Hai V. Pham

Hanoi University of Science and Technology · School of Information Technology and Communication

Fuzzy Knowledge Graph (FKG) has recently been emerging as one of the key techniques for supporting classification and decision-making problems. FKG is a novel concept that was firstly introduced in 2020 by integrating approximate reasoning with inference mechanism to find labels of new records, which are impossible for inference by the rule base. H...

With the prosperity of social networks, Influence maximization is a crucial analysis drawback within the field of network science due to its business value. In this regard, we propose the EAVoteRank++, inspired by VoteRank++, to iteratively select the influential node. It is commonly recognized that degree is a well-known centrality metric for iden...

This paper presents a deep reinforcement learning AI that uses sound as the input on the DareFightingICE platform at the DareFightingICE Competition in IEEE CoG 2022. In this work, an AI that only uses sound as the input is called blind AI. While state-of-the-art AIs rely mostly on visual or structured observations provided by their environments, l...

Identifying influential nodes has great theoretical and practical implications in real-world scenarios such as search engines, social networks, and recommendation systems. Among the most essential issues in the field of complicated networks. Many approaches have been developed and deployed that have proven to be as effective as the gravity model. H...

Evaluation of E-Learning resources plays a significant role in the context of pedagogic systems. Resource evaluation is important in both conventional ‘talk-and-chalk’ teaching and in blended learning. In on-line (e-learning) teaching [an enforced feature of pedagogic systems in tertiary education during the Covid-19 pandemic] the effective evaluat...

Precipitation nowcasting is one of the main tasks of weather forecasting that aims to predict rainfall events accurately, even in low-rainfall regions. It has been observed that few studies have been devoted to predicting future radar echo images in a reasonable time using the deep learning approach. In this paper, we propose a novel approach, Rain...

Periapical Inflammation (PI) is one of the most popular diseases in adults due to complication of endodontitis or dental trauma with corresponding consequences to quality-of-life like tiredness and signs of infection. Specifically, patients having severe PI are often tiredness and high fever accompanied by signs of infection such as dry lips, dirty...

Group Decision-Making techniques have been applied to combine a group of decision maker’s preferences to deal with an evaluation of alternatives in a static environment. However, these conventional techniques are only concerned with an evaluation in a static environment. They cannot solve the policy evaluation problems in a dynamic environment or u...

Conventional methods used in brain tumors detection, diagnosis, and classification such as magnetic resonance imaging and computed tomography scanning technologies are unbridged in their results. This paper presents a proposed model combination, convolutional neural networks with fuzzy rules in the detection and classification of medical imaging su...

Deep learning methods predicated on convolutional neural networks and graph neural networks have enabled significant improvement in node classification and prediction when applied to graph representation with learning node embedding to effectively represent the hierarchical properties of graphs. An interesting approach (DiffPool) utilises a differe...

The next generation of E-Government and healthcare has the potential to increase the more intelligent governance with improvements in transparency, accountability, efficiency, and effectiveness. It enables organizations to use the benefits of information via big data analysis to settle the difficulties effectively. Big Data has emerged which plays...

Digital transformation is a long process that changes the managing human profiles in both offline and online approaches. This generates the amount of huge data stored in both relational databases and many others like social networks or graph databases. To exploit effectively big data, several measures and algorithms in Picture Fuzzy Graph (PFG) are...

Recently, many investigations focus on studying to detect of forest fires using IoT devices such as remote sensors or conventional fire detector sensors. However, supports in fire forest in real-time are hard for current studies in large forests. This paper has presented a novel approach to forest fire detection implemented using an improved rule-b...

Recently, by the explosion of information technology, the valuable and available data exponentially increases in various social media platforms which allow us to exploit and attain convenient information and transform it into knowledge. This means that prominent topics are extracted on time in the social media community by leveraging the proper tec...

Recently, social networks play significant roles in real-time content analysis. Many studies have investigated social networks by analysis of contents based on users. However, these studies have some limitations of social network analysis while clustering contents based on users’ behavior. The paper has presented the Hybrid Louvain-Clustering model...

This article describes how the objective of recent advances in soft computing and machine learning models is the resolution of issues related to security monitoring for information systems. Most current techniques and models face significant limitations, in the monitoring of information systems. To address these limitations, the authors propose a n...

In the original article, family name of one of the co-authors (Duong Thi Thu Huyen) has been missed in the online publication.

Context and background: Complex fuzzy theory has a strong practical implication in many real-world applications. Complex Fuzzy Inference System (CFIS) is a powerful technique to overcome the challenges of uncertain, periodic data. However, a question is raised for CFIS: How can we deduce and predict the result in case there is little knowledge abou...

Hospital cost analysis (HCA) becomes a key topic and forefront of politics, social welfare and medical discourse. HCA includes a wide range of expenses; yet the foremost attention relates to the money expense in which hospital managers would like to draw a figure of incomes in the past and future. Based on the HCA results, they can develop many pla...

Motivation: There is a paradox at the heart of informatics where practical implementation generally fails to understand the socio-technical impact of novel technologies and disruptive innovation when adopted in `real-world’ systems. This phenomenon, termed technological determinism, is manifested in a time-lag between the adoption of novel technolo...

This paper presents JUSTIN standing for Japanese Ukiyo-e Streaming That Improves Narrative, a game system that is designed for collecting descriptive data for artwork images (Japanese ukiyo-e in this study). The proposed game is the first “Audience Participation Game With a Purpose (APGWAP),” which combines two existing concepts: Audience Participa...

Recently, many requests from customers at the same time can make over working load to a service call center. Conventional approaches have focused on scheduling cost, time, and human resource in a service call center, so it takes time with increasing high costs. This paper has presented a proposal of an intelligent rule-based support model using dat...

In this article, we use the monotonic optimization approach to propose an outcome-space outer approximation by copolyblocks for solving strictly quasiconvex multiobjective programming problems and especially in the case that the objective functions are nonlinear fractional. After the algorithm is terminated, with any given tolerance, we obtain an a...

In this article, we use a monotonic optimization approach to propose an outcome-space outer approximation by copolyblocks for solving strictly quasiconvex multiobjective programming problems which include many classes of captivating problems, for example when the criterion functions are nonlinear fractional. After the algorithm is terminated, with...

In recent years, there are huge data extracted from social networks in both static and real-time analysis, such as Facebook, Twitter, LinkedIn, and Instagram. Recently, most researchers have investigated in classifying textual content without user interests/behaviors from huge data of social networks. This paper has presented a novel approach using...

Pedagogic systems in higher education have often relied on the traditional approach using face-to-face tutorial sessions with an on-line presence to deliver information relating to the specific course of study. There is however a paradigm shift in pedagogic systems characterised by the availability of teaching materials ‘anytime’ and ‘anywhere’ usi...

With a view to increase recommendation systems accuracy and practical applicability, using traditional methods which are namely interaction model between users and items, collaborative filtering and matrix factorization cannot achieve the supposed results. In fact, the properties between users or items always remains as social and knowledge relatio...

In emergency scenarios service vehicles must identify potential route(s) and use the best available route. However, route identification requires intelligent decision-support systems which generally use non-traditional approaches with tools characterised by flexible non-hierarchical structures. Conventional models using group decision-support syste...

In emergency scenarios service vehicles must identify potential route(s) and use the best available route. However, route identification requires intelligent decision-support systems which generally use non-traditional approaches with tools characterised by flexible non-hierarchical structures. Conventional models using group decision-support syste...

This abstract provides a survey on Games With a Purpose (GWAPs) and Audience Participation Games (APGs). We also discuss potentials in combining GWAPs and APGs on live-streaming platforms. Nowadays, many deep learning and machine learning techniques have been developed, which require a large amount of high-quality data in the training process. Howe...

This paper proposes a method for creating informative descriptive sentences for artwork images by using “Games With a Purpose,” or GWAP on a live streaming platform. In existing studies, automatic annotation of images did not perform well, in particular, for artwork images such as Ukiyo-e. On the other hand, existing studies on GWAP, the concept of...

Robotic path planning is a field of research which is gaining traction given the broad domains of interest to which path planning is an important systemic requirement. The aim of path planning is to optimise the efficacy of robotic movement in a defined operational environment. For example, robots have been employed in many domains including: Clean...

Robotics is a highly developed field in industry, and there is a large research effort in terms of humanoid robotics, including the development of multi-functional empathetic robots as human companions. An important function of a robot is to find an optimal coverage path planning, with obstacle avoidance in dynamic environments for cleaning and mon...

Robots are a rapidly evolving development field encompassing variable domains ranging from industrial robots to empathetic robots for human companions. Future robots will be highly dependent on the ability to understand, interpret, and generate a representation of the environment in which they are operating, ideally in both a human and machine-read...

The ensemble is an universal machine learning method that is based on the divide-and-conquer principle. The ensemble aims to improve performance of system in terms of processing speed and quality. The assessment of cluster tendency is a method determining whether a considering data-set contains meaningful clusters. Recently, a silhouette-based asse...

Human behaviour demonstrates environmental awareness and self-awareness which is used to arrive at decisions and actions or reach conclusions based on reasoning and inference. Environmental awareness and self-awareness are traits which autonomous robotic systems must have to effectively plan an optimal route and operate in dynamic operating environ...

A series of MnBi1-xSbx alloys were prepared by a metallurgical method. The samples MnBi1-xSbx were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), differential scanning calorimetry (DSC), vibrating-sample magnetometer (VSM). The effects of Sb substitution on the structural formation, electronic structure and magnetic p...

Robotic decision-support systems must facilitate a robots interactions with their environment, this demands adaptability. Adaptability relates to awareness of the environment and `self-awareness', human behaviour exemplifies the concept of awareness to arrive at an optimal choice of action or decision based on reasoning and inference with learned p...

There is a growing interest in health information technology using evidence-based approaches in clinical decision-support systems, the goal for such systems is ‘precision medicine’ using ‘interventional informatics’. However, the impact has been less than positive and it has been argued that interventional informatics using data-driven intervention...

This article describes how the objective of recent advances in soft computing and machine learning models is the resolution of issues related to security monitoring for information systems. Most current techniques and models face significant limitations, in the monitoring of information systems. To address these limitations, the authors propose a n...

Treatment and management of the increasing complexity in medical conditions experienced by an ageing demographic requires increased use of medical resources and patient management. Effective management may be achieved using autonomic health monitoring systems, a topic much discussed in the literature, however such monitoring has generally been limi...

In this paper, we propose a novel fuzzy inference system on picture fuzzy set called picture inference system (PIS) to enhance inference performance of the traditional fuzzy inference system. In PIS, the positive, neutral and negative degrees of the picture fuzzy set are computed using the membership graph that is the combination of three Gaussian...

In practical dentistry, dentists use their experience to examine dental X-ray images and to derive symptoms from patients for concluding possible diseases. This method is based solely on the own dentists' experience. Dental diagnosis from X-Ray images is proposed to support for dentists in their decision making. This paper presents an application o...

In practical dentistry, dentists use their experience to examine dental X-ray images and to derive symptoms from patients for concluding possible diseases. This method is based solely on the own dentists' experience. Dental diagnosis from X-Ray images is proposed to support for dentists in their decision making. This paper presents an application o...

In this paper, we propose a novel multiple fuzzy clustering method based on internal clustering validation measures with gradient descent. Firstly, some single fuzzy clustering algorithms such as Fuzzy C-Means, Kernel Fuzzy C-Means and Gustafson–Kessel are used to construct similarity matrixes for each partition. Secondly, those similarity matrixes...

The concept of personalization in its many forms has gained traction driven by the demands of computer-mediated interactions generally implemented in large-scale distributed systems and ad hoc wireless networks. Personalization requires the identification and selection of entities based on a defined profile (a context); an entity has been defined a...

Agricultural product intelligence is a new way for biotechnology that can be made multiple food products with a variety of characteristics, enhanced flavor and nutritional quality of foods. To evaluate food products of bio-food products for improvement of the food quality in global bio-food markets, cross-cultural customer behaviors are mostly infl...

There have been far reaching Societal and Geo-Political developments in healthcare domains locally, nationally, and globally. Healthcare systems are essentially patient centric and decision driven with the clinician focus being on the identification of the best treatment options for patients in uncertain environments. Decision-support systems must...

Alternative selection of a portfolio has been a challenging research area, in finance and investment decision making. Recent advances in single Decision Support Systems (DSS), soft computing and machine learning models are to solve the problems in selection of alternatives under uncertain market and risk environments. These models have not consider...

Risk management and stock assessment are key methods for stock trading decisions. In this paper, we present a new stock trading method using Kansei evaluation integrated with a Self-Organizing Map model for improvement of a stock trading system. The proposed approach aims to aggregate multiple expert decisions, achieve the greatest investment retur...

Patient management in hospital environments with the provision of effective care pathways represents a significant challenge. Hospital settings are characterized by uncertainty driven by the need to accommodate both elective treatments and emergency cases [which generally arrive without warning, this can place great strain on the healthcare system....

Meeting the educational needs of students currently requires moving towardcollaborative electronic and mobile learning systems that parallel the vision ofWeb 2.0. However, factors such as data freedom, brokerage, interconnectivityand the Internet of Things add to a vision for Web 3.0 that will require con-sideration in the development of future cam...

Pressures on the availability of healthcare spaces, the high costs of institutional care, and the desires of those being cared for, cause a current move toward care either at home or within low-supervision environments. This brings about an important question: how can smart care spaces be created that intelligently link the home care environment to...

Personalized on demand e-learning has gained traction driven by socio-economic and demographic change. Concomitant with these developments is the revolution in the capability and ubiquity of mobile systems. The result of these developments is interest in personalized e-learning provided on-demand using mobile technologies. Additionally, e-learning...

In pervasive computing environments the availability of real-time computation models is expected to predict a performance of Tunnel Boring Machine (TBM). Context awareness allows an entity adapt to uncertain environment, offering a number of intelligent prediction methods for tunneling. This study presents a proposal of a Context-Aware Tunneling Sy...

Context is inherently complex requiring intelligent context processing to address the broad and diverse range of available data that when processed can be viewed as contextual information useful in intelligent context-aware systems in a broad range of domains and systems. The function of context-aware systems is to target service provision based on...

In our exciting world of pervasive computing and always-available mobile internet, meeting the educational needs of students has seen a growing trend toward collaborative electronic and mobile learning systems that build on the vision of Web 2.0. However, other trends relevant to modern students must not be ignored, including data freedom, brokerag...

Stock markets are dynamically changing in dynamics under uncertainty and risk. The notion of stock trading under uncertainty in stochastic investment trading systems that satisfies dynamic trading problems in market dynamics. This paper presents a novel approach for stock trading; we describe a framework which provides an effective basis upon which...

Society is experiencing an ageing demographic, coupled with increasingly prevalent Alzheimer and Dementia conditions, expected to cause explosive increases in healthcare costs. There is a need to develop pervasive technologies that allow monitoring of patients at home, where medically permissible, to reduce pressures on formal healthcare spaces. Th...

Context-aware systems have traditionally employed a limited range of contextual data. While research is addressing an increasingly broad range of contextual data, the level of intelligence generated in context-aware systems is restricted by the failure to effectively implement emotional response. This paper considers emotion as it relates to contex...

Thomas, A.M., Shah, H., Moore, P., Rayson, P., Wilcox, A.J., Osman, K., Evans, C., Chapman, C., Athwal, C., While, D., Pham, H.V. and Mount, S. (2012) "E-education 3.0: Challenges and Opportunities for the Future of iCampuses", Second International Workshop on Intelligent Context-Aware Systems (ICAS 2012), Proceedings of the 6th International Confe...

Due to complex problems in under ground conditions, Tunnel Boring Machine (TBM) performance prediction is mostly affected by conditional environments of the following: geological formation, rock mass, rock property, and fractured rock. This study has presented a new approach using Hybrid Artificial Neural Networks integrated with fuzzy reasoning ev...

The preferences of decision maker are dynamic changing in collaborative process under uncertainty. Dynamic Group Decision Making is to consider uncertainty measures in the processes of multiple decisions for the selection of alternatives. The aim of this study is to present a new approach using dynamic group decision making, together with expert se...