Statistical Estimation of Resistance to Cyclic Deformation of Structural Steels and Aluminum Alloy

Resistance to cyclic loading is a key property of the material that determines the operational reliability of the structures. When selecting a material for structures operating under low-cycle loading conditions, it is essential to know the cyclic deformation characteristics of the material. Low-cycle strain diagrams are very sensitive to variations in chemical composition, thermal processing technologies, surface hardening, loading conditions, and other factors of the material. The application of probability methods enables the increase in the life characteristics of the structures and the confirmation of the cycle load values at the design phase. Most research papers dealing with statistical descriptions of low-cycle strain properties do not look into the distribution of low-cycle diagram characteristics. The purpose of our paper is to provide a probability assessment of the low-cycle properties of materials extensively used in the automotive and aviation industries, taking into account the statistical assessment of the cyclic elastoplastic strain diagrams or of the parameters of the diagrams. Materials with contrasting cyclic properties were investigated in the paper. The findings of the research allow for a review of durability and life of the structural elements of service facilities subjected to elastoplastic loading by assessing the distribution of low-cycle strain parameters, as well as the allowed distribution limits.

PROBABILITY METHODS OF ANALYSIS OF ASSESSMENT OF THE CONDITION OF ROAD CLOTHES IN USE

This article is a continuation of the analysis of methods and criteria for assessing the condition of non-rigid pavement, which contains in its structural layers such hidden defects as cracks, material disintegration, violation of the structure of intermediate layers of monolithic material and others. The variety of models for assessing the condition of the pavement with destruction is explained by: variability of soil-geological, climatic conditions of operation of pavement; the variety of physical and mechanical characteristics of the materials of the structural layers of the pavement and the soil of the ground; heterogeneity of geometric parameters of pavements in the longitudinal and transverse profiles. According to many scientists to assess the condition of the pavement is a necessary condition for the use of methods of probabilistic analysis. Methods of designing and assessing the condition of the pavement structure must take into account the principles of reliability, including probabilistic methods of reliability analysis. Most of the considered probabilistic models for assessing the condition of pavement are focused on the design of new construction, which allows not to take into account the patterns of changes in physical and mechanical properties of materials of structural layers and their geometric parameters during operation. However, the most relevant is to assess the condition of pavement with damage, including hidden cracks. Much of the article is devoted to the analysis of this area of research. According to the results of the analysis, it is concluded that probabilistic methods allow to take into account the heterogeneity of parameters that characterize the stress-strain state of the pavement structure and can be used in models to assess the condition of pavement with cracks in layers of monolithic materials.

Karakteristik dan Perilaku Ibu dalam Memberikan Stimulasi Perkembangan pada Anak Usia 18-24 Bulan

Providing education is the effort for promotif and prevntif for mother to give growth stimulation children 18-24 month. This research is a descriptive study that aims to explore the characteristics and behavior of mother for give growth stimulation children 18-24 month. This is done to be able to plan the provision of further interventions to mother have children 18-24 month. The sampling technique used probability methods with a clustersampling technique totaling 41 respondents. The research instrument used KAP (Knowledge, Attitudes, and Practices) with a total of 32 questions, Cronbach alpha knowledge (0.542-0,871), attitude (0.521-0.658), and action (0.452-0.713). Data analysis using univariate analysis. Characteristics of respondents at the age of 26-35 years (85.4%), most education is high school (48.1%), mother not work (82.9%), the most ethnic is minang (92,7%), the number of children is first (87.8) and acumulation of children is second (87.8%). The mean value of knowledge is 58.54, attitude is with a mean value of 25.24, and practice is with a mean value of 60.24. Based on the conclusion, the results of research on the behavior of mother to give growth stimulation of children 18-24 month is inadequate make delayed and disturbance of growth.

Construction and Analysis of Queuing and Reliability Models Using Random Graphs

In this paper, the use of the construction of random processes on graphs allows us to expand the models of the theory of queuing and reliability by constructing. These problems are important because the emphasis on the legal component largely determines functioning of these models. The considered models are reliability and queuing. Reliability models arranged according to the modular principle and reliability networks in the form of planar graphs. The queuing models considered here are queuing networks with multi server nodes and failures, changing the parameters of the queuing system in a random environment with absorbing states, and the process of growth of a random network. This is determined by the possibility of using, as traditional probability methods, mathematical logic theorems, geometric images of a queuing network, dual graphs to planar graphs, and a solution to the Dirichlet problem.

An Extended Entropic Model for Cohesive Sediment Flocculation in a Piecewise Varied Shear Environment

In this study, an extended model for describing the temporal evolution of a characteristic floc size of cohesive sediment particles when the flocculation system is subject to a piecewise varied turbulent shear rate was derived by the probability methods based on the Shannon entropy theory following Zhu (2018). This model only contained three important parameters: initial and steady-state values of floc size, and a parameter characterizing the maximum capacity for floc size increase (or decay), and it can be adopted to capture well a monotonic pattern in which floc size increases (or decays) with flocculation time. Comparison with 13 literature experimental data sets regarding floc size variation to a varied shear rate showed the validity of the entropic model with a high correlation coefficient and few errors. Furthermore, for the case of tapered shear flocculation, it was found that there was a power decay of the capacity parameter with the shear rate, which is similar to the dependence of the steady-state floc size on the shear rate. The entropic model was further parameterized by introducing these two empirical relations into it, and the finally obtained model was found to be more sensitive to two empirical coefficients that have been incorporated into the capacity parameter than those in the steady-state floc size. The proposed entropic model could have the potential, as an addition to existing flocculation models, to be coupled into present mature hydrodynamic models to model the cohesive sediment transport in estuarine and coastal regions.

EXAMINING KEY DRIVERS FOR ONLINE IMPULSE BUYING IN MALAYSIAN’S PUBLIC UNIVERSITIES STUDENTS

With the current growth of the internet, there are signs of e-commerce in Malaysia growing and booming, such as Lazada, Mudah.my, Shopee, and others. Malaysians have been increasingly reliant on the internet to obtain product details and to make purchases. This motivates e-commerce entrepreneurs to devise a new strategy for increasing sales by increasing the rate of online impulse purchases among visitors to online shopping platforms. The aim of this research is to look into the connection between key-driven and online impulse buying. The aim of this research is to create a framework that represents the main drivers of online impulse buying among Malaysian public universities. The study also addresses empirical results from a 303-respondent online survey conducted with SPSS version 22.0 and Smart-PLS version 3.0. The research paradigm is focused on the Theory of Planned Behaviour (TPB) Model, which includes online impulse buying as a dependent variable and three independent variables (Flow Experience, Perceived Usefulness, and Trust). Non-probability methods, judgement sampling, and convenience sampling were used to select respondents in this research, who ranged in age from 19 to over 30 years old and were university students in Malaysia. In addition, this research paves the way for future studies by identifying relevant online purchase platform providers and product categories to conduct a new study.

The Influencing Factors of Brand Loyalty and Brand Love

Loving a brand can cause a positive feeling for the brand and want to use the brand for a long time. Research on the factors that make consumers feel love for a brand is still a little. This study aims to know at the factors that influence brand loyalty and brand love on iphone users in City in Souteast Asia. This research is a quantitative study using a quantitative descriptive approach. The analytical tool in this study is the Smart PLS (Path Analysis) application. The research variables consist of Romanticism (X1), Self Expression (X2), Hedonic Product (X3), Brand Loves (Y1) and Brand Loyalty (Y2) as mediating variables. Samples using the Yamane method with statistical probability methods amounted to 96 from all iphone users whose population is unknown. The results showed that romanticism, self expression and hedonic products directly have not been able to influence brand love and brand loyalty variables. However, with the presence of variable of mediator such as brand love, indirectly romanticism, self expression and hedonic products can influence brand loyalty variables with brand love as an intervening variable. Overall the results of this study are able to explain that intervening plays an important role become a mediator for other variables. Keywords : Romanticism, Self Expression, Hedonic Products, Brand Loves, and Brand Loyalty

Leveraging probability concepts for genotype by environment recommendation

Statistical models that capture the phenotypic plasticity of a genotype across environments are crucial in plant breeding programs to potentially identify parents, generate offspring, and obtain highly productive genotypes for distinct environments. In this study, our aim is to leverage concepts of Bayesian models and probability methods of stability analysis to untangle genotype-by-environment interaction (GEI). The proposed method employs the posterior distribution obtained with the No-U-Turn sampler algorithm to get Monte Carlo estimates of adaptation and stability probabilities. We applied the proposed models in two empirical tropical datasets. Our findings provide a basis to enhance our ability to consider the uncertainty of cultivar recommendation for global or specific adaptation. We further demonstrate that probability methods of stability analysis in a Bayesian framework are a powerful tool for unraveling GEI given a defined intensity of selection that results in a more informed decision-making process towards cultivar recommendation in multi-environment trials.