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作者： Gaur, Loveleen Bhatia, Ujwal Jhanjhi, N.Z. Muhammad, Ghulam Masud, Mehedi Amity International Business School Amity University Noida India School of Computer Science and Engineering SCE Taylor’s University Subang Jaya Malaysia Research Chair of Pervasive and Mobile Computing King Saud University Riyadh11543 Saudi Arabia Computer Engineering Department College of Computer and Information Sciences King Saud University Riyadh11543 Saudi Arabia Department of Computer Science College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia

The demand for automatic detection of Novel Coronavirus or COVID-19 is increasing across the globe. The exponential rise in cases burdens healthcare facilities, and a vast amount of multimedia healthcare data is being explored to find a solution. This study presents a practical solution to detect COVID-19 from chest X-rays while distinguishing those from normal and impacted by Viral Pneumonia via Deep Convolution Neural Networks (CNN). In this study, three pre-trained CNN models (EfficientNetB0, VGG16, and InceptionV3) are evaluated through transfer learning. The rationale for selecting these specific models is their balance of accuracy and efficiency with fewer parameters suitable for mobile applications. The dataset used for the study is publicly available and compiled from different sources. This study uses deep learning techniques and performance metrics (accuracy, recall, specificity, precision, and F1 scores). The results show that the proposed approach produced a high-quality model, with an overall accuracy of 92.93%, COVID-19, a sensitivity of 94.79%. The work indicates a definite possibility to implement computer vision design to enable effective detection and screening measures. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： COVID-19

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Use of BIM for the optimized operation of road tunnels: Modelling approach, information requirements, and exemplary implementation

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Geomechanik und Tunnelbau 2022年第2期15卷 167-174页

作者： Vollmann, Goetz Stepien, Marcel Riepe, Werner König, Markus Lehan, Anne Thewes, Markus Wahl, Hendrik Ruhr-University Bochum Institute for Tunnelling and Construction Management IC 6-127 Universitätstr. 150 Bochum44780 Germany Ruhr-University Bochum Chair for Computing in Engineering IC 6-63 Universitätstr. 150 Bochum44780 Germany BUNG Ingenieure AG Englerstr. 4 Heidelberg69126 Germany Referat B3 Brüderstraße 53 Bergisch Gladbach51427 Germany

In the operating phase of a road tunnel, not only maintaining or increasing the availability in the network but the economic optimization regarding the life cycle costs of the structure are also important priorities. A consistent application of the Building Information Modelling (BIM) methodology can theoretically make a useful and targeted contribution, as it provides a complete digital model of the structure with all installed elements and the information required for the operator tasks. In the research project FE https://***/15.0623/2016/RRB "Building Information Modeling (BIM) in Tunneling," the Institute of Tunneling and Construction Management and the Institute of computing in engineering (both Ruhr University Bochum) in cooperation with BUNG Ingenieure AG developed the basics for a BIM-based operating model of road tunnels with funding from the Federal Highway Research Institute commissioned by the Federal Ministry of Transport and Digital Infrastructure. In the article, the results of the research are presented on the basis of specific use cases of a BIM-based operation and maintenance management. © 2022, Ernst und Sohn. All rights reserved.

关键词： Life cycle

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TEACHING engineering ETHICS IN THE DISCIPLINES: STRATEGIES TO INTEGRATE ETHICS INTO THE CLASSROOM 52

TEACHING ENGINEERING ETHICS IN THE DISCIPLINES: STRATEGIES T...

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52nd Annual Conference of the European Society for engineering: Educating Responsible Engineers, SEFI 2024

作者： Børsen, T. Cruz, C.C. Giménez, E. Johnson, A.W. Josa, I. Lord, S. Lunn, S. Hazewindus, I. Mehlich, J. Mitchell, J.E. Prasad, P. Ramachandran, V. Rodrigues, R.D. Department of Sustainability and Planning Aalborg University Aalborg Denmark Universidade Federal de São João del-Rei São João del-Rei Brazil University of Michigan Michigan United States The Bartlett School of Sustainable Construction UCL London United Kingdom University of San Diego San Diego United States School of Universal Computing Construction and Engineering Education Florida International University Florida United States 10Ethicist at Filosofie in Actie and De Wijze Haas Universiteit van Amsterdam Amsterdam Netherlands Center for Life Ethics/Hertz Chair TRA 4 Rheinische Friedrich-Wilhelms-Universität Bonn Germany UCL Centre for Engineering Education London United Kingdom School of Computing and Data Sciences FLAME University Pune India University of Manitoba Manitoba Canada

ISBN: (纸本)9782873520274

The importance of ethics education within the engineering curriculum cannot be *** such, it has received considerable emphasis in progressive engineering education curricula ***, it has been noted that many of the examples used relate to generic issues in engineering, for example, failure to follow codes of ethics, rather than issues that are related specifically to engineering *** argue that while these generic issues are important, it is vital that discipline specific examples are also available for educators to embed ethics issues and concerns within technical *** part of the development of the Routledge International Handbook of engineering Ethics Education (Chance et al., forthcoming), the authors represented here have developed a series of chapters to highlight ethics issues and discussions that are pertinent to Chemical engineering, Civil engineering, Electronic and Electrical engineering, Mechanical and Aerospace engineering and Software *** this workshop we engaged educators in an exploration of the ways that discipline specific ethical topics may be embedded in the technical subjects within their *** workshop aimed to support those that are looking to make sure of the handbook to enhance their coverage of ethics within their teaching and will help promote the open-access publication within the engineering education community. © 2024 SEFI 2024 - 52nd Annual Conference of the European Society for engineering, Proceedings: Educating Responsible Engineers. All rights reserved.

关键词： engineering education

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Structuring Clinical Notes of Italian ST-elevation Myocardial Infarction Patients 1

Structuring Clinical Notes of Italian ST-elevation Myocardia...

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1st Workshop on Patient-Oriented Language Processing, CL4Health 2024

作者： Torri, Vittorio Mazzucato, Sara Dalmiani, Stefano Paradossi, Umberto Passino, Claudio Moccia, Sara Micera, Silvestro Ieva, Francesca MOX - Modelling and Scientific Computing Lab Department of Mathematics Politecnico di Milano Italy Biorobotics Institute Department of Excellence in Robotics and AI Scuola Superiore Sant’Anna Italy Fondazione Toscana Gabriele Monasterio Italy Health Science Interdisciplinary Center Scuola Superiore Sant’Anna Italy Bertarelli Foundation Chair in Translational Neural Engineering Center for Neuroprosthetics Institute of Bioengineering Ecole Polytechnique Federale de Lausanne Switzerland HDS - Health Data Science Centre Human Technopole Italy

ISBN: (纸本)9782493814258

In recent years, it has become common for patients to get full access to their Electronic Health Records (EHRs), thanks to the advancements in the EHRs systems of many healthcare providers. While this access empowers patients and doctors with comprehensive and real-time health information, it also introduces new challenges, in particular due to the unstructured nature of much of the information within EHRs. To address this, we propose a pipeline to structure anamneses, providing patients with a clear and concise overview of their health data and its longitudinal evolution, also allowing clinicians to focus more on patient care during consultations. In this paper, we present preliminary results on extracting structured information from EHRs of patients diagnosed with ST-Elevation Myocardial Infarction from an Italian hospital. Our pipeline exploits text classification models to extract relevant clinical variables, comparing rule-based, recurrent neural network and BERT-based models. While various approaches utilized ontologies or knowledge graphs for Italian data, our work represents the first attempt to develop this type of pipeline. The results for the extraction of most variables are satisfactory (f1-score > 0.80), with the exception of the most rare values of certain variables, for which we propose future research directions to investigate. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Recurrent neural networks

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Bio-Signal Based Multimodal Fusion with Bilinear Model for Emotion Recognition

Bio-Signal Based Multimodal Fusion with Bilinear Model for E...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Ashutosh Singh Nina Holzer Theresa Götz Thomas Wittenberg Stephan Göb Shrutika Sawant Muhammad-Momin Salman Jaspar Pahl Fraunhofer Institute for Integrated Circuits IIS Erlangen Germany Chair of Visual Computing Friedrich-Alexander-Universität Erlangen-Nürnberg Germany Department of Industrial Engineering and Health University of Applied Sciences Amberg-Weiden Germany

In this paper, we propose a feature-based multimodal fusion deep-learning approach to combine biosignals, such as electrocardiogram (ECG) and galvanic skin response (GSR) for effective emotion recognition. We make use of a bilinear fusion method to fuse ECG and GSR based features and to jointly capture and complement the complex information from both modalities to enhance the performance of an emotion recognition system. The performance of the proposed fusion approach is evaluated on the MAHNOB-HCI dataset and compared with existing multimodal fusion approaches. Experimental results show that the combination of ECG and GSR features have a high discriminating ability in classifying (or predicting) the emotional states ‘Arousal’ and ‘Valence’ better than that of a single modality based emotion recognition. We also provide the model’s uncertainty analysis to understand how confident the obtained predictions are.

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Probing the High-Entropy Concept Through the Irradiation Response of Near-Equimolar (CrNbTaTiW)C Ceramic Coatings

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High Entropy Alloys & Materials 2024年 1-10页

作者： Osinger, Barbara Tunes, Matheus A. Willenshofer, Patrick Greaves, Graeme Ström, Petter Malinovskis, Paulius Vishnyakov, Vladimir M. Lewin, Erik Fritze, Stefan Department of Chemistry – Ångström Uppsala University Uppsala Sweden Materials Science and Technology Division Los Alamos National Laboratory Los Alamos USA Chair of Nonferrous Metallurgy Montanuniversität Leoben Austria School of Computing and Engineering University of Huddersfield Huddersfield UK Department of Physics and Astronomy Applied Nuclear Physics Uppsala University Uppsala Sweden

High-entropy ceramics have been studied as potential candidates for applications in extreme environments, such as nuclear fusion reactors. Their beneficial properties and increased radiation tolerance are often attributed to their compositional complexity achieved through equimolarity. A near-equimolar (CrNbTaTiW)C carbide, obtained by magnetron sputtering, was investigated using in situ TEM whilst being exposed to 300-keV Xe heavy ion irradiation at 573 K. The material did not show structural changes or amorphisation after irradiation to 8.5 dpa. The pristine material showed partial elemental segregation of Cr and Ti and after irradiation redistribution and homogenisation of the solid solution was observed. Furthermore, the coating showed signs of erosion damage near the surface and along some of the grain boundaries, likely due to sputtering during the energetic particle bombardment. This work suggests the response to irradiation in these novel multicomponent ceramics to be multifaceted—determined by an interplay of composition, microstructure, and constituent elements’ chemistry—going beyond simply equimolarity.

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Evaluating Dry EEG Technology Out of the Lab

Evaluating Dry EEG Technology Out of the Lab

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Metrology for Extended Reality, Artificial Intelligence and Neural engineering (MetroXRAINE), IEEE International Conference on

作者： Mushfika Sultana Osheen Jain Sebastian Halder Ana Matran-Fernandez Rab Nawaz Reinhold Scherer Ricardo Chavarriaga José del R. Millán Serafeim Perdikis BCI-NE CSEE University of Essex Colchester UK Computing Psychology Dept. Goldsmiths UoL London UK Responsible AI Innovation Group ZHAW School of Engineering Winterthur Switzerland Carol Cockrell Curran Endowed Chair University of Texas at Austin Austin USA

ISBN: (数字)9798350378009

ISBN: (纸本)9798350378016

Dry electroencephalography (EEG) electrodes have emerged as a promising solution for enhancing the usability of non-invasive Brain-Computer Interface (BCI) systems. Recent advancements in dry helmets have demonstrated competitiveness in enabling EEG and BCI applications with state-of-the-art gel-based systems. In this study, we evaluate the performance and signal quality of a dry EEG cap for BCI applications in a large population. The assessment was conducted under extremely noisy conditions at a public exhibition, surrounded by numerous attendees and multiple sources of electromagnetic interference. Our analysis includes 100 participants from the Mental Work exhibition and assesses the acquired signal's integrity through, Motor Imagery (MI) classification accuracy, the kurtosis of the raw signals and the deviation of the Power Spectral Density (PSD) spectra from the ideal curve. Results show that 56 participants achieved above chance-level single-sample accuracy, with even higher accuracy observed for peak performance. Frontal channels exhibited higher artifact presence, yet the overall signal quality was comparable to gel-based systems used in the authors' previous studies. These findings confirm the potential of dry EEG technology to enable BCI applications beyond the lab, facilitating everyday use in homes, clinics, and public spaces.

关键词： Accuracy Neural engineering Metrology Motors Helmets Electroencephalography Kurtosis Noise measurement Usability Signal integrity

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Fast, Favorable, and Fair Blockchain-based Exchange of Digital Goods using State Channels

Fast, Favorable, and Fair Blockchain-based Exchange of Digit...

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IEEE International Conference on Blockchain and Cryptocurrency (ICBC)

作者： Matthias Lohr Sven Peldszus Jan Jürjens Steffen Staab Institute for Software Technology University of Koblenz Koblenz Germany Chair for Software Engineering Ruhr University Bochum Bochum Germany Analytic Computing Institute for Artificial Intelligence University of Stuttgart Stuttgart Germany Web and Internet Science Research Group University of Southampton Southampton United Kingdom

ISBN: (数字)9798350316742

ISBN: (纸本)9798350316759

When exchanging data with an untrusted counterpart, there is a risk that the counterpart will not behave honestly. Fair exchange protocols provide fairness guarantees to involved parties, e.g., by employing blockchains as trusted third parties. However, blockchain transaction fees and block creation times render such protocols expensive and slow. Furthermore, grieving attacks impose the risk of significant unilateral costs. To improve on all three, we propose a state channel-based fair exchange protocol with a mechanism to prevent grieving attacks. Our protocol lowers the cost of repeating exchanges and increases performance while preserving security guarantees of state-of-the-art fair exchange protocols. Using the Ethereum blockchain and the Perun state channel framework, we evaluate our protocol with regard to cost and performance showing significant improvements in comparison to the state-of-the-art.

关键词： Protocols Costs Smart contracts Blockchains Cryptocurrency Security Open source software

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Towards efficient implementation of MLP-ANN classifier on the FPGA-based embedded system

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IFAC-PapersOnLine 2022年第4期55卷 207-212页

作者： Rijad Sarić Nejra Beganović Dejan Jokić Edhem Čustović School of Computing Engineering and Mathematical Sciences La Trobe University 3086 Victoria Melbourne Australia Chair of Dynamics and Control University of Duisburg-Essen 47057 Duisburg Germany Department of Electrical and Electronics Engineering International Burch University 71000 Sarajevo Bosnia and Herzegovina

Epilepsy is a widely known neurological disease, causing atypical brain activity such as seizures. Apparently, it is critical to analyse possible triggers as well as establish appropriate medical treatment based on the seizure type. In general, diagnosis of epilepsy is usually conducted by applying various state-of-the-art algorithms to extract useful information from electroencephalography (EEG) signals. For effective real-time epilepsy diagnosis, the biomedical device integrated with the best performing machine learning algorithm is needed. Multilayer Perceptron (feed-forward) Artificial Neural Network (MLP-ANN) has proven to be a much better choice over traditional supervised machine learning algorithms in achieving high accuracy diagnosis. Challenges exist in handling extremely long data processing time in the case of many features in EEG signals plus complex MLP-ANN structure and computations. This research proposes the 5-12-3 MLP-ANN configuration to classify different types of epileptic seizures using Field Programmable Gate Array (FPGA) as a real-time embedded system.

关键词： MLP-ANN FPGA Epileptic seizure Real-time diagnosis

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Special Session: STT-MRAMs: Technology, Design and Test

Special Session: STT-MRAMs: Technology, Design and Test

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VLSI Test Symposium

作者： Anteneh Gebregiorgis Lizhou Wu Christopher Mü nch Siddharth Rao Mehdi B. Tahoori Said Hamdioui Department of Quantum and Computer Engineering Delft University of Technology Delft Netherlands Chair of Dependable Nano Computing Karlsruhe Institute of Technology Karlsruhe Germany IMEC Leuven Belgium

STT-MRAM has long been a promising non-volatile memory solution for the embedded application space owing to its attractive characteristics such as non-volatility, low leakage, high endurance, and scalability. However, the operating requirements for high-performance computing (HPC) and low power (LP) applications involve different challenges. This paper addresses different aspects of STT-MRAM; it will cover state-of-the-art, some new results and future challenges related to technology, design and test. While STT-MRAM devices have shown encouraging performance metrics at device-level, a key challenge has been achieving backend-of-line (BEOL) CMOS compatibility, while retaining the benefits of low power operation. Scaling demands to improve data densities have placed additional challenges in terms of addressing the impact of process-induced damage on device performance at CD < 100 nm. In addition, the paper discusses the design of reliable read mechanism considering the variability effects. Moreover, the failure of traditional fault modeling and test approaches in model STT-MRAM unique defects for appropriate test solutions is demonstrated in this paper based on silicon data.

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