Search results for "Probabilistic"

Simulating multilevel dynamics of antimicrobial resistance in a membrane computing model

2019

Membrane computing is a bio-inspired computing paradigm whose devices are the so-called membrane systems or P systems. The P system designed in this work reproduces complex biological landscapes in the computer world. It uses nested “membrane-surrounded entities” able to divide, propagate, and die; to be transferred into other membranes; to exchange informative material according to flexible rules; and to mutate and be selected by external agents. This allows the exploration of hierarchical interactive dynamics resulting from the probabilistic interaction of genes (phenotypes), clones, species, hosts, environments, and antibiotic challenges. Our model facilitates analysis of several aspects…

Il bias di ragionamento probabilistico nel birthday-problem. Un contributo di ricerca

Predictive and Contextual Feature Separation for Bayesian Metanetworks

2007

Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of conditional dependency. However, depending on a context, many attributes of the model might not be relevant. If a Bayesian Network has been learned across multiple contexts then all uncovered conditional dependencies are averaged over all contexts and cannot guarantee high predictive accuracy when applied to a concrete case. We are considering a context as a set of contextual attributes, which are not directly effect probability distribution of the target attributes, but they effect on "relevance" of the predictive attributes towards target attribut…

Probabilistic Transition-Based Approach for Detecting Application-Layer DDoS Attacks in Encrypted Software-Defined Networks

2017

With the emergence of cloud computing, many attacks, including Distributed Denial-of-Service (DDoS) attacks, have changed their direction towards cloud environment. In particular, DDoS attacks have changed in scale, methods, and targets and become more complex by using advantages provided by cloud computing. Modern cloud computing environments can benefit from moving towards Software-Defined Networking (SDN) technology, which allows network engineers and administrators to respond quickly to the changing business requirements. In this paper, we propose an approach for detecting application-layer DDoS attacks in cloud environment with SDN. The algorithm is applied to statistics extracted from…

An adaptive probabilistic approach to goal-level imitation learning

2010

Imitation learning has been recognized as a promising technique to teach robots advanced skills. It is based on the idea that robots could learn new behaviors by observing and imitating the behaviors of other skilled actors. We propose an adaptive probabilistic graphical model which copes with three core issues of any imitative behavior: observation, representation and reproduction of skills. Our model, Growing Hierarchical Dynamic Bayesian Network (GHDBN), is hierarchical (i.e. able to characterize structured behaviors at different levels of abstraction), and growing (i.e. skills are learned or updated incrementally - and at each level of abstraction - every time a new observation sequence…

Using recursive Bayesian estimation for matching GPS measurements to imperfect road network data

2010

Map-matching refers to the process of projecting positioning measurements to a location on a digital road network map. It is an important element of intelligent transportation systems (ITS) focusing on driver assistance applications, on emergency and incident management, arterial and freeway management, and other applications. This paper addresses the problem of map-matching in the applications characterized by imperfect map quality and restricted computational resources - e.g. in the context of community-based ITS applications. Whereas a number of map-matching methods are available, often these methods rely on topological analysis, thereby making them sensitive to the map inaccuracies. In …

An adaptive probabilistic graphical model for representing skills in PbD settings

2010

Dynamic Shakedown Sensitivity Analysis by Means of a Probabilistic Approach

2017

The shakedown limit load multiplier problem for elastic plastic structures subjected to a combination of fixed and seismic loads is treated. In particular, reference is firstly made to the unrestricted dynamic shakedown theory. The relevant seismic load history is modeled as a repeated one and, with reference to classically damped structures, appropriate modal analyses are utilized. With the aim of evaluating the reliability of the results arising from the application of the cited theory, a recent probabilistic approach is also utilized. This approach adopts the Monte Carlo method in order to define the necessary seismic acceleration histories and finally compute the related shakedown limit…

Probabilistic models for the fatigue resistance of welded steel joints subjected to constant amplitude loading

2022

Abstract S-N curves found in various rules and regulations are the basic tool for the practicing engineer when carrying out life predictions for welded details in dynamically loaded structures. The present work is investigating the expected fatigue life and associated scatter for welded steel joints subjected to Constant Amplitude (CA) loading. The objective is to obtain more reliable life predictions based on advancements in the probabilistic model fitted to collected life data. A Random Fatigue Limit Model (RFLM) is proposed to obtain fatigue resistance curves at given probability levels of survival. As a distinction to more conventional statistical methods, the model is treating both the…

Employing fuzzy logic in the diagnosis of a clinical case

2010

Fuzzy logic is a logical calculus which operates with many truth values (while classical logic works with the two values of true and false). Since fuzzy logic considers the truth of scientific statements like something softened, it is fruitfully applied to the study of biological phenomena, biology is indeed considered the field of complexity, uncertainty and vagueness. In this paper fuzzy logic is successfully applied to the clinical diagnosis of a patient who suffers from different diseases bound by a complex causal chain. In this work it is presented a mathematical foundation of fuzzy logic (with connectives and inference rules) and then the application of fuzzy reasoning to the study of…