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Exploiting Empirical Variance for Data Stream Classification

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Journal of Shanghai Jiaotong university(Science) 2012年第2期17卷 245-250页

作者： zia-ur rehman Muhammad 李天瑞李涛 School of Information Science and Technology Southwest Jiaotong University School of Computer Science Florida International University

Classification,using the decision tree algorithm,is a widely studied problem in data *** challenge is when to split a decision node into multiple *** inequalities,that exploit variance information such as Bernstein's and Bennett's inequalities,are often substantially strict as compared with Hoeffding's bound which disregards *** machine learning algorithms for stream classification such as very fast decision tree(VFDT) learner,AdaBoost and support vector machines(SVMs),use the Hoeffding's bound as a performance *** this paper,we propose a new algorithm based on the recently proposed empirical Bernstein's bound to achieve a better probabilistic bound on the accuracy of the decision *** results on four synthetic and two real world data sets demonstrate the performance gain of our proposed technique.

关键词： Hoeffding and Bernstein’s bounds data stream classification decision tree anytime algorithm

Electron doping induced semiconductor to metal transitions in ZrSe2 layers via copper atomic intercalation

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Nano Research 2018年第9期11卷 4914-4922页

作者： Zahir Muhammad Kejun Mu Haifeng Lv Chuanqiang Wu zia ur rehman Muhammad Habib Zhe Sun Xiaojun Wu Li Song National Synchrotron Radiation Laboratory CAS Center for Excellence in Nanoscience CAS Key Laboratory of Strongly-coupled Quantum Matter Physics University of Science and Technology of China Hefei 230029 China CAS Key Laboratory of Materials for Energy Conservation Synergetic Innovation Centre of Quantum Information & Quantum Physics CAS Center for Excellence in Nanoscience and Department of Material Science and Engineering University of Science and Technology of China Hefei 230026 China

Atomic intercalation in two-dimensional （2D） layered materials can be used to engineer the electronic structure at the atomic scale and generate tuneable physical and chemical properties which are quite distinct in comparison with the pristine material. Among them, electron-doped engineering induced by intercalation is an efficient route to modulate electronic states in 2D layers. Herein, we demonstrate a semiconducting to metallic phase transition in zirconium diselenide （ZrSe2） single crystals via controllable incorporation of copper （Cu） atoms. Our angle resolved photoemission spectroscopy （ARPES） measurements and first-principles density functional theory （DFT） calculations dearly revealed the emergence of conduction band dispersion at the M/L point of the Brillouin zone due to Cu-induced electron doping in ZrSe2 interlayers. Moreover, electrical measurements in ZrSe2 revealed semiconducting behavior, while the Cu-intercalated ZrSe2 exhibited a linear current-voltage curve with metallic character. The atomic intercalation approach may have high potential for realizing transparent electron-doping systems for many specific 2D-based nanoelectronic applications.

关键词： layered materials phase transition angle resolved photoemission spectroscopy electron doping

Impact of risk management strategies on the credit risk faced by commercial banks of Balochistan

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Financial Innovation 2019年第1期5卷 761-773页

作者： zia ur rehman Noor Muhammad Bilal Sarwar Muhammad Asif Raz Balochistan University of Information Technology Engineering&Management Sciences QuettaPakistan

This study aims to identify risk management strategies undertaken by the commercial banks of Balochistan,Pakistan,to mitigate or eliminate credit *** findings of the study are significant as commercial banks will understand the effectiveness of various risk management strategies and may apply them for minimizing credit *** explanatory study analyses the opinions of the employees of selected commercial banks about which strategies are useful for mitigating credit *** data was collected from 250 employees of commercial banks to perform multiple regression analyses,which were used for the *** results identified four areas of impact on credit risk management(CRM):corporate governance exerts the greatest impact,followed by diversification,which plays a significant role,hedging and,finally,the bank’s Capital Adequacy *** study highlights these four risk management strategies,which are critical for commercial banks to resolve their credit risk.

关键词： Credit risk Risk management strategies Financial risk Capital adequacy ratio Hedging Corporate governance Diversification

Classification of Citrus Plant Diseases Using Deep Transfer Learning

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Computers, Materials & Continua 2022年第1期70卷 1401-1417页

作者： Muhammad zia ur rehman Fawad Ahmed Muhammad Attique Khan Usman Tariq Sajjad Shaukat Jamal Jawad Ahmad Iqtadar Hussain Department of Electrical Engineering HITEC UniversityTaxilaPakistan Department of Computer Science HITEC UniversityTaxilaPakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of Mathematics College of ScienceKing Khalid UniversityAbhaSaudi Arabia School of Computing Edinburgh Napier UniversityUK Department of Mathematics Statisticsand PhysicsQatar UniversityDoha2713Qatar

In recent years,the field of deep learning has played an important role towards automatic detection and classification of diseases in vegetables and *** in turn has helped in improving the quality and production of vegetables and *** fruits arewell known for their taste and nutritional *** are one of the natural and well known sources of vitamin C and planted *** are several diseases which severely affect the quality and yield of citrus *** this paper,a new deep learning based technique is proposed for citrus disease *** different pre-trained deep learning models have been used in this *** increase the size of the citrus dataset used in this paper,image augmentation techniques are ***,to improve the visual quality of images,hybrid contrast stretching has been *** addition,transfer learning is used to retrain the pre-trainedmodels and the feature set is enriched by using feature *** fused feature set is optimized using a meta-heuristic algorithm,the Whale Optimization Algorithm(WOA).The selected features are used for the classification of six different diseases of citrus *** proposed technique attains a classification accuracy of 95.7%with superior results when compared with recent techniques.

关键词： Citrus plant disease classification deep learning feature fusion deep transfer learning

An Efficient Automated Technique for Classification of Breast Cancer Using Deep Ensemble Model

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Computer Systems Science & Engineering 2023年第7期46卷 897-911页

作者： Muhammad zia ur rehman Jawad Ahmad Emad Sami Jaha Abdullah Marish Ali Mohammed A.Alzain Faisal Saeed Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan School of Computing Edinburgh Napier UniversityEdinburghEH105DTUK Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City University15 Bartholomew RowBirminghamB55JUUK

Breast cancer is one of the leading cancers among *** has the second-highest mortality rate in women after lung *** detection,especially in the early stages,can help increase survival ***,manual diagnosis of breast cancer is a tedious and time-consuming process,and the accuracy of detection is reliant on the quality of the images and the radiologist’s ***,computer-aided medical diagnosis has recently shown promising results,leading to the need to develop an efficient system that can aid radiologists in diagnosing breast cancer in its early *** research presented in this paper is focused on the multi-class classification of breast *** deep transfer learning approach has been utilized to train the deep learning models,and a pre-processing technique has been used to improve the quality of the ultrasound *** proposed technique utilizes two deep learning models,Mobile-NetV2 and DenseNet201,for the composition of the deep ensemble *** learning models are fine-tuned along with hyperparameter tuning to achieve better ***,entropy-based feature selection is *** cancer identification using the proposed classification approach was found to attain an accuracy of 97.04%,while the sensitivity and F1 score were 96.87%and 96.76%,*** performance of the proposed model is very effective and outperforms other state-of-the-art techniques presented in the literature.

关键词： Breast cancer image enhancement ensemble model transfer learning feature selection

Tailoring of Bandgap and Spin-Orbit Splitting in ZrSe_(2) with Low Substitution of Ti for Zr

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Chinese Physics Letters 2022年第7期39卷 69-73页

作者： Sheng Wang zia ur rehman Zhanfeng Liu Tongrui Li Yuliang Li Yunbo Wu Hongen Zhu Shengtao Cui Yi Liu Guobin Zhang Li Song Zhe Sun National Synchrotron Radiation Laboratory University of Science and Technology of ChinaHefei 230029China Nanoscale Synthesis&Research Laboratory Department of Applied PhysicsUniversity of KarachiKarachi-75270Pakistan

Tuning the bandgap in layered transition metal dichalcogenides(TMDCs) is crucial for their versatile applications in many fields. The ternary formation is a viable method to tune the bandgap as well as other intrinsic properties of TMDCs, because the multi-elemental characteristics provide additional tunability at the atomic level and advantageously alter the physical properties of TMDCs. Herein, ternary Ti_(x)Zr_(1-x)Se_(2) single crystals were synthesized using the chemical-vapor-transport method. The changes in electronic structures of ZrSe_(2) induced by Ti substitution were revealed using angle-resolved photoemission spectroscopy. Our data show that at a low level of Ti substitution, the bandgap of Ti_(x)Zr_(1-x)Se_(2) decreases monotonically, and the electronic system undergoes a transition from a semiconducting to a metallic state without a significant variation of dispersions of valence bands. Meanwhile, the size of spin-orbit splitting dominated by Se 4p orbitals decreases with the increase of Ti doping. Our work shows a convenient way to alter the bandgap and spin-orbit coupling in TMDCs at the low level of substitution of transition metals.

关键词： red Tailoring of Bandgap and Spin-Orbit Splitting in ZrSe_(2)with Low Substitution of Ti for Zr

Synthesis,Crystal Structure and Spectroscopic Properties of 1,2-Benzothiazine Derivatives:An Experimental and DFT Study

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Chinese Journal of Structural Chemistry 2015年第1期34卷 15-25页

作者： MUHAMMAD Nadeem Arshad TARIQ Mahmood ATHER Faroque Khan MUHAMMAD zia-ur-rehman ABDULLAH M.Asiri ISLAM Ullah Khan RIFFAT-Un-Nisa KHurSHID Ayub AZAM Mukhtar MUHAMMAD Tariq Saeed Chemistry Department Faculty of ScienceKing Abdulaziz University Centre of Excellence for Advanced Materials Research (CEAMR) King Abdulaziz University Department of Chemistry COMSATS Institute of Information TechnologyAbbottabad IRCBM COMSATS Institute of Information Technology Applied Chemistry Research Center PCSIR Laboratories ComplexFerozpur RoadLahore 54600Pakistan Materials Chemistry Laboratory Department of ChemistryGC University Department of Chemistry College of ScienceKing Faisal University Department of Chemistry University of EducationOkara CampusOkara-Pakistan

1,2-Benzothiazine derivatives methyl 3-methoxy-4-oxo-3,4-dihydro-2H-benzo[e] [1,2]thiazine-3-carboxylate 1,1-dioxide（1） and methyl 2-ethyl-3-hydroxy-4-oxo-3,4-dihydro-2Hbenzo[e][1,2]thiazine-3-carboxylate 1,1-dioxide（2） were synthesized, and characterized by spectroscopic techniques; 1H-NMR and infrared（IR） spectroscopy. Crystals of 1 and 2 were grown by slow evaporation of methanol and ethyl acetate, respectively and their crystal structures were investigated by single-crystal X-ray diffraction analysis. Geometric properties were calculated by the B3 LYP method of density functional theory（DFT） at the 6-31G＋（d） basis set to compare with the experimental data. Simulated properties were found in strong agreement with the experimental ones. Intermolecular forces have also been modeled in order to investigate the strength of packing and strong hydrogen bonding was observed in both compounds 1 and 2. Electronic properties such as Ionization Potential（IP）, Electron Affinities（EA） and coefficients of the highest occupied molecular orbital（HOMO） and the lowest unoccupied molecular orbital（LUMO） of com- pounds 1 and 2 were simulated for the first time.

关键词： 1,2-benzothiazine B3LYP/6-31+G (d) density functional theory (DFT) HUMO-LUMO crystal structures

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基于双路径网络的端到端肺结节检测模型

计算机工程与设计 2020年第12期41卷 3503-3509页

作者：张晓宇强彦 zia ur rehman 太原理工大学信息与计算机学院山西晋中030600

为解决肺结节检测方法复杂、耗时且存在检测结果假阳性率高的问题,提出基于双路径网络(daul-path network,DPN)的肺结节自动检测模型。使用DPN自动提取深度特征,结合残差网络和密集连接网络实现特征复用;候选框提取使用三维编码解码网... 详细信息

为解决肺结节检测方法复杂、耗时且存在检测结果假阳性率高的问题,提出基于双路径网络(daul-path network,DPN)的肺结节自动检测模型。使用DPN自动提取深度特征,结合残差网络和密集连接网络实现特征复用;候选框提取使用三维编码解码网络结构,融合结节空间信息和上下文信息准确定位结节位置,生成多尺度候选框;将网络嵌入基于区域的全卷积网络框架中对结节实现分类。实验结果表明,该算法有效提高了结节检出率和检测速度,灵敏度达到90.5%,一个序列的肺部CT图像的处理时间为5.9 s。

关键词：肺结节检测 3D-UNet 特征提取双路径网络深度学习

In situ trapped high-density single metal atoms within graphene： Iron-containing hybrids as representatives for efficient oxygen reduction

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Nano Research 2018年第4期11卷 2217-2228页

作者： Daobin Liu Chuanqiang Wu Shuangming Chen Shiqing Ding Yaofeng Xie Changda Wang Tao Wang Yasir A. Haleem zia ur rehman Yuan Sang Qin Liu Xusheng Zheng Yu Wang Binghui Ge Hangxun Xu Li Song National Synchrotron Radiation Laboratory Department of Physics Department of Polymer Science and Engineering CAS Center for Excellence in Nanoscience University of Science and Technology of China Hefei 230026 China Shanghai Synchrotron Radiation Facility Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai 201204 China Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing 100190 China

Atomically dispersed catalysts have attracted attention in energy conversion applications because their efficiency and chemoselectivity for special catalysis are superior to those of traditional catalysts. However, they have limitations owing to the extremely low metal-loading content on supports, difficulty in the precise control of the metal location and amount as well as low stability at high temperatures. We prepared a highly doped single metal atom hybrid via a single-step thermal pyrolysis of glucose, dicyandiamide, and inorganic metal salts. High-angle annular dark field-scanning transmission electron microscopy （HAADF-STEM） and X-ray absorption fine structure spectroscopy （XAFS） revealed that nitrogen atoms doped into the graphene matrix were pivotal for metal atom stabilization by generating a metal-Nx coordination structure. Due to the strong anchoring effect of the graphene matrix, the metal loading content was over 4 wt.% in the isolated atomic hybrid （the Pt content was as high as 9.26 wt.% in the Pt-doped hybrid）. Furthermore, the single iron-doped hybrid （Fe@N-doped graphene） showed a remarkable electrocatalytic performance for the oxygen reduction reaction. The peak power density was - 199 mW·cm-2 at a current density of 310 mA·cm-2 and superior to that of a commercial Pt/C catalyst when it was used as a cathode catalyst in assembled zinc-air batteries. This work offered a feasible approach to design and fabricate highly doped single metal atoms （SMAs） catalysts for potential energy applications.

关键词： single metal atoms (SMAs) high loading X-ray absorption fine structure spectroscopy (XAFS) high-angle annular dark field-scanning transmission electron microscopy (HAADF-STEM) oxygen reduction reaction(ORR)