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An Improved Adaptive Filtering Algorithm for ECG Signals 7

An Improved Adaptive Filtering Algorithm for ECG Signals

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7th international conference on computer and Communication Systems, ICCCS 2022

作者： Wu, Youyu Xie, YiXiao Ge, Hua WuHan University of Technology School of Information Engineering WuHan China

ISBN: (数字)9781665450607

ISBN: (纸本)9781665450607

In order to filter out the noise interference in the electrocardiogram (ECG) signal, especially the noise interference of motion artifact (MA), the step factor is improved on the basis of the normalized least mean square (NLMS) algorithm, and an improved NLMS (PNLMS) algorithm is proposed. To speed up the convergence speed of the adaptive algorithm, so as to ensure that the amount of offset near the optimal weight coefficient is minimized, and the steady-state accuracy of the algorithm is improved. Experimental results show that the algorithm can obtain a clear and undistorted original ECG signal after the process of improved algorithm and has a good filtering effect. © 2022 IEEE.

关键词： Adaptive filters

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Sentiment Analysis Approaches, Types, Challenges, and Applications: An Exploratory Analysis 7

Sentiment Analysis Approaches, Types, Challenges, and Applic...

引用

7th international conference on Parallel, Distributed and Grid Computing, PDGC 2022

作者： Devi, Vandana Sharma, Avinash Mmdu Computer Science and Engineering Mullana Ambala India

ISBN: (纸本)9781665454018

Even though sociolinguistic and psycholinguistic studies demonstrate that the qualities of the speaker and the intended audience have an impact on the message that is transmitted, the majority of NLP models used today assume language as universal. the difficulty of sentiment analysis, often known as opinion mining, in natural language processing (NLP) is one that is currently being faced. It's also challenging for people to share their ideas on websites like Facebook, Twitter, and Yelp since innovation has grown dramatically. Social media's widespread use has resulted in a huge volume of data generation, including evaluations, comments, and opinions. Researchers claim that the phrase, document, aspect, and user levels are the foundations for sentiment analysis. this data requires more time to analyse and is challenging to process. In order to categorize or determine positive, negative, and neutral opinions, an intelligent system must be developed. © 2022 IEEE.

关键词： Sentiment analysis

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Research and application of gated recursive graph convolutional network in meteorological evapotranspiration data fusion processing 7

Research and application of gated recursive graph convolutio...

引用

7th international conference on computer information Science and Application technology, CISAT 2024

作者： Liu, Chang Zhang, Xiaodan Zhao, Tong You, Shaojie Huo, Wei Zhang, Qiyuan Hu, Naihao Qinghai University Xining810016 China Qinghai Provincial Laboratory for Intelligent Computing and Application Xining810016 China Qinghai Provincial Institute of Meteorological Sciences Xining China

ISBN: (纸本)9798350375107

Hydrological resource management relies on reliable estimation of evapotranspiration (ET). Aiming at the problems of large errors and insufficient spatial feature extraction in the data generated by the existing ET fusion algorithm in Qinghai Province, the study takes Qinghai Province as the research area and proposes a gated recursive graph convolution network (GCN_GRU) model that combines gated recursive unit (GRU) and graph convolution network (GCN) to simulate daily ET estimates. and evaluate the accuracy of the model fusion. the GCN_GRU deep learning model is trained and optimized based on the site ET ERA5_Land and GLEAM reanalysis data, MOD16A2, MOD11A1 multi-source data generated by Penman formula from 50 national stations in the study area, the paper aims to develop a set of multi-source ET data fusion models suitable for the regional characteristics of Qinghai Province, and evaluate the accuracy of the model fusion to derive a regional ET data set with higher spatiotemporal accuracy and longer time series. In the study, random forest (RF), support vector machine (SVM), convolutional neural network (CNN), long short-term memory network (LSTM), graph convolution network (GCN), gated recursive unit (GRU), spatiotemporal Network (CNN_LSTM) and other methods as control experiments, the fusion model was evaluated and analyzed through three evaluation indicators: RMSE, MAE, CC, and RB, the results show: Among the three types of original ET data: ERA5_Land, GLEAM, and MOD16A2, ERA5_Land has the lowest root mean square error (RMSE =1.82) and mean absolute error (MAE=1.39) between station evaporation. the root mean square errors of the three machine learning control experiments are all at 0.61 ∼ 1.13 mm · d-1, the root mean square error between the GCN_GRU fusion model simulation results and the national site data(RMSE =0.60), mean absolute error(MAE=0.43), correlation coefficient (CC=0.90), relative error (RB=0.053)are better than the original data and the test resu

关键词： Mean square error

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Development of Database System Prototype to support Provision of Education for Students with Disabilities 7

Development of Database System Prototype to support Provisio...

引用

7th international conference on Digital Arts, Media and technology, DAMT 2022 and 5th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications Engineering, NCON 2022

作者： Bulao, Suwanna Prongsantia, Siriluck Payakkapong, Chatdanai Tawkaew, Premwit Nakhon Ratchasima Rajabhat University Faculty of Education Nakhon Ratchasima Thailand Nakhon Ratchasima Rajabhat University Computer Center Nakhon Ratchasima Thailand Nakhon Ratchasima Rajabhat University Faculty of Humanities and Social Sciences Nakhon Ratchasima Thailand

ISBN: (纸本)9781665495103

this research aims to develop and evaluate the prototype of database system to support provision of education for students with disabilities. this development outcome will be used as a tool for information management of students with disabilities that will be useful in planning to improve the quality of life of students with disabilities in educational institutions in Mueang Nakhon Ratchasima District, Nakhon Ratchasima Province, thailand. the prototype was developed by PHP language and MySQL database and the principle of Systems Development Life Cycle was applied with 5 phases, namely project planning, analysis, design, implementation, and maintenance. Five information system development experts evaluated the performance of the prototype which was in general at a high level (\bar{x}=4.38, \mathrm{S}.\mathrm{D}.=0.74), and 63 personnel in the educational institutions evaluated satisfaction towards the prototype which was in general at a high level (\bar{x}=4.33, \mathrm{S}.\mathrm{D}. =0.60). © 2022 IEEE.

关键词： Students

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Research on garment image classification and detection algorithm based on improved deep learning 7

Research on garment image classification and detection algor...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Ren, Fei Liu, Ye Gao, Pengfei Devaraj, Madhavi Zhang, Jiahui Li, Hongsheng Mapua University School of Information Technology Manila Philippines Nanjing Institute of Technology School of Automation Nanjing China

ISBN: (纸本)9781665478571

With the development of e-commerce economy, online shopping has become an indispensable part of people's life. therefore, the study of clothing image classification is of great significance to realize the effective operation of online clothing change and clothing recommendation system. this paper uses two classical deep learning algorithms: LeNet and ResNet to construct the clothing image classification model and realize the classification and detection of. At the same time, on the basis of Yolov5, combined with ResNet to improve its backbone network and further improve the accuracy of clothing image classification and detection. Experiments show that on the FashionMnist dataset, the accuracy and precision of LeNet and ResNet are about 93%, the accuracy and precision of improved Yolov5 are more than 98%, which is much higher than the former. © 2022 IEEE.

关键词： Electronic commerce

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Distributed HBase Cluster Storage Engine and Database Performance Optimization 23

Distributed HBase Cluster Storage Engine and Database Perfor...

引用

23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Zhang, Hao Rong-Li, G.A.I. School of Information Engineering Dalian University Dalian China

ISBN: (纸本)9781665494571

With the development of network society, individuals and enterprises generate massive data every day. However, the traditional relational MySQL database has poor performance in storing and processing massive data. In the case of huge amount of data, MySQL may even crash, which obviously cannot meet the needs of massive data storage. Obviously, with more and more emphasis on user-friendliness, the storage and processing application of massive data determine the future development of enterprises. this paper discusses the storage engine, high concurrency, architecture and distributed cluster of HBase, and then compares the performance differences between MySQL and HBase optimized with Bloom filter(Bloom HBase) on Linux platform. © 2021 IEEE.

关键词： Concurrent computing Smart cities Linux Distributed databases Memory Big Data computer crashes

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Review of Researches on the Emotion Recognition and Affective Computing Based on HCI 7

Review of Researches on the Emotion Recognition and Affectiv...

引用

7th international conference on Image, Vision and Computing, ICIVC 2022

作者： Lin, Wenqian Zhang, Yunjian Hangzhou Dianzi University School of Media and Design Hangzhou China Zhejiang University College of Control Science and Technology Hangzhou China

ISBN: (数字)9781665467346

ISBN: (纸本)9781665467346

Human-computer interaction (HCI) is the third revolution of information technology after cloud computing and big data. In the design of HCI, it usually involves physical level, cognitive level and emotional level, while emotion recognition and affective computing (ERAC) are the main contents of emotional level. In this paper, the concept and function of ERAC are described;the progress of research on ERAC from facial expression, voice, text, physiological signal and other aspects are analyzed;the application of ERAC in the computer science, health care, media entertainment, intelligent equipment, education and other fields are expound. Finally, in order to provide reference and basis for further research, the problems that need to be studied and future work are prospected. © 2022 IEEE.

关键词： Human computer interaction

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Enhanced ZSSR for Super-resolution Reconstruction of the Historical Tibetan Document Images 7

Enhanced ZSSR for Super-resolution Reconstruction of the His...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Lu, Yuqi Wang, Tiejun Zhao, Penghai Zhang, Guowei Northwest Minzu University Key Laboratory of China's Ethnic Languages and Information Technology Ministry of Education Lanzhou China

ISBN: (纸本)9781665478571

Due to the poor preservation and imaging conditions, the image quality of historical Tibetan document images is relatively unsatisfactory. In this paper, we adopt super-resolution technology to reconstruct high quality images of historical Tibetan document. To address the problem of low quantity and poor quality of historical Tibetan document images, we propose the EZSSR network based on the Zero-Shot Super-resolution Network (ZSSR), which borrows the idea of feature pyramid in Deep Laplacian Pyramid Networks (LapSRN) to extract different levels of features while alleviating the ringing artifacts. EZSSR neither requires paired training datasets nor preprocessing stage. the computational complexity of EZSSR is low, and thus, EZSSR can also reconstruct image within the acceptable time frame. Experimental results show that EZSSR reconstructs images with better visual effects and higher PSNR and SSIM values. © 2022 IEEE.

关键词： Optical resolving power

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Zomato ETL for Chain of Orders Using Random Forest Algorithm 7

Zomato ETL for Chain of Orders Using Random Forest Algorithm

引用

7th international conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Baskaran, S.U. Gokila, S. Hindustan Institute of Technology and Science Department of Computer Application Chennai India

ISBN: (数字)9798350372816

ISBN: (纸本)9798350372816

In the realm of food delivery services, efficient data processing plays a crucial role in enhancing customer experience and optimizing operational workflows. this study investigates the application of Zomato ETL (Extract, Transform, Load) processes coupled with the Random Forest algorithm to analyze a chain of orders within the platform. By extracting data from various sources such as customer preferences, order history, and delivery patterns, the ETL process transforms this information into actionable insights. the Random Forest algorithm is then employed to predict customer behavior, optimize delivery routes, and personalize recommendations. the high values for accuracy, precision, recall, and F1-score indicate that the Random Forest model used in the Zomato ETL system is performing exceptionally well in classifying or predicting the target variable based on the given dataset. An accuracy of 98.77% and an F1-score of 98.43% are considered excellent scores, demonstrating the model's effectiveness in correctly identifying and predicting the instances in the dataset. this integrated approach not only streamlines order processing and delivery operations but also enables Zomato to offer a more tailored and seamless experience to its users. © 2024 IEEE.

关键词： Sales

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Efficient Cross-Scale Integration For UAV Object Detection 7

Efficient Cross-Scale Integration For UAV Object Detection

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7th international conference on Advanced Algorithms and Control Engineering, ICAACE 2024

作者： Wang, Zhengyang Yu, Yue Hu, Zihan Zhu, Yijia School Of Computer Science And Technology Anhui University Hefei China Hefei Fengle Seed Co. Ltd Hefei China Stony Brook Institute Anhui University Hefei China

ISBN: (纸本)9798350361445

Multi-scale visual representation have shown their advantages in effectiveness in a wide range of applications. However, existing methods fail to fully utilize the specific semantic information of the respective layers, as they focus too much on the interaction between different scale layers. To alleviate this problem, in this paper, we propose a new framework inspired by YOLO efficiency, which injects the unique information of the respective layers for cross-scale communication. Specifically, we first propose the Mining Unique Semantics module (MUS), which explicitly enhances the unique contextual semantics in each layer. Second, although it is crucial to leverage global context-enhanced features from other layers, overemphasis may inadvertently ignore the intrinsic semantic information within each layer. To this end, we design a Multi-Scale information Integration module (MSI) that carefully balances this trade-off, ensuring meaningful integration without sacrificing individual identity. With the help of the above two modules, our proposed method effectively leverages small-scale object features related to spatial positions to improve detection performance in Unmanned Aerial Vehicles (UAV) object detection tasks. Extensive experiments on the VisDrone2019 benchmark dataset show that the proposed framework achieves superior performance compared with advanced UAV object detection methods. © 2024 IEEE.

关键词： Object detection

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