Search results for "lcsh:Electronic computers. Computer science"

Birkhoff's aesthetics, Arnheim's entropy. Some remarks on complexity and fuzzy entropy in arts

2015

A judgement of aesthetic in arts is, by sheer consensus, a daunting task that requires evaluation of a whole host of endogenous and exogenous cultural factors. A few of them can actually provide very useful hints in tackling foundational problems in Information Science in a more natural setting than what is usually provided by a typical engineering stance. This interaction can however work the other way about, as instruments from the Information and Computer Science toolkit may help in focusing the less explored features of art and its evaluation. When all the social, historical, hermeneutical and political considerations are stripped from the living flesh of the piece, we lose most of wha…

Dynamic thermal rating for overhead lines: Self-adaptive protection device

2013

The increase in the consumption of electricity, the stringent environmental restrictions and the need to keep costs, make ever more meaningful the need for a flexible operation of existing overhead lines. This paper studies the possibility to use a dynamic thermal rating for overhead line starting from the analysis of the mathematical model and the ability of the latter to reflect the temperature of an overhead conductor in different ambient condition; then it simulates the thermal behaviour of a conductor both in steady state and dynamic one. Finally the paper shows a method for a self-adaptive thermal protection system.

SMCP: a Secure Mobile Crowdsensing Protocol for fog-based applications

2020

Abstract The possibility of performing complex data analysis through sets of cooperating personal smart devices has recently encouraged the definition of new distributed computing paradigms. The general idea behind these approaches is to move early analysis towards the edge of the network, while relying on other intermediate (fog) or remote (cloud) devices for computations of increasing complexity. Unfortunately, because both of their distributed nature and high degree of modularity, edge-fog-cloud computing systems are particularly prone to cyber security attacks that can be performed against every element of the infrastructure. In order to address this issue, in this paper we present SMCP…

QoS-Aware Fault Detection in Wireless Sensor Networks

2013

Wireless sensor networks (WSNs) are a fundamental building block of many pervasive applications. Nevertheless the use of such technology raises new challenges regarding the development of reliable and fault-tolerant systems. One of the most critical issues is the detection of corrupted readings amidst the huge amount of gathered sensory data. Indeed, such readings could significantly affect the quality of service (QoS) of the WSN, and thus it is highly desirable to automatically discard them. This issue is usually addressed through “fault detection” algorithms that classify readings by exploiting temporal and spatial correlations. Generally, these algorithms do not take into account QoS re…

A Review on Approaches for Condition Based Maintenance in Applications with Induction Machines located Offshore

2012

Published version of an article in the journal: Modeling, Identification and Control. Also available from the publisher at: http://dx.doi.org/10.4173/mic.2012.2.4 Open access This paper presents a review of different approaches for Condition Based Maintenance (CBM) of induction machines and drive trains in offshore applications. The paper contains an overview of common failure modes, monitoring techniques, approaches for diagnostics, and an overview of typical maintenance actions. Although many papers have been written in this area before, this paper puts an emphasis on recent developments and limits the scope to induction machines and drive trains applied in applications located offshore.

Editorial: Robot-Assisted Learning and Education

2020

On modal mu-calculus over finite graphs with bounded strongly connected components.

2010

For every positive integer k we consider the class SCCk of all finite graphs whose strongly connected components have size at most k. We show that for every k, the Modal mu-Calculus fixpoint hierarchy on SCCk collapses to the level Delta2, but not to Comp(Sigma1,Pi1) (compositions of formulas of level Sigma1 and Pi1). This contrasts with the class of all graphs, where Delta2=Comp(Sigma1,Pi1).

Distributed Data Clustering via Opinion Dynamics

2015

We provide a distributed method to partition a large set of data in clusters, characterized by small in-group and large out-group distances. We assume a wireless sensors network in which each sensor is given a large set of data and the objective is to provide a way to group the sensors in homogeneous clusters by information type. In previous literature, the desired number of clusters must be specified a priori by the user. In our approach, the clusters are constrained to have centroids with a distance at least ε between them and the number of desired clusters is not specified. Although traditional algorithms fail to solve the problem with this constraint, it can help obtain a better cluste…

nalysis, Modeling and Simulation of Mechatronic Systems using the Bond Graph Method

2011

The Bond Graph is the proper choice of physical system used for: (i) Modeling which can be applied to systems combining multidisciplinary energy domains, (ii) Analysis to provide a great value proposition for finding the algebraic loops within the system enabling the process of troubleshooting and eliminating the defects by using the proper component(s) to fix the causality conflict even without being acquainted in the proper system, and (iii) Simulation facilitated through derived state space equations from the Bond Graph model is solved using industrial simulation software, such as 20-Sim. The Bond Graph technique is a graphical language of modeling, in which component energy ports are co…

Using Topic Modeling Methods for Short-Text Data: A Comparative Analysis

2020

With the growth of online social network platforms and applications, large amounts of textual user-generated content are created daily in the form of comments, reviews, and short-text messages. As a result, users often find it challenging to discover useful information or more on the topic being discussed from such content. Machine learning and natural language processing algorithms are used to analyze the massive amount of textual social media data available online, including topic modeling techniques that have gained popularity in recent years. This paper investigates the topic modeling subject and its common application areas, methods, and tools. Also, we examine and compare five frequen…