On the construction of probabilistic Newton-type algorithms

It has recently been shown that many of the existing quasi-Newton algorithms can be formulated as learning algorithms, capable of learning local models of the cost functions. Importantly, this understanding allows us to safely start assembling probabilistic Newton-type algorithms, applicable in situations where we only have access to noisy observations of the cost function and its derivatives. This is where our interest lies. We make contributions to the use of the non-parametric and probabilistic Gaussian process models in solving these stochastic optimisation problems. Specifically, we present a new algorithm that unites these approximations together with recent probabilistic line search routines to deliver a probabilistic quasi-Newton approach. We also show that the probabilistic optimisation algorithms deliver promising results on challenging nonlinear system identification problems where the very nature of the problem is such that we can only access the cost function and its derivative via noisy observations, since there are no closed-form expressions available

Inelastic neutron scattering studies of the quantum frustrated magnet clinoatacamite, γ\gamma-Cu2(OD)3Cl, a proposed valence bond solid (VBS)

The frustrated magnet clinoatacamite, $\gamma$-Cu$_2$(OH)$_3$Cl, is attracting a lot of interest after suggestions that at low temperature it forms an exotic quantum state termed a Valence Bond Solid (VBS) made from dimerised Cu$^{2+}$ ($S=1/2$) spins.\cite{Lee_clinoatacamite} Key to the arguments surrounding this proposal were suggestions that the kagom\'e planes in the magnetic pyrochlore lattice of clinoatacamite are only weakly coupled, causing the system to behave as a quasi-2-dimensional magnet. This was reasoned from the near 95$^\circ$ angles made at the bridging oxygens that mediate exchange between the Cu ions that link the kagom\'e planes. Recent work pointed out that this exchange model is inappropriate for $\gamma$-Cu$_2$(OH)$_3$Cl, where the oxygen is present as a $\mu_3$-OH.\cite{Wills_JPC} Further, it used symmetry calculations and neutron powder diffraction to show that the low temperature magnetic structure ($T<6$ K) was canted and involved significant spin ordering on all the Cu$^{2+}$ spins, which is incompatible with the interpretation of simultaneous VBS and N\'eel ordering. Correspondingly, clinoatacamite is best considered a distorted pyrochlore magnet. In this report we show detailed inelastic neutron scattering spectra and revisit the responses of this frustrated quantum magnet.Comment: Proceedings of The International Conference on Highly Frustrated Magnetism 2008 (HFM2008

Spectral Properties From Lyman-alpha to H-alpha For An Essentially Complete Sample of Quasars I: Data

We have obtained quasi-simultaneous ultraviolet-optical spectra for 22 out of 23 quasars in the complete PG-X-ray sample with redshift, z<0.4, and M_B<-23. The spectra cover rest-frame wavelengths from at least Lyman-alpha to H-alpha. Here we provide a detailed description of the data, including careful spectrophotometry and redshift determination. We also present direct measurements of the continua, strong emission lines and features, including Lyman-alpha, SiIV+OIV], CIV, CIII], SiIII], MgII, H-beta, [OIII], He5876+NaI5890,5896, H-alpha, and blended iron emission in the UV and optical. The widths, asymmetries and velocity shifts of profiles of strong emission lines show that CIV and Lyman-alpha are very different from H-beta and H-alpha. This suggests that the motion of the broad line region is related to the ionization structure, but the data appears not agree with the radially stratified ionization structure supported by reverberation mapping studies, and therefore suggest that outflows contribute additional velocity components to the broad emission line profiles.Comment: 42 pages, 10 figures, 13 tables. Accepted by AJ. Supplemental figures not included. Full version available at http://physics.uwyo.edu/~shang/pgxpaper/ShangPaper.pd

Unsupervised clustering approach for network anomaly detection

This paper describes the advantages of using the anomaly detection approach over the misuse detection technique in detecting unknown network intrusions or attacks. It also investigates the performance of various clustering algorithms when applied to anomaly detection. Five different clustering algorithms: k-Means, improved k-Means, k-Medoids, EM clustering and distance-based outlier detection algorithms are used. Our experiment shows that misuse detection techniques, which implemented four different classifiers (naïve Bayes, rule induction, decision tree and nearest neighbour) failed to detect network traffic, which contained a large number of unknown intrusions; where the highest accuracy was only 63.97% and the lowest false positive rate was 17.90%. On the other hand, the anomaly detection module showed promising results where the distance-based outlier detection algorithm outperformed other algorithms with an accuracy of 80.15%. The accuracy for EM clustering was 78.06%, for k-Medoids it was 76.71%, for improved k-Means it was 65.40% and for k-Means it was 57.81%. Unfortunately, our anomaly detection module produces high false positive rate (more than 20%) for all four clustering algorithms. Therefore, our future work will be more focus in reducing the false positive rate and improving the accuracy using more advance machine learning technique

Towards an integrated model for citizen adoption of E-government services in developing countries: A Saudi Arabia case study

This paper considers the challenges that face the widespread adoption of E-government in developing countries, using Saudi Arabian our case study. E-government can be defined based on an existing set of requirements. In this paper we define E-government as a matrix of stakeholders; governments to governments, governments to business and governments to citizens using information and communications technology to deliver and consume services. E-government has been implemented for a considerable time in developed countries. However E-government services still faces many challenges their implemented and general adoption in developing countries. Therefore, this paper presents an integrated model for ascertaining the intention to adopt E-government services and thereby aid governments in accessing what is required to increase adoption

Toward Perfection: Kapellasite, Cu3Zn(OH)6Cl2, a New Model S = 1/2 Kagome Antiferromagnet

The search for the resonating valence bond (RVB) state continues to underpin many areas of condensed matter research. The RVB is made from the dimerisation of spins on different sites into fluctuating singlets, and was proposed by Anderson to be the reference state from which the transition to BCS superconductivity occurs. Little is known about the state experimentally, due to the scarcity of model materials. Theoretical work has put forward the S = 1/2 kagome antiferromagnet (KAFM) as a good candidate for the realization of the RVB state. In this paper we introduce a new model system, the S = 1/2 KAFM Kapellasite, Cu3Zn(OH)6Cl2. We show that its crystal structure is a good approximation to a 2-dimensional kagome antiferromagnet and that susceptibility data indicate a collapse of the magnetic moment below T = 25 K that is compatible with the spins condensing into the non-magnetic RVB state.Comment: Communication, 3 pages, 3 figure

Expert Finding by Capturing Organisational Knowledge from Legacy Documents

Organisations capitalise on their best knowledge through the improvement of shared expertise which leads to a higher level of productivity and competency. The recognition of the need to foster the sharing of expertise has led to the development of expert finder systems that hold pointers to experts who posses specific knowledge in organisations. This paper discusses an approach to locating an expert through the application of information retrieval and analysis processes to an organization’s existing information resources, with specific reference to the engineering design domain. The approach taken was realised through an expert finder system framework. It enables the relationships of heterogeneous information sources with experts to be factored in modelling individuals’ expertise. These valuable relationships are typically ignored by existing expert finder systems, which only focus on how documents relate to their content. The developed framework also provides an architecture that can be easily adapted to different organisational environments. In addition, it also allows users to access the expertise recognition logic, giving them greater trust in the systems implemented using this framework. The framework were applied to real world application and evaluated within a major engineering company