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Construction of Business English Needs Analysis Model Based on Computer Corpus 3rd

Construction of Business English Needs Analysis Model Based ...

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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： Lu, Yao Zhang, Li Ma, Lingya Shandong Management University Shandong Jinan250357 China Hubei Three Gorges Polytechnic Hubei Yichang443000 China

ISBN: (纸本)9783031631290

In order to meet the needs of business English, this article constructs a computer corpus based business English requirement analysis model. By collecting and organizing relevant corpus in the field of business English, establish a large-scale and diverse corpus. Then, using natural language processing technology and machine learning algorithms, the corpus is analyzed and processed to extract common vocabulary, phrases, and grammatical structures in business English. Next, by clustering and mining association rules on the texts in the corpus, the actual needs and characteristics of business English are discovered. In the process of model construction, we will also consider different branches and specialties in the business field, such as marketing, international trade, business communication, etc., to adapt to the needs of different fields. Finally, based on the results of the needs analysis, we will provide targeted suggestions and guidance for business English teaching and training. The construction of this model helps educators and learners better understand the characteristics and needs of business English, in order to carry out business English teaching and training more effectively. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Big data

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Research on data Security Technology Based on Homomorphic Encryption in Cloud Computing Environment

Research on Data Security Technology Based on Homomorphic En...

引用

signal processing, Communications and Engineering Management conference (ISPCEM), international

作者： Liang Chu Guangzhou Huashang Vocational College Guangzhou Guangdong China

With the development of cloud computing, data security issues have become increasingly prominent. As an encryption method that can perform calculations in the ciphertext domain, homomorphic encryption technology provides an effective solution for data security in a cloud computing environment. data security technology based on homomorphic encryption is the main subject of this paper. First, the classification and characteristics of homomorphic encryption technology are introduced, as well as security analysis methods, and then a data security system based on fully homomorphic encryption is designed, including data acquisition and preprocessing modules. Then, the data analysis module adopts a model structure based on a neural network and provides the model training and parameter optimization process. Finally, experiments were conducted based on real data sets to verify the feasibility and effectiveness of the system, and the system was evaluated from the aspects of accuracy, time overhead, and storage overhead. This paper concludes that homomorphic encryption technology can guarantee data privacy and integrity in a cloud computing environment while also improving computing efficiency and scalability.

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Big data Tools, Deep Learning & 3D Objects in the Metaverse 2

Big Data Tools, Deep Learning & 3D Objects in the Metaverse

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2nd international conference on Digitalization and Management Innovation: Build a New Ecology of Lifelong Education, DMI 2023

作者： Ananthachari, Preethi Schutte, Storm AI & Big Data Dept Endicott College of International Studies Woosong University Korea Republic of

ISBN: (纸本)9781643684529

Metaverse is a virtual space to explore, for those who are not physically available in context. We are in the early stages of the development of the metaverse and it promises a rapid phase shift as well as proliferation in every aspect of technology. The metaverse comprises of eight key technologies, such as Extended Reality, Customer (user) Interactivity, Artificial intelligence, Block Chain Technology, Computer Vision, Internet of Things, Robotics, Fog/ Edge/ Cloud Computing, additionally, 5G/ 6G (Future) Mobile networks that are relevant to the metaverse. Big data is a significant source that complements each of these techniques. In this paper, we will discuss how different big data techniques help with the growth of the metaverse. The comparison of 3rd Dimensional objects in terms of Spark architecture with HDFS is carried out. We utilized large-scale 3D data to implement and evaluate various machine learning and deep learning models, facilitating a thorough comparison of their performance. Both of the Models have their own advantages and drawbacks, Random Forest model stands out in terms of processing speed, though SimpleNet requires more time for the validation accuracy improvement. © 2023 IOS Press. All rights reserved.

关键词： Big data

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Electromagnetic Interference of Unmanned Aerial Vehicle in High Voltage Environment 3

Electromagnetic Interference of Unmanned Aerial Vehicle in H...

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2023 3rd international conference on Electrical, Electronics, and Computing Technology, EECT 2023

作者： Li, Xuecheng Wang, Shaolong Li, Haofeng Zhou, Yulong Guo, Haitao Qingyang Power Supply Company of State Grid Gansu Electric Power Company Qingyang745000 China

The X-ray inspection of wire clamps is used more and more widely. X-ray detection uses UAV (Unmanned Aerial Vehicle) to inspect the clamp with high voltage, which directly contacts the electrified wire clamp. When the strength of the overhead transmission line exceeds the air breakdown strength, extreme discharges will occur, so the control and data transmission performance of the UAV is influenced, and even cause a crash. The electromagnetic interference can also cause the wrong magnetic compass, lead the UAV fails to take off. The UAV and Ray detection systems electromagnetic shielding is analyzed in this article. The simulated online test shows that the electromagnetic protection measures for electrified clamp online X-ray detection with UAV are workable. © Published under licence by IOP Publishing Ltd.

关键词： signal interference

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Third international conference on Computer Vision and Pattern Analysis, ICCPA 2023

Third International Conference on Computer Vision and Patter...

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3rd international conference on Computer Vision and Pattern Analysis, ICCPA 2023

ISBN: (纸本)9781510667563

The proceedings contain 140 papers. The topics discussed include: digital multi-scale visual planning model of spatial-geographical landscape pattern of smart parks;visual question answering model based on fusing global-local feature;image processing of the special sensor microwave/imager based on passive microwave remote sensing;image processing of the special sensor microwave/imager based on passive microwave remote sensing;graptolite image classification based on feature transfer and mixup data enhancement;an image classification method based on few-shot learning;fine-grained image recognition based on multi-branch and multi-scale learning;research on road extraction model of remote sensing image based on the fused convolutional module and attention mechanism;unsupervised aircraft detection in SAR images with image-level domain adaption from optical images;the role of echocardiography segmentation evaluation metrics in clinical diagnosis;and machine vision-based measurement of air compressor crankshaft journal dimensions.

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Customer Churn Prediction using Neural Networks and SMOTE-ENN for data Sampling

Customer Churn Prediction using Neural Networks and SMOTE-EN...

引用

international Symposium on Artificial Intelligence and signal processing (AISP)

作者： Shubham Gore Yuvraj Chibber Manan Bhasin Shyam Mehta S Suchitra Data Science and Business Systems SRM Institute of Science & Technology Kattankulathur Chennai India

To survive in the telecommunications industry’s severe competition and to keep existing loyal customers, predicting prospective churn consumers has become a critical task that may be accomplished with efficient predictive models. For many years, churn studies have been utilized to boost profitability and make customer-company relationships more sustainable. Customer churn is estimated using a multi-layer perceptron prediction model based on ANN. Furthermore, the suggested model manages the data’s uneven class distribution using an advanced oversampling strategy called SMOTE-ENN based on K-Nearest Neighbors. The models accuracy was compared with and without SMOTE-ENN and the model using SMOTE-ENN showed better results.

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A novel Tunnel Positioning Approach via Long Term Evolution Cellular signal 3

A novel Tunnel Positioning Approach via Long Term Evolution ...

引用

3rd international conference on Computer, Big data and Artificial Intelligence, ICCBDAI 2022

作者： Jia, Huiqiang Jia, Kebin Tian, Xiuchen Xiong, Daoquan Beijing Century East ZhiHui Technology CO-LTD Beijing102600 China Beijing University of Technology Faculty of Information Technology Beijing100020 China

Currently, Radio Frequency Identification System (RFIS), ZigBee and Ultra-Wide Band (UWB) methods are mainly used to positioning in enclosed space. But they require complex hardware layout and high hardware costs, resulting in the inability to meet the positioning needs of complex environments. Therefore, we designed a novel tunnel positioning approach via Long Term Evolution (LTE) cellular signal. This approach includes: signal acquisition, data preprocessing, feature database construction, model training and real-time positioning. In the data preprocessing stage, we adopt 3sigma and Kalman filtering to filter outliers and noise, and use information gain and information gain rate to select effective features. In the real-time positioning phase, a combination of K-Weighted Nearest Neighbor (KWNN) and Support Vector Regression (SVR) is used for positioning in the tunnel. To verify the designed approach, we did an experiment using data from the actual tunnel. The experimental results show that this approach has better positioning accuracy than FK-NN [1] and TSVR [2]. © Published under licence by IOP Publishing Ltd.

关键词： Long Term Evolution (LTE)

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Multi-View consistency-based point cloud registration method with low overlap rate 3

Multi-View consistency-based point cloud registration method...

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2023 3rd international conference on Measurement Control and Instrumentation, MCAI 2023

作者： Cui, Zhiqiang Liao, Zhaoyang Lin, Xubin Sun, Kezheng Cheng, Taobo Zhou, Xuefeng Institute of Intelligent Manufacturing Guangdong Academy of Sciences Guangdong Key Laboratory of Modern Control Technology Guangzhou China

Accurate and efficient workpiece measurement is crucial for workpiece processing and quality monitoring. Non-contact optical measurement methods have gained more attention due to their simplicity, efficiency, and flexibility compared to complicated and inefficient contact measurement methods. Multi-view registration of measurement data is a key issue in workpiece measurement, as it relies on the system's geometric accuracy and motion stability, presenting challenges such as the insufficient overlap of multi-viewpoint cloud data and cumulative error. To address these challenges, this paper proposes a multi-view planning and registration algorithm with a low overlap rate. The multi-view planning algorithm employs a greedy method to plan the scanning viewpoints of the workpiece to obtain complete point cloud data efficiently. The multi-view registration algorithm extracts features using a multi-scale geometric feature extraction network, matches the features based on the Hungarian algorithm, builds a graph, and optimizes workpiece positions based on the G2O algorithm for multi-view registration, effectively reducing cumulative error. Measurement experiments on blade workpieces confirm the feasibility of the proposed algorithms. © Published under licence by IOP Publishing Ltd.

关键词： Optical data processing

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Investigating the Big data Challenges of Deep Learning for data Science 3

Investigating the Big Data Challenges of Deep Learning for D...

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

作者： Aggarwal, Prateek Singh, Shweta Batri, Krishnan Velusudha, N.T. Kale, Sunil D. Shrimal, Gajendra Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Karnataka Bangalore 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 Computer Science & Engineering Jaipur India

ISBN: (纸本)9798350319125

Deep-gaining knowledge is a subset of synthetic intelligence (AI) that employs superior technology, data mining, and system-gaining knowledge to use massive datasets to find insights and styles. It is an area of advanced computing technology that enables computer systems to get the right of entry to analyze and analyze from many statistics. Even as the ability of deep learning is enormous, where its impact remains uncovered, extensive statistics demanding situations lie at the crossroads of its software and effectiveness. Massive records datasets' high quality and shape are essential for successfully implementing deep studying fashions. There may be an increasing need for highly acceptable statistics, including correctly categorized information, for training deep learning fashions. Moreover, deep studying often requires big datasets to provide correct output. It, therefore, calls for records to be amassed from numerous assets, posing the need for more homogeneous, regular, and standardized information. Adequate statistics garage, processing, and analytic solutions must be followed to analyze massive facts to create reachable and usable datasets for successful deep mastering packages. It includes infrastructure capable of securely keeping a large amount of information, in addition to the cloud-based totally systems to efficiently method extensive quantities of statistics. There has been a shift in the direction of using 'large records' technologies like Apache Hadoop, Apache Spark, and different associated libraries. Even as deep mastering holds massive capability for uncovering new insights and turning in gigantic value to fields which include healthcare, finance, enterprise control, and more incredible, the associated massive data demanding situations ought to be addressed for those programs to reach their full capability. Despite the present-day challenges, advances in extensive records solutions like Apache Hadoop and Apache Spark, coupled with advanced analytic

关键词： challenges efficiently homogeneous management overcoming

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The Numbers’ Sign Language Detection Based on Deep Learning 3

The Numbers’ Sign Language Detection Based on Deep Learning

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3rd international conference on signal Image processing and Communication, ICSIPC 2023

作者： Lian, Li Sheng, Tang School of Big Data and Artificial Intelligence Anhui Xinhua University Hefei China College of Computing and Information Technologies Philippines National University Manila Philippines

ISBN: (纸本)9781510670945

This paper builds an end-to-end custom object detection model that could translate Chinese numbers’ sign language in real time based on deep leaning. The main work of this paper is as follows, collect images for deep learning using OpenCV, label images for sign language detection using LabelImg, setup Tensorflow Object Detection pipeline configuration, and use transfer learning to train a deep learning model. At last, detect sign language in real time using OpenCV. © 2023 SPIE.

关键词： Object detection

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