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Analysis and research on acceleration measurement methods for indoor large length standard devices 3

Analysis and research on acceleration measurement methods fo...

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3rd international conference on machine Vision, Automatic Identification, and Detection, MVAID 2024

作者： Hu, Changan Zhou, Chengyi Li, Xingxing Li, Li Lv, Fei Hu, Baoquan National Institute of Measurement and Testing Technology Chengdu610021 China School of Computer Science Chengdu Normal University Chengdu611130 China School of Engineering Xi’an International University Xi’an710077 China

ISBN: (纸本)9781510681880

The indoor long length standard device is an important large-size measuring standard device, which has an acceleration and deceleration process during the starting and stopping stages of the slide. Studying the acceleration of the indoor long length standard device is of great physical significance for understanding its operating rules. In the article, a laser tracker was used to study the acceleration of indoor large length standards. Through data analysis using a laser tracker at equal sampling frequencies of 50Hz and 100Hz, some conclusions were drawn as follows: the acceleration value significantly increases when the measurement frequency of the laser tracker is increased. The maximum acceleration at 50Hz is 579.75 mm/s2, and the maximum acceleration at 100Hz is 920 mm/s2. After the acceleration phase is completed, the sliding table enters a constant speed phase, and the data oscillates in a zigzag pattern with zero values. After the deceleration phase is completed, the acceleration value of the sliding table steadily approaches zero. © 2024 SPIE.

关键词： Deceleration

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Research on Algorithm for License Plate Detection in Complex Scenarios Based on Artificial intelligence 3

Research on Algorithm for License Plate Detection in Complex...

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3rd international conference on Communication Technology and Information Technology, ICCTIT 2023

作者： Ren, Fei Zhang, Tao Zhang, Chunmei Wang, Jian Yao, Menghan Liu, Sheng Doma, Bonifacio T. Intelligent Networking Engineering Technology Research Center Nanjing Intelligent Transportation Information Co. Ltd. Nanjing210000 China School of Information technology Mapua University Manila999005 Philippines Nanjing Intelligent Transportation Information Co. Ltd. Nanjing210000 China Technology Engineering Department Nanjing Intelligent Transportation Information Co. Ltd. Nanjing210000 China

ISBN: (纸本)9798350359664

With the advancement of transportation technology, the management of vehicles on the roadside has become a pressing issue for traffic management and parking authorities. Consequently, non-fixed-scene license plate detection has become a focal point for academic and industrial research and solutions. In response to the inadequacies of existing license plate detection algorithms in complex environments, such as different locations and angles, the papper employed the PaddleOcrV4 as license plate detection model based on deep learning. This model utilized PaddlePaddle as its foundational framework and replaces MobileNetv3 with PP-LCNetV3 in the license plate detection network to reduce interference from complex environmental backgrounds. In the license plate recognition network, PP-HGNet served as the backbone network, effectively improving detection accuracy. This paper primarily designed a solution for license plate detection and text recognition based on OCR technology. Experimental results indicated that the algorithm presented in this paper outperforms PaddleOcrV3 and PaddleOcrV3 in terms of detection accuracy, achieving a precision rate of 96% on the test dataset. © 2023 IEEE.

关键词： Industrial research

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Deep Learning and IoT for COVID Detection and Health Monitoring 3

Deep Learning and IoT for COVID Detection and Health Monitor...

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3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Devi, D.Rukmani Kingslin, M.Theodore Josphine, C.Vimala Manivannan, Kirankumar Rajavel, A. Ramalakshmi, R. R.M.D Engineering College Department of Electronics and Communication Engineering Chennai India R.M.K College of Engineering College & Technology Department of Electronics and Communication Engineering India R.M.K Engineering College Department of Artificial Intelligence and Data Science Chennai India Easwari Engineering College Department of Electronics and Communication Engineering India Electronics and Instrumentation Engineering Kamaraj College of Engineering and Technology Virudhunagar India Ramco Institute of Technology Department of Electronics and Communication Engineering Rajapalayam India

ISBN: (纸本)9798350343632

Covid-19 has been spreading globally since 2019, and the significant death toll from delayed detection has been a consequence. One way to solve this issue is to use AI to swiftly identify Covid-19 without having to deal with problems like a shortage of testing kits. To this end, this study has developed a system that uses both deep learning and machine learning techniques to detect the presence of Covid-19 in lung X-ray images. While the KNN method is used in machine learning to classify the image and detect COVID-19, DF-Net is used in deep learning to optimize the image and provide more clarity. Because DL and ML algorithms work together, this method combines the advantages of a high degree of accuracy with a shorter training period. This study also integrated a health monitoring system that uses Internet of Things (IoT) sensors to take a patient's temperature and heart rate;the data is updated on the cloud. © 2023 IEEE.

关键词： Deep Learning (DL) DF-Net Global Monitoring (GM) K-Nearest Neighbors (KNN) machine Learning (ML)

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Proceedings of AI4S 2022: Artificial intelligence and machine Learning for Scientific Applications, Held in conjunction with SC 2022: The international conference for High Performance Computing, Networking, Storage and Analysis

Proceedings of AI4S 2022: Artificial Intelligence and Machin...

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3rd IEEE/ACM international Workshop on Artificial intelligence and machine Learning for Scientific Applications, AI4S 2022

ISBN: (纸本)9781665462075

The proceedings contain 8 papers. The topics discussed include: automated continual learning of defect identification in coherent diffraction imaging;a case study on coupling OpenFOAM with different machine learning frameworks;PhySRNet: physics informed super-resolution network for application in computational solid mechanics;determining HEDP foams' quality with multi-view deep learning classification;pattern-based autotuning of OpenMP loops using graph neural networks;ensuring ai for science is science: making randomness portable;practical federated learning infrastructure for privacy-preserving scientific computing;and scalable integration of computational physics simulations with machine learning.

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Systematic Literature Review on Application of Artificial intelligence in Cancer Detection Using Image Processing 3

Systematic Literature Review on Application of Artificial In...

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3rd international conference on Artificial intelligence and Data Sciences, AiDAS 2022

作者： Chandra, Giovanni Irisha, Kevina Diva Vica, Vivianit Indyca Suri, Puti Andam Syahputra, Muhammad Edo School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781665491648

ISBN: (纸本)9781665491648

Having a low survival rate, cancer has become one of the deadliest diseases with complicated prognosis. In this matter, Artificial intelligence (AI) is frequently used to aid humans due to the difficulties of cancer identification. Specifically, the use of AI in cancer detection and treatment uses two of its subclasses, machine learning and deep learning. Because those two subclasses can handle large amounts of data, their algorithms can support humans in making decisions that yield the best possible results with the least amount of risk. The purpose of this research is to find out the effectiveness of the Artificial intelligence algorithm that is used in image processing to diagnose cancer and what is the most effective image processing algorithm for cancer diagnosis. The methods that are used in this research is Systematic Literature Review (SLR). As a result, Artificial intelligence algorithms are sufficiently effective to be used in diagnosing cancer with image processing. Meanwhile, the most effective algorithm is CatBoost with AUC of 0.939 and Support Vector machine (SVM) with AUC of 0.934. © 2022 IEEE.

关键词： Image processing

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3rd international conference on Intelligent Systems and pattern recognition, ISPR 2023

3rd International Conference on Intelligent Systems and Patt...

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3rd international conference on Intelligent Systems and pattern recognition, ISPR 2023

ISBN: (纸本)9783031463372

The proceedings contain 44 papers. The special focus in this conference is on Intelligent Systems and pattern recognition. The topics include: Staged Reinforcement Learning for Complex Tasks Through Decomposed Environments;policy Generation from Latent Embeddings for Reinforcement Learning;deep Learning Models for Aspect-Based Sentiment Analysis Task: A Survey Paper;A Real-Time Deep UAV Detection Framework Based on a YOLOv8 Perception Module;a Deep Neural Architecture Search Net-Based Wearable Object Classification System for the Visually Impaired;Multicarrier Waveforms Classification with LDA and CNN for 5G;Weeds Detection Using Mask R-CNN and Yolov5;Boruta-AttLSTM: A Novel Deep Learning Architecture for Soil Moisture Prediction;graph Autoencoder with Community Neighborhood Network;Study of Support Set Generation Techniques in LAD for Intrusion Detection;question-Aware Deep Learning Model for Arabic machine Reading Comprehension;a Hybrid Deep Learning Scheme for Intrusion Detection in the Internet of Things;identifying Discourse Markers in French Spoken Corpora: Using machine Learning and Rule-Based Approaches;A Comparative Study of the Impact of Different First Order Optimizers on the Learning Process of UNet for Change Detection Task;Minimal Window Duration for Identifying Cognitive Decline Using Movement-Related Versus Rest-State EEG;modeling Graphene Extraction Process Using Generative Diffusion Models;bird Species recognition in Soundscapes with Self-supervised Pre-training;on the Different Concepts and Taxonomies of eXplainable Artificial intelligence;Classifying Alzheimer Disease Using Resting State Coefficient of Variance BOLD Signals;proteus Based Automatic Irrigation System;How AI can Advance Model Driven Engineering Method ?.

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3rd international conference on machine intelligence and Smart Systems, MISS 2023

3rd International Conference on Machine Intelligence and Sma...

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3rd international conference on machine intelligence and Smart Systems, MISS 2023

ISBN: (纸本)9783031691140

The proceedings contain 59 papers. The special focus in this conference is on machine intelligence and Smart Systems. The topics include: Chronic Kidney Disease Prediction and Interpretation Using Explainable AI;systematic Review and Analysis of Artificial intelligence-Based Breast Cancer Classification and Detection;war of Tweets: Sentiment Analysis on Ukraine Russia Conflict;Implementing HRRN for Evaluating Cloud Performance Using Reinforcement Learning;using machine Learning for Prediction of Obstructions for Indoor Location Systems;privacy Threats and Protection in Artificial intelligence and machine Learning;Combining Linguistic Information with BERT for Span Based End-to-End Aspect Based Sentiment Analysis;a Dimensionality Reduction Model: A Retrospective Approach on Dementia Triggering Parameters and Feature Ranking;effective Identification of Lung Diseases Using Few-Shot Learning;comparative Study on Classification Based-Data Mining Techniques in Early Diabetes Prediction;optimize machine Learning Model for Sentiment Analysis of Online Education During Covid-19 Pandemic;review on the Challenges and Future Directions of Deep Learning-Based Techniques for Advance Prediction of Cardiac Attack;different Techniques for Detecting Plant Leaf Disease Using machine Learning;proposed Framework of Extensive Humanoid Design Cycle and Recent Developments in Bipedal Walk;natural Language Processing for Waste Management Using Public Opinions in Smart Cities;prediction of Diabetes During Pregnancy Through Fog Environment;empirical Wavelet Transform Grounded Poignant Ground Target recognition and Classification by Seismic Signal Processing;A Powered-Up Classification of Disabling Distributed Network Cloud-Based Attacks Using MLPNN-BP and MLPNN-LM;stroke Prediction Framework Based on Missing Value Information and Outlier Detection by Using machine Learning Techniques in E-Healthcare;magnetic Resonance Imaging Digitization for Brain Abnormality recognition.

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3rd international conference on machine intelligence and Smart Systems, MISS 2023

3rd International Conference on Machine Intelligence and Sma...

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3rd international conference on machine intelligence and Smart Systems, MISS 2023

ISBN: (纸本)9783031317224

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Characterising IoT for Smart development: Anaylsing the challenges 3

Characterising IoT for Smart development: Anaylsing the chal...

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3rd international conference on Innovative Practices in Technology and Management, ICIPTM 2023

作者： Malhotra, Snighdha Agarwal, Vernika Anjum, Misbah Parashar, Akshay Fortune Institute of International Business New-Delhi India Amity International Business School Amity University Uttar Pradesh Noida India Amity Institute of Information Technology Amity University Uttar Pradesh Noida India

ISBN: (纸本)9798350336238

Industry 4.0 is all about putting industrial data from multiple sources into a data lake and then using analytics, artificial intelligence, machine learning to utilize the data for businesses. The primary reason for that is the advent of the Internet of Things (IoT). IoT has enabled uninterrupted sharing and exchange of data for its users from the consumer to the industrial level. Although still in the nascent stage of evolution, IoT has the potential to significantly impact business outcomes and will be instrumental in bringing a transformation in the way we communicate and exchange information. However, there remains a considerable gap in identifying the challenges in the implementation of IoT platforms and techniques. This paper aims at presenting a comprehensive analysis of the major challenges in the implementation of IoT and classifies them into two broad categories-technological and managerial according to the opinions of the experts. An attempt has been made herein to create a hierarchy depicting the key challenges where the researchers and industry should focus their attention and make better strategic decisions. A multi-criteria decision-making method known as the Best-Worst Method (BWM) has been used to rate the challenges. Results show that power requirement is the major challenge in technological challenges and maintenance is the major challenge in managerial challenges. © 2023 IEEE.

关键词： Internet of things

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23rd international conference on Next Generation Wired/Wireless Networking, NEW2AN 2023, and 16th conference on Internet of Things and Smart Spaces, ruSMART 2023

23rd International Conference on Next Generation Wired/Wirel...

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23rd international conference on Next Generation Wired/Wireless Networking, NEW2AN 2023, and 16th conference on Internet of Things and Smart Spaces, ruSMART 2023

ISBN: (纸本)9783031609930

The proceedings contain 67 papers. The special focus in this conference is on Next Generation Wired/Wireless Networking. The topics include: Detecting PII Leakage Using DPI and machine Learning in an Enterprise Environment;deep Learning for Preventing Botnet Attacks on IoT;Design of Multi-polarisation MIMO Antenna for Heterogeneous Smartphone Applications;potential Possibilities of Voice pattern recognition by a Distributed Fiber Optic Sensor;Enhancing Wireless Connectivity Through Bayesian-Optimized UAV-BS Positioning and Charging;comparison of Centralized and Federated machine Learning Techniques for Beamtracking in 5G/6G Systems;exploring the Efficiencies and Vulnerabilities of Smart Door Control Systems: A Systematic Review;System-Level Model for SINR and HPBW Evaluation in 5G mmWave UDN with Location-Aware Beamforming;reinforcement Learning Based Power Allocation for 6G Heterogenous Networks;The Impact of Capacity Averaging in Packet-Level Modeling of 5G NR with Blockage and Micromobility;Interference Mitigation for Reconfigurable Intelligent Surface (RIS)-Aided Non-terrestrial Base Station (NTBS) in NOMA Downlink HetNets;modeling a Digital Avatar of a Car Drivers Based on the Quantification of the Information Environment;A New Blockage Detection Approach for 6G THz Systems;real-Time Anomaly Detection in Network Traffic Using Graph Neural Networks and Random Forest;addressing Security and Privacy Issues in a Smart Environment by Using Blockchain as a Preemptive Technique;the Role of Cryptocurrencies in the Development of Countries and the Fight Against Financial Problems;Designing the UzBCS Lending Platform Network Based on Blockchain Technology and Ensure Transaction Security;decentralized Blockchain Networks and Economic Security: Balancing Scalability and Security Tradeoffs;study of machine Learning Models for IoT Based Efficient Classroom Usage;transforming Higher Education: A Comprehensive Analysis of Blockchain Technologies and Digitalization.

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