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arXiv 2023年

作者： Yang, Siyuan Liu, Jun Lu, Shijian Hwa, Er Meng Kot, Alex C. Rapid-Rich Object Search Lab Interdisciplinary Graduate Programme Nanyang Technological University Singapore Singapore Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore Singapore School of Computer Science & Engineering Nanyang Technological University Singapore Singapore School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

One-shot skeleton action recognition, which aims to learn a skeleton action recognition model with a single training sample, has attracted increasing interest due to the challenge of collecting and annotating large-scale skeleton action data. However, most existing studies match skeleton sequences by comparing their feature vectors directly which neglects spatial structures and temporal orders of skeleton data. This paper presents a novel one-shot skeleton action recognition technique that handles skeleton action recognition via multi-scale spatialtemporal feature matching. We represent skeleton data at multiple spatial and temporal scales and achieve optimal feature matching from two perspectives. The first is multi-scale matching which captures the scale-wise semantic relevance of skeleton data at multiple spatial and temporal scales simultaneously. The second is cross-scale matching which handles different motion magnitudes and speeds by capturing sample-wise relevance across multiple scales. Extensive experiments over three large-scale datasets (NTU RGB+D, NTU RGB+D 120, and PKU-MMD) show that our method achieves superior one-shot skeleton action recognition, and outperforms SOTA consistently by large margins. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

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Analog field programmable CMOS current conveyor

Analog field programmable CMOS current conveyor

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Students Conference on engineering and Systems (SCES)

作者： G. Kapur S. Mittal C. M. Markan V. P. Pyara VLSI Design Technology Lab Dayalbagh Educational Institute Dayalbagh Agra INDIA Department of Physics & Computer Science Dayalbagh Educational Institute Dayalbagh Agra INDIA Department of Electrical Engineering Dayalbagh Educational Institute Dayalbagh Agra INDIA

We propose a simplified analog design cycle to generate reconfigurable and accurate prototype of several analog ICs. On applying the design cycle a comprehensive design methodology is being developed that make designs customizable and adaptable by a field user. The basic design of a second generation current controlled current conveyor is first analyzed to estimate the basic circuit configuration to verify its basic functionality. Secondly using its small signal equivalent model, ac and dc characteristics are being derived in terms of threshold voltage of transistors, present in the circuit. Indeed, with the help of floating gate transistors, which has a feature of post fabrication programmability of its threshold voltage, an accurate and reconfigurable prototype of the design can be obtained. The circuit is simulated using BSIM3 level49 MOSFET models in T-Spice 0.35μm CMOS process. Various Characteristics of CCCII are being derived and estimated their sensitivity with respect to threshold voltage of respective floating-gate transistors. The simulated results demonstrate that by programming threshold voltages, fine tuning of circuit specifications with wide spectrum can be achieved. The designs fabricated using our methodology can be adaptive to any desired value of specification with very high precision (about 13bit programming precision can attain with floating gate transistor). It can also make Analog ICs immune to most drawbacks like processes variations, device degradation by introducing new possibilities such as self correction and adaptability.

关键词： Transistors Threshold voltage Sensitivity Impedance Programming Mathematical model Equations

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What Matters in Professional Drone Pilots’ Practice? An Interview Study to Understand the Complexity of Their Work and Inform Human-Drone Interaction Research 21

What Matters in Professional Drone Pilots’ Practice? An Int...

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Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

作者： Sara Ljungblad Yemao Man Mehmet Aydın Baytaş Mafalda Gamboa Mohammad Obaid Morten Fjeld Interaction Design Computer Science and Engineering (CSE) University of Gothenburg and Chalmers University of Technology Gothenburg Sweden Interaction Design CSE University of Gothenburg and Chalmers University of Technology Gothenburg Sweden t2i lab Interaction Design CSE Chalmers University of Technology Gothenburg Sweden Interaction Design CSE Chalmers University of Technology Gothenburg Sweden t2i lab Interaction Design CSE Chalmers University of Technology Gothenburg Sweden and University of Bergen Bergen Norway

ISBN: (纸本)9781450380966

Human-drone interaction is a growing topic of interest within HCI research. Researchers propose many innovative concepts for drone applications, but much of this research does not incorporate knowledge on existing applications already adopted by professionals. This limits the validity of said research. To address this limitation, we present our findings from an in-depth interview study with 10 professional drone pilots. Our participants were armed with significant experience and qualifications – pertinent to both drone operations and a set of applications covering diverse industries. Our findings have resulted in design recommendations that should inform both ends and means of human-drone interaction research. These include, but are not limited to: safety-related protocols, insights from domain-specific use cases, and relevant practices outside of hands-on flight.

关键词： pilots piloting quadcopters professionals Drones interview study

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Development of machining alternatives, based on MRSEVs

Development of machining alternatives, based on MRSEVs

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ASME 1993 International computers in engineering Conference and Exposition, CIE 1993

作者： Nau, Dana S. Gupta, Satyandra K. Kramer, Thomas R. Regli, William C. Zhang, Guangmlng Dept. of Computer Science Inst. for Systems Research University of Maryland College ParkMD United States Dept. of Mechanical Eng. Inst. for Systems Research University of Maryland College ParkMD United States Robot Systems Division Manufacturing Eng. Lab NIST GaithersburgMD United States Automation Systems Division Engineering Design Laboratory NIST GaithersburgMD United States

ISBN: (纸本)9780791897645

One missing link between CAD and CAM is the lack of a systematic methodology for generating and evaluating alternative ways to manufacture a proposed design. To address this problem, we are developing a systematic approach for generating and evaluating alternative ways to manufacture machined parts, in order to provide information to the designer about the manufacturability of the proposed design, and information to the process engineer about how best to machine the part. This paper describes our overall approach, and how MRSEVs (Material Removal Shape Element Volumes, a STEP library of machining features) can be used to support it. © 1993 ASME 1993 International computers in engineering Conference and Exposition, CIE 1993. All rights reserved.

关键词： Manufacture

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COVIDx CXR-3: A Large-Scale, Open-Source Benchmark Dataset of Chest X-ray Images for computer-Aided COVID-19 Diagnostics

arXiv

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arXiv 2022年

作者： Pavlova, Maya Tuinstra, Tia Aboutalebi, Hossein Zhao, Andy Gunraj, Hayden Wong, Alexander Vision and Image Processing Lab University of Waterloo Canada Department of Systems Design Engineering University of Waterloo Canada Cheriton School of Computer Science University of Waterloo Canada Waterloo AI Institute University of Waterloo Canada DarwinAI Corp Canada

After more than two years since the beginning of the COVID-19 pandemic, the pressure of this crisis continues to devastate globally. The use of chest X-ray (CXR) imaging as a complementary screening strategy to RT-PCR testing is not only prevailing but has greatly increased due to its routine clinical use for respiratory complaints. Thus far, many visual perception models have been proposed for COVID-19 screening based on CXR imaging. Nevertheless, the accuracy and the generalization capacity of these models are very much dependent on the diversity and the size of the dataset they were trained on. Motivated by this, we introduce COVIDx CXR-3, a large-scale benchmark dataset of CXR images for supporting COVID-19 computer vision research. COVIDx CXR-3 is composed of 30,386 CXR images from a multinational cohort of 17,026 patients from at least 51 countries, making it, to the best of our knowledge, the most extensive, most diverse COVID-19 CXR dataset in open access form. Here, we provide comprehensive details on the various aspects of the proposed dataset including patient demographics, imaging views, and infection types. The hope is that COVIDx CXR-3 can assist scientists in advancing machine learning research against both the COVID-19 pandemic and related diseases. Copyright © 2022, The Authors. All rights reserved.

关键词： COVID-19

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Fast generation of high fidelity RGB-D images by deep-learning with adaptive convolution

arXiv

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arXiv 2020年

作者： Xian, Chuhua Zhang, Dongjiu Dai, Chengkai Wang, Charlie C.L. Guangdong Provincial Key Lab of Computational Intelligence and Cyberspace Information School of Computer Science and Engineering South China University of Technology Guangzhou Guangzhou510006 China Faculty of Industrial Design Engineering Delft University of Technology Netherlands Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong

Using the raw data from consumer-level RGB-D cameras as input, we propose a deep-learning based approach to efficiently generate RGB-D images with completed information in high resolution. To process the input images in low resolution with missing regions, new operators for adaptive convolution are introduced in our deep-learning network that consists of three cascaded modules - the completion module, the refinement module and the super-resolution module. The completion module is based on an architecture of encoder-decoder, where the features of input raw RGB-D will be automatically extracted by the encoding layers of a deep neural-network. The decoding layers are applied to reconstruct the completed depth map, which is followed by a refinement module to sharpen the boundary of different regions. For the super-resolution module, we generate RGB-D images in high resolution by multiple layers for feature extraction and a layer for up-sampling. Benefited from the adaptive convolution operators proposed in this paper, our results outperform the existing deep-learning based approaches for RGB-D image complete and super-resolution. As an end-to-end approach, high fidelity RGB-D images can be generated efficiently at the rate of 22 frames per second. Copyright © 2020, The Authors. All rights reserved.

关键词： Cameras

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PERFORMANCE OF TWO MULTISCALE TEXTURE ALGORITHMS IN CLASSIFYING SILVER GELATIN PAPER VIA K-NEAREST NEIGHBORS

PERFORMANCE OF TWO MULTISCALE TEXTURE ALGORITHMS IN CLASSIFY...

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IEEE International Conference on Image Processing

作者： Kirsten R. Basinet Andrew G. Klein Patrice Abry Stephane Roux Herwig Wendt Paul Messier Engineering and Design / Computer Science Western Washington Univ. Bellingham WA Ens de Lyon Laboratoire de Physique Lyon France IRIT University of Toulouse France IPCH Lens Media Lab Yale University West Haven

As part of the Historic Photographic Paper Classification Challenge, a multitude of approaches to quantifying paper texture similarity have been developed. These approaches have yielded encouraging results when applied to very controlled datasets containing photomicrographs of familiar specimens. In this paper, we report on the k-nearest neighbors classification performance of two multiscale analysis-based texture similarity approaches when applied to a much larger reference collection of silver gelatin photographic papers. The clusters for this data set were derived from a visual sorting experiment conducted by art conservators and paper experts later extended through crowd-sourcing. The results show that these texture similarity approaches, when combined with a simple k-nearest neighbors classification algorithm, yield workable performances with accuracy of up to 69%. We discuss this outcome in the context of available data and the cross-validation procedure used, then provide suggestions for improvement.

关键词： Classification algorithms Art Training Machine learning algorithms Silver Visualization Distance measurement

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Roopkotha: A Companion Robot for Enhancing Interactive Storytelling with Natural Interaction

Roopkotha: A Companion Robot for Enhancing Interactive Story...

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Image Processing and Robotics (ICIP), International Conference on

作者： Kazi Mayesha Mehzabin Md. Zahidul Islam Md. Ashaduzzaman Nur Mohammad Shidujaman Hooman Samani Haipeng Mi RIoT Center and Department of Computer Science & Engineering Independent University Bangladesh Dhaka Bangladesh Creative Computing Institute University of the Arts London London United Kingdom Media and Interaction Lab Academy of Arts and Design Tsinghua University Beijing China

ISBN: (数字)9798350374766

ISBN: (纸本)9798350374773

Roopkotha is a storytelling robot that seamlessly combines traditional storytelling methods and technology, creating a captivating robot storyteller. We are creating a special prototype in the world of robots that tells stories in a way that is easy to understand and enjoy. In this era of technological advancement, Roopkotha combines voice recognition with Bangla Language processing, emotion recognition, human behavior detection. Roopkotha aims to revolutionize the way stories are told and engage with users on a deep emotional level. Furthermore, Roopkotha is equipped with advanced facial expressions and emotion recognition technology. The emotion recognition feature helps the robot to have a profound connection with the users.

关键词： Emotion recognition Image recognition Human-robot interaction Prototypes Speech recognition Linguistics Feature extraction

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Optimal Resource Utilization in Hyperledger Fabric: A Comprehensive SPN-Based Performance Evaluation Paradigm

Optimal Resource Utilization in Hyperledger Fabric: A Compre...

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IEEE Symposium on Network Operations and Management

作者： Carlos Melo Glauber Gonçalves Francisco A. Silva Leonel Feitosa Iure Fé André Soares Eunmi Choi Tuan Anh Nguyen Dugki Min Applied Research on Distributed Systems Lab (PASID) Federal University of Piauí (UFPI) Brazil School of Software College of Computer Science Kookmin University Seoul South Korea Konkuk Aerospace Design-Airworlhiness Research Inslilule (KADA) Konkuk Universily Seoul Soulh Korea Department of Computer Science and Engineering Konkuk University Seoul South Korea

ISBN: (数字)9798350327939

ISBN: (纸本)9798350327946

Hyperledger Fabric stands as a leading framework for permissioned block-chain systems, ensuring data security and audit-ability for enterprise applications. As applications on this platform grow, understanding its complex configuration concerning various block-chain parameters becomes vital. These configurations significantly affect the system’s performance and cost. In this research, we introduce a Stochastic Petri Net (SPN) model to analyze Hyper-ledger Fabric’s performance, considering variations in block-chain parameters, computational resources, and transaction rates. We provide case studies to validate the utility of our model, aiding block-chain administrators in determining optimal configurations for their applications. A key observation from our model highlights the block size’s role in system response time. We noted an increased mean response time, between 1 to 25 seconds, due to variations in transaction arrival rates.

关键词： Performance evaluation Distributed ledger Computational modeling Data security Petri nets Stochastic processes Fabrics

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Nanoscale 3D printing of glass photonic crystals with near-unity reflectance in the visible spectrum

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science Advances 2025年第21期11卷 eadv0267页

作者： Wang Zhang Hongtao Wang Hao Wang Son Tung Ha Lei Chen Xue Liang Li Cheng-Feng Pan Bochang Wu Md. Abdur Rahman Yujie Ke Qifeng Ruan Xiaolong Yang Thomas Christensen Joel K. W. Yang Engineering Product Development Singapore University of Technology and Design Singapore 487372 Singapore. Singapore-HUJ Alliance for Research and Enterprise (SHARE) The Smart Grippers for Soft Robotics (SGSR) Programme Campus for Research Excellence and Technological Enterprise (CREATE) Singapore 138602 Singapore. School of Instrumentation and Optoelectronic Engineering Beihang University Beijing 100191 China. Hangzhou International Innovation Institute Beihang University Hangzhou 311115 China. Institute of Materials Research and Engineering (IMRE) Agency for Science Technology and Research (A*STAR) 2 Fusionopolis Way Innovis #08-03 Singapore 138634 Singapore. College of Mechanical and Vehicle Engineering Hunan University Changsha 410082 China. Department of Electrical and Computer Engineering National University of Singapore (NUS) 4 Engineering Drive 3 Singapore 117576 Singapore. School of Interdisciplinary Studies Lingnan University Tuen Mun Hong Kong SAR China. Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Harbin Institute of Technology (Shenzhen) Shenzhen 518055 China. College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics Nanjing 210016 China. Department of Electrical and Photonics Engineering Technical University of Denmark Kongens Lyngby 2800 Denmark. POLIMA—Center for Polariton-driven Light–Matter Interactions University of Southern Denmark Campusvej 55 DK-5230 Odense M Denmark.

Glass is widely used as an optical material due to its high transparency, thermal stability, and mechanical properties. The ability to fabricate and sculpt glass at the nanoscale would naturally expand its application domain in nanophotonics. Here, we report an approach to print glass in three dimensions with nanoscale resolutions. We developed Glass-Nano, an organic-inorganic hybrid resin containing silicon elements. Using this high-resolution resin, three-dimensional (3D) photonic crystals (PhCs) were printed with two-photon lithography. After printing, the structures were heated to high temperatures in air to remove organic components and convert the remaining material into silica glass. 3D glass PhCs with periodicities as small as 260 nanometers were obtained after sintering at 650°C. The 3D glass PhCs exhibit ~100% reflectance in the visible range, surpassing the typical reflectances observed from similar structures in low–refractive index materials. The quality of PhCs achieved is observed in both electron microscopy and the excellent agreement with band structure calculations of idealized structures.

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