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Temperature control technology based on Smith fuzzy PID 9

Temperature control technology based on Smith fuzzy PID

引用

9th International conference on Energy Materials and Electrical Engineering, ICEMEE 2023

作者： Gu, Wei Zhu, Songqing Guan, Hongyao School of Mechanical Engineering Nanjing Institute of Technology Nanjing211167 China

ISBN: (纸本)9781510672765

In order to improve the response speed, adjustment accuracy and anti-interference performance of the outlet temperature of the heat exchanger of the thermal performance test bench. An algorithm combining fuzzy control, Smith prediction and traditional PID control is proposed, and use Matlab/Simulink to simulate the temperature characteristics and Anti interference characteristics of the system. The experimental results show that compared with the traditional PID and Fuzzy PID algorithms, the response speed of Smith fuzzy PID is 57S and 50S faster 8 than that of traditional PID and Smith PID, respectively, and the overshoot is 18% and 16% less than that of traditional PID and Fuzzy PID respectively. Combined with Smith prediction algorithm, the time lag problem is effectively solved. Therefore, the Smith fuzzy PID control method has a faster response to the outlet temperature control of the heat exchanger, a smaller overshoot, and a faster response to interference signals. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Control systems Temperature control Fuzzy logic Temperature metrology Computer simulations Algorithm development Resistance Signal processing systems modeling

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Revelation and analysis of optical phase delay exhibited by Al-doped 4H-SiC due to current induction

Revelation and analysis of optical phase delay exhibited by ...

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2023 conference on Lasers and Electro-Optics Europe and European Quantum Electronics conference, CLEO/Europe-EQEC 2023

作者： Du, Haoze Takeda, Harunobu Kadowaki, Takuya Tate, Naoya Kawazoe, Tadashi Oki, Yuji Ohtsu, Motoichi Hayashi, Kenshi Depertment of Electronics Kyushu University 744 Motooka Nishi-ku Fukuoka819-0395 Japan Nichia Corporation 3-13-19 Moriya-cho Kanagawa-ku Kanagawa Yokohama221-0022 Japan Research Origin for Dressed Photon 3-13-19 Moriya-cho Kanagawa-ku Kanagawa Yokohama221-0022 Japan

ISBN: (纸本)9798350345995

Magneto-optical (MO) effect-based devices, such as spatial light modulators and optical isolators, have become increasingly prevalent in the fields of optical communication and information processing because of their high-speed response. However, conventional MO devices (e.g., Terbium Gallium Garnet crystals) have poor transparency in the visible range and polarization rotation capability, which constrains the integration of small optical systems. Recently, a silicon carbide spatial light modulator (SiC-SLM) (depicted in Fig. 1(a)) was developed via dressed-photon-phonon (DPP)-assisted annealing of 4H-SiC crystals doped with aluminum atoms [1]. This device exhibited an extremely large MO effect in the visible range, as evidenced by a Verdet constant of 9.51×104 rad/T•m near its absorption edge at 457 nm. There are many unknown aspects such as the spatial distribution of the degree of polarization rotation, optimal annealing conditions, and geometrical conditions of the electrode. In this study, the utilization of the SiC-SLM for spectral filtering of imaging technology and the photophysical properties of the SiC-SLM device, especially the phase delay by birefringence, were investigated, and this progress promises a new SLM application. © 2023 IEEE.

关键词： Silicon carbide

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Communication Protocol Between Embedded Computers and Fog Computing Environment for Image processing 11

Communication Protocol Between Embedded Computers and Fog Co...

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11th Mediterranean conference on Embedded Computing (MECO) / 3rd Summer School on Cyber-Physical + systems and Internet of Things (CPS and IoT)

作者： Zhukova, Nataly Subbotin, Alexey Russian Acad Sci St Petersburg Fed Res Ctr St Petersburg Russia St Petersburg Electrotech Univ LETI St Petersburg Russia

ISBN: (纸本)9781665468282

In this article a new data transmission protocol between embedded computers and the fog computing environment for image processing is considered. The possibilities of using fog environment for intelligent processing of video are revealed. The problems of transmission protocols are indicated. A comparison of existing video processing systems is given. The place of embedded computers in intelligent video surveillance systems and ways of upgrading these systems are considered. Data from the devices is collected using embedded computers and visualized using IoT technologies. The developed data transmission protocol allows processing images in the fog and/or cloud for intelligent video surveillance systems. It assumes packet data transmission of series of frames with additional information that are processed using machine learning algorithms and neural networks. The effectiveness of the new systems is shown. As an example, the problem of processing video coming from cameras used in the subway to determine damage of the escalator tape and steps is considered. systems for image processing that implement the proposed protocol can be used not only in the subway, but also in many other areas where Internet of things technologies are supported.

关键词： Internet of Things mobile technology communication protocol image processing embedded computers intelligent video surveillance video processing system fog computing environment

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Fuzzy Color Computing Based on optical Logical Architecture

Fuzzy Color Computing Based on Optical Logical Architecture

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Intelligent and Fuzzy systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 conference

作者： Timchenko, Victor Kondratenko, Yuriy Kozlov, Oleksiy Kreinovich, Vladik Admiral Makarov National University of Shipbuilding Mykolaiv54025 Ukraine Institute of Artificial Intelligence Problems of MES and NAS of Ukraine Kyiv01001 Ukraine Petro Mohyla Black Sea National University Mykolaiv54003 Ukraine University of Texas at El Paso El PasoTX79968 United States

ISBN: (纸本)9783031397738

This paper is dedicated to the development of intelligent techniques of optical computing for real-time decision support systems (DSS) with a large array of fuzzy input data. Currently offered as an alternative to the binary systems, fuzzy optical computing devices are very complex. To increase the efficiency of logical systems in the formation and processing of an array of input fuzzy data, we propose to use a light emitter of a certain color as a fuzzy set (FS) that is a carrier of logical information. This allows building of logical solutions and conclusions based on the additive and subtractive conversion of light radiation by appropriate color filters, measuring illumination in optical channels, and switching light emitters. The main algorithmic logical procedures based on optical gates that perform the basic logical operations of disjunction and conjunction, negation, and search for a new solution are considered. To solve a problem with a large amount of fuzzy data, we propose the architecture of networks of logical structures and inference procedures. Also, we implement optimization of the optical circuit solutions to increase the reliability of decisions and estimates. When describing color sets using a fuzzy sequence, we propose to implement a non-linear rank scale. This increases the accuracy of solutions, as shown by the decrease in root-means-square estimation error. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Color

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SATELLITE IMAGE FUSION AND DENOISING USING CONVOLUTIONAL NEURAL NETWORKS 44

SATELLITE IMAGE FUSION AND DENOISING USING CONVOLUTIONAL NEU...

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44th Asian conference on Remote Sensing, ACRS 2023

作者： Tung, Shih-Shuo Huang, Li-Fen Chen, Nai-Yu Hwang, Wen-Laing Instutute of Information Science Academia Sinica Taiwan Taiwan Space Agency Taiwan

ISBN: (纸本)9781713893646

Due to the optical errors in the imaging system, the received remote sensing image is blur and noisy. Although some image techniques can restore the image, the different algorithms generate different type of restorations. In this paper, there are two restorations, one is noisy but with rich texture information and another is smooth but noise-free. The goal of this paper is to fuse these two restored images to a sharp and noise-free image. However, the traditional non-learning methods are time consuming and no training dataset for this task. In order to accelerate the processing, the neural network based method is applied. In this paper, we proposed a dataset for training and a convolutional neural network to fuse images where each image was decomposed into three channels, high-frequency, structure, and texture components. The decomposed high-frequency channel contains most noise information. In order to have high quality dataset, denoising is very important. Here, the LISTA (Learned Iterative Shrinkage and Thresholding Algorithm) method was applied to do denoising. According to the three decomposed channels, three rules were designed to fusion. The high quality dataset can be constructed by the previous processing. Therefore, the convolutional neural network learning can be achieved through the dataset. In the experiments, the proposed method achieved the significant performance when comparing to state-of-the-art methods. For a 12000x12000 PAN satellite image fusion, the processing time is about 2 minutes for GeForce RTX 2080 graphics card. If higher level devices, the cost time will decrease. © 2023 ACRS. All Rights Reserved.

关键词： Convolutional Neural Network Image Denoising Image Fusion

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Object Estimation Method for Edge devices Inspired by Multimodal information processing in the Brain 19

Object Estimation Method for Edge Devices Inspired by Multim...

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19th IEEE Annual Consumer Communications and Networking conference, CCNC 2022

作者： Seki, Ryoga Kominami, Daichi Shimonishi, Hideyuki Murata, Masayuki Fujiwaka, Masaya Osaka University Osaka Japan Nec Corp. Japan Nec Corporation System Platform Research Labs Kanagawa Japan

ISBN: (纸本)9781665431620

To realize real-time mobile augmented reality applications, various objects in the real world need to be instantly identified, located, and represented as a digital twin through sensor devices and edge IoT systems. However, it is challenging to make a fast and accurate decision on what the object is from real-time noisy streaming information. Multimodal decision making has been expected to mitigate such incomplete information and improve the accuracy of simplified recognition algorithms tuned for edge devices. In this paper, we propose an object estimation method inspired from the multimodal information processing mechanism of the brain, which makes decisions based on multiple types of uncertain observed information. Through computer simulations, we show that our proposed method identifies an object accurately and quickly from uncertain observed information. © 2022 IEEE.

关键词： Decision making

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A mobile-based lightweight road target recognition algorithm 3

A mobile-based lightweight road target recognition algorithm

引用

3rd International conference on Signal Image processing and Communication, ICSIPC 2023

作者： Li, Zhenlu Chen, Yuxuan Fang, Yushuai Sun, Kai College of Electronic and Information Engineering Inner Mongolia University Hohhot China

ISBN: (纸本)9781510670945

The recognition of road targets represents one of the central technological advancements within intelligent transportation systems, aimed at addressing the critical problem of urban congestion. In light of this, the present paper introduces a road target recognition algorithm, MOLO, specifically designed to navigate complex traffic environments, and subsequently deployed to facilitate detection via mobile devices. MOLO comprises two distinct components: a feature extraction network and a feature fusion network. The former of which, builds upon the structure of SSD network, integrates the lightweight receptive field expansion module RFB-L, whilst the latter introduces a pixel and channel information fusion module termed Fusion, thereby enabling the fusion of both shallow and deep features, ultimately enhancing the overall detection efficacy of the model. The model transformation process uses quantization and inverse quantization strategies between fixed-point and floating-point numbers, significantly reducing the number of parameters, all whilst preserving the accuracy of the detection performance on mobile devices. Experiments show that MOLO, when deployed to mobile, achieves an inference speed of 23.66ms and with 98.96% detection accuracy on the homemade road dataset Hohhot_city, and also shows superior performance in actual road detection. © 2023 SPIE.

关键词： Feature extraction

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Latency-Optimized Multi-User Task Offloading Scheme Using Dynamic Priority and Duplication in Edge Computing 29

Latency-Optimized Multi-User Task Offloading Scheme Using Dy...

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29th IEEE International conference on Parallel and Distributed systems, ICPADS 2023

作者： Peng, Bo Chen, Cheng Li, Qiang Peng, Shilin Lei, Xiang Southwest University of Science and Technology School of Information Engineering Mianyang China

ISBN: (纸本)9798350330717

The extensive development of complex applications in embedded devices has driven the rapid development of edge computing, which provides powerful processing capabilities to the edge network. In this context of development, task offloading has received widespread attention as one of the key issues in edge computing. However, since a task usually consists of multiple subtasks with dependencies, the current computing subtask on the local or edge server must wait for the completion of the previous dependent subtask. As a result, existing offloading schemes are often constrained by the complexity of the task topology. Therefore, this paper is aimed at tasks with dependencies described as Directed Acyclic Graphs (DAGs) in devices. First, we optimize the order of subtasks with dynamic priorities. Meanwhile, we employ task duplication to reduce communication latency and thus overall task completion time. Additionally, to support the edge computing environment of multi-user and multi-server, game theory is used to find the optimal offload position for each user, so as to obtain the minimum average computing delay of all tasks. Experimental results show that the proposed algorithm outperforms existing algorithms in terms of task completion delay. © 2023 IEEE.

关键词： directed acyclic graphs edge computing task offloading

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A Multi-chromosome Genetic Algorithm for Core Direction Allocation in optical Networks with Bidirectional Multicore Fiber

A Multi-chromosome Genetic Algorithm for Core Direction Allo...

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Asia Communications and Photonics conference and Exhibition (ACP)

作者： Jinbiao Nie Xiaodong Liu Shan Yin Xueyu Fan Mengru Cai Shanguo Huang State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350379266

ISBN: (纸本)9798350379273

We propose a multi-chromosome genetic algorithm for fiber core direction allocation in optical network with bidirectional multicore fiber (BMCF) for asymmetric traffic. To the best of our knowledge, this is the first study in fiber core direction allocation, aiming to reduce direction reversal-introduced cost. Simulation results show that it reduces the number of core direction changes.

关键词： Costs Multicore processing Simulation optical fiber networks Network architecture optical fiber devices Resource management optical devices Photonics Genetic algorithms

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A Manager Portrait Method based on Neighborhood Rough Set and Natural Language processing Algorithm 3

A Manager Portrait Method based on Neighborhood Rough Set an...

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3rd International conference on Applied Mathematics, Modelling, and Intelligent Computing, CAMMIC 2023

作者： Liu, Youping Shen, Jiangang Xue, Junshuai China North Talent Research Institute Beijing China Beijing Mafumatou Technology Co. Ltd. Beijing China Xi’an Electronic Engineering Research Institute Xi’an China

ISBN: (数字)9781510667617

ISBN: (纸本)9781510667600

The management of enterprises has long included manager management as a key responsibility. Recently, manager portrait has attracted attention as a research focus in the field of manager management. This paper aims to model the problem of manager portrait using neighborhood Rough Set theory. Personality characteristics of managers are extracted from document materials using Natural Language processing algorithms and integrated into the rough set model. In addition, the distance formula of the KFHARA attribute reduction algorithm is improved. A label attributes construction method and a portrait method suitable for manager portrait are proposed based on the rough set model and the improved KFHARA algorithm. Finally, the practicability of the method is illustrated by an example of an enterprise manager selection and appointment business scenario. © 2023 SPIE.

关键词： Natural language processing systems

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