Factors Determining of Dropping Out from Treatment Among Methadone Clients: A Qualitative Study in Can Tho City, VietNam

Methadone maintenance therapy has been a main pillar of harm reduction for people who injecting drug user in VietNam as well as in Can Tho. Dropout rate has indicated to be high in Can Tho city. Methadone maintenance has been offered since 2008 in VietNam and it implemented in Can Tho since 2010; however, its dropout rate is high. This study aim at exploring the factors related to drop out from treatment. Qualitative conducted to interview 17 methadone clients for both drop out clients and current on treatment clients; 4 health workers and 3 family members of clients. The barriers to stay longer on treatment which included: individual factors, community factors and institutional factors. This study suggests that increasing meaningful involvement of family’s clients, strengthening counselling session on adherence for client

Analysis and Simulation of MRC Diversity Reception in Correlated Composite Nakagami-Lognormal Fading Channels

The physical meaning of the composite Nakagami-lognormal fading model is not well understood by many researchers using the model. The signal power transfer and transform at the interface between the global lognormal shadowing sub-channels and the local Nakagami multipath sub-channels in the presence of correlation between these diversity sub-channels is rather complex. This is the main reason why a thorough analysis or a simulation model is absent to date for the case of correlated composite Nakagami-lognormal diversity channels. This paper presents a novel technique for the estimation of the probability density function (PDF) of the signal-to-noise (SNR) at the output of a maximum ratio combining (MRC) receiver operating in correlated composite diversity fading channels. The PDF is estimated using the recently proposed two-point lossless moment generating function (MGF) matching technique and a closed-form expression for the bit-error rate (BER) for QPSK signal is consequently presented using the Gauss-Hermite polynomial approximation. The paper also presents the complex Monte-Carlo simulation model for the MRC reception and BER counting in correlated composite Nakagami-lognormal fading channels

The Intention to Participate in Voluntary Social Insurance of Informal Sector Workers: the Case in Mekong Delta, Vietnam

Purpose: The objective of this study is to develop the participation of informal sector workers in voluntary social insurance to ensure the Social Security policy of the Government of Vietnam.   Theoretical Framework: Based on the results compiled from expert as: Kotler, 2003; Schiffman and Kanuk, 2007; Ming-Chi Lee, 2009; Holmgren et al., 2016 and Krajaechun and Praditbatuga, 2019. The model was preliminarily designed by the author through eight prefix variables including: Confidence in Benefits, Evaluation of Social Responses, Perception of risks, Beliefs, Motivation, Attitude towards Voluntary social insurance, Subjective norms, and Intention to participate in Voluntary social insurance.   Methodology: This study employs primary data from a survey of 370 people working in informal workers in 04 province of the Mekong Delta region of Vietnam: Kien Giang Province, Tra Vinh Province, Hau Giang Province and Soc Trang Province. The Authors using Partial Least Squares-Structural Equation Modeling (PLS-SEM) and Bootstrap analysis in the SEM reliability test employed for data analysis and interpretation.   Findings: Research results show that two factors that affect the intention to participate in voluntary social insurance of workers in the informal sector: Attitude towards social insurance and subjective norms.   Solutions: From the research results, the authors have proposed solutions to further improve the participation in voluntary social insurance of workers in the informal sector in the Mekong Delta, Vietnam in future

Optimal Design of V-Shaped Fin Heat Sink for Active Antenna Unit of 5G Base Station

The active antenna unit (AAU) is one of the main parts of the 5G base station, which has a large size and a high density of chipsets, and operates at a significantly high temperature. This systematic study presents an optimal design for the heat sink of an AAU with a V-shaped fin arrangement. First, a simulation of the heat dissipation was conducted on two designs of the heat sink – in-line and V-shaped fins – which was validated by experimental results. The result shows that the heat sink with V-shaped fins performed better compared to conventional models such as heat sinks with in-line fins. Secondly, computational fluid dynamics (CFD) and the Lagrange interpolation method were applied to find out an optimal set of design parameters for the heat sink. It is worth noting that the optimal parameters of the orientation angle and fin spacing considerably affected the heat sink’s performance.  

Optimal Design of V-Shaped Fin Heat Sink for Active Antenna Unit of 5G Base Station

The active antenna unit (AAU) is one of the main parts of the 5G base station, which has a large size and a high density of chipsets, and operates at a significantly high temperature. This systematic study presents an optimal design for the heat sink of an AAU with a V-shaped fin arrangement. First, a simulation of the heat dissipation was conducted on two designs of the heat sink – in-line and V-shaped fins – which was validated by experimental results. The result shows that the heat sink with V-shaped fins performed better compared to conventional models such as heat sinks with in-line fins. Secondly, computational fluid dynamics (CFD) and the Lagrange interpolation method were applied to find out an optimal set of design parameters for the heat sink. It is worth noting that the optimal parameters of the orientation angle and fin spacing considerably affected the heat sink’s performance.  

Network-Aided Intelligent Traffic Steering in 6G O-RAN: A Multi-Layer Optimization Framework

To enable an intelligent, programmable and multi-vendor radio access network (RAN) for 6G networks, considerable efforts have been made in standardization and development of open RAN (O-RAN). So far, however, the applicability of O-RAN in controlling and optimizing RAN functions has not been widely investigated. In this paper, we jointly optimize the flow-split distribution, congestion control and scheduling (JFCS) to enable an intelligent traffic steering application in O-RAN. Combining tools from network utility maximization and stochastic optimization, we introduce a multi-layer optimization framework that provides fast convergence, long-term utility-optimality and significant delay reduction compared to the state-of-the-art and baseline RAN approaches. Our main contributions are three-fold: i) we propose the novel JFCS framework to efficiently and adaptively direct traffic to appropriate radio units; ii) we develop low-complexity algorithms based on the reinforcement learning, inner approximation and bisection search methods to effectively solve the JFCS problem in different time scales; and iii) the rigorous theoretical performance results are analyzed to show that there exists a scaling factor to improve the tradeoff between delay and utility-optimization. Collectively, the insights in this work will open the door towards fully automated networks with enhanced control and flexibility. Numerical results are provided to demonstrate the effectiveness of the proposed algorithms in terms of the convergence rate, long-term utility-optimality and delay reduction.Comment: 15 pages, 10 figures. A short version will be submitted to IEEE GLOBECOM 202