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Test-based automated program repair (TB-APR) techniques automatically fix buggy programs by relying on a failing test suite. This test suite serves a dual purpose: pinpointing bugs and evaluating the validity of potentia...

ObjectiveCurrently, the insufficient full-element digitization and the prevalence of “data silos” in fully mechanized mining faces (FMMF) result in poor cutting precision and operational instability of shearers under...

Abstract Background Thalassemia is the most prevalent single-gene disorder in Sri Lanka, imposing a significant socioeconomic and healthcare burden. Early carrier detection is essential for genetic counselling and the pr...

Abstract Objective Deep vein thrombosis (DVT) represents a major thrombo-inflammatory disorder with substantial diagnostic challenges. Emerging evidence implicates that neutrophil extracellular traps (NETs) and miR-155 a...

BackgroundInfluenza poses a significant global public health threat, with its pandemic potential and seasonal variability presenting formidable challenges to prediction accuracy. This study leverages high-quality weekly ...

The classification of edible versus poisonous mushrooms presents a critical challenge in the domains of applied biology and public health, particularly due to the serious implications of misidentification. This research ...

This study investigates the performance of the Random Forest algorithm in measuring the quality of Higher Education Institutions (HEIs) in Indonesia. The current reliance on administrative evaluations and conventional ac...

Abstract Background Mortality prediction in critically ill patients is commonly performed with scoring systems such as SOFA and APACHE II. The arterial-to-end-tidal carbon dioxide gradient [P(a–et)CO₂], which can be ...

Understanding how consumers behave in e-commerce is essential for businesses, especially in today’s digital world where people rely heavily on online shopping platforms. A key part of this understanding comes from sent...

Abstract Cloud computing is quite popular because of its scalability and flexibility merits. However, faces significant security risks from malware, which exploits infrastructure weaknesses to cause unauthorized access, ...

In this work, a structured hierarchy of hyperdatasets for Monkeypox image classification is presented, aiming to evaluate the robustness and generalization ability of deep classification models for Mpox detection. A syst...

The rapid advancement of generative artificial intelligence (AI) has obscured the distinction between human- and machine-created art, posing significant challenges to authentication, copyright, and artistic integrity. Th...

This research focuses on developing a neural network model in the Python programming language to solve the technological problem of forecasting potato yields with limited agroclimatic data. The developed program is consi...

Abstract Background Delayed ambulation recovery following major abdominal surgery presents a significant prognostic challenge, contributes to increased morbidity, mortality, and prolonged hospital stay. Despite recommend...

Objective To analyze the prevalence of potentially inappropriate medication use in older adults and develop a nomogram for predicting the individualized risk for potentially inappropriate medication use. Methods A retros...

Abstract Objective: To evaluate the accuracy of neural networks and Naïve Bayes models in diagnosing ectopic pregnancy, using clinical data, hCG levels, and transvaginal ultrasound findings from a real dataset. Method...

One such serious problem in machine learning (ML) is imbalanced datasets. Minority class samples are usually sparse but hold significant meaning. The model can become biased toward the majority class due to unbalanced cl...

ObjectiveTo investigate the association of serum N-terminal pro-brain natriuretic peptide (NT-proBNP), red cell distribution width (RDW), homocysteine (Hcy), and clinical parameters with new-onset atrial fibrillation (NO...

Botnet communications often rely on Domain Generation Algorithms (DGAs) to establish channels among attack orchestrators and compromised hosts (bots). Our approach leverages on Artificial Intelligence (AI) to differentia...

Although vaccination remains one of the most impactful interventions in contemporary public health, with consistent and widely documented reductions in morbidity and mortality, the traditional empirical development of va...

Abstract Accurate differentiation of pulmonary emphysema from chest X-rays remains challenging due to imbalanced data, image noise, and the limitations of traditional deep networks in managing diagnostic uncertainty. In ...

Background Identifying priority projects in industry–education integration is critical for optimizing policy support and resource allocation. While prior studies have primarily relied on qualitative assessments, there ...

In this study, experiments on milk sales estimation were conducted in two phases to optimize stock ordering. Sales data of two brands of milk between 2007 and 2008 were obtained through 9 stores in Ishikawa Prefecture. I...

Traffic congestion prediction plays a crucial role in mitigating congestion. However, the COVID-19 pandemic and associated government control measures have significantly altered urban travel behavior, increasing the comp...