A Mixed-Attribute Approach in Ant-Miner Classification Rule Discovery Algorithm

In this paper, we introduce Ant-MinerMA to tackle mixed-attribute classification problems. Most classification problems involve continuous, ordinal and categorical attributes. The majority of Ant Colony Optimization (ACO) classification algorithms have the limitation of being able to handle categorical attributes only, with few exceptions that use a discretisation procedure when handling continuous attributes either in a preprocessing stage or during the rule creation. Using a solution archive as a pheromone model, inspired by the ACO for mixed-variable optimization (ACO-MV), we eliminate the need for a discretisation procedure and attributes can be treated directly as continuous, ordinal, or categorical. We compared the proposed Ant-MinerMA against cAnt-Miner, an ACO-based classification algorithm that uses a discretisation procedure in the rule construction process. Our results show that Ant-MinerMA achieved significant improvements on computational time due to the elimination of the discretisation procedure without affecting the predictive performance

An intelligent assistant for exploratory data analysis

In this paper we present an account of the main features of SNOUT, an intelligent assistant for exploratory data analysis (EDA) of social science survey data that incorporates a range of data mining techniques. EDA has much in common with existing data mining techniques: its main objective is to help an investigator reach an understanding of the important relationships ina data set rather than simply develop predictive models for selectd variables. Brief descriptions of a number of novel techniques developed for use in SNOUT are presented. These include heuristic variable level inference and classification, automatic category formation, the use of similarity trees to identify groups of related variables, interactive decision tree construction and model selection using a genetic algorithm

Exploitation of Dynamic Communication Patterns through Static Analysis

Abstract not provide

Online Human Activity Recognition using Low-Power Wearable Devices

Human activity recognition~(HAR) has attracted significant research interest due to its applications in health monitoring and patient rehabilitation. Recent research on HAR focuses on using smartphones due to their widespread use. However, this leads to inconvenient use, limited choice of sensors and inefficient use of resources, since smartphones are not designed for HAR. This paper presents the first HAR framework that can perform both online training and inference. The proposed framework starts with a novel technique that generates features using the fast Fourier and discrete wavelet transforms of a textile-based stretch sensor and accelerometer. Using these features, we design an artificial neural network classifier which is trained online using the policy gradient algorithm. Experiments on a low power IoT device (TI-CC2650 MCU) with nine users show 97.7% accuracy in identifying six activities and their transitions with less than 12.5 mW power consumption.Comment: This is in proceedings of ICCAD 2018. The datasets are available at https://github.com/gmbhat/human-activity-recognitio

Quasiparticle-quasiparticle Scattering in High Tc Superconductors

The quasiparticle lifetime and the related transport relaxation times are the fundamental quantities which must be known in order to obtain a description of the transport properties of the high T_c superconductors. Studies of these quantities have been undertaken previously for the d-wave, high T_c superconductors for the case of temperature-independent elastic impurity scattering. However, much less is known about the temperature-dependent inelastic scattering. Here we give a detailed description of the characteristics of the temperature-dependent quasiparticle-quasiparticle scattering in d-wave superconductors, and find that this process gives a natural explanation of the rapid variation with temperature of the electrical transport relaxation rate.Comment: 4 page

Neutron scattering in a d_{x^2-y^2}-wave superconductor with strong impurity scattering and Coulomb correlations

We calculate the spin susceptibility at and below T_c for a d_{x^2-y^2}-wave superconductor with resonant impurity scattering and Coulomb correlations. Both the impurity scattering and the Coulomb correlations act to maintain peaks in the spin susceptibility, as a function of momentum, at the Brillouin zone edge. These peaks would otherwise be suppressed by the superconducting gap. The predicted amount of suppression of the spin susceptibility in the superconducting state compared to the normal state is in qualitative agreement with results from recent magnetic neutron scattering experiments on La_{1.86}Sr_{0.14}CuO_4 for momentum values at the zone edge and along the zone diagonal. The predicted peak widths in the superconducting state, however, are narrower than those in the normal state, a narrowing which has not been observed experimentally.Comment: 24 pages (12 tarred-compressed-uuencoded Postscript figures), REVTeX 3.0 with epsf macros, UCSBTH-94-1

Swift J164449.3+573451 event: generation in the collapsing star cluster?

We discuss the multiband energy release in a model of a collapsing galactic nucleus, and we try to interpret the unique super-long cosmic gamma-ray event Swift J164449.3+573451 (GRB 110328A by early classification) in this scenario. Neutron stars and stellar-mass black holes can form evolutionary a compact self-gravitating subsystem in the galactic center. Collisions and merges of these stellar remnants during an avalanche contraction and collapse of the cluster core can produce powerful events in different bands due to several mechanisms. Collisions of neutron stars and stellar-mass black holes can generate gamma-ray bursts (GRBs) similar to the ordinary models of short GRB origin. The bright peaks during the first two days may also be a consequence of multiple matter supply (due to matter release in the collisions) and accretion onto the forming supermassive black hole. Numerous smaller peaks and later quasi-steady radiation can arise from gravitational lensing, late accretion of gas onto the supermassive black hole, and from particle acceleration by shock waves. Even if this model will not reproduce exactly all the Swift J164449.3+573451 properties in future observations, such collapses of galactic nuclei can be available for detection in other events.Comment: 7 pages, replaced by the final versio

Motion-corrected multiparametric renal arterial spin labelling at 3T: Reproducibility and effect of vasodilator challenge

Objectives We investigated the feasibility and reproducibility of free-breathing motion-corrected multiple inversion time (multi-TI) pulsed renal arterial spin labelling (PASL), with general kinetic model parametric mapping, to simultaneously quantify renal perfusion (RBF), bolus arrival time (BAT) and tissue T1. Methods In a study approved by the Health Research Authority, 12 healthy volunteers (mean age, 27.6 ± 18.5 years; 5 male) gave informed consent for renal imaging at 3 T using multi-TI ASL and conventional single-TI ASL. Glyceryl trinitrate (GTN) was used as a vasodilator challenge in six subjects. Flow-sensitive alternating inversion recovery (FAIR) preparation was used with background suppression and 3D-GRASE (gradient and spin echo) read-out, and images were motion-corrected. Parametric maps of RBF, BAT and T1 were derived for both kidneys. Agreement was assessed using Pearson correlation and Bland-Altman plots. Results Inter-study correlation of whole-kidney RBF was good for both single-TI (r2 = 0.90), and multi-TI ASL (r2 = 0.92). Single-TI ASL gave a higher estimate of whole-kidney RBF compared to multi-TI ASL (mean bias, 29.3 ml/min/100 g; p <0.001). Using multi-TI ASL, the median T1 of renal cortex was shorter than that of medulla (799.6 ms vs 807.1 ms, p = 0.01), and mean whole-kidney BAT was 269.7 ± 56.5 ms. GTN had an effect on systolic blood pressure (p < 0.05) but the change in RBF was not significant. Conclusions Free-breathing multi-TI renal ASL is feasible and reproducible at 3 T, providing simultaneous measurement of renal perfusion, haemodynamic parameters and tissue characteristics at baseline and during pharmacological challenge