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Optical and electrical properties of crystalline indium tin oxide thin film deposited by vacuum evaporation technique

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Optoelectronics Letters 2019年第5期15卷 356-359页

作者： md.mottaleb Hosen a.k.m.atique ullah md.mahbubul Haque S.m.Abdur Rahim k.m.Abdus Sobahan m.N.I.khan Department of Electrical and Electronic Engineering Islamic University Kushtia 7003 Bangladesh Nanoscience and Technology Research Laboratory Atomic Energy Centre Bangladesh Atomic Energy Commission Dhaka 1000 Bangladesh Analytical Chemistry Laboratory Chemistry Division Atomic Energy Centre Bangladesh Atomic Energy Commission Dhaka 1000 Bangladesh Department of Physics Jagannath University Dhaka 1100 Bangladesh materials Science Division Atomic Energy Centre Bangladesh Atomic Energy Commission Dhaka 1000 Bangladesh

Indium tin oxide(ITO) thin film was deposited on glass substrate by means of vacuum evaporation technique and annealed at 200 ℃, 300℃ and 400 ℃ in air for 1 h. The characterization and properties of the deposited film samples were analyzed by X-ray diffraction(XRD), scanning electron microscopy(SEm), and UV-VIS-NIR spectroscopy techniques. From the XRD patterns, it was found that the deposited thin film was of crystalline at an annealing temperature of 400℃. The crystalline phase was indexed as cubic structure with lattice constant and crystallite size of 0.511 nm and 40 nm, respectively. The SEm images showed that the films exhibited uniform surface morphology with well-defined spherical grains. The optical transmittance of ITO thin film annealed at 400 ℃ was improved from 44% to 84% in the wavelength range from 250 nm to 2 100 nm and an optical band gap was measured as 3.86 e V. Hall effect measurement was used to measure the resistivity and conductivity of the prepared film.

关键词： Indium tin oxide(ITO) X-ray diffraction(XRD) scanning electron microscopy(SEm)

IDS-INT:Intrusion detection system using transformer-based transfer learning for imbalanced network traffic

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Digital Communications and Networks 2024年第1期10卷 190-204页

作者： Farhan ullah Shamsher ullah Gautam Srivastava Jerry Chun-Wei Lin School of Software Northwestern Polytechnical UniversityXian710072ShaanxiChina knowledge Unit of Systems and Technology University of Management and TechnologySialkot 51040Pakistan Department of math and Computer Science Brandon UniversityBrandonMB R7A 6A9Canada Department of Computer Science and math Lebanese American UniversityBeirut1102Lebanon Western Norway University of Applied Sciences BergenNorway Research Centre for Interneural Computing China Medical UniversityTaichungTaiwanChina

A network intrusion detection system is critical for cyber security against llegitimate *** terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a subcategory of attack,host information,malicious scripts,*** terms of network perspectives,network traffic may contain an imbalanced number of harmful attacks when compared to normal *** is challenging to identify a specific attack due to complex features and data imbalance *** address these issues,this paper proposes an Intrusion Detection System using transformer-based transfer learning for Imbalanced Network Traffic(IDS-INT).IDS-INT uses transformer-based transfer learning to learn feature interactions in both network feature representation and imbalanced ***,detailed information about each type of attack is gathered from network interaction descriptions,which include network nodes,attack type,reference,host information,***,the transformer-based transfer learning approach is developed to learn detailed feature representation using their semantic ***,the Synthetic minority Oversampling Technique(SmOTE)is implemented to balance abnormal traffic and detect minority ***,the Convolution Neural Network(CNN)model is designed to extract deep features from the balanced network ***,the hybrid approach of the CNN-Long Short-Term memory(CNN-LSTm)model is developed to detect different types of attacks from the deep *** experiments are conducted to test the proposed approach using three standard datasets,i.e.,UNsWNB15,CIC-IDS2017,and *** explainable AI approach is implemented to interpret the proposed method and develop a trustable model.

关键词： Network intrusion detection Transfer learning Features extraction Imbalance data Explainable AI Cybersecurity

Considering solid shear stress in mP-PIC simulation of a CFB riser

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Particuology 2024年第6期89卷 79-87页

作者： Tagir kadyrov Fei Li Atta ullah Nature-inspired Engineering Center University of TyumenTyumen 625003Russia Laboratory of Theory and Optimization of Chemical and Technological Processes University of TyumenTyumen625003Russia State key Laboratory of multi-phase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China Department of Chemical Engineering Pakistan Institute of Engineering&Applied SciencesIslamabad 45650Pakistan

To enable successful multi-phase particle-in-cell(mP-PIC)simulations of circulating fluidized beds(CFBs),both the interphase drag force and interparticle collisions need to be carefully *** collisions are usually represented by the solid stress consisting of the normal and shear components,in which the normal stress was found to have a leading role in the numerical stability of mP-PIC simulations,whereas the impact of the shear stress has seldom been *** this work,the effects of the solid shear stress are investigated by using two-dimensional simulations of the moderately dense laboratory-scale CFB riser with in-house mP-PIC code implemented on mFIX open-source *** including only normal solid stress and those considering both normal and shear solid stresses are *** results of solids flux,axial and radial solids profiles are compared with available experimental *** results show that the solid shear stress plays a minor role on the accuracy of simulation,and the increase of PPP(number particles per parcel)leads to a lower accuracy of simulation.

关键词： Simulation Fluidization multiphase particle-in-cell(mP-PIC) Solid shear stress

Improving Prediction Efficiency of machine Learning models for Cardiovascular Disease in IoST-Based Systems through Hyperparameter Optimization

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Computers, materials & Continua 2024年第9期80卷 3485-3506页

作者： Tajim md.Niamat ullah Akhund Waleed m.Al-Nuwaiser Department of Computer Science and Engineering(CSE) Daffodil International UniversityDhaka1216Bangladesh Graduate School of Science and Engineering Saga UniversitySaga8408502Japan Computer Science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11623Saudi Arabia

This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)*** distinct machine learning approaches were implemented and systematically evaluated before and after hyperparameter *** improvements were observed across various models,with SVm and Neural Networks consistently showing enhanced performance metrics such as F1-Score,recall,and *** study underscores the critical role of tailored hyperparameter tuning in optimizing these models,revealing diverse outcomes among *** Trees and Random Forests exhibited stable performance throughout the *** enhancing accuracy,hyperparameter optimization also led to increased execution *** representations and comprehensive results support the findings,confirming the hypothesis that optimizing parameters can effectively enhance predictive capabilities in cardiovascular *** research contributes to advancing the understanding and application of machine learning in healthcare,particularly in improving predictive accuracy for cardiovascular disease management and intervention strategies.

关键词： Internet of sensing things(IoST) machine learning hyperparameter optimization cardiovascular disease prediction execution time analysis performance analysis wilcoxon signed-rank test

CD9 role in proliferation, rejuvenation, and therapeutic applications

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Genes & Diseases 2024年第3期11卷 95-97页

作者： Sai Priyanka kodam Neda Baghban mujib ullah Institutefor Immunityand Transplantation Stem Cell Biology and Regenerative MedicineSchool of MedicineMolecular Medicine Department of MedicineStanford UniversityPaloAltoCA94304USA

The CD9 gene,also known as the Tspan29 gene,codes for a protein called CD9,which is a member of the tetraspanin family of transmembrane proteins.^(1) The CD9 protein is involved in various cellular processes,including cell proliferation,differentiation,adhesion,and migration.^(1,2) CD9 has also been found to play a role in the regulation of stem cell proliferation and differentiation.

关键词： migration. therapeutic CD9

Assessing the impact of heat mitigation measures on thermal performance and energy demand at the community level:A pathway toward designing net-zero energy communities

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Building Simulation 2024年第8期17卷 1379-1400页

作者： khan Rahmat ullah Veljko Prodanovic Gloria Pignatta Ana Deletic mattheos Santamouris School of Built Environment Faculty of ArtsDesign&ArchitectureUniversity of New South WalesSydney2052 NSWAustralia School of Civil and Environmental Engineering University of New South WalesSydney2052 NSWAustralia Institute for Artificial Intelligence Research and Development of Serbia 21000 Novi SadSerbia Institute for multidisciplinary Research University of BelgradeKneza Višeslava 111000 BelgradeSerbia School of Civil and Environmental Engineering Engineering FacultyQueensland University of TechnologyQLD 4001Australia

In the context of escalating global energy demands,urban areas,specifically the building sector,contribute to the largest energy consumption,with urban overheating exacerbating this *** urban modelling for heat-mitigation and reduction of energy demand is crucial steps towards a sustainable built-environment,complementing onsite energy generation in the design and development of Net-zero Energy(NZE)Settlement,especially in the context of Australian weather *** a significant gap in existing literature,this study offers empirical analysis on the climate and energy efficacy of integrated heat mitigation strategies applied in 14 neighbourhood typologies located in Sydney,*** the application of cool materials on roads,pavements,and rooftops,alongside urban vegetation enhancement,the analysis demonstrates scenario effectiveness on heat mitigation that leads to reduce ambient temperature and energy demands along with CO_(2)emissions within the *** building arrangement,built-area ratio,building height,and locations,ENVI-met and CitySim are utilized to assess the heat-mitigation and the energy demand of neighbourhoods,*** indicate that mitigation measures can lead up to a 2.71℃reduction in ambient temperature and over 25%reduction in Cooling Degree Hours,with a 34.34%reduction in cooling energy demand and overall energy savings of up to 12.49%.In addition,the annual energy-saving yields a CO_(2)reduction of approximately 141.12 tonnes,where additional vegetation further amplifies these reductions by enhancing CO_(2)*** study showcases the pathway towards achieving NZE goals in climates similar to that of Australia,highlighting significant benefits in heat-mitigation,environmental impact,and energy-savings.

关键词： urban overheating cool materials vegetation,heat mitigation energy savings CO_(2)reduction

Inclusion of CoTiO_(3) to ameliorate the re/dehydrogenation properties of the mg–Na–Al system

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Journal of magnesium and Alloys 2024年第3期12卷 1215-1226页

作者： N.A.Ali N.Y.Yusnizam N.A.Sazelee Sami-ullah Rather Haizhen Liu m.Ismail Energy Storage Research Group Faculty of Ocean Engineering TechnologyUniversiti Malaysia Terengganu21030 Kuala NerusTerengganuMalaysia Department of Chemical and materials Engineering King Abdulaziz UniversityP.O.Box80204Jeddah 21589Saudi Arabia Guangxi Novel Battery materials Research Center of Engineering Technology School of Physical Science and TechnologyGuangxi UniversityNanning 530004China State key Laboratory of Featured metal materials and Life-Cycle Safety for Composite Structures Nanning 530004China

For the first time,the mgH_(2)–NaAlH_(4)(ratio 4:1)destabilized system with CoTiO_(3) addition has been *** CoTiO_(3)-doped mgH_(2)–NaAlH_(4) sample begins to dehydrogenate at 130℃,which is declined by 40℃ compared to the undoped mgH_(2)–NaAlH_(4).moreover,the de/rehydrogenation kinetics characteristics of the CoTiO_(3)-doped mgH_(2)–NaAlH_(4) were greatly *** the inclusion of CoTiO_(3),the mgH_(2)–NaAlH_(4) composite absorbed 5.2 wt.%H_(2),higher than undoped mgH_(2)–NaAlH_(4).In the context of dehydrogenation,the CoTiO_(3)-doped mgH_(2)–NaAlH_(4) sample desorbed 2.6 wt.%H_(2),almost doubled compared to the amount of hydrogen desorbed from the undoped mgH_(2)–NaAlH_(4) *** activation energy obtained by the kissinger analysis for mgH_(2) decomposition was significantly lower by 35.9 kJ/mol than the undoped mgH_(2)–NaAlH_(4) *** reaction mechanism demonstrated that new phases of mgCo and AlTi_(3) were generated in situ during the heating process and are likely to play a substantial catalytic function and be useful in ameliorating the de/rehydrogenation properties of the destabilized mgH_(2)–NaAlH_(4) system with the inclusion of CoTiO_(3).

关键词： Destabilize system magnesium hydride Sodium alanate Hydrogen storage Additive.

A Traffic-Aware and Cluster-Based Energy Efficient Routing Protocol for IoT-Assisted WSNs

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Computers, materials & Continua 2024年第8期80卷 1831-1850页

作者： Hina Gul Sana ullah ki-Il kim Farman Ali Department of Computer and Software Technology University of SwatMingora19130Pakistan Department of Computer Science and Engineering Chungnam National UniversityDaejeon34134Republic of Korea Department of Applied AI Sungkyunkwan UniversitySeoul03063Republic of Korea

The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications,such as remote health monitoring,industrial monitoring,transportation,and smart *** and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of *** paper presents a traffic-aware,cluster-based,and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such *** proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual *** protocol considers multi-criteria attributes,i.e.,energy,traffic load,and distance parameters to select the next hop for data delivery towards the base *** performance of the proposed protocol is evaluated through the network simulator *** different traffic rates,number of nodes,and different packet sizes,the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio,energy consumption,end-to-end delay,and network *** 100 nodes,the proposed protocol achieved a 13%improvement in packet delivery ratio,10 ms improvement in delay,and 10 mJ improvement in average energy consumption over LoRaWAN.

关键词： Internet of Things wireless sensor networks traffic load clustering routing energy efficiency

DeBERTa-GRU: Sentiment Analysis for Large Language model

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Computers, materials & Continua 2024年第6期79卷 4219-4236页

作者： Adel Assiri Abdu Gumaei Faisal mehmood Touqeer Abbas Sami ullah Department of Informatics for Business College of BusinessKing Khalid UniversityAbha61421Saudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou450001China Department of Computer Science and Technology Beijing University of Chemical TechnologyBeijing100029China Department of Computer Science Government College University FaisalabadFaisalabadPunjab38000Pakistan

modern technological advancements have made social media an essential component of daily *** media allow individuals to share thoughts,emotions,and *** analysis plays the function of evaluating whether the sentiment of the text is positive,negative,neutral,or any other personal emotion to understand the sentiment context of the *** analysis is essential in business and society because it impacts strategic *** analysis involves challenges due to lexical variation,an unlabeled dataset,and text distance *** execution time increases due to the sequential processing of the sequence ***,the calculation times for the Transformer models are reduced because of the parallel *** study uses a hybrid deep learning strategy to combine the strengths of the Transformer and Sequence models while ignoring their *** particular,the proposed model integrates the Decoding-enhanced with Bidirectional Encoder Representations from Transformers(BERT)attention(DeBERTa)and the Gated Recurrent Unit(GRU)for sentiment *** the Decoding-enhanced BERT technique,the words are mapped into a compact,semantic word embedding space,and the Gated Recurrent Unit model can capture the distance contextual semantics *** proposed hybrid model achieves F1-scores of 97%on the Twitter Large Language model(LLm)dataset,which is much higher than the performance of new techniques.

关键词： DeBERTa GRU Naive Bayes LSTm sentiment analysis large language model