Closing the Gap Between Designers and Developers in a Low-Code Ecosystem

Digital systems play an important role in the strategy of companies nowadays as they are crucial to achieve their business goals as well as gain a competitive advantage. This is particularly true for systems designed for the end-users market. Not only has the number of such systems been growing steadily but the requirements and expectations of users regarding usability and performance have also increased. Developing software systems is a complex process that comprises several stages and involves multiple professionals responsible for different tasks. Two stages of the process are the design and implementation of User Interfaces. UX and UI designers produce artifacts such as mockups and prototypes using design tools describing what should be the systems behavior, interactivity and look and feel. Next, Front-end and Back-end developers implement the system according to the specifications defined by designers. Designers and developers use different methodologies, languages, and tools. This introduces a communication gap between both groups, and hence collaboration between them is not always smooth. This ends up causing less efficient processes, rework and loss of information. Developers sometimes overlook the importance of User Experience and Front-end De velopment. The corresponding project stages suffer when collaboration between groups is not optimal. Problems are particularly striking during the transition from design arti facts to front-end code. The procedures for doing this are often manual, very error-prone, and time-consuming for developers that end-up completely re-doing the designers’ work in the target web technology. The aim of this dissertation is to improve the efficiency of collaboration between de signers and front-end developers in the OutSystems ecosystem. This was carried out by developing a tool that transforms UX/UI design artefacts into low-code web-technology using model transformation and meta-modelling techniques. The approach has been evaluated in practice by a team of professional designers and front-end developers. Re sults show savings between 20 and 75% according to the project complexity in the effort invested by development teams in the above mentioned process.Os sistemas digitais têm um papel muito importante hoje em dia na estratégia das empresas, uma vez que as ajudam a atingir os seus objetivos de negócios assim como a ganhar vantagem competitiva face às demais. Isto é particularmente verdade para os sistemas destinados ao mercado dos utilizadores finais. Não só aumentou significativamente o número de tais sistemas como aumentaram também os requisitos e expectativas dos seus utilizadores. O desenvolvimento de sistemas de software é um processo complexo que envolve um número alargado de profissionais com diferentes perfis. Duas das fases são o design de interfaces e a sua implementação. Os UI e UX designers produzem um conjunto de ficheiros utilizando ferramentas de design descrevendo o comportamento, interação e aparência do sistema. Os Front-end e Back-end developers implementam as funcionalidades do sistema com base nas especificações dos designers. Designers e developers trabalham utilizando diferentes metodologias, linguagens e ferramentas. Isto introduz uma lacuna entre os grupos e dificulta a sua colaboração, originando processos menos eficientes, trabalho refeito e perda de informação. Os engenheiros de software por vezes negligenciam disciplinas tais como a Experi ência do Utilizador e o Front-end. Estas fases dos projetos são prejudicadas quando a colaboração entre os grupos não é ótima. Os problemas são particularmente evidentes durante a transição entre design e Front-end. Os procedimentos são manuais, altamente propensos a erros e demorados para os developers, que acabam por refazer o trabalho dos designers na tecnologia web desejada. O objetivo desta dissertação é melhorar a eficiência da colaboração entre designers e front-end developers no ecossistema OutSystems. Isto foi levado a cabo desenvolvendo uma ferramenta capaz de transformar artefactos de UX/UI em low-code utilizando transformações de modelos e técnicas de meta-modeling. A abordagem foi avaliada em prática por uma equipa profissional de designers e front-end developers. Os resultados obtidos mostram poupanças entre os 20 e os 75% de acordo com a complexidade do projeto no esforço investido pelas equipas de desenvolvimento no processo mencionado acima

Internet of Vehicles and Real-Time Optimization Algorithms: Concepts for Vehicle Networking in Smart Cities

Achieving sustainable freight transport and citizens’ mobility operations in modern cities are becoming critical issues for many governments. By analyzing big data streams generated through IoT devices, city planners now have the possibility to optimize traffic and mobility patterns. IoT combined with innovative transport concepts as well as emerging mobility modes (e.g., ridesharing and carsharing) constitute a new paradigm in sustainable and optimized traffic operations in smart cities. Still, these are highly dynamic scenarios, which are also subject to a high uncertainty degree. Hence, factors such as real-time optimization and re-optimization of routes, stochastic travel times, and evolving customers’ requirements and traffic status also have to be considered. This paper discusses the main challenges associated with Internet of Vehicles (IoV) and vehicle networking scenarios, identifies the underlying optimization problems that need to be solved in real time, and proposes an approach to combine the use of IoV with parallelization approaches. To this aim, agile optimization and distributed machine learning are envisaged as the best candidate algorithms to develop efficient transport and mobility systems

Design and implementation of a platform for predicting pharmacological properties of molecules

Tese de mestrado, Bioinformática e Biologia Computacional, Universidade de Lisboa, Faculdade de Ciências, 2019O processo de descoberta e desenvolvimento de novos medicamentos prolonga-se por vários anos e implica o gasto de imensos recursos monetários. Como tal, vários métodos in silico são aplicados com o intuito de dimiuir os custos e tornar o processo mais eficiente. Estes métodos incluem triagem virtual, um processo pelo qual vastas coleções de compostos são examinadas para encontrar potencial terapêutico. QSAR (Quantitative Structure Activity Relationship) é uma das tecnologias utilizada em triagem virtual e em optimização de potencial farmacológico, em que a informação estrutural de ligandos conhecidos do alvo terapêutico é utilizada para prever a actividade biológica de um novo composto para com o alvo. Vários investigadores desenvolvem modelos de aprendizagem automática de QSAR para múltiplos alvos terapêuticos. Mas o seu uso está dependente do acesso aos mesmos e da facilidade em ter os modelos funcionais, o que pode ser complexo quando existem várias dependências ou quando o ambiente de desenvolvimento difere bastante do ambiente em que é usado. A aplicação ao qual este documento se refere foi desenvolvida para lidar com esta questão. Esta é uma plataforma centralizada onde investigadores podem aceder a vários modelos de QSAR, podendo testar os seus datasets para uma multitude de alvos terapêuticos. A aplicação permite usar identificadores moleculares como SMILES e InChI, e gere a sua integração em descritores moleculares para usar como input nos modelos. A plataforma pode ser acedida através de uma aplicação web com interface gráfica desenvolvida com o pacote Shiny para R e directamente através de uma REST API desenvolvida com o pacote flask-restful para Python. Toda a aplicação está modularizada através de teconologia de “contentores”, especificamente o Docker. O objectivo desta plataforma é divulgar o acesso aos modelos criados pela comunidade, condensando-os num só local e removendo a necessidade do utilizador de instalar ou parametrizar qualquer tipo de software. Fomentando assim o desenvolvimento de conhecimento e facilitando o processo de investigação.The drug discovery and design process is expensive, time-consuming and resource-intensive. Various in silico methods are used to make the process more efficient and productive. Methods such as Virtual Screening often take advantage of QSAR machine learning models to more easily pinpoint the most promising drug candidates, from large pools of compounds. QSAR, which means Quantitative Structure Activity Relationship, is a ligand-based method where structural information of known ligands of a specific target is used to predict the biological activity of another molecule against that target. They are also used to improve upon an existing molecule’s pharmacologic potential by elucidating the structural composition with desirable properties. Several researchers create and develop QSAR machine learning models for a variety of different therapeutic targets. However, their use is limited by lack of access to said models. Beyond access, there are often difficulties in using published software given the need to manage dependencies and replicating the development environment. To address this issue, the application documented here was designed and developed. In this centralized platform, researchers can access several QSAR machine learning models and test their own datasets for interaction with various therapeutic targets. The platform allows the use of widespread molecule identifiers as input, such as SMILES and InChI, handling the necessary integration into the appropriate molecular descriptors to be used in the model. The platform can be accessed through a Web Application with a full graphical user interface developed with the R package Shiny and through a REST API developed with the Flask Restful package for Python. The complete application is packaged up in container technology, specifically Docker. The main goal of this platform is to grant widespread access to the QSAR models developed by the scientific community, by concentrating them in a single location and removing the user’s need to install or set up software unfamiliar to them. This intends to incite knowledge creation and facilitate the research process

Systems, methods and apparatus for developing and maintaining evolving systems with software product lines

Systems, methods and apparatus are provided through which an evolutionary system is managed and viewed as a software product line. In some embodiments, the core architecture is a relatively unchanging part of the system, and each version of the system is viewed as a product from the product line. Each software product is generated from the core architecture with some agent-based additions. The result may be a multi-agent system software product line

Open reWall: Survey-to-production workflow for building renovation

A reabilitação de espaços interiores, num contexto de personalização em série, requer uma mudança na forma como os sistemas construtivos são desenhados, construídos e reutilizados. Recorrendo a plataformas digitais para a participação os arquitetos, em colaboração com outros atores na indústria AEC, podem desenvolver e oferecer soluções personalizadas e desmontáveis a utilizadores genéricos. Esta investigação propõe o uso de sistemas de construção personalizada em série (CPS) para fornecer sistemas de divisórias desmontáveis fabricadas digitalmente usando metodologias do levantamento à produção ligadas a configuradores online, em que os utilizadores co-projetam soluções para a reabilitação de espaços interiores. A metodologia de investigação socorre-se de pesquisa e análise teórica para definir critérios e objetivos a serem explorados em resolução de problemas de projeto. A partir destas experiências são sintetizados princípios e uma metodologia para a conceção de sistemas CPS de sistemas de divisórias personalizáveis e desmontáveis para a reabilitação. A metodologia clarifica os papeis dos atores, passos, e arquitetura do sistema para implementar um sistema CPS do levantamento à produção. A investigação demonstra que a metodologia de levantamento proposta é utilizável por utilizadores especialistas e não-especialistas, com os últimos a apresentarem em média melhores resultados, e que estes levantamentos têm precisão suficiente para processos do desenho à produção. Também se demonstra que a metodologia do levantamento à produção, a gramática genérica, e os critérios são úteis para os arquitetos conceberem sistemas de divisórias desmontáveis e personalizáveis para sistemas CPS abertos.Building renovation of interior spaces, in the context of mass customization, requires a shift in how construction systems are designed, built, and reused. Leveraging digital frameworks for user participation, architects in collaboration with other stakeholders in the AEC industry may design anddeliver customized and disassemble-able solutions to generic end-users. The research proposes mass customization construction (MCC) systems can deliver cost-effective digitally fabricated and disassemble-able construction systems using survey-to-production workflows deployed in web configurators for end-users to co-design solutions in building renovation. The research methodology uses theoretical inquiry and analysis to define criteria and objectives to be explored in design problem solving. From these experiments generalizable principles and a lowkey workflow for the design of MCC systems of customizable and disassemble-able partition wall construction systems for open building renovation are synthetized. The workflow clarifies stakeholder roles, steps, and system architecture to implement an MCC system from survey to production. This investigation demonstrates the proposed survey workflow is usable by non-expert and expert instance-designers, with the former having on-average better results, and that these can survey spaces with sufficient precision for design-to-production workflows. It is also shown the survey-to-production workflow, the generic grammar, and criteria are useful for architects to design customizable and disassemble-able partition wall systems for open MCC systems

Programmable flexible cores for SoC applications

Tese de mestrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200

A Methodology for Extracting Human Bodies from Still Images

Monitoring and surveillance of humans is one of the most prominent applications of today and it is expected to be part of many future aspects of our life, for safety reasons, assisted living and many others. Many efforts have been made towards automatic and robust solutions, but the general problem is very challenging and remains still open. In this PhD dissertation we examine the problem from many perspectives. First, we study the performance of a hardware architecture designed for large-scale surveillance systems. Then, we focus on the general problem of human activity recognition, present an extensive survey of methodologies that deal with this subject and propose a maturity metric to evaluate them. One of the numerous and most popular algorithms for image processing found in the field is image segmentation and we propose a blind metric to evaluate their results regarding the activity at local regions. Finally, we propose a fully automatic system for segmenting and extracting human bodies from challenging single images, which is the main contribution of the dissertation. Our methodology is a novel bottom-up approach relying mostly on anthropometric constraints and is facilitated by our research in the fields of face, skin and hands detection. Experimental results and comparison with state-of-the-art methodologies demonstrate the success of our approach

Service-oriented architecture for device lifecycle support in industrial automation

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores Especialidade: Robótica e Manufactura IntegradaThis thesis addresses the device lifecycle support thematic in the scope of service oriented industrial automation domain. This domain is known for its plethora of heterogeneous equipment encompassing distinct functions, form factors, network interfaces, or I/O specifications supported by dissimilar software and hardware platforms. There is then an evident and crescent need to take every device into account and improve the agility performance during setup, control, management, monitoring and diagnosis phases. Service-oriented Architecture (SOA) paradigm is currently a widely endorsed approach for both business and enterprise systems integration. SOA concepts and technology are continuously spreading along the layers of the enterprise organization envisioning a unified interoperability solution. SOA promotes discoverability, loose coupling, abstraction, autonomy and composition of services relying on open web standards – features that can provide an important contribution to the industrial automation domain. The present work seized industrial automation device level requirements, constraints and needs to determine how and where can SOA be employed to solve some of the existent difficulties. Supported by these outcomes, a reference architecture shaped by distributed, adaptive and composable modules is proposed. This architecture will assist and ease the role of systems integrators during reengineering-related interventions throughout system lifecycle. In a converging direction, the present work also proposes a serviceoriented device model to support previous architecture vision and goals by including embedded added-value in terms of service-oriented peer-to-peer discovery and identification, configuration, management, as well as agile customization of device resources. In this context, the implementation and validation work proved not simply the feasibility and fitness of the proposed solution to two distinct test-benches but also its relevance to the expanding domain of SOA applications to support device lifecycle in the industrial automation domain