Huong T. Bui

PurposeVietnam has repositioned itself from a war-torn country to a popular tourist destination. Although research on Vietnam tourism has grown in number, a macro analysis of national tourism governance and policies has largely been missing.Design/methodology/approachThis synthesis paper offers a systemic analysis of Vietnam’s tourism accommodating intensified government intervention and dramatic market changes in recent decades. The authors offer a chronological analysis of tourism development along with the major political and economic turns of the country.FindingsThe patterns of tourism development reflect a compromise between centralization and decentralization of the governance system and a trade-off between economic and social objectives of development. Balancing these opposites, the internal strength of the domestic market and the resilience of communities and businesses become key …

The development of robust and inexpensive catalysts for the electrochemical CO reduction reaction (CORR) is key for sustainable production of valuable chemicals, yet it remains a long-standing challenge. Herein, we conduct a systematic theoretical investigation on p-block doping of semi-metallic xene monolayers to afford transition metal free catalysts for the CORR. Silicene (Si) and germanene (Ge) are suitable platforms for capturing the dopant (B/Al) to ensure high stability. Our single atom catalysts (SACs) are promising candidates for CORR due to their favorable initial CO adsorption and the selectivity of CO reduction over H2 evolution. B@Si, Al@Si, Al@Ge and B@Ge exhibit superior CORR catalytic activity with a limiting potential UL of 0.04, −0.39, −0.40, and −0.40 V, respectively. Notably, B@Si is identified as the best CORR electrocatalyst with an overpotential of less than 0.1 V. B@Si, Al@Si, Al@Ge …

Herein, a stable and efficient CoS2-ReS2 electrocatalyst is successfully constructed by using the different molar ratios of CoS2 on ReS2. The size and morphology of the catalysts are significantly changed after the CoS2 is grown on ReS2, providing regulation of the catalytic activity of ReS2. Particularly, the optimized CoS2-ReS2 shows superior electrocatalytic properties with a low voltage of 1.48 V at 20 mA cm−2 for overall water splitting in 1.0 M KOH, which is smaller than the noble metal-based catalysts (1.77 V at 20 mA cm−2). The XPS, XAS, and theoretical data confirm that the interfacial regulation of ReS2 by CoS2 can provide rich edge catalytic sites, which greatly optimizes the catalytic kinetics and drop the energy barrier for oxygen/hydrogen evolution reactions. Our results demonstrated that interfacial engineering is an efficient route for fabricating high-performance water splitting electrocatalysts.

The mining of frequent weighted utility patterns (FWUPs) is an important task in the field of data mining that aims to discover frequent patterns from quantitative databases while taking into account the importance or weight of each item. Although there are many approaches that have been proposed to solve this problem, all of these methods focus on databases in which the weight of each item is fixed. In real-life situations, the weight of each item may change over time; for example, the weights of the products in a store may change every month, every quarter, or every year. This is an important aspect that previous studies have not considered. In this paper, we first introduce a new problem that involves mining FWUPs with dynamic weighted items from quantitative databases (called dynamic quantitative databases, dQDBs). Following this, we propose an algorithm called dFWUT that uses a tidset data structure to solve …

Mountain peaks are a major target for nature-based tourism (NBT). This chapter investigates past and present Mount Fuji climbers to re-design experiences that use historical elements of pilgrimage to moderate contemporary peak-bagging trends. The literature review offers a framework to contrast ‘pilgrims’ and ‘peak-baggers’ in the context of contemporary NBT motivations. Our case study combines ethnographic and historical analyses with visitor surveys to triangulate findings from primary and secondary data. Fuji’s ‘worship ascent’ offers not only a legacy of pilgrims’ past heritage but also a means to reimagine current climber experience along a more sustainable trajectory at one of the world’s most accessible peaks. Findings show that few of the contemporary climbers recognize the sacred rites of their pilgrim predecessors, instead seeking to summit quickly without following Shugendō customs such as pre …

Nowadays, air pollution is a big environmental problem in developing countries. In this problem, particulate matter 2.5 (PM2. 5) in the air is an air pollutant. When its concentration in the air is high in developing countries like Vietnam, it will harm everyone’s health. Accurate prediction of PM2. 5 concentrations can help to make the correct decision in protecting the health of the citizen. This study develops a hybrid deep learning approach named PM25-CBL model for PM2. 5 concentration prediction in Ho Chi Minh City, Vietnam. Firstly, this study analyzes the effects of variables on PM2. 5 concentrations in Air Quality HCMC dataset. Only variables that affect the results will be selected for PM2. 5 concentration prediction. Secondly, an efficient PM25-CBL model that integrates a convolutional neural network (CNN) and Bidirectional Long Short-Term Memory (Bi-LSTM) is developed. This model consists of three following modules: CNN, Bi-LSTM, and Fully connected modules. Finally, this study conducts the experiment to compare the performance of our approach and several state-of-the-art deep learning models for time series prediction such as LSTM, Bi-LSTM, the combination of CNN and LSTM (CNN-LSTM), and ARIMA. The empirical results confirm that PM25-CBL model outperforms other methods for Air Quality HCMC dataset in terms of several metrics including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE).

Mining patterns that satisfy both frequency and utility constraints is an interesting problem in data mining. Currently, there are two main approaches to solving this problem: the first considers these two factors separately (skyline frequent-utility patterns), and the second combines these two factors to form a composite measure (frequent weighted utility patterns). In the second approach, the weighted utility support (wus), which represents the percentage occupancy of the total weighted utility of all transactions in a quantitative database, is used. This approach has the advantage of satisfying the downward-closure property, so it is easy to implement divide-and-conquer and pruning strategies on the candidate search space, as shown by algorithms such as MWIT-FWUI, MBiS-FWUI, and WUN-Miner. This study proposes an SWUN-list structure, a shortened version of the N-list structure, to effectively represent and mine …

Mining frequent weighted utility patterns (FWUPs) is an important activity in data mining to discover frequent patterns from quantitative databases with considering the weight (mean the importance) of each item. In practical, the weight of each item in a database may varies with time. For example, the weights of the products in a store may change by each month, each quarter, or each year. Therefore, this paper will concern with that issue. At first, we introduce a new problem of mining FWUPs with the dynamic weighted items in the quantitative databases (called dynamic quantitative databases - dQDB). Then, we propose an algorithm named dFWUT using Tidset data structure to solve this problem. Finally, some experiments were conducted to compare the proposed algorithm with a modification of WUN-Miner (denoted by WUN-Miner-Mod), a state-of-the-art algorithm for mining FWUPs in dQDB, in terms of time and …