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Recent advances and new frontier of flexible pressure sensors: Structure engineering, performances and applications

MATERIALS TODAY PHYSICS 2024年 48卷

作者： Jiang, Tianhui Wang, Chunnan Ling, Tianyi Sun, Shuqing Yang, Lei Shenzhen Univ Shenzhen Peoples Hosp 2 Dept Spine Surg & Orthoped Affiliated Hosp 2 Shenzhen 518035 Peoples R China Shenzhen Second Peoples Hosp Med Innovat Technol Transformat Ctr Shenzhen 518035 Peoples R China Tsinghua Univ Inst Biopharmaceut & Healthcare Engn Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China

Global research on flexible pressure sensors for evaluating human wellness and intelligent robotics is intensifying due to their advantages of excellent flexibility, lightweight design, high sensitivity and ease of integration. To facilitate practical applications, challenges associated with high-performance must be addressed, such as the trade-off between high sensitivity and a wide linear sensing range, fast response/recovery time, limited hysteresis, and stability under both dynamic and static pressure conditions. Moreover, ensuring the sensors' reliability under various interferences and their multi-functionality to meet diverse usage requirements is essential for future applications. In this review, we summarize the latest advancements in multiple microstructures within the active layer and/or electrodes, which ensure excellent sensing performances, superior reliability and multifunctional features. Specifically, we focus on the design, working principles and sensing features of advanced micropattern, micropores, fiber-network, and hybrid microstructures in pressure sensors based on hierarchical micro-/nano-structure, conductive gradient coatings or multilayer structures. Additionally, the applications of microstructured pressure sensors in the fields of healthcare and human-machine interaction are summarized. Finally, we discuss the challenges and future prospects in the development of the next generation of flexible pressure sensors.

关键词： Flexible pressure sensor Multiple microstructures Sensing performance Wearable electronics Health monitoring

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LES Analysis on the Impact of Mass Conservation Uncertainty on the Static Pressure Fluctuation in Spatially Periodic Steady Turbulence 2

LES Analysis on the Impact of Mass Conservation Uncertainty ...

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2nd international conference on Automation, robotics and Computer engineering, ICARCE 2023

作者： Gong, Xuanyou Suzuki, Hiroki Nakahama, Mikio Kouchi, Toshinori Graduate School of Environmental Life Natural Science and Technology Okayama University Okayama City Japan Graduate School of Natural Science and Technology Okayama University Okayama City Japan

ISBN: (纸本)9798350308341

This study investigates the effect of mass-conserving uncertainty on the static pressure fluctuation characteristics in incompressible isotropic steady turbulence. The mass conservation uncertainty can be produced by relaxing the convergence of the Poisson equation solved in the fractional stages. This mass-conserving uncertainty may often be found acceptable in fluid analysis. In incompressible flows, the mass conservation uncertainty is quantified as the spatial variation RMS of the velocity divergence. The analysis is analyzed as a large-eddy simulation, and the SGS components are modelled using the Smagorinsky and coherent structure models. First, the steady-state turbulence generated in the case without mass-conserving uncertainty is tested to be independent of the differences between these SGS models. Then the spatial fluctuation RMS of the velocity divergence is validated to be significant. © 2023 IEEE.

关键词： Turbulence

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Recent Advancements in Machine Learning and IoT for Health care 15

Recent Advancements in Machine Learning and IoT for Health c...

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15th international conference on advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Vani, K.S. Basavaraju, T.G. Surekha, K.B. Department of Information Science and Engineering Nitte Meenakshi Institute of Technology Karnataka Bangalore India Department of Computer Science and Engineering Government College of Engineering Hassan India Department of Information Science and Engineering BMSIT Bangalore India

ISBN: (纸本)9798331300579

In the current landscape of healthcare, Machine Learning (ML) and the Internet of Things (IoT) are making significant strides. Ongoing research focuses on remote patient monitoring, disease prediction, and diagnostic imaging, utilizing wearable devices and sensors. ML algorithms contribute to drug discovery, personalized medicine, and operational efficiency, predicting equipment failures and optimizing resource allocation. This paper surveys the most recent papers on ML and IoT in health care. This survey of ML and IoT in healthcare highlights diverse applications, from automated diabetes prediction to breast cancer detection. Utilizing wearable devices and sensors, these technologies provide real-time health insights and personalized interventions. Challenges such as data security and limited datasets are identified, prompting the need for future improvements. © Grenze Scientific Society, 2024.

关键词： Electronic health record

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Breakthroughs in Cognitive Robots and AI Programming Underpinned by Discoveries in Intelligence science and Software science

Breakthroughs in Cognitive Robots and AI Programming Underpi...

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2023 international conference on Frontiers of robotics and Software engineering, FRSE 2023

作者： Wang, Yingxu Schulich School of Engineering and Hotchkiss Brain Institute University of Calgary 2500 University Drive NW CalgaryABT2N 1N4 Canada

ISBN: (纸本)9798350301113

Breakthroughs of basic research in Intelligence science (IS) [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], Cognitive Computing (CC) [14], [15], [16], [17], [18], [19], [20], [21], [22], [22], [23], [24], [25], [26], and Cognitive Informatics (CI) [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], have triggered the emergence of Cognitive Robots (CR) [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49] towards software science (SS) [50], [51], [52], [53], [54], [55] and autonomous software engineering (SE) [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66]. These latest advances have enabled the synergy of classical pre-programmed software engineering and pre-trained AI to an unprecedented platform of training-free machine intelligence generation mimicking human brains and Brain-Inspired Systems (BIS) [67], [68], [69], [70], [71], [72], [73], [74]. It is discovered in IS and CC in general, as well as in CR and SE in particular, that the target entities across these contemporary fields had already out of the denotational power of the classic mathematical domains of real (R) and binary (B) numbers [76]. This leads to the latest discovery that the basic unit of human knowledge as a hyperstructure [50] is a binary relation (bir) [74]. Therefore, a new framework of Intelligence Mathematics (IM) [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94], [95], [96], [97], [98], [99], [100] has been created for rigorously manipulating the cognitive entities in the brain and CRs spanning from formal concepts, semantics, knowledge, causalities, inferences, and consciousness by contemporary IMs for advancing both AI [1], [2], [3] and SE [56], [58]. This keynote lecture presents fundamental theories and ground-breaking technologies for designing and implementing cognitive robots based on AI Programming (AIP) [101], [102], [103], [104], and Autonomous

关键词： Robot programming

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An Intuitive Six-DOF Admittance Control Method for Human-Robot Collaboration

An Intuitive Six-DOF Admittance Control Method for Human-Rob...

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2024 IEEE international conference on robotics and Biomimetics, ROBIO 2024

作者： Meng, Yuming Jiang, Xin Brelen, Marten Erik Liu, Yun-Hui School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China The Chinese University of Hong Kong Department of Ophthalmology and Visual Sciences Hong Kong Hong Kong T Stone Robotics Institute The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Hong Kong Hong Kong

ISBN: (纸本)9781665481090

Admittance control is a well-established frame-work for enhancing human-robot collaboration. Although it is widely applied in translational tasks, the a six-degree-of-freedom (6-DOF) admittance control involving the use of a handle in both translational and rotational spaces is rarely addressed in the literature. This paper introduces 6-DOF admittance control method that utilizes a handle equipped with a force/torque sensor mounted on the robotic arm to intuitively farme the operation of the end effector. By transforming the force/torque applied to the handle into the operation of the end-effector while preserving the operator's intent, intuitive 6-DOF admittance control is achieved. To eliminate the operational risks associated with the uncertainty of the hand's contact point on the handle, uncertainty shielding is implemented, ensuring stable force/torque calculations. The effectiveness of the proposed 6-DOF admittance control method is validated through an assembly operation and a specific trajectory operation. © 2024 IEEE.

关键词： End effectors

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Agriculture Monitoring System Using IoT and ML Smart and Improved Farming

Agriculture Monitoring System Using IoT and ML Smart and Imp...

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2024 international conference on advances in Computing Research on science engineering and technology, ACROSET 2024

作者： Jamwal, Anupama Kumari, Nikita Pandey, Priyanka Rohan Heenureet Chandigarh University Computer Science Chandigarh India

ISBN: (纸本)9798350388800

This research paper investigates the development of a Smart Agriculture Monitoring System using IoT technology to optimize agricultural processes. The project aims to enhance crop yield, reduce resource consumption, and provide real-time insights to farmers. The system concentrates on data preparation, anomaly detection, and classification to efficiently monitor and manage agricultural activities. It does this by utilizing machine learning and Python programming approaches. The suggested method incorporates Internet of Things sensors to gather information on a number of variables, including humidity, temperature, and soil moisture. Prior to being examined for anomalies suggestive of possible problems such as insect infestation or nutritional deficits, these data are preprocessed to guarantee accuracy and dependability. For classification jobs, machine learning techniques are used, which allows the system to classify data & give farmers useful insights. The Smart Agriculture Monitoring System enables farmers to make well-informed decisions, increase crop yield, and optimize resource consumption by offering real-time monitoring and analysis. Through encouraging effective resource management and proactive problem-solving in farming operations, the project supports sustainable agriculture practices. © 2024 IEEE.

关键词： Smart agriculture

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A Review of Activity Detection Methods Used in Videos Streaming

A Review of Activity Detection Methods Used in Videos Stream...

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2023 international conference on robotics and Automation in Industry, ICRAI 2023

作者： Khursheed, Sehrish Khalid, Samina Riaz, Farzana Shehryar, Tehmina Department of Computer Science & Information Technology AJK Mirpur Pakistan

ISBN: (纸本)9781665464727

Activity detection in videos embraces many recent sub-research directions, such as Action Recognition (what type of activity is being performed), Temporal Action Detection (that states the time of action occurred in a large video), Spatio-Temporal Action Detection (localizing activities both in space and time). New advances in convolutional Neural Network Architectures and increased computing resources have made it possible. 3 Dimensional CNNs outperform 2D CNNs in balancing both spatial and temporal information in activity recognition while working with videos. Various approaches which incorporate these networks have been discussed in the paper. Locating a specific action in a video is an advanced and more complex task. Our focus of the paper is to give a summary of methods and advances used in the domain of action recognition and action localization. © 2023 IEEE.

关键词： Video streaming

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Research on the Automatic Statistical technology of Construction Progress of Substation engineering Based on AI and AR 5

Research on the Automatic Statistical Technology of Construc...

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5th international conference on advances in Electrical engineering and Computer Applications, AEECA 2024

作者： Qin, Kuangyu Zhong, Bin Lan, Qiaoqian State Grid Shanghai Municipal Electric Power Company State Grid Shanghai Electric Power Company Development Planning Department Shanghai China

ISBN: (纸本)9798350355253

Currently, mobile augmented reality (AR)-based construction visualization technologies offer diverse interaction modes but struggle with in-depth applications such as schedule and investment statistics due to issues of low accuracy and inadequate system integration. To mitigate these challenges, this study leverages simultaneous localization and mapping (SLAM) technology to capture real-time, comprehensive images from construction sites. This approach is grounded in the investment management "cascade neural network model."By integrating building information modeling (BIM) and image recognition technologies, we achieve real-time registration of the construction scene and BIM models using mobile AR technology. This enables the comparison of engineering quantities, analysis of project completion, and precise monitoring of project progress, thereby laying a critical foundation for subsequent digital and intelligent statistical analyses. © 2024 IEEE.

关键词： Investments

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Navigating Player Performance Clusters for Sports Excellence

Navigating Player Performance Clusters for Sports Excellence

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2024 international conference on advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Melvin, A. Sai Sabitha, A. Hindustan Institute Of Technology And Sciences Department Of Computer Science And Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350364828

A strategic tactics is required to navigate the challenging process of athlete selection within budgetary limits, seeing it as a multiple-objective, multi-criteria optimization challenge. However, judgments made by humans are fallible and subjective, and choices made using a single criterion are insufficient and erratic. An approximate decision making in the calculation of cricket players selection is addressed in this work. The player can be selection based on the batsman and bowler object. The value is calculated using the various bowler and batsmen parameters. The performance of the selection of players are evaluated with using K-mean and GMM (Gaussian Mixture Model) machine learning algorithms and Recommender System Method. © 2024 IEEE.

关键词： Sports

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Logistic Regression Based Approach for Human Sentiment Analysis Across Domains

Logistic Regression Based Approach for Human Sentiment Analy...

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2024 international conference on advances in Computing Research on science engineering and technology, ACROSET 2024

作者： Nagar, Sameer Bhanodia, Praveen Sethi, Kamal Kumar Rathore, Narendra Pal Singh Acropolis Institute of Technology and Research Department of Computer Science and Engineering Indore India

ISBN: (纸本)9798350388800

This research paper presents a pioneering approach to cross-domain sentiment analysis utilizing logistic regression, a widely employed technique for binary classification tasks. Sentiment analysis, crucial for understanding subjective information in text data, finds applications in market analysis, customer feedback processing, and brand management. Our methodology involves extracting sentiment features from text data, leveraging techniques such as bag-of-words or word embeddings, and training logistic regression models on labeled datasets from diverse domains. Unlike conventional methods relying solely on domain-specific features, our approach incorporates domain-independent features to facilitate knowledge transfer across domains. Through extensive experiments on various datasets including product reviews, social media posts, and news articles, we demonstrate the effectiveness of our approach in achieving competitive performance compared to state-of-the-art methods. Additionally, we explore the impact of domain adaptation techniques such as domain adversarial training and transfer learning on model performance, providing insights into the interpretability of sentiment models and enabling more accurate sentiment prediction in real-world scenarios across diverse domains. © 2024 IEEE.

关键词： Logistic regression

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