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检索条件"任意字段=3rd International Conference on Computing and Data Science, CONF-CDS 2021"

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3rd international conference on computing and data science, conf-cds 2021

3rd International Conference on Computing and Data Science, ...

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3rd international conference on computing and data science, conf-cds 2021

ISBN: (纸本)9789811688843

The proceedings contain 31 papers. The special focus in this conference is on computing and data science. The topics include: Application of Graphical Convolutional Networks to the Safety Assessment of Container Ship Voyages;evaluation of Quantization Techniques for Deep Neural Networks;multi-channel Relation Modeling for Session-Based Recommendation with Self-supervised Learning;Polyp Segmentation Using Fully Convolutional Neural Network with Dropout and CBAM;Evaluation of the Effectiveness of COVID-19 Prevention and Control Based on Modified SEIR Model;finite Difference Method for Convection-Diffusion Equation;A Review of Bayesian Posterior Distribution Based on MCMC Methods;roboTutor: Predictions of Students’ Answer Type;PM2.5 Density Prediction Based on a Two-Stage Rolling Forecast Model Using LightGBM;stock Market Movement Prediction: A Comparative Study Between Machine Learning and Deep Time Series Models;a Spatial-Temporal Adaptive Video Denoising Algorithm;you Are What You Eat: Predictive Model of Eating Habits and Health Outcomes;using Co-evolution of Artefacts in Git Repository to Establish Test-to-Code Traceability Links on Method-Level;convergence Media Related Information Production Platform Based on Kalman Filter Video Target Tracking;Supervised Sliding Window Smoothing Loss Function Based on MS-TCN for Video Segmentation;statistics and Machine Learning for Behavioral Prediction of Operational Transconductance Amplifiers with Focus on Regression Analysis;comparative Study of Loss Function Based on Neural Network;Research on the Prediction of Logistics Demand for Emergencies Based on BP Neural Network;research on Twitter data Crawling and data Visualization Analysis Based on Python;the Survey of Joint Entity and Relation Extraction;occluded Face Recognition with Deep Learning.

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2nd international conference on computing and data science, conf-cds 2021 - Number 3

2nd International Conference on Computing and Data Science, ...

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2nd international conference on computing and data science, conf-cds 2021

The proceedings contain 298 papers. The topics discussed include: effect monitoring of physical education curriculum based on wearable sensor in intelligent environment;the application and optimization of phase method in laser distance measurement;design of an intelligent fiber Bragg grating temperature measurement system for electrical equipment;study on impact properties of new composite metal porous materials based on data analysis;relationship between the line structured light vision calibration accuracy and hardware parameters;estimation of the price range of power grid technological transformation based on Walsh average;application of RFID information technology in fresh food cold chain logistics management;pollution-free cultivation techniques of leafy vegetables under the background of information technology;design and realization of modern smart home system based on multimedia network technology;optimal analysis of transmission lines using ant colony-improved matter-element extension method;analysis and research of city contactless distribution based on big data background;application of information security in image encryption processing based on big data;and application research on the integration of civil engineering and computer-aided building system based on the development of BIM.

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A Study on Interpolation of Missing Values in Multivariate Sand and Dust data Considering Timeseries Features 3

A Study on Interpolation of Missing Values in Multivariate S...

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3rd international conference on Artificial Intelligence, Internet of Things and Cloud computing Technology, AIoTC 2024

作者： Wang, Yongsheng Tan, Shiyi Wang, Gang Liu, Guangwen Liu, Chunlei School of Data Science and Application Inner Mongolia University of Technology Hohhot010080 China

ISBN: (纸本)9798331530280

The production and survival of humans are threatened by sand and dust storms;yet, the research of sand and dust storms is always beset by the issue of partially absent data. In order to address the missing data issue, we presented the sand-dust data interpolation technique (SDIM) in this study. While maintaining the overall structure of the Transformer model, our model employs an automatic coding and decoding technique for improved interpolation of sand and dust data, along with a timelag decay strategy along with positional coding and masking matrices. The associated results analysis reveals that the three evaluation indexes of mean absolute error, mean absolute percentage error, and root mean square error are the lowest when compared to the interpolation performance of conventional data interpolation methods like mean interpolation. © 2024 IEEE.

关键词： Interpolation

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A Systematic Study About Chronic Disease Prediction Strategies using Artificial Intelligence based Algorithms 3

A Systematic Study About Chronic Disease Prediction Strategi...

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3rd international conference on Automation, computing and Renewable Systems, ICACRS 2024

作者： Priya, P. Kavya, S. Department of Computer Science and Engineering M.Kumarasamy College of Engineering Karur India

ISBN: (纸本)9798331532420

The challenge of chronic diseases will take its deserved place among the top global health issues, mainly because they account for 74% of deaths every year, as reported by the WHO. This systematic review will discuss possible applications of machine learning and AI techniques to predict, diagnose, and treat cds such as diabetes, cancer, cardiovascular diseases, and liver disease. Integration of ML algorithms: RF, SVM, DT, ANN, and boosting techniques has transformed healthcare by improving the quality of predictive information for potential cases, reducing healthcare costs, and contributing to innovative clinical decision support systems. The research focuses on several approaches of ML, namely supervised and unsupervised learning, for predicting patient-specific treatment regimens and hence better outcomes in chronic disease management. Another discussion from the study is on how to apply ML on large, structured and unstructured datasets collected from the healthcare system about the predictive powers of AI-based models in order to be able to address complications arising from CD. Research aims at providing a comprehensive overview of the understanding of predictive models (PMs) under one heading, making an amalgamation of the desired workings of PMs for chronic disease prediction, useful for knowledge collection for future reference. The paper also provides a descriptive analysis of data sources, methodologies, and algorithms adopted, accompanied by a tabular representation of previous studies to avoid redundancy and enhance accuracy. © 2024 IEEE.

关键词： Prediction models

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Student Management Information Platform based on Clustering Algorithm 3

Student Management Information Platform based on Clustering ...

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3rd IEEE international conference on Distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Zhao, Huijun Changchun Humanities And Science College Changchun China

ISBN: (纸本)9798350318609

In today's world, the rapid progress of knowledge economy makes education the key asset that determines the level of economic and social development of a country. This situation has received a lot of attention from all the people concerned with student management. Research on the self-management style of college and university students can improve students' ability to self-direct their learning and self-consciously conduct and serve their own education. Nevertheless, the flaw in the building of this model of college administration needs to be analyzed. To overcome these issues, the platform of student management information is proposed by utilizing clustering based data mining. Experimentation in the student growth rate is plotted, which shows an increase from 10% to 33% in the year 2019 and 21% in the year 2020 through 35% in the year 2021. The rise of the economy is the indication itself of the number of people that have access to higher education has increased in a few years. © 2024 IEEE.

关键词： Students

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Study on Location of Fresh Product Cold Chain Logistics Distribution Center Based on Adaptive Genetic Algorithm 3

Study on Location of Fresh Product Cold Chain Logistics Dist...

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3rd international conference on data Analytics, computing and Artificial Intelligence, ICDACAI 2024

作者： You, Jianglong Wei, Ziqiu Hebei University of Science and Technology Handan China

ISBN: (纸本)9798331519032

Fresh cold chain logistics hold a crucial position in modern supply chain management, ensuring the quality and freshness of fresh products from production bases to consumers is a complex and important task. With the increasing demand for fresh products, reducing costs and minimizing losses during the logistics process has become a major challenge for businesses. To address this issue, this paper focuses on the transportation of fresh products, considering three factors: fixed costs, transportation costs, and spoilage costs. We establish an objective function that minimizes total costs, incorporating multiple coefficients to better align with actual conditions. On this basis, we develop a location model for cold chain logistics distribution centers and utilize an adaptive genetic algorithm for optimization analysis. Simulations and solutions conducted using MATLAB 2021a software verify the effectiveness and practicality of the model and algorithm in the study of location problems. © 2024 IEEE.

关键词： MATLAB

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Bitcoin price prediction based on financial data, technical indicators, and news headlines sentiment analysis using CNN and GRU deep learning algorithms 3

Bitcoin price prediction based on financial data, technical ...

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3rd international conference on Distributed computing and High Performance computing, DCHPC 2024

作者： Arjmand, Masoud Kazeminia, Saman Sajedi, Hedieh University of Tehran Kish International Campus Department of Computer Engineering Kish Iran NHL Stenden University of Applied Science Department of Computer Vision and Data Science Leeuwarden Netherlands University of Tehran Department of Mathematics Statistics and Computer Science Tehran Iran

ISBN: (纸本)9798350381580

Bitcoin is the leading cryptocurrency with the highest market value among digital currencies. Therefore, predicting the value of Bitcoin can help to understand the entire cryptocurrency market. However, Bitcoin has had a lot of price fluctuations since its inception. In this paper, we are going to forecast the price of Bitcoin using news headline analysis, technical analysis indicators, and historical financial data. The news headlines used in this article are scraped from the Cointelegraph news website, which contains 3988 news headlines related to Bitcoin between 2/7/2020 and 3/8/2021. A transformer pre-trained model on cryptocurrency-related texts called CryptoBERT, which is a BERT-based sentiment analysis model, has been used to analyze the textual data. Also, a novel hybrid 2DCNN-GRU deep learning model has been used to predict the price. To adjust the parameters of this model, a parameter tuning method based on orthogonal arrays called the Taguchi method has been employed. Finally, to examine the proposed model's efficiency, the obtained results have been compared with other deep learning models from the literature review that used text data to predict bitcoin prices. The results show that this model outperformed other models in terms of MAE criterion, while in the other three criteria, namely MSE, RMSE and MAPE, it still demonstrated good results. © 2024 IEEE.

关键词： Forecasting

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data Agent-Based Volumetric Progress Monitoring over Mobile Ad-Hoc Network in Disaster Management 3rd

Data Agent-Based Volumetric Progress Monitoring over Mobile ...

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3rd international conference on Advanced Network Technologies and Intelligent computing (ANTIC)

作者： Tiwari, Pranjal Pattanaik, K. K. Nain, Garima ABV IIITM Dept Informat Technol Gwalior India

ISBN: (纸本)9783031640636;9783031640643

Post disaster rescue operations are usually undertaken in a severely constrained communication environment, often leading to difficulties in coordination among various machineries. This work proposes an autonomous data agent-based automation of post disaster progress monitoring of volumetric activities over Mobile Ad-hoc NETwork (MANET) by leveraging WiFi Direct communication functionalities. This approach enables efficient and reliable communication among rescue teams, facilitating coordination and information exchange in challenging post disaster scenarios. The proposed work enables a Light Detection and Ranging (LIDAR)-based volumetric analysis with minimal computing overhead. A mobile application for Android 11 demonstrated the practical applicability of the proposed system.

关键词： Post disaster management data Agent LIDAR WiFi Direct and Legacy WiFi Wireless sensor network

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Research on Rehabilitation Assessment Methods for Patients After Rotator Cuff Surgery Based on Attitude Sensors and XGBoost Algorithm 3

Research on Rehabilitation Assessment Methods for Patients A...

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

作者： Xu, Kang Feng, Hao He, Gang Li, Minghui College of Computer Science and Technology Southwest University of Science and Technology Mianyang China Southwest University of Science and Technology Sichuan Electronic and Mechanic Vocational College Mianyang China

ISBN: (纸本)9798331528386

The rotator cuff, as a complex and flexible key part of the human musculoskeletal system, necessitates frequent and precise evaluations during its rehabilitation process after injury. However, traditional evaluation methods heavily rely on doctors' subjective judgments, which not only leads to inconsistent evaluation standards but also increases the number of patient visits to the hospital due to the long evaluation cycles, causing much inconvenience. To address this issue, this paper introduces wearable posture sensor technology. By collecting patients' real-time posture data and combining it with the XGBoost algorithm model, the rehabilitation progress of patients can be objectively and efficiently evaluated. Experimental results have demonstrated that this method performs excellently in assessing the rehabilitation status of patients with rotator cuff injuries, exhibiting good application prospects and practical value. © 2024 IEEE.

关键词： Musculoskeletal system

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Depth Feature Matching Based Coherence Registration of 3D Biological Images 3

Depth Feature Matching Based Coherence Registration of 3D Bi...

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3rd international conference on Image Processing and Media computing (ICIPMC)

作者： Li, Yuanyuan Huang, Haimeng Wu, Jun Qu, Lei Liu, Chao Tian, Chong Yang, Bo Han, Tingting Anhui Univ Informat Mat & Intelligent Sensing Lab Anhui Prov Hefei Peoples R China Elect Technol Grp Corp Res Inst China 38 Hefei Peoples R China Southeast Univ SEU ALLEN Joint Ctr Inst Brain & Intelligence Nanjing Peoples R China

ISBN: (纸本)9798350386660;9798350386677

Establishing dense anatomical correspondences across different imaging modalities is a fundamental yet challenging task in many medical image analysis studies. Existing multimodal registration algorithms depend on optimal transformation estimation based on feature point matching or deformation prediction based on depth learning. However, the former fails to capture the deeper semantic information of images effectively, while the latter tends to lose critical detail features when registering high-resolution images. In this paper, we propose a three-dimensional coherent registration method for biological images (DFMCR), based on deep feature matching. Leveraging deep neural networks trained on large-scale data, we learn a multimodal feature representation and similarity metric. Through feature point matching, we significantly reduce the computational burden, enabling registration of images at resolutions of 25um and higher.

关键词： Cross-mode registration Biomedical imaging Deep feature matching Similarity measure

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