Método para la evaluación de usabilidad de sitios web transaccionales basado en el proceso de inspección heurística

La usabilidad es considerada uno de los factores más importantes en el desarrollo de productos de software. Este atributo de calidad está referido al grado en que, usuarios específicos de un determinado aplicativo, pueden fácilmente hacer uso del software para lograr su propósito. Dada la importancia de este aspecto en el éxito de las aplicaciones informáticas, múltiples métodos de evaluación han surgido como instrumentos de medición que permiten determinar si la propuesta de diseño de la interfaz de un sistema de software es entendible, fácil de usar, atractiva y agradable al usuario. El método de evaluación heurística es uno de los métodos más utilizados en el área de Interacción Humano-Computador (HCI) para este propósito debido al bajo costo de su ejecución en comparación otras técnicas existentes. Sin embargo, a pesar de su amplio uso extensivo durante los últimos años, no existe un procedimiento formal para llevar a cabo este proceso de evaluación. Jakob Nielsen, el autor de esta técnica de inspección, ofrece únicamente lineamientos generales que, según la investigación realizada, tienden a ser interpretados de diferentes maneras por los especialistas. Por tal motivo, se ha desarrollado el presente proyecto de investigación que tiene como objetivo establecer un proceso sistemático, estructurado, organizado y formal para llevar a cabo evaluaciones heurísticas a productos de software. En base a un análisis exhaustivo realizado a aquellos estudios que reportan en la literatura el uso del método de evaluación heurística como parte del proceso de desarrollo de software, se ha formulado un nuevo método de evaluación basado en cinco fases: (1) planificación, (2) entrenamiento, (3) evaluación, (4) discusión y (5) reporte. Cada una de las fases propuestas que componen el protocolo de inspección contiene un conjunto de actividades bien definidas a ser realizadas por el equipo de evaluación como parte del proceso de inspección. Asimismo, se han establecido ciertos roles que deberán desempeñar los integrantes del equipo de inspectores para asegurar la calidad de los resultados y un apropiado desarrollo de la evaluación heurística. La nueva propuesta ha sido validada en dos escenarios académicos distintos (en Colombia, en una universidad pública, y en Perú, en dos universidades tanto en una pública como en una privada) demostrando en todos casos que es posible identificar más problemas de usabilidad altamente severos y críticos cuando un proceso estructurado de inspección es adoptado por los evaluadores. Otro aspecto favorable que muestran los resultados es que los evaluadores tienden a cometer menos errores de asociación (entre heurística que es incumplida y problemas de usabilidad identificados) y que la propuesta es percibida como fácil de usar y útil. Al validarse la nueva propuesta desarrollada por el autor de este estudio se consolida un nuevo conocimiento que aporta al bagaje cultural de la ciencia.Tesi

Food Supply Chain through Ongoing Evolution: Lessons from Continuous Transformations

Considering their constant evolution and transformation, in this Special Issue, several authors provide contributions bringing light to different aspects related to food supply chains, based on several conceptual frameworks, agri-food areas and contexts, as well as multiple levels of analysis. In this book, the promotion of win–win investments in Brazil’s Agribusiness is discussed, as well as how family farmers can thrive in commodity markets in long agribusiness supply chains. The Logic of Collective Action for Rural Warehouse Condominiums, which is a new configuration in the agribusiness supply chain, is also addressed. In this book, the Brazilian Jabuticaba Supply Chain is analyzed through a multi-methodological approach. The role of logistics in food-waste reduction for wholesalers and small retailers of fruits and vegetables is also presented. The issue of transparency in global agribusiness in the Brazilian soybean supply chain is discussed based on companies’ accountability. Finally, the transformation of the food supply chain through technology and future research directions are highlighted in this Special Issue. This book aims to assist students, researchers and practitioners interested in the evolution and transformations of food supply chains

The Effects of the COVID-19 Pandemic on the Digital Competence of Educators

The Covid-19 pandemic is having an undeniable impact on all the statements of society. Regarding teaching and learning activities, most educational institutions suspended in-person instruction and moved to remote learning during the lockdown of March and April 2020. Although nowadays many countries have progressively re-opened their educational systems, blended learning is a common practice aimed to reduce the spread of the Covid-19 disease. This disruption has supposed an unprecedented acceleration to the digitalization of teaching and learning. Teaching professionals have been forced to develop their digital competence in a short amount of time, getting mastery in the management of information, the creation of audiovisual contents, and the use of technology to keep their students connected. This Special Issue presents contributions regarding the adoption of distance learning strategies, experiences, or lessons learned in this domain

Exploring attributes, sequences, and time in Recommender Systems: From classical to Point-of-Interest recommendation

Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Ingenieria Informática. Fecha de lectura: 08-07-2021Since the emergence of the Internet and the spread of digital communications throughout the world, the amount of data stored on the Web has been growing exponentially. In this new digital era, a large number of companies have emerged with the purpose of ltering the information available on the web and provide users with interesting items. The algorithms and models used to recommend these items are called Recommender Systems. These systems are applied to a large number of domains, from music, books, or movies to dating or Point-of-Interest (POI), which is an increasingly popular domain where users receive recommendations of di erent places when they arrive to a city. In this thesis, we focus on exploiting the use of contextual information, especially temporal and sequential data, and apply it in novel ways in both traditional and Point-of-Interest recommendation. We believe that this type of information can be used not only for creating new recommendation models but also for developing new metrics for analyzing the quality of these recommendations. In one of our rst contributions we propose di erent metrics, some of them derived from previously existing frameworks, using this contextual information. Besides, we also propose an intuitive algorithm that is able to provide recommendations to a target user by exploiting the last common interactions with other similar users of the system. At the same time, we conduct a comprehensive review of the algorithms that have been proposed in the area of POI recommendation between 2011 and 2019, identifying the common characteristics and methodologies used. Once this classi cation of the algorithms proposed to date is completed, we design a mechanism to recommend complete routes (not only independent POIs) to users, making use of reranking techniques. In addition, due to the great di culty of making recommendations in the POI domain, we propose the use of data aggregation techniques to use information from di erent cities to generate POI recommendations in a given target city. In the experimental work we present our approaches on di erent datasets belonging to both classical and POI recommendation. The results obtained in these experiments con rm the usefulness of our recommendation proposals, in terms of ranking accuracy and other dimensions like novelty, diversity, and coverage, and the appropriateness of our metrics for analyzing temporal information and biases in the recommendations producedDesde la aparici on de Internet y la difusi on de las redes de comunicaciones en todo el mundo, la cantidad de datos almacenados en la red ha crecido exponencialmente. En esta nueva era digital, han surgido un gran n umero de empresas con el objetivo de ltrar la informaci on disponible en la red y ofrecer a los usuarios art culos interesantes. Los algoritmos y modelos utilizados para recomendar estos art culos reciben el nombre de Sistemas de Recomendaci on. Estos sistemas se aplican a un gran n umero de dominios, desde m usica, libros o pel culas hasta las citas o los Puntos de Inter es (POIs, en ingl es), un dominio cada vez m as popular en el que los usuarios reciben recomendaciones de diferentes lugares cuando llegan a una ciudad. En esta tesis, nos centramos en explotar el uso de la informaci on contextual, especialmente los datos temporales y secuenciales, y aplicarla de forma novedosa tanto en la recomendaci on cl asica como en la recomendaci on de POIs. Creemos que este tipo de informaci on puede utilizarse no s olo para crear nuevos modelos de recomendaci on, sino tambi en para desarrollar nuevas m etricas para analizar la calidad de estas recomendaciones. En una de nuestras primeras contribuciones proponemos diferentes m etricas, algunas derivadas de formulaciones previamente existentes, utilizando esta informaci on contextual. Adem as, proponemos un algoritmo intuitivo que es capaz de proporcionar recomendaciones a un usuario objetivo explotando las ultimas interacciones comunes con otros usuarios similares del sistema. Al mismo tiempo, realizamos una revisi on exhaustiva de los algoritmos que se han propuesto en el a mbito de la recomendaci o n de POIs entre 2011 y 2019, identi cando las caracter sticas comunes y las metodolog as utilizadas. Una vez realizada esta clasi caci on de los algoritmos propuestos hasta la fecha, dise~namos un mecanismo para recomendar rutas completas (no s olo POIs independientes) a los usuarios, haciendo uso de t ecnicas de reranking. Adem as, debido a la gran di cultad de realizar recomendaciones en el ambito de los POIs, proponemos el uso de t ecnicas de agregaci on de datos para utilizar la informaci on de diferentes ciudades y generar recomendaciones de POIs en una determinada ciudad objetivo. En el trabajo experimental presentamos nuestros m etodos en diferentes conjuntos de datos tanto de recomendaci on cl asica como de POIs. Los resultados obtenidos en estos experimentos con rman la utilidad de nuestras propuestas de recomendaci on en t erminos de precisi on de ranking y de otras dimensiones como la novedad, la diversidad y la cobertura, y c omo de apropiadas son nuestras m etricas para analizar la informaci on temporal y los sesgos en las recomendaciones producida

Novel Validation Techniques for Autonomous Vehicles

The automotive industry is facing challenges in producing electrical, connected, and autonomous vehicles. Even if these challenges are, from a technical point of view, independent from each other, the market and regulatory bodies require them to be developed and integrated simultaneously. The development of autonomous vehicles implies the development of highly dependable systems. This is a multidisciplinary activity involving knowledge from robotics, computer science, electrical and mechanical engineering, psychology, social studies, and ethics. Nowadays, many Advanced Driver Assistance Systems (ADAS), like Emergency Braking System, Lane Keep Assistant, and Park Assist, are available. Newer luxury cars can drive by themselves on highways or park automatically, but the end goal is to develop completely autonomous driving vehicles, able to go by themselves, without needing human interventions in any situation. The more vehicles become autonomous, the greater the difficulty in keeping them reliable. It enhances the challenges in terms of development processes since their misbehaviors can lead to catastrophic consequences and, differently from the past, there is no more a human driver to mitigate the effects of erroneous behaviors. Primary threats to dependability come from three sources: misuse from the drivers, design systematic errors, and random hardware failures. These safety threats are addressed under various aspects, considering the particular type of item to be designed. In particular, for the sake of this work, we analyze those related to Functional Safety (FuSa), viewed as the ability of a system to react on time and in the proper way to the external environment. From the technological point of view, these behaviors are implemented by electrical and electronic items. Various standards to achieve FuSa have been released over the years. The first, released in 1998, was the IEC 61508. Its last version is the one released in 2010. This standard defines mainly: • a Functional Safety Management System (FSMS); • methods to determine a Safety Integrated Level (SIL); • methods to determine the probability of failures. To adapt the IEC61508 to the automotive industry’s peculiarity, a newer standard, the ISO26262, was released in 2011 then updated in 2018. This standard provides guidelines about FSMS, called in this case Safety Lifecycle, describing how to develop software and hardware components suitable for functional safety. It also provides a different way to compute the SIL, called in this case Automotive SIL (ASIL), allowing us to consider the average driver’s abilities to control the vehicle in case of failures. Moreover, it describes a way to determine the probability of random hardware failures through Failure Mode, Effects, and Diagnostic Analysis (FMEDA). This dissertation contains contributions to three topics: • random hardware failures mitigation; • improvementoftheISO26262HazardAnalysisandRiskAssessment(HARA); • real-time verification of the embedded software. As the main contribution of this dissertation, I address the safety threats due to random hardware failures (RHFs). For this purpose, I propose a novel simulation-based approach to aid the Failure Mode, Effects, and Diagnostic Analysis (FMEDA) required by the ISO26262 standard. Thanks to a SPICE-level model of the item, and the adoption of fault injection techniques, it is possible to simulate its behaviors obtaining useful information to classify the various failure modes. The proposed approach evolved from a mere simulation of the item, allowing only an item-level failure mode classification up to a vehicle-level analysis. The propagation of the failure modes’ effects on the whole vehicle enables us to assess the impacts on the vehicle’s drivability, improving the quality of the classifications. It can be advantageous where it is difficult to predict how the item-level misbehaviors propagate to the vehicle level, as in the case of a virtual differential gear or the mobility system of a robot. It has been chosen since it can be considered similar to the novel light vehicles, such as electric scooters, that are becoming more and more popular. Moreover, my research group has complete access to its design since it is realized by our university’s DIANA students’ team. When a SPICE-level simulation is too long to be performed, or it is not possible to develop a complete model of the item due to intellectual property protection rules, it is possible to aid this process through behavioral models of the item. A simulation of this kind has been performed on a mobile robotic system. Behavioral models of the electronic components were used, alongside mechanical simulations, to assess the software failure mitigation capabilities. Another contribution has been obtained by modifying the main one. The idea was to make it possible to aid also the Hazard Analysis and Risk Assessment (HARA). This assessment is performed during the concept phase, so before starting to design the item implementation. Its goal is to determine the hazards involved in the item functionality and their associated levels of risk. The end goal of this phase is a list of safety goals. For each one of these safety goals, an ASIL has to be determined. Since HARA relies only on designers expertise and knowledge, it lacks in objectivity and repeatability. Thanks to the simulation results, it is possible to predict the effects of the failures on the vehicle’s drivability, allowing us to improve the severity and controllability assessment, thus improving the objectivity. Moreover, since simulation conditions can be stored, it is possible, at any time, to recheck the results and to add new scenarios, improving the repeatability. The third group of contributions is about the real-time verification of embedded software. Through Hardware-In-the-Loop (HIL), a software integration verification has been performed to test a fundamental automotive component, mixed-criticality applications, and multi-agent robots. The first of these contributions is about real-time tests on Body Control Modules (BCM). These modules manage various electronic accessories in the vehicle’s body, like power windows and mirrors, air conditioning, immobilizer, central locking. The main characteristics of BCMs are the communications with other embedded computers via the car’s vehicle bus (Controller Area Network) and to have a high number (hundreds) of low-speed I/Os. As the second contribution, I propose a methodology to assess the error recovery system’s effects on mixed-criticality applications regarding deadline misses. The system runs two tasks: a critical airplane longitudinal control and a non-critical image compression algorithm. I start by presenting the approach on a benchmark application containing an instrumented bug into the lower criticality task; then, we improved it by injecting random errors inside the lower criticality task’s memory space through a debugger. In the latter case, thanks to the HIL, it is possible to pause the time domain simulation when the debugger operates and resume it once the injection is complete. In this way, it is possible to interact with the target without interfering with the simulation results, combining a full control of the target with an accurate time-domain assessment. The last contribution of this third group is about a methodology to verify, on multi-agent robots, the synchronization between two agents in charge to move the end effector of a delta robot: the correct position and speed of the end effector at any time is strongly affected by a loss of synchronization. The last two contributions may seem unrelated to the automotive industry, but interest in these applications is gaining. Mixed-criticality systems allow reducing the number of ECUs inside cars (for cost reduction), while the multi-agent approach is helpful to improve the cooperation of the connected cars with respect to other vehicles and the infrastructure. The fourth contribution, contained in the appendix, is about a machine learning application to improve the social acceptance of autonomous vehicles. The idea is to improve the comfort of the passengers by recognizing their emotions. I started with the idea to modify the vehicle’s driving style based on a real-time emotions recognition system but, due to the difficulties of performing such operations in an experimental setup, I move to analyze them offline. The emotions are determined on volunteers’ facial expressions recorded while viewing 3D representa- tions showing different calibrations. Thanks to the passengers’ emotional responses, it is possible to choose the better calibration from the comfort point of view

Novel Validation Techniques for Autonomous Vehicles

L'abstract è presente nell'allegato / the abstract is in the attachmen

Divergence in Architectural Research

ConCave Ph.D. Symposium 2020: Divergence in Architectural Research, March 5-6, 2020, Georgia Institute of Technology, Atlanta, GA.The essays in this volume have come together under the theme “Divergence in Architectural Research” and present a snapshot of Ph.D. research being conducted in over thirty architectural research institutions, representing fourteen countries around the world. These essays also provide a window into the presentations and discussions that took place March 5-6, 2020, during the ConCave Ph.D. Symposium “Divergence in Architectural Research,” under the auspices of the School of Architecture, Georgia Institute of Technology, in Atlanta, Georgia. On a preliminary reading, the essays respond to the call of divergence by doing just that; they present the great diversity of research topics, methodologies, and practices currently found under the umbrella of “architectural research.” They inform inquiry within architectural programs and across disciplinary concentrations, and also point to the ways that the academy, research methodologies, and the design profession are evolving and encroaching upon one another, with the unspoken hope of encouraging new relationships, reconfiguring previous assumptions about the discipline, and interweaving research and practice

SBE16 Brazil & Portugal - Sustainable Urban Communities towards a Nearly Zero Impact Built Environment

Vol. IThe organizers of SBE 16 Brazil & Portugal were challenged to promote discussions and the development of solutions for an important and, at the same time, very ambitious topic ? Sustainable Urban Communities towards a Nearly Zero Impact Built Environment. This is the main focus of the international conference SBE16 Brazil & Portugal; the only event of the SBE16/17 conference series being held in Latin America, more precisely, in Vitória (Espírito Santo), Brazil, from the 7th until the 9th of September 2016. The conference offered a unique opportunity to bring together researchers from all over the world to share evidence-based knowledge in the field and succeeded to achieve its goals since many contributions from various parts of the planet were received, addressing a tiny part of the problem or trying to perform the difficult task of making the sum of the parts a coherent whole.info:eu-repo/semantics/publishedVersio