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Numerical Analysis of Complicated Heat and mass Transfer inside a Wustite Pellet during Reducing to Sponge Iron by H_2 and CO Gaseous mixture

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Journal of Iron and Steel Research International 2016年第11期23卷 1142-1150页

作者： Zare ghadi.ARIYAN Valipour mOHAmmAD SADEGH Biglari mOJTABA Faculty of mechanical Engineering Semnan University

Heat and mass transfer through a wustite pellet during converting to sponge iron was investigated. Pellet was reduced by a gaseous mixture containing CO and Hz. The grain model was considered to simulate gas solid reac- tion rate. A finite volume method （FVm） was implemented for solving the governing equations. The heat transfer mechanism around the pellet includes radiation and convection and within the pellet, effective heat transfer is consid- ered as a blend of particles conduction and intraparticle radiation. Heat and mass distribution along the radius of pel- let for two cases of reducing gases composed of pure H2 and pure CO was investigated. Local fractional reduction through the pellet was plotted to examine the heat and mass transfer behavior within the pellet and find their rele- vance with reduction degree. Afterwards, the impacts of pertinent parameters including gas ratio, pellet size and po rosity were studied.

关键词： heat transfer mass transfer wustite pellet reduction grain model

Diffusion mechanism in molten salt baths during the production of carbide coatings via thermal reactive diffusion

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International Journal of minerals,metallurgy and materials 2017年第12期24卷 1448-1458页

作者： Aliakbar ghadi.Hassan Saghafian mansour Soltanieh Zhi-gang Yang Center of Excellence for High Strength Alloys Technology School of Metallurgy and Materials EngineeringIran University of Science and Technology Key Laboratory of Advanced materials of ministry of Education School of Materials Science and EngineeringTsinghua University

The diffusion mechanism of carbide-forming elements from a molten salt bath to a substrate surface was studied in this research, with particular focus on the processes occurring in the molten bath at the time of coating. metal, oxide, and metal-oxide baths were investigated, and the coating process was performed on H13 steel substrates. Scanning electron microscopy and electron-probe microanalysis were used to study the coated samples and the quenched salt bath. The thickness of the carbide coating layer was 6.5 ± 0.5, 5.2 ± 0.5, or 5.7 ± 0.5 μm depending on whether it was deposited in a metal, oxide, or metal-oxide bath, respectively. The phase distribution of vanadium-rich regions was 63%, 57%, and 74% of the total coating deposited in metal, oxide, and metal-oxide baths, respectively. The results obtained using the metal bath indicated that undissolved suspended metal particles deposited onto the substrate surface. Then, carbon subsequently diffused to the substrate surface and reacted with the metal particles to form the carbides. In the oxide bath, oxide powders dissolved in the bath with or without binding to the oxidative structure(Na_2O) of borax; they were then reduced by aluminum and converted into metal particles. We concluded that, in the metal and oxide baths, the deposition of metal particles onto the sample surface is an important step in the formation of the coating.

关键词： thermal reactive diffusion diffusion mechanism carbide coating films metal particles borax bath

Automated Facial Expression Recognition and Age Estimation Using Deep Learning

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Computers, materials & Continua 2022年第6期71卷 5235-5252页

作者： Syeda Amna Rizwan Yazeed Yasin ghadi.Ahmad Jalal Kibum Kim Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science and Software Engineering Al Ain UniversityAbu Dhabi122612UAE Department of Human-Computer Interaction Hanyang UniversityAnsan15588Korea

With the advancement of computer vision techniques in surveillance systems,the need for more proficient,intelligent,and sustainable facial expressions and age recognition is *** main purpose of this study is to develop accurate facial expressions and an age recognition system that is capable of error-free recognition of human expression and age in both indoor and outdoor *** proposed system first takes an input image pre-process it and then detects faces in the entire *** that landmarks localization helps in the formation of synthetic face mask prediction.A novel set of features are extracted and passed to a classifier for the accurate classification of expressions and age *** proposed system is tested over two benchmark datasets,namely,the Gallagher collection person dataset and the Images of Groups *** system achieved remarkable results over these benchmark datasets about recognition accuracy and computational *** proposed system would also be applicable in different consumer application domains such as online business negotiations,consumer behavior analysis,E-learning environments,and emotion robotics.

关键词： Feature extraction face expression model local transform features and recurrent neural network(RNN)

Assessing Secure OpenID-Based EAAA Protocol to Prevent mITm and Phishing Attacks in Web Apps

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Computers, materials & Continua 2023年第6期75卷 4713-4733页

作者： muhammad Bilal Sandile C.Showngwe Abid Bashir Yazeed Y.ghadi College of Computer Science and Technology Zhejiang UniversityHangzhou310027China Department of mathematical Statistics and Actuarial Science Faculty of Natural and Agricultural SciencesUniversity of the Free StateBloemfontein9301South Africa Department of Computer Science National Textile UniversityFaisalabad38000Pakistan Department of Computer Science/Software Engineering Al Ain UniversityAbu DhabiUAE

To secure web applications from man-In-The-middle(mITm)and phishing attacks is a challenging task *** this purpose,authen-tication protocol plays a vital role in web communication which securely transfers data from one party to *** authentication works via OpenID,Kerberos,password authentication protocols,***,there are still some limitations present in the reported security *** this paper,the presented anticipated strategy secures both Web-based attacks by leveraging encoded emails and a novel password form pattern *** proposed OpenID-based encrypted Email’s Authentication,Authorization,and Accounting(EAAA)protocol ensure security by relying on the email authenticity and a Special Secret Encrypted Alphanumeric String(SSEAS).This string is deployed on both the relying party and the email server,which is unique and *** first authentication,OpenID Uniform Resource Locator(URL)identity,is performed on the identity provider side.A second authentication is carried out by the hidden Email’s server side and receives a third authentication *** Email’s third SSEAS authentication link manages on the relying party(RP).Compared to existing cryptographic single sign-on protocols,the EAAA protocol ensures that an OpenID URL’s identity is secured from mITm and phishing *** study manages two attacks such as mITm and phishing attacks and gives 339 ms response time which is higher than the already reported methods,such as Single Sign-On(SSO)and *** experimental sites were examined by 72 information technology(IT)specialists,who found that 88.89%of respondents successfully validated the user authorization provided to them via *** proposed EAAA protocol minimizes the higher-level risk of mITm and phishing attacks in an OpenID-based atmosphere.

关键词： Secure user authentication SSO OpenID phishing attack mITm attack

An Ingenious IoT Based Crop Prediction System Using mL and EL

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Computers, materials & Continua 2024年第4期79卷 183-199页

作者： Shabana Ramzan Yazeed Yasin ghadi.Hanan Aljuaid Aqsa mahmood Basharat Ali Department of Computer Science&IT Government Sadiq CollegeWomen UniversityBahawalpur63100Pakistan Department of Computer Science/Software Engineering Al Ain UniversityAl Ain64141UAE Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman University(PNU)Riyadh11671Saudi Arabia Agronomic Research Station Bahawalpur63100Pakistan

Traditional farming procedures are time-consuming and expensive as based on manual labor. Farmers haveno proper knowledge to select which crop is suitable to grow according to the environmental factors and soilcharacteristics. This is the main reason for the low yield of crops and the economic crisis in the agricultural sectorof the different countries. The use of modern technologies such as the Internet of Things (IoT), machine learning,and ensemble learning can facilitate farmers to observe different factors such as soil electrical conductivity (EC),and environmental factors like temperature to improve crop yield. These parameters play a vital role in suggestinga suitable crop to cope the food scarcity. This paper proposes a systemcomprised of twomodules, first module usesstatic data and the second module takes hybrid data collection (IoT-based real-time data and manual data) withmachine learning and ensemble learning algorithms to suggest the suitable crop in the farm to maximize the *** is used to train the model that predicts the crop. This system proposed an intelligent and low-cost solutionfor the farmers to process the data and predict the suitable *** implemented the proposed system in the *** efficiency and accuracy of the proposed system are confirmed by the generated results to predict the crop.

关键词： machine learning Internet of Things sensors ensemble learning

Automatic Eyewitness Identification During Disasters by Forming a Feature-Word Dictionary

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Computers, materials & Continua 2022年第9期72卷 4755-4769页

作者： Shahzad Nazir muhammad Asif Shahbaz Ahmad Hanan Aljuaid Shahbaz Ahmad Yazeed ghadi.Zubair nawaz Department of Computer Science National Textile UniversityFaisalabadPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman University(PNU)P.O.Box 84428Riyadh 11671Saudi Arabia Department of Software Engineering and Computer Science Al Ain UniversityAbu DhabiUnited Arab Emirates Department of Data Science University of the PunjabPakistan

Social media provide digitally interactional technologies to facilitate information sharing and exchanging ***,in case of disasters,a massive corpus is placed on platforms such as *** accounts can benefit humanitarian organizations and agencies,but identifying the eyewitness Tweets related to the disaster from millions of Tweets is *** approaches have been developed to address this kind of *** recent state-of-the-art system was based on a manually created dictionary and this approach was further refined by introducing linguistic ***,these approaches suffer from limitations as they are dataset-dependent and not *** this paper,we proposed a method to identify eyewitnesses from *** experiment,we utilized 13 features discovered by the pioneer of this domain and can classify the tweets to determine the *** each feature,a dictionary of words was created with the Word Dictionary maker algorithm,which is the crucial contribution of this *** algorithm inputs some terms relevant to a specific feature for its initialization and then creates the words ***,keyword matching for each feature in tweets is *** a feature exists in a tweet,it is termed as 1;otherwise,***,for 13 features,we created a file that reflects features in each *** classify the tweets based on features,Naïve Bayes,Random Forest,and Neural Network were *** approach was implemented on different disasters like earthquakes,floods,hurricanes,and Forest *** results were compared with the state-of-the-art linguistic rule-based system with 0.81 F-measure *** the same time,the proposed approach gained a 0.88 value of *** results were comparable as the proposed approach is not ***,it can be used for the identification of eyewitness accounts.

关键词： Word dictionary social media eyewitness identification disasters

Human Pose Estimation and Object Interaction for Sports Behaviour

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Computers, materials & Continua 2022年第7期72卷 1-18页

作者： Ayesha Arif Yazeed Yasin ghadi.mohammed Alarfaj Ahmad Jalal Shaharyar Kamal Dong-Seong Kim Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science and Software Engineering Al Ain UniversityAl Ain15551UAE Department of Electrical Engineering College of EngineeringKing Faisal UniversityAl-AhsaSaudi Arabia Department of IT Convergence Engineering Kumoh National Institute of TechnologyGumiKorea

In the new era of technology,daily human activities are becoming more challenging in terms of monitoring complex scenes and *** understand the scenes and activities from human life logs,human-object interaction(HOI)is important in terms of visual relationship detection and human pose *** understanding and interaction recognition between human and object along with the pose estimation and interaction modeling have been *** existing algorithms and feature extraction procedures are complicated including accurate detection of rare human postures,occluded regions,and unsatisfactory detection of objects,especially small-sized *** existing HOI detection techniques are instancecentric(object-based)where interaction is predicted between all the *** estimation depends on appearance features and spatial ***,we propose a novel approach to demonstrate that the appearance features alone are not sufficient to predict the ***,we detect the human body parts by using the Gaussian matric model(Gmm)followed by object detection using *** predict the interaction points which directly classify the interaction and pair them with densely predicted HOI vectors by using the interaction *** interactions are linked with the human and object to predict the *** experiments have been performed on two benchmark HOI datasets demonstrating the proposed approach.

关键词： Human object interaction human pose estimation object detection sports estimation sports prediction

A New S-Box Design System for Data Encryption Using Artificial Bee Colony Algorithm

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Computers, materials & Continua 2023年第10期77卷 781-797页

作者： Yazeed Yasin ghadi.mohammed SAlshehri Sultan Almakdi Oumaima Saidani Nazik Alturki Fawad masood muhammad Shahbaz Khan Department of Computer Science Al Ain UniversityAbu Dhabi112612United Arab Emirates Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Electrical Engineering Institute of Space TechnologyIslamabad4400Pakistan School of Computing Engineering and the Built EnvironmentEdinburgh Napier UniversityEdinburghEH105DTUK

Securing digital image data is a key concern in today’s information-driven *** encryption techniques are required to protect sensitive image data,with the Substitution-box(S-box)often playing a pivotal role in many symmetric encryption *** study introduces an innovative approach to creating S-boxes for encryption *** proposed S-boxes are tested for validity and non-linearity by incorporating them into an image encryption *** nonlinearity measure of the proposed S-boxes is *** qualities significantly enhance its resistance to common cryptographic attacks,ensuring high image data ***,to assess the robustness of the S-boxes,an encryption system has also been proposed and the proposed S-boxes have been integrated into the designed encryption *** validate the effectiveness of the proposed encryption system,a comprehensive security analysis including brute force attack and histogram analysis has been *** addition,to determine the level of security during the transmission and storage of digital content,the encryption system’s Number of Pixel Change Rate(NPCR),and Unified Averaged Changed Intensity(UACI)are *** results indicate a 99.71%NPCR and 33.51%*** results demonstrate that the proposed S-boxes offer a significant level of security for digital content throughout its transmission and storage.

关键词： S-box chaos artificial bee colony image encryption

CNN Based multi-Object Segmentation and Feature Fusion for Scene Recognition

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Computers, materials & Continua 2022年第12期73卷 4657-4675页

作者： Adnan Ahmed Rafique Yazeed Yasin ghadi.Suliman AAlsuhibany Samia Allaoua Chelloug Ahmad Jalal Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science and Software Engineering Al Ain UniversityAl Ain15551UAE Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Korea

Latest advancements in vision technology offer an evident impact on multi-object recognition and scene *** sceneunderstanding task is a demanding part of several technologies,like augmented reality-based scene integration,robotic navigation,autonomous driving,and tourist *** visual information in contextually unified segments,convolution neural networks-based approaches will significantly mitigate the clutter,which is usual in classical frameworks during scene *** this paper,we propose a convolutional neural network(CNN)based segmentation method for the recognition of multiple objects in an ***,after acquisition and preprocessing,the image is segmented by using ***,CNN features are extracted from these segmented objects,and discrete cosine transform(DCT)and discrete wavelet transform(DWT)features are *** the extraction of CNN features and computation of classical machine learning features,fusion is performed using a fusion ***,to select theminimal set of features,genetic algorithm-based feature selection is *** order to recognize and understand the multi-objects in the scene,a neuro-fuzzy approach is *** objects in the scene are recognized,the relationship between these objects is examined by employing the object-to-object relation ***,a decision tree is incorporated to assign the relevant labels to the scenes based on recognized objects in the *** experimental results over complex scene datasets including SUN Red Green Blue-Depth(RGB-D)and Cityscapes’demonstrated a remarkable performance.

关键词： Convolutional neural network decision tree feature fusion neurofuzzy system