Reports of the AAAI 2010 Fall Symposia

The Association for the Advancement of Artificial Intelligence was pleased to present the 2010 Fall Symposium Series, held Thursday through Saturday, November 11-13, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the eight symposia are as follows: (1) Cognitive and Metacognitive Educational Systems; (2) Commonsense Knowledge; (3) Complex Adaptive Systems: Resilience, Robustness, and Evolvability; (4) Computational Models of Narrative; (5) Dialog with Robots; (6) Manifold Learning and Its Applications; (7) Proactive Assistant Agents ; and (8) Quantum Informatics for Cognitive, Social, and Semantic Processes. The highlights of each symposium are presented in this report.

TutorJ: un Intelligent Tutoring System di Supporto all'Apprendimento di Java

A SOM/ARSOM Hierarchy for the Description of Dynamic Scenes

A neural architecture is presented, aimed to describe the dynamic evolution of complex structures inside a video sequence. The proposed system is arranged as a tree of self-organizing maps. Leaf nodes are implemented by ARSOM networks as a way to code dynamic inputs, while classical SOM's are used to implement the upper levels of the hierarchy. Depending on the application domain, inputs are made by suitable low level features extracted frame by frame of the sequence. Theoretical foundations of the architecture are reported along with a detailed outline of its structure, and encouraging experimental results.

Semantics driven interaction using natural language in students tutoring

The aim of this work is to introduce a semantic integration between an ontology and a chatbot in an Intelligent Tutoring Systems (ITS) to interact with students using natural language. The interaction process is driven by the use of a purposely defined ontology. In the ontology two types of conceptual relations are defined. Besides the usual relations, which are used to define the domain's structure, another type of relation is used to define the navigation schema inside the ontology according to the need of managing uncertainty. Uncertainty level is related to student knowledge level about the involved concepts. In this work we propose an ITS for the Java programming language called TutorJ…

Segmentation of MR brain images with bias artifact

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.

GAIML: A New Language for Verbal and Graphical Interaction in Chatbots

Natural and intuitive interaction between users and complex systems is a crucial research topic in human-computer interaction. A major direction is the definition and implementation of systems with natural language understanding capabilities. The interaction in natural language is often performed by means of systems called chatbots. A chatbot is a conversational agent with a proper knowledge base able to interact with users. Chatbots appearance can be very sophisticated with 3D avatars and speech processing modules. However the interaction between the system and the user is only performed through textual areas for inputs and replies. An interaction able to add to natural language also graph…

Homomorphic Approach to RF-Inhomogeneity Removal Based on Gabor Filter

In this paper a bias correction algorithm for magnetic resonance imaging (MRI) is presented. The magnetic resonance (MR) images affected by this artifact, also called RF-inhomogeneity, exhibit irregular spatial brightness variations caused by magnetic field inhomogeneity. Here we present an original algorithm based on E2D - HUM, already proposed by some of the authors, where a modified Gabor filter is introduced in the elaboration chain to provide directional capabilities to suppress the artifact. The process of restoration doesn't care about the structure of the image and it has been applied to MR images of different parts of body like knee, abdomen, pelvis and brain. A comparison with oth…

UNA PROCEDURA PER VALUTARE “AUTOMATICAMENTE” IL LIVELLO DI APPRENDIMENTO DEGLI STUDENTI

Semantic technologies for industry: From knowledge modeling and integration to intelligent applications

Artificial Intelligence technologies are growingly used within several software systems ranging from Web services to mobile applications. It is by no doubt true that the more AI algorithms and methods are used the more they tend to depart from a pure "AI" spirit and end to refer to the sphere of standard software. In a sense, AI seems strongly connected with ideas, methods and tools that are not (yet) used by the general public. On the contrary, a more realistic view of it would be a rich and pervading set of successful paradigms and approaches. Industry is currently perceiving semantic technologies as a key contribution of AI to innovation. In this paper a survey of current industrial expe…

I-ChatbIT: An intelligent chatbot for the Italian Language

A novel chatbot architecture for the Italian language is presented that is aimed at implementing cognitive under- standing of the query by locating its cor- respondent subgraph in the agent’s KB by means of a graph matching strategy pur- posely devised. The FCG engine is used for producing replies starting from the se- mantic poles extracted from the candidate answers’ subgraphs. The system imple- ments a suitable disambiguation strategy for selecting the correct answer by analyz- ing the commonsense knowledge related to the adverbs in the query that is embed- ded in the lexical constructions of the ad- verbs themselves as a proper set of fea- tures. The whole system is presented, and a com…

Blood vessels and feature points detection on retinal images

In this paper we present a method for the automatic extraction of blood vessels from retinal images, while capturing points of intersection/overlap and endpoints of the vascular tree. The algorithm performance is evaluated through a comparison with handmade segmented images available on the STARE project database (STructured Analysis of the REtina). The algorithm is performed on the green channel of the RGB triad. The green channel can be used to represent the illumination component. The matched filter is used to enhance vessels w.r.t. the background. The separation between vessels and background is accomplished by a threshold operator based on gaussian probability density function. The len…

Named Entity Recognition and Linking in Tweets Based on Linguistic Similarity

This work proposes a novel approach in Named Entity rEcognition and Linking (NEEL) in tweets, applying the same strategy already presented for Question Answering (QA) by the same authors. The previous work describes a rule-based and ontology-based system that attempts to retrieve the correct answer to a query from the DBPedia ontology through a similarity measure between the query and the ontology labels. In this paper, a tweet is interpreted as a query for the QA system: both the text and the thread of a tweet are a sequence of statements that have been linked to the ontology. Provided that tweets make extensive use of informal language, the similarity measure and the underlying processes …

Automatic Extraction of Blood Vessels, Bifurcations and End Points in the Retinal Vascular Tree

In this paper we present an effective algorithm for automated extraction of the vascular tree in retinal images, including bifurcations, crossovers and end-points detection. Correct identification of these features in the ocular fundus helps the diagnosis of important systematic diseases, such as diabetes and hypertension. The pre-processing consists in artefacts removal based on anisotropic diffusion filter. Then a matched filter is applied to enhance blood vessels. The filter uses a full adaptive kernel because each vessel has a proper orientation and thickness. The kernel of the filter needs to be rotated for all possible directions. As a consequence, a suitable kernel has been designed …

Pervasive access to MRI bias artifact suppression service on a grid.

Bias artifact corrupts magnetic resonance images in such a way that the image is afflicted by illumination variations. Some of the authors proposed the Exponential Entropy Driven - Homomorphic Unsharp Masking (E2D-HUM) algorithm that corrects this artifact without any a priori hypothesis about the tissues or the Magnetic Resonance image modality. Moreover, E2D-HUM does not care about the body part under examination and does not require any particular training task. People who want to use this algorithm, which is Matlab-based, have to set their own computers in order to execute it. Furthermore, they have to be Matlab-skilled to exploit all the features of the algorithm. In our work we propos…

Fuzzy C-Means Inspired Free Form Deformation Technique for Registration

This paper presents a novel method aimed to free form deformation function approximation for purpose of image registration. The method is currently feature-based. The algorithm is inspired to concepts derived from Fuzzy C-means clustering technique such as membership degree and cluster centroids. After algorithm explanation, tests and relative results obtained are presented and discussed. Finally, considerations on future improvements are elucidated.

Pose classification using support vector machines

In this work a software architecture is presented for the automatic recognition of human arm poses. Our research has been carried on in the robotics framework. A mobile robot that has to find its path to the goal in a partially structured environment can be trained by a human operator to follow particular routes in order to perform its task quickly. The system is able to recognize and classify some different poses of the operator's arms as direction commands like "turn-left", "turn-right", "go-straight", and so on. A binary image of the operator silhouette is obtained from the gray-level input. Next, a slice centered on the silhouette itself is processed in order to compute the eigenvalues …

A Neural Architecture for Segmentation and Modelling of Range Data

A novel, two stage, neural architecture for the segmentation of range data and their modeling with undeformed superquadrics is presented. The system is composed by two distinct neural stages: a SOM is used to perform data segmentation, and, for each segment, a multi-layer feed-forward network performs model estimation. The topology preserving nature of the SOM algorithm makes this architecture suited to cluster data with respect to sudden curvature variations. The second stage is designed to model and compute the inside-outside function of an undeformed superquadric in whatever attitude, starting form the (x, y, z) data triples. The network has been trained using backpropagation, and the we…

A Multi-Scale Colour and Keypoint Density-Based Approach for Visual Saliency Detection

In the first seconds of observation of an image, several visual attention processes are involved in the identification of the visual targets that pop-out from the scene to our eyes. Saliency is the quality that makes certain regions of an image stand out from the visual field and grab our attention. Saliency detection models, inspired by visual cortex mechanisms, employ both colour and luminance features. Furthermore, both locations of pixels and presence of objects influence the Visual Attention processes. In this paper, we propose a new saliency method based on the combination of the distribution of interest points in the image with multiscale analysis, a centre bias module and a machine …

A Teledentistry system for the second opinion

In this paper we present a Teledentistry system aimed to the Second Opinion task. It make use of a particular camera called intra-oral camera, also called dental camera, in order to perform the photo shooting and real-time video of the inner part of the mouth. The pictures acquired by the Operator with such a device are sent to the Oral Medicine Expert (OME) by means of a current File Transfer Protocol (FTP) service and the real-time video is channeled into a video streaming thanks to the VideoLan client/server (VLC) application. It is composed by a HTML5 web-pages generated by PHP and allows to perform the Second Opinion both when Operator and OME are logged and when one of them is offline.

ChiLab4It system in the QA4FAQ competition

ChiLab4It is the Question Answering system (QA) for Frequently Asked Questions (FAQ) developed by the Computer-Human Interaction Laboratory (ChiLab) at the University of Palermo for participating to the QA4FAQ task at EVALITA 2016 competition. The system is the versioning of the QuASIt framework developed by the same authors, which has been customized to address the particular task. This technical report describes the strategies that have been imported from QuASIt for implementing ChiLab4It, the actual system implementation, and the comparative evaluations with the results of the other participant tools, as provided by the organizers of the task. ChiLab4It was the only system whose score re…

Fuzzy C-Means Segmentation on Brain MR Slices Corrupted by RF-Inhomogeneity

Brain MR Images corrupted by RF-Inhomogeneity exhibit brightness variations in such a way that a standard Fuzzy C-Means (fcm) segmentation algorithm fails. As a consequence, modified versions of the algorithm can be found in literature, which take into account the artifact. In this work we show that the application of a suitable pre-processing algorithm, already presented by the authors, followed by a standard fcm segmentation achieves good results also. The experimental results ones are compared with those obtained using SPM5, which can be considered the state of the art algorithm oriented to brain segmentation and bias removal.

A Two Stage Neural Architecture for Segmentation and Superquadrics Recovery from Range Data

A novel, two stage, neural architecture for the segmentation of range data and their modeling with undeformed superquadrics is presented. The system is composed by two distinct neural networks: a SOM is used to perform data segmentation, and, for each segment, a multilayer feed-forward network performs model estimation.

Physical Metaphor for Streaming Media Retargeting

We here introduce an image/video retargeting method that operates arbitrary aspect ratios resizing achieved in real-time performances. Most of the literature retargeting approaches sacrifice real-time performances in behalf of quality. On the other hand, existing fast methods provide arguable results. We can obtain a valuable trade-off between effectiveness and efficiency. The method named Spring Simulation Retargeting (SSR) is mainly based on a physical springs-based simulation. The media are assumed as flexible objects composed of particles and springs with different local stiffness properties, related to the visual importance of the content. The variation of the object size generates ela…

Noise Filtering Using Edge-Driven Adaptive Anisotropic Diffusion

This paper presents a method aimed to noise removal in MRI (Magnetic Resonance Imaging). We propose an improvement of Perona and Malik's anisotropic diffusion filter. In our schema, the diffusion equation of the filter has been modified to take into account the edges direction, This allows the filter to blur uniform areas, while it better preserves the edges. Both quantitative and qualitative evaluation is presented and the results are compared with other methods.

Semi-automated evaluation of small bowel mural attenuation at CT enterography using different temporal windows in patients affected by active Crohn disease

A combined semantic-syntactic sentence analysis for students assessment

TutorJ is an Intelligent Tutoring System able to fulfill the requests of a student with a learning path inside didactical materials. To this aim, it must assess the level of training of the learner. In the first version of TutorJ this goal was reached through a conversational agent whose linguistic interaction enriched by a LSA-based text analysis. This approach suffers from the limitations of LSA as a bag-of- words approach. Next, morphosyntactic comparison of sentences' structures was implemented. In this paper we present a new version of the assessment procedure involving both semantic, and morphosyntactic analysis user's sentences.

EMBER—Embedding Multiple Molecular Fingerprints for Virtual Screening

In recent years, the debate in the field of applications of Deep Learning to Virtual Screening has focused on the use of neural embeddings with respect to classical descriptors in order to encode both structural and physical properties of ligands and/or targets. The attention on embeddings with the increasing use of Graph Neural Networks aimed at overcoming molecular fingerprints that are short range embeddings for atomic neighborhoods. Here, we present EMBER, a novel molecular embedding made by seven molecular fingerprints arranged as different “spectra” to describe the same molecule, and we prove its effectiveness by using deep convolutional architecture that assesses ligands&…

A Map-Based Visualization Tool To Support Tutors In E-Learning 2.0

Web 2.0 regards essentially the social issues about the new usage of web applications, but participative web and user generated contents induce a new way to think about the design of the web applications themselves. This is particularly true in the field of educational systems that are all web based applications. Many researchers are now devoted to study what is called e-learning 2.0 both as regards the technological issues in the field of computer science, and in relation to the impact of the web 2.0 social and psychological issues on the education process itself. One of the most crucial topics in e-learning 2.0 is the way to provide support to the teacher/tutor to avoid cognitive overload…

Learning Path Generation by Domain Ontology Transformation

An approach to automated learning path generation inside a domain ontology supporting a web tutoring system is presented. Even if a terminological ontology definition is needed in real systems to enable reasoning and/or planning techniques, and to take into account the modern learning theories, the task to apply a planner to such an ontology is very hard because the definition of actions along with their preconditions and effects has to take into account the semantics of the relations among concepts, and it results in building an ontology of learning. The proposed methodology is inspired to the Knowledge Space Theory, and proposes some heuristics to transform the original ontology in a weig…

A PCA Interpretation of the Glasgow Coma Scale in the Trauma Brain Injury PECARN Dataset

CT scan is strongly recommended for a patient affected by head trauma, but he/she must absorb a certain amount of radiations. For this reason, the physician tries to avoid such a practice for pediatric patients. The symptoms analysis, visual/tactile inspection, and reactions to appropriate stimuli from the physician could induce him/her to put the patient in a period of observation instead of performing an immediate CT scan. As a consequence, the correct evaluation of those symptoms is a crucial task. For this reason, the Pediatric Glasgow Coma Scale (PGCS) plays a fundamental role, because it is a numeric scale regarding the patient’s mental status. It is computed as the sum of the score f…

Springs-based Simulation for Image Retargeting

In this paper an efficient method for image retargeting is pro- posed. It relies onto a mechanical model based on springs network. Each pixel displacement (compression or expan- sion) is given by the network response, according to the springs stiffness. The properties of the springs are deter- mined as function of the visual relevance of the pixels. Such model does not require any optimization, since its so- lution is obtained simply from a linear system of equations, allowing real-time application even for large images. The approach is fully automatic, though can be improved by interactively providing cues such as geometric constraints and/or manual relevant object labeling. The results pr…

VEBO: Validation of E-R diagrams through ontologies and WordNet

In the semantic web vision, ontologies are building blocks for providing applications with a high level description of the operating environment in support of interoperability and semantic capabilities. The importance of ontologies in this respect is clearly stated in many works. Another crucial issue to increase the semantic aspect of web is to enrich the level of expressivity of database related data. Nowadays, databases are the primary source of information for dynamical web sites. The linguistic data used to build the database structure could be relevant for extracting meaningful information. In most cases, this type of information is not used for information retrieval. The work present…

Clinical Anatomy and information technology.

Linear density-based clustering with a discrete density model

Density-based clustering techniques are used in a wide range of data mining applications. One of their most attractive features con- sists in not making use of prior knowledge of the number of clusters that a dataset contains along with their shape. In this paper we propose a new algorithm named Linear DBSCAN (Lin-DBSCAN), a simple approach to clustering inspired by the density model introduced with the well known algorithm DBSCAN. Designed to minimize the computational cost of density based clustering on geospatial data, Lin-DBSCAN features a linear time complexity that makes it suitable for real-time applications on low-resource devices. Lin-DBSCAN uses a discrete version of the density m…

Biological target volume segmentation for radiotherapy treatment planning

Lemongrass Plant as Potential Sources of Reinforcement for Biocomposites: A Preliminary Experimental Comparison Between Leaf and Culm Fibers

AbstractNowadays, the world requires more sustainable and eco-friendly materials to replace or limit the usage of synthetic materials. Moreover, several researchers focused their attention on the use of agricultural sources as reinforcement for biocomposites since they are abundant, cost-effective and environmentally favorable sources. In such a context, purpose of the present paper is the evaluation of lemongrass plant (Cymbopogon flexuosus) as possible source of natural reinforcement for biocomposites. To this aim, natural fibers were obtained from the leaf and the stem of lemongrass and their main properties were compared for the first time. To this scope, mechanical and thermal characte…

An Innovative Statistical Tool for Automatic OWL-ERD Alignment

Aligning two representations of the same domain with different expressiveness is a crucial topic in nowadays semantic web and big data research. OWL ontologies and Entity Relation Diagrams are the most widespread representations whose alignment allows for semantic data access via ontology interface, and ontology storing techniques. The term ""alignment" encompasses three different processes: OWL-to-ERD and ERD-to-OWL transformation, and OWL-ERD mapping. In this paper an innovative statistical tool is presented to accomplish all the three aspects of the alignment. The main idea relies on the use of a HMM to estimate the most likely ERD sentence that is stated in a suitable grammar, and corre…

Restoration of out-of-focus images based on circle of confusion estimate

In this paper a new method for a fast out-of-focus blur estimation and restoration is proposed. It is suitable for CFA (Color Filter Array) images acquired by typical CCD/CMOS sensor. The method is based on the analysis of a single image and consists of two steps: 1) out-of-focus blur estimation via Bayer pattern analysis; 2) image restoration. Blur estimation is based on a block-wise edge detection technique. This edge detection is carried out on the green pixels of the CFA sensor image also called Bayer pattern. Once the blur level has been estimated the image is restored through the application of a new inverse filtering technique. This algorithm gives sharp images reducing ringing and c…

Reports of the AAAI 2009 Fall Symposia

The Association for the Advancement of Artificial Intelligence was pleased to present the 2009 Fall Symposium Series, held Thursday through Saturday, November 5–7, at the Westin Arlington Gateway in Arlington, Virginia. The Symposium Series was preceded on Wednesday, November 4 by a one-day AI funding seminar. The titles of the seven symposia were as follows: (1) Biologically Inspired Cognitive Architectures, (2) Cognitive and Metacognitive Educational Systems, (3) Complex Adaptive Systems and the Threshold Effect: Views from the Natural and Social Sciences, (4) Manifold Learning and Its Applications, (5) Multirepresentational Architectures for Human-Level Intelligence, (6) The Uses of Comp…

A Web-Oriented Java3D Talking Head

Facial animation denotes all those systems performing speech synchro- nization with an animated face model. These kinds of systems are named Talking Heads or Talking Faces. At the same time simple dialogue systems called chatbots have been developed. Chatbots are software agents able to interact with users through pattern-matching based rules. In this paper a Talking Head oriented to the creation of a Chatbot is presented. An answer is generated in form of text trig- gered by an input query. The answer is converted into a facial animation using a 3D face model whose lips movements are synchronized with the sound produced by a speech synthesis module. Our Talking Head exploits the naturalnes…

Volumetric Bias Correction

This paper presents a method to suppress the bias artifact, also known as RF-inhomogeneity, in Magnetic Resonance Imaging (MRI). This artifact produces illumination variations due to magnetic field fluctuations of the device. In the latest years many works have been devoted to face this problem. In this work we present the 3D version of a new approach to bias correction, which is called Exponential Entropy Driven Homomorphic Unsharp Masking (E2D-HUM). This technique has been already presented by some of the authors for the 2D case only. The description of the whole method is detailed, and some experimental results are reported.

A vision system for symbolic interpretation of dynamic scenes using arsom

We describe an artificial high-level vision system for the symbolic interpretation of data coming from a video camera that acquires the image sequences of moving scenes. The system is based on ARSOM neural networks that learn to generate the perception-grounded predicates obtained by image sequences. The ARSOM neural networks also provide a three-dimensional estimation of the movements of the relevant objects in the scene. The vision system has been employed in two scenarios: the monitoring of a robotic arm suitable for space operations, and the surveillance of an electronic data processing (EDP) center.

Population and Query Interface for a Content-Based Video Database

In this paper we describe the first full implementation of a content-based indexing and retrieval system for MPEG-2 and MPEG-4 videos. We consider a video as a collection of spatiotemporal segments called video objects; each video object is a sequence of video object planes. A set of representative video object planes is used to index each video object. During the database population, the operator, using a semi-automatic outlining tool we developed, manually selects video objects and insert some semantical information. Low-level visual features like color, texture, motion and geometry are automatically computed. The system has been implemented on a commercial relational DBMS and is based on…

Accessibility of the Italian institutional web pages: a survey on the compliance of the Italian public administration web pages to the Stanca Act and its 22 technical requirements for web accessibility

Accessibility of the Italian public administration web pages is ruled by the Stanca Act and in particular the Decree of the Minister issued on July 8, 2005. In this paper, an objective test is performed on the official web pages of the Italian province and region chief towns to check their compliance to the 22 technical requirements defined by the Stanca Act. A sample of 976 web pages belonging to the websites of the Italian chief towns have been downloaded in the period October---December 2012. Such a data collection has been submitted to Achecker, the worldwide recognized syntax and accessibility validation service. Several accessibility and syntax errors have been found following the aut…

Modeling ontologies for robotic environments

On the basis of a multiple abstraction levels specification process, we developed a representational model for environmental robotic knowledge through the definition of a set of ontologies using a multi perspective approach. A general ontological model for typical indoor environments has been first developed, followed by its specialization using an implementation perspective. Actual software implementation of the ontology has been obtained via a XML-based markup language, used to build a repository for robotic environmental knowledge. Copyright 2002 ACM.

A M3G Talking Head for Smartphones

Often customer information services or virtual support guides make use of friendly interface to facilitate human-machine interaction. Indeed, virtual guided tours or helpdesks use a talking anthropomorphic head to communicate with the user. In this paper, we present a talking head for Smart phones, PDAs and, in general, all the mobile devices able to support J2ME and MIDP protocol. The objective of this article is to illustrate how to make such an interface as portable as possible by maximizing the limited computational resources of these devices.

HCI for biomedical decision-making: From diagnosis to therapy.

Abstract Human-Computer Interaction (HCI) plays a fundamental role in the design of software oriented towards clinical decision-making tasks. Currently, physicians have to deal with an ensemble of systems and software tools in the clinical environment, such as clinical Decision Support Systems (CDSSs), Electronic Health Records (EHRs), Picture Archiving and Communication Systems (PACSs). Moreover, additional platforms aim at collaborative work particularly in telemedicine, where rehabilitation technologies and conversational agents can support the healthcare professionals.

A computer support system to support diagnosis by imaging and its experimental application to images of patients affected by multiple sclerosis

Multi-modal Image Registration Using Fuzzy Kernel Regression

This paper presents a study aimed to the realization of a novel multiresolution registration framework. The transformation function is computed iteratively as a composition of local deformations determined by the maximization of mutual information. At each iteration, local transformations are joint together using fuzzy kernel regression. This technique represents the core of the mothod and it's formally described from a probabilistic perspective. It avoids blocking artifacts and allows to keep the final deformation spatially congruent and smooth. Both qualitative and quantitative experimental results show that this approach is equally effective for registering datasets acquired from both si…

SAIApp: un'app dell'Università di Palermo dedicata ai bambini con malattie autoinfiammatorie

Bias Correction on Knee MR Images

Knowledge Discovery and Digital Cartography for the ALS (Linguistic Atlas of Sicily) Project

In this paper the latest developments of the ALS (Linguistic Atlas of Sicily) project are presented. The ALS project has the purpose to define methodologies and tools to allow researches in the socio-linguistic field. Different types of variables (both quantitative and qualitative) are involved. The whole framework is based on the definition of ontology-based applications for the creation, retrieval, manipulation and browsing of related data. To this aim, some mapping processes have been defined. The framework eventually shows the result in many ways including spatial maps. The on-going collaboration process is a perfect example a domain hybridizing process, enabling the training on-the-fie…

Application of an intelligent study and research support system for clinical anatomy in a cooperation scenario

Scientific research and teaching are strongly interrelated. A student should be educated both to the fundamentals of a discipline and to the research tasks as the future development of a discipline is entrusted to the students of today. Computer based tutoring systems already showed useful in pursuing the former target while the Intelligent Study and Research Support System developed at DINFO may be used to fulfill both in an integrated manner. This paper introduces the possible application of the ISRSS to training of Clinical Anatomy in a scenario of international cooperation among academic institutions.

QuASIt: A Cognitive Inspired Approach to Question Answering for the Italian Language

In this paper we present QuASIt, a Question Answering System for the Italian language, and the underlying cognitive architecture. The term cognitive is meant in the procedural semantics perspective, which states that the interpretation and/or production of a sentence requires the execution of some cognitive processes over both a perceptually grounded model of the world, and a linguistic knowledge acquired previously. We attempted to model these cognitive processes with the aim to make an artificial agent able both to understand and produce natural language sentences. The agent runs these processes on its inner domain representation using the linguistic knowledge also. In this sense, QuASIt …

Biologically Inspired Vision Architectures: a Software/Hardware Perspective

Even tough the field of computer vision has seen huge improvement in the last few decades, computer vision systems still lack, in most cases, the efficiency of biological vision systems. In fact biological vision systems routinely accomplish complex visual tasks such as object recognition, obstacle avoidance, and target tracking, which continue to challenge artificial systems. The study of biological vision system remains a strong cue for the design of devices exhibiting intelligent behaviour in visually sensed environments but current artificial systems are vastly different from biological ones for various reasons. First of all, biologically inspired vision architectures, which are continu…

Cognitive Linguistics as the Underlying Framework for Semantic Annotation

In recent years many attempts have been made to design suitable sets of rules aimed at extracting the semantic meaning from plain text, and to achieve annotation, but very few approaches make extensive use of grammars. Current systems are mainly focused on extracting the semantic role of the entities described in the text. This approach has limitations: in such applications the semantic role is conceived merely as the meaning of the involved entities without considering their context. As an example, current semantic annotators often specify a date entity without any annotation regarding the kind of the date itself i.e. a birth date, a book publication date, and so on. Moreover, these system…

GAIML: A New Language for Verbal and Graphical Interaction in Chatbots

One of the aims of the research in the field of the human-computer interaction is the design of a natural and intuitive interaction modalities. In particular, many efforts have been devoted in the development of systems able to interact with the user in natural language. Chatbots are the classical interfaces for natural language interaction. Such systems can be very sophisticated, including support for 3D avatars and speech analysis and synthesis. However, all of them present only a text area allowing the user to input her sentences. No doubt, an interaction involving also the natural language can increase the comfort of the user with respect to common interfaces using only graphical widget…

A Semantic Similarity Measure for the SIMS Framework

The amount of currently available digital information grows rapidly. Relevant information is often spread over different information sources. An efficient and flexible framework to allow users to satisfy ef- fectively their information needs is required. The work presented in this paper describes SIMS (Semantic Information Management System), a ref- erence architecture for a framework performing semantic annotation, search and retrieval of information from multiple sources. The work pre- sented in this paper focuses on a specific SIMS module, the SIMS Semantic Content Navigator, proposing an algorithm and the related implementa- tion to calculate a semantic similarity measure inside an OWL …

Evolving Tree Algorithm Modifications

There are many variants of the original self-organizing neural map algorithm proposed by Kohonen. One of the most recent is the Evolving Tree, a tree-shaped self-organizing network which has many interesting characteristics. This network builds a tree structure splitting the input dataset during learning. This paper presents a speed-up modification of the original training algorithm useful when the Evolving Tree network is used with complex data as images or video. After a measurement of the effectiveness an application of the modified algorithm in image segmentation is presented.

Lessico e e-learning

An image retrieval system for artistic database on cultural heritage

A Low Cost Solution for NOAA Remote Sensing

United States National Oceanic and Atmospheric Administration (NOAA) weather satellites adopt Advanced Very High Resolution Radiometer (AVHRR) sensors to acquire remote sensing data and broadcast Automatic Picture Transmission (APT) images. The orientation of the scan lines is perpendicular to the orbit of the satellite. In this paper we propose a new low cost solution for NOAA remote sensing. More in detail, our method focuses on the possibility of directly sampling the modulated signal and processing it entirely in software enabled by recent breakthroughs on Software Defined Radios (SDR) and CPU computational speed, while keeping the costs extremely low. We aim to achieve good results wit…

A software system to support the description and the explanation of medical images based on medical diagnosis criteria

Discovering learning paths on a domain ontology using natural language interaction

The present work investigates the problem of determining a learning path inside a suitable domain ontology. The proposed approach enables the user of a web learning application to interact with the system using natural language in order to browse the ontology itself. The course related knowledge is arranged as a three level hierarchy: content level, symbolic level, and conceptual level bridging the previous ones. The implementation of the ontological, the interaction, and the presentation component inside the TutorJ system is explained, and the first results are presented.

An Emotional Talking Head for a Humoristic Chatbot

The interest about enhancing the interface usability of applications and entertainment platforms has increased in last years. The research in human-computer interaction on conversational agents, named also chatbots, and natural language dialogue systems equipped with audio-video interfaces has grown as well. One of the most pursued goals is to enhance the realness of interaction of such systems. For this reason they are provided with catchy interfaces using humanlike avatars capable to adapt their behavior according to the conversation content. This kind of agents can vocally interact with users by using Automatic Speech Recognition (ASR) and Text To Speech (TTS) systems; besides they can c…

A Neuro-Genetic Approach to Real-Time Visual Grasp Synthesis

Grasping is an essential prerequisite for an agent, either human or robotic, to manipulate various kinds of objects present in the world. It is a fact that we would like robots to have the same skills as we do. However, despite the construction of human-hand-like robotic effectors, much work is still to be done in order to give robots the capability to grasp and manipulate objects. The goal of this work is to automatically perform grasp synthesis of unknown planar objects. In other words, we must compute points on the object's boundary to be reached by the robotic fingers such that the resulting grasp, among infinite possibilities, optimizes some given criteria. The space of possible config…

Medical image registration: Interpolations, similarities and optimizations strategies

This paper presents a study conducted for evaluating different interpolation schemes, similarity metrics and optimization algorithms for the purpose of volumetric medical image registration. Each technique has been implemented to be plugged in a modular system. Rotation, translation and scale error has been measured to obtain a performance evaluation for all of the combinations of the considered techniques. Several experimental tests were conducted for validation both on synthetic and real datasets providing an exhaustive overview of the various strategies used.

A Hidden Markov Model for Automatic Generation of ER Diagrams from OWL Ontology

Connecting ontological representations and data models is a crucial need in enterprise knowledge management, above all in the case of federated enterprises where corporate ontologies are used to share information coming from different databases. OWL to ERD transformations are a challenging research field in this scenario, due to the loss of expressiveness arising when OWL axioms have to be represented using ERD notation. In this paper we propose an innovative technique for estimating the most likely composition of ERD constructs that correspond to a given sequence of OWL axioms. We model such a process using a Hidden Markov Model (HMM) where the OWL inputs are the observable states, while E…

Semantic sense extraction from Wikipedia pages

This paper presents a technique aimed to extract structured information from unstructured Wikipedia contents related to a particular topic, and to arrange it in a semantic way inside an ontology. The general framework is the design of an artificial agent able to deliberate when increasing its domain knowledge. In particular, this cognitive agent acts as a dialogue manager in an Intelligent Tutoring System (ITS) already presented by the authors. Our approach is based on the definition of useful patterns able to extract and identify novel concepts and relations to be added to the knowledge base. We propose a method that uses information from the wiki page’s structure. We define different stra…

Convolutional architectures for virtual screening

Abstract Background A Virtual Screening algorithm has to adapt to the different stages of this process. Early screening needs to ensure that all bioactive compounds are ranked in the first positions despite of the number of false positives, while a second screening round is aimed at increasing the prediction accuracy. Results A novel CNN architecture is presented to this aim, which predicts bioactivity of candidate compounds on CDK1 using a combination of molecular fingerprints as their vector representation, and has been trained suitably to achieve good results as regards both enrichment factor and accuracy in different screening modes (98.55% accuracy in active-only selection, and 98.88% …

L'Interazione tra uomo e robot attraverso la rete:tecnologie innovative, applicazioni e risorse

Slice to Volume Registration

A framework for data-driven adaptive GUI generation based on DICOM

Computer applications for diagnostic medical imaging provide generally a wide range of tools to support physicians in their daily diagnosis activities. Unfortunately, some functionalities are specialized for specific diseases or imaging modalities, while other ones are useless for the images under investigation. Nevertheless, the corresponding Graphical User Interface (GUI) widgets are still present on the screen reducing the image visualization area. As a consequence, the physician may be affected by cognitive overload and visual stress causing a degradation of performances, mainly due to unuseful widgets. In clinical environments, a GUI must represent a sequence of steps for image investi…

MORPHOLOGICAL BRAIN EXTRACTION FROM PD-WEIGHTED MR IMAGES: ALGORITHM AND EXPERIMENTATION

Real-Time Visual Grasp Synthesis Using Genetic Algorithms and Neural Networks

This paper addresses the problem of automatic grasp synthesis of unknown planar objects. In other words, we must compute points on the object’s boundary to be reached by the robotic fingers such that the resulting grasp, among infinite possibilities, optimizes some given criteria. Objects to be grasped are represented as superellipses, a family of deformable 2D parametric functions. They can model a large variety of shapes occurring often in practice by changing a small number of parameters. The space of possible grasp configurations is analyzed using genetic algorithms. Several quality criteria from existing literature together with kinematical and mechanical considerations are considered.…

Effective and Efficient Interpolation for Mutual Information based Multimodality Elastic Image Registration

Mutual information (MI) is a popular similarity metric for multimodality image registration purpose. However, it is negatively influenced by artifacts due to interpolation effects. As a result, registration algorithms performance could be affected. In this paper a novel interpolation scheme is presented. It is both effective and efficient. Effective because it limits the presence of local maxima in the mutual information curve, efficient because it is simple to compute being based on simple and optimized distance measures. The method is validated and compared against other techniques both from performance and time complexity persepectives. Differently from other reference works, which perfo…

A KST-BASED SYSTEM FOR STUDENT TUTORING

Abstract: A novel assessment procedure based on knowledge space theory (KST) is presented along with a complete implementation of an intelligent tutoring system. (ITS) that has been used to test our theoretical findings. The key idea is that correct assessment of the student knowledge is strictly related to the structure of the domain ontology. Suitable relationships between the concepts must be present to allow the creation of a reverse path from the "knowledge state" representing the student goal to the one that contains her actual knowledge about this topic. Knowledge space theory is a very good framework to guide the process of building the ontology used, by the artificial tutor The sys…

Managing conversation uncertainty in TutorJ

Uncertainty in natural language dialogue is often treated through stochastic models. Some of the authors already presented TutorJ mat is an Intelligent Tutoring System, whose interaction with the user is very intensive, and makes use of both dialogic and graphical modality. When managing the interaction, the system needs to cope with uncertainty due to the understanding of the user's needs and wishes. In this paper we present the extended version of TutorJ, focusing on the new features added to its chatbot module. These features allow to merge deterministic and probabilistic reasoning in dialogue management, and in writing the rules of the system's procedural memory.

A convolutional neural network for virtual screening of molecular fingerprints

In the last few years, Deep Learning (DL) gained more and more impact on drug design because it allows a huge increase of the prediction accuracy in many stages of such a complex process. In this paper a Virtual Screening (VS) procedure based on Convolutional Neural Networks (CNN) is presented, that is aimed at classifying a set of candidate compounds as regards their biological activity on a particular target protein. The model has been trained on a dataset of active/inactive compounds with respect to the Cyclin-Dependent Kinase 1 (CDK1) a very important protein family, which is heavily involved in regulating the cell cycle. One qualifying point of the proposed approach is the use of molec…

An Explorable Immersive Panorama

The immersive panoramas are widely used to provide virtual tours of real scene. Their use covers a wide field of applications: art, industry, space research, topography, forensic investigation and all those systems requiring the exploration of a virtual environment which simulates a real one. Often sophisticated devices are used to perform the panorama acquisition. In this paper, we present an image based immersive panorama requiring low cost devices for the acquisition task and provides an innovative human-computer interaction approach. Many panoramic images of the same location are captured. The visualization system changes the panorama in a transparent way with respect to the user intera…

A Tunable Digital Ishihara Plate for Pre-School Aged Children

Colors play a fundamental role for children, both in the everyday life and in education. They recognize the surrounding world, and play games making a large use of colors. They learn letters and numbers by means of colors. As a consequence, early diagnosis of color blindness is an crucial to support an individual affected by this visual perception alteration at the initial phase of his/her life. The diagnosis of red-green color deficiencies (protanopia or deuteranopia) is commonly accomplished by means of the Ishihara test, which consists of plates showing dots with different sizes where some of them compose numbers within a gamut of colors while the ones composing the background have diffe…

Virtual conversation with a real talking head

A talking head is system performing an animated face model synchronized with a speech synthesis module. It is used as a presentation layer of a conversational Agent which provide an answer. It provides an answer when a query is written as an input by the user. The textual answer is converted into facial movements of a 3D face model whose lips and tongue movements are synchronized with the sound of the synthetic voice. The Client-Server paradigm has been used for the WEB infrastructure delegating the animation and synchronization to the client, so that the server can satisfy multiple requests from clients; while the Chatbot, the Digital Signal Processing and the Natural language Processing a…

Aligning Relational Schema and OWL Ontologies with Hidden Markov Model

The problem of bridging the gap between relational schema and ontologies is actively investigated in the Semantic Web and business communities. The main motivations are the OBDA scenario, where a domain ontology allows to hidden the technical details of the db to end-users; and the persistent storage of ontologies in db for facilitating search and retrieval keeping the benefits of DBMSs such as security and integrity. In these cases, the ABox is usually stored into a db, and the TBox is maintained in an ontology; for this reason, schema alignment is a more significant problem than the instance matching one. The use of manual mappings is hard and expensive, especially for large representatio…

Monte-Carlo image retargeting

In this paper an efficient method for image retargeting is proposed. It relies on a monte-carlo model that makes use of image saliency. Each random sample is extracted from deformation probability mass function defined properly, and shrinks or enlarges the image by a fixed size. The shape of the function, determining which regions of the image are affected by the deformations, depends on the image saliency. High informative regions are less likely to be chosen, while low saliency regions are more probable. Such a model does not require any optimization, since its solution is obtained by extracting repeatedly random samples, and allows real-time application even for large images. Computation…

A system based on neural architectures for the reconstruction of 3-D shapes from images

The connectionist approach to the recovery of 3-D shape information from 2-D images developed by the authors, is based on a system made up by two cascaded neural networks. The first network is an implementation of the BCS, an architecture which derives from a biological model of the low level visual processes developed by Grossberg and Mingolla: this architecture extracts a sort of brightness gradient map from the image. The second network is a backpropagation architecture that supplies an estimate of the geometric parameters of the objects in the scene under consideration, starting from the outputs of the BCS. A detailed description of the system and the experimental results obtained by si…

Illumination Correction on MR Images

Objective. An important artifact corrupting Magnetic Resonance Images is the rf inhomogeneity, also called bias artifact. This anomaly produces an abnormal illumination fluctuation on the image, due to variations of the device magnetic field. This artifact is particularly strong on images acquired with a device specialized on upper and lower limbs due to their coil configuration. A method based on homomorphic filtering aimed to suppress this artifact was proposed by Guillemaud. This filter has two faults: it doesnt provide an indication about the cutoff frequency (cf) and introduces another illumination artifact on the edges of the foreground. This work is an improvement to this method because i…

Fuzzy Smoothed Composition of Local Mapping Transformations for Non-rigid Image Registration

This paper presents a novel method for medical image regis- tration. The global transformation is obtained by composing affine trans- formations, which are recovered locally from given landmarks. Transfor- mations of adjacent regions are smoothed to avoid blocking artifacts, so that a unique continuous and differentiable global function is obtained. Such composition is operated using a technique derived from fuzzy C- means clustering. The method was successfully tested on several datasets; results, both qualitative and quantitative, are shown. Comparisons with other methods are reported. Final considerations on the efficiency of the technique are explained.

Collective Reasoning over Shared Concepts for the Linguistic Atlas of Sicily

In this chapter, collective intelligence principles are applied in the context of the Linguistic Atlas of Sicily (ALS - Atlante Linguistico Siciliano), an interdisciplinary research focusing on the study of the Italian language as it is spoken in Sicily, and its correlation with the Sicilian dialect and other regional varieties spoken in Sicily. The project has been developed over the past two decades and includes a complex information system supporting linguistic research; recently it has grown to allow research scientists to cooperate in an integrated environment to produce significant scientific advances in the field of ethnologic and sociolinguistic research. An interoperable infrastruc…

WATERSHED BASED DETECTION OF MULTIPLE SCLEROSIS LESIONS IN MR IMAGES

Morphological exponential entropy driven-HUM.

This paper presents an improvement to the Ex- ponential Entropy Driven - Homomorphic Unsharp Masking (E 2 D − HUM ) algorithm devoted to illumination artifact sup- pression on Magnetic Resonance Images. E 2 D−HUM requires a segmentation step to remove dark regions in the foreground whose intensity is comparable with background, because strong edges produce streak artifacts on the tissues. This new version of the algorithm keeps the same good properties of E 2 D − HUM without a segmentation phase, whose parameters should be chosen in relation to the image. I. INTRODUCTION Most of the studies on illumination correction found in literature are oriented to brain (18) magnetic resonance images (…

HOWERD: A Hidden Markov Model for Automatic OWL-ERD Alignment

The HOWERD model for estimating the most likely alignment between an OWL ontology and an Entity Relation Diagram (ERD) is presented. Automatic alignment between relational schema and ontology represents a big challenge in Semantic Web research due to the different expressiveness of these representations. A relational schema is less expressive than the ontology; this is a non trivial problem when accessing data via an ontology and for ontology storing by means of a relational schema. Existent alignment methodologies fail in loosing some contents of the involved representations because the ontology captures more semantic information, and several elements are left unaligned. HOWERD relies on a…

New systems for extracting 3-D shape information from images

Neural architectures may offer an adequate way to deal with early vision since they are able to learn shape features or classify unknown shapes, generalising the features of a few meaningful examples, with a low computational cost after the training phase. Two different neural approaches are proposed by the authors: the first one consists of a cascaded architecture made up by a first stage named BWE (Boundary Webs Extractor) which is aimed to extract a brightness gradient map from the image, followed by a backpropagation network that estimates the geometric parameters of the object parts present in the perceived scene. The second approach is based on the extraction of the boundary webs map …

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.

Three-dimensional Fuzzy Kernel Regression framework for registration of medical volume data

Abstract In this work a general framework for non-rigid 3D medical image registration is presented. It relies on two pattern recognition techniques: kernel regression and fuzzy c-means clustering. The paper provides theoretic explanation, details the framework, and illustrates its application to implement three registration algorithms for CT/MR volumes as well as single 2D slices. The first two algorithms are landmark-based approaches, while the third one is an area-based technique. The last approach is based on iterative hierarchical volume subdivision, and maximization of mutual information. Moreover, a high performance Nvidia CUDA based implementation of the algorithm is presented. The f…

Grounding concepts as emerging clusters in multiple conceptual spaces

A novel framework for symbol grounding in artificial agents is presented, which relies on the key idea that concepts "emerge" implicitly at the perceptual level as clusters of points with similar features forming homogeneous regions in multiple perceptual Conceptual Spaces (pCS). Such spaces describe percepts such as color, texture, shape, and position that in turn are the properties of the objects populating the agent's environment. Objects are represented in a suitable object Conceptual Space where all their features are composed together again using clustering in pCSs. Symbols will be learned from such a tensor space. A detailed description of both the framework and its theoretical found…

GUI Usability in Medical Imaging

The diffusion of computer technologies in everyday life has involved the birth of standard methodologies to control their development. Indeed, the purpose of standardization procedures consists of providing rules aimed to control technologies leaving no space for empirical improvisations. In general, medical software manufacturers provide their applications with Graphic User Interfaces (GUI) that are not compliant with any clear and standard usability criterion. The only guideline is the creation of GUIs inherited from the ones adopted on medical consoles because physicians use them routinely. This paper addresses this issue: medical software interfaces should be designed trying to overcome…

Second Opinion System for Intraoral Lesions

In this paper we present the prototype of a teledentistry system to perform the remote diagnosis of oral diseases. It makes use of a particular device called intra-oral (or dental) camera properly designed to shoot video and take pictures of the inner part of the mouth. The intra-oral cameras can be connected via USB to a common PC and they are very cheap, unlike the intra-oral photography kit for DSLR cameras. Usually this kind of devices are used in dentistry studies for local visualization by means of specialized software. The novelty of our system is that the real-time video produced by this device is canalized into a video streming by means of Video LAN client server (VLC) and pictures…

A fully automatic method for biological target volume segmentation of brain metastases

Leksell Gamma Knife is a mini-invasive technique to obtain a complete destruction of cerebral lesions delivering a single high dose radiation beam. Positron Emission Tomography (PET) imaging is increasingly utilized for radiation treatment planning. Nevertheless, lesion volume delineation in PET datasets is challenging because of the low spatial resolution and high noise level of PET images. Nowadays, the biological target volume (BTV) is manually contoured on PET studies. This procedure is time expensive and operator-dependent. In this article, a fully automatic algorithm for the BTV delineation based on random walks (RW) on graphs is proposed. The results are compared with the outcomes of…

Exponential Entropy Driven HUM on Knee MR Images

A very important artifact corrupting Magnetic Resonance Images is the RF inhomogeneity. This kind of artifact generates variations of illumination which trouble both direct examination by the doctor and segmentation algorithms. Even if homomorphic filtering approaches have been presented in literature, none of them has developed a measure to determine the cut-off frequency. In this work we present a measure based on information theory with a large experimental setup aimed to demonstrate the validity of our approach.

An A* Based Semantic Tokenizer for Increasing the Performance of Semantic Applications

Semantic Applications (SAs) makes use of ontolo- gies and their performance can depend on the syntactic labels of the modeled entities; even if several approaches have been devised to formalize ontologies, no formal approaches have been devised for naming their constituents, which look as long word concatenations without any particular separation. We present a novel semantic tokenizer that finds the sub-words through an application of the A* based search algorithm; the A* functions rely on a set of linguistic criteria and on the meta-cognitive perspective of the activity of reading.

An intelligent assistant for medical knowledge discovery

Nowadays the availability of a huge amount of raw medical data makes it possible to use suitable data mining techniques to produce new knowledge. Usually, only data mining experts are able enough to carry out such tasks, and not so many researchers in medical ¯eld are also skilled in data analysis. This paper describes the Medical Knowledge Discovery Assistant (MKDA), a web based framework able to advice a medical researcher in such tasks. MKDA plans a Knowledge Discovery Process (KDP) on the basis of the requests of the user and of a set of rules in a knowledge base. The requests of the user are related to accu- racy, computational load, type of the produced model. They de¯ne the goal to b…

The ALSWEB Framework: A Web-based Framework for the Linguistic Atlas of Sicily Project

In this work the ALSWEB framework is presented. The ALSWEB is a virtual linguistic laboratory for linguistic research developed as a web application. The purpose of the framework is to model the entire process regarding the different steps of data acquisition, data transformation, information acquisition from different data and research hypotheses verification in the ALS (Linguistic Atlas of Sicily) project. The nature of the ALS research involves different type of data. The socio-linguistic researcher that is the main actor of the proposed framework has to acquire information in many formats: multimedia data, audio data, question-answer (textual) from particular questionnaires. In this wor…

Acquisition of New Knowledge In TutorJ

This paper presents a methodology to acquire new knowledge in TutorJ using external information sources. TutorJ is an ITS whose architecture is inspired to the HIPM cognitive model, while meta-cognition principles have been used to design the knowledge acquisition process. The system behavior is intended to increase its own knowledge as a consequence of the interaction with users. The implemented methodology uses external links and services to capture new knowledge from contents related to discussion topics and transforms these contents into structured knowledge that is stored inside an ontology. The purpose of the proposed methodology is to lower the effort of system scaffolding creation a…

A meta-cognitive architecture for planning in uncertain environments

Abstract The behavior of an artificial agent performing in a natural environment is influenced by many different pressures and needs coming from both external world and internal factors, which sometimes drive the agent to reach conflicting goals. At the same time, the interaction between an artificial agent and the environment is deeply affected by uncertainty due to the imprecision in the description of the world, and the unpredictability of the effects of the agent’s actions. Such an agent needs meta-cognition in terms of both self-awareness and control. Self-awareness is related to the internal conditions that may possibly influence the completion of the task, while control is oriented t…

Knowledge discovery for the linguistic atlas of sicily project

Theidentificationofnewusefulpatternsindataisacorepro- cess for intelligent systems. In this work a knowledge discovery method- ology to retrieve useful and novel information from data stored in a DBMS. This methodology is mainly used in the ALS (Linguistic Atlas of Sicily) Project. The ALS project is a joint effort led by researchers at the Dipartimento di Scienze Filologiche e Linguistiche of the University of Palermo that has the purpose to track and study the geo-linguistic and lexicographic processes about the function and usage of the Sicilian di- alect. The whole framework is based on the definition of ontology-based applications for the creation, retrieval, manipulation and browsing …

Real-time content-aware image resizing using reduced linear model

In this paper an effective and efficient method for contentaware image resizing is proposed. It is based on the solution of a linear system where each pixel displacement (compression or expansion) is determined in dependence of the visual relevance of the pixel itself. The linear nature of the model allows real-time application of the method even for large images. This fully automatic approach can be also improved by interactively providing cues such as geometric constraints and/or manual relevant object labeling. The results have proven that the presented method achieves results comparable or superior to existent strategies, while improving efficiency.

Image Content Enhancement Through Salient Regions Segmentation for People With Color Vision Deficiencies

Color vision deficiencies affect visual perception of colors and, more generally, color images. Several sciences such as genetics, biology, medicine, and computer vision are involved in studying and analyzing vision deficiencies. As we know from visual saliency findings, human visual system tends to fix some specific points and regions of the image in the first seconds of observation summing up the most important and meaningful parts of the scene. In this article, we provide some studies about human visual system behavior differences between normal and color vision-deficient visual systems. We eye-tracked the human fixations in first 3 seconds of observation of color images to build real f…

Improving Assessment of Students through Semantic Space Construction

Assessment is one of the hardest tasks an Intelligent Tutoring System has to perform. It involves different and sometimes uncorrelated sub-tasks: building a student model to define her needs, defining tools and procedures to perform tests, understanding students' replies to system prompts, defining suitable procedures to evaluate the correctness of students' replies, and strategies to improve students' abilities after the assessment session.In this work we  present an improvement of our system, TutorJ, with particular attention to the assessment phase. Many tutoring systems offer only a limited set of assessment options like multiple-choice questions,fill-in-the-blanks tests or other types …

Multi-modal non-rigid registration of medical images based on mutual information maximization

In this paper, a new multi-modal non-rigid registration technique for medical images is presented. Firstly, the registration problem is outlined and some of the most common approaches reported, then, the proposed algorithm is presented. The proposed technique is based on mutual information maximization and computes a deformation field through a suitable globally smoothed affine piecewise transformation. The algorithm has been conceived with particular attention to computational load and accuracy of results. Experimental results involving intra-patient, inter-patients and atlas images on brain CT and MR (T1, T2 and PD modalities) are reported.

A Gabor-based Technique for Bias Removal in MR images

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…

Towards MKDA: A Knowledge Discovery Assistant for Researches in Medicine

Nowadays doctors are generating a huge amount of raw data. These data, analyzed with data mining techniques, could be sources of new knowledge. Unluckily such tasks need skilled data analysts, and not so much researchers in Medicine are also data mining experts. In this paper we present a web based system for knowledge discovery assistance in Medicine able to advice a medical researcher in this kind of tasks. The user must define only the experiment specifications in a formal language we have defined. The system GUI helps users in their composition. Then the system plans a Knowledge Discovery Process (KDP) on the basis of rules in a knowledge base. Finally the system executes the KDP and pr…

A Web-based Intelligent Tutoring System for Clinical Anatomy

Physical simulation for real-time image/video retargeting

Retargeting methods present content on arbitrary aspect ratio me- dia displays limiting distortions in relevant objects. This is done by means of applying non-homogeneous resizing operators across the whole media, constraining it to fit into the required size. Several succesful systems have been proposed to achieve image retargeting, while video retargeting is still challenging due to time consistency and computational complexity requirements. Two important con- tributes were proposed: non-homogeneous retargeting [Wolf et al. 2007] and improved seam-carving [Rubinstein et al. 2008]. The first one claims to achieve real-time performance but considers spa- tial coordinates separately. The lat…

Restoration of out of focus images based on circle of confusion estimates

In this paper a new method for a fast out-of-focus blur estimation and restoration is proposed. It is suitable for CFA (Color Filter Array) images acquired by typical CCD/CMOS sensor. The method is based on the analysis of a single image and consists of two steps: 1) out-of-focus blur estimation via Bayer pattern analysis; 2) image restoration. Blur estimation is based on a block-wise edge detection technique. This edge detection is carried out on the green pixels of the CFA sensor image also called Bayer pattern. Once the blur level has been estimated the image is restored through the application of a new inverse filtering technique. This algorithm gives sharp images reducing ringing and c…

Comprehensive Uncertainty Management in MDPs

Multistage decision-making in robots involved in real-world tasks is a process affected by uncertainty. The effects of the agent’s actions in a physical en- vironment cannot be always predicted deterministically and in a precise manner. Moreover, observing the environment can be a too onerous for a robot, hence not continuos. Markov Decision Processes (MDPs) are a well-known solution inspired to the classic probabilistic approach for managing uncertainty. On the other hand, including fuzzy logics and possibility theory has widened uncertainty representa- tion. Probability, possibility, fuzzy logics, and epistemic belief allow treating dif- ferent and not always superimposable facets of unce…

Morphological Exponential Entropy Driven Hum on Knee MR Images

Acquisition of New Knowledge to Manage Conversation in TutorJ

This paper presents new conversation modules developed for TutorJ to support the use of meta-cognitive strategies in the learners. TutorJ is an Intelligent Tutoring System able to interact with users to assess their skills, and improve their knowledge in a specific domain. New models are devoted to plan the conversation and to acquire new knowledge from semi-structured data sources. Conversation planning is based on probabilistic techniques. Knowledge acquisition is based on retrieval, transformation and alignment of data from wikis to enrich the replies to students questions.

Bias artifact suppression on MR volumes.

RF-Inhomogeneity correction is a relevant research topic in the field of Magnetic Resonance Imaging (MRI). A volume corrupted by this artifact exhibits nonuni- form illumination both inside a single slice and between adjacent ones. In this work a bias correction technique is presented, which suppresses this artifact on MR vol- umes scanned from different body parts without any a-priori hypothesis on the artifact model. Theoretical foundations of the method are reported together with experimental results and a comparison is presented with both the 2D version of the algorithm and other techniques that are widely used in MRI literature.

Conceptual representations of actions for autonomous robots

An autonomous robot involved in long and complex missions should be able to generate, update and process its own plans of action. In this perspective, it is not plausible that the meaning of the representations used by the robot is given from outside the system itself. Rather, the meaning of internal symbols must be firmly anchored to the world through the perceptual abilities and the overall activities of the robot. According to these premises, in this paper we present an approach to action representation that is based on a "conceptual" level of representation, acting as an intermediate level between symbols and data coming from sensors. Symbolic representations are interpreted by mapping …

Shape Description for Content-Based Image Retrieval

The present work is focused on a global image characterization based on a description of the 2D displacements of the different shapes present in the image, which can be employed for CBIR applications.To this aim, a recognition system has been developed, that detects automatically image ROIs containing single objects, and classifies them as belonging to a particular class of shapes.In our approach we make use of the eigenvalues of the covariance matrix computed from the pixel rows of a single ROI. These quantities are arranged in a vector form, and are classified using Support Vector Machines (SVMs). The selected feature allows us to recognize shapes in a robust fashion, despite rotations or…

A computer support system to support diagnosis by imaging and its experimental application in Images of patients affected by multiple sclerosis

Dal web al web semantico

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 ADVANCED WEB BASED SYSTEM TO SUPPORT LEARNING OF CLINICAL ANATOMY

Recent advances of HCI in decision-making tasks for optimized clinical workflows and precision medicine.

The ever-increasing amount of biomedical data is enabling new large-scale studies, even though ad hoc computational solutions are required. The most recent Machine Learning (ML) and Artificial Intelligence (AI) techniques have been achieving outstanding performance and an important impact in clinical research, aiming at precision medicine, as well as improving healthcare workflows. However, the inherent heterogeneity and uncertainty in the healthcare information sources pose new compelling challenges for clinicians in their decision-making tasks. Only the proper combination of AI and human intelligence capabilities, by explicitly taking into account effective and safe interaction paradigms,…

A tutoring system based on a hierarchical representation of information

Towards MKDA: A Knowledge Discovery Assistant For Researches in Medicine

Nowadays doctors are generating a huge amount of raw data. These data, analyzed with data mining techniques, could be sources of new knowledge. Unluckily such tasks need skilled data analysts, and not so much researchers in Medicine are also data mining experts. In this paper we present a web based system for knowledge discovery assistance in Medicine able to advice a medical researcher in this kind of tasks. The user must define only the experiment specifications in a formal language we have defined. The system GUI helps users in their composition. Then the system plans a Knowledge Discovery Process (KDP) on the basis of rules in a knowledge base. Finally the system executes the KDP and pr…

Automatic induction of rules for computer-aided diagnosis in the multiple sclerosis by analysis of brain MR images

Content based indexing of MPEG-4 video on relational DBMS

An architecture for automatic gesture analysis

The field of human-computer interaction has been widely investigated in the last years, resulting in a variety of systems used in different application fields like virtual reality simulation environments, software user interfaces, and digital library systems.A very crucial part of all these systems is the input module which is devoted to recognize the human operator in terms of tracking and/or recognition of human face, arms position, hand gestures, and so on.In this work a software architecture is presented, for the automatic recognition of human arms poses. Our research has been carried on in the robotics framework. A mobile robot that has to find its path to the goal in a partially struc…

Population and query interface for a content-based video database

Fuzzy-based Kernel Regression Approaches for Free Form Deformation and Elastic Registration of Medical Images

In modern medicine, a largely diffused method for gathering knowledge about organs and tissues is obtained by means of merging information from several datasets. Such data are provided from multimodal or sequential acquisitions. As a consequence, a pre-processing step that is called “image registration” is required to achieve data integration. Image registration aims to obtain the best possible spatial correspondence between misaligned datasets. This procedure is also useful to correct distortions induced by magnetic interferences with the acquisition equipment signals or the ones due patient’s involuntary movements such as heartbeat or breathing. The problem can be regarded as finding the …

A Proposal for a System able to analyse forum discussions and to build personalized learning paths

New shape from Shading methods

Shape from Shading is perhaps the most difficult topic to deal with in Artificial Vision: several researchers have faced it using different approaches. The most part of these methods are based on the Horn algorithm so they require very heavy regularity assumptions about the perceived objects' shape and are computationally expensive.