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International Conference on Cyber and IT Service Management (CITSM)

作者： Diana Teresia Spits Warnars Leonardo Primadala Putra Logiansa Harco Leslie Hendric Spits Warnars Wiranto Herry Utomo School of Information Systems Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Computing President University Bekasi Indonesia

Special need is a person who need assistance for their disabilities which include medical, physical, mental or psychological such as person with autism, down syndrome, dyslexia, Attention Deficit Hyperactivity Disorder (ADHD), multiple sclerosis, schizophrenia, cystic fibrosis, cerebral palsy, muscular dystrophy, blindness, deafness, epilepsy, chronic asthma and so on. In this proposed research idea about intelligent E-commerce for special needs, we limited to four types of difficulties such as hearing difficulty, vision difficulty, language difficulty, and learning difficulty. In this paper, we interest in those special needs persons who can use e-commerce and how to model a system that can help them to joy and easy to join with e-commerce. For some, this intelligent e-commerce is not only for shopping only but will become part of their healing for special needs in order to engage with daily human activities and increase their daily confidence in life. This paper also a preliminary investigation that can be used for Ph.D. or Doctoral research degree who is interested in building e-commerce framework for people with a special need or disability.

关键词： Companies Machine learning Speech recognition Tools Pricing

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Proposal of IoT based Learning Material and its Management System for Primary/Secondary Education 19

Proposal of IoT based Learning Material and its Management S...

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Proceedings of the 3rd International Conference on Digital Technology in Education

作者： Takafumi Todoriki Mizue Kayama Nobuyuki Tachi Takashi Nagai Takao Futagami Takehiko Asuke Graduate School of Science and Technology Shinshu University Nagano Nagano Japan Shinshu University Nagano Nagano Japan Nagoya University Center for Embedded Computing Systems Furotyou Nagoya Aichi Japan Institute of Technologists Department of Mechanical and Production Engineering Maeya Gyoda Saitama Japan TOYO Corporation Chuo-ku Tokyo Japan Ina City Takato Junior Highschool Takato Machi Higashi Ina Nagano Japan

ISBN: (纸本)9781450372206

The purpose of this study was lesson support by building a system which IoT based learning material and using it. This system is assumed to use the regular curriculum of primary and secondary education in Japan. We previously examined that apply IoT technology to learning material. That learning material use when experiment with a measurement. And, we designed its management system. Here we describe the outline of IoT based learning material and its management system. And we report about concrete IoT based learning material.

关键词： Learning material STEM Design of System IoT

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Correction to: Social influence and unfollowing accelerate the emergence of echo chambers

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Journal of Computational Social Science 2022年第2期5卷 1779-1779页

作者： Sasahara, Kazutoshi Chen, Wen Peng, Hao Ciampaglia, Giovanni Luca Flammini, Alessandro Menczer, Filippo Graduate School of Informatics Nagoya University Nagoya Japan JST PRESTO Saitama Japan Center for Complex Networks and Systems Research Indiana University Bloomington Bloomington USA Luddy School of Informatics Computing and Engineering Indiana University Bloomington USA School of Information University of Michigan Ann Arbor USA Network Science Institute Indiana University Bloomington USA Department of Computer Science and Engineering University of South Florida Tampa USA

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Sign language recognition using the fusion of image and hand landmarks through multi-headed convolutional neural network

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Scientific reports 2023年第1期13卷 16975页

作者： Refat Khan Pathan Munmun Biswas Suraiya Yasmin Mayeen Uddin Khandaker Mohammad Salman Ahmed A F Youssef Department of Computing and Information Systems School of Engineering and Technology Sunway University 47500 Bandar Sunway Selangor Malaysia. Department of Computer Science and Engineering BGC Trust University Bangladesh Chittagong 4381 Bangladesh. Department of Computer and Information Science Graduate School of Engineering Tokyo University of Agriculture and Technology Koganei Tokyo 184-0012 Japan. Centre for Applied Physics and Radiation Technologies School of Engineering and Technology Sunway University 47500 Bandar Sunway Selangor Malaysia. mayeenk@sunway.edu.my. Faculty of Graduate Studies Daffodil International University Daffodil Smart City Birulia Savar Dhaka 1216 Bangladesh. mayeenk@sunway.edu.my. College of Engineering and Technology American University of the Middle East Egaila Kuwait.

Sign Language Recognition is a breakthrough for communication among deaf-mute society and has been a critical research topic for years. Although some of the previous studies have successfully recognized sign language, it requires many costly instruments including sensors, devices, and high-end processing power. However, such drawbacks can be easily overcome by employing artificial intelligence-based techniques. Since, in this modern era of advanced mobile technology, using a camera to take video or images is much easier, this study demonstrates a cost-effective technique to detect American Sign Language (ASL) using an image dataset. Here, "Finger Spelling, A" dataset has been used, with 24 letters (except j and z as they contain motion). The main reason for using this dataset is that these images have a complex background with different environments and scene colors. Two layers of image processing have been used: in the first layer, images are processed as a whole for training, and in the second layer, the hand landmarks are extracted. A multi-headed convolutional neural network (CNN) model has been proposed and tested with 30% of the dataset to train these two layers. To avoid the overfitting problem, data augmentation and dynamic learning rate reduction have been used. With the proposed model, 98.981% test accuracy has been achieved. It is expected that this study may help to develop an efficient human-machine communication system for a deaf-mute society.

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Simulating the shastry-sutherland ising model using quantum annealing

arXiv

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arXiv 2020年

作者： Kairys, Paul King, Andrew D. Ozfidan, Isil Boothby, Kelly Raymond, Jack Banerjee, Arnab Humble, Travis S. Bredesen Center for Interdisciplinary Research and Graduate Education University of Tennessee KnoxvilleTN United States Quantum Computing Institute Oak Ridge National Laboratory Oak RidgeTN United States D-Wave Systems Inc. BurnabyBC Canada Neutron Sciences Division Oak Ridge National Laboratory Oak RidgeTN United States Department of Physics and Astronomy Purdue University West LafayetteIN United States

Frustration represents an essential feature in the behavior of magnetic materials when constraints on the microscopic Hamiltonian cannot be satisfied simultaneously. This gives rise to exotic phases of matter including spin liquids [1], spin ices [2], and stripe phases [3]. Here we demonstrate an approach to understanding the microscopic effects of frustration by computing the phases of a 468-spin Shastry-Sutherland Ising Hamiltonian using a quantum annealer. Our approach uses mean-field boundary conditions to mitigate effects of finite size and defects alongside an iterative quantum annealing protocol to simulate statistical physics. We recover all phases of the Shastry-Sutherland Ising model - including the well-known fractional magnetization plateau - and the static structure factor characterizing the critical behavior at these transitions. These results establish quantum annealing as an emerging method in understanding the effects of frustration on the emergence of novel phases of matter and pave the way for future comparisons with real experiments. Copyright © 2020, The Authors. All rights reserved.

关键词： Ising model

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Robot Hand Interaction Using Plastic Deformation Control with Inner Position Loop

Robot Hand Interaction Using Plastic Deformation Control wit...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Kenichi Murakami Koki Ishimoto Taku Senoo Masatoshi Ishikawa Data Science Research Division Information Technology Center The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo Japan Department of Information Physics and Computing The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo Japan Electrical Systems and Control Engineering Program Graduate School of Advanced Science and Engineering Hiroshima University 1-4-1 Kagamiyama Higashi-Hiroshima City Hiroshima Japan

ISBN: (数字)9781728167947

ISBN: (纸本)9781728167954

In this study, the inner position loop addition for plastic deformation control of the error robustness of the model and actual parameters is proposed. The inner position loop is a type of position feedback control based on the estimation of model parameters and dynamics of robots. This position control system with proportional and derivative gains modifies the trajectory of the end effector close to the desired trajectory. The robustness of the proposed control scheme is evaluated by comparing it with plastic deformation control without an inner position loop in both simulation and actual environments. Finally, the stable reaction with the proposed control is demonstrated for the case where a human pushes the robot finger.

关键词： Strain Plastics Force Deformable models Robots Friction Trajectory

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Identifying the active ingredients in payment for performance programmes using system dynamics modelling

SSM - health systems

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SSM - health systems 2025年 4卷 100040页

作者： Rachel Cassidy Agnes Rwashana Semwanga Peter Binyaruka Karl Blanchet Neha S Singh John Maiba Josephine Borghi Department of Global Health and Development London School of Hygiene and Tropical Medicine 15-17 Tavistock Place London WC1H 9SH UK. KPM Center for Public Management University of Bern Bern 3012 Switzerland. Swiss Institute for Translational and Entrepreneurial Medicine Bern 3010 Switzerland. Information Systems Department College of Computing and Information Sciences Makerere University P.O. Box 7062 Kampala Uganda. Ifakara Health Institute PO Box 78373 Dar es Salaam 78373 Tanzania. Geneva Centre of Humanitarian Studies University of Geneva and the Graduate Institute Rue Rothschild 22 Genève 1211 Switzerland.

Payment for performance (P4P) is not a uniform intervention, with programme effect dependent on several interconnected factors. In this study, a system dynamics model was developed to explore the pathways to improved outcomes and how changes in the design, implementation and context of a P4P programme affected maternal and child health (MCH) service delivery outcomes in Tanzania. A previously developed causal loop diagram of the programme effects was used to inform model development, with further data sources (including an impact evaluation of programme, health surveys, stakeholder feedback and relevant literature) used to build the model. A number of pathways were identified to improved services under P4P, with increased availability of drugs underpinning the content of care outcome (intermittent preventative treatment during ANC), which together with increased supervision, enhanced health worker motivation. This in turn increased perceived quality of care at the facility which improved the coverage of services outcome (facility-based deliveries), and with increased outreach, increased awareness of services also boosted demand. Minor delays in payment reduced provider purchasing power for medicines, with severe delays driving erosion of provider trust and motivation for programme participation. Allocating a larger share of funds for facility operations can enhance performance effects, particularly for those services that rely on efficient drug administration. Contextual factors including limited baseline provision of essential medications, lower community awareness of facility services and dispersed/distant populations reduced programme effect. This paper demonstrates the feasibility and the potential of such models to inform the design of effective health system interventions.

关键词： Evaluation Health systems Maternal and child health Payment for performance Primary care System dynamics modelling Tanzania

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An Ultra-Scalable Blockchain Platform for Universal Asset Tokenization: Design and Implementation

TechRxiv

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TechRxiv 2022年

作者： Buldas, Ahto Draheim, Dirk Gault, Mike Laanoja, Risto Nagumo, Takehiko Saarepera, Märt Shah, Syed Attique Simm, Joosep Steiner, Jamie Tammet, Tanel Truu, Ahto Centre for Digital Forensics and Cyber Security Tallinn University of Technology Akadeemia tee 15a Tallinn12618 Estonia Information Systems Group Tallinn University of Technology Akadeemia tee 15a Tallinn12618 Estonia Guardtime Avenue d’Ouchy 4 Lausanne1006 Switzerland Guardtime A. H. Tammsaare tee 60 Tallinn11316 Estonia Mitsubishi UFJ Research and Consulting 5-11-2 Toranomon Minato City Tokyo105-8501 Japan Graduate School of Management Kyoto University Yoshida Honmachi Sakyo-ku Kyoto-shi Kyoto606-8501 Japan Martest Research Pärnu mnt 160a Tallinn11317 Estonia School of Computing and Digital Technology Birmingham City University Millennium Point BirminghamB4 7XG United Kingdom Applied Artificial Intelligence Group Tallinn University of Technology Akadeemia tee 15a Tallinn12618 Estonia

Since its introduction with Bitcoin in 2009, blockchain technology has received tremendous attention by academia, industry, politics and media alike, in particular, through extended blockchain-based visions such as smart contracts, decentralized finance, and, most recently, Web3. The critical prerequisite for any such blockchain-based vision to be turned into reality is uncapped scalability. Furthermore, and equally important, blockchain technology needs to transcend the stage of specialized tokens into an adaptive, heterogeneous tokenization platform. In this paper, we explain the Alphabill family of technologies that addresses both unlimited scalability and unrestricted adaptivity. We deliver a sharded blockchain technology with unlimited scalability and performance, called KSI Cash, which is based on a new form of electronic money scheme, the bill scheme. We present performance tests of KSI Cash that we have conducted with the European Central Bank and a group of eight national central banks from the Eurosystem in order to assess the technological feasibility of a digital euro, showing the system operating with 100 million wallets and 15 thousand transactions per second (under simulation of realistic usage), having an estimated carbon footprint of 0.0001g CO2 per transaction (Bitcoin = 100 kg and more);furthermore, showing the system operating with up to 2 million payment orders per second, an equivalent of more than 300,000 transactions per second (in a laboratory setting with the central components of KSI Cash), scaling linearly in terms of the number of deployed shards. We explain, in detail, the key concepts that unlock this performance (i.e., the concepts of the bill money scheme). The results provide evidence that the scalability of our technology is unlimited in both permissioned and permissionless scenarios, resulting into the Alphabill Money technology. Next, we contribute the architecture of a universal tokenization platform that allows for universal as

关键词： Blockchain

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FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

arXiv

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arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

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Front Cover: Micrometer-Sized Liposome-Based systems: A Hierarchical Breakdown (ChemsystemsChem 3/2025)

ChemSystemsChem

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ChemsystemsChem 2025年第3期7卷

作者： Prof. Dr. Shogo Hamada Dr. Hironori Sugiyama Prof. Dr. Yiting Zhang Prof. Dr. Shoji Iwabuchi Soichiro Hiroi Toshiki Maruyama Yuktesh Balaji Sota Kumagai Prof. Dr. Satoshi Murata Prof. Dr. Taro Toyota Department of Computer Science School of Computing & Department of Systems and Control Engineering School of Engineering Institute of Science Tokyo 4259 Nagatsuta-cho Midori-ku Yokohama-city Kanagawa 226-8501 Japan These authors contributed equally. Department of Applied Chemistry Graduate School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan Department of Chemistry College of Science Rikkyo University 3-34-1 Nishi-Ikebukuro Toshima-ku Tokyo 171-8501 Japan Department of Biotechnology and Life Science Tokyo University of Agriculture and Technology 2-24-16 Naka-cho Koganei-shi Tokyo 185-8588 Japan Department of Basic Science Graduate School of Arts and Sciences The University of Tokyo 3-8-1 Komaba Meguro-ku Tokyo 153-8902 Japan Department of Robotics Graduate School of Engineering Tohoku University 6-6-01 Aramaki-Aza Aoba Aoba-ku Sendai Miyagi 980-8579 Japan Universal Biology Institute The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan

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