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Efficient Data Augmentation Techniques for Improved Classification in Limited Data Set of Oral Squamous Cell Carcinoma

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Computer modeling in Engineering & Sciences 2022年第6期131卷 1387-1401页

作者： Wael Alosaimi m.irfan Uddin Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan

Deep Learning(DL)techniques as a subfield of data science are getting overwhelming attention mainly because of their ability to understand the underlying pattern of data in making *** techniques require a considerable amount of data to efficiently train the DL ***,when the data size is larger,the DL models perform ***,it is not possible to have a considerable amount of data in different domains such as *** healthcare,it is impossible to have a substantial amount of data to solve medical problems using Artificial Intelligence,mainly due to ethical issues and the privacy of *** solve this problem of small dataset,different techniques of data augmentation are used that can increase the size of the training ***,these techniques only change the shape of the image and hence the classification model does not increase *** Adversarial Networks(GANs)are very powerful techniques to augment training data as new samples are *** technique helps the classification models to increase their *** this paper,we have investigated augmentation techniques in healthcare image *** objective of this research paper is to develop a novel augmentation technique that can increase the size of the training set,to enable deep learning techniques to achieve higher *** have compared the performance of the image classifiers using the standard augmentation technique and *** results demonstrate that GANs increase the training data,and eventually,the classifier achieves an accuracy of 90%compared to standard data augmentation techniques,which achieve an accuracy of up to 70%.Other advanced CNN models are also tested and have demonstrated that more deep architectures can achieve more than 98%accuracy for making classification on Oral Squamous Cell Carcinoma.

关键词： Data science deep learning data augmentation classification data manipulation

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PeachNet: Peach Diseases Detection for Automatic Harvesting

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Computers, materials & Continua 2021年第5期67卷 1665-1677页

作者： Wael Alosaimi Hashem Alyami m.irfan Uddin Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan

To meet the food requirements of the seven billion people on Earth,multiple advancements in agriculture and industry have been *** main threat to food items is from diseases and pests which affect the quality and quantity of *** scientific mechanisms have been developed to protect plants and fruits from pests and diseases and to increase the quantity and quality of *** these mechanisms require manual efforts and human expertise to diagnose *** the current decade Artificial Intelligence is used to automate different processes,including agricultural processes,such as automatic *** Learning techniques are becoming popular to process images and identify different *** can use machine Learning algorithms for disease identification in plants for automatic harvesting that can help us to increase the quantity of the food produced and reduce crop *** this paper,we develop a novel Convolutional Neural Network(CNN)model that can detect diseases in peach plants and *** proposed method can also locate the region of disease and help farmers to find appropriate treatments to protect peach *** the detection of diseases in Peaches VGG-19 architecture is *** the localization of disease regions mask R-CNN is *** proposed technique is evaluated using different techniques and has demonstrated 94%*** hope that the system can help farmers to increase peach production to meet food demands.

关键词： Convolutional neural network computer vision image processing segmentation plant diseases

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magnetohydrodynamic Stagnation Point Flow of a maxwell Nanofluid with Variable Conductivity

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Communications in Theoretical Physics 2019年第12期71卷 1493-1500页

作者： m.irfan m.Khan W.A.Khan m.Alghamdi Department of mathematics Quaid-i-Azam UniversityIslamabad 44000Pakistan School of mathematics and Statistics Beijing Institute of TechnologyBeijing 100081China Department of mathematics Faculty of ScienceKing Khalid UniversityAbha 61413Kingdom of Saudi Arabia

This article reports the simultaneous properties of variable conductivity and chemical reaction in stagnation point flow of magneto maxwell *** Buongiorno’s theory has been established to picture the inducement of Brownian and thermophrotic diffusions ***,the aspect of heat sink/source is *** homotopic analysis method(HAm)has been worked out for the solution of nonlinear *** behavior of inferential variables on the velocity,temperature,concentration and local Nusselt number for maxwell nanofluid are sketched and *** attained outcomes specify that both the temperature and concentration of maxwell fluid display analogous behavior,while the depiction of Brownian motion is quite conflicting on both temperature and concentration *** is further noted that the influence of variable thermal conductivity on temperature field is similar to that of Brownian motion ***,for the confirmation of our study comparison tables are reported.

关键词： maxwell nanofluid stagnation point flow magnetohydrodynamic(mHD) variable conductivity chemical reaction

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municipal solid waste landfill site selection for the city of Sanliurfa-Turkey:an example using mCDA integrated with GIS

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International Journal of Digital Earth 2012年第2期5卷 147-164页

作者： m.irfan Yesilnacar m.Lutfi Suzen Basak Sener Kaya Vedat Doyuran Department of Environmental Engineering Harran UniversityS¸anliurfaTurkey Department of Geological Engineering Middle East Technical UniversityAnkaraTurkey Colorado School of mines Division of EngineeringGoldenCOUSA

A municipal solid waste(mSW)management system needs solid waste management(SWm)techniques where the presence of a sanitary landfill is *** of the most important issues of sanitary landfilling is to locate the facility to an optimal *** the versatility and case-dependent nature of conventional expert-based site selection procedures,the number of sites to be chosen increases with increased population forcing a number of ***quently,constraints and environmental regulations mechanically mask unsuitable areas,leaving very little areas to be *** turns the situation into a challenging issue for a geographical information system(GIS)used with multicriteria decision analysis(mCDA),to select optimal *** study aims to apply mCDA integrated with GIS to select possible sites of a mSW landfill with the same expert and same cognitive parameters while compared with the already present *** of this study revealed that conventional expert-based methods could not always evaluate all constraints at the same time and map reproduction is limited when parameter maps are changing rapidly in *** order to produce cognitive and reproducible analyses,GIS with mCDA integration offers a good solution for site selection issue and forms a good alternative for conventional methods.

关键词： municipal solid waste(mSW) landfill site selection geographical information systems(GIS) multi-criteria decision analysis(mCDA)

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Drought-mediated modulation in metabolomic Profiling of Nigella Sativa Leaf, Growth, Ecophysiology and Antioxidants

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Phyton-International Journal of Experimental Botany 2023年第12期92卷 3323-3344页

作者： Khalid Rehman Hakeem Hesham F.Alharby m.irfan Qureshi Department of Biological Sciences Faculty of ScienceKing Abdulaziz UniversityJeddahSaudi Arabia Princess Dr.Najla Bint Saud Al-Saud Center for Excellence Research in Biotechnology King Abdulaziz UniversityJeddahSaudi Arabia Department of Public Health Daffodil International UniversityDhakaBangladesh Department of Biotechnology Jamia Millia IslamiaNew DelhiIndia

Abiotic stresses,including drought,have been found to affect the growth and medicinal quality of numerous *** proposed study aims to study the effects of different drought regimes on the metabolic profile,growth,ecophysiology,cellular antioxidants,and antioxidant potential of Nigella sativa(Black cumin)***-day-old seedlings of *** were exposed to three regimes of drought(control,moderate and high)for a ***/mS metabolic profile of the leaf reveals the presence of more than a hundred metabolites belonging to anthocyanins,chalcones,dihydro flavonoids,flavonoids,flavanols,flavones,flavonoid carbonoside,isoflavones,*** was found to alter the contents of identified *** stress-induced oxidative stress and increased production of hydrogen peroxide and superoxide *** changes,activities of antioxidant enzymes,contents of antioxidants,and proline were significantly high under drought to protect against the low water ***,stressed leaf extract had higher antioxidant ***,*** leaf bears multiple metabolic pathways and can tolerate a higher degree of drought or osmotic stress.

关键词： Nigella sativa metabolomics drought antioxidant mechanism flavonoids

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Speech Recognition-Based Automated Visual Acuity Testing with Adaptive mel Filter Bank

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Computers, materials & Continua 2022年第2期70卷 2991-3004页

作者： Shibli Nisar muhammad Asghar Khan Fahad Algarni Abdul Wakeel m.irfan Uddin Insaf Ullah Department of Electrical Engineering National University of Sciences and Technology(NUST)Islamabad44000Pakistan Hamdard Institute of Engineering&Technology Islamabad44000Pakistan College of Computing and Information Technology University of BishaBishaSaudi Arabia Institute of Computing Kohat University of Science and TechnologyKohatPakistan

One of the most commonly reported disabilities is vision loss,which can be diagnosed by an ophthalmologist in order to determine the visual system of a *** procedure,however,usually requires an appointment with an ophthalmologist,which is both time-consuming and expensive *** issues that can arise include a lack of appropriate equipment and trained practitioners,especially in rural *** on a cognitively motivated attribute extraction and speech recognition approach,this paper proposes a novel idea that immediately determines the eyesight *** proposed system uses an adaptive filter bank with weighted mel frequency cepstral coefficients for feature *** adaptive filter bank implementation is inspired by the principle of spectrum sensing in cognitive radio that is aware of its environment and adapts to statistical variations in the input stimuli by learning from the *** performance evaluation demonstrates the potential of our automated visual acuity test method to achieve comparable results to the clinical ground truth,established by the expert ophthalmologist’s *** overall accuracy achieved by the proposed model when compared with the expert ophthalmologist test is 91.875%.The proposed method potentially offers a second opinion to ophthalmologists,and serves as a cost-effective pre-screening test to predict eyesight loss at an early stage.

关键词： Eyesight test speech recognition Hmm SVm feature extraction

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An Efficient Proxy Blind Signcryption Scheme for IoT

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Computers, materials & Continua 2022年第3期70卷 4293-4306页

作者： Aamer Khan Insaf Ullah Fahad Algarni muhammad Naeem m.irfan Uddin muhammad Asghar Khan Department of Information Technology Abbottabad University of Science and TechnologyAbbotabadPakistan Hamdard Institute of Engineering and Technology Islamabad44000Pakistan College of Computing and Information Technology University of BishaBishaSaudi Arabia Institute of Computing Kohat University of Science and TechnologyKohatPakistan

Recent years have witnessed growing scientific research interest in the Internet of Things(IoT)technologies,which supports the development of a variety of applications such as health care,Industry 4.0,agriculture,ecological data management,and other various *** utilizes the Internet as a prime medium of communication for both single documents as well as multi-digital ***,due to the wide-open nature of the Internet,it is important to ensure the anonymity,untraceably,confidentiality,and unforgeability of communication with efficient computational complexity and low *** designed a light weight and secure proxy blind signcryption for multi-digital messages based on a hyperelliptic curve(HEC).Our results outperform the available schemes in terms of computational cost and communication *** designed scheme also has the desired authentication,unforgeability of warrants and/or plaintext,confidentiality,integrity,and blindness,***,our scheme is more suitable for devices with low computation power such as mobiles and tablets.

关键词： Proxy signcryption multi-digital-documents proxy blind signcryption hyperelliptic curve IoT

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Quality of Service Aware Cluster Routing in Vehicular Ad Hoc Networks

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Computers, materials & Continua 2021年第6期67卷 3949-3965页

作者： Ishtiaq Wahid Fasee Ullah masood Ahmad Atif Khan m.irfan Uddin Abdullah Alharbi Wael Alosaimi Department of Computer Science Abdul Wali Khan University MardanMardan23200Pakistan Department of Computer and Information Technology Sarhad University of Science and Information TechnologyPeshawar25000Pakistan Department of Computer Science Islamia College PeshawarPeshawar25000Pakistan Institute of Computing Kohat University of Science and TechnologyKohat2600Pakistan Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

In vehicular ad hoc networks(VANETs),the topology information(TI)is updated frequently due to vehicle *** frequent changes in topology increase the topology maintenance *** reduce the control message overhead,cluster-based routing schemes are *** clusterbased routing schemes,the nodes are divided into different virtual groups,and each group(logical node)is considered a *** topology changes are accommodated within each cluster,and broadcasting TI to the whole VANET is not *** cluster head(CH)is responsible for managing the communication of a node with other nodes outside the ***,transmitting real-time data via a CH may cause delays in *** real-time data require quick service and should be routed through the shortest path when the quality of service(QoS)is *** paper proposes a hybrid scheme which transmits time-critical data through the QoS shortest path and normal data through *** this way,the real-time data are delivered efciently to the destination on ***,the routine data are transmitted through CHs to reduce the topology maintenance *** work is validated through a series of simulations,and results show that the proposed scheme outperforms existing algorithms in terms of topology maintenance overhead,QoS and real-time and routine packet transmission.

关键词： QoS VANETs routing real-time communication IoT

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machine Learning Approach for COVID-19 Detection on Twitter

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Computers, materials & Continua 2021年第8期68卷 2231-2247页

作者： Samina Amin m.irfan Uddin Heyam H.Al-Baity m.Ali Zeb m.Abrar Khan Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Department of Information Technology College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

Social networking services(SNSs)provide massive data that can be a very influential source of information during pandemic *** study shows that social media analysis can be used as a crisis detector(e.g.,understanding the sentiment of social media users regarding various pandemic outbreaks).The novel Coronavirus Disease-19(COVID-19),commonly known as coronavirus,has affected everyone worldwide in *** Twitter data have revealed the status of the COVID-19 outbreak in the most affected *** study focuses on identifying COVID-19 patients using tweets without requiring medical records to find the COVID-19 pandemic in Twitter messages(tweets).For this purpose,we propose herein an intelligent model using traditional machine learning-based approaches,such as support vector machine(SVm),logistic regression(LR),naïve Bayes(NB),random forest(RF),and decision tree(DT)with the help of the term frequency inverse document frequency(TF-IDF)to detect the COVID-19 pandemic in Twitter *** proposed intelligent traditional machine learning-based model classifies Twitter messages into four categories,namely,confirmed deaths,recovered,and *** the experimental analysis,the tweet data on the COVID-19 pandemic are analyzed to evaluate the results of traditional machine learning approaches.A benchmark dataset for COVID-19 on Twitter messages is developed and can be used for future research *** experiments show that the results of the proposed approach are promising in detecting the COVID-19 pandemic in Twitter messages with overall accuracy,precision,recall,and F1 score between 70%and 80%and the confusion matrix for machine learning approaches(i.e.,SVm,NB,LR,RF,and DT)with the TF-IDF feature extraction technique.

关键词： Artificial intelligence coronavirus COVID-19 pandemic social network Twitter machine learning natural language processing

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machine Learning-based USD/PKR Exchange Rate Forecasting Using Sentiment Analysis of Twitter Data

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Computers, materials & Continua 2021年第6期67卷 3451-3461页

作者： Samreen Naeem Wali Khan mashwani Aqib Ali m.irfan Uddin marwan mahmoud Farrukh Jamal Christophe Chesneau Department of Computer Science&IT Glim Institute of Modern StudiesBahawalpur63100Pakistan Institute of Numerical Sciences Kohat University of Science&TechnologyKohat26000Pakistan Department of Computer Science Concordia College BahawalpurBahawalpur63100Pakistan Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Faculty of Applied Studies King Abdulaziz UniversityJeddah21577Saudi Arabia Department of Statistics The Islamia University of BahawalpurBahawalpur63100Pakistan Department of mathematics Universitéde CaenLMNOCampus IIScience 3Caen14032France

This study proposes an approach based on machine learning to forecast currency exchange rates by applying sentiment analysis to messages on Twitter(called tweets).A dataset of the exchange rates between the United States Dollar(USD)and the Pakistani Rupee(PKR)was formed by collecting information from a forex website as well as a collection of tweets from the business community in Pakistan containing finance-related *** dataset was collected in raw form,and was subjected to natural language processing by way of data *** variable labeling was then applied to the standardized dataset,where the response variables were divided into two classes:“1”indicated an increase in the exchange rate and“−1”indicated a decrease in *** better represent the dataset,we used linear discriminant analysis and principal component analysis to visualize the data in three-dimensional vector *** that were obtained using a sampling approach were then used for data *** machine learning classifiers—the simple logistic classifier,the random forest,bagging,naïve Bayes,and the support vector machine—were applied to the optimized *** results show that the simple logistic classifier yielded the highest accuracy of 82.14%for the USD and the PKR exchange rates forecasting.

关键词： machine learning exchange rate sentiment analysis linear discriminant analysis principal component analysis simple logistic

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