检索结果-内蒙古大学图书馆

A Novel Krill Herd Based Random Forest Algorithm for Monitoring Patient Health

Computers, Materials & Continua 2023年第5期75卷 4553-4571页

作者： Md.Moddassir Alam Md Mottahir Alam Muhammad Moinuddin Mohammad Tauheed Ahmad Jabir Hakami Anis Ahmad Chaudhary Asif Irshad Khan Tauheed Khan Mohd Department of Health Information Management and Technology University of Hafr Al-BatinSaudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing AbdulazizJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems King Abdul Aziz UniversityJeddahSaudi Arabia College of Medicine King Khalid UniversityAbhaSaudi Arabia Department of Physics College of ScienceJazan UniversityP.O.Box.114Jazan45142Saudi Arabia Department of Biology College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11623Saudi Arabia Computer Science Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Math and Computer Science Augustana CollegeIL61201United States

Artificial Intelligence(AI)is finding increasing application in healthcare *** learning systems are utilized for monitoring patient health through the use of IoT sensor,which keep track of the physiological state by way of various health ***,early detection of any disease or derangement can aid doctors in saving patients’***,there are some challenges associated with predicting health status using the common algorithms,such as time requirements,chances of errors,and improper *** propose an Artificial Krill Herd based on the Random Forest(AKHRF)technique for monitoring patients’health and eliciting an optimal prescription based on their health *** begin with,various patient datasets were collected and trained into the system using IoT *** a result,the framework developed includes four processes:preprocessing,feature extraction,classification,and result ***,preprocessing removes errors,noise,and missing values from the dataset,whereas feature extraction extracts the relevant ***,in the classification layer,we updated the fitness function of the krill herd to classify the patient’s health status and also generate a *** found that the results fromthe proposed framework are comparable to the results from other state-of-the-art techniques in terms of sensitivity,specificity,Area under the Curve(AUC),accuracy,precision,recall,and F-measure.

关键词： Healthcare system health monitoring clinical decision support internet of things artificial intelligence machine learning diagnosis

来源：评论

学校读者我要写书评

暂无评论

An Intellectual Fusion Classification Prototypical for an Imbalanced Electrocardiogram data

引用

SN Computer science 2023年第6期4卷 721页

作者： Ruth Isabels, K. Mrudula Devi, K. Anand, R. Athe, Ramesh Chowdhury, Sumit Singha Pund, Sachin S. Department of Mathematics Saveetha Engineering College (Autonomous) Chennai India BS&H Vignans Institute of Information Technology (A) Visakhapatnam India Department of MCA Acharya Institute of Technology Bangalore India Data Science and Intelligent Systems Indian Institute of Information Technology Dharwad Dharwad India Acharya Institute of Technology Bangalore India Department of Industrial Engineering Shri Ramdeobaba College of Engineering and Management Maharashtra Nagpur India

One of the greatest threats posed by progress around the world is cardiovascular diseases (CVD). Each year, CVD accounts for the vast majority of deaths worldwide. The vast majority of people who die from CVD do so suddenly, and their families have no hope of getting them medical help in time. Because of this, there is a pressing need for a real-time, intelligent system that can keep tabs on cardiac patients round the clock. Internet of Things (IoT)-enabled systems are a viable choice for real-time data monitoring. Internet-based smart healthcare has several potential uses, including monitoring physiological data, such as electrocardiograms (ECGs), heart rates (HRs), blood pressures (BPs), and more. IoT-based smart healthcare paradigms present significant issues, not the least of which is selecting the suitable model. This research proposes a heart rate sensor and a sophisticated hybrid classification algorithm as components of an IoT-based electrocardiogram (ECG) monitoring system. The goal of this study is to aid in the development of an automated key for social happiness by creating an intelligent hybrid classification model that can handle the class imbalance problem with more precision. No matter what validation criterion was used (twofold, fivefold, or tenfold cross-validation), the results of the empirical evaluation showed that the proposed hybrid model achieved better outcomes than the additional ingrained classification models in terms of accuracy and efficiency for both classes. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： BP CVD ECG HR IoT

来源：评论

学校读者我要写书评

暂无评论

Wind-Robust Sea-Ice Discrimination from Sentinel-1 Texture Features

Wind-Robust Sea-Ice Discrimination from Sentinel-1 Texture F...

引用

Iranian Conference on Electrical engineering (ICEE)

作者： Parsa Shamsaddini Ahmad Keshavarz Stefano Zecchetto Electrical Engineering Department Faculty of Intelligent Systems Engineering and Data Science Persian Gulf university Bushehr Iran Istituto di Scienze Polari Consiglio Nazionale delle Ricerche & Persian Gulf university Padova Italy

Sea and ice discrimination and classification in the polar regions from satellite data gained importance in remote sensing and geosciences, essentially because of the undergoing climate change. Synthetic Aperture Radar (SAR) is one of the best instruments in remote sensing for sea-ice discrimination at high spatial resolution (hundreds of m), because it provides images day and night with whatever cloud coverage. The available ice masks are generally at spatial resolution of km, thus not fully suitable to be used with SAR images. This study is to discriminate sea and ice in high resolution (250 m) with good accuracy. The proposed methodology uses fuzzy c-mean clustering on selected Gray Level Co-occurrence Matrix (GLCM) features which are robust against the wind. The obtained results show the proposed method discriminates the ice from sea with the existence of wind.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Exploring the IT’s Needs in Morocco Using Online Job Ads

Exploring the IT’s Needs in Morocco Using Online Job Ads

引用

International Symposium on Automatic Control and Emerging Technologies, ACET 2023

作者： Sellamy, Khadija El Farouki, Mohamed Sabri, Zineb Nouib, Hamza Qostal, Aniss Fakhri, Youssef Moumen, Aniss Laboratory of Research in Computer Science Faculty of Sciences University Ibn Tofail Kenitra Morocco Laboratory of Research Intelligent Processing and Security of Systems University Mohammed V Rabat Morocco Laboratory of Systems Engineering ENSA of Kenitra University Ibn Tofail Kenitra Morocco S.I.G.E.R Laboratory FST Sidi Mohamed Ben Abdellah University Fez Morocco

ISBN: (纸本)9789819701254

Researchers have the opportunity to better understand the labor market and its needs as job offers/advertisements become more accessible. This study aims to better understand the expectations of employers in the IT sector by collecting and analyzing the data becoming job offers posted on job search websites in Morocco. In this work, we used multiple techniques of Text Mining and machine learning, for the scraping and the analysis of the offers. This sector is explored to draw descriptive and statistical conclusions related to the demand like Job titles, Required Skills, Years of Education, Experience, Contract type, Natural Languages, Telecommuting. And which are beneficial for several actors (job seekers, researchers, trainers, students, etc.) with the aim of better decision-making. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Commerce

来源：评论

学校读者我要写书评

暂无评论

Virtual Plant Based Training: Exploring Innovative Educational Mode for Agriculture 4

Virtual Plant Based Training: Exploring Innovative Education...

引用

4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Wang, Haoyu Wang, Xiujuan Hua, Jing Wang, Zhaoxun Shao, Zede Kang, Mengzhen Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multi Modal Artificial Intelligence Systems Beijing China Shandong Xingke Intelligent Technology Co. Ltd Jinan China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automatio Beijing China Macau University of Science and Technology Faculty of Innovation Engineering China

ISBN: (纸本)9798350349252

Traditional agricultural education mainly relies on text and images, while the teaching of smart agriculture requires new technologies. With the development of virtual reality technology, the training and teaching mode based on plant and environmental modelling are gradually becoming an innovative practice in the field of agricultural education. Based on GreenLab model and an interactive interface, a training software for uderstanding plant behaviour has been developed for the training of agricultural colleges and universities. By analysing the application of computational plant, this paper discusses how this mode can improve learning efficiency, enhance students' practical ability, and provide new ideas and methods for agricultural education. © 2024 IEEE.

关键词： Virtual environments

来源：评论

学校读者我要写书评

暂无评论

Neutrosophic Generalized Rayleigh Distribution with Application

引用

Neutrosophic Sets and systems 2023年 58卷 248-262页

作者： Norouzirad, Mina Rao, Gadde Srinivasa Mazarei, Danial FCT NOVA Portugal Department of Mathematics and Statistics The University of Dodoma PO. Box: 259 Dodoma Tanzania United Republic of Department of Statistics Faculty of Intelligent Systems Engineering and Data Science Persian Gulf University Bushehr Iran

In this paper, we consider the neutrosophic generalized Rayleigh distribution (NGRD). Various neutrosophic properties of NGRD are developed and discussed. The developed distribution is specifically more useful to model indeterminate data which are skewed lifetime data. Also, the neutrosophic parameters are estimated using the well-known method of maximum likelihood (ML) estimation based on a neutrosophic environment. A simulation study is carried out to establish the achievement of the estimated neutrosophic parameters. As a final point, the proposed NGRD applications in the real world have been discussed with the help of real data. A comparative studies also carried out with some recent proposed neutrosophic distributions. © (2023). All Rights Reserved.

关键词： Maximum likelihood estimation

来源：评论

学校读者我要写书评

暂无评论

An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

引用

Computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： Walid El-Shafai Noha A.El-Hag Ahmed Sedik Ghada Elbanby Fathi E.Abd El-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.Abdel Samea Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and *** learning provides a high performance for several medical image analysis *** paper proposes a deep learning model for the medical image fusion *** model depends on Convolutional Neural Network(CNN).The basic idea of the proposed model is to extract features from both CT and MR ***,an additional process is executed on the extracted *** that,the fused feature map is reconstructed to obtain the resulting fused ***,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement *** realistic datasets of different modalities and diseases are tested and ***,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis

来源：评论

学校读者我要写书评

暂无评论

Detection of Alzheimer’s Disease progression from Structural MRIs using ConvMixer based Deep Learning Model

引用

Procedia Computer science 2025年 258卷 420-429页

作者： Mahak Lashkary Kanika Bansal Samyak Jain Praveen Kumar Shukla Hitesh Tekchandani Vijaypal Singh Dhaka School of Computing and Intelligent Systems Manipal University Jaipur Jaipur-303007 Rajasthan India School of Computer Science and Engineering Manipal University Jaipur Jaipur-303007 Rajasthan India Department of artificial Intelligence and Data Science Koneru Lakshmaiah Education Foundation Hyderabad-500075 Telangana India

Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder that significantly impacts cognitive functions and quality of life. Affecting over 50 million people worldwide, early and accurate detection of AD progression is crucial for timely intervention and management. This paper presents a reliable method for classifying Alzheimer’s stages using Deep Learning based ConvMixer model on structural MRI data. The proposed deep learning based convmixer model significantly utilizes the patch based learning with depthwise separable convolution to achieve improved performance. The dataset used in this work has been extracted from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and comprises of three classes: Alzheimer’s Disease (AD), Cognitive Impairment (CI), and Cognitively Normal (CN). The proposed approach demonstrated exceptional performance, achieving an accuracy of 99.88%, specificity of 99.87%, sensitivity of 99.90 and precision of 99.95%. The achieved results demonstrate the proposed model’s accuracy in distinguishing Alzheimer’s stages, making it a promising tool for early diagnosis and disease progression monitoring.

关键词： Alzheimer’s Disease Cognitive Impairment (CI) Cognitively Normal (CN) ConvMixer deep learning structural MRI neuroimaging Classification early detection machine learning

来源：评论

学校读者我要写书评

暂无评论

Thermal and mechanical properties of a high-density polyethylene (HDPE) composite reinforced with wood flour

引用

Materials Today: Proceedings 2023年 72卷 3602-3608页

作者： Fatima Ezzahrae, Morchid Nacer, Akkouri Latifa, Elfarissi Abdellah, Zamma Mohamed, Idiri Mustapha, Jammoukh Laboratory of Modeling and Simulation of Intelligent Industrial Systems M2S2I Higher Normal School of Technical Education Mohammedia University of Hassan II Casablanca Mohammedia Morocco Technical Center of Plastics and Rubber CTPC Casablanca Morocco Laboratory of Engineering and Materials LIMAT Faculty of Science Ben M'Sik University of Hassan II Casablanca Casablanca Morocco

To keep up with the rate of growth and global demand, it is necessary to manufacture products with high performance and improved durability. Wood-plastic composites (WPCs) are a rapidly growing class of construction materials formed by mixing wood fibers with a polymer matrix at a high temperature. However, significant technical issues remain, such as low thermal resistance, low water resistance, and limited interfacial contact or compatibility between wood fiber and the polymer matrix, which results in poor adhesion of the wood particles, etc. The structure and properties of the matrix/fiber interface can indeed have an impact on the final properties of the composites. To this end, good interfacial adhesion improves stress transmission from the matrix to the fiber, as well as composite performance. Therefore, chemical modification has been the most effective way to chemically bond the matrix to the filler. In this study, the modification is achieved by using maleic anhydride as a coupling agent which promotes the formation of chemical or material bonds between the wood flour (WF) and the polymer matrix. Three WF/high-density polyethylene (HDPE) composite blends with WF contents of 40%, 50%, and 60% were evaluated for density, flexural properties, hardness test, and thermal analysis. Physical tests showed that increasing the wood content of the composite from 40% to 60% increases the density and hardness of the WPC from 1,047 g/cm3 to 1,097 g/cm3 and from 64.5 to 67.7 respectively. On the other hand, increasing the wood flour content to 60% decreases the flexural strength from 37.524 MPa to 27.512 MPa, while the flexural modulus increases from 2176.125 MPa to 3568.284 MPa. In general, the results indicate that the developed WF/HDPE has suitable mechanical and thermal properties for outdoor applications. © 2022

关键词： High density polyethylenes

来源：评论

学校读者我要写书评

暂无评论

Low Profile UHF Antenna Design for Low Earth-Observation CubeSats

引用

Computers, Materials & Continua 2022年第5期71卷 2533-2542页

作者： Md.Amanath Ullah Touhidul Alam Ali F.Almutairi Mohammad Tariqul Islam School of Electrical and Data Engineering Faculty of Engineering and Information TechnologyUniversity of Technology SydneyUltimo NSW2007Australia Space Science Centre(ANGKASA) Institute of Climate Change(IPI)Universiti Kebangsaan MalaysiaBangi43600SelangorMalaysia Department of CSE International Islamic University Chittagong(IIUC)Chattogram4318Bangladesh Electrical Engineering Department Kuwait University13060KuwaitCityKuwait Department of Electrical Electronic and Systems EngineeringFaculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaBangi43600SelangorMalaysia

This paper reveals a new design of UHF CubeSat antenna based on a modified Planar Inverted F Antenna(PIFA)for CubeSat *** design utilizes a CubeSat face as the ground *** is a gap of 5 mm beneath the radiating element that facilitates the design providing with space for solar *** prototype is fabricated using Aluminum metal sheet and *** antenna achieved resonance at 419 *** of the antenna has been investigated after placing a solar *** properties of solar panels made the resonance shift about 20 *** design addresses the frequency shifting issue after placing the antenna with the CubeSat *** phenomenon has been analyzed considering a typical 1U and 2U CubeSat body with the *** antenna achieved a positive realized gain of 0.7 dB and approximately 78%of efficiency at the resonant frequency with providing 85%of open space for solar irradiance onto the solar panel.

关键词： CubeSat antenna UHF antenna small satellite satellite communication

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：