The development of an eBook for teaching and learning mathematics

Mobile devices, smartphones, phablets and tablets, are widely avail‐ able. This is a generation of digital natives. We cannot ignore that they are no longer the same students for which the education system was designed tradition‐ ally. Studying math is many times a cumbersome task. But this can be changed if the teacher takes advantage of the technology that is currently available. We are working in the use of different tools to extend the classroom in a blended learning model. In this paper, it is presented the development of an eBook for teaching mathematics to secondary students. It is developed with the free and open standard EPUB 3 that is available for Android and iOS platforms. This specification supports video embedded in the eBook. In this paper it is shown how to take advantage of this feature, making videos available about lectures and problems resolutions, which is especially interesting for learning mathematics.

Kinematics and Local Motion Planning for Quasi-static Whole-body Mobile Manipulation

This thesis studies mobile robotic manipulators, where one or more robot manipulator arms are integrated with a mobile robotic base. The base could be a wheeled or tracked vehicle, or it might be a multi-limbed locomotor. As robots are increasingly deployed in complex and unstructured environments, the need for mobile manipulation increases. Mobile robotic assistants have the potential to revolutionize human lives in a large variety of settings including home, industrial and outdoor environments.

Mobile Manipulation is the use or study of such mobile robots as they interact with physical objects in their environment. As compared to fixed base manipulators, mobile manipulators can take advantage of the base mechanism’s added degrees of freedom in the task planning and execution process. But their use also poses new problems in the analysis and control of base system stability, and the planning of coordinated base and arm motions. For mobile manipulators to be successfully and efficiently used, a thorough understanding of their kinematics, stability, and capabilities is required. Moreover, because mobile manipulators typically possess a large number of actuators, new and efficient methods to coordinate their large numbers of degrees of freedom are needed to make them practically deployable. This thesis develops new kinematic and stability analyses of mobile manipulation, and new algorithms to efficiently plan their motions.

I first develop detailed and novel descriptions of the kinematics governing the operation of multi- limbed legged robots working in the presence of gravity, and whose limbs may also be simultaneously used for manipulation. The fundamental stance constraint that arises from simple assumptions about friction and the ground contact and feasible motions is derived. Thereafter, a local relationship between joint motions and motions of the robot abdomen and reaching limbs is developed. Baseeon these relationships, one can define and analyze local kinematic qualities including limberness, wrench resistance and local dexterity. While previous researchers have noted the similarity between multi- fingered grasping and quasi-static manipulation, this thesis makes explicit connections between these two problems.

The kinematic expressions form the basis for a local motion planning problem that that determines the joint motions to achieve several simultaneous objectives while maintaining stance stability in the presence of gravity. This problem is translated into a convex quadratic program entitled the balanced priority solution, whose existence and uniqueness properties are developed. This problem is related in spirit to the classical redundancy resoxlution and task-priority approaches. With some simple modifications, this local planning and optimization problem can be extended to handle a large variety of goals and constraints that arise in mobile-manipulation. This local planning problem applies readily to other mobile bases including wheeled and articulated bases. This thesis describes the use of the local planning techniques to generate global plans, as well as for use within a feedback loop. The work in this thesis is motivated in part by many practical tasks involving the Surrogate and RoboSimian robots at NASA/JPL, and a large number of examples involving the two robots, both real and simulated, are provided.

Finally, this thesis provides an analysis of simultaneous force and motion control for multi- limbed legged robots. Starting with a classical linear stiffness relationship, an analysis of this problem for multiple point contacts is described. The local velocity planning problem is extended to include generation of forces, as well as to maintain stability using force-feedback. This thesis also provides a concise, novel definition of static stability, and proves some conditions under which it is satisfied.

Music Learning Tools for Android Devices

In this paper, a musical learning application for mobile devices is presented. The main objective is to design and develop an application capable of offering exercises to practice and improve a selection of music skills, to users interested in music learning and training. The selected music skills are rhythm, melodic dictation and singing. The application includes an audio signal analysis system implemented making use of the Goertzel algorithm which is employed in singing exercises to check if the user sings the right musical note. This application also includes a graphical interface to represent musical symbols. A set of tests were conducted to check the usefulness of the application as musical learning tool. A group of users with different music knowledge have tested the system and reported to have found it effective, easy and accessible.

Implementazione e analisi di algoritmi dinamici per trasmissione MPEG-DASH su client Android

Attualmente, la maggior parte dei dati che transitano sulla rete appartiene a contenuti multimediali. Più nello specifico, è lo Streaming Video ad avere la predominanza nella condivisione di Internet; vista la crescita che tale servizio ha subìto negli ultimi anni, si sono susseguiti diversi studi volti allo sviluppo di tecniche e metodologie che potessero migliorarlo. Una di queste è sicuramente l'Adaptive Video Streaming, tecnica utilizzata per garantire all'utente una buona Quality of Experience (QoE) mediante l'utilizzo dei cosiddetti "algoritmi di rate adaptation". Il lavoro svolto in questi studi si è voluto concentrare su due filoni distinti, ma allo stesso tempo confrontabili: la prima parte della tesi riguarda lo sviluppo e l'analisi di alcuni algoritmi di rate adaptation per DASH, mentre la seconda è relativa all'implementazione di un nuovo algoritmo che li possa affiancare, migliorando la QoE nel monitorare lo stato della connessione. Si è quindi dovuta implementare un'applicazione Android per lo streaming video, che fosse conforme allo standard MPEG-DASH e potesse fornire le informazioni di testing da utilizzare per le analisi. La tesi è suddivisa in quattro capitoli: il primo introduce l'argomento e definisce la terminologia necessaria alla comprensione degli studi; il secondo descrive alcuni dei lavori correlati allo streaming adattivo e introduce i due filoni principali della tesi, ovvero gli algoritmi di rate adaptation e la proposta di algoritmo per la selezione dinamica del segmento; il terzo presenta l'app SSDash, utilizzata come mezzo per le analisi sperimentali; infine, il quarto ed ultimo capitolo mostra i risultati delle analisi e le corrispondenti valutazioni.

iGrooving: A Generative Music Mobile Application for Runners

iGrooving is a generative music mobile application specifically designed for runners. The application’s foundation is a step-counter that is programmed using the iPhone’s built-in accelerometer. The runner’s steps generate the tempo of the performance by mapping each step to trigger a kick-drum sound file. Additionally, different sound files are triggered at specific step counts to generate the musical performance, allowing the runner a level of compositional autonomy. The sonic elements are chosen to promote a meditative aspect of running. iGrooving is conceived as a biofeedback-stimulated musical instrument and an environment for creating generative music processes with everyday technologies, inspiring us to rethink our everyday notions of musical performance as a shared experience. Isolation, dynamic changes, and music generation are detailed to show how iGrooving facilitates novel methods for music composition, performance and audience participation.

Dynamic Bayesian network for semantic place classification in mobile robotics

In this paper, the problem of semantic place categorization in mobile robotics is addressed by considering a time-based probabilistic approach called dynamic Bayesian mixture model (DBMM), which is an improved variation of the dynamic Bayesian network. More specifically, multi-class semantic classification is performed by a DBMM composed of a mixture of heterogeneous base classifiers, using geometrical features computed from 2D laserscanner data, where the sensor is mounted on-board a moving robot operating indoors. Besides its capability to combine different probabilistic classifiers, the DBMM approach also incorporates time-based (dynamic) inferences in the form of previous class-conditional probabilities and priors. Extensive experiments were carried out on publicly available benchmark datasets, highlighting the influence of the number of time-slices and the effect of additive smoothing on the classification performance of the proposed approach. Reported results, under different scenarios and conditions, show the effectiveness and competitive performance of the DBMM.

Integration of process planning and scheduling using mobile-agent based approach in a networked manufacturing environment

Effective and efficient implementation of intelligent and/or recently emerged networked manufacturing systems require an enterprise level integration. The networked manufacturing offers several advantages in the current competitive atmosphere by way to reduce, by shortening manufacturing cycle time and maintaining the production flexibility thereby achieving several feasible process plans. The first step in this direction is to integrate manufacturing functions such as process planning and scheduling for multi-jobs in a network based manufacturing system. It is difficult to determine a proper plan that meets conflicting objectives simultaneously. This paper describes a mobile-agent based negotiation approach to integrate manufacturing functions in a distributed manner; and its fundamental framework and functions are presented. Moreover, ontology has been constructed by using the Protégé software which possesses the flexibility to convert knowledge into Extensible Markup Language (XML) schema of Web Ontology Language (OWL) documents. The generated XML schemas have been used to transfer information throughout the manufacturing network for the intelligent interoperable integration of product data models and manufacturing resources. To validate the feasibility of the proposed approach, an illustrative example along with varied production environments that includes production demand fluctuations is presented and compared the proposed approach performance and its effectiveness with evolutionary algorithm based Hybrid Dynamic-DNA (HD-DNA) algorithm. The results show that the proposed scheme is very effective and reasonably acceptable for integration of manufacturing functions.

Plan de negocios Bicigo app

La gran cantidad de personas interesadas actualmente en cuidar de su salud por medio de la Bicicleta, es una tendencia que cada vez toma más fuerza y por esto, se tomara como ventaja que la ciudad de Bogotá con sus últimos alcaldes han decidió apoyar el uso de esta. Aplicación para realizar grupos de ciclistas y poder salir cualquier día de la semana acompañado de más personas por un tema de transporte pero también de ocio. El objetivo es que las personas que no utilizan la bicicleta por miedo a salir solos, puedan unirse a diferentes grupos y hacer bici paseos por la ciudad, también contemplamos el hecho de que existen personas que quieren montar bicicleta como aficionados, es decir que salen por la carreteras aledañas a la capital pero muchas veces no tienen grupo con quien rodar. Queremos para el año 2020, lograr ser una de las aplicaciones de Bicicletas más exitosa de la ciudadanía de Bogotá, siendo una de las aplicaciones que mas apoya el uso diario y deportivo de la bicicleta. Nuestra aplicación ofrece el servicio principalmente de reunir gente y hacer paseos con diferentes personas haciendo uso de las bicicletas, dentro de la ciudad como ocio y transporte se realizarían en la mañana y noches, pero así mismo realizar grupos para hacer uso de la bicicleta por carreteras, es decir más como modo profesional o aficionado. Nuestra aplicación cuenta con una interface para seleccionar el tipo de bici usuario y segundo por donde o a donde quiere dirigirse para así mismo mostrarle las rutas cercanas a él. Nuestra característica principal es la unión de diferentes grupos, personas y entidades para hacer uso de la Bicicleta, tenemos una plataforma interactiva y fácil de usar, tan fácil que cualquier persona que no esté inmersa en el mundo de los Smartphone o aplicaciones pueda aprender a usarla. Unas de las ventajas con las que cuento es que desde muy joven me ha gustado montar en bicicletas y es así como decido crear una aplicación ya que compañeros, familiares y conocidos no salían a montar bicicleta solo conmigo, preferían que fuese un grupo más grande. Así mismo cuento con 3 compañeros de la universidad Javeriana que son programadores y ellos me van a brindar apoyo con la programación de la aplicación, y una compañera cercana a mí que estudio diseño industrial y me brindara apoyo con el diseño e imagen corporativa de la aplicación. Cuento con planta física para ubicar la oficina de nuestra empresa. Esta aplicación va dirigida principalmente a los habitantes de la ciudad de Bogotá, interesados en el cuidado de su salud combinado con medio de transporte, y personas correspondientes al estrato 2 en adelante, ya que son las personas que normalmente hacen uso de la bicicleta o que son personas potenciales para empezar hacer uso de la bicicleta. . La ciudad de Bogotá cuenta con 8’037.732 habitantes y este proyecto va ser desarrollado en toda la ciudad, toca tener en cuenta que la ciudad esta mesclada entre la diferente estratificación, no dirigimos a los estratos 2 y 3 que tenga la posibilidad de tener su Bicicleta y un celular tipo Smartphone, para los estratos 4, 5 y 6 sabemos que tiene la facilidad de obtener una bicicleta y ellos son nuestro usuario potencial el cual generaríamos un cambio y tomarían su bicicleta para hacer ejercicio como ocio y como medio de transporte. En cuanto a la proyección financiera para la aplicación, como se mencionó anteriormente, contamos con una gran ventaja, ya que la inversión requerida será menor debido a la propiedad con la que cuento para llevar a cabo el proyecto. Una propiedad de 60 metros cuadrados para empezar, la cual cuenta con salas de reunión y auditorio, un parqueaderos exteriores. Al hacer la calculación se va tener en cuenta el pago de un arriendo sin importan que sea de nuestra propiedad y así poder evidenciar realmente como es el estado financiero y no subsidiarla. Por otro lado, la inversión en efectivo que se necesitara será aproximadamente de $100.000.000 que serán $50.000.000 de mis padres y el restante saldrán de mis ahorros, Javier Amortegui Babativa, los cuales serán distribuidos para adecuación de planta, equipos y sistemas $17.616.880, para publicidad y mercadeo: $30.000.000, creación de la aplicación $34.000.000, sistemas IOS + Android $421.600, Gastos de composición empresarial y bancarios $11.000.000 y por último se va tener un provisión para imprevistos por el restante $6.961.520. Nuestras proyecciones de ventas han sido basadas en aplicaciones similares con un mismo formato de lucro con el tema de bicicletas pero no con la misma idea de negocio, nuestras proyecciones de ventas estimadas serán de $20.000.000 a $25.000.000 los primeros 3 meses, mientras tomamos fuerza en el mercado.

Aplicativos Android para agricultura: benefícios do desenvolvimento em parceria com o usuário.

RESUMO - Com a popularização de tablets e smartphones e as peculiaridades do desenvolvimento de aplicativos para esses dispositivos, surge a necessidade de adaptar os métodos de avaliação de usabilidade para resultados mais precisos. Este trabalho propõe o método Coldemob para validação de interfaces de aplicativos móveis com a participação de representantes do usuário final, com uma etapa presencial e uma etapa remota após o lançamento do aplicativo, detalhando a aplicação da segunda etapa. O método foi testado com um aplicativo do domínio agrícola e os resultados mostraram que ao incluir o usuário no processo de construção do aplicativo, a compreensão dos desenvolvedores acerca do domínio aumentou. A etapa remota se mostrou complementar à presencial, possibilitando um maior número de problemas identificados.

Design and implementation of a Reinforcement Learning framework for iOS devices

Reinforcement Learning is an increasingly popular area of Artificial Intelligence. The applications of this learning paradigm are many, but its application in mobile computing is in its infancy. This study aims to provide an overview of current Reinforcement Learning applications on mobile devices, as well as to introduce a new framework for iOS devices: Swift-RL Lib. This new Swift package allows developers to easily support and integrate two of the most common RL algorithms, Q-Learning and Deep Q-Network, in a fully customizable environment. All processes are performed on the device, without any need for remote computation. The framework was tested in different settings and evaluated through several use cases. Through an in-depth performance analysis, we show that the platform provides effective and efficient support for Reinforcement Learning for mobile applications.

Applying machine learning: a multi-role perspective

Machine (and deep) learning technologies are more and more present in several fields. It is undeniable that many aspects of our society are empowered by such technologies: web searches, content filtering on social networks, recommendations on e-commerce websites, mobile applications, etc., in addition to academic research. Moreover, mobile devices and internet sites, e.g., social networks, support the collection and sharing of information in real time. The pervasive deployment of the aforementioned technological instruments, both hardware and software, has led to the production of huge amounts of data. Such data has become more and more unmanageable, posing challenges to conventional computing platforms, and paving the way to the development and widespread use of the machine and deep learning. Nevertheless, machine learning is not only a technology. Given a task, machine learning is a way of proceeding (a way of thinking), and as such can be approached from different perspectives (points of view). This, in particular, will be the focus of this research. The entire work concentrates on machine learning, starting from different sources of data, e.g., signals and images, applied to different domains, e.g., Sport Science and Social History, and analyzed from different perspectives: from a non-data scientist point of view through tools and platforms; setting a problem stage from scratch; implementing an effective application for classification tasks; improving user interface experience through Data Visualization and eXtended Reality. In essence, not only in a quantitative task, not only in a scientific environment, and not only from a data-scientist perspective, machine (and deep) learning can do the difference.

Integrated communication and learning towards autonomous mobile radio networks

The integration of distributed and ubiquitous intelligence has emerged over the last years as the mainspring of transformative advancements in mobile radio networks. As we approach the era of “mobile for intelligence”, next-generation wireless networks are poised to undergo significant and profound changes. Notably, the overarching challenge that lies ahead is the development and implementation of integrated communication and learning mechanisms that will enable the realization of autonomous mobile radio networks. The ultimate pursuit of eliminating human-in-the-loop constitutes an ambitious challenge, necessitating a meticulous delineation of the fundamental characteristics that artificial intelligence (AI) should possess to effectively achieve this objective. This challenge represents a paradigm shift in the design, deployment, and operation of wireless networks, where conventional, static configurations give way to dynamic, adaptive, and AI-native systems capable of self-optimization, self-sustainment, and learning. This thesis aims to provide a comprehensive exploration of the fundamental principles and practical approaches required to create autonomous mobile radio networks that seamlessly integrate communication and learning components. The first chapter of this thesis introduces the notion of Predictive Quality of Service (PQoS) and adaptive optimization and expands upon the challenge to achieve adaptable, reliable, and robust network performance in dynamic and ever-changing environments. The subsequent chapter delves into the revolutionary role of generative AI in shaping next-generation autonomous networks. This chapter emphasizes achieving trustworthy uncertainty-aware generation processes with the use of approximate Bayesian methods and aims to show how generative AI can improve generalization while reducing data communication costs. Finally, the thesis embarks on the topic of distributed learning over wireless networks. Distributed learning and its declinations, including multi-agent reinforcement learning systems and federated learning, have the potential to meet the scalability demands of modern data-driven applications, enabling efficient and collaborative model training across dynamic scenarios while ensuring data privacy and reducing communication overhead.

Power sharing e controllo modulare di macchine elettriche multi-trifase

La costante ricerca e lo sviluppo nel campo degli azionamenti e dei motori elettrici hanno portato ad una loro sempre maggiore applicazione ed utilizzo. Tuttavia, la crescente esigenza di sistemi ad alta potenza sempre più performanti da una parte ha evidenziato i limiti di certe soluzioni, dall’altra l’affermarsi di altre. In questi sistemi, infatti, la macchina elettrica trifase non rappresenta più l’unica soluzione possibile: negli ultimi anni si è assistito ad una sempre maggiore diffusione di macchine elettriche multifase. Grazie alle maggiori potenzialità che sono in grado di offrire, per quanto alcune di queste siano ancora sconosciute, risultano già essere una valida alternativa rispetto alla tradizionale controparte trifase. Sicuramente però, fra le varie architetture multifase, quelle multi-trifase (ovvero quelle con un numero di fasi multiplo di tre) rappresentano una soluzione particolarmente vantaggiosa in ambito industriale. Infatti, se impiegate all’interno di architetture multifase, la profonda conoscenza dei tradizionali sistemi trifase consente di ridurre i costi ed i tempi legati alla loro progettazione. In questo elaborato la macchina elettrica multi-trifase analizzata è una macchina sincrona esafase con rotore a magneti permanenti superficiali. Questa particolare tipologia di macchina elettrica può essere modellizzata attraverso due approcci completamente differenti: uno esafase ed uno doppio trifase. Queste possibilità hanno portato molti ricercatori alla ricerca della migliore strategia di controllo per questa macchina. L’obiettivo di questa tesi è di effettuare un’analisi comparativa tra tre diverse strategie di controllo applicate alla stessa macchina elettrica multi-trifase, analizzandone la risposta dinamica in diverse condizioni di funzionamento.

MySafePlace: un'applicazione per sentirsi al sicuro

La Tesi descrive un'applicazione per la sicurezza della persona che vuol essere un trampolino di lancio per innovare questo mercato ampio ma a molti sconosciuto. La principale innovazione è la chiamata random che permette ad un utente di avere la possibilità di poter parlare con un altro utente che utilizza, come lui, l'applicazione. L'applicazione è stata sviluppata come tesi per Laboratorio di applicazioni mobili ed è scritta in linguaggio swift per dispositivi iOS a partire dalla versione 15

PickingList App: progettazione ed implementazione di un’applicazione mobile per magazzini ospedalieri

Questo documento illustra la progettazione e lo sviluppo di un’applicazione Android in ambito aziendale. L’idea è stata concepita dall’azienda Vettore Rinascimento, la quale richiesta era d’implementare un’applicazione per la gestione di liste di prelievo in magazzini di strutture mediche. Lo scopo è di rendere il lavoro manuale più efficiente e affidabile aumentando così le prestazioni dei dipendenti. La tesi analizza le fasi tipiche di sviluppo di un software ovvero: l’analisi dei requisiti, la progettazione, la realizzazione e il collaudo. Durante ciascuna fase saranno analizzate anche le scelte progettuali e implementative. La discussione non si limiterà al solo sviluppo di un’applicazione mobile: siccome il prodotto sviluppato non sarà un software stand-alone, verrà anche spiegato il funzionamento del server preesistente e dello sviluppo di un’api per caricare e salvare i dati. Si presenterà inoltre il prodotto finale con tutte le sue features, alcune delle più interessanti sono la sua capacità di funzionare sia online che offline, di adattarsi a ogni tipo di magazzino, previa configurazione, e di poter scannerizzare i codici a barre degli articoli da prelevare con la fotocamera del dispositivo.