|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Big data storage technologies: a survey显示文摘对于容量快速增长、日趋多元化的大数据,业界亟需开发可行性更好的存储工具。为满足大数据存储需求,存储机制已经形成从传统数据管理系统到No SQL技术的结构化转移。然而,目前可用的大数据存储技术无法为持续增长的异构数据提供一致、可扩展和可用的解决方案。在科学实验、医疗保健、社交网络和电子商务等实际应用中,存储是大数据分析的第一步。截至目前,亚马逊、谷歌和阿帕奇等公司形成了大数据存储方案的行业标准,但尚未有关于大数据存储技术性能和容量提升的深入调查和文献报告。本文旨在对目前可用于大数据的最先进的存储技术进行全面调查,提供了一个明确的大数据存储技术分类方法,以帮助数据分析师和研究人员了解和选择更适合其需求的存储机制。我们使用布鲁尔的CAP定理比较和分析了现有存储方法,评估了不同存储架构的性能,讨论了存储技术的意义、应用及其对其他类别数据的支持。为了加快部署可靠和可扩展的存储系统,文中还突出了未来研究面临的几个挑战。 | Aisha SIDDIQA Ahmad KARIM Abdullah GANI | 2017 | Frontiers of Information Technology & Electronic Engineering2017，18，8： | 15 |
| 2 | Review:Data center network architecture in cloud computing:review, taxonomy, and open research issues显示文摘The data center network(DCN), which is an important component of data centers, consists of a large number of hosted servers and switches connected with high speed communication links. A DCN enables the deployment of resources centralization and on-demand access of the information and services of data centers to users. In recent years, the scale of the DCN has constantly increased with the widespread use of cloud-based services and the unprecedented amount of data delivery in/between data centers, whereas the traditional DCN architecture lacks aggregate bandwidth, scalability, and cost effectiveness for coping with the increasing demands of tenants in accessing the services of cloud data centers. Therefore, the design of a novel DCN architecture with the features of scalability, low cost, robustness, and energy conservation is required. This paper reviews the recent research findings and technologies of DCN architectures to identify the issues in the existing DCN architectures for cloud computing. We develop a taxonomy for the classification of the current DCN architectures, and also qualitatively analyze the traditional and contemporary DCN architectures. Moreover, the DCN architectures are compared on the basis of the significant characteristics, such as bandwidth, fault tolerance, scalability, overhead, and deployment cost. Finally, we put forward open research issues in the deployment of scalable, low-cost, robust, and energy-efficient DCN architecture, for data centers in computational clouds. | Han QI Muhammad SHIRAZ Jie-yao LIU Abdullah GANI Zulkanain ABDUL RAHMAN Torki A.ALTAMEEM | 2014 | Journal of Zhejiang University-Science C(Computers and Electronics)2014，15，9： | 1 |
| 3 | Radio fre- quency combination for TCP/IP suite protocol improve- ment in 4G mobile internet networks显示文摘 | Abdullah Gani LI Xichun Yang Lian | 2008 | International Journal of Communications2008，2，1： | 1 |
| 4 | A study on virtual machine deployment for application outsourcing in mobile cloud computing显示文摘 | Muhammad Shiraz Saeid Abolfazli Zohreh Sanaei Abdullah Gani | 2013 | The Journal of Supercomputing2013，，3： | 1 |
| 5 | A survey on vehicular cloud computing显示文摘 | Md Whaiduzzaman Mehdi Sookhak Abdullah Gani Rajkumar Buyya | 2013 | Journal of Network and Computer Applications2013，，： | 1 |
| 6 | The impact of electronic communication technology on written language显示文摘 | Mohd. Sahandri Gani B. Hamzah Mohd. Reza Ghorbani Saifuddin Kumar B. Abdullah | 2009 | 美中教育评论2009，6，11： | 1 |
| 7 | 求解整数线性规划问题的量子近似优化算法显示文摘量子近似优化算法是一种量子经典混合算法,它可以在多项式时间内求得组合优化问题的最优解。但是在低迭代水平时,得到问题最优解的概率较低。为了应对这一挑战,基于改进的目标哈密顿量,设计了一种具有较少量子门的量子线路,简化了求解过程,提高了求解精度。通过求解整数线性规划问题进行实验,以验证所提出解决方案的可靠性,实验部署在本源量子的pyQpanda环境中。结果表明,平均执行时间为原始时间的20.8%,概率由54.1563%提高到82.9%。 | 戚晗 何婉莹 邱涛 Abdullah Gani | 2023 | 沈阳航空航天大学学报2023，40，3： | 0 |
| 8 | Detecting and Mitigating DDOS Attacks in SDNs Using Deep Neural Network显示文摘Distributed denial of service(DDoS)attack is the most common attack that obstructs a network and makes it unavailable for a legitimate user.We proposed a deep neural network(DNN)model for the detection of DDoS attacks in the Software-Defined Networking(SDN)paradigm.SDN centralizes the control plane and separates it from the data plane.It simplifies a network and eliminates vendor specification of a device.Because of this open nature and centralized control,SDN can easily become a victim of DDoS attacks.We proposed a supervised Developed Deep Neural Network(DDNN)model that can classify the DDoS attack traffic and legitimate traffic.Our Developed Deep Neural Network(DDNN)model takes a large number of feature values as compared to previously proposed Machine Learning(ML)models.The proposed DNN model scans the data to find the correlated features and delivers high-quality results.The model enhances the security of SDN and has better accuracy as compared to previously proposed models.We choose the latest state-of-the-art dataset which consists of many novel attacks and overcomes all the shortcomings and limitations of the existing datasets.Our model results in a high accuracy rate of 99.76%with a low false-positive rate and 0.065%low loss rate.The accuracy increases to 99.80%as we increase the number of epochs to 100 rounds.Our proposed model classifies anomalous and normal traffic more accurately as compared to the previously proposed models.It can handle a huge amount of structured and unstructured data and can easily solve complex problems. | Gul Nawaz Muhammad Junaid Adnan Akhunzada Abdullah Gani Shamyla Nawazish Asim Yaqub Adeel Ahmed Huma Ajab | 2023 | Computers, Materials & Continua2023，77，11： | 0 |
| 9 | Deep Learning Based Classification of Wrist Cracks from X-ray Imaging显示文摘Wrist cracks are the most common sort of cracks with an excessive occurrence rate.For the routine detection of wrist cracks,conventional radiography(X-ray medical imaging)is used but periodically issues are presented by crack depiction.Wrist cracks often appear in the human arbitrary bone due to accidental injuries such as slipping.Indeed,many hospitals lack experienced clinicians to diagnose wrist cracks.Therefore,an automated system is required to reduce the burden on clinicians and identify cracks.In this study,we have designed a novel residual network-based convolutional neural network(CNN)for the crack detection of the wrist.For the classification of wrist cracks medical imaging,the diagnostics accuracy of the RN-21CNN model is compared with four well-known transfer learning(TL)models such as Inception V3,Vgg16,ResNet-50,and Vgg19,to assist the medical imaging technologist in identifying the cracks that occur due to wrist fractures.The RN-21CNN model achieved an accuracy of 0.97 which is much better than its competitor`s approaches.The results reveal that implementing a correct generalization that a computer-aided recognition system precisely designed for the assistance of clinician would limit the number of incorrect diagnoses and also saves a lot of time. | Jahangir Jabbar Muzammil Hussain Hassaan Malik Abdullah Gani Ali Haider Khan Muhammad Shiraz | 2022 | Computers, Materials & Continua2022，，10： | 0 |
| 10 | Test Item Analysis" An Educator Professionalism Approach显示文摘 | Mohd Sahandri Gani Hamzah Saifuddin Kumar Abdullah | 2011 | US-China Education Review(A)2011，1，3X： | 0 |
| 11 | 基于随机量子层的变分量子卷积神经网络鲁棒性研究显示文摘近年来,量子机器学习被证明与经典机器学习一样会被一个精心设计的微小扰动干扰从而造成识别准确率严重下降。目前增加模型对抗鲁棒性的方法主要有模型优化、数据优化和对抗训练。文章从模型优化角度出发,提出了一种新的方法,旨在通过将随机量子层与变分量子神经网络连接组成新的量子全连接层,与量子卷积层和量子池化层组成变分量子卷积神经网络(Variational Quantum Convolutional Neural Networks,VQCNN),来增强模型的对抗鲁棒性。文章在KDD CUP99数据集上对基于VQCNN的量子分类器进行了验证。实验结果表明,在快速梯度符号法(Fast Gradient Sign Method,FGSM)、零阶优化法(Zeroth-Order Optimization,ZOO)以及基于遗传算法的生成对抗样本的攻击下,文章提出的VQCNN模型准确率下降值分别为11.18%、15.21%和33.64%,与其它4种模型相比准确率下降值最小。证明该模型在对抗性攻击下具有更高的稳定性,其对抗鲁棒性更优秀。同时在面对基于梯度的攻击方法(FGSM和ZOO)时的准确率下降值更小,证明文章提出的VQCNN模型在面对此类攻击时更有效。 | 戚晗 王敬童 ABDULLAH Gani 拱长青 | 2024 | 信息网络安全2024，，3： | 0 |
| 12 | Mary Ewell, Doctor of Physical Sciences, term associate professor, Department of Physics and Astronomy, George Mason University.显示文摘 | Mohd Sahandri Gani Bin Hamzah Saifuddin Kumar Bin Abdullah Mazura Mastura Binti Muhammad | 2016 | US-China Education Review(A)2016，6，4： | 0 |
| 13 | Effectiveness of the selected techniques in enhancing the achievement in science among the children with learning disabilities: Sharing experiences显示文摘 | Mohd. Sahandri Gani Hamzah Vijayaletchumy a/p Subramamam Saifuddin Kumar Abdullah | 2009 | 美中教育评论2009，6，9： | 0 |
| 14 | Working commitment among trainee teachers: A meta evaluation approach显示文摘 | Mohd Sahandri Gani B. Hamzah Hapidah Bt. Mohamed Saifuddin Kumar B. Abdullah Roselan B. Baki | 2008 | 美中教育评论2008，5，10： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员