1,720,983 research outputs found
Semantic Modelling of Smart Healthcare Data
No full textNowadays, healthcare is becoming increasingly connected
and increasingly complex. These changes provide opportunities
and challenges to the research community. For instance,
the enormous volume of data gathered from IoT wearable fitness
devices and wellness appliances, if effectively analysed and understood,
can be exploited to improve people’s well-being and identify
predictive markers of future diseases. However, due to the lack of
devices interoperability and heterogeneity of data representation
formats, the IoT healthcare landscape is characterised by a
pervasive presence of ”data silos” which prevents users and health
practitioners from obtaining an overall view of whole knowledge.
Semantic web technologies, such as ontologies and inference rules,
have been shown as a promising way for the integration and
exploitation of data from heterogeneous sources. In this paper, we
present a semantic data model useful to: (a) analyse information
from unstructured data sources along with generic or domain
specific datasets; (b) unify them in an interlinked data processing
area. The proposed semantic eHealth system enables automatic
inferences and logical reasoning, and can significantly facilitate
reuse, exploitation and possible extension of IoT health data
sources.. Nowadays, healthcare is becoming increasingly connected and increasingly complex. These changes provide opportunities and challenges to the research community. For instance, the enormous volume of data gathered from IoT wearable fitness devices and wellness appliances, if effectively analysed and understood, can be exploited to improve peo-ple’s well-being and identify predictive markers of future diseases. However, due to the lack of devices interoperability and heterogeneity of data representation formats, the IoT healthcare landscape is characterised by a pervasive presence of “data silos” which prevents users and health practitioners from obtaining an overall view of whole knowledge. Semantic web technologies, such as ontologies and inference rules have been shown as a promising way for the integration and exploitation of data from heterogeneous sources. In this paper, we present a semantic data model useful to: (a) analyse information from unstructured data sources along with generic or domain specific datasets; (b) unify them in an interlinked data processing area. The proposed semantic eHealth system enables automatic inferences and logical reasoning, and can significantly facilitate reuse, exploitation and possible extension of IoT health data sources
Friend recommendation in a social bookmarking system: Design and architecture guidelines
No full textSocial media systems allow users to share resources with the people connected to them. In order to handle the exponential growth of the content in these systems and of the amount of users that populate them, recommender systems have been introduced. As social media systems with different purposes arose, also different types of social recommender systems were developed in order to filter the specific information that each domain handles. A form of social media, known as social bookmarking system, allows to share bookmarks in a social network. A user adds as a friend or follows another user and receives updates on the bookmarks added by that user. In this paper, we present an analysis of the state-of- the-art on user recommendation in social environments and of the structure of a social bookmarking system, in order to derive design guidelines and an architecture of a friend recommender system in the social bookmarking domain. This study can be useful for future research, by highlighting the aspects that characterize this domain and the features that this type of recommender system has to offer
Novel Synchronous Brain Computer Interface Based on 2-D EEG Local Binary Patterning
No full textThis paper proposes the design and the validation through in-vivo measurements, of an innovative machine learning (ML) approach for a synchronous Brain Computer Interface (BCI). The here-proposed system analyzes EEG signals from 8 wireless smart electrodes, placed in motor, and sensory-motor cortex area. For its functioning, the BCI exploits a specific brain activity patterns (BAP) elicited during the measurements by using clinical-inspired stimulation protocol that is suitable for the evocation of the Movement-Related Cortical Potentials (MRCPs). The proposed BCI analyzes the EEGs through symbolization-based algorithm: the Local Binary Patterning, which – due to its end-to-end binary nature - strongly reduces the computational complexity of the features extraction (FE) and real-time classification stages.
As last step, the user intentions discrimination is entrusted to a weighted Support Vector Machine (wSVM) with linear kernel. The data have been collected from 3 subjects (aged 26 ± 1), creating an overall dataset that consists of 391 ± 106 observations per participant. The in-vivo real-time validation showed an intention recognition accuracy of 85.61 ± 1.19%. The overall computing chain requests, on average, just 3 ms beyond the storage time
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A class-based strategy to user behavior modeling in recommender systems
No full textA recommender system is a tool employed to filter the huge amounts of data that companies have to deal with, and produce effective suggestions to the users. The estimation of the interest of a user toward an item, however, is usually performed at the level of a single item, i.e., for each item not evaluated by a user, canonical approaches look for the rating given by similar users for that item, or for an item with similar content. Such approach leads toward the so-called overspecialization/serendipity problem, in which the recommended items are trivial and users do not come across surprising items. This work first shows that user preferences are actually distributed over a small set of classes of items, leading the recommended items to be too similar to the ones already evaluated, then we propose a novel model, named Class Path Information (CPI), able to represent the current and future preferences of the users in terms of a ranked set of classes of items. The proposed approach is based on a semantic analysis of the items evaluated by the users, in order to extend their ground truth and infer the future preferences. The performed experiments show that our approach, by including in the CPI model the same classes predicted by a state-of-the-art recommender system, is able to accurately model the user preferences in terms of classes, instead of in terms of single items, allowing to recommend non trivial items
Determining a Framework for the Generation and Evaluation of Ambient Intelligent Agent System Designs
No full textThe design and realization of Ambient Intelligence (AmI) systems
using Artificially Intelligent (AI) agents is a rising field of research. However,
the absence of clearly defined working criteria, supporting the generation and
evaluation of AmI agent system designs, is a conspicuous obstacle to their
advancement. The contribution of this paper is that we determine and test a
framework for the generation and evaluation of AmI system designs, based on
user experience and business criteria. Specifically, the process of designing a
personal lighting AI agent, in collaboration with a leading lighting design
company, is used as a case study to determine and test a framework for the
generation and evaluation of AmI system designs based on feasibility and
acceptability. First, we use storytelling videos to describe and communicate the
user values and design scenarios to the stakeholders. Second, we generate design
proposals for a lighting AmI agent based on five distinct systemic factors,
namely: (a) the context of interaction; (b) the required system data; (c) the
required sensing input; (d) the required user input; and (e) the desired system
output. Finally third we determine an evaluation framework that is based on
three distinct levels of in-built system intelligence, from lower to higher. The
three levels reflect the feasibility and acceptability of the system. Feasibility is
what a specific company is capable of producing, and in what timeframe.
Acceptability is the potential of familiarity and trust that the users can feel while
interacting with the AI agent
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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