pinecone/core-2020-05-10-deduplication huggingface dataset:
MC2: Multicore and Cache Analysis via Deterministic and Probabilistic Jitter Bounding

In critical domains, reliable software execution is increasingly involving aspects related to the timing dimension. This is due to the advent of high-performance (complex) hardware, used to provide the rising levels of guaranteed performance needed in those domains. Caches and multicores are two of the hardware features that have the potential to significantly reduce WCET estimates, yet they pose new challenges on current-practice measurement-based timing analysis (MBTA) approaches. In this paper we propose MC2, a technique for multilevel-cache multicores that combines deterministic and probabilistic jitter-bounding approaches to reliably handle both the variability in execution time generated by caches and the contention in accessing shared hardware resources. We evaluate MC2 on a COTS quad-core LEON-based board and our initial results show how it effectively captures cache and multicore contention in pWCET estimates with respect to actual observed values.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under grant TIN2015-65316-P and the HiPEAC Network of Excellence. Jaume Abella has been partially\ud
supported by the MINECO under Ramon y Cajal postdoctoral fellowship number\ud
RYC-2013-14717. Carles Hernández is jointly funded by the MINECO and FEDER funds through grant TIN2014-60404-JIN.Peer ReviewedPostprint (author's final draft
Main characteristics and anthropometrics of people with down syndrome – Impact in garment design

Among the human chromosome abnormalities, Down Syndrome is the most prominent. Social perception challenges include prejudice, myth and exclusion, with social inclusion having been subject of several studies. From this perspective, the main objective of this study is to contribute to a higher social inclusion of people with Down Syndrome. This is addressed by an anthropometric characterization study of Down Syndrome individuals, performed with the technology of body scanning (3D Body Scanner). The presented study can support the development of inclusive clothing, adapted to people with special needs, promoting the anthropometric and ergonomic aspects of shape, comfort and aesthetics, which would lead to an increased quality of life, self-esteem and security, contributing to a higher inclusion in our society. The results from the data obtained through the measuring tables provided by the 3D Body Scanner System allow the identification of the main body shapes of the analyzed sample, as well as the main variables of their measurements. The impact characteristics from this specific population in the garment design process is also discussed.(UID/CTM/000264)info:eu-repo/semantics/publishedVersio
Investigating Social Presence and Communication with Embodied Avatars in Room-Scale Virtual Reality

Room-scale virtual reality (VR) holds great potential as a medium for communication and collaboration in remote and same-time, same-place settings. Related work has established that movement realism can create a strong sense of social presence, even in the absence of photorealism. Here, we explore the noteworthy attributes of communicative interaction using embodied minimal avatars in room-scale VR in the same-time, same-place setting. Our system is the first in the research community to enable this kind of interaction, as far as we are aware. We carried out an experiment in which pairs of users performed two activities in contrasting variants: VR vs. face-to-face (F2F), and 2D vs. 3D. Objective and subjective measures were used to compare these, including motion analysis, electrodermal activity, questionnaires, retrospective think-aloud protocol, and interviews. On the whole, participants communicated effectively in VR to complete their tasks, and reported a strong sense of social presence. The system's high fidelity capture and display of movement seems to have been a key factor in supporting this. Our results confirm some expected shortcomings of VR compared to F2F, but also some non-obvious advantages. The limited anthropomorphic properties of the avatars presented some difficulties, but the impact of these varied widely between the activities. In the 2D vs. 3D comparison, the basic affordance of freehand drawing in 3D was new to most participants, resulting in novel observations and open questions. We also present methodological observations across all conditions concerning the measures that did and did not reveal differences between conditions, including unanticipated properties of the think-aloud protocol applied to VR.Submission includes video
EEG-engagement index and auditory alarm misperception: an inattentional deafness study in actual flight condition

The inability to detect auditory alarms is a critical issue in many do- mains such as aviation. An interesting prospect for flight safety is to understand the neural mechanisms underpinning auditory alarm misperception under actual flight condition. We conducted an experiment in which four pilots were to re- spond by button press when they heard an auditory alarm. The 64 channel Cognionics dry-wireless EEG system was used to measure brain activity in a 4 seat light aircraft. An instructor was present on all flights and in charge of initi- ating the various scenarios to induce two levels of task engagement (simple navigation task vs. complex maneuvering task). Our experiment revealed that inattentional deafness to single auditory alarms could take place as the pilots missed a mean number of 12.5 alarms occurring mostly during the complex maneuvering condition, when the EEG engagement index was high
A trial of intellectual work performance estimation by using physiological indices

The AHFE 2017 International Conference on Neuroergonomics and Cognitive Engineering, July 17–21, 2017, The Westin Bonaventure Hotel, Los Angeles, California, USA.In order to evaluate the intellectual productivity quantitatively, most of conventional studies have utilized task performance of cognitive tasks. Meanwhile, more and more studies use physiological indices which reflect cognitive load so as to evaluate the intellectual productivity quantitatively. In this study, the method which estimates task performance of intellectual workers by using several physiological indices (pupil diameter and heart rate variability) has been proposed. As the estimation models of task performance, two machine learning models, Support Vector Regression (SVR) and Random Forests (RF), have been employed. As the result of a subject experiment, it was found that coefficient of determination (R²) of SVR was 0.875 and higher than that of RF (p < 0.01). The result suggested that pupil diameter and heart rate variability were effective as the explanatory variables and SVR estimation was also effective in task performance estimation
Statistical data analysis of culture for innovation using an open data set from the Australian public service

Opportunities for replicating large data sets that have already been collected by government, and made available to the public to provide the possibility of statistical data analysis, are starting to emerge. This study examines the factor structure of ambidextrous culture for innovation. Survey data was extracted from the State of the Service Employee Census 2014 comprising 3,125 engineering professionals in Commonwealth of Australia departments. Data were analysed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). EFA returned a two-factor structure explaining 61.1% of the variance of the construct. CFA revealed that a two-factor structure was indicated as a validated model (GFI = 0.99, AGFI = 0.98, RMSEA = 0.05, RMR = 0.02, IFI = 0.99, NFI = 0.99, CFI = 0.99, and TLI = 0.98). From the results, the two factors extracted as characterising ambidextrous culture for innovation were innovative culture and performance-oriented culture.Griffith Sciences, Griffith School of EngineeringFull Tex
Dissimilar Symmetric Word Pairs in the Human Genome

In this work we explore the dissimilarity between symmetric word pairs, by
comparing the inter-word distance distribution of a word to that of its
reversed complement. We propose a new measure of dissimilarity between such
distributions. Since symmetric pairs with different patterns could point to
evolutionary features, we search for the pairs with the most dissimilar
behaviour. We focus our study on the complete human genome and its
repeat-masked version.Comment: Submitted 13-Feb-2017; accepted, after a minor revision, 17-Mar-2017;
  11th International Conference on Practical Applications of Computational
  Biology & Bioinformatics, PACBB 2017, Porto, Portugal, 21-23 June, 201
A critical evaluation of automatic atom mapping algorithms and tools

The identification of the atoms which change their position in chemical reactions is an important knowledge within the field of Metabolic Engineering. This can lead to new advances at different levels from the reconstruction of metabolic networks to the classification of chemical reactions, through the identification of the atomic changes inside a reaction. The Atom Mapping approach was initially developed in the 1960s, but recently suffered important advances, being used in diverse biological and biotechnological studies. The main methodologies used for atom mapping are the Maximum Common Substructure and the Linear Optimization methods, which both require computational know-how and powerful resources to run the underlying tools.

In this work, we assessed a number of previously implemented atom mapping frameworks, and built a framework able of managing the different data inputs and outputs, as well as the mapping process provided by each of these third-party tools. We evaluated the admissibility of the calculated atom maps from different algorithms, also assessing if with different approaches we were capable of returning equivalent atom maps for the same chemical reaction.ERDF -European Regional Development Fund(UID/BIO/04469/2013)info:eu-repo/semantics/publishedVersio
Classification tools for carotenoid content estimation in Manihot esculenta via metabolomics and machine learning

Cassava genotypes (Manihot esculenta Crantz) with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The color variability of cassava roots, which can vary from white to red, is related to the presence of several carotenoid pigments. The present study has shown how CIELAB color measurement on cassava roots tissue can be used as a non-destructive and very fast technique to quantify the levels of carotenoids in cassava root samples, avoiding the use of more expensive analytical techniques for compound quantification, such as UV-visible spectrophotometry and the HPLC. For this, we used machine learning techniques, associating the colorimetric data (CIELAB) with the data obtained by UV-vis and HPLC, to obtain models of prediction of carotenoids for this type of biomass. Best values of R2 (above 90%) were observed for the predictive variable TCC determined by UV-vis spectrophotometry. When we tested the machine learning models using the CIELAB values as inputs, for the total carotenoids contents quantified by HPLC, the Partial Least Squares (PLS), Support Vector Machines, and Elastic Net models presented the best values of R2 (above 40%) and Root-Mean-Square Error (RMSE). For the carotenoid quantification by UV-vis spectrophotometry, R2 (around 60%) and RMSE values (around 6.5) are more satisfactory. Ridge regression and Elastic Network showed the best results. It can be concluded that the use colorimetric technique (CIELAB) associated with UV-vis/HPLC and statistical techniques of prognostic analysis through machine learning can predict the content of total carotenoids in these samples, with good precision and accuracy.CAPES -Coordenação de Aperfeiçoamento de Pessoal de Nível Superior(407323/2013-9)info:eu-repo/semantics/publishedVersio
UV-Vis spectrophotometry and chemometrics as tools for recognition of the biochemical profiles of organic banana peels (Musa sp.) according to the seasonality in southern Brazil

Banana (Musa sp.) has received wide interest in popular and scientific medicine because of its rich composition in bioactive metabolites, e.g., phenolic compounds, found in interesting concentrations in its peel. Banana peel is a residue that is under-exploited by the industry. Thus, with the intention to give a destination to this by-product towards health care or cosmetics industries, we evaluated its aqueous extract (AE) as a source of bioactive phenolic compounds, aiming at to apply them in future studies of biological activities. For that, in this study samples of banana peels were chemically profiled throughout the year to identify the best harvest time of those biomasses regarding their phenolic composition. In this sense, we used additional information on the chemical heterogeneity of the samples determined by the seasoning, through a set of analytical and climatic data to elaborate chemometric models, supported by bioinformatics tools. Through PCA and HCA analyzes, it was detected that low temperatures; normally observed in winter; strongly modulate the banana metabolism, leading to increased amounts of phenolic compounds, and improving the antioxidant activity of the banana peel AE. The samples collected during the months of winter showed a similar profile and a relatively high concentration of phenolic compounds with potential for future studies of biological activities.CAPES -Coordenação de Aperfeiçoamento de Pessoal de Nível Superior(407323/2013-9)info:eu-repo/semantics/publishedVersio
Influence of solar radiation on the production of secondary metabolites in three rice (Oryza sativa) cultivars

Rice (Oryza sativa L.) is one of the most produced and consumed cereals worldwide and has its importance highlighted mainly in developing countries, where it plays a strategic economic and social role. Due to the importance of rice in the diet, its composition and nutritional characteristics are directly related to the health of the population. In the rice production systems, some climatic factors are determinants for the good performance of the crop, inducing the biosynthesis of primary and secondary metabolites. The present study determined the metabolic profiles through UV-visible spectrophotometry of leaf samples of three rice cultivars (Marques -- white, \\^Onix -- black, and Rubi -- red pericarp) throughout the rice's vegetative stages in two experimental times, from September to December 2015 and from January to April 2016. Solar radiation was recorded along the experimental period. To the organosolvent extracts of leaf samples, UV-vis spectrophotometric techniques were applied and the quantitative results of certain metabolites, e.g., chlorophylls, carotenoids, phenolics, flavonoids, and sugars, as well the antioxidant activity, which were analyzed by chemometrics tools. The results showed that biochemical parameters carotenoids, chlorophylls and sugars are more affected by the intensity of the radiation do que as vari\\'\a\veis phenolics, flavonoids and these alterations may be detected through statistical analysis of biochemical concentrations and UV-vis spectra.CAPES -Coordenação de Aperfeiçoamento de Pessoal de Nível Superior(407323/2013-9)info:eu-repo/semantics/publishedVersio
Characterization of the chemical composition of banana peels from southern Brazil across the seasons using nuclear magnetic resonance and chemometrics

Banana peels are a source of important bioactive compounds, such as phenolics, carotenoids, biogenic amines, among others. For industrial usage of that by-product, a certain homogeneity of its chemical composition is claimed, a trait affected by the effect of (a)bioatic ecological factors. In this sense, this study aimed to investigate the banana peels chemical composition, to get insights on eventual metabolic changes caused by the seasons, in southern Brazil. For this purpose, a Nuclear Magnetic Resonance (NMR)-based metabolic profiling strategy was adopted, followed by chemometrics analysis, using the specmine package for the R environment. The obtained results show that the different seasons can, in fact, influence the metabolic composition, namely the levels of metabolites extracted from the bananas peels. The analytical approach herein adopted, i.e., NMR-based metabolomics coupled to chemometrics analysis, seems to enable identifying the chemical heterogeneity of banana peels over the harvest seasons, allowing obtaining standardized extracts for further technological purposes of usage.CAPES -Coordenação de Aperfeiçoamento de Pessoal de Nível Superior(407323/2013-9)info:eu-repo/semantics/publishedVersio
Development of text mining tools for information retrieval from patents

Biomedical literature is composed of an ever increasing number of publications in natural language. Patents are a relevant fraction of those, being important sources of information due to all the curated data from the granting process. However, their unstructured data turns the search of information a challenging task. To surpass that, Biomedical text mining (BioTM) creates methodologies to search and structure that data. Several BioTM techniques can be applied to patents. From those, Information Retrieval is the process where relevant data is obtained from collections of documents. In this work, a patent pipeline was developed and integrated intoFEDER -Federación Española de Enfermedades Raras(NORTE-01-0145-FEDER-000004)info:eu-repo/semantics/publishedVersio
Analysis learning styles though attentiveness

Attention is one of the most widely misused and overgeneralized
constructs found in the educational, learning, instructional, and psychological
sciences. It would be convenient for teachers if they could grasp the attentiveness
states of learners in their classes precisely so that they could try to improve
the way to deliver the course material in a manner that could attract more learners.
When students are doing learning activities using the news technologies is
very hard for the teacher detected if each student her/his level of attentiveness.
Furthermore, different student learn in different ways, each one preferring a different
learning style. This paper presents an experience using different learning
styles with a system that monitoring attention, with the aim of providing a nonintrusive
and non-invasive way, reliable and easy tool that can be used freely in
schools, without changing or interfering with the established working routines.
Specifically, we look at desk students in learning activities, in which the student
spends long time interacting with the computer.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and
FCT – Fundação para a Ciência e Tecnologia within the Project Scope:
UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio
A Proposal of Machine Learning by Rule Generation from Tables with Non-deterministic Information and Its Prototype System

A logical framework on Machine Learning by Rule Generation (MLRG) from tables with non-deterministic information is proposed, and its prototype system in SQL is implemented. In MLRG, the certain rules defined in Rough Non-deterministic Information Analysis (RNIA) are obtained at first, and each uncertain attribute value is estimated so as to cause the certain rules as many as possible, because the certain rules show us the most reliable information. This strategy is similar to the maximum likelihood estimation in statistics. By repeating this process, a standard table and the rules in its table are learned (or estimated) from a given table with non-deterministic information. Even though it will be hard to know the actual unknown values, MLRG will give a plausible estimation value.IJCRS 2017, 3-7 July, Olsztyn, Polan
Forward kinematics of the general triple-arm robot using a distance-based formulation

The final publication is available at link.springer.comDistance-based formulations have successfully been used to obtain closure polynomialsfor planar mechanisms without relying, in most cases, on variable eliminations. The methods re-sulting from previous attempts to generalize these techniques to spatial mechanisms exhibit somelimitations such as the impossibility of incorporating orientation constraints. For the first time, thispaper presents a complete satisfactory generalization. As an example, it is applied to obtain a clo-sure polynomial for the the general triple-arm parallel robot (that is, the 3-RPS 3-DOF robot). Thispolynomial, not linked to any particular reference frame, is obtained without variable eliminationsor tangent-half-angle substitutionsPeer ReviewedPostprint (author's final draft
A new insight into the coupler curves of the RCCC four-bar linkage

The final publication is available at link.springer.comBased on the condition for four points to lie on the unit sphere, derived using Distance Geometry, a new mathematical formulation for the coupler curves of the RCCC linkage is presented. The relevance of this formulation is not only its simplicity, but the elegant way in which we can obtain the derivative of any variable with respect to any other, and the simple way in which intervals of monotonicity can be detected. All these results are compactly expressed in terms of Gramians and, as a consequence, they have a direct geometric meaning contrarily to what happens with previous approaches based on kinematic loop equations.Peer ReviewedPostprint (author's final draft
Robust laparoscopic instruments tracking using colored strips

To assist surgeons in the acquisition of the required skills for the proper execution of the laparoscopic procedure, surgical simulators are used. During training with simulators it is useful to provide a surgical performance quantitative evaluation. Recent research works showed that such evaluation can be obtained by tracking the laparoscopic instruments, using only the images provided by the laparoscope and without hindering the surgical scene. In this work the state of the art method is improved so that a robust tracking can run even with the noisy background provided by realistic simulators. The method was validated by comparison with the tracking of a â\u80\u9cchess-boardâ\u80\u9d pattern and following tests were performed to check the robustness of the developed algorithm. Despite the noisy environment, the implemented method was found to be able to track the tip of the surgical instrument with a good accuracy compared to the other studies in the literature
Improved CTA Coronary Segmentation with a Volume-Specific Intensity Threshold

State-of-the-art CTA imaging equipment has increased increased clinician's ability to make non-invasive diagnoses of coronary heart disease; however, an effective interpretation of the cardiac CTA becomes cumbersome due to large amount of imaged data. Intensity based background suppression is often used to enhance the coronary vasculature but setting a fixed threshold to discriminate coronaries from fatty muscles could be misleading due to non-homogeneous response of contrast medium in CTA volumes. In this work, we propose a volumespecific model of the contrast medium in the coronary segmentation process to improve the segmentation accuracy. The influence of the contrast medium in a CTA volume was modelled by approximating the intensity histogram of the descending aorta with Gaussian approximation. It should be noted that a significant variation in Gaussian mean for 12 CTA volumes validates the need of volume-wise exclusive intensity threshold for accurate coronary segmentation. Moreover, the effectiveness of the adaptive intensity threshold is illustrated with the help of qualitative and quantitative results