Search results for "Machine"
showing 10 items of 2592 documents
Alle Wege Führen Zum Text
2016
The intention of this chapter is to review the development of linguistic research during the twentieth century in Europe and the United States, in order to show that the genesis of text linguistics as a comprehensive theoretical framework was necessary, considering the events from a post-eventum perspective. Firstly, structural linguistics is presented as well as its main exponents; secondly, generative linguistics is discussed; thirdly, the genesis and the development of text linguistics is presented. Concerning the structural linguistics, the key issues investigated by 4 linguists (namely, de Saussure, Benveniste, Hjelmslev and Bloomfield) are summarized. Concerning the generative linguis…
A probabilistic expert system for predicting the risk of Legionella in evaporative installations
2011
Research highlights? The bacterium Legionella usually lives in water sources such as cooling towers. ? We discuss a probabilistic expert system for predicting the risk of Legionella. ? The expert system has a master-slave architecture. ? The inference engine is implemented through Bayesian reasoning. ? Bayesian networks model and connect relationships for chemical and physical variables. Early detection in water evaporative installations is one of the keys to fighting against the bacterium Legionella, the main cause of Legionnaire's disease. This paper discusses the general structure, elements and operation of a probabilistic expert system capable of predicting the risk of Legionella in rea…
The Insect Mushroom Bodies: a Paradigm of Neural Reuse
2013
This paper is devoted to discuss the implementation of models,which are inspired by the fly Drosophila melanogaster and able to handle open problems in the field of robotics such as attention, expectation and sequence learning. The role of the Mushroom Bodies (MBs) in solving these tasks is analyzed in detail and a unifying plausible biologically inspired model is proposed. The developed neural structure is able to show different capabilities in line with the paradigm of neural reuse. The same neural circuit can be exploited to accomplish multiple tasks showing interesting capabilities such as attention, expectation and delayed match-to-sample. The simulation results here reported suggest a…
Machine Learning: An Overview and Applications in Pharmacogenetics.
2021
This narrative review aims to provide an overview of the main Machine Learning (ML) techniques and their applications in pharmacogenetics (such as antidepressant, anti-cancer and warfarin drugs) over the past 10 years. ML deals with the study, the design and the development of algorithms that give computers capability to learn without being explicitly programmed. ML is a sub-field of artificial intelligence, and to date, it has demonstrated satisfactory performance on a wide range of tasks in biomedicine. According to the final goal, ML can be defined as Supervised (SML) or as Unsupervised (UML). SML techniques are applied when prediction is the focus of the research. On the other hand, UML…
Applying Finite State Process Algebra to Formally Specify a Computational Model of Security Requirements in the Key2phone-Mobile Access Solution
2015
Key2phone is a mobile access solution which turns mobile phone into a key for electronic locks, doors and gates. In this paper, we elicit and analyse the essential and necessary safety and security requirements that need to be considered for the Key2phone interaction system. The paper elaborates on suggestions/solutions for the realisation of safety and security concerns considering the Internet of Things (IoT) infrastructure. The authors structure these requirements and illustrate particular computational solutions by deploying the Labelled Transition System Analyser (LTSA), a modelling tool that supports a process algebra notation called Finite State Process (FSP). While determining an in…
Semi-supervised Hyperspectral Image Classification with Graphs
2006
This paper presents a semi-supervised graph-based method for the classification of hyperspectral images. The method is designed to exploit the spatial/contextual information in the im- ages through composite kernels. The proposed method produces smoother classifications with respect to the intrinsic structure collectively revealed by known labeled and unlabeled points. Good accuracy in high dimensional spaces and low number of labeled samples (ill-posed situations) are produced as compared to standard inductive support vector machines.
Including invariances in SVM remote sensing image classification
2012
This paper introduces a simple method to include invariances in support vector machine (SVM) for remote sensing image classification. We rely on the concept of virtual support vectors, by which the SVM is trained with both the selected support vectors and synthetic examples encoding the invariance of interest. The algorithm is very simple and effective, as demonstrated in two particularly interesting examples: invariance to the presence of shadows and to rotations in patchbased image segmentation. The improved accuracy (around +6% both in OA and Cohen's κ statistic), along with the simplicity of the approach encourage its use and extension to encode other invariances and other remote sensin…
Boosting working memory with accelerated clocks
2021
Our perception of time varies with the degree of cognitive engagement in tasks. The perceived passage of time accelerates while working on demanding tasks, whereas time appears to drag during boring situations. Our experiment aimed at investigating whether this relationship is mutual: Can manipulated announcements of elapsed time systematically affect the attentional resources applied to a cognitive task? We measured behavioral performance and the EEG in a whole report working memory paradigm with six items of different colors that each had to be reported after a short delay period. The 32 participants were informed about the current time after each 20 trials, while the clock was running at…
Sulphate-reducing bacteria in paper machine waters and in suction roll perforations
1978
To define some aspects of the biological corrosion sulphate-reducing bacteria were studied in paper machine waters and in plugged perforations of a suction roll. The desulphuricants were most active on passive fiber recipients. Most bacteria found in fiber plugs taken from the perforations of suction rolls belonged to the genus Desulfovibrio. Desulphuricants were found mainly at the outer ends of plugged perforations, where corrosion of the roll metal is most evident.