C. Eira Nunes, B. Mouton, S. Van Petegem

Psycho-Oncologie, Vol.16, No.4, pp. 351-358, 2022, DOI:10.3166/pson-2022-0216

Abstract Cet article, bien que non exhaustif, présente un état actuel des connaissances empiriques et théoriques sur la surprotection parentale dans des familles où l’enfant est atteint d’un cancer. Nous abordons les caractéristiques de cette surprotection ainsi que la question de sa fonction adaptative et ses effets potentiellement délétères sur l’enfant dans ce contexte spécifique. Cette revue identifie également certains facteurs familiaux et sociétaux qui peuvent promouvoir la surprotection chez les mères et les pères, soulignant l’importance du contexte familial et sociétal dans l’étude des pratiques parentales en oncologie pédiatrique. More >

Luc Merchez¹ , Hélène Mathian² , Julie Le Gall³

Revue Internationale de Géomatique, Vol.30, No.1, pp. 85-104, 2020, DOI:10.3166/rig.2020.00103

Abstract La question de l’alimentation et de la caractérisation des environnements alimentaires a déjà fait l’objet de nombreuses études et développements méthodologiques pour rendre compte des différentiels d’accessibilité. Aux Etats-Unis, essentiellement à l’aune de questions sur la santé, ces études ont conduit à identifier des « déserts alimentaires . Cette question éminemment spatiale, qui repose sur la notion d’accessibilité, est souvent approchée par des enquêtes et entretiens ou des approches quantitatives basées sur des calculs d’accessibilités géographiques. Dans la lignée de ces travaux, nous proposons d’explorer la transférabilité de cette notion de « désert » à un espace métropolitain français. La… More >

Claire Prudhomme¹ , Ana Roxin² , Christophe Cruz² , Frank Boochs¹

Revue Internationale de Géomatique, Vol.30, No.1, pp. 37-65, 2020, DOI:10.3166/rig.2020.00102

Abstract La gestion de catastrophe nécessite une préparation collaborative entre les divers intervenants. Les exercices collaboratifs visent à entraîner les intervenants à appliquer les plans préparés ainsi qu’à identifier les problèmes et points d’améliorations potentiels. Ces exercices étant coûteux, la simulation informatique est un outil permettant d’optimiser la préparation à l’aide d’une plus grande diversité de cas. Cependant, les travaux de recherche centrés sur la simulation et la gestion de catastrophe sont spécialisés sur un problème spécifique plutôt que sur l’optimisation globale des plans préparés. Cette limite s’explique par le défi que constitue la réalisation d’un modèle de simulation capable de… More >

Zhifang Liao¹, Hao Gu¹, Shichao Zhang¹, Ronghui Mo¹, Yan Zhang^2,*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 599-618, 2023, DOI:10.32604/iasc.2023.036794

Abstract Context-Sensitive Task (CST) is a complex task type in crowdsourcing, such as handwriting recognition, route plan, and audio transcription. The current result inference algorithms can perform well in simple crowdsourcing tasks, but cannot obtain high-quality inference results for CSTs. The conventional method to solve CSTs is to divide a CST into multiple independent simple subtasks for crowdsourcing, but this method ignores the context correlation among subtasks and reduces the quality of result inference. To solve this problem, we propose a result inference algorithm based on the Partially ordered set and Tree augmented naive Bayes Infer (P&T-Inf) for CSTs. Firstly, we… More >

Muhammad Aasim Qureshi^1,*, Muhammad Asif², Saira Anwar³

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 439-453, 2023, DOI:10.32604/iasc.2023.036102

Abstract Learning programming and using programming languages are the essential aspects of computer science education. Students use programming languages to write their programs. These computer programs (students or practitioners written) make computers artificially intelligent and perform the tasks needed by the users. Without these programs, the computer may be visioned as a pointless machine. As the premise of writing programs is situated with specific programming languages, enormous efforts have been made to develop and create programming languages. However, each programming language is domain-specific and has its nuances, syntax and semantics, with specific pros and cons. These language-specific details, including syntax and… More >

Kun Yang^1,2, Lei Zhao¹, Xianghui Wang¹, Mingyang Zhang¹, Linyan Xue^1,2, Shuang Liu^1,2, Kun Liu^1,2,3,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5159-5176, 2023, DOI:10.32604/cmc.2023.036401

Abstract The diagnosis of COVID-19 requires chest computed tomography (CT). High-resolution CT images can provide more diagnostic information to help doctors better diagnose the disease, so it is of clinical importance to study super-resolution (SR) algorithms applied to CT images to improve the resolution of CT images. However, most of the existing SR algorithms are studied based on natural images, which are not suitable for medical images; and most of these algorithms improve the reconstruction quality by increasing the network depth, which is not suitable for machines with limited resources. To alleviate these issues, we propose a residual feature attentional fusion… More >

R. Sujatha^1,*, T. Abirami²

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1775-1787, 2023, DOI:10.32604/csse.2023.031552

Abstract The digital technologies that run based on users’ content provide a platform for users to help air their opinions on various aspects of a particular subject or product. The recommendation agents play a crucial role in personalizing the needs of individual users. Therefore, it is essential to improve the user experience. The recommender system focuses on recommending a set of items to a user to help the decision-making process and is prevalent across e-commerce and media websites. In Context-Aware Recommender Systems (CARS), several influential and contextual variables are identified to provide an effective recommendation. A substantial trade-off is applied in… More >

Miaomiao Yang^1,2, Guosheng Huang^1,2, Junwei Liu³, Yanshuang Gui^1,2, Qixu Wang^1,2,*, Xingshu Chen^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1879-1898, 2023, DOI:10.32604/cmes.2023.026371

Abstract With the advantages of lightweight and high resource utilization, cloud-native technology with containers as the core is gradually becoming the mainstream technical architecture for information infrastructure. However, malware attacks such as Doki and Symbiote threaten the container runtime’s security. Malware initiates various types of runtime anomalies based on process form (e.g., modifying the process of a container, and opening the external ports). Fortunately, dynamic monitoring mechanisms have proven to be a feasible solution for verifying the trusted state of containers at runtime. Nevertheless, the current routine dynamic monitoring mechanisms for baseline data protection are still based on strong security assumptions.… More >

Yizhi Liu^1,3, Rutian Qing^1,3, Yijiang Zhao^1,3,*, Xuesong Wang^1,3, Zhuhua Liao^1,3, Qinghua Li^1,2, Buqing Cao^1,3

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2505-2519, 2023, DOI:10.32604/csse.2023.021615

Abstract Short-term GPS data based taxi pick-up area recommendation can improve the efficiency and reduce the overheads. But how to alleviate sparsity and further enhance accuracy is still challenging. Addressing at these issues, we propose to fuse spatio-temporal contexts into deep factorization machine (STC_DeepFM) offline for pick-up area recommendation, and within the area to recommend pick-up points online using factorization machine (FM). Firstly, we divide the urban area into several grids with equal size. Spatio-temporal contexts are destilled from pick-up points or points-of-interest (POIs) belonged to the preceding grids. Secondly, the contexts are integrated into deep factorization machine (DeepFM) to mine… More >

Zhiyun Yang^1,#, Qi Liu^1,#,*, Hao Wu¹, Xiaodong Liu², Yonghong Zhang³

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 45-64, 2023, DOI:10.32604/cmes.2022.022045

Abstract Accurate precipitation nowcasting can provide great convenience to the public so they can conduct corresponding arrangements in advance to deal with the possible impact of upcoming heavy rain. Recent relevant research activities have shown their concerns on various deep learning models for radar echo extrapolation, where radar echo maps were used to predict their consequent moment, so as to recognize potential severe convective weather events. However, these approaches suffer from an inaccurate prediction of echo dynamics and unreliable depiction of echo aggregation or dissipation, due to the size limitation of convolution filter, lack of global feature, and less attention to… More > Graphic Abstract