Abstract
When learning from images, it is desirable to augment the dataset with plausible transformations of its images. Unfortunately, it is not always intuitive for the user how much shear or translation to apply. For this reason, training multiple models through hyperparameter search is required to find the best augmentation policies. But these methods are computationally expensive. Furthermore, since they generate static policies, they do not take advantage of smoothly introducing more aggressive augmentation transformations. In this work, we propose repeating each epoch twice with a small difference in data augmentation intensity, walking towards the best policy. This process doubles the number of epochs, but avoids having to train multiple models. The method is compared against random and Bayesian search for classification and segmentation tasks. The proposal improved twice over random search and was on par with Bayesian search for 4% of the training epochs.

Abstract
Evaluating scientists based on their scientific production is a controversial topic. Nevertheless, bibliometrics and algorithmic approaches can assist traditional peer review in numerous tasks, such as attributing research grants, deciding scientific committees, or choosing faculty promotions. Traditional bibliometrics rank individual entities (e.g., researchers, journals, faculties) without looking at the whole data (i.e., the whole network). Network algorithms, such as PageRank, have been used to measure node importance in a network, and have been applied to author ranking. However, traditional PageRank only uses network topology and ignores relevant features of scientific collaborations. Multiple extensions of PageRank have been proposed, more suited for author ranking. These methods enrich the network with information about the author’s productivity or the venue and year of the publication/citation. Most state-of-the-art (STOA) feature-enriched methods either ignore or do not combine effectively this information. Furthermore, STOA algorithms typically disregard that the full network is not known for most real-world cases.Here we describe OTARIOS, an author ranking method recently developed by us, which combines multiple publication/citation criteria (i.e., features) to evaluate authors. OTARIOS divides the original network into two subnetworks, insiders and outsiders, which is an adequate representation of citation networks with missing information. We evaluate OTARIOS on a set of five real networks, each with publications in distinct areas of Computer Science, and compare it against STOA methods. When matching OTARIOS’ produced ranking with a ground-truth ranking (comprised of best paper award nominations), we observe that OTARIOS is >30% more accurate than traditional PageRank (i.e., topology based method) and >20% more accurate than STOA (i.e., competing feature enriched methods). We obtain the best results when OTARIOS considers (i) the author’s publication volume and publication recency, (ii) how recently the author’s work is being cited by outsiders, and (iii) how recently the author’s work is being cited by insiders and how individual he is. Our results showcase (a) the importance of efficiently combining relevant features and (b) how to adequately perform author ranking in incomplete networks.

Abstract

Abstract
Purpose: The purpose of this paper is, first, to examine the design requirements of Islamic fashion in the new product-development process; second, to explore the different practices of new product-development activities from successful and unsuccessful new product lines; and third, to investigate the sequence of the new product-development practice in the fashion industry, specifically the Islamic fashion industry in Indonesia. Design/methodology/approach: Questionnaires were distributed and semi-structured interviews were conducted to collect information regarding the practice of the new product-development activities. The Mann–Whitney U test was performed based on the quality of the new product-development activities of 100 Islamic fashion firms, including five innovative companies that had won several awards in Indonesia. An analysis of the extent to which fashion firms were engaging in new product-development activities provided a more detailed picture of the sequence of those activities. Findings: Islamic norms were adapted during the early design and promotional phases of new product development in Islamic fashion. Various choices of design and colour in Islamic fashion were also perceived as a way of preaching to women to dress more accordingly to the Islamic norm. The new product-development activities that were conducted differently for successful vs unsuccessful new product lines were idea conceptualisation, market analysis, technical and engineering analysis, financial analysis and commercialisation. The commercialisation phase was given the least priority of all the activities. Nevertheless, it contributed to the very first communication to the customers about new product lines. Originality/value: This study makes an important contribution to the deeper and more detailed research on how Islamic fashion companies perceive Islamic values during new product developments and how they perform new product-development activities between successful and unsuccessful products.

Abstract
Current designs for all three extremely large telescopes show the overwhelming adoption of the pyramid wavefront sensor (P-WFS) as the WFS of choice for adaptive optics (AO) systems sensing on natural guide stars (NGS) or extended objects. The key advantages of the P-WFS over the Shack-Hartmann are known and are mainly provided by the improved sensitivity (fainter NGS) and reduced sensitivity to spatial aliasing. However, robustness and tolerances of the P-WFS for the ELTs are not currently well understood. In this paper, we present simulation results for the single-conjugate AO mode of HARMONI, a visible and near-infrared integral field spectrograph for the European Extremely Large Telescope. We first explore the wavefront sensing issues related to the telescope itself; namely the island effect (i.e. differential piston) and M1 segments phasing errors. We present mitigation strategies to the island effect and their performance. We then focus on some performance optimisation aspects of the AO design to explore the impact of the RTC latency and the optical gain issues, which will in particular affect the high-contrast mode of HARMONI. Finally, we investigate the influence of the quality of glass pyramid prism itself, and of optical aberrations on the final AO performance. By relaxing the tolerances on the fabrication of the prism, we are able to reduce hardware costs and simplify integration. We show the importance of calibration (i.e. updating the control matrix) to capture any displacement of the telescope pupil and rotation of the support structure for M4. We also show the importance of the number of pixels used for wavefront sensing to relax tolerances of the pyramid prism. Finally, we present a detailed optical design of the pyramid prism, central element of the P-WFS.

Abstract
In today’s world, technology is an indispensable part of our daily life. More and more products are produced to satisfy the needs of a growing population and the Internet is creating new services every day. However, to be able to keep up with the growing demand, new technologies needed to be invented to increase the pace of production and to lower costs. Automating tasks was the solution and for many years machines did repetitive tasks, replaced people and created new and better jobs to substitute the old ones. Nowadays automation is reaching incredible levels and it is not creating enough jobs to replace the old ones. Will unemployment increase in the upcoming years or will humanity be able to adapt to a different job market? Our study focuses on the types of unemployment caused by automation and on the possible solutions that society needs to implement. The research also points out how people from different social classes face the changing job market and how all can benefit from it. A new form of governance of society may be needed, in view of previous failed forms including fascism, communism, and, more recently, liberalism. In the future there will be fewer and fewer jobs that cannot be replaced by a robot. With this, the probability of mass unemployment is very high. An ideology promoting a Universal Basic Income could be a solution to combat the massive unemployment that automation may cause in the future, especially in medium-skilled jobs. © Springer Nature Switzerland AG 2019.