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7th International Conference on Information Systems, Logistics and Supply Chain, ILS 2018

作者： Machado, Sivanilza Teixeira Dos Reis, João Gilberto Mendes Da Silva, Adriano Maniçoba Bueno, Régis Cortez Tanaka, Wilson Yoshio De Felice Zampini, Eugenio Toloi, Rodrigo Carlo NAPOLE - Advanced Production Operations Logistics and Strategy Center Federal Institute of São Paulo 1501 Mogi das Cruzes Avenue Suzano SP Brazil RESUP - Supply Chain Research Group Post-graduate Program in Production Engineering Paulista University 1212 Dr. Bacelar St. São Paulo SP Brazil iLAB - Image Pattern Recognition Laboratory Federal Institute of São Paulo 1501 Mogi das Cruzes Avenue Suzano SP Singapore

Public health problem is associated to eating habits, such as higher consumption of fast food and popular snakes. Excessive consumption of these foods can cause health problems such as obesity due to its high energy densities. These foods have become commonplace in world culture for their low price and the easy-to-eat foods mass production. It is known that fruits are essential in balanced diets and an important part of the nutrition strategies programs by contribute to a healthy life. Some works has shown a consumer's global trend demand for product and the life quality and between fresh food and healthy. The Brazil are the third in the word in fruit supply chain and one of the biggest problems facing is fruit loss. It is estimated that mean of fruits losses occurs in households. The present study aimed to determine Brazilian preference towards fruit and the Brazilian consumer behavior influence which might contribute to losses during consumption stage. We explored the literature and created a survey with 275 participants, 46% of men and 53% of women, to identify the perception of Brazilian consumers that may contribute to fruit loss. The results shown the consumer preferences in buying mature fruits is associated with habits and can contribute to food losses and waste, because according best practice to fruit preservation is recommended that the majority types of mellow fruits should be stored in refrigerator and some of them should be consume as soon as possible. © ILS 2018 - Information Systems, Logistics and Supply Chain, Proceedings. All rights reserved.

关键词： Citrus fruits

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An Adjustable Face Recognition System for Illumination Compensation Based on Differential Evolution 44th

An Adjustable Face Recognition System for Illumination Compe...

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Conferencia Latinoamericana En Informatica (CLEI)

作者： Guilherme Felippe Plichoski Chidambaram Chidambaram Rafael Stubs Parpinelli Graduate Program in Applied Computing State University of Santa Catarina Joinville Santa Catarina Brazil Department of Production Engineering State University of Santa Catarina Joinville Brazil

ISBN: (纸本)9781728104386

It is well known that face recognition (FR) systems cannot perform well under uncontrolled conditions, but there are no general and robust approaches with total immunity to all conditions. Hence, we present an adjustable FR framework with the aid of the Differential Evolution (DE) optimization algorithm. This approach implements several preprocessing and feature extraction techniques aiming to compensate the illumination variation. The main feature of the present work stands on the use of the DE which is responsible for choosing which strategies to use, as well as tunning the parameters involved. In this case study, we aim to address the illumination compensation problem applying on the well known Yale Extended B face dataset. According to the proposed FR framework, the DE can choose any combination of the following techniques and tune its necessary parameters achieving optimized values: the Gamma Intensity Correction (GIC), the Wavelet-based Illumination Normalization (WBIN), the Gaussian Blur, the Laplacian Edge Detection, the Discrete Wavelet Transform (DWT), the Discrete Cosine Transform (DCT), and the Local Binary Patterns (LBP). Our experimental analysis confirms that the proposed approach is suitable for FR using images under varying conditions. It is proved by the average recognition rate of 99.95% obtained using four different datasets.

关键词： Lighting Feature extraction Discrete wavelet transforms Discrete cosine transforms Optimization Image edge detection

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Food losses in the vegetable supply chain: Evidence from brazilian consumer behaviour 7

Food losses in the vegetable supply chain: Evidence from bra...

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7th International Conference on Information Systems, Logistics and Supply Chain, ILS 2018

作者： Machado, Sivanilza Teixeira Dos Reis, João Gilberto Mendes Da Silva, Adriano Maniçoba Bueno, Régis Cortez Tanaka, Wilson Yoshio De Felice Zampini, Eugenio NAPOLE - Advanced Production Operations Logistics and Strategy Center Federal Institute of São Paulo 1501 Mogi das Cruzes Avenue Suzano SP Brazil RESUP - Supply Chain Research Group Post-graduate Program in Production Engineering Paulista University 1212 Dr. Bacelar St. São Paulo SP Brazil iLAB - Image Pattern Recognition Laboratory Federal Institute of São Paulo 1501 Mogi das Cruzes Avenue Suzano SP Singapore

Food Losses and wastes can become a major social and economic problem if not managed properly. Over the last decades, some research has focused on the waste and loss of fruits and vegetables due to the population growth, which makes essential to find out ways to reduce these wastes and losses. However, few studies dealt with the amount of fruit and vegetables that are wasted by consumers. The purpose of this study is to identify the main causes that affect the generation of wastes in household's consumer behavior. A structured survey was applied to 275 Brazilian consumers, where 53% were female and 47% male, restricted a region of Brazil to identify these causes. The results show that a high education level does not imply a low food waste. Moreover, it indicates that, despite the low volume waste by family, the sum of these wastes represents a huge volume affecting logistics and supply chain management, waste disposal areas and environmental pollution. © ILS 2018 - Information Systems, Logistics and Supply Chain, Proceedings. All rights reserved.

关键词： Vegetables

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Impact of cargo railway transportation service quality on enterprises in Piauí, Brazil

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Supply Chain Forum 2017年第2期18卷 69-75页

作者： Luz, José Alberto Alencar Mendes dos Reis, João Gilberto Macêdo, Jorge Luiz de PostGraduate Program in Production Engineering Universidade Paulista São Paulo Brazil Business Administration Associação de Ensino Superior do Piauí Teresina Brazil Business Administration Faculdade Santo Agostinho Teresina Brazil Production Engineering Uninovapi Teresina Brazil

Railway transportation is critical to the flow of goods, primarily those with low added value and high cargo volume. In this paper, we report findings from a case study featuring interviews with five companies regarding the railway situation in the state of Piauí, Brazil. The results reveal that the railway system loads adopted in Piauí are restricted due to the low availability of routes and poor-quality infrastructure, which increase lead times. Moreover, we found that since the railways are not connected along main production routes, trains cannot be used to export goods. © 2017 Kedge Business School.

关键词： developing country railway transportation Transport infrastructure

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An analysis of the role of trading companies in Brazil's soybean complex using SNA 7

An analysis of the role of trading companies in Brazil's soy...

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7th International Conference on Information Systems, Logistics and Supply Chain, ILS 2018

作者： Toloi, Rodrigo Carlo Dos Reis, João Gilberto Mendes Toloi, Marley Nunes Vituri Bonilla, Silvia Helena Machado, Sivanilza Teixeira RESUP - Supply Chain Research Group Post-Graduate Program in Production Engineering Paulista University 1212 Dr. Bacelar St. São Paulo SP Brazil Federal Institute of Mato Grosso Campus Rondonópolis Rondonópolis Brazil Federal Institute of São Paulo Campus Suzano Suzano Brazil

The soybean complex is one of the largest agribusiness sectors in Brazil. Growers are distributed in different regions of the country and far from cargo ports. The state of Mato Grosso accounts for the largest number of soybeans grown in Brazil and is responsible for around 30% of Brazil's production. The commercialization and distribution of soybean crops are controlled by trading companies who make decisions on exports and the destination of soybean exports. The objective of this work is to determine the influence of trading companies in the Mato Grosso soybean network. To this end, we conducted a network analysis using social networking analysis tools. The results show that two trading companies centralize the commercialization between the Mato Grosso growers and the buyers, and five countries are the major destination of Mato Grosso soybean exports. © ILS 2018 - Information Systems, Logistics and Supply Chain, Proceedings. All rights reserved.

关键词： Supply chains

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Handling Paraconsistency and Paracompleteness in Robotics

Handling Paraconsistency and Paracompleteness in Robotics

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IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA)

作者： Jair M. Abe Kazumi Nakamatsu Seiki Akama Alireza Ahrary Graduate Program in Production Engineering Paulista University São Paulo Brazil University of Hyogo Hyogo Japan C-Republic Tokyo Japan Sojo University Kumamoto Japan

ISBN: (纸本)9781538651513

Automation, and Robotics have experienced incredible improvements over the past decades. Due to the high sophistication more and more elaborated logical tool became necessary to overcome what classical logic offers. In this work, it is shown how a new class of non-classical logics, namely paraconsistent annotated evidential logic Eτ, can be used to deal situations where the presence of conflicting, diffuse and paracomplete must be treated in a non-trivial way. Our purpose is to show its usefulness through examples that have been successfully applied.

关键词： Robot sensing systems Lattices Voltage control Detectors Logic gates

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Paraconsistent Extractor of Mammographic Images Applied in the Process of Diagnosis of Breast Cancer Assisted by Computer

Paraconsistent Extractor of Mammographic Images Applied in t...

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IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA)

作者： Fábio Vieira do Amaral Lauro Henrique de Castro Tomiatti Jair Minoro Abe Kazumi Nakamatsu Henry Costa Ungaro Graduate Program in Production Engineering Paulista University – UNIP São Paulo Brazil School of Human Science and Environment H.S.E University of Hyogo Hyogo Japan

ISBN: (纸本)9781538651513

In this expository work, we show an application of a new class of ANN, namely the Paraconsistent Artificial Neural Network - PANN. Also, we use an algorithm - the Paraconsistent Extractor - for our studies. It was performed on the attributes of mammographic images. To perform these simulations, we used two different databases. The first one is used to classify calcifications, is composed of 143 samples divided into 64 benign cases and 79 malignant cases represented by form. The second is intended for mammographic masses and tumors classification and is composed of 57 regions of interest divided into 37 malignant and 20 benign cases, represented by form factors, transition edges and texture measures. The results demonstrate the qualities of Paraconsistent classifier when using a small number of samples for training the neural network and its low processing time. The proposed classifier can be rated as a Computer-Aided Diagnosis system (CAD). The Paraconsistent Extractor can obtain image parameters and sends them to the paraconsistent artificial neural network to analyze them.

关键词： Shape Breast cancer Artificial neural networks Tumors Training Pattern recognition

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Global priority areas for ecosystem restoration (vol 586, pg 724, 2022)

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NATURE 2022年第7926期609卷 E7-E7页

作者： Strassburg, Bernardo B. N. Iribarrem, Alvaro Beyer, Hawthorne L. Cordeiro, Carlos Leandro Crouzeilles, Renato Jakovac, Catarina C. Braga Junqueira, Andre Lacerda, Eduardo Latawiec, Agnieszka E. Balmford, Andrew Brooks, Thomas M. Butchart, Stuart H. M. Chazdon, Robin L. Erb, Karl-Heinz Brancalion, Pedro Buchanan, Graeme Cooper, David Diaz, Sandra Donald, Paul F. Kapos, Valerie Leclere, David Miles, Lera Obersteiner, Michael Plutzar, Christoph de M. Scaramuzza, Carlos Alberto Scarano, Fabio R. Visconti, Piero Rio Conservation and Sustainability Science Centre Department of Geography and the Environment Pontifical Catholic University Rio de Janeiro Brazil International Institute for Sustainability Rio de Janeiro Brazil Programa de Pós Graduacão em Ecologia Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil Botanical Garden Research Institute of Rio de Janeiro Rio de Janeiro Brazil Forest Ecology and Management Group Wageningen University Wageningen The Netherlands Institut de Ciència i Tecnologia Ambientals Universitat Autònoma de Barcelona Barcelona Spain Department of Geography Fluminense Federal University Niterói Brazil Department of Production Engineering Logistics and Applied Computer Science Faculty of Production and Power Engineering University of Agriculture in Kraków Kraków Poland School of Environmental Sciences University of East Anglia Norwich UK Department of Ecology and Evolutionary Biology University of Connecticut Storrs CT USA World Resources Institute Global Restoration Initiative Washington DC USA Tropical Forests and People Research Centre University of the Sunshine Coast Sunshine Coast Queensland Australia School of Biological Sciences University of Queensland St Lucia Queensland Australia Department of Zoology University of Cambridge Cambridge UK BirdLife International Cambridge UK RSPB Centre for Conservation Science Royal Society for the Protection of Birds Edinburgh UK International Union for Conservation of Nature (IUCN) Gland Switzerland World Agroforestry Center (ICRAF) University of the Philippines Los Baños The Philippines Institute for Marine and Antarctic Studies University of Tasmania Hobart Tasmania Australia Institute of Social Ecology University of Natural Resources and Life Sciences Vienna Vienna Austria Division of Conservation Biology Vegetation Ecology and Landscape Ecology University of Vienna Vienna Austria Department of Forest Sciences ‘Luiz de Queiroz’ College of Agriculture University of São Pau

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Mapping the Conceptual Relationship among Data Analysis, Knowledge Generation and Decision-making in Industrial Processes

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Procedia Manufacturing 2017年 11卷 1751-1758页

作者： dos Santos, Cleiton Ferreira Piechnicki, Flávio de Freitas Rocha Loures, Eduardo Santos, Eduardo Alves Portela Pontifical Catholic University of Paraná (PUC-PR) Graduate Program in Production and Systems Engineering (PPGEPS) 1155 Imaculada Conceição Street Curitiba 80215-901 Brazil

In accordance with Industry 4.0, data should be used for process and/or system integration, including the decision-making process. In this context, this paper aims to relate the process of decision-making with process mining through concept maps, assisting the areas of Data engineering and Analytics. To do so, some Multiple-Criteria Decision-Making/Analysis (MCDM/A) methods will be addressed in order to conceptually highlight the relationship between knowledge and decision dimensions. As a result, the definitions about these fields of study allow perceiving an information and knowledge conciliation approach promoted by the integrated view of process mining and MCDM/A methods. © 2017 The Authors

关键词： Concept Map Industry 4.0. Knowledge Discovery Multiple-Criteria Decision-Making/Analysis (MCDM/A) Process Mining (PM)

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Semi-Supervised Online Elastic Extreme Learning Machine for Data Classification

Semi-Supervised Online Elastic Extreme Learning Machine for ...

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International Joint Conference on Neural Networks

作者： Carlos A. S. da Silva Renato A. Krohling Graduate Program in Computer Science PPGI - Federal University of Espirito Santo (UFES) Vitoria ES Brazil Production Engineering Department Federal University of Espirito Santo (UFES) Vitoria ES Brazil

The Extreme Learning Machine (ELM) is a fast and efficient learning algorithm for single-hidden layer feedforward neural networks (SLFN). Recently, with the increase in data volume in real-world applications, and the need to process data from streaming, two problems have become recurrent in data classification: it is not possible to gather all the necessary data before training the algorithms, and it is difficult to manually label the data for the classification tasks. To address these problems, many variations of ELM have been proposed to allow semi-supervised learning, online sequential learning, or both. In this paper, we propose a variation of ELM called Semi-Supervised Online Elastic Extreme Learning Machine (SSOE-ELM), an algorithm that uses both labeled and unlabeled data to learn in an online sequential way (chunk-by-chunk). We compare our approach to the SOS-ELM in several benchmarks. Our experimental results show that SSOE-ELM outperforms SOS-ELM in accuracy, generalization ability and in training speed.

关键词： Training Partitioning algorithms Matrix decomposition Neurons Heuristic algorithms Laplace equations Cost function

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