ICSEA 2021: the sixteenth international conference on software engineering advances

The Sixteenth International Conference on Software Engineering Advances (ICSEA 2021), held on October 3 - 7, 2021 in Barcelona, Spain, continued a series of events covering a broad spectrum of software-related topics. The conference covered fundamentals on designing, implementing, testing, validating and maintaining various kinds of software. The tracks treated the topics from theory to practice, in terms of methodologies, design, implementation, testing, use cases, tools, and lessons learnt. The conference topics covered classical and advanced methodologies, open source, agile software, as well as software deployment and software economics and education. The conference had the following tracks: Advances in fundamentals for software development Advanced mechanisms for software development Advanced design tools for developing software Software engineering for service computing (SOA and Cloud) Advanced facilities for accessing software Software performance Software security, privacy, safeness Advances in software testing Specialized software advanced applications Web Accessibility Open source software Agile and Lean approaches in software engineering Software deployment and maintenance Software engineering techniques, metrics, and formalisms Software economics, adoption, and education Business technology Improving productivity in research on software engineering Trends and achievements Similar to the previous edition, this event continued to be very competitive in its selection process and very well perceived by the international software engineering community. As such, it is attracting excellent contributions and active participation from all over the world. We were very pleased to receive a large amount of top quality contributions. We take here the opportunity to warmly thank all the members of the ICSEA 2021 technical program committee as well as the numerous reviewers. The creation of such a broad and high quality conference program would not have been possible without their involvement. We also kindly thank all the authors that dedicated much of their time and efforts to contribute to the ICSEA 2021. We truly believe that thanks to all these efforts, the final conference program consists of top quality contributions. This event could also not have been a reality without the support of many individuals, organizations and sponsors. We also gratefully thank the members of the ICSEA 2021 organizing committee for their help in handling the logistics and for their work that is making this professional meeting a success. We hope the ICSEA 2021 was a successful international forum for the exchange of ideas and results between academia and industry and to promote further progress in software engineering research

Chatbot assistant for diabetic patients

Dissertação de mestrado em Informatics EngineeringNowadays, with the existence of several chronic health conditions, Diabetes Mellitus (DM) being one of the main ones, there is a great burden that patients must have in order to be able to take care of themselves. Thus, in addition to seeking to resolve their needs by obtaining information from health professionals, they increasingly seek information and advices in forums, communities and groups. The use of dialogue systems has become essential in people’s lives. The development of conversational agents is still an unresolved research problem that poses many challenges in the Artificial Intelligence (AI) community. This work aims to build an AI chatbot that is based on the principles and techniques of AI directed to Natural Language Processing (NLP) and Deep Learning to help people newly diagnosed with DM in the self management of the disease. A literature search of DM education and information for people newly diagnosed with DM was con ducted. Additionally, the main topics in which patients ask for support were retrieved from a search of several online support groups of DM, as well as questionnaires with 8 patients and interviews with 3 health professionals. The application were developed through the back-end side in Python and the front-end side in React Native and its communication was made through WebSockets. Furthermore, an interaction and interface design are developed in this work using Human-Centered Design (HCD) methodology. For that purpose, iterative usability test sessions were conducted with 12 users using Think Aloud methods and the System Usability Scale (SUS). The chatbot developed is Information Retrieval (IR) type and answered questions asked by users in a human-like way. The result of the usability tests of the final version of the application was satisfactory (with a System Usability Scale (SUS) score of 88) and users found the application quite intuitive and robust. Further studies should concentrate on customizing the chatbot to each user by collecting information from prior interactions and verifying the impact of using this chatbot for newly diagnosed Portuguese users with DM.Atualmente, com a existência de várias condições crónicas de saúde sendo uma das principais a Diabetes Mellitus (DM), há um grande fardo que os pacientes devem ter para poderem cuidar de si mesmos. Assim, para além dos pacientes buscarem procurar resolver as suas necessidades por meio da obtenção de informações junto aos profissionais de saúde, cada vez mais buscam informações e conselhos em fóruns, comunidades e grupos. O uso de sistemas de diálogo tornou-se essencial na vida das pessoas. O desenvolvimento de agentes conversacionais é ainda um problema de pesquisa não resolvido que apresenta muitos desafios na comunidade da Inteligência Artificial (IA). Este trabalho visa construir um IA chatbot que é baseado nos princípios e técnicas de Inteligência Artificial (IA) direcionado a Processamento de Linguagem Natural (PLN) e Aprendizagem Profunda para ajudar pessoas recém-diagnosticadas com DM no autocuidado desta doença. Neste trabalho, foi acompanhada uma pesquisa bibliográfica sobre a educação e informações da DM para pessoas recém-diagnosticadas com DM. Além disso, foram abordados em vários grupos de apoio online relacionados com a DM os principais tópicos que os pacientes pedem apoio, a utilização de um questionário com 8 pacientes e entrevistas com 3 profissionais de saúde. A aplicação foi desenvolvida através do back-end em Python e front-end em React Native e a sua comunicação foi feita através de WebSockets. Foi também desenvolvido um design de interação e interface através da metodologia Human-Centered Design (HCD). Para tal, foram realizadas sessões de testes iterativos de usabilidade com 12 participantes seguindo os métodos Think Aloud e System Usability Scale (SUS). O chatbot desenvolvido é do tipo Information Retrieval (IR) e responde às perguntas feitas pelos utilizadores de forma humana. O resultado dos testes de usabilidade da versão final da aplicação foram satisfatórios (SUS de 88) e os utilizadores acharam a aplicação bastante intuitiva e robusta. Os estudos futuros devem concentrar-se na personalização do chatbot para cada utilizador, com a coleção de informações e de interações anteriores e na verificação do impacto da utilização deste chatbot para utilizadores portugueses recém-diagnosticados com DM

Natural Language Processing: Emerging Neural Approaches and Applications

This Special Issue highlights the most recent research being carried out in the NLP field to discuss relative open issues, with a particular focus on both emerging approaches for language learning, understanding, production, and grounding interactively or autonomously from data in cognitive and neural systems, as well as on their potential or real applications in different domains

Proceedings, MSVSCC 2017

Proceedings of the 11th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 20, 2017 at VMASC in Suffolk, Virginia. 211 pp