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arXiv 2023年

作者： Choudhary, Kamal Wines, Daniel Garrity, Kevin F. Williams, Maureen Tavazza, Francesca Li, Kangming Hattrick-Simpers, Jason Gupta, Vishu Romero, Aldo H. Krogel, Jaron T. Saritas, Kayahan Fuhr, Addis Ganesh, Panchapakesan Kent, Paul R.C. Yan, Keqiang Lin, Yuchao Ji, Shuiwang Blaiszik, Ben Reiser, Patrick Friederich, Pascal Agrawal, Ankit Tiwary, Pratyush Beyerle, Eric Minch, Peter Rhone, Trevor David Takeuchi, Ichiro Wexler, Robert B. Mannodi-Kanakkithodi, Arun Ertekin, Elif Mishra, Avanish Mathew, Nithin Wood, Mitchell Rohskopf, Andrew Dale Wang, Shih-Han Achenie, Luke E.K. Xin, Hongliang Biacchi, Adam J. Material Measurement Laboratory National Institute of Standards and Technology MD20899 United States Department of Materials Science and Engineering University of Toronto 27 King’s College Cir TorontoON Canada Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States Lewis-Sigler Institute for Integrative Genomics Princeton University PrincetonNJ08544 United States Ludwig Institute for Cancer Research Princeton University PrincetonNJ08544 United States Department of Physics and Astronomy West Virginia University MorgantownWV26506 United States Materials Science and Technology Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Center for Nanophase Materials Science Oak Ridge National Laboratory Oak RidgeTN37831 United States Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Computer Science and Engineering Texas A&M University College StationTX77843 United States Globus University of Chicago IL60637 United States Data Science Learning Division National Lab ArgonneIL60439 United States Institute of Nanotechnology Karlsruhe Institute of Technology Kaiserstraße 12 Karlsruhe76131 Germany Institute of Theoretical Informatics Karlsruhe Institute of Technology Kaiserstraße 12 Karlsruhe76131 Germany Department of Chemistry and Biochemistry Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute TroyNY12180 United States Department of Materials Science and Engineering University of Maryland College ParkMD20742 United States Department of Chemistry Institute of Materials Science and Engineering Washington University in St. Louis St. LouisMO63130 United States School of Materials Engineering Purdue University West LafayetteIN47907 United States Department of Mechan

Lack of rigorous reproducibility and validation are significant hurdles for scientific development across many fields. Materials science, in particular, encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC) and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data-points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://***/jarvis_leaderboard/ © 2023, CC BY.

关键词： Electronic structure

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Qick bootstrapping of a Personalized gaze model from real-use interactions

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ACM Transactions on Intelligent Systems and technology 2018年第4期9卷

作者： Huang, Michael Xuelin Li, Jiajia Ngai, Grace Leong, Hong Va Max Planck Institute for Informatics Saarbrucken Informatics Campus Germany South China University of Technology School of Design Guangzhou China Department of Computing Hong Kong Polytechnic University Hong Kong

Understanding human visual attention is essential for understanding human cognition, which in turn benefits human-computer interaction. Recent work has demonstrated a Personalized, Auto-Calibrating Eye-tracking (PACE) system, which makes it possible to achieve accurate gaze estimation using only an off-the-shelf webcam by identifying and collecting data implicitly from user interaction events. However, this method is constrained by the need for large amounts of well-annotated data. We thus present fast-PACE, an adaptation to PACE that exploits knowledge from existing data from different users to accelerate the learning speed of the personalized model. The result is an adaptive, data-driven approach that continuously "learns" its user and recalibrates, adapts, and improves with additional usage by a user. Experimental evaluations of fast-PACE demonstrate its competitive accuracy in iris localization, validity of alignment identification between gaze and interactions, and effectiveness of gaze transfer. In general, fast-PACE achieves an initial visual error of 3.98 degrees and then steadily improves to 2.52 degrees given incremental interaction-informed data. Our performance is comparable to state-of-the-art, but without the need for explicit training or calibration. Our technique addresses the data quality and quantity problems. It therefore has the potential to enable comprehensive gaze-aware applications in the wild. © 2018 ACM.

关键词： Eye tracking

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Noisy quantum amplitude estimation without noise estimation

arXiv

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arXiv 2021年

作者： Tanaka, Tomoki Uno, Shumpei Onodera, Tamiya Yamamoto, Naoki Suzuki, Yohichi Quantum Computing Center Keio University Hiyoshi 3-14-1 Kohoku-ku Yokohama223-8522 Japan Mitsubishi UFJ Financial Group Inc. MUFG Bank Ltd. 2-7-1 Marunouchi Chiyoda-ku Tokyo100-8388 Japan Graduate School of Science and Technology Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama223- 8522 Japan Mizuho Research & Technologies Ltd 2-3 Kanda-Nishikicho Chiyoda-ku Tokyo101-8443 Japan IBM Quantum IBM Research-Tokyo 19-21 Nihonbashi Hakozaki-cho Chuo-ku Tokyo103-8510 Japan Department of Applied Physics and Physico-Informatics Keio University Hiyoshi 3-14-1 Kohoku-ku Yokohama223-8522 Japan

Many quantum algorithms contain an important subroutine, the quantum amplitude estimation. As the name implies, this is essentially the parameter estimation problem and thus can be handled via the established statistical estimation theory. However, this problem has an intrinsic difficulty that the system, i.e., the real quantum computing device, inevitably introduces unknown noise;the probability distribution model then has to incorporate many nuisance noise parameters, resulting that the construction of an optimal estimator becomes inefficient and difficult. For this problem, we apply the theory of nuisance parameters (more specifically, the parameter orthogonalization method) to precisely compute the maximum likelihood estimator for only the target amplitude parameter, by removing the other nuisance noise parameters. That is, we can estimate the amplitude parameter without estimating the noise parameters. We validate the parameter orthogonalization method in a numerical simulation and study the performance of the estimator in the experiment using a real superconducting quantum device. Copyright © 2021, The Authors. All rights reserved.

关键词： Maximum likelihood estimation

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Overcome the Limitations of Performance Parameters of On-Chip Antennas Based on Metasurface and Coupled Feeding Approaches for Applications in System-on-Chip for THz Integrated-Circuits

Overcome the Limitations of Performance Parameters of On-Chi...

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Asia-Pacific Conference on Microwave

作者： Mohammad Alibakhshikenari Bal S. Virdee Chan H. See Raed A. Abd-Alhameed Francisco Falcone Ernesto Limiti University of Rome “Tor Vergata” Via del Politecnico 1 Rome ITALY London Metropolitan University Center for Communications Technology & Mathematics School of Computing & Digital Media London UK School of Engineering University of Bolton Deane Road Bolton UK Faculty of Engineering & Informatics University of Bradford Bradford UK Public University of Navarre Pamplona SPAIN

ISBN: (数字)9781728135175

ISBN: (纸本)9781728135182

This paper proposes a new solution to improve the performance parameters of on-chip antenna designs on standard CMOS silicon (Si.) technology. The proposed method is based on applying the metasurface technique and exciting the radiating elements through coupled feed mechanism. The on-chip antenna is constructed from three layers comprising Si.-GND-Si. layers, so that the ground (GND) plane is sandwiched between two Si. layers. The silicon and ground-plane layers have thicknesses of 20μ m and 5μ m, respectively. The 3×3 array consisting of the asterisk-shaped radiating elements has implemented on the top silicon layer by applying the metasurface approach. Three slot lines in the ground-plane are modelled and located directly under the radiating elements. The radiating elements are excited through the slot-lines using an open-circuited microstrip-line constructed on the bottom silicon layer. The proposed method to excite the structure is based on the coupled feeding mechanism. In addition, by the proposed feeding method the on-chip antenna configuration suppresses the substrate losses and surface-waves. The antenna exhibits a large impedance bandwidth of 60GHz from 0.5THz to 0.56THz with an average radiation gain and efficiency of 4.58dBi and 25.37%, respectively. The proposed structure has compact dimensions of 200×200×45μm 3 . The results shows that, the proposed technique is therefore suitable for on-chip antennas for applications in system-on-chip for terahertz (THz) integrated circuits.

关键词： System-on-chip Silicon Slot antennas Dielectric resonator antennas Substrates

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Biomedical image analysis competitions: The state of current participation practice

arXiv

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arXiv 2022年

作者： Eisenmann, Matthias Reinke, Annika Weru, Vivienn Tizabi, Minu Dietlinde Isensee, Fabian Adler, Tim J. Godau, Patrick Cheplygina, Veronika Kozubek, Michal Maier-Hein, Klaus Jäger, Paul F. Kopp-Schneider, Annette Maier-Hein, Lena Ali, Sharib Gupta, Anubha Kybic, Jan Noble, Alison de Solórzano, Carlos Ortiz Pachade, Samiksha Petitjean, Caroline Sage, Daniel Wei, Donglai Wilden, Elizabeth Alapatt, Deepak Andrearczyk, Vincent Baid, Ujjwal Bakas, Spyridon Balu, Niranjan Bano, Sophia Bawa, Vivek Singh Bernal, Jorge Bodenstedt, Sebastian Casella, Alessandro Choi, Jinwook Commowick, Olivier Daum, Marie Depeursinge, Adrien Dorent, Reuben Egger, Jan Eichhorn, Hannah Engelhardt, Sandy Ganz, Melanie Girard, Gabriel Hansen, Lasse Heinrich, Mattias Heller, Nicholas Hering, Alessa Huaulmé, Arnaud Kim, Hyunjeong Li, Hongwei Bran Landman, Bennett Li, Jianning Ma, Jun Martel, Anne Martín-Isla, Carlos Menze, Bjoern Nwoye, Chinedu Innocent Oreiller, Valentin Padoy, Nicolas Pati, Sarthak Payette, Kelly Sudre, Carole van Wijnen, Kimberlin Vardazaryan, Armine Vercauteren, Tom Wagner, Martin Wang, Chuanbo Yap, Moi Hoon Yu, Zeyun Yuan, Chun Zenk, Maximilian Zia, Aneeq Zimmerer, David Bao, Rina Choi, Chanyeol Cohen, Andrew Dzyubachyk, Oleh Galdran, Adrian Gan, Tianyuan Guo, Tianqi Gupta, Pradyumna Haithami, Mahmood Ho, Edward Jang, Ikbeom Li, Zhili Luo, Zhengbo Lux, Filip Makrogiannis, Sokratis Müller, Dominik Oh, Young-Tack Pang, Subeen Pape, Constantin Polat, Gorkem Reed, Charlotte Rosalie Ryu, Kanghyun Scherr, Tim Thambawita, Vajira Wang, Haoyu Wang, Xinliang Xu, Kele Yeh, Hung Yeo, Doyeob Yuan, Yixuan Zeng, Yan Zhao, Xin Abbing, Julian Adam, Jannes Adluru, Nagesh Agethen, Niklas Ahmed, Salman Al Khalil, Yasmina Alenyà, Mireia Alhoniemi, Esa An, Chengyang Arega, Tewodros Weldebirhan Avisdris, Netanell Aydogan, Dogu Baran Bai, Yingbin Calisto, Maria Baldeon Basaran, Berke Doga Beetz, Marcel Bian, Hao Blansit, Kevin Bloch, Louise Bohnsack, Robert Bosticardo, Sara Breen, Jack Brudfors, Mikael Brüngel, Raphael Cabezas, Mariano Cacciola, Alb Heidelberg Division of Intelligent Medical Systems Germany Heidelberg HI Helmholtz Imaging Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Biostatistics Germany Heidelberg Division of Medical Image Computing Germany Heidelberg HI Applied Vision Lab Germany IT University of Copenhagen Copenhagen Denmark Centre for Biomedical Image Analysis Masaryk University Brno Czech Republic Heidelberg Interactive Machine Learning Group Germany Faculty of Mathematics and Computer Science and Medical Faculty Heidelberg University Heidelberg Germany NCT Heidelberg DKFZ University Hospital Heidelberg Germany School of Computing University of Leeds Leeds United Kingdom SBILab Department of ECE IIIT-Delhi India Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Institute of Biomedical Engineering University of Oxford United Kingdom Center for Applied Medical Research Pamplona Spain Shri Guru Gobind Singhji Institute of Engineering and Technology Maharashtra Nanded India Université de Rouen Normandie France Lausanne Switzerland School of Engineering and Applied Science Harvard University United States ICube University of Strasbourg CNRS France Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Techno-Pôle 3 Sierre3960 Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Rue du Bugnon 46 LausanneCH-1011 Switzerland University of Pennsylvania PhiladelphiaPA United States Department of Radiology University of Washington United States Wellcome EPSRC Centre for Interventional and Surgical Sciences University College London London United Kingdom Visual Artificial Intelligence Lab Oxford Brookes University Oxford United Kingdom Universitat Autònoma de Barcelona & Computer Vision Center Spain Dresden Fetscherstraße 74 PF 64 Dresden01307 Germany

The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known about the common practice as well as bottlenecks faced by the community in tackling the research questions posed. To shed light on the status quo of algorithm development in the specific field of biomedical imaging analysis, we designed an international survey that was issued to all participants of challenges conducted in conjunction with the IEEE ISBI 2021 and MICCAI 2021 conferences (80 competitions in total). The survey covered participants' expertise and working environments, their chosen strategies, as well as algorithm characteristics. A median of 72% challenge participants took part in the survey. According to our results, knowledge exchange was the primary incentive (70%) for participation, while the reception of prize money played only a minor role (16%). While a median of 80 working hours was spent on method development, a large portion of participants stated that they did not have enough time for method development (32%). 25% perceived the infrastructure to be a bottleneck. Overall, 94% of all solutions were deep learning-based. Of these, 84% were based on standard architectures. 43% of the respondents reported that the data samples (e.g., images) were too large to be processed at once. This was most commonly addressed by patch-based training (69%), downsampling (37%), and solving 3D analysis tasks as a series of 2D tasks. K-fold cross-validation on the training set was performed by only 37% of the participants and only 50% of the participants performed ensembling based on multiple identical models (61%) or heterogeneous models (39%). 48% of the respondents applied postprocessing steps. © 2022, CC BY.

关键词： Benchmarking

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Experimental Evaluation of a Novel Personal Assistant in Greek Language for Ambient Assisted Living Environments employing home robots

Experimental Evaluation of a Novel Personal Assistant in Gre...

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2018 South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference, SEEDA_CECNSM 2018

作者： Spournias, Alexandros Christopoulos, Konstantinos Antonopoulos, Konstantinos Panagiotou, Christos Antonopoulos, Christos Orfanoudakis, Theofanis Voros, Nikolaos Computer and Informatics Engineering Department Embedded System Design and Application Laboratory TEI of Western Greece Antirio Greece Embedded System Design and Application Laboratory School of Science and Technology Digital Systems and Media Computing Laboratory TEI of Western Greece Hellenic Open University Patras Greece Embedded System Design and Application Laboratory TEI of Western Greece Antirio Greece School of Science and Technology Digital Systems and Media Computing Laboratory Hellenic Open University Patras Greece

ISBN: (纸本)9786188331419

A personal assistance, is a software component offering advanced Human Machine Interface (HMI) features by initiating and making a "conversations" between humans and machines. Its main objective is to identify the sentences and the context from human's question and respectively give an adequate response to the question posed. The proper response is given after analyzing the words of the question with those registered in its database. This type of application is called a personal assistant - chatbot. In this work, such an application is presented where it can be installed in any smart home as well as assisted living environment. Through the application, all automations, as well as the home robot also, are controlled by human voice in Greek language. Also, a number of auxiliary applications can be performed in the direction of better human service. © 2018 Tei of Western Macedonia.

关键词： Assisted living

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How research achievements can influence delivering of a course - Siebog agent middleware 12th

How research achievements can influence delivering of a cour...

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12th KES Conference on Agent and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2018

作者： Vidaković, Milan Ivanović, Mirjana Stantić, Dejan Vidaković, Jovana Department of Computing and Control Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia Department of Mathematics and Informatics Faculty of Sciences University of Novi Sad Novi Sad Serbia School of Information and Communication Technology Griffith University Gold CoastQLD Australia

ISBN: (纸本)9783319920306

Computer science is one of the fastest changing area and we constantly witness novelties and therefore it is extremely important to also introduce new approaches for computer science education and introduce significant change into curricula. This paper presents the experience in using agent middleware, which has been initially developed as part of the research project in agent oriented graduate-level course. We present the course structure, the tools, teachers’ and students’ experiences with regard to the course delivery. Experiences with the introduction of the teamwork in the course, and characteristics particularly related to the specific methodology have been elaborated. © Springer International Publishing AG, part of Springer Nature 2019.

关键词： Middleware

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Does collaboration bring high-impact studies? A preliminary study

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Proceedings of the Association for Information Science and technology 2017年第1期54卷 750-751页

作者： Lu, Chao Bu, Yi Zhang, Chenwei Ding, Ying Torvik, Vetle I. Zhang, Chengzhi School of Economics and Management Nanjing University of Science and Technology China School of Informatics and Computing Indiana University United States School of Information Sciences University of Illinois United States

Team formation becomes important when scientific collaborations become common and important to scholars. This study initially tries to understand how research team size may influence the impact of a study measured by number of citations. Thus, publications in the biology domain are specifically investigated by correlation analysis between team size and scientific impact. The weak correlation suggests that larger team size can positively increase the impact of scientific publications on average;however, it cannot literally bring more highly cited articles. Copyright © 2017 by Association for Information Science and technology

关键词： scientific collaboration scientific impact team size

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Robust coalition structure generation 21st

Robust coalition structure generation

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21st International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2018

作者： Okimoto, Tenda Schwind, Nicolas Demirović, Emir Inoue, Katsumi Marquis, Pierre Kobe University Kobe Japan National Institute of Advanced Industrial Science and Technology Tokyo Japan School of Computing and Information Systems University of Melbourne Melbourne Australia National Institute of Informatics Tokyo Institute of Technology Tokyo Japan CRIL-CNRS Université d’Artois Institut Universitaire de France Lens France

ISBN: (纸本)9783030030971

How to form effective coalitions is an important issue in multi-agent systems. Coalition Structure Generation (CSG) involves partitioning a set of agents into coalitions so that the social surplus (i.e. the sum of the rewards obtained by each coalition) is maximized. In many cases, one is interested in computing a partition of the set of agents which maximizes the social surplus, but is robust as well, which means that it is not required to recompute new coalitions if some agents break down. In this paper, the focus is laid on the Robust Coalition Structure Generation (RCSG) problem. A formal framework is defined and some decision and optimization problems for RCSG are pointed out. The computational complexity of RCSG is then identified. An algorithm for RCSG (called AmorCSG) is presented and evaluated on a number of benchmarks. © Springer Nature Switzerland AG 2018.

关键词： Multi agent systems

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HCI's making agendas

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Foundations and Trends in Human-Computer Interaction 2017年第3期11卷 126-200页

作者： Bardzell, Jeffrey Bardzell, Shaowen Lin, Cindy Lindtner, Silvia Toombs, Austin Indiana University School of Informatics Computing and Engineering United States University of Michigan School of Information United States Purdue University Department of Computer Graphics Technology United States

In this survey, we examine how making emerged as an interdisciplinary arena of scholarship, research and design that connects entrepreneurs, designers, researchers, critical theorists, historians, anthropologists, computer scientists and engineers. HCI is one among many other fields and domains that has declared having a stake in making. And yet, a lot of what and who defines making is happening outside the familiar research laboratory or design studio. We take this article as an opportunity to reflect on HCI's relationship to making and how this relationship has changed over the last years. Making, we argue, presents HCI with the opportunity to question and revisit underlying principles and long-held aspirations and values of the field. Exactly because HCI and making share some fundamental ideals such as user empowerment and the democratization of participation and technology production, making confronts us with both the potential and the unintended consequences of our own work. © 2017 J. Bardzell, S. Bardzell, C. Lin, S. Lindtner and H. Toombs.

关键词： Research laboratories

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