Reinforcement Learning is a branch of machine learning to learn control strategies that achieve a given objective through trial-And-error in the environment. Because this can be applicable even when the state transiti...
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Reinforcement Learning is a branch of machine learning to learn control strategies that achieve a given objective through trial-And-error in the environment. Because this can be applicable even when the state transition function of the control object is unknown or it is difficult to create its model properly, this can reduce the designer's burden. Reinforcement learning repeats evaluating a policy and improving it based on that evaluation. An algorithm called value function approximation is used in this evaluation. Value function approximation is a general term for algorithms of approximating a function called value function, which maps an arbitrary state to how much reward can be obtained in the future when acting according to a policy from that state. Value function approximation should have high approximation accuracy and hyperparameter easy to tune. Although various value function approximation methods have been proposed so far, some of them does not have convergent guarantee and the others' hyperparameter tuning is difficult. The purpose of this paper is to propose a value function approximation method that have convergence guarantee even with nonlinear function approximator and whose hyperparameter tuning is easy and to verify its performance through numerical experiments. To this end, we focused on GTD2 method, which is one of the value function approximation methods that has convergence guarantee even with a nonlinear function approximator. GTD2 method has the drawback that its hyperparameter is difficult to tune appropriately so that the approximation does not diverge during learning. Therefore, we firstly clarified the cause of the divergence of GTD2 method. Secondly, based on this cause, we proposed Normalized and Regularized GTD2 (NRGTD2) method, that incorporates a method for suppressing divergence into GTD2 method. Finally, through numerical experiments, it was clarified that the proposed method suppresses the divergence and can achieve better approxim
This paper presents a metaheuristic optimization-based approach for selecting a pre-determined number of measurement markers from the set of available markers that optimizes the performance of the recently introduced ...
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Beryllium-copper alloys, the most widely used copper alloys, are utilised extensively in diverse sectors, including the electrical, electronics, instrumentation, metallurgy, aerospace, automotive, petrochemical, machi...
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Beryllium-copper alloys, the most widely used copper alloys, are utilised extensively in diverse sectors, including the electrical, electronics, instrumentation, metallurgy, aerospace, automotive, petrochemical, machinery manufacturing, and die and mould-making industries. The main drawback of these alloys is that they produce the toxic component, beryllium oxide, which can lead to a chronic lung disease known as berylliosis. Beryllium-free copper alloys, such as copper-nickel-silicon-chromium, are eco-friendly, less costly, and possess properties similar to those of beryllium-copper alloys. Hence, they are now replacing beryllium-copper alloys in the applications mentioned earlier. Due to their high strength and hardness, these alloys are often fabricated into components using unconventional machining techniques, such as electrical discharge machining. Electrical discharge machining is particularly advantageous in industrial applications where precisely controlled random surface textures on these alloys are required. However, despite the industrial significance, research on the electrical discharge machining process of copper-nickel-silicon-chromium alloys is scarce. Therefore, the current work aims to address this research gap by conducting an experimental investigation of the random surfaces generated on copper-nickel-silicon-chromium alloy components after the die-sinking electrical discharge machining process through a comprehensive three-dimensional surface topography analysis. Three-dimensional surface topography parameters overcome the drawbacks of two-dimensional roughness parameters by considering the majority of surface points. This work investigates the effects of input factors, including electrode material, dielectric fluid material, flushing condition, and current on nearly all relevant areal texture (3D) parameters. ANOVA is performed to study the level of significance of each input parameter. The regression analyses reveal that current is the most si
The simultaneous optimization of the bulk and surface characteristics of photoelectrodes is essential to maximize their photoelectrochemical(PEC)*** report a novel one-pot hydrothermal synthesis of textured and surfac...
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The simultaneous optimization of the bulk and surface characteristics of photoelectrodes is essential to maximize their photoelectrochemical(PEC)*** report a novel one-pot hydrothermal synthesis of textured and surface-reconstructed BiVO_(4)photoanodes(ts-BVO),achieving significant improvements in PEC water *** controlling precursor molarity and ethylene glycol(EG)addition,we developed a stepwise dual reaction(SDR)mechanism,which enables simultaneous bulk texture development and surface *** optimized CoBi/ts-BVO photoanode exhibited a photocurrent density of 4.3 mA∙cm^(−2)at 1.23 V *** hydrogen electrode(RHE)with a high Faradaic efficiency of 98%under one sun *** with nontextured BiVO_(4),the charge transport efficiency increased from 8%to 70%,whereas the surface charge transfer efficiency improved from 9%to 85%.These results underscore the critical role of both bulk and surface engineering in enhancing PEC *** findings offer a streamlined approach for improving the intrinsic properties of photoanodes in solar water splitting.
The Centrifugal Nuclear Thermal Rocket (CNTR) is a Nuclear Thermal Propulsion (NTP) concept designed to heat propellant directly by the reactor fuel. The primary difference between the CNTR concept and traditional NTP...
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Magnesium-based batteries are potential candidates for next-generation rechargeable batteries due to the divalent nature of magnesium cations and the natural abundance of magnesium resources. In this study, the electr...
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A hydrothermal wave (HTW) refers to a flow pattern that arises during unsteady thermocapillary convection, negatively impacting the purity of single crystals during zone melting. This study utilized active control thr...
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Continuous blood pressure monitoring is crucial because of its dynamic nature, influenced by factors such as physical activity and mental stress. Although cuffless blood pressure estimation is a promising technique fo...
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In this study, we propose an extension-type flexible pneumatic actuator (EFPA) with a high extension force and no buckling. In a previous study, soft actuators that extended in the axial direction by applying a supply...
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Wind energy is a rising renewable energy source that plays an important role in the transition to a more sustainable energy system. Variation in wind power generation is one of the main challenges facing this energy s...
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