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2023

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 (2023) 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.

2022

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 (2022) 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 Wed Jun 19 23:47:12 2024 UTC.

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

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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="/12750/1/s41598-024-63831-0.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Efficient deep learning-based approach for malaria detection using red blood cell smears

Malaria is an extremely malignant disease and is caused by the bites of infected female mosquitoes. This disease is not only infectious among humans, but among animals as well. Malaria causes mild symptoms like fever, headache, sweating and vomiting, and muscle discomfort; severe symptoms include coma, seizures, and kidney failure. The timely identification of malaria parasites is a challenging and chaotic endeavor for health staff. An expert technician examines the schematic blood smears of infected red blood cells through a microscope. The conventional methods for identifying malaria are not efficient. Machine learning approaches are effective for simple classification challenges but not for complex tasks. Furthermore, machine learning involves rigorous feature engineering to train the model and detect patterns in the features. On the other hand, deep learning works well with complex tasks and automatically extracts low and high-level features from the images to detect disease. In this paper, EfficientNet, a deep learning-based approach for detecting Malaria, is proposed that uses red blood cell images. Experiments are carried out and performance comparison is made with pre-trained deep learning models. In addition, k-fold cross-validation is also used to substantiate the results of the proposed approach. Experiments show that the proposed approach is 97.57% accurate in detecting Malaria from red blood cell images and can be beneficial practically for medical healthcare staff.

Producción Científica

Muhammad Mujahid mail , Furqan Rustam mail , Rahman Shafique mail , Elizabeth Caro Montero mail elizabeth.caro@uneatlantico.es, Eduardo René Silva Alvarado mail eduardo.silva@funiber.org, Isabel de la Torre Diez mail , Imran Ashraf mail ,

Mujahid

<a href="/12751/1/s12874-024-02249-8.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Feature group partitioning: an approach for depression severity prediction with class balancing using machine learning algorithms

In contemporary society, depression has emerged as a prominent mental disorder that exhibits exponential growth and exerts a substantial influence on premature mortality. Although numerous research applied machine learning methods to forecast signs of depression. Nevertheless, only a limited number of research have taken into account the severity level as a multiclass variable. Besides, maintaining the equality of data distribution among all the classes rarely happens in practical communities. So, the inevitable class imbalance for multiple variables is considered a substantial challenge in this domain. Furthermore, this research emphasizes the significance of addressing class imbalance issues in the context of multiple classes. We introduced a new approach Feature group partitioning (FGP) in the data preprocessing phase which effectively reduces the dimensionality of features to a minimum. This study utilized synthetic oversampling techniques, specifically Synthetic Minority Over-sampling Technique (SMOTE) and Adaptive Synthetic (ADASYN), for class balancing. The dataset used in this research was collected from university students by administering the Burn Depression Checklist (BDC). For methodological modifications, we implemented heterogeneous ensemble learning stacking, homogeneous ensemble bagging, and five distinct supervised machine learning algorithms. The issue of overfitting was mitigated by evaluating the accuracy of the training, validation, and testing datasets. To justify the effectiveness of the prediction models, balanced accuracy, sensitivity, specificity, precision, and f1-score indices are used. Overall, comprehensive analysis demonstrates the discrimination between the Conventional Depression Screening (CDS) and FGP approach. In summary, the results show that the stacking classifier for FGP with SMOTE approach yields the highest balanced accuracy, with a rate of 92.81%. The empirical evidence has demonstrated that the FGP approach, when combined with the SMOTE, able to produce better performance in predicting the severity of depression. Most importantly the optimization of the training time of the FGP approach for all of the classifiers is a significant achievement of this research.

Producción Científica

Tumpa Rani Shaha mail , Momotaz Begum mail , Jia Uddin mail , Vanessa Yélamos Torres mail vanessa.yelamos@funiber.org, Josep Alemany Iturriaga mail josep.alemany@uneatlantico.es, Imran Ashraf mail , Md. Abdus Samad mail ,

Shaha

<a href="/11941/1/healthcare-12-00942.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Risk Factors for Eating Disorders in University Students: The RUNEAT Study

The purpose of the study is to assess the risk of developing general eating disorders (ED), anorexia nervosa (AN), and bulimia nervosa (BN), as well as to examine the effects of gender, academic year, place of residence, faculty, and diet quality on that risk. Over two academic years, 129 first- and fourth-year Uneatlántico students were included in an observational descriptive study. The self-administered tests SCOFF, EAT-26, and BITE were used to determine the participants’ risk of developing ED. The degree of adherence to the Mediterranean diet (MD) was used to evaluate the quality of the diet. Data were collected at the beginning (T1) and at the end (T2) of the academic year. The main results were that at T1, 34.9% of participants were at risk of developing general ED, AN 3.9%, and BN 16.3%. At T2, these percentages were 37.2%, 14.7%, and 8.5%, respectively. At T2, the frequency of general ED in the female group was 2.5 times higher (OR: 2.55, 95% CI: 1.22–5.32, p = 0.012). The low-moderate adherence to the MD students’ group was 0.92 times less frequent than general ED at T2 (OR: 0.921, 95%CI: 0.385–2.20, p < 0.001). The most significant risk factor for developing ED is being a female in the first year of university. Moreover, it appears that the likelihood of developing ED generally increases during the academic year.

Producción Científica

Imanol Eguren García mail imanol.eguren@uneatlantico.es, Sandra Sumalla Cano mail sandra.sumalla@uneatlantico.es, Sandra Conde González mail , Anna Vila-Martí mail , Mercedes Briones Urbano mail mercedes.briones@uneatlantico.es, Raquel Martínez Díaz mail raquel.martinez@uneatlantico.es, Iñaki Elío Pascual mail inaki.elio@uneatlantico.es,

Eguren García

<a href="/11592/1/fchem-12-1361980.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Efficacy and classification of Sesamum indicum linn seeds with Rosa damascena mill oil in uncomplicated pelvic inflammatory disease using machine learning

Background and objectives: As microbes are developing resistance to antibiotics, natural, botanical drugs or traditional herbal medicine are presently being studied with an eye of great curiosity and hope. Hence, complementary and alternative treatments for uncomplicated pelvic inflammatory disease (uPID) are explored for their efficacy. Therefore, this study determined the therapeutic efficacy and safety of Sesamum indicum Linn seeds with Rosa damascena Mill Oil in uPID with standard control. Additionally, we analyzed the data with machine learning. Materials and methods: We included 60 participants in a double-blind, double-dummy, randomized standard-controlled study. Participants in the Sesame and Rose oil group (SR group) (n = 30) received 14 days course of black sesame powder (5 gm) mixed with rose oil (10 mL) per vaginum at bedtime once daily plus placebo capsules orally. The standard group (SC), received doxycycline 100 mg twice and metronidazole 400 mg thrice orally plus placebo per vaginum for the same duration. The primary outcome was a clinical cure at post-intervention for visual analogue scale (VAS) for lower abdominal pain (LAP), and McCormack pain scale (McPS) for abdominal-pelvic tenderness. The secondary outcome included white blood cells (WBC) cells in the vaginal wet mount test, safety profile, and health-related quality of life assessed by SF-12. In addition, we used AdaBoost (AB), Naïve Bayes (NB), and Decision Tree (DT) classifiers in this study to analyze the experimental data. Results: The clinical cure for LAP and McPS in the SR vs SC group was 82.85% vs 81.48% and 83.85% vs 81.60% on Day 15 respectively. On Day 15, pus cells less than 10 in the SR vs SC group were 86.6% vs 76.6% respectively. No adverse effects were reported in both groups. The improvement in total SF-12 score on Day 30 for the SR vs SC group was 82.79% vs 80.04% respectively. In addition, our Naive Bayes classifier based on the leave-one-out model achieved the maximum accuracy (68.30%) for the classification of both groups of uPID. Conclusion: We concluded that the SR group is cost-effective, safer, and efficacious for curing uPID. Proposed alternative treatment (test drug) could be a substitute of standard drug used for Female genital tract infections.

Producción Científica

X. Sumbul mail , Arshiya Sultana mail , Md Belal Bin Heyat mail , Khaleequr Rahman mail , Faijan Akhtar mail , Saba Parveen mail , Mercedes Briones Urbano mail mercedes.briones@uneatlantico.es, Vivian Lipari mail vivian.lipari@uneatlantico.es, Isabel De la Torre Díez mail , Azmat Ali Khan mail , Abdul Malik mail ,

Sumbul