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Block-Wise Neural Network for Brain Tumor Identification in Magnetic Resonance Images

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Computers, Materials & Continua 2022年第12期73卷 5735-5753页

作者： Abdullah A.Asiri Muhammad Aamir Ahmad Shaf Tariq Ali Muhammad Zeeshan Muhammad Irfan Khalaf A.Alshamrani Hassan A.Alshamrani fawaz f.alqahtani Ali H.D.Alshehri Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran 61441Saudi Arabia Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan Department of Computer Science Bahauddin Zakariya UniversityMultan 66000Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia

The precise brain tumor diagnosis is critical and shows a vital role in the medical support for treating tumor *** brain tumor segmentation for cancer analysis from many Magnetic Resonance Images(MRIs)created in medical practice is a problematic and timewasting task for *** a result,there is a critical necessity for more accurate computeraided methods for early tumor *** remove this gap,we enhanced the computational power of a computer-aided system by proposing a finetuned Block-Wise Visual Geometry Group19(BW-VGG19)*** this method,a pre-trained VGG19 is fine-tuned with CNN architecture in the block-wise mechanism to enhance the system`s *** publicly accessible Contrast-Enhanced Magnetic Resonance Imaging(CE-MRI)dataset collected from 2005 to 2020 from different hospitals in China has been used in this *** proposed method is simple and achieved an accuracy of 0.98%.We compare our technique results with the existing Convolutional Neural network(CNN),VGG16,and VGG19 *** results indicate that our proposed technique outperforms the best results associated with the existing methods.

关键词： CNN brain tumor block-wise structure VGG19 VGG16

A Novel Hybrid Machine Learning Approach for Classification of Brain Tumor Images

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Computers, Materials & Continua 2022年第10期73卷 641-655页

作者： Abdullah A.Asiri Amna Iqbal Javed ferzund Tariq Ali Muhammad Aamir Khalaf A.Alshamrani Hassan A.Alshamrani fawaz f.alqahtani Muhammad Irfan Ali H.D.Alshehri Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan College of Engineering Najran UniversityNajran61441Saudi Arabia

Abnormal growth of brain tissues is the real cause of brain *** for the diagnosis of brain tumor at initial stages is one of the key step for saving the life of a *** manual segmentation of brain tumor magnetic resonance images(MRIs)takes time and results vary significantly in low-level *** address this issue,we have proposed a ResNet-50 feature extractor depended on multilevel deep convolutional neural network(CNN)for reliable images segmentation by considering the low-level features of *** this model,we have extracted features through ResNet-50 architecture and fed these feature maps to multi-level CNN *** handle the classification process,we have collected a total number of 2043 MRI patients of normal,benign,and malignant *** model CNN,multi-level CNN,and ResNet-50 based multi-level CNN have been used for detection and classification of brain *** the model results are calculated in terms of various numerical values identified as precision(P),recall(R),accuracy(Acc)and f1-score(f1-S).The obtained average results are much better as compared to already existing *** modified transfer learning architecture might help the radiologists and doctors as a better significant system for tumor diagnosis.

关键词： Brain tumor magnetic resonance images convolutional neural network classification

Experimental Electromagnetic Characterization of High Temperature Superconductors Coils Located in Proximity to Electromagnetically Active Materials

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fluid Dynamics & Materials Processing 2022年第5期18卷 1529-1537页

作者： Yazid Statra Sara fawaz Hocine Menana Bruno Douine Universitéde Lorraine GREENNancyF-54000France

The electromagnetic properties of high temperature superconductors(HTS)are characterized with the explicit intent to improve their integration in electric power systems.A tape and a coil made of Bismuth Strontium Calcium Copper Oxide(BSCCO)are considered in the presence of electromagnetically active materials in order to mimic properly the electromagnetic environment typical of electrical *** characterization consists of the determining the critical current and the AC losses at different values of the frequency and the transport *** effects induced by the proximity of the active materials are studied and some related experimental issues are analyzedc.

关键词： AC losses HTS coils experimental characterization proximity of electromagnetically active materials

Machine Learning-Based Models for Magnetic Resonance Imaging(MRI)-Based Brain Tumor Classification

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Intelligent Automation & Soft Computing 2023年第4期36卷 299-312页

作者： Abdullah A.Asiri Bilal Khan fazal Muhammad Shams ur Rahman Hassan A.Alshamrani Khalaf A.Alshamrani Muhammad Irfan fawaz f.Alqhtani Department of Radiological Sciences College of Applied Medical SciencesNajran UniversityNajranSaudi Arabia Department of Computer Science City University of Science and Information TechnologyPeshawarPakistan Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan Department of Computer Science Engineering University of Engineering and TechnologyMardan23200Pakistan Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia

In the medical profession,recent technological advancements play an essential role in the early detection and categorization of many diseases that cause *** technique rising on daily basis for detecting illness in magnetic resonance through pictures is the inspection of ***(computerized)illness detection in medical imaging has found you the emergent region in several medical diagnostic *** diseases that cause death need to be identiﬁed through such techniques and technologies to overcome the mortality *** brain tumor is one of the most common causes of *** have already proposed various models for the classiﬁcation and detection of tumors,each with its strengths and weaknesses,but there is still a need to improve the classiﬁcation process with improved efﬁ***,in this study,we give an in-depth analysis of six distinct machine learning(ML)algorithms,including Random forest(Rf),Naïve Bayes(NB),Neural Networks(NN),CN2 Rule Induction(CN2),Support Vector Machine(SVM),and Decision Tree(Tree),to address this gap in improving *** the Kaggle dataset,these strategies are tested using classiﬁcation accuracy,the area under the Receiver Operating Characteristic(ROC)curve,precision,recall,and f1 Score(f1).The training and testing process is strengthened by using a 10-fold cross-validation *** results show that SVM outperforms other algorithms,with 95.3%accuracy.

关键词： MRI images brain tumor machine learning-based classiﬁcation

Association Rule Analysis-Based Identification of Influential Users in the Social Media

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Computers, Materials & Continua 2022年第12期73卷 6479-6493页

作者： Saqib Iqbal Rehan Khan Hikmat Ullah Khan fawaz Khaled Alarfaj Abdullah Mohammed Alomair Muzamil Ahmed College of Engineering Al Ain UniversityAl AinUnited Arab Emirates Department of Computer Science COMSATS University IslamabadWah CampusWah Cantt47040Pakistan Department of Computer Science and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)Al-HoufufSaudi Arabia

The exchange of information is an innate and natural process that assist in content *** networking sites emerge to enrich their users by providing the facility for sharing information and social *** extensive adoption of social networking sites also resulted in user content *** are diverse research areas explored by the researchers to investigate the influence of social media on users and confirmed that social media sites have a significant impact on markets,politics and social *** is extensively used platform to share information,thoughts and opinions through posts and *** identification of influential users on the social web has grown as hot research field because of vast applications in diverse areas for instance political campaigns marketing,e-commerce,commercial and,*** research studies either uses linguistic content or graph-based representation of social network for the detection of influential *** this article,we incorporate association rule mining algorithms to identify the top influential users through frequent *** association rules have been computed using the standard evaluation measures such as support,confidence,lift,and *** verify the results,we also involve conventional metrics for example accuracy,precision,recall and f1-measure according to the association rules *** detailed experiments are carried out using the benchmark College-Msg dataset extracted by *** obtained results validate the quality and visibility of the proposed *** outcome of propose model verify that the association rule mining is able to generate rules to identify the temporal influential users on facebook who are consistent on regular *** preparation of rule set help to create knowledge-based systems which are efficient and widely used in recent era for decision making to solve real-world problems.

关键词： Association rule mining ranking social web influential users social media

Automatic Approach and Landing Trajectory Planner for Unpowered Reusable Launch Vehicle

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Advances in Aerospace Science and Technology 2017年第4期2卷 31-47页

作者： fawaz f. AL-Bakri Craig A. Kluever Mechanical and Aerospace Engineering College of Engineering University of Missouri-Columbia Missouri USA

A new guidance scheme for the approach and landing (A & L) phase of an unpowered reusable launch vehicle (RLV) has been developed. The main advantage of the new guidance is the use of glide-efficiency factor as the independent variable to compute the geometrical flare parameters by a set of analytical functions. The trajectory-planning algorithm generates its reference geometry based on the steep and shallow subphases, respectively. During the steep segment, the quasi-equilibrium glide (QEG) solution, which assumes a constant dynamic pressure and flight-path angle during the flight, is used to create the flight reference while the shallow segment is defined by polynomial functions for altitude and dynamic pressure profiles. Standard linearization methods are used to design a closed-loop command in order to track the QEG profile. furthermore, proportion-derivative (PD) control is used to modulate the lift coefficient during the flare flight. Once the reference trajectory is created, a closed-loop simulation is obtained to track the reference. Off-nominal conditions, in terms of change in initial glide-efficiency factor, dynamic pressure, flight-path angle, and altitude are tested using a Monte-Carlo simulation. The simulated results demonstrate the effectiveness of the proposed algorithm to land the vehicle successfully under large dispersions of glide-efficiency factor.

关键词： Entry Vehicle Guidance System Trajectory Planning

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上位效应对遗传算法可靠性的影响（英文）

Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2019年第2期20卷 109-116页

作者： Sajad JAfARI Tomasz KAPITANIAK Karthikeyan RAJAGOPAL Viet-Thanh PHAM fawaz E.ALSAADI Biomedical Engineering Department Amirkabir University of Technology Division of Dynamics Lodz University of Technology Center for Nonlinear Dynamics Defence University6020 BishoftuEthiopia Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical&Electronics EngineeringTon Duc Thang University Department of Information Technology Faculty of Computing and ITKing Abdulaziz University

目的:探讨遗传算法的局限性和实用性,并分析基于相互作用产生的上位效应对遗传算法可靠性的影响。创新点:1.指出遗传算法缺陷的根源;2.基于测试样本函数定义目标函数,以判断遗传算法的适用性。方法:1.基于非上位效应函数(表1)和上位效... 详细信息

目的:探讨遗传算法的局限性和实用性,并分析基于相互作用产生的上位效应对遗传算法可靠性的影响。创新点:1.指出遗传算法缺陷的根源;2.基于测试样本函数定义目标函数,以判断遗传算法的适用性。方法:1.基于非上位效应函数(表1)和上位效应函数(表2),以及非上位效应函数f4和上位效应函数f6的结构图来验证遗传算法可靠性;2.通过计算样本函数(公式(1))和遗传算法流程(图3)表达遗传算法的工作原理。3.利用克洛弗函数(公式(2))和计算不同结构角下的函数分布(图4),进一步判断匹配度(表3)和计算效率(表4);定义新的目标函数(公式(9))和一组新的变量(公式(10))来实现变量相关性解离。结论:1.对当前遗传算法存在的不足给出了独到见解,并认为正定性的假设并非可以保证遗传算法实际的有效性和优化性。2.定义成本代价函数用以判断遗传算法可靠性,并分别考虑上位性和非上位性效应两种情形。当成本代价函数在非上位性效应下时,遗传算法是有效的;否则,可以把N维函数降级为N个一维函数,从而采用更简单的算法来判断。基于一些通用的基准,进一步设计三类样本函数来证实以上判断,且这些样本函数适合于上位性效应情形和非上位效应情形。3.遗传算法的瓶颈在于主算子和相干匹配性;可以通过破坏某些结构来实现变量关系的解离,从而抑制相干匹配性对遗传算法的影响。希望相关读者在处理实际优化问题时能验证作者关于上位效应的定性结论,并给出更可靠的方法来表征这种效应。

关键词：上位性效应遗传算法相干匹配性叠加性优化成本代价函数

Study Genetic Variation Using DNA Molecular Markers and Identification Physiological Races of Wheat Stripe （yellow） Rust Puccinia striiformis *** tritici during 2010-2014 in Some Regions of Syria

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Journal of food Science and Engineering 2017年第3期7卷 161-172页

作者： Shoula Kharoui fawaz Azmeh Buthainah N. Alsalamah National Commission for Biotechnology (NCBT) P.O. Box: 31902 Damascus Syria Damascus University faculty of Agriculture (G.C.B.T) 00963 11 5138309 Damascus Syria

Yellow Rust （stripe） rust （Puccinia striiformis West. f. sp. tritici） is one of the most epidemic diseases infect wheat in cold and wet regions. In 1988, this disease caused a loss of seasonal production amounted 70% on wheat variety Mexipak in Syria, and recurrent infection in 2010, caused by a virulent race called Yr27, caused a considerable loss in the production of bread wheat cultivars （Cham 8, Cham 6 particularly） amounted 90%. Recently, 15 races of yellow rust had been addressed in Syria for seasons 2010-2014; 159E256, 166E254, 166E256, 255 E112, 0 E0, 64 E 6, 230 El50, 0 E 18, 198 El30, 166 El50, 102 El60, 128 E0, 126 El50, 214E150, and 6E16. The race 6E16 was the most frequent during the two seasons, while the race 255El12 was the most virulent, followed by the race 230E222 and the race 0E0 was the weakest one. This study revealed the presence of fourteen newly observed races in Syria. Molecular Variance Analysis of Molecular Variance （AMOVA） of 55 yellow rust Puccinia striiformis *** tritici isolates examined by Amplify fragment Length Polymorphism （AfLP） revealed high genetic variation within population, and the dimensional scale analysis （MSD） and tree diagram showed that the Syrian yellow rust isolates were clustered in three groups： the first group contained isolates derived from durum wheat, the second one contained bread wheat isolates, but the third was made of isolates derived from both durum and bread wheat species.

关键词： Wheat yellow (stripe) rust Puccinia striiformis West f. sp. tritici DNA molecular markers AfLP PCR races Syria.

Community Knowledge about Bleeding Control in Jazan, KSA: Is There a Need for first Aid Educational Programs

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Journal of Biosciences and Medicines 2024年第6期12卷 64-84页

作者： Md Mazharul Hoque Hamoud Yahya Alsuriha Mohamed E. Moukhyer Bahja Siddig Mohamed Mubarak Almaki Amna Moukhyer fawaz Yahya Masswadi Mofareh Salman Harubi Elias Yosef Modabish Talal Omar Khasawi Yaser Mohammed Hantool Mohammed Awaji Mohammed Madkhali Aziza Mukhayer Emergency Medical Services Department Faculty of Applied Medical Sciences Jazan University Jazan Saudi Arabia Emergency Room University Hospital Jazan University Jazan Saudi Arabia Public Health Programmes School of Medicine University of Limerick Limerick Ireland School of Medicine Ahfad University for Women Omdurman Sudan Department of Medical Laboratory Faculty of Applied Medical Sciences Jazan Jazan University Saudi Arabia freelance Research Assistant Maastricht The Netherlands Department of Health Promotion University of Maastricht Maastricht The Netherland

The current study aimed to evaluate the first aid knowledge and general awareness of bleeding control, and their relations with different variables among the population of Jazan City, Saudi Arabia, in 2023. A cross-sectional study was conducted in Jazan City, Saudi Arabia between April 2023 and May 2023. Participants, >13 years old, living in Jazan City, were self-enrolled. Data collection was carried out by distributing a self-reported online survey questionnaire via email and social media apps. A validated, pretested online self-report questionnaire was used for data collection, with data analysis performed using (MS) Excel 2022 and SPSS version 26. A Chi-square test was used to determine the association of sociodemographic variables and Bleeding Control (BC) knowledge with, significance set at p f 250 participants completed the questionnaire, predominantly aged between 16 - 25 years, with 152 (60.8%) being male, and about 90% being Saudi citizens. Only 53 (21.2%) participated in previous first aid training concentrating on bleeding control. Only 76 (30.4%) of participants had good knowledge, while 131 (52.4%) exhibited positive attitude towards BC first aid. There were no statistically significant associations between BC knowledge and age, gender, occupation, nationality, and education. However, a significant association was observed between previous BC training and knowledge (Chi-test = 40.373, d.f = 1, p = 0.000) at p f poor knowledge of bleeding control among community members in Jazan City was high. The findings of this study should be carefully considered by various healthcare organizations to implement educational first-aid programs and activities aimed at enhancing community awareness and knowledge of bleeding control.

关键词： Injury Uncontrolled Bleeding first Aid Knowledge Attitude Jazan City