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A

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Named Entity Recognition (NER) is a natural language processing task that has been widely explored for different languages in the recent decade but is still an under-researched area for the Urdu language due to its rich morphology and language complexities. Existing state-of-the-art studies on Urdu NER use various deep-learning approaches through automatic feature selection using word embeddings. This paper presents a deep learning approach for Urdu NER that harnesses FastText and Floret word embeddings to capture the contextual information of words by considering the surrounding context of words for improved feature extraction. The pre-trained FastText and Floret word embeddings are publicly available for Urdu language which are utilized to generate feature vectors of four benchmark Urdu language datasets. These features are then used as input to train various combinations of Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), Gated Recurrent Unit (GRU), CRF, and deep learning models. The results show that our proposed approach significantly outperforms existing state-of-the-art studies on Urdu NER, achieving an F-score of up to 0.98 when using BiLSTM+GRU with Floret embeddings. Error analysis shows a low classification error rate ranging from 1.24% to 3.63% across various datasets showing the robustness of the proposed approach. The performance comparison shows that the proposed approach significantly outperforms similar existing studies. metadata Khan, Hikmat Ullah and Anam, Rimsha and Anwar, Muhammad Waqas and Jamal, Muhammad Hasan and Bajwa, Usama Ijaz and Diez, Isabel de la Torre and Silva Alvarado, Eduardo René and Soriano Flores, Emmanuel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, eduardo.silva@funiber.org, emmanuel.soriano@uneatlantico.es, UNSPECIFIED (2024) A deep learning approach for Named Entity Recognition in Urdu language. PLOS ONE, 19 (3). e0300725. ISSN 1932-6203

E

Revista Subjects > Engineering Ibero-american International University > Research > Scientific Magazines
Europe University of Atlantic > Research > Scientific Magazines
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Universidad Internacional do Cuanza > Research > Scientific Magazines Abierto Español La revista Environmental Sciences and Practices (ESAP) nace como una publicación semestral con el objetivo de invitar a la reflexión y el debate para entender correctamente cual es la función, aporte y responsabilidad medioambiental no solo del mundo académico sino además en el espacio profesional. Comenzando por entender que el área de ESAP, es un espacio interdisciplinario, bajo un concepto innovador, colaborativo e integral hacia todas las áreas que convergen en una temática de interés común: el medio ambiente. Los artículos incluidos en esta revista se publican en español, portugués e inglés, atendiendo de esta manera a un espacio internacional y multicultural que permita una gestión del conocimiento actual, propia y necesaria del área medioambiental. A partir de esta página, podrá acceder a los índices de todas las ediciones de la revista Environmental Sciences and Practices, los resúmenes del artículo y los textos completos. Asimismo, en la sección "Acerca de" encontrará toda la información sobre nuestra revista, su equipo editorial, sistema de publicación y envíos en línea. metadata UNSPECIFIED mail mls@devnull.funiber.org (2022) Environmental Sciences and Practices. [Revista]

M

Revista Subjects > Comunication Europe University of Atlantic > Research > Scientific Magazines
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Universidad Internacional do Cuanza > Research > Scientific Magazines Abierto Inglés El objetivo principal de Revista MLS Communication Journal es difundir obras inéditas relacionadas con los grandes retos y desafíos de la comunicación en sus diferentes ámbitos: el periodismo, la publicidad, la comunicación audiovisual, la comunicación interactiva o la comunicación en las organizaciones, entre otros. La revista tiene interés en la difusión de trabajos académicos y científicos que identifiquen, describan y divulguen hallazgos inéditos y de interés en estos campos desde la revisión teórica, la innovación metodológica, la experimentación y la apuesta por la innovación. Los estudios publicados en MLS Communication Journal se centran en reflexionar sobre los grandes hitos, las principales interrogantes y las tendencias más destacadas del escenario comunicativo, adoptando una perspectiva de estudio teórico-práctica. La revista tiene un marcado carácter iberoamericano e internacional, por lo que puede ser utilizada para su publicación en cualquier país de origen, siempre que éstos cumplan con las diferentes fases de la investigación con rigor metodológico. Constituye, por lo tanto, un medio de difusión del conocimiento derivado de diferentes entornos socioculturales. MLS Communication Journal pública trabajos en el idioma castellano, portugués e inglés, y se edita totalmente en el último idioma, manteniendo también una edición en el idioma original del manuscrito. Su estructura organizativa se compone principalmente de investigadores, ya que una revista científica, basada en principios, debe tener sus raíces en la comunidad investigadora que tiene la producción intelectual y las contribuciones relevantes en el tema dentro de sus respectivas instituciones. metadata UNSPECIFIED mail mls@devnull.funiber.org (2021) MLS Communication Journal. [Revista]

Revista Subjects > Nutrition Europe University of Atlantic > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Universidad Internacional do Cuanza > Research > Scientific Magazines
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines Abierto Inglés La revista MLS Health and Nutrition Research nace como una publicación semestral con el objetivo de publicar artículos originales de investigación y de revisión tanto en áreas básicas como aplicadas y metodológicas que supongan una contribución científica al progreso de cualquier ámbito de la salud y nutrición como objetivo principal. Los artículos incluidos en esta revista se publican en español, portugués e inglés. La vocación internacional de esta revista promueve la difusión del conocimiento en sus diferentes áreas. metadata UNSPECIFIED mail mls@devnull.funiber.org (2022) MLS Health and Nutrition Research. [Revista]

Revista Subjects > Teaching Europe University of Atlantic > Research > Scientific Magazines
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Universidad Internacional do Cuanza > Research > Scientific Magazines Abierto Inglés Antigua Revista internacional de apoyo a la inclusión, logopedia, sociedad y multiculturalidad La revista MLS Inclusion and Society Journal es la continuación de la Revista internacional de apoyo a la inclusión, logopedia, sociedad y multiculturalidad (RIAI), revista heredera de la revista RIALAIM con mayor antigüedad, pero de la cual se independizó para tomar las directrices de las revistas actuales con indicadores de impacto. La revista MLS Inclusion and Society Journal cuenta actualmente con artículos de investigación y teóricos, tanto internacionales como nacionales, que están arbitrados por pares ciegos externos a la revista, en un proceso riguroso de selección. Los ejes temáticos son: educación inclusiva, logopedia, sociedad y multiculturalidad. La MLS Inclusion and Society Journal tiene una periodicidad de dos números al año (junio y diciembre) metadata UNSPECIFIED mail mls@devnull.funiber.org (2022) MLS Inclusion and Society Journal. [Revista]

Revista Subjects > Social Sciences Europe University of Atlantic > Research > Scientific Magazines
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Universidad Internacional do Cuanza > Research > Scientific Magazines Abierto Español MLS - Law and International politics (MLSLIP) es una publicación de periodicidad semestral con el objetivo de ser un canal que contribuya a la discusión, el intercambio de conocimiento y el debate entre académicos, responsables de política pública, empresarios, tecnólogos, científicos y los distintos actores interesados en temas de Derecho y Política, que deriven en el crecimiento del conocimiento científico de esas ciencias, producto de trabajo vinculado entre sectores público, privado y académico. MLS - Law and International politics (MLSLIP) se enfoca también en colaboraciones que engloben avances en materia de ciencia jurídica y política, con un impacto social y que contribuyan a la solución de problemas nacionales e internacionales. metadata UNSPECIFIED mail mls@devnull.funiber.org (2022) MLS Law and International Politics. [Revista]

Revista Subjects > Psychology Europe University of Atlantic > Research > Scientific Magazines
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Universidad Internacional do Cuanza > Research > Scientific Magazines Abierto Inglés MLS Psychology Research es una revista científica que tiene como finalidad publicar artículos originales de investigación y de revisión tanto en áreas básicas como aplicadas y metodológicas que supongan una contribución al progreso de cualquier ámbito de la psicología científica como objetivo principal. MLSPR acogerá a artículo que analicen la conducta y procesos mentales tanto de individuos como de grupos, y que abarque aspectos de la experiencia humana. MLSPR atenderá a diferentes enfoques dentro de la psicología: Psicología clínica, Psicoterapea, Psicología educativa, Psicología del desarrollo, Neuropsicología, Psicología social, etc. metadata UNSPECIFIED mail mls@devnull.funiber.org (2018) MLS Psychology Research. [Revista]

Revista Subjects > Physical Education and Sport Europe University of Atlantic > Research > Scientific Magazines
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Universidad Internacional do Cuanza > Research > Scientific Magazines Abierto Inglés MLS Sport Research es una revista científica que tiene como objetivo publicar artículos originales de investigación y de revisión tanto en áreas básicas como aplicadas y metodológicas que supongan una contribución al progreso en el ámbito de las Ciencias de la Actividad Física y del Deporte. Los estudios publicados deben cumplir con las diferentes fases de la investigación con rigor metodológico. MLS Sport Research atenderá a diferentes ámbitos dentro de la actividad física y el deporte: salud, educación física, prevención y readaptación de lesiones, socorrismo, nuevas tecnologías, fisiología, nutrición, psicología, dirección y gestión, entrenamiento y rendimiento deportivo. metadata UNSPECIFIED mail mls@devnull.funiber.org (2021) MLS Sport Research. [Revista]

P

Revista Subjects > Engineering Europe University of Atlantic > Research > Scientific Magazines
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Universidad Internacional do Cuanza > Research > Scientific Magazines Abierto Español La revista Project Design and Management nace como una publicación semestral con el objetivo de invitar a la reflexión y el debate para entender correctamente cual es la función, aporte y responsabilidad del área Project, Design y Management (PDM) en la actualidad, no solo del mundo académico sino además en el espacio profesional. Comenzando por entender que el área de PDM, es un espacio interdisciplinario, bajo un concepto innovador, colaborativo e integral hacia todas las áreas que participan, no solo en la administración de los recursos necesarios para un proyecto sino además, en el diseño o desarrollo del mismo. Los artículos incluidos en esta revista se publican en español, portugués e inglés, atendiendo de esta manera a un espacio internacional y multicultural que permita una gestión del conocimiento actual, propia y necesaria del área PDM. metadata UNSPECIFIED mail mls@devnull.funiber.org (2019) Project Design and Management. [Revista]

open

DiabSense: early diagnosis of non-insulin-dependent diabetes mellitus using smartphone-based human activity recognition and diabetic retinopathy analysis with Graph Neural Network

Non-Insulin-Dependent Diabetes Mellitus (NIDDM) is a chronic health condition caused by high blood sugar levels, and if not treated early, it can lead to serious complications i.e. blindness. Human Activity Recognition (HAR) offers potential for early NIDDM diagnosis, emerging as a key application for HAR technology. This research introduces DiabSense, a state-of-the-art smartphone-dependent system for early staging of NIDDM. DiabSense incorporates HAR and Diabetic Retinopathy (DR) upon leveraging the power of two different Graph Neural Networks (GNN). HAR uses a comprehensive array of 23 human activities resembling Diabetes symptoms, and DR is a prevalent complication of NIDDM. Graph Attention Network (GAT) in HAR achieved 98.32% accuracy on sensor data, while Graph Convolutional Network (GCN) in the Aptos 2019 dataset scored 84.48%, surpassing other state-of-the-art models. The trained GCN analyzed retinal images of four experimental human subjects for DR report generation, and GAT generated their average duration of daily activities over 30 days. The daily activities in non-diabetic periods of diabetic patients were measured and compared with the daily activities of the experimental subjects, which helped generate risk factors. Fusing risk factors with DR conditions enabled early diagnosis recommendations for the experimental subjects despite the absence of any apparent symptoms. The comparison of DiabSense system outcome with clinical diagnosis reports in the experimental subjects was conducted using the A1C test. The test results confirmed the accurate assessment of early diagnosis requirements for experimental subjects by the system. Overall, DiabSense exhibits significant potential for ensuring early NIDDM treatment, improving millions of lives worldwide.

Producción Científica

Md Nuho Ul Alam mail , Ibrahim Hasnine mail , Erfanul Hoque Bahadur mail , Abdul Kadar Muhammad Masum mail , Mercedes Briones Urbano mail mercedes.briones@uneatlantico.es, Manuel Masías Vergara mail manuel.masias@uneatlantico.es, Jia Uddin mail , Imran Ashraf mail , Md. Abdus Samad mail ,

Alam

open

Clinical phenotypes and short-term outcomes based on prehospital point-of-care testing and on-scene vital signs

Emergency medical services (EMSs) face critical situations that require patient risk classification based on analytical and vital signs. We aimed to establish clustering-derived phenotypes based on prehospital analytical and vital signs that allow risk stratification. This was a prospective, multicenter, EMS-delivered, ambulance-based cohort study considering six advanced life support units, 38 basic life support units, and four tertiary hospitals in Spain. Adults with unselected acute diseases managed by the EMS and evacuated with discharge priority to emergency departments were considered between January 1, 2020, and June 30, 2023. Prehospital point-of-care testing and on-scene vital signs were used for the unsupervised machine learning method (clustering) to determine the phenotypes. Then phenotypes were compared with the primary outcome (cumulative mortality (all-cause) at 2, 7, and 30 days). A total of 7909 patients were included. The median (IQR) age was 64 (51–80) years, 41% were women, and 26% were living in rural areas. Three clusters were identified: alpha 16.2% (1281 patients), beta 28.8% (2279), and gamma 55% (4349). The mortality rates for alpha, beta and gamma at 2 days were 18.6%, 4.1%, and 0.8%, respectively; at 7 days, were 24.7%, 6.2%, and 1.7%; and at 30 days, were 33%, 10.2%, and 3.2%, respectively. Based on standard vital signs and blood test biomarkers in the prehospital scenario, three clusters were identified: alpha (high-risk), beta and gamma (medium- and low-risk, respectively). This permits the EMS system to quickly identify patients who are potentially compromised and to proactively implement the necessary interventions.

Producción Científica

Raúl López-Izquierdo mail , Carlos del Pozo Vegas mail , Ancor Sanz-García mail , Agustín Mayo Íscar mail , Miguel A. Castro Villamor mail , Eduardo René Silva Alvarado mail eduardo.silva@funiber.org, Santos Gracia Villar mail santos.gracia@uneatlantico.es, Luis Alonso Dzul López mail luis.dzul@uneatlantico.es, Silvia Aparicio Obregón mail silvia.aparicio@uneatlantico.es, Rubén Calderón Iglesias mail ruben.calderon@uneatlantico.es, Joan B. Soriano mail , Francisco Martín-Rodríguez mail ,

López-Izquierdo

open

Novel model to authenticate role-based medical users for blockchain-based IoMT devices

The IoT (Internet of Things) has played a promising role in e-healthcare applications during the last decade. Medical sensors record a variety of data and transmit them over the IoT network to facilitate remote patient monitoring. When a patient visits a hospital he may need to connect or disconnect medical devices from the medical healthcare system frequently. Also, multiple entities (e.g., doctors, medical staff, etc.) need access to patient data and require distinct sets of patient data. As a result of the dynamic nature of medical devices, medical users require frequent access to data, which raises complex security concerns. Granting access to a whole set of data creates privacy issues. Also, each of these medical user need to grant access rights to a specific set of medical data, which is quite a tedious task. In order to provide role-based access to medical users, this study proposes a blockchain-based framework for authenticating multiple entities based on the trust domain to reduce the administrative burden. This study is further validated by simulation on the infura blockchain using solidity and Python. The results demonstrate that role-based authorization and multi-entities authentication have been implemented and the owner of medical data can control access rights at any time and grant medical users easy access to a set of data in a healthcare system. The system has minimal latency compared to existing blockchain systems that lack multi-entity authentication and role-based authorization.

Producción Científica

Shadab Alam mail , Muhammad Shehzad Aslam mail , Ayesha Altaf mail , Faiza Iqbal mail , Natasha Nigar mail , Juan Castanedo Galán mail juan.castanedo@uneatlantico.es, Daniel Gavilanes Aray mail daniel.gavilanes@uneatlantico.es, Isabel de la Torre Díez mail , Imran Ashraf mail ,

Alam

open

Ultra-Wide Band Radar Empowered Driver Drowsiness Detection with Convolutional Spatial Feature Engineering and Artificial Intelligence

Driving while drowsy poses significant risks, including reduced cognitive function and the potential for accidents, which can lead to severe consequences such as trauma, economic losses, injuries, or death. The use of artificial intelligence can enable effective detection of driver drowsiness, helping to prevent accidents and enhance driver performance. This research aims to address the crucial need for real-time and accurate drowsiness detection to mitigate the impact of fatigue-related accidents. Leveraging ultra-wideband radar data collected over five minutes, the dataset was segmented into one-minute chunks and transformed into grayscale images. Spatial features are retrieved from the images using a two-dimensional Convolutional Neural Network. Following that, these features were used to train and test multiple machine learning classifiers. The ensemble classifier RF-XGB-SVM, which combines Random Forest, XGBoost, and Support Vector Machine using a hard voting criterion, performed admirably with an accuracy of 96.6%. Additionally, the proposed approach was validated with a robust k-fold score of 97% and a standard deviation of 0.018, demonstrating significant results. The dataset is augmented using Generative Adversarial Networks, resulting in improved accuracies for all models. Among them, the RF-XGB-SVM model outperformed the rest with an accuracy score of 99.58%.

Producción Científica

Hafeez Ur Rehman Siddiqui mail , Ambreen Akmal mail , Muhammad Iqbal mail , Adil Ali Saleem mail , Muhammad Amjad Raza mail , Kainat Zafar mail , Aqsa Zaib mail , Sandra Dudley mail , Jon Arambarri mail jon.arambarri@uneatlantico.es, Ángel Gabriel Kuc Castilla mail , Furqan Rustam mail ,

Siddiqui

open

A Comparison of the Clinical Characteristics of Short-, Mid-, and Long-Term Mortality in Patients Attended by the Emergency Medical Services: An Observational Study

Aim: The development of predictive models for patients treated by emergency medical services (EMS) is on the rise in the emergency field. However, how these models evolve over time has not been studied. The objective of the present work is to compare the characteristics of patients who present mortality in the short, medium and long term, and to derive and validate a predictive model for each mortality time. Methods: A prospective multicenter study was conducted, which included adult patients with unselected acute illness who were treated by EMS. The primary outcome was noncumulative mortality from all causes by time windows including 30-day mortality, 31- to 180-day mortality, and 181- to 365-day mortality. Prehospital predictors included demographic variables, standard vital signs, prehospital laboratory tests, and comorbidities. Results: A total of 4830 patients were enrolled. The noncumulative mortalities at 30, 180, and 365 days were 10.8%, 6.6%, and 3.5%, respectively. The best predictive value was shown for 30-day mortality (AUC = 0.930; 95% CI: 0.919–0.940), followed by 180-day (AUC = 0.852; 95% CI: 0.832–0.871) and 365-day (AUC = 0.806; 95% CI: 0.778–0.833) mortality. Discussion: Rapid characterization of patients at risk of short-, medium-, or long-term mortality could help EMS to improve the treatment of patients suffering from acute illnesses.

Producción Científica

Rodrigo Enriquez de Salamanca Gambara mail , Ancor Sanz-García mail , Carlos del Pozo Vegas mail , Raúl López-Izquierdo mail , Irene Sánchez Soberón mail , Juan F. Delgado Benito mail , Raquel Martínez Díaz mail raquel.martinez@uneatlantico.es, Cristina Mazas Pérez-Oleaga mail cristina.mazas@uneatlantico.es, Nohora Milena Martínez López mail nohora.martinez@uneatlantico.es, Irma Dominguez Azpíroz mail irma.dominguez@unini.edu.mx, Francisco Martín-Rodríguez mail ,

Enriquez de Salamanca Gambara

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