Tho T. Quan

Tho T. Quan
Ho Chi Minh City University of Technology (HCMUT) | HCMUT · Department of Software Engineering

About

173
Publications
26,290
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
1,511
Citations
Citations since 2017
84 Research Items
715 Citations
2017201820192020202120222023050100150
2017201820192020202120222023050100150
2017201820192020202120222023050100150
2017201820192020202120222023050100150

Publications

Publications (173)
Article
Full-text available
5G is the fifth generation of cellular networks and has been used in a lot of different areas. 5G often requires sudden rises in power consumption. To stabilize the power supply, a 5G system requires a lithium-ion battery (LIB) or a mechanism called AC main modernization to provide energy support during the power peak periods. The LIB approach is t...
Conference Paper
Abstract—The importance of online social networks (OSNs) has been fueled by the human need for digital communication and broadcasting, as well as the improved state of internet connections and electronic devices. Meanwhile, social bots have been designed to automatically replicate the behavior of legitimate users in order to manipulate these OSNs....
Article
Natural Language Processing (NLP) is one of the major branches in the emerging field of Artificial Intelligence (AI). Classical approaches in this area were mostly based on parsing and information extraction techniques, which suffered from great difficulty when dealing with very large textual datasets available in practical applications. This issue...
Conference Paper
For humans, the COVID-19 pandemic and Coron- avirus have undeniably been a nightmare. Although there are effective vaccines, specific drugs are still urgent. Normally, to identify potential drugs, one needs to design and then test interactions between the drug and the virus in an in silico manner for determining candidates. This Drug-Target Interac...
Chapter
Nowadays, with the undeniable development of 5G technologies, Advanced Artificial Intelligence (AAI) systems using IoT sensors have been widely deployed in many different applications. The emerging requirement on these platforms is the identification of real situations (or contexts) based on time-series information given by sensors, which are ideal...
Chapter
Speech synthesis, which aims to generate natural and comprehensible speech from input text, is a popular research topic with a wide range of industrial applications. However, it appears to be a difficult problem due to its strong dependency on data, particularly for accent-sensitive and multi-dialect languages, e.g. Vietnamese. Perhaps the most com...
Chapter
Covid-19 is a global disaster that needs computing power to analyze, predict and interpret. So far, there have been several models doing the job. With a huge amount of daily data, deep learning models can be trained to achieve highly accurate forecasts but their mechanism lacks explainability. Epidemiological models, e.g. SIR, on the other hand, ca...
Article
Full-text available
Hydrological drought forecasting is a key component in water resources modeling as it relates directly to water availability. It is crucial in managing and operating dams, which are constructed in rivers. In this study, multiple extreme learning machines (ELMs) are utilized to forecast hydrological drought. For this purpose, the standardized hydrol...
Article
In the current era, the amount of information from the Internet in general and the electronic press in particular has increased rapidly and has extremely useful information value in all aspects of life, many popular users have posted several high-quality writings as casual blogs, notes or reviews. Some of them are even selected by editors to be pub...
Article
Full-text available
From the end of 2019, one of the most serious and largest spread pandemics occurred in Wuhan (China) named Coronavirus (COVID-19). As reported by the World Health Organization, there are currently more than 100 million infectious cases with an average mortality rate of about five percent all over the world. To avoid serious consequences on people’s...
Chapter
With the rapid development of social media channels, many popular users have posted several high-quality writings as casual blogs, notes or reviews. Some of them are even selected by editors to be published in professional venues. However, the original posts often come without titles, which are needed to be manually added by the editing teams. This...
Article
Full-text available
In recent years, lithium-ion batteries (LIB) have been used widely in portable electronic devices because of their advantages of durability, stability, high-capacity, low-cost, light-weight and smallscale. It makes LIB also deployed in various complex systems, in which efficient prediction of battery data, especially state-of-health (SoH), becomes...
Chapter
Full-text available
State-of-Health (SOH) prediction of a Lithium-ion battery is essential for preventing malfunction and maintaining efficient working behaviors for the battery. In practice, this task is difficult due to the high level of noise and complexity. There are many machine learning methods, especially deep learning approaches, that have been proposed to add...
Preprint
Recently, Transformer-based models have been proven effective in the abstractive summarization task by creating fluent and informative summaries. Nevertheless, these models still suffer from the short-range dependency problem, causing them to produce summaries that miss the key points of document. In this paper, we attempt to address this issue by...
Article
Full-text available
This study examines rainfall forecasting for the Perfume (Huong) River basin using the machine learning method. To be precise, statistical measurement indicators are deployed to evaluate the reliability of the actual accumulated data. At the same time, this study applied and compared two popular models of multi-layer perceptron and the k -nearest n...
Article
Wireless sensor networks (WSNs) are important tools to monitor various events happening in specific environments. In WSNs, regarding the network size and number of sensor nodes, several mobile sink nodes can be used to collect the monitored data. In such cases, having a clustered WSN helps to get the sensed data more efficiently to the sink nodes....
Chapter
Non-dominated sorting genetic algorithm II (NSGA-II) is introduced as a powerful variant of genetic algorithm because it alleviates computational complexity and removes sharing parameter in comparing to other multiobjective evolutionary algorithms (MOEAs). Master-slave, island model and diffusion model are three approaches to parallel MOEAs. Howeve...
Preprint
Full-text available
From the end of 2019, one of the most serious and largest spread pandemics occurred in Wuhan (China) named Coronavirus (COVID-19). As reported by the World Health Organization, there are currently more than 100 million infectious cases with an average mortality rate of about five percent all over the world. To avoid serious consequences on people’s...
Article
Full-text available
Most of the information on the Internet is represented in the form of microtexts, which are short text snippets such as news headlines or tweets. These sources of information are abundant, and mining these data could uncover meaningful insights. Topic modelling is one of the popular methods to extract knowledge from a collection of documents; howev...
Article
The increasing number of security attacks have inspired researchers to employ various classifiers, such as support vector machines (SVMs), to deal with them in Intrusion detection systems (IDSs). This paper presents a comprehensive study and investigation of the SVM-based intrusion detection and feature selection systems proposed in the literature....
Article
Full-text available
Object coreference resolution is used in sentiment analysis to identify sentiment words referring to an aspect of an object in a document. However, this poses a challenge in natural language processing and is consequently an area of ongoing research. Further, to the best of our knowledge, object coreference resolution with more than one object has...
Conference Paper
The Unified Medical Language System, or UMLS, is a repository of medical terminology developed by the U.S. National Library of Medicine for improving the computer system’s ability of understanding the biomedical and health languages. The UMLS Metathesaurus is one of the three UMLS knowledge sources, containing medical terms and their relationships....
Chapter
Identification of license plates on intermodal containers (or containers) while entering and departing from the yard provides a wide range of practical benefits, such as organizing automatic opening of the rising arm barrier at the entrance and exit to and from the site. In addition, automatic container code recognition can also assist in thwarting...
Article
Full-text available
This paper discusses detection of brand crisis on online social media, i.e. when a brand is being suffered from unexpectedly high frequency of negative comments on online channels such as social networks, electronic news, blog and forum. In order to do so, we combined the usage of probabilistic model for burst detection with ontology-based aspect-l...
Article
Full-text available
A prosthesis is an equipment provided to people who lost one or some parts of their limbs to help them having almost normal behaviors in daily or hard activities. The convenience and intelligence of devices should create easiness and flexibility for users. Artificial devices require inter-disciplinary collaboration from neurosurgeons, surgical surg...
Preprint
Full-text available
Network alignment, the problem of identifying similar nodes across networks, is an emerging research topic due to its ubiquitous applications in many data domains such as social-network reconciliation and protein-network analysis. While traditional alignment methods struggle to scale to large graphs, the state-of-the-art representation-based method...
Article
Network alignment, the problem of identifying similar nodes across networks, is an emerging research topic due to its ubiquitous applications in many data domains such as social-network reconciliation and protein-network analysis. While traditional alignment methods struggle to scale to large graphs, the state-of-the-art representation-based method...
Article
Full-text available
Battery module safety is a major concern for the commercial success of electric vehicles (EVs). Concurrently, its also important to have a mechanically sound and ergonomically fit battery pack design. To solve this problem, a Hybrid Multi‐Output‐Predictive Modelling based NSGA II approach is proposed. In this approach, the multiple predictive model...
Article
Full-text available
Cloud-edge computing is a hybrid model of computing where resources and services provided via the Internet of Things (IoT) between large-scale and long-term data informs of the cloud layer and small-scale and short-term data as edge layer. The main challenge of the cloud service providers is to select the optimal candidate services that are doing t...
Article
Purpose This paper proposes an approach to identify categorical influencers (i.e. influencers is the person who is active in the targeted categories) in social media channels. Categorical influencers are important for media marketing but to automatically detect them remains a challenge. Design/methodology/approach We deployed the emerging deep lea...
Article
Full-text available
Author gender detection (AGD) is a serious and crucial issue in Internet security applications, in particular in email, messenger, and social network communications. Detecting the gender of communication partner helps preventing massive fraud and abuses happening through social media such as email, blogs, forums. Text and writings of people on the...
Chapter
Recommendation systems are powerful tools that can alleviate system overload problems by recommending the most relevant items (contents) to users. Recommendation systems allow users to find useful, interesting items from a significantly large space and also enhance the user’s browsing experience. Relevant items are determined by predicting user’s r...
Article
Full-text available
Automatic classification of virus instances into a concept hierarchy has been attracting much attention from malware research community. However, it is definitely not a trivial work, because malwares usually come in binary forms whose actions are complicated and obfuscated. Therefore, the typical data mining approaches based on feature extraction a...
Preprint
During the last two decades, we easilly see that the World Wide Web's link structure is modeled as the directed graph. In this paper, we will model the World Wide Web's link structure as the directed hypergraph. Moreover, we will develop the PageRank algorithm for this directed hypergraph. Due to the lack of the World Wide Web directed hypergraph d...
Conference Paper
Full-text available
A prosthesis is equipment provided to people who lost one or some parts of their limbs to help them having almost normal behaviors in daily or hard activities. Convenience and intelligence of devices should create easiness and flexibility for users. Artificial devices require interdisciplinary collaboration from neurosurgeons, surgical surgeons, ph...
Article
Aspect-based Opinion Summary (AOS), consisting of aspect discovery and sentiment classification steps, has recently been emerging as one of the most crucial data mining tasks in e-commerce systems. Along this direction, the LDA-based model is considered as a notably suitable approach, since this model offers both topic modeling and sentiment classi...
Preprint
Full-text available
Most of the information on the Internet is represented in the form of microtexts, which are short text snippets like news headlines or tweets. These source of information is abundant and mining this data could uncover meaningful insights. Topic modeling is one of the popular methods to extract knowledge from a collection of documents, nevertheless...
Article
Full-text available
Entity co-reference resolution and sentiment analysis are independent problems and popular research topics in the community of natural language processing. However, the combination of those two problems has not been getting much attention. Thus, this paper susgests to apply knowledge base to solve co- reference between object and aspect with sentim...
Preprint
Aspect-based Opinion Summary (AOS), consisting of aspect discovery and sentiment classification steps, has recently been emerging as one of the most crucial data mining tasks in e-commerce systems. Along this direction, the LDA-based model is considered as a notably suitable approach, since this model offers both topic modeling and sentiment classi...
Article
Full-text available
Social media channels such as social networks, forum or online blogs have been emerging as major sources from which brands can gather user opinions about their products, especially the negative mentions. This kind of task, popular known as sentiment analysis, has been addressed recently by many deep learning approaches. However, negative mentions o...
Conference Paper
Chi giả (tay hoặc chân giả) là thiết bị được cung cấp cho người khuyết tật bị mất một phần chi, giúp họ có được hoạt động gần như bình thường qua hoạt động hằng ngày hoặc các hoạt động gắng sức. Chi giả càng được cải tiến tiện lợi và thông minh thì con người càng dễ điều khiển và hoạt động của họ càng linh hoạt. Việc sản xuất và phát triển chi giả...
Article
Full-text available
Sentiment analysis has been emerging recently as one of the major natural language processing (NLP) tasks in many applications. Especially, as social media channels (e.g. social networks or forums) have become significant sources for brands to observe user opinions about their products, this task is thus increasingly crucial. However, when applied...
Article
Nowadays, learning activities at universities in Vietnam are mostly in the form of credit-based mode. That is, to graduate students have to complete the subjects specified in the curriculum including the compulsory and optional ones. Therefore, to achieve their best performance, students would need guidelines on study direction in the compulsory su...
Conference Paper
Early detection and prediction of cardiac anomalies play an important role in the diagnosis and treatment of car- diovascular diseases. In medicine, electrocardiography provides valuable information for the doctors since they can accurately determine what is happening concerning the heart activities. Nevertheless, electrocardiography classification...
Conference Paper
Full-text available
This paper proposes an auto-pricing system, known as Fast-and-Fit. This system is intended for travel online agencies, who always aim at varying the ticket prices to optimize the possible revenue. This system is developed based on the two following intelligent techniques. Firstly, a pattern mining algorithm is deployed to quickly identify flight ro...
Preprint
Keyword-based information processing has limitations due to simple treatment of words. In this paper, we introduce named entities as objectives into document clustering, which are the key elements defining document semantics and in many cases are of user concerns. First, the traditional keyword-based vector space model is adapted with vectors defin...
Preprint
Early detection and prediction of cardiac anomalies play an important role in the diagnosis and treatment of cardiovascular diseases (CVD). In medicine, electrocardiography (ECG or EKG) is valuable information for every doctor since they can accurately determine what is happening to heart activities. Nevertheless, ECG classification is a non-trivia...
Preprint
Early detection and prediction of cardiac anomalies play an important role in the diagnosis and treatment of cardiovascular diseases (CVD). In medicine, electrocardiography (ECG or EKG) is valuable information for every doctor since they can accurately determine what is happening to heart activities. Nevertheless, ECG classification is a non-trivia...
Article
To date, industrial antivirus tools are mostly using signature-based methods to detect malware occurrences. However, sophisticated malware, such as metamorphic or polymorphic virus, can effectively evade those tools by using some advanced obfuscation techniques, including mutation and the dynamically executed contents (DEC) methods, which dynamical...
Article
Recently, web service composition (WSC) has been widely emerging since it is obviously hopeless to develop a specific web service which can singlehandedly fulfil completely a requirement posed by clients. Moreover, as a WSC solution often needs to satisfy various kinds of constraints, its correctness is also required to be formally verified. Howeve...
Article
In the past, many dimensional reduction methods such as Local Linear Embedding (LLE) and Laplacian Eigenmaps (LE) have been successfully developed. However, in many real world applications, representing the dataset as un-directed graph, used in Laplacian Eigenmaps and Local Linear Embedding methods, is not complete. Approximating complex relationsh...
Conference Paper
To date, entity coreference resolution and sentiment analysis still exist as independent problems, but they are both popular research topics in the community of natural language processing. However, the combination of those two problems. even though very potentially useful, has not been getting much attention. This paper addresses this issue by pro...
Conference Paper
Malware applies lots of obfuscation techniques, which are often automatically generated by the use of packers. This paper presents a packer identification of packed code based on metadata signature, which is a frequency vector of occurrences of classified obfuscation techniques. First, BE-PUM (Binary Emulator for PUshdown Model generation) disassem...
Conference Paper
Full-text available
The emerging technique of deep learning has been widely applied in many different areas. However, when adopted in a certain specific domain, this technique should be combined with domain knowledge to improve efficiency and accuracy. In particular, when analyzing the applications of deep learning in sentiment analysis, we found that the current appr...
Conference Paper
Most of modern malware are packed by packers to evade the anti-virus software. Basically, packers will apply various obfuscating techniques to hide their true behaviors from static analysis methods. Thus, how to deal with packed malware has always been a tough problem so far. This paper proposes a novel approach for packer detection using a combina...
Conference Paper
Explosion of information and communication technologies providing worldwide connection through the Internet as well as the unstoppable development of technology is transforming how development is done locally and globally. Blockchain technology aims to build applications based on decentralized architecture, in which has received extensive attention...
Article
Automatic classification of virus samples into a concept hierarchy has been attracting much attention from malware research community. This would help anti-virus experts to have an obvious and systematic view on the landscape of virus samples, whose numbers have been rapidly increasing recently. However, it is not a trivial work, since malwares usu...
Article
Purpose Service-Oriented Architecture (SOA) is an emerging software architecture, in which web service (WS) plays a crucial role. In this architecture, the task of web service composition and verification is required when handling complex requirement of services from users. When the number of WS becomes very huge in practice, the complexity of the...