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Characteristics of settling of dilute suspension of particles with different density at high Reynolds numbers

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Particuology 2021年第3期19卷 62-74页

作者： ali abbas zaidi Department of Mechanical and Process Engineering ETH Zurich8092 ZurichSwitzerland

Dilute suspension of particles with same density and size develops clusters when settle at high Reynolds number(≥250).It is due to particles entrapment in the wakes produced by upstream *** this work,this phenomenon is studied for suspension having particles with different densities by numerical *** particle-fluid interactions are modelled using immersed boundary method and inter-particle collisions are modelled using discrete element *** simulations,settling Reynolds number is always kept above 250 and the suspension solid volume fraction is nearly 0.1 *** particle density ratios(*** of heavy particles to lighter particles)equal to 4:1 and 2:1 and particles with same density are *** each density ratio,the percentage volume fraction of each particle density is nearly varied from 0.8 to *** characteristics such as microstructures of settling particle,average settling velocity and velocity fluctuations of settling particles are *** show that for different density particles settling characteristics of suspension is largely dominated by heavy *** the end of paper,the underlying physics is explained for the anomalies observed in simulation.

关键词： Particle clustering at high reynolds number Suspension with different density particles Particle microstructure due to settling Immersed boundary method

Securing Cloud-Encrypted Data:Detecting Ransomware-as-a-Service(RaaS)Attacks through Deep Learning Ensemble

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Computers, Materials & Continua 2024年第4期79卷 857-873页

作者： Amardeep Singh Hamad ali Abosaq Saad Arif Zohaib Mushtaq Muhammad Irfan Ghulam abbas Arshad ali Alanoud Al Mazroa School of Computer Information Sciences University of CumberlandsWilliamsburgKentucky40769USA Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Electrical Engineering The University of LahoreLahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware *** study provides a new approach for RaaS attack detection which uses an ensemble of deep learning *** this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is *** the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are ***,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested *** proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%*** empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual *** expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.

关键词： Cloud encryption RaaS ensemble threat detection deep learning cybersecurity

Designing single atom catalysts for exceptional electrochemical CO_(2) reduction

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Chinese Journal of Structural Chemistry 2024年第1期43卷 3-5页

作者： Muhammad Humayun Mohamed Bououdina abbas Khan Sajjad ali Chundong Wang Energy Water and Environment LabCollege of Humanities and SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia School of Integrated Circuits Wuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074PR China Department of Chemistry Abdul Wali Khan University MardanMardan23200Pakistan

The release of anthropogenic CO_(2)emissions into the atmosphere has significantly accelerated global warming within the past few *** to the latest data,it is predicted that the concentration of CO_(2)will rise to 800 ppm over this century,and could reach 2000 ppm by *** high level of CO_(2)is expected to result in significant increase in global temperature as well as ocean acidification[1].

关键词： exceptional global release

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 ***,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 imbalance between electricity production and *** 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 *** energy management is an essential and complex subject because of the excessive consumption in residential buildings,which necessitates energy optimization and increased user *** 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 *** 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 *** 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)*** IoE network is playing a vital role in the energy sector for collecting effective data and usage,resulting in smart resource *** this research work,an IEMS is proposed for Smart Cities(SC)using the ML technique to better resolve the energy management *** 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

Classification and Comprehension of Software Requirements Using Ensemble Learning

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Computers, Materials & Continua 2024年第8期80卷 2839-2855页

作者： Jalil abbas Arshad Ahmad Syed Muqsit Shaheed Rubia Fatima Sajid Shah Mohammad Elaffendi Gauhar ali School of Computer Science and Technology Anhui UniversityHefei230039China School of Computing Sciences Pak Austria FachhochschuleInstitute of Applied Sciences and TechnologyHaripur22620Pakistan Department of Computer Science and IT University of LahoreLahore55150Pakistan Department of Computer Science Emerson UniversityPunjabMultan60000Pakistan EIAS(Emerging Intelligent Autonomous Systems)Data Science Lab Prince Sultan UniversityRiyad12435Saudi Arabia

The software development process mostly depends on accurately identifying both essential and optional ***,user needs are typically expressed in free-form language,requiring significant time and human resources to translate these into clear functional and non-functional *** address this challenge,various machine learning(ML)methods have been explored to automate the understanding of these requirements,aiming to reduce time and human ***,existing techniques often struggle with complex instructions and large-scale *** our study,we introduce an innovative approach known as the Functional and Non-functional Requirements Classifier(FNRC).By combining the traditional random forest algorithm with the Accuracy Sliding Window(ASW)technique,we develop optimal sub-ensembles that surpass the initial classifier’s accuracy while using fewer *** results demonstrate that our FNRC methodology performs robustly across different datasets,achieving a balanced Precision of 75%on the PROMISE dataset and an impressive Recall of 85%on the CCHIT *** datasets consistently maintain an F-measure around 64%,highlighting FNRC’s ability to effectively balance precision and recall in diverse *** findings contribute to more accurate and efficient software development processes,increasing the probability of achieving successful project outcomes.

关键词： Ensemble learning machine learning non-functional requirements requirement engineering accuracy sliding window

Genuine entanglement under squeezed generalized amplitude damping channels with memory

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Chinese Physics B 2024年第2期33卷 158-163页

作者： Mazhar ali Department of Electrical Engineering Faculty of EngineeringIslamic University MadinahMadinah 107Saudi Arabia

We study genuine entanglement among three qubits undergoing a noisy process that includes dissipation, squeezing,and decoherence. We obtain a general solution and analyze the asymptotic quantum states. We find that most of these asymptotic states can be genuinely entangled depending upon the parameters of the channel, memory parameter, and the parameters of the initial states. We study Greenberger–Horne–Zeilinger(GHZ) states and W states, mixed with white noise,and determine the conditions for them to be genuinely entangled at infinity. We find that for these mixtures, it is possible to start with a bi-separable state(with a specific mixture of white noise) and end with genuine entangled states. However, the memory parameter μ must be very high. We find that in contrast to the two-qubit case, none of the three-qubit asymptotic states for n → ∞ are genuinely entangled.

关键词： genuine entanglement squeezed thermal baths multipartite states

AMachine Learning Approach to Cyberbullying Detection in Arabic Tweets

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Computers, Materials & Continua 2024年第7期80卷 1033-1054页

作者： Dhiaa Musleh Atta Rahman Mohammed abbas Alkherallah Menhal Kamel Al-Bohassan Mustafa Mohammed Alawami Hayder ali Alsebaa Jawad ali Alnemer Ghazi Fayez Al-Mutairi May Issa Aldossary Dalal A.Aldowaihi Fahd Alhaidari Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Computer Information Systems College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Networks and Communications College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

With the rapid growth of internet usage,a new situation has been created that enables practicing *** has increased over the past decade,and it has the same adverse effects as face-to-face bullying,like anger,sadness,anxiety,and *** the anonymity people get on the internet,they tend to bemore aggressive and express their emotions freely without considering the effects,which can be a reason for the increase in cyberbullying and it is the main motive behind the current *** study presents a thorough background of cyberbullying and the techniques used to collect,preprocess,and analyze the ***,a comprehensive review of the literature has been conducted to figure out research gaps and effective techniques and practices in cyberbullying detection in various languages,and it was deduced that there is significant room for improvement in the Arabic *** a result,the current study focuses on the investigation of shortlisted machine learning algorithms in natural language processing(NLP)for the classification of Arabic datasets duly collected from Twitter(also known as X).In this regard,support vector machine(SVM),Naive Bayes(NB),Random Forest(RF),Logistic regression(LR),Bootstrap aggregating(Bagging),Gradient Boosting(GBoost),Light Gradient Boosting Machine(LightGBM),Adaptive Boosting(AdaBoost),and eXtreme Gradient Boosting(XGBoost)were shortlisted and investigated due to their effectiveness in the similar ***,the scheme was evaluated by well-known performance measures like accuracy,precision,Recall,and ***,XGBoost exhibited the best performance with 89.95%accuracy,which is promising compared to the state-of-the-art.

关键词： Supervised machine learning ensemble learning cyberbullying Arabic tweets NLP

Simulation of the deformable lateral boundaries in biaxial test using DEM

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Particuology 2024年第5期88卷 161-175页

作者： ali Momeni Barry Clarke Yong Sheng ali Hassanpour WSP 3 Wellington PlaceLeedsLS1 4APUK Hull University HullHU6 7RXUK School of Civil Engineering University of LeedsLeedsLS2 9JTUK School of Computer Science University of HullHullHU6 7RXUK School of Chemical and Process Engineering University of LeedsLeedsLS2 9JTUK

Applying the discrete element method(DEM)in soil mechanics can provide abundant information at the particle-scale and facilitates illustration of the macro-mechanical behaviour of soils based on the inter-particle *** triaxial test is one of the most common laboratory methods to study the macro-mechanical behaviour of particulate materials such as ***,many problems in geotechnical design can be assumed and simplified as a plane strain *** a biaxial test can be conducted to reproduce the macro-mechanical behaviour of soil,where the sample is enclosed by two horizontal rigid platens and a vertical latex membrane,which is a deformable continuous element and allows the enclosed specimen to deform freely while maintaining confining stress during *** paper presents an algorithm to represent physical and mechanical characteristics of latex membrane in the 2D DEM simulation of biaxial test using the PFC^(2D) *** investigate the impact of the lateral boundary conditions on the micro-macro mechanical behaviours of soil samples,two sets of DEM biaxial tests are conducted,*** rigid and deformable lateral boundary *** DEM modeling results indicate that the lateral boundary conditions have a significant effect on the micro-scale fabric properties,thickness and inclination of the shear *** comparison between these two simulations also demonstrates that the lateral boundary conditions play a major role in the peak and post-peak stress-strain behaviours as well as the dilation and critical state behaviours of granular soils.

关键词： Discrete element method Biaxial test Deformable boundaries Shear band Critical state Fabric anisotropy Geometrical stability index

Sensing the heavy water concentration in an H_(2)O-D_(2)O mixture by solid-solid phononic crystals

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Chinese Physics B 2024年第4期33卷 493-498页

作者： Mohammadreza Rahimi ali Bahrami Optoelectronic and Nanophotonics Research Laboratory(ONRL) Faculty of Electrical EngineeringSahand University of TechnologyTabrizIran

A new method based on phononic crystals is presented to detect the concentration of heavy water(D_(2)O)in an H_(2)O-D_(2)O *** have been obtained and analyzed in the concentration range of 0%-10%and 90%-100%D_(2)O.A proposed structure of tungsten scatterers in an aluminum host is *** order to detect the target material,a cavity region is considered as a sound wave resonator in which the target material with different concentrations of D_(2)O is *** changing the concentration of D_(2)O in the H_(2)O-D_(2)O mixture,the resonance frequency undergoes a frequency *** 1%change in D_(2)O concentration in the H_(2)O-D_(2)O mixture causes a frequency change of about 120 *** finite element method is used as the numerical method to calculate and analyze the natural frequencies and transmission spectra of the proposed *** performance evaluation index shows a high Q factor up to 1475758 and a high sensitivity up to 13075,which are acceptable values for sensing *** other figures of merit related to the detection performance also indicate high-quality performance of the designed sensor.

关键词： phononic crystals sensor H_(2)O-D_(2)O mixture cavity