检索结果-内蒙古大学图书馆

Empirical Assessment of Bacillus Calmette-Guérin Vaccine to Combat COVID-19

computers, Materials & Continua 2022年第1期70卷 213-231页

作者： Nikita Jain Vedika Gupta Chinmay Chakraborty Agam Madan Deepali Virmani Lorenzo Salas-Morera Laura Garcia-Hernandez Department of Computer Science&Engineering Bharati Vidyapeeth’s College of EngineeringNew Delhi110063India Department of Electronics&Communication Engineering Birla Institute of TechnologyMesra814142India Department of Computer Science&Engineering Bhagwan Parshuram Institute of TechnologyNew Delhi110063India Area of Project Engineering University of CórdobaCórdoba14071Spain

COVID-19 has become one of the critical health issues globally,which surfaced first in latter part of the year *** is the topmost concern for many nations’governments as the contagious virus started mushrooming over adjacent regions of infected *** 1980,a vaccine called Bacillus Calmette-Guérin(BCG)was introduced for preventing tuberculosis and lung *** that have made the BCG vaccine mandatory have witnessed a lesser COVID-19 fatality rate than the countries that have not made it *** paper’s initial research shows that the countries with a longtermcompulsory BCGvaccination system are less affected by COVID-19 than those without a BCG vaccination *** paper discusses analytical data patterns for medical applications regarding COVID-19 impact on countries with mandatory BCG status on fatality *** paper has tackled numerous analytical challenges to realize the full potential of heterogeneous *** analogy is drawn to demonstrate how other factors can affect fatality and infection rates other than BCG vaccination only,such as age groups affected,other diseases,and stringency *** data of Spain,Portugal,and Germany have been taken for a case study of BCG impact analysis.

关键词： Bacillus Calmette-Guérin COVID-19 fatality rate lockdown gross domestic product vaccine

来源：评论

学校读者我要写书评

暂无评论

Resource Based Automatic Calibration System (RBACS) Using Kubernetes Framework

引用

Intelligent Automation & Soft Computing 2023年第1期35卷 1165-1179页

作者： Tahir Alyas Nadia Tabassum Muhammad Waseem Iqbal Abdullah S.Alshahrani Ahmed Alghamdi Syed Khuram Shahzad Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science&IT Virtual University of PakistanLahore54000Pakistan Department of Software Engineering The Superior UniversityLahore54000Pakistan Department of Computer Science&Artificial Intelligence College of Computer Science&EngineeringUniversity of Jeddah21493Saudi Arabia Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Informatics&Systems University of Management&TechnologyLahore54000Pakistan

Kubernetes,a container orchestrator for cloud-deployed applications,allows the application provider to scale automatically to match thefluctuating intensity of processing *** cluster technology is used to encapsulate,isolate,and deploy applications,addressing the issue of low system reliability due to interlocking ***-based platforms usually entail users define application resource supplies for eco container *** is a constant problem of over-service in data centers for cloud service *** operating costs and incompetent resource utilization can occur in a waste of *** revolutionized the orchestration of the container in the cloud-native *** can adaptively manage resources and schedule containers,which provide real-time status of the cluster at runtime without the user’s *** clusters face unpredictable traffic,and the cluster performs manual expansion configuration by the *** to operational delays,the system will become unstable,and the service will be *** work proposed an RBACS that vigorously amended the distribution of containers operating in the entire Kubernetes *** allocation pattern is analyzed with the Kubernetes *** estimate the overall cost of RBACS,we use several scientific benchmarks comparing the accomplishment of container to remote node migration and on-site *** experiments ran on the simulations to show the method’s effectiveness yielded high precision in the real-time deployment of resources in eco *** to the default baseline,Kubernetes results in much fewer dropped requests with only slightly more supplied resources.

关键词： Docker container virtualization cloud resource kubernetes

来源：评论

学校读者我要写书评

暂无评论

Hybrid Bacterial Foraging Optimization with Sparse Autoencoder for Energy Systems

引用

computer Systems science & engineering 2023年第4期45卷 701-714页

作者： Helen Josephine V L Ramchand Vedaiyan V.M.Arul Xavier Joy Winston J A.Jegatheesan D.Lakshmi Joshua Samuel Raj Business Analytics School of Business and ManagementChrist UniversityBangalore560029India Department of Computer Science and IT School of SciencesJain Deemed to be UniversityBangalore560027India Department of Computer Science and Engineering Karunya Institute of Technology and SciencesCoimbatore641114India College of Computer Studies University of Technology Bahrain18041Bahrain Institute of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai602105India Department of Computer Science and Engineering Panimalar Institute of TechnologyChennai600123India Department of Information Science&Engineering CMR Institute of TechnologyBengaluru560037India

The Internet of Things(IoT)technologies has gained significant interest in the design of smart grids(SGs).The increasing amount of distributed generations,maturity of existing grid infrastructures,and demand network transformation have received maximum *** essential energy storing model mostly the electrical energy stored methods are developing as the diagnoses for its procedure was becoming further *** dynamic electrical energy stored model using Electric Vehicles(EVs)is comparatively standard because of its excellent electrical property and flexibility however the chance of damage to its battery was there in event of overcharging or deep discharging and its mass penetration deeply influences the *** paper offers a new Hybridization of Bacterial foraging optimization with Sparse Autoencoder(HBFOA-SAE)model for IoT Enabled energy *** proposed HBFOA-SAE model majorly intends to effectually estimate the state of charge(SOC)values in the IoT based energy *** accomplish this,the SAE technique was executed to proper determination of the SOC values in the energy ***,for improving the performance of the SOC estimation process,the HBFOA is *** addition,the HBFOA technique is derived by the integration of the hill climbing(HC)concepts with the BFOA to improve the overall *** ensuring better outcomes for the HBFOA-SAE model,a comprehensive set of simulations were performed and the outcomes are inspected under several *** experimental results reported the supremacy of the HBFOA-SAE model over the recent state of art approaches.

关键词： Internet of things energy systems state of charge estimation machine learning deep learning metaheuristics

来源：评论

学校读者我要写书评

暂无评论

Leveraging EfficientNetB3 in a Deep Learning Framework for High-Accuracy MRI Tumor Classification

引用

computers, Materials & Continua 2024年第10期81卷 867-883页

作者： Mahesh Thyluru Ramakrishna Kuppusamy Pothanaicker Padma Selvaraj Surbhi Bhatia Khan Vinoth Kumar Venkatesan Saeed Alzahrani Mohammad Alojail Department of Computer Science&Engineering Faculty of Engineering and TechnologyJAIN(Deemed-to-be University)Bengaluru562112India School of Computer Science and Engineering VIT-AP UniversityAmaravati522241India Department of Computer Science&Technology Madanapalle Institute of Technology&ScienceMadanapalle517325India School of Science Engineering and EnvironmentUniversity of SalfordManchesterM54WTUK School of Computer Science Engineering&Information Systems(SCORE) Vellore Institute of Technology(VIT)Vellore632014India Management Information System Department College of Business AdministrationKing Saud UniversityRiyadh11531Saudi Arabia Adjunct Research Faculty Centre for Research Impact&OutcomeChitkara UniversityRajpuraPunjab140401India

Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient *** different types of brain tumors,including gliomas,meningiomas,pituitary tumors,as well as confirming the absence of tumors,poses a significant challenge using MRI *** approaches predominantly rely on traditional machine learning and basic deep learning methods for image *** methods often rely on manual feature extraction and basic convolutional neural networks(CNNs).The limitations include inadequate accuracy,poor generalization of new data,and limited ability to manage the high variability in MRI *** the EfficientNetB3 architecture,this study presents a groundbreaking approach in the computational engineering domain,enhancing MRI-based brain tumor *** approach highlights a major advancement in employing sophisticated machine learning techniques within computer science and engineering,showcasing a highly accurate framework with significant potential for healthcare *** model achieves an outstanding 99%accuracy,exhibiting balanced precision,recall,and F1-scores across all tumor types,as detailed in the classification *** successful implementation demonstrates the model’s potential as an essential tool for diagnosing and classifying brain tumors,marking a notable improvement over current *** integration of such advanced computational techniques in medical diagnostics can significantly enhance accuracy and efficiency,paving the way for wider *** research highlights the revolutionary impact of deep learning technologies in improving diagnostic processes and patient outcomes in neuro-oncology.

关键词： Deep learning MRI brain tumor cassification EfficientNetB3 computational engineering healthcare technology artificial intelligence in medical imaging tumor segmentation neuro-oncology

来源：评论

学校读者我要写书评

暂无评论

Crafting chirality in three dimensions via a novel fabrication technique for bound states in the continuum metasurfaces

引用

Light(science & Applications) 2024年第3期13卷 390-392页

作者： Zaid Haddadin Anna My Nguyen Lisa V.Poulikakos Department of Electrical&Computer Engineering University of California San DiegoLa JollaCAUSA Department of Mechanical&Aerospace Engineering University of California San DiegoLa JollaCAUSA Program of Materials Science&Engineering University of California San DiegoLa JollaCAUSA

An additional deposition step was added to a multi-step electron beam lithographic fabrication process to unlock the height dimension as an accessible parameter for resonators comprising unit cells of quasi-bound stat... 详细信息

关键词： dimensions dimension intrinsic

来源：评论

学校读者我要写书评

暂无评论

Cryptomining Malware Detection Based on Edge Computing-Oriented Multi-Modal Features Deep Learning

引用

China Communications 2022年第2期19卷 174-185页

作者： Wenjuan Lian Guoqing Nie Yanyan Kang Bin Jia Yang Zhang College of Computer Science&Engineering Shandong University of Science and TechnologyQingdaoShandong 266590China College of Foreign Languages Shandong University of Science and TechnologyQingdaoShandong 266590China

In recent years,with the increase in the price of cryptocurrencies,the number of malicious cryptomining software has increased *** their powerful spreading ability,cryptomining malware can unknowingly occupy our resources,harm our interests,and damage more legitimate ***,although current traditional rule-based malware detection methods have a low false alarm rate,they have a relatively low detection rate when faced with a large volume of emerging *** though common machine learning-based or deep learning-based methods have certain ability to learn and detect unknown malware,the characteristics they learn are single and independent,and cannot be learned *** at the above problems,we propose a deep learning model with multi-input of multi-modal features,which can simultaneously accept digital features and image features on different *** model in turn includes parallel learning of three sub-models and ensemble learning of another specific *** four sub-models can be processed in parallel on different devices and can be further applied to edge computing *** model can adaptively learn multi-modal features and output prediction *** detection rate of our model is as high as 97.01%and the false alarm rate is only 0.63%.The experimental results prove the advantage and effectiveness of the proposed method.

关键词： cryptomining malware multi-modal ensemble learning deep learning edge computing

来源：评论

学校读者我要写书评

暂无评论

A Novel Cluster Analysis-Based Crop Dataset Recommendation Method in Precision Farming

引用

computer Systems science & engineering 2023年第9期46卷 3239-3260页

作者： K.R.Naveen Kumar Husam Lahza B.R.Sreenivasa Tawfeeq Shawly Ahmed A.Alsheikhy H.Arunkumar C.R.Nirmala Department of Computer Science&Engineering Bapuji Institute of Engineering&TechnologyDavangereKarnatakaIndia Department of Information Technology Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Information Science&Engineering Bapuji Institute of Engineering&TechnologyDavangereKarnatakaIndia Department of Electrical Engineering Faculty of Engineering at RabighKing Abdulaziz UniversityJeddahSaudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityArarSaudi Arabia

Data mining and analytics involve inspecting and modeling large pre-existing datasets to discover decision-making *** agriculture uses datamining to advance agricultural *** farmers aren’t getting the most out of their land because they don’t use precision *** harvest crops without a well-planned recommendation *** crop production is calculated by combining environmental conditions and management behavior,yielding numerical and categorical *** existing research still needs to address data preprocessing and crop categorization/***,statistical analysis receives less attention,despite producing more accurate and valid *** study was conducted on a dataset about Karnataka state,India,with crops of eight parameters taken into account,namely the minimum amount of fertilizers required,such as nitrogen,phosphorus,potassium,and pH *** research considers rainfall,season,soil type,and temperature parameters to provide precise cultivation recommendations for high *** presented algorithm converts discrete numerals to factors first,then reduces ***,the algorithm generates six datasets,two fromCase-1(dataset withmany numeric variables),two from Case-2(dataset with many categorical variables),and one from Case-3(dataset with reduced factor variables).Finally,the algorithm outputs a class membership allocation based on an extended version of the K-means partitioning method with lambda *** presented work produces mixed-type datasets with precisely categorized crops by organizing data based on environmental conditions,soil nutrients,and ***,the prepared dataset solves the classification problem,leading to a model evaluation that selects the best dataset for precise crop prediction.

关键词： Data mining crop prediction k-prototypes k-means cluster machine learning

来源：评论

学校读者我要写书评

暂无评论

Improved Soil Quality Prediction Model Using Deep Learning for Smart Agriculture Systems

引用

computer Systems science & engineering 2023年第5期45卷 1545-1559页

作者： P.Sumathi V.V.Karthikeyan M.S.Kavitha S.Karthik Department of Information Technology SNS College of EngineeringCoimbatoreTamilnaduIndia Department of Electrical and Electronics Engineering SNS College of TechnologyCoimbatoreTamilnaduIndia Department of Computer Science&Engineering SNS College of TechnologyCoimbatoreTamilnaduIndia

Soil is the major source of infinite lives on Earth and the quality of soil plays significant role on Agriculture practices all ***,the evaluation of soil quality is very important for determining the amount of nutrients that the soil require for proper *** present decade,the application of deep learning models in many fields of research has created greater *** increasing soil data availability of soil data there is a greater demand for the remotely avail open source model,leads to the incorporation of deep learning method to predict the soil *** that concern,this paper proposes a novel model called Improved Soil Quality Prediction Model using Deep Learning(ISQP-DL).The work considers the chemical,physical and biological factors of soil in particular area to estimate the soil ***,pH rating of soil samples has been collected from the soil testing laboratory from which the acidic range has been categorized through soil test and the same data has been taken as input to the Deep Neural Network Regression(DNNR)***,soil nutrient data has been given as second input to the DNNR *** utilizing this data set,the DNNR method is used to evaluate the fertility rate by which the soil quality has been *** training and testing,the model uses Deep Neural Network Regression(DNNR),by utilizing the *** results show that the proposed model is effective for SQP(Soil Quality Prediction Model)with efficient good fitting and generality is enhanced with input features with higher rate of classification *** results show that the proposed model achieves 96.7%of accuracy rate compared with existing models.

关键词： Soil quality classification accuracy deep learning neural network soil features training and testing

来源：评论

学校读者我要写书评

暂无评论

Weather Classification for Autonomous Vehicles under Adverse Conditions Using Multi-Level Knowledge Distillation

引用

computers, Materials & Continua 2024年第12期81卷 4327-4347页

作者： Parthasarathi Manivannan Palaniyappan Sathyaprakash Vaithiyashankar Jayakumar Jayakumar Chandrasekaran Bragadeesh Srinivasan Ananthanarayanan Md Shohel Sayeed School of Computing SASTRA Deemed to be UniversityThanjavur613401India School of Computer science&Engineering Presidency UniversityBengaluru560064India Dr.A.P.J.Abdul Kalam School of Engineering Garden City UniversityBengaluru560049India Independent Researcher OxnardCA 93036USA Faculty of Information Science and Technology Multimedia UniversityMelaka75450Malaysia

Achieving reliable and efficient weather classification for autonomous vehicles is crucial for ensuring safety and operational ***,accurately classifying diverse and complex weather conditions remains a significant *** advanced techniques such as Vision Transformers have been developed,they face key limitations,including high computational costs and limited generalization across varying weather *** challenges present a critical research gap,particularly in applications where scalable and efficient solutions are needed to handle weather phenomena’intricate and dynamic nature in *** address this gap,we propose a Multi-level Knowledge Distillation(MLKD)framework,which leverages the complementary strengths of state-of-the-art pre-trained models to enhance classification performance while minimizing computational ***,we employ ResNet50V2 and EfficientNetV2B3 as teacher models,known for their ability to capture complex image features and distil their knowledge into a custom lightweight Convolutional Neural Network(CNN)student *** framework balances the trade-off between high classification accuracy and efficient resource consumption,ensuring real-time applicability in autonomous *** Response-based Multi-level Knowledge Distillation(R-MLKD)approach effectively transfers rich,high-level feature representations from the teacher models to the student model,allowing the student to perform robustly with significantly fewer parameters and lower computational *** proposed method was evaluated on three public datasets(DAWN,BDD100K,and CITS traffic alerts),each containing seven weather classes with 2000 samples per *** results demonstrate the effectiveness of MLKD,achieving a 97.3%accuracy,which surpasses conventional deep learning *** work improves classification accuracy and tackles the practical challenges of model complexity,resource consumption,and real-time deployment,of

关键词： EfficientNetV2B3 multi-level knowledge distillation RestNet50V2 weather classification

来源：评论

学校读者我要写书评

暂无评论

Automated Deep Learning Based Cardiovascular Disease Diagnosis Using ECG Signals

引用

computer Systems science & engineering 2022年第7期42卷 183-199页

作者： S.Karthik M.Santhosh M.S.Kavitha A.Christopher Paul Department of Computer Science&Engineering SNS College of TechnologyCoimbatore641035India Department of Information Technology Karpagam Institute of TechnologyCoimbatore641105India

Automated biomedical signal processing becomes an essential process to determine the indicators of diseased *** the same time,latest develop-ments of artiﬁcial intelligence(AI)techniques have the ability to manage and ana-lyzing massive amounts of biomedical datasets results in clinical decisions and real time *** can be employed for medical imaging;however,the 1D biomedical signal recognition process is still needing to be ***(ECG)is one of the widely used 1-dimensional biomedical sig-nals,which is used to diagnose cardiovascular *** assisted diag-nostic modelsﬁnd it difﬁcult to automatically classify the 1D ECG signals owing to time-varying dynamics and diverse proﬁles of ECG *** resolve these issues,this study designs automated deep learning based 1D biomedical ECG sig-nal recognition for cardiovascular disease diagnosis(DLECG-CVD)*** DLECG-CVD model involves different stages of operations such as pre-proces-sing,feature extraction,hyperparameter tuning,and classiﬁ*** the initial stage,data pre-processing takes place to convert the ECG report to valuable data and transform it into a compatible format for further *** addition,deep belief network(DBN)model is applied to derive a set of feature ***,improved swallow swarm optimization(ISSO)algorithm is used for the hyper-parameter tuning of the DBN ***,extreme gradient boosting(XGBoost)classiﬁer is employed to allocate proper class labels to the test ECG *** order to verify the improved diagnostic performance of the DLECG-CVD model,a set of simulations is carried out on the benchmark PTB-XL dataset.A detailed comparative study highlighted the betterment of the DLECG-CVD model interms of accuracy,sensitivity,speciﬁcity,kappa,Mathew correlation coefﬁcient,and Hamming loss.

关键词： Biomedical signals 1-dimensional signal electrocardiogram artiﬁcial intelligence deep learning cardiovascular disease decision making

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：