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检索条件"任意字段=Conference on Algorithms, Devices, and Systems for Optical Information Processing III"

共 250 条记录，以下是21-30 订阅

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processing pipeline for automated data mining of the single astronomical objects from blurred CCD frames 12

Processing pipeline for automated data mining of the single ...

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12th International Scientific and Practical conference "information Control systems and Technologies", ICST 2024

作者： Khlamov, Sergii Savanevych, Vadym Vlasenko, Vladimir Hadzhyiev, Emil Bondar, Yehor Netrebin, Yuriy Kharkiv National University of Radio Electronics Nauki avenue 14 Kharkiv61166 Ukraine National Space Facilities Control and Test Center Moskovska street 8 Kyiv01010 Ukraine INTTVE Limited O'Connell Bridge House D'Olier Street 2 DublinD02RR99 Ireland

In this paper the authors presented a sophisticated data mining pipeline, which was designed for restoring the high-quality images from the blurred frames made by the Charge-Coupled Device (CCD) cameras. The developed data mining pipeline leverages the modern informational technologies for the horizontal and vertical scalability. The core methodology integrates the following mathematical methods and algorithms: an inverse median filtration method for the noise reduction and the Lucy-Richardson algorithm for deblurring. The inverse median filtration effectively reduces impulsive noise while preserving edges, and the Lucy-Richardson algorithm iteratively refines the image by correcting for blurring effects encoded in the point spread function (PSF). The proposed system's architecture of the processing pipeline for automated data mining of the single astronomical objects from blurred CCD frames utilizes the following modern technologies: Python programming language, Redis, FastAPI, React, Docker, and Caddy to ensure high performance, scalability, and ease of deployment. This integrated approach significantly enhances the accuracy of astronomical observations, facilitating more precise studies of celestial objects. The proposed pipeline addresses the unique challenges of astronomical image processing, offering a robust solution for automated data mining of single astronomical objects. Our work demonstrates the potential to advance astronomical research by improving image clarity and reliability, contributing to various fields within astronomy. The combination of effective noise reduction and deblurring techniques, along with a scalable and high-performance system architecture, provides a comprehensive solution to the challenges faced in processing astronomical images. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Noise abatement

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processing pipeline for data mining of the primary orbits of the Solar System objects using the Väisälä method 12

Processing pipeline for data mining of the primary orbits of...

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12th International Scientific and Practical conference "information Control systems and Technologies", ICST 2024

作者： Troianskyi, Volodymyr Bazyey, Olexander Khlamov, Sergii Trunova, Tetiana Orlov, Stanislav Astronomical Institute of the Slovak Academy of Sciences Vysoké Tatry Tatranska Lomnica05960 Slovakia Odesa I. I. Mechnikov National University Pastera street 42 Odesa65082 Ukraine Vasyl Stefanyk Precarpathian National University Shevchenko Street 57 Ivano-Frankivsk76000 Ukraine Odesa National Maritime University Mechnykov Street 34 Odesa65029 Ukraine Kharkiv National University of Radio Electronics Nauki avenue 14 Kharkiv61166 Ukraine National Aerospace University Kharkiv Aviation Institute Chkalova street 17 Kharkiv61000 Ukraine

In this paper we presented the processing pipeline for data mining of the primary orbits and discovery of the new Solar System objects using the CoLiTec software and classical Väisälä method. The 1st step of a such method is performing the sequential astronomical observations and the classical astrometric data reduction. It is implemented as a combination of the general mathematical algorithms for processing of the astronomical frames incapsulated in the CoLiTec software. It contains the inverse median filter, astronomical calibration with usage of the master-frames, detection of the astronomical objects and its trajectories in series of frames and others features. After that the especial parameters of the object's orbit (right ascension and declination) are calculated at the certain time. When we receive at least two observations of the same object under study at different moments, the classic Väisälä algorithm can be applied. For this, the primary orbit from the two nearest observations is calculated. Then the geocentric rectangular coordinates and the appropriate geocentric velocity components are computed. This give us an opportunity for determining the Keplerian elements of orbit of the investigated object at any time we are interested in. The developed algorithm is implemented as a processing pipeline that includes a combination of the CoLiTec software and created tool with encapsulation of the Väisälä method. The created processing pipeline for data mining of the primary orbits and discovery of the new Solar System objects using the CoLiTec software and classical Väisälä method is practically verified. Using it a few new asteroids are first reported and a few lost small bodies of the Solar System are found in the Kyiv comet station and the Odesa - Mayaky observatory. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

关键词： Median filters

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FE-YOLOv8n: A YOLOV8 Enhancement Algorithm for Effective Fire Extinguisher Detection

FE-YOLOv8n: A YOLOV8 Enhancement Algorithm for Effective Fir...

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Image processing, Computer Vision and Machine Learning (ICICML), International conference on

作者： Tianyang Lan Hongbo Li College of Electrical Engineering and Information Northeast Agricultural University Harbin China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

People often rely on optical devices to identify the source of fire in a timely manner in order to prevent fires, but it is also crucial to promptly activate firefighting equipment. At present, there are models on the market that combine neural networks such as CNN with location algorithms for real-time detection of fire extinguisher positions, which can make real-time detection and alarm through cloud services. However, there is a lack of algorithms that can accurately identify the type of fire extinguisher and specific occlusion situations. Firstly, this article proposes using a model, based on YOLOv8n, to detect several main types of fire extinguishers (which can be determined by shape). Secondly, we propose a target detection algorithm based on CNN (Convolutional Neural Network) that can effectively detect specific fire extinguishers: FE-YOLOv8. The dataset consists of CSDM, Billbill videos, and on-site images, and specific image enhancements have been made for different types of fire *** trained model achieved a mAP of 90%, outperformed the original, and increased by 1.2 percentage points.

关键词： Fire extinguishers Training Shape Refining Object detection Real-time systems Convolutional neural networks Object recognition optical devices Videos

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Case-Study for Integration of COTS SoC devices in Reliable Space systems for On-Board processing

Case-Study for Integration of COTS SoC Devices in Reliable S...

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2023 European Data Handling and Data processing conference for Space, EDHPC 2023

作者： Rodriguez-Ferrandez, Ivan Steenari, David Tali, Maris Kosmidis, Leonidas Tonicello, Ferdinando Barcelona Spain Barcelona Spain Noordwijk Netherlands

ISBN: (纸本)9789090379241

Recent trends in Data Handling systems (DHS) include increased data-rates, in-orbit reconfiguration and the introduction of advanced On-Board processing (OBP) methods to extract actionable information on-board, with low latency. At the same time, NewSpace industry has successfully deployed COTS-based DHS and processing equipment in space. In particular for OBP, COTS-based processors and FPGAs can offer higher computational performances than space qualified equivalents-which in turn can enable new applications through more advanced OBP algorithms. The individual component cost is also lower for COTS than space qualified components, which can allow overall cost-optimisations on mission *** internal working group at ESA has studied the concept of using "safety barriers"to ensure no propagation of failure from functions implemented with COTS to other on-board units. Thanks to ESA studies there is a path to use Class IV equipment on missions with higher class (Class I-iii), through the use of hardware "safety barriers"to limit failure propagation from Commercial Off-The-Shelf (COTS) *** our work, we take the above mentioned concepts and apply them to reference implementations, targeting payload processing modules based on standard form factors (ADHA) and automotive-grade GPU systems-on-Chip (SoCs). In addition, we make use of previous work on improving in-flight availability of complex COTS SoC processors, through system and software Fault Detection, Isolation and Recovery (FDIR) techniques. © 2023 ESA.

关键词： System-on-chip

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Mining Alarm Association Rules in optical Transmission Networks Using a Statistical Approach 24

Mining Alarm Association Rules in Optical Transmission Netwo...

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24th IEEE International conference on High Performance Computing and Communications, 8th IEEE International conference on Data Science and systems, 20th IEEE International conference on Smart City and 8th IEEE International conference on Dependability in Sensor, Cloud and Big Data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Deng, Miao Li, Peng Liu, Yu Zhu, Rongjing Zhang, Yujie School of Computer Science and Technology Wuhan University of Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System China

ISBN: (纸本)9798350319934

Due to the interconnection between devices in the optical transmission network (OTN), when one device fails and generates alarm information, a large number of other invalid alarms are generated in OTN. How to mining association rules in alarm data is an important problem. In this paper, we investigate the association rules mining problem based on a statistical method. First, we remove the chattering alarm in preprocess to reduce data redundancy. Second, we propose a statistics-based association rule mining algorithm. We use a sliding time window to scan the alarm data, and we exploit the matrix to record the corresponding results. According to the matrix, we calculate the support and confidence of association rules. Compared with other traditional association rule mining algorithms, the proposed algorithm does not need to set the minimum support artificially, and the obtained association rules have strong causality. Through extensive experiments on syn-thetic and real OTN alarm datasets, we verify the effectiveness of our proposed algorithm and the correctness of the obtained association rules. © 2022 IEEE.

关键词： Association rules

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Multi-attitude based target localization method

Multi-attitude based target localization method

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2024 International conference on Mechatronic Engineering and Artificial Intelligence, MEAI 2024

作者： Yan, Suqing Xu, Xiaoyue Xiao, Jianming Ji, Yuanfa Hawari Bin Ghazali, Kamarul Guangxi Key Laboratory of Precision Navigation Technology and Application Guilin University of Electronic Technology Guilin China School of Information and Communication Guilin University of Electronic Technology Guilin China Department of Science and Engineering Guilin University Guilin China National & Local Joint Engineering Research Center of Satellite Navigation Localization and Location Service GUET-Nanning E-Tech Research Institute Co. Ltd. Nanning China Centre for Advanced Industrial Technology University of Malaysia Pahang Al Sultan Abdullah Pekan Campus Pahang Pekan Malaysia

ISBN: (纸本)9781510689176

In recent years, location-based services have gradually penetrated all aspects of people's daily life, bringing great convenience to people's work and life. Pedestrian Dead Reckoning (PDR) is a positioning method that can derive a pedestrian's movement trajectory by relying on sensors information, with a high degree of autonomy and continuity. However, existing PDR tends to restrict the target posture to remain steadily pointing in the direction of pedestrian movement throughout the localization process. In addition, although it can achieve a high degree of positioning accuracy in a short period of time, it generates a cumulative error over time. To these problems, this paper proposes a fusion localization method that combines PDR based on multiple smartphones pose recognition and acoustic localization. In this method, we first employ a GWO-ELM based target posture recognition model. Then based on the posture recognition result for PDR localization, Time Difference of Arrival (TDOA) technique is used for acoustic localization. Finally, particle filtering is utilized to combine the two methods. To demonstrate the validity of the method, we performed several experiments on a motion trajectory with a length of 97.2 meters. The results show that the method has better localization performance than the traditional method. In addition, it can realize high-precision localization under different devices with universality and stability. © 2025 SPIE.

关键词： Acoustics Target recognition Detection and tracking algorithms Particles Sensors Education and training Gesture recognition Satellite navigation systems Tunable filters Machine learning

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Concentration prediction of binary mixed gases based on random forest algorithm in the electronic nose system 13

Concentration prediction of binary mixed gases based on rand...

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13th International conference on Signal processing systems, ICSPS 2021

作者： Wang, Tao Wu, Yu Zhang, Yongwei Lv, Wen Chen, Xinwei Yang, Zhi Department of Micro/Nano Electronics School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China

ISBN: (数字)9781510653184

ISBN: (纸本)9781510653177

The concentration prediction of mixed gases is crucial to the pattern recognition research of electronic nose (E-nose) systems. The response experiments of the E-nose towards the ethanol and propanol mixture with different concentrations are carried out. Five kinds of machine learning algorithms, including linear regression, support vector machine, K-nearest neighbor, random forest, and decision tree, are used for training the multiple output regressors to predict the content of each component simultaneously. The R2 score, root mean squared error, and mean absolute error are used to evaluate the performance of these models. The relationship between prediction accuracy and concentration distribution has also been studied. The results show that the model based on the random forest has superior performance for forecasting the concentration of ethanol and propanol, with the R2 score more than 0.98 in the 5-fold cross-validation. This study provides a significant inspiration for designing a multi-output regression model to realize the quantitative prediction of mixed gases by the E-nose. © COPYRIGHT SPIE.

关键词： Electronic nose

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Revolutionizing Waste Management: Harnessing the Power of IoT 7

Revolutionizing Waste Management: Harnessing the Power of Io...

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7th IET Smart Cities Symposium, SCS 2023

作者： Karale, Ankita Rajawat, Anand Singh Goyal, S.B. Computer Engineering Sandip Foundation’s Sandip Institute of Research Center Nashik School of Computer Science & Engineering Sandip University Nashik India Faculty of Information Technology City University Petaling Jaya Malaysia

ISBN: (纸本)9781839539831

Waste management has become a pressing problem in a world that is becoming more and more urbanised. Traditional ways of dealing with trash are usually inefficient and bad, leading to pollution, health problems, and wasted resources. As an answer to these problems, the Internet of Things (IoT) has changed the way trash is handled in a big way. This abstract looks at how smart waste management based on the Internet of Things could totally change the business of garbage disposal. Through a network of sensors and devices, the Internet of Things (IoT) connects trash cans, garbage trucks, and waste processing facilities so that they can be monitored and improved in real time. A smart waste management system that is built on IoT has many benefits. With the real-time information it gives about how much trash is being made, routes for collecting trash can be made more efficient in terms of time and fuel use. This cuts down on the number of times trash needs to be picked up, reduces the amount of greenhouse gases released, and saves money. Sensors in trash cans can also find dangerous or flammable items, so they can be dealt with right away and any problems can be avoided. Also, the Internet of Things makes it possible for predictive analytics, which help waste management officials predict how much trash will be made and use their resources well. Using smart waste sorting methods like optical sensors and machine learning algorithms, recyclable and non-recyclable trash can be correctly found and sorted. This helps people recycle more and puts less pressure on landfills. Smart trash management systems that are based on the Internet of Things (IoT) get more people involved and help them understand. Mobile apps and smart devices can tell a person when their trash will be picked up, where the nearest recycling sites are, and how much trash they make. People are encouraged to act responsibly and throw away trash in ways that are good for the environment. Smart waste management base

关键词： Internet of things

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Research on Light Source Power and Temperature Control and Fast-start Technology of Fiber Optic Gyroscope

Research on Light Source Power and Temperature Control and F...

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2024 8th International conference on Electrical, Mechanical and Computer Engineering (ICEMCE)

作者： Sheng Qin Yang Zuo Shengkai Jiang Yuekang Qian Heng Li Wehua Gu School of Microelectronics (School of Integrated Circuits) Nanjing University of Science and Technology Key Laboratory of Near-Range RF Sensing ICs & Microsystems (Nanjing University of Science and Technology) Ministry of Education Nanjing China

ISBN: (数字)9798331506230

ISBN: (纸本)9798331506247

The traditional optical power control technology of fiber optic gyroscope is to sample, demodulate and other processing of the electrical signal output by the PIN-FET to obtain real-time optical power, and then maintain the stability of optical power through feedback control. In this paper, the accurate optical power information is obtained in real time through the Micro-photodetector (MPD), and then the PID optical power control algorithm is introduced, with the digital current source as the controlled object, and the optical power fluctuation under full temperature conditions is minimized by adjusting the control parameters. At the same time, in order to cope with the problem of slow system start at the extreme temperature, the double-layer PID algorithm is used to nest, and the PID fast start algorithm is started when the fiber optic gyro system is just powered on, which makes the optical power approach the target faster and more conducive to fast start, and after the start is completed, it is switched to the optical power control algorithm to achieve accurate control, and the smooth switching of the two sets of PID algorithms makes the system have the advantages of fast startup and small optical power fluctuation at full temperature.

关键词： optical fibers Integrated optics optical feedback Power control Real-time systems Gyroscopes Temperature control optical devices Thermal stability optical control

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An Investigation for Cursive Context-Specific Printed Script Recognition Techniques

An Investigation for Cursive Context-Specific Printed Script...

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IEEE SSD International Multi-conference on systems, Signals and devices

作者： Humera Rafique Tariq Javid Dept. of Electrical Engineering Graduate School of Engineering Sciences & Information Technology Hamdard University Karachi Pakistan

Selecting suitable techniques and datasets for a machine learning problem is a great challenge. This research investigates the available machine learning architectures, datasets, and software tools, for cursive context-specific printed text. Despite the existence of millions of speakers around the globe and rich literary history of more than thousands of years, it is hard to find computational linguistic works related to the Punjabi Shahmukhi script, a member of Perso-Arabic context-specific script – a low-resource language family. An investigation of related work through collected statistics inspired by the popularity and success of artificial neural networks and associated techniques have presented. The historical development of the script follows it in a literary sense and the importance and motivation in the development of optical character recognition systems, algorithms, and techniques. The paper discussed the available datasets and the need for a custom dataset. Based on recent research trends in machine learning frameworks, the work presents the most popular deep learning techniques, convolutional neural networks, and recursive neural networks for cursive context-specific scripts. This paper incorporates actual knowledge to promote research in machine learning and natural language processing disciplines and the selection of algorithms, architectures, and resources.

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