Daniel Ramos
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View article: Oxidative Stress and Inflammation in Hypoxemic Respiratory Diseases and Their Comorbidities: Molecular Insights and Diagnostic Advances in Chronic Obstructive Pulmonary Disease and Sleep Apnea
Oxidative Stress and Inflammation in Hypoxemic Respiratory Diseases and Their Comorbidities: Molecular Insights and Diagnostic Advances in Chronic Obstructive Pulmonary Disease and Sleep Apnea Open
In chronic respiratory diseases (CRDs), oxidative stress and inflammation are closely linked, driving disease onset, progression, and comorbidities. Oxidative stress activates inflammatory pathways, while chronic inflammation promotes furt…
View article: Oxidative Stress and Inflammation in COPD and Sleep Apnea and Its Comorbidities. Molecular Insights and Artificial Intelligence Approaches in Diagnosis and Prognosis
Oxidative Stress and Inflammation in COPD and Sleep Apnea and Its Comorbidities. Molecular Insights and Artificial Intelligence Approaches in Diagnosis and Prognosis Open
In chronic respiratory diseases (CRDs), oxidative stress and inflammation exhibit a strong pathophysiological interplay, playing essential roles in the onset and progression of these conditions and their associated comorbidities. Oxidative…
View article: Feature Integration Strategies for Neural Speaker Diarization in Conversational Telephone Speech
Feature Integration Strategies for Neural Speaker Diarization in Conversational Telephone Speech Open
This paper addresses the challenge of optimizing end-to-end neural diarization systems for conversational telephone speech, focusing on diverse acoustic features beyond traditional Mel-filterbanks. We present a methodological framework for…
View article: Exploring Large Protein Language Models in Constrained Evaluation Scenarios within the FLIP Benchmark
Exploring Large Protein Language Models in Constrained Evaluation Scenarios within the FLIP Benchmark Open
In this study, we expand upon the FLIP benchmark-designed for evaluating protein fitness prediction models in small, specialized prediction tasks-by assessing the performance of state-of-the-art large protein language models, including ESM…
View article: Evaluating Posterior Probabilities: Decision Theory, Proper Scoring Rules, and Calibration
Evaluating Posterior Probabilities: Decision Theory, Proper Scoring Rules, and Calibration Open
Most machine learning classifiers are designed to output posterior probabilities for the classes given the input sample. These probabilities may be used to make the categorical decision on the class of the sample; provided as input to a do…
View article: Enhancing Conformer-Based Sound Event Detection Using Frequency Dynamic Convolutions and BEATs Audio Embeddings
Enhancing Conformer-Based Sound Event Detection Using Frequency Dynamic Convolutions and BEATs Audio Embeddings Open
Over the last few years, most of the tasks employing Deep Learning techniques for audio processing have achieved state-of-the-art results employing Conformer-based systems. However, when it comes to sound event detection (SED), it was scar…
View article: Voxceleb-ESP: preliminary experiments detecting Spanish celebrities from their voices
Voxceleb-ESP: preliminary experiments detecting Spanish celebrities from their voices Open
This paper presents VoxCeleb-ESP, a collection of pointers and timestamps to YouTube videos facilitating the creation of a novel speaker recognition dataset. VoxCeleb-ESP captures real-world scenarios, incorporating diverse speaking styles…
View article: Spreading the Love for Mathematical Research Data
Spreading the Love for Mathematical Research Data Open
The Mathematical Research Data Initiative (MaRDI) is the NFDI consortium for the mathematics community. We outline some of the challenges we face in spreading a culture of mathematical research data to a large community and starting a cult…
View article: Building Energy Consumption Forecast under Different Anticipations on a Green Computation Perspective
Building Energy Consumption Forecast under Different Anticipations on a Green Computation Perspective Open
Electrical buildings are composed by smart grids technologies intended on improving the energy efficiency. Nowadays, forecasting algorithms are crucial to formulate advance decisions resulting in lower energy costs. This paper uses two for…
View article: Dp71 Point Mutations Induce Protein Aggregation, Loss of Nuclear Lamina Integrity and Impaired Braf35 and Ibraf Function in Neuronal Cells
Dp71 Point Mutations Induce Protein Aggregation, Loss of Nuclear Lamina Integrity and Impaired Braf35 and Ibraf Function in Neuronal Cells Open
Dystrophin Dp71 is the most abundant product of the Duchenne muscular dystrophy gene in the nervous system, and mutations impairing its function have been associated with the neurodevelopmental symptoms present in a third of DMD patients. …
View article: Gaussian Processes for radiation dose prediction in nuclear power plant reactors
Gaussian Processes for radiation dose prediction in nuclear power plant reactors Open
In nuclear power plants, there are high-exposure jobs, like refuelling and maintenance, that require getting close
\nto the reactor between operation cycles. Therefore, reducing radiation dose during these periods is of paramount
\nimporta…
View article: Adaptive Temperature Scaling for Robust Calibration of Deep Neural Networks
Adaptive Temperature Scaling for Robust Calibration of Deep Neural Networks Open
In this paper, we study the post-hoc calibration of modern neural networks, a problem that has drawn a lot of attention in recent years. Many calibration methods of varying complexity have been proposed for the task, but there is no consen…
View article: Introduction to Speech Processing: 2nd Edition
Introduction to Speech Processing: 2nd Edition Open
This release is primarily about migrating all content to jupyter-books and git. The published version is now hosted at https://speechprocessingbook.aalto.fi. In addition to github, the release has long-term storage location at Zenodo, whic…
View article: Energy Forecast in Buildings Addressing Computation Consumption in a Green Computing Approach
Energy Forecast in Buildings Addressing Computation Consumption in a Green Computing Approach Open
The decrease of the energy costs and the sustainability in buildings are important to ensure the energy management of buildings. The use of algorithms for forecasting activities is crucial to reduce the energy costs. Green computing plays …
View article: Selection of features in reinforcement learning applied to energy consumption forecast in buildings according to different contexts
Selection of features in reinforcement learning applied to energy consumption forecast in buildings according to different contexts Open
The management of buildings responsible for the energy storage and control can be optimized with the support of forecasting techniques. These are essential on the finding of load consumption patterns being these last involved in decisions …
View article: Green computing: a realistic evaluation of energy consumption for building load forecasting computation
Green computing: a realistic evaluation of energy consumption for building load forecasting computation Open
Aim: The methodology proposed in this paper aims at analyzing the energy consumption, electricity costs, computation time, and accuracy associated with each forecasting algorithm and approach. Furthermore, a monitoring infrastructure is co…
View article: A Contextual Reinforcement Learning Approach for Electricity Consumption Forecasting in Buildings
A Contextual Reinforcement Learning Approach for Electricity Consumption Forecasting in Buildings Open
The energy management of buildings plays a vital role in the energy sector. With that in mind, and targeting an accurate forecast of electricity consumption, in the present paper is aimed to provide decision on the best prediction algorith…