KEYNOTES

Mobile Health Technologies: Challenges and Opportunities

This keynote speech will focus on a new hot topic on e-health technologies considering recent advances on e-Health systems, including mobility environments and mobile technologies. Information and communication technologies have rapidly grown in the few last decades along with mobile Internet concept of anywhere and anytime connection. In this context, Mobile Health (m-Health) proposes to deliver healthcare services, overcoming geographical, temporal and even organizational barriers. Pervasive and m-Health services aim to respond several emerging problems in health services, including, the increasing number of chronic diseases related to lifestyle, high costs in existing national health services, the need to empower patients and families to self-care and manage their own healthcare, and the need to provide direct access to health services, regardless of time and place. This keynote speech will address the most relevant contributions for healthcare, e-health systems, and ambient assisted living, focusing on the mobile health revolution and evolution. The top and more used m-health applications in the mobile market and several ongoing works will be presented. Trends and insights on future research works are also considered.

Conferencista: Joel José Puga Coelho Rodrigues

Instituto Nacional de Telecomunicações (Inatel), Brasil. Instituto de Telecomunicações, Portugal. Universidade de Fortaleza (UNIFOR), Brasil.
Introdução a Mundos Procedurais

Modelagem procedural tem se popularizado nos últimos anos, está presente em jogos, simuladores e ambiente virtuais. Sua principal vantagem é a geração de cenas complexas e sistemáticas com pouca ou nenhuma interferência humana. A base para construir mundos procedurais é feita pela observação da natureza e as regras que a regem. Dessa forma, podemos gerar cenas 3D ou 2D baseado em metamodelagem ao contrário da forma tradicional que consiste em replicar objetos reais em modelos virtuais. Ou seja, nessa abordagem não se preocupa mais em modelar uma árvore e sim regras que expressam todas as árvores de uma dada espécie. Então, com esse poder em mãos podemos criar mundos procedurais infinitos que são consistentes e convincentes baseado em um conjunto de regras.

Conferencista: Wallas Henrique Sousa dos Santos

Mestre em Ciência da Computação pela Universidade Federal do Maranhão (UFMA). Atualmente é doutorando em Informática pela Pontifícia Universidade Católica do Rio de Janeiro, PUC-Rio, e estagiário de Research na IBM Brasil Rio.
Conexão entre makers e empresas para um ecossistema sustentável de inovação

Acreditamos na conexão entre makers e empresas porque é através dela que iremos criar um ecossistema sustentável de inovação pelo fazer. Acreditamos que empresas podem ser contaminadas pela atitude maker e transformar a forma com que trabalham e desenvolvem processos, projetos e produtos. Acreditamos na formação constante de uma comunidade composta pelos melhores makers e que tenham interesse na conexão com empresas a fim de criarmos um ecossistema de projetos inovadores e com propósito. Acreditamos também na linguagem maker que é a da materialização de ideias através de protótipos pois sabemos que eles são a forma mais valiosa de aprofundar, comunicar e validar uma ideia.

Conferencista: Luciana Hashiba

Membro do Conselho da WebFab, conexão do movimento maker com o mundo corporativo. MBA em Gestão de Negócios pela INSPER. Realizou mestrado (2008) e doutorado (2013) em Administração de Empresas pela Fundação Getúlio Vargas, na linha de Gestão de Operações e Competitividade, nos temas colaboração e desempenho, inovação e sustentabilidade, respectivamente. Professora extra-carreira em Gestão de Inovação, Redes de Inovação, Inovação Aberta, Maker Innovation - Innovation Management, Innovation Networks, Open Innovation. Participa do Conselho Deliberativo do CNPq, do Conselho Superior da Agência USP de Inovação e do Conselho da Escola Metodista de Educação Corporativa.
Data Science in practice: dealing with image across domains using machine learning

Research across science domains are increasingly reliant on image-based data coming from experiments, but domain scientists continue to struggle to uncover relevant, but hidden, information from digital images. To better exploit the scientific value of a broad array of high resolution, multidimensional datasets, a Berkeley lab multi-disciplinary project was designed around a coordinated research effort connecting (1) state-of-the-art data analysis methods with basis on pattern recognition and machine learning; (2) emerging algorithms for dealing with massive datasets; and (3) advances in evolving computer architectures to process the torrent of data. Aimed at delivering a new *modus operandi* for analyzing results of experiments conducted across imaging facilities, our team has provided tools to guide and optimize experiments, in collaboration with colleagues in Biology, Math, Physics and Arts. The result has been a set of data science models and new software infrastructure that provides tools that work for processing experimental data at scale and across domains.

Conferencista: Dani Ushizima, PhD

Dani Ushizima is a Staff Scientist at Berkeley Lab and a Data Scientist at the Berkeley Institute for Data Science (BIDS). During her PhD in Computational Physics at the University of Sao Paulo and Computer Vision at UC Santa Barbara, she designed cell analysis and classification software targeting leukemia cell screening. During the last decade at LBNL, her research in computer vision and pattern recognition has impacted a broad array of scientific investigation that depends on experimental data, such as materials design. In 2015, Dani received the U.S. Department of Energy Early Career Award to focus on image analysis and pattern recognition applied to diverse scientific domains obtained at DOE imaging facilities. She has also led the Image Analysis/Machine Vision team for the Center for Advanced Mathematics for Energy Related Applications (CAMERA) and acted as Chief Data Scientist for Cell Recognition for Inspection of the Cervix (CRIC) consortium.
Online Privacy Anonymity and Censorship Circumvention/Detection: Tor and OONI 

This talk will introduce the concepts of anonymity, privacy and censorship circumvention on the Internet (or other networks). The Tor network, a distributed anonymous network is a group of volunteer-operated servers that allows people to improve their privacy and security on the Internet. Tor's users employ this network by connecting through a series of virtual tunnels rather than making a direct connection, thus allowing both organizations and individuals to share information over public networks without compromising their privacy. Along the same line, Tor is an effective censorship circumvention tool, allowing its users to reach otherwise blocked destinations or content. Tor can also be used as a building block for software developers to create new communication tools with built-in privacy features (https://www.torproject.org). Additionally cases of internet blocking or censorship will be demonstrated with open network measurement data collected by the Open Observatory of Network Interference (OONI) a global observation network which aims is to collect high quality data using open methodologies, using Free and Open Source Software to share observations and data about the various types, methods, and amounts of network tampering in the world (https://ooni.torproject.org).

Conferencista: Vasilis Ververis

Humboldt University Belin, Germany. Universidade Estadual do Piauí (UESPI), Brazil. The Tor project. Open Observatory of Network Interference (OONI).

ENUCOMP

© 2015 Todos os Direitos Reservados. ENUCOMP 2017.
Desenvolvido por TDA Informática