Binarised regression tasks: methods and evaluation metrics

Some supervised tasks are presented with a numerical output but decisions have to be made in a discrete, binarised, way, according to a particular cutoff. This binarised regression task is a very common situation that requires its own analysis, different from regression and classification—and ordinal regression. We first investigate the application cases in terms of the information about the distribution and range of the cutoffs and distinguish six possible scenarios, some of which are more common than others. Next, we study two basic approaches: the retraining approach, which discretises the training set whenever the cutoff is available and learns a new classifier from it, and the reframing approach, which learns a regression model and sets the cutoff when this is available during deployment. In order to assess the binarised regression task, we introduce context plots featuring error against cutoff. Two special cases are of interest, the \( UCE \) and \( OCE \) curves, showing that the area under the former is the mean absolute error and the latter is a new metric that is in between a ranking measure and a residual-based measure. A comprehensive evaluation of the retraining and reframing approaches is performed using a repository of binarised regression problems created on purpose, concluding that no method is clearly better than the other, except when the size of the training data is small.     

Fuzzy fault tolerant predictive control for a diesel engine air path

This paper proposes a Fuzzy Fault Tolerant Predictive Control (FFTPC) with integral action method for a class of nonlinear systems. The Takagi-Sugeno (T-S) fuzzy approach is introduced as a modelling technique in order to consider the active control methods adapted to linear models. The proposed control strategy is based on a combination between Parallel Distributed Compensation (PDC) control law and Model Predictive Control (MPC) where the T-S fuzzy aspect uses the Unmeasurable Premise Variables (UPV). A T-S fuzzy observer provides an L2 norm estimation of system state vector and faults. The controller and observer gains are obtained by solving Linear Matrix Inequalities (LMIs) derived from the Lyapunov theory. The validity of the proposed Fault Tolerant Control (FTC) strategy is illustrated through an application to a Diesel Engine Air Path (DEAP) system.     

The magnetic-distortion probe: velocimetry in conducting fluids

A new type of velocimeter, capable of local velocity measurements in conducting fluids, is introduced. The principle of the "magnetic-distortion probe" is based on the measurement of the induced magnetic field by the flow of a conducting fluid in the vicinity of a localized magnetic field. The new velocimeter has no moving parts, and can be enclosed in a sealed cap, easing the implementation in harsh environments, such as liquid metals. The proposed method allows one to probe both the continuous part and fluctuations of the velocity, the temporal and spatial resolution being linked to the actual geometric configuration of the probe. A prototype probe has been tested in a gallinstan pipe flow and in a fully turbulent flow of liquid gallium generated by the counter rotation of two coaxial impellers in a cylinder. The signals have been compared to a reference potential probe and show very good agreement both for time-averaged velocities and turbulent fluctuations. The prototype is shown to detect motion from a few cm s(-1) to a few m s(-1). Moreover, the use of the magnetic-distortion probe with large-scale applied magnetic field is discussed.     

On matrices, automata, and double counting in constraint programming

Matrix models are ubiquitous for constraint problems. Many such problems have a matrix of variables $\mathcal{M}$ , with the same constraint C defined by a finite-state automaton $\mathcal{A}$ on each row of $\mathcal{M}$ and a global cardinality constraint $\mathit{gcc}$ on each column of $\mathcal{M}$ . We give two methods for deriving, by double counting, necessary conditions on the cardinality variables of the $\mathit{gcc}$ constraints from the automaton $\mathcal{A}$ . The first method yields linear necessary conditions and simple arithmetic constraints. The second method introduces the cardinality automaton, which abstracts the overall behaviour of all the row automata and can be encoded by a set of linear constraints. We also provide a domain consistency filtering algorithm for the conjunction of lexicographic ordering constraints between adjacent rows of $\mathcal{M}$ and (possibly different) automaton constraints on the rows. We evaluate the impact of our methods in terms of runtime and search effort on a large set of nurse rostering problem instances.     

Dual-color fluorescence lifetime correlation spectroscopy to quantify protein-protein interactions in live cell

Dual-color fluorescence correlation spectroscopy is an interesting method to quantify protein interaction in living cells. But, when performing these experiments, one must compensate for a known spectral bleed through artifact that corrupts cross-correlation data. In this article, problems with crosstalk were overcome with an approach based on fluorescence lifetime correlation spectroscopy (FLCS). We show that FLCS applied to dual-color EGFP and mCherry cross-correlation allows the determination of protein-protein interactions in living cells without the need of spectral bleed through calibration. The methodology was validated by using EGFP-mCherry tandem in comparison with coexpressed EGFP and mCherry in live cell. The dual-color FLCS experimental procedure where the different laser intensities do not have to be controlled during experiment is really very helpful to study quantitatively protein interactions in live sample.     

Oblivious transfer and quantum channels as communication resources

We show that from a communication-complexity perspective, the primitive called oblivious transfer—which was introduced in a cryptographic context—can be seen as the classical analogue to a quantum channel in the same sense as non-local boxes are of maximally entangled qubits. More explicitly, one realization of non-cryptographic oblivious transfer allows for the perfect simulation of sending one qubit and measuring it in an orthogonal basis. On the other hand, a qubit channel allows for realizing non-cryptographic oblivious transfer with probability roughly 85 %, whereas 75 % is the classical limit.     

Particle Level Set Advection for the Interactive Visualization of Unsteady 3D Flow

Typically, flow volumes are visualized by defining their boundary as iso‐surface of a level set function. Grid‐based level sets offer a good global representation but suffer from numerical diffusion of surface detail, whereas particle‐based methods preserve details more accurately but introduce the problem of unequal global representation. The particle level set (PLS) method combines the advantages of both approaches by interchanging the information between the grid and the particles. Our work demonstrates that the PLS technique can be adapted to volumetric dye advection via streak volumes, and to the visualization by time surfaces and path volumes. We achieve this with a modified and extended PLS, including a model for dye injection. A new algorithmic interpretation of PLS is introduced to exploit the efficiency of the GPU, leading to interactive visualization. Finally, we demonstrate the high quality and usefulness of PLS flow visualization by providing quantitative results on volume preservation and by discussing typical applications of 3D flow visualization.     

A knowledge-based approach to manage information systems interoperability

Interoperability is a key property of enterprise applications, which is hard to achieve due to the large number of interoperating components and semantic heterogeneity. The inherent complexity of interoperability problems implies that there exists no silver bullet to solve them. Rather, the knowledge about how to solve wicked interoperability problems is hidden in the application cases that expose those problems. The paper addresses the question of how to organise and use method knowledge to resolve interoperability problems. We propose the structure of a knowledge-based system that can deliver situation-specific solutions, called method chunks. Situational Method Engineering promotes modularisation and formalisation of method knowledge in the form of reusable method chunks, which can be combined to compose a situation-specific method. The method chunks are stored in a method chunk repository. In order to cater for management and retrieval, we introduce an Interoperability Classification Framework, which is used to classify and tag method chunks and to assess the project situation in which they are to be used. The classification framework incorporates technical as well as business and organisational aspects of interoperability. This is an important feature as interoperability problems typically are multifaceted spanning multiple aspects. We have applied the approach to analyse an industry case from the insurance sector to identify and classify a set of method chunks.