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检索条件"任意字段=International Conference on Measurement and Modeling of Computer Systems"

共 92012 条记录，以下是1531-1540 订阅

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Enhanced Non-Contact Vital Sign Monitoring via Depth Camera-Assisted Millimeter-Wave Radar

Enhanced Non-Contact Vital Sign Monitoring via Depth Camera-...

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2024 international conference on Artificial Intelligence of Things and systems, AIoTSys 2024

作者： Zhang, Hanwen Dou, Chenglong Liu, Yucheng Wu, Yuan Qian, Liping Shi, Zhiguo Lu, Rongxing University of Macau State Key Laboratory of Internet of Things for Smart City China Zhuhai UM Science and Technology Research Institute Zhuhai China College of Information Engineering Zhejiang University of Technology Hangzhou310023 China College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China University of New Brunswick Faculty of Computer Science FrederictonNBE3B 5A3 Canada

ISBN: (纸本)9798331507886

Non-contact vital sign monitoring with mmWave radar has been regarded as an effective method for identifying lung and heart diseases due to its strong penetration and non-invasive capabilities. Nevertheless, relying solely on millimeter-wave radar for vital sign monitoring is susceptible to interference from multipath reflections, which degrades the measurement accuracy. To address this issue and enhance measurement accuracy, we propose a system design that leverages the depth camera for precise target location and subsequently employs dynamic beamforming techniques to effectively monitor the specified region. The experimental results demonstrate that our proposed system achieves an average error of 2.44 beats per minute (BPM) for heart rate monitoring and 0.22 breaths per minute (BPM) for respiratory rate monitoring. Compared to systems without beamforming, our system reduces the mean error for heart rate monitoring by 4.21 BPM and for respiratory rate monitoring by 0.51 BPM. © 2024 IEEE.

关键词： Heart

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Efficiency Electrical Power Edge-end Computing with Patch-based Low-rank Transformer

Efficiency Electrical Power Edge-end Computing with Patch-ba...

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2024 international conference on Energy and Electrical Engineering, EEE 2024

作者： Zhou, Mi Qian, Bin Lin, Xiaoming Zhang, Fan Luo, Yi Wu, Binquan Electric Power Research Institute Csg Guangdong Provincial Key Laboratory of Intelligent Measurement and Advanced Metering of Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Measurement and Advanced Metering of Power Grid Guangzhou China

ISBN: (纸本)9798350341768

The development of communication technology has made the need to build more reliable and efficient smart power grid systems imminent. The emergence of edge computing has significantly alleviated the pressure of data transmission in systems, enhancing the reliability and stability of cloud-edge based smart grid systems. However, the deep algorithms on which current Edge Computing platforms rely increase the overall computation time consumption and memory consumption of the whole system, which is inconsistent with the responsiveness and reliability requirements of smart power grid system services. Therefore, in this paper, we propose Patch-based Low-rank Transformer (PLT) that balances accuracy and efficiency, which can greatly alleviate the computation time consumption and memory consumption of Edge Computing platforms. Specifically, we cut the original electric power time series into subsequence-level patches to ensure the accuracy of the model for long and short-term sequential dependencies learning. Then, we introduce a low-rank attention mechanism to reduce the computational consumption of the model, and design a simple but efficient knowledge distillation module that transferring knowledge from the Transformer-based model to a lightweight MLP to speed up the computation of the model at inference phrase. Extensive experiments on 11 public datasets (10 UCR and 1 cluster-trace-v2018 released by Alibaba Cloud) and 13 collected electric power time series datasets show that the proposed PLT outperforms baseline models and reaches the design purpose. © 2024 IEEE.

关键词： Power systems computer aided design

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17th international Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2024

17th International Joint Conference on Biomedical Engineerin...

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17th international Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2024

The proceedings contain 204 papers. The special focus in this conference is on Biomedical Engineering systems and Technologies. The topics include: A POCT to Rapid Detect GBS with Highly Sensitivity;Characterization of sEMG Spectral Properties During Lower Limb Muscle Activation;an Event-Driven Closed-Loop Ultrasound Stimulator Composed of a Micro-Transducer and Multi-Site Electrodes in Vitro;3D Nuclei Segmentation by Combining GAN Based Image Synthesis and Existing 3D Manual Annotations;centrality of the Fingerprint Core Location;breast Cancer Detection Using Smart Wearable Devices with Thermal Sensors;preliminary Results on the Evaluation of Different Feedback Methods for the Operation of a Muscle-Controlled Serious Game;integrated Driver Pose Estimation for Autonomous Driving;A Comparison of Recurrent and Convolutional Deep Learning Architectures for EEG Seizure Forecasting;biodegradable Biodevices: A Design Approach Based on Cellular Automaton;prototyping a Low-Cost Flexible Sensor Glove For Diagnostics and Rehabilitation;Performance Review of Retraining and Transfer Learning of DeLTA2 for Image Segmentation for Pseudomonas Fluorescens SBW25;assembling Close Strains in Metagenome Assemblies Using Discrete Optimization;Agent Simulation Using Path Telemetry for modeling COVID-19 Workplace Hazard and Risk;compositional Techniques for Asynchronous Boolean Networks;unsupervised Domain Adaptation for Medical Images with an Improved Combination of Losses;Classification of Fine-ADL Using sEMG Signals Under Different measurement Conditions;feature Selection Improves Speech Based Parkinson’s Disease Detection Performance;Contactless Camera-Based Detection of Oxygen Desaturation Events and ODI Estimation During Sleep in SAS Patients;hand Movement Recognition Based on Fusion of Myography Signals;Prediction of Oxygen Saturation from Graphene Respiratory Signals with PPG Trained DNN.

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17th international Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2024

17th International Joint Conference on Biomedical Engineerin...

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17th international Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2024

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Vertical Launch Angle measurement of a Golf Ball Using Audio and Monocular Video Data 11

Vertical Launch Angle Measurement of a Golf Ball Using Audio...

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11th international conference on Sport Sciences Research and Technology Support, icSPORTS 2023

作者： Menke-Zumbragel, Jan-Bernd Brinkmann, Anna Hein, Andreas Assistance Systems and Medical Device Technology Carl von Ossietzky University of Oldenburg Germany

ISBN: (纸本)9789897586736

In golf, several parameters can be measured that describe how the golf ball was hit and how the ball lifts after impact with the golf club, the so-called launch parameters. In addition to the spin rate or the velocity of the ball and club head, the launch angle is an important value that describes the vertical component of the ball's launch direction. For professional use, there are systems called launch monitors that use either radar-technology, multiple high-speed cameras or a combination of both to measure the above parameters. Despite their high accuracy, these systems can suffer from disadvantages such as some inconvenience regarding size, weight or setup, and an inaccessibility regarding high cost. Therefore we present a method for vertical launch angle measurement based on monocular low frame rate video and audio data, by detecting the motion blur structure created by the launching golf ball. This approach allows the vertical launch angle to be measured with a simple and inexpensive setup that achieves an accuracy of } 0.74°, which is comparable to a commercial launch monitor. © 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： computer vision

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Enhancing Session-Based Recommendation via Inter-Session Similar Intent modeling and Graph Neural Networks

Enhancing Session-Based Recommendation via Inter-Session Sim...

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2024 IEEE international conference on systems, Man, and Cybernetics, SMC 2024

作者： Li, Yunhan An, Chunyan Yang, Conghao Wang, Mingyuan College of Computer Science Inner Mongolia University Inner Mongolia Hohhot China

ISBN: (纸本)9781665410205

Session-based recommendation (SBR) is a challenging task that aims to make item recommendations based on anonymized user session data. Mainstream SBR efforts focus on modeling information within a session and do not use information from other sessions. Although some works try to use other session information, there are still many limitations, and how to model other session information is still a challenging task. To overcome these limitations, we propose a new method for learning similar intentions between sessions, aiming to better model the recommendation information contained in other sessions. Specifically, we contribute a new model named ISIM-GNN that learns and integrates three levels of information simultaneously: (i) In the intra-session representation learning layer, we represent the session as a session graph and model it using a gated graph neural network. (ii) In the global item embedding learning layer, we use the graph attention mechanism to propagate and aggregate relevant item information from other sessions on the global graph. (iii) In the inter-session similar intent learning layer, we employ both 'hard similarity' and 'soft similarity' to select similar sessions, and use the attention mechanism to conduct session-level aggregation on the selected similar sessions to make better use of the inter-session collaboration information. Experiments on three real-world datasets show a significant performance improvement of our approach compared to state-of-the-art work. © 2024 IEEE.

关键词： Contrastive Learning

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computer Vision-Based Structural Deformation Monitoring System on Android Smartphones: Design and Implementation 26

Computer Vision-Based Structural Deformation Monitoring Syst...

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26th international conference on Advanced Communications Technology, ICACT 2024

作者： Dong, Xiang Lai, Maokai Liang, Hui Wu, Peng Wang, Chaoxia Peng, Ting Chang'an University Xi'an710064 China Shaanxi Huashan Road and Bridge Group Co. Ltd Xi'an710016 China Shaanxi Zhengcheng Road and Bridge Engineering Research Institute Co. Ltd Xi'an712000 China Xi'an University of Posts and Telecommunications Xi'an710061 China

ISBN: (纸本)9791188428120

computer vision displacement monitoring techniques offer a promising alternative to traditional displacement sensors, but most current approaches or systems use high-cost cameras and require limited measurement sites. To facilitate widespread implementation in real-world engineering, simpler systems or approaches are needed. This paper introduces a computer vision-based structural deformation monitoring system, written and developed using OpenCV and Kotlin. The system uses an Android smartphone camera and telescope as the acquisition device and adopts template matching technology based on digital image correlation to realize target displacement monitoring. A real-time display of the offset curve is realized with MPAndroidChart, and socket TCP communication is used to transmit the monitoring data. The detailed operation process of the system is shown as an example of dynamic detection. The test results show that the system runs smoothly, is easy to operate, and has the following advantages: 1) Low cost of hardware composition and simple construction process;2) High monitoring accuracy (accurate to 0.01 mm);3) High monitoring frequency (up to 10 frames per second in dynamic detection mode);4) Visualization of monitoring data, with the monitoring structural offset presented in real time as a curve for easy user comprehension. Overall, this system can provide technical and auxiliary decision support for structural deformation monitoring. © 2024 Global IT Research Institute - GIRI.

关键词： computer vision

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M-FUSE: Multi-frame Fusion for Scene Flow Estimation 23

M-FUSE: Multi-frame Fusion for Scene Flow Estimation

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23rd IEEE/CVF Winter conference on Applications of computer Vision (WACV)

作者： Mehl, Lukas Jahedi, Azin Schmalfuss, Jenny Bruhn, Andres Univ Stuttgart Inst Visualizat & Interact Syst Stuttgart Germany

ISBN: (纸本)9781665493468

Recently, neural network for scene flow estimation show impressive results on automotive data such as the KITTI benchmark. However, despite of using sophisticated rigidity assumptions and parametrizations, such networks are typically limited to only two frame pairs which does not allow them to exploit temporal information. In our paper we address this shortcoming by proposing a novel multi-frame approach that considers an additional preceding stereo pair. To this end, we proceed in two steps: Firstly, building upon the recent RAFT-3D approach, we develop an improved two-frame baseline by incorporating an advanced stereo method. Secondly, and even more importantly, exploiting the specific modeling concepts of RAFT-3D, we propose a U-Net architecture that performs a fusion of forward and backward flow estimates and hence allows to integrate temporal information on demand. Experiments on the KITTI benchmark do not only show that the advantages of the improved baseline and the temporal fusion approach complement each other, they also demonstrate that the computed scene flow is highly accurate. More precisely, our approach ranks second overall and first for the even more challenging foreground objects, in total outperforming the original RAFT-3D method by more than 16%. Code is available at https://***/cv-stuttgart/M-FUSE

关键词： Extrapolation computer vision Codes Neural networks Buildings Estimation computer architecture

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Dynamic traffic simulation for transportation system resilience assessment 12th

Dynamic traffic simulation for transportation system resilie...

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12th international conference on Bridge Maintenance, Safety and Management, IABMAS 2024

作者： Wang, X. Bocchini, P. Venkitasubramaniam, P. Xie, S. Civil and Environmental Engineering Department Lehigh University BethlehemPA United States Electrical and Computer Engineering Department Lehigh University BethlehemPA United States Thrust of Artificial Intelligence Hong Kong University of Science and Technology Guangzhou China

ISBN: (纸本)9781032770406

Quality resilience assessment for transportation systems relies on realistic representations of the network and traffic demand, and credible network traffic modeling. This paper presents a framework that incorporates time-dependent functionality analysis of disrupted networks and dynamic traffic simulations. Focusing on bridge disruptions, two distinct types of events are considered, earthquake and civil protest. The mesoscopic traffic flow model and the dynamic traffic assignment approach (as opposed to the static assignment approach) are utilized to realistically represent traffic dynamics. The presented results show that the dynamic traffic simulations provide traffic measures at a fine-grained spatiotemporal level which are valuable for post-event performance assessment. Traffic congestion effects are identified in earthquake-disrupted networks. Despite the limited disruption scope, protests on bridges can have significant impact on local travel cost. These findings promote using dynamic traffic modeling for transportation network analysis, highlighting the usefulness of more reliable and granular metrics for decision-making. © 2024 The Author(s).

关键词： Earthquakes

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Dual-IMU-WIP: An easy-to-build Walk-in-Place System based on Inertial measurement Units 10

Dual-IMU-WIP: An easy-to-build Walk-in-Place System based on...

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10th IEEE international conference on Computational Intelligence and Virtual Environments for measurement systems and Applications (IEEE CIVEMSA)

作者： Uhlmann, Tom Brunnett, Guido Tech Univ Chemnitz Chemnitz Germany

ISBN: (数字)9781665434454

ISBN: (纸本)9781665434454

Locomotion interfaces for virtual environments remain an active field of research. Walk-in-place (WIP), where the intent to move is communicated to the system by taking steps on the spot, provides a realistic experience to the user without being confined to a limited tracking area. The proposed systems found in the literature have complex setups, require bulky hardware, and use closed source software, which makes reproduction of the results as well as follow-up research difficult or impossible. We propose an easy-to-build wireless WIP system based on consumer grade electronic components which is versatile, affordable, and extensible. We use the rotation and position data of inertial measurement units attached to the user's left and right shin, perform signal processing directly on the device, and show how to use this data for continuous movement in a virtual environment. Our locomotion interface uses a state machine and features low start and stop latencies as well as the detection of foot gestures for rotation and sideward movements. The proposed device is small enough to be mounted on a pair of shin guards. We developed an exercise application to proof that our system works in a practical scenario, where the user moves through a virtual environment by using her/his legs only. We publish building plans of the device and make our software open source in order to make our results replicable and allow for follow-up research.

关键词： Walk-in-Place Locomotion Interface Virtual Environment Input Device Human-computer Interaction

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