Learning Styles of Vietnamese Medical Students

Background: The purpose of this study was to assess the learning styles of Vietnamese medical students at the Ho Chi Minh City University of Medicine and Pharmacy.Method:  Participants were 856 (147 first-year, 144 second-year, 144 third-year, 136 fourth-year, 148 fifth-year, and 137 sixth-year students) medical students who completed the 100-item Vermunt’s Inventory of Learning Styles.Results:  Factor analysis resulted in four factors with adequate reliability (α range: 0.71 - 0.86):  Meaning-directed learning style (factor 1), passive, undirected learning style (factor 2), application-directed learning style (factor 3), and reproduction-directed learning style (factor 4).  Final-year students employed more deep processing, concrete processing, self regulation, use of knowledge, but more stepwise processing, certification orientation, intake of knowledge than did the freshmen. Students with higher achievement classifications had higher mean score of deep processing, concrete processing, self-regulation, construction of knowledge, and use of knowledge, lower certificate and ambivalent orientation. Discussion:  Four theoretically meaningful and cohesive factors underlying learning patterns emerged from the factor analysis.  The learning styles of Vietnamese medical students were relatively similar to Asian students, but there were some differences from European students.Conclusion:  The assessment of learning styles of medical students may help curriculum renewal, the application of teaching and assessment methods, and improve student learning

Detecting Earning Management of Companies Listing on HOSE

The study is aimed to detecting earning management from companies listing in Ho Chi Minh Stock Exchange (HOSE) during the period from 2013 – 2015 by using 2 models, Jones (1991) and Modified Jones Model developed by Dechow et al. (1995). Moreover, we also tested the effectiveness of Jones (1991) for detecting firms’ earning management since prior researches showed that Jones (1991) has lower standard error in detecting accruals based earning management compared with other models as suggested by DeAngelo et al. (1994). Hence we proposed that Jones (1991) provides a more significant outcome for estimating the nondiscretionary component of accruals and thus less exposed to misspecifications error from absent variables. We found that Jones (1991) illustrates a better explainable ability even though the adjusted R-square of the models is closely similar with each other

Effects of TikTok Influencers on the Purchase Intention of Gen-Z: Cosmetic Industry

This study investigates how TikTok influencers affect Generation Z's purchase intention toward the cosmetic industry in HCMC. The research issue is a lack of knowledge on how TikTok influencers affect Generation Z's buying intentions for cosmetics. The research objective is to investigate the relationships among influencers' credibility, physical attractiveness, expertise, social advocacy, customers' trust, gender, and purchase intention. The literature study emphasizes the significance of customer trust and influencer characteristics in influencing consumer intention. A questionnaire survey is used as a data gathering technique in this research employing a quantitative methodology. To analyze the data, SPSS will be used as the statistical program. Descriptive statistics will be computed to summarize the data. Multiple regression analysis will examine the relationship between influencers' characteristics and customer trust toward their purchase intention. According to the findings, all influencers' characteristics, including credibility, physical attractiveness, expertise, and social advocacy, have favorable effects on Gen Z's purchasing intention. Surprisingly, customer trust has the most influence on Gen Z behavior. It indicates that there is a difference in purchase intention for different genders. The outcomes will offer valuable insights to cosmetic industry marketers at HCMC to develop effective influencer marketing strategies for Generation Z consumers

On Throughput for UAV Relay Assisted for Use in Disaster Communications

In this paper, the system performance of an energy harvesting (EH) unmanned aerial vehicle (UAV) system for use in disasters was investigated. The communication protocol was divided into two phases. In the first phase, a UAV relay (UR) harvested energy from a power beacon (PB). In the second phase, a base station (BS) transmitted the signal to the UR using non-orthogonal multiple access (NOMA); then, the UR used its harvested energy from the first phase to transfer the signal to two sensor clusters, i.e., low-priority and high-priority clusters, via the decode-and-forward (DF) technique. A closed-form expression for the throughput of the cluster heads of these clusters was derived to analyze the system performance. Monte Carlo simulations were employed to verify our approach

Vibration and buckling behaviours of thin-walled composite and functionally graded sandwich I-beams

The paper proposes a Ritz-type solution for free vibration and buckling analysis thin-walled composite and functionally graded sandwich I-beams. The variation of material through the thickness of functionally graded beams follows the power-law distribution. The displacement field is based on the first-order shear deformation theory, which can reduce to non-shear deformable one. The governing equations of motion are derived from Lagrange's equations. Ritz method is used to obtain the natural frequencies and critical buckling loads of thin-walled beams for both non-shear deformable and shear deformable theory. Numerical results are compared to those from previous works and investigate the effects of fiber angle, material distribution, span-to-height's ratio, and shear deformation on the critical buckling loads and natural frequencies of thin-walled I-beams for various boundary conditions

Secrecy outage performance analysis for energy harvesting sensor networks with a jammer using relay selection strategy

In this paper, we study radio frequency energy harvesting (EH) in a wireless sensor network in the presence of multiple eavesdroppers (EAVs). Specifically, the sensor source and multiple sensor relays harvest energy from multiple power transfer stations (PTSs), and then, the source uses this harvested energy to transmit information to the base station (BS) with the help of the relays. During the transmission of information, the BS typically faces a risk of losing information due to the EAVs. Thus, to enhance the secrecy of the considered system, one of the relays acts as a jammer, using harvested energy to generate interference with the EAVs. We propose a best-relay-and-best-jammer scheme for this purpose and compare this scheme with other previous schemes. The exact closed-form expression for the secrecy outage probability (SOP) is obtained and is validated through Monte Carlo simulations. A near-optimal EH time algorithm is also proposed. In addition, the effects on the SOP of key system parameters such as the EH efficiency coefficient, the EH time, the distance between the relay and BS, the number of PTSs, the number of relays, and the number of EAVs are investigated. The results indicate that the proposed scheme generally outperforms both the best-relay-and-random-jammer scheme and the random-relay-and-best-jammer scheme in terms of the secrecy capacity

SYNTHESIS OF STARCH MODIFIED MONTMORILLONITE AS AN EFFECTIVE ADSORBENT FOR Pb (II) REMOVAL FROM WATER

The adsorbent is prepared by the montmorillonite co-modification with starch for the removal of Pb (II) ions from aqueous solution. The Fourier-transformed infrared (FTIR), X-ray diffraction (XRD) spectroscopies were used to determine the structure and characteristics of the adsorbent. The main factors affecting the removal of Pb (II) ions were investigated, including the effect of pH, contact time, adsorbent dosage and the initial concentration of Pb (II). Batch process can be used for adsorption and equilibrium studies. The experimental data were fitted using Freundlich and Langmuir adsorption models. The Langmuir isotherm best fitted the experimental data with R2 0.99 and maximum Pb (II) adsorption capacity of 21.5 mg/g indicated monolayer adsorption. Kinetic studies using pseudo-first-order and pseudo-second-order rate models showed that the process complied well with the pseudo second-order rate model