In this paper, we propose a novel dexterous technique for fast and accurate recognition of online handwritten Kannada and Tamil characters. Based on the primary classifier output and prior knowledge, the best classifier is chosen from set of three classifiers for second stage classification. Prior knowledge is obtained through analysis of the confusion matrix of primary classifier which helped in identifying the multiple sets of confused characters. Further, studies were carried out to check the performance of secondary classifiers in disambiguating among the confusion sets. Using this technique we have achieved an average accuracy of 92.6% for Kannada characters on the MILE lab dataset and 90.2% for Tamil characters on the HP Labs dataset.

E-speranto is a formal language for generating multilingual texts on the World Wide Web. It is currently still under development. The vocabulary and grammar rules of E-speranto are based on Esperanto; the syntax of E-speranto, however, is based on XML (eXtensible Markup Language). The latter enables the integration of documents generated in E-speranto into web pages. When a user accesses a web page generated in E-speranto, the interpreter interprets the document into a chosen natural language, which enables the user to read the document in any arbitrary language supported by the interpreter.

The basic parts of the E-speranto interpreting system are the interpreters and information resources, which complies with the principle of separating the interpretation process from the data itself. The architecture of the E-speranto interpreter takes advantage of the resemblance between the languages belonging to the same linguistic group, which consequently results in a lower production cost of the interpreters for the same linguistic group.

We designed a proof-of-concept implementation for interpreting E-speranto in three Slavic languages: Slovenian, Serbian and Russian. These languages share many common features in addition to having a similar syntax and vocabulary. The content of the information resources (vocabulary, lexicon) was limited to the extent that was needed to interpret the test documents. The testing confirmed the applicability of our concept and also indicated the guidelines for future development of both the interpreters and E-speranto itself.

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.

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%.

Les images sont « belles », elles tournent en boucle sur les réseaux sociaux, elles tendent à vouloir accréditer la thèse d’un mouvement composé d’ultra des deux extrêmes. La chose devrait donc être entendue, pour les « bons » militants ; rassurons-nous...

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

This research explores vehicular ad hoc networks (VANETs) and their extensive applications, such as enhancing traffic efficiency, infotainment, and passenger safety. Despite significant study, widespread deployment of VANETs has been hindered by security and privacy concerns. Challenges in implementation, including scalability, flexibility, poor connection, and insufficient intelligence, have further complicated VANETs. This study proposes leveraging cloud computing to address these challenges, marking a paradigm shift. Cloud computing, recognised for its cost-efficiency and virtualisation, is integrated with VANETs. The paper details the nomenclature, architecture, models, services, applications, and challenges of VANET-based cloud computing. Three architectures for VANET clouds - vehicular clouds (VCs), vehicles utilising clouds (VuCs), and hybrid vehicular clouds (HVCs) - are discussed in detail. The research provides an overview, delves into related work, and explores VANET cloud computing's architectural frameworks, models, and cloud services. It concludes with insights into future work and a comprehensive conclusion.

1. The Stanchies: Canucks stomp out Flames in 3-1 victory  Canucks Army
2. Pettersson, Canucks having fun again with bounce-back win over Flames  Sportsnet.ca
3. Three takeaways as Flames cap gruelling stretch with loss to Canucks  Calgary Herald
4. Pettersson has goal, assist to lift Canucks past Flames  NHL.com
5. I Watched This Game: Brännström gets first goal as a Canuck in comfy win over Flames  Vancouver Is Awesome

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

1. UN chief warns COP29 summit to pay up or face climate-led disaster for humanity  The Globe and Mail
2. Climate Summit, in Early Days, Is Already on a ‘Knife Edge’  The New York Times
3. At COP29 summit, nations big and small get chance to bear witness to climate change  The Globe and Mail
4. Terence Corcoran: COP29 hit by political ‘dunkelflaute’  Financial Post
5. COP29: Albania PM goes off script to ask 'What on Earth are we doing?'  Euronews

Online journal dedicated to nursing informatics

by Mitchell Longan[1] Introduction The European Parliament is currently considering a proposal to address problems of piracy and other forms of copyright infringement associated with the digital world.[2] Article 13 of the proposed Directive on Copyright in the Digital Single

The problem of dispatching is key to management of shared bicycles. Considering the number of borrowing and returning events during the dispatching period, optimisation plans of shared bicycles dispatching are studied in this paper. Firstly, the dispatching model of shared bicycles is built, which regards the dispatching cost and lost demand as optimised objectives. Secondly, the solution algorithm is designed based on non-dominated Genetic Algorithm. Finally, a case is given to illustrate the application of the method. The research results show that the method proposed in the paper can get optimised dispatching plans, and the model considering borrowing and returning during dispatching period has better effects with a 39.3% decrease in lost demand.

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 order to further improve the teaching quality of multimedia teaching in school daily teaching, a classroom facial expression emotion recognition model is proposed based on convolutional neural network. VGGNet and CliqueNet are used as the basic expression emotion recognition methods, and the two recognition models are fused while the attention module CBAM is added. Simulation results show that the designed classroom face expression emotion recognition model based on V-CNet has high recognition accuracy, and the recognition accuracy on the test set reaches 93.11%, which can be applied to actual teaching scenarios and improve the quality of classroom teaching.

To achieve psychological and emotional analysis of massive internet chats, researchers have used statistical methods, machine learning, and neural networks to analyse the dynamic tendencies of texts dynamically. For long readers, the author first compares and explores the differences between the two psychoanalysis algorithms based on the emotion dictionary and machine learning for simple sentences, then studies the expansion algorithm of the emotion dictionary, and finally proposes an extended text psychoanalysis algorithm based on conditional random field. According to the experimental results, the mental dictionary's accuracy, recall, and F-score based on the cognitive understanding of each additional ten words were calculated. The optimisation decreased, and the memory and F-score improved. An <i>F</i>-value greater than 1, which is the most effective indicator for evaluating the effectiveness of a mental analysis problem, can better demonstrate that the algorithm is adaptive in the literature dictionary. It has been proven that this scheme can achieve good results in analysing emotional tendencies and has higher efficiency than ordinary weight-based psychological sentiment analysis algorithms.

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

This article explores dual affiliated graduate students that conduct research involving both universities and firms, which we conceptualise as a form of academic engagement, e.g., knowledge networks. We explore what they do during their studies, and their perceptions about their contributions to the firm's capacities for technology and innovation. So far, university-industry interactions in engineering are less researched than other fields, and this qualitative study focuses upon one department of Electrical Engineering in Sweden. First, we define and describe how the partner firms and universities organise this research collaboration as a form of academic engagement. Secondly, we propose a conceptual framework specifying how graduate students act as boundary-spanners between universities and firms. This framework is used for the empirical analysis, when exploring their perceptions of impact. Our results reveal that they primarily engage in problem-solving activities in technology, which augment particularly the early stages of absorptive capacities in firms.

Many parents, educators, and policy makers see great potential for leveraging tools like laptop computers, tablets, and smartphones in the classrooms of the world. Although increasing students’ technology access may be associated with increased student achievement, there is little research directly investigating objective measures of student achievement. This study addresses the short-term and long-term quantitative impacts of one of the world’s first school efforts to provide Kindergarten through 3rd grade classrooms with 1:1 iPad access and a range of English Language Arts (ELA) and math Apps. This report summarizes two investigations conducted during this iPad implementation. First, a 9-week pre/post randomized control trial was conducted in which 8 Kindergarten classes used literacy and numeracy apps while another 8 Kindergarten classes used their traditional (non-iPad) resources. At the end of this short implementation period, slightly stronger literacy performance gains were observed in the iPad settings. In a second longitudinal study, three years of assessment data were explored before and after the 1:1 iPad implementation in grades K to 2. Results from the longitudinal study provide emerging evidence of potential increases in ELA achievement, but no consistent results in math achievement. This paper adds to the sparse literature in this area and provides a springboard for further research.

Teaching advanced programming can be a challenge, especially when the students are pursuing different majors with diverse analytical and problem-solving capabilities. The purpose of this paper is to explore the efficacy of using a particular problem as a vehicle for imparting a broad set of programming concepts and problem-solving techniques. We present a classic brain teaser that is used to communicate and demonstrate advanced software development concepts and techniques. Our results show that students with varied academic experiences and goals, assuming at least one procedural/structured programming pre-requisite, can benefit from and also be challenged by such an exercise. Although this problem has been used by others in the classroom, we believe that our use of this problem in imparting such a broad range of topics to a diverse student population is unique.

This research study explores peer teaching and learning without a domain expert teacher, within the context of an activity where teams of second level students (~16 years old) are required to create a learning experience for their peers. The study looks at how participants would like to be taught and how they would teach their peers if given the opportunity and examines the support they require, their motivation levels, and if they actually learn curriculum content using this approach. An exploratory case study methodology was used, and the findings suggest that students want varied learning experiences that include many of the elements which would fall under the heading of 21st century learning, that with some support and encouragement they can create innovative learning experiences for their peers, and that they can learn curriculum content from the process.

The ways people connect, interact, share, and communicate have changed due to recent developments in information technology. These developments, categorized as social media, have captured the attention of business executives, technologists, and education professionals alike, and have altered many business models. Additionally, the concept of social media impacts numerous sub-disciplines within business and has become an important issue with operational, tactical, and strategic considerations. Despite this interest, many business schools do not have courses involving social media technologies and applications. In those that do, the placement and focus of the course varies considerably. This article provides motivation and insight into the process of developing an approach for effectively teaching social media use in business. Additionally, it offers implementation examples of courses taught at three major universities. The article concludes with lessons-learned that will give instructors practical guidance and ensure that social media courses taught in a business school provide students with a solid basis for integrating social media into business practice.

Prior work demonstrates the importance of introducing young children to programming and engineering content before gender stereotypes are fully developed and ingrained in later years. However, very little research on gender and early childhood technology interventions exist. This pilot study looks at N=45 children in kindergarten through second grade who completed an eight-week robotics and programming curriculum using the KIWI robotics kit. KIWI is a developmentally appropriate robotics construction set specifically designed for use with children ages 4 to 7 years old. Qualitative pre-interviews were administered to determine whether participating children had any gender-biased attitudes toward robotics and other engineering tools prior to using KIWI in their classrooms. Post-tests were administered upon completion of the curriculum to determine if any gender differences in achievement were present. Results showed that young children were beginning to form opinions about which technologies and tools would be better suited for boys and girls. While there were no significant differences between boys and girls on the robotics and simple programming tasks, boys performed significantly better than girls on the advanced programming tasks such as, using repeat loops with sensor parameters. Implications for the design of new technological tools and curriculum that are appealing to boys and girls are discussed.

Aim/Purpose: This study aimed to examine whether there is a difference between manual feedback and online feedback with regard to feedback quality, respondents’ percentage, reliability and the amount of verbal comments written by students. Background: The quality of teaching is an important component of academic work. There are various methods for testing the quality of teaching; one of these methods is through students’ feedback. Methodology: This study used a quantitative approach, including the quantification of qualitative verbal data collected through an open question in the questionnaire. A sample of 180 courses was randomly chosen, 90 courses were evaluated manually and 90 were evaluated online. The number of students ranges from 7 to 60 students per course. In total 4678 students participated in the study. Contribution: The findings show that there is almost an identical pattern of feedback of manual and online course teaching evaluation. These findings encourage a continued use of this evaluation method. Findings: No significant differences were found between manual feedback and online feedback in the students’ evaluation of the lecturer/course. The percentage of respondents was significantly higher in the manual feedback than in the online feedback. The number of qualitative comments was significantly greater in the online feedback than in the manual feedback. Impact on Society: The findings of this study refute the claims with regard to the unreliability of an online teaching evaluation. These findings reflect the advantages of using online feedback, such as cost savings, granting more time to students in order to provide feedback, and reducing disturbance during lectures. Future Research: The gender aspect was not taken into account in the study. Therefore, we recommend conducting a follow-up study that will examine gender differences in directions of- difference between male and female lecturers, and differences between male and female students in teaching evaluation.