Abstract Modern financial markets produce massive datasets that need to be analysed using new modelling techniques like those from (deep) Machine Learning and Artificial Intelligence. The common goal of these is forecast the behaviour market, which can translated into various classification tasks, such as, for instance, predicting likelihood companies’ bankruptcy or in fraud detection systems. ...

A screening for submicroscopic rearrangements was performed in 111 patients with idiopathic mental retardation (MR) using fluorescence in situ hybridization (FISH) probes from the subtelomeric regions of all chromosome arms. Ten cryptic rearrangements were found (9%): five de novo deletions; one unbalanced de novo translocation; three unbalanced inherited translocations; and one unbalanced reco...

In this paper we provide the answer to following question: given an arbitrary pure input state and a general, unbalanced, Mach-Zehnder interferometer, what transmission coefficient of first beam splitter maximizes quantum Fisher information (QFI)? We consider question for both single- two-parameter QFI, or, in other words, with or without having access external phase reference. give analytical ...

Three-phase unbalance is an important power quality issue that can cause many negative effects to the power system. Effective mitigation and management of voltage unbalance will benefit from the knowledge of how the unbalanced sources contribute to the voltage asymmetry at the point of evaluation (POE). In this paper, a method is proposed to assess the overall unbalance contribution of the mult...

The design of compact unbalanced-/balanced-to- unbalanced diplexer (U2U/B2U) based on full dual-mode dielectric resonator (DR) is investigated for the first time. relationships external quality factors ( Q e ) under two modes are analyzed. It found that can be controlled independently, which mak...

in this paper, a new topology is proposed for three-phase to single-phase matrix converters, where more voltage levels are produced in the output in comparison with the conventional topologies. in addition, a new control method based on minimum error between the generated and the desired output voltages is proposed for three-phase to single-phase matrix converters. in the proposed control metho...

In classification, machine learning algorithms can suffer a performance bias when data sets are unbalanced. Binary data sets are unbalanced when one class is represented by only a small number of training examples (called the minority class), while the other class makes up the rest (majority class). In this scenario, the induced classifiers typically have high accuracy on the majority class but...

Neurons in sensory cortex show stimulus selectivity and sparse population response, even in cases where no strong functionally specific structure in connectivity can be detected. This raises the question whether selectivity and sparseness can be generated and maintained in randomly connected networks. We consider a recurrent network of excitatory and inhibitory spiking neurons with random conne...