The Role of Cloud-Native Infrastructures in Supporting Autonomous and Uncrewed Systems (UXS) in Operations
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
This study examined the role of cloud-native infrastructures in supporting autonomous and uncrewed systems (UXS) in operations, addressing the problem that many UXS deployments depend on rigid, centralized, or insufficiently scalable infrastructures that struggle to support dynamic workloads, mission reconfiguration, fault tolerance, communication continuity, and secure data exchange in complex operational environments. The purpose of the research was to determine whether key cloud-native capabilities significantly enhance UXS operational effectiveness across case-based settings. A quantitative, cross-sectional, case-study-based design was adopted, using purposive sampling and a structured five-point Likert scale questionnaire administered to professionals engaged in logistics, industrial inspection, maritime surveillance, emergency/security, and ICT/infrastructure contexts. Out of 180 distributed questionnaires, 156 were returned, and 150 valid responses were used for analysis, producing an 83.3% usable response rate. The independent variables were scalability, flexibility, reliability, and security with data management, while the dependent variable was UXS operational effectiveness. Data were analyzed through descriptive statistics, Cronbach’s alpha, Pearson correlation, and multiple regression. The findings showed consistently high perceptions across all major constructs, with mean scores of 4.18 for scalability, 4.09 for flexibility, 4.23 for reliability, 4.15 for security and data management, and 4.21 for UXS operational effectiveness. Reliability coefficients were strong, ranging from 0.81 to 0.88. Correlation results indicated significant positive relationships with operational effectiveness, led by reliability (r = .71), followed by security and data management (r = .67), scalability (r = .64), and flexibility (r = .58), all significant at p < .01. Regression analysis further showed that the model explained 65.9% of the variance in UXS operational effectiveness (R² = .659, F = 69.98, p < .001), with reliability emerging as the strongest predictor (β = .31, p < .001), followed by security and data management (β = .26, p = .002), scalability (β = .24, p = .003), and flexibility (β = .17, p = .021). The study implies that organizations should treat cloud-native infrastructure as mission-critical operational architecture for improving resilience, coordination, adaptability, and readiness in UXS environments.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle