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Design of Latency-Aware IoT Modules in Heterogeneous Fog-Cloud Computing Networks

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Computers, Materials & Continua 2022年第3期70卷 6057-6072页

作者： syed Rizwan Hassan Ishtiaq Ahmad Jamel Nebhen Ateeq Ur Rehman muhammad Shafiq Jin-Ghoo Choi Department of Electrical Engineering The University of LahoreLahore54000Pakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAlkharj11942Saudi Arabia Department of Electrical Engineering Government College UniversityLahore54000Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

The modern paradigm of the Internet of Things(IoT)has led to a significant increase in demand for latency-sensitive applications in Fog-based cloud ***,such applications cannot meet strict quality of service(QoS)*** large-scale deployment of IoT requires more effective use of network infrastructure to ensure QoS when processing big ***,cloud-centric IoT application deployment involves different modules running on terminal devices and cloud *** devices with different computing capabilities must process the data generated by the end device,so deploying latency-sensitive applications in a heterogeneous fog computing environment is a difficult *** addition,when there is an inconsistent connection delay between the fog and the terminal device,the deployment of such applications becomes more *** this article,we propose an algorithm that can effectively place application modules on network nodes while considering connection delay,processing power,and sensing data *** with traditional cloud computing deployment,we conducted simulations in iFogSim to confirm the effectiveness of the *** simulation results verify the effectiveness of the proposed algorithm in terms of end-to-end delay and network ***,latency and execution time is insensitive to the number of sensors.

关键词： IoT fog-cloud computing architecture module placement latency sensitive application resource aware placement

Automated File Labeling for Heterogeneous Files Organization Using Machine Learning

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Computers, Materials & Continua 2023年第2期74卷 3263-3278页

作者： Sagheer Abbas syed Ali Raza MAKhan muhammad Adnan Khan Atta-ur-Rahman Kiran Sultan Amir Mosavi School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Science GC University LahorePakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Software Pattern Recognition and Machine Learning LabGachon UniversitySeongnam13120Korea Department of Computer Science College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal University(IAU)P.O.Box 1982Dammam31441Saudi Arabia Department of CIT The Applied CollegeKing Abdulaziz UniversityJeddah31261Saudi Arabia John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

File labeling techniques have a long history in analyzing the anthological trends in computational *** situation becomes worse in the case of files downloaded into systems from the ***,most users either have to change file names manually or leave a meaningless name of the files,which increases the time to search required files and results in redundancy and duplications of user ***,no significant work is done on automated file labeling during the organization of heterogeneous user files.A few attempts have been made in topic ***,one major drawback of current topic modeling approaches is better *** rely on specific language types and domain similarity of the *** this research,machine learning approaches have been employed to analyze and extract the information from heterogeneous corpus.A different file labeling technique has also been used to get the meaningful and`cohesive topic of the *** results show that the proposed methodology can generate relevant and context-sensitive names for heterogeneous data files and provide additional insight into automated file labeling in operating systems.

关键词： Automated file labeling file organization machine learning topic modeling

5G Antenna Gain Enhancement Using a Novel Metasurface

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Computers, Materials & Continua 2022年第8期72卷 3601-3611页

作者： Mubashir Ashfaq Shahid Bashir syed Imran Hussain Shah Nisar Ahmad Abbasi Hatem Rmili muhammad Abbas Khan Department of Electrical Engineering UETPeshawar25000Pakistan Department of Electrical Engineering Chungnam National UniversityDaejeonKorea Department of Electrical Engineering University of Hafr Al BatinKSA Electrical and Computer Engineering Department Faculty of EngineeringKing Abdulaziz UniversityJeddahKSA K.A.CARE Energy Research and Innovation Center King Abdulaziz UniversityJeddah21589KSA Department of Electrical Engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuettaPakistan

This article presents a Sub-6 GHz microstrip patch antenna(MPA)with enhanced gain using metamaterial(MTM)*** source MPA operates at 4.8 GHz and has a peak gain of 5.3 dBi at the resonance frequency.A window-shaped unit cell is designed and investigated through the material wave propagation *** unit cell shows an EpsilonNear Zero(ENZ)-Mu Very Large(MVL)behavior around 4.8 *** unit cell has a fourfold geometry which makes it a polarization independent metamaterial.A double layer antenna is designed by placing a 4×4 MTM slab as a superstrate above the MPA at a height of 0.208λ0;whereλ0 is the free-space wavelength at the resonance frequency of the *** matching and gain of the source antenna is improved using the *** simulation as well as measurement results show that novel antenna system has a peak gain of 7.68 dBi at 4.8 GHz and an impedance bandwidth of 0.22 *** overall dimension of the antenna is 75×60×15 mm^(3).The proposed antenna operates in the Sub-6 GHz band and is suitable for 5G applications.

关键词： Metasurface 5G gain directivity polarization

Optical dromions for complex Ginzburg Landau model with nonlinear media

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Applied Mathematics(A Journal of Chinese Universities) 2023年第1期38卷 111-125页

作者： syed T.R.Rizvi Aly R.Seadawy muhammad Younis S.O.Abbas Abdul Khaliq Department of Mathematics COMSATS University IslamabadLahore CampusPakistan Mathematics Department Faculty of ScienceTaibah UniversityAl-Madinah Al-Munawarah 41411Kingdom of Saudi Arabia Punjab University College of Information Technology University of the PunjabLahore Pakistan Mathematics Department Riphah Institute of Computing and Applied SciencesRiphah International UniversityLahorePakistan

This manuscript studies the optical dromions with beta derivative(BD)applied to the Complex Ginzburg Landau equation(CGLE)with Kerr law,parabolic law,cubic quintic septic law and quadratic cubic *** obtain bright dromians by using the sine-cosine method(SCM).We will also obtain domain walls with the assistance of Bernoulli equation approach(BEA).Constraint conditions are also listed.

关键词： CGLE optical dromians non-Kerr laws

A Compact Rhombus Shaped Antenna with Extended Stubs for Ultra-Wideband Applications

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Computers, Materials & Continua 2022年第11期73卷 2637-2650页

作者： syed Misbah un Noor muhammad Amir Khan Shahid Khan NZ Jhanjhi Mamoona Humayun Hesham A.Alhumyan Department of Electrical Engineering IIC University of TechnologyPhnom PenhCambodia Department of Computer Science COMSATS University IslamabadAbbottabad Campus22060Pakistan Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad Campus22060Pakistan School of Computer Science SCSTaylor’s UniversitySubang Jaya47500SelangorMalaysia 5Center for Smart Society 0 CSS5 Faculty of Innovation and TechnologyTaylor’s UniversitySubang Jaya47500Malaysia Department of Information Systems College of Computer and Information SciencesJouf UniversityAl-JoufKSA

Ultra-wideband(UWB)is highly preferred for short distance *** a result of this significance,this project targets the design of a compact UWB *** paper describes a printed UWB rhombusshaped antenna with a partial ground *** achieve wideband response,two stubs and a notch are incorporated at both sides of the rhombus design and ground plane *** excite the antenna,a simple microstrip feed line is *** suggested antenna is built on a 1.6 mm thick FR4 *** proposed design is very compact with overall electrical size of 0.18λ×0.25λ(14×18 mm2).The rhombus shaped antenna covers frequency ranging from 3.5 to 11 GHz with 7.5 GHz impedance *** proposed design simulated and measured bandwidths are 83.33%and 80%,*** pattern in terms of E-field and H-field are discussed at 4,5.5 and 10 GHz *** proposed design has 65%radiation efficiency and 1.5 dBi peak *** proposed design is simulated in CST(Computer Simulation Technology)simulator and the simulated design is fabricated for the measured *** simulated and measured findings are in close *** obtained results confirm the application of the proposed design for the ultra-wide band applications.

关键词： Ultra-wideband impedance bandwidth radiation pattern CST electrical size

PAN-DeSpeck:A Lightweight Pyramid and Attention-Based Network for SAR Image Despeckling

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Computers, Materials & Continua 2023年第9期76卷 3671-3689页

作者： Saima Yasmeen muhammad Usman Yaseen syed Sohaib Ali Moustafa M.Nasralla Sohaib Bin Altaf Khattak Department of Computer Sciences Comsats UniversityIslamabadPakistan Department of Research and Development Shearwater GeoservicesCrawleyWest SussexUK Department of Communications&Networks Engineering Prince Sultan UniversityRiyadhSaudi Arabia

SAR images commonly suffer fromspeckle noise,posing a significant challenge in their analysis and *** convolutional neural network(CNN)based despeckling methods have shown great performance in removing speckle ***,these CNN-basedmethods have a *** do not decouple complex background information in ***,they have deep network structures thatmay result in many parameters,limiting their applicability tomobile ***,extracting key speckle information in the presence of complex background is also a major problem with *** proposed study addresses these limitations by introducing a lightweight pyramid and attention-based despeckling(PAN-Despeck)*** primary objective is to enhance image quality and enable improved information interpretation,particularly on mobile devices and scenarios involving complex *** PAN-Despeck network leverages domainspecific knowledge and integrates Gaussian Laplacian image pyramid decomposition for multi-resolution image *** utilizing this approach,complex background information can be effectively decoupled,leading to enhanced despeckling ***,the attention mechanism selectively focuses on key speckle features and facilitates complex background *** network incorporates recursive and residual blocks to ensure computational efficiency and accelerate training speed,making it lightweight while maintaining high *** comprehensive evaluations,it is demonstrated that PAN-Despeck outperforms existing image restoration *** an impressive average peak signal-to-noise ratio(PSNR)of 28.355114 and a remarkable structural similarity index(SSIM)of 0.905467,it demonstrates exceptional performance in effectively reducing speckle noise in SAR *** source code for the PAN-DeSpeck network is available on GitHub.

关键词： Synthetic Aperture Radar(SAR) SAR image despeckling speckle noise deep learning pyramid networks multiscale image despeckling

Translation of English Language into Urdu Language Using LSTM Model

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Computers, Materials & Continua 2023年第2期74卷 3899-3912页

作者： Sajadul Hassan Kumhar syed Immamul Ansarullah Akber Abid Gardezi Shafiq Ahmad Abdelaty Edrees Sayed muhammad Shafiq SSSUTMS Sehore466001India Department of Computer Science GDC SumbalJ&K193502India Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

English to Urdu machine translation is still in its beginning and lacks simple translation methods to provide motivating and adequate English to Urdu *** order tomake knowledge available to the masses,there should be mechanisms and tools in place to make things understandable by translating from source language to target language in an automated *** translation has achieved this goal with encouraging *** decoding the source text into the target language,the translator checks all the characteristics of the *** achieve machine translation,rule-based,computational,hybrid and neural machine translation approaches have been proposed to automate the *** this research work,a neural machine translation approach is employed to translate English text into *** Short Term Short Model(LSTM)Encoder Decoder is used to translate English to *** various steps required to perform translation tasks include preprocessing,tokenization,grammar and sentence structure analysis,word embeddings,training data preparation,encoder-decoder models,and output text *** results show that the model used in the research work shows better performance in *** results were evaluated using bilingual research metrics and showed that the test and training data yielded the highest score sequences with an effective length of ten(10).

关键词： Machine translation Urdu language word embedding

Automated White Blood Cell Disease Recognition Using Lightweight Deep Learning

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Computer Systems Science & Engineering 2023年第7期46卷 107-123页

作者： Abdullah Alqahtani Shtwai Alsubai Mohemmed Sha muhammad Attique Khan Majed Alhaisoni syed Rameez Naqvi College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Computer Science HITEC University TaxilaTaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

White blood cells(WBC)are immune system cells,which is why they are also known as immune *** protect the human body from a variety of dangerous diseases and outside *** majority of WBCs come from red bone marrow,although some come from other important organs in the *** manual diagnosis of blood disorders is difficult,it is necessary to design a computerized *** have introduced various automated strategies in recent years,but they still face several obstacles,such as imbalanced datasets,incorrect feature selection,and incorrect deep model *** proposed an automated deep learning approach for classifying white blood disorders in this *** data augmentation approach is initially used to increase the size of a ***,a Darknet-53 pre-trained deep learning model is used and finetuned according to the nature of the chosen *** the fine-tuned model,transfer learning is used,and features engineering is done on the global average pooling *** retrieved characteristics are subsequently improved with a specified number of iterations using a hybrid reformed binary grey wolf optimization *** that,machine learning classifiers are used to classify the selected best features for final *** experiment was carried out using a dataset of increased blood diseases imaging and resulted in an improved accuracy of over 99%.

关键词： White blood cells augmentation deep features feature selection classification

Liquidity connectedness in cryptocurrency market

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Financial Innovation 2022年第1期8卷 81-105页

作者： Mudassar Hasan muhammad Abubakr Naeem muhammad Arif syed Jawad Hussain Shahzad Xuan Vinh Vo Lahore Business School The University of LahoreLahorePakistan Smurfit Graduate School of Business University Col-lege DublinDublinIreland Institute of Business Research University of Economics Ho Chi Minh CityHo Chi Minh CityVietnam Department of Business Administration Shaheed Benazir Bhutto UniversityShaheed BenazirabadPakistan Montpellier Business School MontpellierFrance South Ural State University ChelyabinskRussian Federation Institute of Business Research and CFVG University of Economics Ho Chi Minh CityHo Chi Minh CityVietnam

We examine the dynamics of liquidity connectedness in the cryptocurrency *** use the connectedness models of Diebold and Yilmaz(Int J Forecast 28(1):57–66,2012)and Baruník and Křehlík(J Financ Econom 16(2):271–296,2018)on a sample of six major cryptocurrencies,namely,Bitcoin(BTC),Litecoin(LTC),Ethereum(ETH),Ripple(XRP),Monero(XMR),and *** static analysis reveals a moderate liquidity connectedness among our sample cryptocurrencies,whereas BTC and LTC play a significant role in connectedness magnitude.A distinct liquidity cluster is observed for BTC,LTC,and XRP,and ETH,XMR,and Dash also form another distinct liquidity *** frequency domain analysis reveals that liquidity connectedness is more pronounced in the short-run time horizon than the medium-and long-run time *** the short run,BTC,LTC,and XRP are the leading contributor to liquidity shocks,whereas,in the long run,ETH assumes this *** with the medium term,a tight liquidity clustering is found in the short and long *** time-varying analysis indicates that liquidity connectedness in the cryptocurrency market increases over time,pointing to the possible effect of rising demand and higher acceptability for this unique ***,more pronounced liquidity connectedness patterns are observed over the short and long run,reinforcing that liquidity connectedness in the cryptocurrency market is a phenomenon dependent on the time–frequency connectedness.

关键词： Liquidity Time-frequency connectedness Cryptocurrencies