1. Justin Welby resigns as archbishop of Canterbury over abuse scandal  Al Jazeera English
2. Church of England head resigns over handling of sex abuse scandal  CTV News
3. The four bishops at risk from child abuse cover-up report  The Telegraph
4. The archbishop and the abuser  The Economist
5. Archbishop of Canterbury Justin Welby resigns in abuse fallout: All to know  Al Jazeera English

Canada launches $2-billion public-private finance platform for developing countries at COP29  The Globe and MailView Full Coverage on Google News

Special counsel Jack Smith looking at stepping down before Trump takes office and is discussing how to end prosecutions  CNN

1. Niagara Health offering free parking after delays reported  News Talk 610 CKTB
2. Implementation of new Niagara Health patient info system resulting in long wait times  St. Catharines Standard
3. Temporary delays impacting registration at emergency departments  Thorold News
4. Niagara Health Working Through Delays  101.1 More FM
5. Niagara Health experiencing temporary delays impacting registration and EDs  Niagara Health

Overwhelmed families surrendering custody of their children to CAS  CTV News Northern Ontario

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

1. Trump says Elon Musk, Vivek Ramaswamy will lead the Department of Government Efficiency  The Globe and Mail
2. Why is Elon Musk becoming Donald Trump's efficiency adviser?  BBC.com
3. Elon Musk and Vivek Ramaswamy will lead new 'Department of Government Efficiency' in Trump administration  CTV News
4. George Conway: Musk, Ramaswamy to lead ‘nonexistent department’  The Hill

J'ai lu les titres et articles de presse à propos d'Asia Argento et de sa supposée agression contre Jimmy Bennett. Ça sent le traquenard à plein nez. 

Le type assure avoir été agressé sexuellement par l'actrice à l'âge de 17 ans. Il se fout de la gueule de qui, le petit traumatisé ? La prétendue agression ne l'empêchait pas de titrer quelques semaines après que "Maman" lui manquait. Pour la petite histoire, les deux acteurs jouent à la mère et au fils depuis qu'ils ont tourné ensemble dans un film alors que Jimmy avait 7 ans et qu'Asia incarnait sa ...

(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)

Ghislaine Maxwell, condamnée en juin à vingt ans de prison pour trafic sexuel de mineures, a affirmé dans une interview diffusée lundi qu'elle aurait aimé "ne jamais avoir rencontré" Jeffrey Epstein, dont elle se dit convaincue "qu'il a été assassiné".

L'ex-mondaine britannique a été condamnée en juin à New York pour trafic sexuel de mineures pour le compte du financier américain décédé, accusé d'exploitation sexuelle de dizaines de mineures. "J'aimerais honnêtement ne l'avoir jamais rencontré", a-t-elle affirmé à propos de son ancien compagnon, dans l'entretien accordé depuis sa prison aux Etats-Unis à la chaîne britannique TalkTV. 

"Clairement (...) le fait que je travaille avec lui et que je passe du temps avec lui et que je le connaisse a détruit ma vie et blessé énormément de gens qui me sont chers et que j'aime", a-t-elle affirmé. Elle a souligné qu'elle ne "savait pas" qu'Epstein était "aussi horrible" même si "évidemment maintenant, quand on regarde en arrière, bien sûr que oui".

Le financier américain, accusé d'avoir, entre 2002 et 2005 au moins, fait venir des mineures dans ses résidences "pour se livrer à des actes sexuels avec lui", a été retrouvé pendu dans sa cellule le 10 août 2019. Si l'autopsie confirme un suicide par pendaison, Mme Maxwell se dit elle convaincue "qu'il a été assassiné".

Déjà dimanche, des extraits de l'interview avaient été publiés et Mme Maxwell y prenait la défense du prince Andrew, affirmant qu'une photo montrant le frère du roi Charles III avec une jeune fille qui l'a ensuite accusé d'agressions sexuelles était "un faux". 

L'Américaine Virginia Giuffre, aujourd'hui âgée de 39 ans, accuse le prince de l'avoir agressée sexuellement à trois reprises en 2001, quand elle avait 17 ans. Elle a affirmé l'avoir rencontré par l'entremise d'Epstein.

Andrew, ami de Ghislaine Maxwell et Jeffrey Epstein, a scellé avec elle en février 2022 un accord à l'amiable, en payant des millions de dollars, ce qui lui a permis d'éviter un procès au civil à New York, qui aurait été extrêmement embarrassant pour la famille royale britannique.

Le prince de 62 ans, tombé en disgrâce après ces accusations, a toutefois toujours contesté les accusations. Selon des journaux britanniques, il étudie désormais les options légales pour tenter d'annuler l'accord avec Virginia Giuffre.

(Belga) Un Américain, qui avait été immortalisé les pieds sur une table dans le bureau de la cheffe démocrate Nancy Pelosi lors de l'assaut sur le Capitole, a été reconnu coupable lundi de plusieurs délits.

Après une courte délibération, les jurés ont déclaré Richard Barnett, 62 ans, coupable, entre autres, d'entrave à une procédure officielle, vol et intrusion dans un bâtiment officiel avec une arme dangereuse (un bâton de marche capable d'envoyer des décharges électriques). Le 6 janvier 2021, il avait envahi, comme des centaines de partisans de l'ex-président républicain Donald Trump, le siège du Congrès au moment où les élus certifiaient la victoire du démocrate Joe Biden à la présidentielle. Il avait été photographié par l'AFP dans le bureau de la cheffe de la chambre des représentants, Nancy Pelosi, les pieds sur un meuble. Le cliché avait fait le tour du monde et permis à la police de l'interpeller rapidement. Selon le dossier d'accusation, ce partisan de la mouvance complotiste Qanon avait laissé un message insultant à la démocrate et volé une enveloppe qu'elle avait signée. Pendant son procès, il s'était montré défiant, assurant avoir été "poussé à l'intérieur" du Capitole par la foule. Sa peine sera prononcée en mai. En attendant, il reste assigné à résidence avec un bracelet électronique. En deux ans d'enquête, plus de 950 participants à cette attaque ont été arrêtés, et près de 200 condamnés à des peines de prison. (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)

Elon Musk a tenté de montrer lundi au tribunal que ses fameux tweets de 2018, sur sa volonté de sortir Tesla de la Bourse, n'avaient rien de trompeurs ou de frauduleux, contrairement aux accusations d'investisseurs qui disent avoir perdu des millions de dollars à cause du milliardaire.

Le patron de Tesla -- et de Twitter, depuis fin octobre -- a assuré qu'il n'avait "jamais" cherché à tromper les investisseurs, et que l'accusation de fraude était "scandaleuse".

Il avait créé la stupeur le 7 août 2018 en affirmant qu'il voulait retirer son groupe automobile de la Bourse au prix de 420 dollars par action, puis en assurant que le financement était "sécurisé".

"Je ne disais pas que c'était fait, je disais simplement que je l'envisageais, que j'y pensais. Et qu'à mon avis le financement était sécurisé", a déclaré Elon Musk à la barre, dans le tribunal de San Francisco où a lieu le procès.

La semaine dernière, le principal avocat des plaignants, Nicholas Porritt, avait accusé le dirigeant d'avoir "menti" et d'être responsable des pertes des investisseurs.

Le titre avait bondi dans la foulée des tweets très inhabituels (et le Nasdaq avait temporairement suspendu le cours de l'action Tesla), avant de décliner les jours suivants. Des articles de presse avaient fini par révéler que le patron n'avait pas vraiment les fonds.

Tesla était restée cotée en Bourse.

A travers ses questions, Nicholas Porritt a cherché à montrer qu'Elon Musk n'avait pas réalisé les consultations appropriées, et ne disposait pas ni des éléments nécessaires, ni de l'autorité pour faire une annonce aussi fracassante, surtout sur Twitter, et surtout pendant que les marchés étaient ouverts.

- "M. Tweet" -

L'avocat a mis en avant des échanges acerbes le 12 août 2018 entre le milliardaire et Yasir Al-Rumayyan, le directeur du fonds souverain saoudien, qui s'était engagé "catégoriquement" et "sans hésitation" à financer l'opération, selon Elon Musk.

"Le financement n'était pas vraiment sécurisé, n'est-ce pas?", a demandé M Porritt.

Yasir Al-Rumayyan a fait du "rétropédalage", a rétorqué le patron de Tesla.

Il a assuré qu'il avait de toute façon la possibilité de vendre ses actions de son autre fleuron, SpaceX, "l'entreprise non cotée la plus valorisée des Etats-Unis".

"Cela m'aurait brisé le cœur (de les vendre), mais je l'aurais fait si besoin", a-t-il déclaré, évoquant comment il avait dû se séparer d'actions de Tesla pour racheter Twitter l'année dernière.

Costume sombre, chemise blanche et cravate, il est apparu hésitant, ne se souvenant pas de nombreux emails et détails, et répondant souvent à côté des questions pour répéter à l'envie les messages qu'il voulait faire passer au jury.

Au point de faire perdre patience à l'avocat des investisseurs. "Nous avons passé toute une journée ensemble à Austin, vous vous en souvenez M. Tweet?!", a lancé Nicholas Porritt, avant de corriger pour "M. Musk".

- "Karma" -

L'accusation est aussi revenue sur le prix proposé par Elon Musk, 420 dollars par action. Aux Etats-Unis, les chiffres 4 et 20 accolés sont associés à la consommation de cannabis. Quand le milliardaire a proposé de racheter Twitter au printemps dernier, il a choisi un prix de 54,20 dollars par action.

"Avez-vous arrondi à 420 en guise de blague à l'attention de votre petite amie?", a demandé Nicholas Porritt.

"Ce n'était pas une blague, cela représentait une prime de 20% au-dessus du prix de l'action", a répondu Elon Musk, reconnaissant cependant qu'il y a "un certain karma autour de 420".

"Pas sûr que ce soit un bon ou un mauvais karma à ce stade", a-t-il encore plaisanté.

Son avocat Alex Spiro l'a ensuite aidé à dresser le portrait d'un immigré parti de rien, venu aux Etats-Unis - "là où les grandes choses sont possibles" - après une enfance "malheureuse" en Afrique du Sud, selon les mots du milliardaire.

"On m'a traité de fou à de nombreuses reprises", a déclaré Elon Musk après avoir énuméré les entreprises qu'il a cofondées.

Mais "à ce stade je crois que j'ai levé plus d'argent que quiconque dans l'histoire", s'est-il vanté, attribuant sa réussite à son "honnêteté" à l'égard des investisseurs.

Le procès doit durer trois semaines. Dans une précédente décision liée à cette affaire, un juge avait estimé que le fameux tweet de 2018 pouvait être considéré comme "faux et trompeur".

Le gendarme boursier américain, la SEC, avait de son côté obligé Elon Musk à céder la présidence du conseil d'administration, à payer une amende et à faire pré-approuver par un juriste ses tweets directement liés à l'activité de Tesla.

(Belga) Sept personnes ont été tuées lundi lors d'une double fusillade près de San Francisco, en Californie, ont indiqué les médias américains sur la base des déclarations de la police locale.

Le suspect a été arrêté, a annoncé sur Twitter le bureau du shérif du comté de San Mateo, qui comprend la ville de Half Moon Bay où ont eu lieu les drames. "Il n'y a plus de danger pour la population à cette heure", a-t-il assuré. Les deux fusillades sont intervenues dans des exploitations agricoles proches l'une de l'autre, ont précisé les médias. Cette nouvelle tuerie intervient moins de 48 heures après qu'un tireur a tué 11 personnes dans un club de danse près de Los Angeles. (Belga)

Vous n'avez pas eu le temps de lire Le Canard enchaￜnￜ, Mediapart, Le Monde, Arrￜt sur images et tous les autres titres de presse ? On s'en charge pour vous.

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...

L'information est passï¿œe inaperï¿œue mais elle ne manque pas de sel. Alors que la gestion de la crise du covid-19 par le gouvernement est trï¿œs contestï¿œe (au retard dans la livraison de masques s'ajoute...

Aiming at the problems of high error rate, low evaluation accuracy and low investment return in traditional methods, a random forest-based e-bank investment risk evaluation method is proposed. First, establish a scientific e-bank investment risk evaluation index system. Then, G1-COWA combined weighting method is used to calculate the weights of each index. Finally, the e-bank investment risk evaluation index data is taken as the input vector, and the e-bank investment risk evaluation result is taken as the output vector. The random forest model is established and the result of e-banking investment risk evaluation is obtained. The experimental results show that the maximum relative error rate of this method is 4.32%, the evaluation accuracy range is 94.5~98.1%, and the maximum return rate of e-banking investment is 8.32%. It shows that this method can accurately evaluate the investment risk of electronic banking.

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.

To achieve the benefits as much as possible, it is required to identify the available PEV capacity and prepare scheduling plans based on that. The analysis revealed that the risk-based scheduling of the microgrid could reduce the financial risk completely from $9.89 to $0.00 and increases the expected operation cost by 24% from $91.38 to $112.94, in turn. This implies that the risk-averse decision-maker tends to spend more money to reduce the expected risk-in-cost by using the proposed downside risk management technique. At the end, by the help of fuzzy satisfying method, the suitable risk-averse strategy is determined for the studied case.

Smart cities research is growing all over the world seeking to understand the effect of smart cities from different angles, domains and countries. The aim of this study is to analyse how the smart city ICTs (e.g., big data analytics, AI, IoT, cloud computing, smart grids, wireless communication, intelligent transportation system, smart building, e-governance, smart health, smart education and cyber security) are related to government. services and society welfare from the perspective of China. This research confirmed a positive correlation of smart city ICTs to e-Govt. Services (e-GS). On the other hand, the research showed a positive influence of smart city ICTs on society's welfare. These findings about smart cities and ICTs inform us how the thought paradigm to smart technologies can cause the improvement of e-GS through economic development, job creation and social welfare. The study offers different applications of the theoretical perspectives and the management perspective which are significant to building a society during recent technologised era.

In this paper, a second-order sliding mode adaptive controller with finite time stability is proposed for trajectory tracking of robotic systems. In order to reduce the chattering phenomenon in the response of the variable structure resistant controller, two dependent sliding surfaces are used. In the outer loop, a kinematic controller is used to compensate the geometric uncertainty of the robot, and in the inner loop, the proposed resistive control is used as the main loop. On the other hand, considering the dynamic uncertainty and disturbance of the robot, an adaptive strategy has been used to estimate the uncertainty limit during the control process in order to eliminate the need for basic knowledge to determine the uncertainty limit in the resistant structure. The proposed control method demonstrates significant enhancements in performance, with the linear velocity error improving by approximately 80%, leading to a more accurate and responsive system.

Several challenges exist in disseminating multi-level secure (MLS) data in multi-domain environments. First, the security domains participating in data dissemination generally use different MLS labels and lattice structures. Second, when MLS data objects are transferred across multiple domains, there is a need for an agreed security policy that must be properly applied, and correctly enforced for the data objects. Moreover, the data sender may not be able to predetermine the data recipients located beyond its trust boundary. To address these challenges, we propose a new framework that enables secure dissemination and access of the data as intended by the owner. Our novel framework leverages simple public key infrastructure and active bundle, and allows domains to securely disseminate data without the need to repackage it for each domain.

Image forgery detection techniques refer to the process of detecting manipulated or altered images, which can be used for various purposes, including malicious intent or misinformation. Image forgery detection is a crucial task in digital image forensics, where researchers have developed various techniques to detect image forgery. These techniques can be broadly categorised into active, passive, machine learning-based and hybrid. Active approaches involve embedding digital watermarks or signatures into the image during the creation process, which can later be used to detect any tampering. On the other hand, passive approaches rely on analysing the statistical properties of the image to detect any inconsistencies or irregularities that may indicate forgery. In this paper for the detection of scaling and cropping attack a deep learning method has been proposed using ResNet. The proposed method (Res-Net-Adam-Adam) is able to achieve highest amount of accuracy of 99.14% (0.9914) while detecting fake and real images.

Access to quality healthcare is a fundamental right but unfortunately, India suffers from gender disparities in healthcare access. Telemedicine has the potential to improve access to healthcare services for women by eliminating traditional barriers. Therefore, our research aims to investigate the factors influencing the adoption of telemedicine among Indian women. This study has collected 442 responses and analysed them through structural equation modelling. The result indicates a strong and positive connection between the willingness to adopt telemedicine services and factors like performance expectancy, perceived benefits, e-health literacy, and perceived reliability. Notably, perceived reliability emerges as the most impactful predictor, closely followed by perceived benefits, while factors like effort expectancy and user resistance show no significant influence. This underscores the pivotal role of reliability and perceived benefits in shaping women's inclination toward adopting telemedicine. The study provides practical insights for telemedicine providers and policymakers to customise strategies and policies for effective promotion.

This systematic literature study employed bibliometric analysis to identify workplace mindfulness-related methods and practices in literature published from 2000 to 2020 by leading nations, institutions, journals, authors, and keywords. We also assessed the impact of workplace mindfulness research papers. Scopus analysis tools provided a literature report for 638 Scopus articles used in the study. Using VOSviewer, leading nations, institutions, articles, authors, journals, and keyword co-occurrence network maps were constructed. PRISMA was used to identify 56 publications to recognise workplace mindfulness literature's significant achievements. The research's main contribution is a deep review of neurological mindfulness and psychological measuring tools as workplace mindfulness tool categories. The study is the first to use the PRISMA technique to capture the essential contributions of workplace mindfulness papers from 2000 to 2020.

Although artificial intelligence provides a new method to gather, process, analyse data, generate insights, and offer customised solutions, such methods could change how marketers deal with customers, and there is a lack of literature to portray the application of artificial intelligence in marketing. This study aims to recognise and portray the use of artificial intelligence from a marketing standpoint, as well as to provide a conceptual framework for the application of artificial intelligence in marketing. This study uses a systematic literature review analysis as a research method to achieve the aims. Data from 142 articles were extracted from the Scopus database using relevant search terms for artificial intelligence and marketing. The systematic review identified significant usage of artificial intelligence in conversational artificial intelligence, content creation, audience segmentation, predictive analytics, personalisation, paid ads, sales forecasting, dynamic pricing, and recommendation engines and the bibliometric analysis produced the trend in co-authorship, citation, bibliographic coupling, and co-citation analysis. Practitioners and academics may use this study to decide on the marketing area in which artificial intelligence can be invested and used.

This study investigates the effects of social media marketing efforts (SMME) on smartphone brand identification, attachment, association, and willingness to pay premium prices. A survey of 320 smartphone users who followed official social media handles managed by smartphone companies was conducted for this purpose. PLS-SEM was used to analyse the collected data. The findings demonstrated importance of SMME dimensions. According to the study's findings, the smartphone brand's SMMEs had significant impact on brand identification, brand association, and brand attachment. The results revealed that SMMEs had significant impact on willingness to pay the premium price. The findings also show that brand identification, attachment, and association mediated the relationship between SMMEs and willingness to pay a premium price. The findings of this study will be useful in developing social media marketing strategies for smartphones. This study demonstrates the use of social media marketing to promote mobile phones, particularly in emerging markets.

TCP BBR is one of the most powerful congestion control algorithms. In this article, we provide a comprehensive review of BBR analysis, expanding on existing knowledge across various fronts. Utilising ns3 simulations, we evaluate BBR's performance under diverse conditions, generating graphical representations. Our findings reveal flaws in the probe's RTT phase duration estimation and unequal bandwidth sharing between BBR and CUBIC protocols. Specifically, we demonstrated that the probe's RTT phase duration estimation algorithm is flawed and that BBR and CUBIC generally do not share bandwidth equally. Towards the end of the article, we propose a new improved version of TCP BBR which minimises these problems of inequity in bandwidth sharing and corrects the inaccuracies of the two key parameters RTprop and cwnd. Consequently, the BBR' protocol maintains very good fairness with the Cubic protocol, with an index that is almost equal to 0.98, and an equity index over 0.95.

Constrained programming is the concept used to select possible alternatives from an incredibly diverse range of candidates. This paper proposes an AI-assisted Backtracking Scheme (AI-BS) by integrating the generic backtracking algorithm with Artificial Intelligence (AI). The detailed study observes that the extreme dual ray associated with the infeasible linear program can be automatically extracted from minimum unfeasible sets. Constraints are used in artificial intelligence to list all possible values for a group of variables in a given universe. To put it another way, a solution is a way of assigning a value to each variable that these values satisfy all constraints. Furthermore, this helps the study reach a decreased search area for smart backtracking without paying high costs. The evaluation results exhibit that the IB-BC algorithm-based smart electricity schedule controller performs better electricity bill during the scheduled periods than comparison approaches such as binary backtracking and binary particle swarm optimiser.

Physical Layer Security (PLS) and relay technology have emerged as viable methods for enhancing the security of wireless networks. Relay technology adoption enhances the extent of coverage and enhances dependability. Moreover, it can improve the PLS. Choosing relay and jammer nodes from the group of intermediate nodes effectively mitigates the presence of powerful eavesdroppers. Current methods for Joint Relay and Jammer Selection (JRJS) address the optimisation problem of achieving near-optimal secrecy. However, most of these techniques are not scalable for large networks due to their computational cost. Secrecy will decrease if eavesdroppers are aware of the relay and jammer intermediary nodes because beamforming can be used to counter the jammer. Consequently, this study introduces a multi-agent Q-learning-based PLS-enhanced secured joint relay and jammer in dual-hop wireless cooperative networks, considering the existence of several eavesdroppers. The performance of the suggested algorithm is evaluated in comparison to the current algorithms for secure node selection. The simulation results verified the superiority of the proposed algorithm.

We introduce a unique inductive bias to improve the reconstruction quality of Neural Radiance Fields (NeRF), NeRF employs the Fourier transform to map 3D coordinates to a high-dimensional space, enhancing the representation of high-frequency information in scenes. However, this transformation often introduces significant noise, affecting NeRF's robustness. Our approach allocates attention effectively by segregating channels within NeRF using attention-based gating units. We conducted experiments on an open-source data set to demonstrate the effectiveness of our method, which leads to significant improvements in the quality of synthesised new-view images compared to state-of-the-art methods. Notably, we achieve an average PSNR increase of 0.17 compared to the original NeRF. Furthermore, our method is implemented through a carefully designed special Multi-Layer Perceptron (MLP) architecture, ensuring compatibility with most existing NeRF-based methods.

The spread of COVID-19 results in disruption, uncertainty, complexity, and ambiguity in all businesses. Employees help companies achieve their aims. To manage human resources sustainably, analyse organisational strategy. This thorough research study attempts to find previously unidentified challenges, cutting-edge techniques, and surprising decisions in human resource management outside of healthcare organisations during the COVID-19 pandemic. The narrative review examined corporate human resource management measures to mitigate COVID-19. Fifteen publications were selected for the study after removing duplicates and applying the inclusion and exclusion criteria. This article examines HR's COVID-19 response. Human resource management's response to economic and financial crises has been extensively studied, but the COVID-19 pandemic has not. This paper reviewed the literature to reach its goal. The results followed the AMO framework for human resource policies and procedures and the HR management system. This document suggests COVID-19 pandemic-related changes to human resource management system architecture, policies, and practises. The study created a COVID-19 pandemic human resource management framework based on the literature. The COVID-19 pandemic had several negative effects, including social and behavioural changes, economic shock, and organisational disruption.

The proliferation of technology and communication has resulted in increased digitalisation that includes digital payments. This study is aimed at unravelling the relationship between awareness of individuals about the digital payment system and customer satisfaction with digital payments. Two models were developed in this study. First model considers awareness → usage pattern → customer satisfaction. Second model considers usage pattern → customer satisfaction → perception of digital payments. These two alternative models were tested by collecting data from 507 respondents in southern India was analysed using the structural equation modelling. The results indicate that usage pattern acted as a mediator between awareness and satisfaction, and satisfaction acted as a mediator between usage pattern and consumers' perception of digital payments. The implications for theory and practice are discussed.

In order to further improve the public health assurance system and the infectious diseases early warning system to give play to their positive roles and enhance their collaborative capacity, this paper, based on the big and thick data analytics technology, designs a 'rolling-type' data synergy model. This model covers districts and counties, municipalities, provinces, and the country. It forms a data blockchain for the public health assurance system and enables high sharing of data from existing system platforms such as the infectious diseases early warning system, the hospital medical record management system, the public health data management system, and the health big and thick data management system. Additionally, it realises prevention, control and early warning by utilising data mining and synergy technologies, and ideally solves problems of traditional public health assurance system platforms such as excessive pressure on the 'central node', poor data tamper-proofing capacity, low transmission efficiency of big and thick data, bad timeliness of emergency response, and so on. The realisation of this technology can greatly improve the application and analytics of big and thick data and further enhance the public health assurance capacity.

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.

Emergency disaster management presents substantial risks and obstacles to shield tunnel building projects, particularly in the event of water leakage accidents. Contemporary water leak detection is critical for guaranteeing safety by reducing the likelihood of disasters and the severity of any resulting damages. However, it can be difficult. Deep learning models can analyse images taken inside the tunnel to look for signs of water damage. This study introduces a unique strategy that employs deep learning techniques, generative adversarial networks (GAN) with long short-term memory (LSTM) for water leakage detection i shield tunnel construction (WLD-STC) to conduct classification and prediction tasks on the massive image dataset. The results demonstrate that for identifying and analysing water leakage episodes during shield tunnel construction, the WLD-STC strategy using LSTM-based GAN networks outperformed other methods, particularly on huge data.

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.

With the expansion of business scope, the environment faced by enterprises has also changed, and competition is becoming increasingly fierce. Traditional financial systems are increasingly difficult to handle complex tasks and predict potential financial risks. In the context of the digital economy era, the booming financial sharing services have reduced labour costs and improved operational efficiency. This paper designs and implements an intelligent financial sharing platform, establishes a fund payment risk early warning model based on an improved support vector machine algorithm, and tests it on the Financial Distress Prediction dataset. The experimental results show that the effectiveness of using F2 score and AUC evaluation methods can reach 0.9484 and 0.9023, respectively. After using this system, the average financial processing time per order decreases by 43%, and the overall financial processing time decreases by 27%. Finally, this paper discusses the role of intelligent financial sharing platform in accounting transformation and optimisation of production.

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.

This article studies the application of artificial intelligence technology in natural resource planning and management. This article first introduces the background of NR and AI intelligent technology, then conducts academic research and summary on NR planning management and AI intelligent technology. Then, an algorithm model based on multi-objective intelligent planning algorithm is established. Finally, simulation experiments are conducted, and experiments summary and discussion are provided. The experimental results show that the average efficiency value of the four stages of NR planning and management before use is 5.25, and the average efficiency value of the four stages of NR planning and management after use is 7. The difference in the average efficiency value before and after use is 1.75. It can be seen that the use of AI intelligent technology can effectively improve the efficiency of natural resource planning and management.

With the development of urban construction, its spatial evolution is also influenced by behavioural actors such as enterprises, residents, and environmental factors, leading to some decision-making behaviours that are not conducive to urban public space and environmental design. At the same time, some cities are vulnerable to various factors such as distance factors, transportation factors, and human psychological factors during the construction of public areas, resulting in a decline in the quality of urban human settlements. Urban public space is the guarantee of urban life. For this, in order to standardise urban public space and improve the quality of urban living environment, the standardisation of the environment of urban public space is required. The rapid development of intelligent algorithms and fuzzy control provides technical support for the environmental design of urban public spaces. Through the modelling of intelligent algorithms and the construction of fuzzy space, it can meet the diverse.

Intelligent digital virtual technology has become an indispensable part of modern construction, but there are also some problems in its practical application. Therefore, it is necessary to strengthen the design of intelligent building image processing systems from many aspects. Starting from image digital processing methods, this paper studies the digital twin virtual design scene construction method and related algorithms, converts the original image into a colour digital image through a greyscale algorithm, and then combines morphological knowledge and feature point extraction methods to complete the construction of a three-dimensional virtual environment. Finally, through the comparison of traditional image processing effects with smart building images based on digital twins and BIM technology, the results show that the optimised image processing results have higher clarity, sharper contrast, and a sensitivity increased by 5.84%, presenting better visual effects and solving the risk of misjudgement caused by inaccurate image recognition.

Physiological indicators are an important basis for reflecting the physiological health status of the human body and play an important role in medical practice. Association rules have also been one of the important research hotspots in recent years. This study aims to create a data mining system of association rules and artificial intelligence in biochemical indicators of sports training. This article uses Markov logic for network creation and system training, and tests whether the Markov logic network can be associated with the training system. The results show that the accuracy and recall rate obtained are about 90%, which shows that it is feasible to establish biochemical indicators of sports training based on Markov logic network, and the system has universal, guiding and constructive significance, ensuring that the construction of training system indicators will not go in the wrong direction.