Applying black-box testing to UML/OCL database models

Most Unified Modeling Language (UML) computer-aided software engineering tools have been insufficient in the development process because they provide little support for conceptual model testing. Model testing aims to ensure the correctness of a UML/OCL class diagram, or, in other words, that a given class diagram can perfectly meet the user’s requirements. This study proposes the validation of class diagrams with black-box testing, a technique used to test software without focusing on the software’s implementation or structure. An approach is proposed for the automatic transformation of the constraints of a UML/OCL class diagram into test cases. Following the creation of the test cases, they are executed with JUnit and the results produced are shown to the tester. To demonstrate the applicability of this approach, an effectiveness evaluation and an efficiency evaluation are performed here. Evaluation studies show that all faults included in a class diagram have been detected within an efficient time.     

MOE prediction in Abies pinsapo Boiss. timber: Application of an artificial neural network using non-destructive testing

Determining the modulus of elasticity of wood by applying an artificial neural network using the physical properties and non-destructive testing can be a useful method in assessments of the timber structure in old constructions. The modulus of elasticity of Abies pinsapo Boiss. timber was predicted in this study through the parameters of density, width, thickness, moisture content, ultrasonic wave propagation velocity and visual grading of the test pieces. A feedforward multilayer perceptron network was designed for this purpose, achieving 75.0% success in the testing or unknown group.     

Reinforcement learning of pedagogical policies in adaptive and intelligent educational systems

In an adaptive and intelligent educational system (AIES), the process of learning pedagogical policies according the students needs fits as a Reinforcement Learning (RL) problem. Previous works have demonstrated that a great amount of experience is needed in order for the system to learn to teach properly, so applying RL to the AIES from scratch is unfeasible. Other works have previously demonstrated in a theoretical way that seeding the AIES with an initial value function learned with simulated students reduce the experience required to learn an accurate pedagogical policy. In this paper we present empirical results demonstrating that a value function learned with simulated students can provide the AIES with a very accurate initial pedagogical policy. The evaluation is based on the interaction of more than 70 Computer Science undergraduate students, and demonstrates that an efficient and useful guide through the contents of the educational system is obtained.     

Visual specification of measurements and redesigns for domain specific visual languages

Ensuring model quality is a key success factor in many computer science areas, and becomes crucial in recent software engineering paradigms like the one proposed by model-driven software development. Tool support for measurements and redesigns becomes essential to help developers improve the quality of their models. However, developing such helper tools for the wide variety of (frequently domain specific) visual notations used by software engineers is a hard and repetitive task that does not take advantage from previous developments, thus being frequently forgotten.In this paper we present our approach for the visual specification of measurements and redesigns for Domain Specific Visual Languages (DSVLs). With this purpose, we introduce a novel DSVL called SLAMMER that contains generalisations of some of the more used types of internal product measurements and redesigns. The goal is to facilitate the task of defining measurements and redesigns for any DSVL, as well as the generation of tools from such specification reducing or eliminating the necessity of coding. We rely on the use of visual patterns for the specification of the relevant elements for each measurement and redesign type. In addition, SLAMMER allows the specification of redesigns either procedurally or by means of graph transformation rules. These redesigns can be triggered when the measurements reach a certain threshold.These concepts have been implemented in the meta-modelling tool AToM³. In this way, when a DSVL is designed, it is possible to specify measurements and redesigns that will become available in the final modelling environment generated for the language. As an example, we show a case study in the web modelling domain.     

Methodological variations in the production of CORINE land cover and consequences for long-term land cover change studies. The case of Spain.

ABSTRACT

Land cover information at national or regional scale is essential for science, monitoring, reporting, and policy making. CORINE Land Cover (CLC) is the most consistent land cover map for the entire European territory, with four repetitions during the period 1985–2012. The long-term consistency of CLC maps is the most appreciated strength and it should be guaranteed. Beyond some common general guidelines, the mapping approaches used in individual countries differ and change over time, leading to inconsistencies that should be known and reported. Through a series of metrics over the Spanish CLC most recent layers (CLC2006 and CLC2012) and comparisons with eight other countries CLC statistics, we demonstrate that the methodological changes recently implemented have introduced some discrepancies with previous CLC versions. The most affected classes in Spain were transitional woodland-shrub, complex cultivation patterns, artificial, grasslands, and forests. Users should be aware of the important implications these discrepancies may have in land use and land cover change studies, trend analysis, and reports.     

Rheological changes during thermal processing of low-fat meat emulsions formulated with different texture-modifying ingredients

The rheological behaviour of high-fat (22%) and low-fat (8%) meat emulsions during thermal processing in the presence (3%) of various texture-modifying non-meat ingredients, namely maltodextrin, starch, wheat flour, egg white and apple fibre, was analysed. Rheological properties of emulsions were assessed using non-destructive measurements (thermal scanning rigidity monitor, TSRM). The lower the fat content, the lower were the rigidity values of meat emulsions throughout the temperature range studied. Emulsions made with maltodextrin proved less rigid. Addition of starch and egg white favoured the formation of more rigid structures in low-fat meat emulsions at temperatures over 55 °C. Low-fat meat batters containing wheat flour and apple fibre exhibited the highest rigidity values over the given temperature range. The presence of wheat flour caused variations in the modulus of rigidity at all stages of the thermal gelation process, very similar to those observed in high-fat emulsions.     

Predictors of user perceptions of web recommender systems: How the basis for generating experience and search product recommendations affects user responses

One critical question suggested by Web 2.0 is as follows: When is it better to leverage the knowledge of other users vs. rely on the product characteristic-based metrics for online product recommenders? Three recent and notable changes of recommender systems have been as follows: (1) a shift from characteristic-based recommendation algorithms to social-based recommendation algorithms; (2) an increase in the number of dimensions on which algorithms are based; and (3) availability of products that cannot be examined for quality before purchase. The combination of these elements is affecting users’ perceptions and attitudes regarding recommender systems and the products recommended by them, but the psychological effects of these trends remain unexplored. The current study empirically examines the effects of these elements, using a 2 (recommendation approach: content-based vs. collaborative-based, within)×2 (dimensions used to generate recommendations: 6 vs. 30, between)×2 (product type: experience products (fragrances) vs. search products (rugs), between) Web-based study (N=80). Participants were told that they would use two recommender systems distinguished by recommendation approach (in fact, the recommendations were identical). There were no substantive main effects, but all three variables exhibited two-way interactions, indicating that design strategies must be grounded in a multi-dimensional understanding of these variables. The implications of this research for the psychology and design of recommender systems are presented.     

A new family of synthetic diterpenes that regulates cytokine synthesis by inhibiting IkappaBalpha phosphorylation

The synthesis and the biological evaluation of a new family diterpenes are presented. The synthetic studies were inspired by the structural framework of acanthoic acid (1) and yielded a family of compounds that were evaluated as anti-inflammatory agents. Among them, compounds 2, 10, 12, and 16 exhibited a very low nonspecific cytotoxicity and inhibited the synthesis of TNF-alpha with greater than 65 % efficacy at low micromolar concentrations. Cytokine-specificity studies revealed that these compounds also inhibited the synthesis of the proinflammatory cytokines IL-1beta and IL-6, while inhibition of IL-1ra and IL-8 synthesis was marginal and only occurred at high concentrations. Further studies, through EMSA and Western blot analyses, indicated that these compounds decreased the extent of phosphorylation of IkappaBalpha; this suggests that they exert their anti-inflammatory profile by inhibiting NF-kappaB-mediated cytokine synthesis. These findings imply that these diterpenes represent promising leads for the development of novel anti-inflammatory agents.     

Modification of the optical and structural properties of ZnO nanowires by low-energy Ar+ ion sputtering

The effects of low-energy (≤2 kV) Ar⁺ irradiation on the optical and structural properties of zinc oxide (ZnO) nanowires (NWs) grown by a simple and cost-effective low-temperature technique were investigated. Both photoluminescence spectra from ZnO NW-coated films and cathodoluminescence analysis of individual ZnO NWs demonstrated obvious evidences of ultraviolet/visible luminescent enhancement with respect to irradiation fluence. Annihilation of the thinner ZnO NWs after the ion bombardment was appreciated by means of high-resolution scanning electron microscopy and transmission electron microscopy (TEM), which results in an increasing NW mean diameter for increasing irradiation fluences. Corresponding structural analysis by TEM pointed out not only significant changes in the morphology but also in the microstructure of these NWs, revealing certain radiation-sensitive behavior. The possible mechanisms accounting for the decrease of the deep-level emissions in the NWs with the increasing irradiation fluences are discussed according to their structural modifications.     

Effect on Ordering of the Growth of GaInP Layers on (111)-GaAs Faces

GaInP, an essential material for multijunction structures of III–V compounds for solar cells, can achieve better photovoltaic responses when grown on (111)GaAs faces, due to the large internal electric fields generated by the off-diagonal strain. In this work, we explored metalorganic chemical vapor deposition growth of GaInP layers on (001)-, (111)Ga-, and (111)As-GaAs substrates, using different phosphine flow rates. The structural and optical properties of the layers have been studied by micro-Raman spectroscopy, microphotoluminescence, and cathodoluminescence. Problems such as composition control, growth rate, and the presence of ordered phases are addressed.