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| 1 | K-Banhatti Sombor Invariants of Certain Computer Networks显示文摘Any number that can be uniquely determined by a graph is called a graph invariant.During the last twenty years’countless mathematical graph invariants have been characterized and utilized for correlation analysis.However,no reliable examination has been embraced to decide,how much these invariants are related with a network graph or molecular graph.In this paper,it will discuss three different variants of bridge networks with good potential of prediction in the field of computer science,mathematics,chemistry,pharmacy,informatics and biology in context with physical and chemical structures and networks,because k-banhatti sombor invariants are freshly presented and have numerous prediction qualities for different variants of bridge graphs or networks.The study solved the topology of a bridge graph/networks of three different types with two invariants KBanhatti Sombor Indices and its reduced form.These deduced results can be used for the modeling of computer networks like Local area network(LAN),Metropolitan area network(MAN),and Wide area network(WAN),backbone of internet and other networks/structures of computers,power generation,bio-informatics and chemical compounds synthesis. | Khalid Hamid Muhammad Waseem Iqbal Abaid Ur Rehman Virk Muhammad Usman Ashraf Ahmed Mohammed Alghamdi Adel A.Bahaddad Khalid Ali Almarhabi | 2022 | Computers, Materials & Continua2022，，10： | 0 |
| 2 | Local-Tetra-Patterns for Face Recognition Encoded on Spatial Pyramid Matching显示文摘Face recognition is a big challenge in the research field with a lot of problems like misalignment,illumination changes,pose variations,occlusion,and expressions.Providing a single solution to solve all these problems at a time is a challenging task.We have put some effort to provide a solution to solving all these issues by introducing a face recognition model based on local tetra patterns and spatial pyramid matching.The technique is based on a procedure where the input image is passed through an algorithm that extracts local features by using spatial pyramid matching andmax-pooling.Finally,the input image is recognized using a robust kernel representation method using extracted features.The qualitative and quantitative analysis of the proposed method is carried on benchmark image datasets.Experimental results showed that the proposed method performs better in terms of standard performance evaluation parameters as compared to state-of-the-art methods on AR,ORL,LFW,and FERET face recognition datasets. | Khuram Nawaz Khayam Zahid Mehmood Hassan Nazeer Chaudhry Muhammad Usman Ashraf Usman Tariq Mohammed Nawaf Altouri Khalid Alsubhi | 2022 | Computers, Materials & Continua2022，，3： | 0 |
| 3 | Ontology Driven Testing Strategies for IoT Applications显示文摘Internet-of-Things(IoT)has attained a major share in embedded software development.The new era of specialized intelligent systems requires adaptation of customized software engineering approaches.Currently,software engineering has merged the development phases with the technologies provided by industrial automation.The improvements are still required in testing phase for the software developed to IoT solutions.This research aims to assist in developing the testing strategies for IoT applications,therein ontology has been adopted as a knowledge representation technique to different software engineering processes.The proposed ontological model renders 101 methodology by using Protégé.After completion,the ontology was evaluated in three-dimensional view by the domain experts of software testing,IoT and ontology engineering.Satisfied results of the research are showed in interest of the specialists regarding proposed ontology development and suggestions for improvements.The Proposed reasoning-based ontological model for development of testing strategies in IoT application contributes to increase the general understanding of tests in addition to assisting for the development of testing strategies for different IoT devices. | Muhammad Raza Naqvi Muhammad Waseem Iqbal Muhammad Usman Ashraf Shafiq Ahmad Ahmed T.Soliman Shahzada Khurram Muhammad Shafiq Jin-Ghoo Choi | 2022 | Computers, Materials & Continua2022，，3： | 0 |
| 4 | Fake News Classification: Past, Current, and Future显示文摘The proliferation of deluding data such as fake news and phony audits on news web journals,online publications,and internet business apps has been aided by the availability of the web,cell phones,and social media.Individuals can quickly fabricate comments and news on social media.The most difficult challenge is determining which news is real or fake.Accordingly,tracking down programmed techniques to recognize fake news online is imperative.With an emphasis on false news,this study presents the evolution of artificial intelligence techniques for detecting spurious social media content.This study shows past,current,and possible methods that can be used in the future for fake news classification.Two different publicly available datasets containing political news are utilized for performing experiments.Sixteen supervised learning algorithms are used,and their results show that conventional Machine Learning(ML)algorithms that were used in the past perform better on shorter text classification.In contrast,the currently used Recurrent Neural Network(RNN)and transformer-based algorithms perform better on longer text.Additionally,a brief comparison of all these techniques is provided,and it concluded that transformers have the potential to revolutionize Natural Language Processing(NLP)methods in the near future. | Muhammad Usman Ghani Khan Abid Mehmood Mourad Elhadef Shehzad Ashraf Chaudhry | 2023 | Computers, Materials & Continua2023，77，11： | 0 |
| 5 | MagneFi: Multiuser, Multi-Building and Multi-Floor Geomagnetic Field Dataset for Indoor Positioning显示文摘Indoor positioning and localization have emerged as a potential research area during the last few years owing to the wide proliferation of smartphones and the inception of location-attached services for the consumer industry.Due to the importance of precise location information,several positioning technologies are adopted such as Wi-Fi,ultrawideband,infrared,radio frequency identification,Bluetooth beacons,pedestrian dead reckoning,and magnetic field,etc.Although Wi-Fi and magnetic field-based positioning are more attractive concerning the deployment of Wi-Fi access points and ubiquity of magnetic field data,the latter is preferred as it does not require any additional infrastructure as other approaches do.Despite the advantages of magnetic field positioning,comparing the performance of positioning and localization algorithms is very difficult due to the lack of good public datasets that cover various aspects of the magnetic field data.Available datasets do not provide the data to analyze the impact of device heterogeneity,user heights,and time-specific magnetic field mutation.Moreover,multi-floor and multibuilding data are available for the evaluation of state-of-the-art approaches.To overcome the above-mentioned issues,this study presents multi-user,multidevice,multi-building magnetic field data which is collected over a longer period.The dataset contains the data from five different smartphones including Samsung Galaxy S8,S9,A8,LG G6,and LG G7 for three geographically separated buildings.Three users including one female and two males collected the data for various path geometry and data collection scenarios.Moreover,the data contains the magnetic field samples collected on stairs to test multifloor localization.Besides the magnetic field data,the data from inertial measurement unit sensors like the accelerometer,motion sensors,and barometer is provided as well. | Imran Ashraf Muhammad Usman Ali Soojung Hur Gunzung Kim Yongwan Park | 2022 | Computers, Materials & Continua2022，，10： | 0 |
| 6 | Optimized Evaluation of Mobile Base Station by Modern Topological Invariants显示文摘Due to a tremendous increase in mobile traffic,mobile operators have started to restructure their networks to offload their traffic.Newresearch directions will lead to fundamental changes in the design of future Fifthgeneration(5G)cellular networks.For the formal reason,the study solves the physical network of the mobile base station for the prediction of the best characteristics to develop an enhanced network with the help of graph theory.Any number that can be uniquely calculated by a graph is known as a graph invariant.During the last two decades,innumerable numerical graph invariants have been portrayed and used for correlation analysis.In any case,no efficient assessment has been embraced to choose,how much these invariants are connected with a network graph.This paper will talk about two unique variations of the hexagonal graph with great capability of forecasting in the field of optimized mobile base station topology in setting with physical networks.Since K-banhatti sombor invariants(KBSO)and Contrharmonic-quadratic invariants(CQIs)are newly introduced and have various expectation characteristics for various variations of hexagonal graphs or networks.As the hexagonal networks are used in mobile base stations in layered,forms called honeycomb.The review settled the topology of a hexagon of two distinct sorts with two invariants KBSO and CQIs and their reduced forms.The deduced outcomes can be utilized for the modeling of mobile cellular networks,multiprocessors interconnections,microchips,chemical compound synthesis and memory interconnection networks.The results find sharp upper bounds and lower bounds of the honeycomb network to utilize the Mobile base station network(MBSN)for the high load of traffic and minimal traffic also. | Khalid Hamid Muhammad Waseem Iqbal Muhammad Usman Ashraf Ahmed Mohammed Alghamdi Adel A.Bahaddad Khalid Ali Almarhabi | 2023 | Computers, Materials & Continua2023，，1： | 0 |
| 7 | Recognition of Urdu Handwritten Alphabet Using Convolutional Neural Network (CNN)显示文摘Handwritten character recognition systems are used in every field of life nowadays,including shopping malls,banks,educational institutes,etc.Urdu is the national language of Pakistan,and it is the fourth spoken language in the world.However,it is still challenging to recognize Urdu handwritten characters owing to their cursive nature.Our paper presents a Convolutional Neural Networks(CNN)model to recognize Urdu handwritten alphabet recognition(UHAR)offline and online characters.Our research contributes an Urdu handwritten dataset(aka UHDS)to empower future works in this field.For offline systems,optical readers are used for extracting the alphabets,while diagonal-based extraction methods are implemented in online systems.Moreover,our research tackled the issue concerning the lack of comprehensive and standard Urdu alphabet datasets to empower research activities in the area of Urdu text recognition.To this end,we collected 1000 handwritten samples for each alphabet and a total of 38000 samples from 12 to 25 age groups to train our CNN model using online and offline mediums.Subsequently,we carried out detailed experiments for character recognition,as detailed in the results.The proposed CNN model outperformed as compared to previously published approaches. | Gulzar Ahmed Tahir Alyas Muhammad Waseem Iqbal Muhammad Usman Ashraf Ahmed Mohammed Alghamdi Adel A.Bahaddad Khalid Ali Almarhabi | 2022 | Computers, Materials & Continua2022，，11： | 0 |
| 8 | Molecular evolution,virology and spatial distribution of HCV genotypes in Pakistan:A meta-analysis显示文摘Background:Hepatitis C,caused by the Hepatitis C Virus(HCV),is the second most common form of viral hepatitis.The geographical distribution of HCV genotypes can be quite complex,making it challenging to ascertain the most prevalent genotype in a specific area.Methods:To address this,a review was conducted to determine the prevalence of HCV genotypes across various provinces and as a whole in Pakistan.The scientific literature regarding the prevalence,distribution,genotyping,and epidemiology of HCV was gathered from published articles spanning the years 1996-2020.Results:Genotype 1 accounted for 5.1%of the patients,with its predominant subtype being 1a at 4.38%.The frequencies of its other subtypes,1b and 1c,were observed to be 1.0%and 0.31%respectively.Genotype 2 had a frequency of 2.66%,with the most widely distributed subtype being 2a at 2.11%of the patients.Its other subtypes,2b and 2c,had frequencies of 0.17%and 0.36%respectively.The most prevalent genotype among all isolates was 3(65.35%),with the most frequent subtype being 3a(55.15%),followed by 3b(7.18%).The prevalence of genotypes 4,5,and 6 were scarce in Pakistan,with frequencies of 0.97%,0.08%,and 0.32%respectively.The prevalence of untypeable and mixed genotypes was 21.34%and 3.53%respectively.Estimating genotypes proves to be a productive method in assisting with the duration and selection of antiviral treatment.Different HCV genotypes can exhibit variations in their response to specific antiviral treatments.Different genotypes may have distinct natural histories,including variations in disease progression and severity.Some genotypes may lead to more rapid liver damage,while others progress more slowly.Conclusions:This information can guide screening and testing strategies,helping to identify individuals at higher risk of developing severe complications.Studying the distribution of HCV genotypes in a population can provide valuable insights into the transmission dynamics of the virus. | Arslan Habib Nadiya Habib Khalid Mahmood Anjum Riffat Iqbal Zeeshan Ashraf Muhammad Usman Taj Muhammad Asim Kanwal Javid Faezeh Idoon Saeid Dashti Cassio Rocha Medeiros Ana Pavla Almeida Diniz Gurgel Henrique Douglas Melo Coutinho | 2023 | Infectious Medicine2023，2，4： | 0 |
| 9 | Leaching Fraction (LF) of Irrigation Water for Saline Soils Using Machine Learning显示文摘Soil salinity is a serious land degradation issue in agriculture.It is a major threat to agriculture productivity.Extra irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)of irrigation water.For the leaching process to be effective,the LF of irriga-tion water needs to be adjusted according to the environmental conditions and soil salinity level in the form of Evapotranspiration(ET)rate.The relationship between environmental conditions and ET rate is hard to be defined by a linear relationship and data-driven Machine learning(ML)based decisions are required to determine the calibrated Evapotranspiration(ETc)rate.ML-assisted ETc is pro-posed to adjust the LF according to the ETc and soil salinity level.A regression model is proposed to determine the ETc rate according to the prevailing tempera-ture,humidity,and sunshine,which would be used to determine the smart LF according to the ETc and soil salinity level.The proposed model is trained and tested against the Blaney Criddle method of Reference evapotranspiration(ETo)determination.The validation of the model from the test dataset reveals the accu-racy of the ML model in terms of Root mean squared errors(RMSE)are 0.41,Mean absolute errors(MAE)are 0.34,and Mean squared errors(MSE)are 0.28 mm day-1.The applications of the proposed solution in a real-time environ-ment show that the LF by the proposed solution is more effective in reducing the soil salinity as compared to the traditional process of leaching. | Rab Nawaz Bashir Imran Sarwar Bajwa Muhammad Waseem Iqbal Muhammad Usman Ashraf Ahmed Mohammed Alghamdi Adel ABahaddad Khalid Ali Almarhabi | 2023 | Intelligent Automation & Soft Computing2023，，5： | 0 |
| 10 | Triple Key Security Algorithm Against Single Key Attack on Multiple Rounds显示文摘In cipher algorithms,the encryption and decryption are based on the same key.There are some limitations in cipher algorithms,for example in polyalphabetic substitution cipher the key size must be equal to plaintext otherwise it will be repeated and if the key is known then encryption becomes useless.This paper aims to improve the said limitations by designing of Triple key security algorithm(TKS)in which the key is modified on polyalphabetic substitution cipher to maintain the size of the key and plaintext.Each plaintext character is substituted by an alternative message.The mode of substitution is transformed cyclically which depends on the current position of the modified communication.Three keys are used in the encryption and decryption process on 8 or 16 rounds with the Exclusively-OR(XOR)of the 1st key.This study also identifies a single-key attack on multiple rounds block cipher in mobile communications and applied the proposed technique to prevent the attack.By utilization of the TKS algorithm,the decryption is illustrated,and security is analyzed in detail with mathematical examples. | Muhammad Akram Muhammad Waseem Iqbal Syed Ashraf Ali Muhammad Usman Ashraf Khalid Alsubhi Hani Moaiteq Aljahdali | 2022 | Computers, Materials & Continua2022，，9： | 0 |
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