Mansoura Engineering Journal最新文献

Rehabilitation of existing university buildings to reduce energy consumption through the application of sustainable design standards (Case study of the building of the Modern Academy of Engineering) 通过采用可持续设计标准修复现有大学建筑以降低能耗（现代工程学院建筑案例研究）

Mansoura Engineering Journal Pub Date : 2024-05-22 DOI: 10.58491/2735-4202.3118

Mohamed Mahmoud Hassan

引用次数: 0

Side Lobe Level Reduction and Array Thinning of Concentric Circular Antenna Arrays 同心圆天线阵列的侧叶电平降低和阵列稀化

Mansoura Engineering Journal Pub Date : 2024-01-10 DOI: 10.58491/2735-4202.3129

Alzahraa H. Nosier, Ahmed M. Elkhawaga, Mohamed E. Nasr, Nessim M. Mahmoud, Amr H. Hussein

引用次数: 0

Deep Learning Based Classification of Focal Liver Lesions with 3 and 4 Phase Contrast-Enhanced CT Protocols 基于深度学习的三相位和四相位对比增强 CT 病灶分类法

Mansoura Engineering Journal Pub Date : 2024-01-01 DOI: 10.58491/2735-4202.3185

Ahmed El-Emam, Hossam El-Din Moustafa, Mohamed Moawad, Mohamed Aouf

{"title":"Deep Learning Based Classification of Focal Liver Lesions with 3 and 4 Phase Contrast-Enhanced CT Protocols","authors":"Ahmed El-Emam, Hossam El-Din Moustafa, Mohamed Moawad, Mohamed Aouf","doi":"10.58491/2735-4202.3185","DOIUrl":"https://doi.org/10.58491/2735-4202.3185","url":null,"abstract":"It has been noticed that three-phase and four-phase computed tomography protocols with contrast serve as standard examinations for diagnosing liver tumors. Additionally, many patients require periodic follow-up, which entails signi ﬁ cant radiation exposure for them. Advancements in image processing facilitate automated liver lesion segmentation. However, the challenge remains in classifying these small lesions by doctors, especially when the liver has different types of lesions with very little intensity difference. Therefore, deep learning can be utilized for the classi ﬁ cation of liver lesions. The present work introduces a CNN-based module for the classi ﬁ cation of liver lesions. The module consists of four stages: data acquisition, preprocessing, modeling, and evaluating. The proposed system has achieved an accuracy of 96 and 97% for three-phase and four-phase protocols, respectively. Moreover it has been shown that the three-phase protocol outperforms the four-phase protocol, according to the dose report, with only a 1% loss of accuracy. However, this loss has not altered the multiclassi ﬁ cation process. Thus, a three-phase protocol is recommended as a diagnostic tool for detecting focal liver lesions.","PeriodicalId":510600,"journal":{"name":"Mansoura Engineering Journal","volume":"13 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140519810","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

Application of machine learning models in the capacity prediction of CCFST columns 机器学习模型在 CCFST 柱容量预测中的应用

Mansoura Engineering Journal Pub Date : 2024-01-01 DOI: 10.58491/2735-4202.3178

Khaled Megahed, Nabil Said Mahmoud, Saad Elden Mostafa Abd-Rabou

引用次数: 0

Effect of the Shape and Volume of Capsulated Phase Change Materialon the Melting Process and Exergy Efficiency 带帽相变材料的形状和体积对熔化过程和能效的影响

Mansoura Engineering Journal Pub Date : 2024-01-01 DOI: 10.58491/2735-4202.3182

A. S. Soliman, Ahmed A. Sultan, Mohamed A. Sultan

引用次数: 0

An Enhanced Lane Detection Technique based on Active Learning 基于主动学习的增强型车道检测技术

Mansoura Engineering Journal Pub Date : 2024-01-01 DOI: 10.58491/2735-4202.3183

Ahmed M. Radwan, A. Haikal, Hisham E. Gad, Mohamed M. Abdelsalam

{"title":"An Enhanced Lane Detection Technique based on Active Learning","authors":"Ahmed M. Radwan, A. Haikal, Hisham E. Gad, Mohamed M. Abdelsalam","doi":"10.58491/2735-4202.3183","DOIUrl":"https://doi.org/10.58491/2735-4202.3183","url":null,"abstract":"The lane detecting algorithm plays a major role in advanced driver assistance systems and autonomous driving systems. In recent years, deep learning-based lane detection techniques have shown encouraging results; nonetheless, the quality and size of the training data set have a signi ﬁ cant impact on how effective these techniques are. Active learning is a technique that can improve the capacity of deep learning-based lane identi ﬁ cation systems to repeatedly choose and classify valuable samples from a large body of unlabeled data. In this research, a novel 1-dimensional deep learning approach is used to present an augmented Active Learning based Lane Detection Algorithm (ALDA) that picks informative samples based on diversity-and uncertainty-based criteria. Several benchmark datasets, including the CUlane, have been used to assess the suggested technique, In terms of accuracy and robustness, the suggested method ALDA performs better than four cutting-edge lane-detecting algorithms. The ﬁ ndings show that active learning can signi ﬁ cantly reduce the quantity of labeled data required for training while preserving good performance. The suggested method may improve the dependability and security of advanced driver assistance systems and autonomous driving systems. When compared with other distinct Deep Learning approaches, the proposed ALDA obtains an accuracy of 98.01 %, Precision of 98.5173 %, Recall of 95.2296 %, F1 score of 96.845 %, mAP of 92.7 %, and MSE of 0.0097.","PeriodicalId":510600,"journal":{"name":"Mansoura Engineering Journal","volume":"26 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140526748","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

Estimation of Origin-Destination Matrix Using Open-Source Applications Based on Traffic Counts for Mansoura City in Egypt 基于埃及曼苏拉市交通流量统计，利用开源应用程序估算起点-终点矩阵

Mansoura Engineering Journal Pub Date : 2024-01-01 DOI: 10.58491/2735-4202.3193

Ahmed N. Awaad, S. El-Badawy, Elsayed Abd-Elazem Shwaly, Usama Shahdah

引用次数: 0

Study the application of different building technology systems Case study: A residential villa in Al-Qassim region, KSA 研究不同建筑技术系统的应用案例研究：阿联酋卡西姆地区的一栋住宅别墅

Mansoura Engineering Journal Pub Date : 2024-01-01 DOI: 10.58491/2735-4202.3188

Ahmed AbdelMonteleb M. Ali, Essam S. Almahmoud, Basem O. Elgendy, Azzam I. Aljutayli, Meshal A. Alhrabi, Khattab I. Alyahya

引用次数: 0

A Novel Method for the Production of Pig Iron in “Hadisolb” Company (Industrial-Scale Experiments) 哈迪索布 "公司生产生铁的新方法（工业规模实验）

Mansoura Engineering Journal Pub Date : 2024-01-01 DOI: 10.58491/2735-4202.3198

El-Sayed A. Rassoul

引用次数: 0

Numerical and Analytical Solution for Nonlinear Free Vibration of Tapered Beams 锥形梁非线性自由振动的数值和分析解决方案

Mansoura Engineering Journal Pub Date : 2024-01-01 DOI: 10.58491/2735-4202.3179

Zain Abu Shaeer Abu Shaeer, Ramy I. Shahin, G. I. El–Baghdady, S. Yehia

引用次数: 0