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

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. Affaire Squarcini-LVMH : que reproche la justice à l'ancien patron du renseignement intérieur ?  franceinfo
2. Comment LVMH a échappé à un procès malgré l’espionnage de François Ruffin  Le HuffPost
3. Bernard Squarcini devant la justice pour « trafic d’influence »  Le Monde
4. Affaire Squarcini : le « Squale », comme un poisson à LVMH  Sud Ouest
5. Espionnage sur le tournage de "Merci patron" de François Ruffin, le député réclame un euro symbolique  France 3 Régions

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

Online journal dedicated to nursing informatics

(Belga) Les archéologues ont fait plusieurs découvertes archéologiques datant de la période romaine et du Moyen Âge à Roulers, communique la province de Flandre occidentale ce lundi. Les excavations se sont déroulées dans le cadre de travaux liées à l'aménagement d'un bassin tampon. Celui-ci sera construit au bout de la Wagenweg dans le quartier De Ruiter à Roulers dans le courant du printemps.

C'est pourquoi une étude archéologique est en cours. Elle a mis au jour des vestiges de l'époque romaine et du Moyen Âge. Un certain nombre de traces de fondations, un fossé, un four à charbon de bois et un tombeau contenant des restes brûlés avec des jarres en céramique ont été retrouvés. Ils prouvent l'existence d'activités et d'habitations qui remontent à l'époque romaine. Plusieurs fossés et fosses peuvent aussi être associés au Moyen Âge, entre le Xe et le XIIe siècle. "Ensemble, ils nous donnent un meilleur aperçu de l'histoire des habitations et de l'implantation paysagère des activités qui ont eu lieu sur le hameau de De Ruiter dans le passé. Dans une perspective plus large, ils contribuent à une meilleure compréhension de l'évolution de la vallée du Mandel vers ce qu'elle est devenue aujourd'hui", affirment les archéologues. Mercredi prochain, les personnes intéressées auront l'occasion de voir les fouilles de plus près et de participer à une visite guidée. L'archéologue Willem Hantson, du service du patrimoine archéologique et architectural RADAR, emmènera les visiteurs pour une visite de 40 minutes. Toutes les informations sont disponibles sur www.midwest.be/opgraving-roeselare-collievijverbeek. La province de Flandre occidentale prévoit de commencer au printemps la construction de la zone d'inondation contrôlée (ZIC) et du bassin de rétention d'eau pour l'agriculture. (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%.

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.

Along with amazing advancements in the field of digital payments, this article seeks to provide a summary of research undertaken over the last four decades and to suggest areas in need of additional study. This study employs a two-pronged technique for analysing its data. The first is concerned with performance analysis, and the second with science mapping. The study uses the apps VOS viewer and R-studio to do bibliometric data analysis. From 1982 until May 2022, the most trustworthy database, Scopus, is used to compile a database of 923 publications The findings of this study identify the scope of current research interest, which is explored with critical contributions from a variety of authors, journals, countries, affiliations, keyword analysis, citation analysis, co-citation analysis, and bibliometric coupling, as well as a potential research direction for further investigation in this emerging field.

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

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

This 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.

Aim/Purpose: This paper describes the context, development, implementation, and the potential transferability of an integrated online research environment that allows its users to conduct all aspects of research online. Background: While the content of most traditional courses can be delivered online and learning outcomes can be achieved by adopting equivalents to face-to-face pedagogic approaches, certain courses, such as those that require a substantial research component, present significant constraints for delivery online. To overcome these limitations, Australia’s largest university developed and implemented a Research Portal. Methodology: The development team conducted a functional requirements analysis, identified the components that would be necessary to meet user needs, and reviewed existing solutions. The Monash University Psychology Research Portal was designed, tested, developed, tested for user experience, implemented, and reviewed. The Research Portal is structured according to the usual research sequence and provides users with access to supporting information and integrated capacities including research supervision, participant acquisition, and data collection, analysis, and storage. Contribution: This integrated online research environment is equivalent to and, in some ways, superior to an on campus/non-online research capacity. Findings: The usage of the Research Portal has grown rapidly and has satisfied the requirements and met the research needs of students of an online course that includes a research project, providing a common, ubiquitously accessible, and integrated online research environment. Recommendations for Practitioners: Further refinement, personalization, and expanded implementation and dissemination of the Research Portal components are required. The formation of networks and working partnerships to operate, maintain, and promote Research Portal initiatives is recommended to reduce operational costs, increase access, and create an impact. Impact on Society: The Research Portal is an efficient resource that provides easy access to a standard interface at any time and from anywhere and can potentially be used by other online research courses, as well as by online and non-online researchers.

Aim/Purpose: This research aims to describe layering of career-like experiences over existing curriculum to improve perceived educational value. Background: Feedback from students and regional businesses showed a clear need to increase student’s exposure to career-like software development projects. The initial goal was to develop an instructor-optional project that could be used in a single mid-level programming course; however, the pilot quickly morphed into a multi-year study examining the feasibility of agile projects in a variety of settings. Methodology: Over the course of four years, an agile project was honed through repeated Design Based Research (DBR) cycles of design, implementation, testing, communication, and reflective analysis. As is common with DBR, this study did not follow single methodology design; instead, analysis of data coupled with review of literature led to exploration and testing of a variety of methodologies. The review phase of each cycle included examination of best practices and methodologies as determined by analysis of oral and written comments, weekly journals, instructor feedback, and surveys. As a result of participant feedback, the original project was expanded to a second project, which was tested in another Software Engineering (SE) course. The project included review and testing of many academic and professional methodologies, such as Student Ownership of Learning, Flipped Classroom, active learning, waterfall, agile, Scrum, and Kanban. The study was homogenous and quasi-experimental as the population consisted solely of software engineering majors taking required courses; as based on validity of homogenous studies, class sizes were small, ranging from 8 to 20 students. Close interactions between respondents and the instructor provided interview-like settings and immersive data capture in a natural environment. Further, the iterative development practices of DBR cycles, along with the inclusion of participants as active and valued stakeholders, was seen to align well with software development practitioner practices broadly known as agile. Contribution: This study is among the first to examine layering a career-like software development project on top of a course through alteration of traditional delivery, agile development, and without supplanting existing material. Findings: In response to industry recommendations for additional career-like experiences, a standalone agile capstone-like project was designed that could be layered over an existing course. Pilot data reflected positive perceptions of the project, although students did not have enough time to develop a working prototype in addition to completing existing course materials. Participant feedback led to simultaneous development of a second, similar project. DBR examination of both projects resulted in a simplified design and the ability to develop a working prototype, if and only if the instructor was willing to make adjustments to delivery. After four years, a solution was developed that is both stable and flexible. The solution met the original charge in that it required course delivery, not course material, to be adjusted. It is critical to note that when a working prototype is desired, a portion of the lecture should be flipped allowing more time for guided instruction through project-focused active learning and study group requirements. The results support agile for standalone software development projects, as long as passive delivery methods are correspondingly reduced. Recommendations for Practitioners: Based on the findings, implementation of a career-like software development project can be well received as long as active learning components are also developed. Multiple cycles of DBR are recommended if future researchers wish to customize instructional delivery and develop complex software development projects. Programming instructors are recommended to explore hybrid delivery to support development of agile career-like experiences. Small class sizes allowed the researchers to maintain an interview-like setting throughout the study and future studies with larger classes are recommended to include additional subject matter experts such as graduate students as interaction with a subject matter expert was highly valued by students. Recommendation for Researchers: Researchers are recommended to further examine career-like software development experiences that combine active learning with agile methods; more studies following agile and active learning are needed to address the challenges faced when complex software development is taught in academic settings. Further testing of standalone agile project development has now occurred in medium sized in person classes, online classes, independent studies, and creative works research settings; however, further research is needed. Future research should also examine the implementation of agile projects in larger class sizes. Increasing class size should be coupled with additional subject matter experts such as graduate students. Impact on Society: This study addresses professional recommendations for development of agile career-like experiences at the undergraduate level. This study provides empirical evidence of programming projects that can be layered over existing curriculum, with no additional cost to the students. Initial feedback from local businesses and graduates, regarding agile projects with active learning, has been positive. The area business that refused to hire our underprepared SE graduates has now hired several. Future Research: Future research should explore layering agile projects over a broader range of software development courses. Feedback from hiring professionals and former students has been positive. It is also recommended that DBR be used to develop career-like experiences for online programming courses.

Aim/Purpose: The purpose of this article is to provide an overview and analysis of the emerging research landscape surrounding the integration of ChatGPT into education. The main problem appears to be that this is a new, rapidly developing research area for which there is no comprehensive synthesis of the current literature. The aim of the article is to fill this gap by conducting a timely bibliometric study to map publication trends, influential works, themes, and opportunities, thus representing the growth and structure of ChatGPT educational research. Background: This article addresses the issue of the lack of a comprehensive synthesis of the new research on ChatGPT in education by conducting a bibliometric analysis. Specifically, the authors use statistical and network analysis techniques to examine the patterns of publication, citation, and keywords and map the growth, contributions, themes, structure, and opportunities in this evolving field. The bibliometric approach provides a comprehensive, evidence-based overview of the current state of the literature to uncover trends and gaps and help researchers improve their understanding of appropriate and effective applications of ChatGPT in educational contexts. Methodology: The authors used bibliometric analysis as the primary method to summarize the new research on ChatGPT in education. We searched the database of the Web of Science Core Collection to find 51 relevant documents from 2023 that included ChatGPT in the title and were classified as ‘educational research.’ The sample consisted of these 51 documents, including articles, early access articles, editorials, reviews, and letters. Statistical techniques examined publication, citation, and keyword patterns. Network analysis visualized citation and co-occurrence networks to reveal intellectual structure. The multifaceted bibliometric approach allowed a comprehensive study of the sample from a productive, conceptual, and intellectual perspective. Contribution: This article conducts comprehensive bibliometric analysis of this emerging research area and synthesizes publication, citation, and keyword data to map the growth and structure of the literature. The results reveal important trends, such as the rapid growth of publications since the release of ChatGPT, initial authorship patterns, the focus on higher education applications, and distinct research clusters around pedagogical, ethical, and assessment issues. Visualizing citation networks identifies seminal studies while mapping co-occurrence clarifies conceptual relationships between topics. The comparative analysis highlights the differences between document types, topics, and time periods. Knowledge mapping highlights gaps in the literature, such as lack of focus on K-12 contexts, and highlights opportunities for further research. Findings: Key findings from this bibliometric analysis of the emerging research land-scape surrounding ChatGPT integration in education include the following: • Since ChatGPT was released in late 2022, the number of releases has increased significantly, indicating rapid growth in this emerging space. • The most cited authors initially came primarily from Anthropic, but over time, the citations spread throughout the research community. • The topics focused primarily on higher education applications, with a clear focus on pedagogical strategies, ethical risks, and implications for assessment. • Citation networks visualized seminal studies, while the co-occurrence of keywords clarified conceptual connections. • Gaps such as applications in the K-12 context were uncovered, and opportunities for further research were highlighted. • The literature is rapidly evolving and requires ongoing monitoring of the development of this field. In general, the analysis presents the productivity, contributors, themes, struc-ture, and opportunities in this emerging area around the integration of ChatGPT in education based on current scientific evidence. The key findings focus on the growing early interest, gaps and developments that can provide insight for researchers and educators. Recommendations for Practitioners: Practitioners should carefully integrate ChatGPT into education based on new evidence, carefully assess contextual applicability, and proactively develop guidelines for ethical and equitable implementation. Ongoing advice, impact monitoring, and research partnerships are crucial to informing best practices. Educators must be vigilant for risks such as privacy, student well-being, and competence impairment while staying abreast of advances in knowledge to dynamically adapt integration strategies. The introduction should empower diverse learners through measured, integrative approaches based on continuous contextual analysis and ethical principles. Recommendation for Researchers: This article recommends that researchers conduct more studies in under-researched contexts, use multiple methods to capture nuanced impacts, increase focus on responsible integration strategies, develop tailored assessments, conduct interdisciplinary collaborations, monitor long-term adoption, mix with interactive explain and publish open access technologies, help guide adoption pathways through actionable studies, and synthesize the exponentially growing literature through updated systematic reviews. Impact on Society: The rapid publication growth and prevailing optimism suggest that the integration of ChatGPT into education will accelerate, increasing the need for rigorous research that guides ethical, responsible innovations that avoid risks and improve outcomes in all educational contexts. The findings have broader implications for guiding adoption trajectories through ongoing evidence synthesis and expanded investigations in under-researched areas to address knowledge gaps. Ultimately, continued monitoring and updated guidance are critical to ensure that ChatGPT’s educational penetration progresses carefully by maximizing benefits and minimizing harms in rapidly evolving AI-powered learning ecosystems. Future Research: Based on the basic mapping provided by this paper, recommended research directions include longitudinal impact studies, research tailored to under-researched contexts such as K-12, qualitative research to capture stakeholder perspectives, development and testing of AI-calibrated assessments as well as explorations that combine conversational and interactive learning technologies, updated systematic reviews, and co-designed implementation research that explain pedagogical strategies that ethically unlock learning potential while mitigating risks in diverse educational environments. Such multilayered tracking can provide critical insights to guide context-specific, responsible ChatGPT integration and monitor impact within rapidly evolving AI-powered education ecosystems.

Aim/Purpose: This study explores the subject structure, social networks, research trends, and issues in the domain that have the potential to derive an overview of the development of virtual reality-based learning media in vocational education. Background: Notwithstanding the increasingly growing interest in the application of virtual reality in vocational learning, the existing research literature may still leave out some issues necessary for a comprehensive understanding. This study will point out such areas that need more exploration and a more comprehensive synthesis of the literature by conducting a bibliometric analysis. It will be interesting to keep track of the changing concepts and methodologies applied in the development of VR-based learning media in vocational education research. Methodology: This review was carried out using bibliometric methodology, which can highlight patterns of publication and research activity in this hitherto little studied area. The results of the study have the potential to lead to evidence-based priority in VR development, which will tailor work for vocational contexts and set the compass against the growing worldwide interest in this area. The study provides a descriptive analysis of publications, citations, and keyword data for 100 documents published between the years 2013 and 2022 from the Scopus database, which is conducted to illustrate the trends in the field. Contribution: This study also counts as a contribution to understanding the research hotspots of VR-based learning media in vocational education. Through bibliometric analysis, this study thoroughly summarized the relevant research and literature laying a knowledge foundation for researchers and policy makers. Additionally, this analysis identified knowledge gaps, recent trends, and directions for future research. Findings: The bibliometric analysis revealed the following key findings: 1. A growing publication trajectory, with output increasing from 7 articles in 2013 to 25 articles in 2022. 2. The United States led the contributions, followed by China, and Germany. 3. The most prominent authors are affiliated with American medical institutions. 4. Lecture proceedings include familiar sources that reflect this nascent domain. 5. Citation analysis identified highly influential work and researchers. 6. Keyword analysis exposed technology-oriented topics rather than learning-oriented terms. These findings present an emerging landscape with opportunities to address geographic and pedagogical research gaps. Recommendations for Practitioners: This study will be beneficial for designers and developers of VR-based learning programs because it aligns with the most discussed and influential VR technologies within the literature. Such an alignment of an approach with relevant research trends and focus can indeed be very useful for the effective application and use of VR-based learning media for quality improvements in vocational students' learning. Recommendation for Researchers: In fact, in this bibliometric review of VR integration within vocational classrooms, a future call for focused research is presented, especially on teaching methods, course design, and learning impact. This is a framework that seeks to establish its full potential with effective and integrated use of VR in the various vocational curricula and settings of learners. Impact on Society: From the findings of the bibliometric analysis, it is evident that virtual reality technologies (VR) have significantly led to transformation within educational media. There is no denying that the growing interest and investment in the integration of virtual reality into vocational education has been well manifested in the substantive increase in publications in the last decade. This shows what the innovation driving factor is in the United States. At the same time the rapid contributions from China signal worldwide recognition of the potential of VR to improve technical skills training. This study points the way for more research to bridge critical gaps, specifically how VR tools can be used in vocational high school classrooms. Furthermore, research should be aligned to meet specific needs of vocational learners and even promote international cross-border partnerships, pointing out the potential of virtual reality to be a universally beneficial tool in vocational education. The examination of highly cited articles provides evidence of the potential of VR to be an impactful pedagogical tool in vocational education. The findings suggest that researchers need to move forward looking at the trajectory of VR in vocational education and how promising it is in defining the future for innovative and effective learning methodologies. Future Research: This study is an exceptionally valuable contribution, a true landmark in the field of dynamic development, and one that denotes very meaningful implications for the future course of research in the dynamically developing field of bibliometric analysis of VR-based learning media for vocational education. The increase in the number of publications emanates from growing interests in the application of virtual reality (VR) technologies in vocational education. The high concentration of authorship from the USA, along with the ever increasing contributions from China, spotlights the increasing worldwide recognition of the impact of immersive technologies in the enhancement of training in technical skills. These are emerging trends that call for research to exemplify the diverse views and global teamwork opportunities presented by VR technologies. The study also highlights critical areas that need focused attention in future research endeavors. The fact that the embedding of VR tools into classrooms in vocational high schools has been poorly researched points to the major gap in pedagogical research within authentic educational settings. Therefore, further investigations should evaluate teaching methods in VR, lesson designs, and the impacts of VR in specific vocational trades. This supports the need for learner-centered frameworks that are tailor-made to the needs of vocational learners. This calls for more direct and focused investigations into identified research gaps noting a growing dominance in the field of health-related research with the most cited articles in this field, to integrate virtual reality into additional vocational education contexts. In this way, the gaps present an opportunity for researchers to make significant contributions to the development of interventions responsive to the unique needs of vocational learners; this will contribute to strengthening the evidence base for the worldwide implementation of VR within vocational education systems. This was recommended as the intention of such a bibliometric analysis: supporting the potential of VR as a pedagogical tool in vocational contexts and providing grounding for a strong and focused future research agenda within this burgeoning area of educational technology.

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.

A well-documented architecture can greatly improve comprehension and maintainability. However, shorter release cycles and quick delivery patterns results in negligence of architecture. In such situations, the architecture can be recovered from its current implementation based on considering dependency relations. In literature, structural and semantic dependencies are commonly used software features, and directory information along with co-change/change history information are among rarely utilised software features. But, they are found to help improve architecture recovery. Therefore, we consider investigating various features that may further improve the accuracy of existing architecture recovery techniques and evaluate their feasibility by considering them in different pairs. We compared five state-of-the-art methods under different feature subsets. We identified that two of them commonly outperform others but surprisingly with low accuracy in some evaluations. Further, we propose a new subset of features that reflects more accurate user perceptions and hence, results in improving the accuracy of architecture recovery techniques.

Evaluation of research artefacts (such as models, frameworks and methodologies) is essential to determine their quality and demonstrate worth. However, in the information quality (IQ) research domain there is no existing standard set of criteria available for researchers to use to evaluate their IQ artefacts. This paper therefore describes our experience of selecting and synthesising a set of evaluation criteria used in three related research areas of information systems (IS), software products (SP) and conceptual models (CM), and analysing their relevance to different types of IQ research artefact. We selected and used a subset of these criteria in an actual evaluation of an IQ artefact to test whether they provide any benefit over a standard evaluation. The results show that at least a subset of the criteria from the other domains of IS, SP and CM are relevant for IQ artefact evaluations, and the resulting set of criteria, most importantly, enabled a more rigorous and systematic selection of what to evaluate.

To assess a country's economic outlook and achieve higher economic growth, econometric models and prediction techniques are significant tools. Policymakers are always concerned with the correct future estimates of economic variables to take the right economic decisions, design better policies and effectively implement them. Therefore, there is a need to improve the predictive accuracy of the existing models and to use more sophisticated and superior algorithms for accurate forecasting. Deep learning models like recurrent neural networks are considered superior for forecasting as they provide better predictive results as compared to many of the econometric models. Against this backdrop, this paper presents the feasibility of using different deep-learning neural network architectures for trade forecasting. It predicts export trade using different recurrent neural architectures such as 'vanilla recurrent neural network (VRNN)', 'bi-directional long short-term memory network (Bi-LSTM)', 'bi-directional gated recurrent unit (Bi-GRU)' and a hybrid 'bi-directional LSTM and GRU neural network'. The performances of these models are evaluated and compared using different performance metrics such as Mean Square Error (MSE), Mean Absolute Error (MAE) Root Mean Squared Error (RMSE), Root Mean Squared Logarithmic Error (RMSLE) and coefficient of determination <em>R</em>-squared (<em>R</em>²). The results validated the effective export prediction for India.

In the perspective of institutional theory, business education is an institutional field, in which two major institutional forces are accreditations and rankings. In this context, French business schools (BS) have adopted an isomorphic response by starting to engage in research and publishing in academic journals. Studies have discussed their research as a new institutional trajectory. However, what remains unknown is how they differ from each other in such research dynamics. To bring new insights to the discussion, this quantitative study examines, over the period of 2008-2018, the evolution of research of French BS by systematically comparing the 'best' schools with other schools in all analyses. The results indicate a strong isomorphism in terms of publication quantity and productivity, scale of research collaboration and the internationalisation of research. However, these schools are heterogeneous in terms research quality and scale of international research collaboration, reflecting the diversity in their research strategy.

Under the current framework of police online teaching, in order to effectively solve the lack of high-quality resources of the traditional platform, backward sharing technology, poor performance of the digital platform and the privacy problems faced by each subject in sharing. This paper designs and implements the online teaching platform based on blockchain and interplanetary file system (IPFS). Based on the architecture of a 'decentralised' police online teaching platform, the platform uses blockchain to store hashes of encrypted private information and user-set access control policies, while the real private information is stored in IPFS after encryption. In the realisation of privacy information security storage at the same time to ensure the effective control of the user's own information. In order to achieve flexible rights management, the system classifies private information. In addition, the difficulties of police online teaching and training reform in the era of big data are solved one by one from the aspects of communication mode, storage facilities, incentive mechanism and confidentiality system, which effectively improves the stability and security of police online teaching.

The research goal is to solve the problems of low accuracy and long time existing in traditional teaching reform performance evaluation methods, a performance evaluation method of teaching reform based on hierarchical multi-task deep learning is proposed. Under the principle of constructing the evaluation index system, the evaluation indicator system should be constructed. The weight of the evaluation index is calculated through the analytic hierarchy process, and the calculation result of the evaluation weight is taken as the model input sample. A hierarchical multi-task deep learning model for teaching reform performance evaluation is built, and the final teaching reform performance score is obtained. Through relevant experiments, it is proved that compared with the experimental comparison method, this method has the advantages of high evaluation accuracy and short time, and can be further applied in relevant fields.

In order to overcome the problems of poor evaluation accuracy and long evaluation time in traditional customer relationship evaluation methods, this study proposes a new customer relationship evaluation method for e-commerce platform based on decision tree algorithm. Firstly, analyse the connotation and characteristics of customer relationship; secondly, the importance of customer relationship in e-commerce platform is determined by using decision tree algorithm by selecting and dividing attributes according to the information gain results. Finally, the decision tree algorithm is used to design the classifier, the weighted sampling method is used to obtain the training samples of the base classifier, and the multi-period excess income method is used to construct the customer relationship evaluation function to achieve customer relationship evaluation. The experimental results show that the accuracy of the customer relationship evaluation results of this method is 99.8%, and the evaluation time is only 51 minutes.

In order to improve the classification accuracy and online allocation accuracy of teaching resources and shorten the allocation time, this paper proposes a new online allocation method of college ideological and political curriculum teaching resources based on differential search algorithm. Firstly, the feedback parameter model of teaching resources cleaning is constructed to complete the cleaning of teaching resources. Secondly, according to the results of anti-interference consideration, the linear feature extraction of ideological and political curriculum teaching resources is carried out. Finally, the online allocation objective function of teaching resources for ideological and political courses is constructed, and the differential search algorithm is used to optimise the objective function to complete the online allocation of resources. The experimental results show that this method can accurately classify the teaching resources of ideological and political courses, and can shorten the allocation time, with the highest allocation accuracy of 97%.

Because of the problems of low mining precision and slow mining speed in traditional enterprise marketing investment data mining methods, a fast mining method for enterprise marketing investment databased on improved association rules is proposed. First, the enterprise marketing investment data is collected through the crawler framework, and then the collected data is cleaned. Then, the cleaned data features are extracted, and the correlation degree between features is calculated. Finally, according to the calculation results, all data items are used as constraints to reduce the number of frequent itemsets. A pruning strategy is designed in advance. Combined with the constraints, the Apriori algorithm of association rules is improved, and the improved algorithm is used to calculate all frequent itemsets, Obtain fast mining results of enterprise marketing investment data. The experimental results show that the proposed method is fast and accurate in data mining of enterprise marketing investment.

In order to solve the problems of large generalisation error, low recall rate and low retrieval accuracy of customer evaluation information in traditional trust evaluation methods, an evaluation method of customer trust in e-commerce market based on entropy weight analytic hierarchy process was designed. Firstly, build an evaluation index system of customer trust in e-commerce market. Secondly, the customer trust matrix is established, and the index weight is calculated by using the analytic hierarchy process and entropy weight method. Finally, five-scale Likert method is used to analyse the indicator factors and establish a comment set, and the trust evaluation value is obtained by combining the indicator membership. The experiment shows that the maximum generalisation error of this method is only 0.029, the recall rate is 97.5%, and the retrieval accuracy of customer evaluation information is closer to 1.

As academia in general, and research funders in particular, place ever greater importance on data as an output of research, so the value of good research data management practices becomes ever more apparent. In response to this, the Innovative Design and Manufacturing Research Centre (IdMRC) at the University of Bath, UK, with funding from the JISC, ran a project to draw up a data management planning regime. In carrying out this task, the ERIM (Engineering Research Information Management) Project devised a visual method of mapping out the data records produced in the course of research, along with the associations between them. This method, called Research Activity Information Development (RAID) Modelling, is based on the Unified Modelling Language (UML) for portability. It is offered to the wider research community as an intuitive way for researchers both to keep track of their own data and to communicate this understanding to others who may wish to validate the findings or re-use the data.

Open data is becoming increasingly important in research. While individual researchers are slowlybecoming aware of the value, funding agencies are taking the lead by requiring data be made available, and also by requiring data management plans to ensure the data is available in a useable form. Some journals also require that data be made available. However, in most cases, “available upon request” is considered sufficient. We describe a number of historical examples of data use and discovery, then describe two current test cases at the University of New Mexico. The lessons learned suggest that an instituional data services program needs to not only facilitate fulfilling the mandates of granting agencies but to realize the true value of open data. Librarians and institutional archives should actively collaborate with their researchers. We should also work to find ways to make open data enhance a researchers career. In the long run, better quality data and metadata will result if researchers are engaged and willing participants in the dissemination of their data.

The paper describes the investigations and outcomes of the JISC-funded Kindura project, which is piloting the use of hybrid cloud infrastructure to provide repository-focused services to researchers. The hybrid cloud services integrate external commercial cloud services with internal IT infrastructure, which has been adapted to provide cloud-like interfaces. The system provides services to manage and process research outputs, primarily focusing on research data. These services include both repository services, based on use of the Fedora Commons repository, as well as common services such as preservation operations that are provided by cloud compute services. Kindura is piloting the use of the DuraCloud2, open source software developed by DuraSpace, to provide a common interface to interact with cloud storage and compute providers. A storage broker integrates with DuraCloud to optimise the usage of available resources, taking into account such factors as cost, reliability, security and performance. The development is focused on the requirements of target groups of researchers.

In the realm of digital data, vendor-supplied cloud systems will still leave the user with responsibility for curation of digital data. Some of the very tasks users thought they were delegating to the cloud vendor may be a requirement for users after all. For example, cloud vendors most often require that users maintain archival copies. Beyond the better known vendor cloud model, we examine curation in two other models: inhouse clouds, and what we call "open" clouds—which are neither inhouse nor vendor. In open clouds, users come aboard as participants or partners—for example, by invitation. In open cloud systems users can develop their own software and data management, control access, and purchase their own hardware while running securely in the cloud environment. To do so will still require working within the rules of the cloud system, but in some open cloud systems those restrictions and limitations can be walked around easily with surprisingly little loss of freedom. It is in this context that REDDnet (Research and Education Data Depot network) is presented as the place where the Texas Tech University (TTU)) Libraries have been conducting research on long-term digital archival storage. The REDDnet network by year's end will be at 1.2 petabytes (PB) with an additional 1.4 PB for a related project (Compact Muon Soleniod Heavy Ion [CMS-HI]); additionally there are over 200 TB of tape storage. These numbers exclude any disk space which TTU will be purchasing during the year. National Science Foundation (NSF) funding covering REDDnet and CMS-HI was in excess of $850,000 with $850,000 earmarked toward REDDnet. In the terminology we used above, REDDnet is an open cloud system that invited TTU Libraries to participate. This means that we run software which fits the REDDnet structure. We are beginning to complete the final design of our system, and starting to move into the first stages of construction. And we have made a decision to move forward and purchase one-half petabyte of disk storage in the initial phase. The concerns, deliberations and testing are presented here along with our initial approach.