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A Novel Locomotion Rule Rmbedding Long Short-Term Memory Network with Attention for Human Locomotor Intent Classification Using Multi-Sensors Signals

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computers, Materials & Continua 2024年第6期79卷 4349-4370页

作者： Jiajie Shen Yan Wang Dongxu Zhang Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of EducationColleague of Computer Science and TechnologyJilin UniversityChangchun130012China College of Software and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin UniversityChangchun130012China

Locomotor intent classification has become a research hotspot due to its importance to the development of assistive robotics and wearable *** work have achieved impressive performance in classifying steady locomotion ***,it remains challenging for these methods to attain high accuracy when facing transitions between steady locomotion *** to the similarities between the information of the transitions and their adjacent steady ***,most of these methods rely solely on data and overlook the objective laws between physical activities,resulting in lower accuracy,particularly when encountering complex locomotion modes such as *** address the existing deficiencies,we propose the locomotion rule embedding long short-term memory(LSTM)network with Attention(LREAL)for human locomotor intent classification,with a particular focus on transitions,using data from fewer sensors(two inertial measurement units and four goniometers).The LREAL network consists of two levels:One responsible for distinguishing between steady states and transitions,and the other for the accurate identification of locomotor *** classifier in these levels is composed of multiple-LSTM layers and an attention *** introduce real-world motion rules and apply constraints to the network,a prior knowledge was added to the network via a rule-modulating *** method was tested on the ENABL3S dataset,which contains continuous locomotion date for seven steady and twelve transitions *** results showed that the LREAL network could recognize locomotor intents with an average accuracy of 99.03%and 96.52%for the steady and transitions states,*** is worth noting that the LREAL network accuracy for transition-state recognition improved by 0.18%compared to other state-of-the-art network,while using data from fewer sensors.

关键词： Lower-limb prosthetics deep neural networks motion classification

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General Rotation Invariance Learning for Point Clouds via Weight-Feature Alignment

arXiv

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arXiv 2023年

作者： Xie, Liang Yang, Yibo Wang, Wenxiao Lin, Binbin Cai, Deng He, Xiaofei Liang, Ronghua Colleague of Computer Science and Technology Zhejiang University of Technology Hangzhou China State Key Lab of CAD & CG Zhejiang University Hangzhou China School of Software Technology Zhejiang University Ningbo China JD Explore Academy Beijing China Fabu Inc. Hangzhou China

Compared to 2D images, 3D point clouds are much more sensitive to rotations. We expect the point features describing certain patterns to keep invariant to the rotation transformation. There are many recent SOTA works dedicated to rotation-invariant learning for 3D point clouds. However, current rotation-invariant methods lack generalizability on the point clouds in the open scenes due to the reliance on the global distribution, i.e., the global scene and backgrounds. Considering that the output activation is a function of the pattern and its orientation, we need to eliminate the effect of the orientation. In this paper, inspired by the idea that the network weights can be considered a set of points distributed in the same 3D space as the input points, we propose Weight-Feature Alignment (WFA) to construct a local Invariant Reference Frame (IRF) via aligning the features with the principal axes of the network weights. Our WFA algorithm provides a general solution for the point clouds of all scenes. WFA ensures the model achieves the target that the response activity is a necessary and sufficient condition of the pattern matching degree. Practically, we perform experiments on the point clouds of both single objects and open large-range scenes. The results suggest that our method almost bridges the gap between rotation invariance learning and normal methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Pattern matching

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Intelligent COVID-19 forecasting, diagnoses and monitoring systems: A survey

TechRxiv

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TechRxiv 2021年

作者： Anjum, Nasreen Asif, Amna Kiran, Mehreen Jabeen, Fouzia Yang, Zhahoui Huang, Chongwen Noor, Salma Imran, Kanwal Ali, Ihsan Mohamed, Ehab Mahmoud The Department of Computer Science Shaheed Benazir Bhutto Women University Peshawar Pakistan The Department of Electronic and Electrical Engineering University College London LondonWC1E 6BT United Kingdom College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China International Joint Innovation Center Zhejiang University Haining314400 China Hangzhou310027 China Faculty of Computer Science and Information Technology University of Malaya Malaysia Electrical Engineering Dept. Colleague of Engineering Prince Sattam Bin Abdulaziz University Wadi Addwasir Saudi Arabia Electrical Engineering Dept. Faculty of Engineering Aswan University Aswan Egypt

To date, the novel Corona virus (SARS-CoV-2) has infected millions and has caused the deaths of thousands of people around the world. At the moment, five antibodies, two from China, two from the U.S., and one from the UK, have already been widely utilized and numerous vaccines are under the trail process. In order to reach herd immunity, around 70% of the population would need to be inoculated. It may take several years to hinder the spread of SARS-CoV-2. Governments and concerned authorities have taken stringent measurements such as enforcing partial, complete, or smart lockdowns, building temporary medical facilities, advocating social distancing, and mandating masks in public as well as setting up awareness campaigns. Furthermore, there have been massive efforts in various research areas and a wide variety of tools, technologies and techniques have been explored and developed to combat the war against this pandemic. Interestingly, machine learning algorithms and internet of Things (IoTs) technology are the pioneers in this race. Up till now, several real-time and intelligent COVID-19 forecasting, diagnosing, and monitoring systems have been proposed to tackle the COVID-19 pandemic. In this article based on our extensive literature review, we provide a taxonomy based on the intelligent COVID-19 forecasting, diagnosing, and monitoring systems. We review the available literature extensively under the proposed taxonomy and have analyzed a significantly wide range of machine learning algorithms and IoTs which can be used in predicting the spread of COVID-19 and in diagnosing and monitoring the infected individuals. Furthermore, we identify the challenges and also provide our vision about the future research on COVID-19. © 2021, CC BY.

关键词： Coronavirus

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Detail-enhanced medical image fusion in NSCT domain

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous Engineering 2015年第8期10卷 171-180页

作者： Yang, Guocheng Chen, Leiting Li, Meiling School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Department of Biomedical Engineering Luzhou Medical Colleague Zhongshan Road LuzhouSichuan China Provincial Key Laboratory of Digital Media Chengdu China School of Life Science and Technology University of Electronic Science and Technology of China Chengdu China

Multimodal medical image fusion technique plays an important role in clinical applications, such as pathologic diagnosis and surgical options. However, many traditional fusion methods cannot well preserve details of source images in the fused image. To address this problem, a detail-enhanced image fusion scheme based on non-subsampled contourlet transform (NSCT) and gain control (i.e., NCGC) is developed in this paper, which can effectively combine the spectral information and the spatial features of source images. The proposed method applies power law transformation to tune coefficients of each decomposed subband, and adjusts the strength of subband signals by smooth gain control. Eventually, the fused image with more anatomical details and functional information is constructed by the inverse NSCT. Three pairs of medical images with different modalities and three fusion metrics are applied to validate the feasibility of this algorithm. Experimental results demonstrate that the proposed method can achieve superior performance in both visual perception and objective assessment. © 2015 SERSC.

关键词： Contourlet transform

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Model for Efficient Delivery of Dynamic Web Pages with Automatic Detection of Shared Fragments

Model for Efficient Delivery of Dynamic Web Pages with Autom...

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2013 22nd Wireless and Optical Communication Conference

作者： Lingli Zhang Colleague of Computer Science and Technology Xuchang University

ISBN: (纸本)9781467356985

With the rapid development of Web,personalized and dynamic web pages have increasing dominated current-day WWW *** is an urgent problem to solve that how to save bandwidth and reduce latency for the *** the whole dynamic pages can not be cached,web pages from the same web site tend to contain many of the same ***-based caching is an effective solution for the delivery of dynamic web pages,however,good methods are needed for dividing web pages into *** markup of fragments in dynamic web pages is labor-intensive,error-prone,and *** paper proposes a model for efficient delivery of dynamic web pages with automatic detection of shared *** model can automatically detect the shared fragments in large collections of web *** results show that the model can reduce more latency and save more bandwidth efficiently.

关键词： web caching dynamic web page web page delivery shared fragments fragments detection

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Improvement of TF-IDF algorithm based on hadoop framework

Improvement of TF-IDF algorithm based on hadoop framework

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2012 2nd International Conference on computer Application and System Modeling, ICCASM 2012

作者： Li, Bin Yuan, Guoyong Department of Computer Science Colleague of Information Science and Technology Jinan University Guangzhou China

ISBN: (纸本)9789491216008

TF-IDF algorithm is often used in search engine, text similarity computation, web data mining, etc. These applications are often faced with the massive data processing. Therefore, how to calculate the tf-idf quickly and efficiently is very important. In this paper, we give a tf-idf algorithm based on the hadoop framework. Experiments show that in the case of massive data computing, the new method applying hadoop framework is more efficient than the traditional methods. © the authors.

关键词： Search engines

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Improvement of TF-IDF Algorithm Based on Hadoop Framework

Improvement of TF-IDF Algorithm Based on Hadoop Framework

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2012年计算机应用与系统建模国际会议

作者： Bin Li Yuan Guoyong Department of Computer Science Colleague of Information Science & Technology Jinan University

关键词： Hadoop, TF-IDF, distributed computing

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Improvement of snapshot differential algorithm based on hadoop platform

Improvement of snapshot differential algorithm based on hado...

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2011 Cross Strait Quad-Regional Radio science and Wireless technology Conference, CSQRWC 2011

作者： Yuan, Guoyong Li, Bin Xiao, Taiyang Department of Computer Science Colleague of Information Science and Technology Jinan University Guangzhou China

ISBN: (纸本)9781424497904

Snapshot differential algorithm is one of ways of extracting delta from views in the data warehouse in data integration circumstance. Due to the scale of the views in data warehouse is likely to be very massive, it will take lots of time to run snapshot differential algorithm and become the bottleneck of the system performance. In this paper, in order to improve efficiency of Snapshot Differential Algorithm, by using the massive data processing platform, we modify traditional Partition Hash algorithm, improve the efficiency and reduce the calculating time. At the end of this paper, we show a test which will demonstrate the improvement of efficiency after modification. © 2011 IEEE.

关键词： Distributed computer systems

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