Conceptual Blending in Biomusic Composition Space: The "Brainswarm" Paradigm

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On Modeling the Quality of Nutrition for Healthy Ageing Using Fuzzy Cognitive Maps

Modelling dietary intake of older adults can prevent nutritional deficiencies and diet-related diseases, improving their quality of life. Towards such direction, a Fuzzy Cognitive Map (FCM)-based modelling approach that models the interdependencies between the factors that affect the Quality of Nutrition (QoN) is presented here. The proposed FCM-QoN model uses a FCM with seven input-one output concepts, i.e., five food groups of the UK Eatwell Plate, Water (H2O), and older adult’s Emotional State (EmoS), outputting the QoN. The weights incorporated in the FCM structure were drawn from an experts’ panel, via a Fuzzy Logic-based knowledge representation process. Using various levels of analysis (causalities, static/feedback cycles), the role of EmoS and H2O in the QoN was identified, along with the one of Fruits/Vegetables and Protein affecting the sustainability of effective food combinations. In general, the FCM-QoN approach has the potential to explore different dietary scenarios, helping health professionals to promote healthy ageing and providing prognostic simulations for diseases effect (such as Parkinson’s) on dietary habits, as used in the H2020 i-Prognosis project (www.i-prognosis.eu)

An Integrated Platform Supporting Intangible Cultural Heritage Learning and Transmission: Definition of Requirements and Evaluation Criteria

The paper offers an experience-based viewpoint on two key phases of the development of an Information and Communication Technologies (ICTs)-based system: the definition of requirements and identification of related criteria and methodology for its evaluation. In doing so, it refers to the unique context of the i-Treasures EU project, which deals with the development of an innovative integrated platform to support the learning and transmission of Intangible Cultural Heritage (ICH). The i-Treasures integrated platform is conceived to support both traditional learning approaches and innovative and active learning processes, based on extensive use of sensor-technologies. In this light, during the development process, particular attention has been devoted to the definition of requirements with specific reference to sensor-mediated Human Computer Interaction (HCI) issues and the evaluation process was designed accordingly, in coherence with the specific advanced features of the integrated platform. The paper offers a view of the complexity of the design of ICT-based tools supporting the preservation and transmission of ICH and also provides an insight (and this could have a broader impact) into the methodology adopted to harmonize the requirements and the evaluation phases which are key pillars for the construction of any educationally effective ICT-based learning system

Rare and contemporary dance as cultural mediators within a b-learning mode: the fuzzy logic perspective

The concept of cultural mediation via undergraduate courses in rare and contemporary dance within a blended learning (b-learning) mode is approached here through a fuzzy logic (FL)-based.modelling perspective. Students’ online interaction on the Moodle Learning Management System (LMS).during such b-learning courses was logged over an entire academic year, and the resulting data were.analysed using FL, in order to estimate users’ LMS Quality of Interaction (QoI). Using documental.analysis, the pedagogical design strategies per semester were transformed into concept maps and related.with the dynamically (per week) estimated QoIs. The latter were used by the teachers at the end of the.first semester to reflect upon and update their pedagogical planning, so as to enhance QoI in the second.semester. The results show the beneficial role of QoI in supporting more dynamic design of educational.scenarios, yet considering the inherent tendencies/attitudes of users’ interaction within different cultural.expressions

A Hybrid EMD-Kurtosis Method for Estimating Fetal Heart Rate from Continuous Doppler Signals

Monitoring of fetal heart rate (FHR) is an important measure of fetal wellbeing during the months of pregnancy. Previous works on estimating FHR variability from Doppler ultrasound (DUS) signal mainly through autocorrelation analysis showed low accuracy when compared with heart rate variability (HRV) computed from fetal electrocardiography (fECG). In this work, we proposed a method based on empirical mode decomposition (EMD) and the kurtosis statistics to estimate FHR and its variability from DUS. Comparison between estimated beat-to-beat intervals using the proposed method and the autocorrelation function (AF) with respect to RR intervals computed from fECG as the ground truth was done on DUS signals from 44 pregnant mothers in the early (20 cases) and late (24 cases) gestational weeks. The new EMD-kurtosis method showed significant lower error in estimating the number of beats in the early group (EMD-kurtosis: 2.2% vs. AF: 8.5%, p < 0.01, root mean squared error) and the late group (EMD-kurtosis: 2.9% vs. AF: 6.2%). The EMD-kurtosis method was also found to be better in estimating mean beat-to-beat with an average difference of 1.6 ms from true mean RR compared to 19.3 ms by using the AF method. However, the EMD-kurtosis performed worse than AF in estimating SNDD and RMSSD. The proposed EMD-kurtosis method is more robust than AF in low signal-to-noise ratio cases and can be used in a hybrid system to estimate beat-to-beat intervals from DUS. Further analysis to reduce the estimated beat-to-beat variability from the EMD-kurtosis method is needed

Fetal Heart Sounds Detection Using Wavelet Transform and Fractal Dimension

Phonocardiography is a non-invasive technique for the detection of fetal heart sounds (fHSs). In this study, analysis of fetal phonocardiograph (fPCG) signals, in order to achieve fetal heartbeat segmentation, is proposed. The proposed approach (namely WT–FD) is a wavelet transform (WT)-based method that combines fractal dimension (FD) analysis in the WT domain for the extraction of fHSs from the underlying noise. Its adoption in this field stems from its successful use in the fields of lung and bowel sounds de-noising analysis. The efficiency of the WT–FD method in fHS extraction has been evaluated with 19 simulated fHS signals, created for the present study, with additive noise up to (3 dB), along with the simulated fPCGs database available at PhysioBank. Results have shown promising performance in the identification of the correct location and morphology of the fHSs, reaching an overall accuracy of 89% justifying the efficacy of the method. The WT–FD approach effectively extracts the fHS signals from the noisy background, paving the way for testing it in real fHSs and clearly contributing to better evaluation of the fetal heart functionality