Supervised Aggregative Feature Extraction for Big Data Time Series Regression

In many applications, and especially those where batch processes are involved, a target scalar output of interest is often dependent on one or more time series of data. With the exponential growth in data logging in modern industries such time series are increasingly available for statistical modeling in soft sensing applications. In order to exploit time series data for predictive modelling, it is necessary to summarise the information they contain as a set of features to use as model regressors. Typically this is done in an unsupervised fashion using simple techniques such as computing statistical moments, principal components or wavelet decompositions, often leading to significant information loss and hence suboptimal predictive models. In this paper, a functional learning paradigm is exploited in a supervised fashion to derive continuous, smooth estimates of time series data (yielding aggregated local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The proposed Supervised Aggregative Feature Extraction (SAFE) methodology can be extended to support nonlinear predictive models by embedding the functional learning framework in a Reproducing Kernel Hilbert Spaces setting. SAFE has a number of attractive features including closed form solution and the ability to explicitly incorporate first and second order derivative information. Using simulation studies and a practical semiconductor manufacturing case study we highlight the strengths of the new methodology with respect to standard unsupervised feature extraction approaches.

Determinants of pediatric cataract program outcomes and follow-up in a large series in Mexico.

PURPOSE:

To report determinants of outcomes and follow-up in a large Mexican pediatric cataract project.

SETTING:

Hospital Luis Sanchez Bulnes, Mexico City, Mexico.

METHODS:

Data were collected prospectively from a pediatric cataract surgery program at the Hospital Luis Sanchez Bulnes, implemented by Helen Keller International. Preoperative data included age, sex, baseline visual acuity, type of cataract, laterality, and presence of conditions such as amblyopia. Surgical data included vitrectomy, capsulotomy, complications, and use of intraocular lenses (IOLs). Postoperative data included final visual acuity, refraction, number of follow-up visits, and program support for follow-up.

RESULTS:

Of 574 eyes of 415 children (mean age 7.1 years +/- 4.7 [SD]), IOLs were placed in 416 (87%). At least 1 follow-up was attended by 408 patients (98.3%) (mean total follow-up 3.5 +/- 1.8 months); 40% of eyes achieved a final visual acuity of 6/18 or better. Children living farther from the hospital had fewer postoperative visits (P = .04), while children receiving program support had more visits (P = .001). Factors predictive of better acuity included receiving an IOL during surgery (P = .04) and provision of postoperative spectacles (P = .001). Predictive of worse acuity were amblyopia (P = .003), postoperative complications (P = .0001), unilateral surgery (P = .0075), and female sex (P = .045).

CONCLUSIONS:

The results underscore the importance of surgical training in reducing complications, early intervention before amblyopia (observed in 40% of patients) can develop, and vigorous treatment if amblyopia is present. The positive impact of program support on follow-up is encouraging, although direct financial support may pose a problem for sustainability. More work is needed to understand reasons for worse outcomes in girls.

Parallel Time Series Analysis and Income Inequality: A New Approach to Comparative Case Studies

This case study deals with the role of time series analysis in sociology, and its relationship with the wider literature and methodology of comparative case study research. Time series analysis is now well-represented in top-ranked sociology journals, often in the form of ‘pooled time series’ research designs. These studies typically pool multiple countries together into a pooled time series cross-section panel, in order to provide a larger sample for more robust and comprehensive analysis. This approach is well suited to exploring trans-national phenomena, and for elaborating useful macro-level theories specific to social structures, national policies, and long-term historical processes. It is less suited however, to understanding how these global social processes work in different countries. As such, the complexities of individual countries - which often display very different or contradictory dynamics than those suggested in pooled studies – are subsumed. Meanwhile, a robust literature on comparative case-based methods exists in the social sciences, where researchers focus on differences between cases, and the complex ways in which they co-evolve or diverge over time. A good example of this is the inequality literature, where although panel studies suggest a general trend of rising inequality driven by the weakening power of labour, marketisation of welfare, and the rising power of capital, some countries have still managed to remain resilient. This case study takes a closer look at what can be learned by applying the insights of case-based comparative research to the method of time series analysis. Taking international income inequality as its point of departure, it argues that we have much to learn about the viability of different combinations of policy options by examining how they work in different countries over time. By taking representative cases from different welfare systems (liberal, social democratic, corporatist, or antipodean), we can better sharpen our theories of how policies can be more specifically engineered to offset rising inequality. This involves a fundamental realignment of the strategy of time series analysis, grounding it instead in a qualitative appreciation of the historical context of cases, as a basis for comparing effects between different countries.

Optimal alarms systems and its application to financial time series

This thesis focuses on the application of optimal alarm systems to non linear time series models. The most common classes of models in the analysis of real-valued and integer-valued time series are described. The construction of optimal alarm systems is covered and its applications explored. Considering models with conditional heteroscedasticity, particular attention is given to the Fractionally Integrated Asymmetric Power ARCH, FIAPARCH(p; d; q) model and an optimal alarm system is implemented, following both classical and Bayesian methodologies. Taking into consideration the particular characteristics of the APARCH(p; q) representation for financial time series, the introduction of a possible counterpart for modelling time series of counts is proposed: the INteger-valued Asymmetric Power ARCH, INAPARCH(p; q). The probabilistic properties of the INAPARCH(1; 1) model are comprehensively studied, the conditional maximum likelihood (ML) estimation method is applied and the asymptotic properties of the conditional ML estimator are obtained. The final part of the work consists on the implementation of an optimal alarm system to the INAPARCH(1; 1) model. An application is presented to real data series.

Integer-valued APARCH processes in the analysis of time series of counts

The Asymmetric Power Arch representation for the volatility was introduced by Ding et al.(1993) in order to account for asymmetric responses in the volatility in the analysis of continuous-valued financial time series like, for instance, the log-return series of foreign exchange rates, stock indices or share prices. As reported by Brannas and Quoreshi (2010), asymmetric responses in volatility are also observed in time series of counts such as the number of intra-day transactions in stocks. In this work, an asymmetric power autoregressive conditional Poisson model is introduced for the analysis of time series of counts exhibiting asymmetric overdispersion. Basic probabilistic and statistical properties are summarized and parameter estimation is discussed. A simulation study is presented to illustrate the proposed model. Finally, an empirical application to a set of data concerning the daily number of stock transactions is also presented to attest for its practical applicability in data analysis.

The Ethical Gold series

A series of five articles, published over six months in 2010, which explained the key ethical issues relating to sourcing gold. The Ethical Gold Series was written for practising jewellers, industrial jewellery manufacturers and the wider design community. The Ethical Gold Series was published in the Benchpeg Newsletter, an online jewellery industry journal, which in 2010 had over 5,500 subscribers. The material for the articles was drawn from a year of ethnographic fieldwork in the UK jewellery sector, funded by the AHRC, and field visits to preserved, operating and proposed gold mining sites in Alaska, California, Sweden, Wales and Scotland. The ethnographic fieldwork included ‘ethical gold’ promotional events, private industry meetings and jewellery trade shows and meetings with jewellery manufacturers and retailers, assayers, gold refiners and traders and environmental and fair trade campaigners.

Case-series Evaluating a Transdiagnostic Cognitive-behavioral Treatment For Co-occurring Anxiety Disorders.

Background. Patients with anxiety disorder diagnoses commonly have more than one anxiety diagnosis. While cognitive-behavioral interventions have proven efficacy in treating single anxiety disorder diagnoses, there has been little investigation of their efficacy in treating cooccurring anxiety disorders. Aims. To evaluate the efficacy of a transdiagnostic cognitive-behavioral intervention for treating co-occurring anxiety disorders. Methods. An A-B single case study design (N = 6) was used to evaluate the efficacy of a 12 to 13 session modular transdiagnostic cognitive-behavioral intervention for treating co-occurring anxiety disorders across patients with at least two of the following diagnoses: GAD, Social Phobia, Panic Disorder and/or OCD. Results. Five of the six participants completed treatment. At post-treatment assessment the five treatment completers achieved diagnostic and symptomatic change with three participants being diagnosis free. All participants who completed treatment no longer met criteria for any DSM-IV-TR Axis-I diagnosis at the three-month follow-up assessment, and demonstrated reliable and clinically-significant improvements in symptoms. Across the participants, statistically significant improvements from pre- to post-intervention were found on measures of anxiety, depression and general well-being, and all improvements were maintained at three-month follow-up. Conclusions. Results suggest that transdiagnostic cognitive behavioral interventions can be of benefit to patients with co-occurring anxiety disorders.

Introduction to the Transforming Dementia Care in Hospitals Series

A short series of articles in Nursing Older People, starting in September, presents case study examples of the positive work achieved by trusts that participated in the RCN’s development programme to improve dementia care in acute hospitals. This introductory article reports on the independent evaluation of the programme. The programme included a launch event, development days, site visits, ongoing support by the RCN lead and carer representatives and a conference to showcase service improvements. The evaluation drew on data from a survey, the site visits, trust action plans and a range of self-assessment tools for dementia care. The findings highlight substantial progress towards programme objectives and learning outcomes and suggest that the programme provided the focus, impetus and structure for trusts to make sustainable changes. It also equipped participants with the strategies and confidence to change practice. Recommendations are made for taking the programme forward.

Music of Today Series, Garth Knox, October 22, 2013

Concert Program for Music of Today, Garth Knox, October 22, 2013

Music of Today Series, UW Modern Ensemble, Inverted Space, "Music by Luigi Nono," February 25, 2014

Concert Program for Music of Today Series, UW Modern Ensemble, Inverted Space, Andre Richard, February 25, 2014

Music of Today Series, UW Modern Ensemble, May 19, 2014

Concert Program for Music of Today Series, UW Modern Ensemble, May 19, 2014