检索结果-内蒙古大学图书馆

Proof of Activity Protocol for IoMT Data Security

computer Systems science & engineering 2023年第1期44卷 339-350页

作者： R.Rajadevi K.Venkatachalam Mehedi Masud Mohammed A.AlZain Mohamed Abouhawwash Department of Information Technology Kongu Engineering CollegeErode638060TamilnaduIndia Department of Applied Cybernetics Faculty of ScienceUniversity of Hradec KrálovéHradec Králové50003Czech Republic Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

The Internet of Medical Things(IoMT)is an online device that senses and transmits medical data from users to physicians within a time ***,recent years,IoMT has rapidly grown in the medicalfield to provide healthcare services without physical *** the use of sensors,IoMT applications are used in healthcare *** such applications,one of the most important factors is data security,given that its transmission over the network may cause *** data security in IoMT systems,blockchain is used due to its numerous blocks for secure data *** this study,Blockchain-assisted secure data management framework(BSDMF)and Proof of Activity(PoA)protocol using malicious code detection algorithm is used in the proposed data security for the healthcare *** main aim is to enhance the data security over the *** PoA protocol enhances high security of data from the literature *** replacing the malicious node from the block,the PoA can provide high security for medical data in the *** with existing systems shows that the proposed simulation with BSD-Malicious code detection algorithm achieves higher accuracy ratio,precision ratio,security,and efficiency and less response time for Blockchain-enabled healthcare systems.

关键词： Blockchain IoMT malicious code detection security secure data management framework data management PoA

来源：评论

学校读者我要写书评

暂无评论

Prescribing Decision Conservativeness in Two-Stage Power Markets: A Distributionally Robust End-to-End Approach 59

Prescribing Decision Conservativeness in Two-Stage Power Mar...

引用

59th Annual Conference on Information sciences and Systems, CISS 2025

作者： Liang, Zhirui Li, Qi Liu, Anqi Dvorkin, Yury Johns Hopkins University Department of Applied Mathematics and Statistics BaltimoreMD United States Johns Hopkins University Department of Computer Science BaltimoreMD United States Johns Hopkins University Department of Electrical and Computer Engineering BaltimoreMD United States Johns Hopkins University Department of Civil and System Engineering BaltimoreMD United States

ISBN: (纸本)9798331513269

This paper presents an end-to-end framework for calibrating wind power forecast models to minimize operational costs in two-stage power markets, where the first stage involves a distributionally robust optimal power flow (DR-OPF) model. Unlike traditional methods that adjust forecast parameters and uncertainty quantification (UQ) separately, this framework jointly optimizes both the forecast model parameters and the decision conservativeness, which determines the size of the ambiguity set in the DR-OPF model. The framework aligns UQ with actual uncertainty realizations by directly optimizing downstream operational costs, a process referred to as cost-oriented calibration. The calibration is achieved using a gradient descent approach. To enable efficient differentiation, the DR-OPF problem is reformulated into a convex form, and the Envelope Theorem is leveraged to simplify gradient derivation in the two-stage setting. Additionally, the framework supports distributed implementation, effectively reducing computational overhead and enhancing efficiency. By proactively calibrating forecast parameters and prescribing optimal decision conservativeness, the framework significantly enhances cost efficiency and reliability in power system operations. Numerical experiments on an IEEE 5-bus system demonstrate the effectiveness and efficiency of the proposed approach. © 2025 IEEE.

关键词： Wind forecasting

来源：评论

学校读者我要写书评

暂无评论

Analysis of Viral and Non-viral Categories of Video Through Social Media Using Machine Learning Techniques 15th

Analysis of Viral and Non-viral Categories of Video Through ...

引用

15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Nagashree, B.A. Satheesh Kumar, S. Muthukumaran, V. Joseph, P. Rose Bindu Amrita Vishwa Vidyapeetham Mysuru Campus Mysuru570026 India Department of Computer Science School of Applied Sciences REVA University Bangalore India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Chennai India Department of Mathematics Dayananda Sagar College of Engineering Bangalore India

ISBN: (纸本)9783031889912

People frequently use technological means to collect information from many sources, share it with others on social media, and communicate with friends on these platforms. Social media is therefore a crucial new tool for communication. Collaborative wikis, blogs, and content communities are just a few of the tools and technologies that make up social media. YouTube is the most widely used of these. The influencer’s content gets visible to the users of such platforms. The expansion of social media use has enabled massive and rapid spread ability of content, often called virality. This paper aims to examine the virality of different categories of YouTube videos using machine learning technique, where it plays a major role in analysis of YouTube data such as likes, dislikes, comment count and views. YouTube can serve as a path to virality and fabricate online videos, hence finding the correlation analysis among the videos, which enables us to classify the viral and non-viral video categories, thereby analysing the linear relationship among the features (likes, dislike, views and comment count. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Tweets

来源：评论

学校读者我要写书评

暂无评论

Colouring of COVID-19 Affected Region Based on Fuzzy Directed Graphs

引用

computers, Materials & Continua 2021年第7期68卷 1219-1233页

作者： Rupkumar Mahapatra Sovan Samanta Madhumangal Pal Jeong-Gon Lee Shah Khalid Khan Usman Naseem Robin Singh Bhadoria Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar UniversityMidnapore721102India Department of Mathematics Tamralipta MahavidyalayaTamluk721636India Division of Applied Mathematics Wonkwang UniversityIksan-SiJeonbuk54538Korea School of Engineering RMIT UniversityMelbourne3001Australia School of Computer Science University of Sydney Sydney2006Australia Department of Computer Science&Engineering Birla Institute of Applied Sciences(BIAS)BhimtalUttarakhand263136India

Graph colouring is the system of assigning a colour to each vertex of a *** is done in such a way that adjacent vertices do not have equal *** is fundamental in graph *** is often used to solve real-world problems like traffic light signalling,map colouring,scheduling,***,social networks are prevalent systems in our ***,the users are considered as vertices,and their connections/interactions are taken as *** users follow other popular users’profiles in these networks,and some don’t,but those non-followers are connected directly to the popular *** means,along with traditional relationship(information flowing),there is another relation among *** depends on the domination of the relationship between the *** type of situation can be modelled as a directed fuzzy *** the colouring of fuzzy graph theory,edge membership plays a vital *** membership is a representation of flowing information between end nodes of the *** from the communication relationship,there may be some other factors like domination in *** influence of power is captured *** this article,the colouring of directed fuzzy graphs is defined based on the influence of *** with this,the chromatic number and strong chromatic number are provided,and related properties are *** application regarding COVID-19 infection is presented using the colouring of directed fuzzy graphs.

关键词： Graph colouring chromatic index directed fuzzy graphs

来源：评论

学校读者我要写书评

暂无评论

Novel Noise Filter Techniques and Dynamic Ensemble Selection for Classification

引用

Recent Advances in computer science and Communications 2022年第1期15卷 48-59页

作者： Nguyen, Thi Ngoc A. Nhu, Quynh P. Solanki, Vijender K. School of Applied Mathematics and Informatics Hanoi University of Science and Technology Hanoi Viet Nam CMC Institute of Science and Technology 11 Duy Tan Cau Giay Hanoi Viet Nam Department of Computer Science and Engineering CMR Institute of Technology TS Hyderabad India

Background: Ensemble selection is one of the most researched topics for ensemble learning. Researchers have been attracted to selecting a subset of base classifiers that may perform more helpful than the whole ensemble system classifiers. Dynamic Ensemble Selection (DES) is one of the most effective techniques in classification problems. DES systems select the most appropriate classifiers from the candidate classifier pool. Ensemble models that balance diversity and accuracy in the training process improve performance than the whole classifiers. Objective: In this paper, novel techniques are proposed by combining Noise Filter (NF) and Dynamic Ensemble System (DES) to have better predictive accuracy. In other words, a noise filter and DES make the data cleaner and DES improves the performance of classification. Methods: The proposed NF-DES model, which was demonstrated on twelve datasets, especially has three credit scoring datasets and a performance measure accuracy. Results: The results show that our proposed model is better than other models. Conclusion: The novel noise filer and dynamic ensemble learning with the aim to improve the classification ability are presented. To improve the performance of classification, noise filter with dynamic ensemble learning makes the noise data toward the correct class. Then, novel dynamic ensemble learning chooses the appropriate subset classifiers in the pool of base classifiers. © 2022 Bentham science Publishers.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

DeepONet: Learning the sound propagation in 1D with parameterized sources using deep learning for approximating the wave equation operators 24

DeepONet: Learning the sound propagation in 1D with paramete...

引用

24th International Congress on Acoustics, ICA 2022

作者： Borrel-Jensen, Nikolas Engsig-Karup, Allan P. Jeong, Cheol-Ho Technical University of Denmark Department of Electrical and Photonics Engineering Denmark Technical University of Denmark Department of Applied Mathematics and Computer Science Denmark

Realistic acoustics for virtual environments – such as computer games and mixed reality – is essential to achieve an immersive user experience and is getting more attention these years. Numerical methods have traditionally been used for calculating the sound propagation off-line;however, when solving for moving sources, these methods quickly get intractable both from a calculation time and storage viewpoint. Therefore, we propose a novel approach, where the wave equation operators (contrary to functions) are learned for arbitrary source inputs. The DeepONet architecture is used, as it is a general framework having already demonstrated its capability to approximate operators in other applications. As a result, an efficient surrogate model handling impedance boundaries in 1-D is learned. We present results of a model showing errors below 2%, executes in milliseconds and can be trained in less than 5 minutes, leaving optimistic expectations for extending the method to more complex 3-D scenes. © 2022 Proceedings of the International Congress on Acoustics. All rights reserved.

关键词： computer games

来源：评论

学校读者我要写书评

暂无评论

Gaussian Support Vector Machine Algorithm Based Air Pollution Prediction

引用

computers, Materials & Continua 2022年第4期71卷 683-695页

作者： K.S.Bhuvaneshwari J.Uma K.Venkatachalam Mehedi Masud Mohamed Abouhawwash T.Logeswaran Department of Computer Sceince and Engineering Karpagam College of EngineeringCoimbatore641032India Department of Electrical and Electronics Engineering M.Kumarasamy College of EngineeringKarur639113India Department of Applied Cybernetics Faculty of ScienceUniversity of Hradec KrálovéHradec Králové50003Czech Republic Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Electrical and Electronics Engineering Kongu Engineering CollegeErode638060India

Air pollution is one of the major concerns considering detriments to human *** type of pollution leads to several health problems for humans,such as asthma,heart issues,skin diseases,bronchitis,lung cancer,and throat and eye *** pollution also poses serious issues to the *** from the vehicle industry is the cause of greenhouse effect and CO2 ***,real-time monitoring of air pollution in these areas will help local authorities to analyze the current situation of the city and take necessary *** monitoring process has become efficient and dynamic with the advancement of the Internet of things and wireless sensor *** is the main issue in WSNs;if the sensor node location is unknown,then coverage and power and routing are not *** study concentrates on localization-based air pollution prediction systems for real-time monitoring of smart *** systems comprise two phases considering the prediction as heavy or light traffic area using the Gaussian support vector machine algorithm based on the air pollutants,such as PM2.5 particulate matter,PM10,nitrogen dioxide(NO2),carbon monoxide(CO),ozone(O3),and sulfur dioxide(SO2).The sensor nodes are localized on the basis of the predicted area using the meta-heuristic algorithms called fast correlation-based elephant herding *** dataset is divided into training and testing parts based on 10 *** evaluation on predicting the air pollutant for localization is performed with the training *** error prediction in localizing nodes is 9.83 which is lesser than existing solutions and accuracy is 95%.

关键词： Air pollution monitoring air pollutant SVM Gaussian EHO fast correlation WSN localization

来源：评论

学校读者我要写书评

暂无评论

Construction and application of high-quality genome-scale metabolic model of Zymomonas mobilis to guide rational design of microbial cell factories

引用

Synthetic and Systems Biotechnology 2023年第3期8卷 498-508页

作者： Yalun Wu Qianqian Yuan Yongfu Yang Defei Liu Shihui Yang Hongwu Ma State Key Laboratory of Biocatalysis and Enzyme Engineering School of Life SciencesHubei UniversityWuhan430062HubeiChina Biodesign Center Key Laboratory of Systems Microbial BiotechnologyTianjin Institute of Industrial BiotechnologyChinese Academy of SciencesTianjin300308China Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and StatisticsHubei UniversityWuhan430062HubeiChina Artificial Intelligence and Knowledge Engineering Lab School of Computer Science and Information EngineeringHubei UniversityWuhan430062HubeiChina

High-quality genome-scale metabolic models(GEMs)could play critical roles on rational design of microbial cell factories in the classical Design-Build-Test-Learn cycle of synthetic biology *** of the constant establishment and update of GEMs for model microorganisms such as Escherichia coli and Saccharomyces cerevisiae,high-quality GEMs for non-model industrial microorganisms are still *** mobilis *** ZM4 is a non-model ethanologenic microorganism with many excellent industrial characteristics that has been developing as microbial cell factories for biochemical *** five GEMs of *** have been constructed,these models are either generating ATP incorrectly,or lacking information of plasmid genes,or not providing standard format *** this study,a high-quality GEM iZM516 of *** ZM4 was *** information from the improved genome annotation,literature,datasets of Biolog Phenotype Microarray studies,and recently updated Gene-Protein-Reaction information was combined for the curation of ***,516 genes,1389 reactions,1437 metabolites,and 3 cell compartments are included in iZM516,which also had the highest MEMOTE score of 91%among all published GEMs of *** growth was then predicted by iZM516,which had 79.4%agreement with the experimental results of the substrate *** addition,the potential endogenous succinate synthesis pathway of *** ZM4 was proposed through simulation and analysis using ***,metabolic engineering strategies to produce succinate and 1,4-butanediol(1,4-BDO)were designed and then simulated under anaerobic condition using *** results indicated that 1.68 mol/mol succinate and 1.07 mol/mol 1,4-BDO can be achieved through combinational metabolic engineering strategies,which was comparable to that of the model species *** study thus not only established a high-quality GEM iZM516 to help understand and design microbial cell fac

关键词： Genome-scale metabolic models(GEMSs) Non-model industrial microorganism Zymomonas mobilis Biolog phenotype microarray Succinate 1,4-Butanediol

来源：评论

学校读者我要写书评

暂无评论

Dermatological Diagnostics: A Unified Deep Learning Framework for Skin Lesion and Cancer Classification 1

Dermatological Diagnostics: A Unified Deep Learning Framewor...

引用

1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Kumar, Vinod Jain, Isha Dongla, Durga Sritha Rai, Shivangi Rastogi, Vani Kaushik, Eva Kaushik, Rohit George Washington University School of Engineering and Applied Science WashingtonDC United States Dr. Akhilesh Das Gupta Institute of Technology and Management Computer Science and Engineering Department New Delhi India Gandhi Institute of Technology and Management Computer Science and Engineering Department Andhra Pradesh Visakhapatnam India Data Scientist DXC Technology Noida India Data Analytics Program University of Illinois CS and Mathematics Department Springfield United States

ISBN: (纸本)9798350356816

Skin pathologies encompass a spectrum of conditions, with malignancies such as melanoma representing a critical diagnostic urgency. This investigation delineates the deployment of Convolutional Neural Networks (CNNs) for the classification of dermatological anomalies, benchmarking CNN diagnostic fidelity against dermatological expert evaluations. The study underscores the efficacy of CNN classifiers in expediting the diagnostic workflow for various cutaneous disorders. Advocating for an automated diagnostic framework, the research introduces a CNN-based system aimed at reducing human diagnostic load, accelerating diagnostic timelines, and enhancing survival outcomes. Utilizing advanced image processing algorithms and deep learning architectures, the research presents an automated classification system for skin pathologies, addressing both benign and malignant presentations. The classification matrix includes nine dermatological conditions: actinic keratosis, basal cell carcinoma, benign keratosis, dermatofibroma, melanoma, nevus, seborrheic keratosis, squamous cell carcinoma, and vascular lesions. The objective is to engineer a CNN model with robust diagnostic performance across a diverse lesion dataset, ensuring accurate identification and categorization of dermatological conditions. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Evaluation of State-of-the-Art Deep Learning Models for Road Surface Type Classification

引用

Intelligent Automation & Soft Computing 2023年第8期37卷 1275-1291页

作者： Narit Hnoohom Sakorn Mekruksavanich Anuchit Jitpattanakul Image Information and Intelligence Laboratory Department of Computer EngineeringFaculty of EngineeringMahidol UniversityNakhon Pathom73170Thailand Department of Computer Engineering School of Information and Communication TechnologyUniversity of PhayaoPhayao56000Thailand Department of Mathematics Faculty of Applied ScienceKing Mongkut’s University of Technology North BangkokBangkok10800Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research InstituteKing Mongkut’s University of Technology North BangkokBangkok10800Thailand

In recent years,as intelligent transportation systems(ITS)such as autonomous driving and advanced driver-assistance systems have become more popular,there has been a rise in the need for different sources of traffic situation *** classification of the road surface type,also known as the RST,is among the most essential of these situational data and can be utilized across the entirety of the ITS ***,the benefits of deep learning(DL)approaches for sensor-based RST classification have been demonstrated by automatic feature extraction without manual *** ability to extract important features is vital in making RST classification more *** work investigates the most recent advances in DL algorithms for sensor-based RST classification and explores appropriate feature extraction *** used different convolutional neural networks to understand the functional architecture better;we constructed an enhanced DL model called SE-ResNet,which uses residual connections and squeeze-and-excitation mod-ules to improve the classification *** experiments with a publicly available benchmark dataset,the passive vehicular sensors dataset,have shown that SE-ResNet outperforms other state-of-the-art *** proposed model achieved the highest accuracy of 98.41%and the highest F1-score of 98.19%when classifying surfaces into segments of dirt,cobblestone,or asphalt ***,the proposed model significantly outperforms DL networks(CNN,LSTM,and CNN-LSTM).The proposed RE-ResNet achieved the classification accuracies of asphalt roads at 98.98,cobblestone roads at 97.02,and dirt roads at 99.56%,respectively.

关键词： Road surface type classification deep learning inertial sensor deep pyramidal residual network squeeze-and-excitation module

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：