Problems of texture classification are consistently challenging once the patterns of different instances can be very similar. In the context of medical imaging, this group of methods can aid in diagnosing patients as part of the concept of Computer-Aided Diagnosis (CAD). In this paper, we propose a method for texture classification in the context of classifying Interstitial Pulmonary Diseases (IPDs) on high-resolution Computed Tomographies (CTs) using concepts of complex networks and statistical metrics. Our approach is based on mapping the input image into multiscale graphs and extracting the closeness centrality metric. We combine the feature vector resulting from the closeness analysis with Haralick and Local Binary Pattern descriptors. We analyze the proposed approach’s performance by comparing it with other methods and discussing its metrics for each class (IPD pattern) of the dataset. Based on the results, we can highlight our technique as an aid on the problem of diagnosing patients with COVID-19.

This paper describes and discusses the results of an empirical study about social-networks/microblogging adoption in a financial institution. Social networking at the workplace literature is overviewed and then presented the methodology and hypothesis of the study. Interviews, a survey and a experimental pilot were used as data collection methods. An extract of the results related with the experimental pilot are discussed and some conclusions derived from them.

The most widely used materials in building construction are porous materials and the combined effect of rising dampness with soluble salts is one major problem. This phenomenon is caused by the migration of the salt ions dissolved in water into the porous network of the construction materials in the building walls, which causes fractures in the materials after several cycles of crystallization/dissolution. This work presents an extensive experimental campaign with different cycles of water absorption (capillarity absorption tests) and drying (drying tests). The samples of building material used are red brick, and the samples were, previously, submitted to capillarity absorption tests with two different saturated solutions (sodium sulphate and potassium chloride). The results showed that the two salts studied influence the porous materials and their capillary coefficient in clearly different ways and the samples immersed in sodium chloride present higher drying rates than those immersed in a saturated sodium sulphate solution.