Effect Of Random Factors Research Articles

Effect of random factors on liquid flow over the sheets of a structured packing

Effect of random factors on liquid flow over the sheets of a structured packing

A new method to investigate the intermediate crack-induced debonding strain

In order to investigate the interfacial debonding (IC) strain of the reinforced concrete structures strengthened by fiber-reinforced polymer (FRP), this paper proposed some data-driven models to explore it, considering the effect of random factors both in material and environment. The concrete strength, shear span proportion, the proportion of anchorage length to shear width, tensile reinforcement proportion, steel yield strength, stirrup reinforcement ratio, FRP stiffness, the proportion of sheet span to beamwidth, ratios of environmental temperature to the maintenance standard temperature, and ratios of environmental humidity to the relative humidity were regarded as the inputs, the IC debonding strain was regarded as the output. The results indicate that the neural network optimized by the sparrow search algorithm not only has a relatively small error but also has stronger robustness. In addition, a study on the importance of the inputs on the IC debonding strain indicates that the concrete strength, FRP stiffness, and ratios of environmental temperature to the maintenance standard temperature are the most significant factor to influence the IC debonding strain.

The Circular Economy Approach to Production Inefficiency: A Stochastic Frontier Analysis

The Circular Economy concept, which is based on the 3R principle, has led to the emergence of different ideas on waste management. On the one hand, waste management is expanded with the recommendations of the 5R and 10R hierarchies, on the other hand, it is defined to cover a significant part of the R stages of the recovery process. CE discussions are the efficiency analysis and use different indicators in performance measurements for which DEA is widely preferred. The stochastic frontier analysis (SFA) consists of assumptions about the functional relationship between inputs and outputs variables. Additionally, compared with non-parametric (SFA) considers the effects of random factors on outputs which strengthen the used estimation procedure. In this study, it is thought that one of the important variables of reducing inefficiency in the production function is the recovery in which the recycling of losses in the production process creates an important economic value while reducing the use of inputs or substituting them. Therefore, recovery is directly designed as an additional input using the Cobb-Douglas functional form. In the study, the 2000-2017 period data of OECD countries were used to analyze the effects of waste management, focusing on the recovery process, on economic growth. As a result, it was seen that the efficiency value calculated for OECD countries was 0,84 and the inefficiency in the production process decreased as the recovery rate increased. Even though the economic contribution of the recovery process is accepted by local governments, the initial costs of carrying out this process may require significant expenditures. Therefore, policies should be developed by taking into account the capacities and scales of the municipalities for the financing of these expenditures.

Developing an artificial neural network model to predict the durability of the RC beam by machine learning approaches

The chloride diffusivity is a significant index to describe the degradation rate of concrete structures. At present, a lot of models have been proposed by previous studies to investigate the chloride diffusivity in concrete specimens. However, most of these models only consider the effect of exposure time, and erosion depth on the chloride diffusivity and ignore the uncertain factor in the environment. This may lead to a tremendous difference existed in the predicted-to-experimental ratios of all typical chloride diffusivity models. Machine learning approaches as potential alternative predictors are often used to cope with this bias. This paper adopted five contemporary ML approaches, namely, the backpropagation (BP) neural network, the decision tree (DT), the random forest (RF), the linear regression (LR), and ridge regression (RR) to explore the chloride diffusivity. Input features considered in this study are water-cement ratios, the thickness of concrete specimens, coarse aggregate fraction volume, ratios of environmental temperature to the maintenance standard temperature, and ratios of environmental humidity to the relative humidity. It was found that the backpropagation (BP) neural network is the most accurate prediction (85%) with the lowest root mean squared error. With this superiority, A study on the importance of the input parameters reveals that the volume fraction of coarse aggregate, water-cement ratios, the thickness of the protective layer, and ratios of environment humidity to the relative humidity are the most influential parameters on chloride diffusivity. In addition, a data-driven model was established to investigate the chloride diffusivity considering the effect of random factors both in material and environment. Compared with the test results, the results indicated that the prediction results are closer to the test results, which is helpful for in-depth exploring the durability of the concrete structures.

Middle East Green Islands of Economic Growth: Egyptian, Turkish and Iranian Economies during the Covid-19 Pandemic

Purpose: Despite the heavy toll of the Covid-19 pandemic, Egyptian, Iranian and Turkish economies experienced growth in 2020. The article aims to explain this incredible performance. Was it a sign of more profound strength and resilience of each economy or rather the effect of random factors, unlikely to be repeated? Design/Methodology/Approach: The article is based on qualitative and quantitative analysis of the primary (government and international organizations data) and secondary (literature, press reports) data. Descriptive and comparative methods highlight the economic situation before the pandemic shock, the spread of the virus, and government responses. Analytical and deductive methods are used to explain the positive growth indicators. Findings: The surprising resilience of the Egyptian, Iranian and Turkish economies during the pandemic is explained by a mixture of policy responses, structural characteristics of each economy, and pure coincidence. Practical Implications: The policy response was the most important in Turkey, while the other two factors played the leading role in Egypt and Iran. Originality/Value: Despite favorable growth rates, all three countries need to redefine the state's role in the economy and promote manufacturing and export-led growth through selective industrial and technology policies.

Stability of a planetary climate system with the biosphere species competing for resources.

With the growing number of discovered exoplanets, the Gaia concept finds its second wind. The Gaia concept defines that the biosphere of an inhabited planet regulates a planetary climate through feedback loops such that the planet remains habitable. Crunching the "Gaia" puzzle has been a focus of intense empirical research. Much less attention has been paid to the mathematical realization of this concept. In this paper, we consider the stability of a planetary climate system with the dynamic biosphere by linking a conceptual climate model to a generic population dynamics model with random parameters. We first show that the dynamics of the corresponding coupled system possesses multiple timescales and hence falls into the class of slow-fast dynamics. We then investigate the properties of a general dynamical system to which our model belongs and prove that the feedbacks from the biosphere dynamics cannot break the system's stability as long as the biodiversity is sufficiently high. That may explain why the climate is apparently stable over long time intervals. Interestingly, our coupled climate-biosphere system can lose its stability if biodiversity decreases; in this case, the evolution of the biosphere under the effect of random factors can lead to a global climate change.

Simulation of Soil Water Evaporation during Freeze–Thaw Periods under Different Straw Mulch Thickness Conditions

Straw mulching is an effective agricultural technology to reduce soil water loss in arid and semi-arid areas. Herein, the soil temperature and soil water content of bare land (LD) and 5 cm (JG5), 10 cm (JG10), 15 cm (JG15), 20 cm (JG20) and 30 cm (JG30) straw mulch thicknesses were measured through field experiments performed to assess the soil water evaporation using the simultaneous heat and water model during a freeze–thaw period. The results showed that the inhibiting effect of straw mulching on soil water evaporation during the freeze-thaw period reached 24–56.7%, and straw mulch reduced the range of daily soil water evaporation by 2.02–2.48 mm, the effects of random factors on the daily soil water evaporation were significantly decreased. The highest soil water evaporation rate occurs during the unstable freezing stage, and the lowest occurs during the stable freezing stage. When the straw mulch thickness exceeded 10 cm, the effect of increasing straw mulch thickness on daily soil water evaporation was reduced. The straw mulch layer could not completely inhibit the effect of the external environment on soil water evaporation even when the straw mulch thickness was increased to 30 cm. This research results can provide a basis for the scientific evaluation and prevention of soil water evaporation in arid and semi-arid areas.

An Efficiency Analysis of Female Hair Dressers in Empangeni, South Africa: The Role of Infrastructure

Infrastructure is widely considered an important determinant of firm performance but evidence on its importance on technical efficiency of hairdressers is very limited. Against this background, this study sought to compute and compare the technical efficiency levels of female hairdressers operating by the road side with those operating within formalised and designated salons. Primary cross-sectional data were collected using questionnaires and analysed within a quantitative research design. Technical efficiency was measured using a stochastic frontier technique which, in computing efficiency scores, separates the effect of random factors that are exogenous to the hairdressers. Based on a Cobb Douglas functional form chosen by relevant statistical tests, results from the stochastic frontier model estimated by the maximum likelihood confirm that hairdressers operating in designated saloons are more efficient when compared with hairdressers operating by the road side. A policy implication arising from this finding is that the provision of proper infrastructure is necessary to improve technical efficiency of hairdressers currently operating by the road side.

INVESTIGATION OF THE INFLUENCE OF THROMBOPHILIC GENES POLYMORPHISM, INCLUDING SERPIN 1 (PAI-I), FII, PROTHROMBIN AND ITGB3-Β INTEGRIN, ON THE FREQUENCY OF STROKE IN ASSOCIATION WITH CONTROLLABLE RISK FACTORS FOR ITS OCCURRENCE

The aim is the analysis of the relationship between the polymorphism of thrombophilic genes, in particular Serpin 1 (PAI-1), F2-prothrombin and ITGB3-α integrin, and the incidence of stroke, as well as the study of factor effects of this polymorphism in association with controlled risk factors (hypertonic disease, smoking, alcohol consumption, diabetes mellitus, obesity, atrial fibrillation). Materials and methods: A total of 134 patients were examined (men accounted for 44.8%, women 55.2%, average age 62.5 ± 2.1). The statistical analysis was carried out using the following criteria: χ2-Pearson, Fisher's exact criterion (reversible), Chuprov's coefficient of conjugation and dispersion analysis (alternative complex). Results: The relationship between the frequency of a specific allele of thrombophilia and the incidence of stroke is absent. The reason for such results can be a significant effect of random factors (hypertension, diabetes ...), a significant variability of risk factors, their different frequency in groups (inter- and intra-group differences), a significant (95%) total effect of these factors. Conclusions:Identification of biochemical or genetic markers of thrombophilic conditions, including polymorphism of the hemostasis system genes, will significantly increase the possibility of adequate pathogenetic treatment and timely prevention of acute cerebrovascular disorders, especially persons of working age, which has great medical and social importance.

Dynamic behaviors of the FitzHugh–Nagumo neuron model with state-dependent impulsive effects

In present work, in order to reproduce spiking and bursting behavior of real neurons, a new hybrid biological neuron model is established and analyzed by combining the FitzHugh–Nagumo (FHN) neuron model, the threshold for spike initiation and the state-dependent impulsive effects (impulse resetting process). Firstly, we construct Poincaré mappings under different conditions by means of geometric analysis, and then obtain some sufficient criteria for the existence and stability of order-1 or order-2 periodic solution to the impulsive neuron model by finding the fixed point of Poincaré mapping and some geometric analysis techniques. Numerical simulations are given to illustrate and verify our theoretical results. The bifurcation diagrams are presented to describe the phenomena of period-doubling route to chaos, which implies that the dynamic behavior of the neuron model become more complex due to impulsive effects. Furthermore, the correctness and effectiveness of the proposed FitzHugh–Nagumo neuron model with state-dependent impulsive effects are verified by circuit simulation. Finally, the conclusions of this paper are analyzed and summarized, and the effects of random factors on the electrophysiological activities of neuron are discussed by numerical simulation.

Stochastic risk assessment of water quality using advection dispersion equation and Bayesian approximation: A case study

ABSTRACTThe influence of various heterogeneous parameters, stochastic uncertain factors, and pollutant particles from the industrial effluents in the water system is investigated using advection dispersion equation (ADE) and the Bayesian approximation. Here, the decay coefficient is decomposed into the exact part and the deviation part. The coefficient is used to find out the errors and deviation in decay during the flow of pollutants. Two Bayesian models are developed to analyze the posterior distributions and to find out the Bayes factor for the stochastic covariance estimation. The Bayesian calibration focused the characteristics of both on mechanistic and statistical approximation. The efficiency and accuracy of the developed models are checked from the results obtained on the basis of the confidence interval. Markov chain Monte Carlo simulation is used to acquire the convergence point of parameters for the posterior estimation. The stochastic covariance or white noise represents the effect of random factors on the river system. The analysis revealed that the rate of decay is dependent upon the duration and distance traveled by the pollutants. The collaboration of ADE and Bayesian approximation encourage the water-quality management and environmental modeling.

Coupled LAI assimilation and BEPS model for analyzing the spatiotemporal pattern and heterogeneity of carbon fluxes of the bamboo forest in Zhejiang Province, China

Bamboo forests are widely distributed in the tropical and sub-tropical regions, and have a great carbon sequestration capacity. However, the carbon dynamics of bamboo forest are still poorly understood. This study developed an algorithm for assimilating LAI dynamics based on an integrated ensemble Kalman filter using MODIS LAI data, MODIS reflectance data, and canopy reflectance data modeled by PROSAIL for two typical bamboo forests. The assimilated LAI was highly consistent with the observed LAI, yielding correlation coefficient (r) of 0.84 and 0.94 for Moso bamboo forest and Lei bamboo forest, respectively. Then, the spatiotemporal pattern of the CO2 fluxes within bamboo forest were modeled for Zhejiang Province during 2011–2014 using the Boreal Ecosystem Productivity Simulator model driven by assimilated LAI. The modeled CO2 fluxes were in agreement with the CO2 fluxes measured by eddy covariance technology at two selected sites within the study region. Average r, absolute deviation, and root mean square error values were 0.77, 0.65gCm−2day−1, and 0.82gCm−2day−1, respectively. Bamboo stands with high Net Ecosystem Exchange (NEE) values were found to be distributed throughout mountainous areas in the northwest, southwest, and northeast of Zhejiang, while low NEE stands were located in the mountain basin areas, high altitude areas, and the majority of coastal areas. Among the eleven cities in Zhejiang Province, Hangzhou was the highest annual total NEE city (0.34±0.06TgCyr−1), and Huzhou was the highest NEE density city (7.65±1.02MgChm−2yr−1). The carbon sequestrated by bamboo forest was 1.74TgCyr−1, accounted 6.36Tg CO2 yr−1, which indicated the bamboo forested area in Zhejiang Province was a carbon sink. The spatial heterogeneity of CO2 fluxes of bamboo forest can be revealed by an exponential semivariance model. The analysis of the model structure indicated that the spatial heterogeneity of CO2 fluxes of bamboo forest was characterized by significant autocorrelation, with an average autocorrelation range of 3.00km, however the effect of random factors (management levels, management measures, etc.) cannot be ignored. This is the first time that the CO2 fluxes of bamboo forest in Zhejiang Province have been mapped and this study provides a new estimate of CO2 fluxes in this region.

INCREASED VOLATILITY OF EXCHANGE PRICES ON ENERGY RESOURCES AS AN ILLUSTRATION OF THE NEW REALITIES OF THE GLOBAL ECONOMY DEVELOPMENT IN THE SECOND DECADE OF THE XXI CENTURY

Sokhatska O. Increased volatility of exchange prices on energy resources as an illustration of the new realities of the global economy development in the second decade of the XXI century. Introduction. Increased volatility in the exchange markets of energy resources, primarily oil, is the reality of the global economy development in the second decade of the XXI century. Sharp drops in prices and fast change of trends make these markets difficult to predict, that increases the risks for both producers and consumers, for exporting countries and importers. Purpose. The purpose of the article is the systematization of reasons of increased volatility of energy exchange’s prices primarily oil in the second decade of the XXI century, and development on this basis recommendations for their consideration in the process of reforming energy sector and in determination of controlling parameters in the annual budgets of Ukraine. Results. Global economy restructuring in the context of computerization, robotics and the transition to “clean” types of energy is fait accompli. In implementing the strategy of comprehensive reformation of all spheres of activity in our country, consideration of these trends in global economic development is not only appropriate, but necessary. In this context provided the limitation of resources, there is no doubt concerning their focus on technological and informational innovations. The above-mentioned follows from the direct need for the withdrawal of Ukraine’s economy from the XX century to the XXI century. Conclusions. Increased volatility in the exchange markets of energy resources, primarily oil, is the reality of the global economy development in the second decade of the XXI century. Sharp drops in prices and fast changing of trends make these markets difficult to predict, that increases the risks for both producers and consumers, for exporting countries and importers. Until recently, increased volatility and lack of methods for accurate predictions of future prices of energy markets had been explained by the effect of random factors (natural and manmade disasters, political conflicts and military actions in the area of production) and the presence of significant by volumes speculative component of exchange markets. However, in the post-crisis period more significant factors of influence on hydrocarbon prices in general and oil in particular are clearly manifested, the effect of which is caused by deep structural transformation, serving the global economy. It is about innovative development, including the transition of humanity to the era of the fourth industrial revolution, which involves fundamental changes of forms and types of business in general, and its energy supply in particular

A performance-based service life design method for reinforced concrete structures under chloride environment

The chloride-induced reinforcement steel corrosion usually causes premature failure of performance in reinforced concrete structures subjected to chloride environment. However, conventional prescriptive design methods or fully probabilistic methods cannot ensure an explicit performance in design stage. The main objective of this study is to develop a performance-based service life design method, by which concrete structures such as bridges can be designed according to a predefined performance level to satisfy the target service life, reliability and deterioration level. The mechanism of chloride-induced reinforcement steel corrosion initiation was analyzed to deduce a time-varying limit state function, and the corresponding stochastic model was developed considering the effects of random factors. Through first-order reliability method, a partial factor formula was deduced to realize performance verification in performance-based design process. Finally, a case study of a concrete bridge deck exposed to marine environment was presented and the sensitivity analysis of steel corrosion was carried out. The proposed performance-based design method can rationally deal with the uncertainties of random parameters and ensure the predefined target performance to be satisfied during design process instead of predicting performance after design.

On statistical properties of the detection range of a moving target

The detection range of a moving target at which an approaching target is first detected by a radar according to some criterion is analyzed. Because of the effect of random factors (noise, fluctuations of the target’s echo signal, etc.), the detection range of a moving target is a random quantity. The probability density function of the detection range is calculated. It is shown that the most probable value of the detection range of a moving target may differ substantially from the traditional maximum detection range with specified probabilities of correct detection and false alarms. It is found that the detection range of a moving target depends substantially of the target velocity and its statistical spread is rather large as compared to the mean value of this range.

Malware Behavior Classification Approach Based on Naive Bayes

Because of the interference of obfuscation and polymorphism on malware analysis and detection, the dynamic analysis of malware binaries during run-time is becoming a research hotspot in intrusion detection field. Malware classification is a key problem in the research of dynamic malware behavior analysis. On the basis of the malware behavior monitoring result reports, after discussing of malware behavior characteristics, operation similarity of behavior and the effect of random factors on behavior pattern, this paper proposed a framework for automatic malware behavior classification using Naive Bayes machine learning model. The framework improves the accuracy and efficiency of classification by introducing the Naive Bayes. Then we designed and implemented automatic malware behavior classifier prototype called MalwareClassifier. In case study, we evaluated the prototype using behavior sequence reports which were generated through true malware. The experiment results show that our approach is effective, and the performance of training and classification is improved through the

Factors affecting the reproductive performance of Finnish trotter stallions

Acknowledgements: *Suomen Hippos, the Finnish Trotting and Breeding Association, generously provided their mating and pedigree databases for the purpose of this study Materials and methods The original data* consisted of all registered matings of FH and SB during the years 1991-2005 in Finland. There were 69205 cases (= one mare bred by one stallion per breeding season) altogether. Analyses were performed with SAS (proc freq and chi-square test), PEDIG-software (inbreeding coefficients), WSYS software (building a linear fixed effects model, analysis of variance), VCE6 program package (estimating the effects of random factors with a mixed model), and PEST program package (best linear unbiased estimates (BLUE) for fixed factors). Studied variable was foaling outcome, because it was considered more reliable than pregnancy outcome in this kind of data recording: 1 = a full term live or dead foal was born, and 0 = not pregnant, aborted or mare died during gestation Fixed factors in the models were month and year of mating, mating type (on-site insemination, transported semen, frozen semen, natural mating), age group of stallion, inbreeding level of the expected foal, and mare type (maiden, barren, rested or foaled) and age. Genetic components were included as random factors. Results The average foaling rates were 64.5 % for FH and 70.8 % for SB. The effects of all fixed factors were found to be statistically significant in the fixed effects model. The yearly foaling rates of both breeds exhibited a downward trend, which was more apparent for FH (Figure 1). Increasing stallion age (Figure 2) had a negative impact on fertility. Mating type (Figure 3) and inbreeding class of the expected foal (Figures 4 and 5) also affected foaling rates.

Concept of randomness in chemistry and ambiguity in the results of chemical experiments

A general approach to the analysis of the effect of random factors on processes in physicochemical and chemical systems is proposed. A probabilistic model of a system is constructed, which is based on the principle of variability of complex systems. The simplest functions of distribution of systems with respect to the parameters of state are presented. The function of distribution of replica experiments with respect to the measurement results in the presence of uncontrollable random factors is described.

Determination of the porosity of spray-deposited coatings by hydrostatic weighing

An analysis of the accuracy possible in the experimental determination of the apparent densities and open, total, and closed porosities of spray-deposited coatings has demonstrated that the hydrostatic weighing method permits reliable determination of only the first two of these parameters. Use of the parameters ∏∑ and ∏cl in conjunction with the hydrostatic weighing method for assessing the properties of multiphase spray-deposited coatings and the quality of deposition conditions is not recommended. To minimize the effect of random factors in the coating impregnation process on the accuracy of determination of parameters and simplify the weighing operation, a special apparatus has been developed.