In today’s manufacturing sector, high-quality materials that satisfy customers’ needs at a reduced cost are drawing attention in the global market. Also, as new applications are emerging, high-performance biocomposite products that complement them are required. The production of such high-performance materials requires suitable optimization techniques in the formulation/process design, not simply mixing natural fibre/filler, additives, and plastics, and characterization of the resulting biocomposites. However, a comprehensive review of the optimization strategies in biocomposite production intended for infrastructural applications is lacking. This study, therefore, presents a detailed discussion of the various optimization approaches, their strengths, and weaknesses in the formulation/process parameters of biocomposite manufacturing. The report explores the recent progress in optimization techniques in biocomposite material production to provide baseline information to researchers and industrialists in this field. Therefore, this review consolidates prior studies to explore new areas.

This research examines three data mining approaches employing cost management datasets from 391 Thai contractor companies to investigate the predictive modeling of construction project failure with nine parameters. Artificial neural networks, naive bayes, and decision trees with attribute selection are some of the algorithms that were explored. In comparison to artificial neural network’s (91.33%) and naive bays’ (70.01%) accuracy rates, the decision trees with attribute selection demonstrated greater classification efficiency, registering an accuracy of 98.14%. Finally, the nine parameters include: 1) planning according to the current situation; 2) the company’s cost management strategy; 3) control and coordination from employees at different levels of the organization to survive on the basis of various uncertainties; 4) the importance of labor management factors; 5) the general status of the company, which has a significant effect on the project success; 6) the cost of procurement of the field office location; 7) the operational constraints and long-term safe work procedures; 8) the implementation of the construction system system piece by piece, using prefabricated parts; 9) dealing with the COVID-19 crisis, which is crucial for preventing project failure. The results show how advanced data mining approaches can improve cost estimation and prevent project failure, as well as how computational methods can enhance sustainability in the building industry. Although the results are encouraging, they also highlight issues including data asymmetry and the potential for overfitting in the decision tree model, necessitating careful consideration.

Through the combination of the geographic information systems (GIS) and the integrated information model, the stability of regional bank slope was comprehensively evaluated. First, a regional bank slope stability evaluation index system was established through studying seven selected factors (slope grade, slope direction, mountain shadow, elevation, stratigraphic lithology, geological structure and river action) that have an impact on the stability of the slope. Then, each factor was rasterized by GIS. According to the integrated information model, the evaluation index distribution map based on rasterized factors was obtained to evaluate the stability of the regional bank slope. Through the analysis of an actual project, it was concluded that the geological structure and stratigraphic lithology have a significant impact on the evaluation results. Most of the research areas were in the relatively low stable areas. The low and the relatively low stable areas accounted for 15.2% and 51.5% of the total study area respectively. The accuracy of slope evaluation results in the study area reached 95.41%.

Lattice Boltzmann models for diffusion equation are generally in Cartesian coordinate system. Very few researchers have attempted to solve diffusion equation in spherical coordinate system. In the lattice Boltzmann based diffusion model in spherical coordinate system extra term, which is due to variation of surface area along radial direction, is modeled as source term. In this study diffusion equation in spherical coordinate system is first converted to diffusion equation which is similar to that in Cartesian coordinate system by using proper variable. The diffusion equation is then solved using standard lattice Boltzmann method. The results obtained for the new variable are again converted to the actual variable. The numerical scheme is verified by comparing the results of the simulation study with analytical solution. A good agreement between the two results is established.

This article concerns  with  the  construction of the  analytical traveling  wave so- lutions  for the Generalized-Zakharov System  by the Riccati-Bernoulli Sub- ODE technique. Also, we will discuss this  technique  in random  case by using random  traveling  wave trans- formation  in order  to  find what  is the  effect of the  randomness  input  for this  technique. We presented the Generalized-Zakharov System as an example to show the difference effect between the deterministic and stochastic Riccati-Bernoulli Sub-ODE technique.  The first moment of random solution is computed for different statistical probability distributions.

The development of critical thinking (CT) enhances academic and professional opportunities. A review of literature reveals the use of fragmented analysis techniques, such as descriptive and correlational methods, among others, which hinder a deeper understanding of CT levels. This research aims to develop a methodology for analyzing Critical Thinking test scores, integrating five phases: exploratory, item analysis, scoring, gap analysis, and correlational. Using a quantitative approach, CT skills were analyzed with the Halpern Critical Thinking Assessment, which includes both open- and closed-ended questions to measure five skills: Verbal Reasoning (VR), Argument Analysis (AA), Hypothesis Testing (HT), Probability Use (PU), and Problem Solving (PS). The sample consisted of 214 students aged 18 and older. The item analysis phase categorized the items into quadrants: satisfactory, for review, or for elimination, based on difficulty and discrimination indices. The gap analysis revealed that Verbal Reasoning and open-ended formats were less satisfactory. The correlational phase, using heat maps, showed a stronger association between Verbal Reasoning and Probability Use. The methodological contributions include a variety of strategies that provide recommended procedures for analyzing tests or questionnaires in general. In today’s digital age, the development of critical thinking is not only a desirable skill but an essential necessity for the higher education system.