Search results

The eventual adaptation of archives to new technological possibilities could begin with the creation of digital versions of archival finding aids, which would allow the international diffusion of descriptive information. The Standard Generalized Markup Language (SGML), document type definition (DTD) for archival description known as encoded archival description (EAD) is an appropriate tool for this purpose. Presents a methodological strategy that begins with an analysis of EAD and the informational object to be marked up, allowing the semiautomatic creation of a digital version.

Sociological neoinstitutional approaches indicate that nation-states follow “worldwide models constructed and propagated through global cultural and associational processes” (Meyer, Boli, Thomas, & Ramirez, 1997, p. 144). These worldwide-legitimate models affect every single aspect of social life, molding national policy agendas. Pushed by pressures to conform to global forces, money borrowing, and professionalized knowledge, transitional nations enact models of progress through national planning that may be inconsistent with local practice and requirements (Ramirez & Rubinson, 1979). The analysis presented in this chapter builds upon previous comparative education research by discussing one of those current models: education decentralization. This study centers around one specific aspect of recent decentralization efforts: community participation.

Strategic planning (SP) enables enterprises to plan management and operations activities efficiently in the medium and large term. During its implementation, many processes and methods are manually applied and may be time consuming. The purpose of this paper is to introduce an automatic method to define strategic plans by using text mining (TM) algorithms within a generic SP model especially suited for small- and medium-sized enterprises (SMEs).

Textual feedbacks were collected through a SWOT matrix during the implementation of a SP model in a company dedicated to the local distribution of food. A four-step TM process (performing acquisition, pre-processing, processing, and validation tasks) is applied via a framework developed under the cloud computer paradigm in order to determine the strategic plans.

The use of categorization and clustering algorithms show that unstructured textual information produced during the SP can be efficiently processed and capitalized. Collected evidence reveals the potential to enhance the strategic plans creation with less effort and time, improving the relevance, and producing new technological resources accessible to SMEs.

An innovative framework especially suited for the SMEs based on the synergy assumption of the coupling between TM and a generic SP model.

The Mechanical Engineering course at the University of Campinas is composed of different disciplines in the areas of materials, mechanical design, manufacturing (production and manufacturing), computational systems, thermal and fluids. In the manufacturing area, in particular, there is a discipline entitled Productive Systems whose main objective is to offer to the student a global vision about operations management. In the field of operations management, sustainability is gaining more and more importance; thus, it is important to develop in the students a critical sense about social and environmental aspects. Thus, this paper aims to present the main initiatives developed in the discipline to promote sustainability in engineering students.

Since 2015, the professors responsible for the Productive Systems discipline, assisted by post-graduate students and professors from other universities, have begun to redesign the discipline, including debates, lectures, projects and other initiatives to provide a critical view concerning the traditional concepts taught. The discipline has been performed three times with this new conception. The methodology to structure this research was literature review, documental analyses of the discipline records and meetings with professors that participated in the initiatives. An Action Research approach was performed by two professors and a graduate student. The authors of this paper also compared the results with those obtained by initiatives performed at Chalmers University of Technology (Sweden).

This study allowed to reinforce some results from initiatives performed at Chalmers University of Technology (Sweden); however, some differences were identified. For example, similar to the initiatives mentioned, the professors of University of Campinas had problems with didactic books, as they loosely integrate the basic operations management concepts with sustainable development fundamentals. On the other hand, debates related to social sustainability were considered positive from the point of view of the professors and students, differing from initiatives performed at Chalmers University of Technology.

Results come from one field study (University of Campinas) when professors of the Mechanical Engineering course try to integrate operations management concepts and sustainable development. Different results may be observed by other higher education institutions.

The authors of this paper believe that the diffusion of these initiatives can stimulate other professors and researchers in the field to broaden the academic debate about the insertion of sustainability into engineering courses.

There are few papers presenting didactic experiences and empirical results about the integration of operations management concepts and sustainable development. Results of this paper reinforce some good practices and they also present other ones, in a way that extend the debate about educational engineering.

This study aims to support electricity distribution companies on measuring and predicting customer satisfaction.

The developed methodology selects and applies machine learning techniques such as decision trees, support vector machines and ensemble learning to predict customer satisfaction from service data, power outage data and reliability indices.

The results on the predicted main indicator diverged only by 1.36 per cent of the results obtained by the survey with company customers.

Social, economic and political conjunctures of the regional and national scenario can influence the indicators beyond the input variables considered in this paper.

Currently, the actions taken to increase customer satisfaction are based on the track record of a yearly survey; therefore, the methodology may assist in identifying disturbances on customer satisfaction, enabling decision-making to deal with it in a timely manner.

Development of an intelligent algorithm that can improve its performance with time. Understanding customer satisfaction may improve companies’ performance.

This study aims to analyze the configuration of the board of directors of the five largest banks operating in Brazil, which are members of a financial elite that directly influences the socioeconomic life in Latin America.

This assessment is inspired by Bourdieu's sociological approach and in the discussion on his work in organization studies and economic sociology. It addresses the organization as a field and investigates its associated field of power. The authors conducted qualitative research and relationally analyzed data related to the trajectory and the social properties of the councilors using the statistical technique called multiple correspondence analysis (MCA).

The results show that forms of social and cultural capital are particularly influential in the production of distinctions among banks' board members. Moreover, councils' priorities and configurations are diverse: some idealized and based on knowledge, others pragmatic and based on customs, others still anchored in a double logic of market satisfaction and family wealth preservation.

Understanding the objective power relations among these top agents may be crucial for effectively regulating certain aspects of their activities. Furthermore, understanding how different forms of capital affect the relative position of the board members may help us reduce representative bias in what seems today an inner circle.

This study is relevant because it makes an in-depth analysis of the composition of one of the most influential financial elites in Latin America, combining sociological theory and advanced statistical techniques for qualitative grouping (MCA).

Aiming at the shortcomings of EEG signals generated by brain's sensorimotor region activated tasks, such as poor performance, low efficiency and weak robustness, this paper proposes an EEG signals classification method based on multi-dimensional fusion features.

First, the improved Morlet wavelet is used to extract the spectrum feature maps from EEG signals. Then, the spatial-frequency features are extracted from the PSD maps by using the three-dimensional convolutional neural networks (3DCNNs) model. Finally, the spatial-frequency features are incorporated to the bidirectional gated recurrent units (Bi-GRUs) models to extract the spatial-frequency-sequential multi-dimensional fusion features for recognition of brain's sensorimotor region activated task.

In the comparative experiments, the data sets of motor imagery (MI)/action observation (AO)/action execution (AE) tasks are selected to test the classification performance and robustness of the proposed algorithm. In addition, the impact of extracted features on the sensorimotor region and the impact on the classification processing are also analyzed by visualization during experiments.

The experimental results show that the proposed algorithm extracts the corresponding brain activation features for different action related tasks, so as to achieve more stable classification performance in dealing with AO/MI/AE tasks, and has the best robustness on EEG signals of different subjects.