Search results for "artificial intelligence"
showing 10 items of 6122 documents
Cognitive Systems Research: Special Issue on Biologically Inspired Cognitive Architectures: Papers from the Tenth Annual International Conference on …
2021
This Special Issue of Cognitive System Research on Biologically Inspired Cognitive Architectures: Papers from the Tenth Annual International Conference on Biologically Inspired Cognitive Architectures (BICA 2019) have solicited and collected research papers in all domains of science and technology that directly or indirectly may help us to make an advance toward the BICA Challenge, which is to implement the top essential functionality of the human mind in a machine. The selected papers included here are based on presentations given from 16 to 18 August 2019 during the 10th Annual International Conference on Biologically Inspired Cognitive Architectures (BICA 2019) held at the Microsoft Main…
A Platform for the Evaluation of Distributed Reputation Algorithms
2018
In distributed environments, where unknown entities cooperate to achieve complex goals, intelligent techniques for estimating agents' truthfulness are required. Distributed Reputation Management Systems (RMSs) allow to accomplish this task without the need for a central entity that may represent a bottleneck and a single point of failure. The design of a distributed RMS is a challenging task due to a multitude of factors that could impact on its performances. In order to support the researcher in evaluating the RMS robustness against security attacks since its beginning design phase, in this work we present a distributed simulation environment that allows to model both the agent's behaviors…
Smart Auctions for Autonomic Ambient Intelligence Systems
2020
The main goal of Ambient Intelligence (AmI) is to support users in their daily activities by satisfying and anticipating their needs. To achieve such goal, AmI systems rely on physical infrastructures made of heterogenous sensing devices which interact in order to exchange information and perform monitoring tasks. In such a scenario, a full achievement of AmI vision would also require the capability of the system to autonomously check the status of the infrastructure and supervise its maintenance. To this aim, in this paper, we extend some previous works in order to allow the self-management of AmI devices enabling them to directly interact with maintenance service providers. In particular,…
Short-Term Sensory Data Prediction in Ambient Intelligence Scenarios
2014
Predicting data is a crucial ability for resource-constrained devices like the nodes of a Wireless Sensor Network. In the context of Ambient Intelligence scenarios, in particular, short-term sensory data prediction becomes a key enabler for more difficult tasks such as prolonging network lifetime, reducing the amount of communication required and improving user-environment interaction. In this chapter we propose a software module designed for clustered wireless sensor networks, able to predict various environmental quantities, namely temperature, humidity and light. The software module is supported by an ontology that describes the topology of the AmI scenario and the effects of the actuato…
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…
Detection of User Activities in Intelligent Environments
2014
Research on Ambient Intelligence (AmI) focuses on the development of smart environments adaptable to the needs and preferences of their inhabitants. For this reason it is important to understand and model user preferences. In this chapter we describe a system to detect user behavior patterns in an intelligent workplace. The system is designed for a workplace equipped in the context of Sensor9k, a project carried out at the Department of Computer Science at the University of Palermo (Italy). © Springer International Publishing Switzerland 2014.
Mimicking biological mechanisms for sensory information fusion
2013
Current Artificial Intelligence systems are bound to become increasingly interconnected to their surrounding environment in the view of the newly rising Ambient Intelligence (AmI) perspective. In this paper, we present a comprehensive AmI framework for performing fusion of raw data, perceived by sensors of different nature, in order to extract higher-level information according to a model structured so as to resemble the perceptual signal processing occurring in the human nervous system. Following the guidelines of the greater BICA challenge, we selected the specific task of user presence detection in a locality of the system as a representative application clarifying the potentialities of …
Segmentation of MR brain images with bias artifact
2009
Brain MR Images corrupted by RF- Inhomogeneity (bias artifact) exhibit brightness variations across the image. As a consequence, a standard Fuzzy C-Means (fern) segmentation algorithm may fail. In this work we show a new general-purpose bias removing algorithm, which can be used as a pre-processing step for a fern segmentation. We also compare our experimental results with the ones achieved by using E2 D - H U M filter, showing an improvement in brain segmentation and bias removal.
A Gabor-based Technique for Bias Removal in MR images
2007
Magnetic Resonance images are often characterized by irregularly displaced luminance fluctuations that are called bias artifact. This disturb is due to a drop in signal intensity caused by the distance between imaged sample and receiver coil. An original approach to bias removal in Magnetic Resonance images is presented, which is based on the use of Gabor filter to extract the artifact. The proposed technique restores the image using a correction model, which is derived from the attenuation of signal diffusion across the tissues. No hypotheses are made about the structure of the tissues under investigation and the used MR spectrum. The approach is presented in detail, and extensive experime…
Gaining insight by structural knowledge extraction
2016
The availability of increasingly larger and more complex datasets has boosted the demand for systems able to analyze them automatically. The design and implementation of effective systems requires coding knowledge about the application domain inside the system itself; however, the designer is expected to intuitively grasp the most relevant features of the raw data as a. preliminary step. In this paper we propose a framework to get useful insight about a set of complex data, and we claim that a shift in perspective may be of help to tackle with the unaddressed goal of representing knowledge by means of the structure inferred from the collected samples. We will present a formulation of knowle…