Sistema de gestión y guía turística para dispositivos móviles en El Salvador

Este documento, refiere al trabajo realizado para la Alcaldía Municipal de San Vicente, con el propósito de ayudar a la promoción del turismo en el Municipio de San Vicente y en toda la Zona paracentral, se desarrolló una aplicación web que se compone de tres módulos principales a los cuales se puede acceder desde un dispositivo móvil con acceso a internet y un módulo para administradores del sistema para la gestión de centros turísticos y turistas los cuales serán operados desde un administrador principal, el sistema se desarrolló para poder contribuir a la promoción del turismo en El Salvador. Esta herramienta se desarrolló usando las tecnologías existentes para dispositivos móviles de HTML5 y PHP. Al finalizar el aplicativo web se han logrado obtener beneficios para los dueños de destinos turísticos ya que pueden promocionarse de manera gratuita, además la Institución beneficiaria cuenta con un recurso más para poder catalogar y mapear destinos existentes y así sugerirlos. Al finalizar este trabajo se logró cumplir con el objetivo planteado que fue ayudar a la promoción del turismo en El Salvador. SUMMARY This document refers to work done for the Municipality of San Vicente, in order to help promote tourism in the municipality of San Vicente and throughout the paracentral area, is developing a web application that consists of three main modules to which can be accessed from a mobile device with internet access and a module for system administrators to manage resorts and tourists which will be operated from a main administrator, the system development to contribute to the promotion of tourism in El Salvador. This tool was developed using existing technologies for mobile devices HTML5 and PHP. At the end of the web application has been made a profit for the owners of tourist destinations because they can promote themselves for free, also the beneficiary institution has a resource to catalog and map existing and destinations and suggest them. Upon completion of this work failed to meet the stated objective was to help the promotion of tourism in El Salvador.

La enseñanza de la Ciencia Política en Colombia: una aproximación desde los macrocurrículos de pregrado

En vista del rápido crecimiento del número de programas de formación profesional en Ciencia Política a nivel de pregrado en el país, vale la pena detenerse e indagar, a modo de evaluación, por el estado de la enseñanza en esta disciplina. Esto bien podría llevar a un análisis de las metodologías pedagógicas utilizadas en el aula de clase y fuera de ella, los grados de for-mación de los docentes en el área, o incluso las lecturas que componen los microcurrículos de los distintos cursos impartidos por 32 universidades en el país. Sin embargo, en este trabajo se opta por un acercamiento a esta cuestión desde los macrocurrículos, es decir, a partir de los cursos o materias dictadas en los diferentes programas. La metodología adoptada para este trabajo es estadística, y se complementa con reflexiones teóricas, discusiones existentes en la literatura sobre el tema y con las declaraciones de los propios programas en sus sitios web.

Implementación de un framework para la inclusión de logros en "¡Acepta el Reto!"

“Implementación de un framework para la inclusión de logros en ¡Acepta el Reto!” es un proyecto que tiene como objetivo la inclusión de un sistema de logros en ¡Acepta el reto! Los logros son reconocimientos, independientes de la funcionalidad de la web, dentro de ¡Acepta el reto!, que es una página web que propone ejercicios de programación y a su vez los compila y los ejecuta. La labor del framework desarrollado es vigilar las acciones que los usuarios van realizando en el portal para otorgarles los distintos logros implementados. Durante el diseño se ha prestado especial atención a la posibilidad de añadir nuevos logros tras el despliegue del sistema y a la eficiencia en el proceso de comprobación de los mismos. Para demostrar su efectividad, se han hecho pruebas de carga utilizando los datos de usuarios, envíos y ejercicios actuales de la web.

Everglades R-EMAP 2005

The Everglades R-EMAP project for year 2005 produced large quantities of data collected at 232 sampling sites. Data collection and analysis is an on-going long-term activity conducted by scientists of different disciplines at irregular intervals of several years. The data sets collected for 2005 include bio-geo-chemical (including mercury and hydro period), fish, invertebrate, periphyton, and plant data. Each sampling site is associated with a location, a description of the site to provide a general overview and photographs to provide a pictorial impression. The Geographic Information Systems and Remote Sensing Center(GISRSC) at Florida International University (FIU) has designed and implemented an enterprise database for long-term storage of the project�s data in a central repository, providing the framework of data storage for the continuity of future sampling campaigns and allowing integration of new sample data as it becomes available. In addition GISRSC provides this interactive web application for easy, quick and effective retrieval and visualization of that data.

Monitoring system for small sized photovoltaic power plants

This paper presents a monitoring system devoted to small sized photovoltaic (PV) power plants. The system is characterized by: a high level of integration; a low cost, when compared to the cost of the PV system to be monitored; and an easy installation in the majority of the PV plants with installed power of some kW. The system is able to collect, store, process and display electrical and meteorological parameters that are crucial when monitoring PV facilities. The identification of failures in the PV system and the elaboration of performance analysis of such facilities are other important characteristics of the developed system. The access to the information about the monitored facilities is achieved by using a web application, which was developed with a focus on the mobile devices. In addition, there is the possibility of an integration between the developed monitoring system and the central supervision system of Martifer Solar (a company focused on the development, operation and maintenance of PV systems).

Sviluppo di YouCrowd: una piattaforma per campagne mobile crowdsensing on-demand

Con il termine "crowdsensing" si intende una tecnica in cui un folto gruppo di individui aventi dispositivi mobili acquisiscono e condividono dati di natura diversa in maniera collettiva, al fine di estrarre informazioni utili. Il concetto di Mobile Crowdsensing è molto recente e derivante dalle ultime innovazioni tecnologiche in materia di connettività online e cattura di dati di vario genere; pertanto non si trova attualmente una vera e propria applicazione in campo reale, la modellazione solo teorica e fin troppo specifica pone un limite alla conoscenza di un ambito che può rivelarsi molto utile ai fini di ricerca. YouCrowd è un piattaforma web che va ad implementare un sistema di crowdsourcing completo, in grado di leggere dati dai numerosi sensori di uno smartphone e condividerli, al fine di ottenere una remunerazione per gli utenti che completano una campagna. La web application vede la sua implementazione di base supportata da NodeJS e si configura come una piattaforma dinamica che varia la propria interfaccia con l'utente in base alle richieste di dati da parte degli administrators. Il test di YouCrowd ha coinvolto un buon numero di partecipanti più o meno esperti nell'utilizzo degli strumenti informatici, rivelando delle buone prestazioni in relazione alla difficoltà del task e alle prestazioni del device in test.

Supervised and weakly supervised counting-by-segmentation: the fluorescent microscopy use case

This thesis focuses on automating the time-consuming task of manually counting activated neurons in fluorescent microscopy images, which is used to study the mechanisms underlying torpor. The traditional method of manual annotation can introduce bias and delay the outcome of experiments, so the author investigates a deep-learning-based procedure to automatize this task. The author explores two of the main convolutional-neural-network (CNNs) state-of-the-art architectures: UNet and ResUnet family model, and uses a counting-by-segmentation strategy to provide a justification of the objects considered during the counting process. The author also explores a weakly-supervised learning strategy that exploits only dot annotations. The author quantifies the advantages in terms of data reduction and counting performance boost obtainable with a transfer-learning approach and, specifically, a fine-tuning procedure. The author released the dataset used for the supervised use case and all the pre-training models, and designed a web application to share both the counting process pipeline developed in this work and the models pre-trained on the dataset analyzed in this work.

L'inclusione lavorativa tra accesso e partecipazione

La Convenzione delle Nazioni Unite sui Diritti delle Persone con Disabilità (UNCRPD) riconosce il diritto di tutte le persone al lavoro “gli Stati Parti adottano misure adeguate a garantire alle persone con disabilità, su base di uguaglianza con gli altri, l’accesso all’ambiente fisico, ai trasporti, all’informazione e alla comunicazione, compresi i sistemi e le tecnologie di informazione e comunicazione e ad altre attrezzature e servizi aperti o forniti al pubblico”(United Nation 2016 p.14). Nonostante i progressi (in ambito politico culturale) che si stanno compiendo in ambito internazionale in termini di pari opportunità e di inclusione, le persone in situazione di disabilità continuano a incontrare barriere che limitano la loro partecipazione attiva al mondo del lavoro. A partire da questo scenario, la ricerca si propone di indagare i bisogni (es. di accoglienza, di accesso al contesto fisico e digitale, di partecipazione nella vita dell’azienda ecc.) delle persone con disabilità e di sviluppare una applicazione digitale (web app), rivolta alle imprese, finalizzata a monitorare e a promuovere l'inclusione lavorativa. Ripercorrendo il modello di progettazione del design thinking e valorizzando un processo di ricerca basato su metodi misti (qualitativi e qualitativi) è stato ideato Job inclusion for all; un ambiente digitale fondato sull’adattamento di due strumenti di “metariflessione”: l’Index for inclusion job version e l’employment role mapping. Lo strumento digitale prototipato è stato testato e validato, durante l’ultimo anno di ricerca, da parte di una equipe multidisciplinare internazionale; tale processo ha consentito di raccogliere feedback (rispetto alla rilevanza e alla chiarezza degli item, rispetto ai punti di forza e di debolezza) che hanno consentito di migliorare e implementare la versione finale del prototipo di web app.

Supporting requirement elicitation and ontology testing in knowledge graph engineering

Knowledge graphs and ontologies are closely related concepts in the field of knowledge representation. In recent years, knowledge graphs have gained increasing popularity and are serving as essential components in many knowledge engineering projects that view them as crucial to their success. The conceptual foundation of the knowledge graph is provided by ontologies. Ontology modeling is an iterative engineering process that consists of steps such as the elicitation and formalization of requirements, the development, testing, refactoring, and release of the ontology. The testing of the ontology is a crucial and occasionally overlooked step of the process due to the lack of integrated tools to support it. As a result of this gap in the state-of-the-art, the testing of the ontology is completed manually, which requires a considerable amount of time and effort from the ontology engineers. The lack of tool support is noticed in the requirement elicitation process as well. In this aspect, the rise in the adoption and accessibility of knowledge graphs allows for the development and use of automated tools to assist with the elicitation of requirements from such a complementary source of data. Therefore, this doctoral research is focused on developing methods and tools that support the requirement elicitation and testing steps of an ontology engineering process. To support the testing of the ontology, we have developed XDTesting, a web application that is integrated with the GitHub platform that serves as an ontology testing manager. Concurrently, to support the elicitation and documentation of competency questions, we have defined and implemented RevOnt, a method to extract competency questions from knowledge graphs. Both methods are evaluated through their implementation and the results are promising.

Network analysis and machine learning assist drug repurposing and safety assessment in neurological diseases

In recent decades, two prominent trends have influenced the data modeling field, namely network analysis and machine learning. This thesis explores the practical applications of these techniques within the domain of drug research, unveiling their multifaceted potential for advancing our comprehension of complex biological systems. The research undertaken during this PhD program is situated at the intersection of network theory, computational methods, and drug research. Across six projects presented herein, there is a gradual increase in model complexity. These projects traverse a diverse range of topics, with a specific emphasis on drug repurposing and safety in the context of neurological diseases. The aim of these projects is to leverage existing biomedical knowledge to develop innovative approaches that bolster drug research. The investigations have produced practical solutions, not only providing insights into the intricacies of biological systems, but also allowing the creation of valuable tools for their analysis. In short, the achievements are: • A novel computational algorithm to identify adverse events specific to fixed-dose drug combinations. • A web application that tracks the clinical drug research response to SARS-CoV-2. • A Python package for differential gene expression analysis and the identification of key regulatory "switch genes". • The identification of pivotal events causing drug-induced impulse control disorders linked to specific medications. • An automated pipeline for discovering potential drug repurposing opportunities. • The creation of a comprehensive knowledge graph and development of a graph machine learning model for predictions. Collectively, these projects illustrate diverse applications of data science and network-based methodologies, highlighting the profound impact they can have in supporting drug research activities.

Self-supervised Information Retrieval basato su deep metric learning

La tesi ha lo scopo di ricercare, esaminare ed implementare un sistema di Machine Learning, un Recommendation Systems per precisione, che permetta la racommandazione di documenti di natura giuridica, i quali sono già stati analizzati e categorizzati appropriatamente, in maniera ottimale, il cui scopo sarebbe quello di accompagnare un sistema già implementato di Information Retrieval, istanziato sopra una web application, che permette di ricercare i documenti giuridici appena menzionati.

Un ponte tra Crowdsourcing e Crowdsensing: L'implementazione di SmartCrowd

L’elaborato presenta lo sviluppo di un’applicazione web che unisce il con- cetto di crowdsourcing, ovvero un paradigma in cui una colletività esegue una mansione per il raggiungimento di un obiettivo; e il concetto di crowd- sensing, paradigma nel quale un gruppo di persone, utilizzando il proprio dispositivo mobile, condivide dati, che possono essere successivamente stu- diati. SmartCrowd si pone come intermediario tra questi due modelli, e la sua implementazione permette di raccogliere dati da una “folla” che faccia uso dei dispositivi mobili, usufruendo di una piattaforma di crowdsourcing. Con SmartCrowd vengono create le campagne, ovvero insieme di attività svol- te dagli utenti finali; esiste un sistema di interazione con la piattaforma di crowdsourcing di Microworkers, volta al reclutamento delle persone; la con- divisione dei dati tramite smartphone, usando il sensore GPS, eseguita dagli utenti ed infine, tramite SmartCrowd è possibile analizzare i dati ricevuti e fare una valutazione positiva o negativa.

Smart Mirror: remote verification of an identity document holder

Nowadays, some activities, such as subscribing an insurance policy or opening a bank account, are possible by navigating through a web page or a downloadable application. Since the user is often “hidden” behind a monitor or a smartphone, it is necessary a solution able to guarantee about their identity. Companies are often requiring the submission of a “proof-of-identity”, which usually consists in a picture of an identity document of the user, together with a picture or a brief video of themselves. This work describes a system whose purpose is the automation of these kinds of verifications.

Towards a Smart Campus Digital Twin: Promoting Awareness and Sustainability Through Wayfinding and Real-Time Environmental Data

The newly inaugurated Navile District of the University of Bologna is a complex created along the Navile canal, that now houses various teaching and research activities for the disciplines of Chemistry, Industrial Chemistry, Pharmacy, Biotechnology and Astronomy. A Building Information Modeling system (BIM) gives staff of the Navile campus several ways to monitor buildings in the complex throughout their life cycle, one of which is the ability to access real-time environmental data such as room temperature, humidity, air composition, and more, thereby simplifying operations like finding faults and optimizing environmental resource usage. But smart features at Navile are not only available to the staff: AlmaMap Navile is a web application, whose development is documented in this thesis, that powers the public touch kiosks available throughout the campus, offering maps of the district and indications on how to reach buildings and spaces. Even if these two systems, BIM and AlmaMap, don't seem to have many similarities, they share the common intent of promoting awareness for informed decision making in the campus, and they do it while relying on web standards for communication. This opens up interesting possibilities, and is the idea behind AlmaMap Navile 2.0, an app that interfaces with the BIM system and combines real-time sensor data with a comfort calculation algorithm, giving users the ability not just to ask for directions to a space, but also to see its comfort level in advance and, should they want to, check environmental measurements coming from each sensor in a granular manner. The end result is a first step towards building a smart campus Digital Twin, that can support all the people who are part of the campus life in their daily activities, improving their efficiency and satisfaction, giving them the ability to make informed decisions, and promoting awareness and sustainability.

Using the web graph to influence application behaviour

The Web's link structure (termed the Web Graph) is a richly connected set of Web pages. Current applications use this graph for indexing and information retrieval purposes. In contrast the relationship between Web Graph and application is reversed by letting the structure of the Web Graph influence the behaviour of an application. Presents a novel Web crawling agent, AlienBot, the output of which is orthogonally coupled to the enemy generation strategy of a computer game. The Web Graph guides AlienBot, causing it to generate a stochastic process. Shows the effectiveness of such unorthodox coupling to both the playability of the game and the heuristics of the Web crawler. In addition, presents the results of the sample of Web pages collected by the crawling process. In particular, shows: how AlienBot was able to identify the power law inherent in the link structure of the Web; that 61.74 per cent of Web pages use some form of scripting technology; that the size of the Web can be estimated at just over 5.2 billion pages; and that less than 7 per cent of Web pages fully comply with some variant of (X)HTML.