Report on the Second International Workshop on the Evaluation on Collaborative Information Seeking and Retrieval (ECol'2017 @ CHIIR)

The 2nd workshop on the evaluation of collaborative information retrieval and seeking (ECol) was held in conjunction with the ACM SIGIR Conference on Human Information Interaction & Retrieval (CHIIR) in Oslo, Norway. The workshop focused on discussing the challenges and difficulties of researching and studying collaborative information retrieval and seeking (CIS/CIR). After an introductory and scene setting overview of developments in CIR/CIS, participants were challenged with devising a range of possible CIR/CIS tasks that could be used for evaluation purposes. Through the brainstorming and discussions, valuable insights regarding the evaluation of CIR/CIS tasks become apparent ? for particular tasks efficiency and/or effectiveness is most important, however for the majority of tasks the success and quality of outcomes along with knowledge sharing and sense-making were most important ? of which these latter attributes are much more difficult to measure and evaluate. Thus the major challenge for CIR/CIS research is to develop methods, measures and methodologies to evaluate these high order attributes

Beautiful Disease: The Story of Angelina Jolie’s Mastectomy in the American Media

In 2013 Angelina Jolie revealed in a New York Times editorial that she underwent a preventive double mastectomy earlier that year. This qualitative study examines the social meaning of that Times piece. Using fantasy theme analysis, I unearth the story the American media told about Jolie, her surgery and her editorial. I find that newspapers and magazines dramatized Jolie’s gender traits and portrayed her as an ultra-feminine hero protected from the physical and social threats of breast cancer

LoGANv2: Conditional Style-Based Logo Generation with Generative Adversarial Networks

Domains such as logo synthesis, in which the data has a high degree of multi-modality, still pose a challenge for generative adversarial networks (GANs). Recent research shows that progressive training (ProGAN) and mapping network extensions (StyleGAN) enable both increased training stability for higher dimensional problems and better feature separation within the embedded latent space. However, these architectures leave limited control over shaping the output of the network, which is an undesirable trait in the case of logo synthesis. This paper explores a conditional extension to the StyleGAN architecture with the aim of firstly, improving on the low resolution results of previous research and, secondly, increasing the controllability of the output through the use of synthetic class-conditions. Furthermore, methods of extracting such class conditions are explored with a focus on the human interpretability, where the challenge lies in the fact that, by nature, visual logo characteristics are hard to define. The introduced conditional style-based generator architecture is trained on the extracted class-conditions in two experiments and studied relative to the performance of an unconditional model. Results show that, whilst the unconditional model more closely matches the training distribution, high quality conditions enabled the embedding of finer details onto the latent space, leading to more diverse output.Comment: accepted for poster presentation at ICMLA 2019, data+code available: https://github.com/cedricoeldorf/ConditionalStyleGA

Larger Genomes Linked to Slower Development and Loss of Late-Developing Traits

Genome size varies widely among organisms and is known to affect vertebrate development, morphology, and physiology. In amphibians, genome size is hypothesized to contribute to loss of late-forming structures, although this hypothesis has mainly been discussed in salamanders. Here we estimated genome size for 22 anuran species and combined this novel dataset with existing genome size data for an additional 234 anuran species to determine whether larger genome size is associated with loss of a late-forming anuran sensory structure, the tympanic middle ear. We established that genome size is negatively correlated with development rate across 90 anuran species and found that genome size evolution is correlated with evolutionary loss of the middle ear bone (columella) among 241 species (224 eared and 17 earless). We further tested whether the development of the tympanic middle ear could be constrained by large cell sizes and small body sizes during key stages of tympanic middle ear development (metamorphosis). Together, our evidence suggests that larger genomes, slower development rate, and smaller body sizes at metamorphosis may contribute to the loss of the anuran tympanic middle ear. We conclude that increases in anuran genome size, although less drastic than in salamanders, may affect development of late-forming traits

T¡f'ereth de Emanuel Nunes: el esplendor emblemático del espacio.

Sin resume

Logo generation through artificial intelligence

In recent years, much has been said about the possibility of artificial intelligence becoming an ally of the designer, as well as the possibility that in the future it will replace the designer in brand design. This study purposes to analyze and understand what impacts the advances in technology and more precisely artificial intelligence can contribute to the development of brand design. It was made a literature review (in AI and design), analysis of previous studies and interviews, in order to create a conceptual proposal for a logo creation model through artificial intelligence. It was concluded that although it appears that artificial intelligence could be close to creating logos, in reality is still far from that goal. Despite this, the study of artificial intelligence in design can even help designers, with new tools that will allow them to work better, especially in terms of formalizing ideas and research and solidifying the discipline theoretically.Nos últimos anos, muito se tem falado sobre a possibilidade da inteligência artificial se tornar uma aliada do designer, bem como sobre a possibilidade de, no futuro, substituir o designer na identidade visual das marcas. Este estudo tem como objetivo analisar e compreender quais os impactos que os avanços da tecnologia e mais precisamente da inteligência artificial podem contribuir para o desenvolvimento do design de marcas. Foi realizada uma revisão de literatura (em AI e design), analise de estudos feitos anteriormente e entrevistas, para assim criar uma proposta conceptual de um modelo de criação de logos através de inteligência artificial. Concluiu-se que apesar de parecer que a inteligência artificial poderá estar perto de criar logos, na realidade ainda se encontra longe de tal objetivo. Apesar disso, o estudo da inteligência artificial em design pode mesmo ajudar os designers, com ferramentas novas que permitirão este trabalhar melhor, especialmente na parte de formalização de ideias e pesquisa e a solidificarem a disciplina teoricamente

Erarbeitung von Kriterien zur weltweiten Beschaffung von myAVR-Komponenten

nicht vorhande

Does One Size Fit All? Why Our Genes Show the Need for Tailor-Made Solutions

Since the human genome was first sequenced in 2003, millions of consumers and medical professionals have swarmed the field of medical genetics, seeking to peer into the crystal ball and see what their own, or their patients’, futures may hold. Also rushing in are direct-to-consumer genetic testing companies like 23andMe and AncestryDNA, which can circumvent medical privacy laws by offering genetic testing without a medical provider. Medical privacy regulations, such as the Health Information Portability and Accountability Act of 1996 (HIPAA), the Genetic Information Discrimination Act of 2008 (GINA), and those promulgated by the Federal Trade Commission, do not regulate these companies adequately for a litany of reasons. These loopholes and shortcomings in regulation leave American consumers substantially less protected, less medically informed, and in some instances can jeopardize national security. This Note proposes that Congress should enact legislation overhauling the current regulatory regime in at least three ways: (1) the “covered entity” approach should be abandoned and replaced with a data-driven model; (2) the Safe Harbor provision of HIPAA should explicitly exclude genomic data; and (3) consumers should be given a “right to be forgotten” and compel companies to delete their data. These reforms would significantly strengthen consumers’ genetic privacy and give them an escape hatch to safeguard the core of their identity

A Deep Learning Pipeline for the Synthesis of Graphic Novels

peer reviewedIn this paper, we present what is to the best of our knowledge, the first deep learning pipeline to produce a synthetic graphic novel. Our method can synthesize from scratch engaging sequences of graphic novel pages, focusing on the Manga genre. To achieve this, we extract images and text from around 670 thousand Manga pages, which we use separately in order to train state-of-the-art generative architectures, such as GPT-2 for text generation and StyleGAN2 for image synthesis. Using these as sources of synthetic content, we develop a set of algorithmic aesthetic rules in order to bring together complete and continuous Manga pages