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Abstract Background A solid understanding of anatomy is fundamental in dental education, and accurate interpretation of maxillofacial structures is essential across clinical contexts. Implantology is an example of a comp...

Abstract A prompt and precise diagnosis is necessary to lessen the worldwide burden of asthma, a common chronic respiratory condition. Spirometry is one of the resource-intensive conventional methods that frequently misc...

The remarkable success of large language models (LLMs) in code generation has transformed software development, with systems like Codex, CodeGen, and StarCoder demonstrating strong capabilities in synthesizing functional...

Power transformers are critical components of power systems, and their safe and reliable operation is essential for both industrial and residential applications. Real-time condition monitoring and early fault detection a...

Customer feedback is pivotal in enhancing service quality and user satisfaction across digital platforms. However, traditional sentiment analysis methods often struggle with informal languages, contextual nuances, and as...

Abstract Accurate prediction of compressive strength is important for the efficient design of sustainable concrete incorporating palm oil fuel ash (POFA). This study developed a hybrid artificial neural network model opt...

Abstract Lung cancer remains the primary cause of cancer-related deaths throughout the world. The main reason behind this is late diagnosis and the restrictions in the manual interpretation of imaging data. In these days...

This research paper introduces UniEats, a recipe recommendation website designed to help university students better organize their meals and adopt healthier eating habits. The system aims to address common challenges stu...

The necessity for sophisticated recommender systems in the movie recommendation sphere has become particularly pronounced, generating a more personalized movie recommendation due to people nowadays who like to watch movi...

Abstract The increasing number of Internet of Things (IoT) devices demands a rigid and adaptive routing methodologies to ensure the reliable communication especially for the low-power and lossy networks. The Routing Prot...

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 ...

Abstract The integration of the sixth-generation (6G) communication technology and the Industrial Internet of Things (IIoT) has realized the intelligence and automation of industrial applications. However, due to the com...

Abstract This research employs hybrid machine learning techniques to optimize the mechanical properties of 3D-printed polylactic acid (PLA) lattice structures. By integrating random forest (RF) and XGBoost (XGB) algorith...

Abstract This study presents a novel hybrid methodology combining machine learning (ML) with conventional reservoir simulation to optimize waterflooding in the geologically complex Bahariya Formation, Western Desert, Egy...

This work presents a hybrid deep learning approach for identifying students who are likely to experience academic difficulties in virtual learning environments. The proposed framework is evaluated on the Open University ...

This research aims to develop a hybrid reflective micro-teaching model. The research method used is a type of research and development referring to the Borg and Gall R&D Cycle. The research results from reflection sheets...

The purpose of this research is to (1) develop a hybrid flipbook-based media in e-learning Pancasila Education courses as a step to reduce the use of internet quotas, (2) make Pancasila Education lectures varied and fun,...

Wildfires are among the most destructive natural disasters and pose significant risks to ecosystems, infrastructure, and human lives. This study focuses on wildfire susceptibility mapping in Los Angeles County, a region ...

Abstract The new energy vehicle plays a crucial role in green transportation, and the energy management strategy of hybrid power systems is essential for ensuring energy-efficient driving. This paper presents a state-of-...

Abstract Unsupervised visible-infrared person re-identification (USL-VI-ReID) aims to match person images across visible and infrared modalities without any labeled data, which is severely hindered by the large cross-mod...

Abstract Accurate prediction of cascading faults in power grids can ensure system stability and prevent large-scale outages. Existing methods typically require learning effective statistical information from datasets wit...

Abstract The deep reinforcement learning techniques offers a novel approach to real-time control for hybrid power flow controllers. This paper introduces a bus voltage optimization adjustment strategy, utilizing a Markov...

Carbon allowances constitute a foundational component of national carbon emission control frameworks, as they govern the equitable distribution of subsequent allocations and directly shape the overall effectiveness of gr...

Abstract Why do foreign investors exit Central and Eastern Europe (CEE) despite formal alignment with EU institutional standards? We argue that divestment reflects not cyclical volatility but strategic responses to insti...