Addressing practical challenges of Bayesian optimisation

This thesis focuses on addressing several challenges in applying Bayesian optimisation in real world problems. The contributions of this thesis are new Bayesian optimisation algorithms for three practical problems: finding stable solutions, optimising cascaded processes and privacy-aware optimisation

The Current Status of Historical Preservation Law in Regularory Takings Jurisprudence: Has the Lucas Missile Dismantled Preservation Programs?

This paper describes our NIHRIO system for SemEval-2018 Task 3 "Irony detection in English tweets". We propose to use a simple neural network architecture of Multilayer Perceptron with various types of input features including: lexical, syntactic, semantic and polarity features.  Our system achieves very high performance in both subtasks of binary and multi-class irony detection in tweets. In particular, we rank at fifth in terms of the accuracy metric and the F1 metric. Our code is available at: https://github.com/NIHRIO/IronyDetectionInTwitte

Sentiment classification on polarity reviews: an empirical study using rating-based features

We present a new feature type named rating-based feature and evaluate the contribution of this feature to the task of document-level sentiment analysis. We achieve state-of-the-art results on two publicly available standard polarity movie datasets: on the dataset consisting of 2000 reviews produced by Pang and Lee (2004) we obtain an accuracy of 91.6% while it is 89.87% evaluated on the dataset of 50000 reviews created by Maas et al. (2011). We also get a performance at 93.24% on our own dataset consisting of 233600 movie reviews, and we aim to share this dataset for further research in sentiment polarity analysis task

VnCoreNLP: A Vietnamese Natural Language Processing Toolkit

We present an easy-to-use and fast toolkit, namely VnCoreNLP---a Java NLP annotation pipeline for Vietnamese. Our VnCoreNLP supports key natural language processing (NLP) tasks including word segmentation, part-of-speech (POS) tagging, named entity recognition (NER) and dependency parsing, and obtains state-of-the-art (SOTA) results for these tasks. We release VnCoreNLP to provide rich linguistic annotations to facilitate research work on Vietnamese NLP. Our VnCoreNLP is open-source and available at: https://github.com/vncorenlp/VnCoreNLPComment: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, NAACL 2018, to appea

Simulation of Storm Surges in the South Central Coast of Vietnam Under Climate Change

The research was supported by National Research Project Program of Vietnam: science and technology in response to climate change, natural resources and environmental management in the 2016-2020 period (program number: BĐKH/16-20), Developing a sustainable socio-economic model adapting to extreme natural disasters under climate change in the South Central region of Viet Nam. A case study of Ninh Thuan province (grant number: BĐKH.04/16-20). Abstract This paper presents the results of storm surge simulation in the South Central region of Vietnam using the Mike 21-FM HD model. Wind pressure fields of typical storms were first identified in period of 1986-2005 using the parametric wind field model. Storm surge risk was then simulated based on the rare 10, 50 and 100-year frequency corresponding to 2030, 2050, and 2100 scenarios. Storm surge model was finally calibrated and validated using the level of water measured in the November 2009 Typhoon Mirinae and October 2013 Typhoon Nari. The results show that storm surges were consistent with water level variation and amplitude; the maximum and minimum storm surges were 2.34m in the Binh Thuan coastal area and 0.78m in the Khanh Hoa coastal area, respectively. The results of this study demonstrated the use of MIKE 21-FM HD model for the simulation of storm surges in the future plays an important role in damage risk reduction caused by storm surges. Keywords: storm surge simulation, climate change, Mike 21-FM HD model, South Central coast of Vietnam. DOI: 10.7176/JEES/9-6-08 Publication date:June 30th 201

Multiobjective Logistics Optimization for Automated ATM Cash Replenishment Process

In the digital transformation era, integrating digital technology into every aspect of banking operations improves process automation, cost efficiency, and service level improvement. Although logistics for ATM cash is a crucial task that impacts operating costs and consumer satisfaction, there has been little effort to enhance it. Specifically, in Vietnam, with a market of more than 20,000 ATMs nationally, research and technological solutions that can resolve this issue remain scarce. In this paper, we generalized the vehicle routing problem for ATM cash replenishment, suggested a mathematical model and then offered a tool to evaluate various situations. When being evaluated on the simulated dataset, our proposed model and method produced encouraging results with the benefits of cutting ATM cash operating costs