It's written in the cloud: The hype and promise of cloud computing

Purpose of paper: This viewpoint discusses the emerging IT platform of Cloud Computing and discusses where and how this has developed in terms of the collision between internet and enterprise computing paradigms – and hence why cloud computing will be driven not by computing architectures but more fundamental ICT consumption behaviours. Design/methodology/approach: The approach has been based upon the discussion and recent developments of Software as a Service (SaaS) and associated ICT computing metaphors and is largely based upon the contemporary discussion at the moment of the impact of social, open source and configurable technology services. Findings: It is suggested that whilst cloud computing and SaaS are indeed innovations within ICT, the real innovation will come when such platforms allow new industries, sectors, ways of doing business, connecting with and engaging with people to emerge. Thus looking beyond the technology itself. Research limitations/applications: Author viewpoint only, not research based. Practical applications: Brings together some of the recent discussions within the popular as well as business and computing press on social networking, open source and utility computing. Social implications: Suggests that cloud computing can potentially transform and change the way in which IS and IT are accessed, consumed, configured and used in daily life. Originality / value of paper: Author viewpoint on a contemporary subject

Toward a collective intelligence recommender system for education

The development of Information and Communication Technology (ICT), have revolutionized the world and have moved us into the information age, however the access and handling of this large amount of information is causing valuable time losses. Teachers in Higher Education especially use the Internet as a tool to consult materials and content for the development of the subjects. The internet has very broad services, and sometimes it is difficult for users to find the contents in an easy and fast way. This problem is increasing at the time, causing that students spend a lot of time in search information rather than in synthesis, analysis and construction of new knowledge. In this context, several questions have emerged: Is it possible to design learning activities that allow us to value the information search and to encourage collective participation?. What are the conditions that an ICT tool that supports a process of information search has to have to optimize the student's time and learning? This article presents the use and application of a Recommender System (RS) designed on paradigms of Collective Intelligence (CI). The RS designed encourages the collective learning and the authentic participation of the students. The research combines the literature study with the analysis of the ICT tools that have emerged in the field of the CI and RS. Also, Design-Based Research (DBR) was used to compile and summarize collective intelligence approaches and filtering techniques reported in the literature in Higher Education as well as to incrementally improving the tool. Several are the benefits that have been evidenced as a result of the exploratory study carried out. Among them the following stand out: • It improves student motivation, as it helps you discover new content of interest in an easy way. • It saves time in the search and classification of teaching material of interest. • It fosters specialized reading, inspires competence as a means of learning. • It gives the teacher the ability to generate reports of trends and behaviors of their students, real-time assessment of the quality of learning material. The authors consider that the use of ICT tools that combine the paradigms of the CI and RS presented in this work, are a tool that improves the construction of student knowledge and motivates their collective development in cyberspace, in addition, the model of Filltering Contents used supports the design of models and strategies of collective intelligence in Higher Education.Postprint (author's final draft

Applying the sciences of the natural and the artificial for an effective design

Includes bibliographical references.This study examines the current use of quantitative and qualitative research methods for Information Systems research. These research methods may have a tendency to limit the evolution of the Information Systems field; it is thus important to consider a new framework for gathering Information Systems research. The new paradigm proposed is a combination of the science of the natural and the science of artificial. The science of the natural focuses on the characteristics and properties objects have in the real world and how they behave and interact with each other. The science of the artificial is related closely to the science of engineering and design and focuses on how objects ought to be in order to attain goals and to function. By combining the sciences of the natural and the artificial, a researcher can more fully understand the system problem and discuss alternative solutions. This project utilizes both research paradigms for developing an effective Website for students. A survey is used to represent the quantitative side of the natural sciences and action research, representing the science of the artificial, is used to analyze what students' value in a Website.B.S. (Bachelor of Science

Bag of Tricks for Long-Tailed Multi-Label Classification on Chest X-Rays

Clinical classification of chest radiography is particularly challenging for standard machine learning algorithms due to its inherent long-tailed and multi-label nature. However, few attempts take into account the coupled challenges posed by both the class imbalance and label co-occurrence, which hinders their value to boost the diagnosis on chest X-rays (CXRs) in the real-world scenarios. Besides, with the prevalence of pretraining techniques, how to incorporate these new paradigms into the current framework lacks of the systematical study. This technical report presents a brief description of our solution in the ICCV CVAMD 2023 CXR-LT Competition. We empirically explored the effectiveness for CXR diagnosis with the integration of several advanced designs about data augmentation, feature extractor, classifier design, loss function reweighting, exogenous data replenishment, etc. In addition, we improve the performance through simple test-time data augmentation and ensemble. Our framework finally achieves 0.349 mAP on the competition test set, ranking in the top five.Comment: Accepted for the ICCV 2023 Workshop on Computer Vision for Automated Medical Diagnosis (CVAMD

Value function estimation using conditional diffusion models for control

A fairly reliable trend in deep reinforcement learning is that the performance scales with the number of parameters, provided a complimentary scaling in amount of training data. As the appetite for large models increases, it is imperative to address, sooner than later, the potential problem of running out of high-quality demonstrations. In this case, instead of collecting only new data via costly human demonstrations or risking a simulation-to-real transfer with uncertain effects, it would be beneficial to leverage vast amounts of readily-available low-quality data. Since classical control algorithms such as behavior cloning or temporal difference learning cannot be used on reward-free or action-free data out-of-the-box, this solution warrants novel training paradigms for continuous control. We propose a simple algorithm called Diffused Value Function (DVF), which learns a joint multi-step model of the environment-robot interaction dynamics using a diffusion model. This model can be efficiently learned from state sequences (i.e., without access to reward functions nor actions), and subsequently used to estimate the value of each action out-of-the-box. We show how DVF can be used to efficiently capture the state visitation measure for multiple controllers, and show promising qualitative and quantitative results on challenging robotics benchmarks

Motivations and challenges for stream processing in edge computing

The 2030 Agenda for Sustainable Development of the United Nations General Assembly defines 17 development goals to be met for a sustainable future. Goals such as Industry, Innovation and Infrastructure and Sustainable Cities and Communities depend on digital systems. As a matter of fact, billions of Euros are invested into digital transformation within the European Union, and many researchers are actively working to push state-of-the-art boundaries for techniques/tools able to extract value and insights from the large amounts of raw data sensed in digital systems. Edge computing aims at supporting such data-to-value transformation. In digital systems that traditionally rely on central data gathering, edge computing proposes to push the analysis towards the devices and data sources, thus leveraging the large cumulative computational power found in modern distributed systems. Some of the ideas promoted in edge computing are not new, though. Continuous and distributed data analysis paradigms such as stream processing have argued about the need for smart distributed analysis for basically 20 years. Starting from this observation, this talk covers a set of standing challenges for smart, distributed, and continuous stream processing in edge computing, with real-world examples and use-cases from smart grids and vehicular networks

Manufacturing-as-a-Service (MaaS): state-of-the-art of up and running solutions and a framework to assess the level of development of a Cloud Manufacturing platform

During the last decades manufacturers tried to find new sources of flexibility because of the uncertainty of the market. Both practitioners and academics started to study new paradigms aiming to make companies more flexible up and downstream of their value chains leveraging on suppliers and customers. Cloud Manufacturing (CM) is certainly one of the most interesting concepts because it comes from the success of Cloud Computing and belongs to the complex fourth industrial revolution (i.e. Industry 4.0 paradigm). It has been introduced in 2010, defined as the “manufacturing version of cloud computing” where manufacturing resources are available to users on-demand, with outstanding flexibility. CM pursues the idea of creating Manufacturing as-a-Service (MaaS) leveraging on the benefits of the platform economy. In spite of its interest, after ten years debate there is not consensus on the essential characteristics of this paradigm because of the very limited number of real applications (prototypes excluded). In this paper we explore 6 cases of up and running platforms which resemble some of the characteristics of CM, define them as “CM Early adopters” and inductively propose a framework to assess the level of development of a CM platform. This study contributes to theory as it shows that CM is already arising in some businesses, the approach to the paradigm can vary significantly from one case to another, and different levels of development can be assessed. From a managerial point of view, this paper helps to understand the CM paradigm as it shows concrete examples of real companies pursuing the MaaS idea. In conclusion, MaaS seems ready to land on some industrial sectors and this can be either a new opportunity for competitiveness or a serious threat

Smart transformer: a revolutionary paradigm toward sustainable power grids

Electrical power grids are evolving technologically from different perspectives, specifically, aiming to guarantee the sustainability of the power grid itself, the introduction of new and emerging technologies for the production and storage of energy, advanced communication systems, as well as higher levels of power quality for all sectors of activity (from production to consumption). Particularly, with special focus over the last two decades, power grids are undergoing a depth transformation, moving from a centralized and unidirectional architecture to a decentralized and bidirectional architecture, mainly due to the massive incorporation of new electrical engineering technologies. This change also presents an important aspect for the entire power grid: the possibility of energy storage and management according to the real-time needs. In this context, within the scope of this paper, the sustainability of power grids is considered, focusing on the new paradigms offered by the smart transformer and hybrid AC/DC power grids, including all the added value that can be established in terms of power management. Encompassed in a smart transformer context, the contextualization of the conceivable arrangements of solid-state transformers, and the various configurations of smart hybrid transformers, are evaluated from the point of view of offering advantages of improved efficiency and power quality. In addition to a theoretical introductory context, the paper presents computational validations and a comparison regarding the various configurations that can be obtained

Bacteria Hunt: Evaluating multi-paradigm BCI interaction

The multimodal, multi-paradigm brain-computer interfacing (BCI) game Bacteria Hunt was used to evaluate two aspects of BCI interaction in a gaming context. One goal was to examine the effect of feedback on the ability of the user to manipulate his mental state of relaxation. This was done by having one condition in which the subject played the game with real feedback, and another with sham feedback. The feedback did not seem to affect the game experience (such as sense of control and tension) or the objective indicators of relaxation, alpha activity and heart rate. The results are discussed with regard to clinical neurofeedback studies. The second goal was to look into possible interactions between the two BCI paradigms used in the game: steady-state visually-evoked potentials (SSVEP) as an indicator of concentration, and alpha activity as a measure of relaxation. SSVEP stimulation activates the cortex and can thus block the alpha rhythm. Despite this effect, subjects were able to keep their alpha power up, in compliance with the instructed relaxation task. In addition to the main goals, a new SSVEP detection algorithm was developed and evaluated