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| 1 | A novel bioactive polyurethane with controlled degradation and L-Arg release used as strong adhesive tissue patch for hemostasis and promoting wound healing显示文摘Effective strategy of hemostasis and promoting angiogenesis are becoming increasingly urgent in modern medicine due to millions of deaths caused by tissue damage and inflammation. The tissue adhesive has been favored as an optimistic and efficient path to stop bleeding, while, current adhesive presents limitations on wound care or potential degradation safety in clinical practice. Therefore, it is of great clinical significance to construct multifunctional wound adhesive to address the issues. Based on pro-angiogenic property of L-Arginine (L-Arg), in this study, the novel tissue adhesive (G-DLPUs) constructed by L-Arg-based degradable polyurethane (DLPU) and GelMA were prepared for wound care. After systematic characterization, we found that the G-DLPUs were endowed with excellent capability in shape-adaptive adhesion. Moreover, the L-Arg released and the generation of NO during degradation were verified which would enhance wound healing. Following the in vivo biocompatibility was verified, the hemostatic effect of the damaged organ was tested using a rat liver hemor-rhage model, from which reveals that the G-DLPUs can reduce liver bleeding by nearly 75% and no obvious inflammatory cells observed around the tissue. Moreover, the wound care effect was confirmed in a mouse full-thickness skin defect model, showing that the hydrogel adhesive significantly improves the thickness of newly formed dermis and enhance vascularization (CD31 staining). In summary, the G-DLPUs are promising candidate to act as multifunctional wound care adhesive for both damaged organ and trauma. | Faxing Zou Yansen Wang Yudong Zheng Yajie Xie Hua Zhang Jishan Chen M.Irfan Hussain Haoye Meng Jiang Peng | 2022 | Bioactive Materials2022，7，11： | 2 |
| 2 | Machine Learning Approach for COVID-19 Detection on Twitter显示文摘Social networking services(SNSs)provide massive data that can be a very influential source of information during pandemic outbreaks.This 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 2020.Streaming Twitter data have revealed the status of the COVID-19 outbreak in the most affected regions.This 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 messages.The proposed intelligent traditional machine learning-based model classifies Twitter messages into four categories,namely,confirmed deaths,recovered,and suspected.For 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 studies.The 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. | Samina Amin M.Irfan Uddin Heyam H.Al-Baity M.Ali Zeb M.Abrar Khan | 2021 | Computers, Materials & Continua2021，，8： | 1 |
| 3 | Machine Learning-based USD/PKR Exchange Rate Forecasting Using Sentiment Analysis of Twitter Data显示文摘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 words.The dataset was collected in raw form,and was subjected to natural language processing by way of data preprocessing.Response 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 it.To better represent the dataset,we used linear discriminant analysis and principal component analysis to visualize the data in three-dimensional vector space.Clusters that were obtained using a sampling approach were then used for data optimization.Five machine learning classifiers—the simple logistic classifier,the random forest,bagging,naïve Bayes,and the support vector machine—were applied to the optimized dataset.The results show that the simple logistic classifier yielded the highest accuracy of 82.14%for the USD and the PKR exchange rates forecasting. | Samreen Naeem Wali Khan Mashwani Aqib Ali M.Irfan Uddin Marwan Mahmoud Farrukh Jamal Christophe Chesneau | 2021 | Computers, Materials & Continua2021，，6： | 1 |
| 4 | Detecting Information on the Spread of Dengue on Twitter Using Articial Neural Networks显示文摘Social media platforms have lately emerged as a promising tool for predicting the outbreak of epidemics by analyzing information on them with the help of machine learning techniques.Many analytical and statistical models are available to infer a variety of user sentiments in posts on social media.The amount of data generated by social media platforms,such as Twitter,that can be used to track diseases is increasing rapidly.This paper proposes a method for the classication of tweets related to the outbreak of dengue using machine learning algorithms.An articial neural network(ANN)-based method is developed using Global Vector(GloVe)embedding to use the data in tweets for the automatic and efcient identication and classication of dengue.The proposed method classies tweets related to the outbreak of dengue into positives and negatives.Experiments were conducted to assess the proposed ANN model based on performance evaluation matrices(confusion matrices).The results show that the GloVe vectors can efciently capture a sufcient amount of information for the classier to accurately identify and classify tweets as relevant or irrelevant to dengue outbreaks.The proposed method can help healthcare professionals and researchers track and analyze epidemic outbreaks through social media in real time. | Samina Amin M.Irfan Uddin M.Ali Zeb Ala Abdulsalam Alarood Marwan Mahmoud Monagi H.Alkinani | 2021 | Computers, Materials & Continua2021，，4： | 1 |
| 5 | Regular perturbation solution of Couette flow(non-Newtonian)between two parallel porous plates: a numerical analysis with irreversibility显示文摘The unavailability of wasted energy due to the irreversibility in the process is called the entropy generation.An irreversible process is a process in which the entropy of the system is increased.The second law of thermodynamics is used to define whether the given system is reversible or irreversible.Here,our focus is how to reduce the entropy of the system and maximize the capability of the system.There are many methods for maximizing the capacity of heat transport.The constant pressure gradient or motion of the wall can be used to increase the heat transfer rate and minimize the entropy.The objective of this study is to analyze the heat and mass transfer of an Eyring-Powell fluid in a porous channel.For this,we choose two different fluid models,namely,the plane and generalized Couette flows.The flow is generated in the channel due to a pressure gradient or with the moving of the upper lid.The present analysis shows the effects of the fluid parameters on the velocity,the temperature,the entropy generation,and the Bejan number.The nonlinear boundary value problem of the flow problem is solved with the help of the regular perturbation method.To validate the perturbation solution,a numerical solution is also obtained with the help of the built-in command NDSolve of MATHEMATICA 11.0.The velocity profile shows the shear thickening behavior via first-order Eyring-Powell parameters.It is also observed that the profile of the Bejan number has a decreasing trend against the Brinkman number.Whenηi→0(i=1,2,3),the Eyring-Powell fluid is transformed into a Newtonian fluid. | M.NAZEER M.I.KHAN S.KADRY Yuming CHU F.AHMAD W.ALI M.IRFAN M.SHAHEEN | 2021 | Applied Mathematics and Mechanics(English Edition)2021，42，1： | 1 |
| 6 | Efficient Data Augmentation Techniques for Improved Classification in Limited Data Set of Oral Squamous Cell Carcinoma显示文摘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 classifications.These techniques require a considerable amount of data to efficiently train the DL models.Generally,when the data size is larger,the DL models perform better.However,it is not possible to have a considerable amount of data in different domains such as healthcare.In 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 patients.To solve this problem of small dataset,different techniques of data augmentation are used that can increase the size of the training set.However,these techniques only change the shape of the image and hence the classification model does not increase accuracy.Generative Adversarial Networks(GANs)are very powerful techniques to augment training data as new samples are created.This technique helps the classification models to increase their accuracy.In this paper,we have investigated augmentation techniques in healthcare image classification.The 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 accuracy.We have compared the performance of the image classifiers using the standard augmentation technique and GANs.Our 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. | Wael Alosaimi M.Irfan Uddin | 2022 | Computer Modeling in Engineering & Sciences2022，，6： | 0 |
| 7 | Mg和Ni共掺杂的ZnO稀释磁性半导体在磁性和光催化的应用显示文摘随着引入磁性元素,氧化锌最近被广泛用作磁性半导体.本文报告了Mg和Ni共掺杂的ZnO的纯相合成,并研究其结构、光学、磁性和光催化特性.X射线衍射分析显示其六方纤锌矿型结构具有P63mc构型且不含任何杂质.紫外可见分光光度法表明,随着ZnO中掺杂的Mg和Ni含量增加,带隙发生变化.磁性测量实验显示Ni和Mg共掺杂的ZnO磁性加强,带隙的稳定进一步证实其结构的稳定性,实现了其在现代自旋电子设备的磁调谐性能.对甲基绿的光催化降解实验结果表明,Mg和Ni共掺杂ZnO的活性增强. | Tahir Iqbal M.Irfan Shahid M.Ramay Abdullah Alhamidi Hamid Shaikh Murtaza Saleem Saadat A.Siddiqi | 2020 | Chinese Journal of Chemical Physics2020，33，6： | 0 |
| 8 | A Bio-Inspired Routing Optimization in UAV-enabled Internet of Everything显示文摘Internet of Everything(IoE)indicates a fantastic vision of the future,where everything is connected to the internet,providing intelligent services and facilitating decision making.IoE is the collection of static and moving objects able to coordinate and communicate with each other.The moving objects may consist of ground segments and ying segments.The speed of ying segment e.g.,Unmanned Ariel Vehicles(UAVs)may high as compared to ground segment objects.The topology changes occur very frequently due to high speed nature of objects in UAV-enabled IoE(Ue-IoE).The routing maintenance overhead may increase when scaling the Ue-IoE(number of objects increases).A single change in topology can force all the objects of the Ue-IoE to update their routing tables.Similarly,the frequent updating in routing table entries will result more energy dissipation and the lifetime of the Ue-IoE may decrease.The objects consume more energy on routing computations.To prevent the frequent updation of routing tables associated with each object,the computation of routes from source to destination may be limited to optimum number of objects in the Ue-IoE.In this article,we propose a routing scheme in which the responsibility of route computation(from neighbor objects to destination)is assigned to some IoE-objects in the Ue-IoE.The route computation objects(RCO)are selected on the basis of certain parameters like remaining energy and mobility.The RCO send the routing information of destination objects to their neighbors once they want to communicate with other objects.The proposed protocol is simulated and the results show that it outperform state-of-the-art protocols in terms of average energy consumption,messages overhead,throughput,delay etc. | Masood Ahmad Fasee Ullah Ishtiaq Wahid Atif Khan M.Irfan Uddin Abdullah Alharbi Wael Alosaimi | 2021 | Computers, Materials & Continua2021，，4： | 0 |
| 9 | Magnetohydrodynamic Stagnation Point Flow of a Maxwell Nanofluid with Variable Conductivity显示文摘This article reports the simultaneous properties of variable conductivity and chemical reaction in stagnation point flow of magneto Maxwell nanofluid.The Buongiorno’s theory has been established to picture the inducement of Brownian and thermophrotic diffusions effects.Additionally,the aspect of heat sink/source is reported.The homotopic analysis method(HAM)has been worked out for the solution of nonlinear ODEs.The behavior of inferential variables on the velocity,temperature,concentration and local Nusselt number for Maxwell nanofluid are sketched and discussed.The 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 fields.It is further noted that the influence of variable thermal conductivity on temperature field is similar to that of Brownian motion parameter.Moreover,for the confirmation of our study comparison tables are reported. | M.Irfan M.Khan W.A.Khan M.Alghamdi | 2019 | Communications in Theoretical Physics2019，71，12： | 0 |
| 10 | Speech Recognition-Based Automated Visual Acuity Testing with Adaptive Mel Filter Bank显示文摘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 patient.This procedure,however,usually requires an appointment with an ophthalmologist,which is both time-consuming and expensive process.Other issues that can arise include a lack of appropriate equipment and trained practitioners,especially in rural areas.Centered on a cognitively motivated attribute extraction and speech recognition approach,this paper proposes a novel idea that immediately determines the eyesight deficiency.The proposed system uses an adaptive filter bank with weighted mel frequency cepstral coefficients for feature extraction.The 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 environment.Comparative 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 tests.The 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. | Shibli Nisar Muhammad Asghar Khan Fahad Algarni Abdul Wakeel M.Irfan Uddin Insaf Ullah | 2022 | Computers, Materials & Continua2022，，2： | 0 |
| 11 | An Abstractive Summarization Technique with Variable Length Keywords as per Document Diversity显示文摘Text Summarization is an essential area in text mining,which has procedures for text extraction.In natural language processing,text summarization maps the documents to a representative set of descriptive words.Therefore,the objective of text extraction is to attain reduced expressive contents from the text documents.Text summarization has two main areas such as abstractive,and extractive summarization.Extractive text summarization has further two approaches,in which the first approach applies the sentence score algorithm,and the second approach follows the word embedding principles.All such text extractions have limitations in providing the basic theme of the underlying documents.In this paper,we have employed text summarization by TF-IDF with PageRank keywords,sentence score algorithm,and Word2Vec word embedding.The study compared these forms of the text summarizations with the actual text,by calculating cosine similarities.Furthermore,TF-IDF based PageRank keywords are extracted from the other two extractive summarizations.An intersection over these three types of TD-IDF keywords to generate the more representative set of keywords for each text document is performed.This technique generates variable-length keywords as per document diversity instead of selecting fixedlength keywords for each document.This form of abstractive summarization improves metadata similarity to the original text compared to all other forms of summarized text.It also solves the issue of deciding the number of representative keywords for a specific text document.To evaluate the technique,the study used a sample of more than eighteen hundred text documents.The abstractive summarization follows the principles of deep learning to create uniform similarity of extracted words with actual text and all other forms of text summarization.The proposed technique provides a stable measure of similarity as compared to existing forms of text summarization. | Muhammad Yahya Saeed Muhammad Awais Muhammad Younas Muhammad Arif Shah Atif Khan M.Irfan Uddin Marwan Mahmoud | 2021 | Computers, Materials & Continua2021，，3： | 0 |
| 12 | Quality of Service Aware Cluster Routing in Vehicular Ad Hoc Networks显示文摘In vehicular ad hoc networks(VANETs),the topology information(TI)is updated frequently due to vehicle mobility.These frequent changes in topology increase the topology maintenance overhead.To reduce the control message overhead,cluster-based routing schemes are proposed.In clusterbased routing schemes,the nodes are divided into different virtual groups,and each group(logical node)is considered a cluster.The topology changes are accommodated within each cluster,and broadcasting TI to the whole VANET is not required.The cluster head(CH)is responsible for managing the communication of a node with other nodes outside the cluster.However,transmitting real-time data via a CH may cause delays in VANETs.Such real-time data require quick service and should be routed through the shortest path when the quality of service(QoS)is required.This paper proposes a hybrid scheme which transmits time-critical data through the QoS shortest path and normal data through CHs.In this way,the real-time data are delivered efciently to the destination on time.Similarly,the routine data are transmitted through CHs to reduce the topology maintenance overhead.The 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. | Ishtiaq Wahid Fasee Ullah Masood Ahmad Atif Khan M.Irfan Uddin Abdullah Alharbi Wael Alosaimi | 2021 | Computers, Materials & Continua2021，，6： | 0 |
| 13 | Biochar Application Improves the Drought Tolerance in Maize Seedlings显示文摘Application of biochar to agricultural soils is mostly used to improve soil fertility.Experimental treatments were comprised of two factors:i)drought at two level,i.e.,80%and 40%water holding capacity(WHC)which was maintained on gravimetric basis ii)three levels of biochar i.e.,control,2 t ha^(-1) and 4 t ha^(-1) added to soil.Experimentation was done to examine potential of biochar application to enhance the growth attributes,water relations,photosynthetic pigments and antioxidants activities in maize(Zea mays L.)seedlings.Results of study revealed that biochar application increased the growth qualities(total seedlings biomass,dry weight of shoot and root,shoot length and root length).In addition;contents of photosynthetic pigments(chlorophyll a,b,a+b and a/b),water relation(relative water contents,turgor potential,osmotic potential and water potential)were improved significantly due to addition of biochar.Addition of 4 t ha^(-1) biochar led to significant rise activity of enzymatic antioxidant catalase(CAT),superoxide dismutase(SOD)and peroxidase(POD)in leaf of maize seedling sunder drought as well as well watered circumstances.However,biochar applied at the rate 4 t ha^(-1) improved the all the physiological and biochemical attributes in maize seedlings under drought.From the results it was concluded that biochar application is an efficient way to alleviate adverse effect of drought stress on maize.In drought prone areas,long term impacts of biochar on production of maize and properties of soil could be recommended as upcoming shove. | A.Sattar A.Sher M.Ijaz M.Irfan M.Butt T.Abbas S.Hussain A.Abbas M.S.Ullah M.A.Cheema | 2019 | Phyton-International Journal of Experimental Botany2019，88，4： | 0 |
| 14 | Ambiguity Resolution in Direction of Arrival Estimation with Linear Antenna Arrays Using Differential Geometry显示文摘Linear antenna arrays(LAs)can be used to accurately predict the direction of arrival(DOAs)of various targets of interest in a given area.However,under certain conditions,LA suffers from the problem of ambiguities among the angles of targets,which may result inmisinterpretation of such targets.In order to cope up with such ambiguities,various techniques have been proposed.Unfortunately,none of them fully resolved such a problem because of rank deficiency and high computational cost.We aimed to resolve such a problem by proposing an algorithm using differential geometry.The proposed algorithm uses a specially designed doublet antenna array,which is made up of two individual linear arrays.Two angle observation models,ambiguous observation model(AOM)and estimated observation model(EOM),are derived for each individual array.The ambiguous set of angles is contained in the AOM,which is obtained from the corresponding array elements using differential geometry.The EOM for each array,on the other hand,contains estimated angles of all sources impinging signals on each array,as calculated by a direction-finding algorithm such as the genetic algorithm.The algorithm then contrasts the EOM of each array with its AOM,selecting the output of that array whose EOM has the minimum correlation with its corresponding AOM.In comparison to existing techniques,the proposed algorithm improves estimation accuracy and has greater precision in antenna aperture selection,resulting in improved resolution capabilities and the potential to be used more widely in practical scenarios.The simulation results using MATLAB authenticates the effectiveness of the proposed algorithm. | Alamgir Safi Muhammad Asghar Khan Fahad Algarni Muhammad Adnan Aziz M.Irfan Uddin Insaf Ullah Tanweer Ahmad Cheema | 2022 | Computers, Materials & Continua2022，，1： | 0 |
| 15 | Drought-Mediated Modulation in Metabolomic Profiling of Nigella Sativa Leaf, Growth, Ecophysiology and Antioxidants显示文摘Abiotic stresses,including drought,have been found to affect the growth and medicinal quality of numerous herbs.The 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)leaf.Forty-day-old seedlings of N.sativa were exposed to three regimes of drought(control,moderate and high)for a week.UPLCMS/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,etc.Drought was found to alter the contents of identified metabolites.Drought stress-induced oxidative stress and increased production of hydrogen peroxide and superoxide anions.Physiological changes,activities of antioxidant enzymes,contents of antioxidants,and proline were significantly high under drought to protect against the low water regimes.Furthermore,stressed leaf extract had higher antioxidant potential.Thus,N.sativa leaf bears multiple metabolic pathways and can tolerate a higher degree of drought or osmotic stress. | Khalid Rehman Hakeem Hesham F.Alharby M.Irfan Qureshi | 2023 | Phyton-International Journal of Experimental Botany2023，92，12： | 0 |
| 16 | Enhanced room temperature ferromagnetism in Cr-doped ZnO nanoparticles prepared by auto-combustion method显示文摘Zn_(1-x)Cr_xO(x=0.00,0.01,0.03,0.05,0.07,and 0.09)nanoparticles were synthesized,by an auto-combustion method.Structural,optical,and magnetic characteristics of Cr-doped Zn O samples calcined at 600°C have been analyzed by using X-ray diffraction(XRD),field emission scanning electron microscope(FESEM),UV–Vis spectroscopy and vibrating sample magnetometer(VSM).The XRD data confirmed the hexagonal wurtzite structure of pure and Cr-doped Zn O nanoparticles.The calculated values of grain size using Scherrer's formula are in the range of 30.7–9.2 nm.The morphology of nanopowders has been observed by FESEM,and EDS results confirmed a systematic increase of Cr content in the samples and clearly indicate with no impurity element.The band gaps,computed by UV–Vis spectroscopy,are in the range of 2.83–2.35 e V for different doping concentrations.By analyzing VSM data,significantly enhanced room temperature ferromagnetism is identified in Cr-doped Zn O samples.The value of magnetization is a 12 times increased of the value reported by Daun et al.(2010).Room temperature ferromagnetism of the nanoparticles is of vital prominence for spintronics applications. | Khizar-ul Haq M.Irfan Muhammad Masood Murtaza Saleem Tahir Iqbal Ishaq Ahmad M.A.Khan M.Zaffar Muhammad Irfan | 2018 | Journal of Semiconductors2018，39，4： | 0 |
| 17 | Municipal solid waste landfill site selection for the city of Sanliurfa-Turkey:an example using MCDA integrated with GIS显示文摘A municipal solid waste(MSW)management system needs solid waste management(SWM)techniques where the presence of a sanitary landfill is vital.One of the most important issues of sanitary landfilling is to locate the facility to an optimal location.Despite 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 constraints.Consequently,constraints and environmental regulations mechanically mask unsuitable areas,leaving very little areas to be assessed.This turns the situation into a challenging issue for a geographical information system(GIS)used with multicriteria decision analysis(MCDA),to select optimal site.The 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 one.Results 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 time.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. | M.Irfan Yesilnacar M.Lutfi Suzen Basak Sener Kaya Vedat Doyuran | 2012 | International Journal of Digital Earth2012，5，2： | 0 |
| 18 | Adaptation of Vehicular Ad hoc Network Clustering Protocol for Smart Transportation显示文摘Clustering algorithms optimization can minimize topology maintenance overhead in large scale vehicular Ad hoc networks(VANETs)for smart transportation that results from dynamic topology,limited resources and noncentralized architecture.The performance of a clustering algorithm varies with the underlying mobility model to address the topology maintenance overhead issue in VANETs for smart transportation.To design a robust clustering algorithm,careful attention must be paid to components like mobility models and performance objectives.A clustering algorithm may not perform well with every mobility pattern.Therefore,we propose a supervisory protocol(SP)that observes the mobility pattern of vehicles and identies the realistic Mobility model through microscopic features.An analytical model can be used to determine an efcient clustering algorithm for a specic mobility model(MM).SP selects the best clustering scheme according to the mobility model and guarantees a consistent performance throughout VANET operations.The simulation has performed in three parts that is the central part simulation for setting up the clustering environment,In the second part the clustering algorithms are tested for efciency in a constrained atmosphere for some time and the third part represents the proposed scheme.The simulation results show that the proposed scheme outperforms clustering algorithms such as honey bee algorithm-based clustering and memetic clustering in terms of cluster count,re-afliation rate,control overhead and cluster lifetime. | Masood Ahmad Abdul Hameed Fasee Ullah Ishtiaq Wahid Atif Khan M.Irfan Uddin Shaq Ahmad Ahmed M.El-Sherbeeny | 2021 | Computers, Materials & Continua2021，，5： | 0 |
| 19 | PeachNet: Peach Diseases Detection for Automatic Harvesting显示文摘To meet the food requirements of the seven billion people on Earth,multiple advancements in agriculture and industry have been made.The main threat to food items is from diseases and pests which affect the quality and quantity of food.Different scientific mechanisms have been developed to protect plants and fruits from pests and diseases and to increase the quantity and quality of food.Still these mechanisms require manual efforts and human expertise to diagnose diseases.In the current decade Artificial Intelligence is used to automate different processes,including agricultural processes,such as automatic harvesting.Machine Learning techniques are becoming popular to process images and identify different objects.We 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 losses.In this paper,we develop a novel Convolutional Neural Network(CNN)model that can detect diseases in peach plants and fruits.The proposed method can also locate the region of disease and help farmers to find appropriate treatments to protect peach crops.For the detection of diseases in Peaches VGG-19 architecture is utilized.For the localization of disease regions Mask R-CNN is utilized.The proposed technique is evaluated using different techniques and has demonstrated 94%accuracy.We hope that the system can help farmers to increase peach production to meet food demands. | Wael Alosaimi Hashem Alyami M.Irfan Uddin | 2021 | Computers, Materials & Continua2021，，5： | 0 |
| 20 | An Efficient Proxy Blind Signcryption Scheme for IoT显示文摘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 domains.IoT utilizes the Internet as a prime medium of communication for both single documents as well as multi-digital messages.However,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 bandwidth.We 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 bandwidth.The designed scheme also has the desired authentication,unforgeability of warrants and/or plaintext,confidentiality,integrity,and blindness,respectively.Further,our scheme is more suitable for devices with low computation power such as mobiles and tablets. | Aamer Khan Insaf Ullah Fahad Algarni Muhammad Naeem M.Irfan Uddin Muhammad Asghar Khan | 2022 | Computers, Materials & Continua2022，，3： | 0 |
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