches. Shannon's Entropy index clearly depicted the outgrowth of sprawl areas in different zones of Delhi. (C) 2014 Elsevier Ltd. All rights reserved.

Performance Analysis of Space-Shift Keying in Decode-and-Forward Multihop MIMO Networks

In this paper, space-shift keying (SSK) is considered for multihop multiple-input-multiple-output (MIMO) networks. In SSK, only one among n(s) = 2(m) available transmit antennas, chosen on the basis of m information bits, is activated during transmission. We consider two different systems of multihop co-operation, where each node has multiple antennas and employs SSK. In system I, a multihop diversity relaying scheme is considered. In system II, a multihop multibranch relaying scheme is considered. In both systems, we adopt decode-and-forward (DF) relaying, where each relay forwards the signal only when it correctly decodes. We analyze the end-to-end bit error rate (BER) and diversity order of both the systems with SSK. For binary SSK (n(s) = 2), our analytical BER expression is exact, and our numerical results show that the BERs evaluated through the analytical expression overlap with those obtained through Monte Carlo simulations. For nonbinary SSK (n(s) > 2), we derive an approximate BER expression, where the analytically evaluated BER results closely follow the simulated BER results. We show the comparison of the BERs of SSK and conventional phase-shift keying (PSK) and also show the instances where SSK outperforms PSK. We also present the diversity analyses for SSK in systems I and II, which predict the achievable diversity orders as a function of system parameters.

Space-Vector-Based Hybrid PWM Technique to Reduce Peak-to-Peak Torque Ripple in Induction Motor Drives

Special switching sequences involving division of active state time are used in space-vector-based generation of pulse width modulation (PWM) waveforms. This paper proposes a hybrid PWM technique which is a combination of the conventional and special switching sequences. The proposed hybrid PWM technique reduces the peak-to-peak torque ripple at high speeds of an induction motor drive. Supporting simulation and experimental results are presented from a closed-loop controlled motor drive.

Space-Time Coded Spatial Modulated Physical Layer Network Coding for Two-Way Relaying

Using the spatial modulation approach, where only one transmit antenna is active at a time, we propose two transmission schemes for two-way relay channel using physical layer network coding with space time coding using coordinate interleaved orthogonal designs (CIODs). It is shown that using two uncorrelated transmit antennas at the nodes, but using only one RF transmit chain and space-time coding across these antennas can give a better performance without using any extra resources and without increasing the hardware implementation cost and complexity. In the first transmission scheme, two antennas are used only at the relay, adaptive network coding (ANC) is employed at the relay and the relay transmits a CIOD space time block code (STBC). This gives a better performance compared to an existing ANC scheme for two-way relay channel which uses one antenna each at all the three nodes. It is shown that for this scheme at high SNR the average end-to-end symbol error probability (SEP) is upper bounded by twice the SEP of a point-to-point fading channel. In the second transmission scheme, two transmit antennas are used at all the three nodes, CIOD STBCs are transmitted in multiple access and broadcast phases. This scheme provides a diversity order of two for the average end-to-end SEP with an increased decoding complexity of O(M-3) for an arbitrary signal set and O(M-2 root M) for square QAM signal set. Simulation results show that the proposed schemes performs better than the existing ANC schemes under perfect and imperfect channel state information.

Belief propagation for minimum weight many-to-one matchings in the random complete graph

In a complete bipartite graph with vertex sets of cardinalities n and n', assign random weights from exponential distribution with mean 1, independently to each edge. We show that, as n -> infinity, with n' = n/alpha] for any fixed alpha > 1, the minimum weight of many-to-one matchings converges to a constant (depending on alpha). Many-to-one matching arises as an optimization step in an algorithm for genome sequencing and as a measure of distance between finite sets. We prove that a belief propagation (BP) algorithm converges asymptotically to the optimal solution. We use the objective method of Aldous to prove our results. We build on previous works on minimum weight matching and minimum weight edge cover problems to extend the objective method and to further the applicability of belief propagation to random combinatorial optimization problems.

Sparse coding based VLAD for efficient image retrieval

Representing images and videos in the form of compact codes has emerged as an important research interest in the vision community, in the context of web scale image/video search. Recently proposed Vector of Locally Aggregated Descriptors (VLAD), has been shown to outperform the existing retrieval techniques, while giving a desired compact representation. VLAD aggregates the local features of an image in the feature space. In this paper, we propose to represent the local features extracted from an image, as sparse codes over an over-complete dictionary, which is obtained by K-SVD based dictionary training algorithm. The proposed VLAD aggregates the residuals in the space of these sparse codes, to obtain a compact representation for the image. Experiments are performed over the `Holidays' database using SIFT features. The performance of the proposed method is compared with the original VLAD. The 4% increment in the mean average precision (mAP) indicates the better retrieval performance of the proposed sparse coding based VLAD.

Excited electronic state decomposition mechanisms of clusters of dimethylnitramine and aluminum

In this report, electronically non-adiabatic decomposition pathways of clusters of dimethylnitramine and aluminum (DMNA-Al and DMNA-Al-2) are discussed in comparison to isolated dimethylnitramine (DMNA). Electronically excited state processes of DMNA-Al and DMNA-Al-2 are explored using the complete active space self-consistent field (CASSCF) and the restricted active space self-consistent field (RASSCF) theories, respectively. Similar to the nitro-nitrite isomerization reaction pathway of DMNA, DMNA-Al-n clusters also exhibit isomerization pathway. However, it involves several other steps, such as, first Al-O bond dissociation, then N-N bond dissociation followed by isomerization and finally NO elimination. Furthermore, DMNA-Al-n clusters exhibit overall exothermic decomposition reaction pathway and isolated DMNA shows overall endothermic reaction channel.

Bayesian parameter identification in dynamic state space models using modified measurement equations

When Markov chain Monte Carlo (MCMC) samplers are used in problems of system parameter identification, one would face computational difficulties in dealing with large amount of measurement data and (or) low levels of measurement noise. Such exigencies are likely to occur in problems of parameter identification in dynamical systems when amount of vibratory measurement data and number of parameters to be identified could be large. In such cases, the posterior probability density function of the system parameters tends to have regions of narrow supports and a finite length MCMC chain is unlikely to cover pertinent regions. The present study proposes strategies based on modification of measurement equations and subsequent corrections, to alleviate this difficulty. This involves artificial enhancement of measurement noise, assimilation of transformed packets of measurements, and a global iteration strategy to improve the choice of prior models. Illustrative examples cover laboratory studies on a time variant dynamical system and a bending-torsion coupled, geometrically non-linear building frame under earthquake support motions. (C) 2015 Elsevier Ltd. All rights reserved.

Investigations on Optimal Pulse-Width Modulation to Minimize Total Harmonic Distortion in the Line Current

PWM waveforms with positive voltage transition at the positive zero crossing of the fundamental voltage (type-A) are generally considered for PWM waveform with even number of switching angles per quarter whereas, waveforms with negative voltage transition at the positive zero crossing (type-B) are considered for odd number of switching angles per quarter. Optimal PWM, for minimization of total harmonic distortion of line to line (VWTHD), is generally solved with the aforementioned criteria. This paper establishes that a combination of both types of waveforms gives better performance than any individual type in terms of minimum VWTHD for complete range of modulation index (M). Optimal PWM for minimum VWTHD is solved for PWM waveforms with pulse numbers (P) of 5 and 7. Both type-A and type-B waveforms are found to be better in different ranges of M. The theoretical findings are confirmed through simulation and experimental results on a 3.7 kW squirrel cage induction motor in an open-loop V/f drive. Further, the optimal PWM is analysed from a space vector point of view.