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A probe into the medicinal potential of Viola canescens-A threatened medicinal plant from Himalaya

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Journal of Coastal Life Medicine 2016年第7期4卷 575-579页

作者： Sidra Sabir Abida Akram Naveed Iqbal Raja zia-ur-rehman mashwani Sohail Huma Mehreen Sadaf Mubashir Hussain Iqra Riaz Nabeela Ahmad Ejaz Ahmed Department of Botany PMAS-Arid Agriculture UniversityRawalpindiPakistan

Viola canescens *** *** a perennial herb belonging to family Violaceae,and it is almost cosmopolitan in *** plant is widely used in Ayurveda and Unani medicinal systems for curing various ailments,most commonly for cough and *** studies releaved that this plant is rich in secondary *** plant revealed significant antimicrobial,anti-inflamatory,antioxidant,hepatoprotective,laxative,analgesic as well as antitumor *** to all these important pharmacological activities,market demand of Viola canescens is increasing day by day and this plant is facing tremendous over exploitation and becomes a threatened plant according to International Union for Conservation of Nature and Natural *** present review compiles that the ethnobotanical,phytochemical and pharmacological aspects of the plant need to be conserved.

关键词： Viola canescens Medicinal systems Secondary metabolites Pharmacological activities

Potential for Pakistani traditional medicinal plants to combat diabetes

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Journal of Traditional Chinese Medicine 2014年第4期34卷 488-490页

作者： mashwani zia-ur-rehman Khan Mirajab Ahmad Mushtaq Department of Botany Pir Mehr Ali Shah Arid Agriculture University Rawalpindi 46300 Pakistan Department of Plant Sciences QuaidiAzam UniversityIslamabad 45320Pakistan Department of Plant Sciences QuaidiAzam UniversityIslamabad 45320Pakistan

OBJECTIVE: To investigate the potential of medicinal plants used in traditional healing in Pakistan to inhibit the glycation process. This may be useful in combatting diabetes mellitus and its ***: The in vitro antiglycation activity of 10 medicinal plants was examined by testing the ability of the extracts to inhibit the methyl-glyoxal-mediated development of fluorescence of bovine ***: Of the tested plants, Persicaria barbata,Geranium collinum and Berberis lyciumshowed significant inhibition of the formation of advanced glycation end products. The inhibitory capacity of these plants was 68.89%, 62.06% and 54.23%, respectively, compared with the positive control(rutin; 86%). All other plants inhibited AGE formation ***:These findings will be helpful for further research into the use of traditional herbal medicines with antiglycation properties in the treatment of diabetes.

关键词：药用植物抗糖尿病巴基斯坦传统晚期糖基化终产物抑制能力并发症乙二醛

Emotion Recognition from Occluded Facial Images Using Deep Ensemble Model

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Computers, Materials & Continua 2022年第12期73卷 4465-4487页

作者： zia Ullah Muhammad Ismail Mohmand Sadaqat ur rehman Muhammad Zubair Maha Driss Wadii Boulila Rayan Sheikh Ibrahim Alwawi Department of Computer Science The Brains InstitutePeshawar25000Pakistan School of Natural and Computing Sciences University of AberdeenAberdeenUK Department of Neurosciences KU Leuven Medical SchoolLeuven3000Belgium Security Engineering Laboratory CCISPrince Sultan UniversityRiyadh12435Saudi Arabia Robotics and Internet of Things Lab Prince Sultan UniversityRiyadh12435Saudi Arabia Department of Computer Science Robert Gordon UniversityAberdeenUK

Facial expression recognition has been a hot topic for decades,but high intraclass variation makes it *** overcome intraclass variation for visual recognition,we introduce a novel fusion methodology,in which the proposed model first extract features followed by feature ***,RestNet-50,VGG-19,and Inception-V3 is used to ensure feature learning followed by feature ***,the three feature extraction models are utilized using Ensemble Learning techniques for final expression *** representation learnt by the proposed methodology is robust to occlusions and pose variations and offers promising *** evaluate the efficiency of the proposed model,we use two wild benchmark datasets Real-world Affective Faces Database(RAF-DB)and AffectNet for facial expression *** proposed model classifies the emotions into seven different categories namely:happiness,anger,fear,disgust,sadness,surprise,and ***,the performance of the proposed model is also compared with other algorithms focusing on the analysis of computational cost,convergence and accuracy based on a standard problem specific to classification applications.

关键词： Ensemble learning emotion recognition feature fusion occlusion

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

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

Techno-economic assessment of energy generation through municipal solid waste:a case study for small/medium size districts in Pakistan

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Waste Disposal and Sustainable Energy 2020年第4期2卷 337-350页

作者： Ubaid ur rehman zia Tanzeel ur Rashid Muzaffar Ali Waqas Nazir Awan Sustainable Development Policy Institute IslamabadPakistan Mechanical Engineering Department University of Engineering and TechnologyTaxilaPakistan

There is an increase in annual waste generation due to urbanization,industrialization,and population *** waste management crisis in developing countries and its complexity from region to region has inspired extensive research work in this *** management not only results in environmental hazards,but it also causes significant socio-economic *** to the absence of comprehensive studies on waste to energy(WTE)assessment,this study assesses and reports the merits of alternative technologies for converting WTE in small and medium-size *** analysis for waste collection data in this study uses a pilot study approach to provide useful insights and waste classification.A cantonment district of Pakistan(Wah Cantt)has been used as a case study for performing a technological and economic assessment of energy generation through the use of thermal and biological treatment processes.A mathematical modeling approach has been adopted for generating an economic value of each technology through which this waste can be ***,the levelized cost of energy(LCOE)based assessment has been performed to provide a methodological framework for selecting the most feasible WTE technology in a small or medium-size *** on the model results,anaerobic digestion appears to be the most sustainable technology due to the organic nature of waste in Wah Cantt,land legislation,and availability of area to install a waste *** all the waste collected,the district can generate approximately 14.4 MW of energy through thermal treatment,19,110 m^(3) of daily biogas through anaerobic digestion,and 5 million tons of fertilizer through ***,if a proper supply chain is established for converting a portion of Pakistan’s annual waste generation,a significant amount of waste energy potential can be restored.

关键词： Municipal solid waste Waste to energy Levelized cost of energy Technological assessment Economic assessment

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