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Artificial Intelligence Prediction of One-Part Geopolymer Compressive Strength for Sustainable Concrete

Computer Modeling in Engineering & Sciences 2024年第10期141卷 525-543页

作者： Mohamed Abdel-Mongy Mudassir Iqbal M.Farag Ahmed.M.Yosri Fahad Alsharari Saif Eldeen A.S.Yousef department of Civil Engineering College of EngineeringJouf UniversitySakaka72388Saudi Arabia department of Civil Engineering University of Engineering and TechnologyPeshawar54890Pakistan Civil Engineering department Faculty of EngineeringAl-Azhar UniversityCairo11884Egypt Civil Engineering department Faculty of EngineeringAswan UniversityAswan81528Egypt

Alkali-activated materials/geopolymer(AAMs),due to their low carbon emission content,have been the focus of recent studies on ecological *** terms of performance,fly ash and slag are preferredmaterials for precursors for developing a one-part ***,determining the optimum content of the input parameters to obtain adequate performance is quite challenging and scarcely ***,in this study,machine learning methods such as artificial neural networks(ANN)and gene expression programming(GEP)models were developed usingMATLAB and GeneXprotools,respectively,for the prediction of compressive strength under variable input materials and content for fly ash and slag-based one-part *** database for this study contains 171 points extracted from literature with input parameters:fly ash concentration,slag content,calcium hydroxide content,sodium oxide dose,water binder ratio,and curing *** performance of the two models was evaluated under various statistical indices,namely correlation coefficient(R),mean absolute error(MAE),and rootmean square error(RMSE).In terms of the strength prediction efficacy of a one-part geopolymer,ANN outperformed *** and parametric analysis were also performed to identify the significant contributor to *** to a sensitivity analysis,the activator and slag contents had the most effects on the compressive strength at 28 *** water binder ratio was shown to be directly connected to activator percentage,slag percentage,and calcium hydroxide percentage and inversely related to compressive strength at 28 days and curing temperature.

关键词： Artificial intelligence techniques one-part geopolymer artificial neural network gene expression modelling sustainable construction polymers

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Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular networks

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Computers, Materials & Continua 2024年第3期78卷 4243-4262页

作者： Youseef Alotaibi B.Rajasekar R.Jayalakshmi Surendran Rajendran department of Software Engineering College of ComputingUmm Al-Qura UniversityMakkah21955Saudi Arabia department of Electronics and Communication Engineering Sathyabama Institute of Science and TechnologyChennai600119India department of Computer Science and Engineering Panimalar Engineering CollegeChennai600123India department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical ScienceChennai602105India

Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)*** networks give a safe and more effective driving experience by presenting time-sensitive and location-aware *** communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with ***,the scheme of an effectual routing protocol for reliable and stable communications is *** research demonstrates that clustering is an intelligent method for effectual routing in a mobile ***,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in *** FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the *** accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust *** the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR *** experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.

关键词： Vehicular networks communication protocol clustering falcon optimization algorithm routing

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A Traffic-Aware and Cluster-Based Energy Efficient Routing Protocol for IoT-Assisted WSNs

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Computers, Materials & Continua 2024年第8期80卷 1831-1850页

作者： Hina Gul Sana Ullah Ki-Il Kim Farman Ali department of Computer and Software Technology University of SwatMingora19130Pakistan department of Computer Science and Engineering Chungnam National UniversityDaejeon34134Republic of Korea department of Applied AI Sungkyunkwan UniversitySeoul03063Republic of Korea

The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications,such as remote health monitoring,industrial monitoring,transportation,and smart *** and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of *** paper presents a traffic-aware,cluster-based,and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such *** proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual *** protocol considers multi-criteria attributes,i.e.,energy,traffic load,and distance parameters to select the next hop for data delivery towards the base *** performance of the proposed protocol is evaluated through the network simulator *** different traffic rates,number of nodes,and different packet sizes,the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio,energy consumption,end-to-end delay,and network *** 100 nodes,the proposed protocol achieved a 13%improvement in packet delivery ratio,10 ms improvement in delay,and 10 mJ improvement in average energy consumption over LoRaWAN.

关键词： Internet of Things wireless sensor networks traffic load clustering routing energy efficiency

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An artificial intelligence diabetes management architecture based on 5G

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Digital Communications and networks 2024年第1期10卷 75-82页

作者： Ruochen Huang Wei Feng Shan Lu Tao shan Changwei Zhang Yun Liu department of Geriatrics The First Affiliated Hospital of Nanjing Medical UniversityNanjing210096China department of Information The First Afliated Hospital of Nanjing Medical UniversityNanjing210096China department of Medical Informatics School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjing211166China department of Outpatient The First Affiliated Hospital of Nanjing Medical UniversityNanjing210096China Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and TelecommunicationsNanjing210003China

Along with the development of 5G network and Internet of Things technologies,there has been an explosion in personalized healthcare *** the 5G and Artificial Intelligence(Al)is introduced into diabetes management architecture,it can increase the efficiency of existing systems and complications of diabetes can be handled more effectively by taking advantage of *** this article,we propose a 5G-based Artificial Intelligence Diabetes Management architecture(AIDM),which can help physicians and patients to manage both acute complications and chronic *** AIDM contains five layers:the sensing layer,the transmission layer,the storage layer,the computing layer,and the application *** build a test bed for the transmission and application ***,we apply a delay-aware RA optimization based on a double-queue model to improve access efficiency in smart hospital wards in the transmission *** application layer,we build a prediction model using a deep forest *** on real-world data show that our AIDM can enhance the efficiency of diabetes management and improve the screening rate of diabetes as well.

关键词： Diabetes 5G Artificial intelligence Deep forest Smart hospital ward

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MoBShield:A Novel XML Approach for Securing Mobile Banking

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Computers, Materials & Continua 2024年第5期79卷 2123-2149页

作者： Saeed Seraj Ali Safaa Sadiq OmprakashKaiwartya Mohammad Aljaidi Alexandros Konios Mohammed Ali Mohammed Abazeed department of Computer Science Nottingham Trent UniversityClifton LaneNottinghamNG118NSUK department of Computer Science Faculty of Information TechnologyZarqa UniversityZarqa13110Jordan department of Computer Science King Khalid UniversityAbha61421Saudi Arabia

Mobile banking security has witnessed significant R&D attention from both financial institutions and *** is due to the growing number of mobile baking applications and their reachability and usefulness to ***,these applications are also attractive prey for cybercriminals,who use a variety of malware to steal personal banking *** literature in mobile banking security requiresmany permissions that are not necessary for the application’s intended security *** this context,this paper presents a novel efficient permission identification approach for securing mobile banking(MoBShield)to detect and prevent malware.A permission-based dataset is generated for mobile banking malware detection that consists large number of malicious adware apps and benign apps to use as training *** dataset is generated from 1650 malicious banking apps of the Canadian Institute of Cybersecurity,University of New Brunswick and benign apps from Google Play.A machine learning algorithm is used to determine whether amobile banking application ismalicious based on its permission ***,an eXplainable machine learning(XML)approach is developed to improve trust by explaining the reasoning behind the algorithm’s *** evaluation tests that the approach can effectively and practically identify mobile banking malware with high precision and reduced false ***,the adapted artificial neural networks(ANN),convolutional neural networks(CNN)and XML approaches achieve a higher accuracy of 99.7%and the adapted deep neural networks(DNN)approach achieves 99.6%accuracy in comparison with the state-of-the-art *** promising results position the proposed approach as a potential tool for real-world scenarios,offering a robustmeans of identifying and thwarting malware inmobile-based banking ***,MoBShield has the potential to significantly enhance the security and trustworthiness of

关键词： Security malware detection deep learning convolutional neural networks deep neural networks

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Image enhancement with intensity transformation on embedding space

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 101-115页

作者： Hanul Kim Yeji Jeon Yeong Jun Koh department of Applied Artificial Intelligence Seoul National University of Science and TechnologySeoulSouth Korea department of Computer Science and Engineering Chungnam National UniversityDaejeonSouth Korea

In recent times,an image enhancement approach,which learns the global transformation function using deep neural networks,has gained ***,many existing methods based on this approach have a limitation:their transformation functions are too simple to imitate complex colour transformations between low-quality images and manually retouched high-quality *** order to address this limitation,a simple yet effective approach for image enhancement is *** proposed algorithm based on the channel-wise intensity transformation is ***,this transformation is applied to the learnt embedding space instead of specific colour spaces and then return enhanced features to *** this end,the authors define the continuous intensity transformation(CIT)to describe the mapping between input and output intensities on the embedding ***,the enhancement network is developed,which produces multi-scale feature maps from input images,derives the set of transformation functions,and performs the CIT to obtain enhanced *** experiments on the MIT-Adobe 5K dataset demonstrate that the authors’approach improves the performance of conventional intensity transforms on colour space ***,the authors achieved a 3.8%improvement in peak signal-to-noise ratio,a 1.8%improvement in structual similarity index measure,and a 27.5%improvement in learned perceptual image patch ***,the authors’algorithm outperforms state-of-the-art alternatives on three image enhancement datasets:MIT-Adobe 5K,Low-Light,and Google HDRþ.

关键词： computer vision deep learning image enhancement image processing

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Efficient and Secure IoT Based Smart Home Automation Using Multi-Model Learning and Blockchain Technology

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3387-3415页

作者： Nazik Alturki Raed Alharthi Muhammad Umer Oumaima Saidani Amal Alshardan Reemah M.Alhebshi Shtwai Alsubai Ali Kashif Bashir department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia department of Computer Science and Engineering University of Hafr Al-BatinHafar Al-BatinSaudi Arabia department of Computer Science&Information Technology The Islamia University of BahawalpurBahawalpurPakistan department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUK Woxsen School of Business Woxsen UniversityHyderabadIndia department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon

The concept of smart houses has grown in prominence in recent *** challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device *** home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical *** paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in *** have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT *** system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing *** have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache *** feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time *** is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation ***,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber *** trial results support the proposed system and demonstrate its potential for use in everyday life.

关键词： Blockchain Internet of Things(IoT) smart home automation cybersecurity

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Restoration of the JPEG Maximum Lossy Compressed Face Images with Hourglass Block-GAN

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Computers, Materials & Continua 2024年第3期78卷 2893-2908页

作者： Jongwook Si Sungyoung Kim department of Computer AI Convergence Engineering Kumoh National Institute of TechnologyGumi39177Korea department of Computer Engineering Kumoh National Institute of TechnologyGumi39177Korea

In the context of high compression rates applied to Joint Photographic Experts Group(JPEG)images through lossy compression techniques,image-blocking artifacts may *** necessitates the restoration of the image to its original *** challenge lies in regenerating significantly compressed images into a state in which these become ***,this study focuses on the restoration of JPEG images subjected to substantial degradation caused by maximum lossy compression using Generative Adversarial networks(GAN).The generator in this network is based on theU-Net *** features a newhourglass structure that preserves the characteristics of the deep *** addition,the network incorporates two loss functions to generate natural and high-quality images:Low Frequency(LF)loss and High Frequency(HF)*** loss uses a pretrained VGG-16 network and is configured using a specific layer that best represents *** can enhance the performance in the high-frequency *** contrast,LF loss is used to handle the low-frequency *** two loss functions facilitate the generation of images by the generator,which can mislead the discriminator while accurately generating high-and low-frequency ***,by removing the blocking effects frommaximum lossy compressed images,images inwhich identities could be recognized are *** study represents a significant improvement over previous research in terms of the image resolution performance.

关键词： JPEG lossy compression restoration image generation GAN

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Secure android IoT mobile and collaborative machine learning for controlling the management of enterprise

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Journal of Control and Decision 2024年第1期11卷 15-25页

作者： Hamza Mohammed Ridha Al-Khafaji Refed Adnan Jaleel Biomedical Engineering department Al-Mustaqbal University CollegeHillahIraq Information and Communication Engineering department Al-Nahrain UniversityBaghdadIraq

There is a need for increased security measures because of wide variety of android Internet of Thing(IoT)mobile devices that can communicate with each other via networks for controlling the management of *** Curve Deffie Hellman(ECDH)and Rivest Shamir Adleman(RSA)are used to secure data in android IoT phones in efficient *** mobile can store a lot of data,including sensitive *** data saved on mobile has become a critical *** android IoT,Collaborative Machine Learning describes a method for collaboratively mining data,which makes it easier to manage and lowers cost of *** increase security in IoT phones,suggested system uses ECDH,RSA,and CML algorithms,which have been considered novelty of this *** and ECDH are computed using time of decryption,encryption,and key *** show ECDH beats other alternatives like ***,all users of the network have been tested.

关键词： IoT ECDH RSA CML android encryption decryption

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Location of Disaster Management Bases Using Spatial Analysis

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Journal of Systems Science and Systems Engineering 2024年第1期33卷 1-29页

作者： Hadi Nayyeri Sahar Zandi Mahmood Souri department of Geomorphology Faculty of Natural ResourceUniversity of KurdistanSanandajKurdistanIran department of Geography Sciences Kharazmi UniversityTehranIran Red Crescent Society of the Islamic Republic Employee of Iran HamedanIran

Pre-crisis management involves the optimal selection of relief and rescue centers to minimize *** is particularly vulnerable due to its location on the Alpine-Himalaya seismic belt,resulting in an average death rate six times higher than the global average during ***,selecting appropriate relief and rescue centers is crucial to Iran’s disaster *** selecting the placement of rescue centers,accessibility and the appropriateness of the land should be taken into account as well as the distance from high-risk *** location of these centers does not require any particular *** address this issue,a study was conducted utilizing GIS,artificial neural networks,fuzzy logic,and mathematical models to determine the optimal placement based on 12 indicators within two clusters:natural and *** examine the information layers of the initial stage,a spatial data repository concerning the variables impacting the placement of these centers was established using *** functions and algorithms such as Fuzzy Logic in IDRISI,TOPSIS,and VIKOR software,the layers were assessed for weightage before being *** study’s analysis of the models used revealed that the positioning priority limits of the areas differed across all four ***,the areas with high desirability varied to a greater extent:the fuzzy model varied by 9.3%,neural network by 12.4%,VIKOR by 4.5%,and TOPSIS by 16.2%.The variance in results can be attributed to the differing levels of risk acceptance and non-acceptance in each ***,the study yielded other significant findings such as the correlation between study area size and model ***,smaller study areas exhibited higher model *** research also demonstrated that both fuzzy and VIKOR models achieved greater *** a result,employing these models in crisis management planning,particularly in pre-crisis management for identifying rescue center lo

关键词： Crisis management GIS earthquake risk site selection

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