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Undergraduate Talents Training system of Chinese international Education Major Based on Artificial intelligence 3rd

Undergraduate Talents Training System of Chinese Internation...

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3rd EAI international conference on Application of Big Data, Blockchain, and Internet of Things for Education Informatization, BigIoT-EDU 2023

作者： Chen, Dongping Jing, Zhang Yunnan Technology and Business University Kunming65000 China

ISBN: (纸本)9783031631351

With the prosperity of the global economy, the languages of all countries are in urgent need of breaking national boundaries to show the world their unique language charm, and at the same time expect that languages can serve the people of the world. The size of the scope of language use determines the influence of a country's national image accordingly. As the representative of China's image, Chinese participates in the competition of world languages. More and more people begin to understand Chinese. Chinese is warming up around the world. Colleges of Chinese international Education have been established in major universities across the country. This paper focuses on the research on the talent training system for Chinese international education undergraduates based on AI, and mainly develops the talent training system based on AI for Chinese international education undergraduates. The research team has developed an intelligent learning management system (ILMS) to support the development process of ILM courseware. ILMS integrates with MOOC platform, student information system and other systems to provide online courses for students majoring in international education or those who want to study. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Students

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AGV magnetic navigation unmanned vehicle handling wood automation 3

AGV magnetic navigation unmanned vehicle handling wood autom...

引用

3rd international conference on Control and Intelligent Robotics, ICCIR 2023

作者： Bi, Xinwei He, Qiwen Li, Yonheng Liu, Guangyan Li, Xiangshan School of Artificial Intelligence and Manufacturing Hechi University Hechi546300 China

ISBN: (纸本)9781510671867

To improve the efficiency and safety of wood handling, an AGV magnetically guided handling unmanned vehicle is designed. The AGV magnetic navigation unmanned vehicle uses the STM32 as the control system, acquisition of magnetic signals using the MGS-16FP magnetic navigation sensor, HC-SR04 ultrasonic distance measurement module collects distance information, MFRC522 module reads and writes line information, LCD shows unmanned vehicle status. The ESP8266 module transmits data via the MQTT protocol for path planning and real-time monitoring. The AGV magnetic navigation unmanned vehicle designed in this paper has high efficiency and stability and can work stably indoors to automate wood handling, which greatly improves the efficiency and safety of wood handling. © 2023 SPIE.

关键词： Efficiency

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Deep Learning Approaches for Enhancing Content Retrieval 3

Deep Learning Approaches for Enhancing Content Retrieval

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Khurana, Saniya Singh, Shweta Ranganathaswamy, M.K. Renuka, G. Diwakar, Mandar P. Jain, Sandeep Kumar Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Mechanical Engineering Karnataka Ramnagar562112 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Vivekananda Global University Department of Electrical Engineering Jaipur India

ISBN: (纸本)9798350319125

Deep learning strategies for content material retrieval have been explored and updated to cope with the want for accurate search effects. This machine up to date is used to date apprehend and examine text-up-to-date content material from sources, up-to-date webpages, or virtual up-todate motion pictures. As the quantity and complexity of online content will increase, so up-to-date have the want for higher up-to-date up to date those resources. Recent advancements in deep gaining knowledge have enabled better content retrieval structures that are up to date, updated correctly, and speedy to understand statistics from one-of-a-kind sources. Such structures include natural language processing (NLP), sentiment analysis, entity reputation, and up-to-date updated reputation. Those deep studying technologies have been used to decorate content material retrieval by enhancing search effects' accuracy, robotically updated extracting applicable statistics, categorizing information, and identifying patterns. Additionally, deep-getting, updated systems are up-to-date and quick to examine large volumes of data, generating and relevant consequences than up-to-date methods. In summary, deep up-to-date techniques can beautify the retrieval system of content material efficiently, enhancing the accuracy and pace of seek effects. © 2023 IEEE.

关键词： categorizing comprehend effectively learning techniques

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Research on Intention Tendency detection for Chinese Medical Question Answering Task 3

Research on Intention Tendency Detection for Chinese Medical...

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3rd international conference on Artificial intelligence and Computer Engineering, ICAICE 2022

作者： Chen, Musheng Liu, Ying Wu, Junhua School of Software Engineering Jiangxi University of Science and Technology Jiangxi Nanchang330013 China Nanchang Key Laboratory of Virtual Digital Engineering and Cultural Communication Jiangxi Nanchang330013 China

ISBN: (纸本)9781510663473

In the Chinese medical question and answer task, question intention detection is a very important part. At present, the common intention detection methods mainly use the manually designed matching rules to find the problem features to detect the intention of the problem, but the use of a large amount of labor usually brings about problems such as high cost and poor versatility. A novel method of intention detection is proposed in this paper. First, the collected questions with different intention categories are used to construct intention feature words. Then, based on the BERT pre-training language model, a two-classification model of phrase similarity is constructed. By comparing the combination results of problem word segmentation and the similarity of intention feature words, the multi-classification problem of problem intention detection is transformed into a two-classification problem between multiple phrases. Then we can get the inclination of the question for each intention category, that is the intention category of the question. The experiment shows that the method based on the two-classification model of phrase similarity has better effect than the previous methods, and the F1 value in the test set reaches 90.1. © 2023 SPIE.

关键词： Classification (of information)

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Efficient Approach Towards detection and Classification for Image Forgery by Using Machine Learning Technique 3

Efficient Approach Towards Detection and Classification for ...

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3rd IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Hussein, Abbas Hameed Abdul Kavitha, R. Kumar, Bura Vijay Issa, Ali Ashoor Al-Attabi, Kassem College of Pharmacy Ahl Al Bayt University Karbala Iraq Department of ECE Tiruchengode India School of Computer Science and Artificial Intelligence SR University Telangana Warangal India National University of Science and Technology Dhi Qar Iraq The Islamic University Najaf Iraq

ISBN: (纸本)9798350317022

Copy-move forgery (CMF) is one of the most malicious forgery attacks often manipulated to spread misinformation and influence security. In the paper, utilized Machine Learning techniques specifically, a Multiclass Support Vector Machine (MSVM)-based Particle Swarm Optimization (PSO) algorithm was utilized for image forgery. PSO is an optimization algorithm in which a group of particles representing individual solutions moves through a search space to find the best solution. The objective function that the PSO algorithm seeks to minimize or maximize is typically related to the MSVM's performance on a validation dataset. The MICC-F200 dataset was used to verify the uniqueness of CMF and evaluate the model's image classification performance. It's important to note that MSVM based PSO can become computationally expensive and memory-intensive when dealing with a large number of classes. They are also sensitive to noisy or mislabeled data points, which can potentially lead to suboptimal performance. The results obtained from this study reveal that the MSVM-based PSO model achieves a high accuracy of 0.9936 on the MICC-F200 dataset, outperforming other existing models such as VGG16 and Mobile Net, thereby ensuring accurate image classification. © 2023 IEEE.

关键词： Copy-Move Forgery Gray Scale Technique Machine Learning Particle Swarm Optimization and Support Vector Machine

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An Improved Fuzzy Logic Based Alcohol detection system to Preserve Road Safety using Smart Sensors Association 3

An Improved Fuzzy Logic Based Alcohol Detection System to Pr...

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3rd IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Kavitha, V.R. Muthu, Annamalai Geetha, B. Pandi, V. Samuthira Dinesh, M. Princy, B. Anni R.M.K. Engineering College Department of Computer Science and Business Systems Tamil Nadu Chennai India University of Technology & Applied Science Department of Engineering Nizwa Oman Prince Shri Venkateshwara PadmavathyEngineering College Department of Science & Humanities Tamil Nadu Chennai India Centre for Advanced Wireless Integrated Technology Chennai Institute of Technology Tamil Nadu Chennai India Saveetha School of Engineering SIMATS Department of VLSI Microelectronics Tamil Nadu Chennai India Panimalar Engineering College Department of Computer and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350317022

The increased risk of being involved in a traffic collision is directly proportional to the rate at which the number of vehicles on the road is growing. The majority of people in the world believe that driving under the influence of alcohol is a significant factor in the number of people killed in car accidents. The fundamental purpose of this investigation is to develop a device that is able to determine the degree of drunkenness that is present in the driver of a motor vehicle. The purpose of the proposed system is to discourage users from getting behind the wheel while under the influence of alcohol or drugs in order to reduce the number of accidents that are caused by intoxicated drivers. As part of this investigation, we propose the Fuzzy Assisted Alcohol detection Mechanism (FAADM), which is a logical fuzzy-based alcohol detection mechanism. It uses a Direct Current (DC) motor as the vehicle's engine and a push button as its ignition system. This mechanism detects the presence of alcohol using a fuzzy-logic approach. The efficiency of this system is always being evaluated to ensure that it performs as designed. If this system were put into place, there would be a reduction in the number of accidents on the roads of smart cities that were caused by drivers who were under the influence of alcohol. It is strongly suggested that this system be fitted and installed inside the vehicle. In the event of an unexpected emergency, the engine should be turned off and the alarm should be activated. If there has been no drinking or accidents, the security system can be disarmed and the vehicle's engine should be started. If alcohol is found, the car will be turned off and an alarm will ring. As the number of incidents caused by intoxicated drivers continues to rise, the implementation of a system that combines alcohol detection and vehicle immobilization has been proposed as a potential solution. Engineers have developed a gadget that can detect the amount of alcohol in a d

关键词： Alcohol detection Mechanism Alcohol Identification Drunk and Drive FAADM Fuzzy Logic Microcontroller Road Safety Sensors

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Third international conference on Sensors and Information technology, ICSI 2023

Third International Conference on Sensors and Information Te...

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3rd international conference on Sensors and Information technology, ICSI 2023

ISBN: (纸本)9781510666122

The proceedings contain 36 papers. The topics discussed include: sensor fusion-based obstacle detection method for hazy environment;study on the spatial distribution of potential fire sources in highway tunnels;research on key technologies of performance navigation for civil aircraft based on multi-sensor information fusion;improvement of the swirlmeter with anti-jamming performance;research on cell activity sensor based on impedance principle;ensemble kernel-based broad learning system for fast gas recognition in electronic nose systems;research on the application of remote sensing and GIS technology in railroad engineering geology survey;broadband current array sensing system for transformer and its stability control technology;impedance characteristics of flexible strain sensors based on zero-dimensional carbon nanocomposites;and monocular visual-inertial odometry with wheel encoder for urban vehicle.

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Framework and Key Technologies for High-speed Railway Comprehensive Transport Hub 3

Framework and Key Technologies for High-speed Railway Compre...

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3rd IEEE international conference on Digital Twins and Parallel intelligence, DTPI 2023

作者： Xiong, Gang Zhang, Wei Liu, Xiaoming Yuan, Zhiming Zhu, Fenghua Zhang, Zundong Chinese Academy of Sciences State Key Laboratory for Multimodal Artificial Intelligence Systems Beijing China North China University of Technology School of Electrical and Control Engineering Beijing China China Academy of Railway Science Communication Signal Research Institute Beijing China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing China

ISBN: (纸本)9798350318470

The surge in urban population density in China has underscored the vital role of high-speed rail and subway systems in urban transit. Comprehensive transportation hubs, notably high-speed rail passenger terminals, have emerged as linchpins for seamless multimodal transit both within and beyond urban centers. China's railway sector vigorously champions the innovative concept of "station-city integration"and has articulated a forward-looking "16-word policy"for modern railway stations: "Seamless integration, environmental friendliness, economic viability, and intelligent accessibility". The judicious allocation of resources and the augmentation of coordination and control capabilities within comprehensive transportation hubs are imperative for the harmonious evolution of urban transit. The implementation of intelligent control systems for transportation hubs has emerged as a pivotal area of research. This study delves into the framework and critical technologies for high-speed railway comprehensive transport hubs, encompassing various components and their intricate interplay, including transport modalities, infrastructure, travelers, environmental factors, and information systems, thus forming a prototypical cyber-physical-social system. Addressing the prevalent and pressing imperative for the advancement of "station-city integration"high-speed railway comprehensive transport hubs, this research endeavor aims to surmount bottleneck challenges and refine the oversight of passenger flows at high-speed rail terminals. The findings hold noteworthy theoretical import and portend promising practical applications. © 2023 IEEE.

关键词： Integration

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A system to Increase the Accuracy of Deep Learning based Classification by the Distribution of Labels 24

A System to Increase the Accuracy of Deep Learning based Cla...

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3rd international conference on Computer, Artificial intelligence and Control Engineering, CAICE 2024

作者： Jin, Guanghao Wang, Yuqing Wang, Jieying Du, Hui Ma, Lei Song, Qingzeng School of Artificial Intelligence Beijing Polytechnic Beijing China School of Computer Science and Technology Tiangong University Tianjin China

ISBN: (纸本)9798400716942

In some deep learning-based applications, we can use the distribution of labels to increase the classification accuracy like the distribution of the labels in the corresponding application. This kind distribution can be obtained by the experience of human being while it is generally imprecise. Using validation set can be a solution to compute precise distribution of labels while this is affected by the application change. In this paper, we propose a novel system, which efficiently utilizes the experience of human being and validation set to improve the performance of classification models. Firstly, our method selects and trains an existing deep learning model on the training set. Then, these models can output the probability of labels on each testing sample. Secondly, our system utilizes the user input and the validation set, which is to get the precise distribution of labels in an application. Finally, the computed distribution of labels is selectively combined with the probability of labels on testing samples to get the final classification results. We selected some existing deep learning models on three public datasets to evaluate the models. As the evaluation results show, our system can improve the performance of classification tasks, which is obviously higher than state-of-art methods. © 2024 ACM.

关键词： Contrastive Learning

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Survey on the Effectiveness of Traffic Sign detection and Recognition system 1

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3rd international conference on Information technology, InCITe 2023

作者： Patel, Pranav A. Vekariya, Vipul Shah, Jaimeel Vala, Brijesh Parul Institute of Engineering and Technology Vadodara Gujarat Limda India

ISBN: (数字)9789819959945

ISBN: (纸本)9789819959938

Advanced driving assistance systems - ADAS are essential for Recognition and detection. The term "ADAS" refers to various cutting-edge in-vehicle technologies created to improve road traffic safety by assisting drivers in becoming more aware of the road, its potential hazards, and other vehicles around. Constructing reliable methods for recognizing traffic signs has been an important and exciting field of study. The research community has shown a more interest in investigating traffic sign detection and recognition (TSDR), primarily driven by detection and classification. In recent years various TSDR approaches have been introduced. This research provides a comprehensive look at methods for identifying and classifying traffic signs. It briefly reviews the most recent technology in this area and then discusses a future trend. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Traffic signs

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