Genetic Programming for Smart Phone Personalisation

Personalisation in smart phones requires adaptability to dynamic context based on user mobility, application usage and sensor inputs. Current personalisation approaches, which rely on static logic that is developed a priori, do not provide sufficient adaptability to dynamic and unexpected context. This paper proposes genetic programming (GP), which can evolve program logic in realtime, as an online learning method to deal with the highly dynamic context in smart phone personalisation. We introduce the concept of collaborative smart phone personalisation through the GP Island Model, in order to exploit shared context among co-located phone users and reduce convergence time. We implement these concepts on real smartphones to demonstrate the capability of personalisation through GP and to explore the benefits of the Island Model. Our empirical evaluations on two example applications confirm that the Island Model can reduce convergence time by up to two-thirds over standalone GP personalisation.Comment: 43 pages, 11 figure

Delivering IoT Services in Smart Cities and Environmental Monitoring through Collective Awareness, Mobile Crowdsensing and Open Data

The Internet of Things (IoT) is the paradigm that allows us to interact with the real world by means of networking-enabled devices and convert physical phenomena into valuable digital knowledge. Such a rapidly evolving field leveraged the explosion of a number of technologies, standards and platforms. Consequently, different IoT ecosystems behave as closed islands and do not interoperate with each other, thus the potential of the number of connected objects in the world is far from being totally unleashed. Typically, research efforts in tackling such challenge tend to propose a new IoT platforms or standards, however, such solutions find obstacles in keeping up the pace at which the field is evolving. Our work is different, in that it originates from the following observation: in use cases that depend on common phenomena such as Smart Cities or environmental monitoring a lot of useful data for applications is already in place somewhere or devices capable of collecting such data are already deployed. For such scenarios, we propose and study the use of Collective Awareness Paradigms (CAP), which offload data collection to a crowd of participants. We bring three main contributions: we study the feasibility of using Open Data coming from heterogeneous sources, focusing particularly on crowdsourced and user-contributed data that has the drawback of being incomplete and we then propose a State-of-the-Art algorith that automatically classifies raw crowdsourced sensor data; we design a data collection framework that uses Mobile Crowdsensing (MCS) and puts the participants and the stakeholders in a coordinated interaction together with a distributed data collection algorithm that prevents the users from collecting too much or too less data; (3) we design a Service Oriented Architecture that constitutes a unique interface to the raw data collected through CAPs through their aggregation into ad-hoc services, moreover, we provide a prototype implementation

A review of the role of sensors in mobile context-aware recommendation systems

Recommendation systems are specialized in offering suggestions about specific items of different types (e.g., books, movies, restaurants, and hotels) that could be interesting for the user. They have attracted considerable research attention due to their benefits and also their commercial interest. Particularly, in recent years, the concept of context-aware recommendation system has appeared to emphasize the importance of considering the context of the situations in which the user is involved in order to provide more accurate recommendations. The detection of the context requires the use of sensors of different types, which measure different context variables. Despite the relevant role played by sensors in the development of context-aware recommendation systems, sensors and recommendation approaches are two fields usually studied independently. In this paper, we provide a survey on the use of sensors for recommendation systems. Our contribution can be seen from a double perspective. On the one hand, we overview existing techniques used to detect context factors that could be relevant for recommendation. On the other hand, we illustrate the interest of sensors by considering different recommendation use cases and scenarios

Geolocation of Internet hosts

Diplomová práce se zabývá metodami geolokace stanic v síti Internet, či-li odhadem geografické polohy neznámé stanice, která je do této sítě připojena. Úvodní část práce popisuje metody, které k určování pozice nepotřebují žádná měření v síti. Následující kapitola je věnována příčinám a místům vzniku zpoždění v Internetu, jejich typům a některým obvyklým hodnotám. Dále jsou uvedeny způsoby měření zpoždění a trasy, včetně několika nástrojů k tomu určených. Předposlední část popisuje některé vybrané geolokační techniky založené na měření RTT. Závěrečná kapitola se věnuje praktické ukázce geolokace za použití metody CBG, kdy měření zpoždění proběhlo v experimentální síti PlanetLab.This master thesis deals with methods of stations’ geolocation on the Internet, it means the estimation geographic location of unknown station, which is conected to this network. The introductory part describes the methods for determining position, which don‘t need any measeruments of the network. The next section is devoted to points, where delay is invoked, to the causes of latency in the Internet, to their types and some usual values. The following part features ways to measure delays and route, including several tools for this purpose. The penulminate section describes some chosen geolocation techniques based on RTT measurement. The final chapter is devoted to practical demonstration geolocation using the CBG method, when the delay measurement was carried out in an experimental PlanetLab network.

IP Geolocation in Metropolitan Areas

In this thesis, we propose a robust methodology to geolocate a target IP Address in a metropolitan area. We model the problem as a Pattern Recognition problem and present algorithms that can extract patterns and match them for inferring the geographic location of target's IP Address. The first algorithm is a relatively non-invasive method called Pattern Based Geolocation (PBG) which models the distribution of Round Trip Times (RTTs) to a target and matches them to that of the nearby landmarks to deduce the target's location. PBG builds Probability Mass Functions (PMFs) to model the distribution of RTTs. For comparing PMFs, we propose a novel `Shifted Symmetrized Divergence' distance metric which is a modified form of Kullback-Leibler divergence. It is symmetric as well as invariant to shifts. PBG algorithm works in almost stealth mode and leaves almost undetectable signature in network traffic. The second algorithm, Perturbation Augmented PBG (PAPBG), gives a higher resolution in the location estimate using additional perturbation traffic. The goal of this algorithm is to induce a stronger signature of background traffic in the vicinity of the target, and then detect it in the RTT sequences collected. At the cost of being intrusive, this algorithm improves the resolution of PBG by approximately 20-40%. We evaluate the performance of PBG and PAPBG on real data collected from 20 machines distributed over 700 square miles large Washington-Baltimore metropolitan area. We compare the performance of the proposed algorithms with existing measurement based geolocation techniques. Our experiments show that PBG shows marked improvements over current techniques and can geolocate a target IP address to within 2-4 miles of its actual location. And by sending an additional traffic in the network PAPBG improves the resolution to within 1-3 miles

Raising your arms towards branding: how Narta found its place in a mature market

The main purpose of this project is to understand how a brand can differentiate itself in a mature market, having as key drivers the Brand Experience and Brand Communication Management. In this case, these conceptual models will be applied to Garnier’s deodorant brand – Narta. Narta is a ten years old brand in Portugal of deodorants, sold in the mass-market circuit and with a flat performance in the last years. "What people really desire are not products but satisfying experiences" (Abbot, 1955). This quote highlights the increasing importance of experiencing a brand and how it can lead to a powerful and unique differentiation strategy. Regarding Brand Experience dimension, the constructs of parity and similarity will be analyzed and, in order to provide a strong differentiation, the Isomorphic Change Model will help us to guide the management of external and internal pressures that pushes into similarity and parity. At last, a brief look at the Herzberg’s motivational theory will be performed in order to fully understand the positive impact of a brand differentiation in the consumers’ satisfaction/dissatisfaction dichotomy. Communicating such difference will make a brand valuable and considered when the purchase act occurs. Matching the importance of the consumer journey with an Integrated Marketing Communication plan, Narta will be able to communicate its new positioning and enhance its performance. This study will not only take in consideration market insights from Nielsen but also shopper and consumer insights in both quantitative and qualitative ways from independent agencies. These studies will help to establish a proper conclusion about the brand’s perception and the brand’s competitiveness when comparing with other deodorants brands in Portugal. Hence, this project aims to diagnose the reason beyond the flat performance of Narta and implement a new positioning, expressed with the proper Marketing Communication Plan. Matching the theory with the reality of daily business will lead to a positive impact on Narta’s performance in the deodorant market, helping the brand to reach its fair position in awareness and image fields while leveraging its sales in this competitive and mature but huge market.O principal objetivo deste projeto é perceber como uma marca se consegue diferenciar num mercado maduro, tendo como principais vetores a Gestão da Experiência e da Comunicação da Marca. Neste caso, iremos aplicar os modelos conceptuais serão aplicados à marca de desodorizantes Narta, de Garnier. Narta é uma marca presente há dez anos em Portugal no segmento de desodorizantes, comercializada no circuito dos Produtos de Grande Consumo, mas com uma performance estável nos últimos anos. "O que as pessoas realmente desejam não são produtos, mas experiências que as satisfaçam" (Abbot, 1955). Esta citação sublinha a importância crescente da Experiência de Marca e como ela pode conduzir a uma estratégia de diferenciação. Considerando a Experiência de Marca, os conceitos de paridade e semelhança serão analisados e, de modo a tornar possível a diferenciação, o Modelo da Mudança Isomórfica irá permitir gerir as pressões internas e externas que conduzem à paridade e/ou à semelhança. Por último, realizaremos uma breve análise da teoria motivacional de Herzberg para perceber o impacto positivo da diferenciação da marca na dicotomia satisfação/dessatisfação dos consumidores. Comunicar tal diferença irá tornar a marca mais valiosa e considerada aquando do ato de compra. Combinando a importância do caminho do consumidor em direção à compra com um Plano de Comunicação Integrado, Narta será então capaz de comunicar o seu novo posicionamento e, por consequente, melhorar a sua performance. Este estudo terá em consideração não só dados de mercado providenciados pela Nielsen mas também dados de comprador e consumidor, quantitativos e qualitativos, providenciados por agências independentes. Estes estudos irão ajudar a inferir acerca da perceção e competitividade da marca, em comparação com as restantes marcas de desodorizantes em Portugal. Em jeito de conclusão, propomo-nos a diagnosticar as razões que estão por detrás da performance estável da marca Narta e implementar um novo posicionamento, comunicado com um plano de Comunicação Integrado próprio. Combinando a teoria com a realidade diária do negócio, o projeto irá criar um impacto positivo no desempenho de Narta permitindo que atinja a sua justa posição em termos de awareness e imagem e ao mesmo tempo incrementar as suas vendas neste competitivo, maduro, mas relevante mercado

Strategic knowledge creation through the analysis of the structure of the network formed by the participants of european R&D projects. Case of the emerging sector of renewable energies, at organizatio

321 p.La estrategia del Espacio Europeo de Investigación (ERA) tiene como objetivo aumentar el porcentaje de energías renovables en el mix energético hasta el 20% para el año 2020, impulsando este sector multidisciplinar y emergente. Existe la incertidumbre de crear consorcios de proyectos de I+D incluyendo colaboraciones ineficientes de transmisión de información y conocimiento entre los socios y las regiones locales. Esta tesis doctoral se centra en los proyectos europeos de I + D en los sectores de energía eólica, solar, marina, geotérmica y biomasa, para el período 2000 2013. El objetivo final de la tesis ha sido presentar el potencial de la técnica Análisis de Redes Sociales, para obtener conocimiento estratégico para la toma de decisiones de un sector tecnológico emergente y multidisciplinar. Para ello, se ha tomado como base la aplicabilidad de la teoría de redes sociales y la utilidad de la información que proporcionan los proyectos de I+D. Por un lado, muestra teóricamente el potencial de la información sobre proyectos para crear conocimiento estratégico a través de la aplicación integrada de los enfoques de centralidad y ¿structural hole¿ de Análisis de Redes Sociales. Por otro lado, aporta la creación de conocimiento estratégico en el sector de las energías renovables en Europa, proporcionando conocimiento de valor añadido en base a la eficiencia sobre las organizaciones y regiones locales participantes en estos proyectos. Concluye en cómo influyen estos en el resto de actores de las redes de colaboración, quiénes son eficientes y quiénes tienen un rol facilitador de cohesión de la red de transferencia de información y conocimiento adquirido a través de los proyectos I&D, aplicable a cualquier sector, normalmente subvencionados por organismos públicos cuando son sectores emergentes. Este estudio constituye una novedosa contribución, siendo una herramienta complementaria a los estudios de patentes y publicaciones que los responsables políticos deben considerar al invertir en proyectos públicos de I+D, para construir ERA eficientemente