Spatial Modulation and Space Shift Keying in Single Carrier Communication

Spatial modulation (SM) and space shift keying (SSK) are relatively new modulation techniques which are attractive in multi-antenna communications. Single carrier (SC) systems can avoid the peak-to-average power ratio (PAPR) problem encountered in multicarrier systems. In this paper, we study SM and SSK signaling in cyclic-prefixed SC (CPSC) systems on MIMO-ISI channels. We present a diversity analysis of MIMO-CPSC systems under SSK and SM signaling. Our analysis shows that the diversity order achieved by (n(t), n(r)) SSK scheme and (n(t), n(r), Theta(M)) SM scheme in MIMO-CPSC systems under maximum-likelihood (ML) detection is n(r), where n(t), n(r) denote the number of transmit and receive antennas and Theta(M) denotes the modulation alphabet of size M. Bit error rate (BER) simulation results validate this predicted diversity order. Simulation results also show that MIMO-CPSC with SM and SSK achieves much better performance than MIMO-OFDM with SM and SSK.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

High speed optical communication systems: From modulation formats to radically new fibres

High volumes of data traffic along with bandwidth hungry applications, such as cloud computing and video on demand, is driving the core optical communication links closer and closer to their maximum capacity. The research community has clearly identifying the coming approach of the nonlinear Shannon limit for standard single mode fibre [1,2]. It is in this context that the work on modulation formats, contained in Chapter 3 of this thesis, was undertaken. The work investigates the proposed energy-efficient four-dimensional modulation formats. The work begins by studying a new visualisation technique for four dimensional modulation formats, akin to constellation diagrams. The work then carries out one of the first implementations of one such modulation format, polarisation-switched quadrature phase-shift keying (PS-QPSK). This thesis also studies two potential next-generation fibres, few-mode and hollow-core photonic band-gap fibre. Chapter 4 studies ways to experimentally quantify the nonlinearities in few-mode fibre and assess the potential benefits and limitations of such fibres. It carries out detailed experiments to measure the effects of stimulated Brillouin scattering, self-phase modulation and four-wave mixing and compares the results to numerical models, along with capacity limit calculations. Chapter 5 investigates hollow-core photonic band-gap fibre, where such fibres are predicted to have a low-loss minima at a wavelength of 2μm. To benefit from this potential low loss window requires the development of telecoms grade subsystems and components. The chapter will outline some of the development and characterisation of these components. The world's first wavelength division multiplexed (WDM) subsystem directly implemented at 2μm is presented along with WDM transmission over hollow-core photonic band-gap fibre at 2μm. References: [1]P. P. Mitra, J. B. Stark, Nature, 411, 1027-1030, 2001 [2] A. D. Ellis et al., JLT, 28, 423-433, 2010.

Documents and Dependencies: an Exploration of Vector Space Models for Semantic Composition

In most previous research on distributional semantics, Vector Space Models (VSMs) of words are built either from topical information (e.g., documents in which a word is present), or from syntactic/semantic types of words (e.g., dependency parse links of a word in sentences), but not both. In this paper, we explore the utility of combining these two representations to build VSM for the task of semantic composition of adjective-noun phrases. Through extensive experiments on benchmark datasets, we find that even though a type-based VSM is effective for semantic composition, it is often outperformed by a VSM built using a combination of topic- and type-based statistics. We also introduce a new evaluation task wherein we predict the composed vector representation of a phrase from the brain activity of a human subject reading that phrase. We exploit a large syntactically parsed corpus of 16 billion tokens to build our VSMs, with vectors for both phrases and words, and make them publicly available.

Vector representation of directional modulation transmitters

Directional Modulation (DM) is a recently proposed technique for securing wireless communication. In this paper we point out that modulation-directionality is a consequence of varying the beamforming network, either in baseband or in the RF stage, at the information rate In order to formalize and extend on previous analysis and synthesis methods a new theoretical treatment using vector representations of directional modulation (DM) systems is introduced and used to obtain the necessary and sufficient con

NEW CHARACTERIZATIONS OF COMPLETE SPACELIKE SUBMANIFOLDS IN SEMI-RIEMANNIAN SPACE FORMS

In this paper we study n-dimensional complete spacelike submanifolds with constant normalized scalar curvature immersed in semi-Riemannian space forms. By extending Cheng-Yau`s technique to these ambients, we obtain results to such submanifolds satisfying certain conditions on both the squared norm of the second fundamental form and the mean curvature. We also characterize compact non-negatively curved submanifolds in De Sitter space of index p.

Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.

The triplite–triploidite supergroup: structural modulation in wagnerite, discreditation of magniotriplite, and the new mineral hydroxylwagnerite

Electron-microprobe analysis, single-crystal X-ray diffraction with an area detector, and high-resolution transmission electron microscopy show that minerals related to wagnerite, triplite and triploidite, which are monoclinic Mg, Fe and Mn phosphates with the formula Me2+ 2PO4(F,OH), constitute a modulated series based on the average triplite structure. Modulation occurs along b and may be commensurate with (2b periodicity) or incommensurate but generally close to integer values (∼3b, ∼5b, ∼7b, ∼9b), i.e. close to polytypic behaviour. As a result, the Mg- and F-dominant minerals magniotriplite and wagnerite can no longer be considered polymorphs of Mg2PO4F, i.e., there is no basis for recognizing them as distinct species. Given that wagnerite has priority (1821 vs. 1951), the name magniotriplite should be discarded in favour of wagnerite. Hydroxylwagnerite, end-member Mg2PO4OH, occurs in pyrope megablasts along with talc, clinochlore, kyanite, rutile and secondary apatite in two samples from lenses of pyrope–kyanite–phengite–quartz-schist within metagranite in the coesite-bearing ultrahigh-pressure metamorphic unit of the Dora-Maira Massif, western Alps, Vallone di Gilba, Val Varaita, Piemonte, Italy. Electron microprobe analyses of holotype hydroxylwagnerite and of the crystal with the lowest F content gave in wt%: P2O5 44.14, 43.99; SiO2 0.28, 0.02; SO3 –, 0.01; TiO2 0.20, 0.16; Al2O3 0.06, 0.03; MgO 48.82, 49.12; FeO 0.33, 0.48; MnO 0.01, 0.02; CaO 0.12, 0.10; Na2O 0.01, –; F 5.58, 4.67; H2O (calc) 2.94, 3.36; –O = F 2.35, 1.97; Sum 100.14, 99.98, corresponding to (Mg1.954Fe0.007Ca0.003Ti0.004Al0.002Na0.001)Σ=1.971(P1.003Si0.008)Σ=1.011O4(OH0.526F0.474)Σ=1 and (Mg1.971Fe0.011Ca0.003Ti0.003Al0.001)Σ=1.989(P1.002Si0.001)Σ=1.003O4(OH0.603F0.397)Σ=1, respectively. Due to the paucity of material, H2O could not be measured, so OH was calculated from the deficit in F assuming stoichiometry, i.e., by assuming F + OH = 1 per formula unit. Holotype hydroxylwagnerite is optically biaxial (+), α 1.584(1), β 1.586(1), γ 1.587(1) (589 nm); 2V Z(meas.) = 43(2)°; orientation Y = b. Single-crystal X-ray diffraction gives monoclinic symmetry, space group P21/c, a = 9.646(3) Å, b = 12.7314(16) Å, c = 11.980(4) Å, β = 108.38(4) , V = 1396.2(8) Å3, Z = 16, i.e., hydroxylwagnerite is the OH-dominant analogue of wagnerite [β-Mg2PO4(OH)] and a high-pressure polymorph of althausite, holtedahlite, and α- and ε-Mg2PO4(OH). We suggest that the group of minerals related to wagnerite, triplite and triploidite constitutes a triplite–triploidite super-group that can be divided into F-dominant phosphates (triplite group), OH-dominant phosphates (triploidite group), O-dominant phosphates (staněkite group) and an OH-dominant arsenate (sarkinite). The distinction among the three groups and a potential fourth group is based only on chemical features, i.e., occupancy of anion or cation sites. The structures of these minerals are all based on the average triplite structure, with a modulation controlled by the ratio of Mg, Fe2+, Fe3+ and Mn2+ ionic radii to (O,OH,F) ionic radii.

On the Set of Locally Convex Topologies Compatible with a Given Topology on a Vector Space: Cardinality Aspects

For a topological vector space (X, τ ), we consider the family LCT (X, τ ) of all locally convex topologies defined on X, which give rise to the same continuous linear functionals as the original topology τ . We prove that for an infinite-dimensional reflexive Banach space (X, τ ), the cardinality of LCT (X, τ ) is at least c.

Third space in cyberspace : Indigenous youth, new technologies and literacies

This chapter analyses the affordances and constraints of an online literacy program designed for Indigenous Australian youth through a partnership between the Indigenous community, university staff and local schools. The after-school program sought to build on the cultural resources and experiences of the young people through a dialogic process of planning, negotiating, implementing, reflecting, and renegotiating the program with participants and a range of stakeholders. In the majority of cases, students presented themselves as part of pervasive global popular cultures, often hot-linking their webpages to pop icons and local sports stars. Elders regarded their competency as a potential cultural tool and community resource.

Selected new training documents to update user profile

Relevance Feedback (RF) has been proven very effective for improving retrieval accuracy. Adaptive information filtering (AIF) technology has benefited from the improvements achieved in all the tasks involved over the last decades. A difficult problem in AIF has been how to update the system with new feedback efficiently and effectively. In current feedback methods, the updating processes focus on updating system parameters. In this paper, we developed a new approach, the Adaptive Relevance Features Discovery (ARFD). It automatically updates the system's knowledge based on a sliding window over positive and negative feedback to solve a nonmonotonic problem efficiently. Some of the new training documents will be selected using the knowledge that the system currently obtained. Then, specific features will be extracted from selected training documents. Different methods have been used to merge and revise the weights of features in a vector space. The new model is designed for Relevance Features Discovery (RFD), a pattern mining based approach, which uses negative relevance feedback to improve the quality of extracted features from positive feedback. Learning algorithms are also proposed to implement this approach on Reuters Corpus Volume 1 and TREC topics. Experiments show that the proposed approach can work efficiently and achieves the encouragement performance.