Proposal of visual strength grading rules for Uruguayan pine timber

A previous database with bending and density data of 261 structural size specimens of currently produced Uruguayan slash pine and loblolly pine timber was adjusted to meet testing and characterization requirements of European standards. Visual parameters and mechanical properties for each specimen were evaluated and their relationship was statistically analyzed. Results suggested that all specimens can be grouped in one visual grade with engineered properties similar to those of European C14 strength class. Modulus of elasticity and characteristic bending strength were the defining properties for class assignation.     

Typing artifacts in megamodeling

Model management is essential for coping with the complexity introduced by the increasing number and varied nature of artifacts involved in model-driven engineering-based projects. Global model management (GMM) addresses this issue by enabling the representation of artifacts, particularly transformation composition and execution, within a model called a megamodel. Type information about artifacts can be used for preventing type errors during execution. Built on our previous work, in this paper we present the core elements of a type system for GMM that improves its original typing approach and enables both typechecking and type inference on artifacts within a megamodel. This type system is able to deal with non-trivial situations such as the use of higher order transformations. We also present a prototypical implementation of such a type system.     

DETONATION CLASSIFICATION FROM ACOUSTIC SIGNATURE WITH THE RESTRICTED BOLTZMANN MACHINE

We compare the recently proposed Discriminative Restricted Boltzmann Machine (DRBM) to the classical Support Vector Machine (SVM) on a challenging classification task consisting in identifying weapon classes from audio signals. The three weapon classes considered in this work (mortar, rocket, and rocket‐propelled grenade), are difficult to reliably classify with standard techniques because they tend to have similar acoustic signatures. In addition, specificities of the data available in this study make it challenging to rigorously compare classifiers, and we address methodological issues arising from this situation. Experiments show good classification accuracy that could make these techniques suitable for fielding on autonomous devices. DRBMs appear to yield better accuracy than SVMs, and are less sensitive to the choice of signal preprocessing and model hyperparameters. This last property is especially appealing in such a task where the lack of data makes model validation difficult.     

Precise segmentation of the bulbar conjunctiva for hyperaemia images

Hyperaemia is an excess of blood in a tissue that causes the appearance of an unusual red hue in the affected area. It is a common occurrence in the bulbar conjunctiva, where it can be related to multiple pathologies, such as conjunctivitis or dry eye syndrome. Specialists grade hyperaemia by means of a tedious, subjective, non-repeatable and time-consuming process. These drawbacks can be solved with the automatisation of the process by means of image processing techniques. The automatic segmentation of the conjunctiva is an important part of the process, as it ensures the absence of noise in posterior stages of the methodology. However, there are several issues of illumination and focus in the input videos that difficult the process. In this work, several segmentation algorithms are proposed and compared in order to obtain an accurate location of the bulbar conjunctiva.     

Presentation of a mixed reality software with a HoloLens headset for a nutrition workshop

Multimedia Tools and Applications - Microsoft has recently released a mixed reality headset called HoloLens. This semi-transparent visor headset allows the user who wears it to view the projection...     

Non-conventional high-pressure extraction process: A comparative study for astaxanthin recovery from Xanthophyllomyces dendrorhous

Xanthophyllomyces dendrorhous is one of the most attractive natural sources of astaxanthin. The yeast produces the compound intracellularly, therefore, it is necessary to evaluate cell rupture methods using clean and efficient technologies for its extraction and it subsequent use in industries. At present work, two non-conventional high-pressure extraction methods were evaluated for astaxanthin recovery: Supercritical fluid extraction and microfluidisation. Results: Effect of pressure (15, 30, and 45 Megapascals; MPa), Temperature (313 and 343 °K) and usage of co-solvent were studied in supercritical extraction process, meanwhile the effect of microfluidisation process (five stages and 160 MPa) for cell rupture and its combination with conventional technics (lithic enzymes, glass beads and ultrasonication) for the recovery of astaxanthin were evaluated. Supercritical fluid extraction presented a higher astaxanthin recovery, 54% yield extraction, at 32.5 MPa and 313 °K, and using ethanol as co-solvent, compared to a 31% yield extraction by mean microfluidisation process at 160 MPa combined with 15 min of sonication (amplitude of 80%).     

What do stakeholders think about knowledge transfer offices? The perspective of firms and research groups in a regional innovation system

Knowledge transfer offices (KTOs) are required to adopt a comprehensive approach to managing a broad set of channels of university–industry collaboration, including collaborative research, business services, exchange of human resources and informal relations within a regional innovation system. The perspectives of firms and academic researchers, the main stakeholders of KTOs, are useful complements to assess KTO activity. The goal of this article is to study the effectiveness that these stakeholders attribute to KTOs. Based on survey data collected in the Spanish region of Andalusia, the article explores stakeholders’ perceptions and determinants. The results show that the level of engagement in a diversified range of activities and the importance attributed to knowledge transfer in the strategy of both research groups and firms are the best predictors of the perceived effectiveness of KTOs. The article also underlines specific differences between the two types of stakeholders.