Cash holding, state ownership and firm value: The case of Vietnam

Using a sample of 650 listed firms on the Vietnamese stock exchange over the period 2008-2015, we examine the effect of cash holding level on firm value. The results find out the cash holding has an impact on firm value in an inverted U-shaped form. Furthermore, this study investigates whether the state ownership influences firm value. We point out that there is a statistically insignificant positive relationship between state ownership and firm value unless the state ownership’s advantages are utilized. The findings have implications of cash management in state-owned firms. © 2016, Econjournals. All rights reserved

The ideology of “taking people as the root” of the Ly dynasty in Vietnam

Ideology is always an issue that plays an important role in the life of a society, and that ideology also greatly influences the process of ruling the country of dynasties in the history. Unlike previous dynasties, which lasted only a few decades, the Ly dynasty represents a flourishing period of feudalism lasting more than 200 years. A major event was that King Ly Thanh Tong changed the country name from Dai Co Viet to Dai Viet in 1054, ushering in a brilliant era in Vietnamese history. The ideology of “taking people as the root” of Vietnamese feudal dynasties highlights the unyielding and indomitable fighting spirit for the right to enjoy independence and freedom in the old land of Giao Chi and Cuu Chan, which later was Dai Viet and is now Vietnam. It also reflects the desire for people to live in peace and harmony. This articles focuses on studying the ideology of “taking people as the root” through the reign of kings of the Ly dynasty in Vietnam. From there, the article points out the achievements and limitations in the process of taking care of people, as well as historical lessons for the development of the country today

Uso de variables de mercado en la predicción de dificultades financieras para las empresas que cotizan en Vietnam

This paper aims to investigate the classification power of market variables as predictors in the financial distress prediction model for listed companies in a frontier market as Vietnam securities market. Data is collected from 70 financially distressed companies that suffer a loss in 3 consecutive years and 156 non-financially distressed companies in Vietnam from 2010 to 2017. Four different models have been constructed using Logit regression and SVM analysis technique to make a prediction in 1 to 3-year ahead. The analysis results show that combining accounting ratios with market variables such as price volatility and P/E can improve the classification ability of the ex-ante model. In addition, contrary to the results of related previous researches in emerging markets, in this study, Logit models outperform SVM models. Therefore, for future research, models that apply other machine learning classifiers such as Decision Tree (DT) or Neural Network (NN) should be investigated.Este artículo tiene como objetivo investigar el poder de clasificación de las variables del mercado como factores predictivos en el modelo de predicción de dificultades financieras para las empresas que cotizan en bolsa en un mercado fronterizo como el mercado de valores de Vietnam. Los datos se recopilan de 70 compañías con dificultades financieras que sufrieron una pérdida en 3 años consecutivos y 156 empresas sin dificultades financieras en Vietnam desde 2010 a 2017. Se han construido cuatro modelos diferentes utilizando regresión Logit y la técnica de análisis de SVM para hacer una predicción en 1 a 3 años por delante. Los resultados del análisis muestran que la combinación de ratios contables con variables de mercado como la volatilidad de los precios y el P / E puede mejorar la capacidad de clasificación del modelo ex ante. Además, a diferencia de los resultados de investigaciones anteriores relacionadas en mercados emergentes, en este estudio, los modelos Logit superan a los modelos SVM. Por lo tanto, para futuras investigaciones, se deben investigar los modelos que aplican otros clasificadores de aprendizaje automático, como el Árbol de decisiones (DT) o la Red neuronal (NN)

Overlapping community detection algorithms using Modularity and the cosine

The issue of network community detection has been extensively studied across many fields. Most community detection methods assume that nodes belong to only one community. However, in many cases, nodes can belong to multiple communities simultaneously.This paper presents two overlapping network community detection algorithms that build on the two-step approach, using the extended modularity and cosine function. The applicability of our algorithms extends to both undirected and directed graph structures. To demonstrate the feasibility and effectiveness of these algorithms, we conducted experiments using real data

An improvement on the Louvain algorithm using random walks

We will present improvements to famous algorithms for community detection, namely Newman's spectral method algorithm and the Louvain algorithm. The Newman algorithm begins by treating the original graph as a single cluster, then repeats the process to split each cluster into two, based on the signs of the eigenvector corresponding to the secondlargest eigenvalue. Our improvement involves replacing the time-consuming computation of eigenvalues with a random walk during the splitting process. The Louvain algorithm iteratively performs the following steps until no increase in modularity can be achieved anymore: each step consists of two phases, phase 1 for partitioning the graph into clusters, and phase 2 for constructing a new graph where each vertex represents one cluster obtained from phase 1. We propose an improvement to this algorithm by adding our random walk algorithm as an additional phase for refining clusters obtained from phase 1. It maintains a complexity comparable to the Louvain algorithm while exhibiting superior efficiency. To validate the robustness and effectiveness of our proposed algorithms, we conducted experiments using randomly generated graphs and real-world data

The Impact of Education on Child Abuse Prevention

This research investigates the impact of education on child abuse prevention in Vietnam by using Vietnamese government's reports (2012 – 2019) on child abuse. In order to analyze the impact of education on child abuse prevention, this study focuses on reviewing the previous policies in preventing child abuse, surveying three main determinants of parents, teachers and children and testing the data collected from the survey. The result shows that education plays an important role in improving the ability to take actions against child abuse. Some recommendations to parents, teachers, children and the government are also proposed for encouraging improvements in child abuse prevention education. Keywords: Child Abuse Prevention, Education, Vietnam DOI: 10.7176/EJBM/12-20-09 Publication date:July 31st 202

SITUATION OF THE TEACHING PHYSICAL EDUCATION FOR SEVENTH GRADERS IN THAI NGUYEN CITY FROM THE PERSPECTIVE OF DIVISION IN EDUCATION

Differentiation-oriented physical education (PE) helps learners participate in learning activities with content and forms suitable to their personal characteristics. Through researching documents, interviews, and pedagogical observations, the project explores the current status of teaching physical education to 7th graders in Thai Nguyen City from the perspective of division in education. The results of this research are an important practical basis to propose measures to organize teaching physical education in a differentiated direction for 7th graders in Thai Nguyen City.  Article visualizations

Sustainability assessment of coastal ecosystems: DPSIR analysis for beaches at the Northeast Coast of Vietnam

The Northeastern coastal zone of Vietnam possesses high biodiversity and rich ecosystems like coral reefs, seagrasses, beaches and mangroves. It also includes the Ha Long Bay Natural Heritage site (UNESCO 1994) and the Cat Ba Biosphere Reserve (MAB/UNESCO 2004) as well as hosts the Economic Development Triangle (Hai Phong-Ha Noi-Quang Ninh) established by the Government of Vietnam. As one of the coastal ecosystems, sandy beach ecosystems attracted more attention during recent decades because of their essential role for human welfare and in environmental protection. A few studies concentrated on sustainable management of sandy beach based on environmental and ecological protection and enhance the beach quality for recreational use. The DPSIR (Driving force Pressure State Impact Response) framework describes the logical interaction among systems and finds out the cause and consequence of social-economic development activities to the environment and resources. In this study, the DPSIR was applied on the sandy beaches in the Northeastern coast of Vietnam to reveal the main environmental problems on sandy beaches including the decline of the natural landscape around the beaches and the degradation of the environment. It also pointed out that tourism development in association with urbanization and sea reclamation is the main driving forces for environmental degradation of the sandy beaches. Therefore, local authorities of Hai Phong and Quang Ninh should take into account several main responses to policies on inter-province coordination and managerial measures with a wider scope, which integrate socio-economic and physical factors, proximity, accessibility, and neighborhood to manage healthy coastal ecosystems and sandy beaches in particular. An integrated coastal management program for the Northeastern coast of Vietnam needs to be developed and carried out to follow the laws of Vietnam as well as to meet local urgent requirements

Performance Investigation of High-Speed Train OFDM Systems under the Geometry-Based Channel Model

The high-speed of train (HST) in combination with the high carrier frequency of HST systems leads to the severe inter carrier interference (ICI) in the HST orthogonal frequency division multiplexing (HST-OFDM) systems. To avoid the complexity in OFDM receiver design for ICI eliminations, the OFDM system parameters such as symbol duration, signal bandwidth, and the number of subcarriers should be chosen appropriately. This paper aims to propose a process of HST-OFDM system performance investigation to determine these parameters in order to enhance spectral efficiency and meet a given quality-of-service (QoS) level. The signal-to-­interference-­plus-­noise ratio (SINR) has been used as a figure of merit to analyze the system performance instead of signal-to-noise ratio (SNR) as most of recent research studies. Firstly, using the non-stationary geometry-based stochastic HST channel model, the SINR of each subcarrier has been derived for different speeds of the train, signal bandwidths, and number of subcarriers. Consequently, the system capacity has been formulated as the sum of all the single channel capacity from each sub-carrier. The constraints on designing HST-OFDM system parameters have been thoughtfully analyzed using the obtained expressions of SINR and capacity. Finally, by analyzing the numerical results, the system parameters can be found for the design of HST-OFDM systems under different speeds of train. The proposed process can be used to provide hints to predict performance of HST communication systems before doing further high cost implementations as hardware designs