Archive of

Advanced Engineering Science

Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-21-07-2022-247

Abstract : Energy dissipation on weirs and spillways are one of significant issues due to the high kinetic energy of downstream flow which might cause damage to hydraulic structures as well as downstream channels. So, to enhance energy dissipation, weirs of stepped type can be used. Recently, stepped weirs are more interesting because they work well with the positioning of gabions and roller-compacted concrete (RCC) construction. In this investigation and comparison of energy dissipation on impervious stepped weirs and gabion is presented. Three lab-scale models of impervious stepped weirs and three models of gabion stepped weirs, each with three downstream slopes, were explored for this purpose (1:1, 1:2 & 1:3, V:H). Results indicates gabion weirs dissipate energy more than impervious weirs by about 15% in the lowest discharge and 7% at the highest discharge. Additionally, for gabion and impervious stepped weirs, results indicate that, energy dissipation increased when slope of the downstream direction decreased. Lastly, for gabion and impervious stepped weirs, the rate of energy dissipation falls as flow rate increases..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-21-07-2022-246

Abstract : The purpose of this research is to determine the influence of the beliefs of higher education students towards the adoption of cryptocurrencies, based on the theory of planned behavior. The hypothesized model was tested on 174 students from a university in northern Chile, through an online survey. The results partially support the theory, that is, attitudes and perceived behavioral control have a positive and significant relationship with respect to intention, and this last one has a positive and significant relationship with respect to purchasing behavior. Finally, the theoretical and practical implications, as well as the limitations of the study, are discussed..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-21-07-2022-244

Abstract : The growing era of social networks and ubiquity of the Internet have paved the way for extensive research in the area of social network analysis. Wide range of research challenges have been identified in the domain of social network analysis such as how individuals interact with each other, and what is the structure of the social network when diverse interactions are taking place. Detection of overlapping communities is one of the upcoming research challenges due to the participation of individuals in diverse network groups at the same time. The main objective of this paper is to present a comprehensive review of overlapping community detection methods for various types of social networks. The paper provides a systematic segregation of overlapping community detection methods and draws inferences regarding their application. Since the main issues in community detection in social networks are- scalability considering the huge scale of networks, dynamic nature of associations, and time-variant participation in communities, this paper brings forth critical analysis of computational complexity of overlapping community detection methods in literature. The parameters that can be used for evaluation of these methods as well as listing of real-world and synthetic benchmark datasets used for evaluation of each clique and non-clique method have also been detailed. This paper is intended to serve as a ready reference for the researchers in the area of social network analysis to develop efficient and accurate community detection methods for current social networks..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-16-07-2022-241

Abstract : Artificial intelligence techniques play a promising role in designing decision-making systems in agriculture. Several artificial intelligence techniques have been adopted to design various agricultural decision support systems worldwide during the past three and a half decades. Over time, the application trend of such techniques has been changed and opened several new frontiers. A scientific study can lead aspirant researchers to choose an appropriate technique before designing such systems in agriculture. Instead of a mere literature survey, a statistical method of trend analysis and forecasting is essential to explore the past, present, and future trajectory of applying such techniques. This paper presents a statistical framework to analyze and forecast the application trend of the five most popular intelligent techniques in agriculture using the time-series data of the past 35 years. In the first step, as a well-established nonparametric method of trend test, the Mann-Kendall statistics have been applied to assess the existence of a trend. In the second step, a forecasting model has been proposed using the Autoregressive Integrated Moving Average approach to predict the future trend and prospect of applications of such systems with precision. Finally, the prediction accuracy has been measured using three popular scaled error metrics..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-28-06-2022-234

Abstract : Exposure to ambient gaseous components is a significant issue for people’s health. This study aims to check the modification effect of seasonal temperature variation on the association of ambient air pollutants in the selected traffic crossroads in Baghdad city. The study continued for around 180 calendar days from the winter of 2020 to the summer of 2021; during this period, seven major gaseous parameters, including VOCs, NO2, CO, CO2, H2S, SO2, and ground O3, were tested via using the devices of GIG6 and GIG2. The results showed that the high temperature significantly affected the dispersion of air pollutants, whereas the increase in air temperature from 10˚C to 48˚C led to an increase in the concentration of H2S about ten times, and an increase in emission of CO around three times, while there are varying increases for the rest of the other air pollutants..
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