Browse by Lenguaje

Up a level
Export as [feed] Atom [feed] RSS 1.0 [feed] RSS 2.0
Group by: Date | Title | Creators | Item Type | No Grouping
Jump to: Thesis
Number of items: 2.

Thesis

Thesis Subjects > Social Sciences Ibero-american International University > Research > Doctoral Thesis
Ibero-american International University > Research > Doctoral Thesis
Cerrado Francés La problématique posée par le handicap a été et reste une préoccupation majeure des pouvoirs publics car elle véhicule des représentations conduisant à des attitudes répréhensibles. Depuis l'Antiquité, la prise en charge des personnes handicapées est dépendante de la stigmatisation liée à des politiques sociales contextualisées. Pour ce faire, afin de rendre efficaces les interventions des acteurs et de définir des projets et programmes susceptibles d'améliorer la qualité de vie des personnes handicapées, la communauté scientifique a jugé opportun de procéder à des classifications du handicap : la classification internationale des maladies chroniques (CIM), la Classification internationale du handicap (CIH) et la Classification internationale du fonctionnement (CIF). Ainsi, on note une nette ressemblance entre les composantes de la qualité de vie et celles de la CIF. Cet état de fait est corroboré par les résultats des enquêtes qui militent en faveur de la mobilisation des dimensions objectives et subjectives de la qualité de vie. C'est dans ce contexte que l'étude révèle que 59% des personnes interrogées perçoivent la bonne santé comme l'équivalent d'une bonne qualité de vie, tandis que 92,3% la considèrent comme sa dimension la plus importante. Par conséquent, les politiques publiques d'action sociale traduites en projets et programmes doivent sans aucun doute porter sur la santé au sens large afin de contribuer à l'amélioration de la qualité de vie des personnes handicapées. De manière explicite, chaque personne handicapée définira son projet de vie axé sur : la réadaptation à base communautaire, l'approche territoriale, l'autonomisation et l'érection d'infrastructures sociales. metadata SAMB, Sérigne Mapathé mail serigne.samb@doctorado.unib.org (2024) Analyse des politiques publiques d'action sociale sur la qualité de vie des personnes handicapées du Sénégal: le cas du département de bignona. Doctoral thesis, UNSPECIFIED.

Thesis Subjects > Social Sciences Ibero-american International University > Research > Doctoral Thesis Cerrado Francés L’économie ivoirienne a connu un dynamisme au cours de la dernière décennie, marqué par des taux de croissance du Produit Intérieur Brut (PIB) successifs de 7% en moyenne. Cependant, le pays reste confronté au problème de sous-emploi notamment des jeunes, en dépit d’un faible niveau de taux de chômage (2,8% en moyenne), voilant une précarité des emplois et un chômage accru chez les jeunes diplômés. D’où la nécessité de disséquer les composantes du marché du travail afin d’élaborer des politiques publiques d’emploi plus adaptées.La présente recherche décrit la structure actuelle du marché du travail, ses interactions avec les différents acteurs, avec un focus sur l’efficacité de certains programmes et projets d’emploi. La méthodologie utilisée est basée sur les méthodes statistiques quantitatives d’analyse descriptive, notamment l’analyse factorielle. Par ailleurs, l’analyse de l’efficacité des projets et programmes s’est faite à l’aide des outils d’analyse de la science indicamétrique. Les données de cette recherche proviennent de l’Enquête Nationale sur l’Emploi (ENE) réalisée en 2019 auprès de plus de 10 000 ménages. Les analyses mettent en exergue les principales caractéristiques suivantes du marché du travail ivoirien :-Les femmes sont désavantagées sur le marché du travail par rapport aux hommes, notamment en milieu urbain ;-Les personnes moins instruites ou n’ayant aucun diplôme sont plus insérées que celles plus instruites ;-Les jeunes détenteurs de diplômes de l’enseignement technique et professionnel sont plus insérés que leurs homologues détenteurs de diplômes de l’enseignement général ;-Le chômage est plus élevé chez les jeunes de moins de 35 ans par rapport aux autres groupes d’âge ;-Le chômage est plus élevé chez les personnes célibataires par rapport à celles en union ;-La prise en compte des capacités intrinsèques des gestionnaires des projets accroit significativement leur probabilité de succès. metadata Meite, Inza mail mitmsginza@yahoo.fr (2024) Structure du marché du travail en Côte d’Ivoire : une étude descriptive à la lumière des programmes et projets publics d’emploi. Doctoral thesis, UNSPECIFIED.

This list was generated on Thu Oct 10 18:13:08 2024 UTC.

<a href="/10290/1/Influence%20of%20E-learning%20training%20on%20the%20acquisition%20of%20competences%20in%20basketball%20coaches%20in%20Cantabria.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

en

open

Influence of E-learning training on the acquisition of competences in basketball coaches in Cantabria

The main aim of this study was to analyse the influence of e-learning training on the acquisition of competences in basketball coaches in Cantabria. The current landscape of basketball coach training shows an increasing demand for innovative training models and emerging pedagogies, including e-learning-based methodologies. The study sample consisted of fifty students from these courses, all above 16 years of age (36 males, 14 females). Among them, 16% resided outside the autonomous community of Cantabria, 10% resided more than 50 km from the city of Santander, 36% between 10 and 50 km, 14% less than 10 km, and 24% resided within Santander city. Data were collected through a Google Forms survey distributed by the Cantabrian Basketball Federation to training course students. Participation was voluntary and anonymous. The survey, consisting of 56 questions, was validated by two sports and health doctors and two senior basketball coaches. The collected data were processed and analysed using Microsoft® Excel version 16.74, and the results were expressed in percentages. The analysis revealed that 24.60% of the students trained through the e-learning methodology considered themselves fully qualified as basketball coaches, contrasting with 10.98% of those trained via traditional face-to-face methodology. The results of the study provide insights into important characteristics that can be adjusted and improved within the investigated educational process. Moreover, the study concludes that e-learning training effectively qualifies basketball coaches in Cantabria.

Producción Científica

Josep Alemany Iturriaga mail josep.alemany@uneatlantico.es, Álvaro Velarde-Sotres mail alvaro.velarde@uneatlantico.es, Javier Jorge mail , Kamil Giglio mail ,

Alemany Iturriaga

<a class="ep_document_link" href="/14584/1/s41598-024-73664-6.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

en

open

Performance of the 4C and SEIMC scoring systems in predicting mortality from onset to current COVID-19 pandemic in emergency departments

The evolution of the COVID-19 pandemic has been associated with variations in clinical presentation and severity. Similarly, prediction scores may suffer changes in their diagnostic accuracy. The aim of this study was to test the 30-day mortality predictive validity of the 4C and SEIMC scores during the sixth wave of the pandemic and to compare them with those of validation studies. This was a longitudinal retrospective observational study. COVID-19 patients who were admitted to the Emergency Department of a Spanish hospital from December 15, 2021, to January 31, 2022, were selected. A side-by-side comparison with the pivotal validation studies was subsequently performed. The main measures were 30-day mortality and the 4C and SEIMC scores. A total of 27,614 patients were considered in the study, including 22,361 from the 4C, 4,627 from the SEIMC and 626 from our hospital. The 30-day mortality rate was significantly lower than that reported in the validation studies. The AUCs were 0.931 (95% CI: 0.90–0.95) for 4C and 0.903 (95% CI: 086–0.93) for SEIMC, which were significantly greater than those obtained in the first wave. Despite the changes that have occurred during the coronavirus disease 2019 (COVID-19) pandemic, with a reduction in lethality, scorecard systems are currently still useful tools for detecting patients with poor disease risk, with better prognostic capacity.

Producción Científica

Pedro Ángel de Santos Castro mail , Carlos del Pozo Vegas mail , Leyre Teresa Pinilla Arribas mail , Daniel Zalama Sánchez mail , Ancor Sanz-García mail , Tony Giancarlo Vásquez del Águila mail , Pablo González Izquierdo mail , Sara de Santos Sánchez mail , Cristina Mazas Pérez-Oleaga mail cristina.mazas@uneatlantico.es, Irma Dominguez Azpíroz mail irma.dominguez@unini.edu.mx, Iñaki Elío Pascual mail inaki.elio@uneatlantico.es, Francisco Martín-Rodríguez mail ,

de Santos Castro

<a class="ep_document_link" href="/14482/1/sensors-24-06325.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

en

open

Smart Physiotherapy: Advancing Arm-Based Exercise Classification with PoseNet and Ensemble Models

Telephysiotherapy has emerged as a vital solution for delivering remote healthcare, particularly in response to global challenges such as the COVID-19 pandemic. This study seeks to enhance telephysiotherapy by developing a system capable of accurately classifying physiotherapeutic exercises using PoseNet, a state-of-the-art pose estimation model. A dataset was collected from 49 participants (35 males, 14 females) performing seven distinct exercises, with twelve anatomical landmarks then extracted using the Google MediaPipe library. Each landmark was represented by four features, which were used for classification. The core challenge addressed in this research involves ensuring accurate and real-time exercise classification across diverse body morphologies and exercise types. Several tree-based classifiers, including Random Forest, Extra Tree Classifier, XGBoost, LightGBM, and Hist Gradient Boosting, were employed. Furthermore, two novel ensemble models called RandomLightHist Fusion and StackedXLightRF are proposed to enhance classification accuracy. The RandomLightHist Fusion model achieved superior accuracy of 99.6%, demonstrating the system’s robustness and effectiveness. This innovation offers a practical solution for providing real-time feedback in telephysiotherapy, with potential to improve patient outcomes through accurate monitoring and assessment of exercise performance.

Producción Científica

Shahzad Hussain mail , Hafeez Ur Rehman Siddiqui mail , Adil Ali Saleem mail , Muhammad Amjad Raza mail , Josep Alemany Iturriaga mail josep.alemany@uneatlantico.es, Álvaro Velarde-Sotres mail alvaro.velarde@uneatlantico.es, Isabel De la Torre Díez mail , Sandra Dudley mail ,

Hussain

<a href="/14281/1/s41598-024-69663-2.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

en

open

An enhanced approach for predicting air pollution using quantum support vector machine

The essence of quantum machine learning is to optimize problem-solving by executing machine learning algorithms on quantum computers and exploiting potent laws such as superposition and entanglement. Support vector machine (SVM) is widely recognized as one of the most effective classification machine learning techniques currently available. Since, in conventional systems, the SVM kernel technique tends to sluggish down and even fail as datasets become increasingly complex or jumbled. To compare the execution time and accuracy of conventional SVM classification to that of quantum SVM classification, the appropriate quantum features for mapping need to be selected. As the dataset grows complex, the importance of selecting an appropriate feature map that outperforms or performs as well as the classification grows. This paper utilizes conventional SVM to select an optimal feature map and benchmark dataset for predicting air quality. Experimental evidence demonstrates that the precision of quantum SVM surpasses that of classical SVM for air quality assessment. Using quantum labs from IBM’s quantum computer cloud, conventional and quantum computing have been compared. When applied to the same dataset, the conventional SVM achieved an accuracy of 91% and 87% respectively, whereas the quantum SVM demonstrated an accuracy of 97% and 94% respectively for air quality prediction. The study introduces the use of quantum Support Vector Machines (SVM) for predicting air quality. It emphasizes the novel method of choosing the best quantum feature maps. Through the utilization of quantum-enhanced feature mapping, our objective is to exceed the constraints of classical SVM and achieve unparalleled levels of precision and effectiveness. We conduct precise experiments utilizing IBM’s state-of-the-art quantum computer cloud to compare the performance of conventional and quantum SVM algorithms on a shared dataset.

Producción Científica

Omer Farooq mail , Maida Shahid mail , Shazia Arshad mail , Ayesha Altaf mail , Faiza Iqbal mail , Yini Airet Miro Vera mail , Miguel Angel Lopez Flores mail , Imran Ashraf mail ,

Farooq

<a href="/14282/1/s40537-024-00959-w.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

en

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