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轴向和循环荷载下外环板节点的剪切性能

轴向和循环荷载下外环板节点的剪切性能

作者： khan suliman 天津大学

学位级别：硕士

钢管混凝土柱(CFST)与钢梁之间的节点在组合框架结构的安全性和稳定性中起着至关重要的作用。由于其卓越的应用,已被广泛用于各种CSFT结构的工程设计。近年来,钢筋混凝土柱和钢梁的应用率不断提高。混凝土柱中的钢管通常会限制混凝土从... 详细信息

钢管混凝土柱(CFST)与钢梁之间的节点在组合框架结构的安全性和稳定性中起着至关重要的作用。由于其卓越的应用,已被广泛用于各种CSFT结构的工程设计。近年来,钢筋混凝土柱和钢梁的应用率不断提高。混凝土柱中的钢管通常会限制混凝土从而使得混凝土在三轴应力下提高混凝土强度,同时管内的混凝土限制了钢管的局部屈曲。一般而言,节点是框架结构中最关键的部位,其破坏可能导致整个结构在极端载荷下完全或部分坍塌。目前的研究是针对钢管混凝土结构内各梁柱节的剪切性能进行的。根据几何要求制造三个缩小尺寸的外环板节点。连接的设计基于强大的构件和弱核心区的概念,以确保在核心区发生剪切破坏。分别针对循环和轴向载荷测试十字形节点试件。考虑外环板,填充混凝土和钢管的分别作用,以检查节点的剪切表现。使用测试样本的实验数据获得的滞回曲线和骨架曲线显示出延展性以及较好的地震能量耗散能力。三个试件极限承载力分别为140.66 kN,120 kN和158.9 kN,相应的位移分别为56.57 mm,41.81 mm和56.65 mm。采用屈服前的力控制和屈服后的位移控制进行实验过程。试验结果显示,在核心区混凝土中观察到斜压杆,这增强了核心区的剪切承载力。在后弹性阶段期间在钢管腹板上以对角线方式发生张力场作用。核心区混凝土和钢管的这种复合作用对于提高外环板节点的极限剪切承载能力具有显着效果。采用一般静力方法建立非线性三维有限元模型。有限元分析结果表明,试验和有限元试件的屈服和极限承载力具有非常独特的相似性,实验结果表明,可以基于该模型进行参数化分析。通过改变混凝土材料性能,钢材性能,钢管腹板和翼缘的厚度以及使用有限元加载方法。基于参数研究得出的结论是,增加管腹板的厚度和在板区使用高等级混凝土在很大程度上有助于外环板节点的剪切性能,而梁翼缘的宽度或厚度对于剪切承载能力没有主要作用。

关键词：钢管混凝土柱(CFST) 外环板节点实验研究剪切承载力

Cluster Modulation: A Generalized Modulation Scheme Leading to NOMA or Adaptive Modulation

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Journal of Computer and Communications 2024年第7期12卷 12-22页

作者： Jamal S. Rahhal suliman J. Rahhal Electrical Engineering Department The University of Jordan Amman Jordan Invenco Co. Tampa USA

The need for higher data rate and higher systems capacity leads to several solutions including higher constellation size, spatial multiplexing, adaptive modulation and Non-Orthogonal Multiple Access (NOMA). Adaptive Modulation makes use of the user’s location from his base station, such that, closer users get bigger constellation size and hence higher data rate. A similar idea of adaptive modulation that makes use of the user’s locations is the NOMA technique. Here the base station transmits composite signals each for a different user at a different distance from the base station. The transmitted signal is formed by summing different user’s constellations with different weights. The closer the users the less average power constellation is used. This will allow the closer user to the base station to distinguish his constellation and others constellation. The far user will only distinguish his constellation and other user’s data will appear as a small interference added to his signal. In this paper, it is shown that the Adaptive modulation and the NOMA are special cases of the more general Cluster Modulation technique. Therefore, a general frame can be set to design both modulation schemes and better understanding is achieved. This leads to designing a multi-level NOMA and/or flexible adaptive modulation with combined channel coding.

关键词： Cluster Modulation Adaptive Modulation NOMA

方钢管-H型钢梁隔板贯通节点核心区抗震性能研究

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建筑结构 2021年第9期51卷 136-140页

作者：孙轶良吴海亮张戊晨荣彬杨子恒 suliman khan 国网河北省电力有限公司经济技术研究院石家庄050021 天津大学建筑工程学院天津300072

对3个十字形隔板贯通节点进行柱顶恒定轴力和梁端横向往复荷载作用下的试验。3个足尺试件设计变化的参数为隔板厚度和核心区柱壁厚度。基于试验结果,采用有限元软件ABAQUS对试件进行非线性分析和计算,得到梁端荷载-位移滞回曲线并与试... 详细信息

对3个十字形隔板贯通节点进行柱顶恒定轴力和梁端横向往复荷载作用下的试验。3个足尺试件设计变化的参数为隔板厚度和核心区柱壁厚度。基于试验结果,采用有限元软件ABAQUS对试件进行非线性分析和计算,得到梁端荷载-位移滞回曲线并与试验进行对比,且利用有限元软件对试验过程应力分布进行分析。试验结果及有限元分析表明:对于隔板贯通节点,其隔板的厚度以及核心区柱壁的厚度对核心区的承载力有重要影响;梁端塑性铰破坏模式与核心区凹曲剪切破坏模式下,试件的滞回曲线均饱满而稳定,且耗能能力均能满足要求;核心区在受剪破坏模式下,其承载力和性能基本上只与核心区柱腹板和隔板厚度有关,而与核心区柱翼缘厚度无关。

关键词：隔板贯通节点核心区抗剪性能抗震性能

A New Multi Chaos-Based Compression Sensing Image Encryption

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Computers, Materials & Continua 2023年第7期76卷 437-453页

作者： Fadia Ali khan Jameel Ahmed suliman A.Alsuhibany Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia

The advancements in technology have substantially grown the size of image *** image encryption algorithms have limited capabilities to deal with the emerging challenges in big data,including compression and noise *** image encryption method that is based on chaotic maps and orthogonal matrix is proposed in this *** proposed scheme is built on the intriguing characteristics of an orthogonal *** Schmidt disperses the values of pixels in a plaintext image by generating a random orthogonal matrix using logistic chaotic *** the diffusion process,a block-wise random permutation of the data is performed using *** proposed scheme provides sufficient security and resilience to JPEG compression and channel noise through a series of experiments and security *** enables Partial Encryption(PE)for faster processing as well as complete encryption for increased *** higher values of the number of pixels change rates and unified average change intensity confirm the security of the encryption *** contrast to other schemes,the proposed approach can perform full and partial encryption depending on security requirements.

关键词： Chaos compression image encryption

Learning Patterns from COVID-19 Instances

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Computer Systems Science & Engineering 2022年第2期40卷 765-777页

作者： Rehan Ullah khan Waleed Albattah suliman Aladhadh Shabana Habib Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia

Coronavirus disease,which resulted from the SARS-CoV-2 virus,has spread worldwide since early 2020 and has been declared a pandemic by the World Health Organization(WHO).Coronavirus disease is also termed *** affects the human respiratory system and thus can be traced and tracked from the Chest X-Ray ***,Chest X-Ray alone may play a vital role in identifying COVID-19 *** this paper,we propose a Machine Learning(ML)approach that utilizes the X-Ray images to classify the healthy and affected patients based on the patterns found in these *** article also explores traditional,and Deep Learning(DL)approaches for COVID-19 patterns from Chest X-Ray images to predict,analyze,and further understand this *** experimental evaluation of the proposed approach achieves 97.5% detection performance using the DL model for COVID-19 versus normal *** contrast,for COVID-19 versus Pneumonia Virus scenario,we achieve 94.5% accurate *** extensive evaluation in the experimental section guides and helps in the selection of an appropriate model for similar ***,the approach can be used for medical usages and is particularly pertinent in detecting COVID-19 positive patients using X-Ray images alone.

关键词： Coronavirus COVID-19 machine learning deep learning convolutional neural network

Dates Fruit Recognition: From Classical Fusion to Deep Learning

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Computer Systems Science & Engineering 2022年第1期40卷 151-166页

作者： Khaled Marji Alresheedi suliman Aladhadh Rehan Ullah khan Ali Mustafa Qamar Department of Computer Science College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computing School of Electrical Engineering and Computer Science(SEECS)National University of Sciences and Technology(NUST)IslamabadPakistan

There are over 200 different varieties of dates fruit in the ***,every single type has some very specific features that differ from the *** recent years,sorting,separating,and arranging in automated industries,in fruits businesses,and more specifically in dates businesses have inspired many research *** this regard,this paper focuses on the detection and recognition of dates using computer vision and machine *** experimental setup is based on the classical machine learning approach and the deep learning approach for nine classes of dates *** machine learning includes the Bayesian network,Support Vector Machine,Random Forest,and Multi-Layer Perceptron(MLP),while the Convolutional Neural Network is used for the deep learning *** feature set includes Color Layout features,Fuzzy Color and Texture Histogram,Gabor filtering,and the Pyramid Histogram of the Oriented *** fusion of various features is also extensively explored in this *** MLP achieves the highest detection performance with an F-measure of ***,deep learning shows better accuracy than the classical machine learning *** fact,deep learning got 2%more accurate results as compared to the MLP and the Random *** also show that classical machine learning could give increased classification performance which could get close to that provided by deep learning through the use of optimized tuning and a good feature set.

关键词： features Deep separating

The Impact of Check Bits on the Performance of Bloom Filter

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Computers, Materials & Continua 2022年第12期73卷 6037-6046页

作者： Rehan Ullah khan Ali Mustafa Qamar suliman A.Alsuhibany Mohammed Alsuhaibani Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydahSaudi Arabia

Bloom filter(BF)is a space-and-time efficient probabilistic technique that helps answermembership ***,BF faces several *** problems with traditional BF are generally ***,a large number of false positives can return wrong content when the data is ***,the large size of BF is a bottleneck in the speed of querying and thus uses large *** order to solve the above two issues,in this article,we propose the check bits *** the implementation perspective,in the check bits approach,before saving the content value in the BF,we obtain the binary representation of the content ***,we take some bits of the content value,we call these the check *** bits are stored in a separate array such that they point to the same location as the ***,the content value(data)is stored in the BF based on the hash function *** retrieval of data from BF,the reverse process of the steps ensures that even if the same hash functions output has been generated for the content,the check bits make sure that the retrieval does not depend on the hash output *** thus helps in the reduction of false *** the experimental evaluation,we are able to reduce more than 50%of false *** our proposed approach,the false positives can still occur,however,false positives can only occur if the hash functions and check bits generate the same value for a particular *** chances of such scenarios are less,therefore,we get a reduction of approximately more than 50%false positives in all *** believe that the proposed approach adds to the state of the art and opens new directions as such.

关键词： Bloom filter big data network processing optimization check bits

A Secure and Lightweight Chaos Based Image Encryption Scheme

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Computers, Materials & Continua 2022年第10期73卷 279-294页

作者： Fadia Ali khan Jameel Ahmed Fehaid Alqahtani suliman A.Alsuhibany Fawad Ahmed Jawad Ahmad Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Computer Science King Fahad Naval AcademyAl Jubail35512Saudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Cyber Security Pakistan Navy Engineering CollegeNUSTKarachi 75350Pakistan School of Computing Edinburgh Napier UniversityEdinburghEH105DTUnited Kingdom

In this paper,we present an image encryption scheme based on the multi-stage chaos-based image encryption *** method works on the principle of confusion and *** proposed scheme containing both confusion and diffusion modules are highly secure and effective as compared to the existing ***,an image(red,green,and blue components)is partitioned into blocks with an equal number of *** block is then processed with Tinkerbell Chaotic Map(TBCM)to get shuffled pixels and shuffled *** Fractal Function(CFF)change the value of pixels of each color component(layer)to obtain a random *** the obtained random sequence,three layers of plain image are ***,with each encrypted layer,Brownian Particles(BP)are XORed that added an extra layer of *** experimental tests including a number of statistical tests validated the security of the presented *** results reported in the paper show that the proposed scheme has higher security and is lightweight as compared to state-of-the-art methods proposed in the literature.

关键词： Chaos fractals fibonacci tinkerbell chaotic map confusion diffusion brownian motion

Data Augmentation and Random Multi-Model Deep Learning for Data Classification

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Computers, Materials & Continua 2023年第3期74卷 5191-5207页

作者： Fatma Harby Adel Thaljaoui Durre Nayab suliman Aladhadh Salim EL Khediri Rehan Ullah khan Computer Science Department Future Academy-Higher Future Institute for Specialized Technological StudiesEgypt Department of Computer Systems Engineering Faculty of Electrical and Computer EngineeringUniversity of Engineering and TechnologyPeshawar25120Pakistan Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer Sciences Faculty of Sciences of GafsaUniversity of GafsaGafsaTunisia

In the machine learning(ML)paradigm,data augmentation serves as a regularization approach for creating ML *** increase in the diversification of training samples increases the generalization capabilities,which enhances the prediction performance of classifiers when tested on unseen *** learning(DL)models have a lot of parameters,and they frequently ***,to avoid overfitting,data plays a major role to augment the latest improvements in ***,reliable data collection is a major limiting ***,this problem is undertaken by combining augmentation of data,transfer learning,dropout,and methods of normalization in *** this paper,we introduce the application of data augmentation in the field of image classification using Random Multi-model Deep Learning(RMDL)which uses the association approaches of multi-DL to yield random models for *** present a methodology for using Generative Adversarial Networks(GANs)to generate images for data *** experiments,we discover that samples generated by GANs when fed into RMDL improve both accuracy and model *** across both MNIST and CIAFAR-10 datasets show that,error rate with proposed approach has been decreased with different random models.

关键词： Data augmentation generative adversarial networks classification machine learning random multi-model deep learning