Search results for " Computer"
showing 10 items of 6910 documents
Neural networks for the diagnostics of gas turbine engines
1996
The paper describes the activities carried out for developing and testing Back Propagation Neural Networks (BPNN) for the gas turbine engine diagnostics. One of the aims of this study was to analyze the problems encountered during training using large number of patterns. Each pattern contains information about the engine thermodynamic behaviour when there is a fault in progress. Moreover the research studied different architectures of BPNN for testing their capability to recognize patterns even when information is noised. The results showed that it is possible to set-up and optimize suitable and robust Neural Networks useful for gas turbine diagnostics. The methods of Gas Path Analysis furn…
Probabilities of conditionals and previsions of iterated conditionals
2019
Abstract We analyze selected iterated conditionals in the framework of conditional random quantities. We point out that it is instructive to examine Lewis's triviality result, which shows the conditions a conditional must satisfy for its probability to be the conditional probability. In our approach, however, we avoid triviality because the import-export principle is invalid. We then analyze an example of reasoning under partial knowledge where, given a conditional if A then C as information, the probability of A should intuitively increase. We explain this intuition by making some implicit background information explicit. We consider several (generalized) iterated conditionals, which allow…
Taxonomic categorisation of motivic patterns
2009
The issue of pattern description in computational models for motivic analysis is closely related to the cognitive debate on categorisation, in which are traditionally opposed “well-defined” and “ill-defined” categorisations. The ill-defined conceptualisation has been considered as a suitable framework for the formalisation of musical categorisation as it takes into account motivic variations. It seems that computational models rely rather on well-defined categorisation, due to its better controllability. The computational model we previously presented (Lartillot & Toiviainen, 2007) strikes a balance by developing a new flexible framework allowing the taking into account of unrestricted…
Durability assessment of basalt fiber polymer as reinforcement to expanded clay concrete in harsh environment
2021
Basalt fiber-reinforced polymer composites are receiving considerable attention as they represent a low-cost green source of raw materials. In most cases, fiber-reinforced polymer composites face harsh environments, such as chloride ions in coastal marine environments or cold regions with salt deicing. The resistance of fiber-reinforced polymers subjected to the above environments is critical for the safe design and application of such composites. This research aims to develop a framework to investigate the durability properties of the lightweight expanded clay basalt fiber polymer reinforced concrete exposed to the NaCl environment. The specified quantity of concrete structural elements wa…
On-board Energy Consumption Assessment for Symbolic Execution Models on Embedded Devices
2020
Internet of Things (IoT) applications operate in several domains while requiring seamless integration among heterogeneous objects. Regardless of the specific platform and context, IoT applications demand high energy efficiency. Adopting resource-constrained embedded devices for IoT applications means ensuring low power consumption, low maintenance costs and possibly longer battery life. Meeting these requirements is particularly arduous as programmers are not able to monitor the energy consumption of their own software during development or when applications are finally deployed. In this paper, we discuss on-board real-time energy evaluation of both hardware and software during the developm…
Wireless Power Transmission for house appliances: A small-scale resonant coupling prototype
2016
This paper presents a low cost prototype of wireless power transfer system based on resonant coupling. The system here proposed can be useful for house appliances battery charging systems: as a matter of fact, it consists mainly of two copper wire coils or windings, placed one in front of the other on the same axis. By exploiting the coils resonance coupling effect, electric energy can be transferred from the inductor coil to the receiver in order to charge the batteries. Low cost experimental tests demonstrated the effectiveness of the proposed wireless power transfer prototype, being it capable to reach an efficiency of about 80% and more along a distance of 30 cm.
Rejection odds and rejection ratios: A proposal for statistical practice in testing hypotheses
2016
Much of science is (rightly or wrongly) driven by hypothesis testing. Even in situations where the hypothesis testing paradigm is correct, the common practice of basing inferences solely on p-values has been under intense criticism for over 50 years. We propose, as an alternative, the use of the odds of a correct rejection of the null hypothesis to incorrect rejection. Both pre-experimental versions (involving the power and Type I error) and post-experimental versions (depending on the actual data) are considered. Implementations are provided that range from depending only on the p-value to consideration of full Bayesian analysis. A surprise is that all implementations -- even the full Baye…
Solving two‐armed Bernoulli bandit problems using a Bayesian learning automaton
2010
PurposeThe two‐armed Bernoulli bandit (TABB) problem is a classical optimization problem where an agent sequentially pulls one of two arms attached to a gambling machine, with each pull resulting either in a reward or a penalty. The reward probabilities of each arm are unknown, and thus one must balance between exploiting existing knowledge about the arms, and obtaining new information. The purpose of this paper is to report research into a completely new family of solution schemes for the TABB problem: the Bayesian learning automaton (BLA) family.Design/methodology/approachAlthough computationally intractable in many cases, Bayesian methods provide a standard for optimal decision making. B…
Predicting mobile apps spread: An epidemiological random network modeling approach
2017
[EN] The mobile applications business is a really big market, growing constantly. In app marketing, a key issue is to predict future app installations. The influence of the peers seems to be very relevant when downloading apps. Therefore, the study of the evolution of mobile apps spread may be approached using a proper network model that considers the influence of peers. Influence of peers and other social contagions have been successfully described using models of epidemiological type. Hence, in this paper we propose an epidemiological random network model with realistic parameters to predict the evolution of downloads of apps. With this model, we are able to predict the behavior of an app…
Decoding Children's Social Behavior
2013
We introduce a new problem domain for activity recognition: the analysis of children's social and communicative behaviors based on video and audio data. We specifically target interactions between children aged 1-2 years and an adult. Such interactions arise naturally in the diagnosis and treatment of developmental disorders such as autism. We introduce a new publicly-available dataset containing over 160 sessions of a 3-5 minute child-adult interaction. In each session, the adult examiner followed a semi-structured play interaction protocol which was designed to elicit a broad range of social behaviors. We identify the key technical challenges in analyzing these behaviors, and describe met…