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International Youth Conference on Energetics (IYCE)

作者： Adelino S. Nabais João R. Galvão Rita M. T. Ascenso Sérgio A. Leitão Department of Energy and Environment Leiria Polytechnic Institute Portugal Department of Computer Science Leiria Polytechnic Institute Portugal Department of Electrical Engineering R&D Unit Portugal INESC-TEC (UTAD pole) School of Sciences and Technology Vila Real Portugal

In this work we present a greenhouse case study with a new energy model based on a Biomass energy source, once it is a more profitable and sustainable energy system, but demands special safety measures. Biomass has so... 详细信息

关键词： Biomass Combustion Boilers Green products Explosions Temperature measurement

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Forecasting: theory and practice

arXiv

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arXiv 2020年

作者： Petropoulos, Fotios Apiletti, Daniele Assimakopoulos, Vassilios Babai, Mohamed Zied Barrow, Devon K. Taieb, Souhaib Ben Bergmeir, Christoph Bessa, Ricardo J. Bijak, Jakub Boylan, John E. Browell, Jethro Carnevale, Claudio Castle, Jennifer L. Cirillo, Pasquale Clements, Michael P. Cordeiro, Clara Oliveira, Fernando Luiz Cyrino de Baets, Shari Dokumentov, Alexander Ellison, Joanne Fiszeder, Piotr Franses, Philip Hans Frazier, David T. Gilliland, Michael Gönül, M. Sinan Goodwin, Paul Grossi, Luigi Grushka-Cockayne, Yael Guidolin, Mariangela Guidolin, Massimo Gunter, Ulrich Guo, Xiaojia Guseo, Renato Harvey, Nigel Hendry, David F. Hollyman, Ross Januschowski, Tim Jeon, Jooyoung Jose, Victor Richmond R. Kang, Yanfei Koehler, Anne B. Kolassa, Stephan Kourentzes, Nikolaos Leva, Sonia Li, Feng Litsiou, Konstantia Makridakis, Spyros Martin, Gael M. Martinez, Andrew B. Meeran, Sheik Modis, Theodore Nikolopoulos, Konstantinos Önkal, Dilek Paccagnini, Alessia Panagiotelis, Anastasios Panapakidis, Ioannis Pavía, Jose M. Pedio, Manuela Pedregal, Diego J. Pinson, Pierre Ramos, Patrícia Rapach, David E. Reade, J. James Rostami-Tabar, Bahman Rubaszek, Michal Sermpinis, Georgios Shang, Han Lin Spiliotis, Evangelos Syntetos, Aris A. Talagala, Priyanga Dilini Talagala, Thiyanga S. Tashman, Len Thomakos, Dimitrios Thorarinsdottir, Thordis Todini, Ezio Arenas, Juan Ramón Trapero Wang, Xiaoqian Winkler, Robert L. Yusupova, Alisa Ziel, Florian School of Management University of Bath United Kingdom Politecnico di Torino Turin Italy Forecasting and Strategy Unit School of Electrical and Computer Engineering National Technical University of Athens Greece Kedge Business School France Department of Management Birmingham Business School University of Birmingham United Kingdom Belgium Faculty of Information Technology Monash University Melbourne Australia INESC TEC – Institute for Systems and Computer Engineering Technology and Science Porto Portugal Department of Social Statistics and Demography University of Southampton United Kingdom Centre for Marketing Analytics and Forecasting Lancaster University Management School Lancaster University United Kingdom School of Mathematics and Statistics University of Glasgow United Kingdom Department of Mechanical and Industrial Engineering University of Brescia Italy Magdalen College University of Oxford United Kingdom ZHAW School of Management and Law Zurich University of Applied Sciences Switzerland ICMA Centre Henley Business School University of Reading United Kingdom Faculdade de Ciências e Tecnologia Universidade do Algarve Portugal CEAUL Faculdade de Ciências Universidade de Lisboa Portugal Brazil Department of Business Informatics and Operations Management Faculty of Economics and Business Administration Universiteit Gent Belgium Let’s Forecast Australia Faculty of Economic Sciences and Management Nicolaus Copernicus University in Torun Poland Econometric Institute Erasmus School of Economics Rotterdam Netherlands Department of Econometrics and Business Statistics Monash University Melbourne Australia SAS United States Newcastle Business School Northumbria University Newcastle upon Tyne United Kingdom Department of Statistical Sciences University of Padua Italy Darden School of Business University of Virginia United States Finance Department Bocconi University Baffi-CAREFIN Centre Milan Italy Department of Tourism and Service Management MODUL Un

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases. © 2020, CC BY.

关键词： Forecasting

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P2550The influence of tonic-clonic seizures on heart rate variability in patients with refractory epilepsyGet access

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European Heart Journal 2019年第SUPPLEMENT_1期40卷

作者： Faria, M T Rodrigues, S Dias, D Rego, R Rocha, H Sa, F Oliveira, A Campelo, M Pereira, J Rocha-Goncalves, F Cunha, J P S Martins, E Centro Hospitalar Universitário de São João E.P.E. Nuclear Medicine Department Porto Portugal Institute for Systems Engineering and Computers - Technology and Science (INESC TEC) FEUP Porto Portugal Centro Hospitalar Universitário de São João E.P.E. Neurophysiology Unit Neurology Department Porto Portugal Centro Hospitalar Universitário de São João E. P. E. Cardiology Department Porto Portugal Faculty of Medicine University of Porto Medicine Department Porto Portugal

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P5346The effect of seizure type on ictal and early post-ictal Heart Rate Variability in patients with focal resistant epilepsyGet access

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European Heart Journal 2019年第SUPPLEMENT_1期40卷

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P278Validation of HMPAO-Tc-99m as a myocardial perfusion radiotracer: preliminary results

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European Heart Journal - Cardiovascular Imaging 2019年第SUPPLEMENT_3期20卷

作者： Faria, M T Oliveira, A Vilas-Boas, M C Maia, P M Rego, R Sousa, J Pereira, J Cunha, J P S Rocha-Goncalves, F Martins, E Centro Hospitalar Universitário de São João E.P.E. Nuclear Medicine Department Porto Portugal Institute for Systems Engineering and Computers - Technology and Science (INESC TEC) FEUP Porto Portugal Centro Hospitalar Universitário de São João E.P.E. Neurophysiology Unit Neurology Department Porto Portugal Centro Hospitalar Universitário de São João E.P.E. Angiology and Vascular Surgery Department Porto Portugal Faculty of Medicine University of Porto Medicine Department Porto Portugal

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International Conference on technology and Innovation in Sports, Health and Wellbeing (TISHW) Vila Real, Portugal. 01-03 December 2016 Abstracts

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BMC SPORTS science MEDICINE AND REHABILITATION 2017年第SUPPL 1期9卷 5-5页

作者： [Anonymous] GAIA Association of Electronic and Information Technologies in the Basque Country Bilbao Spain Universidade de Trás-os-Montes e Alto Douro Vila Real Portugal INESC TEC and Universidade de Trás-os-Montes e Alto Douro Vila Real Portugal Vienna University of Technology Vienna Austria motion3D GmbH Vienna Austria Department of Psychology Masaryk University Faculty of Arts Brno Czech Republic Universidade Nova de Lisboa NOVA IMS Lisboa Portugal NOVA IMS Lisboa Portugal Department of Sport Sciences and CIDESD University of Beira Interior Covilhã Portugal Department of Sport Sciences University of Beira Interior and Research Centre in Sports Sciences Health Sciences and Human Development Covilhã Portugal Department of Sport Sciences University of Beira Interior Research Centre in Sports Sciences Health Sciences and Human Development Covilhã Portugal INESC TEC and University of Trás-os-Montes and Alto Douro Vila Real Portugal Digital Sports Group Pattern Recognition Lab Department of Computer Science Friedrich-Alexander University Erlangen-Nuremberg (FAU) Erlangen Germany Institute for Factory Automation and Production Systems Friedrich-Alexander University Erlangen-Nuremberg (FAU) Erlangen Germany Fisio Lógic Centro de Fisioterapia Lisboa Portugal Faculdade de Motricidade Humana Universidade de Lisboa Laboratório de Comportamento Motor Estrada da Costa 1499-002 Cruz Quebrada Portugal Universidade de Trás-os-Montes e Alto Douro (UTAD) Vila Real Portugal Universidade de Trás-os-Montes e Alto Douro (UTAD) and Instituto de Engenharia de Sistemas e Computadores Tecnologia e Ciência (INESC TEC) Vila Real Portugal INESC TEC and University of Trás-os-Montes e Alto Douro Vila Real Portugal

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BACH: grand challenge on breast cancer histology images

arXiv

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arXiv 2018年

作者： Aresta, Guilherme Araújo, Teresa Kwok, Scotty Chennamsetty, Sai Saketh Safwan, Mohammed Alex, Varghese Marami, Bahram Prastawa, Marcel Chan, Monica Donovan, Michael Fernandez, Gerardo Zeineh, Jack Kohl, Matthias Walz, Christoph Ludwig, Florian Braunewell, Stefan Baust, Maximilian Vu, Quoc Dang Nhat To, Minh Nguyen Kim, Eal Kwak, Jin Tae Galal, Sameh Sanchez-Freire, Veronica Brancati, Nadia Frucci, Maria Riccio, Daniel Wang, Yaqi Sun, Lingling Ma, Kaiqiang Fang, Jiannan Kone, Ismael Boulmane, Lahsen Campilho, Aurélio Eloy, Catarina Polónia, António Aguiar, Paulo INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto4200-465 Portugal Faculty of Engineering of University of Porto Porto4200-465 Portugal Seek AI Limited Hong Kong Bangalore India Gurgaon India Chennai India Center for Computational and Systems Pathology Dpt. of Pathology Icahn School of Medicine at Mount Sinai Mount Sinai Hospital New York United States Konica Minolta Laboratory Europe Munich Germany Institute of Pathology Faculty of Medicine LMU Munich Munich Germany Department of Computer Science and Engineering Sejong University Seoul05006 Korea Republic of Chicago IL United States Naples Italy University of Naples "Federico II" Naples Italy Key Laboratory of RF Circuits and Systems Ministry of Education Hangzhou Dianzi University Hangzhou310018 China Zhejiang Provincial Laboratory of Integrated Circuits Design Hangzhou Dianzi University Hangzhou310018 China p2MIA Research Group LEM2A Lab Faculté des Sciences Université Moulay Ismail Meknes Morocco qLaboratório de Anatomia Patológica Ipatimup Diagnósticos Rua Júilio Amaral de Carvalho 45 Porto4200-135 Portugal Faculdade de Medicina Universidade do Porto Alameda Prof Hernâni Monteiro Porto4200-319 Portugal Universidade do Porto Rua Alfredo Allen 208 Porto4200-135 Portugal Universidade do Porto Rua Alfredo Allen 208 Porto4200-135 Portugal

Breast cancer is the most common invasive cancer in women, affecting more than 10% of women worldwide. Microscopic analysis of a biopsy remains one of the most important methods to diagnose the type of breast cancer. This requires specialized analysis by pathologists, in a task that i) is highly time- and cost-consuming and ii) often leads to nonconsensual results. The relevance and potential of automatic classification algorithms using hematoxylin-eosin stained histopathological images has already been demonstrated, but the reported results are still sub-optimal for clinical use. With the goal of advancing the state-of-the-art in automatic classification, the Grand Challenge on BreAst Cancer Histology images (BACH) was organized in conjunction with the 15th International Conference on Image Analysis and Recognition (ICIAR 2018). BACH aimed at the classification and localization of clinically relevant histopathological classes in microscopy and whole-slide images from a large annotated dataset, specifically compiled and made publicly available for the challenge. Following a positive response from the scientific community, a total of 64 submissions, out of 677 registrations, effectively entered the competition. The submitted algorithms improved the state-of-the-art in automatic classification of breast cancer with microscopy images to an accuracy of 87%. Convolutional neuronal networks were the most successful methodology in the BACH challenge. Detailed analysis of the collective results allowed the identification of remaining challenges in the field and recommendations for future developments. The BACH dataset remains publicly available as to promote further improvements to the field of automatic classification in digital pathology. Copyright © 2018, The Authors. All rights reserved.

关键词： Neurons

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Message Security for Automation and Control Applications based on IEC61131-3

Message Security for Automation and Control Applications bas...

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Future technologies Conference

作者： Aydin Homay Mario de Sousa Antonio Pina Martins Fred Kashefi SYSTEC - Research Center for Systems - Faculty of Engineering University of Porto Porto 4200-465 Portugal INESC TEC - INESC Technology and Science and Faculty of Engineering University of Porto Porto 4200-465 Portugal Computer Science and Engineering University of Texas at Arlington Arlington TX 76019-0015 USA

ISBN: (纸本)9781509041725

Cyber-Physical systems are integration of computer-based equipment used in industrial automation, embedded systems, control systems and etc. computer-based equipment needs to be protected against unauthorized access and control. The widely accepted approach to computer security is based on security in depth, meaning that the computer system is viewed as a layered structure and security is introduced at each of the layers. In this paper, we propose a method of adding security at what is commonly viewed as the lowest level of control the PLC. The approach is based on hashing the process variables or called signals. In this approach an attacking virus is not able to interpret the variables being addressed by the control logic, and therefore inhibiting targeted attacks by a virus wishing to subtly change the controlled system operation without actually destroying the controlled plant. The approach is focused towards DCS whose operation is based on maintaining all variables in an RTDB that exist in the RTOS and used by IEC61131-3 based application.

关键词： Message Virus Cybersecurity Authentication Industrial Control systems

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A novel portable, low-cost kinect-based system for motion analysis in neurological diseases

A novel portable, low-cost kinect-based system for motion an...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： João Paulo Silva Cunha Ana Patricia Rocha Hugo Miguel Pereira Choupina José Maria Fernandes Maria José Rosas Rui Vaz Felix Achilles Anna Mira Loesch Christian Vollmar Elisabeth Hartl Soheyl Noachtar Institute for Systems Engineering and Computers - Technology and Science (INESC TEC) and Faculty of Engineering (FEUP) Universidade do Porto Porto Porto PT Institute of Electronics and Telematics Engineering of Aveiro (IEETA) University of Aveiro Aveiro Portugal Movement Disorders Group São João University Hospital Porto Portugal Neurosciences Unit University of Porto Porto Portugal Epilepsy Center University of Munich Munich Germany Chair for Computer Aided Medical Procedures Technische Universität München Munich Germany

Many neurological diseases, such as Parkinson's disease and epilepsy, can significantly impair the motor function of the patients, often leading to a dramatic loss of their quality of life. Human motion analysis is regarded as fundamental towards an early diagnosis and enhanced follow-up in this type of diseases. In this contribution, we present NeuroKinect, a novel system designed for motion analysis in neurological diseases. This system includes an RGB-D camera (Microsoft Kinect) and two integrated software applications, KiT (KinecTracker) and KiMA (Kinect Motion Analyzer). The applications enable the preview, acquisition, review and management of data provided by the sensor, which are then used for motion analysis of relevant events. NeuroKinect is a portable, low-cost and markerless solution that is suitable for use in the clinical environment. Furthermore, it is able to provide quantitative support to the clinical assessment of different neurological diseases with movement impairments, as demonstrated by its usage in two different clinical routine scenarios: gait analysis in Parkinson's disease and seizure semiology analysis in epilepsy.

关键词： Three-dimensional displays Epilepsy Cameras Monitoring Two dimensional displays Data acquisition

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Magnetic microfluidic platform for biomedical applications using magnetic nanoparticles 4

Magnetic microfluidic platform for biomedical applications u...

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4th International Conference on Materials and Applications for Sensors and Transducers, MAST 2014

作者： Stipsitz, Martin Kokkinis, Georgios Gooneratne, Chinthaka Kosel, Jurgen Cardoso, Susana Cardoso, Filipe Giouroudi, Ioanna Institute of Sensor and Actuator Systems Vienna University of Technology Gusshausstrasse 27-29/366-ISS Vienna1040 Austria Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology Saudi Arabia INESC Microsystems and Nanotechnologies and in Rua Alves Redol 9 Lisbon1000-029 Portugal

ISBN: (纸本)9783038354413

Microfluidic platforms are well-suited for biomedical analysis and usually consist of a set of units which guarantee the manipulation, detection and recognition of bioanalyte in a reliable and flexible manner. Additionally, the use of magnetic fields for perfoming the aforementioned tasks has been steadily gainining interest. This is due to the fact that magnetic fields can be well tuned and applied either externally or from a directly integrated solution in the diagnostic system. In combination with these applied magnetic fields, magnetic nanoparticles are used. In this paper, we present some of our most recent results in research towards a) microfluidic diagnostics using MR sensors and magnetic particles and b) single cell analysis using magnetic particles. We have successfully manipulated magnetically labeled bacteria and measured their response with integrated GMR sensors and we have also managed to separate magnetically labeled jurkat cells for single cell analysis. © 2015 Trans tech Publications, Switzerland.

关键词： Microfluidics

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