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ssRN 2024年

作者： Pablo-García, sergio García, Ángel Akkoc, Gun Deniz sim, Malcolm Cao, Yang somers, Maxine Hattrick, Chance Yoshikawa, Naruki Dworschak, Dominik Hao, Han Aspuru-Guzik, Alán Department of Chemistry University of Toronto Lash Miller Chemical Laboratories 80 St. George Street TorontoONM5S 3H6 Canada Department of Computer Science University of Toronto Sandford Fleming Building 10 King’s College Rd. TorontoONM5S 2E4 Canada Badalona Catalonia Spain Cauerstraße 1 Erlangen91058 Germany Friedrich-Alexander-Universität Erlangen-Nürnberg Department of Chemical and Biological Engineering Egerlandstraße 3 Erlangen91058 Germany Acceleration Consortium 80 St George St TorontoONM5S 3H6 Canada Vector Institute for Artificial Intelligence 661 University Ave. Suite 710 TorontoONM5G 1M1 Canada Department of Materials Science & Engineering University of Toronto 184 College St. TorontoONM5S 3E4 Canada Department of Chemical Engineering & Applied Chemistry University of Toronto 200 College St. TorontoONM5S 3E5 Canada 661 University Ave. TorontoONM5G 1M1 Canada

Electrochemical techniques are pivotal for material discovery and renewable energy;however, often the extensive chemical spaces to be explored require high-throughput experimentation (HtE) to ensure timely results, which are costly both for instrument and materials/consumables. While self-driving laboratories (sDL) promise efficient chemical exploration, most contemporary implementations demand significant time, economic investment, and expertise. this study introduces an open and cost-effective autonomous electrochemical setup, comprising a synthesis platform and a custom-designed potentiostat device. We present an sDL platform that offers rapid deployment and extensive control over electrochemical experiments compared to commercial alternatives. Using ChemOs 2.0 for orchestration, we showcase our setup's capabilities through a campaign in which different metal ions reacts with ligands to form coordination compounds., yielding a database of 400 electrochemical measurements. Committed to open science, we provide a potentiostat design, campaign software, and raw data, aiming to democratize customized components in sDLs and ensure transparent data sharing and reproducibility. © 2024, the Authors. All rights reserved.

关键词： Electrochemistry

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Roadmapping the Next Generation of silicon Photonics

arXiv

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arXiv 2023年

作者： shekhar, sudip Bogaerts, Wim Chrostowski, Lukas Bowers, John E. Hochberg, Michael soref, Richard shastri, Bhavin J. Department of Electrical & Computer Engineering University of British Columbia 2332 Main Mall VancouverBCV6T1Z4 Canada Department of Information Technology Ghent University IMEC Technologiepark-Zwijnaarde 126 Ghent9052 Belgium Department of Electrical & Computer Engineering University of California Santa Barbara Santa BarbaraCA93106 United States Luminous Computing 4750 Patrick Henry Drive Santa ClaraCA95054 United States College of Science and Mathematics University of Massachusetts Boston 100 William T. Morrissey Blvd. BostonMA02125 United States Department of Physics Engineering Physics & Astronomy Queen’s University 64 Bader Lane KingstonONK7L3N6 Canada

silicon photonics has developed into a mainstream technology driven by advances in optical communications. the current generation has led to a proliferation of integrated photonic devices from thousands to millions—mainly in the form of communication transceivers for data centers. Products in many exciting applications, such as sensing and computing, are around the corner. What will it take to increase the proliferation of silicon photonics from millions to billions of units shipped? What will the next generation of silicon photonics look like? What are the common threads in the integration and fabrication bottlenecks that silicon photonic applications face, and which emerging technologies can solve them? this perspective article is an attempt to answer such questions. We chart the generational trends in silicon photonics technology, drawing parallels from the generational definitions of CMOs technology. We identify the crucial challenges that must be solved to make giant strides in CMOs-foundry-compatible devices, circuits, integration, and packaging. We identify challenges critical to the next generation of systems and applications - in communication, signal processing, and sensing. By identifying and summarizing such challenges and opportunities, we aim to stimulate further research on devices, circuits, and systems for the silicon photonics ecosystem. Copyright © 2023, the Authors. All rights reserved.

关键词： silicon photonics

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statistical Complexity of Quantum Learning

arXiv

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arXiv 2023年

作者： Banchi, Leonardo Pereira, Jason Luke Jose, sharu theresa simeone, Osvaldo Department of Physics and Astronomy University of Florence via G. Sansone 1 FI Sesto FiorentinoI-50019 Italy INFN Sezione di Firenze via G. Sansone 1 FI Sesto FiorentinoI-50019 Italy Department of Computer Science University of Birmingham BirminghamB15 2TT United Kingdom Department of Engineering King's College London Strand LondonWC2R 2LS United Kingdom

Recent years have seen significant activity on the problem of using data for the purpose of learning properties of quantum systems or of processing classical or quantum data via quantum computing. As in classical learning, quantum learning problems involve settings in which the mechanism generating the data is unknown, and the main goal of a learning algorithm is to ensure satisfactory accuracy levels when only given access to data and, possibly, side information such as expert knowledge. this article has two main goals. First, it reviews and generalizes different results on the complexity of quantum learning, using information-theoretic techniques and focusing on data complexity and model complexity. second, it introduces the notion of copy complexity, which quantifies the number of copies of a quantum state required to achieve a target accuracy level. Copy complexity arises from the destructive nature of quantum measurements, which irreversibly alter the state to be processed, limiting the information that can be extracted about quantum data. As a result, in a quantum system, unlike in classical machine learning, it is generally not possible to evaluate the training loss simultaneously on multiple hypotheses using the same quantum data, making empirical risk minimization generally inapplicable. Furthermore, copy complexity also affects the performance at test time, as the information that can be obtained from a quantum system increases with the number of available copies. the paper presents novel results on the copy complexity for both training and testing. to make the paper self-contained and approachable by different research communities, we provide extensive background material on classical results from statistical learning theory, as well as on the distinguishability of quantum states. throughout, we highlight the differences between quantum and classical learning by addressing both supervised and unsupervised learning, and we provide extensive pointers to the

关键词： Learning algorithms

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Design of Compact Dual Band-stop Frequency selective surface for shielding Application

Design of Compact Dual Band-Stop Frequency Selective Surface...

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international Conference on computer Communication and informatics (iCCCi)

作者： Rahul Krishnan R Ganesh Babu K. Lalitha Rajasekhar Atla Vanaja. s swetha. D Rajalakshmi Institute of Technology Chennai India SRM TRP Engineering College Tiruchirappalli India S.R.M. Institute of Science and Technology Chennai India N.B.K.R.I.S.T Vidyanagar India

this paper introduces a compact dual bandstop frequency selective surface (F.s.s.) for shielding applications. the octagonal and square looped model projected in this paper act as a band rejects filter for the frequencies 2.4 GHz and 5 GHz. the proposed model simulated using Cst MWs electromagnetic simulation software. the current distribution for the two resonance frequencies is analyzed well. the proposed unit cell provides a symmetrical shape which enable stable performance in both t.E. and t.M. mode. the angular stability was assessed in various angles of incidence from (0°-60°). in t.E. polarization, the transmission and reflection coefficient for second resonance frequency shifted by +0.5 GHz and -0.5 GHz.

关键词： Frequency selective surfaces shape Resonant frequency stability analysis software Reflection coefficient informatics

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Assessment of Mental Workload by Visual Motor Activity among Control Group and Patient suffering from Depressive Disorder

引用

Computational intelligence and Neuroscience 2022年第0期2022卷 8555489页

作者： Murugesan, G. Ahmed, tousief irshad shabaz, Mohammad Bhola, Jyoti Omarov, Batyrkhan swaminathan, R. sammy, F. sumi, sharmin Akter Department of Computer Science and Engineering St. Joseph's College of Engineering Chennai600119 India Department of Clinical Biochemistry Sher-i-Kashmir Institute of Medical Sciences Soura JandK Srinagar India Model Institute of Engineering and Technology JandK Jammu India Electronics and Communication Engineering Department National Institute of Technology Hamirpur India Al-Farabi Kazakh National University Almaty Kazakhstan International University of Tourism and Hospitality Turkistan Kazakhstan Suleiman Demirel University Kaskelen Kazakhstan Saveetha School of Engineering Tamil Nadu Chennai India Department of Information Technology Dambi Dollo University Dembi Dolo Welega Ethiopia Department of Anatomy Bangabandhu Sheikh Mujib Medical University Dhaka Bangladesh

Major depressive disorder (MDD) is a mood state that is not usually associated with vision problems. Recent research has found that the inhibitory neurotransmitter GABA levels in the occipital brain have dropped. Aim. the aim of the research is to evaluate mental workload by single channel electroencephalogram (EEG) approach through visual-motor activity and comparison of parameter among depressive disorder patient and in control group. Method. two tests of a visual-motor task similar to reflect drawings were performed in this study to compare the visual information processing of patients with depression to that of a placebo group. the current study looks into the accuracy of monitoring cognitive burden with single-channel portable EEG equipment. Results. the alteration of frontal brain movement in reaction to fluctuations in cognitive burden stages generated through various vasomotor function was examined. By applying a computerised oculomotor activity analogous to reflector image diagram, we found that the complexity of the path to be drawn was more important than the real time required accomplishing the job in determining perceived difficulty in depressive disorder patients. the overall perceived difficulty of the exercise is positively linked with EEG activity measured from the motor cortex region at the start of every experiment test. the average rating for task completion for depression patients and in control group observed and no statistical significance association reported between rating scale and time spent on each trial (p=1.43) for control group while the normalised perceived difficulty rating had 0.512, 0.623, and 0.821 correlations with the length of the pathway, the integer of inclination in the pathway, and the time spent to complete every experiment test, respectively (p © 2022 G. Murugesan et al.

关键词： Electroencephalography

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Deep Learning Architecture for Automatic Essay scoring

arXiv

引用

arXiv 2022年

作者： tashu, tsegaye Misikir Maurya, Chandresh Kumar Horváth, tomáš ELTE Eötvös Loránd University Faculty of Informatics Department of Data Science and Engineering Telekom Innovation Laboratories Pázmány Péter sétány 1/C Budapest1117 Hungary Pavol Jozef Šafárik University in Košice Faculty of Science Institute of Computer Science Jesenná 5 Košice040 01 Slovakia Wollo University Kombolcha Institute of Technology College of Informatics Kombolcha 208 Ethiopia

Automatic evaluation of essay (AEs) and also called automatic essay scoring has become a severe problem due to the rise of online learning and evaluation platforms such as Coursera, Udemy, Khan academy, and so on. Researchers have recently proposed many techniques for automatic evaluation. However, many of these techniques use hand-crafted features and thus are limited from the feature representation point of view. Deep learning has emerged as a new paradigm in machine learning which can exploit the vast data and identify the features useful for essay evaluation. to this end, we propose a novel architecture based on recurrent networks (RNN) and convolution neural network (CNN). in the proposed architecture, the multichannel convolutional layer learns and captures the contextual features of the word n-gram from the word embedding vectors and the essential semantic concepts to form the feature vector at essay level using max-pooling operation. A variant of RNN called Bi-gated recurrent unit (BGRU) is used to access both previous and subsequent contextual representations. the experiment was carried out on eight data sets available on Kaggle for the task of AEs. the experimental results show that our proposed system achieves significantly higher grading accuracy than other deep learning-based AEs systems and also other state-of-the-art AEs systems. Copyright © 2022, the Authors. All rights reserved.

关键词： semantics

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Position: Bayesian Deep Learning is Needed in the Age of Large-scale Ai

arXiv

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arXiv 2024年

作者： Papamarkou, theodore skoularidou, Maria Palla, Konstantina Aitchison, Laurence Arbel, Julyan Dunson, David Filippone, Maurizio Fortuin, Vincent Hennig, Philipp Hernández-Lobato, José Miguel Hubin, Aliaksandr immer, Alexander Karaletsos, theofanis Khan, Mohammad Emtiyaz Kristiadi, Agustinus Li, Yingzhen Mandt, stephan Nemeth, Christopher Osborne, Michael A. Rudner, tim G.J. Rügamer, David teh, Yee Whye Welling, Max Wilson, Andrew Gordon Zhang, Ruqi Department of Mathematics The University of Manchester Manchester United Kingdom Eric and Wendy Schmidt Center Broad Institute of MIT and Harvard Cambridge United States Spotify London United Kingdom Computational Neuroscience Unit University of Bristol Bristol United Kingdom Centre Inria de l'Université Grenoble Alpes Grenoble France Department of Statistical Science Duke University United States Statistics Program KAUST Saudi Arabia Helmholtz AI Munich Germany Department of Computer Science Technical University of Munich Munich Germany Munich Center for Machine Learning Munich Germany Tübingen AI Center University of Tübingen Tübingen Germany Department of Engineering University of Cambridge Cambridge United Kingdom Department of Mathematics University of Oslo Oslo Norway Bioinformatics and Applied Statistics Norwegian University of Life Sciences Ås Norway Department of Computer Science ETH Zurich Switzerland Chan Zuckerberg Initiative CA United States Center for Advanced Intelligence Project RIKEN Tokyo Japan Vector Institute Toronto Canada Department of Computing Imperial College London London United Kingdom Department of Computer Science UC Irvine Irvine United States Department of Mathematics and Statistics Lancaster University Lancaster United Kingdom Department of Engineering Science University of Oxford Oxford United Kingdom Center for Data Science New York University New York United States Department of Statistics LMU Munich Munich Germany DeepMind London United Kingdom Department of Statistics University of Oxford Oxford United Kingdom Informatics Institute University of Amsterdam Amsterdam Netherlands Courant Institute of Mathematical Sciences Center for Data Science Computer Science Department New York University New York United States Department of Computer Science Purdue University West Lafayette United States

in the current landscape of deep learning research, there is a predominant emphasis on achieving high predictive accuracy in supervised tasks involving large image and language datasets. However, a broader perspective reveals a multitude of overlooked metrics, tasks, and data types, such as uncertainty, active and continual learning, and scientific data, that demand attention. Bayesian deep learning (BDL) constitutes a promising avenue, offering advantages across these diverse settings. this paper posits that BDL can elevate the capabilities of deep learning. it revisits the strengths of BDL, acknowledges existing challenges, and highlights some exciting research avenues aimed at addressing these obstacles. Looking ahead, the discussion focuses on possible ways to combine large-scale foundation models with BDL to unlock their full potential. © 2024, CC BY-NC-ND.

关键词： Large datasets

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WELL-POsEDNEss OF tHE stOKEs EQUAtiONs ON A WEDGE WitH NAViER-sLiP BOUNDARY CONDitiONs

arXiv

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arXiv 2024年

作者： Bravin, Marco Gnann, Manuel V. Knüpfer, Hans Masmoudi, Nader Roodenburg, Floris B. sauer, Jonas Departmento de Matemática Aplicada y Ciencias de la Computacíon E.T.S.I. Industriales y de Telecomunicacíon Universidad de Cantabria Santander39005 Spain Delft Institute of Applied Mathematics Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Mekelweg 4 Delft2628CD Netherlands Institute for Applied Mathematics and IWR Heidelberg University INF 205 Heidelberg69120 Germany NYUAD Research Institute New York University Abu Dhabi Saadiyat Island P.O. Box Abu Dhabi129188 United Arab Emirates Courant Institute of Mathematical Sciences New York University 251 Mercer Street New YorkNY10012 United States Delft Institute of Applied Mathematics Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Mekelweg 4 Delft2628CD Netherlands Institute for Mathematics Faculty of Mathematics and Computer Science University of Jena Ernst-Abbe-Platz 2 Jena07737 Germany

We consider the incompressible and stationary stokes equations on an infinite two-dimensional wedge with non-scaling invariant Navier-slip boundary conditions. We prove well-posedness and higher regularity of the stokes problem in a certain class of weighted sobolev spaces. the novelty of this work is the occurrence of two different scalings in the boundary condition, which is not treated so far for the stokes system in unbounded wedge-type domains. these difficulties are overcome by first constructing a variational solution in a second order weighted sobolev space and subsequently proving higher regularity up to the tip of the wedge by employing an iterative scheme. We believe that this method can be used for other problems with variational structure and multiple scales. Copyright © 2024, the Authors. All rights reserved.

关键词： Boundary conditions

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Curating a National student Presence in the space sector: A Comparative Case study of students for the Exploration and Development of space in Canada

Curating a National Student Presence in the Space Sector: A ...

引用

iAF space Education and Outreach symposium 2021 at the 72nd international Astronautical Congress, iAC 2021

作者： Andres, Chimira N. Motaghed, sepand Dyanatkar Rosenstein, Aaron Lee, Kaitlyn de Korte, Marieke Kunitskaya, Alina Nadeem, sobia van Decker, Vanessa 330 Rue Avro Pointe-ClaireQCH9R 5W9 Canada Lassonde School of Engineering Department of Earth and Space Science and Engineering York University 4700 Keele St TorontoONM3J 1P3 Canada Department of Computer Science The University of British Columbia 2366 Main Mall VancouverBCV6T 1Z4 Canada Institute of Biomedical Engineering University of Toronto 164 College Street TorontoONM5S 3G9 Canada Kaitlyn Lee Department of Mechanical & Mechatronics Faculty of Engineering The University of Waterloo 200 University Ave W WaterlooONN2L 3G1 Canada Department of Laboratory Medicine and Pathobiology Temerty Faculty of Medicine University of Toronto 27 King’s College Circle TorontoONM5S 1A1 Canada Michael Smith Laboratories The School of Biomedical Engineering The University of British Columbia 2185 E Mall VancouverBCV6T 1Z4 Canada Department of Engineering Physics McMaster University 1280 Main St W HamiltonONL8S 4L8 Canada Department of Mechanical and Industrial Engineering Ryerson University 350 Victoria St TorontoONM5B 2K3 Canada

ISBN: (纸本)9781713843177

As the space sector looks to secure its next generation of innovators, educational institutions are seeking to expand their aerospace programming to attract students into the field. However, many of these programs are detached from the national space sector, and the opportunity to make connections with leaders in industry as well as other students and researchers are sparse before entering into the professional world. Non-for-profit student organizations that seek to create a national student presence in the space sector have an important role to play in facilitating the growth and handover of the space sector on the national stage. Using students for the Exploration and Development of space Canada (sEDs-Canada) as a comparative case study, we sought to identify the opportunities and challenges that exist for student organizations in the space sector. A survey (via theme analysis and structured interviews) of other national student space organizations, including sEDs-UsA, sEDs-india, UKsEDs, sEDs sriLanka, the roots of the developing sEDs-italy, and other members of the sEDs-Earth Council of Nations (CoN) provided a snapshot of the recruitment, membership structure, membership benefits, programming, and financial strategy of national student space organizations in various levels of establishment. through this survey and comparative study with the growth of sEDs-Canada over the past 5 years, we identified several benefits to a strong national student presence in the space sector, most notably 1) the creation of opportunities for students at all levels through various project competitions and scholarships, 2) the ability to connect students with each other as well as industry mentors through national conferences such as Ascension (sEDs-Canada) and spaceVision (sEDs-UsA), 3) access to national student recruitment for industry through the student organization’s job postings, and 4) maintenance and development of student involvement in space activities on an intergovernm

关键词： students

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innovative Method for Earthquake Prediction system using Hybrid Convolutional Neural Network and sVM

Innovative Method for Earthquake Prediction System using Hyb...

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Artificial intelligence and Applications (iCAiA), international Conference on, technology Conference (AtCON-1), Alliance

作者： N. Rajkumar N. Kanimozhi P. saravanakumar sireesha Koneru Puneet sapra Ravi Rastogi Department of CSE Vel Tech R. Dr.S. R&D I.S.T. Vel Tech Nagar Chennai Tamilnadu India Department of C.I School of Computing SRM Institute of Science and Technology Chennai Tamilnadu India Department of C.E Sri Krishna College of Engg. and Techn Coimbatore Tamilnadu India Department of Mechanical Engineering Koneru Lakshmaiah Edu.Foundation Guntur Andhra Pradesh India Department of CSE Rayat Bahra University Mohali Punjab India NIELIT Gorakhpur Uttar Pradesh India

the ability to estimate casualties from earthquakes is crucial for effective disaster response. Conventional forecasting techniques have stringent sample data requirements and several parameters that must be manually specified, which can lead to subpar outcomes with prediction accuracy as low and a slow rate of learning. in the suggested hybrid model, CNN is employed as an automatic feature extractor, while sVM is used as a binary classifier. traditional CNN’s completely linked layers are swapped out for a support vector machine in this model to improve prediction accuracy. this proposed approach employs CNN for automatic feature extraction, and an sVM classifier for automatic classification. the experimental findings showed that compared to the CNN model (89%), our hybrid model was significantly more accurate at 98.5%

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