检索结果-内蒙古大学图书馆

7th International Conference on Smart City Applications, SCA 2022

作者： Zahoor, Kanwal Bawany, Narmeen Zakaria Center for Computing Research Department of Computer Science and Software Engineering Jinnah University for Women Karachi74600 Pakistan

ISBN: (纸本)9783031268519

A rapid technology change has significant opportunities for almost every industry, especially for healthcare. By using advanced network technologies and Internet of Medical Things (IoMT) devices, health professionals can monitor remotely and respond to emergency cases efficiently. Ambient Assistive living (AAL) aims to improve living conditions for the elderly and disabled people. Data from heterogeneous sensors allow AAL systems to continuously monitor the health status of the elderly. The main contribution of this paper is to propose an Ambient Assisted Living Framework (ALF) for health care. The framework - ALF for health care comprises four layers namely, data sources, data integration, data analytics and ambient assisted living applications for healthcare. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Mining User Behavior in Decentralized Applications for Blockchain Trust and Security Analytics 5

Mining User Behavior in Decentralized Applications for Block...

引用

5th International Conference on Blockchain Computing and Applications, BCCA 2023

作者： You, Shengwei Joshi, Aditya Kuehlkamp, Andrey Nabrzyski, Jarek University of Notre Dame Center for Research Computing Department of Computer Science and Engineering Notre Dame United States

ISBN: (纸本)9798350339239

This paper presents a cutting-edge data mining approach to investigate user trust in decentralized applications (dApps) on public blockchains. Our innovative data analysis methodology enables a comprehensive exploration of dApp user behaviors, uncovering crucial insights. Contrary to popular belief, large-scale hacking incidents on centralized exchanges (CEX) have a limited impact on decentralized exchange (DEX) migration and inactive user rates. Additionally, our results reveal a notable trend of increased user outflow in older dApp protocols compared to their newer counterparts and emphasize the significant role of government regulations on DEX user inactivity. This research advances the understanding of dApp scalability and user trust, laying the groundwork for future inquiries in this rapidly evolving field. © 2023 IEEE.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

A study of the leverage effect in Bitcoin Conditional Heteroskedasticity prediction 10

A study of the leverage effect in Bitcoin Conditional Hetero...

引用

10th International Conference on Artificial Intelligence and Robotics, QICAR 2024

作者： Abarghouie, Masoud Omidvari Alizadeh, Sasan H. Khademzadeh, Ahmad Department of Computer Engineering Science and Research branch Islamic Azad University Tehran Iran Faculty of Information Technology Iran Telecommunication Research Center Tehran Iran Iran Telecommunication Research Center Tehran Iran

ISBN: (纸本)9798350348873

In today's world, countries establish large companies specifically designed to effectively manage the risks associated with volatility exchange rates and leveraged assets. Bitcoin is widely recognized as the leading cryptocurrency, making it highly appealing to investors and traders. The recorded data reveals a growing number of transactions conducted using Bitcoin cryptocurrency. Consequently, accurately predicting the volatility of Bitcoin's conditional heteroskedasticity holds significant importance for the financial markets. Cryptocurrencies present a challenging situation due to their complex dynamics, extreme observations, asymmetry, and various other non-linear features. Modeling these cryptocurrencies accurately becomes difficult using statistical models, as they fail to consider the leverage effect and provide precise predictions. In this paper, we have employed a hybrid modeling approach by utilizing MLP neural network and GARCH statistical model. The experiments conducted on Bitcoin time series data have yielded promising results, showcasing a notable reduction in the prediction error of conditional heteroskedasticity volatility. ©2024 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Performance comparison of different algorithms for land surface temperature (LST) retrieval from Landsat-8 and the use of deep neural network regression to enhance the LST result (Case Study: Dallas, Texas and surrounding areas) 8

Performance comparison of different algorithms for land surf...

引用

Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications VIII 2024

作者： Ayudyanti, Amalia Gita Chen, Ying-Nong Jamaluddin, Ilham Center for Space and Remote Sensing Research National Central University Taiwan Department of Computer Science and Information Engineering National Central University Taiwan

ISBN: (数字)9781510682757

ISBN: (纸本)9781510682740

Land Surface Temperature (LST) is important data for various fields, especially for monitoring global warming. Landsat-8 satellite imagery provides thermal data with a spatial resolution of 30m (resampled from 100m) as the main data for LST retrieval. This research aims to compare several LST retrieval algorithms such as LST retrieval using band 10, Single Channel Model (SCM), Qin's Split-Window Algorithm (Q-SWA), Sobrino's Split-Window Algorithm (S-SWA), and LST from the analysis ready data of Landsat 8 Level-2. The study focuses on Dallas, Texas, and surrounding areas in March 2023. We collected air temperature data from 20 U.S. Environmental Protection Agency (EPA) stations for indirect validation. Based on the results, the Q-SWA method outperformed other retrieval algorithms with mean absolute error (MAE) and root mean squared error (RMSE) were 0.683°C and 0.842°C, respectively. Given that Landsat-8's thermal band data is resampled from 100m to 30m, this research also explores enhancing the retrieved LST using deep neural network regression (DNNR). The best retrieved LST from the Q-SWA method served as the target data while several bands and spectral indices from Landsat-8 were used as the input for DNNR model. Due to the large scale of data, we randomly selected 10 million pixels and divided into 80% of training and 20% of testing data. The DNNR model achieved MAE of 1.022°C on the testing dataset. The enhanced LST from the DNNR model was also validated with the same air temperature validation data and achieved the MAE score of 1.037°C. Based on the visual comparison result, the DNNR model successfully enhanced the retrieved LST by providing more detailed results at the same 30m resolution and showing promising performance based on error metrics. This finding suggests the potential for using deep learning regression in LST downscaling to achieve better spatial resolution. © 2024 SPIE.

关键词： Landsat

来源：评论

学校读者我要写书评

暂无评论

Integrating Chatbot Functionality in a Patient Summary Based Healthcare System

Integrating Chatbot Functionality in a Patient Summary Based...

引用

34th Medical Informatics Europe Conference, MIE 2024

作者： Vasili, Aliki Schiza, Eirini Schizas, Christos N. Pattichis, Constantinos S. Department of Computer Science and Biomedical Engineering Research Center University of Cyprus Cyprus CYENS Centre of Excellence Cyprus National eHealth Authority Cyprus

ISBN: (纸本)9781643685335

The integration of chatbots in healthcare has gained attention due to their potential to enhance patient engagement and satisfaction. This paper presents a healthcare chatbot providing comprehensive access to patient summaries, aligned with the European Patient Summary. Leveraging Natural Language Processing (NLP) capabilities, our chatbot employs intent classification using the fine-tuned bioBERT model to categorize user queries effectively and extract relevant information from the patient summary stored in a database. We detail our methodology, which involves dataset creation, hyperparameter tuning, and model evaluation. Results demonstrate the effectiveness of our approach, with the trained model achieving high precision, recall, and F1 score across intent classes. Our study underscores the potential of emerging NLP techniques in patient interaction and healthcare delivery, covering the way for smarter, user-friendly companions. © 2024 The Authors.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

引用

computer Modeling in engineering & sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

来源：评论

学校读者我要写书评

暂无评论

A Character Flow Framework for Multi-Oriented Scene Text Detection

引用

Journal of computer science & Technology 2021年第3期36卷 465-477页

作者： Wen-Jun Yang Bei-Ji Zou Kai-Wen Li Shu Liu School of Computer Science and Engineering Central South UniversityChangsha410083China Hunan Engineering Research Center of Machine Vision and Intelligent Medicine Changsha410083China

Scene text detection plays a significant role in various applications,such as object recognition,document management,and visual *** instance segmentation based method has been mostly used in existing research due to its advantages in dealing with multi-oriented ***,a large number of non-text pixels exist in the labels during the model training,leading to text *** this paper,we propose a novel multi-oriented scene text detection framework,which includes two main modules:character instance segmentation(one instance corresponds to one character),and character flow construction(one character flow corresponds to one word).We use feature pyramid network(FPN)to predict character and non-character instances with arbitrary directions.A joint network of FPN and bidirectional long short-term memory(BLSTM)is developed to explore the context information among isolated characters,which are finally grouped into character *** experiments are conducted on ICDAR2013,ICDAR2015,MSRA-TD500 and MLT datasets to demonstrate the effectiveness of our *** F-measures are 92.62%,88.02%,83.69%and 77.81%,respectively.

关键词： multi-oriented scene text detection character instance segmentation character flow feature pyramid network(FPN) bidirectional long short-term memory(BLSTM)

来源：评论

学校读者我要写书评

暂无评论

EventLFM:event camera integrated Fourier light field microscopy for ultrafast 3D imaging

引用

Light(science & Applications) 2024年第7期13卷 1401-1415页

作者： Ruipeng Guo Qianwan Yang Andrew S.Chang Guorong Hu Joseph Greene Christopher V.Gabel Sixian You Lei Tian Department of Electrical and Computer Engineering Boston UniversityBostonMA 02215USA Department of Physiology and Biophysics Boston UniversityBostonMA 02215USA. Neurophotonics Center Boston UniversityBostonMA 02215USA. Research Laboratory of Electronics(RLE)in the Department of Electrical Science and Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA. Department of Biomedical Engineering Boston UniversityBostonMA 02215USA

Ultrafast 3D imaging is indispensable for visualizing complex and dynamic biological *** scanning-based techniques necessitate an inherent trade-off between acquisition speed and space-bandwidth product(SBP).Emerging single-shot 3D wide-field techniques offer a promising alternative but are bottlenecked by the synchronous readout constraints of conventional CMOS systems,thus restricting data throughput to maintain high SBP at limited frame *** address this,we introduce EventLFM,a straightforward and cost-effective system that overcomes these challenges by integrating an event camera with Fourier light field microscopy(LFM),a state-of-theart single-shot 3D wide-field imaging *** event camera operates on a novel asynchronous readout architecture,thereby bypassing the frame rate limitations inherent to conventional CMOS *** further develop a simple and robust event-driven LFM reconstruction algorithm that can reliably reconstruct 3D dynamics from the unique spatiotemporal measurements captured by *** results demonstrate that EventLFM can robustly reconstruct fast-moving and rapidly blinking 3D fluorescent samples at kHz frame ***,we highlight EventLFM’s capability for imaging of blinking neuronal signals in scattering mouse brain tissues and 3D tracking of GFP-labeled neurons in freely moving *** believe that the combined ultrafast speed and large 3D SBP offered by EventLFM may open up new possibilities across many biomedical applications.

关键词： field linking overcome

来源：评论

学校读者我要写书评

暂无评论

Belief Combination of Classifiers for Incomplete Data

引用

IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 652-667页

作者： Zuowei Zhang Songtao Ye Yiru Zhang Weiping Ding Hao Wang IEEE the Research Center for Optical Fiber Sensing Zhejiang Laboratory the School of Automation Northwestern Polytechnical University the School of Cyber Engineering Xidian University the Department of Computer Science CY Cergy Paris Université the School of Information Science and Technology Nantong University the School with of Cyber Engineering Xidian University the Department of Computer Science Norwegian University of Science and Technology

Data with missing values,or incomplete information,brings some challenges to the development of classification,as the incompleteness may significantly affect the performance of *** this paper,we handle missing values in both training and test sets with uncertainty and imprecision reasoning by proposing a new belief combination of classifier(BCC)method based on the evidence *** proposed BCC method aims to improve the classification performance of incomplete data by characterizing the uncertainty and imprecision brought by *** BCC,different attributes are regarded as independent sources,and the collection of each attribute is considered as a ***,multiple classifiers are trained with each subset independently and allow each observed attribute to provide a sub-classification result for the query ***,these sub-classification results with different weights(discounting factors)are used to provide supplementary information to jointly determine the final classes of query *** weights consist of two aspects:global and *** global weight calculated by an optimization function is employed to represent the reliability of each classifier,and the local weight obtained by mining attribute distribution characteristics is used to quantify the importance of observed attributes to the pattern *** comparative experiments including seven methods on twelve datasets are executed,demonstrating the out-performance of BCC over all baseline methods in terms of accuracy,precision,recall,F1 measure,with pertinent computational costs.

关键词： Classifier fusion classification evidence theory incomplete data missing values

来源：评论

学校读者我要写书评

暂无评论

Distinguishing Between Natural and GAN-Generated Face Images by Combining Global and Local Features

引用

Chinese Journal of Electronics 2022年第1期31卷 59-67页

作者： CHEN Beijing TAN Weijin WANG Yiting ZHAO Guoying Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science and Technology School of Computer Nanjing University of Information Science and Technology Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET) Nanjing University of Information Science and Technology Warwick Manufacturing Group University of Warwick Center for Machine Vision and Signal Analysis University of Oulu

With the development of face image synthesis and generation technology based on generative adversarial networks(GANs), it has become a research hotspot to determine whether a given face image is natural or generated. However, the generalization capability of the existing algorithms is still to be improved. Therefore,this paper proposes a general algorithm. To do so, firstly,the learning on important local areas, containing many face key-points, is strengthened by combining the global and local features. Secondly, metric learning based on the Arc Face loss is applied to extract common and discriminative features. Finally, the extracted features are fed into the classification module to detect GAN-generated *** experiments are conducted on two publicly available natural datasets(Celeb A and FFHQ) and seven GANgenerated datasets. Experimental results demonstrate that the proposed algorithm achieves a better generalization performance with an average detection accuracy over 0.99 than the state-of-the-art algorithms. Moreover, the proposed algorithm is robust against additional attacks, such as Gaussian blur, and Gaussian noise addition.

关键词： feature extraction neural nets GAN-generated datasets local features metric learning generative adversarial networks face image GAN-generated faces generation technology learning (artificial intelligence) discriminative features GAN-generated face images face recognition face image synthesis generalization performance global features face key-points

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：