No Comment : les mariachis se réunissent à Mexico pour battre le record du monde de chant

No Comment : des slackliners se balancent entre des montgolfières à 2 500 mètres d'altitude

No Comment : des couronnes de coquelicots pour le Dimanche du Souvenir 

No Comment : l'Antarctica Ice Ultra ou la course de l'extrême 

No Comment : manifestation pour la paix à la COP 29

No Comment : des heurts et des incendies dans la capitale haïtienne Port-au Prince

No Comment : funérailles collectives au Liban

No Comment : un psychanaliste dans le métro new-yorkais

No Comment : Tyrannosaure Rex, un mannequin pas comme les autres

No Comment : en Serbie, des centaines d’œufs jetés sur le siège d’Euro Lithium Balkan

No Comment : les universités en crise en Argentine 

No Comment : l'éruption d'un volcan cloue les avions au sol à Bali

Improving website structures is the main task of a website designer. In recent years, numerous web engineering researchers have investigated navigation recommendation systems. Page recommendation systems are critical for mobile website navigation. Accordingly, we propose a smart and adaptive navigation recommendation system based on reinforcement learning. In this system, user navigation history is used as the input for reinforcement learning model. The model calculates a surf value for each page of the website; this value is used to rank the pages. On the basis of this ranking, the website structure is modified to shorten the user navigation path length. Experiments were conducted to evaluate the performance of the proposed system. The results revealed that user navigation paths could be decreased by up to 50% with training on 12 months of data, indicating that users could more easily find a target web page with the help of the proposed adaptive navigation recommendation system.

1. XV de France – Antoine Dupont bien là, Thibaud Flament itou : la compo probable des Bleus pour la Nouvelle-Zélande  Rugbyrama
2. Bleus : Maxime Lamothe et Giorgi Beria appelés pour préparer le match de l'équipe de France contre les All Blacks  L'Équipe
3. XV de France : Dupont et Flament titulaires contre les All Blacks, Jalibert libéré ?  Le Figaro
4. Rugby : Giorgi Beria, le pilier gauche de l’USAP, appelé avec le XV de France pour préparer le choc contre les All Blacks  L'Indépendant
5. XV de France : Fabien Galthié rappelle deux joueurs à quelques jours du choc face aux All Blacks  La Dépêche du Midi

1. "Gladiator II" : comment Hollywood se jette dans l'arène politique avec ses péplums  franceinfo
2. « Gladiator », le film qui ressuscite les morts et détruit le cinéma  Le Monde
3. "Gladiator II" : "Ridley Scott respecte surtout les codes bien établis du gladiateur hollywoodien", estime un spécialiste  franceinfo
4. « Gladiator II » : bis repetita, triste cirque  Le Point
5. Gladiator 2, Une part manquante, Le royaume… les films à voir ou à éviter cette semaine  La Provence

1. Long ago, Voyager 2 might have caught Uranus at a bad time  Space.com
2. The anomalous state of Uranus’s magnetosphere during the Voyager 2 flyby  Nature.com
3. Potential For Life Found On Uranus' Moons, Scientists Reveal  NDTV
4. New Uranus research suggests what’s known about the planet could be wrong  CNN
5. Uranus Might Have Experienced a Freak Event When Voyager 2 Visited  The New York Times

1. McDavid closing in on 1,000 points, rare company at ‘remarkable’ pace  NHL.com
2. Draisaitl lifts in the OT winner  NHL.com
3. McDavid on brink of 1,000 points after huge performance in Oilers' OT win  Sportsnet.ca
4. McDavid's 4-point night leaves him one shy of 1,000-point milestone  TSN
5. Player grades: McDavid, Draisaitl to the rescue as Oilers pull another one out in overtime  Edmonton Journal

1. First Oppo Reno13 image appears online - GSMArena.com news  GSMArena.com
2. First look at Oppo Reno 13 shows an iPhone-like design  Notebookcheck.net
3. Oppo Reno13 series to arrive on November 25 - GSMArena.com news  GSMArena.com

1. Struggling DNA-testing site 23andMe to lay off 40% of its workers  BBC.com
2. 23andMe lays off 40% of its workforce, ends therapeutics division  CBC.ca
3. Genetic testing firm 23andMe cuts 40% of its workforce amid financial struggles  The Guardian
4. 23andMe reports sales decline a day after announcing plans to cut 40% of workforce  CNBC
5. 23andMe warns of ‘substantial doubt’ over its survival without new funding  Financial Times

1. Israel has missed US deadline to boost Gaza aid, UN agency says  BBC.com
2. US says Israel hasn't breached its law against blocking aid in Gaza  BBC.com
3. Israel misses deadline to let more aid into Gaza, but U.S. maintains support  CBC News
4. Antony Blinken decides against changing U.S. military assistance to Israel: report  The Globe and Mail
5. U.S. says it will not limit Israel arms transfers after some improvements in flow of aid to Gaza  CTV News

(Belga) L'ex-député européen Mark Demesmaeker, désormais sénateur coopté N-VA, sera la tête de liste du parti nationaliste pour les élections communales d'octobre 2024 à Hal (Brabant flamand), a-t-il indiqué lundi, confirmant des informations de presse.

M. Demesmaeker est conseiller communal à Hal depuis 2007 et y a été échevin durant six ans. La N-VA a terminé à deux reprises, lors des scrutins communaux de 2012 et 2018, comme premier parti de la commune. M. Demesmaeker a affirmé lundi toujours avoir cette ambition. "Nous avons une équipe jeune et soudée, avec expertise et vision. Je vise une progression", a-t-il dit. Il s'est dit convaincu que le changement de législation en Flandre - qui prévoit que le plus grand parti dispose d'un droit d'initiative pour former une coalition communale et que le candidat du plus grand groupe ayant recueilli le plus de voix de préférence devienne bourgmestre - lui offre un solide avantage. "Nous avons de bonnes chances, a-t-il souligné. L'élu nationaliste a affirmé vouloir se concentrer sur des thèmes comme l'urbanisation de Hal et la politique en matière de langue, en évoquant la "francisation de la ville". (Belga)

(Belga) Le taux de cellules commerciales vides dans le centre-ville carolo est tendanciellement à la baisse, a indiqué lundi soir lors du conseil communal de la Ville de Charleroi Babette Jandrain, l'échevine carolo du Commerce en réponse à une question qui lui était adressée.

Selon l'élue, qui a indiqué reprendre les chiffres de l'Association de Management du Centre-Ville (AMCV), le taux actuel de cellules commerciales vides dans l'intra-ring carolo est de 29% contre 33,6% en 2020. Et ce malgré le Covid et la crise énergétique qui ont mis en difficulté l'activité commerciale dans les grandes villes. Si le taux de cellules commerciales vides reste élevé à Charleroi, il n'en reste pas moins que la situation a tendance à s'améliorer, a indiqué Babette Jandrain. Les chiffres donnés par l'échevine ont été constatés par la conseillère communale du PTB Sofie Merckx, évoquant une situation de "désolation" concernant le quartier de la Ville Basse et interrogeant par ailleurs la volonté de la Ville de faire de certaines cellules vides des logements. (Belga)

Hasard du calendrier ou volontￜ de prￜserver le nouveau Premier ministre ? Selon Mediapart, une enquￜte judiciaire ouverte par le parquet de Perpignan, potentiellement gￜnante pour Jean Castex, a ￜtￜ...

In order to solve the problems of long prediction consumption time and many prediction iterations existing in traditional prediction models, an e-commerce growth prediction model based on grey Markov chain is proposed. The Scrapy crawler framework is used to collect a variety of e-commerce data from e-commerce websites, and the feedforward neural network model is used to clean the collected data. With the cleaned e-commerce data as the input vector and the e-commerce growth prediction results as the output vector, an e-commerce growth prediction model based on the grey Markov chain is built. The prediction model is improved by using the background value optimisation method. After training the model through the improved particle swarm optimisation algorithm, accurate e-commerce growth prediction results are obtained. The experimental results show that the maximum time consumption of e-commerce growth prediction of this model is only 0.032, and the number of iterations is small.

To reduce the location cost of cross-border e-commerce logistics sites, this article proposes a multi-logistics site location method based on return uncertainty. Firstly, a site selection model is established with the objective function of minimising site construction costs, transportation costs, return costs, and operating costs, and the constraint conditions of return recovery costs and delayed pick-up time; Then, using the Monte Carlo method to simulate the number of returned items, and using an improved chicken swarm algorithm based on simulated annealing, the cross-border e-commerce multi-logistics site location model is solved to complete the location selection. Experimental results show that this method can effectively reduce the related costs of cross-border e-commerce multi-logistics site selection. After applying this method, the total cost of multi-logistics site selection is 19.4 million yuan, while the total cost of the five comparative methods exceeds 20 million yuan.

With the rapid development and application of driverless technology, the number and location of vehicles, the channel and bandwidth of wireless network are time-varying, which leads to the increase of offloading delay and energy consumption of existing algorithms. To solve this problem, the vehicle terminal task offloading decision problem is modelled as a Markov decision process, and a task offloading algorithm based on DDQN is proposed. In order to guide agents to quickly select optimal strategies, this paper proposes an offloading mechanism based on task feature. In order to solve the problem that the processing delay of some edge server tasks exceeds the upper limit of their delay, a task scheduling mechanism based on buffer delay is proposed. Simulation results show that the proposed method has greater performance advantages in reducing delay and energy consumption compared with existing algorithms.

The confluence of the internet of things (IoT) with smart grids has ushered in a paradigm shift in energy management, promising unparalleled efficiency, economic robustness and unwavering reliability. However, this integrative evolution has concurrently amplified the grid's susceptibility to cyber intrusions, casting shadows on its foundational security and structural integrity. Machine learning (ML) and deep learning (DL) emerge as beacons in this landscape, offering robust methodologies to navigate the intricate cybersecurity labyrinth of IoT-infused smart grids. While ML excels at sifting through voluminous data to identify and classify looming threats, DL delves deeper, crafting sophisticated models equipped to counteract avant-garde cyber offensives. Both of these techniques are united in their objective of leveraging intricate data patterns to provide real-time, actionable security intelligence. Yet, despite the revolutionary potential of ML and DL, the battle against the ceaselessly morphing cyber threat landscape is relentless. The pursuit of an impervious smart grid continues to be a collective odyssey. In this review, we embark on a scholarly exploration of ML and DL's indispensable contributions to enhancing cybersecurity in IoT-centric smart grids. We meticulously dissect predominant cyber threats, critically assess extant security paradigms, and spotlight research frontiers yearning for deeper inquiry and innovation.

The prevalence of social media transforms e-business into social commerce and facilitates consumers' engagement in cross-cultural social commerce. However, social commerce operations encounter unpredictable challenges in cross-cultural business environment. It is vital to further investigate how contextual elements affect consumers' trust and their engagement when they are exposed to the complexity of cross-cultural business environment. The stimuli-organism-response paradigm is employed to examine how the two dimensions of social media usage influence consumers' engagement in cross-cultural social commerce. The current study surveyed 2,058 samples from 135 countries, and the regression analysis results illustrate the mechanism whereby informational and socialising usage of social media positively influences consumers' engagement in social commerce through consumers' trust toward social commerce websites. Additionally, the associations between two aspects of social media usage and consumers' trust towards social commerce are negatively moderated by cultural distance. Both theoretical and practical implications are also discussed.

5G mobile communication systems are an in-depth fusion of multi-radio access technologies characterised with frequent handover between cells. Handover management is a particularly challenging issue for 5G networks development. In this article, a novel optimised handover framework is proposed to find the optimal network to connect with a good quality of service in accordance with the user's preferences. This framework is based on an extension of IEEE 802.21 standard with new components and new service primitives for seamless handover. Moreover, the proposed vertical handover process is based on an adaptive heuristic model aimed at achieving an optimised network during the decision-making stage. Simulation results demonstrate that, compared to other existing works, the proposed framework is capable of selecting the best network candidate accurately based on the quality-of-service requirements of the application, network conditions, mobile terminal conditions and user preferences. It significantly reduces the handover delay, handover blocking probability and packet loss rate.

The intelligent financial sharing platform in the online realm is capable of collecting, storing, processing, analysing and sharing financial data through the integration of AI and big data processing technologies. However, as data volume grows exponentially, the cost of financial data storage and processing increases, and the asset accounting and financial profit data sharing analysis structure in financial sharing platforms is inadequate. To address the issue of data security sharing in the intelligent financial digital sharing platform, this paper proposes a data-sharing framework based on blockchain and edge computing. Building upon this framework, a non-separable task distribution algorithm based on data sharing is developed, which employs multiple nodes for cooperative data storage, reducing the pressure on the central server for data storage and solving the problem of non-separable task distribution. Multiple sets of comparative experiments confirm the proposed scheme has good feasibility in improving algorithm performance and reducing energy consumption and latency.

In the context of smart city development, the managed pressure drilling (MPD) drilling process faces many uncertainties, but the characteristics of the process are complex and require accurate wellbore pressure control. However, this process runs the risk of introducing un-modelled dynamics into the system. To this problem, this paper employs neural network control techniques to construct a dual-network system for throttle pressure control, the design encompasses both the controller and identifier components. The radial basis function (RBF) network and proportional features are connected in parallel in the controller structure, and the RBF network learning algorithm is used to train the identifier structure. The simulation results show that the actual wellbore pressure can quickly track the reference pressure value when the pressure setpoint changes. In addition, the controller based on neural network realises effective control, which enables the system to track the input target quickly and achieve stable convergence.

In order to reduce the challenges encountered by learners and educators in engaging in educational activities, this paper classifies learners' roles in virtual learning communities, and explores the role of behaviour characteristics and their positions in collaborative knowledge construction networks in promoting the process of knowledge construction. This study begins with an analysis of the relationship structure among learners in the virtual learning community and then applies the FCM algorithm to arrange learners into various dimensional combinations and create distinct learning communities. The test results demonstrate that the FCM method performs consistently during the clustering process, with less performance oscillations, and good node aggregation, the ARI value of the model is up to 0.90. It is found that they play an important role in the social interaction of learners' virtual learning community, which plays a certain role in promoting the development of artificial intelligence.

To explore the computer-aided translation technology based on the intelligent algorithm of edge computing. This paper presents the research on computer-aided translation technology based on edge computing intelligent algorithm. In the K-means computer edge algorithm, it analyses the traditional way of average resource allocation and the way of virtual machine allocation. In the process of online solution, we have a more detailed understanding of the data information at the edge, and also avoid the connection relationship between network users and the platform, which has a certain impact on the internal operation efficiency of the system. The network user group is divided into several different types of existence through K-means computer algorithm, and various information resources are counted according to their own characteristics. Computer-aided translation technology can significantly improve the quality of translation, improve the translation efficiency, and reduce the translation cost.

As IOT develops drastically these years, the application of cloud computing in many fields has become possible. In this paper, we take low-voltage current transformers in power systems as the research object and propose a TCN-BI-GRU power measurement method that incorporates the signal characteristics based on the transformer input and output. Firstly, the basic signal enhancement extraction of input and output is completed by using EMD and correlation coefficients. Secondly, multi-dimensional feature extraction is completed to improve the data performance according to the established TCN network. Finally, the power prediction is completed by using BI-GRU, and the results show that the RMSE of this framework is 5.69 significantly lower than other methods. In the laboratory test, the device after being subjected to strong disturbance, its correlation coefficient feature has a large impact, leading to a large deviation in the prediction, which provides a new idea for future intelligent prediction.

The application of computer image digitisation has realised the transformation of people's production and lifestyle, and also promoted the development of the construction industry. This article aims to realise the research on architectural decoration design and production under computer network environment and promote the ecological development of indoor and outdoor design in the construction industry. This article proposes to use virtual reality technology in image digitisation to guide architectural decoration design research. In the comparative analysis of the weight of architectural decoration elements, among the calculated weights of secondary elements, the spatial function has the largest weight, which is 0.2155, and the landscape has the smallest weight, which is 0.0113. Among the three-level unit weights, the service area has the largest weight, which is 0.0976, and the fence frame has the smallest weight, which is 0.0119.

This study investigates the well-being of healthcare professionals in India, with a specific focus on the detrimental effects of the pandemic on their mental and physical health, including stress, burnout, and fatigue. This research examines the roles played by calling, mindfulness, and compassionate love as essential resources in promoting the well-being of healthcare professionals. Utilising structural equation modelling (SEM), the results reveal a significant cause and effect relationship between calling, mindfulness, and compassionate love and their influence on overall well-being. Furthermore, the study identifies a noteworthy parallel mediation effect, demonstrating that mindfulness and compassionate love serve as mediators in the relationship between calling and well-being. This research offers practitioners invaluable insights into the effective utilisation of mindfulness and compassionate love practices to enhance the overall well-being of healthcare professionals.

The study investigated the influence of ebullient supervision on employee commitment in a Ghanaian public university through the mediating role of employee engagement. The simple random sampling technique was used to draw 302 administrative staff of the university to respond to the self-administered questionnaire on the constructs. Furthermore, the partial least square structural equation technique was deployed to test the research hypotheses in the study. The results showed that ebullient supervision had a significant positive relationship with employee commitment and employee engagement. The findings further revealed that employee engagement positively correlated with employee commitment. Finally, the study's findings established that employee engagement partially mediated the link between ebullient supervision and employee commitment. The study emphasised that various supervisors in a university's administration should create an environment that favours fun where subordinates can form ties with one another.

Disease pandemics, once thought to be historical relics, are now again challenging healthcare systems globally. Of essential importance is sufficiently investing in preparedness and responsiveness, but approaches to such investments vary significantly by country. These variations provide excellent opportunities to learn and prepare for future pandemics. Therefore, we examine digital health infrastructure and the state of healthcare and public health services in relation to pandemic preparedness and responsiveness. The research focuses on two countries: South Africa and the USA. We apply case analysis at the country level toward understanding digital health policy preparedness and responsiveness to a pandemic. We also provide a teaching note at the end for use in guiding students in this area to formulate digital health policy recommendations for pandemic preparedness and responsiveness.