A PLC Variable Identification Method by Manual Declaration of Time-Stamped Events

International audienc

Machine Learning for Cyber Physical Systems

This open access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments

Simplified literature review on the applicability of process mining to RPA

Business processes play an important role in any enterprise value chain and are involved in key activities such as the purchase of material, sales, and hiring of staff. Hence, mediumsized and large companies are inherently process-oriented. Managing business processes is yet, due to new regulations, technologies, and market changes, not a trivial task. In addition to that, the execution of business processes may be repetitive, tedious and time demanding. For this reason, there is a high motivation to automate such processes, which has been facilitated by the popularisation of Robotic Process Automation (RPA). RPA brings a cost-efficient solution for process automation along with a substantial challenge that is to decide what process to automate and how. Process Mining tools and techniques have been largely adopted to address challenges faced during RPA implementations. The goal of this work is to present the usage of Process Mining in RPA implementations through a simplified systematic literature review.Processos de negócio possuem um papel importante em qualquer cadeia de valores corporativa e estão envolvidos em atividades chave como compras de suprimentos, vendas e contratações de recursos humanos. Por esse motivo, empresas de médio e grande porte são inerentemente orientadas a processos. Devido à novas regulamentações, tecnologias e mudanças de mercado, a gestão de processos de negócio é ainda uma tarefa não trivial. Além disso, a execução de processos de negócio pode ser repetitiva, entendiante e demandar tempo. Por isso, existe uma alta motivação para automatizar processos de negócio, o que tem sido facilitado pela popularização da Automação de Processos Robóticos (Robotic Process Automation - RPA). RPA provê uma solução eficiente em custo para automação de processos e trás desafios no âmbito das escolhas de quais precessos automatizar e como. As ferramentas e metodologias de Mineração de Processos têm sido amplamente utilizadas para endereçar os desafios provenietes de implementações de RPA. O objetivo deste trabalho é apresentar as aplicações da Mineração de Processos em RPA, através de uma revisão sistemática simplificada da literatura

A DEVELOPMENT OF A COMPUTER AIDED GRAPHIC USER INTERFACE POSTPROCESSOR FOR ROTOR BEARING SYSTEMS

Rotor dynamic analysis, which requires extensive amount of data and rigorous analytical processing, has been eased by the advent of powerful and affordable digital computers. By incorporating the processor and a graphical interface post processor in a single set up, this program offers a consistent and efficient approach to rotor dynamic analysis. The graphic user interface presented in this program effectively addresses the inherent complexities of rotor dynamic analyses by linking the required computational algorithms together to constitute a comprehensive program by which input data and the results are exchanged, analyzed and graphically plotted with minimal effort by the user. Just by selecting an input file and appropriate options as required, the user can carry out a comprehensive rotor dynamic analysis (synchronous response, stability analysis, critical speed analysis with undamped map) of a particular design and view the results with several options to save the plots for further verification. This approach helps the user to modify the design of turbomachinery quickly, until an efficient design is reached, with minimal compromise in all aspects

The Challenge of Machine Learning in Space Weather Nowcasting and Forecasting

The numerous recent breakthroughs in machine learning (ML) make imperative to carefully ponder how the scientific community can benefit from a technology that, although not necessarily new, is today living its golden age. This Grand Challenge review paper is focused on the present and future role of machine learning in space weather. The purpose is twofold. On one hand, we will discuss previous works that use ML for space weather forecasting, focusing in particular on the few areas that have seen most activity: the forecasting of geomagnetic indices, of relativistic electrons at geosynchronous orbits, of solar flares occurrence, of coronal mass ejection propagation time, and of solar wind speed. On the other hand, this paper serves as a gentle introduction to the field of machine learning tailored to the space weather community and as a pointer to a number of open challenges that we believe the community should undertake in the next decade. The recurring themes throughout the review are the need to shift our forecasting paradigm to a probabilistic approach focused on the reliable assessment of uncertainties, and the combination of physics-based and machine learning approaches, known as gray-box.Comment: under revie

Nomenclature and Benchmarking Models of Text Classification Models: Contemporary Affirmation of the Recent Literature

In this paper we present automated text classification in text mining that is gaining greater relevance in various fields every day Text mining primarily focuses on developing text classification systems able to automatically classify huge volume of documents comprising of unstructured and semi structured data The process of retrieval classification and summarization simplifies extract of information by the user The finding of the ideal text classifier feature generator and distinct dominant technique of feature selection leading all other previous research has received attention from researchers of diverse areas as information retrieval machine learning and the theory of algorithms To automatically classify and discover patterns from the different types of the documents 1 techniques like Machine Learning Natural Language Processing NLP and Data Mining are applied together In this paper we review some effective feature selection researches and show the results in a table for