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arXiv 2022年

作者： Aleksic, Slavisa Atanasov, Michael Agius, Jean Calleja Camilleri, Kenneth Čartolovni, Anto Climent-Pérez, Pau Colantonio, Sara Cristina, Stefania Despotovic, Vladimir Ekenel, Hazım Kemal Erakin, Ekrem Florez-Revuelta, Francisco Germanese, Danila Grech, Nicole Sigurðardóttir, Steinunn Gróa Emirzeoğlu, Murat Iliev, Ivo Jovanovic, Mladjan Kampel, Martin Kearns, William Klimczuk, Andrzej Lambrinos, Lambros Lumetzberger, Jennifer Mucha, Wiktor Noiret, Sophie Pajalic, Zada Pérez, Rodrigo Rodriguez Petrova, Galidiya Petrovica, Sintija Pocta, Peter Poli, Angelica Pudane, Mara Spinsante, Susanna Salah, Albert Ali Santofimia, Maria Jose Islind, Anna Sigríður Stoicu-Tivadar, Lacramioara Tellioğlu, Hilda Zgank, Andrej Leipzig University of Applied Sciences Germany TU Wien Austria Department of Anatomy University of Malta Malta Centre for Biomedical Cybernetics Faculty of Engineering Department of Systems and Control Engineering Malta Catholic University of Croatia Croatia Universidad de Alicante Spain Institute of Information Science and Technologies The National Research Council of Italy Italy Department of Systems and Control Engineering University of Malta Malta University of Luxembourg Luxembourg Dept. of Computer Engineering Istanbul Technical University Turkey Reykjavik University School of Computer Science Iceland Sağlık Bilimleri Fakültesi Fizyoterapi ve Rehabilitasyon Karadeniz Technical University Research Information System Turkey TU Sofia Bulgaria Singidunum University Belgrade Serbia University of South Florida United States SGH Warsaw School of Economics Poland Department of Communication and Internet Studies Cyprus University of Technologies Cyprus Technical University of Vienna Austria VID Specialized University Oslo Norway Getafe University Hospital Spain Riga Technical University Latvia University of Zilina Slovakia Università Politecnica Marche Italy Utrecht University Netherlands Universidad de Castilla-La Mancha Spain Reykjavik University Iceland University Politehnica Timisoara Romania University of Maribor Slovenia

It is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living (AAL) technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may

关键词： computer vision

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HIGH SENSITIVITY ISOTOPE CONCENTRATION-RATIO MEASUREMENT CO2 INFRARED LASER system（Ⅱ）

HIGH SENSITIVITY ISOTOPE CONCENTRATION-RATIO MEASUREMENT CO2...

引用

2000 25～(th) International Conference on Infrared and Millimeter Waves Conference Digest

作者： Tomoshi Matsushima Jun-ichi Kawanabe Hiroshi Maekawa Shohei Saimi Tadasi Sueta Yoshio Cho Nara National College of Technology 22 Yata-cho Yamato-Koriyama Nara 369-1080 Japan Aloka Co. Ltd. 19 Imai 3-7 Oume-shi 198-0023 Japan Aloka Co. Ltd. 19 Imai 3-7 Oume-shi 198-0023 Japan Aloka Co. Ltd. 19 Imai 3-7 Oume-shi 198-0023 Japan Setsunan University 8 Ikeda-Nakamachi 17 Neyagawa-shi 572-8505 Japan Faculty of Computer Science and System Engineering Okayama Prefectural University 111 Kuboki Soja Okayama 719-1197 Japan

For high sensitivity measurements of isotope concentration-ratios of trace-level gas mixture,particulaly including carbon dioxide isotopes,we tested a CO-CO composite laser system containingintracavity absorption *** enhancement obtainable by the intracavity absorption cellconfiguration is examined *** in atmospheric air is readily detected and minimumdetectable concentration by the present system was estimated to be 70 *** isotopes,we tested a CO-CO composite laser system containingintracavity absorption *** enhancement obtainable by the intracavity absorption cellconfiguration is examined *** in atmospheric air is readily detected and minimumdetectable concentration by the present system was estimated to be 70 ppb.

关键词： HIGH SENSITIVITY ISOTOPE CONCENTRATION-RATIO MEASUREMENT CO2 INFRARED LASER system

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The Localized Subtraction Approach For EEG and MEG Forward Modeling

arXiv

引用

arXiv 2023年

作者： Höltershinken, Malte B. Lange, Pia Erdbrügger, Tim Buschermöhle, Yvonne Wallois, Fabrice Buyx, Alena Pursiainen, Sampsa Vorwerk, Johannes Engwer, Christian Wolters, Carsten H. Institute for Biomagnetism and Biosignalanalysis University of Münster Münster Germany Institute of Medical Informatics University of Münster Münster Germany Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience University of Münster Münster Germany INSERM U1105 Research Group on Multimodal Analysis of Brain Function Jules Verne University of Picardie Amiens France Pediatric functional exploration of the nervous system department CHU Picardie Amiens France Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Computing Sciences Unit Faculty of Information Technology and Communication Sciences Tampere University Tampere Finland Institute of Electrical and Biomedical Engineering Private University for Health Sciences Medical Informatics and Technology Hall in Tyrol Austria Faculty of Mathematics and Computer Science University of Münster Münster Germany

In FEM-based EEG and MEG source analysis, the subtraction approach has been proposed to simulate sensor measurements generated by neural activity. While this approach possesses a rigorous foundation and produces accurate results, its major downside is that it is computationally prohibitively expensive in practical applications. To overcome this, we developed a new approach, called the localized subtraction approach. This approach is designed to preserve the mathematical foundation of the subtraction approach, while also leading to sparse right-hand sides in the FEM formulation, making it efficiently computable. We achieve this by introducing a cut-off into the subtraction, restricting its influence to the immediate neighborhood of the source. In this work, this approach will be presented, analyzed, and compared to other state-of-the-art FEM right-hand side approaches. Furthermore, we discuss how to arrive at an efficient and stable implementation. We perform validation in multi-layer sphere models where analytical solutions exist. There, we demonstrate that the localized subtraction approach is vastly more efficient than the subtraction approach. Moreover, we find that for the EEG forward problem, the localized subtraction approach is less dependent on the global structure of the FEM mesh, while the subtraction approach is sensitive to the mesh structure even at a distance to the source. Additionally, we show the localized subtraction approach to rival, and in many cases even surpass, the other investigated approaches in terms of accuracy. Especially for the MEG forward problem, where Biot-Savart’s law is employed, we show the localized subtraction approach and the subtraction approach to produce highly accurate approximations of the volume currents close to the source. The localized subtraction approach thus reduces the computational cost of the subtraction approach to an extent that makes it usable in practical applications without sacrificing the rigorousness and

关键词： Mesh generation

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Abstracts from the 6th International Conference on the engineering of Sport, 10-14 July 2006, Olympic Hall, Munich, Germany Abstracts

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SPORTS engineering 2006年第2期9卷 107-127页

作者： [Anonymous] University of Massachusetts Lowell USA Science & Mathematics Department Kettering University Flint USA University of Illinois USA Western Michigan University USA Washington State University USA Casecade Engine USA Kanazawa University Japan Sumitomo Light Metal Japan Massachusetts Institute of Technology USA Nanyang Technological University Bioengineering Singapore University of Vienna Anthropology Austria Department of Mechanical Engineering University of Bath UK INSA Lyon France PETZL France Sports Materials Research Group University of Birmingham UK Laboratoire de Modélisation des Activités Sportives Bourget du Lac France Technical University Kaiserslautern Germany Department of Engineering Mechanics United States Air Force Academy Colorado Springs USA SRAM Corporation Colorado Springs USA Sports Engineering Research Group University of Sheffield UK Sports Engineering CSES Sheffield Hallam University USA Sports Engineering CSES Sheffield Hallam University UK Technische Universität München Germany Rush University Medical Center Chicago USA Faculty of Sports Science Department of Sport Equipment & Materials TU München Germany RMIT University Australia Institute of Health and Sports Sciences University of Tsukuba Ibaraki Japan Machine and Control Department Polytechnic University Kanagawa Japan SRI Sports Ltd. Hyogo Japan SRI Research and Development Ltd. Hyogo Japan Mizuno Corporation Osaka Japan Fukuoka Institute of Technology Fukuoka Japan University of Limerick Éire Graduate School of Engineering Hokkaido University Japan Faculty of Engineering Kitami Institute of Technology Japan University of Calgary Canada TaylorMade-adidas Golf Company USA Davis Mechanical Engineering University of California USA Davis Mechanical & Aeronautical Engineering University of California USA University of Wales Institute Cardiff Cardiff School of Sport UWIC Cardiff Cardiff School of Sport UWIC Wales Loughborough University UK Cranfield University UK Cr

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Corrigendum to “Preparation and characterization of vertically arrayed hydroxyapatite nanoplates on electrospun nanofibers for bone tissue engineering” [Chem. Eng. J. (2014) 612–622]

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Chemical engineering Journal 2015年 264卷 972-972页

作者： Abdalla Abdal-hay Pablo Vanegas Abdel Salam Hamdy Felix B. Engel Ju Hyun Lim Dept. of Bionano System Engineering College of Engineering Chonbuk National University Jeonju 561-756 Republic of Korea Dept. of Computer Science Faculty of Engineering Universidad de Cuenca 01.01.168 Ecuador Dept. of Engineering Materials and Mechanical Design Faculty of Engineering South Valley of University Qena 83523 Egypt Dept. of Manufacturing Engineering College of Engineering and Computer Science University of Texas Pan-American 1201 West University Dr. Edinburg TX 78541-2999 USA Universität Erlangen-Nürnberg Experimental Renal and Cardiovascular Research Department of Nephrology Institute of Pathology 91054 Erlangen Germany Dept. of Urology Gangneung Asan Hospital University of Ulsan College of Medicine Gangneung Republic of Korea

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Spaces of innovation and venture formation: the case of biotech in the United Kingdom

arXiv

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arXiv 2023年

作者： Marzolla, Francesco Nowak, Przemyslaw Sahasrabuddhe, Rohit Singh, Chakresh Straccamore, Matteo Zhivkoplias, Erik Arcaute, Elsa SONY Computer Science Laboratories Rome Via Panisperna 89A Rome00184 Italy Sapienza Univ. of Rome Physics Dept. Piazzale Aldo Moro 2 Rome00185 Italy Warsaw University of Technology Faculty of Physics ul. Koszykowa 75 Warsaw00-662 Poland Mathematical Institute University of Oxford United Kingdom Université Paris Cité Inserm System Engineering and Evolution Dynamics ParisF-75004 France Centro Ricerche Enrico Fermi Via Panisperna 89/A Rome00184 Italy Stockholm Resilience Centre Stockholm University Stockholm106 91 Sweden Centre for Advanced Spatial Analysis University College London United Kingdom

Patents serve as valuable indicators of innovation and provide insights into the spaces of innovation and venture formation within geographic regions. In this study, we utilise patent data to examine the dynamics of innovation and venture formation in the biotech sector across the United Kingdom (UK). By analysing patents, we identify key regions that drive biotech innovation in the UK. Our findings highlight the crucial role of biotech incubators in facilitating knowledge exchange between scientific research and industry. However, we observe that the incubators themselves do not significantly contribute to the diversity of innovations which might be due to the underlying effect of geographic proximity on the influences and impact of the patents. These insights contribute to our understanding of the historical development and future prospects of the biotech sector in the UK, emphasising the importance of promoting innovation diversity and fostering inclusive enterprise for achieving equitable economic growth. © 2023, CC BY.

关键词： Digital storage

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Digital Health and Deep Learning: Opportunities, Challenges, and the Imperative of Data Protection in Wearable Devices

SSRN

引用

SSRN 2024年

作者： Norman, Azah Anir Eke, Christopher Ifeanyi Phiri, Musa Al-Garadi, M.A. Ahmed, Abdulaziz Yeh, Wan-Ju Department of Information System FCSIT University of Malaya Malaysia Department of Computer Science Faculty of Computing Federal University of Lafia Nasarawa state Nigeria Department of Engineering and Technology Mulungushi University PO Box 80415 Kabwe Zambia Department of Biomedical Informatics School of Medicine Vanderbilt University 1161 21st Ave S # D3300 NashvilleTN37232 United States Department of Health Services Administration School of Health Professions University of Alabama at Birmingham 1716 9th Ave S BirminghamAL35233 United States National Cheng-Kung University Department of Law No. 1 University Road Tainan City70 Taiwan

The rapid expansion of digital health technologies has been revolutionized by the combination of deep learning and machine learning models with wearable devices, making it possible to perform sophisticated data analytics, predictive health analytics, and real-time monitoring. The paper examines the fascinating possibilities of deep learning, wearable technology, and digital health while emphasizing the challenges and urgent need for data protection. Deep learning and digital health hold great promise for individualized treatment plans, early disease identification, and ongoing health monitoring. Large volumes of health data can be analyzed by machine learning/deep learning models, which can then produce findings and recommendations that are timely and instructive for patients, doctors, and scholars. However, these opportunities also provide significant challenges such as security and privacy. It becomes critical to protect data against misuse, unauthorized access, and data breaches. Strong data protection protocols, compliance with legal requirements, and ethical considerations to uphold user trust are necessary for ensuring the responsible use of machine learning/algorithms in the healthcare industry. This article also highlights the significance of encouraging transparency, guaranteeing accountability among business players, and developing data protection rules and guidelines for wearable devices. Collaboration between policymakers, healthcare professionals, researchers, and technology developers are essential to address the ethical, legal, and technical complexities surrounding data protection in wearable healthcare devices. By addressing the challenges and imperative of data protection, stakeholders can shape a responsible and secure landscape for digital health and deep learning applications, ensuring the long-term success and adoption of wearable devices in healthcare. © 2024, The Authors. All rights reserved.

关键词： Wearable technology

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Hypertensive retinopathy identification through retinal fundus image using backpropagation neural network

引用

Journal of Physics: Conference Series 2018年第1期978卷

作者： M F Syahputra C Amalia R F Rahmat D Abdullah D Napitupulu M I Setiawan W Albra Nurdin U Andayani Department of Information Technology Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Research Center for Quality System and Testing Technology - Indonesian Institute of Sciences Department of Civil Engineering Narotama University Surabaya Indonesia Department of Management Universitas Malikussaleh Aceh Indonesia

Hypertension or high blood pressure can cause damage of blood vessels in the retina of eye called hypertensive retinopathy (HR). In the event Hypertension, it will cause swelling blood vessels and a decrese in retina performance. To detect HR in patients body, it is usually performed through physical examination of opthalmoscope which is still conducted manually by an ophthalmologist. Certainly, in such a manual manner, takes a ong time for a doctor to detetct HR on aa patient based on retina fundus iamge. To overcome ths problem, a method is needed to identify the image of retinal fundus automatically. In this research, backpropagation neural network was used as a method for retinal fundus identification. The steps performed prior to identification were pre-processing (green channel, contrast limited adapative histogram qualization (CLAHE), morphological close, background exclusion, thresholding and connected component analysis), feature extraction using zoning. The results show that the proposed method is able to identify retinal fundus with an accuracy of 95% with maximum epoch of 1500.

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Scanning Acoustic Microscopy for Quantifying Two-phase Transfer in Operando Alkaline Water Electrolyzer

arXiv

引用

arXiv 2024年

作者： Dou, Zehua Rox, Hannes Ramos, Zyzi Baumann, Robert Ravishankar, Rachappa Czurratis, Peter Yang, Xuegeng Lasagni, Andrés Fabian Eckert, Kerstin Czarske, Juergen Weik, David Faculty of Electrical and Computer Engineering Laboratory of Measurement and Sensor System Technique Technische Universität Dresden Helmholtzstraße 18 Dresden01069 Germany Institute of Fluid Dynamics Helmholtz-Zentrum Dresden-Rossendorf Bautzner Landstraße 400 Dresden01328 Germany PVA TePla Analytical Systems GmbH Deutschordenstraße 38 Westhausen73463 Germany Institute of Manufacturing Science and Engineering Technische Universität Dresden George-Baehr-Straße 3c Dresden01069 Germany Fraunhofer Institute for Material and Beam Technology IWS Winterbergstraße 28 Dresden01277 Germany Institute of Process Engineering and Environmental Technology Technische Universität Dresden Helmholtzstraße 14 Dresden01069 Germany Hydrogen Lab School of Engineering Technische Universität Dresden Helmholtzstraße 14 Dresden01062 Germany Institute for Emerging Electronic Technologies Leibniz Institute for Solid State and Materials Research Dresden Helmholtzstraße 20 Dresden01069 Germany

Improved understandings of two-phase transport in electrochemical gas-evolving systems are increasingly demanded, while high-performance imaging techniques using simplified instrumentations are not readily available. This work presents volumetric scanning acoustic microscopy (SAM) imaging for quantifying the dynamics of gas bubbles and electrolyte in porous Nickel electrodes with different wettability and structures during alkaline water electrolysis (AWE). We realize high-resolution 3D imaging at 10's µm level using high frequency spherically focused ultrasound. The high resolution allowed us to clearly visualize the spatial distributions of produced bubbles in the porous electrodes over time. Moreover, we are able to quantify the residual gas volume in an electrode and its coverage due to bubble evolution, which dominate its transport overpotential. Taking these advantages, we elucidate the impacts of electrodes' wettability and structures on their electrolysis performance, on a regular laboratory base. The obtained knowledge provides us important optimization guidelines of AWE designs and operating schemes. Copyright © 2024, The Authors. All rights reserved.

关键词： Mass transfer

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Preface

EAI/Springer Innovations in Communication and Computing

引用

EAI/Springer Innovations in Communication and Computing 2022年 vii-viii页

作者： Johri, Prashant Diván, Mario José Khanam, Ruqaiya Marciszack, Marcelo Will, Adrián Yamuna Expressway School of Computing Science & Engineering Galgotias University G.B.Nagar Plot No 2 Sector 17 A Greater Noida Uttar Pradesh India Computer Science and Engineering Department SET Sharda University Greater Noida Uttar Pradesh India Information System Department National Technological University-Tucumán Regional Faculty Tucumán Tucumán Argentina Data Science Research Group at Economy School National University of La Pampa Santa Rosa Argentina National Technological University-Córdoba Regional Faculty Córdoba Argentina

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