In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading...In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading.Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning(MARL)and Explainable AI(XAI)within Fintech,aiming to refine Algorithmic Trading strategies.Through meticulous examination,we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm,employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions.These AI-infused Fintech platforms harness collective intelligence to unearth trends,mitigate risks,and provide tailored financial guidance,fostering benefits for individuals and enterprises navigating the digital landscape.Our research holds the potential to revolutionize finance,opening doors to fresh avenues for investment and asset management in the digital age.Additionally,our statistical evaluation yields encouraging results,with metrics such as Accuracy=0.85,Precision=0.88,and F1 Score=0.86,reaffirming the efficacy of our approach within Fintech and emphasizing its reliability and innovative prowess.展开更多
Utilizing fly ash(FA)as reinforcement for magnesium matrix composites(MMCs)brings down the production cost and the land pollution.Magnesium alloy AZ31 was reinforced with FA particles(10 vol.%)successfully by two diff...Utilizing fly ash(FA)as reinforcement for magnesium matrix composites(MMCs)brings down the production cost and the land pollution.Magnesium alloy AZ31 was reinforced with FA particles(10 vol.%)successfully by two different processing methods namely conventional stir casting and friction stir processing(FSP).The microstructural features were observed using optical microscope,scanning electron microscope and electron backscatter diffraction.The sliding wear behavior was tested using a pin-on-disc wear apparatus.The stir cast composite showed inhomogeneous particle dispersion and coarse grain structure.Some of the FA particles decomposed and reacted with the matrix alloy to produce undesirable compounds.Conversely,FSP composite showed superior particle dispersion and fine,equiaxed grains by dynamic recrystallization.FA particles encountered disintegration but there was no interfacial reaction.FSP composite demonstrated higher strengthening and wear resistance to that of stir cast composite.The morphology of the worn surface and the wear debris were studied in detail.展开更多
The emphasis of this exploration was to examine the workability and work hardening performance of Mg(Magnesium)specimen and Mg-B_(4)C composites created via the powder metallurgy technique.The pure Mg and Mg-B_(4)C co...The emphasis of this exploration was to examine the workability and work hardening performance of Mg(Magnesium)specimen and Mg-B_(4)C composites created via the powder metallurgy technique.The pure Mg and Mg-B_(4)C composites are made with distinct weight percentages(Mg-5%B_(4)C,Mg-10%B_(4)C,and Mg-15%B_(4)C)at the unit aspect ratio.The powders and composites characterization are executed by SEM(Scanning Electron Microscope),EDS(Energy Dispersive Spectrum)with an elemental map,and XRD(X-ray Diffraction)examination.It displays that,the B_(4)C particles were dispersed consistently with the Mg matrix.The workability and work hardening examination was conducted in triaxial stress conditions using the cold deformation process.The consequence of workability stress exponent factor(β_(σ)),distinct stress proportion factors(σ_(m)/σ_(eff)and σ_(θ)/σ_(eff)),instantaneous work hardening exponent(n_(1)),work hardening exponent(n),coefficient of strength(k)and instantaneous coefficient of strength(k_(1))are recognized.The outcome displays that Mg-15%B_(4)C specimen has greater workability and work hardening parameter,initial relative density,and triaxial stresses compared with the Mg specimen and Mg-(5–10%)B_(4)C composites.展开更多
This study was an attempt made to explore the possibility of increasing the surface properties of the AZ91D magnesium alloy by applying ZrO_(2)coating using Physical Vapour Deposition(PVD-RF)sputtering process.In orde...This study was an attempt made to explore the possibility of increasing the surface properties of the AZ91D magnesium alloy by applying ZrO_(2)coating using Physical Vapour Deposition(PVD-RF)sputtering process.In order to improve the quality of the coating,the PVD process parameter with multiple performance characteristics was optimized by using the Taguchi grey approach.L 18 orthogonal array was selected for conducting the experiments.The proposed Taguchi grey method was find out the optimal process parameter for multiple performance characteristics.The optimal combination was attained at chamber pressure of 0.003 bar,argon gas in millibar and power input of 200 W.The validation experiment result shows an improvement in the micro hardness and surface finish.Also,the performance characterizations such as SEM,EDX,XRD,coating thickness,surface roughness and micro hardness were measured at optimal process parameter.展开更多
基金This project was funded by Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah underGrant No.(IFPIP-1127-611-1443)the authors,therefore,acknowledge with thanks DSR technical and financial support.
文摘In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading.Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning(MARL)and Explainable AI(XAI)within Fintech,aiming to refine Algorithmic Trading strategies.Through meticulous examination,we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm,employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions.These AI-infused Fintech platforms harness collective intelligence to unearth trends,mitigate risks,and provide tailored financial guidance,fostering benefits for individuals and enterprises navigating the digital landscape.Our research holds the potential to revolutionize finance,opening doors to fresh avenues for investment and asset management in the digital age.Additionally,our statistical evaluation yields encouraging results,with metrics such as Accuracy=0.85,Precision=0.88,and F1 Score=0.86,reaffirming the efficacy of our approach within Fintech and emphasizing its reliability and innovative prowess.
文摘Utilizing fly ash(FA)as reinforcement for magnesium matrix composites(MMCs)brings down the production cost and the land pollution.Magnesium alloy AZ31 was reinforced with FA particles(10 vol.%)successfully by two different processing methods namely conventional stir casting and friction stir processing(FSP).The microstructural features were observed using optical microscope,scanning electron microscope and electron backscatter diffraction.The sliding wear behavior was tested using a pin-on-disc wear apparatus.The stir cast composite showed inhomogeneous particle dispersion and coarse grain structure.Some of the FA particles decomposed and reacted with the matrix alloy to produce undesirable compounds.Conversely,FSP composite showed superior particle dispersion and fine,equiaxed grains by dynamic recrystallization.FA particles encountered disintegration but there was no interfacial reaction.FSP composite demonstrated higher strengthening and wear resistance to that of stir cast composite.The morphology of the worn surface and the wear debris were studied in detail.
文摘The emphasis of this exploration was to examine the workability and work hardening performance of Mg(Magnesium)specimen and Mg-B_(4)C composites created via the powder metallurgy technique.The pure Mg and Mg-B_(4)C composites are made with distinct weight percentages(Mg-5%B_(4)C,Mg-10%B_(4)C,and Mg-15%B_(4)C)at the unit aspect ratio.The powders and composites characterization are executed by SEM(Scanning Electron Microscope),EDS(Energy Dispersive Spectrum)with an elemental map,and XRD(X-ray Diffraction)examination.It displays that,the B_(4)C particles were dispersed consistently with the Mg matrix.The workability and work hardening examination was conducted in triaxial stress conditions using the cold deformation process.The consequence of workability stress exponent factor(β_(σ)),distinct stress proportion factors(σ_(m)/σ_(eff)and σ_(θ)/σ_(eff)),instantaneous work hardening exponent(n_(1)),work hardening exponent(n),coefficient of strength(k)and instantaneous coefficient of strength(k_(1))are recognized.The outcome displays that Mg-15%B_(4)C specimen has greater workability and work hardening parameter,initial relative density,and triaxial stresses compared with the Mg specimen and Mg-(5–10%)B_(4)C composites.
基金supported by DRDO Extramural funding agency,IndiaThe authors thank the organization for their financial support with grant no:1103981/M/01/1480 to this work.
文摘This study was an attempt made to explore the possibility of increasing the surface properties of the AZ91D magnesium alloy by applying ZrO_(2)coating using Physical Vapour Deposition(PVD-RF)sputtering process.In order to improve the quality of the coating,the PVD process parameter with multiple performance characteristics was optimized by using the Taguchi grey approach.L 18 orthogonal array was selected for conducting the experiments.The proposed Taguchi grey method was find out the optimal process parameter for multiple performance characteristics.The optimal combination was attained at chamber pressure of 0.003 bar,argon gas in millibar and power input of 200 W.The validation experiment result shows an improvement in the micro hardness and surface finish.Also,the performance characterizations such as SEM,EDX,XRD,coating thickness,surface roughness and micro hardness were measured at optimal process parameter.
