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检索条件"任意字段=7th International Conference on Computing in Engineering and Technology, ICCET 2022"

共 11091 条记录，以下是921-930 订阅

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A Circularly Polarized Filtering Dielectric Resonator Antenna based on SIW Cavity 7

A Circularly Polarized Filtering Dielectric Resonator Antenn...

引用

7th IEEE international conference on Electronic Information and Communication technology, ICEICT 2024

作者： Liu, Xiaozhen Luo, Wei Liu, Meilin Xiong, Teng Chongqing University of Posts and Telecommunications School of Optoelectronic Engineering Chongqing China Chongqing Institute of Digital Arena Chongqing China Shanghai Jiao Tong University College of Aeronautics and Astronautics Shanghai China

ISBN: (纸本)9798350384437

this paper proposes a circularly polarized (CP) filtering dielectric resonator antenna (DRA) based on a substrate-integrated waveguide (SIW) cavity. the antenna is fed by a stacked feeding network to excite the dipole and DRs. the current is generated by a pair of dipoles and the equivalent magnetic current is generated by DRs. In one cycle, the current and the equivalent magnetic current operate alternately along the same direction with a phase difference of 90°, resulting in a circularly polarized wave. SIW cavity has high-pass transmission characteristics. the reflection coefficient and gain of the antenna show some sideband selective characteristics, which indicates that the antenna has a filtering function. the antenna obtained a relative impedance bandwidth of 26.51% (5.04-6.58 GHz) and an axial ratio bandwidth of 15.6% (5.26-6.16 GHz). With outstanding CP performance and compact size, the proposed CP filtering DRA is an attractive candidate for satellite communications. © 2024 IEEE.

关键词： Microwave antennas

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Quantum computing Approaches to Optimize Employee Scheduling in Multi-task Call Centers 3rd

Quantum Computing Approaches to Optimize Employee Scheduling...

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3rd international conference on Smart Manufacturing, Industrial and Logistics engineering, SMILE 2023 and the 7th Asian conference of Management Science and Applications, ACMSA 2023

作者： Li, Cheng Liu, Zhaoyang Song, Yu Liu, Haojie Liu, Hanlin Liu, Xiaodong Comprehensive Research Organization Fukuoka Institute of Technology Fukuoka Japan Graduate School of Engineering Fukuoka Institute of Technology Fukuoka Japan Department of System Management Fukuoka Institute of Technology Fukuoka Japan

ISBN: (纸本)9789819701933

the call center industry urgently needs efficient staff scheduling due to unpredictable customer service demands and challenges in human resource coordination. Appropriate scheduling is vital to enhance operational efficiency, reduce labor costs and improve customer satisfaction. this research is aim to solve the daily multi-task staff scheduling problem by integrating the innovative capabilities of QUBO (Quadratic Unconstrained Binary Optimization) model and Quantum computing. We formulate the intricate parameters related to the number of employees, task type, and skill proficiency using a traditional mixed-integer programming model. Specifically, the study formulates scheduling constraints and objectives and then we convert this model into a QUBO model this transformation makes the problem to be suitable for Quantum Annealing (QA) and enabling subsequent integration with QA technology. this technology enables rapid and advanced exploration of extensive solution spaces and identify the optimal or near-optimal solutions. this research offers valuable insights and substantial groundwork for future explorations and developments in optimizing call center staff scheduling problem. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Customer satisfaction

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Robust Event-Triggered Model Predictive Control for Uncertain Linear Parameter-Varying Systems 7

Robust Event-Triggered Model Predictive Control for Uncertai...

引用

7th IEEE international conference on Electronic Information and Communication technology, ICEICT 2024

作者： Jiang, Hongru Guo, Yue Liu, Tianxin Fan, Quan-Yong Lu, Kuan Northwestern Polytechnical University School of Automation Xi'an China Civil Engineering and Architecture Northwestern Polytechnical University School of Mechanics Xi'an China

ISBN: (纸本)9798350384437

A novel robust composite event-triggered model predictive control method is proposed for linear parameter-varying systems. the proposed controller integrates the nominal and robust compensation elements for optimal control in terms of the error between the observer state and the nominal. Only when the output of the observer violates the measurement error condition, the controller can be updated during the recalculation process of the optimal problem. the activation strategy effectively reduces the communication and computational burden, and the control design framework combines uncertainties and bounded disturbances into a robust invariant set to guarantee system stability. Finally, the viability of the method is verified through simulation experiments. © 2024 IEEE.

关键词： Predictive control systems

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Digital Entrepreneurship Ecosystem: An Exploration 7

Digital Entrepreneurship Ecosystem: An Exploration

引用

7th international conference on Contemporary computing and Informatics, IC3I 2024

作者： Yadav, Shiv Shankar Kumar Mishra, Gaurav Bennett University School of Management Uttar Pradesh Greater Noida India Amity University Uttar Pradesh Amity School of Engineering and Technology Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350350067

With the enriching technological space day by day, digital entrepreneurship has been competing at newer heights. Different bodies such as entrepreneurial hubs, incubations centres and hatcheries are instrumental in weaving this complex yet very productive network in order to extract synergistic performances. Efforts are budding up but how far we have reach? have ecosystem related discussions won the interest of researchers? is the'Digital Entrepreneurship Ecosystem (DEE)' visible as an emerging pattern in the scientific literature? What are the factors affecting the growth of DEE? To find answers to these questions this article explores the development happened so far, for the DEE. For the purpose, the methodology used is the content analysis. the study identifies key parameters affecting the evolution of DEE by examining the extant literature published over these years. © 2024 IEEE.

关键词： Digital Entrepreneurship Ecosystem Emerging Technologies Innovation Policy Stakeholders technology

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Enhancing Farming Practices through a Comprehensive Recommendation System 7

Enhancing Farming Practices through a Comprehensive Recommen...

引用

7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Rafiqi, Simrah Mahato, Manojeet Minu, R.I. SRM Institute of Science and Technology Dept. of Computing Technology India

ISBN: (纸本)9798350372816

In response to the pervasive challenges faced by farmers, including crop failure, insufficient knowledge, and crop damage, a holistic solution has been introduced. this comprehensive approach encompasses a Crop Recommendation System, Fertilizer Suggestions, and Crop Disease Detection Systems. To systematically address soil quality, a sophisticated examination system measures pH, Nitrogen, Phosphorus, and Potassium levels. Leveraging advanced Machine Learning classification algorithms, the system analyzes soil data to provide tailored crop recommendations, factoring in regional nuances and climate variations. this data-driven decision-making process enhances the precision of recommendations, optimizing agricultural outcomes. the holistic approach not only prevents crop failure but also empowers farmers with valuable insights, fostering knowledge enhancement for sustainable farming practices. Additionally, timely disease management is ensured through the early detection capabilities of the system, minimizing the impact of crop damage. Overall, this integrated solution aims to revolutionize agriculture by mitigating risks, improving productivity, and promoting environmentally conscious farming practices. the project endeavors to create a user-friendly platform tailored for farmers, aiming to empower them with precise guidance on crop selection and soil improvement. © 2024 IEEE.

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2023 7th international conference on Communication and Information Systems An Improved IOTA Protocol Based on Optimal Midway Walk 7

2023 7th International Conference on Communication and Infor...

引用

7th international conference on Communication and Information Systems, ICCIS 2023

作者： Wu, Hongcheng Zhi, Hui Liu, Yangyang Anhui University School of Electronic and Information Engineering Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Hefei230601 China Hefei Zhilian Technology Industry Investment Co. Ltd Hefei230601 China

ISBN: (纸本)9798350330540

IOTA (Internet of things Applications) protocol aims to provide a secure and trustworthy protocol for realizing data-value interactions between IoT devices, and it has become the next possible direction for the development of Blockchain applications. IOTA protocol has the problem that the time-consuming cumulative weight update grows too fast with the increase of the number of transactions, this paper proposed an improved IOTA protocol based on optimal midway walk, the improved protocol uses cutting-edge transaction selection algorithm of weighted Monte Carlo Markov random walk to reduce cumulative weight update delay. Firstly, this improved IOTA protocol mainly ensures the efficiency of transaction confirmation without losing the security of consensus by introducing the optimal midway walk method, i.e., the starting point of each walk is chosen to depart at an optimal location. Secondly, this paper designs the indirect verification identity record algorithm and the layer degree of confirmation principle are designed to realize the improved IOTA protocol's resilience and resistance to Parasite chain attack. the experimental results show that the improved IOTA using random function to select the midway walk starting point from i-50λ, to i-75λsubstantially solves the system computational burden problem and greatly reduces the cumulative weight update delay. © 2023 IEEE.

关键词： cumulative weight IOTA midway walk Parasite chain attack

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EAPNet: Enhanced Attention-Guided Network for Fine-Grained Semantic Segmentation 7

EAPNet: Enhanced Attention-Guided Network for Fine-Grained S...

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7th international conference on Robotics, Control and Automation engineering, RCAE 2024

作者： Huang, Minyu Hou, Beiping Pan, Feng Dong, Jianwei Zhejiang University of Science and Technology School of Automation and Electrical Engineering Hangzhou China China Telecom Corporation Ltd. Quzhou Hangzhou China

ISBN: (纸本)9798350355642

Ground-based cloud observation is essential for meteorological research and climate monitoring. Existing methods for cloud detection and classification in whole-sky images (WSIs) often focus solely on binary segmentation (sky and cloud) or image-level classification, which perform poorly in tasks requiring the classification and segmentation of different cloud types. this paper presents an enhanced attention-guided pyramid network (EAPNet) designed to enhance the accuracy and robustness of fine-grained cloud classification in whole-sky images through deep learning techniques. the key innovations include: 1) the utilization of the pyramid spatial pooling (PSP) module to capture multi-scale contextual information;2) the introduction of the convolutional block attention module (CBAM), which leverages an attention mechanism to enhance feature representation;and 3) an improved decoder module that enhances localization accuracy. Experimental results demonstrate that EAPNet outperforms existing mainstream methods in both cloud classification and segmentation tasks. © 2024 IEEE.

关键词： Semantic Segmentation

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Advancing Image Segmentation, Analysis, and Feature Extraction Techniques 7

Advancing Image Segmentation, Analysis, and Feature Extracti...

引用

7th international conference on Contemporary computing and Informatics, IC3I 2024

作者： Asha, V. Rangaiah, Yagateela Pandu Nijhawan, Ginni Kalyani, Susmita Rani, K. Pushpa Albawi, Ali New Horizon College of Engineering Bangalore India Institute of Aeronautical Engineering Department of Electronics and Communication Enfineering Dundigal Hyderabad500043 India Lovely Professional University Phagwara India Lloyd Law College Plot No. 11 Knowledge Park II Uttar Pradesh Greater Noida201315 India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India The Islamic University College of Medical Technology Radiology Techniques Department Najaf Iraq

ISBN: (纸本)9798350350067

this study centers on review, feature extraction, and image segmentation, integrated through the Dual-Path Convolutional Neural Network (DP-CNN). the DP-CNN is designed to accurately identify objects in images, even in the presence of intricate lines and discontinuities. the MAMAM technique efficiently prioritizes critical image regions, expediting the review process and enhancing accuracy in image analysis. Additionally, feature extraction is refined using the Adaptive Feature Selection (AFS) method, facilitating precise and adaptable image processing. Each component of this approach is systematically developed to meet the research objectives. the combined methodology demonstrates robustness and versatility, proving effective across diverse and challenging data scenarios, thereby presenting a promising solution for rapid and accurate complex image processing tasks. © 2024 IEEE.

关键词： Convolutional neural networks

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Fluorescence Image Denoising Based on Self-supervised Deep Learning 7

Fluorescence Image Denoising Based on Self-supervised Deep L...

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7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Huang, Haojian Liu, Yixuan Li, Yang College of Computer Science and Technology Harbin Engineering University Harbin Heilongjiang150001 China College of Transportation Engineering Tongji University Shanghai201804 China College of Electrical Information Wuhan Institute of Technology Wuhan430200 China

ISBN: (纸本)9781665478571

Fluorescence microscopy imaging technology is a crucial imaging technology widely used in biomedical fields such as brain science. However, its images often have random noise without a fixed pattern, causing a series of problems such as image degradation, image segmentation, and classification misalignment. In order to obtain higher signal-to-noise ratio imaging, the input of higher doses of photons increases the cost and causes adverse effects such as photobleaching, phototoxicity, or tissue heating. therefore, researchers have studied many traditional denoising methods and deep learning-based denoising methods. Traditional denoising methods have the advantage of fast and straightforward processing and tend to perform well when the noise level of the image is low, or the noise distribution is known. However, its effectiveness and generalization are minimal when the noise level is high and randomly distributed without a fixed modality. On the contrary, image denoising methods based on self-supervised deep learning can extract high-dimensional features of images, have better effectiveness and robustness in practical denoising applications. Morever, these methods reduce the need for manual annotation of large-scale data, making timely research on cutting- edge pathology possible when there are insufficient labeled data. In this paper, to tackle the denoising problem of fluorescence microscopy images, two classic traditional denoising methods, Wiener filtering, and wavelet transformation, and methods based on deep learning, DeepCAD, are used for comparative experiments. the experimental results show that the deep learning method has good effectiveness and generalization in dealing with high-level random noise, and it performs better than traditional denoising methods. © 2022 IEEE.

关键词： Wavelet transforms

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Auxiliary Classifier GAN-Based Super-resolution Microwave Coincidence Imaging 7

Auxiliary Classifier GAN-Based Super-resolution Microwave Co...

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7th IEEE international conference on Electronic Information and Communication technology, ICEICT 2024

作者： Zhu, Shitao Hu, Chunyu Li, Die Zhang, Anxue School of Information and Communications Engineering Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9798350384437

Microwave coincidence imaging (MCI) has attracted more and more attention, but the number of the low correlated measurement modes is limited leading to a limited imaging performance. the unsupervised data augmentation can be achieved by the Generative Adversarial Networks (GAN) to address the issue of limited samples. In this paper, an Auxiliary Classifier GAN-based super-resolution imaging method for MCI is proposed. To achieve the classification of ten uniformly distributed target points within the 3dB beamwidth (i.e. 10 times super-resolution imaging), a training dataset is designed based on the spatial correlation characteristics of the reference radiation field in MCI systems. Experimental results demonstrate that the proposed approach can effectively generate high-quality samples to meet classification requirements. Compared with other methods, the accuracy and classification efficiency can be improved. © 2024 IEEE.

关键词： Generative adversarial networks

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