Graph edit distance (GED) is a powerful tool to model the dissimilarity between graphs. However, evaluating the exact GED is NP-hard. To tackle this problem, estimation methods of GED were introduced, e.g., bipartite and IPFP, during which heuristics...
Chemical compounds can be represented as attributed graphs. An attributed graph is a mathematical model of an object composed of two types of representations: nodes and edges. Nodes are individual components, and edges are relations between these com...
Background: Amyotrophic lateral sclerosis (ALS) is still a global health challenge, as there is no effective treatment due to the inadequacy of conventional experimental platforms for comprehending pathogenic mechanisms and developing therapy. Object...
Green technology can improve construction and demolition waste recycling, yet an objective payoff advantage does not necessarily lead to sustained adoption. This study examines how enterprise valuation and network learning jointly shape diffusion. A...
Artificial intelligence is increasingly being used in all branches of the media system and has transformed the way specialists in this field work in recent years. Currently, applications of artificial intelligence are used across a range of processes...
Developing climate-resilient and high-quality cotton cultivars remains an urgent challenge, as the key target traits yield, fibre properties, and stress tolerance are highly polygenic and strongly influenced by genotype–environment interactions...
The use of technological learning tools has been increasingly recognized as a useful tool to promote students’ motivation to deal with, and understand, mathematics concepts. Current digital technology allows students to work interactively with...
Three-dimensional object modeling is necessary for developing virtual and augmented reality applications. Traditionally, application engineers must manually use art software to edit object shapes or exploit LIDAR to scan physical objects for construc...
This study proposes a functional framework to enhance the efficiency and effectiveness of e-learning content creation by systematically integrating generative artificial intelligence (AI) technologies. While previous research on e-learning has primar...
The price of food has been affected in recent months in response to events such as the war in Ukraine, energy costs, inflation, the COVID-19 pandemic, and climate change. Indeed, supply problems, as well as the repercussions of global issues, have ha...
Semi-structured documents contain both hierarchical structure and field-level semantics. This makes similarity measurement difficult for methods that focus only on structure or only on global semantic representations. To address this problem, we prop...
Fault prediction is a vital task to decrease the costs of equipment maintenance and repair, as well as to improve the quality level of products and production efficiency. Steel plates fault prediction is a significant materials science problem that c...
Non-Alcoholic Fatty Liver Disease (NAFLD) is characterized by the accumulation of excess fat in the liver. If left undiagnosed and untreated during the early stages, NAFLD can progress to more severe conditions such as inflammation, liver fibrosis, c...
Climate change has attracted global attention, highlighting the critical role of low-carbon technologies in addressing environmental challenges. Due to the multidisciplinary nature, complexity, and diversity of research content on low-carbon technolo...
Volunteered Geographic Information (VGI) is often collected by non-expert users. This raises concerns about the quality and veracity of such data. There has been much effort to understand and quantify the quality of VGI. Extrinsic measures which comp...
This paper applies a hybrid multi-criteria decision-making (MCDM) model that integrates the Analytic Hierarchy Process (AHP) for structured weighting of evaluation criteria with the Net Worth Analysis (NWA) method for value-based aggregation of score...
The presented article describes the design features of an educational robotics project addressed for secondary school students and carried out at the University of Girona (UdG). The project, called Underwater Robotics Workshop, is about the students...
Artificial intelligence (AI), currently a cutting-edge concept, has the potential to improve the quality of life of human beings. The fields of AI and biological research are becoming more intertwined, and methods for extracting and applying the info...
The ability to preemptively identify potential failures in industrial parts is crucial for minimizing downtime, reducing maintenance costs and ensuring system reliability and safety. However, challenges such as data nonlinearity, temporal dependencie...
The changes in our society in recent years and the consequent idiosyncrasy of young people demand new teaching methodologies. The methodology known as flip teaching, in which pupils study the subject before the class experience, using the material gi...
Improving an existing public transport route network is a challenging optimization problem, since service quality and operational efficiency must be improved without excessive changes to the established network. Most public transport network improvem...
Class imbalance remains a central problem in machine learning because the rare class is often the event of scientific, clinical, financial, or operational interest. Yet the literature is fragmented across sampling, cost-sensitive learning, ensembles,...
Robust indoor robot navigation typically demands either costly sensors or extensive training data. We propose a cost-effective RGB-D navigation pipeline that couples feature-based relative pose estimation with a lightweight multi-layer-perceptron (ML...
To overcome the dual bottlenecks of scarce actual strong earthquake records and high computational costs of nonlinear time history analysis, this study proposes a fast prediction method for structural nonlinear response that integrates systematic sei...
Roads are a form of critical infrastructure, influencing economic growth, mobility, and public safety. However, the management, monitoring, and maintenance of road networks remain a challenge, particularly given limited budgets and the complexity of...
Short videos have become a primary medium for news delivery, but their low cost, rapid diffusion, and multimodal nature make misinformation easier to generate and harder to verify. Existing methods often rely on single-modality cues or shallow cross-...
Rapid prediction of vehicle lift coefficient is an important issue in aerodynamic design. Traditional CFD/DSMC methods have high computational costs. Although commonly used machine-learning surrogate models offer high prediction efficiency, they stru...
Reliable text-to-CAD generation remains challenging because syntactically valid programs may fail during geometric execution or produce inaccurate geometric models. Existing approaches often treat geometric execution primarily as a post-generation va...
With the rapidly increasing reliance on advances in IoT, we persist towards pushing technology to new heights. From ordering food online to gene editing-based personalized healthcare, disruptive technologies like ML and AI continue to grow beyond our...
Sorghum is a climate-resilient crop which has been cultivated as a staple food in the semi-arid areas of Africa and Asia for food and nutrition security. However, the current climate change is increasingly affecting sorghum performance, especially at...
Remote sensing is a powerful tool that provides flexibility and scalability for monitoring and investigating glacial lakes in High Mountain Asia (HMA). However, existing methods for mapping glacial lakes are designed based on a combination of several...
Within the neuropsychological assessment, clinicians are responsible for ensuring the validity of obtained cognitive data. As such, increased attention is being paid to performance validity in patients with multiple sclerosis (pwMS). Experts have pro...
Automotive dashboard cameras are widely used to record driving events and often serve as critical evidence in accident investigations and insurance claims. However, the availability of free and low-cost editing tools has increased the risk of video t...
Antimicrobial resistance (AMR) is a growing global health emergency that threatens the effectiveness of modern medicine, exacerbating healthcare costs, morbidity, and mortality, particularly in low- and middle-income countries (LMICs). Traditional ap...
The application of Generative Artificial Intelligence (GenAI)—defined as a class of AI systems capable of autonomously generating new content such as images, texts, and design solutions based on learned data patterns—has become increasing...
3D modelling of urban areas is an attractive and active research topic, as 3D digital models of cities are becoming increasingly common for urban management as a consequence of the constantly growing number of people living in cities. Viewed as a dig...
Background: Metamorphic malware is among the most persistent adversarial challenges in cybersecurity: it rewrites its own instruction stream on every propagation, preserving functional semantics while presenting a syntactically distinct binary that d...
Drought stress is the most pervasive abiotic constraint on global crop productivity, with projected intensification under climate change threatening the yields of staple crops including wheat, rice, maize, and legumes. Conventional breeding approache...