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Deformations of unitary Howe dual pairs

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arXiv 2020年

作者： Ciubotaru, Dan de Bie, Hendrik de Martino, Marcelo Oste, Roy Mathematical Institute University of Oxford OxfordOX2 6GG United Kingdom Department of Electronics and Information Systems Ghent University Krijgslaan 281 Gent9000 Belgium Department of Applied Mathematics Computer Science and Statistics Ghent University Krijgslaan 281-S9 Gent9000 Belgium

We study deformations of the Howe dual pairs (U(n), u(1, 1)) and (U(n), u(2|1)) to the context of a rational Cherednik algebra H1,c(G, E) associated with a real reflection group G acting on a real vector space E of even dimension. For each pair, we show that the Lie (super)algebra structure of one partner is preserved under the deformation, which leads to a multiplicity-free decomposition of the standard module or its tensor product with a spinor space. For the case where E is two-dimensional and G is a dihedral group, we provide complete descriptions for the deformed pair and the relevant *** Codes 16S80, 16W10, 16W22, 17B10 Copyright © 2020, The Authors. All rights reserved.

关键词： Deformation

Global adoption of unified communication technologies as part of digital transformation in organizations: A cross-cultural perspective

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Global adoption of unified communication technologies as par...

Multikonferenz Wirtschaftsinformatik, MKWI 2018 - Multiconference on Business Informatics, MKWI 2018

作者： Meske, Christian Kissmer, Tobias Stieglitz, Stefan Freie Universität Berlin Department of Information Systems Berlin Germany University of Duisburg-Essen Department of Computer Science and Applied Cognitive Science Duisburg Germany

ISBN: (纸本)9783935786720

Unified Communication (UC) is increasingly introduced in global enterprises to support the digital interaction of employees. Cultural differences can influence such adoption of corresponding technologies and need to be considered by IT managers. In this study, we show how cultures with specific characteristics (according to Hofstede and Hall) adopt UC differently. This research paper is based on a unique dataset, consisting of communication data from over 6,000 users of a multi-national enterprise. During the period of six months, 4.6 million records were collected with the purpose of analyzing the adoption after the rollout of a UC technology. Eight subsidiaries in Asia, North America and Europe were analyzed. The results show that especially Hofstede's factors Individualism/Collectivism and Long-Term Orientation as well as Hall's factor Monochronic/Polychronic culture helped to explain post-implementation usage activity. The results help IT managers to understand potential cultural influences on introductions of according technologies in global enterprises. © 2018 Universitatsverlag Gottingen. All rights reserved.

关键词： Managers

Automated Assessment of Balance Rehabilitation Exercises With a Data-Driven Scoring Model: Algorithm Development and Validation Study

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JMIR Rehabilitation and Assistive Technologies 2022年第3期9卷 e37229页

作者： Tsakanikas, Vassilios Gatsios, Dimitris Pardalis, Athanasios Tsiouris, Kostas M. Georga, Eleni Bamiou, Doris-Eva Pavlou, Marousa Nikitas, Christos Kikidis, Dimitrios Walz, Isabelle Maurer, Christoph Fotiadis, Dimitrios Unit of Medical Technology and Intelligent Information Systems Department of Materials Science and Engineering University of Ioannina Ioannina Greece Ear Institute University College London London United Kingdom Biomedical Research Centre Hearing and Deafness University College London Hospitals London United Kingdom Centre for Human and Applied Physiological Sciences King's College London London United Kingdom First Department of Otolaryngology-Head and Neck Surgery Hippokrateio General Hospital National Kapodistrian University of Athens Athens Greece Department of Neurology and Neuroscience Medical Center University of Freiburg Faculty of Medicine University of Freiburg Freiburg Germany Biomedical Research Institute Ioannina Greece

Background: Balance rehabilitation programs represent the most common treatments for balance disorders. Nonetheless, lack of resources and lack of highly expert physiotherapists are barriers for patients to undergo individualized rehabilitation sessions. Therefore, balance rehabilitation programs are often transferred to the home environment, with a considerable risk of the patient misperforming the exercises or failing to follow the program at all. Holobalance is a persuasive coaching system with the capacity to offer full-scale rehabilitation services at home. Holobalance involves several modules, from rehabilitation program management to augmented reality coach presentation. Objective: The aim of this study was to design, implement, test, and evaluate a scoring model for the accurate assessment of balance rehabilitation exercises, based on data-driven techniques. Methods: The data-driven scoring module is based on an extensive data set (approximately 1300 rehabilitation exercise sessions) collected during the Holobalance pilot study. It can be used as a training and testing data set for training machine learning (ML) models, which can infer the scoring components of all physical rehabilitation exercises. In that direction, for creating the data set, 2 independent experts monitored (in the clinic) 19 patients performing 1313 balance rehabilitation exercises and scored their performance based on a predefined scoring rubric. On the collected data, preprocessing, data cleansing, and normalization techniques were applied before deploying feature selection techniques. Finally, a wide set of ML algorithms, like random forests and neural networks, were used to identify the most suitable model for each scoring component. Results: The results of the trained model improved the performance of the scoring module in terms of more accurate assessment of a performed exercise, when compared with a rule-based scoring model deployed at an early phase of the system (k-statistic valu

关键词： balance rehabilitation exercises exercise evaluation persuasive coaching system scoring model

Hesitant bipolar fuzzy set-based decision system for electric vehicle charging station location planning

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Sustainable Energy, Grids and Networks 2025年 43卷

作者： Chakkarapani Sumathi Thilagasree Thippan Jayakumar Lakshmanaraj Ramya Krishnan Suvitha Dragan Pamucar Witold Pedrycz Joseph Varghese Kureethara Department of Mathematics Sri Ramakrishna Mission Vidyalaya College of Arts and Science Coimbatore India Department of Mathematics Bharathiar University Coimbatore 641 046 India Centre for Nonlinear Systems Chennai Institute of Technology Chennai Tamilnadu India Department of Applied Mathematical Science College of Science and Technology Korea University Sejong Republic of Korea Yuan Ze University College of Engineering Department of Industrial Engineering and Managemente Taoyuan City Taiwan Industrial Engineering Department Faculty of Engineering and Natural Sciences İstinye University İstanbul Türkiye Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada Department of Mathematics CHRIST (Deemed to be University) Bangalore India

The selection of electric vehicle (EV) charging station locations is a critical challenge that significantly affects the growth and acceptance of the EV industry. As EVs offer a sustainable solution to fossil fuel depletion and environmental pollution, identifying optimal charging station sites involves dealing with uncertain, inconsistent, and conflicting criteria. To address these challenges, this paper presents an innovative decision-making framework based on Hesitant Bipolar-Valued Fuzzy Sets (HBVFSs), which account for both positive and negative hesitant membership values to better model uncertainty in expert judgments. A novel hybrid Multi-Criteria Decision-Making (MCDM) technique is proposed, combining the Step-wise Weight Assessment Ratio Analysis (SWARA) and Pivot Pairwise Relative Criteria Importance Assessment (PIPRECIA) methods to determine robust criteria weights within the HBVFS environment. The Preference Ranking Organization METHod for Enrichment Evaluation II (PROMETHEE-II) is employed for the final site ranking. This integrated approach enables a more comprehensive and reliable evaluation of potential locations by incorporating both qualitative and quantitative factors. The proposed methodology has practical applications in real-world infrastructure planning and supports more resilient decision-making in sustainable transportation networks. The results demonstrate the model’s effectiveness and adaptability in addressing the site selection problem under uncertainty.

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Why is the Winner the Best?

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Why is the Winner the Best?

Conference on computer Vision and Pattern Recognition (CVPR)

作者： M. Eisenmann A. Reinke V. Weru M. D. Tizabi F. Isensee T. J. Adler S. Ali V. Andrearczyk M. Aubreville U. Baid S. Bakas N. Balu S. Bano J. Bernal S. Bodenstedt A. Casella V. Cheplygina M. Daum M. De Bruijne A. Depeursinge R. Dorent J. Egger D. G. Ellis S. Engelhardt M. Ganz N. Ghatwary G. Girard P. Godau A. Gupta L. Hansen K. Harada M. Heinrich N. Heller A. Hering A. Huaulmé P. Jannin A. E. Kavur O. Kodym M. Kozubek J. Li H. Li J. Ma C. Martín-Isla B. Menze A. Noble V. Oreiller N. Padoy S. Pati K. Payette T. Rädsch J. Rafael-Patiño V. Singh Bawa S. Speidel C. H. Sudre K. Van Wijnen M. Wagner D. Wei A. Yamlahi M. H. Yap C. Yuan M. Zenk A. Zia D. Zimmerer D. Aydogan B. Bhattarai L. Bloch R. Brüngel J. Cho C. Choi Q. Dou I. Ezhov C. M. Friedrich C. Fuller R. R. Gaire A. Galdran Á. García Faura M. Grammatikopoulou S. Hong M. Jahanifar I. Jang A. Kadkhodamohammadi I. Kang F. Kofler S. Kondo H. Kuijf M. Li M. Luu T. Martinčič P. Morais M. A. Naser B. Oliveira D. Owen S. Pang J. Park S. Park S. Płotka E. Puybareau N. Rajpoot K. Ryu N. Saeed A. Shephard P. Shi D. Štepec R. Subedi G. Tochon H. R. Torres H. Urien J. L. Vilaça K. A. Wahid H. Wang J. Wang L. Wang X. Wang B. Wiestler M. Wodzinski F. Xia J. Xie Z. Xiong S. Yang Y. Yang Z. Zhao K. Maier-Hein P. F. Jäger A. Kopp-Schneider L. Maier-Hein Division of Intelligent Medical Systems German Cancer Research Center (DKFZ) Heidelberg Germany Helmholtz Imaging German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Biostatistics German Cancer Research Center (DKFZ) Heidelberg Germany Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Engineering and Physical Sciences School of Computing University of Leeds Leeds UK Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Sierre Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Lausanne Switzerland Technische Hochschule Ingolstadt Ingolstadt Germany Center for Artificial Intelligence and Data Science for Integrated Diagnostics (AI2D) and Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology University of Washington Seattle WA USA Department of Computer Science Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) University College London London UK Universitat Autònoma de Barcelona & Computer Vision Center Barcelona Spain Division of Translational Surgical Oncology National Center for Tumor Diseases (NCT/UCC) Dresden Dresden Germany Department of Advanced Robotics Istituto Italiano di Tecnologia Italy Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy IT University of Copenhagen Copenhagen Denmark Department of General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg Germany Department of Radiology and Nuc

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multicenter study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), image preprocessing (97%), data curation (79%), and post-processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work.

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The impact of user behaviours on the socialisation process in enterprise social networks 29

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The impact of user behaviours on the socialisation process i...

29th Australasian Conference on information systems, ACIS 2018

作者： Hüllmann, Joschka Kroll, Tobias Department of Information Systems University of Münster Münster Germany Department of Computer Science and Applied Cognitive Science University of Duisburg-Essen Duisburg Germany

The success of teams in enterprise social networks (ESN) is of high importance in today’s project-based and digitised work environments. In this context, onboarding of new hires or allocated team members means the adoption of group characteristics and behaviours. Studies identified cohesion and trust as part of the socialisation process and found communication behaviours that facilitate socialisation. ESN not only enable efficient communication or relationship building, they also make the socialisation processes visible and analysable. In this paper, we propose to use metrics from social network analysis (e.g. extraversion, openness and proactiveness) to operationalise communication behaviours identified as positive for socialisation. First evaluations with two ESN data sets in OLS, beta regression and multilevel models sparsely support the influence on closeness, which we expect to reflect the level of group integration. © 2018 Joschka Hüllmann and Tobias Kroll.

关键词： Behavioral research

Reversible modulation of metal-insulator transition in VO2 via chemically-induced oxygen migration

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arXiv 2021年

作者： Han, Kun Wang, Hanyu Wu, Liang Cao, Yu Qi, Dong-Chen Li, Changjian Huang, Zhen Li, Xiao Wang, X. Renshaw Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information Technology Anhui University Hefei230601 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link Singapore637371 Singapore School of Physics and Technology Nanjing Normal University Nanjing210023 China Faculty of Material Science and Engineering Kunming University of Science and Technology Yunnan Kunming650093 China Institute for New Materials Foshan528247 China Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore117583 Singapore Centre for Materials Science School of Chemistry and Physics Queensland University of Technology BrisbaneQLD4001 Australia Department of Materials Science and Engineering Southern University of Science and Technology Guangdong Shenzhen518055 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Ave Singapore639798 Singapore

Metal-insulator transitions (MIT), an intriguing correlated phenomenon induced by the subtle competition of the electrons' repulsive Coulomb interaction and kinetic energy, is of great potential use for electronic applications due to the dramatic change in resistivity. Here, we demonstrate a reversible control of MIT in VO2 films via oxygen stoichiometry engineering. By facilely depositing and dissolving a water-soluble yet oxygen-active Sr3Al2O6 capping layer atop the VO2 at room temperature, oxygen ions can reversibly migrate between VO2 and Sr3Al2O6, resulting in a gradual suppression and a complete recovery of MIT in VO2. The migration of the oxygen ions is evidenced in a combination of transport measurement, structural characterization and first-principles calculations. This approach of chemically-induced oxygen migration using a water-dissolvable adjacent layer could be useful for advanced electronic and iontronic devices and studying oxygen stoichiometry effects on the MIT. Copyright © 2021, The Authors. All rights reserved.

关键词： Vanadium dioxide

SVTest: general purpose software for testing weakly random sources with exemplary application to seismic data analysis enabling quantum amplification

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arXiv 2025年

作者： Stankiewicz, Maciej Salazar, Roberto Czechlewski, Mikolaj Jensen, Alejandra Muñoz Morales-Yáñez, Catalina Sakarya, Omer Carrasco, Julio Viveros Horodecki, Karol Institute of Informatics Faculty of Mathematics Physics and Informatics University of Gdańsk Wita Stwosza 57 Gdańsk80-308 Poland University of Malta MsidaMSD 2080 Malta Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Kraków30-348 Poland Institute of Informatics National Quantum Information Centre Faculty of Mathematics Physics and Informatics University of Gdańsk Wita Stwosza 57 Gdańsk80-308 Poland EMGG TerraData Limitada Concepción Chile Department of Geophysics Universidad de Concepción Concepción Chile Department of Civil Engineering Universidad Católica de la Santísima Concepción Concepción Chile

Generating private randomness is essential for numerous applications ranging from security proofs to online banking. Consequently, the capacity of quantum devices to amplify the privacy of a weak source of randomness, in cases unattainable by classical methods, constitutes a practical advantage. One of the theoretical models of such weak sources are the so-called Santha-Vazirani (SV) sources;however, finding natural sources satisfying the SV model is a paramount challenge. In this article, we take three significant steps on the way to simplify this hard task. We begin with an in-depth analysis of the mathematical background for estimating the quality of a weak randomness source by providing a set of axioms that systematize the possible approaches to such estimation. We then develop software (SVTest) to estimate the parameter characterizing the source’s randomness. The software is general-purpose, i.e., it can test the randomness of any target sequence of bits. Later, we apply the software to test seismic events (earthquakes and local noise) as potential sources of randomness. Our results demonstrate that seismic phenomena are possible sources of randomness, depending on the choice of discretization. Therefore, our work provides strong evidence of the potential of geophysical phenomena as a source of cryptographic resources, building an unprecedented bridge between both fields. Copyright © 2025, The Authors. All rights reserved.

关键词： Seismic response

Multi-level graph convolutional network with automatic graph learning for hyperspectral image classification

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arXiv 2020年

作者： Wan, Sheng Gong, Chen Pan, Shirui Yang, Jie Yang, Jian PCA Lab Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Jiangsu Key Laboratory of Image Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai200240 China Faculty of Information Technology Monash University ClaytonVIC3800 Australia

Nowadays, deep learning methods, especially the Graph Convolutional Network (GCN), have shown impressive performance in hyperspectral image (HSI) classification. However, the current GCN-based methods treat graph construction and image classification as two separate tasks, which often results in suboptimal performance. Another defect of these methods is that they mainly focus on modeling the local pairwise importance between graph nodes while lack the capability to capture the global contextual information of HSI. In this paper, we propose a Multi-level GCN with Automatic Graph Learning method (MGCN-AGL) for HSI classification, which can automatically learn the graph information at both local and global levels. By employing attention mechanism to characterize the importance among spatially neighboring regions, the most relevant information can be adaptively incorporated to make decisions, which helps encode the spatial context to form the graph information at local level. Moreover, we utilize multiple pathways for local-level graph convolution, in order to leverage the merits from the diverse spatial context of HSI and to enhance the expressive power of the generated representations. To reconstruct the global contextual relations, our MGCN-AGL encodes the long range dependencies among image regions based on the expressive representations that have been produced at local level. Then inference can be performed along the reconstructed graph edges connecting faraway regions. Finally, the multi-level information is adaptively fused to generate the network output. In this means, the graph learning and image classification can be integrated into a unified framework and benefit each other. Extensive experiments have been conducted on three real-world hyperspectral datasets, which are shown to outperform the state-of-the-art methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Image classification