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Assistive technology with device for self-inflating bag in neonatology

Research on Biomedical engineering 2025年第2期41卷

作者： Marcelino, Ana Carolina Rodovanski, Giovana Pascoali Bonetti, Karoline Panes, Caio Rabinovich de Almeida Martins, Fernando Moran, Cristiane Aparecida Araranguá Brazil Graduate Program in Neurosciences and Behavior Department of Experimental Psychology of the Institute of Psychology-University of São Paulo Sao Paulo Brazil Araranguá Brazil Computer Engineering Instituto Mauá de Tecnologia São Caetano do Sul Brazil Electronic Engineering and Computing with Emphasis on Electronic Devices and Systems at Instituto Tecnológico de Aeronáutica–ITA São Caetano do Sul Brazil Department of Physiotheraphy and at the Postgraduate Program in Rehabilitation Science of the Federal University of Santa Catarina-UFCS Ararangua Brazil

Purpose: The objectives of this study were to create a device with technological development of the self-inflating bag (SIB) equipment to measure the variables tidal volume, peak inspiratory pressure, and inspiratory flow and to evaluate the knowledge of undergraduate students in handling the SIB. To reduce the risks of mortality, length of hospital stay, and infections, SIB is a resource used to ventilate the patient through the inflation of the device, but it is not capable of measuring the ventilatory parameters. Excess ventilation and incorrect handling of the bag can cause lung injury in newborns. Therefore, measuring these parameters can prevent lung injury resulting from inadequate ventilation. Method: This is a cross-sectional and experimental study, with the development of a device SIB that allows the evaluation of variables of neonatal respiratory mechanics that were tested with an artificial lung. It was approved by the Research Ethics Committee and the research was developed in three stages: the first represents the search for scientific articles for the consensus of neonatal ventilatory variables for the construction of the SIB parameters;the second stage depicts the technological development of a device capable of monitoring such variables through the SIB. In the third stage, the content validation of the device with the handling of the SIB was carried out by students of medicine and physiotherapy courses of Brazil. Results: In this work, a device that analyzes the values of the main ventilatory parameters in neonatology was developed and to generate a safety range for the use of the device, curves with a tolerance of 10% up and down were created. All electronic components were coupled to the equipment, with a display that transmits the parameter values. The web page can be used on a cell phone, tablet, computer, or SmartTv, as long as it is connected to the "RespiratorIoT_AP" network. Among the 29 participants in the study, 8 said they were familiar w

关键词： Students

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MMA-Net: Multi-Modal Attention Network for 2-D Object Detection in Autonomous Driving

MMA-Net: Multi-Modal Attention Network for 2-D Object Detect...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Abhilash Gaur Shubh Goel Kanishk Goel Seshan Srirangarajan Po-Hsuan Tseng Kai-Ten Feng IIT Delhi-NYCU Taiwan Joint Doctoral Program Bharti School of Telecommunication Technology and Management Indian Institute of Technology Delhi (IIT Delhi) New Delhi India International College of Semiconductor Technology National Yang Ming Chiao Tung University (NYCU) Hsinchu Taiwan Department of Electrical Engineering IIT Delhi New Delhi India Department of Electrical Engineering Bharti School of Telecommunication Technology and Management IIT Delhi New Delhi India Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan Department of Electronics and Electrical Engineering NYCU Hsinchu Taiwan

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Autonomous driving technology relies heavily on sensor data for environment perception. Heterogeneous sensors such as lidar, radar, and camera have their own strengths and limitations. Therefore, relying on any single sensor would restrict the effectiveness of autonomous driving technology. However, integrating data from such heterogeneous sensors poses challenges due to differences in their representations. This article outlines a deep learning network aimed at designing modality-agnostic multi-modal fusion architecture. We study sensor data from different modalities and learn fine-grained representations using modality-specific feature encoders independently. Then, a multimodal attention-based network (MMA-Net) is proposed to fuse the data from heterogeneous modalities. The proposed MMA-Net fuses multi-modal sensor data by jointly exploiting the inter-modality and intra-modality relationships among camera, lidar, and radar sensors. The effectiveness of the proposed multi-modal fusion architecture is demonstrated using 2-D object detection metrics through extensive experiments on a dataset generated using the CARLA simulator.

关键词： Laser radar Fuses Multimodal sensors Radar detection Object detection Signal processing Cameras Speech processing Autonomous vehicles Meteorology

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Enhancing Diagnostic Accuracy for Knee Osteoarthritis Using a Deep Learning Approach

Enhancing Diagnostic Accuracy for Knee Osteoarthritis Using ...

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International Symposium on Applied Science 2024, ISAS 2024

作者： Raza, Aquib Ching, Congo Tak Shing Liu, Peng-Ta Phan, Thien-Luan Tran, Ngoc-Luan Nguyen, Ha Anh T. Rameez, Mohammad Li, Hung-Chung Linh, Dao Nguyen Phuong Van Hieu, Nguyen Tran, Trung Nghia National Taiwan University Taipei City10673 Taiwan Research Center for Information Technology Academia Sinica Taipei City11529 Taiwan Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung402 Taiwan Department of Electrical Engineering National Chi Nan University Nantou County Taiwan Advanced Plant and Food Crop Biotechnology Center National Chung Hsing University Taichung402 Taiwan International Doctoral Program in Agriculture National Chung Hsing University Taichung402 Taiwan Fall Prevention Center Department of Physical Medicine & Rehabilitation Changhua Christian Hospital Changhua500 Taiwan Department of Physics and Electronic Engineering University of Science Vietnam National University - Ho Chi Minh City Ho Chi Minh City70000 Viet Nam Department of Computer Science University of York York HeslingtonYO10 5DD United Kingdom Undergraduate Program of Intellectual Creativity Engineering National Chung Hsing University Taichung402 Taiwan Ho Chi Minh City72409 Viet Nam HCMUT Vietnam National University Ho Chi Minh City Thu Duc Ho Chi Minh City71308 Viet Nam

This research introduces a deep learning framework that combines convolutional neural networks with autoencoders to improve the diagnostic accuracy of knee osteoarthritis. The study utilized a publicly available dataset from the Mendeley Data repository, where knee joint images were preprocessed using Contrast Limited Adaptive Histogram Equalization to enhance contrast and ensure consistent image sizing. Initially, an autoencoder was employed in an unsupervised manner to learn compressed representations of the data. These representations were then used to train a CNN to classify knee images into 'healthy' and 'osteoarthritic' categories. The model was trained using an 80:20 split for training and testing data, incorporating early stopping and data augmentation techniques to prevent overfitting and enhance generalization. Performance metrics such as accuracy, precision, recall, and the area under the Receiver Operating Characteristic curve (ROCAUC) were used to evaluate the model, resulting in a high test accuracy of 98.95%. The high precision and recall rates further confirmed the model's robustness in diagnosing KOA. To enhance interpretability, Gradient-weighted Class Activation Mapping (Grad-CAM) was applied to identify critical regions in the images that influenced the model's decisions. Additionally, t-Distributed Stochastic Neighbor Embedding (t-SNE) was used to visualize the high-dimensional encoded features in a two-dimensional space, providing deeper insights into how the model differentiates between classes. The promising results of this deep learning approach suggest its potential for broader applications in medical imaging diagnostics. By providing healthcare professionals with a tool that enhances diagnostic accuracy and operational efficiency, this framework lays the foundation for developing scalable, AI-driven diagnostic systems for various complex medical conditions. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Joints (anatomy)

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Electromagnetic properties of coal using microstrip and an algorithm based on the Nicolson-Ross-Weir method

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International Journal of Information Technology (Singapore) 2024年第7期16卷 4465-4480页

作者： Mancipe-Huérfano, David Leonardo García-Cáceres, Rafael Guillermo Doctoral Program in Engineering with Emphasis on Electronic Engineering Universidad Pedagógica y Tecnológica de Colombia - UPTC Sogamoso Colombia School of Industrial Engineering Universidad Pedagógica y Tecnológica de Colombia - UPTC Sogamoso Colombia

The work implements an experimental methodology to find the dielectric parameters: electrical permittivity, effective permittivity, magnetic permeability, conductivity, absorption coefficient, impedance, and loss tangent of bituminous coal from the municipality of Morcá and Tópaga belonging to the Sogamoso-Jericó sub-basin of the Guaduas formation, one of the most important coal reserves in Colombia. The methodology, known for its efficiency, includes constructing a microstrip-type circuit, measuring scattering parameters or S-parameters at frequencies between 300 kHz and 1 GHz with a vector network analyzer, and extracting electromagnetic properties using the Nicolson-Ross-Weir algorithm. The implemented algorithm allowed us to see the behavior of the coal in a fraction of the ultra-high frequency band and to find quickly and easily the approximate values of the parameters as a function of frequency, which are very important for investigations in mathematical modeling and computational electromagnetics. The results show that the real and imaginary components of the relative dielectric permittivity decrease with increasing frequency, and the absorption coefficient and the loss tangent of the coal increase as a function of frequency, indicating that the coal behaves as a dissipative dielectric. © The Author(s) 2024.

关键词： Coal Dielectric property Electrical property Magnetic property Microstrip Nicolson-Ross-Weir

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Real-time fall detecting system using a tri-axial accelerometer for home care

Real-time fall detecting system using a tri-axial accelerome...

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2012 International Conference on Biomedical engineering and Biotechnology, iCBEB 2012

作者： Lan, Chien-Cheng Hsueh, Ya-Hsin Hu, Rong-Yuan Graduate School of Electronic Engineering Doctoral Program National Yunlin University of Science and Technology Yunlin Taiwan Department of Electronic Engineering National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (纸本)9780769547060

There has been a considerable increase in the population proportion of senior people among global population. Fall often happens among these senior people, which is also the leading cause of their death. A real-time fall detection system may help us to detect fall events among elderly people in time and reduce the overall casualty rate. This paper proposed a home-based, real-time fall detection system that not only can distinguish up to 4 different kinds of fall events (forward, backward, rightward and leftward), but is also portable, low-cost and with high accuracy rate. The system includes a real-time fall detection band, a home server, and GSM instant messaging function which can transfer fall alert, send emergency help messages. © 2012 IEEE.

关键词： Fall detection

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Comparison of lipid extraction methods for the microalgae Acutodesmus obliquus

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International Journal of Agricultural and Biological engineering 2018年第5期11卷 211-217页

作者： Diana Ximena Hurtado Claudia Lorena Garzón-Castro Jhon Cortés-Romero Edisson Tello Camacho Bioprospecting and CAPSAB Research Groups Faculty of EngineeringUniversidad de La SabanaCundinamarca 53753Colombia Biosciences Doctoral Program Faculty of EngineeringUniversidad de La SabanaCundinamarca 53753Colombia Department of Electrical and Electronic Engineering Universidad Nacional de ColombiaBogotá53753Colombia

Microalgae are widely used in the pharmaceutical and energy industries,therefore the conditions for their cultivation and extraction methods play an important role in the profiling and acquisition of *** efficiency of lipid extraction from microalgae has attracted great interest from industry because of the wide variety of lipids and amounts that can be *** obliquus(Scenedesmus obliquus UTEX 393)was used in this *** was cultivated in Bold 3N medium modified with 75%nitrogen at 25℃,pH 6.8,125 r/min and a photoperiod of 18/6 h and illuminated with white light provided by a Light-Emitting Diode Surface Mount Device extensions(LED SMD)with an intensity of 1200μE/(m^(2)·s).The cells were stained with the Red Nile(RN)technique to indicate lipid *** extraction methods were compared,classical,microwave(MW),Soxhlet,and ultrasound(US),using the same solvent proportions(hexane:chloroform:methanol=1:2:3).All samples were analyzed with Fourier Transform Infrared Spectroscopy(FTIR)and Gas Chromatography coupled to Mass Spectrometry(GC-MS).The results showed:1)lipid production detected by RN was consistent with microalgal growth;2)the MW technique was the best extraction method,according to the statistical analysis through Randomized Complete Block(RCB)design and performance of 4.6%;and 3)the presence of saturated and unsaturated acids was indicated by FTIR ***-MS was able to identify palmitic and linoleic acids as the likely major constituents of the sample.

关键词： Acutodesmus obliquus lipid extraction trans-esterification Red Nile(RN)

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Transient analysis of an advanced static Var compensator using quad-series voltage-source PAM inverters

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ELECTRICAL engineering IN JAPAN 1996年第2期117卷 93-106页

作者： Tominaga, S Fujita, H Akagi, H Okayama University [?]Received his Master's degree in Electrical and Electronic Engineering in 1995 from the Engineering Research Division of the Graduate School Okayama University. He is currently in the doctoral program in system science at the Natural Sciences Research Division of the Graduate School of the same university. He is engaged in research on reactive power compensators.

This paper deals with an advanced static Var compensator (ASVC) using quad-series voltage-source PAM inverters. The ASVC consists of four three-phase voltage-source inverters with a common de capacitor and four three-phase transformers, each primary winding of which is connected in series with each other. Each inverter outputs a square-wave voltage, while the synthesized output voltage of the ASVC has a 24-step wave shape. This results not only in a great reduction of harmonic currents and de voltage ripples but also in fewer switching and snubbing losses. In this paper, transient analysis is performed with the focus on the response of reactive power and the resonance between the de capacitor and ac reactors. Experimental results obtained from a small-rated laboratory model of 10 kVA are also shown to verify analytical results based on the p-q transformation. The analytical results help in the design of system parameters such as the capacity of the de capacitor and feedback gains.

关键词： reactive power compensator voltage-source inverter PAM higher harmonics power system stabilization

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Implementation of Multi-process Automatic Loading and Unloading Production System

Implementation of Multi-process Automatic Loading and Unload...

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2023 International Conference on Consumer electronics - Taiwan, ICCE-Taiwan 2023

作者： Tung, Li-Chiuan Chen, Shu-Hung Ye, Yu-Cheng Liu, Guan-Zhi Chen, Lin-Yin Tu, Yu-Rou Lai, Yen-Wen Lee, Jeng-Dao National Formosa University Department of Automation Engineering Yunlin Taiwan Ming Chuan University Department of Electronic Engineering Taoyuan City Taiwan National Yunlin University of Science and Technology Doctoral Program in Industrial Engineering and Management Yunlin Taiwan

ISBN: (纸本)9798350324174

This research develops an intelligent automatic production loading and unloading solution for a multi-process part. According to the posture required for each processing operation of each part, a novel gripper and carrier that can implement multi-position clamping are designed. The Beckhoff controller is adopted as the host controller in the control system to integrate the robotic arm (including the vision system), the automated guided vehicle (AGV), and the computer numerical control (CNC) machine. The main topic of this research is to meet the requirements of automatic loading and unloading in the processing of the entire production line. It will significantly reduce the workforce consumption of the processing production line and avoid human error, thereby improving processing reproducibility and product production stability. © 2023 IEEE.

关键词： Controllers

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Implementation of Green Coffee Bean Quality Classification Using Slim-CNN in Edge Computing 5

Implementation of Green Coffee Bean Quality Classification U...

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5th IEEE International Conference on Knowledge Innovation and Invention, ICKII 2022

作者： Wang, Yan-Feng Cheng, Chen-Chiou Tsai, Jenn-Kai National Formosa University Department of Electronic Engineering Yunlin Taiwan National Formosa University Doctoral Degree Program in Smart Industry Technology Research and Development Yunlin Taiwan

ISBN: (数字)9781665479295

ISBN: (纸本)9781665479295

As one of the most important economic industries, how to improve the quality and output of the coffee industry is important. Defective coffee beans affect the flavor of coffee after roasting and grinding. In order to reduce the cost of labor and time, it is effective to use a convolutional neural network (CNN) model to identify defective green coffee beans. However, the complexity and huge parameters of the CNN model make the edge computing devices spend too much time on identification. Therefore, we introduced a lightweight deep learning network Slim-CNN to classify green coffee beans. Experiment results show that Slim-CNN achieves 92% accuracy with 6 times fewer parameters than MobileNet and 270 times fewer parameters than VGG16. The Slim-CNN model can be used on different edge computing devices to reduce labor costs in the coffee industry and improve the quality of coffee. © 2022 IEEE.

关键词： Convolutional neural networks

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Exploring Regression and Classification in Big Data with Deep Learning

Exploring Regression and Classification in Big Data with Dee...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Pandey, Ravindra Rongali, Aruna Sri Gopinath, S. Anute, Nilesh Nama, Forda Pund, Sachin Hult International Business School United States University of the Cumberlands Doctoral Information Technology Information Technology Emphasis Information Technology United States Karpagam Institute of Technology Department of Electronics and Communication Engineering Coimbatore India ASM's Institute of Business Management and Research Pune India University of Lampung Doctoral Program of Environtmental Science Department of Informatics Bandar Lampung Indonesia Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India

ISBN: (纸本)9798350357769

Deep gaining knowledge is a synthetic intelligence approach used to recognize complex facts. It uses many facts to recognize the complicated relationships between various factors. With deep learning, models can be built which might be capable of understanding the complicated patterns within big datasets. In this paper, we can explore using deep mastering in regression and type tasks on large datasets. In particular, we can use deep learning strategies to build a regression model that predicts a target value primarily based on the functions in a massive dataset and a classification version that can classify an object into one of the many classes of an extensive dataset. We can then discuss the overall performance of the fashions in comparison to standard models and talk about capability areas for development. Moreover, we will analyze the scalability of deep mastering strategies used on large datasets and discuss exceptional practices for building deep mastering fashions on massive datasets. Finally, we will summarize our findings and offer our conclusions approximately the use of deep studying in regression and type obligations on large datasets. © 2023 IEEE.

关键词： approximately gaining knowledge mastering performance regression

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