Big Data Analysis and Computing Visions
Volume:1 Issue: 2, Jun 2022

Due to the fact that science is advancing and construction in our society is increasing, the engineering community is also obliged to introduce new approaches to the country and use them in this field. The traditional method (CAD) used to be used in this field and now the engineering community in most of the world uses Building Information Modeling (BIM) technology. BIM helps the project team observe what will be built in a simulated environment. This study examines the role of BIM in reducing time, cost savings, quality improvement, monitoring, control, estimating time and cost, comparing current conditions with standards, and reporting. We also compared the two projects, one using BIM and the other using the traditional method. The results showed that the use of BIM helps to include value engineering in projects, collisions do not occur during project implementation .

Foreign direct investment (FDI) and environmental quality contributes very significantly to all parts of the world, especially developing countries. These two factors have been so important that are known as the engine of economic growth and progression. This paper aimed to examine the association between environmental sustainability index, economic growth, and FDI in selected developing countries. Estimation of long-run coefficients is carried out by using Dynamic Ordinary Least Square (DOLS) and Fully Modified Ordinary Least Square (FMOLS), and the estimation of short-term coefficients and causality relationships using Pooled Mean Group (PMG) method in panel data for intervals 2000-2020. The outcomes of long-term estimates of variables indicate that each variable is statistically significant; so that, FDI has the greatest effect on the economic growth. The environmental quality index had a significantly positive impact on the economic growth; so that, after FDI variable, it significantly affected economic growth in selected developing countries. There is a significantly positive relationship between FDI and quality of environment and economic growth in short term. In the equation of environmental quality index, economic growth, FDI and trade openness show a significantly negative impact on quality of environment in the short term. Generally, as it was observed from the short-term and long-term relationships, the association between economic growth and quality of environment is a two-way causality relationship.

The goal is to build and create an agricultural monitoring system that uses a wireless sensor network to boost farming production and quality without having to manually monitor it all of the time. In agriculture, temperature, humidity, and carbon dioxide levels are the most critical elements affecting plant productivity, growth, and quality. As a result, this system measures these characteristics in the fields on a regular basis, allowing farmers or agriculture specialists to view the readings on the web at the same time. Furthermore, if a crucial change in one of the metrics occurs, an agriculture specialist will notify the farmer through mobile text message and e-mail. The farmer can study the best environmental conditions for maximum crop productivity, greater productivity, and significant energy savings by continuously monitoring several environmental data.

In this paper we proposed a new neurodynamic model with recurrent learning process for solving ill-condition Generalized eigenvalue problem (GEP) Ax = lambda Bx. our method is based on recurrent neural networks with customized energy function for finding smallest (largest) or all eigenpairs. We evaluate our method on collected structural engineering data from Harwell Boeing collection with high dimensional parameter space and ill-conditioned sparse matrices. The experiments demonstrate that our algorithm using Adam optimizer, in comparison with other stochastic optimization methods like gradient descent works well in practice and improves complexity and accuracy of convergence.

The rough sets theory is a mathematical tool to express vagueness by means of boundary region of a set. The main advantage of this implementation of vagueness is that it requires no human input or domain knowledge other than the given data set. Several efforts have been made to make close the rough sets theory and machine learning tasks. In this regard several extensions and modifications of the original theory are proposed. This paper provides the basic concepts of the theory as well as its well-known extensions and modifications.

The traditional Data Envelopment Analysis (DEA) model on network-structured performance analysis normally considers desirable intermediate measures. In many real cases, the intermediate measures consist of both desirable and undesirable factors. The motivation of this paper is employing “Natural and managerial disposability” in two-stage network structures with undesirable intermediate measure. The non-cooperative game theory is proposed to study the two-stage structure. A real case of 34 OECD countries in 2012 has been illustrated to shed a light on applicability of the proposed methodology.