Graph bisection algorithms

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1986.MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING.Bibliography: leaves 64-66.by Thang Nguyen Bui.Ph.D

The role of information technology in STEM education

The ubiquity of IT (Information technology) for teaching at large is a reality that can be observed, including STEM education, which is the field of study of this research. In view of this situation, this work is intended to determine the role of IT in STEM (Science, Technology, Engineering, Mathematics) education. It was decided to conduct a systematic review based on PRISMA model and adding information obtained from the analysis of fugitive literature. The literature review was carried out on a total of 16 articles. The main inclusion criteria were a temporal selection from 2015 to March 2023, the inclusion of the terms IT and STEM in the title, abstract or keywords of the articles. The main results show an increasing tendency of this topic, especially in English research. Most relevant conclusions of the systematic review evidence a positive relationship between IT and STEM education, although some negative aspects are also highlighted as there is still a lack of resources and teacher training, leading to ineffective application of IT in STEM classes. The research results have important practical implications, it motivates teachers to research, propose and implement measures to enhance the role of IT in STEM education, while minimizing the limitations that have been identified

Quality Assessment During the Fermentation of Cocoa Beans: Effects of Partial Mucilage Removal

Fermentation of cocoa beans is the most important process contributing to the flavor in chocolate and other related products. The present study aimed to investigate the fermentation at a laboratory scale of cocoa beans with and without 10% w/w mucilage removal (whole beans). The physicochemical properties and microorganism development were monitored for six days of continuous fermentation (sampling was conducted every 24 hours). The results indicated the effects of partial mucilage removal of cocoa beans before the fermentation, in which the temperature, pH, and mucilage content (with/without mucilage removal) were recorded as 36.5 oC/38.6 oC, 3.44/3.31, and 18.41%/21.84%, respectively at the final day. Besides, the density of microorganisms (yeast-mold, lactic acid bacteria, and acetic acid bacteria) of cocoa beans with partial mucilage removal was higher than whole cocoa beans due to the increased aeration of the beans with mucilage removal, creating favorable conditions for the growth of microorganisms. After the fermentation, several physicochemical properties of the two cocoa bean types were compared, which demonstrated the more favorable quality of the cocoa beans with partial mucilage removal compared to the whole cocoa beans for the fermentation, e.g., lower seed shell content (14.1% vs. 17.8%), lower total acid (1.67% vs. 2.77%), and pH of around 5.0

Model Updating for Large-Scale Railway Bridge Using Grey Wolf Algorithm and Genetic Alghorithms

This paper proposes a novel hybrid algorithm to deal with an inverse problem of a large-scale truss bridge. Grey Wolf Optimization (GWO) Algorithm is a well-known and widely applied metaheuristic algorithm. Nevertheless, GWO has two major drawbacks. First, this algorithm depends crucially on the positions of the leading Wolf. If the position of the leaderis far from the best solution, the obtained results are poor. On the other hand, GWO does not own capacities to improve the quality of new generations if elements are trapped into local minima. To remedy the shortcomings of GWO, we propose a hybrid algorithm combining GWO with Genetic Algorithm (GA), termed HGWO-GA. This proposed method contains two key features (1) based on crossover and mutation capacities, GA is first utilized to generate the high-quality elements (2) after that, the optimization capacity of GWO is employed to seek the optimal solutions. To assess the effectiveness of the proposed approach, a large-scale truss bridge is employed for model updating. The obtained results show that HGWO-GA not only provides a good agreement between numerical and experimental results but also outperforms traditional GWO in terms of accuracy

Model Updating for Large-Scale Railway Bridge Using Grey Wolf Algorithm and Genetic Alghorithms

This paper proposes a novel hybrid algorithm to deal with an inverse problem of a large-scale truss bridge. Grey Wolf Optimization (GWO) Algorithm is a well-known and widely applied metaheuristic algorithm. Nevertheless, GWO has two major drawbacks. First, this algorithm depends crucially on the positions of the leading Wolf. If the position of the leaderis far from the best solution, the obtained results are poor. On the other hand, GWO does not own capacities to improve the quality of new generations if elements are trapped into local minima. To remedy the shortcomings of GWO, we propose a hybrid algorithm combining GWO with Genetic Algorithm (GA), termed HGWO-GA. This proposed method contains two key features (1) based on crossover and mutation capacities, GA is first utilized to generate the high-quality elements (2) after that, the optimization capacity of GWO is employed to seek the optimal solutions. To assess the effectiveness of the proposed approach, a large-scale truss bridge is employed for model updating. The obtained results show that HGWO-GA not only provides a good agreement between numerical and experimental results but also outperforms traditional GWO in terms of accuracy

Damage detection for a large-scale truss bridge using Tranmissibility and ANNAOA

In this paper, we propose an efficient approach to enhance the capacity of Artificial Neural Network (ANN) to deal with Structural Health Monitoring (SHM) problems.  Over the last decades, ANN has been extensively utilized for damage detection in structures. In order to identify damages, ANN frequently utilizes input information that is based on dynamic features such as mode shapes or natural frequencies. However, this type of data may not be able to detect minor damages if the structural defects are insignificant. To transcend these limitations, in this work, we propose utilizing transmissibility to create input data for the input layer of ANN. Moreover, to deal with local minimum problems of ANN, a combination between the Arithmetic Optimization Algorithm (AOA) and ANN is proposed. The global search capacity of AOA is employed to remedy the local minima of ANN. To evaluate the effectiveness of the proposed approach, a numerical model with different damage scenarios is considered. The suggested approach detects damage location precisely and with higher severity detection precision than the conventional ANN method

Damage detection for a large-scale truss bridge using Tranmissibility and ANNAOA

In this paper, we propose an efficient approach to enhance the capacity of Artificial Neural Network (ANN) to deal with Structural Health Monitoring (SHM) problems.  Over the last decades, ANN has been extensively utilized for damage detection in structures. In order to identify damages, ANN frequently utilizes input information that is based on dynamic features such as mode shapes or natural frequencies. However, this type of data may not be able to detect minor damages if the structural defects are insignificant. To transcend these limitations, in this work, we propose utilizing transmissibility to create input data for the input layer of ANN. Moreover, to deal with local minimum problems of ANN, a combination between the Arithmetic Optimization Algorithm (AOA) and ANN is proposed. The global search capacity of AOA is employed to remedy the local minima of ANN. To evaluate the effectiveness of the proposed approach, a numerical model with different damage scenarios is considered. The suggested approach detects damage location precisely and with higher severity detection precision than the conventional ANN method

Study on the effect of processing methods on the total polyphenol, 2,3,5,4’-tetrahydroxystilben-2-O-β-D-glucoside, and physcion contents in Fallopia multiflora Thunb. Haraldson root

This study investigated the changes in the ingredients in Fallopia multiflora Thunb. Haraldson (FMT) root after processing it with different methods such as soaking, stewing, and steaming or combined methods. The total polyphenol, 2,3,5,4′-tetrahydroxystilben-2-O-β-D-glucoside (THSG), and physcion contents in FMT products after processing were determined using high-performance liquid chromatography (HPLC) and ultraviolet-visible (UV-VIS) methods. The results demonstrated that the processing method and time significantly affected the contents of polyphenol, THSG, and physcion. The physcion and total polyphenol content increased or decreased during processing depending upon the processing time, while the THSG content gradually decreased with an increase in the processing time. The content of physcion (a substance that can cause liver toxicity) was analysed, and the suitable conditions for processing of the FMT products were determined as initial soaking in rice swill for 24 h and subsequent stewing with black beans and water for 12 h