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检索条件"任意字段=3rd IEEE Intelligent Data Acquisition and Advanced Computing Systems"

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Computer data processing mode in the era of big data: From pattern recognition to intelligent sensing 3

Computer data processing mode in the era of big data: From p...

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3rd International Conference on intelligent Sustainable systems, ICISS 2020

作者： Huaiyong, Deng Qing, Ma ChongQing Water Resources and Electric Engineering College Chong qing402160 China

ISBN: (纸本)9781728170893

Computer data processing mode in the era of big data from pattern recognition to intelligent sensing is discussed in this paper. Intelligence refers to the interconnection between things and things and people through the Internet of Things and mobile Internet, combined with the general big data computing, communication, artificial intelligence and other technologies. Neighborhood dependence reflects the proportion of approximate samples to all samples under decision class in mixed information system, and it is also a measure to describe the degree of relationship between conditional attribute set and decision attribute, so it can be used as a heuristic function to reduce the attribute of mixed information system. This paper designed the model from the collection to processing, from pattern analysis to the intelligent sensing. The experimental results have proven that the proposed model can sense the data effectively. © 2020 ieee.

关键词： Pattern recognition

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Investigation of Hybrid Beamforming in mmWave Massive MIMO systems 5

Investigation of Hybrid Beamforming in mmWave Massive MIMO S...

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5th ieee International Symposium on Smart and Wireless systems within the International Conferences on intelligent data acquisition and advanced computing systems, IDAACS-SWS 2020

作者： Mihaylova, Dimitriya Valkova-Jarvis, Zlatka Poulkov, Vladimir Stoynov, Viktor Iliev, Georgi Technical University of Sofia 8 Kliment Ohridsky Blvd Sofia1000 Bulgaria

ISBN: (纸本)9781728199603

Conventional MIMO systems usually achieve diversity gain by the use of baseband Digital Signal Processing. However, in millimeter wave massive MIMO systems digital precoding is impractical, due to the large antenna array which increases the energy consumption and processing complexity. To alleviate these problems, hybrid beamforming can be used instead. In this paper, the main principles and major considerations of hybrid beamforming are presented. A low-complexity hybrid precoder is discussed and its performance is investigated in scenarios where large numbers of users are served. © 2020 ieee.

关键词： Millimeter waves

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Despeckling of Synthetic Aperture Radar (SAR) Images Using Local Statistics-Based Adaptive Filtering 3rd

Despeckling of Synthetic Aperture Radar (SAR) Images Using L...

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3rd International Conference on intelligent computing and Communication (ICICC)

作者： Bhateja, Vikrant Bishnu, Ankita Rai, Ankita Shri Ramswaroop Mem Grp Profess Coll SRMGPC Dept Elect & Commun Engn Faizabad Rd Lucknow 226028 Uttar Pradesh India

ISBN: (纸本)9789811510847;9789811510830

Synthetic Aperture Radar (SAR) images are speckle corrupted right at the initial stage of their acquisition due to repeated backscattering signals from the uniformly distributed target sites. Addition of speckle noise in the images causes poor visualization, image analysis and image translation. For this reason, despeckling of the image data is important to not only remove the speckle but also preserve the finer details without losing them. In this paper, a method of despeckling using local statistics-based adaptive filtering has been proposed which can be used in all kinds of speckle environment especially in higher speckle levels. The filter is adaptive in nature as the size of the filtering window which is being used in this method can be varied to despeckle those regions with fully developed speckle and protect minute details. The filtering competency of the proposed filter is then scrutinized and compared using various metrics like Peak Signal-to-Noise Ratio (PSNR) and Speckle Suppression Index (SSI) on different speckle variances.

关键词： SAR images Speckle Despeckling Adaptive filtering Local statistics

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RGB-D Sensors Extrinsic Calibration In Controlled Environment

RGB-D Sensors Extrinsic Calibration In Controlled Environmen...

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ieee International Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

作者： Krasimir Tonchev Agata Manolova Nikolay Neshov Vladimir Poulkov Teleinfrastructure Lab Technical University of Sofia Bulgaria Faculty of Telecommunications Technical University of Sofia Bulgaria

ISBN: (纸本)9781665426060

RGB-D sensors provide rich information about the scene including color and 3D data. This information is valuable for the forthcoming analysis on the object of interest or the scene as a whole. Depending on the task, multiple sensors might be needed in order to provide details about process under observation. In this case, calibration between the sensors is necessary in order to provide consistent information related to the 3D world. A lot of work has been done related to RGB-D sensor calibration, since the introduction of Kinect in 2010, however it is still an active area of research. In this paper we propose an algorithm for RGB-D sensors extrinsic calibration, in a scenario where each sensor is located in closed and known environment. This knowledge of the environment helps to exploit its structure in the most optimal way for the calibration process. It includes planes locations and planes relative position. We propose two stage procedure for extrinsic calibration, in pairwise and global manner. The experimental results validate our approach for real applications.

关键词： Three-dimensional displays Image color analysis Conferences Semantics data acquisition Lighting Sensor phenomena and characterization

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Research on Hierarchical Autonomous Operation Monitoring of Energy Stations Based on Cloud Technology

Research on Hierarchical Autonomous Operation Monitoring of ...

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3rd ieee Student Conference on Electrical Machines and systems (SCEMS)

作者： Liu, Fei Qiang, Fangyuan Tian, Chao Shi, Ke Wang, Lei Hu, Donggang State Grid Qinghai Elect Power Corp Guoluo Power Supply Co Xining Qinghai Peoples R China Qinghai Green Energy Data Co Ltd Xining Qinghai Peoples R China

ISBN: (纸本)9781728156224

To solve the problem of remote monitoring and hierarchical autonomy of distributed energy stations, the hierarchical autonomous operation monitoring platform of energy stations is studied based on cloud technology. The flow computing framework and wide area message queue technology are introduced to realize distributed data collection and distributed data processing. The platform defines the operators of basic operation of flow data on wide area message queue, and supports the modeling, discovery, programming, providing and hosting of flow computing services;the distributed data acquisition and processing includes channel parser, data aggregation group, channel supervision service, repeater, message service, data calculation, alarm processing and control Each component independently constitutes a docker operator in the flow computing framework to complete the data processing of the configuration or monitoring model specified segments;through the research of data acquisition and processing and equipment operation data analysis and early warning technology, it provides customers with a reasonable, clean and reliable energy supply mode of distributed autonomous operation for power and hot / cold energy required by production. In the simulation environment of open stack and docker, the feasibility of integrated information collection and monitoring and hierarchical monitoring of distributed energy station is verified.

关键词： integrated energy cloud computing flow calculation task scheduling message queue

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Semantic Segmentation of 3D Facial Models Using 2D Annotations

Semantic Segmentation of 3D Facial Models Using 2D Annotatio...

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ieee International Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

作者： Krasimir Tonchev Radostina Petkova Nikolay Neshov Agata Manolova Teleinfrastructure Lab Technical University of Sofia Bulgaria Faculty of Telecommunications Technical University of Sofia Bulgaria

ISBN: (纸本)9781665426060

Semantic information retrieved from the human face can improve human-machine interaction, add new level of information compression and expand the multi-modality in data analysis. Extracting such information is done using semantic segmentation of images of the human face. It consists of automatically identifying the areas of human facial image, defining the different face parts, that meaningful information for humans. These areas include nose, eyes, forehead, ears, etc. In this work we propose a new algorithm based on auto-encoder architecture for semantic segmentation of 3D models of the human face. These models are represented as mesh objects which further motivates us to use graph-convolutional neural networks for the implementation of the auto-encoder. Since no data of 3D face models with annotated facial parts is available, we approach the problem using publicly available 2D annotated data and analysis-by-synthesis approach. Experimental results validate our approach for 3D face semantic segmentation.

关键词： Solid modeling Image segmentation Three-dimensional displays Semantics Neural networks Nose Computer architecture

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Timing Analysis of Car-To-Car Communication systems Using Real-Time Calculus: A Case Study 5

Timing Analysis of Car-To-Car Communication Systems Using Re...

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5th ieee International Symposium on Smart and Wireless systems within the International Conferences on intelligent data acquisition and advanced computing systems, IDAACS-SWS 2020

作者： Bazzal, Mahmoud Krawczyk, Lukas Govindarajan, Ram Prasath Wolff, Carsten Dortmund University Applied Sciences and Arts Otto-Hahn-Str Dortmund2344227 Germany

ISBN: (纸本)9781728199603

The advent of autonomous driving has brought many technologies to attention such as car-Tocar communication systems. Timing analysis of autonomous driving applications that perform car-To-car communication is necessary due to their safety-critical nature. The analysis of such applications is usually conducted using relatively complicated and non-modular traditional approaches such as CPA. In this paper, the applicability of Real-Time Calculus (RTC) for conducting timing analysis of these applications is investigated. We address the mapping of AMALTHEA models of automotive applications to RTC semantics, and use these semantics to conduct a case study where a safe upper bound on the end-To-end latency of a car-To-car communication based automotive subsystem is derived. © 2020 ieee.

关键词： Semantics

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Development of an intelligent Robotic System for Plasma Processing of Industrial Products with Complex Shape

Development of an Intelligent Robotic System for Plasma Proc...

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ieee International Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

作者： Assel Kussaiyn-Murat Alexander Krasavin Darya Alontseva Albina Kadyroldina Alexandr Khozhanov Iurii Krak Patricia Muñoz de Escalona Irina Dyomina D Serikbayev East Kazakhstan Technical University Ust-Kamenogorsk Kazakhstan Taras Shevchenko National University of Kyiv Ukraine Glasgow Caledonian University Glasgow United Kingdom

ISBN: (纸本)9781665426060

The paper presents new results of automated path planning for an industrial robot manipulator performing microplasma spraying of coatings on substrates with complex surface shapes. Path planning and automatic generation of the manipulator motion program are performed using data of a preliminary 3D surface scanning by a laser triangulation distance sensor installed on the same robot arm. The automatic manipulator working tool path planning algorithm is based on the choice of the starting segment of the working tool trace as a geodetic line on the surface. An algorithm for optimal spatial curve approximation by a sequence of line segments and arcs has been developed as a part of the automatic manipulator program generation system. The developed algorithms and their software implementation were experimentally tested through robotic microplasma spraying of a protective coating on the surface of a jaw crusher plate, which was then successfully operated for crushing mineral raw materials.

关键词： Three-dimensional displays Service robots Motion segmentation Software algorithms Spraying Manipulators Approximation algorithms

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Gas Discrimination & Quantification using Sensor Array with 3D Convolution Regression Dual Network

Gas Discrimination & Quantification using Sensor Array with ...

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ieee International Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

作者： Vishakha Pareek Santanu Chaudhury Sanjay Singh CSIR - Central Electronics Engineering Research Institute Pilani India Academy of Scientific and Innovative Research (AcSIR) Ghaziabad India Indian Institute of Technology Delhi India

ISBN: (纸本)9781665426060

Smart sensor system design requires intelligent data processing, which analyzes raw time-series sensor data to efficiently and precisely discriminate and quantify target gases. The work presented here utilizes the response of twin gas sensor arrays for gases such as ethanol, ethylene, methane, and carbon monoxide to discriminate and quantify the target gases. We propose a 3D convolution neural-based regression dual network (3D-CNrdN) for both gas quantification and discrimination. The spatiotemporal correlation of sensor array responses inspired us to design the deep neural network for the gas concentration estimation model. The sensor array set is spatially correlated, and all the twin array responses are temporally related. 3D-CNrdN uses raw time-series gas sensor array data. The data is fed to the network as the 3D pattern, which contains 2D spatial information varying with third dimension time to recognize patterns that eventually predict the concentration. The model evaluation shows that the proposed methods are an effective technique for gas quantification and identification with $\text{RMSE}=0.3179$ and classification accuracy 94.37%. Furthermore, the proposed method outperforms and provides higher discrimination accuracy and lower RMSE than other machine learning and deep learning methods.

关键词： Deep learning Gases Three-dimensional displays Convolution Neural networks Spatiotemporal phenomena Pattern recognition

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Implementation for Geological Environment Sub-node intelligent Search of Geological Cloud 2.0 3

Implementation for Geological Environment Sub-node Intellige...

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3rd ieee International Conference on Computer and Communication Engineering Technology, CCET 2020

作者： Ren, Xiaoxia Huo, Zhibin Zhou, Meng Xue, Yueming Yu, Mengliang China Institute of Geo-Environment Monitoring Beijing China Institute of Hydrology and Environmental Geology Shijiazhuang China

ISBN: (纸本)9781728188119

The "Geological Cloud 2.0"intelligent search system is an engine for fast search of data resources and systems on the cloud. The geological environment sub-node of "Geological Cloud 2.0"as one of distributed sub-nodes on the cloud provides data information for intelligent search. In order to serve better the "Geological Cloud 2.0"intelligent search, the metadata and exchange format of the geological environment entity database was defined to construct intelligent search indexing. And the metadata content interactive push process was introduced from the geological environment sub-node entity database to "Geological Cloud 2.0"intelligent search system. The results show that the geological environmental sub-node search information for Geological Cloud 2.0 intelligent search is synchronized with entity database and has attention, which provides experience for the construction and upgrade of the "Geological Cloud"intelligent search in the future. © 2020 ieee.

关键词： Metadata

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