Regeneration with virtual copies for distributed computing systems

The authors consider the consistency control problem for replicated data in a distributed computing system (DCS) and propose a new algorithm to dynamically regenerate copies of data objects in response to node failures and network partitioning in the system. The DCS is assumed to have strict consistency constraints for data object copies. The algorithm combines the advantages of voting-based algorithms and regeneration mechanisms to maintain mutual consistency of replicated data objects in the case of node failures and network partitioning. The algorithm extends the feasibility of regeneration to DCS on wide area networks and is able to satisfy user queries as long as there is one current partition in the system. A stochastic availability analysis of the algorithm shows that it provides improved availability as compared to previously proposed dynamic voting algorithms     

Generalized adaptive notch filters with frequency debiasing for tracking of polynomial phase systems

Generalized adaptive notch filters are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. For general patterns of frequency variation the generalized adaptive notch filtering algorithms yield biased frequency estimates. We show that when system frequencies change slowly in a smooth way, the estimation bias can be substantially reduced by means of post-filtering of the frequency estimates. The modified (debiased) algorithm has better tracking capabilities than the original algorithm.     

Overcoming intuition: Metacognitive difficulty activates analytic reasoning.

Humans appear to reason using two processing styles: System 1 processes that are quick, intuitive, and effortless and System 2 processes that are slow, analytical, and deliberate that occasionally correct the output of System 1. Four experiments suggest that System 2 processes are activated by metacognitive experiences of difficulty or disfluency during the process of reasoning. Incidental experiences of difficulty or disfluency--receiving information in a degraded font (Experiments 1 and 4), in difficult-to-read lettering (Experiment 2), or while furrowing one's brow (Experiment 3)--reduced the impact of heuristics and defaults in judgment (Experiments 1 and 3), reduced reliance on peripheral cues in persuasion (Experiment 2), and improved syllogistic reasoning (Experiment 4). Metacognitive experiences of difficulty or disfluency appear to serve as an alarm that activates analytic forms of reasoning that assess and sometimes correct the output of more intuitive forms of reasoning. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Value of percutaneous ethanol injection in the treatment of hepatocellular carcinoma in a cirrhotic liver]

Over the last few decades there has been a substantially higher percentage of successful organ transplants but also a significant imbalance between the demand for and the supply of organs, creating the basis for a highly profitable black market trade in human organs. Sometimes there are reports that children have been kidnapped, only to reappear later lacking one kidney, or that they simply disappear and are subsequently killed to have all their transplantable organs removed for profit. The European Union feels that there is a need for action and that it has a duty to act in this field, especially for ethical reasons. There is now established close co-operation between the various European transplant organizations. The legal protection of children with regard to organ transplantation is not specifically mentioned in the existing conventions because this issue was not foreseen at the time of their preparation. However, the issue is covered in a broader sense by more general provisions. There are endless rumours surrounding this area. Members of various organizations who travel in the suspected countries say that the trafficking in children who are sold for transplantation is well known, but it is too difficult and very dangerous to catch the people involved. We have to conclude that it has been impossible to prove or disprove the rumours, but they are consistent and we all, especially in the health care professions, have an obligation to be keenly aware of how and where organs are obtained.     

What can the history of AI learn from the history of science?

There have been few attempts, so far, to document the history of artificial intelligence. It is argued that the historical sociology of scientific knowledge can provide a broad historiographical approach for the history of AI, particularly as it has proved fruitful within the history of science in recent years. The article shows how the sociology of knowledge can inform and enrich four types of project within the history of AI; organizational history; AI viewed as technology; AI viewed as cognitive science and historical biography. In the latter area the historical treatments of Darwin and Turing are compared to warn against the pitfalls of rational reconstructions of the past.     

Code generation for a family of executable modelling notations

We are investigating semantically configurable model-driven engineering (MDE). The goal of this work is a modelling environment that supports flexible, configurable modelling notations, in which specifiers can configure the semantics of notations to suit their needs and yet still have access to the types of analysis tools and code generators normally associated with MDE. In this paper, we describe semantically configurable code generation for a family of behavioural modelling notations. The family includes variants of statecharts, process algebras, Petri Nets, and SDL88. The semantics of this family is defined using template semantics, which is a parameterized structured operational semantics in which parameters represent semantic variation points. A specific notation is derived by instantiating the family’s template semantics with parameter values that specify semantic choices. We have developed a code-generator generator (CGG) that creates a suitable Java code generator for a subset of derivable modelling notations. Our prototype CGG supports 26 semantics parameters, 89 parameter values, and 7 composition operators. As a result, we are able to produce code generators for a sizable family of modelling notations, though at present the performance of our generated code is about an order of magnitude slower than that produced by commercial-grade generators.     

Model-driven design for the visual analysis of heterogeneous data

As heterogeneous data from different sources are being increasingly linked, it becomes difficult for users to understand how the data are connected, to identify what means are suitable to analyze a given data set, or to find out how to proceed for a given analysis task. We target this challenge with a new model-driven design process that effectively codesigns aspects of data, view, analytics, and tasks. We achieve this by using the workflow of the analysis task as a trajectory through data, interactive views, and analytical processes. The benefits for the analysis session go well beyond the pure selection of appropriate data sets and range from providing orientation or even guidance along a preferred analysis path to a potential overall speedup, allowing data to be fetched ahead of time. We illustrate the design process for a biomedical use case that aims at determining a treatment plan for cancer patients from the visual analysis of a large, heterogeneous clinical data pool. As an example for how to apply the comprehensive design approach, we present Stack'n'flip, a sample implementation which tightly integrates visualizations of the actual data with a map of available data sets, views, and tasks, thus capturing and communicating the analytical workflow through the required data sets.