Damage assessment in beam-like structures by correlation of spectrum using machine learning

Damage assessment in the actual operating process of the structure is a modern and exciting problem of construction engineering due to several practical knowledge about the current condition of the inspected structures. However, the problem faced is the difficulty in controlling the excitation in structures. Therefore, the output-based structural damage identification method is becoming attractive because of its potential to be applied to an actual application without being constrained by the collection of the information excitation source. An approach of damage assessment based on supervised Machine Learning is introduced in this study by using the correlation of spectral signal as an input feature for artificial neural network (ANN) and decision tree. The output of machine learning algorithms consists of the appearance of new cuts, the level of cutting and the cutting position. A supported beam model was constructed as an experiment to determine if the method is reasonable for engineering structures. Two machine learning algorithms have been applied to check the relevance of the proposed feature from vibration data. This study contributes a standard in the damage identification problem based on spectral correlation

Impact of Vocational Education and Training On Decent Job Opportunities Regarding Information and Communication Technology

Vocational education and training plays a crucial part in the creation of decent job. The fast growth of information and communication technology (ICT) during the past ten years has increased work opportunities for laborers. This research uses the yearly labor force survey data to study the impact of vocational education and training on decent job opportunities for employees in the context of Vietnam's information and communication technology development. The logit model results indicate that the 2020 rate of decent jobs is still low, at approximately 25.6 percent. However, vocational education and training and the advancement of ICT positively affect decent job opportunities. This long-lasting impact affects laborers in various areas, regions, and industries. These findings suggest that vocational education and training and ICT must play a significant role in transitioning from precarious to more secure employment, so laborers must acquire professional knowledge and information technology skills

Damage assessment in beam-like structures by correlation of spectrum using machine learning

Damage assessment in the actual operating process of the structure is a modern and exciting problem of construction engineering due to several practical knowledge about the current condition of the inspected structures. However, the problem faced is the difficulty in controlling the excitation in structures. Therefore, the output-based structural damage identification method is becoming attractive because of its potential to be applied to an actual application without being constrained by the collection of the information excitation source. An approach of damage assessment based on supervised Machine Learning is introduced in this study by using the correlation of spectral signal as an input feature for artificial neural network (ANN) and decision tree. The output of machine learning algorithms consists of the appearance of new cuts, the level of cutting and the cutting position. A supported beam model was constructed as an experiment to determine if the method is reasonable for engineering structures. Two machine learning algorithms have been applied to check the relevance of the proposed feature from vibration data. This study contributes a standard in the damage identification problem based on spectral correlation

Gender income gap in Vietnam in the 2000s : evidence from household surveys

This paper investigates the determinants and characteristics of changes in the gender wage gap between 2004 and 2010 in Vietnam. Labour force structure, employment by gender, education, and skill level, labour force participation, types of enterprises, geographical area, and wage structure are key determinants analyzed in this study. Results reaffirm that traditional concepts and social bias towards women prevent their access to education and training, selection of occupations, and opportunities to improve professional and technical qualifications. Policy implications are reviewed

The effect of emotional intelligence on the performance of auditors

This study aims to evaluate the impact of effective emotional intelligence on the work of auditors in Ho Chi Minh City, Ho Chi Minh. The authors conducted a survey for 355 auditors at companies and organizations operating in the field of auditing. The results show that there were 4 factors of emotional intelligence that affect job performance, arranged in the following sequence: (1) Perception of emotions, (2) Positive thinking with emotions, (3) Understand emotions, (4) Control emotions. This is the basis for the authors to give some implications to improve the emotional intelligence characteristics of auditors towards work efficiency

Antibacterial hydrogel containing Piper betle L. extract for acne treatment, an ex vivo investigation

The current treatments of acne vulgaris and acne-like disorders such as gram-negative folliculitis possess lots of unwanted side effects. Thus, alternative approach of utilizing natural plant extracts, specifically Piper betle L., have gained much attention. To this end, this work developed, characterized, and ex vivo evaluated novel antibiotics hydrogels containing P. betle L. leaf extract for acne treatment. Firstly, the design of experiments (DoE) D-optimal method was successfully developed, optimized, and validated, to investigate the relationship between P. betle L. extraction conditions and the extract properties. Secondly, the best extract was encapsulated in the hydrogel formulations composed of carbopol 940, propylene glycol, and cocamidopropyl betaine. Finally, the hydrogel was ex vivo determined its antibacterial activity on bacteria isolated from 15 patient acne samples. The optimal extraction condition being an extraction solvent/plant weight ratio of 4.034:1, an extraction time of 2.147 h, and a water extract volume of 91.4 mL. This condition yielded an extract total phenolic content of 3.337±0.034 g GAE/g, and minimum inhibitory concentrations of 32 µg/mL and 128 µg/mL on Staphylococcus aureus ATCC 25923 and Escherichia coli ATCC 25922, respectively. The hydrogel possessed suitable properties for a topical medication, including a viscosity of 6800 cps, a pH of 7.0, and a good foaming ability, at both 10°C, 25°C, and 40°C. The hydrogel showed higher antibacterial activity than the positive controls in both gram-positive and gram-negative bacteria. Conclusively, the hydrogel could become a potential pharmaceutical product for acne treatment