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Graph generation addresses the problem of generating new graphs that have a data distribution similar to real-world graphs. While previous diffusion-based graph generation methods have shown promising results, they often struggle to scale to large graphs. In this work, we propose ARROW-Diff (AutoRegressive RandOm Walk Diffusion), a novel random walk-based diffusion approach for efficient large-scale graph generation. Our method encompasses two components in an iterative process of random walk sampling and graph pruning. We demonstrate that ARROW-Diff can scale to large graphs efficiently, surpassing other baseline methods in terms of both generation time and multiple graph statistics, reflecting the high quality of the generated graphs.

Visual Question Answering (VQA) is an extremely stimulating and challenging research area where Computer Vision (CV) and Natural Language Processig (NLP) have recently met. In image captioning and video summarization, the semantic information is completely contained in still images or video dynamics, and it has only to be mined and expressed in a human-consistent way. Differently from this, in VQA semantic information in the same media must be compared with the semantics implied by a question expressed in natural language, doubling the artificial intelligence-related effort. Some recent surveys about VQA approaches have focused on methods underlying either the image-related processing or the verbal-related one, or on the way to consistently fuse the conveyed information. Possible applications are only suggested, and, in fact, most cited works rely on general-purpose datasets that are used to assess the building blocks of a VQA system. This paper rather considers the proposals that focus on real-world applications, possibly using as benchmarks suitable data bound to the application domain. The paper also reports about some recent challenges in VQA research.

Double parking that often negatively affects traffic operations and safety is not a new phenomenon on urban streets. This study proposes a novel data-driven integrated framework for estimating the actual frequency of double parking so that both microscopic and macroscopic models can be utilized to quantify area-wide impacts in the presence of double parking. The findings of the study can provide transportation agencies with useful insights on identifying locations that will experience the greatest benefits by removing problematic double parking. As a result, various parking enforcement and management strategies can be planned more effectively., Comment: 6 pages, 4 figures, INFORMS Transportation and Logistics Society, First Triennial Conference, Chicago (2017)

One of the main problems in controlling COVID-19 epidemic spread is the delay in confirming cases. Having information on changes in the epidemic evolution or outbreaks rise before lab-confirmation is crucial in decision making for Public Health policies. We present an algorithm to estimate on-stream the number of COVID-19 cases using the data from telephone calls to a COVID-line. By modeling the calls as background (proportional to population) plus signal (proportional to infected), we fit the calls in Province of Buenos Aires (Argentina) with coefficient of determination $R^2 > 0.85$. This result allows us to estimate the number of cases given the number of calls from a specific district, days before the lab results are available. We validate the algorithm with real data. We show how to use the algorithm to track on-stream the epidemic, and present the Early Outbreak Alarm to detect outbreaks in advance to lab results. One key point in the developed algorithm is a detailed track of the uncertainties in the estimations, since the alarm uses the significance of the observables as a main indicator to detect an anomaly. We present the details of the explicit example in Villa Azul (Quilmes) where this tool resulted crucial to control an outbreak on time. The presented tools have been designed in urgency with the available data at the time of the development, and therefore have their limitations which we describe and discuss. We consider possible improvements on the tools, many of which are currently under development., Comment: 16 pages, 8 figs. Includes details on the Villa Azul outbreak in Argentina

Background: One of the most challenging keys to understand COVID-19 evolution is to have a measure on those mild cases which are never tested because their few symptoms are soft and/or fade away soon. The problem is not only that they are difficult to identify and test, but also that it is believed that they may constitute the bulk of the cases and could be crucial in the pandemic equation. Methods: We present a novel algorithm to extract the number of these mild cases by correlating a COVID-line calls to reported cases in given districts. The key assumption is to realize that, being a highly contagious disease, the number of calls by mild cases should be proportional to the number of reported cases. Whereas a background of calls not related to infected people should be proportional to the district population. Results: We find that for Buenos Aires Province, in addition to the background, there are in signal 6.6 +/- 0.4 calls per each reported COVID-19 case. Using this we estimate in Buenos Aires Province 20 +/- 2 COVID-19 symptomatic cases for each one reported. Conclusions: A very simple algorithm that models the COVID-line calls as sum of signal plus background allows to estimate the crucial number of the rate of symptomatic to reported COVID-19 cases in a given district. The result from this method is an early and inexpensive estimate and should be contrasted to other methods such as serology and/or massive testing., Comment: 7 pages, 2 figures

Deaf people are more heavily affected by the digital divide than many would expect. Moreover, most accessibility guidelines addressing their needs just deal with captioning and audio-content transcription. However, this approach to the problem does not consider that deaf people have big troubles with vocal languages, even in their written form. At present, only a few organizations, like W3C, produced guidelines dealing with one of their most distinctive expressions: Sign Language (SL). SL is, in fact, the visual-gestural language used by many deaf people to communicate with each other. The present work aims at supporting e-learning user experience (e-LUX) for these specific users by enhancing the accessibility of content and container services. In particular, we propose preliminary solutions to tailor activities which can be more fruitful when performed in one's own "native" language, which for most deaf people, especially younger ones, is represented by national SL., Comment: anche ISBN 978-3-319-07436-9

One of the continuing challenges of Human Computer Interaction research is the full inclusion of people with special needs into the digital world. In particular, this crucial category includes people that experiences some kind of limitation in exploiting traditional information communication channels. One immediately thinks about blind people, and several researches aim at addressing their needs. On the contrary, limitations suffered by deaf people are often underestimated. This often the result of a kind of ignorance or misunderstanding of the real nature of their communication difficulties. This chapter aims at both increasing the awareness of deaf problems in the digital world, and at proposing the project of a comprehensive solution for their better inclusion. As for the former goal, we will provide a bird's-eye presentation of history and evolution of understanding of deafness issues, and of strategies to address them. As for the latter, we will present the design, implementation and evaluation of the first nucleus of a comprehensive digital framework to facilitate the access of deaf people into the digital world., Comment: SCOPUS - ISI?

We present SWift (SignWriting improved fast transcriber), an advanced editor for computer-aided writing and transcribing using SignWriting (SW). SW is devised to allow deaf people and linguists alike to exploit an easy-to-grasp written form of (any) sign language. Similarly, SWift has been developed for everyone who masters SW, and is not exclusively deaf-oriented. Using SWift, it is possible to compose and save any sign, using elementary components called glyphs. A guided procedure facilitates the composition process. SWift is aimed at helping to break down the "electronic" barriers that keep the deaf community away from Information and Communication Technology (ICT). The editor has been developed modularly and can be integrated everywhere the use of SW, as an alternative to written vocal language, may be advisable.

SWift (SignWriting improved fast transcriber) is an advanced editor for SignWriting (SW). At present, SW is a promising alternative to provide documents in an easy-to-grasp written form of (any) Sign Language, the gestural way of communication which is widely adopted by the deaf community. SWift was developed SW users, either deaf or not, to support collaboration and exchange of ideas. The application allows composing and saving desired signs using elementary components, called glyphs. The procedure that was devised guides and simplifies the editing process. SWift aims at breaking the "electronic" barriers that keep the deaf community away from ICT in general, and from e-learning in particular. The editor can be contained in a pluggable module; therefore, it can be integrated everywhere the use of SW is an advisable alternative to written "verbal" language, which often hinders information grasping by deaf users.

The SignWriting improved fast transcriber (SWift), presented in this paper, is an advanced editor for computer-aided writing and transcribing of any Sign Language (SL) using SignWriting (SW). The application is an editor which allows composing and saving desired signs using the SW elementary components, called "glyphs". These make up a sort of alphabet, which does not depend on the national Sign Language and which codes the basic components of any sign. The user is guided through a fully-automated procedure, making the composition process fast and intuitive. SWift pursues the goal of helping to break down the "electronic barriers" that keep deaf people away from the web, and at the same time to support linguistic research about Sign Languages features. For this reason it has been designed with a special attention to deaf user needs, and to general usability issues. The editor has been developed in a modular way, so it can be integrated everywhere the use of SW as an alternative to written "verbal" language may be advisable., Comment: CITATION INDEX