检索结果-内蒙古大学图书馆

International Conference on Advanced Computing, ICAC

作者： M. Ramprasath A.V. Kalpana T.Nadana Ravishankar M. Anand J. Shobana Department of Data science and business systems SRM Instiute of Science and Technology Kattankulathur Chennai India

Businesses and people together use cloud storage to transfer their vast amounts of data to unknown servers at a significantly lower cost than traditional methods. Several methods have been made to investigate the many aspects of this application scenario, such as efficiency, dependability, and security. Service providers can search and retrieve encrypted data in a cloud storage scenario where customers share their outsourced information with other users and convert their data before outputting it to a cloud storage service. The advanced technologies in cloud computing help them store and retrieve data securely anywhere at any time. Subsequently, in the cloud environment, security problem becomes a massive issue that defends further development in cloud computing and promotes remote data auditing. Several data auditing methods have been discussed in the research fiction, but those schemas still need to be improved for protected data sharing in cloud environments. This paper proposes a data-sharing schema for remote data auditing in a cloud environment. Our proposed method implements the CP-ABE (Attribute-based encryption) schema with minor changes in the access control policy structure to make it suitable for remote data auditing in the cloud environment. The experimental result shows that our protected data-sharing method can reduce data overhead when the user remotely shares the data in the cloud environment.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Flexibility and rigidity index for chromosome packing,flexibility and dynamics analysis

引用

Frontiers of Computer science 2022年第4期16卷 203-213页

作者： Jiajie Peng Jinjin Yang D Vijay Anand Xuequn Shang Kelin Xia School of Computer Science Northwestern Polytechnical UniversityXi’an710129China Key Laboratory of Big Data Storage and Management Northwestern Polytechnical UniversityMinistry of Industry and Information TechnologyXi’an710129China Division of Mathematical Sciences School of Physical and Mathematical SciencesNanyang Technological UniversitySingapore637371Singapore School of Biological Sciences Nanyang Technological UniversitySingapore637371Singapore

The packing of genomic DNA from double helix into highly-order hierarchical assemblies has a great impact on chromosome flexibility,dynamics and *** open and accessible regions of chromosomes are primary binding positions for regulatory elements and are crucial to nuclear processes and biological *** by the success of flexibility-rigidity index(FRI)in biomolecular flexibility analysis and drug design,we propose an FRI-based model for quantitatively characterizing chromosome *** on Hi-C data,a flexibility index for each locus can be ***,flexibility is tightly related to packing *** compacted regions are usually more rigid,while loosely packed regions are more ***,a strong correlation is found between our flexibility index and DNase and ATAC values,which are measurements for chromosome *** addition,the genome regions with higher chromosome flexibility have a higher chance to be bound by transcription ***,the Gaussian network model(GNM)is applied to analyze the chromosome accessibility and a mobility profile has been proposed to characterize chromosome *** with GNM,our FRI is slightly more accurate(1%to 2%increase)and significantly more efficient in both computational time and *** a 5Kb resolution Hi-C data,the flexibility evaluation process only takes FRI a few minutes on a single-core *** contrast,GNM requires 1.5 hours on 10 ***,interchromosome interactions can be easily combined into the flexibility evaluation,thus further enhancing the accuracy of our *** contrast,the consideration of interchromosome information into GNM will significantly increase the size of its Laplacian(or Kirchhoff)matrix,thus becoming computationally extremely challenging for the current *** software and supplementary document are available at https://***/jiajiepeng/FRI_chrFle.

关键词： flexibility-rigidity index 3D genome chromosome flexibility

来源：评论

学校读者我要写书评

暂无评论

FLAP: Federated Learning Aggregation Scheme Based on Privileged Secret Sharing

FLAP: Federated Learning Aggregation Scheme Based on Privile...

引用

2023 International Conference on Networking and Network Applications, NaNA 2023

作者： Mu, Xianyu Tian, Youliang Xiong, Jinbo Wang, Shuai Gong, Boxiang College of Computer Science and Technology Guizhou University State Key Laboratory of Public Big Data Guiyang550025 China College of Computer and Cyber Security Fujian Normal University Fujian Provincial Key Laboratory of Network Security and Cryptology Fuzhou350117 China Guizhou Xishan Technology Co. Ltd China

ISBN: (纸本)9798350327380

Federated Learning (FL) is a privacy-preserving machine learning technique that trains models on client devices and only uploads new model gradients to servers for aggregation. However, transmitting the true gradients introduces the risk of reverse inference attack, which can compromise client privacy. To address this issue, we present the federated learning aggregation scheme based on privileged secret sharing (FLAP). Firstly, we present privileged secret sharing by combining the one-time pad with shamir secret sharing. Secondly, we introduce game theory to generate games between servers to resist collusion attacks. Finally, the analysis demonstrates that FLAP enables the server to successfully update the global gradient while ensuring the utmost protection of client privacy and FLAP achiev the effect of resisting collusion attack and reverse inference attack. We have proved through experiments that FLAP is 26.42% more efficient than the current scheme, and has strong robustness to drop out. © 2023 IEEE.

关键词： Game theory

来源：评论

学校读者我要写书评

暂无评论

Development of a Sensor-Based Wearable Fetal and Maternal Health Monitoring System 1

Development of a Sensor-Based Wearable Fetal and Maternal He...

引用

1st International Conference on Electronics, Communication and Signal Processing, ICECSP 2024

作者： Jayalath, Yugashi Maduranga, M.W.P. Tilwari, Valmik Wijayarathna, Wmsrb Wanniarachchi, Waam Sharma, Debashree School Of Pharmacy & Biomolecular Sciences Liverpool John Moores University Liverpool United Kingdom Sri Lanka Technology Campus Faculty of Computing and IT Department of Data Science Padukka Sri Lanka Indian Institute of Information Technology Department of Electronics & Communication Engineering Guwahati India General Sir Jhon Kotelawala Defence University Department of Information Technology Colombo Sri Lanka

ISBN: (纸本)9798350364590

According to the World Health Organization, approximately 360,000 pregnant women are registered annually in Sri Lanka. Among these, about 328,000 babies are born healthy, while 5,800 are born with birth defects, some of which are severe and impact daily life. To address the Sri Lankan stillbirth rate of 6.01%, continuous monitoring of fetal and maternal health is essential. Although commercial devices exist to fulfill this requirement, their high costs and safety issues often preclude regular use. To overcome these challenges, there is a need for a passive, wearable, and portable monitoring system for fetal and maternal health. This system should track key parameters such as fetal heart rate, fetal movements, and maternal heart rate to mitigate health risks for both the fetus and the mother. In this study, we developed a device using the Arduino, appropriate sensors, and a microcontroller to monitor these vital parameters. The device is user-friendly and suitable for regular use. MATLAB was utilized for the signal processing requirements of the proposed device. Test results demonstrated that fetal movement detection was accurate, although potential errors may arise during real-time testing. For pulse sensor readings, an average percentage difference of 3.025% was observed compared to pulse oximeter readings, likely due to placement errors and sensor instability in the proposed device. © 2024 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Combining spectral and textures of digital imagery for wheat aboveground biomass estimation

Combining spectral and textures of digital imagery for wheat...

引用

2022 International Conference on Electronic Information technology, EIT 2022

作者： Zheng, Ling Tao, Jianpeng Bao, Qian Weng, Shizhuang Zhang, Yakun Zhao, Jinling Huang, Linsheng National Engineering Research Venter for Agro-Ecological Big Data Analysis and Application Anhui University Hefei230601 China College of Agricultural Equipment Engineering Henan University of Science and Technology Luoyang471003 China

ISBN: (纸本)9781510655096

The aboveground biomass (AGB) is a key index for predicting wheat yield. In the case of high biomass, the AGB estimation of single spectral feature or image texture is poor. Therefore, this study evaluated the ability of fusion of spectral reflectance and texture to predict wheat AGB. Among them the reflectance spectrum of the wheat canopy was collected by near-earth spectrometer, and the texture features of three bands of RGB were extracted by gray co-occurrence matrix. Partial least squares regression (PLS) model was used to evaluate the relationship between fusion features and AGB. The experimental results based on the validated data set show that the AGB estimation effect of feature fusion is better than that of single feature (R2 = 0.70;RMSE = 0.06). This shows that the combination of spectral reflectance and texture can improve the accuracy of AGB estimation in the later stage. © 2022 SPIE. All rights reserved.

关键词： Textures

来源：评论

学校读者我要写书评

暂无评论

Development of high-accuracy particle concentration prediction model. An application of remote sensing and machine learning 18

Development of high-accuracy particle concentration predicti...

引用

18th Healthy Buildings Europe Conference 2023: Beyond Disciplinary Boundaries

作者： Moni, Mufaddal Sahu, Manoranjan Aerosol and Nanoparticle Technology Laboratory Environmental Science and Engineering Department Indian Institute of Technology Bombay Mumbai400076 India Interdisciplinary Program in Climate Studies Indian Institute of Technology Bombay Mumbai400076 India Centre for Machine Intelligence and Data Science Indian Institute of Technology Bombay Mumbai400076 India

ISBN: (纸本)9781713877158

Indoor air is a dominant exposure for humans as more than half of the body’s intake during a lifetime is air inhaled indoors. Most of the buildings in developing nations are openly ventilated, and there is no significant difference between the outside and indoor air. Efforts are being made by authorities to build well-controlled indoor environments. The lack of air pollution monitoring systems is one of the major challenges in identifying high-risk zones where the development of healthy buildings is critical. Ground-based monitoring systems are sparsely distributed in major cities only. Whereas low-cost sensors come with challenges related to calibration, accuracy, and reliability. Satellites provide continuous global coverage with high-resolution AOD data. Though significant work has been done correlating AOD and PM2.5, still the models lack accuracy and transferability. The vertical distribution profile of the aerosols significantly affects the surface level concentration which is not accounted for by the majority of the studies done for AOD-PM2.5 modeling. This study emphasizes the use of high-resolution AOD from CHRISTINE code and aerosol vertical distribution profile, along with meteorological parameters and factors affecting particle size distribution, to develop a step-down methodology for more accurate PM2.5 prediction and transferable a larger geographical range. © Healthy Buildings Europe 2023. All rights reserved.

关键词： Air quality

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence Techniques Based Energy Prediction Analysis and Load Forecasting Using a Dynamic Website 1

Artificial Intelligence Techniques Based Energy Prediction A...

引用

1st International Conference on Intelligent Technologies for Sustainable Electric and Communications Systems, iTech SECOM 2023

作者： Ramesh, R. Dharani, S. Asuvanti, M.A. Gowrijayasree, Gowrijayasree Indhu Rekha, U. Bannari Amman Institute of Technology Department of Electronics and Communication Engineering India Dr. Mahalingam College of Engineering and Technology Department of Electronics and Communication Engineering India Sengunthar Engineering College Department of Electronics and Communication Engineering India Bannari Amman Institute of Technology Department of Artificial Intelligence and Data Science India

ISBN: (纸本)9798350371185

Electricity plays a crucial part in human living. The use of electricity has become a necessity. Though energy is a renewable resource it is being wasted often due to energy leakage, short circuit, and load balancing. Numerous actions and choices, including the use of load prediction affect countless decisions and actions, including transportation, unit involvement, fuel reservation, and out-of-service network study. Energy consumption data of a building is generated via an energy meter;it is then trained to fewer models for prediction and forecasting. Energy usage forecasting using LSTM with a higher accuracy of 87% than other Autoregressive models and with a Mean Absolute Error of 0.03 is suitable for implementation. Then the model is built into a Web App that enables users to keep track of the energy usage of their appliances. In the next step a threshold value is set, and whenever the appliances reach the maximum threshold value it is notified to the user or consumer which helps in reducing unwanted energy wastage in any particular area of use. © 2023 IEEE.

关键词： Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Cursive Handwriting Recognition Using CNN with VGG-16

Cursive Handwriting Recognition Using CNN with VGG-16

引用

Artificial Intelligence and Knowledge Discovery in Concurrent Engineering (ICECONF), International Conference on

作者： Anushka Anil Rangari Swagat Das Rajeswari D Department of Data Science and Business Systems SRM Institute of Science and Technology Kattankulathur Tamilnadu India

Cursive handwritten text recognition is a process of identifying handwritten text from images. The recognition process is difficult due to person's unique style of writing. Pattern recognition is used to classify the data into various categories. This study used CNN with VGG16 model to identify cursive English alphabets and words in a given scanned text document. The first phase is image acquisition, which involves acquiring the scanned picture, normalizing the image, extracting the features from the image, and applying segmentation. Three different pre-processing techniques like data augmentation, image segmentation and image data generator are implemented in this work. CNN with VGG 16 model is employed for recognition. Three kinds of experiments were done with various combinations of pre-processing techniques combined with CNN model. The experimental results indicates that data augmentation pre-processing technique with CNN produced 98.36% training accuracy and 95.1% testing accuracy which is best than other combinations.

关键词： Training Image segmentation Handwriting recognition Text recognition Writing Feature extraction Knowledge discovery

来源：评论

学校读者我要写书评

暂无评论

RoyaltyChain: A Blockchain-Powered big data Framework for Accurate Music Royalties Prediction 21

RoyaltyChain: A Blockchain-Powered Big Data Framework for Ac...

引用

21st IEEE India Council International Conference, INDICON 2024

作者： Shah, Megh H. Sheth, Parth V. Kumari, Aparna Tanwar, Sudeep Chawra, Vrajesh Kumar, Sunil Institute of Technology Nirma University Department of Computer Science and Engineering Ahmedabad India Guru Jambheshwar University of Science & Technology Department of Ai and Data Science Haryana Hisar India

ISBN: (纸本)9798350391282

The growth of the commodification of music in the present age has made royalties allocation in an efficient, straight-forward manner to the stakeholders, in general, a complex issue. To address these challenges, this paper introduces RoyaltyChain, a new framework powered by predictive analytics and blockchain. Using factors like streaming data, social media statistics, and geographical factors, Random Forest Regression is employed to predict royalties in a big data environment, with a blockchain-backed system ensuring secure and transparent distribution. Here Ethereum blockchain-based smart contracts are designed in Remix IDE and the Interplanetary File System (IPFS) is incorporated to handle data storage cost issues in blockchain. The performance evaluation shows an increase in the overall efficiency in predicting outcomes and the high scalability of our system in comparison with the related techniques with respect to accuracy, scalability, etc. RoyaltyChain provides a scalable framework to establish efficient and fair distribution of money from the consumption of music in this increasingly complex world. © 2024 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Dynamic nonlinear algebraic models with scale-similarity dynamic procedure for large-eddy simulation of turbulence

引用

Advances in Aerodynamics 2022年第1期4卷 304-326页

作者： Zelong Yuan Yunpeng Wang Chenyue Xie Jianchun Wang Department of Mechanics and Aerospace Engineering Southern University of Science and TechnologyShenzhen518055China Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou) Guangzhou511458China Guangdong-Hong Kong-Macao Joint Laboratory for Data-Driven Fluid Mechanics and Engineering Applications Southern University of Science and TechnologyShenzhen518055China Department of Ocean Science The Hong Kong University of Science and TechnologyHong Kong999077China

A dynamic nonlinear algebraic model with scale-similarity dynamic procedure(DNAM-SSD)is proposed for subgrid-scale(SGS)stress in large-eddy simulation of *** model coefficients of the DNAM-SSD model are adaptively calculated through the scale-similarity relation,which greatly simplifies the conventional Germano-identity based dynamic procedure(GID).The a priori study shows that the DNAM-SSD model predicts the SGS stress considerably better than the conventional velocity gradient model(VGM),dynamic Smagorinsky model(DSM),dynamic mixed model(DMM)and DNAM-GID model at a variety of filter widths ranging from inertial to viscous *** correlation coefficients of the SGS stress predicted by the DNAM-SSD model can be larger than 95%with the relative errors lower than 30%.In the a posteriori testings of LES,the DNAM-SSD model outperforms the implicit LES(ILES),DSM,DMM and DNAM-GID models without increasing computational costs,which only takes up half the time of the DNAM-GID *** DNAM-SSD model accurately predicts plenty of turbulent statistics and instantaneous spatial structures in reasonable agreement with the filtered DNS *** results indicate that the current DNAM-SSD model is attractive for the development of highly accurate SGS models for LES of turbulence.

关键词： Subgrid-scale model Nonlinear algebraic model Large-eddy simulation Incompressible turbulence

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：