Hai V. Pham

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

Coverage path planning describes the process of finding an effective path robots can take to traverse a defined dynamic operating environment where there are static (fixed) and dynamic (mobile) obstacles that must be located and avoided in coverage path planning. However, most coverage path planning methods are limited in their ability to effective...

The effects of Sn dopant on microstructure and magnetic properties of large-scale produced MnBi1 − xSnx (x = 0; 0.05; 0.10; 0.15; 0.20; 0.25) melt-spun ribbons were systematically investigated. With increasing Sn content, the MnBi LTP fraction within the produced ribbons exhibited a decreasing trend, associated with the formation of the Mn3Sn phase...

Generative AI applications have played an increasingly significant role in real-time tracking applications in many domains including, for example, healthcare, consultancy, dialog boxes (common types of window in a graphical user interface of operating systems), monitoring systems, and emergency response. This paper considers generative AI and prese...

ChatGPT plays significant roles in the third decade of the 21st Century. Smart cities applications can be integrated with ChatGPT in various fields. This research proposes an approach for developing large language models using generative artificial intelligence models suitable for small- and medium-sized enterprises with limited hardware resources....

Many real-life problems present multiple options necessitating modern researchers to identify the most suitable choice or decision. In this context, fuzzy sets have proven to be valuable tools for addressing such problems. Picture fuzzy sets (PFSs), due to their increased flexibility and broader domain as compared to other extensions of fuzzy sets...

Tripolar fuzzy sets offer a robust framework that integrates the aspects of intuitionistic fuzzy sets and bipolar fuzzy sets. Complex decision-making problems often involve multiple attributes with specific properties that reflect both negative and positive aspects. In such cases, intuitionistic fuzzy sets (IFS) and bipolar fuzzy sets (BFS) may be...

Recently, machine learning models based on fuzzy inference systems have effectively solved problems in medical diagnosis and received much attention from researchers around the world. For example, Fuzzy Inference System (FIS), Mamdani Complex Fuzzy Inference System with Rule Reduction (M-CFIS-R), Mamdani Complex Fuzzy Inference System with Fuzzy Kn...

Recently, an identification in criminal information of person with its attributes of a human such as name, hand, hairCoverage, hairTexture, faceShape, and skinColor faces with insufficient information since it is mixed information of human recognition under uncertain environment. It is a hard question how sci-entists identify human features in eith...

Traditional fuzzy set theory has recently demonstrated its inefficiency in handling linguistic terms directly, including the degree of neutrality in medical diagnoses. Most decision support systems in medical diagnoses are restricted since both explicit and tacit knowledge of doctors involving linguistic semantics while making decisions have not be...

Recently, measuring users and community influences on social media networks play significant roles in science and engineering. To address the problems, many researchers have investigated measuring users with these influences by dealing with huge data sets. However, it is hard to enhance the performances of these studies with multiple attributes tog...

Pedagogic systems are gaining traction in the provision of training, learning, and continuing professional development (often required to maintain professional qualifications). An essential element in pedagogic systems is the matching of teachers (mentors) and students (mentees). In this paper we present an intelligent context-aware learning system...

The picture fuzzy set (PFS) is a general form of the fuzzy and intuitionistic fuzzy set for solving real-world problems. Entropy and distance measures play significant measures in solving problems involving fuzzy environments. In multi-criteria decision-making (MCDM) problems, entropy is used to determine the weights of each criterion. Distance mea...

The decision-making problems based on fuzzy inference systems have received much attention from the worldwide scientific community. The M-CFIS-FKG model is considered one of the best models to solve classification problems based on uncertain and amplitude input datasets. It can infer and find the output labels of new samples that are not in the fuz...

Problems of preeclampsia sign diagnosis are mostly based on symptom data with the characteristics of data collected periodically in uncertain, ambiguous, and obstetrician opinions. To reduce the effects of preeclampsia, many studies have investigated the disease, prevention, and complication. Conventional fuzzy inference techniques can solve severa...

In the forest, many tasks can be assigned for human being when monitoring on the road in forest. Monitoring on forest roads plays a significant role in multiple tasks such as checking for trees, collecting gapers, clearing roads, etc. However, automated driving is one of the future ways to be used in the development, verification, and validation of...

The picture fuzzy set is an extension of the fuzzy and intuitionistic fuzzy set for solving real-world problems. Entropy and distance measures play significant roles in measures for solving problems involving fuzzy environments. This paper has presented some new distance and entropy measures using picture fuzzy sets to solve problems of medical dia...

In conventional monitoring forest protection, detection methods use optical sensors or RGB cameras combine features including smokes, fires and human-destroyed forests at national forests. This paper has presented a new approach using Deep learning integrated with Picture Fuzzy Set for the surveillance monitoring system to be activated to confirm 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...

In recent years, it has been great interest for Question Answering (QA) systems applied to many areas placing a high value on the community. The study and development of such QA systems through chatbot tools in medicine raise great needs for clinicians in their daily activities. Chatbots use the knowledge that could be retrieved from a database, bu...

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...

In conventional monitoring of human behavior in forest protection, deep learning approaches can be detected human behavior significantly since thousands of visitors’ forest protection is abnormal and normal behaviors coming to national or rural forests. This paper has presented a new approach using a deep learning model integrated with a knowledge...

Motivation Healthcare systems globally face significant resource and financial challenges. Moreover, these challenges have resulted in an existential paradigm shift driven by: (i) the growth in the demand for healthcare services is exacerbated by a global population characterised by an ageing demographic with increasingly complex healthcare needs,...

Currently, many applications of information search tourism are limited in the COVID-19 pandemic using a search engine. However, most application service online has not supported directly, matching end users with their preferences to find suitable tourist places. This paper has presented a proposed model using the Context Matching algorithm mostly b...

Forecasting labor demand play significant roles in the development of planning policies in both national labor markets with strategies of national human resources in order to meet the requirements of industrialization and modernization of the country. This paper has presented the proposed model using multivariate multiple regressions, dealing with...

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...

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...

Recently, COVID-19 pandemic has increasingly affected the lives of the world population. Researchers have investigated various ways including conventional approach about the transmission routes of COVID-19 persons. However, it is difficult to track COVID-19 in real-time at anywhere. The paper has presented a novel approach using Self Organizing Map...

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...

Chẩn đoán bệnh trong y học cổ truyền thường được cốt lại trong bốn cách là “Vọng - Văn - Vấn - Thiết” (haycòn được gọi là “Tứ chẩn”). Trong những năm gần đây, đội ngũ lương y, bác sĩ đã sử dụng kết hợp giữa phác đồ điều trị trong y học cổ truyền với kết quả khám, xét nghiệm trong y học hiện đại nhằm nâng cao chất lượng chẩn đoán bệnh. Điều này đã t...

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...

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...

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...

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...