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Mechanical properties of CNT reinforced hybrid functionally graded materials for bioimplants

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Transactions of Nonferrous Metals Society of China 2014年第S1期24卷 90-98页

作者： M.Asif HUSSAIN adnan maqbool F.Ahmad KHALID Nabi BAKHSH Ali HUSSAIN Jamil Ur RAHMAN Jong Kyu PARK Tae Gone PARK Lee Jae HYUN Myong Ho KIM Faculty of Materials Science and Engineering GIK Institute of Engineering Sciences and Technology Topi KPK Pakistan Engineering Research Center for Integrated Mechatronics Materials and Components Changwon National University

The hybrid functionally graded materials(FGM) of hydroxyapatite(HA), stainless steel 316L(SS316L) and carbon nanotubes(CNT) were synthesized for biomedical implants. Three different types of FGM were produced by the combination of SS316 L and CNT to reinforce HA in discrete layers of FGM. In the first type of FGM, concentration of SS316 L was varied from 10% to 40%(mass fraction) with an increment of 10% to reinforce micro HA. In the second type of FGM, 0.5%(mass fraction) functionalized CNT was added by maintaining the rest of composition as that of the first type of FGM. In the third type of FGM, mixture of micro and nano HA(mass ratio1:1) was used, keeping rest of composition similar to the second type of FGM. All types of FGM were subjected to uniaxial compaction and sintered by pressureless sintering technique at similar compaction and sintering parameters. The results show that the densification is enhanced with the addition of CNT and nanocrystalline HA in the FGM. Hardness and fracture toughness increase in both FGM reinforced with CNT, but the increase of the hardness and fracture toughness are more pronounced in FGM with micro and nanocrystalline HA.

关键词： functionally graded materials hydroxyapatite nanocomposites biomaterial implant

Prediction of corrosion rate for friction stir processed WE43 alloy by combining PSO-based virtual sample generation and machine learning

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Journal of Magnesium and Alloys 2024年第4期12卷 1518-1528页

作者： Annayath maqbool Abdul Khalad Noor Zaman Khan Department of Mechanical Engineering National Institute of Technology SrinagarJ&K 190006India Department of Mechanical Engineering Indian Institute of TechnologyHyderabadSangareddyTelangana 502284India School of Engineering Deakin UniversityVictoria 3216Australia

The corrosion rate is a crucial factor that impacts the longevity of materials in different *** undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corrosion ***,a better understanding of the correlation between the FSP process parameters and the corrosion rate is still *** current study used machine learning to establish the relationship between the corrosion rate and FSP process parameters(rotational speed,traverse speed,and shoulder diameter)for WE43 *** Taguchi L27 design of experiments was used for the experimental *** addition,synthetic data was generated using particle swarm optimization for virtual sample generation(VSG).The application of VSG has led to an increase in the prediction accuracy of machine learning models.A sensitivity analysis was performed using Shapley Additive Explanations to determine the key factors affecting the corrosion *** shoulder diameter had a significant impact in comparison to the traverse speed.A graphical user interface(GUI)has been created to predict the corrosion rate using the identified *** study focuses on the WE43 alloy,but its findings can also be used to predict the corrosion rate of other magnesium alloys.

关键词： Corrosion rate Friction stir processing Virtual sample generation Particle swarm optimization Machine learning Graphical user interface

Sentiment Analysis of Low-Resource Language Literature Using Data Processing and Deep Learning

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Computers, Materials & Continua 2024年第4期79卷 713-733页

作者： Aizaz Ali maqbool Khan Khalil Khan Rehan Ullah Khan Abdulrahman Aloraini Department of IT and Computer Science Pak-Austria Fachhochschule:Institute of Applied Sciences and TechnologyHaripur22620Pakistan Software Competence Center Hagenberg Softwarepark 32aHagenberg4232Austria Department of Computer Science School of Engineering and Digital SciencesNazarbayev UniversityAstana010000Kazakhstan Department of Information Technology College of ComputerQassim UniversityP.O.Box 1162BuraydahSaudi Arabia

Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse *** numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiv

关键词： Urdu sentiment analysis convolutional neural networks recurrent neural network deep learning natural language processing neural networks

Two MADS-box proteins,AGL9 and AGL15,recruit the FIS-PRC2 complex to trigger the phase transition from endosperm proliferation to embryo development in Arabidopsis

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Molecular Plant 2024年第7期17卷 1110-1128页

作者： Shen Zhang Devasantosh Mohanty adnan Muzaffar Min Ni Department of Plant and Microbial Biology University of Minnesota at Twin CitiesSaint PaulMinnesota MN 55108United States of AmericaUSA

Spatiotemporal regulation of gene expression by polycomb repressive complex 2(PRc2)is critical for animal and plant *** Arabidopsis fertilization independent seed(FIS)-PRC2 complex functions specifically during plant reproduction from gametogenesis to seed *** a double fertilization event,triploid endosperm proliferates early,followed by the growth of a diploid embryo,which replaces the endosperm in Arabidopsis and many *** genes critical for endosperm proliferation such as IKkU2 and MINI3 are activated after *** we report that two MADS-box AGAMOUS-LIKE(AGL)proteins associate with the key endosperm proliferation loci and recruit the FIS-PRC2 repressive complex at 4-5 days after pollination(DAP).Interestingly,AGL9 and AGL15 only accumulate toward the end of endosperm proliferation at 4-5 DAP and promote the deposition of H3K27me3 marks at key endosperm proliferation *** of AGL9 and AGL15 or overexpression of AGL9 or AGL15 significantly influence endosperm proliferation and ***-wide analysis with cleavage Under Targets and tagmentation(CUT&Tag)sequencing and RNA sequencing revealed the landscape of endosperm H3K27me3 marks and gene expression profiles in Col-0 and agl9 ***&Tag qPCR also demonstrated the occupancy of the two MADS-box proteins and FIS-PRC2 on a few representative target *** studies suggest that MADS-box proteins could potentially recruit PRc2 to regulate many other developmental processes in plants or even in fungi and animals.

关键词： AGL9 AGL15 embryo endosperm IKU2 MEDEA MINI3

A novel fractional case study of nonlinear dynamics via analytical approach

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Applied Mathematics(A Journal of Chinese Universities) 2024年第2期39卷 276-290页

作者： Hassan Khan adnan Khan Rasool Shah Dumitru Baleanu Department of Mathematics Abdul Wali khan UniversityMardan 23200Pakistan Department of Mathematics Faculty of Arts and SciencesCankaya UniversityAnkara 06530Turkey Institute of Space Sciences Magurele-BucharestRomania

The present work describes the fractional view analysis of Newell-Whitehead-Segal equations,using an innovative *** work is carried with the help of the Caputo operator of fractional *** analytical solutions of some numerical examples are presented to confirm the reliability of the proposed *** derived results are very consistent with the actual solutions to the problems.A graphical representation has been done for the solution of the problems at various fractional-order ***,the solution in series form has the desired rate of convergence and provides the closed-form *** is noted that the procedure can be modified in other directions for fractional order problems.

关键词： Homotopy Perturbation method Shehu transform Newell-Whitehead-Segel Equation Caputo operator

Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

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Computers, Materials & Continua 2024年第3期78卷 3303-3321页

作者： Muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy Muhammad adnan Khan Muhammad Hasnain Azam Khan Muhammad adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi00000United Arab Emirates Department of Computing Skyline University CollegeSharjah1797United Arab Emirates Department of Computer Science Taibah UniversityMedina42353Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Engineering and Development Dubizzle LabsLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam-si13120Korea

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or *** cardiotocography measures infer wrongly and give wrong predictions because of human *** traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as *** condition is very important to measure at numerous stages and give proper medications to the fetus for its *** the current period Machine learning(ML)is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional *** techniques play a pivotal role in detecting fetal disease in its early *** research article uses Federated machine learning(FML)and ML techniques to classify the condition of the *** study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the ***,the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06%and 0.94%of prediction accuracy and misprediction rate,respectively,and parallel the proposed model applying K-nearest neighbor(KNN)and achieves 82.93%and 17.07%of prediction accuracy and misprediction accuracy,***,by comparing both models FML outperformed the KNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results.

关键词： Cardiotocography ML FML fetal disease bio-signal

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

Detailed analysis of the relativistic configuration of Bardeen anisotropic spheres in modified f(G)gravity

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Communications in Theoretical Physics 2024年第6期76卷 45-56页

作者： adnan Malik Ayesha Almas Tayyaba Naz Rubab Manzoor M Z Bhatti School of Mathematical Sciences Zhejiang Normal UniversityJinhuaZhejiangChina Department of Mathematics University of Management and TechnologySialkot CampusLahorePakistan National University of Computer and Emerging Sciences Lahore CampusPakistan Department of Mathematics University of Management and TechnologyJohar Town CampusLahore 54782Pakistan Department of Mathematics University of the PunjabQuaid-i-Azam CampusLahore-54590Pakistan

The aim of this work is to investigate anisotropic compact objects within the framework of f(G)modified theory of *** our present work,we utilize Krori-Barua metrics,i.e.,λ(r)=Xr^(2)+Y andβ(r)=Zr^(2).We use some matching conditions of spherically symmetric spacetime with Bardeen's model as an exterior ***,we establish some expressions of energy density and pressure components to analyze the stellar configuration of Bardeen compact stars by assuming viable f(G)*** examine the energy conditions for different stellar structures to verify the viability of our considered ***,we also investigate some other physical features,such as equilibrium condition,equation of state parameters,adiabatic index,stability analysis,mass function,surface redshift,and compactness factor,*** is worthwhile to mention here for the current study that our stellar structure in the background of Bardeen's model is more viable and stable.

关键词： Bardeen compact stars f(G)modified gravity Krori-Barua potential

Stochastic Computing Convolutional Neural Network Architecture Reinvented for Highly Efficient Artificial Intelligence Workload on Field-Programmable Gate Array

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Research 2024年第2期2024卷 55-79页

作者： Yang Yang Lee Zaini Abdul Halim Mohd Nadhir Ab Wahab Tarik adnan Almohamad School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal 14300 Penang Malaysia School of Computer Sciences Universiti Sains MalaysiaGelugor11800 PenangMalaysia Electrical-Electronics Engineering Department Faculty of EngineeringKarabuk University78050 KarabukTurkiye

Stochastic computing(SC)has a substantial amount of study on application-specific integrated circuit(ASIC)design for artificial intelligence(AI)edge computing,especially the convolutional neural network(CNN)***,SC has little to no optimization on field-programmable gate array(FPGA).Scaling up the ASIC logic without FPGA-oriented designs is inefficient,while aggregating thousands of bitstreams is still challenging in the conventional *** research has reinvented several FPGA-efficient 8-bit SC CNN computing architectures,i.e.,SC multiplexer multiply-accumulate,multiply-accumulate function generator,and binary rectified linear unit,and successfully scaled and implemented a fully parallel CNN model on Kintex7 *** proposed SC hardware only compromises 0.14%accuracy compared to binary computing on the handwriting Modified National Institute of Standards and Technology classification task and achieved at least 99.72%energy saving per image feedforward and 31?more data throughput than modern *** to SC,early decision termination pushed the performance baseline exponentially with minimum accuracy loss,making SC CNN extremely lucrative for AI edge computing but limited to classification *** SC's inherent noise heavily penalizes CNN regression performance,rendering SC unsuitable for regression tasks.

关键词： hardware Highly rendering