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

共 3200 条记录，以下是301-310 订阅

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Iterative approach based on the FDTD method for the design of metal-dielectric photonic crystal devices 8

Iterative approach based on the FDTD method for the design o...

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8th International conference on information Technology and Nanotechnology, ITNT 2022

作者： Mokshin, Pavel Golovashkin, Dimitry Pavelyev, Vladimir Yablokova, Liudmila Samara National Research University Samara Russia Image Processing Systems Institute Branch of the Federal Scientific Research Centre 'Crystallography Photonics' of Russian Academy of Science Samara National Research University Samara Russia

ISBN: (数字)9781665485715

ISBN: (纸本)9781665485715

Present article deals with a noble approach for designing the photonic crystal devices by using information about diffraction patterns at different frequencies;it is useful for optimizing an element designed to operate at one selected wavelength. Proposed approach differs from the known general-purpose optimization methods (for example, a genetic algorithm or gradient procedures). © 2022 IEEE.

关键词： Genetic algorithms

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Improved YOLOv5s Tomato Leaf Small Disease Spot Detection Method for Embedded devices

Improved YOLOv5s Tomato Leaf Small Disease Spot Detection Me...

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2024 International conference on Remote Sensing, Mapping, and Image processing, RSMIP 2024

作者： Li, Xiaojing Fang, Jiandong Zhao, Yvdong College of Information Engineering Inner Mongolia University of Technology China Inner Mongolia Key Laboratory of Perceptual Technology and Intelligent Systems China

ISBN: (纸本)9781510680012

In the field of tomato disease spot detection, despite significant advancements in convolutional neural network technology, challenges still persist in detecting small-sized tomato disease spots. This study aims to enhance the tomato disease spot detection model to improve the accuracy of detecting small disease spots on tomatoes. Firstly, the concept of DenseNet is introduced, and a Dense_C3 module is constructed, which incorporates two 3×3 convolutional layers within the Bottleneck of C3 to achieve dense feature propagation and reuse. Secondly, the Convolutional Block Attention Module (CBAM) is employed to weight the feature maps, enhancing the focus on local and spatial information to enhance model accuracy. To validate the effectiveness of the proposed improvements, experiments were conducted on tomato disease spots of different scales, including Septoria Leaf Spot, Early Blight, Late Blight, and Tomato Yellow Leaf Curl Virus. The experimental results demonstrate that the introduction of the Dense_C3 structure and CBAM improves the detection accuracy for small-scale targets. In a comprehensive evaluation, the improved YOLOv5s model shows increases of 2.4% in F1 score and 2.1% in mAP. © 2024 SPIE.

关键词： Viruses

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Algorithm for optimizing the mode of electric power systems by active power

Algorithm for optimizing the mode of electric power systems ...

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2022 International conference on information Science and Communications Technologies, ICISCT 2022

作者： Porubay, Oksana Siddikov, Isamiddin Madina, Khasanova Fergana Branch of the Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of Information Technologies Fergana Uzbekistan Tashkent State Technical University Named after Islam Karimov Department of Information Processing and Management Tashkent Uzbekistan

ISBN: (纸本)9781665472296

The paper considers the issues of optimizing the modes of electric power systems based on the methods of intelligent technologies: evolutionary and ant algorithms, taking into account the features of the object under consideration. An optimization criterion has been formulated, which includes minimizing the total cost of fuel in electric power facilities. The main restrictions imposed by the dynamics of the functioning of technological units and their mode of operation are determined. These restrictions are presented in the form of a system of linear equations that characterize the steady state of the units, as well as in the form of inequalities, which are the limiting restrictions on the parameters of the generated electricity. To solve this problem, evolutionary modeling algorithms and an ant colony algorithm have been developed. A comparative analysis of these algorithms was carried out in order to determine their capabilities and scope. The use of evolutionary algorithms in problems with discrete values of variables does not require any assumptions and simplifications of the problem. When solving the problem of optimal placement and determination of the parameters of compensating devices and linear regulators, it was possible to reduce losses in the system by 3.5%. © 2022 IEEE.

关键词： Evolutionary algorithms

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In-Memory Massive MIMO Linear Detector Circuit with Extremely High Energy Efficiency and Strong Memristive Conductance Deviation Robustness

In-Memory Massive MIMO Linear Detector Circuit with Extremel...

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2024 IEEE Global Communications conference, GLOBECOM 2024

作者： Bi, Jia-Hui Yang, Shaoshi Zhang, Ping Chen, Sheng Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing100876 China University of Southampton School of Electronics and Computer Science SouthamptonSO17 1BJ United Kingdom

ISBN: (纸本)9798350351255

The memristive crossbar array (MCA) has been successfully applied to accelerate matrix computations of signal detection in massive multiple-input multiple-output (MIMO) systems. However, the unique property of massive MIMO channel matrix makes the detection performance of existing MCA-based detectors sensitive to conductance deviations of memristive devices, and the conductance deviations are difficult to be avoided. In this paper, we propose an MCA-based detector circuit, which is robust to conductance deviations, to compute massive MIMO zero forcing and minimum mean-square error algorithms. The proposed detector circuit comprises an MCA-based matrix computing module, utilized for processing the small-scale fading coefficient matrix, and amplifier circuits based on operational amplifiers (OAs), utilized for processing the large-scale fading coefficient matrix. We investigate the impacts of the open-loop gain of OAs, conductance mapping scheme, and conductance deviation level on detection performance and demonstrate the performance superiority of the proposed detector circuit over the conventional MCA-based detector circuit. The energy efficiency of the proposed detector circuit surpasses that of a traditional digital processor by several tens to several hundreds of times. © 2024 IEEE.

关键词： Operational amplifiers

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Unequal Clustering Protocol in IoT Networks Based on Multiple Criteria processing 23

Unequal Clustering Protocol in IoT Networks Based on Multipl...

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6th International conference on information Science and systems, ICISS 2023

作者： Mir, Foudil Meziane, Farid Faculty of Exact Sciences University of Bejaia Bejaia06000 Algeria Data Science Research Centre University of Derby United Kingdom

ISBN: (纸本)9798400708206

The Internet of Things (IoT) is a rapidly expanding network characterized by a very significant number of heterogeneous devices with limited resources. Clustering is a very powerful technique used to reduce the communication load, conserve energy, aggregate data and optimize the performance of IoT systems. Designing an efficient clustering algorithm is a real challenge. Once the Cluster Heads (CHs) are elected, traditional clustering algorithms typically use a single clustering radius to group nodes to form clusters. However, this approach is potentially not optimized, as devices within a cluster may have different characteristics. In this paper, we focus on the DCOPA protocol proposed for clustering in IoT networks. Once the CHs are elected, the identical clustering radius is applied to these different elected CHs despite their differences in terms of residual energy and Distance to Base Station (DistBS). The new approach, called Unequal-DCOPA (UDCOPA), makes it possible to define for each CH its clustering radius which will be sensitive to the local criteria of energy and DistBS for the CH that is being considered. The radius is modelized as a multicriteria system. Simulation results show that our new protocol UDCOPA outperforms DCOPA in energy management and lifetime parameters of nodes and network. UDCOPA increases lifetime by 34.55% when compared to DCOPA. © 2023 ACM.

关键词： Energy efficiency

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Design of Factory Environmental Monitoring System based on ESP32 5

Design of Factory Environmental Monitoring System based on E...

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5th International conference on Frontiers Technology of information and Computer, ICFTIC 2023

作者： Song, Wenze Wang, Xuezhen Wang, Tianqi Li, Zhixuan Zhang, Zening Yang, Lishan Liaocheng University School of Physics Science and Information Engineering Liaocheng China

ISBN: (纸本)9798350309034

With the rapid population of embedded devices, Industrial Internet of Things (IIoT) has provided a promising opportunity to enhance intelligent industrial systems by leveraging the growing ubiquity of wireless sensor and optical devices, which is crucial to ensure the reliable operation of the traditional industrial system and benefit the manufacturing process. In this paper, an efficient factory environmental monitoring system is designed for production data acquisition, which is based on ESP32-S3 and network database, enabling autonomous data collection, analysis and visualization via graph signal processing method, which reduces transmission volume and conserves network bandwidth. The experimental results show that the designed monitoring system with low cost, convenient operation and strong safety, which provides a practical solution to collect and analyze the data obtained by the industrial wireless sector. © 2023 IEEE.

关键词： data collection ESP32 factory environmental monitoring

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Harnessing the Power of Swarm Intelligence and Long Short-Term Memory Networks in Wearable Healthcare systems 1

Harnessing the Power of Swarm Intelligence and Long Short-Te...

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1st IEEE International conference on Emerging Research in Computational Science, ICERCS 2023

作者： Kumar, K. SriRam Suriya, S. Karpagam Institute of Technology Department of Information Technology Coimbatore India Psg College of Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350359756

Current developments in cloud services, artificial intelligence (AI), and the Internet of Things (IoT) have transformed the traditional healthcare system into smart healthcare. Improved medical services can be achieved by utilising important technologies like AI and IoT. The current study article offers a novel illness detection model for smart healthcare systems that is based on the convergence of AI and IoT. The primary goal of this article is to develop a disease detection model for heart disease by combining data from smart wearable devices with convergence methodologies in artificial intelligence. The model under discussion involves many stages, such as gathering data, pre-processing, categorization, and adjusting parameters. Wearable's and other Internet of Things (IoT) devices facilitate the easy collecting of data, which is then used by artificial intelligence (AI) algorithms to diagnose diseases. For illness diagnosis, the suggested approach makes use of the Swarm Intelligence-Powered Long Short-Term Memory (SILSTM) model. Healthcare data was used to validate the SILSTM model's performance. The research revealed that the SILSTM model that was provided could diagnose cardiac disease with a maximum accuracy of 96.16%. For this reason, smart healthcare systems can make use of the suggested SILSTM model as a suitable instrument for disease diagnosis. © 2023 IEEE.

关键词： Internet of things

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Experimental Study of Applying algorithms Based on Neural Networks to Enhance the Efficiency of Telecommunication systems

Experimental Study of Applying Algorithms Based on Neural Ne...

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International Russian Automation conference (RusAutoCon)

作者： A. A. Kolpakov D. V. Beilekchi Vladimir State university Vladimir Russia

ISBN: (数字)9798350349818

ISBN: (纸本)9798350349825

The research is carried out in order to develop algorithms for the software of devices used in telecommunication systems of dispatch and operational command communication. The use of modern methods and algorithms for information processing using neural networks can significantly improve such characteristics as speech intelligibility and ease of use. The main purpose of the study is to identify the design features of speech recognition units based on single-board computers for further implementation in loudspeaker communication systems. The results of calculating the metrics of the speech recognition library under study, as well as for a number of data smoothing algorithms, are presented, and their effectiveness is evaluated on single-board computers. The results of the study are planned to be used to modernize existing and develop new devices for telecommunication systems of dispatching and operational command communication.

关键词： Computers Smoothing methods Microcontrollers Neural networks Software algorithms Speech recognition Production Software Telecommunications Speech processing

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PHM Fault Diagnosis algorithms, devices and systems Based on Edge Computing with Quantum Genetic Algorithm Optimised XGBoost 8th

PHM Fault Diagnosis Algorithms, Devices and Systems Based on...

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8th International conference on Computing, Control and Industrial Engineering, CCIE 2024

作者： Gao, Mingliang Fu, Changzhao Gao, Shan Tang, Yu Wu, Jianguo Sun, Yi Edge Computing Business Unit of Inspur Electronic Information Industry Co. Ltd. Shandong Jinan250013 China CRRC Changchun Railway Vehicles Co. Ltd. Changchun China EVYD Technology Sdn Bhd Sengkurong B Brunei

ISBN: (纸本)9789819769339

Traditional fault diagnosis methods are significantly challengeable for treating predictive maintenance (PHM) systems, which have high complexity and intensive data, especially real-time data. Thus, an edge computing based PHM fault diagnosis method with a XGBoost model optimized by quantum genetic algorithm (QGA) is proposed herein. It aims to improve the accuracy and real-time performance while diagnosing faults on combination of the efficient data processing capability of edge computing and the fast global optimization property of quantum genetic algorithm. Such an optimized XGBoost model is used on edge computing nodes for monitoring and diagnosing faults of device status at real time. According to the test results, compared with traditional methods, the accuracy and response time of fault diagnosis has been significantly improved, especially while processing large and high-dimensional industrial data. In conclusion, XGBoost optimized by the PHM fault diagnosis algorithm, device and system based on edge computing quantum genetic algorithm can efficiently and accurately diagnose faults, with comprehensive application potential and significantly practical significance.. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Quantum computers

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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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