8 research outputs found
A framework for automation of data recording, modelling, and optimal statistical control of production lines
Unarguably, the automation of data collection and subsequent statistical treatment enhance
the quality of industrial management systems. The rise of accessible digital technologies has
enabled the introduction of the Industry 4.0 pillars in Cariri local companies. Particularly,
such practice positively contributes to the triple bottom line of sustainable development:
People, Environment, and Economy. The present work aims to provide a general automated
framework for data recording and statistical control of conveyor belts in production lines.
The software has been developed in three layers: graphical user interface, in PHP language;
database collection, search, and safeguard, in MySQL; computational statistics, in R; and
hardware control, in C. The computational statistics are based on the combination of
artificial neural nets and autoregressive integrated and moving average models, via minimal
variance method. The hardware components are composed by open source hardware as
Arduino based boards and modular or industrial sensors. Specifically, the embedded system
is designed to constantly monitor and record a number of measurable characteristics of
the conveyor belts (e.g. electric consumption and temperature), via a number of sensors,
allowing both the computation of statistical control metrics and the evaluation of the
quality of the production system. As a case study, the project makes use of a laminated
limestone production line, located at the Mineral Technology Center, Nova Olinda, Ceará
state, Brazil.Indiscutivelmente, a automação da coleta de dados e o subsequente tratamento estatístico
aumentam a qualidade dos sistemas de gestão industrial. O surgimento de tecnologias
digitais acessíveis possibilitou a introdução dos pilares da Indústria 4.0 nas empresas locais
do Cariri. Particularmente, tal prática contribui positivamente para o triplo resultado do
desenvolvimento sustentável: Pessoas, Meio Ambiente e Economia. O presente trabalho
tem como objetivo fornecer um Framework geral automatizado para registro de dados
e controle estatístico de esteiras transportadoras em linhas de produção. O software foi
desenvolvido em três camadas: interface gráfica do usuário, em linguagem PHP; coleta,
pesquisa e proteção de banco de dados em MySQL; estatística computacional, em R; e
controle de hardware, em C. As estatísticas computacionais são baseadas na combinação de
redes neurais artificiais e modelos autorregressivos integrados e de média móvel, via método
de mínima variância. Os componentes de hardware são compostos por hardware open source
como placas baseadas em Arduino e sensores modulares ou industriais. Especificamente, o
sistema embarcado é projetado para monitorar e registrar constantemente uma série de
características mensuráveis das esteiras transportadoras (por exemplo, consumo elétrico e
temperatura), por meio de uma série de sensores, permitindo tanto o cálculo de métricas
de controle estatístico quanto a avaliação da qualidade do sistema de produção. Como
estudo de caso, o projeto utiliza uma linha de produção de calcário laminado, localizada
no Centro de Tecnologia Mineral, Nova Olinda, Ceará, Brasil
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4
While the increasing availability of global databases on ecological communities has advanced our knowledge
of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In
the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of
Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus
crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced
environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian
Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by
2050. This means that unless we take immediate action, we will not be able to establish their current status,
much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost
Contribuições da Sociologia na América Latina à imaginação sociológica: análise, crítica e compromisso social Sociology's contribution in Latin America to sociological imagination: analysis, critique, and social commitment
O artigo aborda o papel desempenhado pela Sociologia na análise dos processos de transformação das sociedades latino-americanas, no acompanhamento do processo de construção do Estado e da Nação, na problematização das questões sociais na América Latina. São analisados seis períodos na Sociologia na América Latina e no Caribe: I) a herança intelectual da Sociologia ; II) a sociologia da cátedra; III) O período da "Sociologia Científica" e a configuração da "Sociologia Crítica"; IV) a crise institucional, a consolidação da "Sociologia Crítica" e a diversificação da sociologia; V) a sociologia do autoritarismo, da democracia e da exclusão; VI) a consolidação institucional e a mundialização da sociologia da América Latina (desde o ano de 2000), podendo-se afirmar que os traços distintivos do saber sociológico no continente foram: o internacionalismo, o hibridismo, a abordagem crítica dos processos e conflitos das sociedades latino-americanas e o compromisso social do sociólogo.<br>The article focuses on the role played by Sociology in the analysis of processes of change in Latin American societies, in the process of construction of Nation and State, in the debate of social issues in Latin America and the Caribbean. Six periods in Sociology in Latin America and the Caribbean are examined: I) sociology's intellectual legacy; II) sociology as a cathedra; III) the period of "Scientific Sociology"; IV) the institutional crisis, the consolidation of "Critical Sociology", and the diversifying of sociology; V) sociology of authoritarianism, democracy and exclusion; VI) institutional consolidation and globalization of Latin American sociology (since 2000). It may be said that the distinctive features of sociological knowledge in the continent were: internationalism, hybridism, the critical approach to processes and conflicts of Latin American societies, and the sociologist social commitment