Search results for "Bayesian [statistical analysis]"

Uncertainty estimation of a complex water quality model: GLUE vs Bayesian approach applied with Box – Cox transformation

2010

In urban drainage modelling, uncertainty analysis is of undoubted necessity; however, several methodological aspects need to be clarified and deserve to be investigated in the future, especially in water quality modelling. The use of the Bayesian approach to uncertainty analysis has been stimulated by its rigorous theoretical framework and by the possibility of evaluating the impact of new knowledge on the modelling estimates. Nevertheless, the Bayesian approach relies on some restrictive hypotheses that are not present in less formal methods like GLUE. One crucial point in the application of Bayesian methods is the formulation of a likelihood function that is conditioned by the hypotheses …

Design of an Adaptive Bayesian System for Sensor Data Fusion

2014

Many artificial intelligent systems exploit a wide set of sensor devices to monitor the environment. When the sensors employed are low-cost, off-the-shelf devices, such as Wireless Sensor Networks (WSN), the data gathered through the sensory infrastructure may be affected by noise, and thus only partially correlated to the phenomenon of interest. One way of overcoming these limitations might be to adopt a high-level method to perform multi-sensor data fusion. Bayesian Networks (BNs) represent a suitable tool for performing refined artificial reasoning on heterogeneous sensory data, and for dealing with the intrinsic uncertainty of such data. However, the configuration of the sensory infrast…

An Adaptive Bayesian System for Context-Aware Data Fusion in Smart Environments

2017

The adoption of multi-sensor data fusion techniques is essential to effectively merge and analyze heterogeneous data collected by multiple sensors, pervasively deployed in a smart environment. Existing literature leverages contextual information in the fusion process, to increase the accuracy of inference and hence decision making in a dynamically changing environment. In this paper, we propose a context-aware, self-optimizing, adaptive system for sensor data fusion, based on a three-tier architecture. Heterogeneous data collected by sensors at the lowest tier are combined by a dynamic Bayesian network at the intermediate tier, which also integrates contextual information to refine the infe…

Assessing Coastal Sustainability: A Bayesian Approach for Modeling and Estimating a Global Index for Measuring Risk

2013

Integrated Coastal Zone Management is an emerg- ing research area. The aim is to provide a global view of dif- ferent and heterogeneous aspects interacting in a geographical area. Decision Support Systems, integrating Computational Intelligence methods, can be successfully used to estimate use- ful anthropic and environmental indexes. Bayesian Networks have been widely used in the environmental science domain. In this paper a Bayesian model for estimating the Sustainable Coastal Index is presented. The designed Bayesian Network consists of 17 nodes, hierarchically organized in 4 layers. The first layer is initialized with the season and the physiographic region information. In the second la…

Fast Fingerprints Classification only using the Directional Image

2007

The classification phase is an important step of an automatic fingerprint identification system, where the goal is to restrict only to a subset of the whole database the search time. The proposed system classifies fingerprint images in four classes using only directional image information. This approach, unlike the literature approaches, uses the acquired fingerprint image without enhancement phases application. The system extracts only directional image and uses three concurrent decisional modules to classify the fingerprint. The proposed system has a high classification speed and a very low computational cost. The experimental results show a classification rate of 87.27%.

A Knowledge Management System using Bayesian Network

2009

In today's world, decision support and knowledge management processes are strategic and interdependent activities in many organizations. The companies' interest on a correct knowledge management is grown, more than interest on the mere knowledge itself. This paper proposes a Knowledge Management System based on Bayesian networks. The system has been tested collecting and using data coming from projects and processes typical of ICT companies, and provides a Document Management System and a Decision Support system to share documents and to plan how to best use firms' knowledge.

Path Modeling and Retrieval in Distributed Video Surveillance Databases

2012

We propose a framework for querying a distributed database of video surveillance data in order to retrieve a set of likely paths of a person moving in the area under surveillance. In our framework, each camera of the surveillance system locally pro- cesses the data and stores video sequences in a storage unit and the metadata for each detected person in the distributed database. A pedestrian’s path is formulated as a dynamic Bayesian network (DBN) to model the dependencies between subsequent observa- tions of the person as he makes his way through the camera net- work. We propose a tool by which the analyst can pose queries about where a certain person appeared while moving in the site duri…

Multisensor Data Fusion in Pervasive Artificial Intelligence Systems

Intelligent systems designed to manage smart environments exploit numerous sensing and actuating devices, pervasively deployed so as to remain invisible to users and subtly learn their preferences and satisfy their needs. Nowadays, such systems are constantly evolving and becoming ever more complex, so it is increasingly difficult to develop them successfully. A possible solution to this problem might lie in delegating certain decisions to the machines themselves, making them more autonomous and able to self-configure and self-manage. This work presents a multi-tier architecture for a complete pervasive system capable of understanding the state of the surrounding environment, as well as usi…

Context-awareness for multi-sensor data fusion in smart environments

2016

Multi-sensor data fusion is extensively used to merge data collected by heterogeneous sensors deployed in smart environments. However, data coming from sensors are often noisy and inaccurate, and thus probabilistic techniques, such as Dynamic Bayesian Networks, are often adopted to explicitly model the noise and uncertainty of data. This work proposes to improve the accuracy of probabilistic inference systems by including context information, and proves the suitability of such an approach in the application scenario of user activity recognition in a smart home environment. However, the selection of the most convenient set of context information to be considered is not a trivial task. To thi…

Bayesian Modeling for Differential Cryptanalysis of Block Ciphers: A DES Instance

2023

Encryption algorithms based on block ciphers are among the most widely adopted solutions for providing information security. Over the years, a variety of methods have been proposed to evaluate the robustness of these algorithms to different types of security attacks. One of the most effective analysis techniques is differential cryptanalysis, whose aim is to study how variations in the input propagate on the output. In this work we address the modeling of differential attacks to block cipher algorithms by defining a Bayesian framework that allows a probabilistic estimation of the secret key. In order to prove the validity of the proposed approach, we present as case study a differential att…