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Optimal Resource allocation method for Device-to-Device Communication in 5G Networks

Computers, materials & Continua 2022年第4期71卷 1-15页

作者： Fahd N.al-Wesabi Imran Khan Saleem Latteef mohammed Huda Farooq Jameel mohammad alamgeer ali m.al-sharafi Byung Seo Kim Department of Computer Science King Khalid UniversityMuhayel AseerKSA Faculty of Computer and IT Sana’a UniversityYemen Department of Electrical Engineering University of Engineering and TechnologyPeshawarPakistan Department of medical Instrumentation Techniques Engineering Electrical Engineering Technical CollegeMiddle Technical UniversityBaghdad10013Iraq Department of Information Systems King Khalid UniversityMayahel AseerKSA Department of Computer Science College of Computers and Information TechnologyUniversity of BishaKSA Department of Software and Communications Engineering Hongik UniversityKorea

With the rapid development of the next-generation mobile network,the number of terminal devices and applications is growing explosively.Therefore,how to obtain a higher data rate,wider network coverage and higher resource utilization in the limited spectrum resources has become the common research goal of scholars.Device-to-Device(D2D)communication technology and other frontier communication technologies have emerged.Device-to-Device communication technology is the technology that devices in proximity can communicate directly in cellular networks.It has become one of the key technologies of the fifth-generation mobile communications system(5G).D2D communication technology which is introduced into cellular networks can effectively improve spectrum utilization,enhance network coverage,reduce transmission delay and improve system throughput,but it would also bring complicated and various interferences due to reusing cellular resources at the same time.So resource management is one of the most challenging and importing issues to give full play to the advantages of D2D communication.Optimal resource allocation is an important factor that needs to be addressed in D2D communication.Therefore,this paper proposes an optimization method based on the game-matching concept.The main idea is to model the optimization problem of the quality-of-experience based on user fairness and solve it through game-matching theory.Simulation results show that the proposed algorithm effectively improved the resource allocation and utilization as compared with existing algorithms.

关键词： D2D communication resource allocation optimization networks

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malicious URL Classification Using Artificial Fish Swarm Optimization and Deep Learning

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Computers, materials & Continua 2023年第1期74卷 607-621页

作者： Anwer mustafa Hilal Aisha Hassan Abdalla Hashim Heba G.mohamed mohamed K.Nour mashael m.Asiri ali m.al-sharafi mahmoud Othman Abdelwahed motwakel Department of Electrical and Computer Engineering International Islamic University Malaysia 53100 Kuala LumpurMalaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science College of Computers and Information TechnologyUniversity of BishaSaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital era.malicious Uniform Resource Locators(URLs)can be embedded in email or Twitter and used to lure vulnerable internet users to implement malicious data in their systems.This may result in compromised security of the systems,scams,and other such cyberattacks.These attacks hijack huge quantities of the available data,incurring heavy financial loss.At the same time,machine Learning(mL)and Deep Learning(DL)models paved the way for designing models that can detect malicious URLs accurately and classify them.With this motivation,the current article develops an Artificial Fish Swarm.algorithm(AFSA)with Deep Learning Enabled malicious URL Detection and Classification(AFSADL-mURLC)model.The presented AFSADL-mURLC model intends to differentiate the malicious URLs from genuine URLs.To attain this,AFSADL-mURLC model initially carries out data preprocessing and makes use of glove-based word embedding technique.In addition,the created vector model is then passed onto Gated Recurrent Unit(GRU)classification to recognize the malicious URLs.Finally,AFSA is applied to the proposed model to enhance the efficiency of GRU model.The proposed AFSADL-mURLC technique was experimentally validated using benchmark dataset sourced from Kaggle repository.The simulation results confirmed the supremacy of the proposed AFSADL-mURLC model over recent approaches under distinct measures.

关键词： malicious URL cybersecurity deep learning machine learning metaheuristics gated recurrent unit

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Enhanced Gorilla Troops Optimizer with Deep Learning Enabled Cybersecurity Threat Detection

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Computer Systems Science & Engineering 2023年第6期45卷 3037-3052页

作者： Fatma S.alrayes Najm.alotaibi Jaber S.alzahrani Sana alazwari Areej alhogail ali m.al-sharafi mahmoud Othman manar Ahmed Hamza Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Prince Saud al Faisal Institute for Diplomatic Studies RiyadhSaudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Information Systems College of Computer and Information SciencesKing Saud UniversitySaudi Arabia Department of Computer Science College of Computers and Information TechnologyUniversity of BishaSaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Recent developments in computer networks and Internet of Things(IoT)have enabled easy access to data.But the government and business sectors face several difficulties in resolving cybersecurity network issues,like novel attacks,hackers,internet criminals,and so on.Presently,malware attacks and software piracy pose serious risks in compromising the security of IoT.They can steal confidential data which results infinancial and reputational losses.The advent of machine learning(mL)and deep learning(DL)models has been employed to accomplish security in the IoT cloud environment.This article pre-sents an Enhanced Artificial Gorilla Troops Optimizer with Deep Learning Enabled Cybersecurity Threat Detection(EAGTODL-CTD)in IoT Cloud Net-works.The presented EAGTODL-CTD model encompasses the identification of the threats in the IoT cloud environment.The proposed EAGTODL-CTD mod-el mainly focuses on the conversion of input binaryfiles to color images,where the malware can be detected using an image classification problem.The EAG-TODL-CTD model pre-processes the input data to transform to a compatible for-mat.For threat detection and classification,cascaded gated recurrent unit(CGRU)model is exploited to determine class labels.Finally,EAGTO approach is employed as a hyperparameter optimizer to tune the CGRU parameters,showing the novelty of our work.The performance evaluation of the EAGTODL-CTD model is assessed on a dataset comprising two class labels namely malignant and benign.The experimental values reported the supremacy of the EAG-TODL-CTD model with increased accuracy of 99.47%.

关键词： Cybersecurity computer networks threat detection internet of things cloud computing deep learning

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A Joint algorithm for Resource allocation in D2D 5G Wireless Networks

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Computers, materials & Continua 2021年第10期69卷 301-317页

作者： Fahd N.al-Wesabi Imran Khan mohammad alamgeer ali m.al-sharafi Bong Jun Choi Abdallah aldosary Ehab mahmood mohammad Department of Computer Science King Khalid UniversityMuhayel AseerKSA Faculty of Computer and IT Sana’a UniversityYemen Department of Electrical Engineering University of Engineering and TechnologyPeshawarP.O.B 814Pakistan Department of Information Systems King Khalid UniversityMayahel AseerKSA Department of Computer Science College of Computers and Information TechnologyUniversity of BishaKSA School of Computer Science and Engineering Soongsil UniversitySouth Korea Department of Computer Science Prince Sattam bin Abdulaziz UniversityAs Sulayyil11991Saudi Arabia Electrical Engineering Department College of EngineeringPrince Sattam Bin Abdulaziz UniversityWadi Addwasir11991Saudi Arabia Electrical Engineering Department Faculty of EngineeringAswan UniversityAswan81542Egypt

With the rapid development of Internet technology,users have an increasing demand for data.The continuous popularization of traffic-intensive applications such as high-definition video,3D visualization,and cloud computing has promoted the rapid evolution of the communications industry.In order to cope with the huge traffic demand of today’s users,5G networks must be fast,flexible,reliable and sustainable.Based on these research backgrounds,the academic community has proposed D2D communication.The main feature of D2D communication is that it enables direct communication between devices,thereby effectively improve resource utilization and reduce the dependence on base stations,so it can effectively improve the throughput of multimedia data.One of the most considerable factor which affects the performance of D2D communication is the co-channel interference which results due to the multiplexing of multiple D2D user using the same channel resource of the cellular user.To solve this problem,this paper proposes a joint algorithm time scheduling and power control.The main idea is to effectively maximize the number of allocated resources in each scheduling period with satisfied quality of service requirements.The constraint problem is decomposed into time scheduling and power control subproblems.The power control subproblem has the characteristics of mixed-integer linear programming of NP-hard.Therefore,we proposed a gradual power control method.The time scheduling subproblem belongs to the NP-hard problem having convex-cordinality,therefore,we proposed a heuristic scheme to optimize resource allocation.Simulation results show that the proposed algorithm effectively improved the resource allocation and overcome the co-channel interference as compared with existing algorithms.

关键词： 6G wireless networks mobile communication linear programming

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Analysis and Assessment of Wind Energy Potential of al-Hodeidah in Yemen

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Computers, materials & Continua 2021年第11期69卷 1995-2011页

作者： Fahd N.al-Wesabi murad A.almekhlafi mohammed Abdullah al-Hagery mohammad alamgeer Khalid mahmood majdy m.Eltahir ali m.al-sharafi Amin m.El-Kustaban Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Electrical Engineering–Communication Engineering Sana’a UniversityYemen Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Department of Information Systems King Khalid UniversityMayahel AseerKSA Department of Computer Science College of Computers and Information TechnologyUniversity of BishaKSA Department of Electronic Faculty of EngineeringUSTSana’aYemen

Renewable energy is one of the essential elements of the social and economic development in any civilized country.The use of fossil fuels and the non-renewable form of energy has many adverse effects on the most of ecosystems.Given the high potential of renewable energy sources in Yemen and the absence of similar studies in the region,this study aimed to examine the wind energy potential of Hodeidah-Yemen Republic by analyzing wind characteristics and assessment,determining the available power density,and calculate the wind energy extracted at different heights.The average wind speed of Hodeidah was obtained only for the data currently available for the five years 2005–2009(due to the current economic and the political situation in Yemen).The results show that the average wind speed in the five years is(25.2 W/m2 at 10 m,93.9 W/m2 at 30 m,and 173.5 W/m2 at 50 m).The average yearly wind power density(25.2 W/m2 at 10 m,93.9 W/m2 at 30 m and 173.5 W/m2 at 50m),and the average yearly energy density(220.8 KWh/m2/year at 10 m,822.6 KWh/m2/year at 30 m and 1519.9 KWh/m2/year at 50 m).This research is a preliminary assessment of the potential of wind energy in Hodeidah,which provides useful information for developing wind energy and an efficient wind approach.According to the International Wind Energy Rating criteria,the region of Hodeidah falls under‘Class 2’and is classified as‘marginal’for most of the year.

关键词： Energy potential wind speed weibull distribution wind power density

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Combinational therapy with myc decoy oligodeoxynucleotides encapsulated in nanocarrier and X-irradiation on breast cancer cells

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Oncology Research 2024年第2期32卷 309-323页

作者： BEHROOZ JOHARI mILAD PARVINZAD LEILAN mAHmOUD GHARBAVI YOUSEF mORTAZAVI ali sharafi HAmED REZAEEJAm Department of medical Biotechnology School of MedicineZanjan University of Medical SciencesZanjanIran Zanjan Pharmaceutical Biotechnology Research Center Zanjan University of Medical SciencesZanjanIran Nanotechnology Research Center Ahvaz Jundishapur University of Medical SciencesAhvazIran Department of Radiology Technology School of Allied Medical SciencesZanjan University of Medical SciencesZanjanIran

The myc gene is the essential oncogene in triple-negative breast cancer(TNBC).This study investigates the synergistic effects of combining myc decoy oligodeoxynucleotides-encapsulated niosomes-selenium hybrid nanocarriers with X-irradiation exposure on the mDA-mB-468 cell line.Decoy and scramble ODNs for myc transcription factor were designed and synthesized based on promoter sequences of the Bcl2 gene.The nanocarriers were synthesized by loading myc ODNs and selenium into chitosan(Chi-Se-DEC),which was then encapsulated in niosome-nanocarriers(NISm@Chi-Se-DEC).FT-IR,DLS,FESEm,and hemolysis tests were applied to confirm its characterization and physicochemical properties.moreover,cellular uptake,cellular toxicity,apoptosis,cell cycle,and scratch repair assays were performed to evaluate its anticancer effects on cancer cells.all anticancer assessments were repeated under X-ray irradiation conditions(fractionated 2Gy).Physicochemical characteristics of niosomes containing SeNPs and ODNs showed that it is synthesized appropriately.It revealed that the anticancer effect of NISm@Chi-Se-DEC can be significantly improved in combination with X-ray irradiation treatment.It can be concluded that NISm@Chi-Se-DEC nanocarriers have the potential as a therapeutic agent for cancer treatment,particularly in combination with radiation therapy and in-vivo experiments are necessary to confirm the efficacy of this nano-drug.

关键词： Combinational therapy Antisense therapy myc signaling pathway Niosomes Radiation therapy SeNPs

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Targeted anti-tumor synergistic effects of myc decoy oligodeoxynucleotides-loaded selenium nanostructure combined with chemoradiotherapy on LNCaP prostate cancer cells

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Oncology Research 2024年第1期32卷 101-125页

作者： ROGHAYEH GHORBANI mAHmOUD GHARBAVI ali sharafi ELHAm RISmANI HAmED REZAEEJAm YOUSEF mORTAZAVI BEHROOZ JOHARI Department of medical Biotechnology School of MedicineZanjan University of Medical SciencesZanjanIran Nanotechnology Research Center Ahvaz Jundishapur University of Medical SciencesAhvazIran Zanjan Pharmaceutical Biotechnology Research Center Zanjan University of Medical SciencesZanjanIran Department of Pharmaceutical Biotechnology School of PharmacyZanjan University of Medical SciencesZanjanIran molecular medicine Department Biotechnology Research CenterPasteur Institute of IranPasteur AvenueTehranIran Department of Radiology Technology School of Allied Medical SciencesZanjan University of Medical SciencesZanjanIran

In the present study,we investigated the synergistic effects of targeted methotrexate-selenium nanostructure containing myc decoy oligodeoxynucleotides along with X-irradiation exposure as a combination therapy on LNCaP prostate cancer cells.myc decoy ODNs were designed based on the promoter of Bcl-2 gene and analyzed by molecular docking and molecular dynamics assays.ODNs were loaded on the synthesized Se@BSA@Chi-mTX nanostructure.The physicochemical characteristics of nanostructures were determined by FTIR,DLS,UV-vis,TEm,EDX,in vitro release,and hemolysis tests.Subsequently,the cytotoxicity properties of them with and without X-irradiation were investigated by uptake,mTT,cell cycle,apoptosis,and scratch assays on the LNCaP cell line.The results of DLS and TEm showed negative charge(−9 mV)and nanometer size(40 nm)for Se@BSA@Chi-DEC-mTX NPs,respectively.The results of FTIR,UV-vis,and EDX showed the proper interaction of different parts and the correct synthesis of nanoparticles.The results of hemolysis showed the hemocompatibility of this nanoparticle in concentrations less than 6 mg/mL.The ODNs release from the nanostructures showed a pH-dependent manner,and the release rate was 15%higher in acidic pH.The targeted Se@BSA@Chi-labeled ODN-mTX NPs were efficiently taken up by LNCaP cells by targeting the prostate-specific membrane antigen(PSmA).The significant synergistic effects of nanostructure(containing mTX drug)treatment along with X-irradiation showed cell growth inhibition,apoptosis induction(~57%),cell cycle arrest(G2/m phase),and migration inhibition(up to 90%)compared to the control.The results suggested that the Se@BSA@Chi-DEC-mTX NPs can potentially suppress the cell growth of LNCaP cells.This nanostructure system can be a promising approach for targeted drug delivery and chemoradiotherapy in prostate cancer treatment.

关键词： Chemoradiotherapy Combination therapy Decoy oligodeoxynucleotides myc transcription factor Selenium nanoparticle Prostate cancer

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Smart Energy management System Using machine Learning

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Computers, materials & Continua 2024年第1期78卷 959-973页

作者： ali Sheraz Akram Sagheer Abbas muhammad Adnan Khan Atifa Athar Taher m.Ghazal Hussam.al Hamadi School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Pattern Recognition and machine Learning Lab Department of SoftwareGachon UniversitySeongnamGyeonggido13120Korea Department of Computer Science COMSATS University IslamabadLahore CampusLahore54000Pakistan School of Information Technology Skyline University CollegeSharjah1797United Arab Emirates Network and Communication Technology Lab Center for Cyber SecurityFaculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia College of Engineering and IT University of DubaiDubaiUnited Arab Emirates

Energy management is an inspiring domain in developing of renewable energy sources.However,the growth of decentralized energy production is revealing an increased complexity for power grid managers,inferring more quality and reliability to regulate electricity flows and less im.alance between electricity production and demand.The major objective of an energy management system is to achieve optimum energy procurement and utilization throughout the organization,minimize energy costs without affecting production,and minimize environmental effects.modern energy management is an essential and complex subject because of the excessive consumption in residential buildings,which necessitates energy optimization and increased user comfort.To address the issue of energy management,many researchers have developed various frameworks;while the objective of each framework was to sustain a balance between user comfort and energy consumption,this problem hasn’t been fully solved because of how difficult it is to solve it.An inclusive and Intelligent Energy management System(IEmS)aims to provide overall energy efficiency regarding increased power generation,increase flexibility,increase renewable generation systems,improve energy consumption,reduce carbon dioxide emissions,improve stability,and reduce energy costs.machine Learning(mL)is an emerging approach that may be beneficial to predict energy efficiency in a better way with the assistance of the Internet of Energy(IoE)network.The IoE network is playing a vital role in the energy sector for collecting effective data and usage,resulting in smart resource management.In this research work,an IEmS is proposed for Smart Cities(SC)using the mL technique to better resolve the energy management problem.The proposed system minimized the energy consumption with its intelligent nature and provided better outcomes than the previous approaches in terms of 92.11% accuracy,and 7.89% miss-rate.

关键词： Intelligent energy management system smart cities machine learning

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Using neural network modeling to improve the detection accuracy of land subsidence due to groundwater withdrawal

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Journal of mountain Science 2024年第7期21卷 2320-2333页

作者： ali m.RAJABI ali EDalAT Yasaman ABOLGHASEmI mahdi KHODAPARAST Department of Engineering Geology University of TehranTehran ***Iran Department of Civil Engineering University of QomQom ***Iran

Despite the high efficiency of remote sensing methods for rapid and large-scale detection of subsidence phenomena,this technique has limitations such as atmospheric impact and temporal and spatial decorrelation that affect the accuracy of the results.This paper proposes a method based on an artificial neural network to improve the results of monitoring land subsidence due to groundwater overexploitation by radar interferometry in the aliabad plain(Central Iran).In this regard,vertical ground deformations were monitored over 18 months using the Sentinel-1A SAR images.To model the land subsidence by a multilayer perceptron(mLP)artificial neural network,four parameters,including groundwater level,alluvial thickness,elastic modulus,and transmissivity have been applied.The model's generalizability was assessed using data derived for 144 days.According to the results,the neural network estimates the land subsidence at each ground point with an accuracy of 6.8 mm.A comparison between the predicted and actual values indicated a significant agreement.The mLP model can be used to improve the results of subsidence detection in the study area or other areas with similar characteristics.

关键词： DInSAR Land subsidence Groundwater withdrawal aliabad plain Artificial neural network

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FlowBreakdown of Hybrid Nanofluid on a Rigid Surface with Power Law Fluid as Lubricated Layers

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Computer modeling in Engineering & Sciences 2024年第2期138卷 1485-1499页

作者： mirza Naveed Jahangeer Baig Nadeem.alamat Sohail Nadeem NaeemUllah mohamed Bechir Ben Hamida Hassan ali Ghazwani Sayed m.Eldin A.S.al-Shafay Instituite of mathematics Khwaja Fareed University of Engineering and Information TechnologyRahim yar Khan64200Pakistan Department of mathematics Quaid-I-Azam UniversityIslamabad44000Pakistan Department of mathematics Wenzhou UniversityWenzhou325035China College of Engineering Department of Mechanical EngineeringImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11564Saudi Arabia Research Laboratory of Ionized Backgrounds and Reagents Studies(EmIR) Preparatory Institute for Engineering Studies of Monastir(IPEIM)University of MonastirMonastir5060Tunisia Higher School of Sciences and Technology of Hammam Sousse Department of PhysicsJazan82511Kingdom of Saudia Arabia Department of mechanical Engineering Faculty of engineeringJazan UniversityP.O.Box 45124JazanKingdom of Saudia Arabia Center of Research Faculty of EngineeringFuture University in EgyptNew Cairo11835Egypt Department of mechanical Engineering College of EngineeringPrince Sattam bin Abdulaziz UniversityAlkharj16436Saudi Arabia

Thiswork investigates an oblique stagnation point flowof hybrid nanofluid over a rigid surface with power lawfluidas lubricated layers. Copper (Cu) and Silver (Ag) solid particles are used as hybrid particles acting in water H2O asa base fluid. The mathematical formulation of flow configuration is presented in terms of differential systemthat isnonlinear in nature. The thermal aspects of the flow field are also investigated by assuming the surface is a heatedsurface with a constant temperature T. Numerical solutions to the governing mathematical model are calculatedby the RK45 algorithm. The results based on the numerical solution against various flow and thermal controllingparameters are presented in terms of line graphs. The specific results depict that the heat flux increases over thelubricated-indexed parameter.

关键词： Oblique stagnation point flow hybrid nanofluid lubricated layer magnetohydrodynamics

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