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"Network publishing (Computer networks)"
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Emoji speak : communication and behaviours on social media
\"Providing an in-depth discussion of emoji use in a global context, this volume presents the use of emoji as a hugely important facet of computer-mediated communication, leading author Jieun Kiaer to coin the term 'emoji speak'. Exploring why and how emojis are born, and the different ways in which people use them, this book highlights the diversity of emoji speak. Presenting the results of empirical investigations with participants of British, Belgian, Chinese, French, Japanese, Jordanian, Korean, Singaporean, and Spanish backgrounds, it raises important questions around the complexity of emoji use. Though emojis have become ubiquitous, their interpretation can be more challenging. What is humorous in one region, for example, might be considered inappropriate or insulting in another. Whilst emoji use can speed up our communication, we might also question whether they convey our emotions sufficiently. Moreover, far from belonging to the youth, people of all ages now use emoji speak, prompting Kiaer to consider the future of our communication in an increasingly digital world.\" -- Provided by publisher.
Book
Digital humanities
A visionary report on the revitalization of the liberal arts tradition in the electronically inflected, design-driven, multimedia language of the twenty-first century. Digital_Humanities is a compact, game-changing report on the state of contemporary knowledge production. Answering the question “Whatis digital humanities?,” it provides an in-depth examination of an emerging field. This collaboratively authored and visually compelling volume explores methodologies and techniques unfamiliar to traditional modes of humanistic inquiry—including geospatial analysis, data mining, corpus linguistics, visualization, and simulation—to show their relevance for contemporary culture. Written by five leading practitioner-theorists whose varied backgrounds embody the intellectual and creative diversity of the field, Digital_Humanities is a vision statement for the future, an invitation to engage, and a critical tool for understanding the shape of new scholarship.
eBook
Congestion aware low power on chip protocols with network on chip with cloud security
This article is to analyze the bottleneck problems of NoC in many more applications like multi-processor communication, computer architectures, and network interface processors. This paper aims to research the advantages and disadvantages of low congestion protocols on highway environments like multiple master multiple slave interconnections. A long-term evolution and effective on-chip connectivity solution for secured, congestion aware and low power architecture is emerged for Network-on-Chip (NoC) for MCSoC. Applications running simultaneously on a different chip are often exchanged dynamically on the chip network. Of-course, in general on chip communication, resources mean that applications may interact with shared resources to influence each other's time characteristics.
Journal Article
Performance Evaluation of the Acquisition Cycle for an Original Modbus Extension IIoT Gateway Based on Sitara AM335x Processor
Abstract-Although Modbus is a widely used and easy-toimplement protocol, it has its limitations. Specifically, it does not include any specification about time variables, making it incomplete. To address this issue, the Modbus Extension was proposed. This extension introduces a time variable, but requires a Base Station Gateway (BSG) to do so. The interval time is determined by the structure of the acquisition cycle (AC), which will be implemented at the BSG level. In this paper, we present a solution for implementing the AC using the PRU (Programmable Real-Time Unit) core of the Sitara AM335x from Texas Instruments. With this approach, we achieved a speed of 12 Mb/s and a payload data channel usage percentage of 53.3 %. Additionally, we evaluated the performance of the acquisition cycle in the context of an IIoT gateway developed around the AM335x processor.
Journal Article
Deep convolutional models improve predictions of macaque V1 responses to natural images
Despite great efforts over several decades, our best models of primary visual cortex (V1) still predict spiking activity quite poorly when probed with natural stimuli, highlighting our limited understanding of the nonlinear computations in V1. Recently, two approaches based on deep learning have emerged for modeling these nonlinear computations: transfer learning from artificial neural networks trained on object recognition and data-driven convolutional neural network models trained end-to-end on large populations of neurons. Here, we test the ability of both approaches to predict spiking activity in response to natural images in V1 of awake monkeys. We found that the transfer learning approach performed similarly well to the data-driven approach and both outperformed classical linear-nonlinear and wavelet-based feature representations that build on existing theories of V1. Notably, transfer learning using a pre-trained feature space required substantially less experimental time to achieve the same performance. In conclusion, multi-layer convolutional neural networks (CNNs) set the new state of the art for predicting neural responses to natural images in primate V1 and deep features learned for object recognition are better explanations for V1 computation than all previous filter bank theories. This finding strengthens the necessity of V1 models that are multiple nonlinearities away from the image domain and it supports the idea of explaining early visual cortex based on high-level functional goals.
Journal Article
Biohackers
Biohackers explores fundamental changes occuring in the circulation and ownership of scientific information. Alessandro Delfanti argues that the combination of the ethos of 20th century science, the hacker movement and the free software movement is producing an open science culture which redefines the relationship between researchers, scientific institutions and commercial companies. Biohackers looks at the emergence of the citizen biology community ‘DIYbio’, the shift to open access by the American biologist Craig Venter and the rebellion of the Italian virologist Ilaria Capua against WHO data-sharing policies. Delfanti argues that these biologists and many others are involved in a transformation of both life sciences and information systems, using open access tools and claiming independence from both academic and corporate institutions.
eBook
A Principal Component Analysis of 39 Scientific Impact Measures
The impact of scientific publications has traditionally been expressed in terms of citation counts. However, scientific activity has moved online over the past decade. To better capture scientific impact in the digital era, a variety of new impact measures has been proposed on the basis of social network analysis and usage log data. Here we investigate how these new measures relate to each other, and how accurately and completely they express scientific impact.
We performed a principal component analysis of the rankings produced by 39 existing and proposed measures of scholarly impact that were calculated on the basis of both citation and usage log data.
Our results indicate that the notion of scientific impact is a multi-dimensional construct that can not be adequately measured by any single indicator, although some measures are more suitable than others. The commonly used citation Impact Factor is not positioned at the core of this construct, but at its periphery, and should thus be used with caution.
Journal Article
Emerging Standards for Enhanced Publications and Repository Technology
Emerging Standards for Enhanced Publications and Repository Technology serves as a technology watch on the rapidly evolving world of digital publication. It provides an up-to-date overview of technical issues, underlying the development of universally accessible publications, their elemental components and linked information. More specifically it deals with questions as how to bring together the communities of the Current Research Information Systems (CRIS) and the Common European Research Information Format (CERIF). Case studies like EGEE, DILIGENT and DRIVER are analyzed, as well as implementations in projects in Ireland, Denmark and The Netherlands. Interoperability is the keyword in this context and this book introduces to new standards and to concepts used in the design of envelopes and packages, overlays and feeds, embedding, publishing formats and Web services and serviceoriented architecture. It is a must-read for quick and comprehensive orientation.
eBook
Big Data, Little Data, No Data
\"Big Data\" is on the covers ofScience, Nature, theEconomist, andWiredmagazines, on the front pages of theWall Street Journaland theNew York Times.But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. In many cases, there are no data -- because relevant data don't exist, cannot be found, or are not available. Moreover, data sharing is difficult, incentives to do so are minimal, and data practices vary widely across disciplines.Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure -- an ecology of people, practices, technologies, institutions, material objects, and relationships. After laying out the premises of her investigation -- six \"provocations\" meant to inspire discussion about the uses of data in scholarship -- Borgman offers case studies of data practices in the sciences, the social sciences, and the humanities, and then considers the implications of her findings for scholarly practice and research policy. To manage and exploit data over the long term, Borgman argues, requires massive investment in knowledge infrastructures; at stake is the future of scholarship.
eBook
Cloud-based multiclass anomaly detection and categorization using ensemble learning
The world of the Internet and networking is exposed to many cyber-attacks and threats. Over the years, machine learning models have progressed to be integrated into many scenarios to detect anomalies accurately. This paper proposes a novel approach named cloud-based anomaly detection (CAD) to detect cloud-based anomalies. CAD consist of two key blocks: ensemble machine learning (EML) model for binary anomaly classification and convolutional neural network long short-term memory (CNN-LSTM) for multiclass anomaly categorization. CAD is evaluated on a complex UNSW dataset to analyze the performance of binary anomaly detection and categorization of multiclass anomalies. Furthermore, the comparison of CAD with other machine learning conventional models and state-of-the-art studies have been presented. Experimental analysis shows that CAD outperforms other studies by achieving the highest accuracy of 97.06% for binary anomaly detection and 99.91% for multiclass anomaly detection.
Journal Article