A5105350782- Biomedical Text Mining and Ontologies
- Fuzzy Logic and Control Systems
- Advanced Database Systems and Queries
- Neural Networks and Applications
- Data Mining Algorithms and Applications
- Topic Modeling
- Semantic Web and Ontologies
- Parallel Computing and Optimization Techniques
- Rough Sets and Fuzzy Logic
- Distributed and Parallel Computing Systems
- Multi-Criteria Decision Making
- Distributed systems and fault tolerance
- Natural Language Processing Techniques
- Stock Market Forecasting Methods
- Data Management and Algorithms
- Service-Oriented Architecture and Web Services
- Fuzzy Systems and Optimization
- Complex Systems and Time Series Analysis
- Financial Markets and Investment Strategies
- Cloud Computing and Resource Management
- Formal Methods in Verification
- Data Stream Mining Techniques
- Data Quality and Management
- Advanced Multi-Objective Optimization Algorithms
- Logic, programming, and type systems
The University of Sydney
2024
University College Cork
2024
University Hospital Waterford
2022-2024
University of Manchester
2013-2022
Cancer Research UK Manchester Institute
2013-2017
Manchester Academic Health Science Centre
2014
University of Ulster
2011-2013
Altnagelvin Area Hospital
2011-2013
University of Birmingham
2011
Alfred Health
2011
Claus Offe is one of the leading social scientists working in Germany today, and his work, particularly on welfare state, has been enormously influential both Europe United States. Contradictions Welfare State first collection Offe's essays to appear a single volume English, it contains selection most important recent work breakdown post-war settlement. The political writings this book are primarily concerned with origins present difficulties - what calls 'crises crisis management'...
A 2 muW, 100 kHz, 480 kb subthreshold SRAM operating at 0.2 V is demonstrated in a 130 nm CMOS process. 10-T cell allows 1 k cells per bitline by eliminating the data-dependent leakage. virtual ground replica scheme proposed for logic "0" level tracking and optimal sensing margin read buffers. Utilizing strong reverse short channel effect region improves writability row decoder performance due to increased current drivability longer length. The sizing method leads an equivalent write...
A 10T SRAM cell with data-independent bitline leakage and a virtual-ground replica scheme allows 1k cells per in subthreshold SRAMs. Reverse short-channel effect is used to improve writability, offer higher speed, reduce junction capacitance, decrease circuit variability. 0.13mum, the 480kb test chip shows minimum operating voltage of 0.20V.
Fuzzy C-means has been utilized successfully in a wide range of applications, extending the clustering capability K-means to datasets that are uncertain, vague and otherwise hard cluster. This paper introduces C-means++ algorithm which, by utilizing seeding mechanism K-means++ algorithm, improves effectiveness speed C-means. By careful disperses initial cluster centers through data space, resulting approach samples starting representatives during initialization phase. The well spread input...
We analyse all Mini Flash Crashes (or Equity Failures) in the US equity markets four most volatile months during 2006-2011. In contrast to previous studies, we find that are result of regulation framework and market fragmentation, particular due aggressive use Intermarket Sweep Orders Regulation NMS protecting only Top Book. strong evidence have an adverse impact on liquidity associated with Fleeting Liquidity.
OBJECTIVE The authors present a system developed for the Challenge in Natural Language Processing Clinical Data-the i2b2 obesity challenge, whose aim was to automatically identify status of and 15 related co-morbidities patients using their clinical discharge summaries. challenge consisted two tasks, textual intuitive. task explicit references diseases, whereas intuitive focused on prediction disease when evidence not explicitly asserted. DESIGN assembled set resources lexically semantically...
Identification of clinical events (eg, problems, tests, treatments) and associated temporal expressions dates times) are key tasks in extracting managing data from electronic health records. As part the i2b2 2012 Natural Language Processing for Clinical Data challenge, we developed evaluated a system to automatically extract narratives. The extracted were additionally normalized by assigning type, value, modifier.The combines rule-based machine learning approaches that rely on morphological,...
Abstract Pairwise comparison (PC) is a well‐established method to assist decision makers (DMs) in estimating their preferences. This paper considers the rationale, design, and evaluation of an open‐source priority estimation tool, PriEsT, which has been developed offer new features related PC method. PriEsT able DMs interactively identifying revising judgments based on different consistency measures graphical aids. When inconsistency cannot be improved due practical limitations, offers wide...
Neurofibromatosis 1 (NF1) is a monogenic model for syndromic autism. Statins rescue the social and cognitive phenotype in animal knockout models, but translational trials with subjects > 8 years using cognition/behaviour outcomes have shown mixed results. This trial breaks new ground by studying statin effects first time younger children NF1 co-morbid autism multiparametric imaging outcomes. A single-site triple-blind RCT of simvastatin vs. placebo was done. Assessment (baseline 12-week...
Derived from practical application in location analysis and pricing, based on the approach of hierarchical structure continuous functions, this paper investigates approximation capabilities fuzzy systems. By first introducing concept natural structure, it is proved that functions with can be naturally effectively approximated by systems to overcome curse dimensionality both number rules parameters. Then, Kolmogorov's theorem, shown any function represented as a superposition then achieve...
The ultimate purpose of a pedestrian-detection system (PDS) is to reduce pedestrian-vehicle-related injury. Most such systems tend adopt expensive sensors, as infrared devices, in expectation better performance. In comparison, low-cost optical-camera-based has much potential practical value, including greater detection range, and can easily be trained detect other objects. However, are difficult design (e.g., little original information collected, the scene very complex). To address these...
During the last decade, neural networks have emerged as one of most powerful and accurate nonlinear models for load forecasting. However, using requires users to in-depth knowledge determine model structure parameters, which limits their wide application. To overcome this weakness, paper proposes an integrated approach combines a self-organizing fuzzy network (SOFNN) learning method with bilevel optimization method. SOFNNs can automatically both while selects best pre-training parameters...
We are constantly being told that we live in the Information Era - Age of BIG data. It is clearly apparent organizations need to employ data-driven decision making gain competitive advantage. Processing, integrating and interacting with more data should make it better data, providing both panoramic granular views aid strategic making. This made possible via Big Data exploiting affordable usable Computational Storage Resources. Many offerings based on Map-Reduce Hadoop paradigms most focus...
Effective Big Data Mining requires scalable and efficient solutions that are also accessible to users of all levels expertise. Despite this, many current efforts provide effective knowledge extraction via large-scale tools focus more on performance than use tuning which complex problems even for experts. Weka is a popular comprehensive workbench with well-known intuitive interface, nonetheless it supports only sequential single-node execution. Hence, the size datasets processing tasks can...
A recent promise to access unstructured clinical data from electronic health records on large-scale has revitalized the interest in automated de-identification of notes, which includes identification mentions Protected Health Information (PHI). We describe methods developed and evaluated as part i2b2/UTHealth 2014 challenge identify PHI defined by 25 entity types longitudinal narratives. Our approach combines knowledge-driven (dictionaries rules) data-driven (machine learning) with a large...
Objective: This study presents a system developed for the 2009 i2b2 Challenge in Natural Language Processing Clinical Data, whose aim was to automatically extract certain information about medications used by patient from his/her medical report. The following each medication: name, dosage, mode/route, frequency, duration and reason. Design: implements rule-based methodology, which exploits typical morphological, lexical, syntactic semantic features of targeted information. These were...
Data wrangling, the multi-faceted process by which data required an application is identified, extracted, cleaned and integrated, often cumbersome labor intensive. In this paper, we present architecture that supports a complete wrangling lifecycle, orchestrates components dynamically, builds on automation wherever possible, informed whatever available, refines automatically produced results in light of feedback, takes into account user's priorities, scientists with diverse skill sets. The...