Quantification of the Phase Transformation Kinetics in High Chromium Cast Irons Using Dilatometry and Metallographic Techniques

Metallurgical and Materials Transactions A - Further development of high chromium cast irons (HCCI) is based on tailoring the microstructure, necessitating an accurate control over the phase...     

Hybrid methodology for precipitation estimation using Hydro-Estimator over Brazil

Rainfall measurement is a very important topic to society and for the understanding of the weather and climate, therefore needs to be calculated as accurately as possible. Counteracting the problem of the high temporal and spatial variability of precipitation, geostationary satellites sensors have been proved an excellent tool to this task, providing scans with high temporal resolution and detecting the growth and decay of rain cells. Using infra-red (IR) images obtained from the Geostationary Operational Environmental Satellites (GOES), the Hydro-Estimator (HYDRO) algorithm produces instantaneous precipitation estimates with 30 min temporal resolution and 4 km spatial resolution with a very low latency compared with other more sophisticated methodologies (i.e. passive microwave-based algorithms). However, the IR algorithm has some limitations to estimate precipitation on some cloud systems. In order to overcome this problem, the main objective of this study is to develop a light and fast algorithm, based on the histogram matching (HM) technique, to combine the superior sampling and low latency of the HYDRO IR product with more accurate active microwave-based products over Brazil. The adjusted HYDRO (AHYDRO) product was validated against Brazil rain gauge network for two years (2016–2017) and the performance was assessed by using standard statistical metrics and categorical indices. Results show that the HM technique is able to minimize the large variability and discrepancies among HYDRO and observed precipitation over Brazil. At same time, is able to generate a better bias performance while maintaining the same correlation levels before the adjustment.     

Efficient driver drowsiness detection at moderate levels of drowsiness

Previous research on driver drowsiness detection has focused primarily on lane deviation metrics and high levels of fatigue. The present research sought to develop a method for detecting driver drowsiness at more moderate levels of fatigue, well before accident risk is imminent. Eighty-seven different driver drowsiness detection metrics proposed in the literature were evaluated in two simulated shift work studies with high-fidelity simulator driving in a controlled laboratory environment. Twenty-nine participants were subjected to a night shift condition, which resulted in moderate levels of fatigue; 12 participants were in a day shift condition, which served as control. Ten simulated work days in the study design each included four 30-min driving sessions, during which participants drove a standardized scenario of rural highways. Ten straight and uneventful road segments in each driving session were designated to extract the 87 different driving metrics being evaluated. The dimensionality of the overall data set across all participants, all driving sessions and all road segments was reduced with principal component analysis, which revealed that there were two dominant dimensions: measures of steering wheel variability and measures of lateral lane position variability. The latter correlated most with an independent measure of fatigue, namely performance on a psychomotor vigilance test administered prior to each drive. We replicated our findings across eight curved road segments used for validation in each driving session. Furthermore, we showed that lateral lane position variability could be derived from measured changes in steering wheel angle through a transfer function, reflecting how steering wheel movements change vehicle heading in accordance with the forces acting on the vehicle and the road. This is important given that traditional video-based lane tracking technology is prone to data loss when lane markers are missing, when weather conditions are bad, or in darkness. Our research findings indicated that steering wheel variability provides a basis for developing a cost-effective and easy-to-install alternative technology for in-vehicle driver drowsiness detection at moderate levels of fatigue.     

An approach to conceptual and embodiment design within a new product development lifecycle framework

The design of new innovative products is the result of an accurate and precise management of knowledge sources all over its life cycle, such as technology, market, competitors and suppliers. The work contributes with a framework that shows how the knowledge sources influence in the state-of-the-art and market needs so that they become opportunities for innovating products addressing the whole product life cycle. It provides a systematic path from the early generation of ideas to the production of a new product proposal. Through a deep analysis of previous research works of new product innovation life cycle development frameworks and linking it with knowledge management, strategic planning and scorecards, we came out with a structured contribution. The result considers the concurrent activities and its relationships all the way through the product life cycle that can help in creativity and innovation, combined with a process management proposal. Managing the sources of knowledge in highly dynamic markets and technologies is one of the major difficulties involved in innovative products design and development. The emerging knowledge from external sources is confronted with organisation internal knowledge and experience in order to achieve the first product correct.     

Energy-saving scheduling on IaaS HPC cloud environments based on a multi-objective genetic algorithm

The Journal of Supercomputing - Nowadays, cloud computing is a growing scenario applied to many scientific and manufacturing areas due to its flexibility for adapting to highly demanding computing...     

A theoretical model for the automatic generation of tag clouds

This paper presents a new approach to information retrieval from non-structured attributes in databases, which involves the processing of text attributes. To make retrieval more effective, frequent text sequences are extracted and mathematically represented as intermediate forms which permit a clearer and more precise definition of operations on texts. These intermediate forms appear to users in the form of tag clouds to facilitate content identification, exploration, and querying. In this sense, tag cloud visualization is a simple, user-friendly visual interface to data. This paper proposes a theoretical model for the representation of frequent text sequences and their operations as well as a general procedure for generating tag clouds from text attributes in databases. The tag clouds thus obtained were compared with conventional tag clouds composed of single terms. Our study showed that automatically generated multi-term tag clouds provide better results than mono-term tag clouds.     

Ontologies versus relational databases: are they so different? A comparison

Two main data models are currently used for representing knowledge and information in computer systems. Database models, especially relational databases, have been the leader in last few decades, enabling information to be efficiently stored and queried. On the other hand, ontologies have appeared as an alternative to databases in applications that require a more ‘enriched’ meaning. However, there is controversy regarding the best information modeling technique, as both models present similar characteristics. In this paper, we present a review of how ontologies and databases are related, of what their main differences are and of the mechanisms used to communicate with each other.     

Those Who are no Longer: Photographic image and representation of women’s absence(s) in Mayra Martell’s Ensayo de la Identidad at Ciudad Juarez

The article analyses the work of Mexican photographer Mayra Martell — particularly her series Ensayo de la identidad. Desaparición de mujeres en Ciudad Juárez, México 2005–2010 (Identity Essay. Disappearance of women in Ciudad Juarez, Mexico 2005–2010) — focusing on the visual strategies chosen to represent the absence of those women. this work is particularly interesting, considering both its points of contact and its distance from the strategies used for the representation of desaparecidos (victims of forced disappearance) in contemporary Argentine photography. Special attention is paid to the visual device proposed by Martell to represent these absent bodies and the strategies chosen to denounce these increasingly occurring individual stories with two biographical elements in common: being female and being young. Further, the relationships with previous productions from the Argentine photographic context are discussed in order to reflect on the specific procedures that can induce a tension on the naturalized link between photography and memory, between absence and representation, and between image and denunciation.     

Magnetic Force Microscopy in Liquids

In this work, the use of magnetic force microscopy (MFM) to acquire images of magnetic nanostructures in liquid environments is presented. Optimization of the MFM signal acquisition in liquid media is performed and it is applied to characterize the magnetic signal of magnetite nanoparticles. The ability for detecting magnetic nanostructures along with the well‐known capabilities of atomic force microscopy in liquids suggests potential applications in fields such as nanomedicine, nanobiotechnology, or nanocatalysis.     

A new fusion strategy for web metasearch

In this paper, we present two new list fusion strategies for the collection fusion problem in web metasearch. The new approaches fall in the category of isolated methods since they consider as input the lists obtained by different search engines only, plus a fuzzy degree of relevance in one of the methods. In the latter case, we employ a recently proposed approach for the representation of fuzzy preferences, namely, RL-preference relations. A remarkable contribution of the approaches is that the result of the fusion is an ordered list of indistinguishable groups of documents. This kind of output represents a good compromise between understandability and accuracy of the result. We have illustrated the performance of the method by means of several experiments and a comparison with other web metasearchers.