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Construction of Foreign Language Translation Recognition System Model Based on Artificial Intelligence Algorithms 3

Construction of Foreign Language Translation Recognition Sys...

引用

3rd IEEE international conference on distributed Computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Li, Xin Gao, Shuai School Of Foreign Languages College Of Humanities & Information Changchun University Of Technology Jilin Changchun China School Of Foreign Languages Changchun University Jilin Changchun China

ISBN: (纸本)9798350318609

With the development of economic globalization, many foreign languages have become the most common languages in the world and have been increasingly applied. However, there is a shortage of personnel with high foreign language proficiency in various industries. People should strengthen the cultivation of language skills according to market needs. Translation is the core of language ability, and in order to apply foreign languages to practical communication activities, it is necessary to pay attention to the correction and research of foreign language pronunciation. Previously, foreign language translation systems were conducted according to the instructions of teachers, which not only consumed a lot of manpower but also made it difficult to implement. Therefore, it is very important to research and establish an intelligent translation system. This mode can monitor students' foreign language pronunciation and provide correct suggestions. The traditional intelligent recognition mode and settings for foreign language translations are not accurate enough to accurately recognize foreign language translations, correct foreign language pronunciation correctly, and even produce incorrect pronunciation, thereby affecting foreign language learning. Based on the above issues, this article studied an intelligent foreign language translation recognition model based on CNN (Convolutional Neural Networks) algorithm and DTW (Dynamic Time Warping) algorithm, in order to automatically recognize foreign language translations. In order to verify the effectiveness of the model, simulation experiments were conducted in the simulated environment in the article. The experimental results showed that compared to existing systems, the machine synchronous translation system of artificial intelligence technology and speech recognition (in this article) had the highest translation recognition accuracy of 95 00%. © 2024 IEEE.

关键词： Speech recognition

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Modeling and Analysis of UAV-Assisted Cellular Networks with Non-Orthogonal Multiple Access 3

Modeling and Analysis of UAV-Assisted Cellular Networks with...

引用

3rd international conference on Computing, Communication, Perception and Quantum Technology, CCPQT 2024

作者： Zhou, Yang Xiu, Minjin Zhai, Daosen He, Zihang Gou, Haosong Zhang, Gaoyi School of Electronics and Information Northwestern Polytechnical University Xi’an China Sichuan Co. Ltd. China Mobile Group Chengdu China

ISBN: (纸本)9798331528386

Unmanned aerial vehicles (UAVs) provide a fast and feasible solution for emergency communications in areas where traditional ground base stations (BSs) cannot provide reliable wireless communication links, relying on their fast and flexible deployment. In this paper, the isolated region of target coverage is modeled as a circle, and the interference BSs outside the area is modeled as a homogeneous Poisson point process (HPPP) in the infinite 2D plane. User equipments (UEs) are evenly distributed in a circular area, served by drones suspended in the center of the area. At the same time, considering the shortage of UAV communication resources, the non-orthogonal multiple access (NOMA) technology enables multiple users to share the same resources to improve the coverage performance of the UAV. At this time, this paper analyzes and solves the UAV downlink transmission performance based on distance and signal-to-noise ratio (SNR) by using stochastic geometry and order statistics theory. In order to better characterize channel fading, we use probabilistic multi-slope path loss large-scale model and Nakagami-m small-scale *** this basis, the influence of various parameters on the coverage performance is studied. © 2024 IEEE.

关键词： Signal to noise ratio

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Decentralized Multi-UAV Management in Mobile Edge Computing: A Hierarchical Reinforcement Learning Approach 3

Decentralized Multi-UAV Management in Mobile Edge Computing:...

引用

3rd international conference on Computing, Communication, Perception and Quantum Technology, CCPQT 2024

作者： Peng, Ziling Liu, Shuai Jaber, Al Jian, Lim W.E.I. Li, Hui Qian, Jin College of Information Engineering Taizhou University Taizhou China

ISBN: (纸本)9798331528386

The integration of drones in Mobile Edge Computing (MEC) has opened new possibilities for enhancing network performance in various fields, such as agriculture, environmental monitoring, and disaster management. However, effective coordination of multiple Unmanned Aerial Vehicles (UAVs) in dynamic and distributed environments poses significant challenges, especially in mobility management and resource allocation. To address these issues, we propose a Decentralized Hierarchical Policy Framework inspired by hierarchical reinforcement learning. This framework employs a two-level structure, consisting of high-level communication coordinators and low-level executors, allowing UAVs to make decentralized decisions based on local observations and partial communication. Our approach models the multi-UAV MEC problem as a Decentralized Partially Observable Markov Decision Process with communication, enabling efficient task allocation and resource management. Experimental evaluations demonstrate that the proposed method improves MEC service coverage, reduces latency, and optimizes UAV energy consumption. Compared to state-of-the-art Multi-Agent Reinforcement Learning methods, our approach achieves superior performance in dynamic and large-scale environments. © 2024 IEEE.

关键词： Reinforcement learning

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Landslide susceptibility assessment in Qingyijiang river basin based on different machine learning methods 3

Landslide susceptibility assessment in Qingyijiang river bas...

引用

3rd international conference on Remote Sensing, Surveying, and Mapping, RSSM 2024

作者： Cheng, Yashan Li, Juan Liu, Xiaocong Department of Information and Communication Officers College of PAP Chengdu China Sichuan Academy of Eco-Environmental Sciences Chengdu China

ISBN: (数字)9781510680081

ISBN: (纸本)9781510680074

Susceptibility assessment is an effective tool for landslide disaster prevention and control. Machine learning algorithms can effectively reduce the subjectivity of determining the weights of factors in disaster risk assessment, which has become a hot spot in current research. We selected maximum monthly rainfall during the year, slope, FVC, distance from rivers, distance from faults and vegetation type as the influencing factors for landslide susceptibility assessment, and used BP neural network and random forest algorithms to evaluate the susceptibility of landslide hazards in the Qingyijiang river basin, and compared the evaluation results. The results show that the fitting results of the random forest algorithm are better. According to the fitting results of the random forest algorithm, the landslide hazard in the Qingyijiang river basin is closely related to the distance from the fault and the distance from the river, and about half of the area (48.75%) in the basin is at risk of small landslides, and most of them are distributed near the river. © 2024 SPIE.

关键词： Rivers

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Compressed YOLOv5 for Oriented Object Detection with Integrated Network Slimming and Knowledge Distillation 3

Compressed YOLOv5 for Oriented Object Detection with Integra...

引用

3rd international conference on information Science, parallel and distributed systems, ISPDS 2022

作者： Xu, Yifan Bai, Yong College of Information and Communication Engineering Hainan University Haikou China

ISBN: (数字)9781665487474

ISBN: (纸本)9781665487474

In recent years, object detection has been expanded to drone scenes, where remote sensing images contain a greater variety and arbitrary-oriented targets. In order to solve the problem of detection difficulty and computational intensity for remote sensing images, oriented object detection is needed and the network model is expected to be deployed on resource-limited devices. This paper proposes a lightweight object detection method for oriented object detection by leveraging and compressing YOLOv5 network model. We integrate the fine-tuning stage in network slimming with knowledge distillation to enhance the accuracy of the detection model and save training time by transferring the important feature information to the student network. Loss function is redesigned by combining Theta loss with other detection and distillation losses to make the compression model more accurate. Extensive experiments are conducted to verify the effectiveness of our proposed method on the remote sensing public dataset DOTA. The compressed model achieves an accuracy of 76.18% on the DOTA dataset, 1.7% increase compared to the original YOLOv5 model. The FLOPs are decreased by 37.0%, the number of parameters is decreased by 58.9%, the weight file size is decreased by 57.6%, and the inference time is decreased by 17.4%. © 2022 IEEE.

关键词： Distillation

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Analysis and Comparison of Mathematical Models PV Array Configurations (Series, parallel, Series-parallel, Bridge-Link and Total-Cross-Tied) Under Various Partial Shading Conditions 1

引用

3rd international conference on Digital Technologies and Applications

作者： Abouyaakoub, Mohcine Hihi, Hicham Univ Sidi Mohamed Ben Abdellah Lab Ingn Syst & Applicat Fes Morocco

ISBN: (数字)9783031298608

ISBN: (纸本)9783031298592;9783031298608

The objective of this work is to study the effect of partial shading on a solar photovoltaic (PV) array configuration mathematically modeled in Matlab/Simulink. We will study five different photovoltaic array configurations 3x3: Series (S), parallel (P), Series-parallel (SP), Bridge-Link (BL) and Total-CrossTied (TCT). In this article we will simulate six partial shading cases (uniform, corner, center, uneven column, uneven row, diagonal, and frame). The performance of five PVconfigurations is evaluated by the determination of open circuit voltages, short circuit currents, maximum powers, the corresponding maximum voltages and currents, the fill factor and mismatch power loss. The results obtained for the PV array 3x3 configuration are an important guide that provides useful information on the performance of each PV array configuration under six shading scenarios.

关键词： Mathematical models PV array configurations Partial shading cases Mismatch Power Loss Fill Factor

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Edge Computing: Architecture, Implications and Future with Latest Trends 3

Edge Computing: Architecture, Implications and Future with L...

引用

3rd international conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Thakkar, Krish Patel, Akash Budhrani, Aishwariya Patel, Khushi Patel, Sachin Nayak, Amit Department of Information Technology Gujarat Changa388421 India Department of Computer Science & Engineering Gujarat Changa388421 India Department of Computer Engineering Gujarat Changa388421 India

ISBN: (纸本)9798350322842

As a result of the proliferation of Internet-connected smart devices brought about by the explosive growth of the Internet of Everything (IoE), lower bandwidth load, slower response, bad security, and poor privacy are just some of the issues that have arisen with data growth. Edge computing solutions have arisen as a response to the limitations of traditional cloud computing in meeting the data processing demands of modern societies. Edge computing, the new era of distributed computing, differs from cloud computing in that it places greater emphasis on being physically proximate to both the user and the data itself. The primary focus of this article is a critical examination of the associated literature and findings around edge computing. Edge computing is first briefly compared with cloud computing. Then, briefly discuss edge computing's architecture, followed by major challenges with edge computing and ending with latest trends with edge computing. © 2023 IEEE.

关键词： Computer architecture

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A Critical Investigation into the Blockchain Technology and Its Present-Day Uses 3

A Critical Investigation into the Blockchain Technology and ...

引用

3rd international conference on Computing and information Technology, ICCIT 2023

作者： Bharany, Salil Maashi, Mashael Lovely Professional University Department of Cse Punjab Phagwara144402 India King Saud University College of Computer and Information Sciences Software Engineering Department Riyadh11543 Saudi Arabia

ISBN: (纸本)9798350321487

The IoT is a new technology that allows for the networking and communication of digital and physical things to provide novel digital services that enhance our daily lives. Though the Internet of Things (IoT) has many benefits, its centralized design raises several problems, such as a lack of redundancy, privacy concerns, transparency, and compromised data integrity. These issues are a roadblock to further advancements in IoT software. Since Bitcoin's introduction as the first and largest cryptocurrency, blockchain technology has been widely recognized as a foundation for digital money. So yet, it has to be utilized primarily to decentralize monetary or payment systems. Blockchain's distributed transaction ledger might be used to store and transmit contracts over a network. This study provides a comprehensive overview of the most recent blockchain-related applications in the academic literature. Several research papers from the canon of literature were hand-picked for inclusion in the blockchain for their potential to advance human understanding. Several observations are examined and addressed in the latter part of the work. © 2023 IEEE.

关键词： Blockchain

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Hybrid Approach for the Classification and Detection of Brain Tumors 3

Hybrid Approach for the Classification and Detection of Brai...

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3rd international conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Ramachandran, R. Senthil, R. Mukunthan, M.A. Kanimozhiraman Balasubramanian, D. Rajalakshmi Engineering College Department of Bio Medical Engineering Thandalam Tamil Nadu Chennai602105 India Muc Muscat112 Oman School of Computing Veltech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Tamil Nadu Chennai600062 India Kcg College of Technology Department of Mathematics Karapakkam Chennai600097 India Jaya Engineering College Tamilnadu Thiruninravur602024 India

ISBN: (纸本)9798350322842

Hyperspectral analysis is a highly complex that supposes the development of algorithms with an enormous computational cost. The practical application of hyperspectral analysis requires the parallelization of said algorithms if it is to provide results in real time, using high-performance and massively parallel processing platforms that allow reducing execution times. In this learning, the potential of hybrid Hyperspectral image classification approaches is demonstrated. In the analysis of spectral information to identify histological samples affected by tumor tissue, the current proposal integrates HSI linear decomposition algorithms with classification methods such as neural networks. The outcomes demonstrate the usefulness of the proposed technique for the classification of histological tissue samples, producing significant accuracy in the analyzed images. © 2023 IEEE.

关键词： Classification (of information)

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Third international conference on Computer Vision and information Technology, CVIT 2022

Third International Conference on Computer Vision and Inform...

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3rd international conference on Computer Vision and information Technology, CVIT 2022

ISBN: (纸本)9781510663039

The proceedings contain 15 papers. The topics discussed include: relative vectors clustering and temporal constraint based generalized Hough transform for high frame rate and ultra-low delay arbitrary shape detection;multi-line buffer based pipeline architecture with junction connectivity analysis for high frame rate and ultra-low delay contour-based corner detection;vision-based fall detection system for the elderly using image processing and deep learning;convolutions vs. sequences: understanding performances of neural-based methods for automatic Baybayin script recognition;research of pavement crack detection system based on image processing;research on target detection based table tennis drop point recognition system;a survey on potential reactive fault tolerance approach for distributed systems in big data;position reset and hybrid feature based particle filter tracking for large-size and long-term full occlusion;and comparative study of informal learning spaces in colleges based on the occurrence probability of informal learning.

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