Dynamic pattern matcher using incomplete data

This invention relates generally to pattern matching systems, and more particularly to a method for dynamically adapting the system to enhance the effectiveness of a pattern match. Apparatus and methods for calculating the similarity between patterns are known. There is considerable interest, however, in the storage and retrieval of data, particularly, when the search is called or initiated by incomplete information. For many search algorithms, a query initiating a data search requires exact information, and the data file is searched for an exact match. Inability to find an exact match thus results in a failure of the system or method

Recently published papers: Heavyweight problems in the intensive care unit?

The management of the obese patient in intensive care is fraught with difficulty, or so conventional wisdom would have us believe. Two recent studies add to the growing evidence that the obese patient is not significantly disadvantaged in terms of outcome following intensive care admission. Another study highlights the increasing burden of end-stage renal disease on intensive care unit resources with some interesting results. And there is more on citrate, the new anticoagulant

Recently published papers: Delivery, volume and outcome – what is best for our patient?

Many studies have demonstrated that prompt appropriate treatment for the critically ill patient improves outcome. Moving patients to the best place for instituting care, however, is not always associated with improved outcome. Recent studies on delivering patients to the best place for treatment as well as further work on the effects of volume are discussed. Finally, a large retrospective cohort study comparing outcomes of patients treated with continuous venovenous haemofiltration or intermittent haemodialysis is outlined

Clinical review: Timing of renal replacement therapy

Acute kidney injury is common in intensive care patients and continuous renal replacement therapy is the preferred treatment for this in most centres. Although these techniques have been adopted internationally, there remains significant variation with regard to their clinical application. This is particularly pertinent when one considers that the fundamental questions regarding any treatment, such as initiation, dose and length of treatment, remain a source of debate and have not as yet all been fully answered. In this narrative review we consider the timing of renal replacement therapy, highlighting the relative paucity of high quality data regarding this fundamental question. We examine the role of the usual biochemical criteria as well as conventional clinical indications for commencing renal replacement therapy together with the application of recent classification systems, namely RIFLE and AKIN. We discuss the potential role of biomarkers for acute kidney injury as predictors for the need for renal support and discuss commencing therapy for indications other than acute kidney injury

Simultaneous structural and control optimization via linear quadratic regulator eigenstructure assignment

A method for simultaneous structural and control design of large flexible space structures (LFSS) to reduce vibration generated by disturbances is presented. Desired natural frequencies and damping ratios for the closed loop system are achieved by using a combination of linear quadratic regulator (LQR) synthesis and numerical optimization techniques. The state and control weighing matrices (Q and R) are expressed in terms of structural parameters such as mass and stiffness. The design parameters are selected by numerical optimization so as to minimize the weight of the structure and to achieve the desired closed-loop eigenvalues. An illustrative example of the design of a two bar truss is presented

Artificial intelligence and augmented intelligence collaboration: Regaining trust and confidence in the financial sector

Robots and chatbots are sophisticated. Artificial intelligence (AI) is increasingly popular in the financial industry due to its ability to provide customers with cheap, efficient and personalised services. This article uses doctrinal sources and a case study to show that many banks and FinTech start-ups are investing in AI. Yet, there are a number of challenges arising from the use of AI which could undermine trust and confidence amongst consumers. This article features the issue of bias and discrimination in banking. There is evidence that algorithms discriminate against certain races and gender. Legislative gaps in the Equality Act 2010 and the General Data Protection Regime will be analysed. Ultimately, human beings are still needed to input, train and help machines to learn. Fortunately, the FCA are leading in regulating technology, from the launch of regulatory sandboxes to their co-operative collaboration with FinTech start-ups on regulatory matters. Augmented intelligence collaboration is needed to enable industry players and regulators to provide seamless regulation and financial stability. The future of AI regulation is inter-disciplinary in approach