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Phishing Websites Detection by Using Optimized Stacking Ensemble Model

Computer Systems Science & Engineering 2022年第4期41卷 109-125页

作者： Zeyad Ghaleb Al-Mekhlafi badiea abdulkarem mohammed mohammed Al-Sarem Faisal Saeed Tawfik Al-Hadhrami Mohammad T.Alshammari Abdulrahman Alreshidi Talal Sarheed Alshammari College of Computer Science and Engineering University of Ha'ilHa'il81481KSA College of Computer Sciences and Engineering Hodeidah UniversityHodeidah967Yemen College of Computer Science and Engineering Taibah UniversityAl-Madinah42353KSA Nottingham Trent University MansfieldNG185BHUnited Kingdom

Phishing attacks are security attacks that do not affect only individuals’or organizations’websites but may affect Internet of Things(IoT)devices and *** environment is an exposed environment for such *** may use thingbots software for the dispersal of hidden junk emails that are not noticed by *** and deep learning and other methods were used to design detection methods for these ***,there is still a need to enhance detection *** of an ensemble classiﬁcation method for phishing website(PW)detection is proposed in this study.A Genetic Algo-rithm(GA)was used for the proposed method optimization by tuning several ensemble Machine Learning(ML)methods parameters,including Random Forest(RF),AdaBoost(AB),XGBoost(XGB),Bagging(BA),GradientBoost(GB),and LightGBM(LGBM).These were accomplished by ranking the optimized classi-ﬁers to pick out the best classiﬁers as a base for the proposed method.A PW data-set that is made up of 4898 PWs and 6157 legitimate websites(LWs)was used for this study's *** a result,detection accuracy was enhanced and reached 97.16 percent.

关键词： Phishing websites ensemble classiﬁers optimization methods genetic algorithm

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Deep Learning and Machine Learning for Early Detection of Stroke and Haemorrhage

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Computers, Materials & Continua 2022年第7期72卷 775-796页

作者： Zeyad Ghaleb Al-Mekhlafi Ebrahim mohammed Senan Taha H.Rassem badiea abdulkarem mohammed Nasrin M.Makbol Adwan Alownie Alanazi Tariq S.Almurayziq Fuad A.Ghaleb Department of Information and Computer Science College of Computer Science and EngineeringUniversity of Ha’ilHa’il81481Saudi Arabia Department of Computer Science&Information Technology Dr.Babasaheb Ambedkar Marathwada UniversityAurangabad431004India Faculty of Science and Technology Bournemouth UniversityPooleBH125BBUK Department of Computer Engineering College of Computer Science and EngineeringUniversity of Ha’ilHa’il81481Saudi Arabia College of Computer Science and Engineering Hodeidah UniversityHodeidah966Yemen School of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaJohor BahruJohor81310Malaysia

Stroke and cerebral haemorrhage are the second leading causes of death in the world after ischaemic heart *** this work,a dataset containing medical,physiological and environmental tests for stroke was used to evaluate the efficacy of machine learning,deep learning and a hybrid technique between deep learning and machine learning on theMagnetic Resonance Imaging(MRI)dataset for cerebral *** the first dataset(medical records),two features,namely,diabetes and obesity,were created on the basis of the values of the corresponding *** t-Distributed Stochastic Neighbour Embedding algorithm was applied to represent the high-dimensional dataset in a low-dimensional data ***,the Recursive Feature Elimination algorithm(RFE)was applied to rank the features according to priority and their correlation to the target feature and to remove the unimportant *** features are fed into the various classification algorithms,namely,Support Vector Machine(SVM),K Nearest Neighbours(KNN),Decision Tree,Random Forest,and Multilayer *** algorithms achieved superior *** Random Forest algorithm achieved the best performance amongst the algorithms;it reached an overall accuracy of 99%.This algorithm classified stroke cases with Precision,Recall and F1 score of 98%,100%and 99%,*** the second dataset,the MRI image dataset was evaluated by using the AlexNet model and AlexNet+SVM hybrid *** hybrid model AlexNet+SVM performed is better than the AlexNet model;it reached accuracy,sensitivity,specificity and Area Under the Curve(AUC)of 99.9%,100%,99.80%and 99.86%,respectively.

关键词： Stroke cerebral haemorrhage deep learning machine learning t-SNE and RFE algorithms

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The Impact of Foreign Education and Training on Entrepreneurship Intention(A Research Study on the Arab World’s Students in China)

The Impact of Foreign Education and Training on Entrepreneur...

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作者： ANAF abdulkarem mohammed 山东大学

学位级别：硕士

This research examined the impact of foreign education and training on promoting entrepreneurial intention among Arab students studying in *** data was collected from 992 students by using questionnaire survey to measure entrepreneurial intention,education,training,volunteer activities,propensity to take risk and family support *** multiple regression analysis and correlation analysis were *** analysis confirms some previous findings in literature on students’entrepreneurial *** findings show that except volunteer activities,all other factors have positive relationship towards entrepreneurial intention of Arab students in *** objective of this thesis is to contribute to the improvement of university education that is provided for foreign students in *** practical implications and recommendations were provided for relevant educational institutions and authorities.

关键词：教育机构留学生创业意向

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也门共和国典型桥梁的地震易损性分析

也门共和国典型桥梁的地震易损性分析

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作者： Al-jaboobi mohammed abdulkarem Saleh 西南交通大学

学位级别：硕士

1982年在达马尔市的地震是自1811年也门历史上的地震事件以来强度最大的,这让工程部门注意到许多已建立的高速公路桥梁延伸出瑕疵和裂缝。然而,这种意识和关心直到1990年也门统一之后都没有解决,那时也门统一地区超过了萨那的地震区,并... 详细信息

1982年在达马尔市的地震是自1811年也门历史上的地震事件以来强度最大的,这让工程部门注意到许多已建立的高速公路桥梁延伸出瑕疵和裂缝。然而,这种意识和关心直到1990年也门统一之后都没有解决,那时也门统一地区超过了萨那的地震区,并处于也门共和国中部和东南部等中强地震区。对中强地震区与桥梁相关的地震问题的这种长期忽略,导致一系列桥梁在防震设计方面存在许多不足之处,为了更长久和有效地使用桥梁,必须对桥梁进行评估和审查。最近,一种新兴的决策工具在地震风险评估研究中变得越来越流行,叫做地震易损性曲线。在也门这五种类型的桥梁被定义为:本研究的目的是改进一种有趣的方法,用于研究也门中部和东南部地区典型桥梁的地震易损性曲线数据。虽然已有对地震易损曲线的研究,但大多数都集中在也门西部和叙利亚的高地震带的桥梁。由于认识到大规模地震的可能性,现在重心更多放在也门地区。为帮助评估该地区的地震危险性,选择了五种典型的桥梁来研究地震易损性曲线:1-多跨支撑连续混凝土梁2-多跨支撑连续钢梁3-多跨支撑连续板4-多跨支撑连续混凝土箱梁5-多跨支护简支混凝土梁这五种桥梁占该地区160,000多条高速公路桥梁的近90%。统计表明,这些桥中的大多数具有三个跨距并且具有标准配置(即略微偏斜或没有偏斜)。但建造大多数这些桥梁时,没有进行抗震设计,这表明大多数这些桥梁都没有抗震设计。本研究中的研究调整了一些现有的非线性时程分析方法,以创建一个更加稳健和限制性的地震易损性曲线。具体而言,调整现有方法,以便在确定系统(桥梁)的易损性时,可以将多个元素的影响集中在一起。第三章强调了也门中部和东南部的地震灾害。可以看出,虽然该地区的地震活动不像也门西部那样频繁,但由于该地区的地质构成,有一个令人担忧的问题。现已确定了两种地震,以帮助确定该地区地震灾害的性质。这项研究包括五种桥梁,其目的是最常见的并且在也门研究区域内建立的。利用分析方法生成易损性曲线。根据在美国,澳大利亚和大多数欧盟国家开展的研究,桥梁会依次明显地受到一组合成地面运动的影响。在第六章中,我探讨了不同建模参数对本研究中考虑的桥梁的影响。这些研究的结果可用于确定哪些建模标准应以概率而非不可避免的方法处理。这也有助于更清楚地了解需要最严格分析模型的参数。测试设计的研究是一种统计方法,用于探索由于不同建模参数值的变化而导致的八个特定组件响应的变化。如果对桥梁只有一个响应,例如对混凝土柱的延性要求,这项研究的结果可能会更稳定。但是,每座桥的重要参数往往会从一个组件变为另一个组件。首先通过评估目标桥梁的典型特征和细节,优先查看现有桥梁库存然后创建详细的3-D分析模型来验证这一点。第七章讨论的另一点是选择适当的强度测量。与普遍看法相反,与光谱量相比,地面峰值的加速度峰值是研究桥梁PSDM最常见的量度。这个结论的一个可能原因是考虑了不止一个因素,并非所有因素都仔细考虑过。地面加速度峰值似乎对实际波动影响不大。然后使用这些分析创建概率地震需求模型(PSDM)。在考虑特定的损坏程度下,已开发的PSD模型对于创建易损性曲线可能很重要。正如易损性曲线向我们展示的那样,考虑的最多的五类桥梁是那些使用钢梁的桥梁,其中最脆弱的桥梁似乎是混凝土梁桥,其次是简单支撑的单跨桥梁。选择地面运动在计算的易损性值中起着重要作用。其中一个原因是地面运动的频率内容不同,如第三章所示。在五种类型桥梁中,最脆弱的桥梁似乎是混凝土梁桥,其次是具有单跨的桥梁。在本研究期间,选择了HAZUS和REDARS等各种不确定性分析软件来进行研究,并直接现有的地震风险评估数据中使用。

关键词：易损性曲线概率地震需求模型地震危险性也门共和国中部和南部风险评估软件HAZUS 公路桥梁 OpenSees CSI Bridge

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Ecological Sound Control Strategies for Population Suppression of Date Palm Borers Oryctes spp.

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Journal of Agricultural Science and Technology(A) 2017年第1期7卷 18-24页

作者： mohammed Zaidan Khalaf Hussain Fadhel Alrubeai mohammed Waleed Khudhaer Aysar abdulkarem Abdulhusein Integrated Pest Control Research Center Directorate of Agricultural Research Ministry of Science & Technology Baghdad00964 Iraq Directorate of Baghdad Agriculture Ministry of Agriculture Baghdad 00964 Iraq

Cultural practices, hand collection of larvae, light traps and entomopathogenic fungi were investigated to manage of palm borers Oryctes spp. in date palm orchards during the years 2010-2015. Cultural practices, such as sanitation and pruning frond bases, hand collection of larvae during regular annual service work and light traps with solar energy were practiced annually in one orchard for five years. In the second orchard, cultural practices were applied for two years, light trap for one year only, and no hand collection of larvae was done during the period. The third orchard was used as a control treatment. Results showed reduction in population density of larvae （91.6% and 53.0%） and adult （76.1% and 41.1%） ofOryects spp. in the 1st and 2nd orchard, respectively The results also demonstrated the impact of moon light phases on the number of Oryctes spp. adults caught by light trap and the existence of an inverse relation between moon light and flight activity of adults. Biological experiments also revealed that entomopathogenic fungi can cause high mortality rate reaching 100% after 29 d. Beauveria bassiana scored higher mortality rate in short time, especially at concentration of 1 × 10^11 conidia/mL with LT50 = 12.75 and LT90 = 20; while, Metarhizium anisopliae caused the higher percentage of malformed adults. The results depicted the effectiveness of some integrated ecological sound control methods for monitoring and population suppression of Oryects spp. in date palm orchards.

关键词： Integrated pest management cultural practices hand collection of larvae light traps moon light entomopathogenic fungi Oryects spp..

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