1,721,195 research outputs found
The reproduction of the physiological behaviour of the axon of nervous cells by means of finite element models
This paper describes 3D Finite Element modelling solutions for a segment of a nervous cell axon, which take into account the non linear and time varying dynamics of the membrane surrounding it in order to reproduce its physiological behaviour, in terms of Action Potentials (AP) elicitation and its temperature dependence. The axial-symmetry of the system is exploited in order to conduct a more efficient analysis. A combination of the so called Hodgkin-Huxley equations modelling the dynamics of the membrane voltage-controlled ionic channels, together with the Maxwell equations in Electro Quasi-Static approximation, describing the electromagnetic behaviour of each medium, is tackled in a numerical procedure implemented in a commercial Finite Elements multiphysical environment. The usefulness of Finite Elements in order to have interesting quantitative responses (field shape and axon physiological behaviour) is investigated. Two different models are presented here. One exploits the typical thin layer approximation for the axon membrane, proving to be useful when the field solution inside the membrane domain is not a matter of interest. Its performances are compared with the other model, which is introduced in order to obtain a more realistic representation of the studied system: the axon membrane is here realized with a non-linear active medium (exploiting its equivalent electric conductivity) allowing the reproduction of the electric potential also inside the membrane. The passive electrotonic nature of the membrane and the elicitation of an AP in presence of different stimuli are computed and the results are in keeping with the predicted ones. Finally the AP temperature dependences and the propagation effect are reproduced by using the corresponding best numerical model, i.e. The coarse one without membrane for the temperature, the more detailed with membrane for the propagation, leading to a trade off between the computational effort and the objective of the analysis. The models open a wide range of applications and extensions in order to understand the true behaviour of a complete neuron
Using multilayer perceptron in computer security to improve intrusion detection
Nowadays computer and network security has become a major cause of concern for experts community, due to the growing number of devices connected to the network. For this reason, optimizing the performance of systems able to detect intrusions (IDS - Intrusion Detection System) is a goal of common interest. This paper presents a methodology to classify hacking attacks taking advantage of the generalization property of neural networks. In particular, in this work we adopt the multilayer perceptron (MLP) model with the back-propagation algorithm and the sigmoidal activation function. We analyse the results obtained using different configurations for the neural network, varying the number of hidden layer sand the number of training epochs in order to obtaina low number of false positives. The obtained results will be presented in terms of type of attacks and training epochs and we will show that the best classification is carried out for DOS and Probe attacks. © Springer International Publishing AG 2018
Adopting decision tree based policy enforcement mechanism to protect reconfigurable devices
Automatic call management in a cellular mobile network by fuzzy threshold logic
The current literature on mobile communication usually considers the channel assignment and the call admission control as two independent problems. However, in practice these two problems are not fully independent. This paper attempts to solve the complete problem uniquely by two alternative approaches. The first approach is concerned with the development of a fuzzy to binary mapping of the measurement variables to decision variables. The latter approach deals with fuzzy to fuzzy matching, and then employs a fuzzy threshold to transform the fuzzy decisions into binary values for execution. The performance of both the call management techniques are studied with the standard Philadelphia benchmark and the results outperform reported results on independent call admission and channel assignment problems
A comparison of character and word embeddings in bidirectional LSTMs for POS tagging in Italian
Word representations are mathematical items capturing a word’s meaning and its grammatical properties in a machine-readable way. They map each word into equivalence classes including words sharing similar properties. Word representations can be obtained automatically by using unsupervised learning algorithms that rely on the distributional hypothesis, stating that the meaning of a word is strictly connected to its context in terms of surrounding words. This assessed notion of context has been recently reconsidered in order to include both distributional and morphological features of a word in terms of characters co-occurrence. This approach has evidenced very promising results, especially in NLP tasks, e.g, POS Tagging, where the representation of the so-called Out of Vocabulary (OOV) words represents a partially solved issue. This work is intended to face the problem of representing OOV words for a POS Tagging task, contextualized to the Italian language. Potential benefits and drawbacks of adopting a Bidirectional Long Short Term Memory (bi-LSTM) fed with a joint character and word embeddings representation to perform POS Tagging also considering OOV words have been investigated. Furthermore, experiments have been performed and discussed by estimating qualitative and quantitative indicators, and, thus, suggesting some possible future direction of the investigation
A recommender system for multimedia art collections
In this paper we present a novel user-centered recommendation approach for multimedia art collections. In particular, preferences (usually coded in the shape of items’ metadata), opinions (textual comments to which it is possible to associate a particular sentiment), behavior (in the majority of cases logs of past items’ observations and actions made by users in the environment), and feedbacks (usually expressed in the form of ratings) are considered and integrated together with items’ features and context information within a general and unique recommendation framework that can support an intelligent browsing of any multimedia repository. Preliminary experiments show the utility of the proposed strategy to perform different browsing tasks
Hemplime Blocks: Innovative Solution for Green Buildings in Italy
In the last years, the attention to an eco-friendly development of the building sector has increased the use of green materials, mainly because the construction sector is one of the most polluting. The hemplime block represents a valid option in this direction: it is a valuable product to improve the sustainability of the building. Like any new product, the main issues are given by the absence of specific rules, starting from the production phase until the installation. For this reason, the main objective of this work is to take a first step toward the long process of identifying possible guidelines for the production and the testing phase of the products to achieve a CE (European Commission) certification. Another essential aspect to clarify is the definition of indications for the laying phase of the prefabricated blocks. This study significantly contributes to reduce uncertainties and skepticism about this technology. With these objectives, some experimental tests have been carried out to verify the reliability of the data declared in the datasheets of hemplime blocks produced in Italy, justifying any incongruity. This study also investigates other aspects of hemplime block, such as the main pathologies that may affect this technology during its lifetime and the maintenance operations necessary to restore the product. Furthermore, the thermal performance of a wall was studied in a climatic chamber to study its behavior in conditions similar to service life
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