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Analysis and prediction of the impact of tunnel underpassing railroad based on ABAQUS 2

Analysis and prediction of the impact of tunnel underpassing...

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2nd international conference on Computer science, Electronic Information engineering and Intelligent Control Technology, CEI 2022

作者： Guo, Renliang Zhang, Yongjuan Qi, Rui College of Civil Engineering and Architecture Shandong University of Science and Technology China

ISBN: (数字)9781665476164

ISBN: (纸本)9781665476164

Based on the background of Qingdao subway tunnel underpassing the railway, the calculation model was established by ABAQUS computer simulation software to study the influence of tunnel construction and train disturbance on railway subgrade. Through ABAQUS and its DLOAD subroutine and Visual Studio programming, different train running speeds were realized, and the variation law of subgrade acceleration was obtained. BP neural network model was used to predict the peak acceleration of subgrade. The results show that with the increase of the speed of the vehicle, the peak acceleration of the subgrade increases continuously, showing a double hump distribution;the vibration acceleration generated by train operation has obvious influence on railway subgrade. BP neural network can accurately predict the peak acceleration of subgrade under the combined action of tunnel construction and train operation. © 2022 IEEE.

关键词： ABAQUS

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The Development of Machine Learning innovation technology for Data Mining In Smart Healthcare 2

The Development of Machine Learning innovation technology fo...

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2nd IEEE international conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Manikandan, V. Sharma, Sonal Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350347456

The field of Smart Healthcare has undergone a revolution due to the development of machine learning technologies. artificial intelligence (AI) has a subfield called machine learning that allows computers to learn from data and develop over time without explicit programming. Healthcare workers can now discover trends, diagnose diseases, and make decisions based on more precise and timely data thanks to machine learning's capacity to comprehend and analyze enormous amounts of data. Finding patterns and links in massive datasets is known as data mining. Data mining is used in Smart Healthcare to locate patterns in patient data that can be utilized to comprehend a patient's health status better, diagnose specific disorders, and forecast the most effective course of therapy. Data mining can create novel cures and treatments customized to a person's genetic profile. Data mining in Smart Healthcare is now considerably more effective and efficient, thanks to machine learning. Using complex algorithms, machine learning models can analyze vast amounts of data markedly faster and more correctly than conventional methods. Healthcare experts may not immediately notice hidden patterns and connections in data that machine learning algorithms can find. As a result, machine learning can assist healthcare practitioners in making decisions that are better informed, improving patient outcomes. © 2023 IEEE.

关键词： Diagnosis

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Application of LSTM in Quantitative Trading with Big Data 2

Application of LSTM in Quantitative Trading with Big Data

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2nd international conference on Big Data, Information and Computer Network, BDICN 2023

作者： Wang, Jieyi Hu, Yixuan Zhao, Yelin School of Computer Engineering and Science Shanghai University NO.99 Shangda Road Shanghai China College of Sciences Shanghai University NO.99 Shangda Road Shanghai city China

ISBN: (纸本)9798350321364

Recently, the global market returns are characterized by year-long episodes of high volatility, leading market traders to struggle to maximize their total return with high-frequency trading. However, in the meantime, some classical financial characteristics have striking similarities. Therefore, an increasing amount of investors are dedicated to finding and making the most of reasonable models with computer science and machine learning, in quest of a general pattern. Accordingly, we developed a comprehensive model to help some traders with optimal transaction decisions. Given that the portfolio of cash, bitcoin and gold is gradually becoming a new choice for high returns, we chose these assets as examples to build a model to forecast the closing prices of bitcoin and gold for the next trading day based on their past stream up to today with LSTM (LongShort Term Memory) Neural Network Model. To achieve the maximum return, we used the Mean-variance Model to set the investment ratio of bitcoin and gold as variables for mathematical programming and solved the multivariate equations to find the optimal portfolio. The investment weights for each trade were obtained by comparing the lowest risk portfolio and the optimal return portfolio, i.e., the minimum variance and maximum Sharpe ratio scenarios. Finally, we evaluated our strategy through quantitative strategy indices and proved its outstanding performance. © 2023 IEEE.

关键词： Big data

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The Impact of Tamil Python programming in Wikisource 2nd

The Impact of Tamil Python Programming in Wikisource

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2nd international conference on Speech and Language Technologies for Low-Resource Languages, SPELLL 2023

作者： Vinoth, A. Thangasamy, Sathiyaraj Nithya, R. Subalalitha, C.N. Mahendhiran, P.D. Info-Farmer Sri Krishna Adithya College of Arts and Sciences Coimbatore641042 India Avinashi641654 India SRM College of Engineering and Technology Kattankulathur Chennai India Sri Krishna College of Engineering and Technology Coimbatore641042 India Tamil Wikimedian Attur Salem636102 India

ISBN: (纸本)9783031584947

Wikipedia, Wiktionary, Wikisource, Wikinews, Wikiquote, Wikiversity, Wikitour, Meta-Wiki, and Wikimedia are all Wikimedia projects that provide copyright-free data. Among these, Wikisource stands out as an online library utilized by 72 languages. Tamil Wikisource specifically caters to Tamil-language content, converting image-based data into text format. While human resources and automated methods contribute to data improvement, this research paper proposes the implementation of a Python program in Tamil for automation to further enhance or operate the Tamil Wikisource project. Given that most volunteers working on Wikimedia projects in Indian languages may be more comfortable with their native language rather than English, this paper highlights the efforts made by Info Farmer in writing Python programs for Wikisource. This initiative is expected to open up more possibilities for scaling similar projects in other Indian languages, thereby assisting volunteers in Wikimedia projects. Additionally, the individual has developed over a hundred Python programs in Tamil, enhancing more than two lakh pages. This underscores a potential lack of awareness regarding the capability to create computer programming content in native languages, a phenomenon not exclusive to Tamil but applicable to other Indian languages as well. The primary aim of this article is to emphasize that when volunteers from various Indian languages recognize this potential, they can develop the necessary automation tools for their respective languages. Consequently, this research paper delves into topics such as wiki projects, the voluntary contributions of individuals involved, the noteworthy Tamil Python contributions of Info-farmer—a Tamil Wikimedian—the use of Python keywords written and executed in Tamil, an exploration of how Python functions, an overview of PAWS (Python Data science environment for Jupyter notebooks), PyWikiBot, and outlines plans for future activities in detail. © The Author(s),

关键词： Python

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A Smart Emergency Platform for Earthquake Disasters Based on Multisource Monitoring Data - A Case Study of Lanzhou City 2

A Smart Emergency Platform for Earthquake Disasters Based on...

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2023 2nd international conference on Environmental Remote Sensing and Geographic Information Technology, ERSGIT 2023

作者： Du, Jinchen Li, Wei Xie, Xukang School of Geomatics Lanzhou Jiaotong University Gansu Lanzhou China National and Local Joint Engineering Research Center of National Geographic State Monitoring Gansu Lanzhou China Gansu Provincial Geographic Condition Monitoring Engineering Laboratory Gansu Lanzhou China

ISBN: (纸本)9781510672949

Earthquakes are one of the natural disasters with the greatest threat to human life, and since earthquake forecasting is not accurate, one of the important tasks of post-earthquake emergency response is to assess the earthquake damage in time and guide the decision-making of emergency rescue and relief materials distribution. The 3D seismic information sharing platform provided by Cesium indeed provides an effective application for 3D visualization of seismic information in the existing network. In this paper, Vue and Cesium jointly build the front end of the platform, Java programming language, and Spring Boot framework to build the back end, using MySQL as the database and MyBatis-plus ORM framework to achieve data persistence. At the same time, Redis is used to store cached data to improve read and write speed and performance. The platform can capture real-time earthquake information and perform intensity estimation based on elliptic attenuation model equations after the earthquake, use empirical models to assess economic losses and casualties, and obtain the Gaode API for route planning to rescue points. The platform not only helps the government to carry out post-earthquake activities but also allows the public to understand the effects of earthquakes more clearly. © 2024 SPIE.

关键词： Decision making

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2nd international conference on Speech and Language Technologies for Low-Resource Languages, SPELLL 2023

2nd International Conference on Speech and Language Technolo...

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2nd international conference on Speech and Language Technologies for Low-Resource Languages, SPELLL 2023

ISBN: (纸本)9783031584947

The proceedings contain 33 papers. The special focus in this conference is on Speech and Language Technologies for Low-resource Languages. The topics include: SamPar: A Marathi Hate Speech Dataset for Homophobia, Transphobia;l3Cube-MahaNews: News-Based Short Text and Long Document Classification Datasets in Marathi;creation and Classification of Kannada Meme Dataset: Exploring Domain and Troll Categories;the Impact of Tamil Python programming in Wikisource;natural Language Processing for Tulu: Challenges, Review and Future Scope;depBoost-TransNet: Boosted Transformer Network for Depression Classification;Optimized BERT Model for Question Answering System on Mobile Platform;A Comparative Analysis of Pretrained Models for Sentiment Analysis on Restaurant Customer Reviews (CAPM-SARCR);lightweight Language Agnostic Data Sanitization Pipeline for Dealing with Homoglyphs in Code-Mixed Languages;textGram: Towards a Better Domain-Adaptive Pretraining;abusive Social Media Comments Detection for Tamil and Telugu;sales Forecasting from Group Conversation Using Natural Language Processing;hands in Harmony: Empowering Communication Through Translation;offensive Text Detection for Tamil Language;Telugu-English Abusive Comment Detection Using XLMRoBERTa and mBERT;a Knowledge engineering Framework Addressing High Incidence of Farmer Suicides;event Categorization from News articles Using Machine Learning Techniques;from Words to Emotions: Identifying Depression Through Social Media Insights;text Summarisation for Low-Resourced Languages, A Review;multi Speaker Activity Detection Using Spectral Centroids;spoken Language Identification System Using Convolutional Neural Networks;exploring the Role of Entropy in Music Classification;spectral Features Based Spoken Dialect Identification for Punjabi Language;hate Speech Detection Using Audio in Portuguese Language;an Empirical Analysis of the Consonantal Phonemic Patterns and Characteristics of English Spoken in India;Multilingual Fake Ne

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Pig-Based Study of Crime Rates in Several Indian States 2

Pig-Based Study of Crime Rates in Several Indian States

引用

2nd IEEE international conference on Disruptive Technologies for Multi-Disciplinary Research and Applications, CENTCON 2022

作者： Mittal, Tanusha Christa, Sharon Graphic Era Deemed to Be University Computer Science and Engineering Dehradun India

ISBN: (纸本)9781665463744

Big data is made up of a wide variety of data thatarrives quickly and in increasing volumes. The size of the data sets makes it impossible for conventional data processing algorithms to manage them. Big data solutions have become more popular as a result of Hadoop's high scalability, availability, and cluster environment mechanism, which enablesworking in a distributed manner. MapReduce, one of the majorcomponents of Hadoop, can handle unstructured data but demands significant programming skills. Because Apache Pig allows us to analyse data by simply running queries, customers are increasingly turning to this tool owing to high programming skill requirements. In this paper, we analyse the crime rates of India of different states from year 2001 to 2015. The crimes are categorized into 6 different categories i.e., Murder, Rape, Kidnapping, Foeticide, suicide and exposure. The motive of this paper is to analyse the pattern of crime in different states of India. © 2022 IEEE.

关键词： MapReduce

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Text Steganography in Images Using Turbo Code-Walsh Code Transforms 2

Text Steganography in Images Using Turbo Code-Walsh Code Tra...

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2nd international conference on Advances in engineering science and Technology, AEST 2022

作者： Jabbar, Rafal Fadhil Qasim Jumah Al-Thahab, Osama University of Babylon College of Engineering Babil Iraq

ISBN: (纸本)9798350334906

Numerous methods, such as integration between steganography and cryptography, have been suggested to protect the privacy of information exchanged. Steganography systems have come to be recognized as a crucial method for enhancing information security by using multimedia to cover up sensitive information which includes information that is invisible to the human eye. In this paper, text was concealed within a digital image using Turbo code and Walsh-code algorithm, in order to result an electronic lung x-ray containing the diagnosis of the condition embedded inside the image. The algorithm was implemented using the MATLAB programming language. The new way is exposed to multi-image noise like Gaussian, slot and paper noise, and it is found that the proposed algorithm has PSNR, BER, RMS, MSE results for Gaussian equal to 84.871, 0.0003, 0.0525, and 0.0027 respectively. These results are considered very suitable as compared to no attack. © 2022 IEEE.

关键词： Steganography

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Direct Differentiation Sensitivity Analysis Based on Reduced Multibody System Transfer Matrix Method 2nd

Direct Differentiation Sensitivity Analysis Based on Reduced...

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2nd international conference of Mechanical System Dynamics, ICMSD 2023

作者： Wang, Guoping Tu, Tianxiong Miao, Yunfei Rui, Xiaoting Institute of Launch Dynamics Nanjing University of Science and Technology Nanjing China National Key Laboratory of Complex Multibody System Dynamics Nanjing University of Science and Technology Nanjing China Chongqing Hongyu Precision Industry Group Co. Ltd. Chongqing China College of Mechanical & Electrical Engineering Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9789819980475

Dynamics analysis has always been an important foundation for improving the dynamics performance of mechanical systems. The effectiveness and efficiency of multibody system dynamics (MSD) analysis method depend on the modelling method of multibody system dynamics. In this paper, a new direct differential sensitivity analysis method for MSD based on RMSTMM and direct differential method is proposed. Combining sensitivity analysis theory and direct differential formulas, the differential form of recurrence relationship of the element is derived, and the solution flow is given. This method has the advantages of no requiring the global dynamics equations of the system and high programming. The numerical examples are carried out to verify the correctness and effectiveness of the proposed method. Compared with the DMM and AVM based on the Lagrange method, the results show that this method has low matrix order, fast computational speed, and higher analysis efficiency. Compared with the DDM based on the NV-MSTMM, the proposed method is more stable for a large system, which provides a new means for rapid analysis of multibody system dynamics. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Sensitivity analysis

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Experimental Design and Maintenance, Towards a Decision-Making Approach Driven by Degradation Models, with Application to Lithium-Ion Batteries 2

Experimental Design and Maintenance, Towards a Decision-Maki...

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2nd Edition IEEE international conference on Metrology for eXtended Reality, artificial Intelligence and Neural engineering, MetroXRAINE 2023

作者： Pievatolo, Antonio Magrini, Alessandro Meccariello, Giovanni Cristaldi, Loredana Patrizi, Gabriele Nikiforova, Nedka D. Institute for Applied Mathematics and Information Technologies 'E. Magenes' National Research Council Milan Italy University of Florence Department of Statistics Computer Science Applications 'G. Parenti' Florence Italy Institute of Sciences and Technologies for Energy and Sustainable Mobility National Research Council Naples Italy Polytechnic of Milan Department of Electronics Information and Bioengineering Milan Italy University of Florence Department of Information Engineering Florence Italy

ISBN: (纸本)9798350300802

We discuss an innovative decision-making frame-work for accelerated degradation tests and predictive maintenance, when information about the state of the system, represented by prior knowledge and experimental data, is encapsulated in a degradation model. We consider dynamic programming and reinforcement learning as the framework for sequential decision making in these areas, also including the degradation model learning when necessary. The application of these methods to the design of life testing experiments and to the maintenance of lithium-ion batteries is proposed. © 2023 IEEE.

关键词： accelerated degradation tests degradation modeling predictive maintenance reinforcement learning remaining useful life

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