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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Ding, Peisheng Wahn, Hannes Chen, Fu-Der Luo, Xianshu Lo, Guo-Qiang Poon, Joyce K.S. Sacher, Wesley D. Max Planck Institute of Microstructure Physics Weinberg 2 Halle06120 Germany Department of Electrical and Computer Engineering University of Toronto 10 King's College Road TorontoONM5S 3G4 Canada Advanced Micro Foundry Pte Ltd 11 Science Park Road Singapore Science Park II 117685 Singapore

We demonstrate a lensless volumetric imaging microendoscope for deep-brain fluorescence microscopy. It consists of a nanophotonic neural probe for light-sheet illumination and an image fiber bundle for light-field flu... 详细信息

ISBN: (纸本)9781957171258

关键词： Nanophotonics

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Innovative Approaches to the Use of Multifunctional Materials in Building Envelopes 7th

Innovative Approaches to the Use of Multifunctional Material...

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7th International Conference on Construction, Real Estate, Infrastructure, and Project Management, ICCRIP 2023

作者： Kumari, Soni Suresh Kumar, R. Abhishek, Kumar Pathak, B.N. Nijhawan, Ginni Khayoon, Ali Talib Rajalakshmi, B. Kalra, Ravi Department of Mechanical Engineering GLA University UP Mathura India Department of Civil Engineering Institute of Aeronautical Engineering Hyderabad500043 India Gujarat Ahmedabad380026 India Department of Mechanical Engineering IMS Engineering College Ghaziabad India Lovely Professional University Panjab Phagwara India College of Engineering Technology National University of Science and Technology Dhi Qar Iraq Department of Computer Science New Horizon College of Engineering Bangalore India Lloyd Institute of Engineering and Technology Knowledge Park II Uttar Pradesh Greater Noida201306 India

ISBN: (纸本)9789819649013

Multifunctional materials have become a hot topic in building envelope design due to their ability to simultaneously perform several functions such as structural support, insulation, energy harvesting, and storage. This paper reviews recent developments in the use of multifunctional materials in building envelopes, including their composition, properties, and potential applications. The paper also examines innovative approaches to integrating these materials into building envelopes to enhance their performance and sustainability. The potential benefits and challenges of using multifunctional materials in building envelopes are discussed, along with future directions for research in this field. However, there are also challenges associated with the use of these materials, including their high cost, complexity of integration, and potential durability issues, which require further research and development. Overall, this review provides insights into the current state and potential of multifunctional materials in building envelopes, highlighting opportunities for future research and application. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Thermal comfort

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Deploying Unsupervised Learning for Daily Activity Windows Analysis in Cancer Patients 2

Deploying Unsupervised Learning for Daily Activity Windows A...

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2nd Edition IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2023

作者： Tramontano, Adriano Feoli, Chiara Tamburis, Oscar Conson, Manuel Salzano, Francesco Magliulo, Mario Institute of Biostructures and Bioimaging National Research Council of Italy Naples Italy University of Naples 'Federico II' Department of Advanced Biomedical Sciences Naples Italy University of Cagliari Department of Mathematics and Computer Science Cagliari Italy University of Molise Stake Lab Campobasso Italy Hassisto S.r.l. Naples Italy

ISBN: (纸本)9798350300802

Radiotherapy (RT) could have significant impact on quality of life (QoL) in cancer patient. The aim of the study is to evaluate Radiation Treatment impact on daily activities in cancer patient using wearable devices technologies to monitor patients in their daily activities. Objective data were collected over RT time and a dedicated in-house algorithm was designed to recognize and analyze several repeated activity windows (RAWs) during days based on the intensity of the subject's activity (steps walked) and the duration of such activity (minutes). Subjective patient reported outcomes (PROs) were collected in the form of an answer scoring to a dedicated questionnaire. Unsupervised machine learning approach (K-means) was used to cluster RAWs over RT time for each patient. 9-18 RAWs were counted in a day per patient, by the conducted analysis. Four RAWs clusters were found characterized by a variation in their parameters. The analysis of the clusters' parameters showed that subjects' activity level could be corelated with the variation in the subjective PRO providing indicators of the RT treatment impact on the patients' QoL. QoL variation evaluation could be improved by blending the objective data collected via a continuous patient monitoring with the powerful information coming from the PRO. © 2023 IEEE.

关键词： Health Related Quality of Life Internet of Things Radiotherapy Treatment Unsupervised Leaning Wearable devices

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The PredictMed-PoMAS Architecture for Intelligent Patient Monitoring within a Complex Healthcare Ecosystem 2

The PredictMed-PoMAS Architecture for Intelligent Patient Mo...

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2nd AIxIA Workshop on Artificial Intelligence for Healthcare, HC@AIxIA 2023

作者： Costantini, Stefania Bertoncelli, Carlo Bertoncelli, Domenico De Meo, Pasquale Falcone, Rino Persia, Fabio Rossi, Silvia Department of Information Engineering Computer Science and Mathematics -DISIM Università di L’Aquila Italy Côte-d’Azur University of Nice and Etablissement pour Enfants ou Adolescents Polyhandicapés H. Germain Fondation Lenval Nice France Department of Computer Science University of West Florida United States Department of Ancient and Modern Civilizations University of Messina Italy Institute of Cognitive Sciences and Technologies National Research Council Rome Italy Department of Electrical Engineering and Information Technologies DIETI University of Naples "Federico II" Italy

In this paper, we leverage our past work to outline and describe, also using examples, a comprehensive architecture that goes from PMAs, i.e., Patient Monitoring Agents, to a novel notion of Hybrid Society (HS) instantiated in this paper to the healthcare domain, different from previous existing proposals. The HS is meant to encompass PMAs and offices of medical specialists, healthcare companies such as medical centres, and institutions such as hospitals. Our approach is based on approaches to agents and Multi-Agent-Systems (MAS) rooted in computational logic, whose nice formal foundation allows properties of agents and MAS to be proved/enforced through theorem proving, model-checking, run-time verification and other techniques. © 2023 CEUR-WS. All rights reserved.

关键词： Multi agent systems

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PW-MAD: Pixel-wise supervision for generalized face morphing attack detection

arXiv

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arXiv 2021年

作者： Damer, Naser Spiller, Noémie Fang, Meiling Boutros, Fadi Kirchbuchner, Florian Kuijper, Arjan Fraunhofer Institute for Computer Graphics Research IGD Germany Department of Computer Science TU Darmstadt Germany

A face morphing attack image can be verified to multiple identities, making this attack a major vulnerability to processes based on identity verification, such as border checks. Various methods have been proposed to detect face morphing attacks, however, with low generalizability to unexpected post-morphing processes. A major post-morphing process is the print and scan operation performed in many countries when issuing a passport or identity document. In this work, we address this generalization problem by adapting a pixel-wise supervision approach where we train a network to classify each pixel of the image into an attack or not, rather than only having one label for the whole image. Our pixel-wise morphing attack detection (PW-MAD) solution proved to perform more accurately than a set of established baselines. More importantly, PW-MAD shows high generalizability in comparison to related works, when evaluated on unknown re-digitized attacks. Additionally to our PW-MAD approach, we create a new face morphing attack dataset with digital and re-digitized samples, namely the LMA-DRD dataset that is publicly available for research purposes upon request. Copyright © 2021, The Authors. All rights reserved.

关键词： Face recognition

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Next-Generation Computational Models for Enhanced Interpretation of Biospeckle Images Leveraging Deep Learning and Fourier Transform Techniques in Biomedical Applications 7

Next-Generation Computational Models for Enhanced Interpreta...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Gowtham Raj, R. Sreekanth, S. Nijhawan, Ginni Gupta, Shubhi Sharma, Saurabh Mounika, T. New Horizon College of Engineering Deparment of Mechanical Engineering Bangalore India Institute of Aeronautical Engineering Dundigal Hyderabad500043 India Lloyd Law College Plot No. 11 Knowledge Park II Greater Uttar Pradesh Noida201314 India Lovely Professional University Phagwara India Amity University Amity School of Engineering & Technology Greater Noida India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India

ISBN: (纸本)9798350350067

This study looks at advanced computational techniques that enhance the understanding of biospeckle images in biological contexts. Our models use Fourier transform and deep learning techniques to achieve improved specificity, recall, accuracy, and precision. The Fourier transform may provide a more accurate description of frequency domain data as biological processes evolve over time. Deep learning algorithms recognise patterns in biospeckle images, facilitating analysis, memory, and response. The analysis research delineates the several components that influence the outcome and provides evidence of their respective roles. This research shows how helpful the models are and offers suggestions on how to make them better. Non-invasive biomedical testing uses these computer models to illustrate the temporal evolution of biological cells. Our techniques improve the interpretation of biospeckle images, potentially revolutionising non-invasive biomedical imaging. Future researchers may evaluate these models using different datasets and testing conditions. This guarantees their adaptability and power in biological contexts. © 2024 IEEE.

关键词： Frequency domain analysis

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Advancing Wire Arc Additive Manufacturing: A New Era of Precision and Efficiency in Large Metal Component Production

Advancing Wire Arc Additive Manufacturing: A New Era of Prec...

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2024 OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Khan, Irfan Anjimoon, Shaik Asha, V. Singla, Atul Akhil, P. Alsultany, Nahed Mahmood Ahmed Lloyd Institute of Engineering & Technology Knowledge Park II Uttar Pradesh Greater Noida201306 India Institute of Aeronautical Engineering Hyderabad Dundigal India New Horizon College of Engineering Department of Computer Applications Bangalore India Lovely Professional University Phagwara India St. Martin's Engineering College Dept. of Cse Telangana Secunderabad India National University of Science and Technology Collage of Dentist Dhi Qar64001 Iraq

ISBN: (纸本)9798350373783

A comprehensive Wire Arc Additive Manufacturing (WAAM) approach that employs five algorithms to improve massive metal components is described in this research. The adaptive layer thickness control algorithm adjusts layer thickness based on real-time complexity. This ensures additive manufacturing accuracy throughout. Also, the Material Versatility Optimization Algorithm simplifies working with multiple materials, making casting more efficient. The Intelligent Path Planning Algorithm allocates the robotic arm's movement to traverse the shortest distance and uniformly distribute heat during deposition. The MultiMaterial-Materialon Strategy Algorithm improves material amounts, making WAAM more usable for additional materials. The Real-Time Excellent Assurance Algorithm constantly examines and adjusts parameters to ensure excellent production. A complete analysis of research reveals how algorithms are related and how vital they are for accuracy, speed, and flexibility. Testing shows that the recommended technique controls layer thickness, material variety, deposition velocity, accuracy, energy efficiency, and real-time tracking better than typical WAAM methods. Figures 6, 7, and 8 indicate that the proposed method delivers superior results across several criteria. The recommended WAAM approach can create more massive metal components by fundamentally changing how things are done. This research provides a comprehensive additive manufacturing approach to solve numerous large-scale metal production issues. © 2024 IEEE.

关键词： Quality control

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Sophisticated Neural Network Architectures for the Holistic Simulation and Performance Enhancement of Convective Boiling Processes in Industrial Applications

Sophisticated Neural Network Architectures for the Holistic ...

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2024 OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Asha, V. Anjimoon, Shaik Singla, Atul Khan, Irfan Alsharifi, Haider Asaad Farhoud Maranan, Ramya New Horizon College of Engineering Department of Computer Applications Bangalore India Institute of Aeronautical Engineering Hyderabad Dundigal India Lovely Professional University Phagwara India Lloyd Institute of Engineering & Technology Knowledge Park II Uttar Pradesh Greater Noida201306 India National University of Science and Technology Collage of Dentist Dhi Qar64001 Iraq Simats Saveetha School of Engineering Department of Research and Innovation Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350373783

In this research, neural network approaches for industrial convective boiling simulation are fully examined. Five strategies address feature extraction, temporal dynamics, memory retention, data enrichment, and knowledge sharing issues. Recurrent neural networks (RNNs) discover temporal changes, whereas CNNs find spatial patterns. Long ShortTerm Memory (LSTM) Networks assist in recalling things;Generative Adversarial Networks (GANs) add data;and Transfer Learning conveys information using taught models. These methods accurately simulate convective boiling 96.0% of the time. Compared to tried-and-true approaches, it's faster, more extensible, and more resilient. Visualizations indicate how superior the technique is at accuracy, stability distribution, and multi-metric scores. Here's a detailed design for modeling convective boiling, including how space and time change, how to protect memories, add data, and exchange information. Industrial usage is possible since the recommended technique mimics convective cooking processes more complexly and cost-effectively. © 2024 IEEE.

关键词： Generative adversarial networks

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Rethinking development and major research plans of Industrial Internet in China

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Fundamental Research 2024年第1期4卷 3-7页

作者： Chunxiao Jiang Yang Cong Jiming Chen Chenghong Wang Guozheng Wu Ruizhen Zhao Zhiheng Wang Bin Xiao Ting Chen Beijing National Research Center for Information Science and Technology Tsinghua UniversityBeijing 100084China Tsinghua Space Center Tsinghua UniversityBeijing 100084China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China College of Control Science and Engineering Zhejiang UniversityHangzhou 310027China Division III Department of Information SciencesNational Natural Science Foundation of ChinaBeijing 100085China Division II Department of Information SciencesNational Natural Science Foundation of ChinaBeijing 100085China Chongqing Key Laboratory of Image Cognition School of Computer Science and TechnologyChongqing University of Posts and TelecommunicationsChongqing 400065China University of Electronic Science and Technology of China Chengdu 611731China

This paper gives a definition of the Industrial Internet and expounds on the academic connotation of the future Industrial *** this foundation,we outline the development and current status of the Industrial Internet in China and ***,we detail the avant-garde paradigms encompassed within the National Natural science Foundation of China(NSFC)’s“Future Industrial Internet Fundamental Theory and Key Technologies”research plan and its corresponding management *** research initiative endeavors to enhance interdisciplinary collaborations,aiming for a synergistic alignment of industry,academia,research,and practical *** primary focus of the research plan is on the pivotal scientific challenges inherent to the future industrial *** is poised to traverse the“first mile”,encompassing foundational research and pioneering innovations specific to the industrial internet,and seamlessly bridges to the“last mile”,ensuring the effective commercialization of scientific and technological breakthroughs into tangible industrial market *** anticipated contributions from this initiative are projected to solidify both the theoretical and practical scaffolding essential for the cultivation of a globally competitive industrial internet infrastructure in China.

关键词： Industrial Internet Academic connotation Major research plan Scientific problem Policy advice

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Complexity of Deciding Injectivity and Surjectivity of ReLU Neural Networks

arXiv

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arXiv 2024年

作者： Froese, Vincent Grillo, Moritz Skutella, Martin Technische Universität Berlin Faculty IV Institute of Software Engineering and Theoretical Computer Science Algorithmics and Computational Complexity Germany Technische Universität Berlin Faculty II Institute of Mathematics Combinatorial Optimization and Graph Algorithms Germany

Neural networks with ReLU activation play a key role in modern machine learning. In view of safety-critical applications, the verification of trained networks is of great importance and necessitates a thorough understanding of essential properties of the function computed by a ReLU network, including characteristics like injectivity and surjectivity. Recently, Puthawala et al. [JMLR 2022] came up with a characterization for injectivity of a ReLU layer, which implies an exponential-time algorithm. However, the exact computational complexity of deciding injectivity remained open. We answer this question by proving coNP-completeness of deciding injectivity of a ReLU layer. On the positive side, as our main result, we present a parameterized algorithm which yields fixed-parameter tractability of the problem with respect to the input dimension. In addition, we also characterize surjectivity for two-layer ReLU networks with one-dimensional output. Remarkably, the decision problem turns out to be the complement of a basic network verification task. We prove NP-hardness for surjectivity, implying a stronger hardness result than previously known for the network verification problem. Finally, we reveal interesting connections to computational convexity by formulating the surjectivity problem as a zonotope containment problem. © 2024, CC BY.

关键词： Complex networks

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