Raffaella Folgieri

Letters: Bio-molecular cancer prediction with random subspace ensembles of support vector machines

Support vector machines (SVMs), and other supervised learning techniques have been experimented for the bio-molecular diagnosis of malignancies, using also feature selection methods. The classification task is particularly difficult because of the high dimensionality and low cardinality of gene expression data. In this paper we investigate a different approach based on random subspace ensembles of SVMs: a set of base learners is trained and aggregated using subsets of features randomly drawn from the available DNA microarray data. Experimental results on the colon adenocarcinoma diagnosis and medulloblastoma clinical outcome prediction show the effectiveness of the proposed approach.

Virtual reality as a communication process

In this work, we consider immersive Virtual Reality (VR) as a communication process between humans, mediated by computer systems, which uses interaction, visualization, and other sensory stimuli to convey information. From this viewpoint, it is relevant to understand how VR can solve a given communication problem, what is therefore the expressive power of VR system, i.e., its ability in establishing the communication, what are the guidelines to design an effective system, and what are the more relevant models of VR applications. Firstly, we try to clarify the notion of reality in Virtual Reality systems and conclude that reality is not an intrinsic characteristic of VR, rather the result of a conventional way of coding information. The purpose of coding is to lead the observer to the conclusion that the VR set is what is called in italian as verisimile (from Latin veri similis), i.e., “similar-to-the-real-thing”. So the creation of an effective VR application is an artifice or an illusion. But in order to avoid an over-reliance on the creativity of the VR designer, we intend to identify a solid ground on which different kinds of VR solutions can be considered in terms of their ability to solve the desired communication objective. To this aim, we will rely on methods derived from rhetoric to semiotics.

Feature Selection Combined with Random Subspace Ensemble for Gene Expression Based Diagnosis of Malignancies

The bio-molecular diagnosis of malignancies represents a difficult learning task, because of the high dimensionality and low cardinality of the data. Many supervised learning techniques, among them support vector machines, have been experimented, using also feature selection methods to reduce the dimensionality of the data. In alternative to feature selection methods, we proposed to apply random subspace ensembles, reducing the dimensionality of the data by randomly sampling subsets of features and improving accuracy by aggregating the resulting base classifiers. In this paper we experiment the combination of random subspace with feature selection methods, showing preliminary experimental results that seem to confirm the effectiveness of the proposed approach.

Analysis of brain activity and response during monoscopic and stereoscopic visualization

Stereoscopic visualization in cinematography and Virtual Reality (VR) creates an illusion of depth by means of two bidimensional images corresponding to different views of a scene. This perceptual trick is used to enhance the emotional response and the sense of presence and immersivity of the observers. An interesting question is if and how it is possible to measure and analyze the level of emotional involvement and attention of the observers during a stereoscopic visualization of a movie or of a virtual environment. The research aims represent a challenge, due to the large number of sensorial, physiological and cognitive stimuli involved. In this paper we begin this research by analyzing possible differences in the brain activity of subjects during the viewing of monoscopic or stereoscopic contents. To this aim, we have performed some preliminary experiments collecting electroencephalographic (EEG) data of a group of users using a Brain- Computer Interface (BCI) during the viewing of stereoscopic and monoscopic short movies in a VR immersive installation.

A revised web objects method to estimate web application development effort

We present a study of the effectiveness of estimating web application development effort using Function Points and Web Objects methods, and a method we propose - the Revised Web Objects (RWO). RWO is an upgrading of WO method, aimed to account for new web development styles and technologies. It also introduces an up-front classification of web applications according to their size, scope and technology, to further refine their effort estimation. These methods were applied to a data-set of 24 projects obtained by Datasiel spa, a mid-sized Italian company, focused on web application projects, showing that RWO performs statistically better than WO, and roughly in the same way as FP.

Negotiating the web science curriculum through shared educational artefacts

The far-reaching impact of the Web on society is widely recognised. The interdisciplinary study of this impact has crystallised in the field of study known as Web Science. However, defining an agreed, shared understanding of what constitutes web science requires complex negotiation and translations of understandings across component disciplines, national cultures and educational traditions. Some individual institutions have already established particular curricula, and discussions in the Web Science Curriculum Workshop series have marked the territory to some extent. This paper reports on a process being adopted across a consortium of partners to systematically create a shared understanding of what constitutes web science. It records and critiques the processes instantiated to agree a common curriculum, and presents a framework for future discussion and development.

BCI Promises in Emotional Involvement in Music and Games

The reliability of commercial non-invasive BCI (brain computer Interface) devices and the lower cost of these EEG-based systems, as well as the equipments portability, determined the increasing interest in their application in different research fields. The latter feature makes BCI devices particularly suited for entertainment applications, especially given the possibility to detect the mental state of the users. The relationship between emotions and entertainment is obvious, as is the influence of music in human emotional states. While BCI devices represent a challenge in gaming motion control, they have been successfully applied in music production [Dan et al. 2009] and composition [Hamadicharef et al. 2010]. In our previous work [Conscious and unconscious music from the brain in press] we focused on conscious production of music notes with the aim of developing a prototype for applications in entertainment. In this work we trace the state-of-the art of our research and present our opinion on possible applications of the preliminary results.

Analysis of brain activity and response to colour stimuli during learning tasks: an EEG study

The research project intends to demonstrate how EEG detection through BCI device can improve the analysis and the interpretation of colours-driven cognitive processes through the combined approach of cognitive science and information technology methods. To this end, firstly it was decided to design an experiment based on comparing the results of the traditional (qualitative and quantitative) cognitive analysis approach with the EEG signal analysis of the evoked potentials. In our case, the sensorial stimulus is represented by the colours, while the cognitive task consists in remembering the words appearing on the screen, with different combination of foreground (words) and background colours. In this work we analysed data collected from a sample of students involved in a learning process during which they received visual stimuli based on colour variation. The stimuli concerned both the background of the text to learn and the colour of the characters. The experiment indicated some interesting results concerning the use of primary (RGB) and complementary (CMY) colours.

A Study on the Moral Implications of Human Disgust-Related Emotions Detected Using EEG-Based BCI Devices

This paper reports results obtained from a set of experiments aiming to compare the behaviour and cerebral rhythms in response to the vision of images related to different types of disgust: core, animal nature and moral. The approach combines Information Technology methods and cognitive technologies (specifically Brain Computer Interfaces) as well as behavioural study methods, especially referring to FACS. The presented experiment has been designed with the intent to define the use of images instead of videos in eliciting a disgust response from participants. A sample of individuals has been involved in a process during which they received visual stimuli based on disgust. The stimuli concerned both core/animal nature disgust and moral disgust. The obtained results show the interesting effects of the reaction of participants, abstracted from freeze framed images, as well as EEG correlates.

A Cognitive Linguistic and Sentiment Analysis of Blogs: Monterosso 2011 Flooding

The aim of this study is to explore the use of web resources in order to trace the discursive strategies enacted to restore the image of a tourist destination. In particular, we analyze the case of Monterosso, damaged by a flood in 2011. The innovation of this paper consists in a twofold approach: a linguistic approach within the framework of Discourse Analysis, and a sentiment analysis approach realised through tools available on the Internet and specific procedures we have developed in the R environment.