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Machine Learning Enabled Novel Real-Time IoT Targeted DoS/DDoS Cyber Attack Detection System

Computers, Materials & Continua 2024年第9期80卷 3655-3683页

作者： Abdullah Alabdulatif Navod Neranjan Thilakarathne mohamed Aashiq Department of Cybersecurity College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of ICT Faculty of TechnologyUniversity of ColomboColombo00700Sri Lanka Department of Computer Science and Engineering Faculty of EngineeringSouth Eastern University of Sri LankaOluvil32360Sri Lanka

The increasing prevalence of Internet of Things(IoT)devices has introduced a new phase of connectivity in recent years and,concurrently,has opened the floodgates for growing cyber *** the myriad of potential attacks,Denial of Service(DoS)attacks and Distributed Denial of Service(DDoS)attacks remain a dominant concern due to their capability to render services inoperable by overwhelming systems with an influx of *** IoT devices often lack the inherent security measures found in more mature computing platforms,the need for robust DoS/DDoS detection systems tailored to IoT is paramount for the sustainable development of every domain that IoT *** this study,we investigate the effectiveness of three machine learning(ML)algorithms:extreme gradient boosting(XGB),multilayer perceptron(MLP)and random forest(RF),for the detection of IoTtargeted DoS/DDoS attacks and three feature engineering methods that have not been used in the existing stateof-the-art,and then employed the best performing algorithm to design a prototype of a novel real-time system towards detection of such DoS/DDoS *** CICIoT2023 dataset was derived from the latest real-world IoT traffic,incorporates both benign and malicious network traffic patterns and after data preprocessing and feature engineering,the data was fed into our models for both training and validation,where findings suggest that while all threemodels exhibit commendable accuracy in detectingDoS/DDoS attacks,the use of particle swarmoptimization(PSO)for feature selection has made great improvements in the performance(accuracy,precsion recall and F1-score of 99.93%for XGB)of the ML models and their execution time(491.023 sceonds for XGB)compared to recursive feature elimination(RFE)and randomforest feature importance(RFI)*** proposed real-time system for DoS/DDoS attack detection entails the implementation of an platform capable of effectively processing and analyzing network traffic in *** inv

关键词： Machine learning Internet of Things(IoT),DoS,DDoS cybersecurity intrusion prevention network security,feature optimization,sustainability

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Shear Let Transform Residual Learning Approach for Single-Image Super-Resolution

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Computers, Materials & Continua 2024年第5期79卷 3193-3209页

作者： Israa Ismail Ghada Eltaweel mohamed Meselhy Eltoukhy Department of Computer Science Faculty of Computers and InformaticsSuez Canal UniversityIsmailia51422Egypt Department of Information Technology College of Computing and Information Technology at KhulaisUniversity of JeddahJeddahSaudi Arabia

Super-resolution techniques are employed to enhance image resolution by reconstructing high-resolution images from one or more low-resolution ***-resolution is of paramount importance in the context of remote sensing,satellite,aerial,security and surveillance ***-resolution remote sensing imagery is essential for surveillance and security purposes,enabling authorities to monitor remote or sensitive areas with greater *** study introduces a single-image super-resolution approach for remote sensing images,utilizing deep shearlet residual learning in the shearlet transform domain,and incorporating the Enhanced Deep Super-Resolution network(EDSR).Unlike conventional approaches that estimate residuals between high and low-resolution images,the proposed approach calculates the shearlet coefficients for the desired high-resolution image using the provided low-resolution image instead of estimating a residual image between the high-and low-resolution *** shearlet transform is chosen for its excellent sparse approximation ***,remote sensing images are transformed into the shearlet domain,which divides the input image into low and high *** shearlet coefficients are fed into the EDSR *** high-resolution image is subsequently reconstructed using the inverse shearlet *** incorporation of the EDSR network enhances training stability,leading to improved generated *** experimental results from the Deep Shearlet Residual Learning approach demonstrate its superior performance in remote sensing image recovery,effectively restoring both global topology and local edge detail information,thereby enhancing image *** to other networks,our proposed approach outperforms the state-of-the-art in terms of image quality,achieving an average peak signal-to-noise ratio of 35 and a structural similarity index measure of approximately 0.9.

关键词： Super-resolution shearlet transform shearlet coefficients enhanced deep super-resolution network

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Insulin resistance as the molecular link between diabetes and Alzheimer's disease

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World Journal of Diabetes 2024年第7期15卷 1430-1447页

作者： Mona mohamed Ibrahim Abdalla Department of Human Biology School of MedicineInternational Medical UniversityBukit Jalil 57000Kuala LumpurMalaysia

Diabetes mellitus(DM)and Alzheimer's disease(AD)are two major health concerns that have seen a rising prevalence *** studies have indicated a possible link between DM and an increased risk of developing ***,while primarily known for its role in regulating blood sugar,also plays a vital role in protecting brain *** resistance(IR),especially prevalent in type 2 diabetes,is believed to play a significant role in AD's *** insulin signalling becomes dysfunctional,it can negatively affect various brain functions,making individuals more susceptible to AD's defining features,such as the buildup of beta-amyloid plaques and tau protein *** research suggests that addressing insulin-related issues might help reduce or even reverse the brain changes linked to *** review aims to explore the relationship between DM and AD,with a focus on the role of *** also explores the molecular mechanisms by which IR might lead to brain changes and assesses current treatments that target *** IR's role in the connection between DM and AD offers new possibilities for treatments and highlights the importance of continued research in this interdisciplinary field.

关键词： Alzheimer's disease Insulin resistance Obesity Dementia Diabetes Metabolic syndrome

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An inverse method for characterization of dynamic response of 2D structures under stochastic conditions

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Chinese Journal of Aeronautics 2024年第3期37卷 440-455页

作者： Xuefeng LI Abdelmalek ZINE mohamed ICHCHOU Noureddine BOUHADDI Pascal FOSSAT Laboratory of Tribology and Systems Dynamic Central School of LyonEcully 69134France Institut Camille Jordan Central School of LyonEcully 69134France Department of Applied Mechanics University of Burgundy Franche-ComtéBesancon 25000France

The reliable estimation of the wavenumber space(k-space)of the plates remains a longterm concern for acoustic modeling and structural dynamic behavior *** current analyses of wavenumber identification methods are based on the deterministic *** this end,an inverse method is proposed for identifying wave propagation characteristics of twodimensional structures under stochastic conditions,such as wavenumber space,dispersion curves,and band *** proposed method is developed based on an algebraic identification scheme in the polar coordinate system framework,thus named Algebraic K-Space Identification(AKSI)***,a model order estimation strategy and a wavenumber filter are proposed to ensure that AKSI is successfully *** main benefit of AKSI is that it is a reliable and fast method under four stochastic conditions:(A)High level of signal noise;(B)Small perturbation caused by uncertainties in measurement points’coordinates;(C)Non-periodic sampling;(D)Unknown structural *** validate the proposed method,we numerically benchmark AKSI and three other inverse methods to extract dispersion curves on three plates under stochastic *** experiment is then performed on an isotropic steel *** investigations demonstrate that AKSI is a good in-situ k-space estimator under stochastic conditions.

关键词： Inverse method Dispersion relation Wavenumber space Periodic plates Stochastic conditions Wave propagation characterization

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A new technique for fault diagnosis in transformer insulating oil based on infrared spectroscopy measurements

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High Voltage 2024年第2期9卷 319-335页

作者： mohamed M.F.Darwish mohamed H.A.Hassan Nagat M.K.Abdel-Gawad Matti Lehtonen Diaa-Eldin A.Mansour Department of Electrical Engineering Faculty of Engineering at ShoubraBenha UniversityCairoEgypt Department of Electrical Engineering and Automation School of Electrical EngineeringAalto UniversityEspooFinland Department of Electrical Power Engineering Egypt-Japan University of Science and Technology(E-JUST)New Borg El-Arab CityEgypt Department of Electrical Power and Machines Engineering Faculty of EngineeringTanta UniversityTantaEgypt

Condition monitoring of the insulating system within power transformers has a massive importance according to the electrical *** gas analysis(DGA)is frequently used for this ***,DGA lacks the necessary level of accuracy to identify all equipment faults,particularly in their initial stages of ***,it does not have the capability for real-time monitoring and relies on manual sampling and laboratory testing,causing potential delays in fault ***,the interpretation of DGA data necessitates specialised expertise,which may pose difficulties for smaller entities that have limited access to ***,the contribution of this research is to use infrared spectroscopy measurements as a new effective technique substituting the DGA method for fault diagnosis in insulating *** inception faults that were considered in this study were the electrical fault(discharges of high energy)and the thermal fault(300°C

关键词： fault diagnosis spectroscopy

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Classified VPN Network Traffic Flow Using Time Related to Artificial Neural Network

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Computers, Materials & Continua 2024年第7期80卷 819-841页

作者： Saad Abdalla Agaili mohamed Sefer Kurnaz Department of Electrical and Computer Engineering Altinbas UniversityIstanbul34000Turkey

VPNs are vital for safeguarding communication routes in the continually changing cybersecurity ***,increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorizeVPNnetwork *** present a novelVPNnetwork traffic flowclassificationmethod utilizing Artificial Neural Networks(ANN).This paper aims to provide a reliable system that can identify a virtual private network(VPN)traffic fromintrusion attempts,data exfiltration,and denial-of-service *** compile a broad dataset of labeled VPN traffic flows from various apps and usage ***,we create an ANN architecture that can handle encrypted communication and distinguish benign from dangerous *** effectively process and categorize encrypted packets,the neural network model has input,hidden,and output *** use advanced feature extraction approaches to improve the ANN’s classification accuracy by leveraging network traffic’s statistical and behavioral *** also use cutting-edge optimizationmethods to optimize network characteristics and *** suggested ANN-based categorization method is extensively tested and *** show the model effectively classifies VPN traffic *** also show that our ANN-based technique outperforms other approaches in precision,recall,and F1-score with 98.79%*** study improves VPN security and protects against new *** VPNtraffic flows effectively helps enterprises protect sensitive data,maintain network integrity,and respond quickly to security *** study advances network security and lays the groundwork for ANN-based cybersecurity solutions.

关键词： VPN network traffic flow ANN classification intrusion detection data exfiltration encrypted traffic feature extraction network security

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A Practical Study of Intelligent Image-Based Mobile Robot for Tracking Colored Objects

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Computers, Materials & Continua 2024年第8期80卷 2181-2197页

作者： Mofadal Alymani mohamed Esmail Karar Hazem Ibrahim Shehata College of Computing and Information Technology Shaqra UniversityShaqra11961Saudi Arabia Faculty of Electronic Engineering Menoufia UniversityMenouf32952Egypt Faculty of Engineering Zagazig UniversityZagazig44519Egypt

Object tracking is one of the major tasks for mobile robots in many real-world ***,artificial intelligence and automatic control techniques play an important role in enhancing the performance of mobile robot *** contrast to previous simulation studies,this paper presents a new intelligent mobile robot for accomplishing multi-tasks by tracking red-green-blue(RGB)colored objects in a real experimental ***,a practical smart controller is developed based on adaptive fuzzy logic and custom proportional-integral-derivative(PID)schemes to achieve accurate tracking results,considering robot command delay and tolerance *** design of developed controllers implies some motion rules to mimic the knowledge of experienced *** scenarios of three colored object combinations have been successfully tested and evaluated by using the developed controlled image-based robot *** PID control failed to handle some tracking scenarios in this *** proposed adaptive fuzzy PID control achieved the best accurate results with the minimum average final error of 13.8 cm to reach the colored targets,while our designed custom PID control is efficient in saving both average time and traveling distance of 6.6 s and 14.3 cm,*** promising results demonstrate the feasibility of applying our developed image-based robotic system in a colored object-tracking environment to reduce human workloads.

关键词： Mobile robot autonomous systems fuzzy logic control real-time image processing

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Erdafitinib and checkpoint inhibitors for first-line and second-line immunotherapy of hepatic,gastrointestinal,and urinary bladder carcinomas:Recent concept

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World Journal of Hepatology 2024年第4期16卷 490-493页

作者： mohamed Wishahi Department of Urology Theodor Bilharz Research InstituteCairo 12411Egypt

Cancer immunotherapy is administered for first-line,second-line,neoadjuvant,or adjuvant treatment of advanced,metastatic,and recurrent cancer in the liver,gastrointestinal tract,and genitourinary tract,and other solid *** is a fibroblast growth factor receptor(FGFR)inhibitor,and it is an adenosine triphosphate competitive inhibitor of FGFR1,FGFR2,FGFR3,and *** checkpoint inhibitors are monoclonal antibodies that block programmed cell death protein 1(PD-1)and its ligand that exert intrinsic antitumor *** promising results of first-line treatment of advanced and metastatic urothelial carcinoma with PD-1 blockades with single or combined agents,indicate a new concept in the treatment of advanced,metastatic,and recurrent hepatic and gastrointestinal *** immunotherapy as first-line treatment will improve overall survival and provide better quality of *** is arising as to whether to apply the cancer immunotherapy as first-line treatment in invasive carcinomas,or as second-line treatment in recurrent or metastatic carcinoma following the standard *** literature in the field is not definite,and so far,there has been no consensus on the best approach in this *** present,as it is described in this editorial,the decision is applied on a case-by-case basis.

关键词： Programmed cell death protein-ligand 1 Erdafitinib Liver cancer Fibroblast growth factor receptor inhibitors Checkpoint inhibitors Bladder cancer Metastases

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Combined CNN-LSTM Deep Learning Algorithms for Recognizing Human Physical Activities in Large and Distributed Manners:A Recommendation System

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Computers, Materials & Continua 2024年第4期79卷 351-372页

作者： Ameni Ellouze Nesrine Kadri Alaa Alaerjan mohamed Ksantini Control and Energy Management Laboratory National Engineering SchoolPreparatory Institute for Engineering StudiesUniversity of SfaxSfax3029Tunisia Higher Institute of Computer Science and Communication Technologies University of SousseSousseBN19RHTunisia College of Computer and Information Sciences Jouf UniversityPO Box 2014SakakahSaudi Arabia

Recognizing human activity(HAR)from data in a smartphone sensor plays an important role in the field of health to prevent chronic *** and weekly physical activities are recorded on the smartphone and tell the user whether he is moving well or ***,smartphones and their associated sensing devices operate in distributed and unstable ***,collecting their data and extracting useful information is a significant *** this context,the aimof this paper is twofold:The first is to analyze human behavior based on the recognition of physical *** the results of physical activity detection and classification,the second part aims to develop a health recommendation system to notify smartphone users about their healthy physical behavior related to their physical *** system is based on the calculation of calories burned by each user during physical *** this way,conclusions can be drawn about a person’s physical behavior by estimating the number of calories burned after evaluating data collected daily or even weekly following a series of physical *** identify and classify human behavior our methodology is based on artificial intelligence models specifically deep learning techniques like Long Short-Term Memory(LSTM),stacked LSTM,and bidirectional *** human activity data contains both spatial and temporal information,we proposed,in this paper,to use of an architecture allowing the extraction of the two types of information *** Convolutional Neural Networks(CNN)has an architecture designed for spatial information,our idea is to combine CNN with LSTM to increase classification accuracy by taking into consideration the extraction of both spatial and temporal *** results obtained achieved an accuracy of 96%.On the other side,the data learned by these algorithms is prone to error and *** overcome this constraint and improve performance(96%),we proposed to use the

关键词： Human physical activities smartphone sensors deep learning distributed monitoring recommendation system uncertainty healthy calories

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Intermittent fasting and the liver: Focus on the Ramadan model

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World Journal of Hepatology 2024年第8期16卷 1070-1083页

作者： mohamed H Emara Hanan Soliman Ebada M Said Hassan Elbatae mostafa Elazab Shady Elhefnawy Tarik I Zaher Ahmed Abdel-Razik mohamed Elnadry Department of Hepatology Gastroenterology and Infectious DiseasesKafrelsheikh UniversityKafr-Elshikh 33516Egypt Department of Medicine Alyousif HospitalAlkhobar 34622Saudi Arabia Department of Tropical Medicine and Infectious Diseases Tanta UniversityTanta 31512Egypt Department of Hepatology Gastroenterology and Infectious DiseasesBenha UniversityBenha 13511Egypt Department of Tropical Medicine Zagazig UniversityZagazig 44519Egypt Department of Tropical Medicine Mansoura UniversityMansoura 35516Egypt Department of Hepato-Gastroenterology and Infectious Diseases Al-Azhar UniversityCairo 11651Egypt

Intermittent fasting(IF)is an intervention that involves not only dietary modific-ations but also behavioral changes with the main core being a period of fasting alternating with a period of controlled *** duration of fasting differs from one regimen to *** fasting(RF)is a religious fasting for Muslims,it lasts for only one month every one lunar *** this model of fasting,observers abstain from food and water for a period that extends from dawn to *** period of daily fasting is variable(12-18 hours)as Ramadan rotates in all seasons of the ***,longer duration of daily fasting is observed during the *** fact,RF is a peculiar type of *** is a dry IF as no water is allowed during the fasting hours,also there are no calorie restrictions during feeding hours,and the mealtime is exclusively *** three variables of the RF model are believed to have a variable impact on different liver *** was evaluated by different observational and interventional studies among patients with non-alcoholic fatty liver disease and it was associated with improve-ments in anthropometric measures,metabolic profile,and liver biochemistry regardless of the calorie restriction among lean and obese *** situation is rather different for patients with liver *** was associated with adverse events among patients with liver cirrhosis irrespective of the underlying etiology of *** patients developed new ascites,ascites were increased,had higher serum bilirubin levels after Ramadan,and frequently developed hepatic encephalopathy and acute upper gastrointestinal *** complications were higher among patients with Child class B and C cirrhosis,and some fatalities occurred due to *** transplant recipients as a special group of patients,are vulnerable to dehydration,fluctuation in blood immunosuppressive levels,likelihood of deterioration and hence observing RF without special precautions

关键词： Intermittent fasting Ramadan fasting Non-alcoholic fatty liver disease Liver cirrhosis Peptic ulcer Liver transplantation Gilbert syndrome

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