LRD : Latent Relation Discovery for vector space expansion and information retrieval

In this paper, we propose a text mining method called LRD (latent relation discovery), which extends the traditional vector space model of document representation in order to improve information retrieval (IR) on documents and document clustering. Our LRD method extracts terms and entities, such as person, organization, or project names, and discovers relationships between them by taking into account their co-occurrence in textual corpora. Given a target entity, LRD discovers other entities closely related to the target effectively and efficiently. With respect to such relatedness, a measure of relation strength between entities is defined. LRD uses relation strength to enhance the vector space model, and uses the enhanced vector space model for query based IR on documents and clustering documents in order to discover complex relationships among terms and entities. Our experiments on a standard dataset for query based IR shows that our LRD method performed significantly better than traditional vector space model and other five standard statistical methods for vector expansion.

Structural funds and the knowledge-based economy:a regional case-study (1999-2009)

The research presented in this thesis investigates the nature of the relationship between the development of the Knowledge-Based Economy (KBE) and Structural Funds (SF) in European regions. A particular focus is placed on the West Midlands (UK) and Silesia (Poland). The time-frame taken into account in this research is the years 1999 to 2009. This is methodologically addressed by firstly establishing a new way of calculating the General Index of the KBE for all of the EU regions; secondly, applying a number of statistical methods to measure the influence of the Funds on the changes in the regional KBE over time; and finally, by conducting a series of semi-structured stakeholder interviews in the two key case study regions: the West Midlands and Silesia. The three main findings of the thesis are: first, over the examined time-frame, the values of the KBE General Index increased in over 66% of the EU regions; furthermore, the number of the “new” EU regions in which the KBE increased over time is far higher than in the “old” EU. Second, any impact of Structural Funds on the regional KBE occurs only in the minority of the European regions and any form of functional dependency between the two can be observed only in 30% of the regions. Third, although the pattern of development of the regional KBE and the correlation coefficients differ in the cases of Silesia and the West Midlands, the analysis of variance carried out yields identical results for both regions. Furthermore, the qualitative analysis’ results show similarities in the approach towards the Structural Funds in the two key case-study regions.

Premonitory urges for tics in adult patients with Tourette syndrome

Objective: Patients with Tourette syndrome (TS) often report characteristic sensory experiences, also called premonitory urges (PUs), which precede tic expression and have high diagnostic relevance. This study investigated the usefulness of a scale developed and validated in children and adolescents-the Premonitory Urge for Tics Scale (PUTS, Woods et al., 2005 [13])-for the assessment of PUs in adult patients with TS. Method: Standard statistical methods were applied to test the psychometric properties of the PUTS in 102 adult TS outpatients recruited from two specialist clinics in the United Kingdom. Results: The PUTS showed good acceptability and endorsement rates, with evenly distributed scores and low floor and ceiling effects. Item-total correlations were moderate to strong; PUTS total scores were significantly correlated with quantitative measures of TS severity. The PUTS showed excellent internal consistency reliability (Cronbach's alpha=0.85) and Spearman's correlations demonstrated satisfactory convergent and discriminant validity. Conclusions: Although originally devised to assess urges to tic in young patients with TS, the PUTS demonstrated good psychometric properties in a large sample of adults recruited at specialist TS clinics. This instrument is therefore recommended for use across the life span as a valid and reliable self-report measure of sensory experiences accompanying tic expression. © 2013 The Japanese Society of Child Neurology.

Guiding local regression using visualisation

Solving many scientific problems requires effective regression and/or classification models for large high-dimensional datasets. Experts from these problem domains (e.g. biologists, chemists, financial analysts) have insights into the domain which can be helpful in developing powerful models but they need a modelling framework that helps them to use these insights. Data visualisation is an effective technique for presenting data and requiring feedback from the experts. A single global regression model can rarely capture the full behavioural variability of a huge multi-dimensional dataset. Instead, local regression models, each focused on a separate area of input space, often work better since the behaviour of different areas may vary. Classical local models such as Mixture of Experts segment the input space automatically, which is not always effective and it also lacks involvement of the domain experts to guide a meaningful segmentation of the input space. In this paper we addresses this issue by allowing domain experts to interactively segment the input space using data visualisation. The segmentation output obtained is then further used to develop effective local regression models.

Quantitative online prediction of peptide binding to the major histocompatibility complex

With its implications for vaccine discovery, the accurate prediction of T cell epitopes is one of the key aspirations of computational vaccinology. We have developed a robust multivariate statistical method, based on partial least squares, for the quantitative prediction of peptide binding to major histocompatibility complexes (MHC), the principal checkpoint on the antigen presentation pathway. As a service to the immunobiology community, we have made a Perl implementation of the method available via a World Wide Web server. We call this server MHCPred. Access to the server is freely available from the URL: http://www.jenner.ac.uk/MHCPred. We have exemplified our method with a model for peptides binding to the common human MHC molecule HLA-B*3501.

MHCPred : a server for quantitative prediction of peptide-MHC binding

Accurate T-cell epitope prediction is a principal objective of computational vaccinology. As a service to the immunology and vaccinology communities at large, we have implemented, as a server on the World Wide Web, a partial least squares-base multivariate statistical approach to the quantitative prediction of peptide binding to major histocom-patibility complexes (MHC), the key checkpoint on the antigen presentation pathway within adaptive,cellular immunity. MHCPred implements robust statistical models for both Class I alleles (HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203,HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3301, HLA-A*6801, HLA-A*6802 and HLA-B*3501) and Class II alleles (HLA-DRB*0401, HLA-DRB*0401and HLA-DRB* 0701).

Entropy Based Approach to Finding Interacting Genes Responsible for Complex Human Disease

2000 Mathematics Subject Classification: 62P10, 92D10, 92D30, 94A17, 62L10.

Probabilistic Approach to Design of Large Antenna Arrays

2000 Mathematics Subject Classification: 78A50

Monte Carlo Method for Reconstruction of Densities

2000 Mathematics Subject Classification: 65C05

Multiple Dipole Source Models for Scalp-Recorded Event-Related Potentials: Example from Complex Visual Processing in the Human Brain

2000 Mathematics Subject Classification: 62P10, 92C20

Classification of Paintings by Artist, Movement, and Indoor Setting Using MPEG-7 Descriptor Features

ACM Computing Classification System (1998): I.4.9, I.4.10.

Does money matter in inflation forecasting?

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two nonlinear techniques, namely, recurrent neural networks and kernel recursive least squares regressiontechniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a nave random walk model. The best models were nonlinear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. Beyond its economic findings, our study is in the tradition of physicists' long-standing interest in the interconnections among statistical mechanics, neural networks, and related nonparametric statistical methods, and suggests potential avenues of extension for such studies. © 2010 Elsevier B.V. All rights reserved.

Identifying spatially overlapping local cortical networks with MEG

Recent modelling studies (Hadjipapas et al. [2009]: Neuroimage 44:1290-1303) have shown that it may be possible to distinguish between different neuronal populations on the basis of their macroscopically measured (EEG/MEG) mean field. We set out to test whether the different orientation columns contributing to a signal at a specific cortical location could be identified based on the measured MEG signal. We used 1.5deg square, static, obliquely oriented grating stimuli to generate sustained gamma oscillations in a focal region of primary visual cortex. We then used multivariate classifier methods to predict the orientation (left or right oblique) of the stimuli based purely on the time-series data from this one location. Both the single trial evoked response (0-300 ms) and induced post-transient power spectra (300-2,300 ms, 20-70 Hz band) due to the different stimuli were classifiable significantly above chance in 11/12 and 10/12 datasets respectively. Interestingly, stimulus-specific information is preserved in the sustained part of the gamma oscillation, long after perception has occurred and all neuronal transients have decayed. Importantly, the classification of this induced oscillation was still possible even when the power spectra were rank-transformed showing that the different underlying networks give rise to different characteristic temporal signatures. © 2009 Wiley-Liss, Inc.

A Public-Private Partnership vélt és valós hangsúlyai Magyarországon = Assumed and actual emphases of Public-Private Partnership in Hungary

Írásunk a Public-Private Partnership (PPP) magyarországi megvalósulásának hangsúlyairól szól. Azt vizsgáljuk, hogy a szakmai közvélemény milyen képet alakíthatott ki e projektekről a szaksajtó olvasásán keresztül. Három tágabb elvi szempont sajtóbeli megjelenésének súlyát elemezzük: a PPP céljai, a feladatok hatékonyabb elvégzésének módja, illetve a társadalmi kontroll megvalósulása áll érdeklődésünk középpontjában. A tartalomelemzés matematikai-statisztikai módszereit alkalmazzuk. Következtetésünk, hogy a PPP-projektek általában még nem elvi lényegük szerint valósultak meg Magyarországon, bár az évek során érzékelhető pozitív irányú elmozdulás: tanulási folyamat történik. Ennek alapján nem szabad a PPP-t mint módszert elvetni a közfeladatok ellátásában, hanem alkalmazási módjának tökéletesítésére kell törekedni. = This working paper focuses on the perceptions of the Hungarian implementation of Public-Private Partnership (PPP) projects. It was examined how PPP was perceived in the wider public through the communication of the most read daily and weekly business journals. We analyzed the proportion of three broad aspects in the articles: the main goals of PPP, efficiency improvement as a substantial opportunity for value creation, and the role of democratic control. We applied the mathematical-statistical methods of content analysis. Our conclusion is that PPP-projects in Hungary are far from the normative model of implementation as discerned from literature, but from year to year a positive shift, a learning process can be observed. Therefore, instead of discarding PPP as a progressive government solution, Hungary should focus on improving the design and implementation of PPP projects.

Macroeconomic characteristics and inventory investment: a multi-country study

The paper is a new element in a series of studies analyzing macroeconomic inventory behavior by use of multi-country data. In this paper, seven hypotheses are tested with positive result. These hypotheses include subjects like relations of inventories with growth and with some other macroeconomic indicators of the use of GDP and the long-term tendencies of global inventory formations. Multivariate statistical analysis is used for evaluation.