Yesterday Yahoo! and Mozilla announced a new 5 year partnership to make “Yahoo the default search experience for Firefox in the United States on mobile and desktop”. The deal will make Yahoo! the default search experience on Firefox in …

Last Friday (19th July 2019) an independent artist’s debut single was placed at the top of Spotify’s New Music Friday playlist and Apple Music’s Best of the Week playlist in the UK. Not only that but at the time of writing this, 5 days later the song is in a total of 54 Spotify editorial...

Peter Drucker, ‘the founder of modern management’ said:

Advanced marketing techniques such as Account-based Marketing (ABM) and 1-1 marketing require a more individualised approach than traditional inbound marketing tactics. No longer can we paint with a broad brush, as marketers. We must find ways to speak directly with individuals, rather than an audience.

Gifts, decorations and festive food.

Not an artisan sourdough loaf in sight.

Plans are put In the freezer, alongside the lamb chops.

Which? research has found evidence of excessive smart device surveillance – from air fryers demanding permission to listen in on your conversations and sharing data with TikTok, to TVs wanting […]

The post Is my Air Fryer spying on me? Evidence of excessive smart home surveillance appeared first on ShinyShiny.

What was this Aston Martin mechanic thinking during the Brazilian Grand Prix weekend? Can you come up with the best caption for this picture?

In the round-up: New simulator 'like Star Wars' - Krack • Pirelli likes 'flexibility' of new C6 • Play NZ anthem when McLaren wins - Lawson

Dan Fallows is stepping down as Aston Martin's technical director, two-and-a-half years after taking over the role.

Niels Wittich has unexpectedly stood down from his role as Formula 1's race director. The FIA named Rui Marques as his replacement.

Today we announced the March 2024 core update. This is designed to improve the quality of Search by showing less content that feels like it was made to attract clicks, and more content that people find useful. We also shared that we have new spam policies to better handle the practices that can negatively impact Google's search results. In this post, we'll go into more detail for creators about both the update and the spam policies.

We're adding support for return policies at the organization level, which means you'll be able to specify a general return policy for your business instead of having to define one for each individual product you sell.

INTERVIEW. Pour le patron du groupe MoDem a l'Assemblee, il faut d'urgence sortir du bal des ego qui mine le << socle commun >> de Barnier et << etre utile aux Francais >>.

L'ecrivain d'origine syrienne a anime dans des colleges franciliens des ateliers organises pour lutter contre la radicalisation et promouvoir la laicite. Il temoigne.

Alors que les procureurs doivent requerir, ce mercredi 13 novembre a son proces, la presidente du groupe RN a l'Assemblee redoute, par-dessus tout, d'etre empechee de se presenter en 2027.

Le fondateur du Front national, age de 96 ans et qui a mis un terme a sa vie politique, est hospitalise afin de passer plusieurs examens, par << souci de securite >>.

El Diccionario de uso del español de María Moliner es una obra monumental. Son dos volúmenes que la autora iba elaborando pacientemente en el salón […]

Origen

Interactive video is increasingly becoming a more and more dominant feature of our media platforms. Especially due to the popular YouTube annotations framework, integrating graphical annotations in a video has become very fashionable these days. However, the current options are limited to a few graphical shapes for which the user can define as good as no dynamic behaviour. Despite the enormous demand for easy-creatable, interactive video there are no such advanced tools available.

In this article we describe an innovative approach, to realize dynamics and interactivity of video annotations. First we explain basic concepts of video-markup like the generic element model and visual descriptors. After that we introduce the event-tree model, which can be used to define event-handling in an interactive video formally as well as visually. By combining these basic concepts, we can give an effective tool to the video community for realizing interactive and dynamic video in a simple, intuitive and focused way.

One important subject associated with personal authentication capabilities is the analysis of handwritten signatures. Among the many known techniques, algorithms based on linguistic formalisms are also possible. However, such techniques require a number of algorithms for intelligent image analysis to be applied, allowing the development of new solutions in the field of personal authentication and building modern security systems based on the advanced recognition of such patterns. The article presents the approach based on the usage of syntactic methods for the static analysis of handwritten signatures. The graph linguistic formalisms applied, such as the IE graph and ETPL(k) grammar, are characterised by considerable descriptive strength and a polynomial membership problem of the syntactic analysis. For the purposes of representing the analysed handwritten signatures, new hierarchical (two-layer) HIE graph structures based on IE graphs have been defined. The two-layer graph description makes it possible to take into consideration both local and global features of the signature. The usage of attributed graphs enables the storage of additional semantic information describing the properties of individual signature strokes. The verification and recognition of a signature consists in analysing the affiliation of its graph description to the language describing the specimen database. Initial assessments display a precision of the method at a average level of under 75%.

Petite nouveauté : j'ouvre mon blog afin de faire vivre le débat et certains auront remarqué le changement d'intitulé. Désormais, Il y aura un nouveau contributeur en la personne de Vincent Grenier qui est entrepreneur et membre du Conseil National du...

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

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. 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

Le 20 avril 2018, un appel au boycott a été lancé sur les réseaux sociaux marocains contre trois entreprises leaders dans leurs secteurs d’activités. L’eau minérale de Sidi Ali, le lait de Centrale Danone et les stations de services Afriquia (pétrole) ont été victimes d’une guerre d’information, justifiée selon les internautes par des prix de vente élevés. Les appels au boycott ont été relayés par les internautes Marocains via des groupes et des pages ...

(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)

Les pycnogonides, une espèce marine apparentée aux araignées, peuvent faire repousser des parties du corps après amputation, et pas seulement de simples membres, selon une étude publiée lundi, ouvrant la voie à de nouvelles découvertes sur la régénération.

"Personne ne s'attendait à cela", a déclaré Gerhard Scholtz de la prestigieuse université Humboldt à Berlin, et l'un des auteurs principaux de cette étude parue dans la revue Proceedings of the National Academy of Sciences. "Nous avons été les premiers à démontrer que c'était possible", a-t-il ajouté. Il est connu qu'une multitude d'espèces d'arthropodes tels que les mille-pattes, les araignées ou d'autres insectes peuvent faire repousser une patte après l'avoir perdue.

"Les crabes peuvent même se débarrasser automatiquement de leurs membres s'ils sont attaqués", a déclaré Gerhard Scholtz, précisant: "ils les remplacent par un nouveau membre". Ce que les chercheurs ont découvert à travers leurs expériences avec ces minuscules créatures à huit pattes, est qu'elles sont capables de régénérer même d'autres parties du corps. Pour l'étude, ils ont amputé différents membres et parties postérieures du corps de 23 pycnogonides juvéniles et adultes, et ont observé les résultats.

Repousse d'un corps à partir de seulement quelques cellules

Aucune régénération de parties du corps n'a été constatée dans les spécimens adultes, mais certains étaient toujours en vie après deux ans. Les spécimens juvéniles, en revanche, ont connu une régénération complète ou quasi-complète des parties du corps manquantes, y compris l'intestin postérieur, l'anus, la musculature, et certaines parties d'organes génitaux.

A long terme, 90% des pycnogonides ont survécu, et 16 spécimens juvéniles ont effectué leur mue par la suite au moins une fois. La régénération postérieure a ainsi été constatée chez 14 des spécimens juvéniles tandis qu'aucun des spécimens adultes n'a mué ou ne s'est régénéré. Les capacités de régénération varient à travers le règne animal.

Les vers plats, par exemple, peuvent faire repousser leur corps à partir de seulement quelques cellules. Les vertébrés, dont les hommes, n'ont quasiment aucune capacité de régénération à l'exception de quelques espèces comme les lézards, qui peuvent faire repousser leurs queues.

Selon Gerhard Scholz, les résultats de l'étude ouvrent de nouvelles voies de recherche dans le domaine. "Une multitude d'espèces différentes peuvent être testées de cette manière", dit-il, ce qui pourrait permettre de comparer les mécanismes de régénération. "Au bout du compte, peut-être que les mécanismes que nous découvrons chez les arthropodes nous aiderons dans les traitements médicaux après la perte d'un membre, d'un doigt, etc... chez les humains", espère le chercheur.

(Belga) La reine Mathilde et la princesse Élisabeth effectueront une visite de travail en Égypte du 14 au 16 mars, a indiqué le Palais royal dans un communiqué lundi soir.

"Cette visite marquera l'intérêt historique de la famille royale pour l'Égypte antique et rendra hommage à la reine Élisabeth, dont l'intérêt et la passion sont à l'origine de l'épanouissement de l'égyptologie en Belgique. La Reine et la Princesse visiteront plusieurs sites que la reine Élisabeth a elle-même visités lors de ses voyages en Égypte, notamment le tombeau de Toutankhamon. Au Caire, elles assisteront également au vernissage d'une exposition consacrée à la reine Élisabeth et à l'égyptologie belge", peut-on lire dans le communiqué. La Reine et la Princesse visiteront aussi différents sites archéologiques à Louxor et ses environs, où des institutions et des universités belges effectuent des fouilles. Cette visite de travail commémore par ailleurs plusieurs anniversaires célébrés en 2022 et 2023: le 200e anniversaire du déchiffrement des hiéroglyphes par Jean-François Champollion, les centenaires de la découverte du tombeau de Toutankhamon et de sa visite par la reine Élisabeth, le 125e anniversaire de l'émergence de l'égyptologie belge et le 75e anniversaire de la mort de l'égyptologue belge Jean Capart. (Belga)

C'est la rentrￜe politique. Et qui dit rentrￜe, dit universitￜ d'ￜtￜ. Cette annￜe, la Rￜpublique en marche a vu les choses en grand en organisant ￜ la fois des journￜes...

The current advertising push methods have low accuracy and poor advertising conversion effects. Therefore, a Weibo marketing advertising push method based on social network data mining is studied. Firstly, establish a social network graph and use graph clustering algorithm to mine the association relationships of users in the network. Secondly, through sparsisation processing, the association between nodes in the social network graph is excavated. Then, evaluate the tightness between user preferences and other nodes in the social network, and use the TF-IDF algorithm to extract user interest features. Finally, an attention mechanism is introduced to improve the deep learning model, which matches user interests with advertising domain features and outputs push results. The experimental results show that the push accuracy of this method is higher than 95%, with a maximum advertising click through rate of 82.7% and a maximum advertising conversion rate of 60.7%.

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.

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.

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.

In the present scenario, the security of medical images is an important aspect in the field of image processing. Support vector machines (SVMs) are a supervised machine learning technique used in image classification. The roots of SVM are from statistical learning theory. It has gained excellent significance because of its robust, accurate, and very effective algorithm, even though it was applied to a small set of training samples. SVM can classify data into binary classification or multiple classifications according to the application's needs. Discrete wavelet transform (DWT) and singular value decomposition (SVD) transform techniques are utilised to enhance the image's security. In this paper, the image is first classified using SVM into ROI and RONI, and thereafter, to enhance the images diagnostic capabilities, the DWT-SVD-based hybrid watermarking technique is utilised to embed the watermark in the RONI region. Overall, our work makes a significant contribution to the field of medical image security by presenting a novel and effective solution. The results are evaluated using both perceptual and imperceptibility testing using PSNR and SSIM parameters. Different attacks were introduced to the watermarked image, which shows the efficacy and robustness of the proposed algorithm.

Screen-shooting will lead to information leakage. Anti-screen-shooting watermark, which can track the leaking sources and protect the copyrights of images, plays an important role in image information security. Due to the randomness of shooting distance and angle, more robust watermark algorithms are needed to resist the mixed attack generated by screen-shooting. A robust digital watermarking algorithm that is resistant to screen-shooting is proposed in this paper. We use improved Harris-Laplace algorithm to detect the image feature points and embed the watermark into the feature domain. In this paper, all test images are selected on the dataset USC-SIPI and six related common algorithms are used for performance comparison. The experimental results show that within a certain range of shooting distance and angle, this algorithm presented can not only extract the watermark effectively but also ensure the most basic invisibility of watermark. Therefore, the algorithm has good robustness for anti-screen-shooting.

The video game industry (VGI) has evolved considerably, transitioning from a niche market to a substantial sector. The VGI's magnitude and the societal implications tied to video game consumption have naturally piqued the interest of scholars in marketing and consumer behaviour. This research serves a dual purpose: firstly, it consolidates existing VG literature by evaluating articles, concepts, and methodologies, systematically tracing their evolution; secondly, it outlines potential directions and implications for forthcoming research. Within this literature, a predominant focus lies on articles investigating purchase decisions concerning VGs, followed by those exploring the integration of video game consumption into broader social contexts. Notably, a limited number of articles delve into player-game interactions and experiences within gaming worlds. This imbalance can be attributed to the fact that such inquiries are often suited to psychology and multidisciplinary journals, while the marketing discipline has predominantly addressed the VGI from a marketing management standpoint.

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.

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.

While digitalisation reforms aiming to enhance the quality of public services were put in place, most stakeholders in developing countries still use paper-based-tendering processes, which are associated with increased costs. To overcome these problems, calls to adopt e-bidding have recently emerged. This study aims to explore the readiness of Moroccan SMEs to adopt e-bidding. To achieve this goal, we proposed an integrated framework combining the TAM and UTAUT models to examine the predictors of SMEs' intention to adopt e-bidding. We empirically tested the conceptual model using a partial least squares (PLS) estimation based on data from 210 SMEs. Our results suggest that effort expectancy, facilitating conditions, and social influence as the key factors influencing SMEs intention to adopt e-bidding. We also suggest firm size as a significant moderator. This will help in improving SMEs' user experience and will also allow a better implementation of e-bidding in Morocco and similar contexts.

Since its birth, the stock market has received widespread attention from many scholars and investors. However, there are many factors that affect stock prices, including the company's own internal factors and the impact of external policies. The extent and manner of fundamental impacts also vary, making stock price predictions very difficult. Based on this, this article first introduces the research significance of the stock market prediction framework, and then conducts academic research and analysis on two key sentences of stock market prediction and artificial intelligence in stock market prediction. Then this article proposes a constructive algorithm theory, and finally conducts a simulation comparison experiment and summarises and discusses the experiment. Research results show that the neural network prediction method is more effective in stock market prediction; the minimum training rate is generally 0.9; the agency's expected dilution rate and the published stock market dilution rate are both around 6%.

Pandemic has compelled the entire world to change their way of life and work. To control the infection rate, academic institutes deliver education online similarly. At least one smartphone is available in every home, and students use their smartphones to attend class. The study investigates the link between smartphone usage (SU) and academic performance (AP) during the pandemic. 490 data were obtained from various institutions and undergraduate students using stratified random sampling. These components were identified using factor analysis and descriptive methods, while the relationship of SU and AP based on gender classification was tested using Smart-PLS-SEM. The findings show that SU has a substantial relationship with academic success, whether done in class or outside of it. Even yet, the study found that SU and AP significantly impact both male and female students. Furthermore, the research focuses on SU outside and within the classroom to improve students' AP.

Electronic portfolios (e-portfolios) have a positive impact on the learning process in a broad range of educational sectors and on learners of all ages. Yet because most e-portfolio-related studies are about their implementation in higher education, this type of research is less usual in the early childhood context, and there is no available research for Greek schools. This study aims to investigate the impact of e-portfolios on learning in a Greek primary school and to provide a resource regarding the educational benefits of e-portfolio in primary education. To do that, it employs the qualitative naturalistic method to collect data, along with mixed methods which were used to achieve triangulation and strengthen confidence in the outcomes. Participants in the research were fourteen 8-year-old pupils, and one of the researchers was their regular teacher. Data evaluation revealed that the e-portfolio added value in pupils’ learning, acted as a medium to involve parents, promoted pupils’ self-esteem, and was acknowledged as a valuable assessment tool and a challenge for the school community. Based on the experience of the e-portfolio implementation, the authors provide some suggestions that would possibly help researchers and primary school teachers adopt and develop e-portfolio systems in their particular settings.

Aim/Purpose: To conduct a needs assessment and subsequently create micro-storytelling media aimed at enhancing the Digital Intelligence Quotient (DQ) skills of young individuals. Background: In today's digital society, DQ has emerged as a vital skill that elevates individuals in all aspects of life, from daily living to education. To empower Thai youth, this study seeks to innovate DQ content by adapting it into a digital format known as micro-storytelling. This unique approach combines the art of storytelling with digital elements, creating engaging and effective micro-learning media Methodology: The methodology comprises three phases: 1) assessing the need for digital micro-storytelling development; 2) developing digital micro-storytelling; and 3) evaluating the DQ skills among young individuals. The sample group consisted of 55 higher education learners for needs assessment and 30 learners in the experiment group. Data analysis involves PNI modified, mean, and standard deviation. Contribution: This research contributes by addressing the urgent need for DQ skills in the digital era and by providing a practical solution in the form of digital micro-storytelling, tailored to the preferences and needs of Thai youth. It serves as a valuable resource for educators and policymakers seeking to empower young learners with essential digital competencies. Findings: The findings demonstrate three significant outcomes: 1) The learners wanted to organize their own learning experience with self-paced learning in a digital landscape, and they preferred digital media in the form of video. They were most interested in developing DQ to enhance their understanding of digital safety, digital security, and digital literacy; 2) according to a consensus of experts, digital micro-storytelling has the greatest degree of quality in terms of its development, content, and utilization, with an overall average of 4.86; and 3) the overall findings of the assessment of DQ skills indicate a favorable level of proficiency. Recommendations for Practitioners: Align materials with micro-learning principles, keeping content concise for effective knowledge retention. Empower students to personalize their digital learning and promote self-paced exploration based on their interests. Recommendation for Researchers: Researchers should continuously assess and update digital learning materials to align with the evolving digital landscape and the changing needs of students and investigate the long-term effects of DQ improvement, especially in terms of online safety and digital literacy in students' future lives and careers. Impact on Society: This study's impact on society is centered around fostering a DQ, promoting innovative educational approaches, and elevating Thai youth with essential digital skills. It contributes to a safer, more informed, and digitally literate generation prepared for the challenges of the digital era. Future Research: Undertake comparative studies to analyze the effectiveness of different digital learning formats and methodologies. Comparing micro-storytelling with other approaches can help identify the most efficient and engaging methods for enhancing DQ.

Smart home devices are vulnerable to various attacks, including distributed-denial-of-service (DDoS) attacks. Current detection techniques face challenges due to nonlinear thought, unusual system traffic, and the fluctuating data flow caused by human activities and device interactions. Identifying the baseline for 'normal' traffic and suspicious activities like DDoS attacks from encrypted data is also challenging due to the encrypted protective layer. This work introduces a concept called synoptic crow search with recurrent transformer network-based DDoS attack detection, which uses the synoptic weighted crow search algorithm to capture varying traffic patterns and prioritise critical information handling. An adaptive recurrent transformer neural network is introduced to effectively regulate DDoS attacks within encrypted data, counting the historical context of the data flow. The proposed model shows effective performance in terms of low false alarm rate, higher detection rate, and accuracy.