Academic Articles & Research Papers

Conformal Mechanics of Serpentine Meshes for Millimeter-Scale Neural Probes.

Overview of Tensor-Based Cooperative MIMO Communication Systems—Part 1: Tensor Modeling

Due to increasingly strong and varied performance requirements, cooperative wireless communication systems today occupy a prominent place in both academic research and industrial development. The technological and economic challenges for fu...

Coalition of explainable artificial intelligence and quantum computing in precision medicine

This survey examines the convergence of Explainable Artificial Intelligence (XAI) and Quantum Computing (QC) toward precision medicine. We review developments from 2018 to 2025, summarizing quantum algorithms, quantum-machine-learning model...

A general theory of glacier surges

We present the first general theory of glacier surging that includes both temperate and polythermal glacier surges, based on coupled mass and enthalpy budgets. Enthalpy (in the form of thermal energy and water) is gained at the glacier bed ...

Psychometric facets of Antifragility: Tolerance of Ambiguity, Hardiness, and Growth

This paper considers the issues, which are concerned with a new concept of antifragility. Quite recently, considerable attention has been paid to the concept of antifragility. Antifragility gains a special importance in studying psychologic...

Electrorefining behavior of a multicomponent copper alloy derived from waste printed circuit boards

Efficient recycling of waste electrical and electronic equipment (WEEE) is a major priority for the circular economy and sustainable resource management. This study proposes and investigates an integrated mechanical, pyrometallurgical, and ...

Domain-Specific Sentiment Analysis: An Optimized Deep Learning Approach for the Financial Markets

Although different studies are caried out by deep learning models for financial markets sentiment analysis, there is a lack of specific embedding method that regards the domain. Therefore, the goal of this study is to discover what type of ...

Empowering text classification with NLP and explainable AI for enhanced interpretability

Abstract Artificial intelligence (AI) models have demonstrated significant success in classifying various types of text. However, the complex nature of these models often complicates the interpretability of their classifications. To address...

A fault location method for secondary virtual circuits in smart substations based on the integration of GAE and GCN

Abstract The secondary virtual circuits in smart substations enable digital and networked information exchange between devices. However, their extensive logical connections, complex structure, and implicit interdependencies pose significant...

Problems In Indoor Mapping and Modelling

Research in support of indoor mapping and modelling (IMM) has been active for over thirty years. This research has come in the form of As-Built surveys, Data structuring, Visualisation techniques, Navigation models and so forth. Much of thi...

PubNavigator Activity to Promote Science Argumentation in Introductory Biology.

Generalizable stereo depth estimation with masked image modelling

Abstract Generalizable and accurate stereo depth estimation is vital for 3D reconstruction, especially in surgery. Supervised learning methods obtain best performance however, limited ground truth data for surgical scenes limits generalizab...

Evaluation of Similarity of Image Explanations Produced by SHAP, LIME and Grad-CAM

Introduction. Convolutional neural networks (CNNs) are a subtype of neural networks developed specifically to work with images [1]. They have achieved great success both in research and in practical applications in recent years, however, on...

Initial failure morphology of shallow loess containing millimeter-scale cracks: Insights from CT 3d imaging.

Evaluating artificial intelligence for a focal nodular hyperplasia diagnosis using magnetic resonance imaging: preliminary findings

PURPOSE: This study aimed to evaluate the effectiveness of artificial intelligence (AI) in diagnosing focal nodular hyperplasia (FNH) of the liver using magnetic resonance imaging (MRI) and compare its performance with that of radiologists....

A Sensor-to-API Data Infrastructure for Building Digital Twins: Harmonizing Multi-Rate IoT Energy and Indoor Data Streams for Proactive Analytics

Digital twins are increasingly used in smart buildings to monitor energy use. This requires reliable sensor data, geospatial information, and semantically rich 3D building geometry. However, building sensor data often has inconsistent sampl...

Machine-learning reprogrammable metasurface imager

Conventional microwave imagers usually require either time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing, making them largely ineffective for complex in-situ sensing and monitoring. Here, we e...

Evaluating Model Resilience to Data Poisoning Attacks: A Comparative Study

Machine learning (ML) has become a cornerstone of critical applications, but its vulnerability to data poisoning attacks threatens system reliability and trustworthiness. Prior studies have begun to investigate the impact of data poisoning ...

Smart IoT device for in field Black Sigatoka Disease recognition and mapping

Recently banana plantations have been affected by the Black Sigatoka Disease (BSD), producing streaks, lesions and yellow and brown spots on the leaves until the appearance of entire dead parts. The disease causes reductions in yield making...