DRSP : Dimension Reduction For Similarity Matching And Pruning Of Time Series Data Streams

Similarity matching and join of time series data streams has gained a lot of relevance in today's world that has large streaming data. This process finds wide scale application in the areas of location tracking, sensor networks, object positioning and monitoring to name a few. However, as the size of the data stream increases, the cost involved to retain all the data in order to aid the process of similarity matching also increases. We develop a novel framework to addresses the following objectives. Firstly, Dimension reduction is performed in the preprocessing stage, where large stream data is segmented and reduced into a compact representation such that it retains all the crucial information by a technique called Multi-level Segment Means (MSM). This reduces the space complexity associated with the storage of large time-series data streams. Secondly, it incorporates effective Similarity Matching technique to analyze if the new data objects are symmetric to the existing data stream. And finally, the Pruning Technique that filters out the pseudo data object pairs and join only the relevant pairs. The computational cost for MSM is O(l*ni) and the cost for pruning is O(DRF*wsize*d), where DRF is the Dimension Reduction Factor. We have performed exhaustive experimental trials to show that the proposed framework is both efficient and competent in comparison with earlier works.Comment: 20 pages,8 figures, 6 Table

Evaluation of triglyceride: HDL-C ratio and Non-HDL-C as harbingers of increased cardiovascular risk in metabolic syndrome

Background: Metabolic syndrome is an aggregate of conditions that together increases the risk of developing cardiovascular disease and type 2 diabetes mellitus. Dyslipidemia consisting of elevated triglyceride, decreased HDL, and altered triglyceride to high density lipoprotein- Cholesterol (TG/HDL-C) ratio is useful in predicting cardiometabolic risk and insulin resistance. The present study aimed to compile further evidence for clinical utility of TG/HDL-C ratio and Non HDL-C as simple, cost effective tools for early identification of cardiovascular disease risk in metabolic syndrome.Methods: This study was carried out with hundred subjects. Fifty of these subjects were diagnosed with metabolic syndrome according to National Cholesterol Education Program Adult Treatment Panel III; while other fifty were age and gender matched healthy control subjects.Results: The impact of cardiometabolic markers on metabolic syndrome was assessed separately in men and women by applying Mann Whitney ‘U’ test. Study showed highly significant increase in TG, HDL, TC/TG and TG/HDL-C ratio in women compared to men with p<0.01. The odds ratio of TG/HDL for women showed the highest ratio of 6, 95% CI (1.5225 to 23.6401) p=0.006 compared to men 4.9583, 95% CI (1.0088-24.3711), p=0.004.Conclusions: This study demonstrated that TG/HDL-C ratio and Non HDL-C are strongly associated with metabolic syndrome in urban population. In comparison, TG/HDL-C is a better predictor of metabolic syndrome than non-HDL-C

Forecasting Stock Time-Series using Data Approximation and Pattern Sequence Similarity

Time series analysis is the process of building a model using statistical techniques to represent characteristics of time series data. Processing and forecasting huge time series data is a challenging task. This paper presents Approximation and Prediction of Stock Time-series data (APST), which is a two step approach to predict the direction of change of stock price indices. First, performs data approximation by using the technique called Multilevel Segment Mean (MSM). In second phase, prediction is performed for the approximated data using Euclidian distance and Nearest-Neighbour technique. The computational cost of data approximation is O(n ni) and computational cost of prediction task is O(m |NN|). Thus, the accuracy and the time required for prediction in the proposed method is comparatively efficient than the existing Label Based Forecasting (LBF) method [1].Comment: 11 page

Exact Chiral Spin Liquids and Mean-Field Perturbations of Gamma Matrix Models on the Ruby Lattice

We theoretically study an exactly solvable Gamma matrix generalization of the Kitaev spin model on the ruby lattice, which is a honeycomb lattice with "expanded" vertices and links. We find this model displays an exceptionally rich phase diagram that includes: (i) gapless phases with stable spin fermi surfaces, (ii) gapless phases with low-energy Dirac cones and quadratic band touching points, and (iii) gapped phases with finite Chern numbers possessing the values {\pm}4,{\pm}3,{\pm}2 and {\pm}1. The model is then generalized to include Ising-like interactions that break the exact solvability of the model in a controlled manner. When these terms are dominant, they lead to a trivial Ising ordered phase which is shown to be adiabatically connected to a large coupling limit of the exactly solvable phase. In the limit when these interactions are weak, we treat them within mean-field theory and present the resulting phase diagrams. We discuss the nature of the transitions between various phases. Our results highlight the richness of possible ground states in closely related magnetic systems.Comment: 9 pages, 9 figure

Evanescence in Coined Quantum Walks

In this paper we complete the analysis begun by two of the authors in a previous work on the discrete quantum walk on the line [J. Phys. A 36:8775-8795 (2003) quant-ph/0303105 ]. We obtain uniformly convergent asymptotics for the "exponential decay'' regions at the leading edges of the main peaks in the Schr{\"o}dinger (or wave-mechanics) picture. This calculation required us to generalise the method of stationary phase and we describe this extension in some detail, including self-contained proofs of all the technical lemmas required. We also rigorously establish the exact Feynman equivalence between the path-integral and wave-mechanics representations for this system using some techniques from the theory of special functions. Taken together with the previous work, we can now prove every theorem by both routes.Comment: 32 pages AMS LaTeX, 5 figures in .eps format. Rewritten in response to referee comments, including some additional references. v3: typos fixed in equations (131), (133) and (134). v5: published versio

Possible scale invariant linear magnetoresistance in pyrochlore iridates Bi2Ir2O7

We report the observation of a linear magnetoresistance in single crystals and epitaxial thin films of the pyrochlore iridate Bi2Ir2O7. The linear magnetoresistance is positive and isotropic at low temperatures, without any sign of saturation up to 35 T. As temperature increases, the linear field dependence gradually evolves to a quadratic field dependence. The temperature and field dependence of magnetoresistance of Bi2Ir2O7 bears strikingly resemblance to the scale invariant magnetoresistance observed in the strange metal phase in high Tc cuprates. However, the residual resistivity of Bi2Ir2O7 is more than two orders of magnitude higher than the curpates. Our results suggest that the correlation between linear magnetoresistance and quantum fluctuations may exist beyond high temperature superconductors

Pairing in the iron arsenides: a functional RG treatment

We study the phase diagram of a microscopic model for the superconducting iron arsenides by means of a functional renormalization group. Our treatment establishes a connection between a strongly simplified two-patch model by Chubukov et al. and a five-band- analysis by Wang et al.. For a wide parameter range, the dominant pairing instability occurs in the extended s-wave channel. The results clearly show the relevance of pair scattering between electron and hole pockets. We also give arguments that the phase transition between the antiferromagnetic phase for the undoped system and the superconducting phase may be first order

Z2_2 topology and superconductivity from symmetry lowering of a 3D Dirac Metal Au2_2Pb

3D Dirac semi-metals (DSMs) are materials that have massless Dirac electrons and exhibit exotic physical properties It has been suggested that structurally distorting a DSM can create a Topological Insulator (TI), but this has not yet been experimentally verified. Furthermore, quasiparticle excitations known as Majorana Fermions have been theoretically proposed to exist in materials that exhibit superconductivity and topological surface states. Here we show that the cubic Laves phase Au$_2$Pb has a bulk Dirac cone above 100 K that gaps out upon cooling at a structural phase transition to create a topologically non trivial phase that superconducts below 1.2 K. The nontrivial Z$_2$ = -1 invariant in the low temperature phase indicates that Au$_2$Pb in its superconducting state must have topological surface states. These characteristics make Au$_2$Pb a unique platform for studying the transition between bulk Dirac electrons and topological surface states as well as studying the interaction of superconductivity with topological surface states

Coined quantum walks on percolation graphs

Quantum walks, both discrete (coined) and continuous time, form the basis of several quantum algorithms and have been used to model processes such as transport in spin chains and quantum chemistry. The enhanced spreading and mixing properties of quantum walks compared with their classical counterparts have been well-studied on regular structures and also shown to be sensitive to defects and imperfections in the lattice. As a simple example of a disordered system, we consider percolation lattices, in which edges or sites are randomly missing, interrupting the progress of the quantum walk. We use numerical simulation to study the properties of coined quantum walks on these percolation lattices in one and two dimensions. In one dimension (the line) we introduce a simple notion of quantum tunneling and determine how this affects the properties of the quantum walk as it spreads. On two-dimensional percolation lattices, we show how the spreading rate varies from linear in the number of steps down to zero, as the percolation probability decreases to the critical point. This provides an example of fractional scaling in quantum walk dynamics.Comment: 25 pages, 14 figures; v2 expanded and improved presentation after referee comments, added extra figur