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.

Proximinality in Banach spaces

In this paper, we study approximatively τ-compact and τ-strongly Chebyshev sets, where τ is the norm or the weak topology. We show that the metric projection onto τ-strongly Chebyshev sets are norm-τ continuous. We characterize approximatively τ-compact and τ-strongly Chebyshev hyperplanes and use them to characterize factor reflexive proximinal subspaces in τ-almost locally uniformly rotund spaces. We also prove some stability results on approximatively τ-compact and τ-strongly Chebyshev subspaces.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Graphene-like two-dimensional ionic boron with double dirac cones at ambient condition

Recently, partially ionic boron (γ-B28) has been predicted and observed in pure boron, in bulk phase and controlled by pressure [Nature, 457 (2009) 863]. By using ab initio evolutionary structure search, we report the prediction of ionic boron at a reduced dimension and ambient pressure, namely, the two-dimensional (2D) ionic boron. This 2D boron structure consists of graphene-like plane and B2 atom pairs, with the P6/mmm space group and 6 atoms in the unit cell, and has lower energy than the previously reported α-sheet structure and its analogues. Its dynamical and thermal stability are confirmed by the phonon-spectrum and ab initio molecular dynamics simulation. In addition, this phase exhibits double Dirac cones with massless Dirac fermions due to the significant charge transfer between the graphene-like plane and B2 pair that enhances the energetic stability of the P6/mmm boron. A Fermi velocity (vf) as high as 2.3 x 106 m/s, which is even higher than that of graphene (0.82 x 106 m/s), is predicted for the P6/mmm boron. The present work is the first report of the 2D ionic boron at atmospheric pressure. The unique electronic structure renders the 2D ionic boron a promising 2D material for applications in nanoelectronics.

Analysis of Energy Quantization Effects on Single-Electron Transistor Circuits

In this paper, the effects of energy quantization on different single-electron transistor (SET) circuits (logic inverter, current-biased circuits, and hybrid MOS-SET circuits) are analyzed through analytical modeling and Monte Carlo simulations. It is shown that energy quantizationmainly increases the Coulomb blockade area and Coulomb blockade oscillation periodicity, and thus, affects the SET circuit performance. A new model for the noise margin of the SET inverter is proposed, which includes the energy quantization effects. Using the noise margin as a metric, the robustness of the SET inverter is studied against the effects of energy quantization. An analytical expression is developed, which explicitly defines the maximum energy quantization (termed as ``quantization threshold'') that an SET inverter can withstand before its noise margin falls below a specified tolerance level. The effects of energy quantization are further studiedfor the current-biased negative differential resistance (NDR) circuitand hybrid SETMOS circuit. A new model for the conductance of NDR characteristics is also formulated that explains the energy quantization effects.

Identification of Hadronically Decaying Tau Leptons in Searches for Heavy MSSM Higgs Bosons with the CMS Detector at the CERN LHC

This thesis describes methods for the reliable identification of hadronically decaying tau leptons in the search for heavy Higgs bosons of the minimal supersymmetric standard model of particle physics (MSSM). The identification of the hadronic tau lepton decays, i.e. tau-jets, is applied to the gg->bbH, H->tautau and gg->tbH+, H+->taunu processes to be searched for in the CMS experiment at the CERN Large Hadron Collider. Of all the event selections applied in these final states, the tau-jet identification is the single most important event selection criterion to separate the tiny Higgs boson signal from a large number of background events. The tau-jet identification is studied with methods based on a signature of a low charged track multiplicity, the containment of the decay products within a narrow cone, an isolated electromagnetic energy deposition, a non-zero tau lepton flight path, the absence of electrons, muons, and neutral hadrons in the decay signature, and a relatively small tau lepton mass compared to the mass of most hadrons. Furthermore, in the H+->taunu channel, helicity correlations are exploited to separate the signal tau jets from those originating from the W->taunu decays. Since many of these identification methods rely on the reconstruction of charged particle tracks, the systematic uncertainties resulting from the mechanical tolerances of the tracking sensor positions are estimated with care. The tau-jet identification and other standard selection methods are applied to the search for the heavy neutral and charged Higgs bosons in the H->tautau and H+->taunu decay channels. For the H+->taunu channel, the tau-jet identification is redone and optimized with a recent and more detailed event simulation than previously in the CMS experiment. Both decay channels are found to be very promising for the discovery of the heavy MSSM Higgs bosons. The Higgs boson(s), whose existence has not yet been experimentally verified, are a part of the standard model and its most popular extensions. They are a manifestation of a mechanism which breaks the electroweak symmetry and generates masses for particles. Since the H->tautau and H+->taunu decay channels are important for the discovery of the Higgs bosons in a large region of the permitted parameter space, the analysis described in this thesis serves as a probe for finding out properties of the microcosm of particles and their interactions in the energy scales beyond the standard model of particle physics.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Sequencing of T-superfamily conotoxins from Conus virgo: Pyroglutamic acid identification and disulfide arrangement by MALDI mass spectrometry

De novo mass spectrometric sequencing of two Conus peptides, Vi1359 and Vi1361, from the vermivorous cone snail Conus virgo, found off the southern Indian coast, is presented. The peptides, whose masses differ only by 2 Da, possess two disulfide bonds and an amidated C-terminus. Simple chemical modifications and enzymatic cleavage coupled with matrix assisted laser desorption ionization (MALDI) mass spectrometric analysis aided in establishing the sequences of Vi1359, ZCCITIPECCRI-NH2, and Vi1361, ZCCPTMPECCRI-NH2, Which differ only at residues 4 and 6 (Z = pyroglutamic acid). The presence of the pyroglutamyl residue at the N-terminus was unambiguously identified by chemical hydrolysis of the cyclic amide, followed by esterification. The presence of Ile residues in both the peptides was confirmed from high-energy collision induced dissociation (CID) studies, using the observation Of W-n- and d(n)-ions as a diagnostic. Differential cysteine labeling, in conjunction with MALDI-MS/MS, permitted establishment of disulfide connectivity in both peptides as Cys2-Cys9 and Cys3-Cys10. The cysteine pattern clearly reveals that the peptides belong to the class of T-superfamily conotoxins, in particular the T-1 superfamily.

On the performance analysis of a class of neuron circuits

A new performance metric, Peak-Error Ratio (PER) has been presented to benchmark the performance of a class of neuron circuits to realize neuron activation function (NAF) and its derivative (DNAF). Neuron circuits, biased in subthreshold region, based on the asymmetric cross-coupled differential pair configuration and conventional configuration of applying small external offset voltage at the input have been compared on the basis of PER. It is shown that the technique of using transistor asymmetry in a cross-coupled differential pair performs on-par with that of applying external offset voltage. The neuron circuits have been experimentally prototyped and characterized as a proof of concept on the 1.5 mu m AMI technology.

Novel peptides of therapeutic promise from Indian Conidae

Highly structured small peptides are the major toxic constituents of the venom of cone snails, a family of widely distributed predatory marine molluscs. These animals use the venom for rapid prey immobilization. The peptide components in the venom target a wide variety of membrane-bound ion channels and receptors. Many have been found to be highly selective for a diverse range of mammalian ion channels and receptors associated with pain-signaling pathways. Their small size, structural stability, and target specificity make them attractive pharmacologic agents. A select number of laboratories mainly from the United States, Europe, Australia, Israel, and China have been engaged in intense drug discovery programs based on peptides from a few snail species. Coastal India has an estimated 20-30% of the known cone species; however, few serious studies have been reported so far. We have begun a comprehensive program for the identification and characterization of peptides from cone snails found in Indian Coastal waters. This presentation reviews our progress over the last 2 years. As expected from the evolutionary history of these venom components, our search has yielded novel peptides of therapeutic promise from the new species that we have studied.

Selective dissemination of XML documents using GAs and SVM

XML has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Self Adaptive Migration Model Genetic Algorithm (SAMCA)[5] and multi class Support Vector Machine (SVM) are used to learn a user model. Based on the feedback from the users the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

On the performance analysis of a class of neuron circuits

A new performance metric, Peak-Error Ratio (PER) has been presented to benchmark the performance of a class of neuron circuits to realize neuron activation function (NAF) and its derivative (DNAF). Neuron circuits, biased in subthreshold region, based on the asymmetric cross-coupled differential pair configuration and conventional configuration of applying small external offset voltage at the input have been compared on the basis of PER. It is shown that the technique of using transistor asymmetry in a cross-coupled differential pair performs on-par with that of applying external offset voltage. The neuron circuits have been experimentally prototyped and characterized as a proof of concept on the 1.5 mu m AMI technology.

Measurement of the kT Distribution of Particles in Jets Produced in pp̅ Collisions at √s=1.96 TeV

We present a measurement of the transverse momentum with respect to the jet axis (kt) of particles in jets produced in pp̅ collisions at √s=1.96  TeV. Results are obtained for charged particles in a cone of 0.5 radians around the jet axis in events with dijet invariant masses between 66 and 737  GeV/c2. The experimental data are compared to theoretical predictions obtained for fragmentation partons within the framework of resummed perturbative QCD using the modified leading log and next-to-modified leading log approximations. The comparison shows that trends in data are successfully described by the theoretical predictions, indicating that the perturbative QCD stage of jet fragmentation is dominant in shaping basic jet characteristics.

Measurement of the kT Distribution of Particles in Jets Produced in pp̅ Collisions at √s=1.96 TeV

We present a measurement of the transverse momentum with respect to the jet axis ($k_{T}$) of particles in jets produced in $p\bar p$ collisions at $\sqrt{s}=1.96$ TeV. Results are obtained for charged particles within a cone of opening angle 0.5 radians around the jet axis in events with dijet invariant masses between 66 and 737 GeV/c$^{2}$. The experimental data are compared to theoretical predictions obtained for fragmentation partons within the framework of resummed perturbative QCD using the modified leading log and next-to-modified leading log approximations. The comparison shows that trends in data are successfully described by the theoretical predictions, indicating that the perturbative QCD stage of jet fragmentation is dominant in shaping basic jet characteristics.

Investigation of activated transport in hole doped rare earth manganites in the high temperature paramagnetic regime

Electronic transport in the high temperature paramagnetic regime of the colossal magnetoresistive oxides, La(1-x)A(x)MnO(3), A=Ca, Sr, Ba, x similar or equal to 0.1-0.3, has been investigated using resistivity measurements. The main motivation for this work is to relook into the actual magnitude of the activation energy for transport in a number of manganites and study its variation as a function of hole doping (x), average A-site cation radius (< r(A)>), cationic disorder (sigma(2)) and strain (epsilon(zz)). We show that contrary to current practice, the description of a single activation energy in this phase is not entirely accurate. Our results clearly reveal a strong dependence of the activation energy on the hole doping as well as disorder. Comparing the results across different substituent species with different < r(A)> reveals the importance of sigma(2) as a metric to qualify any analysis based on (r(A)). (c) 2006 Elsevier Ltd. All rights reserved.