No Arabic abstract
Many memory institutions hold large collections of hand-held media, which can comprise hundreds of terabytes of data spread over many thousands of data-carriers. Many of these carriers are at risk of significant physical degradation over time, depending on their composition. Unfortunately, handling them manually is enormously time consuming and so a full and frequent evaluation of their condition is extremely expensive. It is, therefore, important to develop scalable processes for stabilizing them onto backed-up online storage where they can be subject to highquality digital preservation management. This goes hand in hand with the need to establish efficient, standardized ways of recording metadata and to deal with defective data-carriers. This paper discusses processing approaches, workflows, technical set-up, software solutions and touches on staffing needs for the stabilization process. We have experimented with different disk copying robots, defined our metadata, and addressed storage issues to scale stabilization to the vast quantities of digital objects on hand-held data-carriers that need to be preserved. Working closely with the content curators, we have been able to build a robust data migration workflow and have stabilized over 16 terabytes of data in a scalable and economical manner.
In this paper, we derive a new differential homography that can account for the scanline-varying camera poses in Rolling Shutter (RS) cameras, and demonstrate its application to carry out RS-aware image stitching and rectification at one stroke. Despite the high complexity of RS geometry, we focus in this paper on a special yet common input -- two consecutive frames from a video stream, wherein the inter-frame motion is restricted from being arbitrarily large. This allows us to adopt simpler differential motion model, leading to a straightforward and practical minimal solver. To deal with non-planar scene and camera parallax in stitching, we further propose an RS-aware spatially-varying homography field in the principle of As-Projective-As-Possible (APAP). We show superior performance over state-of-the-art methods both in RS image stitching and rectification, especially for images captured by hand-held shaking cameras.
Videos captured with hand-held cameras often suffer from a significant amount of blur, mainly caused by the inevitable natural tremor of the photographers hand. In this work, we present an algorithm that removes blur due to camera shake by combining information in the Fourier domain from nearby frames in a video. The dynamic nature of typical videos with the presence of multiple moving objects and occlusions makes this problem of camera shake removal extremely challenging, in particular when low complexity is needed. Given an input video frame, we first create a consistent registered version of temporally adjacent frames. Then, the set of consistently registered frames is block-wise fused in the Fourier domain with weights depending on the Fourier spectrum magnitude. The method is motivated from the physiological fact that camera shake blur has a random nature and therefore, nearby video frames are generally blurred differently. Experiments with numerous videos recorded in the wild, along with extensive comparisons, show that the proposed algorithm achieves state-of-the-art results while at the same time being much faster than its competitors.
Open data and open-source software may be part of the solution to sciences reproducibility crisis, but they are insufficient to guarantee reproducibility. Requiring minimal end-user expertise, encapsulator creates a time capsule with reproducible code in a self-contained computational environment. encapsulator provides end-users with a fully-featured desktop environment for reproducible research.
Social media has become integrated into the fabric of the scholarly communication system in fundamental ways: principally through scholarly use of social media platforms and the promotion of new indicators on the basis of interactions with these platforms. Research and scholarship in this area has accelerated since the coining and subsequent advocacy for altmetrics -- that is, research indicators based on social media activity. This review provides an extensive account of the state-of-the art in both scholarly use of social media and altmetrics. The review consists of two main parts: the first examines the use of social media in academia, examining the various functions these platforms have in the scholarly communication process and the factors that affect this use. The second part reviews empirical studies of altmetrics, discussing the various interpretations of altmetrics, data collection and methodological limitations, and differences according to platform. The review ends with a critical discussion of the implications of this transformation in the scholarly communication system.
Research on innovation and sustainability is prolific but fragmented. This study integrates the research on innovation in management and business and STEM fields for sustainability in a unified framework for the case of developing countries (i.e., the Global South). It presents and discusses the output, impact, and structure of such research based on a sample of 14,000+ articles and conference proceedings extracted from the bibliographic database Scopus. The findings reveal research output inflections after global announcements such as UN-Earth Summits. The study also reveals the indisputable leadership of China in overall output and research agenda-setting. Nonetheless, countries such as India, Mexico, and Nigeria are either more efficient or impactful. GS research published in highly reputable journals is still scarce but increasing modestly. Central topic clusters (e.g., knowledge management) remain peripheral to the global Sustainable Development Goals (SDGs) research landscape. Finally, academic-corporate collaboration is in its infancy and limited to particular economic sectors: energy, pharmaceuticals, and high-tech.