Debt detection and debt recovery with advanced classification techniques

University of Technology Sydney. Faculty of Engineering and Information Technology.My study is part of an ARC linkage project between University of Technology, Sydney and Centrelink Australia, which aims to applying data mining techniques to optimise the debt detection and debt recovery. A debt indicates an overpayment made by the government to a customer who is not entitled to that payment. In social security, an interaction between a customer and the government department is recorded as an activity. Each customer’s activities happen sequentially along the time, which can be regarded as a sequence. Based on the experience of debt detection experts, there are usually some patterns in the sequence of activities of customers who commit debts. The patterns indicating the customers’ intention to be overpaid can thus be used to discover or predict debt occurrence. The development of debt detection and recovery over sequential transaction data, however, is a challenging problem due to following reasons. (1) The size of transaction data is vast, and the transaction data are being generated continuously as the business goes on. (2) Transaction data are always time stamped by the business system, and the temporal order of the transaction data is highly related to the business logic. (3) The patterns and relationships hidden behind the transaction data may be affected by a lot of factors. They are not only dependent on business domain knowledge, but also subject to seasonal and social factors outside the business. Based on a survey of existing methods on debt detection and recovery, data mining techniques are studied in this thesis to detect and recovery debt in an adaptive and efficient fashion. Firstly, sequence data is used to model the evolvement of customer activities, and the sequential patterns generalize the trends of sequences. For long running sequence classification issues, even if the sequences come from the same source, the sequential patterns may vary from time to time. An adaptive sequential classification model is to be built to make the sequence classification adapt to the sequential pattern variation. The model is applied to 15,931 activity sequences from Centrelink which includes 849,831 activity records. The experimental results show that the proposed adaptive sequence classification framework performs effectively on the continuously arriving data. Secondly, a new technique of sequence classification using both positive and negative patterns is to be studied, which is able to find the relationship between activity sequences and debt occurrences and also the impact of oncoming activities on the debt occurrence. The same dataset is used for the evaluation. The outcome shows if built with the same number of rules, in terms of recall, the classifier built with both positive and negative rules outperforms traditional classifiers with only positive rules under most conditions. Finally, decision trees are to be built in the thesis to model debt recovery and predict the response of customers if contacted by phone. The customer contact strategy driven by the model aims to improve the efficiency of debt recovery process. The model is utilized in a real life pilot project for debt recovery in Centrelink. The pilot result outperforms the traditional random customer selection. In summary, this thesis studies debt detection and debt recovery in social security using data mining techniques. The proposed models are novel and effective, showing potentials in real business

Influence of ferromagnetic spin waves on persistent currents in one-dimensional mesoscopic rings

The influence of the electron-magnon and the electron-phonon interactions on the persistent current in a one-dimensional mesoscopic ring is studied. We show that, due to the electron-magnon interaction, the amplitude of the persistent current is exponentially reduced compared to the free case. Two features occur in the presence of an electron-phonon interaction. For the normal state of electrons, the persistent current is weakened by the Debye-Waller factor. Considering the so-called Peierls distortions, we show that the effect of the Peierls instability on the amplitude of the persistent current (i.e., the oscillation with respect to the flux) is suppressed significantly and the persistent current will be practically undetectable in the case of a wide-gap Peierls material. © 1996 The American Physical Society.published_or_final_versio

State-independent error-disturbance trade-off for measurement operators

postprin

Dipole Coupling Effect of Holographic Fermion in the Background of Charged Gauss-Bonnet AdS Black Hole

We investigate the holographic fermions in the charged Gauss-Bonnet $AdS_{d}$ black hole background with the dipole coupling between fermion and gauge field in the bulk. We show that in addition to the strength of the dipole coupling, the spacetime dimension and the higher curvature correction in the gravity background also influence the onset of the Fermi gap and the gap distance. We find that the higher curvature effect modifies the fermion spectral density and influences the value of the Fermi momentum for the appearance of the Fermi surface. There are richer physics in the boundary fermion system due to the modification in the bulk gravity.Comment: 16 pages, accepted for publication in JHE

Magnetoresistance in La- and Ca-doped YBa2Cu3O7–δ

We studied the microstructures, electronic, and magnetic properties on La-doped and La- and Ca-codoped YBa2Cu3O7−δ (YBCO). The superconducting transition temperature remains unchanged up to 10% for La-doped YBCO. The competition between electrons and holons was assumed according to the variation of Tc0 in La and Ca codopings in YBCO. The magnetoresistance (MR) effect is about 8%, which is observed obviously near the critical temperature and is independent of the content of La in La-doped YBCO. MR increases up to about 40% with the incorporation of Ca in La-doped YBCO. We present here possible explanations for the magnetoresistance effect in polycrystalline samples based on the microstructure and the increase of oxygen vacancies at grain-boundary interface. © 2006 American Institute of Physicspublished_or_final_versio

Microstructures and resistivity of cuprate/manganite bilayer deposited on SrTiO3 substrate

Thin Yba[SUB2]Cu[SUB3]O[SUB7-δ/La[SUB0.67]Ca[SUB0.33]MnO[SUB3] (YBCO/LCMO) films were grown on SrTiO[SUB3](STO)substrates by magnetron sputtering technique. The microstructures of the bilayers were characterized and a standard four-probe technique was applied to measure the resistivity of the samples. The interdiffusions at the YBCO/LCMO and LCMO/STO interfaces formed two transient layers with the thickness of about 3 and 2 nm, respectively. All the bilayers were well textured along the c axis. At low temperature, the superconductivity can only be observed when the thickness of YBCO is more than 25 nm. When the thickness of YBCO is less than 8 nm, the bilayers show only ferromagnetism. The superconductivity and ferromagnetism perhaps coexist in the bilayer with the YBCO thickness of 12.5 nm. These interesting properties are related to the interaction between spin polarized electrons in the manganites and the cooper pairs in the cuprates. © 2003 American Institute of Physics.published_or_final_versio

Oral health status of asthmatic preschoolers in Hong Kong

published_or_final_versio

Breath-hold FSE for accurate imaging of myocardial and hepatic R2

Session 21: Hepatic Storage Disease - Oral presentationMRI provides a means to non-invasively assess tissue iron concentration by exploiting the paramagnetic effects of iron on T2 or T2*. The most widely used method is T2* imaging is sensitive to non-iron related magnetic field (B0) inhomogeneities, which can confound T2* measurements within the whole heart and liver. An alternative method is T2 imaging, but they are generally performed during free breathing with respiratory gating due to their low data acquisition efficiency. The purpose of this study was to develop a breath-hold fast spin echo (FSE) sequence for fast and accurate imaging of myocardial and hepatic T2.published_or_final_versionThe 17th Scientific Meeting & Exhibition of the International Society of Magnetic Resonance in Medicine (ISMRM), Honolulu, HI., 18-24 April 2009. In Proceedings of ISMRM 17th Scientific Meeting & Exhibition, 2009, p. 20

A breakthrough biosorbent in removing heavy metals: Equilibrium, kinetic, thermodynamic and mechanism analyses in a lab-scale study

© 2015 Elsevier B.V. A breakthrough biosorbent namely multi-metal binding biosorbent (MMBB) made from a combination of tea wastes, maple leaves and mandarin peels, was prepared to evaluate their biosorptive potential for removal of Cd(II), Cu(II), Pb(II) and Zn(II) from multi-metal aqueous solutions. FTIR and SEM were conducted, before and after biosorption, to explore the intensity and position of the available functional groups and changes in adsorbent surface morphology. Carboxylic, hydroxyl and amine groups were found to be the principal functional groups for the sorption of metals. MMBB exhibited best performance at pH. 5.5 with maximum sorption capacities of 31.73, 41.06, 76.25 and 26.63. mg/g for Cd(II), Cu(II), Pb(II) and Zn(II), respectively. Pseudo-first and pseudo-second-order models represented the kinetic experimental data in different initial metal concentrations very well. Among two-parameter adsorption isotherm models, the Langmuir equation gave a better fit of the equilibrium data. For Cu(II) and Zn(II), the Khan isotherm describes better biosorption conditions while for Cd(II) and Pb(II), the Sips model was found to provide the best correlation of the biosorption equilibrium data. The calculated thermodynamic parameters indicated feasible, spontaneous and exothermic biosorption process. Overall, this novel MMBB can effectively be utilized as an adsorbent to remove heavy metal ions from aqueous solutions

R2 imaging of ferritin iron in thalassaemia patients off and on iron-chelation therapy

Myocardial Tissue Characterization: Fat, Hemorrhage & Edema - Poster presentationAccurate assessment of iron burden is crucial for the management of iron-chelation therapy. MRI provides a means to non-invasively assess tissue iron concentration by exploiting the paramagnetic effects of iron on the relaxation rates of solvent protons. The most widely used method is R2* imaging, which has been shown to be sensitive to myocardial iron overload. Recently, a breath-hold fast spin echo sequence has been proposed for fast and accurate imaging of myocardial and hepatic R2. The purpose of this study was to determine which relaxation rates are sensitive to iron-chelation therapy.published_or_final_versionThe 17th Scientific Meeting & Exhibition of the International Society of Magnetic Resonance in Medicine (ISMRM), Honolulu, HI., 18-24 April 2009. In Proceedings of ISMRM 17th Scientific Meeting & Exhibition, 2009, p. 375