Industry 4.0 produces large volumes of sensor and machine data, offering new possibilities for manufacturing analytics but also creating challenges in combining domain knowledge with visual analysis. We present a systematic review of 13 peer-reviewed...
Due to the increasing use of data analytics, information visualization is getting more and more important. However, as data get more complex, so does visualization, often leading to ad hoc and cumbersome solutions. A recent alternative is the use of...
This study develops and implements a scalable system architecture for dynamic data acquisition and knowledge modeling in industrial contexts. The objective is to efficiently process large datasets to support decision-making and process optimization w...
Visual Analytics (VA) is a multidisciplinary field that requires various skills including but not limited to data analytics, visualizations, and the corresponding domain knowledge. Recently, many studies proposed creating and using Domain-Specific La...
The rapid circulation of misleading information through digital media has made credibility assessment increasingly challenging for journalists and audiences. This study examines how linguistic and visual credibility cues contribute to the appearance...
Nowadays, Python is very popular as the first programming language for novices, including high school students, to learn due to its short code features with rich libraries. Thus, it is important to provide a learning environment supporting studies st...
Recent breakthroughs in machine learning, artificial intelligence, and the emergence of large datasets have made the integration of eye tracking increasingly feasible not only in computing but also in many other disciplines to accelerate innovation a...
With the rapid advancement of educational digitalization and generative artificial intelligence, knowledge graphs and AI agents have emerged as key technologies supporting smart higher education. To address challenges in current AI-assisted teaching,...
Scientific dispute and scholarly debate have traditionally served as mechanisms for arbitrating between competing scientific categorizations. However, current AI technologies lack both the ethical framework and technical capabilities to handle the ad...
Healthcare visualization has become a crucial approach for interpreting complex medical data, supporting informed clinical decision-making, and enhancing public health management. However, existing reviews tend to focus on specific technologies or ap...
Application of Artificial Intelligence-Generated Content (AIGC) in architectural design has increased rapidly. However, contemporary interpretations of traditional architectural heritage produced through such approaches often remain visually imitativ...
The development of a decision support system (DSS) to inform policy making has been progressing rapidly. This paper presents a generic framework and the development steps of a decision tool prototype of geographic information systems (GIS)-based dec...
Making decisions is a key task for leaders and managers. Senior leaders are currently exposed to increasing amounts of data which they must process quickly in our current dynamic world. Complex factors in the business world are not always best approa...
State Departments of Transportation (DOTs) face challenges with traditional bridge inspections that are time-consuming, inconsistent, and paper-based. This study focused on an existing research gap regarding automated methods that streamline the brid...
Creating effective computer-assisted learning (CAL) environments for children remains challenging, particularly in sustaining motivation, engagement, and meaningful learning outcomes. While educational games are widely used to address these challenge...
The most crucial component of any smart city traffic management system is traffic flow prediction. It can assist a driver in selecting the most efficient route to their destination. The digitalization of closed-circuit television (CCTV) systems has r...
13 July 2022
Person-centered care (PCC) requires knowledge about patient preferences. An analytic hierarchy process (AHP) is one approach to quantify, weigh and rank patient preferences suitable for People living with Dementia (PlwD), due to simple pairwise compa...
The cornerstone of the global economy, oil and gas reservoir development, faces numerous challenges such as resource depletion, operational inefficiencies, safety concerns, and environmental impacts. In recent years, the integration of artificial int...