Deepak Upreti¹, Eunmok Yang², Hyunil Kim^3,*, Changho Seo^1,4

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2239-2274, 2024, DOI:10.32604/cmes.2024.048932

Abstract Federated learning is an innovative machine learning technique that deals with centralized data storage issues while maintaining privacy and security. It involves constructing machine learning models using datasets spread across several data centers, including medical facilities, clinical research facilities, Internet of Things devices, and even mobile devices. The main goal of federated learning is to improve robust models that benefit from the collective knowledge of these disparate datasets without centralizing sensitive information, reducing the risk of data loss, privacy breaches, or data exposure. The application of federated learning in the healthcare industry holds significant promise More >

Yuetan Wang^1,2,*, Xianle Yan^1,2, Lili Liu^1,2, Xiran Lu^1,2, Lan Luo^1,2, Xiaobin Ding^1,2,*

International Journal of Mental Health Promotion, Vol.26, No.6, pp. 429-438, 2024, DOI:10.32604/ijmhp.2024.050445

Abstract Social anxiety (SA) is a prevalent mental health issue among adolescents, and vulnerable narcissism (VN) can exacerbate this condition. This study aims to investigate the impact of vulnerable narcissism on social anxiety in adolescents, specifically focusing on the mediating effects of self-concept clarity (SCC) and self-esteem (SE) in the relationship between vulnerable narcissism and social anxiety. Through cluster sampling, a questionnaire survey was conducted among 982 students from three secondary schools in two provinces. The data was analyzed using structural equation modeling (SEM). The results revealed that there was a significant negative correlation between vulnerable More >

Tao Liu¹, Huiyin Shi¹, Chen Chen^1,*, Rong Fu^2,*

International Journal of Mental Health Promotion, Vol.26, No.3, pp. 199-209, 2024, DOI:10.32604/ijmhp.2024.046303

Abstract To explore the relationship between social influence, social comparison, clarity of self-concept, and psychological anxiety among young women during their usage of social networking sites, our study selected 338 young women aged 14–34 from the social site platforms of Little Red Book and Weibo for questionnaire surveys. The Passive Social Network Utilization Scale, Social Comparison Scale (SCS), Social Influence Questionnaire, Self-Concept Clarity Scale (SCCS), and Generalized Anxiety Disorder Scale (GAD-7) were employed to measure the subjects. Our results show that the frequency of passive social media use is positively related to the level of psychological… More >

Mohamed Abdel-Basset¹, Hossam Hawash¹, Mohamed Abouhawwash^2,3,*, S. S. Askar⁴, Alshaimaa A. Tantawy¹

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1171-1187, 2024, DOI:10.32604/cmc.2023.044425

Abstract The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT scans. This study aims to investigate the indispensable need for precise and interpretable diagnostic tools for improving clinical decision-making for COVID-19 diagnosis. This paper proposes a novel deep learning approach, called Conformer Network, for explainable discrimination of viral pneumonia depending on the lung Region of Infections (ROI) within a single modality radiographic CT scan. Firstly, an efficient U-shaped transformer network is integrated for lung image segmentation. Then, a robust transfer learning technique is introduced… More >

Mohamed Ammar^1,*, Alireza Mousavi¹, Hamed Al-Raweshidy^2,*

Digital Engineering and Digital Twin, Vol.2, pp. 1-31, 2024, DOI:10.32604/dedt.2023.044930

Abstract The advent of technology around the globe based on the Internet of Things, Cloud Computing, Big Data, Cyber-Physical Systems, and digitalisation. This advancement introduced industry 4.0. It is challenging to measure how enterprises adopt the new technologies. Industry 4.0 introduced Digital Twins, given that no specific terms or definitions are given to Digital Twins still challenging to define or conceptualise the Digital Twins. Many academics and industries still use old technologies, naming it Digital Twins. This young technology is in danger of reaching the plateau despite the immense benefit to sectors. This paper proposes a… More >

Sándor Csibi¹, Mónika Csibi^2,*, József Bognár¹

International Journal of Mental Health Promotion, Vol.25, No.10, pp. 1081-1088, 2023, DOI:10.32604/ijmhp.2023.029390

Abstract Background: Components of Self, completed with the perceived social support determine the individual differences in the evaluation of a stressor and the behavioral responses toward it, such as health-related anxiety. The study set as a goal the analysis of associations between the components of Self, such as self-evaluation, sense of coherence, perceived social support, and reported health-related anxiety in an adult sample. Methods: 147 adults from the 18–73 age group (mean age 37.5) voluntarily completed the questionnaire through Qualtrics online platform containing the Short Health Anxiety Inventory, Core Self-Evaluation Scale, Social Support Assessing Scale, and… More >

Philippe Terral^*, Charlotte Bruneau, Jean-Paul Génolini

Psycho-Oncologie, Vol.17, No.3, pp. 181-189, 2023, DOI:10.32604/po.2023.044917

Abstract Objectif : La dynamique conjointe des savoirs (des bénéficiaires, intervenants, décideurs, chercheurs) et des pouvoirs (pouvoirs de paroles et d’actions, asymétries voire hiérarchies établies entre les individus et leurs savoirs) des personnes qui les portent au cœur des RISP, est analysée au prisme de la gestion des inégalités épistémiques. Nous étudions la nature des partages ou non partages de savoirs entre ces différentes catégories d’acteurs impliqués dans les interventions en santé. Méthode : La méthodologie qualitative s’appuie sur 36 entretiens et 6 années d’observations ethnographiques d’ateliers de conception ou de mise en œuvre d’un programme d’ETP, de… More >

Guillaume Broc^1,*, Julien Carretier^2,3, Sabrina Rouat⁴, Laure Guittard^5,6, Julien Péron^7,8, Béatrice Fervers^3,9, Laurent Letrilliart^6,10, Philippe Sarnin⁴, Jean-Baptiste Fassier^11,12, Marion Lamort-Bouché^6,10

Psycho-Oncologie, Vol.17, No.3, pp. 167-179, 2023, DOI:10.32604/po.2023.044730

Abstract Objectif : Le retour au travail (RAT) après un cancer du sein est un processus complexe qui interroge les trajectoires individuelles des patients et celle des acteurs dans leur environnement (ou écosystème). La planification d’une intervention dans ce contexte nécessite une méthodologie appropriée qui intègre cette complexité, à l’image de l’Intervention Mapping (IM). L’objectif de l’article est de décrire une application de l’IM pour la conception et la production d’un guide patient de RAT après un cancer du sein. Matériel et méthodes : Suivant le protocole d’IM, le guide a été coconstruit avec un comité stratégique (COS)… More >

Yuexin Huang^1,2, Suihuai Yu¹, Jianjie Chu^1,*, Zhaojing Su^1,3, Yangfan Cong¹, Hanyu Wang¹, Hao Fan⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 167-200, 2024, DOI:10.32604/cmes.2023.028268

Abstract The acquisition of valuable design knowledge from massive fragmentary data is challenging for designers in conceptual product design. This study proposes a novel method for acquiring design knowledge by combining deep learning with knowledge graph. Specifically, the design knowledge acquisition method utilises the knowledge extraction model to extract design-related entities and relations from fragmentary data, and further constructs the knowledge graph to support design knowledge acquisition for conceptual product design. Moreover, the knowledge extraction model introduces ALBERT to solve memory limitation and communication overhead in the entity extraction module, and uses multi-granularity information to overcome More >

Quy Thy Truong¹ , Guillaume Touya², Cyril de Runz³

Revue Internationale de Géomatique, Vol.29, No.1, pp. 31-56, 2019, DOI:10.3166/rig.2019.00073

Abstract Dans un contexte où le vandalisme de l’information géographique volontaire constitue une réelle menace pour la qualité des données, cet article propose une technique permettant de le détecter. Tout d’abord, nous examinons les différentes définitions du vandalisme, mettant en avant la complexité de cette notion. Une étude des cas déjà avérés de vandalisme dans OpenStreetMap (OSM) est présentée. Puis, nous expérimentons la détection du vandalisme des données OSM en utilisant une méthode de détection d’anomalie par classification non supervisée. L’analyse de nos résultats initiaux conduit alors à une discussion sur la pertinence de construire un More >