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International Journal of Modeling Simulation and Scientific Computing最新文献

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EfficientNets Transfer Learning Strategies for Hispathological Breast Cancer Image Analysis 组织病理乳腺癌图像分析的高效网络迁移学习策略
IF 1.2 Q3 Mathematics
International Journal of Modeling Simulation and Scientific Computing
Pub Date : 2023-04-05 DOI: 10.1142/s1793962324410095
S. Folorunso, J. B. Awotunde, Y. P. Rangaiah, R. Ogundokun
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引用次数: 1
Digital twin-driven robotic arm operation simulation and health management research 数字双驱动机械臂操作仿真与健康管理研究
IF 1.2 Q3 Mathematics
International Journal of Modeling Simulation and Scientific Computing
Pub Date : 2023-03-30 DOI: 10.1142/s1793962323410337
Guofang Li, Kang Yang, Zhiyu Dong, Xiao-Qiang Ji, Shaopei Wu
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引用次数: 0
An Extreme Convolutional Network Model for Brain Disease Prediction Using Smote and Learning Approaches 使用Smote和学习方法预测脑疾病的极端卷积网络模型
IF 1.2 Q3 Mathematics
International Journal of Modeling Simulation and Scientific Computing
Pub Date : 2023-03-30 DOI: 10.1142/s1793962324410083
N. Ravinder, Moulana Mohammed
{"title":"An Extreme Convolutional Network Model for Brain Disease Prediction Using Smote and Learning Approaches","authors":"N. Ravinder, Moulana Mohammed","doi":"10.1142/s1793962324410083","DOIUrl":"https://doi.org/10.1142/s1793962324410083","url":null,"abstract":"","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84533800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Modeling and Simulation of Stochastic Transients in Power Systems Based on Frequency Shifting Theory 基于移频理论的电力系统随机暂态建模与仿真
IF 1.2 Q3 Mathematics
International Journal of Modeling Simulation and Scientific Computing
Pub Date : 2023-03-23 DOI: 10.1142/s1793962324500144
Peng Zhao, Yue Xia, Zhikai You, Yu Hu
{"title":"Modeling and Simulation of Stochastic Transients in Power Systems Based on Frequency Shifting Theory","authors":"Peng Zhao, Yue Xia, Zhikai You, Yu Hu","doi":"10.1142/s1793962324500144","DOIUrl":"https://doi.org/10.1142/s1793962324500144","url":null,"abstract":"","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75280857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Fusified Model for Soft Tissue Prediction Using a Knowledge-Based Deep Learning Approach 基于知识深度学习的软组织预测融合模型
IF 1.2 Q3 Mathematics
International Journal of Modeling Simulation and Scientific Computing
Pub Date : 2023-03-03 DOI: 10.1142/s1793962324410046
Chandra Sekhar Koppireddy, G. Siva Nageswara Rao
{"title":"A Fusified Model for Soft Tissue Prediction Using a Knowledge-Based Deep Learning Approach","authors":"Chandra Sekhar Koppireddy, G. Siva Nageswara Rao","doi":"10.1142/s1793962324410046","DOIUrl":"https://doi.org/10.1142/s1793962324410046","url":null,"abstract":"","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76380608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Croup Disease Classification Using VGG19 and Resnet 50 Transfer Learning Method 基于VGG19和Resnet 50迁移学习方法的群体疾病分类
IF 1.2 Q3 Mathematics
International Journal of Modeling Simulation and Scientific Computing
Pub Date : 2023-03-03 DOI: 10.1142/s1793962324410071
E. Vetrimani, M. Aruselvi
Detection of any disease in the early stage can save a life. There are many medical imaging modalities like MRI, FMRI, ultrasound, CT, and X-ray used in the detection of disease. In the last decades, neural network-based methods are effective in detecting and classifying the disease based on abnormalities present in the medical images. Acute laryngotracheobronchitis (croup) is one of the common diseases seen in children among the 0.5-3 years age group which infects the respiratory system that can cause the larynx, trachea, and bronchi. Prior detection can lower the risk of spreading and can be treated accurately by a pediatrician. Commonly this infection can be diagnosed though physical examination. But due to the similarity of Covid-19 symptoms urges the physicians to get accurate detection of this disease using X-ray and CT images of the infant's chest and throat. The proposed work aims to develop a croup diagnose system (CDS) which identify the Croup infection through post anterior (PA) view of pediatric X-ray using deep learning algorithm. We used the well-known transfer learning algorithm VGG19 and ResNet50. Data augmentation being adapted for reducing the overfitting and to improve the quantity of image samples. We show that the proposed transfer learning based CDS method can be used to classify the X-ray images into two classes namely, croup and normal. The experiment results confirm that VGG19 performs better than ResNet50 with promising classification accuracy (90.91%.). The results show that the proposed CDS models can be used for more pediatric medical image classification problem. © 2024 World Scientific Publishing Company.
在早期阶段发现任何疾病都可以挽救生命。有许多医学成像方式，如MRI, FMRI，超声，CT和x射线用于疾病的检测。在过去的几十年里，基于神经网络的方法在基于医学图像中存在的异常来检测和分类疾病方面是有效的。急性喉气管支气管炎(群)是0.5-3岁儿童的常见病之一，主要感染呼吸系统，可引起喉、气管和支气管病变。事先检测可以降低传播的风险，并且可以由儿科医生进行准确的治疗。通常这种感染可以通过体格检查来诊断。但由于Covid-19症状的相似性，敦促医生使用婴儿胸部和喉咙的x射线和CT图像来准确检测这种疾病。提出的工作旨在开发一个群体诊断系统(CDS)，该系统使用深度学习算法通过儿科x射线的前路(PA)视图识别群体感染。我们使用了著名的迁移学习算法VGG19和ResNet50。数据增强适应于减少过拟合和提高图像样本的数量。我们证明了基于迁移学习的CDS方法可以将x射线图像分为群和正态两类。实验结果表明，VGG19的分类准确率达到90.91%，优于ResNet50。结果表明，所提出的CDS模型可用于更多的儿科医学图像分类问题。©2024世界科学出版公司。
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引用次数: 0
Design of a Novel Masking-Based Deep Convolutional Neural Network Approach for Accident Classification 基于掩模的深度卷积神经网络事故分类方法设计
IF 1.2 Q3 Mathematics
International Journal of Modeling Simulation and Scientific Computing
Pub Date : 2023-03-03 DOI: 10.1142/s179396232441006x
V. Raviteja Kanakala, K. Jagan Mohan, V. Krishna Reddy
{"title":"Design of a Novel Masking-Based Deep Convolutional Neural Network Approach for Accident Classification","authors":"V. Raviteja Kanakala, K. Jagan Mohan, V. Krishna Reddy","doi":"10.1142/s179396232441006x","DOIUrl":"https://doi.org/10.1142/s179396232441006x","url":null,"abstract":"","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89764181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Design of an Efficient Graph-Based Traversing Method for Establishing Authentication Mechanism in Cloud 一种高效的基于图的云环境下认证机制的遍历方法设计
IF 1.2 Q3 Mathematics
International Journal of Modeling Simulation and Scientific Computing
Pub Date : 2023-03-03 DOI: 10.1142/s1793962324410058
P. Nagesh, N. Srinivasu
{"title":"Design of an Efficient Graph-Based Traversing Method for Establishing Authentication Mechanism in Cloud","authors":"P. Nagesh, N. Srinivasu","doi":"10.1142/s1793962324410058","DOIUrl":"https://doi.org/10.1142/s1793962324410058","url":null,"abstract":"","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90038865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Breast Cancer Detection from Histopathological image Dataset Using Hybrid Convolution Neural Network 基于混合卷积神经网络的组织病理图像数据集乳腺癌检测
IF 1.2 Q3 Mathematics
International Journal of Modeling Simulation and Scientific Computing
Pub Date : 2023-02-18 DOI: 10.1142/s1793962324410034
Nalini Sampath, N. K. Srinath
{"title":"Breast Cancer Detection from Histopathological image Dataset Using Hybrid Convolution Neural Network","authors":"Nalini Sampath, N. K. Srinath","doi":"10.1142/s1793962324410034","DOIUrl":"https://doi.org/10.1142/s1793962324410034","url":null,"abstract":"","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80641834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
An efficient pure meshless method for phase separation dominated by time fractional Cahn-Hilliard equations 基于时间分数阶Cahn-Hilliard方程的一种高效纯无网格相分离方法
IF 1.2 Q3 Mathematics
International Journal of Modeling Simulation and Scientific Computing
Pub Date : 2023-02-16 DOI: 10.1142/s1793962324500120
Weiwei Guo, Yujie Zhen, Tao Jiang
{"title":"An efficient pure meshless method for phase separation dominated by time fractional Cahn-Hilliard equations","authors":"Weiwei Guo, Yujie Zhen, Tao Jiang","doi":"10.1142/s1793962324500120","DOIUrl":"https://doi.org/10.1142/s1793962324500120","url":null,"abstract":"","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79954991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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