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An OPC UA-based industrial Big Data architecture 21

An OPC UA-based industrial Big Data architecture

引用

IEEE 21st International conference on Industrial Informatics (INDIN)

作者： Hirsch, Eduard Hoher, Simon Huber, Stefan Salzburg Univ Appl Sci JR Ctr Intelligent & Secure Ind Automat A-5412 Puch Austria

ISBN: (纸本)9781665493130

Industry 4.0 factories are complex and data-driven. Data is yielded from many sources, including sensors, PLCs, and other devices, but also from IT, like ERP or CRM systems. We ask how to collect and process this data in a way, such that it includes metadata and can be used for industrial analytics or to derive intelligent support systems. This paper describes a new, query model based approach, which uses a big data architecture to capture data from various sources using OPC UA as a foundation. It buffers and preprocesses the information for the purpose of harmonizing and providing a holistic state space of a factory, as well as mappings to the current state of a production site. That information can be made available to multiple processing sinks, decoupled from the data sources, which enables them to work with the information without interfering with devices of the production, disturbing the network devices they are working in, or influencing the production process negatively. Metadata and connected semantic information is kept throughout the process, allowing to feed algorithms with meaningful data, so that it can be accessed in its entirety to perform time series analysis, machine learning or similar evaluations as well as replaying the data from the buffer for repeatable simulations. © 2023 IEEE.

关键词： big data data retrieval device decoupling information model IT/OT integration OPC UA query model

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An Improved Affine Projection Tanh Algorithm for Robust Adaptive Filtering 15

An Improved Affine Projection Tanh Algorithm for Robust Adap...

引用

15th International conference on Signal processing systems, ICSPS 2023

作者： Song, Pucha Zhao, Haiquan Luo, Li School of Electronic Information and Electrical Engineering Chengdu University Chengdu China School of Electrical Engineering Southwest Jiaotong University Chengdu China

ISBN: (纸本)9781510675056

Recently, an affine projection tanh (APT) algorithm has been designed based on optimization criteria with hyperbolic tangent function constraints. However, there is a significant steady-state error in the APT algorithm. To address this drawback, this article presents an improved APT (IAPT) algorithm based on the optimization framework with hyperbolic tangent function square constraints. It is shown that the proposed IAPT algorithm displays strong robustness, higher convergence speed, and smaller estimation error compared to affine projection (AP) algorithm, AP sign algorithm (APSA) and APT algorithms under the impulsive noise disturbance in the system identification application scenario. © 2024 SPIE.

关键词： Impulse noise

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Automated Document processing: Combining OCR and Generative AI for Efficient Text Extraction and Summarization

Automated Document Processing: Combining OCR and Generative ...

引用

2024 International conference on Innovative Computing, Intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Abinaya, G. Rao, Guttulapavan Durga Gopal, Pragada Sri Ram Kaushik, M. Vignesh, B. Sai Venkata Srmist Department of Networking and Communications Chennai603203 India

ISBN: (纸本)9798331543617

Technological advancement including the use of new media formats in creating digital documents calls for the development of enhanced processing techniques and methods. Old school optical Character Recognition (OCR) tools remain useful but are inadequate when faced with sophisticated documents or low-quality scans. Also, summarizing the textual content of such papers continues to be a manual process and adds inefficiency and potential errors in information gathering. Finally, an integrated approach to the automation of both text extraction and summarization based on improved OCR and Google Gemini's generative AI technique is presented in this paper. By using more precise OCR algorithms, the system greatly increases accurate text recognition from poorly quality scans or complex structures. At the same time, the employment of generative AI models contributes to the formulation of brief and relevant summaries and also improves document retrieval and handling. Its effectiveness has thus been confirmed by testing on a variety of documents, and it has increased both accuracy and utility compared to previous techniques. © 2024 IEEE.

关键词： optical character recognition

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Research on optical detection technology for underwater archaeology 3

Research on optical detection technology for underwater arch...

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3rd International conference on Image processing and Intelligent Control, IPIC 2023

作者： Mu, Wei Zheng, Ruohan Zhang, Wenrui Zhuhai519082 China School of Marine Engineering and Technology Sun Yat-Sen University Zhuhai519082 China

ISBN: (纸本)9781510668140

In response to the problem that the current image processing technology and underwater target recognition algorithms are not yet mature enough in the field of underwater archaeology, this article innovatively applies object detection and underwater image clarity technology to the field of underwater archaeology. We propose a method for detecting and recognizing underwater cultural heritage based on optical devices. The method includes ocean image preprocessing and underwater cultural heritage object recognition based on YOLO V4. The results of experiments demonstrate that the proposed method can effectively and accurately detect and recognize targets in the underwater cultural heritage scene, and the clear image of the underwater relics after image preprocessing can better assist archaeologists in observing the species and distribution of samples in the real scene. © 2023 SPIE.

关键词： Object recognition

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Sparse Recovery Space Time Adaptive processing Based on Log-Determinant 15

Sparse Recovery Space Time Adaptive Processing Based on Log-...

引用

15th International conference on Signal processing systems, ICSPS 2023

作者： Chang, Yuqing Du, Xiaolin Jin, Biao Tian, Tuanwei Li, Jianbo School of Computer and Control Engineering Yantai University Yantai China Ocean College Jiangsu University of Science and Technology Zhenjiang China School of Physics and Electronics Henan University Kaifeng China School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (纸本)9781510675056

Airborne radars usually face non-uniform clutter environments, and it is difficult to obtain enough independent and identical distributed (i.i.d.) training samples, which degrades the clutter suppression performance of space time adaptive processing (STAP). To address the problem, a log-determinant sparse rocovery based STAP (LSR-STAP) method is proposed in this paper. Through the sparse recovery theory of low-rank matrices and the prior knowledge of clutter covariance matrices, the corresponding problem is modeled using the log-determinant (LogDet) approximation of the rank function, and the solution of the resulting nonconvex optimization problem is derived in the framework of the symmetric alternating direction method of multipliers (S-ADMM). The simulation results show the superiority of the proposed method over similar algorithms. © 2024 SPIE.

关键词： Space time adaptive processing

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Influence of Histogram Equalization on Multi-Classification of Retinal Diseases in OCT B-scans 27

Influence of Histogram Equalization on Multi-Classification ...

引用

27th IEEE Signal processing: algorithms, Architectures, Arrangements, and Applications, SPA 2024

作者： Marciniak, Tomasz Stankiewicz, Agnieszka Poznan University of Technology Institue of Automatic Control and Robotics Department of Automatic Control Robotics and Electrical Engineering Poznan Poland

ISBN: (纸本)9788362065486

The aim of this article is to analyze the impact of adaptive histogram equalization of the human eye OCT B-scans on the effectiveness of the classification of pathological changes. Tests were performed on two datasets. The first dataset contains 4 class B-scans (CNV, DME, DRUSEN, and NORMAL) taken with the use of Spectralis Heidelberg device, while the second dataset contains images from two devices (Spectralis Heidelberg OCT and Avanti Optovue OCT) and additionally contains the VMT (i.e., vitreomacular traction) class. The images were subjected to standard histogram equalization and contrast limited adaptive histogram equalization (CLAHE) with various parameters. The classification process was carried out using VGG16 artificial neural network. It can be observed that histogram equalization has no significant impact on improving classification performance. © 2024 Division of Signal processing and Electronic systems, Poznan University of Technology (DSPES PUT).

关键词： optical coherence tomography

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Surface segmentation method based on multi-feature fusion for regionally grown workpiece point clouds 4

Surface segmentation method based on multi-feature fusion fo...

引用

4th International conference on Image processing and Intelligent Control, IPIC 2024

作者： Zhao, Haoxi Zhang, Zhijia Wang, Hongyu School of artificial Intelligence Shenyang University of Technology Shenyang China

ISBN: (纸本)9781510682313

In order to improve the segmentation accuracy of 3D point cloud model in feature ambiguous region, the unsupervised clustering algorithm based on surface fusion features combines the depth residuals with the normal deviation angle to form the fusion features with good descriptive properties and significant differentiation. Adopting the point cloud local density median proximity points as the candidate points for point cloud region growth, using point cloud cluster features instead of individual point features, for the problem of feature ambiguity in the edge region, the unattributed points are reclustered, so as to improve the cluster segmentation in the way of extended growth;experiments are conducted on the selected model dataset, and the results show that the method can achieve the reasonable segmentation of the complex point cloud model, and the under-segmentation situation has a obvious improvement on the under-segmentation situation. © 2024 SPIE.

关键词： Point clouds Image segmentation 3D modeling Feature fusion Fuzzy logic Spherical lenses Evolutionary algorithms Feature extraction Image processing algorithms and systems Object recognition

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Lightweight Stereo Image Super-Resolution Using Parallax Attention

Lightweight Stereo Image Super-Resolution Using Parallax Att...

引用

2024 International conference on Advancements in Power, Communication and Intelligent systems, APCI 2024

作者： Govind, Smriti Pradeep, R. College of Engineering Trivandrum Dept. of Electronics and Communication Engineering Kerala India Apj Abdul Kalam Technological University India

ISBN: (纸本)9798350363289

Over the past decade, advancements in cellular phone technology have drastically transformed mobile phones from mere communication devices into powerful mini-computers. The integration of high-quality cameras with smartphones has led to a surge in demand for high-resolution images captured using these compact handheld devices. Prevalent use of dual cameras in smartphones has further motivated the exploration of stereo image super-resolution (SSR) algorithms, which utilizes the complementary information provided by binocular system. In this paper, we propose a novel and simple SSR approach that incorporates depth-wise separable convolutions and a parallax attention module. The algorithm effectively employs depth-wise separable convolutions to extract features from both left and right view of stereo image pair. Additionally, the parallax attention module facilitates the integration of cross-view information to enhance the super-resolution process. By combining these techniques, the proposed SSR model, Light weight Parallax Attention Stereo Image Super-Resolution(L-PASSR) achieves a light weight design while still delivering comparable results in stereo image enhancement. © 2024 IEEE.

关键词： Stereo image processing

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An Efficient Cluster-Based Asynchronous Activity Detection Algorithm for Cell-Free Massive MIMO systems 16

An Efficient Cluster-Based Asynchronous Activity Detection A...

引用

16th International conference on Wireless Communications and Signal processing, WCSP 2024

作者： You, Chenhao Li, Ziheng Wang, Tong Gao, Lin Jiang, Yufei School of Electronics and Information Engineering Harbin Institute of Technology Shenzhen China School of Electronics and Information Engineering Harbin Institute of Technology Guangdong Provincial Key Laboratory of Aerospace Communication and Networking Technology Shenzhen China

ISBN: (纸本)9798350390643

In this paper, we propose an efficient cluster-based activity detection algorithm for asynchronous grant-free random access (GFRA) cell-free massive multiple-input multiple-output (CF-mMIMO) systems. To address the uncertain delay challenge in the asynchronous transmission scenario, we aim to enhance the accuracy of active user devices detection and meanwhile reducing the computational complexity of the detection process by utilizing an efficient cluster-based block coordinate descent (BCD) activity detection algorithm. This challenge is heightened in the context of ultra-reliable low-latency communications (URLLC), where precise and timely detection of active users is crucial. To enhance the efficiency of the detection process, we investigate an active set strategy to reduce the number of potential active user devices requiring identification. The accuracy of active user device detection for asynchronous GFRA in CF-mMIMO systems is significantly enhanced by the implementation of the proposed cluster-based BCD algorithm with active set. Simulation results demonstrate that the proposed algorithm achieves superior detection performance with lower computational complexity compared to the traditional algorithms. © 2024 IEEE.

关键词： Clustering algorithms

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3rd International conference on information Technologies and Intelligent Decision Making systems, ITIDMS 2023

3rd International Conference on Information Technologies and...

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3rd International conference on information Technologies and Intelligent Decision Making systems, ITIDMS 2023

ISBN: (纸本)9783031603174

The proceedings contain 18 papers. The special focus in this conference is on information Technologies and Intelligent Decision Making systems. The topics include: Comparative Analysis of Traditional Machine Learning Approaches for Time Series Clustering Under Colored Noise;on the Open Transport Data Analysis Platform;investigation of the Characteristics of a Frequency Diversity Array Antenna;comparative Analysis of Fuzzy Controllers in a Truck Cruise Control System;implementation of a Blockchain-Based Software Tool to Verify the Authenticity of Paper Documents;development of Methods and algorithms for Dimension Reduction of Space Description for Pattern Recognition Problem;service for Checking Students’ Written Work Using a Neural Network;implementing a Jenkins Plugin to Visualize Continuous Integration Pipelines;elimination of optical Distortions Arising from In Vivo Investigation of the Mouse Brain;quantum Fourier Transform in Image processing;choosing an information Protection Mechanism Based on the Discrete Programming Method;application of Machine Learning Methods for Annotating Boundaries of Meshes of Perineuronal Nets;diagnostics of Animals Diseases Based on the Principles of Neutrosophic Sets and Sugeno Fuzzy Inference;the Technique of processing Non-Gaussian Data Based on Artificial Intelligence;development of Automation and Control System of Waste Gas Production Process Based on information Technology;machine Learning and Data Mining.

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