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Chiral perovskites for room-temperature spin light-emitting diodes

Science Bulletin 2022年第15期67卷 1535-1538页

作者： Wen Su Fanglong Yuan CAS Center for Excellence in Nanoscience National Center for Nanoscience and TechnologyBeijing 100190China Department of Physics Chemistryand Biology(IFM)Linköping UniversityLinköping 58183Sweden Department of Electrical and Computer Engineering University of TorontoToronto M5S 2E8Canada

Light-emitting diodes(LEDs)fabricated based on luminescent materials have revolutionized the full-color display and solid-state lighting technologies[1].Spin LEDs(spin-LEDs)that can emit circularly polarized electroluminescence(CP-EL)show broad promising opto-spintronic applications,including three-dimensional(3D)displays,quantum-based optical computing and information pro-cessing,tomography and encryption[2].

关键词：发光二极管 diodes encryption

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Retraction Note: High performance reconciliation for practical quantum key distribution systems

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Optical and Quantum Electronics 2024年第12期56卷 1-2页

作者： Mao, ao-Kun Li, Qiong Hao, Peng-Lei Abd-El-Atty, Bassem Iliyasu, Abdullah M. Department of Computer Science and Technology Harbin Institute of Technology Harbin China CAS Key Laboratory of Quantum Information University of Science and Technology of China Hefei China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Hefei China Department of Computer Science Faculty of Computers and Information Luxor University Luxor Egypt Electrical Engineering Department College of Engineering Prince Sattam Bin Abdulaziz University Al- Kharj Saudi Arabia School of Computing Tokyo Institute of Technology Yokohama Japan School of Computer Science and Technology Changchun University of Science and Technology Changchun China

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Usability Evaluation of Kids’ Learning Apps

Usability Evaluation of Kids’ Learning Apps

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Business Analytics for Technology and Security (ICBATS), International Conference on

作者： Amer Ibrahim Murad Al-Rajab Khalid Hamid Muhamamd Aqeel Salman Muneer Mehvish Parveen Maryam Saleem College of Computer and Information Technology American University in the Emirates Dubai United Arab Emirates Assistant Professor Computer Scienc and IT College of Engineering Abu Dhabi University Department of Computer Science Superior University Lahore Pakistan Department of Software Engineering Superior University Lahore Pakistan School of Computer Science NCBA&E Lahore Pakistan Applied Science Research Center Applied Science Private University Amman Jordan School of Computer Science NCBAE Lahore Pakistan

The main objective of learning applications is to use modern electronic technologies to impart knowledge, communicate knowledge, and Direct learning models with their learning activities in a timely and effective manner. The preponderance of the apps were designed to up-skill the kids in the fundamentals of letters and numbers. Generally, they were grounded and practice skills in nature, based on a lack of abilities in critical thinking, favoring parrot-fashion skills, and contributing to a deep conceptual comprehension of more specific concepts are unable. By using appropriate evaluation methodologies, the purposed study observes essential characteristics and aspects that affect the usability of interfaces. An evaluation of the app's features will figure out to ensure user contentment. When a kid interacts with a learning interface, the ease of use provided by the interface is validated. Because a large number of the apps were designed to train kids’ fundamentals of alphabetic and numeric. The focus of this research is to see whether self-proclaimed learning apps for kids are built according to developmentally appropriate standards to help kids in formal and informal learning settings develop socially, emotionally, and academically.

关键词： Electronic learning User interfaces Security Usability Standards Business

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RETRACTED ARTICLE: Obstacles Uncovering System for Slender Pathways Using Unmanned Aerial Vehicles with Automatic Image Localization Technique

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International Journal of Computational Intelligence Systems 2023年第1期16卷 1-14页

作者： Selvarajan, Shitharth Manoharan, Hariprasath Khadidos, Alaa O. Shankar, Achyut Khadidos, Adil O. Onyema, Edeh Michael Department of Computer Science Kebri Dehar University Kebri Dehar Ethiopia School of Built Environment Engineering and Computing Leeds Beckett University Leeds UK Department of Electronics and Communication Engineering Panimalar Engineering College Chennai India Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Center of Research Excellence in Artificial Intelligence and Data Science King Abdulaziz University Jeddah Saudi Arabia Secure Cyber Systems Research Group (SCSRG) WMG University of Warwick Coventry UK School of Computer Science Engineering Lovely Professional University Phagwara India Department of Information Technology Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Mathematics and Computer Science Coal City University Enugu Nigeria

In this study, unidentified flying machines are built with real-time monitoring in mid-course settings for obstacle avoidance in mind. The majority of the currently available methods are implemented as comprehensive monitoring systems, with significant success in monitored applications like bridges, railways, etc. So, the predicted model is developed exclusively for specific monitoring settings, as opposed to the broad conditions that are used by the current approaches. Also, in the design model, the first steps are taken by limiting the procedure to specific heights, and the input thrust that is provided for take up operation is kept to a minimum. Due to the improved altitudes, the velocity and acceleration units have been cranked up on purpose, making it possible to sidestep intact objects. In addition, Advanced Image Mapping Localization (AIML) is used to carry out the implementation process, which identifies stable sites at the correct rotation angle. Besides, Cyphal protocol integration improves the security of the data-gathering process by transmitting information gathered from sensing devices. The suggested system is put to the test across five different case studies, where the designed Unmanned aerial vehicle can able to detect 25 obstacles in the narrow paths in considered routs but existing approach can able to identify only 14 obstacle in the same routes.

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Efficient Training Approaches for Performance Anomaly Detection Models in Edge Computing Environments

arXiv

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arXiv 2024年

作者： Fernando, Duneesha Rodriguez, Maria A. Arroba, Patricia Ismail, Leila Buyya, Rajkumar Laboratory School of Computing and Information Systems The University of Melbourne Parkville Australia The CCS Center for Computational Simulation Universidad Politécnica de Madrid Madrid Spain Lab Department of Computer Science and Software Engineering United Arab Emirates University United Arab Emirates

Microservice architectures are increasingly used to modularize IoT applications and deploy them in distributed and heterogeneous edge computing environments. Over time, these microservice-based IoT applications are susceptible to performance anomalies caused by resource hogging (e.g., CPU or memory), resource contention, etc., which can negatively impact their Quality of Service and violate their Service Level Agreements. Existing research on performance anomaly detection for edge computing environments focuses on model training approaches that either achieve high accuracy at the expense of a time-consuming and resource-intensive training process or prioritize training efficiency at the cost of lower accuracy. To address this gap, while considering the resource constraints and the large number of devices in modern edge platforms, we propose two clustering-based model training approaches: (1) intra-cluster parameter transfer learning-based model training (ICPTL) and (2) cluster-level model training (CM). These approaches aim to find a trade-off between the training efficiency of anomaly detection models and their accuracy. We compared the models trained under ICPTL and CM to models trained for specific devices (most accurate, least efficient) and a single general model trained for all devices (least accurate, most efficient). Our findings show that ICPTL's model accuracy is comparable to that of the model per device approach while requiring only 40% of the training time. In addition, CM further improves training efficiency by requiring 23% less training time and reducing the number of trained models by approximately 66% compared to ICPTL, yet achieving a higher accuracy than a single general model. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep learning

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From Rule-Based Models to Deep Learning Transformers Architectures for Natural Language Processing and Sign Language Translation Systems: Survey, Taxonomy and Performance Evaluation

arXiv

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arXiv 2024年

作者： Shahin, Nada Ismail, Leila Intelligent Distributed Computing and Systems Lab Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University United Arab Emirates Emirates Center for Mobility Research United Arab Emirates University Abu Dhabi United Arab Emirates

With the growing Deaf and Hard of Hearing population worldwide and the persistent shortage of certified sign language interpreters, there is a pressing need for an efficient, signs-driven, integrated end-to-end translation system, from sign to gloss to text and vice-versa. There has been a wealth of research on machine translations and related reviews. However, there are few works on sign language machine translation considering the particularity of the language being continuous and dynamic. This paper aims to address this void, providing a retrospective analysis of the temporal evolution of sign language machine translation algorithms and a taxonomy of the Transformers architectures, the most used approach in language translation. We also present the requirements of a real-time Quality-of-Service sign language machine translation system underpinned by accurate deep learning algorithms. We propose future research directions for sign language translation *** Codes I.2, I.2.7, I.4, I.4.9 © 2024, CC BY.

关键词： Neural machine translation

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BaSeNet: A Learning-based Mobile Manipulator Base Pose Sequence Planning for Pickup Tasks

BaSeNet: A Learning-based Mobile Manipulator Base Pose Seque...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Lakshadeep Naik Sinan Kalkan Sune L. Sørensen Mikkel B. Kjærgaard Norbert Krüger SDU Robotics Mærsk Mc-Kinney Møller Institute (MMMI) Faculty of Engineering University of Southern Denmark Odense M Denmark Department of Computer Engineering and ROMER Robotics Center Middle East Technical University (METU) Ankara Turkey SDU Software Engineering Mærsk Mc-Kinney Møller Institute (MMMI) Faculty of Engineering University of Southern Denmark Odense M Denmark Danish Institute for Advanced Studies (DIAS) Odense M Denmark

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In many applications, a mobile manipulator robot is required to grasp a set of objects distributed in space. This may not be feasible from a single base pose and the robot must plan the sequence of base poses for grasping all objects, minimizing the total navigation and grasping time. This is a Combinatorial Optimization problem that can be solved using exact methods, which provide optimal solutions but are computationally expensive, or approximate methods, which offer computationally efficient but sub-optimal solutions. Recent studies have shown that learning-based methods can solve Combinatorial Optimization problems, providing near-optimal and computationally efficient *** this work, we present BaSeNet - a learning-based approach to plan the sequence of base poses for the robot to grasp all the objects in the scene. We propose a Reinforcement Learning based solution that learns the base poses for grasping individual objects and the sequence in which the objects should be grasped to minimize the total navigation and grasping costs using Layered Learning. As the problem has a varying number of states and actions, we represent states and actions as a graph and use Graph Neural Networks for learning. We show that the proposed method can produce comparable solutions to exact and approximate methods with significantly less computation time. The code and Reinforcement Learning environments will be made available on the project webpage * .

关键词： Learning systems Navigation Grasping Reinforcement learning Manipulators Graph neural networks Computational efficiency Planning Optimization Intelligent robots

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Playing the video games during COVID-19 pandemic and its effects on player's well-being

Playing the video games during COVID-19 pandemic and its eff...

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Business Analytics for Technology and Security (ICBATS), International Conference on

作者： Samar Billi Noaman Amer Ibrahim Liaqat Ali M. W. Iqbal Asma Ashraf Usama Haseeb Salman Muneer Rasah Almajed K. Hamid Faculty of Management Canadian University Dubai Dubai UAE College of Computer and Information Technology American University in the Emirates Dubai United Arab Emirates College of Engineering and Technology University of Science and Technology of Fujairah Fujairah UAE Department of Software Engineering Superior University Lahore Pakistan Department of Software Engineering Superior University Lahore Pakistan Department of Computer Science Superior University Lahore Pakistan School of Computer Science NCBA&E Lahore Pakistan Applied Science Research Center Applied Science Private University Amman Jordan College of Computer and Information Technology American University in the Dubai United Arab Emirates

COVID-19 affected our lives intensly. That state of affairs made humans helpless. They had been depressed and experienced loneliness. At that time many human beings were determined to play video games just to loosen up their minds. Many games changed into an additional source of revenue wherein during COVID-19 they were playing while earning money. With these advantages, there were also some poor effects was accrued. A number of players remained playing video games post COVID-19. The carried out survey is based on the social video games results on players’ well-being and additionally on the effects of gamers’ health and their sensible lifestyles. We are going to investigate the behavior of gamers engaged with video games during the COVID-19 lockdown and the video games affects on their well-being, the time they served in playing video games, and the consequential effect on their behavior and social and mental well-being. The results provide a start line for empirically grounded discussions on video games at some stage in the pandemic, their use, and potential outcomes. Different agegroups of players have been investigated. Most players are between 18 and 30 years. A number of the gamers during lock down played a few hours but most of players were males who spent most of their day playing video games. However, now the ratio of playing video games is reduced as examined with past circumstances. Roughly we can say that the condition as a whole is better, the reason why players enforced video games in their post COVID-19 practical life 1 .

关键词： COVID-19 Video games Pandemics Games Machine learning Behavioral sciences Security

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PID Controller Machine Learning Algorithm Applied to the Mathematical Model of Quadrotor Lateral Motion 6

PID Controller Machine Learning Algorithm Applied to the Mat...

引用

6th IEEE International Conference on Actual Problems of Unmanned Aerial Vehicles Development, APUAVD 2021

作者： Kucherov, Dmytro Kozub, Andrei Tkachenko, Valerii Rosinska, Galina Poshyvailo, Olexii Faculty of Cybersecurity Computer and Software Engineering National Aviation University Department of Computerized Control Systems Kyiv Ukraine National Space Facilities Control and Test Center State Space Agency of Ukraine Kyiv Ukraine

ISBN: (纸本)9781665438223

The paper discusses the problem of automatic tuning of the PID controller. The auto-tuning algorithm of the PID controller based on one machine learning method, which is equivalent to the steepest descent, is proposed. A feature of the proposed approach is the vector adjustment of the PID controller parameters, where the angular direction of descent is taken into account at first, and the step sizes are made if taking into account the increased accuracy of the approximation near the optimum point. Modeling performed in the Matlab environment confirms the effectiveness of the proposed approach. © 2021 IEEE.

关键词： Three term control systems

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SLIDE-BASED GRAPH COLLABORATIVE TRAINING FOR HISTOPATHOLOGY WHOLE SLIDE IMAGE ANALYSIS

arXiv

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arXiv 2024年

作者： Shi, Jun Shu, Tong Jiang, Zhiguo Wang, Wei Wu, Haibo Zheng, Yushan School of Software Hefei University of Technology Hefei230601 China School of Computer Science and Information Engineering Hefei University of Technology Hefei230601 China Image Processing Center School of Astronautics Beihang University Beijing102206 China Department of Pathology The First Affiliated Hospital of USTC University of Science and Technology of China Hefei230036 China School of Engineering Medicine Beijing Advanced Innovation Center on Biomedical Engineering Beihang University Beijing100191 China

The development of computational pathology lies in the consensus that pathological characteristics of tumors are significant guidance for cancer diagnostics. Most existing research focuses on the inner-contextual information within each WSI yet ignores the possible inter-correlations between slides. As the development of tumors is a continuous process involving a series of histological, morphological, and genetic changes that accumulate over time, the similarities and differences between WSIs across various stages, grades, locations and patients should potentially contribute to the representation of WSIs and deserve to be taken into account in WSI modeling. To verify the advancement of introducing the slide inter-correlations into the representation learning of WSIs, we proposed a generic WSI analysis pipeline SlideGCD that can be adapted to any existing Multiple Instance Learning (MIL) frameworks and improve their performance. With the new paradigm, the prior knowledge of cancer development can participate in the end-to-end workflow, which concurrently initializes and refines the slide representation, as a guide for message passing in the slide-based graph. Extensive comparisons and experiments are conducted to validate the effectiveness and robustness of the proposed pipeline across 4 different tasks, including cancer subtyping, cancer staging, survival prediction, and gene mutation prediction, with 7 representative SOTA WSI analysis frameworks as backbones. Copyright © 2024, The Authors. All rights reserved.

关键词： WSI circuits

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