Intelligent Agents supporting user interactions within self regulated learning processes

The paper focuses on the main advantages in the defnition and utilization of an open and modular e-learning software platform to support highly cognitive tasks performed by the main actors of the learning process. We present in detail the integration inside the platform of two intelligent agents devoted to talking with the student and to retrieving new information sources on the Web. The process is triggered as a reply to the system’s perception that the student feels discontented with the presented contents. The architecture is detailed, and some conclusions about the growth of the platform’s overall performance are expressed.

Real-time low level feature extraction for on-board robot vision systems

Robot vision systems notoriously require large computing capabilities, rarely available on physical devices. Robots have limited embedded hardware, and almost all sensory computation is delegated to remote machines. Emerging gigascale integration technologies offer the opportunity to explore alternative computing architectures that can deliver a significant boost to on-board computing when implemented in embedded, reconfigurable devices. This paper explores the mapping of low level feature extraction on one such architecture, the Georgia Tech SIMD Pixel Processor (SIMPil). The Fast Boundary Web Extraction (fBWE) algorithm is adapted and mapped on SIMPil as a fixed-point, data parallel imple…

Illumination correction on biomedical images

RF-Inhomogeneity Correction (aka bias) artifact is an important re- search field in Magnetic Resonance Imaging (MRI). Bias corrupts MR images alter- ing their illumination even though they are acquired with the most recent scanners. Homomorphic Unsharp Masking (HUM) is a filtering technique aimed at correcting illumination inhomogeneity, but it produces a halo around the edges as a side effect. In this paper a novel correction scheme based on HUM is proposed to correct the artifact mentioned above without introducing the halo. A wide experimentation has been performed on MR images. The method has been tuned and evaluated using the simulated Brainweb image database. In this framework, the ap…

SAIApp: a web application of the university of palermo dedicated to children with autoinflammatory syndromes

Introduction: The recent epidemic strongly evidenced the necessity of reorganizing physician work, patients’ access to clinics and patient support, especially for chronic diseases. In this field, a good strategy must consider the integration between department pediatricians, multidisciplinary specialists and pediatricians in private practice. Besides, adequate standards of care must be ensured especially for children affected by chronic diseases, as Autoinflammatory syndromes. Objectives: These children need to monitor clinical manifestations, attacks-free intervals, treatment adherence and response, onset of short- and long-term complications. This surveillance is a fundamental step to gua…

Formal Description of Web User Interfaces for Automatic Generation

A Combined Fuzzy Semantic Similarity Measure In Owl Ontologies

An algorithm is presented in this paper to calculate a semantic similarity measure inside an OWL ontology. The formulation is based on a combined measure taking into account the two most important aspects involved in the similarity computation. These are the structural properties of a concept, and the information content inside the ontology. We define a fuzzy system to blend these information sources with a training process over some ontologies. Finding a similarity measure between concepts of an ontology is a fundamental topic to accomplish information exchange on the Web. Through this measure it is possible to perform sophisticated queries over the web where the user is able to request co…

Three-dimensional geometrical models of the inguinal region. Towards a new stereology.

In this work we studied the inguinal-abdominal region and the inguinal canal using three-dimensional geometrical models. We built the models through computer aided geometric modeling techniques on the basis of observations during real dissections, operations and diagnostic medical imaging. The obtained models show in a complete modular synthesis and with a schematic iconology the structural organization of the anatomical districts in a logic sequence of layers and topographic and spatial relationships among its components. The models represent an amazing support to anatomy and clinical anatomy for teaching and research purposes on organogenesis, surgery and diagnosis.

Blood Vessel Detection Algorithm for Tissue Engineering and Quantitative Histology.

AbstractImmunohistochemistry for vascular network analysis plays a fundamental role in basic science, translational research and clinical practice. However, identifying vascularization in histological tissue images is time consuming and markedly depends on the operator’s experience. In this study, we present “blood vessel detection—BVD”, an automatic algorithm for quantitative analysis of blood vessels in immunohistochemical images. BVD is based on extraction and analysis of low-level image features and spatial filtering techniques, which do not require a training phase. BVD algorithm performance was comparatively evaluated on histological sections from three different in vivo experiments. …

DAISY: a distributed architecture for intelligent SYstem

Distributed perceptual systems are endowed with different kind of sensors, from which information flows to suitable modules to perform useful elaborations for decisions making. In this paper a new distributed architecture, named 'Distributed Architecture for Intelligent SYstem' (DAISY), is proposed. It is based on the concept of co-operating behavioral agents supervised by a 'Central Engagement Module'. This module integrates the processing of data coming from the behavioral agents with a symbolic level of representation, by the introduction of a 'conceptual space' intermediate analogue representation. The DAISY project is under development; experiments on navigation and exploration for an …

Platform session

A neural architecture for 3D segmentation

An original neural scheme for segmentation of range data is presented, which is part of a more general 3D vision system for robotic applications. The entire process relies on a neural architecture aimed to perform first order image irradiance analysis, that is local estimation of magnitude and orientation of the image irradiance gradient.In the case of dense 3D data, irradiance is replaced by depth information so irradiance analysis of these pseudo-images provides knowledge about the actual curvature of the acquired surfaces. In particular, boundaries and contours due to mutual occlusions can be detected very well while there are no false contours due to rapid changing in brightness or colo…

An Effective Satellite Remote Sensing Tool Combining Hardware and Software Solutions

In this paper we propose a new effective remote sensing tool combining hardware and software solutions as an extension of our previous work. In greater detail the tool consists of a low cost receiver subsystem for public weather satellites and a signal and image processing module for several tasks such as signal and image enhancement, image reconstruction and cloud detection. Our solution allows to manage data from satellites effectively with low cost components and portable software solutions. We aim at sampling and processing of the modulated signal entirely in software enabled by Software Defined Radios (SDR) and CPU computational speed overcoming hardware limitation such as high receive…

An Automatic Method for PET Delineation of Cervical Tumors

Aim: PET imaging is increasingly utilized for radiation treatment planning. Nevertheless, accurate segmentation of PET images is a complex and unresolved problem. Aim of this work is the development of an automatic segmentation method of Biological Target Volume (BTV) in patients with cervical cancer. Materials and methods: Random walks (RW) is a graph-based method that represents a DICOM (Digital Imaging and COmmunications in Medicine) image as a graph. The voxels are its nodes and the edges are defined by a cost function which maps a change in image intensity to edge weights. Then, RW partitions the nodes into target and background subsets. To create an automatic method starting from prev…