Study of artifacts in thermodynamic and structural properties of Li–Mg alloy in liquid state using linear and exponential models

Gohivar, R.K.; Yadav, S. K.; Koirala, R. P.

doi:10.1016/j.heliyon.2021.e06613

Cited by 4 publications

(3 citation statements)

References 26 publications

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“…The information related to the arrangement of atoms in the nearest neighbourhoods of initial metallic solution can be obtained by computing parameters like concentration fluctuation in the long wave length limit (S CC (0)) [25,26]. The expression for ideal value of S CC (0) is calculated using the relation…”

Section: ) the Partial Excess Free Energy (G Xsmentioning

confidence: 99%

Mixing properties of liquid Al-Au alloys

et al. 2023

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The thermodynamic and structural properties of liquid Al-Au alloy have been studied in frame-work of R-K polynomial using temperature-dependent energy interaction parameters at different temperatures. Thermodynamic properties, excess free energy of mixing and activity, and in structural properties, concentration fluctuation in long wave-length limit have been computed at temperatures 1338 K, 1500 K and 1600 K. The properties, such as surface tension and surface concentration of the system have been computed at above mentioned temperatures using Butler model. The system shows transformation from segregating to ordering in nature with increase in concentration of Au.

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Section: ) the Partial Excess Free Energy (G Xsmentioning

confidence: 99%

Mixing properties of liquid Al-Au alloys

et al. 2023

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“…The linear and exponential properties are the common and widely used mechanisms to solve some mathematical problems in practical [36][37][38][39][40]. To tackle the extreme learning rates of Adam during whole training and achieve a smooth transformation from Adam to SGD, the upper bound is designed to be an asymptotical function from the maximum value of convergence range to the global fixed value.…”

Section: The Design Of Upper Boundmentioning

confidence: 99%

AdaCB: An Adaptive Gradient Method with Convergence Range Bound of Learning Rate

et al. 2022

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Adaptive gradient descent methods such as Adam, RMSprop, and AdaGrad achieve great success in training deep learning models. These methods adaptively change the learning rates, resulting in a faster convergence speed. Recent studies have shown their problems include extreme learning rates, non-convergence issues, as well as poor generalization. Some enhanced variants have been proposed, such as AMSGrad, and AdaBound. However, the performances of these alternatives are controversial and some drawbacks still occur. In this work, we proposed an optimizer called AdaCB, which limits the learning rates of Adam in a convergence range bound. The bound range is determined by the LR test, and then two bound functions are designed to constrain Adam, and two bound functions tend to a constant value. To evaluate our method, we carry out experiments on the image classification task, three models including Smallnet, Network IN Network, and Resnet are trained on CIFAR10 and CIFAR100 datasets. Experimental results show that our method outperforms other optimizers on CIFAR10 and CIFAR100 datasets with accuracies of (82.76%, 53.29%), (86.24%, 60.19%), and (83.24%, 55.04%) on Smallnet, Network IN Network and Resnet, respectively. The results also indicate that our method maintains a faster learning speed, like adaptive gradient methods, in the early stage and achieves considerable accuracy, like SGD (M), at the end.

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“…The independent curriculum is a program that emphasizes independence and freedom for teachers and students to be creative and innovative to maximize potential by discovering their full potential (Nurhayati et al, 2022), (Elihami, 2021). Education is a process that aims to develop the individual potential to fulfill life as a whole, ainningsboth cognitively and emotionally (Gohivar et al, 2021). Education is vital in preparing strong developing skilled human vitals with global competitiveness.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Implementation of Differentiated Learning in the Implementation of the Independent Curriculum in Middle School Mathematics Lessons

Febriana,

Sugiman,

Ariyadi Wijaya

2023

IJHESS

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Differentiated learning is a form of addressing the diverse learning needs of students paying close attention to readiness, learning profiles, interests, and aptitudes. This study aims to find out (1) the planning stage (plan) carried out by the mathematics teacher in implementing differentiation learning, (2) the (do) stage, the differentiation learning process applied in class, (3) the (see) stage, the form of assessment (evaluation). ) carried out by the teacher in the implementation of learning. The research method used is qualitative by collecting data through observation (learning videos) and interviews. The results of the research are that at the planning stage, the teacher does it by preparing everything that supports differentiation learning; at the do stage,e the teacher implements the learning that has been designed at the planning stage and the seeseedage, the teacher evaluates the learning process that has been carried out at the see stage both in terms of using the learning method as well as in terms of student understanding which is carried out to improve the learning stage in the future. In differentiation learning, this is adapted to the school's circumstances and the student’s abilities; one school may be different from another but has the same goal, and in differentiation learning, It must contain 3, namely differentiation of content, process, and product.

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Study of artifacts in thermodynamic and structural properties of Li–Mg alloy in liquid state using linear and exponential models

Cited by 4 publications

References 26 publications

Mixing properties of liquid Al-Au alloys

Mixing properties of liquid Al-Au alloys

AdaCB: An Adaptive Gradient Method with Convergence Range Bound of Learning Rate

Analysis of the Implementation of Differentiated Learning in the Implementation of the Independent Curriculum in Middle School Mathematics Lessons

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