Nowadays, the future development of new industrial robots (parts of machine tools and manipulators) requires also improvement and development of their control. In essence, it means a replacement of existing conventional control approaches (e.g. NC systems, PID/PSD control structures) by new approaches, which enable as much as possible to use available information on properties and behavior of g...

A newborn foal was presented because it was unresponsive and in cardiopulmonary arrest. Aggressive cardiopulmonary cerebral resuscitation was administered to the foal, which revived the foal; however, acute renal failure developed. Fluid retention and azotemia occurred although the foal was alert and able to suckle. A 6-hour renal replacement therapy session using hemodiafiltration and a contin...

This article reports the conclusions of a consensus expert conference on the basic principles and nomenclature of renal replacement therapy (RRT) currently utilized to manage acute kidney injury (AKI). This multidisciplinary consensus conference discusses common definitions, components, techniques, and operations of the machines and platforms used to deliver extracorporeal therapies, utilizing ...

Randomized algorithms that base iteration-level decisions on samples from some pool are ubiquitous in machine learning and optimization. Examples include stochastic gradient descent and randomized coordinate descent. This paper makes progress at theoretically evaluating the difference in performance between sampling withand without-replacement in such algorithms. Focusing on least means squares...

Face replacement system plays an important role in the entertainment industries. However, most of these systems nowadays are assisted by hand and specific tools. In this paper, a new face replacement system for automatically replacing a face with image processing technique is described. The system is divided into two main parts: facial feature extraction and face pose estimation. In the first p...

Randomized algorithms that base iteration-level decisions on samples from some pool are ubiquitous in machine learning and optimization. Examples include stochastic gradient descent and randomized coordinate descent. This paper makes progress at theoretically evaluating the difference in performance between sampling withand without-replacement in such algorithms. Focusing on least means squares...

Stochastic gradient methods for machine learning and optimization problems are usually analyzed assuming data points are sampled with replacement. In contrast, sampling without replacement is far less understood, yet in practice it is very common, often easier to implement, and usually performs better. In this paper, we provide competitive convergence guarantees for without-replacement sampling...

(A) Explain how the tools of statistical learning (Bayesian or otherwise) might be useful in thinking about paradigm shifts in science. Is a paradigm shift just the replacement of one model or hypothesis by another, or does it involve something more? (B) What would be the analogy of a Kuhnian paradigm shift in human learning or machine learning? Give at least one specific example of a phenomeno...

Existing tools for generating phrase tables for phrase-based Statistical Machine Translation (SMT) are generally optimised towards low memory use to allow processing of large corpora with limited memory. Whilst being a reasonable design choice, this approach does not make optimal use of resources when the sufficient memory is available. We present memscore, a new open-source tool to score phras...

This note proposes a different approach to the Form Machine. Specifically, we describe a syntax-driven interpreter that operates on a grammar which is an ordered set of replacement rules. Following the interpreter description are some "real-world" examples of required data reconfigurations that must occur between RAND consoles and the Remote Job System on the UCLA 360/91. Lastly, we suggest tha...