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Retraction notice to "Personal protective equipment-derived pollution during Covid-19 era: A critical review of ecotoxicology impacts, intervention strategies, and future challenges" [Sci. Total Environ. 887(2023) 164164]

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The Science of the total environment 2025年 967卷 178758页

作者： Mehedi Hasan Abu Reza Md Towfiqul Islam Most Mastura Munia Farjana Jion Md Naimur Rahman Susmita Datta Peu Arnob Das A B M Mainul Bari Md Saiful Islam Subodh Chandra Pal Aznarul Islam Tasrina Rabia Choudhury Md Refat Jahan Rakib Abubakr M Idris Guilherme Malafaia Department of Disaster Management Begum Rokeya University Rangpur 5400 Bangladesh. Department of Disaster Management Begum Rokeya University Rangpur 5400 Bangladesh Department of Development Studies Daffodil International University Dhaka 1216 Bangladesh. Department of Geography and Environmental Science Begum Rokeya University Rangpur 5400 Bangladesh. Department of Agriculture Hajee Mohammad Danesh Science and Technology University Dinajpur 5200 Bangladesh. Department of Mechanical Engineering Rajshahi University of Engineering & Technology 6 Rajshahi 6204 Bangladesh. Department of Industrial and Production Engineering Bangladesh University of Engineering and Technology Dhaka 1000 Bangladesh. Department of Soil Science Patuakhali Science and Technology University Dumki Patuakhali 8602 Bangladesh. Department of Geography The University of Burdwan Bardhaman 713104 West Bengal India. Department of Geography Aliah University 17 Gorachand Road Kolkata 700 014 West Bengal India. Analytical Chemistry Laboratory Chemistry Division Atomic Energy Centre Dhaka (AECD) Bangladesh Atomic Energy Commission Dhaka 1000 Bangladesh. Department of Fisheries and Marine Science Faculty of Science Noakhali Science and Technology University Noakhali Bangladesh. Department of Chemistry College of Science King Khalid University Abha 62529 Saudi Arabia Research Center for Advanced Materials Science (RCAMS) King Khalid University Abha Saudi Arabia. Post-Graduation Program in Conservation of Cerrado Natural Resources Goiano Federal Institute Urutaí GO Brazil Post-Graduation Program in Ecology Conservation and Biodiversity Federal University of Uberlândia Uberlândia MG Brazil Post-Graduation Program in Biotechnology and Biodiversity Federal University of Goiás Goiânia GO Brazil.

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The impact of patient clinical information on automated skin cancer detection

arXiv

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arXiv 2019年

作者： Pacheco, Andre G.C. Krohling, Renato R. Graduate Program in Computer Science PPGI Federal University of Espírito Santo UFES Av. Fernando Ferrari 514 Vitória-ES Brazil Production Engineering Department Graduate Program in Computer Science PPGI Federal University of Espírito Santo UFES Av. Fernando Ferrari 514 Vitória-ES Brazil

Skin cancer is one of the most common types of cancer around the world. For this reason, over the past years, different approaches have been proposed to assist detect it. Nonetheless, most of them are based only on dermoscopy images and do not take into account the patient clinical information. In this work, first, we present a new dataset that contains clinical images, acquired from smartphones, and patient clinical information of the skin lesions. Next, we introduce a straightforward approach to combine the clinical data and the images using different well-known deep learning models. These models are applied to the presented dataset using only the images and combining them with the patient clinical information. We present a comprehensive study to show the impact of the clinical data on the final predictions. The results obtained by combining both sets of information show a general improvement of around 7% in the balanced accuracy for all models. In addition, the statistical test indicates significant differences between the models with and without considering both data. The improvement achieved shows the potential of using patient clinical information in skin cancer detection and indicates that this piece of information is important to leverage skin cancer detection systems. Copyright © 2019, The Authors. All rights reserved.

关键词： Dermatology

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Three decades of paraconsistent annotated logics: a review paper on some applications

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Procedia Computer Science 2019年 159卷 1175-1181页

作者： Jair M. Abe Kazumi Nakamatsu João I. da Silva Filho Graduate Program in Production Engineering Paulista University R. Dr. Bacelar 1212 CEP 04026-002 São Paulo – SP Brazil Institute For Advanced Studies – University of São Paulo Brazil School of Human Science and Environment – University of Hyogo Japan Santa Cecília University Brazil

In this expository work, we sketch some applications of annotated logics. Such logics were discovered in the late 1980s and nowadays have become one of the most fertile logics for applications. They constitute a two-s... 详细信息

关键词： annotated logic paraconsistent logic paracomplete logic non-classical logic applications

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RECENT ADVANCES IN DEEP LEARNING APPLIED TO SKIN CANCER DETECTION

arXiv

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arXiv 2019年

Skin cancer is a major public health problem around the world. Its early detection is very important to increase patient prognostics. However, the lack of qualified professionals and medical instruments are significant issues in this field. In this context, over the past few years, deep learning models applied to automated skin cancer detection have become a trend. In this paper, we present an overview of the recent advances reported in this field as well as a discussion about the challenges and opportunities for improvement in the current models. In addition, we also present some important aspects regarding the use of these models in smartphones and indicate future directions we believe the field will take. Copyright © 2019, The Authors. All rights reserved.

关键词： Dermatology

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Sustainable value stream mapping and technologies of Industry 4.0 in manufacturing process reconfiguration: A case study in an apparel company

Sustainable value stream mapping and technologies of Industr...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Ngo Anh Phuong Thomas Guidat Global Production Engineering and Management Faculty of Engineering Vietnamese German University Binh Duong Vietnam Global Production Engineering Program Institute of Machine Tools and Factory Operation Technical University of Berlin Berlin Germany

To optimize resource use in production, Lean manufacturing is the most widely implemented method in the world. One of the most useful tools in Lean production is Value Stream Mapping (VSM). With focus on visualizing key data of a production process in a single picture, VSM attempts to reveal bottleneck steps in a process. As a consequence, industrial engineers can determine which stages of the process should be put emphasis on improving. However, VSM sole consideration is economics and other aspects of sustainability such as societal and environmental are neglected. With Sustainable Value Stream Mapping (SVSM), all necessary illustrations for a sustainable manufacturing process can be visualized, which leads to higher chances to identify potential problems in the efficiency of production processes beyond the ones identified using lean manufacturing. This research provides a case study where SVSM is applied in an apparel company in order to identify potential issues in the sustainability of their production process. Furthermore, this paper highlights several potential solutions such as Radio-frequency identification (RFID), big data and ergonomics improvement by discussing the impact of their implementation on the process sustainability. Finally, the conclusion section discusses limits in the solutions implementation and suggest future research.

关键词： Logistics Informatics production engineering Erbium Machine tools production facilities Industries

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A smartphone application to detection and classification of coffee leaf miner and coffee leaf rust

arXiv

引用

arXiv 2019年

作者： Manso, Giuliano L. Knidel, Helder Krohling, Renato A. Ventura, José A. Labcin-Laboratory of Computing and Engineering Inspired by Nature UFES-Federal University of Espirito Santo Vitória Brazil PPGI-Graduate Program in Computer Science UFES Vitória Brazil Production Engineering Department UFES Vitória Brazil Incaper Rua Afonso Sarlo Vitória ES29052-010 Brazil

Generally, the identification and classification of plant diseases and/or pests are performed by an expert . One of the problems facing coffee farmers in Brazil is crop infestation, particularly by leaf rust Hemileia vastatrix and leaf miner Leucoptera coffeella. The progression of the diseases and or pests occurs spatially and temporarily. So, it is very important to automatically identify the degree of severity. The main goal of this article consists on the development of a method and its i implementation as an App that allow the detection of the foliar damages from images of coffee leaf that are captured using a smartphone, and identify whether it is rust or leaf miner, and in turn the calculation of its severity degree. The method consists of identifying a leaf from the image and separates it from the background with the use of a segmentation algorithm. In the segmentation process, various types of backgrounds for the image using the HSV and YCbCr color spaces are tested. In the segmentation of foliar damages, the Otsu algorithm and the iterative threshold algorithm, in the YCgCr color space, have been used and compared to k-means. Next, features of the segmented foliar damages are calculated. For the classification, artificial neural network trained with extreme learning machine have been used. The results obtained shows the feasibility and effectiveness of the approach to identify and classify foliar damages, and the automatic calculation of the severity. The results obtained are very promising according to experts. Copyright © 2019, The Authors. All rights reserved.

关键词： Neural networks

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Ranking of Classification Algorithms in Terms of Mean–Standard Deviation Using A-TOPSIS

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Annals of Data Science 2018年第1期5卷 93-110页

作者： Pacheco, André G. C. Krohling, Renato A. Graduate Program in Computer Science PPGI UFES - Federal University of Espirito Santo Av. Fernando Ferrari 514 VitóriaESCEP 29060-270 Brazil Production Engineering Department UFES - Federal University of Espirito Santo Av. Fernando Ferrari 514 VitóriaESCEP 29060-270 Brazil

In classification problems when multiple algorithms are applied to different benchmarks a difficult issue arises, i.e., how can we rank the algorithms? In machine learning, it is common to run the algorithms several times and then a statistic is calculated in terms of means and standard deviations. In order to compare the performance of the algorithms, it is very common to employ statistical tests. However, these tests may also present limitations, since they consider only the means and not the standard deviations of the obtained results. In this paper, we present the so-called A-TOPSIS, based on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), to solve the problem of ranking and comparing classification algorithms in terms of means and standard deviations. We use two case studies to illustrate the A-TOPSIS for ranking classification algorithms and the results show the suitability of A-TOPSIS to rank the algorithms. The presented approach can be applied to compare the performance of stochastic algorithms in machine learning. Lastly, to encourage researchers to use the A-TOPSIS for ranking algorithms, we also presented in this work an easy-to-use A-TOPSIS web framework. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Statistical tests

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Retraction notice to "Managing the invisible threat of microplastics in marine ecosystems: Lessons from coast of the Bay of Bengal" [Sci. Total Environ. 889 (2023) 164224]

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The Science of the total environment 2024年 957卷 177730页

作者： Al-Nure Mubin Shahoriar Arefin Md Sonir Mia Abu Reza Md Towfiqul Islam A B M Mainul Bari Md Saiful Islam Mir Mohammad Ali Md Abu Bakar Siddique M Safiur Rahman Venkatramanan Senapathi Abubakr M Idris Guilherme Malafaia Department of Disaster Management Begum Rokeya University Rangpur 5400 Bangladesh. Department of Disaster Management Begum Rokeya University Rangpur 5400 Bangladesh Department of Development Studies Daffodil International University Dhaka 1216 Bangladesh. Department of Industrial and Production Engineering Bangladesh University of Engineering and Technology Dhaka 1000 Bangladesh. Department of Soil Science Patuakhali Science and Technology University Dumki Patuakhali 8602 Bangladesh. Department of Aquaculture Sher - e - Bangla Agricultural University Dhaka 1207 Bangladesh. Institute of National Analytical Research and Service (INARS) Bangladesh Council of Scientific and Industrial Research (BCSIR) Dhanmondi Dhaka 1205 Bangladesh. Analytical Chemistry Laboratory Chemistry Division Atomic Energy Centre Dhaka (AECD) Bangladesh Atomic Energy Commission Dhaka 1000 Bangladesh. Department of Disaster Management Alagappa University Karaikudi Tamilnadu India. Department of Chemistry College of Science King Khalid University Abha 62529 Saudi Arabia Research Center for Advanced Materials Science (RCAMS) King Khalid University Abha Saudi Arabia. Post-Graduation Program in Conservation of Cerrado Natural Resources Goiano Federal Institute Urutaí GO Brazil Post-Graduation Program in Ecology Conservation and Biodiversity Federal University of Uberlândia Uberlândia MG Brazil Post-Graduation Program in Biotechnology and Biodiversity Federal University of Goiás Goiânia GO Brazil.

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Evaluation of Adherence to the Model Six Sigma Using Paraconsistent Logic

Evaluation of Adherence to the Model Six Sigma Using Paracon...

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2018 IEEE International Conference on Innovations in Intelligent Systems and Applications, INISTA 2018

作者： Kirilo, Caique Z. Abe, Jair M. Nogueira, Marcelo Nakamatsu, Kazumi Lozano, Luiz Carlos MacHi De Lima, Luiz A. Software Engineering Research Group Paulista University UNIP São Paulo Brazil Graduate Program in Production Engineering Paulista University UNIP São Paulo Brazil ALGORITMI Centre School of Engineering University of Minho Guimarães Portugal School of Human Science and Environment H.S.E University of Hyogo Hyogo Japan

This study aims to present a compliance analysis tool to Six Sigma by integrating indicative of success and Paraconsistent Method Decision. This way is contributing to a previous scenario analysis that can help the im... 详细信息

ISBN: (纸本)9781538651506

关键词： Six sigma

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Biogas : Alternative energy on supporting environmentally coffee shop in Samosir Island

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IOP Conference Series: Earth and Environmental Science 2020年第1期452卷

作者： Nurzainah Ginting Atifah N Tarigan Inqilab Akbar Royba Animal Production Study Program Faculty of Agriculture Universitas Sumatera Utara Medan 20155 Indonesia Toba Lake & Sustainable Tourism Working Group Universitas Sumatera Utara Medan 20155 Indonesia Architecture Program Study Faculty of Engineering Universitas Sumatera Utara Medan 20155 Indonesia

Samosir Island is one of tourism destination in Indonesia and there was an increasing of coffee shop number. This research tries to investigate how much financial profit received by coffee shop if it use biogas as a new energy source. This research had been conducted from April to June 2018. Research parameter were production costs, income, revenue, Benefit Cost Ratio, Revenue Cost Ratio, Return On Investment, Break Even Point, and identify opportunities, threats, strengths and weaknesses by SWOT analysis to identify whether the community of Samosir is willing to use biogas. The results of financial analysis namely production cost IDR 1,964,500; income of IDR.4,360,000; revenue of IDR. 2,303,000; B/C (%) was 79.7; R/C (%) was 151; ROI (year) of 1.6; BEP Price was IDR. 5,302; BEP production of 361 glass. By SWOT Analysis it was known that development strategies are taken place include socialize biogas technology, benefits of biogas on energy, fertilizer and soil quality to the community, benefits of biogas in saving fuel purchases and providing biogas stock devices on biogas group. The result showed that biogas was worthy of being used as a new energy source on the coffee shop business on Samosir Island.

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