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Journal of Environmental Sciences 2009年第6期21卷 814-820页

作者： Ahmed Zahoor abdul rehman Department of Microbiology and Molecular Genetics University of the PunjabNew Campus

The present study was aimed to assess the ability of Bacillus ***-2-1 and Staphylococcus capitis to reduce hexavalent chromium into its trivalent *** ***-2-1 could tolerate Cr（Ⅵ）（4800 μg/mL） and *** could tolerate Cr（Ⅵ）（2800 μg/mL）.Both organisms were able to resist Cd^2＋（50 μg/mL）,Cu^2＋（200 μg/mL）,Pb^2＋（800 μg/mL）,Hg^2＋（50 μg/mL） and Ni2＋（4000 μg/mL）.*** resisted Zn^2＋ at 700 μg/mL while Bacillus ***-2-1 only showed resistance up to 50 μg/*** ***-2-1 and *** showed optimum growth at pH 6 and 7,respectively,while both bacteria showed optimum growth at 37°*** ***-2-1 and *** could reduce 85% and 81% of hexavalent chromium from the medium after 96 h and were also capable of reducing hexavalent chromium 86% and 89%,respectively,from the industrial effuents after 144 *** free extracts of Bacillus ***-2-1 and *** showed reduction of 83% and 70% at concentration of 10 μg Cr（Ⅵ）/mL,*** presence of an induced protein having molecular weight around 25 kDa in the presence of chromium points out a possible role of this protein in chromium *** bacterial isolates can be exploited for the bioremediation of hexavalent chromium containing wastes,since they seem to have a potential to reduce the toxic hexavalent form to its nontoxic trivalent form.

关键词： Cr(Ⅵ) reducing bacteria bioremediation Bacillus sp. JDM-2-1 Staphylococcus capitis

Numerical Investigation and Non-Axisymmetric Endwall Profiling of a Turbine Stage

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Journal of Thermal Science 2019年第4期28卷 811-825页

作者： rehman abdul LIU Bo School of Power and Energy Northwestern Polytechnical UniversityXi'an 710072China Shaanxi Key Laboratory of Internal Aerodynamics in Aero-Engine Xi’an 710072China

This paper presents an optimization of a high pressure turbine by constructing non-axisymmetric endwalls to the stator row and the rotor *** optimization was quantified by using optimization algorithms based on the multi-objective *** objective was to increase total-to-total efficiency with the constraint on the mass flow rate equal to the design point *** order to ensure that global optimum could be achieved,the function of parameters was first approximated through the artificial neural network,and then optimum was achieved by implementing the genetic *** was adopted through the design and optimization environment of FineTM/Design3 *** individual treatments of the endwalls were ***,the hub and the shroud of the stator were optimized ***,the hub of the rotor was ***,the rotor hub was optimized in the presence of the optimized *** result of the investigation showed that the optimized shape of the endwalls can significantly help to increase the efficiency up to 0.18%with the help of a reduction of the transverse pressure *** coefficient of secondary kinetic energy,entropy coefficient,spanwise mass averaged entropy were *** order to investigate the periodic effects,the design of the optimized turbine under steady simulations was confirmed through unsteady *** last part of the investigation made sure that the performance improvement remained consistent over the full operating line at off-design conditions by the implementation of non-axisymmetric endwalls.

关键词： optimization non-axisymmetric endwall high pressure turbine stage efficiency secondary kinetic energy steady unsteady off-design

Mixed Convection Heat Transfer in Micropolar Nanofluid over a Vertical Slender Cylinder

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Chinese Physics Letters 2012年第12期29卷 127-131页

作者： abdul rehman S.Nadeem Department of Mathematics University of BalochistanQuettaPakistan Department of Mathematics Quaid-i-Azam University 45320Islamabad 44000Pakistan

Analysis is carried for the problem of boundary layer steady flow and heat transfer of a micropolar fluid containing nanoparticles over a vertical *** governing partial differential equations of linear momentum,angular momentum,heat transfer and nano concentration are reduced to nonlinear coupled ordinary differential equations by applying the boundary layer approximations and a suitable similarity *** nonlinear coupled ordinary differential equations,subject to the appropriate boundary conditions,are then solved by using the homotopy analysis *** effects of the physical parameters on the flow,heat transfer and nanoparticle concentration characteristics of the model are presented through graphs and the salient features are discussed.

关键词： method. momentum boundary

COVID-19 Outbreak Prediction by Using Machine Learning Algorithms

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Computers, Materials & Continua 2023年第1期74卷 1561-1574页

作者： Tahir Sher abdul rehman Dongsun Kim Department of Creative Technologies Air UniversityIslamabad44230Pakistan School of Computer Science and Engineering Kyungpook National UniversityDaegu41566Korea

COVID-19 is a contagious disease and its several variants put under stress in all walks of life and economy as *** diagnosis of the virus is a crucial task to prevent the spread of the virus as it is a threat to life in the whole ***,with the advancement of technology,the Internet of Things(IoT)and social IoT(SIoT),the versatile data produced by smart devices helped a lot in overcoming this lethal *** mining is a technique that could be used for extracting useful information from massive *** this study,we used five supervised ML strategies for creating a model to analyze and forecast the existence of COVID-19 using the Kaggle dataset“COVID-19 Symptoms and Presence.”RapidMiner Studio ML software was used to apply the Decision Tree(DT),Random Forest(RF),K-Nearest Neighbors(K-NNs)and Naive Bayes(NB),Integrated Decision Tree(ID3)*** develop the model,the performance of each model was tested using 10-fold cross-validation and compared to major accuracy measures,Cohan’s kappa statistics,properly or mistakenly categorized cases and root means square *** results demonstrate that DT outperforms other methods,with an accuracy of 98.42%and a root mean square error of *** the future,a devisedmodel will be highly recommendable and supportive for early prediction/diagnosis of disease by providing different data sets.

关键词： COVID-19 prediction COVID-19 analysis machine learning(ML) algorithms internet of things(IoT) social IoT(SIoT)

Convolutional Neural Network Model for Fire Detection in Real-Time Environment

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Computers, Materials & Continua 2023年第11期77卷 2289-2307页

作者： abdul rehman Dongsun Kim Anand Paul School of Computer Science and Engineering Kyungpook National UniversityDaeguKorea

Disasters such as conflagration,toxic smoke,harmful gas or chemical leakage,and many other catastrophes in the industrial environment caused by hazardous distance from the peril are *** calamities are causing massive fiscal and human life ***,Wireless Sensors Network-based adroit monitoring and early warning of these dangerous incidents will hamper fiscal and social *** authors have proposed an early fire detection system uses machine and/or deep learning *** article presents an Intelligent Industrial Monitoring System(IIMS)and introduces an Industrial Smart Social Agent(ISSA)in the Industrial SIoT(ISIoT)*** proffered ISSA empowers smart surveillance objects to communicate autonomously with other *** Industrial IoT(IIoT)entity gets authorization from the ISSA to interact and work together to improve surveillance in any industrial *** ISSA uses machine and deep learning algorithms for fire-related incident detection in the industrial *** authors have modeled a Convolutional Neural Network(CNN)and compared it with the four existing models named,FireNet,Deep FireNet,Deep FireNet V2,and Efficient Net for identifying the *** train our model,we used fire images and smoke sensor *** image dataset contains fire,smoke,and no fire *** evaluation,the proposed and existing models have been tested on the *** to the comparative analysis,our CNN model outperforms other state-of-the-art models significantly.

关键词： Fire detection industrial surveillance system smart devices smart social agent(SSA) machine learning algorithms CNN

Securing Cloud Storage by Remote Data Integrity Check with Secured Key Generation

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Chinese Journal of Electronics 2021年第3期30卷 489-499页

作者： abdul rehman LIU Jian Muhammad Qasim Yasin LI Keqiu College of Intelligence and Computing Tianjin University Tianjin Key Laboratory of Advance Networking National University of Modern Languages Faisalabad Campus

In recent decades, a number of protocols for Remote data integrity checking(RDIC) have been proposed. Identity(ID) based RDIC protocols are constructed to guarantee cloud data integrity and data privacy. The known protocols for RDIC always assume that the Private key generator(PKG) is a trusted one, but in real-world applications by corrupt PKG, malicious Cloud server(CS) can easily cheat the third party auditor that the data owner’s outsourced data are kept safe through the data has been deleted or altered. In this paper, we explore the novel model of RDIC with untrusted PKG and malicious CS, by employing the partial key method and Authentication, authorization, accounting(AAA) *** construct a new ID-based RDIC, which provides the ID revocation and key updation. The experimental evaluations show that our scheme is more efficient than known ones.

关键词： key updation outsourcing storage management cryptographic protocols secured key generation private key cryptography data integrity Remote data integrity check public key cryptography data privacy RDIC protocols Remote data integrity checking cloud computing data owner Cloud storage Private key generator known protocols partial key method ID-based RDIC cloud data integrity malicious Cloud server

Exploiting Data Science for Measuring the Performance of Technology Stocks

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Computers, Materials & Continua 2023年第9期76卷 2979-2995页

作者： Tahir Sher abdul rehman Dongsun Kim Imran Ihsan Department of Creative Technologies Air UniversityIslamabad44230Pakistan School of Computer Science and Engineering Kyungpook National UniversityDaegu41566Korea

The rise or fall of the stock markets directly affects investors’interest and ***,it is necessary to measure the performance of stocks in the market in advance to prevent our assets from suffering significant *** our proposed study,six supervised machine learning(ML)strategies and deep learning(DL)models with long short-term memory(LSTM)of data science was deployed for thorough analysis and measurement of the performance of the technology *** discussion are Apple Inc.(AAPL),Microsoft Corporation(MSFT),Broadcom Inc.,Taiwan Semiconductor Manufacturing Company Limited(TSM),NVIDIA Corporation(NVDA),and Avigilon Corporation(AVGO).The datasets were taken from the Yahoo Finance API from 06-05-2005 to 06-05-2022(seventeen years)with 4280 *** already noted,multiple studies have been performed to resolve this problem using linear regression,support vectormachines,deep long short-termmemory(LSTM),and many other *** this research,the Hidden Markov Model(HMM)outperformed other employed machine learning ensembles,tree-based models,the ARIMA(Auto Regressive IntegratedMoving Average)model,and long short-term memory with a robust mean accuracy score of *** statistical analyses and measurements for machine learning ensemble algorithms,the Long Short-TermModel,and ARIMA were also carried out for further investigation of the performance of advanced models for forecasting time series ***,the proposed research found the best model to be HMM,and LSTM was the second-best model that performed well in all aspects.A developedmodel will be highly recommended and helpful for early measurement of technology stock performance for investment or withdrawal based on the future stock rise or fall for creating smart environments.

关键词： Machine learning data science smart environments stocks movement deep learning stock marketing

Segregation behavior of magnetic ions in continuous flowing solution under gradient magnetic field

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Chinese Physics B 2016年第7期25卷 286-293页

作者：冀冰吴平任菡张师平 abdul rehman 王立 Department of Physics School of Mathematics and Physics University of Science and Technology Beijing School of Mechanical Engineering University of Science and Technology Beijing

The research of magnetic separation starts from magnetic solid particles to nanoparticles, and in the research progress,particles become smaller gradually with the development of application of magnetic separation technology. Nevertheless,little experimental study of magnetic separation of molecules and ions under continuous flowing conditions has been reported. In this work, we designed a magnetic device and a ＂layered＂ flow channel to study the magnetic separation at the ionic level in continuous flowing solution. A segregation model was built to discuss the segregation behavior as well as the factors that may affect the separation. The magnetic force was proved to be the driving force which plays an indispensable role leading to the segregation and separation. The flow velocity has an effect on the segregation behavior of magnetic ions,which determines the separation result. On the other hand, the optimum flow velocity which makes maximum separation is related to the initial concentration of solution.

关键词： magnetic ions magnetic separation segregation enrichment

Conservation status evaluation of Berberis species across the Karakoram Mountain Ranges, Pakistan using IUCN Red List Categories and Criteria

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Journal of Forestry Research 2016年第6期27卷 1385-1390页

作者： Tika Khan Imtiaz Ahmed Khan abdul rehman Nisar Ahmed Integrated Mountain Area Research Centre Karakoram International University Department of Biological Sciences Karakoram International University Centre of Agriculture Biochemistry and Biotechnology University of Agriculture Faisalabad

Berberis species medicinal plants in Pakistan are endangered, high-value with important eco-cultural, commercial and livelihood roles in mountain communities. To assess the geographical distribution of Berberis species across the Karakoram Mountain Ranges in Pakistan, we used IUCN Red List Categories and Criteria （2001） to calculate the extent of occurrence （EOO, 〈100 km^2） and the area of occupancy （AOO, 〈10 km^2） of Berberis pseudumbellata subsp, pseudumbellata and B. pseudumbellata subsp. gilgitica. Overgrazing and habitat loss were key population- limiting factors. The two subspecies had contrasting responses to temperature, elevation, precipitation and insect susceptibility. B. pseudumbellata subsp, gilgitica is endemic to Gilgit-Baltistan and grows in single-cropping zone （ar- eas 〉 200 m a.s.1.）. Status evaluation revealed that both subspecies meet the criteria set for critically endangered species. Prolonged disregard of its declining population trend might lead to its extinction; therefore, integrated con- servation efforts are necessary.

关键词： Berberis Ecological zonation Critically endangered Extent of occurrence Karakoram Occupation area Spatial distribution

Privacy Preserved Brain Disorder Diagnosis Using Federated Learning

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Computer Systems Science & Engineering 2023年第11期47卷 2187-2200页

作者： Ali Altalbe abdul rehman Javed Department of Computer Science Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon

Federated learning has recently attracted significant attention as a cutting-edge technology that enables Artificial Intelligence(AI)algorithms to utilize global learning across the data of numerous individuals while safeguarding user data *** advanced healthcare technologies have enabled the early diagnosis of various cognitive ailments like Parkinson’*** user data is frequently used to train machine learning models for healthcare systems to track the health status of *** healthcare industry faces two significant challenges:security and privacy issues and the personalization of cloud-trained AI *** paper proposes a Deep Neural Network(DNN)based approach embedded in a federated learning framework to detect and diagnose brain *** extracted the data from the database of Kay Elemetrics voice disordered and divided the data into two windows to create training models for two clients,each with different *** lessen the over-fitting aspect,every client reviewed the outcomes in three *** proposed model identifies brain disorders without jeopardizing privacy and *** results reveal that the global model achieves an accuracy of 82.82%for detecting brain disorders while preserving privacy.

关键词： Privacy preservation brain disorder detection Parkinson’s disease diagnosis federated learning healthcare machine learning