A low cost and widely applicable methodology of digital imagen analysis of ores for mineral and envirommental engineering

Technological and environmental problems related to ore processing are a serious limitation for sustainable development of mineral resources, particularly for countries / companies rich in ores, but with little access to sophisticated technology, e.g. in Latin America. Digital image analysis (DIA) can provide a simple, unexpensive and broadly applicable methodology to assess these problems, but this methodology has to be carefully defined, to produce reproducible and relevant information.

Combining data mining and ontology engineering to enrich ontologies and linked data

In this position paper, we claim that the need for time consuming data preparation and result interpretation tasks in knowledge discovery, as well as for costly expert consultation and consensus building activities required for ontology building can be reduced through exploiting the interplay of data mining and ontology engineering. The aim is to obtain in a semi-automatic way new knowledge from distributed data sources that can be used for inference and reasoning, as well as to guide the extraction of further knowledge from these data sources. The proposed approach is based on the creation of a novel knowledge discovery method relying on the combination, through an iterative ?feedbackloop?, of (a) data mining techniques to make emerge implicit models from data and (b) pattern-based ontology engineering to capture these models in reusable, conceptual and inferable artefacts.

Preface. The Language of Architecture and Civil Engineering

Preface

Emotions and the Engineering of Adaptiveness in Complex Systems

A major challenge in the engineering of complex and critical systems is the management of change, both in the system and in its operational environment. Due to the growing of complexity in systems, new approaches on autonomy must be able to detect critical changes and avoid their progress towards undesirable states. We are searching for methods to build systems that can tune the adaptability protocols. New mechanisms that use system-wellness requirements to reduce the influence of the outer domain and transfer the control of uncertainly to the inner one. Under the view of cognitive systems, biological emotions suggests a strategy to configure value-based systems to use semantic self-representations of the state. A method inspired by emotion theories to causally connect to the inner domain of the system and its objectives of wellness, focusing on dynamically adapting the system to avoid the progress of critical states. This method shall endow the system with a transversal mechanism to monitor its inner processes, detecting critical states and managing its adaptivity in order to maintain the wellness goals. The paper describes the current vision produced by this work-in-progress.

Emotions and the Engineering of Adaptiveness in Complex Systems

A major challenge in the engineering of complex and critical systems is the management of change, both in the system and in its operational environment. Due to the growing of complexity in systems, new approaches on autonomy must be able to detect critical changes and avoid their progress towards undesirable states. We are searching for methods to build systems that can tune the adaptability protocols. New mechanisms that use system-wellness requirements to reduce the influence of the outer domain and transfer the control of uncertainly to the inner one. Under the view of cognitive systems, biological emotions suggests a strategy to configure value-based systems to use semantic self-representations of the state. A method inspired by emotion theories to causally connect to the inner domain of the system and its objectives of wellness, focusing on dynamically adapting the system to avoid the progress of critical states. This method shall endow the system with a transversal mechanism to monitor its inner processes, detecting critical states and managing its adaptivity in order to maintain the wellness goals. The paper describes the current vision produced by this work-in-progress.

Reliability and quality in the area of statistical thinking in Engineering

There is remarkable growing concern about the quality control at the time, which has led to the search for methods capable of addressing effectively the reliability analysis as part of the Statistic. Managers, researchers and Engineers must understand that 'statistical thinking' is not just a set of statistical tools. They should start considering 'statistical thinking' from a 'system', which means, developing systems that meet specific statistical tools and other methodologies for an activity. The aim of this article is to encourage them (engineers, researchers and managers) to develop a new way of thinking.

Physics and Mathematics in the Engineering Curriculum: Correlation with Applied Subjects

This paper presents a study in which the relationship between basic subjects (Mathematics and Physics) and applied engineering subjects (related to Machinery, Electrical Engineering, Topography and Buildings) in higher engineering education curricula is evaluated. The analysis has been conducted using the academic records of 206 students for five years. Furthermore, 34 surveys and personal interviews were conducted to analyze the connections between the contents taught in each subject and to identify student perceptions of the correlation with other subjects or disciplines. At the same time, the content of the different subjects have been analyzed to verify the relationship among the disciplines.Aproper coordination among subjects will allow students to relate and interconnect topics of different subjects, even with the ones learnt in previous courses, while also helping to reduce dropout rates and student failures in successfully accomplishing the different courses.