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American Journal of Analytical Chemistry 2024年第7期15卷 219-228页

作者： Laila abdullah Alshatti The Public Authority for Applied Education and Training College of Nursing General Science Department Shwaikh B State of Kuwait

The new method proposed is based on the formation of hydralazine-Bromophenol blue ion pair simply and without further extraction or heating. The ion pair was prepared in the presence of pH 3 citrate buffer forming a yellow-colored chromogen. A new maximum UV-visible band formed at 416 nm. The color was stable for more than 10 hours and obeyed Beer’s Law over the concentration range of 10 - 50 µg/mL. The calculated molar absorptivity and Sandell’s sensitivity were 1.01 × 104 L∙mol−1∙cm−1 and 0.0514 µg/mL, respectively. The elements of method validation stipulated by The International Conference on Harmonization [Q2 (R1)] were applied for hydralazine hydrochloride assay in pure and pharmaceutical tablet formulation. The average recoveries of the pure solution and the pharmaceutical formulation were 98.94% and 99.50%, respectively. The results were statistically compared by F-test, which indicates that the method can be precise and repeatable for both pure and pharmaceutical solutions. The method was found to be accurate, reproducible, and cost-effective, and validated for the assay of hydralazine in terms of the routine quality control.

关键词： Spectrophotometry Validation Hydralazine Hydrochloride International Conference on Harmonization Q2 (R1)

Contrast Normalization Strategies in Brain Tumor Imaging:From Preprocessing to Classification

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1539-1562页

作者： Samar M.Alqhtani Toufique A.Soomro Faisal Bin Ubaid Ahmed Ali Muhammad Irfan abdullah A.Asiri Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Electronic Engineering The University of LarkanoLarkanaSindh75660Pakistan Computer Science Department Sukkur IBA UniversitySukkurSindh65200Pakistan Eletrical Engineering Department Sukkur IBA UniversitySukkurSindh65200Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia

Cancer-related to the nervous system and brain tumors is a leading cause of mortality in various *** resonance imaging(MRI)and computed tomography(CT)are utilized to capture brain *** plays a crucial role in the diagnosis of brain tumors and the examination of other brain ***,manual assessment of MRI images by radiologists or experts is performed to identify brain tumors and abnormalities in the early stages for timely ***,early diagnosis of brain tumors is intricate,necessitating the use of computerized *** research introduces an innovative approach for the automated segmentation of brain tumors and a framework for classifying different regions of brain *** proposed methods consist of a pipeline with several stages:preprocessing of brain images with noise removal based on Wiener Filtering,enhancing the brain using Principal Component Analysis(PCA)to obtain well-enhanced images,and then segmenting the region of interest using the Fuzzy C-Means(FCM)clustering technique in the third *** final step involves classification using the Support Vector Machine(SVM)*** classifier is applied to various types of brain tumors,such as meningioma and pituitary tumors,utilizing the Contrast-Enhanced Magnetic Resonance Imaging(CE-MRI)*** proposed method demonstrates significantly improved contrast and validates the effectiveness of the classification framework,achieving an average sensitivity of 0.974,specificity of 0.976,accuracy of 0.979,and a Dice Score(DSC)of ***,this method exhibits a shorter processing time of 0.44 s compared to existing *** performance of this method emphasizes its significance when compared to state-of-the-art methods in terms of sensitivity,specificity,accuracy,and *** enhance the method further in the future,it is feasible to standardize the approach by incorporating a set of classifiers to increase the robustness of the brain classi

关键词： Brain tumor magnetic resonance imaging principal component analysis fuzzy c-clustering support vector machine

DNBP-CCA:A Novel Approach to Enhancing Heterogeneous Data Traffic and Reliable Data Transmission for Body Area Network

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Computers, Materials & Continua 2024年第5期79卷 2851-2878页

作者： Abdulwadood Alawadhi Mohd.Hasbullah Omar abdullah Almogahed Noradila Nordin Salman A.Alqahtani Atif M.Alamri InterNetWorks Research Laboratory School of ComputingUniversiti Utara MalaysiaSintok06010Malaysia Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn MalaysiaParit RajaJohor86400Malaysia School of Games&Creative Technology University for the Creative ArtsFarnhamGU97DSUK Computer Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

The increased adoption of Internet of Medical Things (IoMT) technologies has resulted in the widespread use ofBody Area Networks (BANs) in medical and non-medical domains. However, the performance of IEEE 802.15.4-based BANs is impacted by challenges related to heterogeneous data traffic requirements among nodes, includingcontention during finite backoff periods, association delays, and traffic channel access through clear channelassessment (CCA) algorithms. These challenges lead to increased packet collisions, queuing delays, retransmissions,and the neglect of critical traffic, thereby hindering performance indicators such as throughput, packet deliveryratio, packet drop rate, and packet delay. Therefore, we propose Dynamic Next Backoff Period and Clear ChannelAssessment (DNBP-CCA) schemes to address these issues. The DNBP-CCA schemes leverage a combination ofthe Dynamic Next Backoff Period (DNBP) scheme and the Dynamic Next Clear Channel Assessment (DNCCA)scheme. The DNBP scheme employs a fuzzy Takagi, Sugeno, and Kang (TSK) model’s inference system toquantitatively analyze backoff exponent, channel clearance, collision ratio, and data rate as input parameters. Onthe other hand, the DNCCA scheme dynamically adapts the CCA process based on requested data transmission tothe coordinator, considering input parameters such as buffer status ratio and acknowledgement ratio. As a result,simulations demonstrate that our proposed schemes are better than some existing representative approaches andenhance data transmission, reduce node collisions, improve average throughput, and packet delivery ratio, anddecrease average packet drop rate and packet delay.

关键词： Internet of Medical Things body area networks backoff period tsk fuzzy model clear channel assessment media access control

Human Gait Recognition for Biometrics Application Based on Deep Learning Fusion Assisted Framework

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Computers, Materials & Continua 2024年第1期78卷 357-374页

作者： Ch Avais Hanif Muhammad Ali Mughal Muhammad Attique Khan Nouf abdullah Almujally Taerang Kim Jae-Hyuk Cha Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea

The demand for a non-contact biometric approach for candidate identification has grown over the past ten *** on the most important biometric application,human gait analysis is a significant research topic in computer *** have paid a lot of attention to gait recognition,specifically the identification of people based on their walking patterns,due to its potential to correctly identify people far *** recognition systems have been used in a variety of applications,including security,medical examinations,identity management,and access *** systems require a complex combination of technical,operational,and definitional *** employment of gait recognition techniques and technologies has produced a number of beneficial and well-liked *** proposes a novel deep learning-based framework for human gait classification in video *** framework’smain challenge is improving the accuracy of accuracy gait classification under varying conditions,such as carrying a bag and changing *** proposed method’s first step is selecting two pre-trained deep learningmodels and training fromscratch using deep transfer ***,deepmodels have been trained using static hyperparameters;however,the learning rate is calculated using the particle swarmoptimization(PSO)***,the best features are selected from both trained models using the Harris Hawks controlled Sine-Cosine optimization *** algorithm chooses the best features,combined in a novel correlation-based fusion ***,the fused best features are categorized using medium,bi-layer,and tri-layered neural *** the publicly accessible dataset known as the CASIA-B dataset,the experimental process of the suggested technique was carried out,and an improved accuracy of 94.14% was *** achieved accuracy of the proposed method is improved by the recent state-of-the-art techniques that show the significance of this wor

关键词： Gait recognition covariant factors biometric deep learning fusion feature selection

Nanomaterial-assisted wearable glucose biosensors for noninvasive real-time monitoring:Pioneering point-of-care and beyond

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Nano Materials Science 2024年第3期6卷 263-283页

作者： Moein Safarkhani abdullah Aldhaher Golnaz Heidari Ehsan Nazarzadeh Zare Majid Ebrahimi Warkiani Omid Akhavan YunSuk Huh Navid Rabiee NanoBio High-Tech Materials Research Center Department of Biological Sciences and BioengineeringInha UniversityIncheon22212Republic of Korea Department of Chemistry Sharif University of TechnologyTehranIran School of Natural Sciences Massey UniversityPrivate Bag 11222Palmerston North4410New Zealand School of Chemistry Damghan UniversityDamghan36716-45667Iran School of Biomedical Engineering University of Technology SydneySydneyNSW2007Australia Department of Physics Sharif University of TechnologyP.O.Box 11155-9161TehranIran Centre for Molecular Medicine and Innovative Therapeutics Murdoch UniversityPerthWA 6150Australia School of Engineering Macquarie UniversitySydneyNew South Wales2109Australia

This review explores glucose monitoring and management strategies,emphasizing the need for reliable and userfriendly wearable sensors that are the next generation of sensors for continuous glucose *** addition,examines key strategies for designing glucose sensors that are multi-functional,reliable,and cost-effective in a variety of *** unique features of effective diabetes management technology are highlighted,with a focus on using nano/biosensor devices that can quickly and accurately detect glucose levels in the blood,improving patient treatment and control of potential diabetes-related *** potential of next-generation wearable and touch-sensitive nano biomedical sensor engineering designs for providing full control in assessing implantable,continuous glucose monitoring is also *** challenges of standardizing drug or insulin delivery doses,low-cost,real-time detection of increased blood sugar levels in diabetics,and early digital health awareness controls for the adverse effects of injectable medication are identified as unmet ***,the market for biosensors is expected to expand significantly due to the rising need for portable diagnostic equipment and an ever-increasing diabetic *** paper concludes by emphasizing the need for further research and development of glucose biosensors to meet the stringent requirements for sensitivity and specificity imposed by clinical diagnostics while being cost-effective,stable,and durable.

关键词： Glucose sensor Biosensor Wearable devices Noninvasive Real-time monitoring

Dust particle surface potential in an argonhelium plasma using the(r,q)-distribution function

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Communications in Theoretical Physics 2024年第9期76卷 141-148页

作者： Bahaaudin M Raffah A A Abid abdullah Khan Amin Esmaeili Yas Al-Hadeethi M N S Qureshi Department of Physics Faculty of SciencesKing Abdulaziz UniversityJeddah 21589Saudi Arabia Lithography in Devices Fabrication and Development Research Group Deanship of Scientific ResearchKing Abdulaziz UniversityJeddah 21589Saudi Arabia Joint Laboratory of Plasma Application Technology Institute of Advanced TechnologyUniversity of Science and Technology of ChinaHefei230026China CAS Key Laboratory of Geospace Environment University of Science and Technology of ChinaHefei230026China Department of Physics Zhejiang Normal UniversityJinhua321005China Department of Physics Graduate School of ScienceTokyo Metropolitan UniversityMinami-Osawa 1-1Hachioji City192-0397Japan Department of Physics GC UniversityLahore 54000Pakistan

In this paper,the dust particle surface potential for argon-helium plasma is evaluated analytically and numerically in the context of negatively charged dust particles by employing a power-law(r,q)-distribution *** studies have reported the argon-helium plasma and conducted a brief theoretical and experimental *** deepen our understanding further,this study aims to analyze the argon-helium plasma comprehensively using the same pattern but with the(r,q)-distribution *** this purpose,the current balance equations are derived for electron,helium and argon ions,when these charge species attain the quasineutrality *** numerically examined the currents of plasma species for a broad range of effective distribution function parameters r and *** is revealed that the surface potential of dust particles is significantly affected by the parameters r and q,helium ion-to-electron temperature ratio,argon ion-to-electron temperature ratio,and helium ion to argon ion number density *** incorporating the multi-ion(argon-helium)species,the significance of low-temperature nonMaxwellian dusty(complex)plasma is briefly examined.

关键词： dusty plasma dust charge potential plasma physics helium argon plasma r q distribution function non-Maxwellian distribution

Twinning aspects and their efficient roles in wrought Mg alloys:A comprehensive review

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Journal of Magnesium and Alloys 2024年第6期12卷 2201-2230页

作者： S.S.A.Shah Manping Liu Azim Khan Farooq Ahmad M.R.abdullah Xingquan Zhang Shiwei Xu Zhen Peng School of Materials Science and Engineering Jiangsu UniversityZhenjiang 212013China School of Mechanical Engineering Anhui University of TechnologyMáanshan 243002China College of Mechanical and Vehicle Engineering Hunan UniversityChangsha 410082China

Twinning is widely recognized as an effective and cost-efficient method for controlling the microstructure and properties of wrought magnesium(Mg)***,twins play a crucial role in initiating dynamic recrystallization(DRX),while twin regions experience rapid recrystallization during static recrystallization(SRX).The activation of twinning can lead to changes in lattice orientation,significantly impacting the final texture in Mg *** active roles of twinning are influenced by various factors during the activation process,and the mobility of twin boundaries(TB)can be amplified by stress effects,dislocation interactions,and thermal ***,annealing treatments that involve proper segregation or precipitation on TBs serve to stabilize them,restraining their *** such as segregation may also alter the twinning propensity in Magnesium-rare earth(Mg-RE)***{10–11}contraction twins(CT)and{10–11}-{10–12}double twins(DT)can promote dynamic recrystallization(DRX),they also pose a risk as potential sources of voids and ***,understanding the nucleation and growth mechanisms of twinning is crucial,and these aspects are briefly reviewed in this *** the factors mentioned above,this article summarizes the recent research progress in this field,shedding light on advancements in recent eras.

关键词： Mg alloys Twinning Recrystallization Texture Mechanical properties

Smart Farming for Sustainable Rice Production:An Insight into Application,Challenge,and Future Prospect

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Rice science 2024年第1期31卷 47-61页

作者： Norhashila HASHIM Maimunah Mohd ALI Muhammad Razif MAHADI Ahmad Fikri abdullah Aimrun WAYAYOK Muhamad Saufi Mohd KASSIM Askiah JAMALUDDIN Department of Biological and Agricultural Engineering/SMART Farming Technology Research Centre Faculty of EngineeringUniversiti Putra MalaysiaSelangor 43400Malaysia Department of Food Sciences Faculty of Science and TechnologyUniversiti Kebangsaan MalaysiaSelangor 43600Malaysia Department of Resource Management&Consumer Studies Faculty of Human EcologyUniversiti Putra MalaysiaSelangor 43400Malaysia

Rice has a huge impact on socio-economic growth,and ensuring its sustainability and optimal utilization is *** review provides an insight into the role of smart farming in enhancing rice *** applications of smart farming in rice production including yield estimation,smart irrigation systems,monitoring disease and growth,and predicting rice quality and classifications are *** challenges of smart farming in sustainable rice production to enhance the understanding of researchers,policymakers,and stakeholders are *** efforts have been exerted to combat the issues in rice production in order to promote rice sector *** effective implementation of smart farming in rice production has been facilitated by various technical advancements,particularly the integration of the Internet of Things and artificial *** future prospects of smart farming in transforming existing rice production practices are also *** the utilization of smart farming,the rice industry can attain sustainable and resilient production systems that could mitigate environmental impact and safeguard food ***,the rice industry holds a bright future in transforming current rice production practices into a new outlook in rice smart farming development.

关键词： rice production smart farming food security agriculture sustainability

UNet Based onMulti-Object Segmentation and Convolution Neural Network for Object Recognition

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Computers, Materials & Continua 2024年第7期80卷 1563-1580页

作者： Nouf abdullah Almujally Bisma Riaz Chughtai Naif Al Mudawi Abdulwahab Alazeb Asaad Algarni Hamdan A.Alzahrani Jeongmin Park Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Information Technology Department College of Computing and InformaticsSaudi Electronic UniversityRiyadh13316Saudi Arabia Department of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Republic of Korea

The recent advancements in vision technology have had a significant impact on our ability to identify multiple objects and understand complex *** technologies,such as augmented reality-driven scene integration,robotic navigation,autonomous driving,and guided tour systems,heavily rely on this type of scene *** paper presents a novel segmentation approach based on the UNet network model,aimed at recognizing multiple objects within an *** methodology begins with the acquisition and preprocessing of the image,followed by segmentation using the fine-tuned UNet ***,we use an annotation tool to accurately label the segmented *** labeling,significant features are extracted from these segmented objects,encompassing KAZE(Accelerated Segmentation and Extraction)features,energy-based edge detection,frequency-based,and blob *** the classification stage,a convolution neural network(CNN)is *** comprehensive methodology demonstrates a robust framework for achieving accurate and efficient recognition of multiple objects in *** experimental results,which include complex object datasets like MSRC-v2 and PASCAL-VOC12,have been *** analyzing the experimental results,it was found that the PASCAL-VOC12 dataset achieved an accuracy rate of 95%,while the MSRC-v2 dataset achieved an accuracy of 89%.The evaluation performed on these diverse datasets highlights a notably impressive level of performance.

关键词： UNet segmentation blob fourier transform convolution neural network

High-performance porous transport layers for proton exchange membrane water electrolyzers

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SusMat 2024年第4期4卷 211-242页

作者： Youkun Tao Minhua Wu Meiqi Hu Xihua Xu Muhammad I.abdullah Jing Shao Haijiang Wang School of Science Harbin Institute of TechnologyShenzhenChina College of Chemistry and Environmental Engineering Shenzhen UniversityShenzhenChina Department of Mechanical and Energy Engineering Southern University of Science and TechnologyShenzhenChina

Hydrogen is a favored alternative to fossil fuels due to the advantages of clean-liness,zero emissions,and high calorific ***-scale green hydrogen production can be achieved using proton exchange membrane water electrolyz-ers(PEMWEs)with utilization of renewable *** porous transport layer(PTL),positioned between the flow fields and catalyst layers(CLs)in PEMWEs,plays a critical role in facilitating water/gas transport,enabling electrical/thermal conduction,and mechanically supporting CLs and *** cor-rosion resistance is essential as PTL operates in acidic media with oxygen saturation and high working *** paper covers the development of high-performance titanium-based PTLs for *** heat/electrical con-duction and mass transport mechanisms of PTLs and how they affect the overall performances are *** carefully designing and controlling substrate microstructure,protective coating,and surface modification,the performance of PTL can be regulated and *** two-phase mass transport char-acteristics can be enhanced by fine-tuning the microstructure and surface wettability of *** addition of a microporous top-layer can effectively improve PTL|CL contact and increase the availability of catalytic *** anti-corrosion coatings,which are crucial for chemical stability and conductivity of the PTL,are compared and analyzed in terms of composition,fabrication,and performance.

关键词： mass transport microstructure performance porous transport layer proton exchange mem-brane water electrolysis