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arXiv 2020年

作者： Xu, Kaijie Pedrycz, Witold Li, Zhiwu School of Electro-Mechanical Engineering Xidian University Xi’an710071 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Department of remote sensing science and technology School of Electronic Engineering Xidian University Xi’an710071 China Systems Research Institute Polish Academy of Sciences Warsaw Poland Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia Institute of Systems Engineering Macau University of Science and Technology 999078 China

Information granules have been considered to be the fundamental constructs of Granular Computing (GrC). As a useful unsupervised learning technique, Fuzzy C-Means (FCM) is one of the most frequently used methods to construct information granules. The FCM-based granulation-degranulation mechanism plays a pivotal role in GrC. In this paper, to enhance the quality of the degranulation (reconstruction) process, we augment the FCM-based degranulation mechanism by introducing a vector of fuzzification factors (fuzzification factor vector) and setting up an adjustment mechanism to modify the prototypes and the partition matrix. The design is regarded as an optimization problem, which is guided by a reconstruction criterion. In the proposed scheme, the initial partition matrix and prototypes are generated by the FCM. Then a fuzzification factor vector is introduced to form an appropriate fuzzification factor for each cluster to build up an adjustment scheme of modifying the prototypes and the partition matrix. With the supervised learning mode of the granulation-degranulation process, we construct a composite objective function of the fuzzification factor vector, the prototypes and the partition matrix. Subsequently, the particle swarm optimization (PSO) is employed to optimize the fuzzification factor vector to refine the prototypes and develop the optimal partition matrix. Finally, the reconstruction performance of the FCM algorithm is enhanced. We offer a thorough analysis of the developed scheme. In particular, we show that the classical FCM algorithm forms a special case of the proposed scheme. Experiments completed for both synthetic and publicly available datasets show that the proposed approach outperforms the generic data reconstruction approach. Copyright © 2020, The Authors. All rights reserved.

关键词： Granulation

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Residual-driven fuzzy C-Means clustering for image segmentation

arXiv

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arXiv 2020年

作者： Wang, Cong Pedrycz, Witold Li, Zhi Wu Zhou, Meng Chu School of Electro-Mechanical Engineering Xidian University Xi'an710071 China Department of Electrical and Computer Engineering University of Alberta EdmontonAB T6R 2V4 Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia School of Electro-Mechanical Engineering Xidian University Xi'an710071 China Institute of Systems Engineering Macau University of Science and Technology Macau China Institute of Systems Engineering Macau University of Science and Technology Macau999078 China Helen and John C. Hartmann Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

Due to its inferior characteristics, an observed (noisy) image's direct use gives rise to poor segmentation results. Intuitively, using its noise-free image can favorably impact image segmentation. Hence, the accurate estimation of the residual between observed and noise-free images is an important task. To do so, we elaborate on residual-driven Fuzzy C-Means (FCM) for image segmentation, which is the first approach that realizes accurate residual estimation and leads noise-free image to participate in clustering. We propose a residual-driven FCM framework by integrating into FCM a residual-related fidelity term derived from the distribution of different types of noise. Built on this framework, we present a weighted 2-norm fidelity term by weighting mixed noise distribution, thus resulting in a universal residual-driven FCM algorithm in presence of mixed or unknown noise. Besides, with the constraint of spatial information, the residual estimation becomes more reliable than that only considering an observed image itself. Supporting experiments on synthetic, medical, and real-world images are conducted. The results demonstrate the superior effectiveness and efficiency of the proposed algorithm over existing FCM-related *** Codes 62H30 Copyright © 2020, The Authors. All rights reserved.

关键词： Image segmentation

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Kullback-Leibler divergence-based Fuzzy C-Means clustering incorporating morphological reconstruction and wavelet frames for image segmentation

arXiv

引用

arXiv 2020年

作者： Wang, Cong Pedrycz, Witold Li, ZhiWu Zhou, MengChu School of Electro-Mechanical Engineering Xidian University Xi’an710071 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia Institute of Systems Engineering Macau University of Science and Technology Macau999078 China Helen and John C. Hartmann Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

Although spatial information of images can usually enhance the robustness of the conventional Fuzzy C-Means (FCM) algorithm, it greatly increases the computational costs for image segmentation. To achieve a sound trade-off between the segmentation performance and the speed of clustering, we come up with a Kullback-Leibler divergence-based FCM algorithm by incorporating a tight wavelet frame transform and a morphological reconstruction operation. To enhance FCM’s robustness, an observed image is first filtered by using the morphological reconstruction. A tight wavelet frame system is employed to decompose the observed and filtered images so as to form their feature sets. Considering these feature sets as data of clustering, an modified FCM algorithm is proposed, which introduces a Kullback-Leibler divergence term in the partition matrix into its objective function. The Kullback-Leibler divergence term aims to make membership degrees of each image pixel closer to those of its neighbors, which brings that the membership partition becomes more suitable and the parameter setting of FCM becomes simplified. On the basis of the obtained partition matrix and prototypes, the segmented feature set is reconstructed by minimizing the inverse process of the modified objective function. To modify abnormal features produced in the reconstruction process, each reconstructed feature is reassigned to the closest prototype. As a result, the segmentation accuracy of Kullback-Leibler divergence-based FCM is further improved. What’s more, the segmented image is reconstructed by using a tight wavelet frame reconstruction operation. Finally, supporting experiments coping with synthetic, medical and color images are reported. Experimental results exhibit that the proposed algorithm works well and comes with better segmentation performance than other comparative algorithms. Moreover, the proposed algorithm requires less time than most of the FCM-related *** codes 62H30 Copyright ©

关键词： Image segmentation

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G-image Segmentation: Similarity-preserving fuzzy C-means with spatial information constraint in wavelet space

arXiv

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arXiv 2020年

作者： Wang, Cong Pedrycz, Witold Li, ZhiWu Zhou, MengChu Ge, Shuzhi Sam School of Electro-Mechanical Engineering Xidian University Xi’an710071 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada School of Electro-Mechanical Engineering Xidian University Xi’an710071 China Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia School of Electro-Mechanical Engineering Xidian University Xi’an710071 China Institute of Systems Engineering Macau University of Science and Technology China Institute of Systems Engineering Macau University of Science and Technology 999078 China Department of Electrical and Computer Engineering National University of Singapore Singapore117576 Singapore Institute of Future Qingdao University Qingdao266071 China

G-images refer to image data defined on irregular graph domains. This work elaborates a similarity-preserving Fuzzy C-Means (FCM) algorithm for G-image segmentation and aims to develop techniques and tools for segmenting G-images. To preserve the membership similarity between an arbitrary image pixel and its neighbors, a Kullback-Leibler divergence term on membership partition is introduced as a part of FCM. As a result, similarity-preserving FCM is developed by considering spatial information of image pixels for its robustness enhancement. Due to superior characteristics of a wavelet space, the proposed FCM is performed in this space rather than Euclidean one used in conventional FCM to secure its high robustness. Experiments on synthetic and real-world G-images demonstrate that it indeed achieves higher robustness and performance than the state-of-the-art FCM algorithms. Moreover, it requires less computation than most of *** Codes 62H30 Copyright © 2020, The Authors. All rights reserved.

关键词： Image segmentation

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Assessing Trustworthy AI in Times of COVID-19: Deep Learning for Predicting a Multiregional Score Conveying the Degree of Lung Compromise in COVID-19 Patients

IEEE Transactions on Technology and Society

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IEEE Transactions on Technology and Society 2022年第4期3卷 272-289页

作者： Allahabadi, Himanshi Amann, Julia Balot, Isabelle Beretta, Andrea Binkley, Charles Bozenhard, Jonas Bruneault, Frederick Brusseau, James Candemir, Sema Cappellini, Luca Alessandro Chakraborty, Subrata Cherciu, Nicoleta Cociancig, Christina Coffee, Megan Ek, Irene Espinosa-Leal, Leonardo Farina, Davide Fieux-Castagnet, Genevieve Frauenfelder, Thomas Gallucci, Alessio Giuliani, Guya Golda, Adam Van Halem, Irmhild Hildt, Elisabeth Holm, Sune Kararigas, Georgios Krier, Sebastien A. Kuhne, Ulrich Lizzi, Francesca Madai, Vince I. Markus, Aniek F. Masis, Serg Mathez, Emilie Wiinblad Mureddu, Francesco Neri, Emanuele Osika, Walter Ozols, Matiss Panigutti, Cecilia Parent, Brendan Pratesi, Francesca Moreno-Sanchez, Pedro A. Sartor, Giovanni Savardi, Mattia Signoroni, Alberto Sormunen, Hanna-Maria Spezzatti, Andy Srivastava, Adarsh Stephansen, Annette F. Theng, Lau Bee Tithi, Jesmin Jahan Tuominen, Jarno Umbrello, Steven Vaccher, Filippo Vetter, Dennis Westerlund, Magnus Wurth, Renee Zicari, Roberto V. Ey Netherlands Enterprise Intelligence Department Amsterdam1083 HP Netherlands Eth Zurich Health Ethics and Policy Lab Department of Health Sciences and Technology Zürich8092 Switzerland Center for Diplomatic and Strategic Studies Postgraduate Studies in Diplomacy and International Relations Paris75015 France Pisa56124 Italy Hackensack Meridian Health Bioethics Center EdisonNJ08820 United States University of Oxford Faculty of Philosophy OxfordOX2 6GG United Kingdom Collège André- Laurendeau Philosophie Department MontrealQCH8N 2J4 Canada Université du Québec À Montréal École des Médias MontrealQCH2L 2C4 Canada Pace University Philosophy Department New YorkNY10038 United States The Ohio State University Wexner Medical Center Department of Radiology ColumbusOH43210 United States Humanitas Research Hospital Department of Radiology Milan20089 Italy Humanitas University Department of Biomedical Sciences Milan20089 Italy University of New England Faculty of Science Agriculture Business and Law ArmidaleNSW2351 Australia University of Technology Sydney Faculty of Engineering and Information Technology SydneyNSW2007 Australia Scuola Superiore Sant'Anna European Centre of Excellence on the Regulation of Robotics and Ai Pisa56127 Italy University of Bremen Group of Computer Architecture Bremen28359 Germany New York University Grossman School of Medicine Division of Infectious Diseases and Immunology Department of Medicine New YorkNY10016 United States Digital Institute Ai Research Section Stockholm16731 Sweden Arcada University of Applied Sciences Department of Business Management and Analytics Helsinki00550 Finland University of Brescia Radiological Sciences and Public Health Department of Medical and Surgical Specialties Brescia25121 Italy Sncf Reseau Sa Ethique Groupe La Plaine93418 France Institute of Diagnostic and Interventional Radiology University Hospital Zurich Zürich8091 Switzerland Eindhoven University of Tech

This article's main contributions are twofold: 1) to demonstrate how to apply the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare and 2) to investigate the research question of what does 'trustworthy AI' mean at the time of the COVID-19 pandemic. To this end, we present the results of a post-hoc self-assessment to evaluate the trustworthiness of an AI system for predicting a multiregional score conveying the degree of lung compromise in COVID-19 patients, developed and verified by an interdisciplinary team with members from academia, public hospitals, and industry in time of pandemic. The AI system aims to help radiologists to estimate and communicate the severity of damage in a patient's lung from Chest X-rays. It has been experimentally deployed in the radiology department of the ASST Spedali Civili clinic in Brescia, Italy, since December 2020 during pandemic time. The methodology we have applied for our post-hoc assessment, called Z-Inspection®, uses sociotechnical scenarios to identify ethical, technical, and domain-specific issues in the use of the AI system in the context of the pandemic. © 2020 IEEE.

关键词： COVID-19

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A Study on Computational Methods of the Logistic Map over Integers for a Pseudorandom Number Generator 15

A Study on Computational Methods of the Logistic Map over In...

引用

15th International Symposium on Information Theory and Its Applications, ISITA 2018

作者： Araki, Shunsuke Muraoka, Hideyuki Miyazaki, Takeru Uehara, Satoshi Kakizaki, Kenrichi Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Iizuka Fukuoka820-8502 Japan Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Iizuka Fukuoka820-8502 Japan Faculty of Environmental Engineering University of Kitakyushu 1-1 Hibikino Wakamatsu Kitakyushu Fukuoka808-0135 Japan

ISBN: (纸本)9784885523182

In this paper, we will discuss properties of different computational methods of the logistic map over integers. We will give four computational methods of the map in order to implement the map on a computer with limited memories, and then will evaluate average processing times and lengths of sequences generated by these methods. By these results, we will provide a constructive use of these four computational methods of the logistic map over integers for a design of the pseudorandom number generator. © 2018 IEICE.

关键词： Computational methods

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Valley population of donor states in highly strained silicon

arXiv

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arXiv 2021年

作者： Voisin, B. Ng, K.S.H. Salfi, J. Usman, M. Wong, J.C. Tankasala, A. Johnson, B.C. McCallum, J.C. Hutin, L. Bertrand, B. Vinet, M. Valanoor, N. Simmons, M.Y. Rahman, R. Hollenberg, L.C.L. Rogge, S. Silicon Quantum Computing SydneyNSW2052 Australia School of Physics Sydney The University of New South Wales SydneyNSW2052 Australia Centre for Quantum Computation and Communication Technology School of Physics The University of New South Wales SydneyNSW2052 Australia 5. Physikalisches Institut and Center for Integrated Quantum Science and Technology Universität Stuttgart Stuttgart70569 Germany Department of Electrical and Computer Engineering University of British Columbia VancouverBCV6T 1Z4 Canada Centre for Quantum Computation and Communication Technology School of Physics The University of Melbourne ParkvilleVIC3010 Australia School of Computing and Information Systems Faculty of Engineering and Information Technology The University of Melbourne ParkvilleVIC3010 Australia School of Materials Science and Engineering The University of New South Wales SydneyNSW2052 Australia Electrical and Computer Engineering Department Purdue University West LafayetteIN United States Quantum Photonics Laboratory School of Engineering RMIT University MelbourneVIC3000 Australia Université Grenoble Alpes CEA LETI Grenoble38000 France

Strain is extensively used to controllably tailor the electronic properties of materials. In the context of indirect band-gap semiconductors such as silicon, strain lifts the valley degeneracy of the six conduction band minima, and by extension the valley states of electrons bound to phosphorus donors. Here, single phosphorus atoms are embedded in an engineered thin layer of silicon strained to 0.8% and their wave function imaged using spatially resolved spectroscopy. A prevalence of the out of plane valleys is confirmed from the real-space images, and a combination of theoretical modelling tools is used to assess how this valley repopulation effect can yield isotropic exchange and tunnel interactions in the xy-plane relevant for atomically precise donor qubit devices. Finally, the residual presence of in-plane valleys is evidenced by a Fourier analysis of both experimental and theoretical images, and atomistic calculations highlight the importance of higher orbital excited states to obtain a precise relationship between valley population and strain. Controlling the valley degree of freedom in engineered strained epilayers provides a new competitive asset for the development of donor-based quantum technologies in silicon. Copyright © 2021, The Authors. All rights reserved.

关键词： Landforms

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Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange

arXiv

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arXiv 2024年

作者： Evans, Matthew L. Bergsma, Johan Merkys, Andrius Andersen, Casper W. Andersson, Oskar B. Beltrán, Daniel Blokhin, Evgeny Boland, Tara M. Balderas, Rubén Castañeda Choudhary, Kamal Díaz, Alberto Díaz García, Rodrigo Domínguez Eckert, Hagen Eimre, Kristjan Montero, María Elena Fuentes Krajewski, Adam M. Mortensen, Jens Jørgen Duarte, José Manuel Nápoles Pietryga, Jacob Qi, Ji de Jesús Trejo Carrillo, Felipe Vaitkus, Antanas Yu, Jusong Zettel, Adam de Castro, Pedro Baptista Carlsson, Johan Cerqueira, Tiago F.T. Divilov, Simon Hajiyani, Hamidreza Hanke, Felix Jose, Kevin Oses, Corey Riebesell, Janosh Schmidt, Jonathan Winston, Donald Xie, Christen Yang, Xiaoyu Bonella, Sara Botti, Silvana Curtarolo, Stefano Draxl, Claudia Cobas, Luis Edmundo Fuentes Hospital, Adam Liu, Zi-Kui Marques, Miguel A.L. Marzari, Nicola Morris, Andrew J. Ong, Shyue Ping Orozco, Modesto Persson, Kristin A. Thygesen, Kristian S. Wolverton, Chris Scheidgen, Markus Toher, Cormac Conduit, Gareth J. Pizzi, Giovanni Gražulis, Saulius Rignanese, Gian-Marco Armiento, Rickard Chemin des Étoiles 8 Louvain-la-Neuve1348 Belgium Matgenix SRL 185 Rue Armand Bury Gozée6534 Belgium École Polytechnique Fédérale de Lausanne Avenue de Forel 3 Lausanne1015 Switzerland Institute of Biotechnology Life Sciences Center Vilnius University Sauletekio av. 7 VilniusLT-10257 Lithuania SINTEF P.O. Box 4760 Torgarden TrondheimNO-7465 Norway Materials Design and Informatics unit Department of Physics Chemistry and Biology Linköping University Sweden Baldiri i Reixac 10-12 Barcelona08028 Spain Tilde Materials Informatics Straßmannstraße 25 Berlin10249 Germany Materials Platform for Data Science Sepapaja 6 Tallinn15551 Estonia Computational Atomic-Scale Materials Design Technical University of Denmark Kgs. Lyngby Denmark Av. Miguel de Cervantes 120 Complejo Industrial Chihuahua Chihuahua Chih. 31136 Mexico Material Measurement Laboratory National Institute of Standards and Technology GaithersburgMD20899 United States Department of Mechanical Engineering and Materials Science Duke University DurhamNC27708 United States Center for Extreme Materials Duke University DurhamNC27708 United States École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Universidad Autónoma de Chihuahua Facultad de Ciencias Quimicas Chihuahua31125 Mexico Department of Materials Science and Engineering The Pennsylvania State University University ParkPA16802 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of NanoEngineering University of California 9500 Gilman Drive La Jolla San DiegoCA92093-0448 United States National Institute for Materials Science 1-2-1 Sengen Ibaraki Tsukuba305-0047 Japan Dassault Systèmes Germany GmbH Am Kabellager 11-13 Cologne51063 Germany CFisUC Department of Physics University of Coimbra Rua Larga Coimbra3004-516 Portugal Dassault Systèmes 22 Science Park CB4 0FJ United Kingdom Theory of Condensed Matter Cavendis

The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development. © 2024, CC BY.

关键词： Electronic data interchange

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The adoption of IoT technology in the Malaysian manufacturing industry

引用

AIP Conference Proceedings 2021年第1期2355卷

作者： Toong Hai Sam Whee Yen Wong Zainab Lawan Gwadabe Rajani Balakrishnan Ravindra Poopalaselvam Anbia Adam Kian Sek Tee 1Faculty of Business Communications and Law (FOBCAL) INTI International University Persiaran Perdana BBN Putra Nilai Nilai Negeri Sembilan 71800 MALAYSIA 2Department of Internet Engineering & Computer Science LKC Universiti Tunku Abdul Rahman Faculty of Engineering and Science Jalan Sungai Long Bandar Sungai Long 43000 Kajang Selangor MALAYSIA 3Faculty of Mechanical and Manufacturing Engineering Universiti Tun Hussein Onn Malaysia Parit Raja Batu Pahat Johor 86400 MALAYSIA 4Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Parit Raja Batu Pahat Johor 86400 MALAYSIA

For the global market to achieve a competitive advantage, the companies in the manufacturing industries are working tirelessly to develop new products and services to meet the people’s demands. As a result, manufacturing companies worldwide are using highly advanced technologies to increase efficiency and effectiveness. Even though these high-end technologies are used in factories, they are not as closely integrated as they should be. This paper aims to review the impact of the Internet of Things (IoT) adoption in Malaysia’s manufacturing industry. The study conducted a rigorous review of the literature on (IoT) in the manufacturing industry. The paper reveals that there is a wide coverage and usage of IoT in the manufacturing industries even though the integration of IoT is at a very early stage. Therefore, the study recommended developing good infrastructures and strategies that will support the use of IoT. This will improve the efficiency and effectiveness of this highly relevant and essential sector.

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Prototype Design of Playback and Search System for Lecture Video Content using Google Cloud API

引用

Procedia computer science 2019年 159卷 1517-1526页

作者： Yoshimasa Ohnishi Shin’nosuke Yamaguchi Yoshiki Shimoikura Kazunori Nishino Hideki Kondo Akihiro Hayashi Kyushu Institute of Technology Learning and Teaching Center 680-4 Kawazu Iizuka Fukuoka 820-8502 Japan Kyushu Institute of Technology Faculty of Computer Science and Systems Engineering 680-4 Kawazu Iizuka Fukuoka 820-8502 Japan Kyushu Institute of Technology Institute of Liberal Arts 680-4 Kawazu Iizuka Fukuoka 820-8502 Japan

Recently, it has become possible to easily use video teaching materials in lectures and exercises using high-performance information terminals. In this study, we design and develop playback functions for lecture videos as learning support using a learning management system. The main feature of the proposed system generates keywords from handwritten characters and lecture speech so that learners can search for playback positions related to keywords. Additionally, it becomes possible to create a highly maintainable system in a short development period using speech recognition and still-image recognition functions available on the internet. In this paper, we describe our prototype implementation and present the results of our initial evaluation. The results demonstrate that, regarding the playback of a lecture video, it is possible to use the keyword search function 20–40 min after the lecture video is released. Moreover, we implemented a playback system using a block function on Moodle so that other teaching material in the course could be viewed simultaneously.

关键词： keyword search handwritten characters lecture video internet service Moodle

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