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arXiv 2025年

作者： Brunner, Daniel Shastri, Bhavin J. Al-Qadasi, Mohammed A. Ballani, H. Barbay, Sylvain Biasi, Stefano Bienstman, Peter Bilodeau, Simon Bogaerts, Wim Böhm, Fabian Brennan, G. Buckley, Sonia Cai, Xinlun Strinati, Marcello Calvanese Canakci, B. Charbonnier, Benoit Chemnitz, Mario Chen, Yitong Cheung, Stanley Chiles, Jeff Choi, Suyeon Christodoulides, Demetrios N. Chrostowski, Lukas Chu, J. Clegg, J.H. Cletheroe, D. Conti, Claudio Dai, Qionghai Di Lauro, Luigi Diamantopoulos, Nikolaos-Panteleimon Dinc, Niyazi Ulas Ewaniuk, Jacob Fan, Shanhui Fang, Lu Franchi, Riccardo Freire, Pedro Gentilini, Silvia Gigan, Sylvain Giorgi, Gian Luca Gkantsidis, C. Gladrow, J. Goi, Elena Goldmann, M. Grabulosa, A. Gu, Min Guo, Xianxin Hejda, Matěj Horst, F. Hsieh, Jih-Liang Hu, Jianqi Hu, Juejun Huang, Chaoran Hurtado, Antonio Jaurigue, Lina Kalinin, K.P. Kamalian-Kopae, Morteza Kelly, D.J. Khajavikhan, Mercedeh Kremer, H. Laydevant, Jeremie Lederman, Joshua C. Lee, Jongheon Lenstra, Daan Li, Gordon H.Y. Li, Mo Li, Yuhang Lin, Xing Lin, Zhongjin Lis, Mieszko Lüdge, Kathy Lugnan, Alessio Lupo, Alessandro Lvovsky, A.I. Manuylovich, Egor Marandi, Alireza Marchesin, Federico Massar, Serge McCaughan, Adam N. McMahon, Peter L. Moralis-Pegios, Miltiadis Morandotti, Roberto Moser, Christophe Moss, David J. Mukherjee, Avilash Nikdast, Mahdi Offrein, B.J. Oguz, Ilker Oripov, Bakhrom O'Shea, G. Ozcan, Aydogan Parmigiani, F. Pasricha, Sudeep Pavanello, Fabio Pavesi, Lorenzo Peserico, Nicola Pickup, L. Pierangeli, Davide Pleros, Nikos Porte, Xavier Primavera, Bryce A. Prucnal, Paul Psaltis, Demetri Puts, Lukas Qiao, Fei Rahmani, B. Raineri, Fabrice Ríos Ocampo, Carlos A. Robertson, Joshua Romeira, Bruno Roques-Carmes, Charles Rotenberg, Nir Rowstron, A. Schoenhardt, Steffen Schwartz, Russell L.T. Shainline, Jeffrey M. Shekhar, Sudip Skalli, A. Sohoni, Mandar M. Sorger, Volker J. Soriano, Miguel C. Spall, James Stabile, Ripalta Stiller, Birgit Sunada, Satoshi Tefas, Anastasios Tossoun, Bassem Tsakyridis, Apostolos Turitsyn, Sergei K. Van der Sande, G Université Marie et Louis Pasteur CNRS UMR 6174 Institut FEMTO-ST Besançon25000 France Centre for Nanophotonics Department of Physics Engineering Physics & Astronomy Queen's University Canada Department of Electrical and Computer Engineering The University of British Columbia Vancouver Canada Microsoft Research Cambridge United Kingdom Université Paris-Saclay CNRS Centre de Nanosciences et de Nanotechnologies France Nanoscience Laboratory Department of Physics University of Trento Italy Photonics Research Group Department of Information Technology Ghent University imec Belgium Princeton University NJ United States Hewlett Packard Labs Hewlett Packard Enterprise Böblingen Germany National Institute of Standards and Technology BoulderCO United States State Key Laboratory of Optoelectronic Materials and Technologies School of Electronics and Information Technology Sun Yat-sen University China Enrico Fermi Research Center Rome Italy Université Grenoble-Alpes CEA Leti Grenoble France Leibniz-Institute of Photonic Technology Jena Germany Institute of Applied Optics and Biophysics Jena Germany Department of Automation Tsinghua University Beijing China Department of Electrical and Computer Engineering North Carolina State University NC United States Department of Electrical Engineering Stanford University CA United States University of Southern California Los AngelesCA United States Department of Physics Sapienza University Rome Italy Institute for Complex Systems National Research Council Rome Italy Varennes Canada NTT Device Technology Labs NTT Corporation Kanagawa Atsugi Japan Institute of Electrical and Microengineering School of Engineering École Polytechnique Fédérale de Lausanne Switzerland Edward L. Ginzton Laboratory Stanford University StanfordCA United States Department of Electronic Engineering Tsinghua University China Beijing National Research Center for Information Science and Technology Tsinghua University China Aston Univ

Neuromorphic photonics are processors inspired by the human brain and enabled by light (photons) instead of traditional electronics. Neuromorphic photonics and its associated concepts are experiencing a significant resurgence, building on foundational research from the 1980s and 1990s. This renewed momentum is driven by breakthroughs in photonic integration, nonlinear optics, and advanced materials, alongside the growing necessity of neuro-inspired computing in numerous applications of economic and societal relevance. The increasing demand for energy-efficient artificial intelligence (AI) solutions underscores the need for innovation and a cohesive vision to address key challenges, including scalability, energy efficiency, precision, and standardized performance benchmarks. Together, these efforts present an opportunity to establish a unique photonic advantage with practical, real-world applications. This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementation philosophies reported in the field. It emphasizes the critical role of cross-disciplinary collaboration in this rapidly evolving field. The roadmap introduces various approaches to embedding the high-complexity transformations central to neuromorphic computing, focusing on frequency, delay, and spectral embeddings. This is followed by a discussion of architectures of photonic neural networks (PNNs) and an in-depth analysis of methods for implementing these architectures in photonic hardware. Dedicated sections delve into integrated photonic hardware, the realization of photonic weights and memories, and the optimization of training processes for photonic neuromorphic architectures. The roadmap concludes by exploring numerous potential applications, highlighting the challenges and advances necessary to transition neuromorphic photonic computing from a primarily academic pursuit to a technolog

关键词： Philosophical aspects

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Structure-Preserving Operator Learning: Modeling the Collision Operator of Kinetic Equations

arXiv

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arXiv 2024年

作者： Lee, Jae Yong Schotthöfer, Steffen Xiao, Tianbai Krumscheid, Sebastian Frank, Martin Center for Artificial Intelligence and Natural Sciences Korea Institute for Advanced Study Seoul Korea Republic of Oak Ridge National Laboratory Computer Science and Mathematics Division Oak RidgeTN United States State Key Laboratory of High Temperature Gas Dynamics Centre for Interdisciplinary Research in Fluids Institute of Mechanics Chinese Academy of Sciences Beijing China School of Engineering Science University of Chinese Academy of Sciences Beijing China Karlsruhe Institute of Technology Scientific Computing Center Karlsruhe76131 Germany

This work explores the application of deep operator learning principles to a problem in statistical physics. Specifically, we consider the linear kinetic equation, consisting of a differential advection operator and an integral collision operator, which is a powerful yet expensive mathematical model for interacting particle systems with ample applications, e.g., in radiation transport. We investigate the capabilities of the Deep Operator network (DeepONet) approach to modelling the high dimensional collision operator of the linear kinetic equation. This integral operator has crucial analytical structures that a surrogate model, e.g., a DeepONet, needs to preserve to enable meaningful physical simulation. We propose several DeepONet modifications to encapsulate essential structural properties of this integral operator in a DeepONet model. To be precise, we adapt the architecture of the trunk-net so the DeepONet has the same collision invariants as the theoretical kinetic collision operator, thus preserving conserved quantities, e.g., mass, of the modeled many-particle system. Further, we propose an entropy-inspired data-sampling method tailored to train the modified DeepONet surrogates without requiring an excessive expensive simulation-based data generation. © 2024, CC BY-NC-SA.

关键词： Kinetic energy

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eFAirWrite: Bringing energy efficient text entry to next generation smart devices

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Expert Systems with Applications 2025年 289卷

作者： Muhammad Mohsin Ghaffar Ahmad Abdullah Junaid Younas Vladimir Rybalkin Jonas Ney Paul Lukowicz Norbert Wehn Microelectronic Systems Design Research Group University of Kaiserslautern-Landau Kaiserslautern 67663 Germany School of Electrical Engineering & Computer Science National University of Sciences & Technology Islamabad 44000 Pakistan German Research Centre for Artificial Intelligence Kaiserslautern 67663 Germany

Text entry tasks for emerging wireless Augmented Reality (AR) and Virtual Reality (VR) devices can be realized in many ways, one of the most promising methods is based on an Inertial Measurement Unit (IMU) sensor, which resembles a human writing style and is called air-writing. An existing air-writing Deep Neural Network (DNN) based algorithm called FAirWrite achieves state-of-the-art accuracy. However, this algorithm is optimized only for accuracy without considering the implementation constraints. State-of-the-art implementation executes the algorithm in a cloud, which is associated with large communication latency; privacy issues with respect to data transfer; and a need for reliable internet connection. A solution that tackles all three challenges is executing the algorithm locally at the edge in the closest proximity to the sensor. However, inference at the edge is challenging due to limited memory and computing resources, which can impact accuracy and increase latency. Additionally, battery-powered edge devices must adhere to strict power and energy consumption limits. All these constraints collectively restrict the model size and computational complexity that can be deployed near the sensor. In this work, we explore various optimizations required to enable state-of-the-art FAirWrite algorithm for a real-world deployment scenario, i.e. executing on an edge device. We perform a multi-layer design-space exploration considering multiple levels of design hierarchy spanning from optimizations applied on algorithmic level down to hardware level, considering various deployment run-times and edge platforms including embedded micro-controller, embedded Central Processing Unit (CPU), embedded Graphics Processing Unit (GPU), Neural Processing Unit (NPU), and Field-Programmable Gate Array (FPGA). The complexity reduction optimizations result in a 37 × smaller eFAirWrite model without any accuracy degradation. We propose and implement a custom hardware architecture of the

关键词： Human computer interaction Air-writing Convolution neural network inference Edge computing Energy efficient acceleration

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Technologies for Ocean Sensing project developments in imaging and sensing

Technologies for Ocean Sensing project developments in imagi...

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OCEANS

作者： Matthew Mowlem Fillipa Carvalho Rudolf Hanz Ehsan Abdi Camile Catalano Katherine Hartle Mougiou Rana Abualhaija Susan Evans Dan Hayes Ahmed Alrefaey Reuben Forrester Jean-Olivier Irisson Martin Arundel Sarah Giering Kevin Köser Nathan Briggs Electra Gizeli Patricia Lopez-Garcia Wahida Bhuiyan Peter Glynne-Jones Jake Ludgate Jonathan Butement Lionel Guidi Miguel Massot Campos Christopher L. Cardwell Weili Guo Jon McQuillan Marina Montresor Efstathios Papadimitriou Allison Schaap C. Mark Moore Matthew Patey Nina Schuback Hywel Morgan Marc Picheral Blair Thornton Mojtaba Masoudi Fiona Regan Martha Valiadi Caroline Murphy Julie Robidart John Walk Andrew Morris Fabrizio Siracusa Xiangyu Weng David Nakath Dan Spenser Euan Wilson Kevin Oxborough National Oceanography Centre Ocean Technology and Engineering Group Southampon UK National Oceanography Centre Ocean Biogeochemistry and Geoscience Southampon UK Cyprus Subsea Consulting and Services Nicosia Cyprus Laboratoire d'Oceanographie de Villefranche France Foundation for Research and Technology Hellas Institute for Molecular Biology and Biotechnology Heraklion Greece Electronics and Computer Science University of Southampton Southampton UK In Situ and Remote Intelligent Sensing University of Southampton Southampton UK School of Biotechnology Dublin City University Dublin UK Section Integrated Marine Ecology Stazione Zoologica Anton Dohrn Napoli Italy School of Ocean and Earth Science University of Southampton Southampton UK Chelsea Technologies Group London UK School of Chemical Sciences Dublin City University Dublin UK Head of Research Minderoo Foundation Perth Western Australia Australia Helmholtz Centre for Ocean Research Oceanic Machine Vision Group GEOMAR Kiel Germany

The TechOceanS project is developing new remote ocean sensing technology supporting wider ocean measurement and a drive to net zero. The project will deliver 5 new sensor classes for biogeochemistry, biology and ecosystems addressing 10 of 19 EOVs, 31 of 73 subvariables, 6 of 9 MSFD targets together with microplastics and a range of biotoxins and contaminants. It will also develop a new image processing workflow for extracting EOVs (9) and MSFD (6) and litter measurements from images. These innovations concentrate on key capability gaps in ocean observing from non-ship systems with a focus on low-cost per measurement through minimised instrument and deployment costs. This paper gives a brief overview of the technologies, and were possible, because of progress or protection of intellectual property, details of our approaches and early results.

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Approximate reconstructability of quantum states and noisy quantum secret sharing schemes

arXiv

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arXiv 2023年

作者： Ouyang, Yingkai Goswami, Kaumudibikash Romero, Jacquiline Sanders, Barry C. Hsieh, Min-Hsiu Tomamichel, Marco Department of Physics & Astronomy University of Sheffield SheffieldS3 7RH United Kingdom Centre for Quantum Technologies National University of Singapore Singapore School of Mathematics and Physics University of Queensland BrisbaneQLD4072 Australia Raman Research Institute Sadashivanagar Karnataka Bengaluru560080 India Institute for Quantum Science and Technology University of Calgary ABT2N 1N4 Canada Research Institute Taipei Taiwan Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

We introduce and analyse approximate quantum secret sharing in a formal cryptographic setting, wherein a dealer encodes and distributes a quantum secret to players such that authorized structures (sets of subsets of players) can approximately reconstruct the quantum secret and omnipotent adversarial agents controlling non-authorized subsets of players are approximately denied the quantum secret. In particular, viewing the map encoding the quantum secret to shares for players in an authorized structure as a quantum channel, we show that approximate reconstructability of the quantum secret by these players is possible if and only if the information leakage, given in terms of a certain entanglement-assisted capacity of the complementary quantum channel to the players outside the structure and the environment, is small. Copyright © 2023, The Authors. All rights reserved.

关键词： Quantum entanglement

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Modified Flower Pollination Algorithm for ICMPv6-Based DDoS Attacks Anomaly Detection

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Procedia computer Science 2023年 220卷 776-781页

作者： Adnan Hasan Bdair AIghuraibawi Selvakumar Manickam Rosni Abdullah Zaid Abdi Alkareem Alyasseri Hussam Mohammed Jasim Nor Samsiah Sani National Advanced IPv6 Centre (NAv6) Universiti Sains Malaysia Penang 11800 Malaysia Baghdad College of Economic Sciences University Baghdad Iraq School of Computer Sciences Universiti Sains Malays Penang 11800 Malaysia Information Technology Research and Development Center University of Kufa Najaf Iraq College of Engineering University of Warith Al-Anbiyaa Karbala Iraq Business Administration College of Administration and Financial Sciences Imam Ja'afar Al-Sadiq University Baghdad 10001 Iraq CAIT Faculty of Information Science &Technology Universiti Kebangsaan Malaysia Bangi 43600 Selangor Malaysia

Internet Protocol version 6 (IPv6) is the latest version of IP that goal to host 3.4*10 38 unique IP addresses of devices in the network. IPv6 needed a number of protocols such as the Address Auto-configuration scheme and Internet Control Message Protocol (ICMPv6), IPv6 is vulnerable to numerous attacks such as Denial of Service (DoS) and Distributed Denial of Service (DDoS), DDoS is one of the most dangerous attacks carried out through ICMPv6 messages that impose security and pecuniary implications. Therefore, an Intrusion Detection System (IDS) is a monitoring system of the security of a network that detects suspicious activities and deals with a massive amount of data comprised of repetitive and inappropriate features which affect the detection rate. A feature selection technique helps to reduce the computation time and complexity by selecting the optimum subset of features. This paper proposes a method for detecting ICMPv6 DDoS attacks using a modified Flower Pollination Algorithm (MFPA). The main purpose of the proposed method, first MFPA is to select the most relevant features from the ICMPv6 dataset to the detect ICMPv6 DDoS attacks. Second, an enhanced detecting DDoS flooding attacks model based on a multi-objective FPA has proposed. The results show that the first proposed method (MFPA) achieved the best accuracy equal to 97.96% with 10 features and the second proposed method Multi-Objective FPA achieved the best accuracy 97.01% with 5 features.

关键词： IPv6 ICMPv6 DDoS feature selection flower pollination algorithm anomaly detection

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Nanocomposites of cellulose-modified cerium oxide nanoparticles and their potential biomedical applications

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Case Studies in Chemical and Environmental engineering 2024年 10卷

作者： Putri, Gusliani Eka Arifani, Nurul Wendari, Tio Putra Syafri, Edi Ilyas, R.A. Labanni, Arniati Arief, Syukri Department Biomedical Science Universitas Syedza Saintika Padang 25132 Indonesia Department of Chemistry Universitas Andalas Padang 25163 Indonesia Departement of Agricultural and Computer Engineering Politeknik Pertanian Negeri Payakumbuh Payakumbuh 25271 Indonesia Faculty of Chemical and Energy Engineering Universiti Teknologi Malaysia UTM Skudai Johor 81310 Malaysia Centre for Advanced Composite Materials (CACM) Universiti Teknologi Malaysia (UTM) Johor Johor Bahru 81310 Malaysia Research Center for Environmental and Clean Technology National Research and Innovation Agency of Republic Indonesia (BRIN) KST Samaun Samadikun Bandung 40135 Indonesia

Cellulose is a natural biopolymer extensively utilized in biomedical applications. This study aims to develop a novel cellulose nanofiber (CNF) from areca nut shell, reinforced with cerium oxide nanoparticles (CeO₂NPs). XRD analysis confirms successful synthesis of crystalline CNF and CeO₂NPs with the cubic structure, strengthened by Le-Bail refinement. Following FESEM and EDX analysis, spherical CeO₂NPs nanoparticles with sizes ranging between 18 and 32 nm were formed and finely distributed on the CNF surface. The prepared CNF/CeO₂NPs samples exhibited high antibacterial activity against *** and ***. These findings highlight an innovative approach of materials with environmentally friendly for advanced biomedical applications. © 2024 The Authors

关键词： Antibacterial activity Areca nut shell Cellulose nanofiber Cerium oxide nanoparticle

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Highlighting Nerves in Images for Ultrasound Guided Regional Anesthesia 1

Highlighting Nerves in Images for Ultrasound Guided Regional...

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1st IEEE Bangalore Humanitarian technology Conference, B-HTC 2020

作者： Akkasaligar, Prema T. Koolagudi, Shashidhar G. Biradar, Sunanda Hotagi, Poornima Badiger, Sharan VijayapurKaranataka586103 India Department of Computer Science and Engineering National Institute of Technology Karnataka Surathkal India Department of Medicine BLDEDU's Sri B.M.Patil Medical College and Research Centre VijayapurKarnataka India

ISBN: (纸本)9781728187945

Surgery is a treatment given to the patient, when patient is having injuries in the body parts. While doing the surgery the patient will undergo pain and discomfort, to reduce the pain of patient anesthesia is given before surgery. There are many types of anesthesia procedure called local, regional and general. Local anesthesia is given to specific part of the body;general anesthesia is where the patient is completely senseless. Regional anesthesia is procedure, where anesthetist does injection near a class of nerves to numb the area of human body that requires surgery. There is difference in structure of every person. This makes doctor hard to detect nerve in internal organ. Ultrasound image provide information about structure of body which can be used for regional anesthesia. Ultrasonography is the safest method compared to the other imaging techniques like Xray, CT, and MRI;because it is not based on ionizing radiation. In this paper, we simplify the issue of detection of nerve in ultrasound image. For input, image such as ultrasound images of brachial plexus are used. Initially in preprocessing, filtering technique is used to remove noise from ultrasound image and then segmentation is carried out using active contour model. Performance of segmentation is evaluated using dice coefficient and Jaccard coefficient. The nerve location in ultrasound image is detected to help the doctors in giving regional anesthesia. © 2020 IEEE.

关键词： Median filters

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Control Theory Illustrates the Energy Efficiency in the Dynamic Reconfiguration of Functional Connectivity

arXiv

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arXiv 2022年

作者： Deng, Shikuang Li, Jingwei Yeo, B.T. Thomas Gu, Shi School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Research Center Jülich Jülich Germany Institute for Systems Neuroscience Medical Faculty Heinrich-Heine University Düsseldorf Düsseldorf Germany Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Centre for Sleep & Cognition Centre for Translational Magnetic Resonance Research Yong Loo Lin School of Medicine Singapore N.1 Institute for Health Institute for Digital Medicine National University of Singapore Singapore National University of Singapore Singapore Singapore Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital CharlestownMA02129 United States

The brain’s functional connectivity fluctuates over time instead of remaining steady in a stationary mode even during the resting state. This fluctuation establishes the dynamical functional connectivity that transitions in a non-random order between multiple modes. Yet it remains unexplored how the transition facilitates the entire brain network as a dynamical system and what utility this mechanism for dynamic reconfiguration can bring over the widely used graph theoretical measurements. To address these questions, we propose to conduct an energetic analysis of functional brain networks using resting-state fMRI and behavioral measurements from the Human Connectome Project. Through comparing the state transition energy under distinct adjacent matrices, we justify that dynamic functional connectivity leads to 60% less energy cost to support the resting state dynamics than static connectivity when driving the transition through default mode network. Moreover, we demonstrate that combining graph theoretical measurements and our energy-based control measurements as the feature vector can provide complementary prediction power for the behavioral scores. Our approach integrates statistical inference and dynamical system inspection towards understanding brain networks. Copyright © 2022, The Authors. All rights reserved.

关键词： Dynamical systems

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Spectroscopic detection of pigments in tissues: correlation with tissue aging and cancer development

Spectroscopic detection of pigments in tissues: correlation ...

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2022 International Conference Laser Optics, ICLO 2022

作者： Oliveira, L.M. Goncalves, T.M. Botelho, A.R. Martins, I.S. Silva, H.F. Carneiro, I. Carvalho, S. Henrique, R. Tuchin, V.V. Porto Portugal Center of Innovation in Engineering and Industrial Technology Isep Porto Portugal Department of Electrical and Computer Engineering Porto University-School of Engineering Porto Portugal Department of Pathology and Cancer Biology and Epigenetics Group Portuguese Oncology Institute of Porto Porto Portugal Porto Portugal Viana do Castelo Portugal Dept. of Pathol. and Molecular Immunology Porto University-Institute of Biomedical Sciences Abel Salazar Porto Portugal Science Medical Center Saratov State University Saratov Russia Laboratory of Laser Molecular Imaging and Machine Learning National Research Tomsk State University Tomsk Russia Laboratory of Laser Diagnostics of Technical and Living Systems Institute of Precision Mechanics and Control Frc-Saratov Scientific Centre-of the Russian Academy of Sciences Saratov Russia

ISBN: (纸本)9781665466646

The direct calculation of the absorption coefficient spectra of various tissues from spectral measurements allowed to retrieve the contents of melanin and lipofuscin. In the rabbit brain cortex, 1.8 times higher melanin content is explained by the neuron degeneration process. Similar melanin and lipofuscin contents were found in the rabbit pancreas as a result of the tissue aging process. The conversion of 83 % of the melanin in the human normal kidney into lipofuscin in the cancer kidney indicates that lipofuscin can be considered a kidney cancer marker in humans. © 2022 IEEE.

关键词： Tissue

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