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International Conference on Information technology (INCIT)

作者： Sakorn Mekruksavanich Ponnipa Jantawong Anuchit Jitpattanakul Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Department of Mathematics Faculty of Applied Science King Mongkut's University of Technology North Bangkok Bangkok Thailand

Applying smartphones and smartwatches for Human ActivitiesRecognition (HAR) is beneficial for analyzing the participant's dailybehavior and identifying mishaps, such as fall detection, enabling early healthcare monitoring and fall detection. Numerous HAR studies have investigated different recognition models based on sensor data. Nonetheless, this research mainly focused on basic motions such as sitting, standing and walking. In actual settings, human actions are often accomplished in complex ways. This research will examine the recognition of complicated activities using CNN and LSTM networks as deep learning classifiers. Furthermore, this study presented hybrid CNN for enhancing the identification of complicated activities. We evaluated these deep learning classifiers using WISDM-HARB, a publically available benchmark HAR. This dataset used accelerometer and gyroscope data from smartphones and smartwatches to collect sensor data of complicated activities. The experiment demonstrates that all deep learning classifiers recognize basic actions more accurately than complicated ones. Also, it was observed that the hybrid CNN classifier presented had the most fantastic accuracy with 96.25%. According to the research, these classifiers are effective at recognizing basic activities, but their performance decreases as the sophistication of the actions increases. Nonetheless, hybrid CNN models are competent for handling complicated tasks.

关键词： Deep learning Legged locomotion Medical services Data models Gyroscopes Fall detection Task analysis

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Fermionic Quantum Turbulence: Pushing the Limits of High-Performance Computing

arXiv

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arXiv 2023年

作者： Wlazlowski, Gabriel Forbes, Michael McNeil Sarkar, Saptarshi Rajan Marek, Andreas Szpindler, Maciej Faculty of Physics Warsaw University of Technology Ulica Koszykowa 75 Warsaw00-662 Poland Department of Physics University of Washington SeattleWA98195–1560 United States Department of Physics and Astronomy Washington State University PullmanWA99164 United States Garching near Munich85741 Germany Academic Computer Centre CYFRONET University of Science and Technology in Cracow Nawojki 11 Cracow30-950 Poland

Ultracold atoms provide a platform for analog quantum computer capable of simulating the quantum turbulence that underlies puzzling phenomena like pulsar glitches in rapidly spinning neutron stars. Unlike other platforms like liquid helium, ultracold atoms have a viable theoretical framework for dynamics, but simulations push the edge of current classical computers. We present the largest simulations of fermionic quantum turbulence to date and explain the computing technology needed, especially improvements in the Eigenvalue soLvers for Petaflop Applications (ELPA) library that enable us to diagonalize matrices of record size (millions by millions). We quantify how dissipation and thermalization proceed in fermionic quantum turbulence by using the internal structure of vortices as a new probe of the local effective temperature. All simulation data and source codes are made available to facilitate rapid scientific progress in the field of ultracold Fermi gases. © 2023, CC BY.

关键词： Eigenvalues and eigenfunctions

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Calcination Temperature-Dependent Structural and Photoluminescence Properties of Hydroxyapatite Derived from Labeo Rohita Fish Scales

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Journal of The Institution of Engineers (India): Series D 2020年第2期101卷 223-232页

作者： Sinha, Arijit Pal, Anindya Santra, A. Murmu, S. Ghorai, U.K. Chowdhury, Amit Roy Banerjee, D. Dr. M.N. Dastur School of Materials Science Engineering Indian Institute of Engineering Science and Technology Botanic Garden Shibpur Howrah711103 India Ramakrishna Mission Vidyamandira Department of Industrial Chemistry & Applied Chemistry Swami Vivekananada Research Centre Belur Math Howrah711202 India Aerospace Engineering and Applied Mechanics Indian Institute of Engineering Science and Technology Botanic Garden Shibpur Howrah711103 India Faculty of Engineering and Computer Science Teerthanker Mahaveer University MoradabadUP244001 India

The nanocrystalline hydroxyapatite was synthesized from Labeo Rohita fish scales by calcination of raw scales at temperatures ranges from 400 to 1000 °C. The synthesized powders were characterized using, X-ray diffraction (XRD), thermogravimetric/differential thermal analyzer (TG–DTA), Fourier transform infrared spectroscopy, scanning and high-resolution transmission electron microscope and energy-dispersive X-ray analysis, respectively. Crystallite size, crystallinity and lattice parameters of HAp were evaluated from XRD, and it is shown that the average crystallite sizes were significantly enhanced with the calcination temperature attending its maximum value at ~ 40 nm. TG–DTA analysis predicts the thermal stability of the samples, and it has been observed that the thermal stability increases with the calcination temperature. Moreover, a detailed photoluminescence study of the as-synthesized samples has been carried out for the first time and an appropriate excitation energy gives rise to several distinct peaks in the emission spectra which has not been reported previously. © 2020, The Institution of Engineers (India).

关键词： Optical properties

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Secondary spin current driven efficient THz spintronic emitters

arXiv

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arXiv 2022年

作者： Agarwal, Piyush Yang, Yingshu Medwal, Rohit Asada, Hironori Fukuma, Yasuhiro Battiato, Marco Singh, Ranjan Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link Singapore637371 Singapore Center for Disruptive Photonic Technologies The Photonics Institute Nanyang Technological University Singapore639798 Singapore Department of Physics Indian Institute of Technology Uttar Pradesh Kanpur208016 India Department of Electronic Devices and Engineering Graduate School of Science and Engineering Yamaguchi University Ube755-8611 Japan Department of Physics and Information Technology Faculty of Computer Science and System Engineering Kyushu Institute of Technology Iizuka820-8502 Japan

Femtosecond laser-induced photoexcitation of ferromagnet (FM)/heavy metal (HM) heterostructures have attracted attention by emitting broadband terahertz frequencies. The phenomenon relies on the formation of ultrafast spin current, which is largely attributed to the direct photoexcitation of the FM layer. However, we reveal that during the process, the FM layer also experiences a secondary excitation led by the hot electrons from the HM layer that travel across the FM/HM interface and transfer additional energy in the FM. Thus, the generated secondary spins enhance the total spin current formation and lead to amplified spintronic terahertz emission. The results also emphasize the significance of the secondary spin current, which even exceeds the primary spin currents when FM/HM heterostructures with thicker HM are used. An analytical model is developed to provide deeper insights into the microscopic processes within the individual layers, underlining the generalized ultrafast superdiffusive spin-transport mechanism. Copyright © 2022, The Authors. All rights reserved.

关键词： Hot electrons

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Assessment of Gamma and Neutron Dose of Optimizing the Radiation Protection in TRIGA 2000 BATAN Bandung. 6

Assessment of Gamma and Neutron Dose of Optimizing the Radia...

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6th International Conference on Advances in Nuclear science and Engineering, ICANSE 2018

作者： Oméga, Rakotovao Lovanantenaina Permana, Sidik Oetami, Rini Heroe Rasito Master Program of Physics Department Faculty of Mathematics and Natural Science Bandung Institute of Technology Jalan Ganesha 10 Bandung40132 Indonesia Nuclear Physics Laboratory Physics Department Faculty of Mathematics and Natural Science Bandung Institute of Technology Jalan Ganesha 10 Bandung40132 Indonesia Center for Science and Applied Nuclear Technology National Nuclear Energy Agency Jl. Tamansari 71 Bandung Indonesia

The TRIGA 2000 reactor is a nuclear installation which is operated at 1000 kW. Gamma and neutron radiation exposure will contribute to occupational doses that will be received by operators and other radiation workers. To maintain the safety of radiation workers, assessment of gamma and neutron radiation is needed in the TRIGA 2000 reactor. survey in the hall reactor using the RTD 30 and RadEye NL detectors. In addition to the direct measurement, calculations are also carried out with simulation data dose using Monte Carlo MCNPX for the calculation and followed by PHITS to get the graphical dose distribution of gamma and neutron. The study will focus on the assessment of the diffusion Gamma and neutron doses by doing the measurement and simulation data collect for the aim of the optimization of the Radiation protection policy in the reactor TRIGA 2000 Bandung. The result of the measurement is shown with graph in different power taken during the measurement and the simulation is the graphical distribution dose of gamma and neutron using PHITS code. A preventive dose reduction technique, worker and publics protection elaborate to optimise the Radiation protection program. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Monte Carlo methods

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Music genre influence and artist similarity based on data analysis

Music genre influence and artist similarity based on data an...

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2021 International Conference on applied Mathematics, Modelling and Intelligent Computing, CAMMIC 2021

作者： Xiao, Yuhui He, Zhilin Liao, Huming Huang, Kangjian Zhao, Jianping Wu, Yuchen Nuclear Engineering and Technology Chengdu University of Technology ChengDu SiChuan Province610059 China Mathematics and Applied Mathematics Chengdu University of Technology ChengDu SiChuan Province610059 China Department of Computer Science and Technology Chengdu University of Technology ChengDu SiChuan Province610059 China Southwest Petroleum University ChengDu SiChuan Province610599 China Physics Southwest University ChongQing City00715 China

Based on related data and cluster analysis, this paper creates a mathematical model of similarity measurement based on the data set, and finally obtains the influence of different music genres on their followers and the similarity of artists of different musical genres. Here, since the study is about the similarity of music, it is divided into 2 categories according to the provided music characteristics and related indicators of music type. The data is standardized and normalized. Because there is no clear indicator to measure the similarity of music, we use spss to perform K-means clustering analysis. Here, since the similarity of music is studied, it is built on the music characteristics and music provided. Types of related indicators divide it into two categories for analysis. In order to determine the reliability of the model, this article uses meaningful learning to train 70% of the previous data, 30% to test, and finally establishes a complete mathematical model. © Published under licence by IOP Publishing Ltd.

关键词： Cluster analysis

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Edge Intelligent in IoT: Algorithms and Applications

Edge Intelligent in IoT: Algorithms and Applications

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International Conference on science technology Engineering and Management (ICONSTEM)

作者： Kode Jaya Prakash S. Gobimohan J. Femila Mercy Rani P. S. Latha Mageshwari Iffath Fawad G. Suganya Department of Mechanical Engineering VNR Vignana Jyothi Institute of Engineering & Technology Hyderabad Telangana College of Engineering And Technology University of Technology and Applied Sciences Nizwa Sultanate of Oman Dindigul Tamil Nadu India Department of Mathematics PSNA College of Engineering and Technology (Autonomous) Dindigul Tamil Nadu India Department of Physics (S&H) R.M.K. Engineering College Kavaraipettai Tamil Nadu India Department of Electronics and Telecommunication Engineering Dayananda Sagar College of Engineering Bengaluru Karnataka Department of Computer Science Dr. SNS Rajalakshmi College of Arts and Science Coimbatore Tamil Nadu India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

There are a lot more IoT gadgets and data being made because IoT apps are becoming more common in our daily lives. IoT devices don't have a lot of resources, which makes it harder to handle and store IoT data. Traditional cloud computing helps with some problems caused by the Internet of Things' (IoT) limited resources, but it also causes new problems, like delay in IoT apps that need to work right away. It makes sense that edge-cloud computer technology has changed recently. It is possible to store and handle data at the edge of the network with this technology. Edge computing architectures for the internet of things (ECAsIoT) are grouped in this piece by where the data is stored, the services that help with orchestration, security, and big data. The research looks into and compares each architecture in depth using a number of factors. We look at ECAs-IoT against two other IoT stacked models to see what their pros, cons, chances, and risks are. The research lists the main problems with present ECAs-IoT and suggests ways to fix them. The Internet of Things (IoT) and its effects on edge computing are also talked about in this poll. The research ends with four possible uses for ECAs-IoT in IoT.

关键词： Computational modeling computer architecture Logic gates Data processing Mathematics Delays Internet of Things

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SmartCHANGE: AI-based long-term health risk evaluation for driving behaviour change strategies in children and youth 3

SmartCHANGE: AI-based long-term health risk evaluation for d...

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3rd International Conference on applied Mathematics and computer science, ICAMCS 2023

作者： Rescic, Nina Alberts, Janna Altenburg, Teatske M. Chinapaw, Mai J. M. De Nigro, Antonio Fenoglio, Dario Gjoreski, Martin Gradisek, Anton Jurak, Gregor Kiourtis, Athanasios Kyriazis, Dimosthenis Langheinrich, Marc Mancuso, Elena Mavrogiorgou, Argyro Pechenizkiy, Mykola Pratola, Roberto Ribeiro, Jose Soric, Maroje Taj, Fawad Tammelin, Tuija H. Vastenburg, Martijn Vilanova, Anna Vrijkotte, Tanja G. M. Lustrek, Mitja Jožef Stefan Institute Department of Intelligent Systems Ljubljana Slovenia ConnectedCare Research & Development Nijmegen Netherlands Vrije Universiteit Amsterdam Amsterdam Public Health Research Institute Department of Public and Occupational Health Amsterdam Umc Amsterdam Netherlands Informatica S.p.A. Engineering Ingegneria Rome Italy Università della Svizzera Italiana Faculty of Informatics Lugano Switzerland University of Ljubljana Faculty of Sports Ljubljana Slovenia University of Piraeus Department of Digital Systems Piraeus Greece Eindhoven University of Technology Department of Mathematics and Computer Science Eindhoven Netherlands University of Porto Faculty of Sport Porto Portugal Jamk University of Applied Sciences Likes School of Health and Social Studies Jyväskylä Finland

ISBN: (纸本)9798350324266

The SmartCHANGE project, a Horizon-Europe Research & Innovation project that has been ongoing since May 2023 and is scheduled to conclude in April 2027, aims to develop AI-driven decision-support tools to identify and reduce the long-term risk of non-communicable chronic diseases (NCDs) in children and youth. NCDs have become a significant public health burden in developed countries, with common risk factors including obesity, low physical fitness, and unhealthy lifestyle habits. Childhood and adolescence are critical periods for establishing healthy habits, and early intervention can prevent or delay the onset of NCDs later in life. However, current tools for identifying high-risk individuals mainly focus on adults, leading to missed opportunities for early detection. The SmartCHANGE project aims to address this gap by creating trustworthy AI tools that accurately assess risk factors in children and youth and promote optimised strategies for risk reduction. The paper outlines the plan for the project from the project's proposed methodologies, including dataset utilisation, data cleaning, risk prediction models (basic and complex), and the implementation of federated learning. Additionally, it discusses user experience aspects such as participatory design, suggested applications, and the evaluation of project outcomes. © 2023 IEEE.

关键词： Health risks

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Theory of scanning gate microscopy imaging of the supercurrent distribution in a planar Josephson junction

arXiv

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arXiv 2022年

作者： Kaperek, K. Heun, S. Carrega, M. Wójcik, P. Nowak, Michal P. AGH University of Science and Technology Faculty of Physics and Applied Computer Science al. A. Mickiewicza 30 Krakow30-059 Poland NEST Istituto Nanoscienze CNR Scuola Normale Superiore Piazza San Silvestro 12 Pisa56127 Italy CNR-SPIN Via Dodecaneso 33 Genova16146 Italy AGH University of Science and Technology Academic Centre for Materials and Nanotechnology al. A. Mickiewicza 30 Krakow30-059 Poland

We theoretically investigate the mapping of the supercurrent distribution in a planar superconductor-normal-superconductor junction in the presence of a perpendicular magnetic field via the scanning gate microscopy technique. We find that the distribution of counter-propagating supercurrents aligned in Josephson vortices can be mapped by the change of the critical current induced by the tip of the scanning probe, if the flux in the junction is set close to maxima of the Fraunhofer pattern. Instead, when the magnetic field drives the junction to a supercurrent minimum in the Fraunhofer pattern, the superconducting phase adapts, and the tip always increases the supercurrent. The perpendicular magnetic field leads to the formation of Josephson vortices, whose extension for highly transparent junctions depends on the current circulation direction. We show that this leads to an asymmetric supercurrent distribution in the junction and that this can be revealed by scanning gate microscopy. We explain our findings on the basis of numerical calculations for both short- and long-junction limits and provide a phenomenological model for the observed phenomena. © 2022, CC BY.

关键词： Superconducting materials

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Integrated lithium niobate photonic computing circuit based on efficient and high-speed electro-optic conversion

arXiv

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arXiv 2024年

作者： Hu, Yaowen Song, Yunxiang Zhu, Xinrui Guo, Xiangwen Lu, Shengyuan Zhang, Qihang He, Lingyan Franken, C.A.A. Powell, Keith Warner, Hana Assumpcao, Daniel Renaud, Dylan Wang, Ying Magalhães, Letícia Rosborough, Victoria Shams-Ansari, Amirhassan Li, Xudong Cheng, Rebecca Luke, Kevin Yang, Kiyoul Barbastathis, George Zhang, Mian Zhu, Di Johansson, Leif Beling, Andreas Sinclair, Neil Loncar, Marko John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States State Key Laboratory for Mesoscopic Physics and Frontiers Science Center for Nano-optoelectronics School of Physics Peking University Beijing100871 China Quantum Science and Engineering Harvard University CambridgeMA02138 United States Department of Electrical and Computing Engineering University of Virginia CharlottesvilleVA22903 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States HyperLight Corporation 501 Massachusetts Ave CambridgeMA02139 United States Laser Physics and Nonlinear Optics Group Department of Science and Technology MESA+ Institute of Nanotechnology University of Twente Enschede Netherlands Freedom Photonics 41 Aero Camino GoletaCA United States Department of Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Materials Science and Engineering National University of Singapore Singapore117575 Singapore Singapore138634 Singapore

The surge in artificial intelligence applications, encompassing machine vision, autonomous driving, remote sensing, and process simulation, relies on efficient and large-scale data processing. This requires highly scalable computation with high speed and low energy consumption, calling for innovative solutions to overcome the limitations of electronic systems1–9. Integrated photonics may play a pivotal role in addressing this challenge, leveraging the intrinsic properties of photons, such as natural parallelism, high bandwidth, and low latency10–15. While current photonic computing approaches show promise, they are critically limited by the speed and energy consumption of mapping information from the electronic to optical domain (i.e., electro-optic conversion)1–3,6–8,16 . Here we show a photonic computing accelerator utilizing a system-level thin-film lithium niobate circuit which overcomes this limitation. Leveraging the strong electro-optic (Pockels) effect and the scalability of this platform, we demonstrate photonic computation at speeds up to 1.36 TOPS while consuming 0.057 pJ/OP. Our system features more than 100 thin-film lithium niobate high-performance components working synergistically, surpassing state-of-the-art systems on this platform. We further demonstrate binary-classification, handwritten-digit classification, and image classification with remarkable accuracy, showcasing our system’s capability of executing real algorithms. Finally, we investigate the opportunities offered by combining our system with a hybrid-integrated distributed feedback laser source and a heterogeneous-integrated modified uni-traveling carrier photodiode. Our results illustrate the promise of thin-film lithium niobate as a computational platform, addressing current bottlenecks in both electronic and photonic computation. Its unique properties of high-performance electro-optic weight encoding and conversion, wafer-scale scalability, and compatibility with integrated lasers and

关键词： Distributed feedback lasers

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