检索结果-内蒙古大学图书馆

An Enhanced Ensemble-Based Long Short-Term Memory Approach for Traffic Volume Prediction

Computers, Materials & Continua 2024年第3期78卷 3585-3602页

作者： Duy Quang Tran Huy Q.Tran Minh Van Nguyen Faculty of Civil Engineering Nha Trang UniversityNha Trang650000Vietnam Robotics and Mechatronics Research Group Faculty of Engineering and TechnologyNguyen Tat Thanh UniversityHo Chi Minh City700000Vietnam Department of Civil Engineering Ho Chi Minh City University of Technology and EducationHo Chi Minh City700000Vietnam

With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service *** volume is an influential parameter for planning and operating traffic *** study proposed an improved ensemble-based deep learning method to solve traffic volume prediction problems.A set of optimal hyperparameters is also applied for the suggested approach to improve the performance of the learning *** fusion of these methodologies aims to harness ensemble empirical mode decomposition’s capacity to discern complex traffic patterns and long short-term memory’s proficiency in learning temporal ***,a dataset for automatic vehicle identification is obtained and utilized in the preprocessing stage of the ensemble empirical mode decomposition *** second aspect involves predicting traffic volume using the long short-term memory ***,the study employs a trial-and-error approach to select a set of optimal hyperparameters,including the lookback window,the number of neurons in the hidden layers,and the gradient descent ***,the fusion of the obtained results leads to a final traffic volume *** experimental results show that the proposed method outperforms other benchmarks regarding various evaluation measures,including mean absolute error,root mean squared error,mean absolute percentage error,and *** achieved R-squared value reaches an impressive 98%,while the other evaluation indices surpass the *** findings highlight the accuracy of traffic pattern ***,this offers promising prospects for enhancing transportation management systems and urban infrastructure planning.

关键词： Ensemble empirical mode decomposition traffic volume prediction long short-term memory optimal hyperparameters deep learning

来源：评论

学校读者我要写书评

暂无评论

The Impact of Robots’ Facial Emotional Expressions on Light Physical Exercises 15th

The Impact of Robots’ Facial Emotional Expressions on Lig...

引用

15th International Conference on Social robotics, ICSR 2023

作者： Abdulazeem, Nourhan Hu, Yue Active and Interactive Robotics Lab Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L3G1 Canada

ISBN: (纸本)9789819987146

To address the global challenge of population aging, our goal is to enhance successful aging through the introduction of robots capable of assisting in daily physical activities and promoting light exercises, which would enhance the cognitive and physical well-being of older adults. Previous studies have shown that facial expressions can increase engagement when interacting with robots. This study aims to investigate how older adults perceive and interact with a robot capable of displaying facial emotions while performing a physical exercise task together. We employed a collaborative robotic arm with a flat panel screen to encourage physical exercise across three different facial emotion conditions. We ran the experiment with older adults aged between 66 and 88. Our findings suggest that individuals perceive robots exhibiting facial expressions as less competent than those without such expressions. Additionally, the presence of facial expressions does not appear to significantly impact participants’ levels of engagement, unlike other state-of-the-art studies. This observation is likely linked to our study’s emphasis on collaborative physical human-robot interaction (pHRI) applications, as opposed to socially oriented pHRI applications. Additionally, we foresee a requirement for more suitable non-verbal social behavior to effectively enhance participants’ engagement levels. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Robotic arms

来源：评论

学校读者我要写书评

暂无评论

Cost-Effective Pressure Glove to Measure Forces & Orientation from a Chiropractor

Cost-Effective Pressure Glove to Measure Forces & Orientatio...

引用

2023 IEEE International Opportunity Research Scholars Symposium, ORSS 2023

作者： Butler, Carolyn Shah, Iti Kish, Jacob Salman, Muhammad Kennesaw State University Robotics & Mechatronics United States Kennesaw State University Department of Mechanical Engineering United States

ISBN: (纸本)9798350337006

Currently, there is no affordable, everyday use chiropractic force sensor. Devices that are used to teach chiropractic students, such as activators and drop tables, assist students in learning but do not give adequate feedback. Our design will be implementing the cheapest materials to make the most reliable force sensing glove which chiropractors can use for their daily work needs. Materials needed to complete this project include pressure sensors, electrical wires, resistors, a breadboard, Raspberry Pi Pico W, a laptop with Thonny software installed, and an analog to digital converter. Our design of the chiropractic force sensor glove will help reduce the amount of confusion when determining the correct amount of force to apply to a chiropractor's patient. This research will also help to dramatically reduce any severe pain resulting from misplaced forces and pressure applied to chiropractic patients. © 2023 IEEE.

关键词： Pressure sensors

来源：评论

学校读者我要写书评

暂无评论

CNN coal and rock recognition method based on hyperspectral data

引用

International Journal of Coal Science & Technology 2022年第5期9卷 59-70页

作者： Jianjian Yang Boshen Chang Yuchen Zhang Wenjie Luo Shirong Ge Miao Wu School of Mechatronics and Information Engineering China University of Mining and Technology-BeijingBeijing 100083China Key Laboratory of Intelligent Mining and Robotics Ministry of Emergency ManagementBeijingChina

Aiming at the problem of coal gangue identifcation in the current fully mechanized mining face and coal washing,this article proposed a convolution neural network(CNN)coal and rock identifcation method based on hyperspectral ***,coal and rock spectrum data were collected by a near-infrared spectrometer,and then four methods were used to flter 120 sets of collected data:frst-order diferential(FD),second-order diferential(SD),standard normal variable transformation(SNV),and multi-style *** coal and rock refectance spectrum data were pre-processed to enhance the intensity of spectral refectance and absorption characteristics,as well as efectively remove the spectral curve noise generated by instrument performance and environmental factors.A CNN model was constructed,and its advantages and disadvantages were judged based on the accuracy of the three parameter combinations(i.e.,the learning rate,the number of feature extraction layers,and the dropout rate)to generate the best CNN classifer for the hyperspectral data for rock *** experiments show that the recognition accuracy of the one-dimensional CNN model proposed in this paper reaches 94.6%.Verifcation of the advantages and efectiveness of the method were proposed in this article.

关键词： Hyperspectral data Data pre-processing 1D-CNN Coal gangue identifcation

来源：评论

学校读者我要写书评

暂无评论

Versatile Tasks on Integrated Aerial Platforms Using Only Onboard Sensors: Control, Estimation, and Validation

引用

IEEE Transactions on robotics 2025年 41卷 3518-3538页

作者： Wang, Kaidi Lai, Ganghua Yu, Yushu Du, Jianrui Sun, Jiali Xu, Bin Franchi, Antonio Sun, Fuchun Beijing Institute of Technology School of Mechatronical Engineering Beijing100081 China Beijing Institute of Technology School of Mechanical Engineering Beijing100081 China University of Twente Robotics and Mechatronics Lab Faculty of Electrical Engineering Mathematics and Computer Science Enschede7500 AE Netherlands Tsinghua University Department of Computer Science and Technology China

Connecting multiple aerial vehicles to a rigid central platform through passive spherical joints holds the potential to construct a fully-actuated aerial platform. The integration of multiple vehicles enhances efficiency in tasks like mapping and object reconnaissance. This paper proposes a control and state estimation framework for the Integrated Aerial Platform (IAP), enabling it to perform versatile tasks like object reconnaissance and physical interactive tasks with only onboard sensors. In the framework, the 6D motion control serves as the low-level controller, while the high-level controller comprises a 6D admittance filter and a perception-aware attitude correction module. The 6D admittance filter, serving as the interaction controller, is adaptable for aerial interaction tasks. The perception-aware attitude correction algorithm is carefully designed by adopting a geometric Model Predictive Controller (MPC). This algorithm, incorporating both offline and online calculations, proves to be well-suited for the intricate dynamics of an IAP. A 6D direct wrench controller is also developed for the IAP. Notably, both the interaction controller and the direct wrench controller operate without reliance on force/torque sensors. Instead, a wrench observer algorithm is devised, considering external disturbances. Additionally, based on the kinematics constraints of the multiple aerials in the platform, a fusion algorithm for multiple Visual-Inertial Odometry (VIO) and kinematics constraints is developed, providing more accurate localization. A prototype of the IAP is constructed, and its capabilities are demonstrated through experiments including perception-aware object reconnaissance, aerial mapping, aerial peg-in-hole task, and 6D contact wrench generation. All experiments are conducted exclusively with onboard sensors. These tasks exemplify the merits of the proposed IAP and validate the effectiveness of the proposed control framework and fusion algorithm. © 2004-2012

关键词： State estimation

来源：评论

学校读者我要写书评

暂无评论

Inpatient Monitoring System: Temperature, Oxygen Saturation, Blood Pressure, Heart Rate, and Infusion Automation Based on ESP 32, IoT, and Mobile Application 7

Inpatient Monitoring System: Temperature, Oxygen Saturation,...

引用

7th International Conference of Computer and Informatics engineering, IC2IE 2024

作者： Joseph, Irvanda Anthony, Patrick Astuti, Winda Lie, Zener Sukra Iwan Solihin, Mahmud Bina Nusantara University Binus Aso School of Engineering Automotive and Robotics Program Computer Engineering Department Jakarta11480 Indonesia Ucsi University Department of Mechanical and Mechatronics Engineering Kuala Lumpur Malaysia

ISBN: (纸本)9798331505530

The implementation of a patient monitoring system and infusion automation which aims to ensure regular and periodic monitoring of inpatient conditions are applied in this system. This embedded system is applied in hospitals and addresses the uneven distribution of healthcare workers in Indonesia, particularly in remote areas. Currently, manual checks by nurses can lead to errors and reduced patient comfort. The improvement supervision is developed in this work. The system monitored body temperature, oxygen saturation, blood pressure, heart rate, and automated infusions. All the embedded systems are connected to Internet of Things (IoT) and a real-time database accessible through an application and web. This system allows doctors and hospital authorities to make decisions based on patient condition history. The testing phase of the system shows four data acquisition devices (temperature, oxygen saturation, blood pressure, and heart rate), an ESP 32, and Firebase as a database, have ability to capture and send real-time data every five seconds and can be accessed by doctors, patients, and hospital authorities. © 2024 IEEE.

关键词： Remote patient monitoring

来源：评论

学校读者我要写书评

暂无评论

A deep learning-based model for automated STN localization using local field potentials in Parkinson’s disease

引用

Soft Computing 2025年第4期29卷 2343-2362页

作者： Hosny, Mohamed Naeem, Mohamed A. Zhu, Minwei Gao, Wenpeng Elshenhab, Ahmed M. Fu, Yili Department of Electrical Engineering Benha Faculty of Engineering Benha University Benha Egypt State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150080 China Department of Mechatronics and Robotics Engineering Faculty of Engineering South Valley University Qena Egypt First Affiliated Hospital Harbin Medical University Harbin150001 China School of Life Science and Technology Harbin Institute of Technology Harbin150080 China Department of Mathematics Faculty of Science Mansoura University Mansoura35516 Egypt

Accurate identification of the subthalamic nucleus (STN) borders is time-consuming, relying heavily on the neurosurgeon expertise in manually interpreting the electrophysiological signals. Local field potentials (LFPs) have garnered imperative attention due to their strong correlation with the STN. However, existing detection models often face challenges with high computational complexity, hyperparameter optimization and lack of explainability, making them unreliable for clinicians. Therefore, this study introduces an explanatory framework using convolutional neural networks (CNN) for detecting the STN region from LFPs. Continuous wavelet transform is employed to convert LFPs signals into scalogram images, which are then processed by sixteen CNN models. We evaluated our framework by examining the impact of various limiting factors on the classification performance, including model size, learning rate (LR), optimizers and data scaling. Deep features are extracted from the top-performing CNN architectures to capture rich representations of the scalograms. These features are then fused and classified using k-nearest neighbour algorithm. Gradient-weighted class activation mapping is used to explain the decisions made by the proposed model. Our approach achieved an accuracy of 99.61%, outperforming individual CNN models for STN localization. The experimental results revealed that CNN models, embedded with additional hyperparameters and layers, generally outperformed smaller models. Besides, low LR significantly enhanced the performance compared to high LR. Moreover, features extracted from untuned networks produced lower performance than tuned networks. The proposed system could revolutionize deep brain stimulation surgery by increasing efficiency and reducing reliance on clinician expertise for STN detection. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Wavelet transforms

来源：评论

学校读者我要写书评

暂无评论

Advancement in Smart Cane Technology: Enhancing Mobility for the Visually Impaired Using ROS and LiDAR 6

Advancement in Smart Cane Technology: Enhancing Mobility for...

引用

6th International Conference on robotics and Automation in Industry, ICRAI 2024

作者： Zafar, Saqib Maqbool, Hafiz Farhan Ahmad, Naveed Ali, Arham Moeizz, Abdul Ali, Faizan Taborri, Juri Rossi, Stefano University of Tuscia Department of Economics Engineering Society and Business Organization VT Viterbo01100 Italy University of Engineering and Technology Lahore Department of Mechanical Mechatronics and Manufacturing Engineering Faisalabad Campus Lahore38000 Pakistan National Center of Robotics and Automation Human-Centred Robotics Lab Pakistan

ISBN: (纸本)9798350355703

Visual impairment affects the ability to navigate independently in an unknown environment due to reliance on human/dog assistance, potential miscommunication, and discomfort during mobility. To make the visually impaired (VI) individuals self-reliant and confident in their mobility the proposed system has been developed that contains a light detection and ranging (LiDAR) sensor for obstacle detection and two omni-wheels coupled with the DC gear encoder motors for precise movement in any direction without lifting the cane. Hector Simultaneous Localization and Mapping (SLAM), A, and steering wheel algorithms have been implemented in the robot operating system (ROS) for real-time environment mapping, efficient path planning, and navigating in an unknown indoor static environment, respectively. The Raspberry Pi 3B+ and Arduino Mega 2560 are used in the master-slave configuration for decision-making on path planning and controlling the maneuverability of the system in real-time. The proposed system in the paper is successfully tested on one subject in two indoor environments. The results demonstrate that the system serves as an assistive mobile robot, helping the VI individual to navigate confidently in an unknown environment and reach the destination without assistance. © 2024 IEEE.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

Gait dynamic stability evaluation on inclined surfaces for inverted or everted feet walking

引用

Fuss und Sprunggelenk 2024年第4期22卷 254-268页

作者： Raza, Anam Mahmood, Imran Sultana, Tayyaba Sultana, Salma Dehghani-Sanij, Abbas A. Department of Zoology Government College University Faisalabad Pakistan Mechatronics and Control Engineering Department Faisalabad Campus UET Lahore Pakistan Institute of Design Robotics and Optimisation School of Mechanical Engineering University of Leeds United Kingdom

Background: This study investigates gait dynamic stability on inclined surfaces while walking with foot rotational impairments such as everted and inverted feet. Walking stability is assessed during gait transitional periods i.e. weight loading and unloading phases. Methods: Foot rotational impairments (eversion and inversion) are imitated using wedged foot insoles. A total of ten healthy subjects performed five trials for each of the inverted, everted, and normal feet conditions. Experimental data was collected using a twelve-camera motion capture system and a force plate installed on an inclined platform. Lower limb joint kinematics were computed in Visual-3D motion analysis software to evaluate the degree of foot rotational impairments. Gait dynamic stability was assessed by analysing the centre of mass and centre of pressure signals as neuromechanical input and output responses respectively. Both signals were modelled in time and frequency domains and stability margins were quantified by applying Nyquist and Bode (N&B) methods from control engineering theory. Results: Stability margins quantified from N&B methods illustrated the loading phase as stable and the unloading phase as unstable gait transitions. During the loading phase, both rotational impairments illustrated a decrease in stability (p < 0,05) for the ramp ascent walk and an increase in stability (p < 0,05) for the ramp descent walk. However, there was no difference observed for the respective unloading phases. Results from neuromotor outputs (CoP-velocity) illustrated a strong interlimb correlation (p < 0,001) during gait transitional periods, implying a compensatory stability interaction exists between opposite limbs. Further, stabilities quantified from outputs were found greater in magnitudes than the instability quantified from inputs illustrating the robustness of neuromotor balance control. Conclusions: Results support the hypothesis that gait stability gets affected while walking with rotation

关键词： Balance control Foot Gait stability Inclined walk Rotational impairments

来源：评论

学校读者我要写书评

暂无评论

Magnetically Actuated Capsule with Multiple Sampling Capability for Gut Microbiome Research

Magnetically Actuated Capsule with Multiple Sampling Capabil...

引用

International Conference on Control, Automation and Systems ( ICCAS)

作者： Sanghyeon Park Sukho Park Department of Robotics and Mechatronics Engineering DGIST Daegu Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

Understanding the relationship between gut microbiota and gastrointestinal (GI) diseases through longitudinal analysis is vital for advancing diagnosis and treatment methods. To achieve this, ingestible devices capable of multipoint gut microbiota sampling are necessary. Conventional devices move passively through the GI tract, relying on physiological factors and are unable to perform multipoint sampling. This study introduces a novel magnetically actuated capsule robot designed to collect gut microbiota from various GI tract locations while minimizing cross-contamination. The capsule includes a body, a driving unit, six sampling tools, a central rod, and two heads. It uses electromagnetic field control for precise orientation and position of the capsule, ensuring the sampling channel faces downward for accurate collection. The capsule can collect six distinct microbiota samples, protecting the tools from contamination throughout the process. Its active locomotion and sampling capabilities were tested through ex-vivo tests. The feasibility of clinical application was demonstrated in preclinical trials using a porcine model, confirming the capsule's potential for integration and use in medical settings.

关键词： Wireless communication Performance evaluation Microorganisms Magnetic heads Physiology Magnetic fields Robots Surface treatment Medical diagnostic imaging Diseases

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：