Moving objects forecast in image sequences using autoregressive algorithms

The objective of this paper is to present an overall approach to forecasting the future position of the moving objects of an image sequence after processing the images previous to it. The proposed method makes use of classical techniques such as optical flow to extract objects’ trajectories and velocities, and autoregressive algorithms to build the predictive model. Our method can be used in a variety of applications, where videos with stationary cameras are used, moving objects are not deformed and change their position with time. One of these applications is traffic control, which is used in this paper as a case study with different meteorological conditions to compare with.

Learning teamwork skills in university programming courses

University courses about computer programming usually seek to provide students not only with technical knowledge, but also with the skills required to work in real-life software projects. Nowadays, the development of software applications requires the coordinated efforts of the members of one or more teams. Therefore, it is important for software professionals to master the sort of skills that assure the success of teamwork, such as communication, leadership, negotiation, or team management. However, these abilities are difficult to teach, one of the reasons being that they require true commitment from the students. However, today students are taking a more and more passive role in their own education, two of the more evident consequences being the increase in dropout rates and the decrease in marks obtained in exams. The NUCLEO e-learning framework has been designed to promote the effective acquisition of teamwork skills and, at the same time, to promote the more active participation of the students in their own learning process. NUCLEO adopts a socio-constructivist pedagogical approach that pursues the development of communities of practice for Problem Based Learning. Our research has rooted the design decisions of NUCLEO in the analysis of its socio-cultural environment with Activity Theory, which considers conflicts within groups as the impetus of their evolution and the forges of their environments. This paper presents the analysis of the main features of NUCLEO according to Activity Theory, as well as the experimental results obtained with the framework in three different case studies in university courses.     

Ordinal regression by a gravitational model in the field of educational data mining

Educational data mining (EDM) is a research area where the goal is to develop data mining methods to examine data critically from educational environments. Traditionally, EDM has addressed the following problems: clustering, classification, regression, anomaly detection and association rule mining. In this paper, the ordinal regression (OR) paradigm, is introduced in the field of EDM. The goal of OR problems is the classification of items in an ordinal scale. For instance, the prediction of students' performance in categories (where the different grades could be ordered according to A ? B ? C ? D) is a classical example of an OR problem. The EDM community has not yet explored this paradigm (despite the importance of these problems in the field of EDM). Furthermore, an amenable and interpretable OR model based on the concept of gravitation is proposed. The model is an extension of a recently proposed gravitational model that tackles imbalanced nominal classification problems. The model is carefully adapted to the ordinal scenario and validated with four EDM datasets. The results obtained were compared with state‐of‐the‐art OR algorithms and nominal classification ones. The proposed models can be used to better understand the learning–teaching process in higher education environments.     

Enhancing the semantics of UML association redefinition

Association redefinition is a UML construct that permits us to define an association end more specifically in a particular context. Concretely, it allows specifying some additional participation and cardinality constraints on the association. Association refinements, which have been studied and used by many authors in conceptual modelling languages prior to UML, are closely related to association redefinitions. They also permit to refine the ends of an association adding participation and cardinality constraints. In this paper, we analyze and compare the semantics of both concepts and propose to extend the semantics of association redefinitions in UML to cover all the constraints that may be expressed by association refinements in other conceptual modelling languages. Additionally, we present how to integrate previous results on validation of association refinements to UML and how to generate code for a relational technology platform. Finally, we provide a prototype tool to verify the feasibility of the approach.     

Pigment and colour stability of frozen kiwi-fruit slices during prolonged storage

Changes in major pigment constituents of frozen kiwi-fruit slices during prolonged storage at –18° C and correlation with colour measurements (Hunter Lab parameters) were studied. Kiwi-fruit cultivars (Hayward, Bruno, Monty and Abbot) were processed without previous treatment and vacuum packed after freezing. HPLC using a diode array detector was used to individually quantify and identify the three major pigment components (xanthophylls, chlorophylls and derivatives and-carotene). The colour of fresh and frozen slices by Hunter Color values were correlated with each class of pigment compounds. An apparent first order degradation rate was found for total chlorophylls and xanthophylls. Hayward and Bruno were more suitable for prolonged freezing preservation in terms of colour deterioration.

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Haltbarkeit von Pigment und Farbe gefrorener Kiwifrucht-Scheiben während langer Lagerung

Zusammenfassung Es wurden die Veränderungen der meisten Pigmentbestandteile gefrorener Kiwifrucht-Scheiben während langer Lagerzeit bei –18°C und die Korrelation mit Farbmessungen studiert. Kiwifrüchte der Sorten Hayward, Bruno, Monty und Abbot wurden ohne vorherige Behandlung unter Vakuum direkt nach dem Gefrierprozeß verpackt. Mit HPLC wurde quantitativ gemessen und die drei Pigmentbestandteile Xanthophyll, Chlorophyll und-Carotin identifiziert. Die Farbe der frischen, gefrorenen Scheiben (Hunter-Farb-Werte) korrelierte mit jedem der Pigmentbestandteile. Ein Verlust, scheinbar erster Ordnung, wurde für Chlorophyll und Xantophyll bei den Sorten Hayward und Bruno beobachtet, jedoch sind sie für das Gefrieren bei langer Lagerzeit trotz Farbverlust geeignet.

     

On the differential benchmarking of promotional efficiency with machine learning modelling (II): Practical applications

The assessment of promotional sales with models constructed by machine learning techniques is arousing interest due, among other reasons, to the current economic situation leading to a more complex environment of simultaneous and concurrent promotional activities. An operative model diagnosis procedure was previously proposed in the companion paper, which can be readily used both for agile decision making on the architecture and implementation details of the machine learning algorithms, and for differential benchmarking among models. In this paper, a detailed example of model analysis is presented for two representative databases with different promotional behaviour, namely, a non-seasonal category (milk) and a heavily seasonal category (beer). The performance of four well-known machine learning techniques with increasing complexity is analyzed in detail here. In particular, k-Nearest Neighbours, General Regression Neural Networks, Multilayer Perceptron (MLP), and Support Vector Machines (SVM), are differentially compared. Present paper evaluates these techniques along the experiments described for both categories when applying the methodological findings obtained in the companion paper. We conclude that some elements included in the architecture are not essential for a good performance of the machine learning promotional models, such as the semiparametric nature of the kernel in SVM models, whereas other can be strongly dependent of the database, such as the convenience of multiple output models in MLP regression schemes. Additionally, the specificity of the behaviour of certain categories and product ranges determines the need to establish suitable and specific procedures for a better prediction and feature extraction.     

Ball Milling of Amaranth Starch-Enriched Fraction. Changes on Particle Size,Starch Crystallinity,and Functionality as a Function of Milling Energy

Starch-enriched fractions of amaranth grain were obtained from planetary ball milling and subsequently studied for particle size reduction, hydration properties, and crystallinity loss. Wide-angle X-ray scattering (WAXS) was used to evaluate the crystalline of starch-enriched fractions, using an iterative smoothing algorithm to estimate amorphous background scattering. This methodology was then used to determine initial crystallinity and monitor crystallinity loss during this process. The attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) showed that ball-milling treatment significantly decreased (p?<?0.05) the intensity ratios of the bands at 1,039 and 1,014 cm^?1 corresponding to the crystalline/amorphous part of starch structure. Starch crystallinity degree decreased by ball milling due to starch amorphization during this process. An excellent correlation was found between crystallinity degree obtained by WAXS and ATR-FTIR data for the whole ball-milled-analyzed samples. The energy required for size reduction was satisfactorily explained using a generalized grinding equation. A decrease of span and median diameter (D ₅₀) indicated sample homogenization during ball milling. Water absorption index and water solubility increased with crystallinity loss during process. The flour produced at the higher milling energy (6.52 kJ/g), with a mean size of 68?±?1 μm, showed a low crystallinity degree (<5 %), and high water absorption and solubility indexes in comparison to the starch-enriched fraction sample. Particle activation provided by ball-milling process can offer chances for starch application such as sorbent agent in food or pharmaceutical industries.     

Comparative study between large-scale and small-scale electrochemical potentiokinetic reactivation performed on AISI 316L austenitic stainless steel

This work optimizes the application of electrochemical potentiokinetic reactivation (EPR) to assess the degree of sensitization (DOS) of AISI 316L and compares the large-scale and small-scale EPR with the aim of improving the study of the different zones of AISI 316L welded joints by using an electrochemical minicell. The optimized EPR allows to discriminate better than the standardized EPR among different DOS. Small-scale EPR shows greater sensitivity to assess the DOS than large-scale EPR: (i) at lower deformation levels; (ii) for shorter sensitization times; (iii) when localized microstructural regeneration is caused by the combined effect of deformation and subsequent sensitization.     

Inactivation of Neosartorya fischeri and Paecilomyces variotii on paperboard packaging material by hydrogen peroxide and heat

This study reports on the influence of heat and hydrogen peroxide combination on the inactivation kinetics of two heat resistant molds: Neosartorya fischeri and Paecilomyces variotii. Spores of different ages (1 and 4 months) of these molds were prepared and D-values (the time required at certain temperature/hydrogen peroxide combination to inactivate 90% of the mold ascospores) were determined using thermal death tubes. D-values found for P. variotii ranged from 1.2 to 25.1 s after exposure to different combinations of heat (40 or 60 °C) and hydrogen peroxide (35 or 40% w/w) while for N. fischeri they varied from 2.7 to 14.3 s after exposure to the same hydrogen peroxide concentrations and higher temperatures (60 or 70 °C). The influence of temperature and hydrogen peroxide concentration on the d-values varied with the genus of mold and their ages. A synergistic effect of heat and hydrogen peroxide in reducing D-values of Paecilomyces variotti and N. fischeri has been observed. In addition to strict control of temperature, time and hydrogen concentration, hygienic storage and handling of laminated paperboard material must be considered to reduce the probability of package’s contamination. All these measures together will ensure package’s sterility that is imperative for the effectiveness of aseptic processing and consequently to ensure the microbiological stability of processed foods during shelf-life.     

Assessment of the bioavailability of toxic and non-toxic arsenic species in seafood samples

Bioavailability of total arsenic, toxic (arsenite, As(III); and arsenate, As(V)), and non-toxic (monomethylarsonic acid, MA; dimethylarsonic acid, DMA; arsenobetaine, AB; and arsenocholine, AC) arsenic species has been assessed in different raw seafood samples (white fish, cold water fish and molluscs) by using an in vitro model that combines simulated gastric and intestinal digestion/dialysis methods. Correlations between arsenic species bioavailability and seafood nutrient contents (fat and protein) have also been established. Total arsenic content in seafood samples, and dialyzable and non-dialyzable fractions, were analyzed by inductively coupled plasma – mass spectrometry (ICP–MS) after a microwave-assisted acid digestion treatment. The determination of the different arsenic species concentrations in the samples (after an optimised matrix solid phase dispersion (MSPD) approach) and in the dialyzable fraction was done by high performance liquid chromatography (HPLC) coupled to ICP-MS as a selective detector. Accuracy of the procedure (total arsenic determination) was assessed by analyzing DORM-2 and BCR-627 certified reference materials. The accuracy of the in vitro procedure was established through a mass-balance study. After statistical evaluation (95% confidence interval), good accuracy of the whole in vitro process, for total arsenic and for arsenic speciation, was observed. High dialyzability percentages for total arsenic and for arsenic species were found (i.e. from 84.6 ± 1.7% to 106 ± 2.6%). Bioavailability of arsenic exhibits a negative correlation with the fat content of the seafood. However, no correlation was observed between the bioavailable fraction of total arsenic and arsenic species and the protein content of the seafood studied.