The trains are converted from old Underground trains and will be rolled out in the Thames Valley.

"Having autism, you're recognised as having differences, but being a part of a club, you're the same."

A man in his 20s remains in hospital with serious facial injuries after shots were fired at a park.

A Planning Inspectorate finds the path was "once a highway" so can therefore "always" be a highway.

The iPhone could finally show you how long it’ll take to finish charging. Code spotted in the second iOS 18.2 beta by 9to5Mac shows a new “BatteryIntelligence” feature that will let you […]

The post Apple to roll out ‘Battery Intelligence’ for iPhone, Amazon slashes price of 43inch Hisense smart TV to £228 appeared first on Tech Digest.

The new series is produced by the BBC’s Natural History Unit in Bristol.

By now, you may already be aware of Ashton Kutcher's campaign against the Village Voice, sparked by an article critical of the substance and message of his anti-trafficking adverts. The Voice has form on this one: their earlier article about dodgy stats that get bandied about in the trafficking discussion is a must-read.

The usual disclaimer... I am (as indeed all of Kutcher's critics are) opposed to trafficking in any form, including child sex trafficking. But we must not let emotion exclusively carry the day; it achieves nothing. The Voice hits the nail on the head when they sum up anti-trafficking efforts: "an emotional reaction, based on good intentions, but grounded in bogus information."

The problem of bogus information is this - campaigns such as Kutcher's conflate all sex work with child sex trafficking, and child sex trafficking with all trafficking. Approaches that do so not only encourage criminalisation legislation that harms consenting adults, but also obscures the real victims. How? By using vastly inflated numbers for one kind of trafficking, and pretty much ignoring everything else. Actual children being actually trafficked for actual sex are rarely, if ever, found by the kind of scatterhsot brothel raids and streetwalker crackdowns so many seem to consider "succeses" in the anti-trafficking effort.

Please, please stop kidding yourselves. The raids you hear about are not successes. They are vast wastes of time, money, and manpower. And many groups receiving funding meant to help victims of trafficking seem instead to be lining their own pockets. There is undoubtedly work to be done eliminating trafficking of men and women for any kind of labour. It almost certainly isn't the approach anti-traffickers think will work.

Kutcher’s response against the Village Voice has included tweeting advertisers on Backpage.com, accusing them of supporting slavery. So far, so "concerned". And then this tweet:

"I’ve spent the last 2 years meeting with every expert on the issue of Human Trafficking that I can find, reading countless books, meeting with victims and former traffickers, and studying effective international models to combat trafficking."

Listen to this week's podcast (September 9, 2011) Patterns For Large-Scale JavaScript Application Architecture Patterns For Large-Scale JavaScript Application Architecture is a lengthy article by Addy Osmani detailing some basic principles of writing a large-scale JavaScript application. It's inspired by a classic Nicholas Zakas talk outlining some of the same principles ...

Listen to this week's podcast (Podcast edit: I mistakenly mention Respond.js, which is actually a media query polyfill - I'm actually talking about Responsive images) Google Dart By far the biggest news of the week isn't JavaScript, but rather a language called Dart (formerly Dash?), which certain factions within Google hope will replace ...

Listen to this week's podcast (January 20, 2012)! iOS Orientationchange Fix jQuery Mobile's Scott Jehl has released iOS-Orientationchange-Fix (read his blog post). This has been a persistent annoyance on iOS since its release. You may be familiar with the mobile viewport tag, which allows you to properly fit sites to ...

Even blue states are doing it; what’s the matter with this state?

This paper systematically discusses the security and privacy concerns for e-learning systems. A five-layer architecture of e-learning system is proposed. The security and privacy concerns are addressed respectively for five layers. This paper further examines the relationship among the security and privacy policy, the available security and privacy technology, and the degree of e-learning privacy and security. The digital identity attributes are introduced to e-learning portable devices to enhance the security and privacy of e-learning systems. This will provide significant contributions to the knowledge of e-learning security and privacy research communities and will generate more research interests.

The quality attributes of a software system are, to a large extent, determined by the decisions taken early in the development process. Best practices in software engineering recommend the identification of important quality attributes during the requirements elicitation process, and the specification of software architectures to satisfy these requirements. Over the years the software engineering community has studied the relationship between quality attributes and the use of particular architectural styles and patterns. In this paper we study the relationship between quality attributes and Aspect-Oriented Software Architectures - which apply the principles of Aspect-Oriented Software Development (AOSD) at the architectural level. AOSD focuses on identifying, modeling and composing crosscutting concerns - i.e. concerns that are tangled and/or scattered with other concerns of the application. In this paper we propose to use AO-ADL, an aspect-oriented architectural description language, to specify quality attributes by means of parameterizable, and thus reusable, architectural patterns. We particularly focus on quality attributes that: (1) have major implications on software functionality, requiring the incorporation of explicit functionality at the architectural level; (2) are complex enough as to be modeled by a set of related concerns and the compositions among them, and (3) crosscut domain specific functionality and are related to more than one component in the architecture. We illustrate our approach for usability, a critical quality attribute that satisfies the previous constraints and that requires special attention at the requirements and the architecture design stages.

RDF data can be analyzed with various query languages such as SPARQL. However, due to their nature these query languages do not support fuzzy queries that would allow us to extract a broad range of additional information. In this article we present a new method that transforms the information presented by subject-relationobject relations within RDF data into Activation Patterns. These patterns represent a common model that is the basis for a number of sophisticated analysis methods such as semantic relation analysis, semantic search queries, unsupervised clustering, supervised learning or anomaly detection. In this article, we explain the Activation Patterns concept and apply it to an RDF representation of the well known CIA World Factbook.

The user experience of any software or website consists of elements from the conceptual to the concrete level. These elements of user experience assist in the design and development of user interfaces. On the other hand, ontologies provide a framework for computable representation of user interface elements and underlying data. This paper discusses strategies of introducing ontologies at different user interface layers adapted from user experience elements. These layers range from abstract levels (e.g. User needs/Application Objectives) to concrete levels (e.g. Application User Interface) in terms of data representation. The proposed ontological framework enables device independent, semi-automated GUI construction which we will demonstrate at a personal information management example.

Des dizaines de morts dans le sud-ouest du Pakistan après un attentat suicide

Tensions à l'Université Lyon-3 : la classe politique condamne les attaques contre Yaël Braun-Pivet

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

1. Attention, votre airfryer pourrait produire une substance cancérigène dans vos aliments selon une étude  Yahoo Actualités
2. 3 bonnes raisons de choisir un Airfryer en 2024  La Provence
3. Nos 30 recettes rapides et faciles au Airfryer, du plat de résistance au dessert  Le Figaro
4. Les air fryers sont-ils dangereux pour la santé ? Une étude lance l'alerte  Allo Docteurs
5. Airfryer : attention aux acrylamides potentiellement cancérigènes  Pourquoi Docteur ?

1. Guerre en Ukraine : Vladimir Poutine «est en train de lancer une attaque de missiles sur Kiev», avertit le chef de cabinet de Volodymyr Zelensky  CNEWS
2. Guerre en Ukraine, jour 994 : attaque massive sur Kiev, Blinken promet « une réponse ferme »  La Croix
3. Ukraine: Kiev visée par une attaque de missiles et de drones  RFI
4. Guerre en Ukraine. Alerte aérienne, soldats nord-coréens à Koursk… le point sur la nuit  Ouest-France
5. Vincent Hervouët : Trump mettra-t-il fin à la guerre en Ukraine ?  Le Journal du dimanche

1. Senators make short work of listless Leafs in a flat Battle of Ontario  The Globe and Mail
2. Tavares on Maple Leafs’ lifeless loss to Senators: ‘We should be disappointed’  Sportsnet.ca
3. Ullmark records first shutout of season as Senators smother Maple Leafs  TSN
4. TAKEAWAYS: Ottawa Senators draw first blood in Battle of Ontario  Ottawa Citizen
5. Wednesday FTB: Lose to the Sens, why not?  Pension Plan Puppets

Des files d'attente, la nuit, devant les prￜfectures, pour tenter d'obtenir un rendez-vous afin de demander ou de renouveler un titre de sￜjour. C'ￜtait la rￜalitￜ au dￜbut des annￜes...

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.

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.

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 Hour of Code is a one-hour introduction to computer science organized by Code.org, a non-profit dedicated to expanding participation in computer science. This study investigated the impact of the Hour of Code on students’ attitudes towards computer programming and their knowledge of programming. A sample of undergraduate students from two universities was selected to participate. Participants completed an Hour of Code tutorial as part of an undergraduate course. An electronic questionnaire was implemented in a pre-survey and post-survey format to gauge the change in student attitudes toward programming and their programming ability. The findings indicated the positive impact of the Hour of Code tutorial on students’ attitude toward programming. However, the students’ programming skills did not significantly change. The authors suggest that a deeper alignment of marketing, teaching, and content would help sustain the type of initiative exemplified by the Hour of Code.

Aim/Purpose: The present study investigated and compared students’ attention in terms of time-on-task and number of distractors between using a touchscreen and a pen tablet in mathematical problem-solving activities with virtual manipulatives. Background: Although there is an increasing use of these input devices in educational practice, little research has focused on assessing student attention while using touchscreens or pen tablets in a mathematics classroom. Methodology: A qualitative exploration was conducted in a public elementary school in New Taipei, Taiwan. Six fifth-grade students participated in the activities. Video recordings of the activities and the students’ actions were analyzed. Findings: The results showed that students in the activity using touchscreens maintained greater attention and, thus, had more time-on-task and fewer distractors than those in the activity using pen tablets. Recommendations for Practitioners: School teachers could employ touchscreens in mathematics classrooms to support activities that focus on students’ manipulations in relation to the attention paid to the learning content. Recommendation for Researchers: The findings enhance our understanding of the input devices used in educational practice and provide a basis for further research. Impact on Society: The findings may also shed light on the human-technology interaction process involved in using pen and touch technology conditions. Future Research: Activities similar to those reported here should be conducted using more participants. In addition, it is important to understand how students with different levels of mathematics achievement use the devices in the activities.

Aim/Purpose: This study aimed to reveal the effect of the previous Internet-based education (IBE) experiences of the students’ readiness, attitude, and self-control / self-management variables towards the e-learning process, and also to determine their opinions. Background: The institutions have made efforts to ensure the continuity of education through their learning management systems and the necessity of addressing the e-learning process from the perspective of students once again showed itself as an undeniable fact. Accordingly, the necessity to consider holistically the variables of readiness, attitude, and self-control/self-management, which affect students’ adaptation to e-learning process, has once again emerged based on the relevant literature. Methodology: This research based on the simultaneous mixed method considering the previous IBE experiences of 75 Computer Education and Instructional Technology (CEIT) students taking part in the study in Turkey. The quantitative results of the study were analyzed based on the single-group pretest-posttest weak experimental design. Qualitative results were obtained through the structured interview form and set an example for the case study. Contribution: The results showed that regardless of students’ previous Internet-based education (IBE) experience, it is seen that increasing and continuous experience has a significant effect on the readiness, attitude and self-control / self-management variables towards the e-learning process. The main contribution of experimental results showed that IBE experience is effective on individuals’ perceptions of internet self-efficacy, and has an impact on the self-learning skills of individuals. In addition to this, the e-learning experience has an impact on individuals’ self-evaluation. It is also seen that the certificate presented to learners in the e-learning environment has a positive effect on students’ attitudes towards e-learning processes. Finally, the experiences of e-learning processes, the methods used to transfer the content in the learning environment, the motivation and feedback provided to the learner also support the significant difference obtained in terms of readiness, attitude and self-control / self-management. Findings: After the findings were analyzed holistically in depth, it has been observed that; if the contents offered to students in e-learning environments support their professional development, in this case, their attitudes, readiness (excluding the sub-dimension of learner control), and self-control/self-management skills for these environments differ significantly in the posttest. It is also among the results that students having previous IBE experience have not higher awareness levels on online communication self-efficacy, technology use self-efficacy, readiness for e-learning, e-learning predisposition, self-reinforcement, self-control management, although significantly found. The findings regarding the effectiveness of the experimental process are as follows: Although it is possible for the students having previous IBE experience to use these experiences within the course for their personal development, it has been seen that the observed differences regarding students’ readiness, attitude, and self-control/self-management towards e-learning processes arise from the experimental operation. Recommendations for Practitioners: It is recommended for the policy-makers and practitioners that while e-learning platforms were designing, using different methods for delivering the content is as important as making the interaction meaningful and sustainable. In addition to this, to develop a positive attitude it is recommended that individuals’ participation of an e-learning platform should be supported with a certificate. Recommendation for Researchers: Researchers should test the obtained results by a well-structured e-learning platform with their recorded activities on the platform (e.g. in which section was used mostly by a learner etc.). Hence, the impact of IBE experiences might be discussed in an up level framework. Impact on Society: Actually, this study is based on a mix design and the results were also meaningful especially considering the implacable global pandemic. It is clearly understood by this process that e-learning is very important. In line with this, to support the e-learning process (e.g. with the method while delivering the content, well-structured feedback, motivation strategies etc.) and make it sustainable, the increasing of individual’s readiness, attitude, and self-control through the IBE would be indispensable. Future Research: Future studies might focus on the longitudinal methods. It is worth to find out how the students experiences affect the sustainability of the course content, and what should the program developer make to improve their course content in line with the findings of longitudinal studies.

In today's world, malware has become a part and threat to our computer systems. All electronic devices are very susceptible/vulnerable to various threats like different types of malware. There is one subset of malware called ransomware, which is majorly used to have large financial gains. The attacker asks for a ransom amount to regain access to the system/data. When dynamic technique using machine learning is used, it is very important to select the correct set of features for the detection of a ransomware attack. In this paper, we present two novel algorithms for the detection of ransomware attacks. The first algorithm is used to assign the time stamp to the features (API calls) for the ordering and second is used for the ordering and ranking of the features for the early detection of a ransomware attack.

This study focuses on the importance of monitoring student attendance in education and the challenges faced by educators in doing so. Existing methods for attendance tracking have drawbacks, including high costs, long processing times, and inaccuracies, while security and privacy concerns have often been overlooked. To address these issues, the authors present a novel internet of things (IoT)-based self-lecture attendance system (SLAS) that leverages smartphones and QR codes. This system effectively addresses security and privacy concerns while providing streamlined attendance tracking. It offers several advantages such as compact size, affordability, scalability, and flexible features for teachers and students. Empirical research conducted in a live lecture setting demonstrates the efficacy and precision of the SLAS system. The authors believe that their system will be valuable for educational institutions aiming to streamline attendance tracking while ensuring security and privacy.

Nostalgia has an intrinsic association with consumer behaviour. Retrieval of memories drives emotions among consumers and reinforces experience-led buying decisions. Despite nostalgia, and consumption being a common practice at various times in life, issues regarding the nostalgia stimuli on customers' perceptions and buying decisions remain less explored. This article aims at exploring the consumption pattern of adult consumers by analysing the influence of nostalgic behaviour referring to the autobiographic memories and social motivations. It describes the purchase intentions and consumption pattern among adult consumers in the context of self-reference criteria based on nostalgic memories and social motivations. This article offers constructive understanding on establishing relationship between nostalgic memories and consumption pattern over the temporal framework and establishing the brand loyalty and hedonic satisfaction. It contributes to the existing literature by critically examining the theoretical concepts and empirical findings of previous studies on perceptions of consumers on nostalgic emotions and their role in making buying decisions.

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.

Numerous scandals due to unethical decisions occur despite the growing use of decision support systems (DSS). Several scholars recommend incorporating ethical attributes along with business requirements in DSS design. However, little guidance exists to indicate which ethical attributes to include and the importance ethical attributes should be given in comparison to business requirements. This study addresses this deficiency by identifying ethical requirements to integrate in DSS design drawn from the business ethics literature. This study conducted a large-scale empirical survey with information technology decision-makers to examine the relative importance of DSS fit with ethical and business requirements as well as the appropriate balance of those requirements on perceived DSS performance. The results show that decision makers perceive better DSS performance when the ethical and business requirements align with its organisation's beliefs than from ethical or business requirements alone.

A hybrid network system for mitigating errors due to jamming attacks in cognitive radio networks (CRNs) is named LeNet deep stacked autoencoder (LDSAE) and is developed. In this exploration, the sensing stage and decision-making are considered. The sensing unit is composed of four steps. First, the detected signal is forwarded to filtering progression. Here, BPF is utilised to filter the detected signal. The filtered signal is squared in the second phase. Third, signal samples are combined and jamming attacks occur by including false energy levels. Last, the attack is maliciously affecting the FC decision in the fourth step. On the other hand, FC initiated the decision-making and also recognised jamming attacks that affect the link amidst PU and SN in decision-making stage and it is accomplished by employing LDSAE-based trust model where the proposed module differentiates the malicious and selfish users. The analytic measures of LDSAE gained 79.40%, 79.90%, and 78.40%.

The study aims to analyse the impact of shopping applications on the shopping behaviour of the working women community in Bangalore, a city known as the IT hub. The research uses a quantitative analysis with SPSS version 23 software and a structured questionnaire survey technique to gather data from the working women community. The study uses descriptive statistics, ANOVA, regression, and Pearson correlation analysis to evaluate the perception of working women regarding the significance of online shopping applications. The results show that digital shopping applications are more prevalent among the working women community in Bangalore. The study also evaluates the socio-economic and psychological factors that influence their purchasing behaviour. The findings suggest that online marketers should enhance their strategies to improve their business on digital platforms. The research provides valuable insights into the shopping habits of the working women community in Bangalore.