Vapor Pressure of Ionic Liquids

We argue that the extremely low vapor pressures of room temperature ionic liquids near their triple points are due to the combination of strong ionic characters and of low melting temperatures.Comment: Initially submitted manuscript of article M. Bier and S. Dietrich, Mol. Phys. 108, 211 (2010) [Corrigendum: Mol. Phys. 108, 1413 (2010)

Efficient selection of globally optimal rules on large imbalanced data based on rule coverage relationship analysis

Copyright © SIAM. Rule-based anomaly and fraud detection systems often suffer from massive false alerts against a huge number of enterprise transactions. A crucial and challenging problem is to effectively select a globally optimal rule set which can capture very rare anomalies dispersed in large-scale background transactions. The existing rule selection methods which suffer significantly from complex rule interactions and overlapping in large imbalanced data, often lead to very high false positive rate. In this paper, we analyze the interactions and relationships between rules and their coverage on transactions, and propose a novel metric, Max Coverage Gain. Max Coverage Gain selects the optimal rule set by evaluating the contribution of each rule in terms of overall performance to cut out those locally significant but globally redundant rules, without any negative impact on the recall. An effective algorithm, MCGminer, is then designed with a series of built-in mechanisms and pruning strategies to handle complex rule interactions and reduce computational complexity towards identifying the globally optimal rule set. Substantial experiments on 13 UCI data sets and a real time online banking transactional database demonstrate that MCGminer achieves significant improvement on both accuracy, scalability, stability and efficiency on large imbalanced data compared to several state-of-the-art rule selection techniques

Robust textual data streams mining based on continuous transfer learning

Copyright © SIAM. In textual data stream environment, concept drift can occur at any time, existing approaches partitioning streams into chunks can have problem if the chunk boundary does not coincide with the change point which is impossible to predict. Since concept drift can occur at any point of the streams, it will certainly occur within chunks, which is called random concept drift. The paper proposed an approach, which is called chunk level-based concept drift method (CLCD), that can overcome this chunking problem by continuously monitoring chunk characteristics to revise the classifier based on transfer learning in positive and unlabeled (PU) textual data stream environment. Our proposed approach works in three steps. In the first step, we propose core vocabulary-based criteria to justify and identify random concept drift. In the second step, we put forward the extension of LELC (PU learning by extracting likely positive and negative microclusters)[ 1], called soft-LELC, to extract representative examples from unlabeled data, and assign a confidence score to each extracted example. The assigned confidence score represents the degree of belongingness of an example towards its corresponding class. In the third step, we set up a transfer learning-based SVM to build an accurate classifier for the chunks where concept drift is identified in the first step. Extensive experiments have shown that CLCD can capture random concept drift, and outperforms state-of-the-art methods in positive and unlabeled textual data stream environments

Time resolved imaging of magnetization dynamics in hard disk writer yokes excited by bipolar current pulses

This is the final version of the article. Available from the American Institute of Physics via the DOI in this record.A partially built hard disk writer structure with a NiFe/CoFe/Ru/NiFe/CoFe synthetic antiferromagnetic (SAF) yoke was studied by time and vector resolved scanning Kerr microscopy. All three time dependent components of the magnetization were recorded simultaneously as a bipolar current pulse with 1 MHz repetition rate was delivered to the coil. The component of magnetization parallel to the symmetry axis of the yoke was compared at the pole and above a coil winding in the centre of the yoke. The two responses are in phase as the pulse rises, but the pole piece lags the yoke as the pulse falls. The Kerr signal is smaller within the yoke than within the confluence region during pulse cycling. This suggests funneling of flux into the confluence region. Dynamic images acquired at different time delays showed that the relaxation is faster in the centre of the yoke than in the confluence region, perhaps due to the different magnetic anisotropy in these regions. Although the SAF yoke is designed to support a single domain to aid flux conduction, no obvious flux beaming was observed, suggesting the presence of a more complicated domain structure. The SAF yoke writer hence provides relatively poor flux conduction but good control of rise time compared to single layer and multi-layered yokes studied previously.The authors acknowledge the financial support of Seagate Pla

Time-resolved Kerr microscopy of coupled transverse domain walls in a pair of curved nanowires

This is the final version of the article. Available from the American Institute of Physics via the DOI in this record.Time-resolved scanning Kerr microscopy has been used to directly observe magnetostatically coupled transverse domain walls (TDWs) in a pair of closely spaced, curved nanowires (NWs). Kerr images of the precessional response of the magnetic domain to either side of the TDW revealed the TDW as a minimum in the Kerr signal in the region of closest NW separation. When the TDWs were ejected from the NW pair, the minimum in the Kerr signal was no longer observed. By imaging this transition, the static de-coupling field was estimated to be in the range from 38 to 48 Oe in good agreement with a simple micromagnetic model. This work provides a novel technique by which DC and microwave assisted decoupling fields of TDWs may be explored in NW pairs of different width, separation, and curvature.This work was supported by the EU Grant Master No. NMP-FP7-212257, the UK EPSRC Grant Ref. EP/I038470/1, and partially supported by the EU FP7 Project 3SPIN No. 247368, and the Marie Curie IOF Project No. 299376

A Comprehensive Survey on Graph Neural Networks

Deep learning has revolutionized many machine learning tasks in recent years, ranging from image classification and video processing to speech recognition and natural language understanding. The data in these tasks are typically represented in the Euclidean space. However, there is an increasing number of applications, where data are generated from non-Euclidean domains and are represented as graphs with complex relationships and interdependency between objects. The complexity of graph data has imposed significant challenges on the existing machine learning algorithms. Recently, many studies on extending deep learning approaches for graph data have emerged. In this article, we provide a comprehensive overview of graph neural networks (GNNs) in data mining and machine learning fields. We propose a new taxonomy to divide the state-of-the-art GNNs into four categories, namely, recurrent GNNs, convolutional GNNs, graph autoencoders, and spatial-temporal GNNs. We further discuss the applications of GNNs across various domains and summarize the open-source codes, benchmark data sets, and model evaluation of GNNs. Finally, we propose potential research directions in this rapidly growing field

Time resolved scanning Kerr microscopy of hard disk writer structures with a multilayered yoke

The erratum is available in ORE at http://hdl.handle.net/10871/21966Partially built hard disk writer structures with a multilayered yoke formed from 4 repeats of a NiFe(∼1 nm)/CoFe(50 nm) bilayer were studied by time and vector resolved scanning Kerr microscopy. Dynamic images of the in-plane magnetization suggest an underlying closure domain equilibrium state. This state is found to be modified by application of a bias magnetic field and also during pulse cycling, leading to different magnetization rotation and relaxation behavior within the tip region. © 2013 AIP Publishing LLC.The authors gratefully acknowledge financial support from the Seagate Plan

Erratum: “Time resolved scanning Kerr microscopy of hard disk writer structures with a multilayered yoke” [Appl. Phys. Lett. 102, 162407 (2013)]

This is the final version of the article. Available from the American Institute of Physics via the DOI in this record.The original article is in ORE at http://hdl.handle.net/10871/21958There is no abstract available for this articl

Ferromagnetic resonance of patterned chromium dioxide thin films grown by selective area chemical vapour deposition

This is the final version of the article. Available from the American Institute of Physics via the DOI in this record.A selective area chemical vapour deposition technique has been used to fabricate continuous and patterned epitaxial CrO2 thin films on (100)-oriented TiO2 substrates. Precessional magnetization dynamics were stimulated both electrically and optically, and probed by means of time-resolved Kerr microscopy and vector network analyser ferromagnetic resonance techniques. The dependence of the precession frequency and the effective damping parameter upon the static applied magnetic field were investigated. All films exhibited a large in-plane uniaxial anisotropy. The effective damping parameter was found to exhibit strong field dependence in the vicinity of the hard axis saturation field. However, continuous and patterned films were found to possess generally similar dynamic properties, confirming the suitability of the deposition technique for fabrication of future spintronic devices