Academic Articles & Research Papers

Cyclic order superpositions enable quantum information transmission through completely depolarizing channels

Abstract Noise fundamentally limits quantum communication capacity, completely preventing information transmission in fully depolarizing environments. While indefinite causal order theoretically circumvents this limitation, experimentally r...

Performance prediction and optimization of a high-efficiency tessellated diamond fractal MIMO antenna for terahertz 6G communication using machine learning approaches

Abstract This paper introduces the design and exploration of a compact, high-performance multiple-input multiple-output (MIMO) antenna for 6G applications operating in the terahertz (THz) frequency range. Leveraging a meta learner-based sta...

Beyond Herd Immunity Against Strategic Attackers

Herd immunity, one of the most fundamental concepts in network epidemics, occurs when a large fraction of the population of devices is immune against a virus or malware. The few individuals who have not taken countermeasures against the thr...

Interplay of physical activity, self-rated health, and life satisfaction among large-bodied adolescents in Europe and North America: analysis using clustered binary mixed effects logit modelling

Abstract Background There is a dearth of studies focused on the impact of self-rated health on life satisfaction among large-bodied adolescents, as well as the moderating role of physical activity in this relationship. Large-bodied adolesce...

Lost or Found? Discovering Data Needed for Research

Research Frontiers in the Field of Agricultural Resources and the Environment

From the perspective of project and paper datasets, research frontier recognition in the field of agricultural resources and the environment using the Latent Dirichlet Allocation (LDA) topic extraction model was studied. By combining the wi...

Solving Composite Fixed Point Problems with Block Updates

Various strategies are available to construct iteratively a common fixed point of nonexpansive operators by activating only a block of operators at each iteration. In the more challenging class of composite fixed point problems involving op...

Data-driven materials research enabled by natural language processing and information extraction

Given the emergence of data science and machine learning throughout all aspects of society, but particularly in the scientific domain, there is increased importance placed on obtaining data. Data in materials science are particularly hetero...

Optimising Contextual Embeddings for Meaning Conflation Deficiency Resolution in Low-Resourced Languages

Meaning conflation deficiency (MCD) presents a continual obstacle in natural language processing (NLP), especially for low-resourced and morphologically complex languages, where polysemy and contextual ambiguity diminish model precision in ...

Digital footprints as a tool to evaluate the spatiotemporal environmental impacts of grocery shopping across Great Britain

Introduction & Background Climate change represents one of the most pressing challenges of our time. Within this context, the food sector is a critical domain for intervention, accounting for approximately one-third of global greenhouse gas...

Natural language processing

Abstract Approximately 40 years ago, the goal of endowing computers with the capacity to understand natural language began. These efforts were originally callednatural language understanding, which is now more frequently callednatural langu...

A Scoping Review of Deep Learning Methods for Photoplethysmography Data.

Human Behavior Analysis: A Comprehensive Survey on Techniques, Applications, Challenges, and Future Directions

Human Behavior Analysis (HBA) has emerged as a critical interdisciplinary field, combining psychology, sociology, artificial intelligence, and data science to model, understand, and predict human behavior across diverse domains. This paper ...

Feature Rescaling and Fusion for Tiny Object Detection

Recent years have witnessed rapid developments on computer vision, however, there are still challenges in detecting tiny objects in a large-scale background. The tiny objects knowledge become sparse and weak due to their tiny size, which ma...

A Lightweight Reconstruction Model via a Neural Network for a Video Super-Resolution Model

Super-resolution in image and video processing has been a challenge in computer vision, with its progression creating substantial societal ramifications. More specifically, video super-resolution methodologies aim to restore spatial details...

Data Efficient Vision Transformer Based Model for Brain Tumor Classification in MRI

Accurate detection of brain tumors at early stages is crucial for clinical diagnosis and treatment planning. Magnetic Resonance Imaging (MRI) is the most popular method due to its soft-tissue contrast and spatial resolution. However, manual...

Inverse Evolution Layers: Physics-informed Regularizers for Image Segmentation.

Two-Argument Activation Functions Learn Soft XOR Operations Like Cortical Neurons

Neurons in the brain are complex machines with distinct functional compartments that interact nonlinearly. In contrast, neurons in artificial neural networks abstract away this complexity, typically down to a scalar activation function of a...

Deep Learning

This book focuses on deep learning (DL), which is an important aspect of data science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising....

A Deep Learning-Based Approach for Automated Coarse Registration (ACR) of Image-Guided Surgical Navigation

Coarse registration is the first step in determining the accuracy of surgical navigation. The purpose of this study was to present an automated coarse registration (ACR) methodology to improve the convenience and accuracy. For this purpose,...