Outage probability analysis for hybrid TSR-PSR based SWIPT systems over log-normal fading channels

Employing simultaneous information and power transfer (SWIPT) technology in cooperative relaying networks has drawn considerable attention from the research community. We can find several studies that focus on Rayleigh and Nakagami-m fading channels, which are used to model outdoor scenarios. Differing itself from several existing studies, this study is conducted in the context of indoor scenario modelled by log-normal fading channels. Specifically, we investigate a so-called hybrid time switching relaying (TSR)-power splitting relaying (PSR) protocol in an energy-constrained cooperative amplify-and-forward (AF) relaying network. We evaluate the system performance with outage probability (OP) by analytically expressing and simulating it with Monte Carlo method. The impact of power-splitting (PS), time-switching (TS) and signal-to-noise ratio (SNR) on the OP was as well investigated. Subsequently, the system performance of TSR, PSR and hybrid TSR-PSR schemes were compared. The simulation results are relatively accurate because they align well with the theory

MORE ENVIRONMENTAL FRIENDLY METHOD OF LEAD RECYCLING FROM WASTE BATTERY PASTE-AN ELECTROCHEMICAL INVESTIGATION

Joint Research on Environmental Science and Technology for the Eart

Level of Determinants Impact on Buyer’s Purchasing Intention in Motor Liability Insurance: Case of Vietnam

Motor liability insurance has been included in the compulsory insurance category that each vehicle owner of every type of motor vehicle must participate in in Vietnam. However, in fact, the participation in this type of insurance is not popular and not strictly managed. This paper presents an approach to modeling and analyzing the possible determinants that may affect the intention to buy motor liability insurance for motor vehicle owners in the North of Vietnam. The target audience of this study is motorcycle owners. Based on the theories of buying intention, buying behavior and the specific characteristics of this insurance, this study has proposed a model with 4 factors influencing intention to participate in the insurance: Attitudes towards risk and insurance, subjective standards, Insurance Perceptions, and Product Accessibility. Taken together, these factors model a consumer's tendency toward insurance intentions for motorbike owners. The results show that all of the above factors have influence on the intention of motorcycle owners to participate in insurance. Keywords: Motor liability insurance, Buying intention, Purchase decision DOI: 10.7176/EJBM/13-8-11 Publication date: April 30th 202

Enhancing light scattering effect of white LEDs with ZnO nanostructures

Pc-LEDs, the lighting method that blends blue LED light with yellow light from phosphor to discharge white radiation, is one of the most advance known for high lumen output. However, pc-LEDs has inferior due to angular CCT deviation, which prevent pc-LEDs from reaching better performance. As a result, this research is conducted to address the need of pc-LEDs development by introducing a configuration doped with ZnO nanoparticles. The finite-difference time-domain (FDTD) method and the phosphor layer containing ZnO were applied in the experiments. The effect of ZnO-filled on the performance of color quality pc-LEDs is confirmed through calculated results. In particular, the uniformity of scattered light is improved with the presence of ZnO. In addition, ZnO particles also minimize the deviation of color temperature and enhance the color quality. Although there is a small decline in lumen output to achieve better color temperature uniformity, however, with suitable concentrations such as 0.25% N-ZnO, 0.25% S-ZnO, and 0. 75% R-ZnO, the decline is acceptable. The research on ZnO pc-LEDs demonstrates that this affordable and simple configuration can improve lighting properties and create other directions to enhance white ligh

Clustering lifestyle risk behaviors among Vietnamese adolescents and roles of school : a Bayesian multilevel analysis of global school-based student health survey 2019

Background: Adolescence is a vulnerable period for many lifestyle risk behaviors. In this study, we aimed to 1) examine a clustering pattern of lifestyle risk behaviors; 2) investigate roles of the school health promotion programs on this pattern among adolescents in Vietnam. Methods: We analyzed data of 7,541 adolescents aged 13–17 years from the 2019 nationally representative Global School-based Student Health Survey, conducted in 20 provinces and cities in Vietnam. We applied the latent class analysis to identify groups of clustering and used Bayesian 2-level logistic regressions to evaluate the correlation of school health promotion programs on these clusters. We reassessed the school effect size by incorporating different informative priors to the Bayesian models. Findings: The most frequent lifestyle risk behavior among Vietnamese adolescents was physical inactivity, followed by unhealthy diet, and sedentary behavior. Most of students had a cluster of at least two risk factors and nearly a half with at least three risk factors. Latent class analysis detected 23% males and 18% females being at higher risk of lifestyle behaviors. Consistent through different priors, high quality of health promotion programs associated with lower the odds of lifestyle risk behaviors (highest quality schools vs. lowest quality schools; males: Odds ratio (OR) = 0·67, 95% Highest Density Interval (HDI): 0·46 – 0·93; females: OR = 0·69, 95% HDI: 0·47 – 0·98). Interpretation: Our findings demonstrated the clustering of specific lifestyle risk behaviors among Vietnamese in-school adolescents. School-based interventions separated for males and females might reduce multiple health risk behaviors in adolescence. Funding: The 2019 Global School-based Student Health Survey was conducted with financial support from the World Health Organization. The authors received no funding for the data analysis, data interpretation, manuscript writing, authorship, and/or publication of this article. © 2021 The Author(s

Machine Learning Models for Inferring the Axial Strength in Short Concrete-Filled Steel Tube Columns Infilled with Various Strength Concrete

Concrete-filled steel tube (CFST) columns are used in the construction industry because of their high strength, ductility, stiffness, and fire resistance. This paper developed machine learning techniques for inferring the axial strength in short CFST columns infilled with various strength concrete. Additive Random Forests (ARF) and Artificial Neural Networks (ANNs) models were developed and tested using large experimental data. These data-driven models enable us to infer the axial strength in CFST columns based on the diameter, the tube thickness, the steel yield stress, concrete strength, column length, and diameter/tube thickness. The analytical results showed that the ARF obtained high accuracy with the 6.39% in mean absolute percentage error (MAPE) and 211.31 kN in mean absolute error (MAE). The ARF outperformed significantly the ANNs with an improvement rate at 84.1% in MAPE and 65.4% in MAE. In comparison with the design codes such as EC4 and AISC, the ARF improved the predictive accuracy with 36.9% in MAPE and 22.3% in MAE. The comparison results confirmed that the ARF was the most effective machine learning model among the investigated approaches. As a contribution, this study proposed a machine learning model for accurately inferring the axial strength in short CFST columns

The impact of bank loan announcements on stock liquidity

We examine the impact of bank loan announcements on stock liquidity. Using a comprehensive loan announcement sample over 14 years in Australia, we find that effective spreads and realised spreads of borrowers' stocks fall after the announcements. The findings suggest these announcements send positive signals about borrowers to the market that increases liquidity provision, and reduce transaction costs, leading to improved liquidity for borrowers’ stocks. This liquidity improvement is more pronounced following announcements of new loans than loan renewals. Overall, our findings provide practical implications for firm managers in the financing decision-making process and market participants in trading strategy adjustment

Quality of Life and Suitability with Vietnamese Harmonious Face Index in Class III Malocclusion Patients

BACKGROUND: Maxillary Lefort I osteotomy, mandibular bilateral sagittal split ramus was frequently used in correcting skeletal class III malocclusion. There was a lack of research on class III malocclusion patients’ quality of life (QoL) after bimaxillary osteotomy. AIM: Class I Intermaxillary relationship was achieved, aesthetic was significantly improved. Significant improvement in Class III skeletal patients’ quality of life was acquired. The achievement of harmonious face would be beneficial to the facial aesthetics of patients, thus improving the quality of life. METHODS: Harmonious face index is an effective criterion in assessing the surgery’s outcome. In this study was conducted on 30 patients at Hanoi National Hospital of Odontostomatology, Viet Duc Hospital, and Hong Ngoc Hospital from April 2017 to April 2018, and it was a quasi-experimental study with self-comparison, 12 months follow up. RESULTS: Orthognathic surgery effectively corrected malocclusion crossbite, dental compensation, and helped to improve facial aesthetics. 100% of patients had the quality of life improved, good quality of life consisted of 86.7%. In comparison with a harmonious facial index of Kinh ethnic in Vietnam, 70% of patients achieved skeletal harmony, 63.3% of patients achieved dental harmony, 80% achieved soft tissue harmony. CONCLUSIONS: Vietnamese harmonious facial index should be used in planning and pre-surgical simulatio