Brazil

Blockchain has been widely used to store decentralized and securetransactions involving cryptocurrency (for instance, Bitcoin andEthereum solutions). On the other hand, Smart city applicationsare concerned about how data and services can be safely storedand shared. In this regard, this research investigates the use ofBlockchain in the Smart Cities scenario. Based on that, a platformnamed Orthus was proposed to support Blockchain in Smart Cityinitiatives focused on scalability. This work presents a case studyabout how to use the proposed platform in the Natal Smart CityInitiative in Brazil to handle land registration. Moreover, it also com-pares this platform with other implementations that use Blockchainin different domains. Finally, this research confirms that the useof blockchain technology has much to contribute to Smart Citysolutions once it enables the creation of solutions in distributednetworks to meet the demand of the entire population.

WebMedia 2021

Orthus: A Blockchain Platform for Smart Cities

### Welcome to the Brazilian Symposium on Multimedia Systems and Web 
Promoted annually by the Brazilian Computer Society (SBC), the Brazilian Symposium on Multimedia Systems and Web (WebMedia) is the main event on the subject in Brazil and an excellent opportunity for scientific and technical exchanges between students, researchers and professionals in the areas of Multimedia, Hypermedia and Web. This year, we will be celebrating the 27th edition of WebMedia, to be held from **November 5th to 12th, 2021**, organized by the Federal University of Minas Gerais and Federal University of São João Del Rei. For the second time in its history, the event will be held online, with interaction between the participants being done through tools and web platforms.
 <iframe width="560" height="315" src="https://www.youtube.com/embed/2GvWKRUDtAY" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe> 
The Webmedia 2021 schedule will feature:
 
* Technical sessions for the presentation of scientific articles.
* National and international lectures
* Panel with Companies
* Workshops
* Short courses
* Project meetings open to the community
 

The topics of interest for paper submission are:
 
* Web and Social Networks
* Multimedia
* Digital TV, Ubiquitous and Mobile Computing
 

In addition to the main track, WebMedia 2021 will feature the Tools and Applications Workshop, the Scientific Initiation Papers Contest, the Theses and Dissertations Contest, the RNP CT-Video Workshop.
 
The organization of WebMedia 2021 is under the responsibility of the [Department of Computer Science at UFMG (DCC/UFMG)](http://dcc.ufmg.br/) and [Department of Computer Science at UFSJ (DCOMP/UFSJ)](https://dcomp.ufsj.edu.br/)
 
**#PartiuWebMedia2021 #WebMedia2021**

The Brazilian Symposium on Multimedia Systems and Web (WebMedia) is the main event on the subject in Brazil and an excellent opportunity for scientific and technical exchanges between students, researchers and professionals in the areas of Multimedia, Hypermedia and Web.

technical paper

The massive use of online social media networks is a reality nowa-days. Their increasing usage also raises growth in malicious activ-ities in social media, one of which is the use of automated users(bots) that disseminate false information and can insert bias in anal-yses done on gathered social media data. Based on the concept ofmedia literacy, this research presents a method to teach the humanuser to identify a pattern of a text produced by a bot, providinga tool (guide) to analyze social media text. Users who learned toidentify a bot user with the guide had an average of 90% accuracy inthe classification of new messages, against 57% of the participantswho had no contact with the guide. The produced guide received ausefulness rating between 4 and 5 by the participants (scale from 1to 5, with 5 being the highest value)

Pattern Identification of Bot Messages for Media Literacy

We propose tackling theHit Song Predictionproblem through amultimodal form with songs’ features fused together. Specifically,we describe songs from three feature modalities:music,artistandalbum. Initially, we identify collaboration profiles in a success-based musical network, unveiling how professional connectionscan significantly impact their success. Then, we use time seriesand the Granger Causality test for assessing whether there is acausal relationship between collaboration profiles and artists’ pop-ularity. Finally, we model theHit Song Predictionproblem as twodistinct tasks:classificationandplacement. The former is a classicalbinary classification model and directly applies our fusion strate-gies. The latter is a modeling approach that ranks a song relativeto a given chart, predicts hit songs, and provides comparative pop-ularity information of a set of songs. Furthermore, we emphasizecollaboration artists’ profiles as important features when describingtheir songs. Overall, our empirical studies confirm the effectivenessof our method that fuses heterogeneous data for both tasks.

Collaboration-Aware Hit Song Analysis and Prediction

The encoding of 360 videos presents many challenges. These spherical videos require a planar projection stage prior to encoding, and there are no studies on how projection interferes withthe encoder decisions. Also, due to the increased resolution, encoding 360 videos is computationally costlier than conventional videos. In this work, we perform an extensive evaluation of how the texture distortions caused by the projection interfere withthe encoder’s behavior and exploit these interferences to propose multiple fast algorithms to accelerate the encoding. Experimental results show that the proposed algorithms reduce encoding time significantly with minor coding efficiency penalties, while the evaluations expose novel insights into the encoder behavior. The reached results arepublished in important eventsand journals.

Exploring ERP Distortions to Reduce the Encoding Time of 360 Videos

In this work, we propose a framework that automatically extractssemantic topics from scientific publications related to research onCOVID-19. The framework has four main building blocks: (i) pre-processing, (ii) topic modeling, (iii) topic correlation with authorsand institutions, and (iv) summarization interface. The first blockcorresponds to the application of pre-processing strategies in textson the considered articles and the definition of their semantic repre-sentation. The topic modeling block aims to find semantic topics inthe publications used. The third block correlates these topics withthe articles themselves and the authors, institutions, and countriesrelated to each article. The summary interface provides an intuitiveview for all these analyses. Our evaluation shows that our frame-work is capable of automatically extracting relevant characteristicsfrom the articles, identifying the main themes addressed by them,as well as the correlation of researchers, institutions and countriesfor different topics of research on COVID-19.

Um framework orientado a artigos para análise semântica automática de pesquisas sobre COVID-19

The Brazilian National Cancer Institute (INCA) estimates for eachyear of the 2020/2022 triennium 8,460 new cases of cancer in chil-dren and adolescents in the 1-19 age group. As the second cause ofdeath in this age group in most regions of Brazil, childhood cancer isconsidered a serious public health problem. Fortunately, childhoodcancer is a disease with a high probability of cure if diagnosed earlyand treated in specialized centers. Thus, early diagnosis is an impor-tant public health strategy for treatment and is directly related topatient survival. This paper presents APPonco, a mobile applicationfor agile and safe access to information about childhood cancer forhealthcare professionals (doctors, nurses, nutritionists, etc.) andthe general public (patients, families and caregivers). APPonco wasa demand from a reference center in the treatment of childhoodcancer in Brazil. The paper details the requirements, architecture,and development process of the application. Since 2020, APPoncois available free for Android and iOS. The software is registered inthe Brazilian National Institute of Industrial Property (INPI).

APPonco - Um aplicativo móvel para acesso rápido e seguro à informação sobre o câncer infantojuvenil

The World Wide Web emerged more than three decades ago, andeven after all this time, accessibility is still challenging and a majorobstacle for it to be universal and inclusive. Despite W3C efforts tostandardize and publish best practices towards a more accessibleWeb, we still lack methodologies and tools to collect Web content,measure and assess accessibility at large scale. In this work, wedescribe the Observatório da Acessibilidade Brasileira, a tool thatsupports accessibility assessment, aggregates global indicators andprovides recommendations for improving accessibility on websites.The current version complies with eMAG accessibility standardsand extends and integrates existing free software. We validate anddemonstrate the effectiveness of the tool by assessing the acces-sibility of the brazilian government websites. The tool roadmapincludes adding new accessibility compliance analyses, improvingdata visualization and enriching website seed.

Observatório da Acessibilidade da Web Brasileira

The Internet of Things enables the data collection of the physicalworld in real time, raising opportunities for cost reduction andoptimization at large scale. However, creating an IoT solution thattransforms these data into information by enabling new visualiza-tions and interactions is not trivial. A remote digital electronicslab tool based on the MQTT protocol with energy monitoring, de-vice control and integration with web and mobile dashboards ispresented to support remote learning. The open source tool mightbe useful for teachers and technical staff of digital electronics labcourses by automating the remote lab devices management.

Dashboard IoT Remote Lab with MQTT Protocol

WhatsApp is the most popular instant messaging application inmany countries such as Brazil, India, and Indonesia, where manypeople use it as the main interface to the Web. Recently, What-sApp has been pointed as an important actor in the spreading ofmisinformation. However, due to its encrypted and peer-to-peernature, it is hard for people to explore the content people sharewithin WhatsApp at scale. In this work, we propose theMonitorde WhatsApp(http://www.whatsapp- monitor.dcc.uf mg.br/), aweb-based system that helps researchers and journalists explorethe nature of content shared on WhatsApp public groups fromthree different contexts: Brazil, India, and Indonesia. Our tool mon-itors multiple content categories such as images, videos, audio, andtextual messages posted on a set of WhatsApp groups and displaysthe most shared content ranked per day. Our tool has been usedfor monitoring content during the 2018 Brazilian Elections to the COVID-19 pandemics and was one of the major sources for estimat-ing the spread of misinformation and helping fact-checking effortson WhatsApp scenario.

Monitor de WhatsApp: Um Sistema para Checagem de Fatos no Combate a Desinformação

When the Covid-19 pandemic began, it was up to the Brazilian Ministry of Health (MS) to produce a nationwide health policy, organizing and planning strategies to mitigate health problems related to the SARS-CoV2 infection. In this context, and in cooperation with the Bridge Laboratory at UFSC, they developed a tool for the strategy "O Brasil Conta Comigo" (Brazil countson me) in order to assist health managers to cope with the deficit in the hiring of human resources. An application was developed in record time that allowed the voluntary registration of health professionals willing to act in health care to deal with Covid-19. Thus, it was possible to increase agility in the process of hiring health professionals in several regions of the country, as well as in the production of the largest self-declaratory database of health professionals in Brazil

Strategic Action "O Brasil Conta Comigo": Development of a tool for managing professionals willing to act in the fight against COVID-19

Arboviruses are Neglected Tropical Diseases (NTDs) that mainlyaffect developing countries and Brazil is one of them. Such diseaseshave a negative impact on quality of life of the patients. One of themain challenges in combating these diseases is the difficulty of anaccurate diagnosis among the concomitant arborival diseases duethe similarity of symptoms. This project proposes VALERIA, a low-cost platform based on machine learning (ML) models for assistingthe diagnose of arboviruses in the national scenario. VALERIA isproposed to improve the quality of life of patients, allowing the mostappropriate treatment after a diagnose and therefore presenting agreat potential of generating local public policies of social impact. Aprototype was already developed for diagnosis and is in validationphase by public health specialists.

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Pattern Identification of Bot Messages for Media Literacy

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Computação Afetiva na Web

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