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Facilitating temporal synchronous target selection through user behavior modeling

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2019年第4期3卷 1-24页

作者： Zhang, Tengxiang Yi, Xin Wang, Ruolin Gao, Jiayuan Wang, Yuntao Yu, Chun Li, Simin Shi, Yuanchun Tsinghua University Institute of Computing Technology Chinese Academy of Sciences Kexueyuan South Road Beijing100084 China Key Laboratory of Pervasive Computing Ministry of Education Beijing Key Lab of Networked Multimedia Beijing National Research Center for Information Science and Technology Department of Computer Science and Technology Tsinghua University China Tsinghua University China Global Innovation eXchange Institute Key Laboratory of Pervasive Computing Ministry of Education Beijing Key Lab of Networked Multimedia Department of Computer Science and Technology Tsinghua University Shuangqing Road Beijing100081 China Department of Electrical and Computing Engineering Beihang University Beijing100081 China Tsinghua University Shuangqing Road Beijing100081 China UCLA United States

Temporal synchronous target selection is an association-free selection technique: users select a target by generating signals (e.g., finger taps and hand claps) in sync with its unique temporal pattern. However, classical pattern set design and input recognition algorithm of such techniques did not leverage users' behavioral information, which limits their robustness to imprecise inputs. In this paper, we improve these two key components by modeling users' interaction behavior. In the first user study, we asked users to tap a finger in sync with blinking patterns with various period and delay, and modeled their finger tapping ability using Gaussian distribution. Based on the results, we generated pattern sets for up to 22 targets that minimized the possibility of confusion due to imprecise inputs. In the second user study, we validated that the optimized pattern sets could reduce error rate from 23% to 7% for the classical Correlation recognizer. We also tested a novel Bayesian, which achieved higher selection accuracy than the Correlation recognizer when the input sequence is short. The informal evaluation results show that the selection technique can be effectively scaled to different modalities and sensing techniques. Copyright © 2019 held by the owner/author(s).

关键词： Taps

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An efficient aggregate signature scheme for healthcare wireless sensor networks

Journal of Network Intelligence

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Journal of Network Intelligence 2021年第1期6卷 1-15页

作者： Chen, Jian-Neng Zhou, Yu-Ping Huang, Zhen-Jie Wu, Tsu-Yang Zou, Fu-Min Tso, Raylin Minnan Normal University Zhangzhou363000 China Key Laboratory of Data Science and Intelligence Application Zhangzhou363000 China Lab of Granular Computing Zhangzhou363000 China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Fujian Key Laboratory of Automotive Electronics and Electric Drive Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology National Demonstration Center for Experimental Electronic Information and Electrical Technology Education Fujian University of Technology Fuzhou350008 China Department of Computer Science National Chengchi University Taipei Taiwan

In healthcare wireless sensor networks, there are a large number of sensors, which need to transmit a lot of information in real time. The aggregate signature scheme combines a great deal of signatures signed by different signers on different messages into one short signature, which greatly improves the efficiency of data transmission. In this paper, we present a scheme of certificate based aggregate signature, and prove its security in the random oracle model. The performance analysis shows that the scheme is efficient in sign and verify phase, and suitable for healthcare wireless sensor networks. © 2021, Taiwan Ubiquitous Information. All rights reserved.

关键词： Wireless sensor networks

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GEOM-GCN: Geometric graph convolutional networks

arXiv

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arXiv 2020年

作者： Pei, Hongbin Wei, Bingzhe Chang, Kevin Chen-Chuan Lei, Yu Yang, Bo College of Computer Science and Technology Jilin University China Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign United States Department of Computer Science University of Illinois at Urbana-Champaign United States Department of Computing Hong Kong Polytechnic University Hong Kong Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education China

Message-passing neural networks (MPNNs) have been successfully applied to representation learning on graphs in a variety of real-world applications. However, two fundamental weaknesses of MPNNs' aggregators limit their ability to represent graph-structured data: losing the structural information of nodes in neighborhoods and lacking the ability to capture long-range dependencies in disassortative graphs. Few studies have noticed the weaknesses from different perspectives. From the observations on classical neural network and network geometry, we propose a novel geometric aggregation scheme for graph neural networks to overcome the two weaknesses. The behind basic idea is the aggregation on a graph can benefit from a continuous space underlying the graph. The proposed aggregation scheme is permutation-invariant and consists of three modules, node embedding, structural neighborhood, and bi-level aggregation. We also present an implementation of the scheme in graph convolutional networks, termed Geom-GCN, to perform transductive learning on graphs. Experimental results show the proposed Geom-GCN achieved state-of-the-art performance on a wide range of open datasets of graphs. Copyright © 2020, The Authors. All rights reserved.

关键词： Graphic methods

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STS MICCAI 2023 Challenge: Grand challenge on 2D and 3D semi-supervised tooth segmentation

arXiv

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arXiv 2024年

作者： Wang, Yaqi Zhang, Yifan Chen, Xiaodiao Wang, Shuai Qian, Dahong Ye, Fan Xu, Feng Zhang, Hongyuan Zhang, Qianni Wu, Chengyu Li, Yunxiang Cui, Weiwei Luo, Shan Wang, Chengkai Li, Tianhao Liu, Yi Feng, Xiang Zhou, Huiyu Liu, Dongyun Wang, Qixuan Lin, Zhouhao Song, Wei Li, Yuanlin Wang, Bing Wang, Chunshi Chen, Qiupu Li, Mingqian College of Media Engineering Communication University of Zhejiang Hangzhou China State Key Laboratory of Oral Diseases National Clinical Research Center for Oral Diseases West China Hospital of Stomatology Sichuan University Chengdu China Lishui University School of Medicine Hangzhou Geriatric Stomatology Hospital Hangzhou Dental Hospital Group Hangzhou China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China School of Cyberspace Hangzhou Dianzi University Hangzhou China Suzhou Research Institute of Shandong University Suzhou China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China School of Biomedical Engineering Medical School Shenzhen University Shenzhen China School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Department of Mechanical Electrical and Information Engineering Shandong University Weihai China School of Management Hangzhou Dianzi University Hangzhou China Department of Stomatology Sichuan Provincial People's Hospital University of Electronic Science and Technology of China Chengdu China School of Computing and Mathematical Sciences University of Leicester Leicester United Kingdom Zeta Technology Co. Ltd. No. 1158 Zhangdong Road Pudong New Area Shanghai China China Academy of Information and Communications Technology Beijing China HangZhou Dianzi University Xiasha Higher Education Zone Hangzhou China Southeast University Sipailou Xuanwu District Nanjing China Shanghai Ninth People's Hospital Shanghai Jiao Tong University School of Medicine Shanghai Jiao Tong University Shanghai China School of Computer Science and Technology Changchun University of Science and Technology Changchun China School of Artificial Intelligence Guilin University of Electronic Technology Guilin China University of Science and Technology of China Hefei China Hefei Institutes of Physical Science Chinese Academy of Sciences No. 350 Shushan

computer-aided design (CAD) tools are increasingly popular in modern dental practice, particularly for treatment planning or comprehensive prognosis evaluation. In particular, the 2D panoramic X-ray image efficiently detects invisible caries, impacted teeth and supernumerary teeth in children, while the 3D dental cone beam computed tomography (CBCT) is widely used in orthodontics and endodontics due to its low radiation dose. However, there is no open-access 2D public dataset for children's teeth and no open 3D dental CBCT dataset, which limits the development of automatic algorithms for segmenting teeth and analyzing diseases. The Semi-supervised Teeth Segmentation (STS) Challenge, a pioneering event in tooth segmentation, was held as a part of the MICCAI 2023 ToothFairy Workshop on the Alibaba Tianchi platform. This challenge aims to investigate effective semi-supervised tooth segmentation algorithms to advance the field of dentistry. In this challenge, we provide two modalities including the 2D panoramic X-ray images and the 3D CBCT tooth volumes. In Task 1, the goal was to segment tooth regions in panoramic X-ray images of both adult and pediatric teeth. Task 2 involved segmenting tooth sections using CBCT volumes. Limited labelled images with mostly unlabelled ones were provided in this challenge prompt using semi-supervised algorithms for training. In the preliminary round, the challenge received registration and result submission by 434 teams, with 64 advancing to the final round. This paper summarizes the diverse methods employed by the top-ranking teams in the STS MICCAI 2023 Challenge. Copyright © 2024, The Authors. All rights reserved.

关键词： Image segmentation

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e-SCP-ECG+v2 protocol: Expanding the e-SCP-ECG+ protocol 9th

e-SCP-ECG+v2 protocol: Expanding the e-SCP-ECG+ protocol

引用

9th International EAI Conference on Broadband Communications, Networks, and Systems, Broadnets 2018

作者： Mandellos, George J. Papaioannou, Maria Panagiotakopoulos, Theodor Lymberopoulos, Dimitrios K. Wire Communication Laboratory Electrical and Computer Engineering Department University of Patras Rion26504 Greece Mobile and Pervasive Computing Quality and Ambient Intelligence Laboratory School of Science and Technology Hellenic Open University Patras26335 Greece

ISBN: (纸本)9783030051945

Nowadays, the fast-growing technology market for sensors and smart devices allows anyone to constantly monitor important vital parameters, like electrocardiogram (ECG). Mobile health systems typically employ data transmission to the premises of the health service provider via appropriate telecommunication protocols, which often consider only vital parameters. However, these parameters are likely to vary, depending on each person’s exercise, psychological condition, habits, environmental conditions and many other factors. Thus, it is necessary to utilize a protocol that is able to carry additional data concerning factors that are tightly connected with the quality of vital sign measurements. This paper proposes an extended version of the e-SCP-ECG+ protocol, mainly used for ECG data transmission, in order to include several types of information that affect the quality of the obtained signal, as well as the diagnosis process. The aim is to offer medical experts with an enriched clinical view of the patients so as to diagnose a medical incident more accurately. © ICST Institute for computer sciences, Social Informatics and Telecommunications engineering 2019.

关键词： Electrocardiograms

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Quantum Software engineering: Roadmap and Challenges Ahead

引用

ACM Transactions on Software engineering and Methodology 2025年第5期34卷

作者： Murillo, Juan Manuel Garcia-Alonso, Jose Moguel, Enrique Barzen, Johanna Leymann, Frank Ali, Shaukat Yue, Tao Arcaini, Paolo Pérez-Castillo, Ricardo de Guzmán, Ignacio García-Rodríguez Piattini, Mario Ruiz-Cortés, Antonio Brogi, Antonio Zhao, Jianjun Miranskyy, Andriy Wimmer, Manuel University of Extremadura Cáceres Spain University of Stuttgart Stuttgart Germany Simula Research Laboratory Oslo Norway and Computer Science Oslo Metropolitan University Oslo Norway Computer Science and Engineering Beihang University Beijing China National Institute of Informatics Chiyoda-ku Japan Faculty of Social Sciences and Information Technologies University of Castilla-La Mancha Talavera de la Reina Spain Institute of Technologies and Information Systems University of Castilla-La Mancha Ciudad Real Spain University of Castilla-La Mancha Ciudad Real Spain Computer Languages and Systems University of Seville Seville Spain Department of Computer Science University of Pisa Pisa Italy Faculty of Information Science and Electrical Engineering Kyushu University Fukuoka Japan Toronto Metropolitan University Toronto ON Canada Johannes Kepler University Linz Linz Austria

As quantum computers advance, the complexity of the software they can execute increases as well. To ensure this software is efficient, maintainable, reusable, and cost-effective—key qualities of any industry-grade software—mature software engineering practices must be applied throughout its design, development, and operation. However, the significant differences between classical and quantum software make it challenging to directly apply classical software engineering methods to quantum systems. This challenge has led to the emergence of Quantum Software engineering (QSE) as a distinct field within the broader software engineering landscape. In this work, a group of active researchers analyze in depth the current state of QSE research. From this analysis, the key areas of QSE are identified and explored in order to determine the most relevant open challenges that should be addressed in the next years. These challenges help identify necessary breakthroughs and future research directions for advancing QSE. © 2025 Copyright held by the owner/author(s).

关键词： open challenges QSE Quantum computing Quantum Software engineering

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Picosecond Synchronization of Photon Pairs through a Fiber Link between Fermilab and Argonne National Laboratories

arXiv

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arXiv 2022年

作者： Kapoor, Keshav Xie, Si Chung, Joaquin Valivarthi, Raju Peña, Cristián Narváez, Lautaro Sinclair, Neil Allmaras, Jason P. Beyer, Andrew D. Davis, Samantha I. Fabre, Gabriel Iskander, George Kanter, Gregory S. Kettimuthu, Rajkumar Korzh, Boris Kumar, Prem Lauk, Nikolai Mueller, Andrew Shaw, Matthew Spentzouris, Panagiotis Spiropulu, Maria Thomas, Jordan M. Wollman, Emma E. The Fermi National Accelerator Laboratory BataviaIL60510 United States California Institute of Technology PasadenaCA91125 United States The Argonne National Laboratory LemontIL60439 United States The University of Chicago Physics Department ChicagoIL60637 United States The John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States The Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States The Center for Photonic Communication and Computing Department of Electrical and Computer Engineering McCormick School of Engineering and Applied Science Northwestern University 2145 Sheridan Road EvanstonIL60208 United States NuCrypt LLC 1460 Renaissance Dr #205 Park RidgeIL60068 United States Department of Physics and Astronomy Northwestern University 2145 Sheridan Road EvanstonIL60208 United States The Division of Engineering and Applied Science The Alliance for Quantum Technologies and the Jet Propulsion Laboratory California Institute of Technology PasadenaCA91125 United States

We demonstrate a three-node quantum network for C-band photon pairs using 2 pairs of 59 km of deployed fiber between Fermi and Argonne National Laboratories. The C-band pairs are directed to nodes using a standard telecommunication switch and synchronized to picosecond-scale timing resolution using a coexisting O-or L-band optical clock distribution system. We measure a reduction of coincidence-to-accidental ratio (CAR) of the C-band pairs from 51 ± 2 to 5.3 ± 0.4 due to Raman scattering of the O-band clock pulses. Despite this reduction, the CAR is nevertheless suitable for quantum networks. Copyright © 2022, The Authors. All rights reserved.

关键词： Quantum communication

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Intelligent non-invasive elderly fall monitoring by designing software defined radio frequency sensing system

引用

Digital Communications and Networks 2024年

作者： Adeel Akram Muhammad Bilal Khan Najah Abed Abu Ali Qixing Zhang Awais Ahmad Muhammad Shahid Iqbal Syed Atif Moqurrab Laboratory for Intelligent Sensing and Computing Institute of Advanced Technology University of Science and Technology of China Hefei 230031 Anhui China State Key Laboratory of Fire Science University of Science and Technology of China Hefei 230026 Anhui China College of IT United Arab Emirates University Al-Ain 15551 United Arab Emirates Department of Electrical and Computer Engineering COMSATS University Islamabad Attock 43600 Pakistan College of Computer and Information Sciences Imam Muhammad Ibn Saud Islamic University (IMSIU) Riyadh 11432 Kingdom of Saudi Arabia Department of Computer Science and Information Technology Women University of AJ&K Bagh Pakistan School of Computing Gachon University 1342 Seongnam-daero Sujeong-gu Seongnam-si 13120 Korea

The global increase in life expectancy poses challenges related to the safety and well-being of the elderly population, especially in relation to falls. While falls can lead to significant cognitive impairments, timely intervention can mitigate their adverse effects. In this context, the need for non-invasive, efficient monitoring systems becomes paramount. Although wearable sensors have gained traction for monitoring health activities, they may cause discomfort during prolonged use, especially for the elderly. To address this issue, we present an intelligent, non-invasive Software-Defined Radio Frequency (SDRF) sensing system, tailored red for monitoring elderly people's falls during routine activities. Harnessing the power of deep learning and machine learning, our system processes the Wireless Channel State Information (WCSI) generated during regular and fall activities. By employing sophisticated signal processing techniques, the system captures unique patterns that distinguish falls from normal activities. In addition, we use statistical features to streamline data processing, thereby optimizing the computational efficiency of the system. Our experiments, conducted for a typical home environment while using treadmill, demonstrate the robustness of the system. The results show high classification accuracies of 92.5%, 95.1%, and 99.8% for three Artificial Intelligence (AI) algorithms. Notably, the SDRF-based approach offers flexibility, cost-effectiveness, and adaptability through software modifications, circumventing the need for hardware overhaul. This research attempts to bridge the gap in RF-based sensing for elderly fall monitoring, providing a solution that combines the benefits of non-invasiveness with the precision of deep learning and machine learning.

关键词： AI Elderly falls Intelligent learning SDRF WCSI

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Biodegradability of Partially Reduced Nanographene Oxide by Human, Plant and Microbial Enzymes: Impact of Magnetic Nanoparticles

SSRN

引用

SSRN 2024年

作者： Kurapati, Rajendra Swetha, K. Sudeshna, Samantaray Silva, Filipa A.L.S. Silva, Filipa C. Freitas, Bruno Incorvia, Jean Anne C. Banerjee, Sourav Afonso Fernandes, José Ramiro Jayaraj, Arya Singh, N. Sadananda Magalhães, Fernão D. Pinto, Artur M. School of Chemistry Indian Institute of Science Education and Research Thiruvananthapuram Maruthimala PO Thiruvananthapuram India LEPABE - Laboratory for Process Engineering Environment Biotechnology and Energy Faculdade de Engenharia Universidade do Porto Rua Dr. Roberto Frias s/n Porto4200-180 Portugal ALiCE - Associate Laboratory in Chemical Engineering Faculdade de Engenharia Universidade do Porto Rua Dr. Roberto Frias s/n Porto4200-180 Portugal i3S - Instituto de Investigação e Inovação em Saúde Universidade do Porto Rua Alfredo Allen 208 Porto4200-180 Portugal INEB - Instituto de Engenharia Biomédica Universidade do Porto Rua Alfredo Allen 208 Porto4200-180 Portugal IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto Universidade do Porto Porto4200-180 Portugal Department of Electrical and Computer Engineering University of Texas at Austin. AustinTX78712 United States CQVR – Centro de Química Vila Real Universidade de Trás-os-Montes e Alto Douro Portugal Physical Department University of Trás-os-Montes and Alto Douro Quinta dos Prados Vila Real5000-801 Portugal School of Biology Indian Institute of Science Education and Research Thiruvananthapuram Maruthimala PO Thiruvananthapuram India

Although graphene-based materials continuously expand their range of industrial and biomedical applications, understanding their long-term fate in the organisms and environment is still in its infancy. Herein we examine the biodegradation of partially reduced graphene oxide (p-rGOn) and magnetic nanoparticles (IONPs) embedded rGOn (@rGOn) by incubating with the human myeloperoxidase (hMPO) isolated from the neutrophils, including with plant enzyme, horseradish peroxidase and treating with microbial laccase in the presence of its redox mediator ABTS [2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)]. Further, the biodegradation of p-rGOn and @rGOn was investigated by incubating with the laccase-secreting fungi, Aspergillus sp, present in the compost soil. The biodegradation of both rGO samples was analyzed for morphological and structural changes using electron microscopy and Raman spectroscopy. The results confirmed the efficient degradation of p-rGOn and that the presence of IONPs enhanced the biodegradability of @rGOn (magnetic) over p-rGOn, which could be attributed to the Fenton-type reaction because of IONPs. These results confirmed that the presence of IONPs facilitates the magnetic manipulation of @rGOn and increases their biodegradability. The current work could be crucial for better designing the potential biomedical applications of @rGOn (magnetic) for near-infrared photothermal (PTT) and externally controlled magnetotherapy applications useful in cancer treatment. © 2024, The Authors. All rights reserved.

关键词： Enzymes

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Multi-stage Speaker Extraction with Utterance and Frame-Level Reference Signals

arXiv

引用

arXiv 2020年

作者： Ge, Meng Xu, Chenglin Wang, Longbiao Chng, Eng Siong Dang, Jianwu Li, Haizhou Tianjin Key Laboratory of Cognitive Computing and Application College of Intelligence and Computing Tianjin University Tianjin China School of Computer Science and Engineering Nanyang Technological University Singapore Japan Advanced Institute of Science and Technology Ishikawa Japan Department of Electrical and Computer Engineering National University of Singapore Singapore Machine Listening Lab University of Bremen Germany

Speaker extraction requires a sample speech from the target speaker as the reference. However, enrolling a speaker with a long speech is not practical. We propose a speaker extraction technique, that performs in multiple stages to take full advantage of short reference speech sample. The extracted speech in early stages is used as the reference speech for late stages. For the first time, we use frame-level sequential speech embedding as the reference for target speaker. This is a departure from the traditional utterance-based speaker embedding reference. In addition, a signal fusion scheme is proposed to combine the decoded signals in multiple scales with automatically learned weights. Experiments on WSJ0-2mix and its noisy versions (WHAM! and WHAMR!) show that SpEx++ consistently outperforms other state-of-the-art baselines. Copyright © 2020, The Authors. All rights reserved.

关键词： Embeddings

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