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Deep Learning Based Cyber Event Detection from Open-Source Re-Emerging Social Data

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Computers, Materials & Continua 2023年第8期76卷 1423-1438页

作者： Farah Mohammad saad Al-Ahmadi Jalal Al-Muhtadi Center of Excellence in Information Assurance(CoEIA) King Saud UniversityRiyadh11543Saudi Arabia College of Computer&Information Sciences King Saud UniversityRiyadh11543Saudi Arabia

Social media forums have emerged as the most popular form of communication in the modern technology era,allowing people to discuss and express their *** increases the amount of material being shared on social media *** is a wealth of information about the threat that may be found in such open data *** security of already-deployed software and systems relies heavily on the timely detection of newly-emerging threats to their safety that can be gleaned from such *** the fact that several models for detecting cybersecurity events have been presented,it remains challenging to extract security events from the vast amounts of unstructured text present in public data *** majority of the currently available methods concentrate on detecting events that have a high number of *** is because the unstructured text in open data sources typically contains a large number of ***,to react to attacks quicker than they can be launched,security analysts and information technology operators need to be aware of critical security events as soon as possible,regardless of how often they are *** research provides a unique event detection method that can swiftly identify significant security events from open forums such as *** proposed work identified new threats and the revival of an attack or related event,independent of the volume of mentions relating to those events on *** this research work,deep learning has been used to extract predictive features from open-source *** proposed model is composed of data collection,data transformation,feature extraction using deep learning,Latent Dirichlet Allocation(LDA)based medium-level cyber-event detection and final Google Trends-based high-level cyber-event *** proposed technique has been evaluated on numerous *** results show that the proposed method outperforms existing methods in detecting cyber events by giving 95.96

关键词： Social media twitter cyber events deep learning

Torsional behavior of triangular web profile （TRIWP） steel section by experimental study

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Frontiers of Structural and Civil Engineering 2016年第4期10卷 409-419页

作者： Fatimah DE'NAN Hazwani HASAN Mohd Hanim OSMAN Sariffudin saad School of Civil Engineering Engineering Campus Universiti Sains Malaysia Pulau Pinang 14300 Malaysia Faculty of Civil Engineering Universiti Teknologi Malaysia Skudai Johor 8131 O Malaysia

A triangular web profile （TriWP） is a modified section where the flanges are connected to a web plate of triangular profile. This study examined the torsional behavior of TriWP steel sections and compared to that of the fiat web （FW） steel sections. Three types of specimen sizes were used： 180 mmx 75 mm × 5 mm× 2 mm, 200 mm × 100 mm× 8 mm ×6 mm, and 200 mm× 100 mm × 6 mm× 5 mm. All the specimens were loaded vertically until the maximum load was achieved and then the load was released. For both types of specimens, it was observed that the torsional rotation for bigger size [200 mm× 100 mm× 8 mm × 6 mm] were smaller than that of smaller size [ 180 mm × 75 mm×5 mm× 2 mm] of the specimens. At the maximum torsional loading, the experimental result was compared to the theoretical calculation. The comparison showed that the percentage difference ranged from 1.10% to 16.80%. From the graph of torsional load versus rotational angle, the torsional rotation for all TriWP steel sections were smaller than that of the FW steel section under the same torsional loading i.e., 0.2 kNm and 1 kNm. The range between FW and TriWP were 3.74 to 71.83 at 0.2 kNm while 14.5 to 75.1 at 1.0 kNm. The findings were shown that the TriWP steel sections had better resistance against torsion in comparison to FW steel section.

关键词： corrugated web i-beam non uniform steel section torsion resistance torsion angle triangular web profile steel section

RoGRUT: A Hybrid Deep Learning Model for Detecting Power Trapping in Smart Grids

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Computers, Materials & Continua 2024年第5期79卷 3175-3192页

Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity *** hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by *** development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data,including information on client consumption,which may be used to identify electricity theft using machine learning and deep learning ***,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive ***-based solutions are presented in the literature to identify electricity theft but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of such models lead to poor *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious *** key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft *** advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for *** effectiveness of the RoGRUTis evaluated using the dataset fromactual smartmeters.A significant number of simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classification *** performance evaluation of the proposed model revealed exemplary results across *** accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The F1-Score,a measure of overall performance,stood at 85%.Furthermore,themodel exhibited a noteworthyMatthew correlation coefficient of 78%and excelled with an area under the curve of 91%.

关键词： Electricity theft smart grid RoBERTa GRU transfer learning

Numerical and experimental comparison of the vaned diffuser interaction inside the impeller velocity field of a centrifugal pump

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Science China(Technological Sciences) 2011年第2期54卷 286-294页

作者： ATIF Abdelmadjid BENMANSOUR saad BOIS Gerard DUPONT Patrick Laboratory of Advanced Mechanics FGMGP/USTHBBP32 El Alia16111AlgerAlgeria Laboratory of Mechanics of Lille ENSAM-Lille8 Bd Louis XIV59046LilleFrance Laboratory of Mechanics of Lille EC-LilleBP48 Villeneuve d’Ascq59651LilleFrance

The paper refers to the analysis of interactions between the impeller and the vaned diffuser based on the air model of a radial flow *** study deals with a numerical simulation of the flow for a full 360°entire impeller and *** task is carried out closely under the design operating conditions and for one particular position of the impeller blade with respect to the diffuser *** all the results,the focus is mainly on the flow pattern at the exit part inside the impeller facing the diffuser *** results are compared to the available PIV measurements.

关键词： centrifugal pump impeller vaned diffuser rotor-stator interaction

Wormhole solutions and energy conditions in f(R,G)gravity

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Communications in Theoretical Physics 2021年第11期73卷 131-141页

作者： M Farasat Shamir G Mustafa saad Waseem Mushtaq Ahmad National University of Computer and Emerging Sciences Lahore CampusPakistan Department of Mathematics Shanghai UniversityShanghai200444China National University of Computer and Emerging Sciences Chiniot-Faisalabad CampusPakistan

In this manuscript,the traversable wormhole solutions have been explored in modified f(R,G)gravity by taking into consideration the model f(R,G)=R+rG2,where R is the Ricci curvature scalar and G is the Gauss–Bonnet *** acceptable form of the redshift function has been incorporated which is a non-constant in nature along with the implementation of those already defined in literature,the two shape functions namely b(r)=r/exp(r-r0)and b(r)=r0log(r+1)/log(r0+1).It is shown by studying the energy condition and through the graphical analysis that the null energy bounds for the effective energy-momentum tensor are generally violated for the presence of the ordinary matter in modified f(R,G)*** conditions associated with the matter content threading the wormhole geometries are evaluated and in general are found to favor the null energy conditions in the vicinity of the wormhole throat,the existence of the nonexotic wormhole geometries threaded by the matter has been confirmed under this gravity.

关键词： f(R,G)gravity energy conditions wormholes shape function

Optoelectronic properties of SnO2 thin films sprayed at different deposition times

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Chinese Physics B 2016年第4期25卷 296-302页

作者： Allag Abdelkrim saad Rahmane Ouahab Abdelouahab Attouche Hafida Kouidri Nabila Laboratoire de Physique des Couches Minces et Applications Universit de Biskra BP 145 RP 07000 Biskra Alg&ie

This article presents the elaboration of tin oxide （SnO2） thin films on glass substrates by using a home-made spray pyrolysis system. Effects of film thickness on the structural, optical, and electrical film properties are investigated. The films are characterized by several techniques such as x-ray diffraction （XRD）, atomic force microscopy （AFM）, ultraviolet- visible （UV-Vis） transmission, and four-probe point measurements, and the results suggest that the prepared films are uniform and well adherent to the substrates. X-ray diffraction （XRD） patterns show that SnO2 film is of polycrystal with cassiterite tetragonal crystal structure and a preferential orientation along the （110） plane. The calculated grain sizes are in a range from 32.93 nm to 56.88 nm. Optical transmittance spectra of the films show that their high transparency average transmittances are greater than 65% in the visible region. The optical gaps of SnO2 thin films are found to be in a range of 3.64 eV-3.94 eV. Figures of merit for SnO2 thin films reveal that their maximum value is about 1.15 x 10-4 Ω-1 at λ = 550 nm. Moreover, the measured electrical resistivity at room temperature is on the order of 10^-2 Ω.cm.

关键词： thin film SnO2 spray pyrolysis thickness properties

Global Piecewise Analysis of HIV Model with Bi-Infectious Categories under Ordinary Derivative and Non-Singular Operator with Neural Network Approach

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 609-633页

作者： Ghaliah Alhamzi Badr saad TAlkahtani Ravi Shanker Dubey Mati ur Rahman Department of Mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh13318Saudi Arabia Department of Mathematics College of ScienceKing Saud UniversityRiyadh11989Saudi Arabia Department of Mathematics Amity School of Applied SciencesAmity University RajasthanJaipur302002India School of Mathematical Sciences Jiangsu UniversityZhenjiang212013China Department of Computer Science and Mathematics Lebanese American UniversityBeirut13-5053Lebanon

This study directs the discussion of HIV disease with a novel kind of complex dynamical generalized and piecewise operator in the sense of classical and Atangana Baleanu(AB)derivatives having arbitrary *** HIV infection model has a susceptible class,a recovered class,along with a case of infection divided into three sub-different levels or categories and the recovered *** total time interval is converted into two,which are further investigated for ordinary and fractional order operators of the AB derivative,*** proposed model is tested separately for unique solutions and existence on bi *** numerical solution of the proposed model is treated by the piece-wise numerical iterative scheme of Newtons *** proposed method is established for piece-wise derivatives under natural order and non-singular Mittag-Leffler *** cross-over or bending characteristics in the dynamical system of HIV are easily examined by the aspect of this research having a memory effect for controlling the said *** study uses the neural network(NN)technique to obtain a better set of weights with low residual errors,and the epochs number is considered *** obtained figures represent the approximate solution and absolute error which are tested with NN to train the data accurately.

关键词： HIV infection model qualitative scheme approximate solution piecewise global operator neural network

Classification COVID-19 Based on Enhancement X-Ray Images and Low Complexity Model

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Computers, Materials & Continua 2022年第7期72卷 561-576页

作者： Aymen saad Israa SKamil Ahmed Alsayat Ahmed Elaraby Department of Information Technology Technical College of ManagementKufaAl Furat Alawsat UniversityIraq Department of Medical Laboratory Techniques Al-Mustaqbal University CollegeHillaIraq Department of Computer Science College of Computer and Information SciencesJouf UniversitySaudi Arabia Department of Computer Science Faculty of Computers and InformationSouth Valley UniversityQenaEgypt

COVID-19 has been considered one of the recent epidemics that occurred at the last of 2019 and the beginning of 2020 that world *** spread of COVID-19 requires a fast technique for diagnosis to make the appropriate decision for the treatment.X-ray images are one of the most classifiable images that are used widely in diagnosing patients’data depending on radiographs due to their structures and tissues that could be *** Neural Networks(CNN)is the most accurate classification technique used to diagnose COVID-19 because of the ability to use a different number of convolutional layers and its high classification *** using CNNs techniques requires a large number of images to learn and obtain satisfactory *** this paper,we used SqueezNet with a modified output layer to classify X-ray images into three groups:COVID-19,normal,and *** this study,we propose a deep learning method with enhance the features of X-ray images collected from Kaggle,Figshare to distinguish between COVID-19,Normal,and Pneumonia *** this regard,several techniques were used on the selected image samples which are Unsharp filter,Histogram equal,and Complement image to produce another view of the *** Squeeze Net CNN model has been tested in two scenarios using the 13,437 X-ray images that include 4479 for each type(COVID-19,Normal and Pneumonia).In the first scenario,the model has been tested without any enhancement on the *** achieved an accuracy of 91%.But,in the second scenario,the model was tested using the same previous images after being improved by several techniques and the performance was high at approximately 95%.The conclusion of this study is the used model gives higher accuracy results for enhanced images compared with the accuracy results for the original images.A comparison of the outcomes demonstrated the effectiveness of ourDLmethod for classifying COVID-19 based on enhanced X-ray images.

关键词： COVID-19 X-ray image enhancement classification CNN SqueezNet model

An efficient hash-based authenticated key agreement scheme for multi-server architecture resilient to key compromise impersonation

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Digital Communications and Networks 2021年第1期7卷 140-150页

作者： Inam ul haq Jian Wang Youwen Zhu saad Maqbool College of Computer Science and Technology Nanjing University o f Aeronautics and AstronauticsNanjing210016China National University of Science and Technology Islamabad4600Pakistan

During the past decade,rapid advances in wireless communication technologies have made it possible for users to access desired services using hand-held *** providers have hosted multiple servers to ensure seamless online services to *** ensure the security of this online communication,researchers have proposed several multi-server authentication schemes incorporating various cryptographic *** to the low power and computational capacities of mobile devices,the hash-based multi-server authenticated key agreement schemes with offline Registration Server(RS)are the most efficient ***,Kumar-Om presented such a scheme and proved its security against all renowned ***,we find that their scheme bears an incorrect login phase,and is unsafe to the trace attack,the Session-Specific Temporary Information Attack(SSTIA),and the Key Compromise Impersonation Attack(KCIA).In fact,all of the existing multi-server authentication schemes(hash-based with offline RS)do not withstand *** deal with this situation,we propose an improved hash-based multi-server authentication scheme(with offline RS).We analyze the security of the proposed scheme under the random oracle model and use the t4Automated Validation of Internet Security Protocols and Applications''(AVISPA)*** comparative analysis of communication overhead and computational complexity metrics shows the efficiency of the proposed scheme.

关键词： Multi-server architecture Authenticated key agreement Registration server One-way hash function Key compromise impersonation