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Chinese Physics C 2015年第7期39卷 6-11页

作者： ali Zaman Mais Suleymanov muhammad Ajaz Kamal Hussain Khan Department of Physics COMSATS Institute of Information Technology Department of Physics Abdul Wali Khan University Mardan

We investigate the effects of jet production on the following parameters： pseudorapidity, transverse momentum and transverse mass distributions of secondary charged particles produced in pp-collisions at 1.8 Te V,using the HIJING code. These distributions are analyzed for the whole range and for six selected regions of the polar angle as a function of the different number of jets. The obtained simulation results for these parameters are interpreted and discussed in connection to the increase observed in the multiplicity of secondary charged particles as a result of its multi-jet dependence, and are also discussed in comparison with the experimental results from the CDF Collaboration.

关键词： jet production charged particles in pp-interactions HIJING pseudorapidity transverse momentum transverse mass

Ensemble Learning Models for Classification and Selection of Web Services: A Review

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Computer Systems Science & Engineering 2022年第1期40卷 327-339页

作者： muhammad Hasnain Imran Ghani Seung Ryul Jeong Aitizaz ali Monash University Petaling Jaya46150Malaysia Indiana University of Pennsylvania IndianaPA 15705USA Kookmin University Seoul02707Korea

This paper presents a review of the ensemble learning models proposed for web services classification,selection,and *** service is an evo-lutionary research area,and ensemble learning has become a hot spot to assess web services’earlier mentioned *** proposed research aims to review the state of art approaches performed on the interesting web services *** literature on the research topic is examined using the preferred reporting items for systematic reviews and meta-analyses(PRISMA)as a research *** study reveals an increasing trend of using ensemble learning in the chosen papers within the last ten ***ïve Bayes(NB),Support Vector Machine’(SVM),and other classifiers were identified as widely explored in selected *** analysis of web services classification suggests that web services’performance aspects can be investigated in future *** paper also identified performance measuring metrics,including accuracy,precision,recall,and f-measure,widely used in the literature.

关键词： Web services composition quality improvement class imbalance machine learning

Opportunities and Challenges in Advancing Plant Research with Single-cell Omics

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Genomics, Proteomics & Bioinformatics 2024年第2期22卷 13-26页

作者： Mohammad Saidur Rhaman muhammad ali Wenxiu Ye Bosheng Li Peking University Institute of Advanced Agricultural Sciences Shandong Laboratory of Advanced Agricultural Sciences in WeifangWeifang 261325China

Plants possess diverse cell types and intricate regulatory mechanisms to adapt to the ever-changing environment of *** strategies have been employed to study cell types and their developmental progressions,including single-cell sequencing methods which provide high-dimensional catalogs to address biological *** recent years,single-cell sequencing technologies in transcriptomics,epigenomics,proteomics,metabolomics,and spatial transcriptomics have been increasingly used in plant science to reveal intricate biological relationships at the single-cell ***,the application of single-cell technologies to plants is more limited due to the challenges posed by cell *** review outlines the advancements in single-cell omics technologies,their implications in plant systems,future research applications,and the challenges of single-cell omics in plant systems.

关键词： Multi-omics Single-cell transcriptomics Spatial transcriptomics Single-cell epigenomics Single-cell proteomics

Severity Recognition of Aloe vera Diseases Using AI in Tensor Flow Domain

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Computers, Materials & Continua 2021年第2期66卷 2199-2216页

作者： Nazeer muhammad Rubab Nargis Bibi Oh-Young Song muhammad Attique Khan Sajid ali Khan Department of IT&CS Pak-Austria Fachhochschule Institute of Applied Sciences and TechnologyHaripur22620Pakistan COMSATS University Islamabad Wah CampusWah Cantt47040Pakistan Fatima Jinnah Women University Rawalpindi44000Pakistan Software Department Sejong UniversitySeoulSouth Korea Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Software Engineering Foundation University IslamabadIslamabadPakistan

Agriculture plays an important role in the economy of all ***,plant diseases may badly affect the quality of food,production,and ultimately the *** plant disease detection and management,agriculturalists spend a huge amount of ***,the manual detection method of plant diseases is complicated and ***,automated systems for plant disease detection using machine learning(ML)approaches are ***,most of the existing ML techniques of plants diseases recognition are based on handcrafted features and they rarely deal with huge amount of input *** address the issue,this article proposes a fully automated method for plant disease detection and recognition using deep neural *** the proposed method,AlexNet and VGG19 CNNs are considered as pre-trained *** is capable to obtain the feature extraction of the given data with fine-tuning *** convolutional neural network feature extraction,it selects the best subset of features through the correlation coefficient and feeds them to the number of classifiers including K-Nearest Neighbor,Support Vector Machine,Probabilistic Neural Network,Fuzzy logic,and Artificial Neural *** validation of the proposed method is carried out on a self-collected dataset generated through the augmentation *** achieved average accuracy of our method is more than 96%and outperforms the recent techniques.

关键词： Plants diseases wavelet transform fast algorithm deep learning feature extraction classification

Mass Transfer of MHD Nanofluid in Presence of Chemical Reaction on A Permeable Rotating Disk with Convective Boundaries, Using Buongiorno’s Model

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Computer Modeling in Engineering & Sciences 2018年第7期116卷 31-49页

作者： muhammad Shoaib Arif Yasir Nawaz Mairaj Bibi Zafar ali Department of Mathematics Air UniversityPAF Complex E-9Islamabad44000Pakistan Department of Mathematics Comsats UniversityPark Road Chak Shahzad CampusIslamabad44000Pakistan

This communiquéis opted to study the flow of nanofluid because of heated disk rotation subjected to the convective boundaries with chemical reaction of first *** Buongiorno’s model for nanofluids is used due to its wide range of applications and the rotating disk under investigation is *** magneto Reynolds parameter and boundary layer assumptions are carried out to formulate the *** system of nonlinear partial differential equations governing the flow problem is converted into the set of ordinary differential equations by using particular relations known as Von Karman *** complicated set of coupled ordinary differential equations with complicated boundary conditions is set to solve by an analytical technique Homotopy Analysis Method(HAM).Whereby the results obtained by the aforementioned method are provided analytically and analyzed *** validation of the work is confirmed by providing comparison of previous works in tabular *** of chemical reaction parameter on mass transfer rate is also highlighted tabularly for its *** and Sherwood numbers calculated and compared to the like literature and found in good agreement.

关键词： Chemical reaction rotating disk nanoparticles velocity slip magnetic effect.

Interrelationships between Deformation and Metamorphic Events across the Western Hinterland Zone, NW Pakistan

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Journal of Earth Science 2016年第4期27卷 584-598页

作者： Asghar ali Mustafa Yar muhammad Asif Khan Shah Faisal Department of Geology University of Peshawar Department of Earth and Environmental Sciences Bahria University National Centre of Excellence in Geology University of Peshawar Earth and Environmental Sciences IKBAS University of British Columbia

Microscopic to mesoscopic structural investigations and foliation intersection axes（FIAs） preserved in porphyroblasts reveal a very complex history of deformation and tectonism within the southwestern part of the western hinterland zone along the northern margin of the Indian plate, NW Pakistan. D_1, D_2, and D_3 related structures in the southwestern part resemble the F_1/F_2, F_3, and F_4 related structures in the northeastern part of the western hinterland zone. These structures developed at the same time through the same changes in the direction of bulk shortening in southwestern and northeastern parts of the western hinterland zone. FIA set 1 indicates NW-SE shortening. The D_2 fabrics, mineral lineations and fold axes indicate E-W shortening. FIA set 2, D_3 fold axes and mineral lineations indicate NNE-SSW shortening. D_3 deformation event is equivalent to the F_4 deformation event in the northeastern part of the western hinterland zone. D_4 fold axes, mineral stretching lineations and axial plane foliation suggest ENE-WSW shortening. The D_4 NNW-SSE fabrics, which formed in the region after the formation of the MMT（main mantle thrust）, Khairabad-Panjal thrust fault, Hissartang thrust fault and MBT（main boundary thrust）, likely resulted from ENE-WSW bulk shortening related to development of the Hazara-Kashmir syntaxis.

关键词： FIA western hinterland zone microstructure mesostructure metamorphism tectonics,NW Pakistan.

Stochastic Computational Approach for Complex Nonlinear Ordinary Differential Equations

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Chinese Physics Letters 2011年第2期28卷 20-23页

作者： Junaid ali Khan muhammad Asif Zahoor Raja Ijaz Mansoor Qureshi Department of Electronic Engineering International Islamic UniversityIslamabadPakistan Department of Electrical Engineering Air UniversityIslamabadPakistan

We present an evolutionary computational approach for the solution of nonlinear ordinary differential equations(NLODEs).The mathematical modeling is performed by a feed-forward artificial neural network that defines an unsupervised *** training of these networks is achieved by a hybrid intelligent algorithm,a combination of global search with genetic algorithm and local search by pattern search *** applicability of this approach ranges from single order NLODEs,to systems of coupled differential *** illustrate the method by solving a variety of model problems and present comparisons with solutions obtained by exact methods and classical numerical *** solution is provided on a continuous finite time interval unlike the other numerical techniques with comparable *** the advent of neuroprocessors and digital signal processors the method becomes particularly interesting due to the expected essential gains in the execution speed.

关键词： technique methods ordinary

A Machine Learning Approach for Early COVID-19 Symptoms Identification

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Computers, Materials & Continua 2022年第2期70卷 3803-3820页

作者： Omer ali Mohamad Khairi Ishak muhammad Kamran Liaquat Bhatti School of Electrical and Electronic Engineering Universiti Sains Malaysia(USM)Nibong Tebal14300PenangMalaysia Department of Electrical Engineering NFC Institute of Engineering and Technology(NFC IET)Multan60000Pakistan

Symptom identification and early detection are the first steps towards a health condition ***-19 virus causes pneumonialike symptoms such as fever,cough,and shortness of ***-19 contraction tests necessitate extensive clinical protocols in medical *** studies help with the accurate analysis of COVID-19,where the virus has already spread to the lungs in most *** majority of existing supervised machine learning-based disease detection techniques are based on clinical data like x-rays and computerized *** is heavily reliant on a larger clinical study and does not emphasize early symptom *** aim of this study is to investigate anomalies in patient physiological data for early COVID-19 symptoms *** this context,two of the most prevalent symptoms,fever and cough,were examined in a two-fold manner utilizing an unsupervised machine *** examine disease progression,physiological features from a chest-worn device were ***,a Single Vector Activity Index(SVAI)parameter is proposed to monitor the breathing and cough ***,the dataset’s variance is examined using the DBSCAN method for clustering and outlier ***,the model accuracy is evaluated to identify outliers on real-time data based on feature dissimilarities,yielding an overall detection accuracy of 90.34%.

关键词： COVID-19 symptoms identification machine learning dbscan

Suitable energy platform significantly improves charge separation of g-C3N4 for CO2 reduction and pollutant oxidation under visible-light

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Progress in Natural Science:Materials International 2019年第2期29卷 138-144页

作者： Amir Zada Nauman ali Fazle Subhan Natasha Anwar muhammad Ishaq ali Shah muhammad Ateeq Zahid Hussain Khair Zaman Momin Khan Department of Chemistry Abdul Wali Khan University Key Laboratory of Functional Inorganic Materials Chemistry (Heilongjiang University) Ministry of Education School of Chemistry and Materials Science International Joint Research Center for Catalytic Technology Institute of Chemical Sciences University of Peshawar

The photocatalytic activities of g-C3N4can be significantly improved by increasing life time of the photogenerated charges. Here, in this work we introduced TiO2as proper energy platform to accept the photogenerated electrons from g-C3N4during photocatalysis. The nanophotocatalysts formed from the combination of a suitable amount of TiO2nanoparticles and g-C3N4nanosheets showed 8.75 and 4.22% enhancement in photocatalytic activities for CO2reduction and 2-chlorophenol(2-CP) degradation under visible light illumination as compared to bare g-C3N4. Based on the surface photovoltage spectra, photoluminescence spectra and examination of formed hydroxyl radicals, it was confirmed that these enhanced photoactivities were attributed to the much-improved charge separation via the electron transfer from g-C3N4to TiO2. From trapping experiments,it was found that hydroxyl radicals were the major species involved in the photocatalytic degradation of *** study is helpful to synthesize efficient photocatalysts to cope with energy and environmental issues.

关键词： Nanophotocatalyst Charge separation CO2 reduction Pollutant degradation

Intrusion Detection Based on Bidirectional Long Short-Term Memory with Attention Mechanism

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Computers, Materials & Continua 2023年第1期74卷 801-815页

作者： Yongjie Yang Shanshan Tu Raja Hashim ali Hisham Alasmary muhammad Waqas muhammad Nouman Amjad Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information TechnologyBeijing University of TechnologyBeijing100124China Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan Department of Computer Science College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Information Security and Cybersecurity Unit King Khalid UniversityAbhaSaudi Arabia Computer Engineering Department College of Information TechnologyUniversity of Bahrain32038Bahrain School of Engineering Edith Cowan UniversityJoondalup PerthWA6027Australia School of Engineering University of Management and TechnologyLahorePakistan

With the recent developments in the Internet of Things(IoT),the amount of data collected has expanded tremendously,resulting in a higher demand for data storage,computational capacity,and real-time processing *** computing has traditionally played an important role in establishing ***,fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility,location awareness,heterogeneity,scalability,low latency,and geographic ***,IoT networks are vulnerable to unwanted assaults because of their open and shared *** a result,various fog computing-based security models that protect IoT networks have been developed.A distributed architecture based on an intrusion detection system(IDS)ensures that a dynamic,scalable IoT environment with the ability to disperse centralized tasks to local fog nodes and which successfully detects advanced malicious threats is *** this study,we examined the time-related aspects of network traffic *** presented an intrusion detection model based on a twolayered bidirectional long short-term memory(Bi-LSTM)with an attention mechanism for traffic data classification verified on the UNSW-NB15 benchmark *** showed that the suggested model outperformed numerous leading-edge Network IDS that used machine learning models in terms of accuracy,precision,recall and F1 score.

关键词： Fog computing intrusion detection bi-LSTM attention mechanism