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Discovery of rare association rules in the distribution of lawsuits in the federal justice system of Southern Brazil

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International Journal of Business Intelligence and Data Mining 2021年第2期18卷 127-154页

作者： dos Santos Gruginskie, Lúcia Adriana Roehe Vaccaro, Guilherme Luís Chiwiacowsky, Leonardo Dagnino Blesz, Attila Elod Graduate Program in Production Engineering and Systems Unisinos Sao Leopoldo RS Brazil Program in Industrial Engineering UCS-Universidade de Caxias do Sul Bento Gonçalves City RS Brazil

In the context of data mining, infrequent association rules may be beneficial for analysing rare or extreme cases with very low support values and high confidence. In researching risky situations or allocating specific resources, such rules may have a much greater impact than rules with high support value. The objective of this study is to obtain association rules from the database of lawsuits filed in the Federal Court of Southern Brazil in 2016, including both frequent and rare rules. By finding these rules, especially rare ones, the information collected can assist in the decision-making process, in this case, such as training clerks or establishing specialised courts. Copyright © 2021 Inderscience Enterprises Ltd.

关键词： Association rules

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Machine learning techniques in bank credit analysis of companies: A case study of a Brazilian bank 49

Machine learning techniques in bank credit analysis of compa...

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49th International Conference on Computers and industrial engineering, CIE 2019

作者： Assef, F.M. Steiner, M.T.A. Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Paraná Curitiba Brazil

The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, not always did the best accuracy represent the best technique for the assessment of this problem. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study. © 2019, Computers and industrial engineering. All rights reserved.

关键词： Support vector machines

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Computer Vision with Cognitive Learning to Improve the Decision-Making During the Sales Process in Physical Stores 16th

Computer Vision with Cognitive Learning to Improve the Decis...

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16th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2019

作者： da Silva Ramalho, Vinícius Szejka, Anderson Luis Rudek, Marcelo Junior, Osiris Canciglieri Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil

ISBN: (纸本)9783030422493

In a world where the information is obtained faster than ever seem, new methods to process that high volume of data are being developed frequently. This is more notorious in a virtual ambient where the data is generated in a manner that is faster and easier to analyze than in the real world. This is very evident in the retail field, where virtual stores have easy access to all the advertisement a user visited and simple to obtain user profile, on the other hand physical stores are limited to basically create a register in a database when there is a purchase. In an attempt to improve the retailers experience from physical stores to manage their business this document has the objective to develop a computational tool that will analyze the people flux going in the establishment, trying to inform the retailer the amount of people and their gender to help the sales process in physical stores. To this end, computational vision methods and algorithms were raised, which after selection, theoretical conception and tool’s implementation it was tested with benchmarks to operate locally and in real time by accessing the cameras installed strategically in a real scenario. Two scenarios were tested: static ambient light and dynamic light. Two tests were conducted: YOLOv2 against background subtraction-based counter;gender classification using full body features. Even though the results were not as positive as needed for commercial use, the tool demonstrated potential and space for improvements. © 2019, IFIP International Federation for Information Processing.

关键词： Computer vision

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An Approach to Semantic Interoperability for Product Development Through Automatic Requirement Extraction and Semantic Reconciliation 16th

An Approach to Semantic Interoperability for Product Develop...

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16th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2019

作者： Canciglieri, Matheus Beltrame de Moura Leite, Athon Francisco Curi Staben Szejka, Anderson Luis Junior, Osiris Canciglieri Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil

ISBN: (纸本)9783030422493

The strong competitiveness challenges manufacturing industry to rationalize different ways of bringing new products to the market in the shortest time with competitive prices while ensuring higher quality. Industries need to effectively share product requirements, which comes from various sources and are heterogeneous in nature, during the Product Development Process (PDP) to stay competitive. However, problems with misinterpretation of such requirements have been identified during its sharing due to semantic interoperability obstacles related to the process of automatically gathering requirements and their translation and reuse. This research proposes an approach to automatically gather product requirements, extracting its knowledge and translate it for further use and reuse along PDP. The research structure consisted of firstly studying the current issues of the topic, secondly by exploring an approach, to be validated in an experimental case. Current issues point out to gaps related to the process of semantic reconciliation and knowledge extraction perspectives, giving it a multi-dimensional panorama where semantic issues are intertwined among different perspectives. The later solution presents an approach which considers raw information being processed into product features, refining knowledge during PDP and making it reusable in different cycles. The approach brings a new view on practical methods for automatically collect product requirements, extract its knowledge and translate it into product features, based on knowledge extraction methods and by using semantic reconciliation as means for translating product’s requirements. Further research will focus on expanding the approach and including more features to increasingly complex cases, to explore the full potential of the approach. © 2019, IFIP International Federation for Information Processing.

关键词： Product design

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Industry 4.0 and Lean Manufacturing Contribute to the Development of the PDP and Market Performance? A Framework 1

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22nd IFIP WG 6.11 Conference on e-Business, e-Services and e-Society, I3E 2023

作者： Tardio, Paulo Roberto Schaefer, Jones Luís Gonçalves, Marcelo Carneiro Nara, Elpidio Oscar Benitez Industrial and Systems Engineering Graduate Program Pontifical Catholic University PR Curitiba Brazil

ISBN: (数字)9783031500404

ISBN: (纸本)9783031500398

To improve production processes, manufacturing companies have made efforts to implement Industry 4.0 technologies and spread the use of Lean Manufacturing (LM) tools. Besides, in addition to the improvements in production processes, these efforts have also been reflected in other issues such as in the Product Development Process (PDP) and Market Performance. In this sense, the objective of this article is to elaborate a conceptual framework covering the constructs of Industry 4.0, LM, and PDP, and to evaluate the importance of these constructs on Market Performance in manufacturing companies in the South of Brazil. The conceptual framework, elaborated with the help of high-impact articles in the area, was evaluated by managers of 111 manufacturing companies in the southern Brazil. The research showed that the implementation of LM tools is more related to the PDP than Industry 4.0 and that large companies have had more positive effects in the implementation of both Industry 4.0 technologies and LM tools. This research can serve as a guide for manufacturing companies, showing the benefits, challenges and opportunities regarding the implementation of LM and Industry 4.0 tools and technologies aiming to improve PDP and Market Performance. It is possible to observe through a structured and systemic framework. © IFIP International Federation for Information Processing 2023.

关键词： Lean production

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Discrete Differential Evolution with Local Search to Solve the Traveling Salesman Problem: Fundamentals and Case Studies

Discrete Differential Evolution with Local Search to Solve t...

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7th IEEE International Conference on Cybernetic Intelligent systems

作者： Sauer, Joao Guilherme Coelho, Leandro dos Santos Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana (PPGEPS/PUCPR) Curitiba Parana Brazil

ISBN: (纸本)9781424429141

Traveling Salesman Problem (TSP) is one of the most difficult problems in the Combinatorial Optimization area. The goal of TSP is to find one path that can travel between all the nodes (instances) of the graph just once (Hamiltonian tour) in the smallest tour, that is, smallest Euclidian distance. In this context, many other meta-heuristics techniques based on evolutionary algorithms have been propose in literature to solve TSP problems. Differential Evolution (DE) is a relatively new simple evolutionary algorithm, which is an effective adaptive approach to global optimization over continuous search spaces. The design principles of DE are simplicity and efficiency. The most distinct feature of DE is that it mutates vectors by adding weighted. random vector differentials to them. Since its invention. DE has been applied with high success on many numerical optimization problems outperforming other more popular meta-heuristics such as the genetic algorithms. Recently. some researchers extended with success the application of DE to complex combinatorial optimization problems with discrete decision variables such as the traveling salesman problem, the machine layout problem, the now-shop scheduling problem. In this paper, the following discrete DE approaches for the TSP are proposed and evaluated: i) DE approach without local search, ii) DE with local search based on Lin-Kernighan-Heulsgaun (LKH) method, and iii) DE with local search based on Variable Neighborhood Search (VNS) and together with LKH method. Numerical study is carried out using the TSPLIB of test TSP problems. In this context, the computational results are compared with the other results in the recent TSP literature. The obtained results show that LKH method is the best method to reach optimal results for TSPLIB benchmarks, but for largest problems, the ED+VNS improve the quality of obtained results.

关键词： Optimization Traveling salesman problem Evolutionary Algorithm Differential Evolution Variable Neighbor Search Local Search Lin-Kernighan-Heulsgaun

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Self-Aware Smart Products: Systematic Literature Review, Conceptual Design and Prototype Implementation

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Procedia Manufacturing 2017年 11卷 1471-1480页

作者： Filho, Marcelo Feliciano Liao, Yongxin Loures, Eduardo Rocha Canciglieri, Osiris Graduate Program in Industrial and Systems Engineering (PPGEPS) Pontifical University Catholic of Paraná Curitiba 80215-901 Brazil

The fourth industrial revolution makes more effective use of data generated during manufacturing processes and creates a more interconnected manufacturing network. The data stored inside a product can be updated, analyzed and protected throughout its life cycle. It is currently becoming a reality to speed up the modern mass-customization. The aim of this paper is firstly to explore the state of art about smart products through a systematic literature review. Second, to design a self-aware smart product in a smart factory production environment based on the review findings. Finally, to turn the conceptual design into a prototype implementation. © 2017

关键词： CPS Industrie 4.0 Intelligent Products IoT RFID Smart Factory Smart Products Systematic Literature Review

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Product lifecycle management and sustainable development in the context of industry 4.0: A systematic literature review 28

Product lifecycle management and sustainable development in ...

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28th ISTE International Conference on Transdisciplinary engineering, TE 2021

作者： De Oliveira, Michele Marcos Andreatta, Luisa Geraldi Stjepandić, Josip Junior, Osiris Canciglieri Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Paraná Curitiba - Paraná Brazil

ISBN: (纸本)9781643682082

The Fourth industrial Revolution and its disruptive technologies are emerging massively. With various motivations for its implementation such as elevation of speed, reducing costs, mitigating errors, and other different factors, more and more technology are being employed to solve business problems and increase profit. Through the years, product lifecycles have been shorted as a good reason to reduce production costs and give to consumers the experience of replacing goods in shorter periods. This linear cycle of 'produce-use-dispose' reached a massive success in the last decades, but have started to show lack of sustainability for consumer and industry. This work aims to conduct a Systematic Literature Review about the future challenges for Product Lifecycle Management and Sustainable Development, considering the context of Industry 4.0. The expected outcome for this study is to find elements that can support the use of 4.0 technologies in Product Lifecycle Management with a strong background for Sustainable Development. © 2021 The authors and IOS Press.

关键词： Industry 4.0

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Water management and conductivity studies in novel polymer zirconium-based membranes for PEM fuel cells

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Case Studies in Chemical and Environmental engineering 2025年 11.0卷

作者： Ahmed, Tallah Magdi Al Othman, Amani Shamayleh, Abdulrahim Tawalbeh, Muhammad Engineering Systems Management Graduate Program American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Department of Chemical and Biological Engineering American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Energy Water and Sustainable Environment Research Center American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Department of Industrial Engineering American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Sustainable and Renewable Energy Engineering Department University of Sharjah PO. Box 27272 Sharjah United Arab Emirates Sustainable Energy & Power Systems Research Centre RISE University of Sharjah P.O. Box 27272 Sharjah United Arab Emirates

Proton exchange membrane fuel cells (PEMFCs) are among the promising alternatives for clean energy generation, especially when hydrogen is the fuel used. Their operation is still faced with several challenges, and one of them is water accumulation in the cathode compartment. If PEMFCs are operated at temperatures above the boiling point of water, a significant obstacle would be eliminated due to the formation of water in the vapor phase. This prevents water from accumulating in the liquid phase which causes flooding. Therefore, this work aims to develop a novel composite membrane based on zirconium silicate (ZrSiO₄) and Polyvinylidene fluoride (PVDF) for such high-temperature operation. The composite membrane was synthesized using solution casting, and its structural and chemical properties were characterized using thermogravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) techniques. The ZrSiO₄/PVDF membrane demonstrated a maximum proton conductivity of 2.14 × 10⁻³ S/cm at room temperature with 8 wt% ZrSiO₄, along with a water uptake value of 43.85 %. Consequently, when tested above the boiling point of water, the membrane exhibited a high conductivity of 2.13 × 10⁻³ S/cm at 105 °C. The results suggest the suitability of such zirconium silicate-based composite membranes for fuel cell applications operating above the boiling point of water. © 2024 The Author(s)

关键词： Composite membranes PEM fuel cells Proton conduction PVDF Water management Zirconium silicate

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Towards an integrated MCDM and BSC method to support the digital transformation strategy in railway companies 28

Towards an integrated MCDM and BSC method to support the dig...

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28th ISTE International Conference on Transdisciplinary engineering, TE 2021

作者： Zanon, Gabriel Nogueira Szejka, Anderson Luis De Freitas Rocha Loures, Eduardo Industrial and Systems Engineering Graduate Program - PPGEPS Pontifical Catholic University of Paraná - PUCPR Curitiba Brazil

ISBN: (纸本)9781643682082

Digital transformation is now widely discussed and applied in different enterprises and under various organizational aspects. Traditional industries recognize the need to innovate and digitalize their business processes and models. Among these industries, the railway sector presents a vast space for digital transformation. The railway has several operational, regulatory, regional and technological specificities that must be taken into account in the digitalization processes. Given the multiple aspects involved and the transdisciplinarity, the digital transformation strategy and roadmap of companies must be defined in a way that fits it to the corporate strategy, allowing digital transformation program to be implemented effectively, prioritizing internal sectors with the greatest strategic impact, generating greater productivity, business models improvement, security and, above all, competitiveness for the sector. This research aims to propose a model for the definition of the digital transformation strategy in the railway companies using the Balanced Scorecard (BSC) as a tool for strategic organizational analysis and multi-criteria decision-making (MCDM) to define the drivers for digital transformation in the railway. Finally, to demonstrate the proposal, a case study will be carried out at a Brazilian railway company. © 2021 The authors and IOS Press.

关键词： Decision making

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