Drivers and barriers to digital television adoption in Portugal: the perspectives of the TV viewers and other main stakeholders

To understand what are the most significant factors for digital TV adoption by the Portuguese population in the switchover context is the main goal of the research project here presented. In April 26, 2012, the analogue terrestrial television switchoff is planned to occur in Portugal, according to the schedule published by the national telecommunication regulator Anacom. Digital terrestrial TV was launched in the country in April 2009, making Portugal one of the countries with a more ambitious schedule – or risky, depending on the perspective - for the full transition from analogue to digital terrestrial television. In this paper we will start by presenting the research project’s objectives, theoretical framework and research design. Next, we will present first results of the project focused on the barriers and drivers to digital TV adoption from two of the empirical studies which integrate it, namely, the quantitative inquiry administered to a representative sample of the Portuguese population and interviews with main stakeholders in the area of digital TV in Portugal. The perspectives of the television viewers are compared with other main stakeholders in this process. The paper will be concluded with a brief discussion of these results and a brief enumeration of next steps for the project.

Evolving graphs: dynamical models, inverse problems and propagation

Applications such as neuroscience, telecommunication, online social networking, transport and retail trading give rise to connectivity patterns that change over time. In this work, we address the resulting need for network models and computational algorithms that deal with dynamic links. We introduce a new class of evolving range-dependent random graphs that gives a tractable framework for modelling and simulation. We develop a spectral algorithm for calibrating a set of edge ranges from a sequence of network snapshots and give a proof of principle illustration on some neuroscience data. We also show how the model can be used computationally and analytically to investigate the scenario where an evolutionary process, such as an epidemic, takes place on an evolving network. This allows us to study the cumulative effect of two distinct types of dynamics.

Modeling the effects of node heterogeneity on the performance of a real grid application

The performance benefit when using Grid systems comes from different strategies, among which partitioning the applications into parallel tasks is the most important. However, in most cases the enhancement coming from partitioning is smoothed by the effect of the synchronization overhead, mainly due to the high variability of completion times of the different tasks, which, in turn, is due to the large heterogeneity of Grid nodes. For this reason, it is important to have models which capture the performance of such systems. In this paper we describe a queueing-network-based performance model able to accurately analyze Grid architectures, and we use the model to study a real parallel application executed in a Grid. The proposed model improves the classical modelling techniques and highlights the impact of resource heterogeneity and network latency on the application performance.

Handling single node failures using agents in computer clusters

The work reported in this paper is motivated towards handling single node failures for parallel summation algorithms in computer clusters. An agent based approach is proposed in which a task to be executed is decomposed to sub-tasks and mapped onto agents that traverse computing nodes. The agents intercommunicate across computing nodes to share information during the event of a predicted node failure. Two single node failure scenarios are considered. The Message Passing Interface is employed for implementing the proposed approach. Quantitative results obtained from experiments reveal that the agent based approach can handle failures more efficiently than traditional failure handling approaches.

Bistability through triadic closure

We propose and analyse a class of evolving network models suitable for describing a dynamic topological structure. Applications include telecommunication, on-line social behaviour and information processing in neuroscience. We model the evolving network as a discrete time Markov chain, and study a very general framework where, conditioned on the current state, edges appear or disappear independently at the next timestep. We show how to exploit symmetries in the microscopic, localized rules in order to obtain conjugate classes of random graphs that simplify analysis and calibration of a model. Further, we develop a mean field theory for describing network evolution. For a simple but realistic scenario incorporating the triadic closure effect that has been empirically observed by social scientists (friends of friends tend to become friends), the mean field theory predicts bistable dynamics, and computational results confirm this prediction. We also discuss the calibration issue for a set of real cell phone data, and find support for a stratified model, where individuals are assigned to one of two distinct groups having different within-group and across-group dynamics.

An overview of the use of neural networks for data mining tasks

In the recent years, the area of data mining has been experiencing considerable demand for technologies that extract knowledge from large and complex data sources. There has been substantial commercial interest as well as active research in the area that aim to develop new and improved approaches for extracting information, relationships, and patterns from large datasets. Artificial neural networks (NNs) are popular biologically-inspired intelligent methodologies, whose classification, prediction, and pattern recognition capabilities have been utilized successfully in many areas, including science, engineering, medicine, business, banking, telecommunication, and many other fields. This paper highlights from a data mining perspective the implementation of NN, using supervised and unsupervised learning, for pattern recognition, classification, prediction, and cluster analysis, and focuses the discussion on their usage in bioinformatics and financial data analysis tasks. © 2012 Wiley Periodicals, Inc.

Grid job scheduling using Route with Genetic Algorithm support

In 2006 the Route load balancing algorithm was proposed and compared to other techniques aiming at optimizing the process allocation in grid environments. This algorithm schedules tasks of parallel applications considering computer neighborhoods (where the distance is defined by the network latency). Route presents good results for large environments, although there are cases where neighbors do not have an enough computational capacity nor communication system capable of serving the application. In those situations the Route migrates tasks until they stabilize in a grid area with enough resources. This migration may take long time what reduces the overall performance. In order to improve such stabilization time, this paper proposes RouteGA (Route with Genetic Algorithm support) which considers historical information on parallel application behavior and also the computer capacities and load to optimize the scheduling. This information is extracted by using monitors and summarized in a knowledge base used to quantify the occupation of tasks. Afterwards, such information is used to parameterize a genetic algorithm responsible for optimizing the task allocation. Results confirm that RouteGA outperforms the load balancing carried out by the original Route, which had previously outperformed others scheduling algorithms from literature.

The use of colloidal ferrofluid as building blocks for nanostructured layer-by-layer films fabrication

The electrostatic layer-by-layer technique has been exploited as an useful strategy for fabrication of nanostructured thin films, in which specific properties can be controlled at the molecular level. Ferrofluids consist of a colloidal suspension of magnetic grains (with only a few nanometers of diameter) with present interesting physical properties and applications, ranging from telecommunication to drug delivery systems. In this article, we developed a new strategy to manipulate ferrofluids upon their immobilization in nanostructured layered films in conjunction with conventional polyelectrolytes using the layer-by-layer technique. We investigated the morphological, optical, and magnetic properties of the immobilized ferrofluid as a function of number of bilayers presented in the films. Ferrofluid/polyelectrolyte multilayers homogeneously covered the substrates surface, and the magnetic and optical properties of films exhibited a linear dependence on the number of bilayers adsorbed.

Improved voice activity detection algorithm using wavelet and support vector machine

This paper proposes an improved voice activity detection (VAD) algorithm using wavelet and support vector machine (SVM) for European Telecommunication Standards Institution (ETS1) adaptive multi-rate (AMR) narrow-band (NB) and wide-band (WB) speech codecs. First, based on the wavelet transform, the original IIR filter bank and pitch/tone detector are implemented, respectively, via the wavelet filter bank and the wavelet-based pitch/tone detection algorithm. The wavelet filter bank can divide input speech signal into several frequency bands so that the signal power level at each sub-band can be calculated. In addition, the background noise level can be estimated in each sub-band by using the wavelet de-noising method. The wavelet filter bank is also derived to detect correlated complex signals like music. Then the proposed algorithm can apply SVM to train an optimized non-linear VAD decision rule involving the sub-band power, noise level, pitch period, tone flag, and complex signals warning flag of input speech signals. By the use of the trained SVM, the proposed VAD algorithm can produce more accurate detection results. Various experimental results carried out from the Aurora speech database with different noise conditions show that the proposed algorithm gives considerable VAD performances superior to the AMR-NB VAD Options 1 and 2, and AMR-WB VAD. (C) 2009 Elsevier Ltd. All rights reserved.

Grafisk profilering och identitetsskapande

This degree project has been done in parallel to the advertising agency Hera in Uppsala, and containsthe creating of a logotype and graphic profile for Aircall, a new big chain of shops dealing with telecommunication.Aircall was found 1 February 2004, when three smaller companies became one. Thisnew company were in need of a common brand and a uniform profile. The created graphic profile hasbeen applied to visiting cards, letterhead, envelopes, letter cards, bags, cars and advertisement. Thegraphic profile has also been used when designing the shop interior end exterior. Research has beendone on competitors graphic profiles and advertisement. The project also contains a deepening in corporateidentity.

Analysis of EnterpriseVoIP Traffic from aWire line IMS System

With the rapid development of telecommunication industry, the IP multimedia Subsystem (IMS) could very well be the panacea for most telecom operators. It is originally defined as the core network for 3G mobile systems by the 3rd Generation Partnership Project (3GPP), the more recent development is merging between fixed line network and wireless networkd This report researchs the characteristic of the IMS data and proposes an IMS characterization analysis. We captured the IMS traffic data with 10 tousands users for about 41 hours. By analyzing the characteristics of the IMS, we know that the most important application in the IMS is VoIP call. Then we use the tool designed by Tsinghua University & Ericsson Company to recognize the data, and the results we got can be used to build the traffic models. From the results of the traffic models, I will get some reasons and conclusion. The traffic model gives out the types of session and types of VoIP call. I bring into a concept—busy hour. This concept is very important because it can help us to know which period is the peak of the VoIP call. The busy hour is from 10:00 to 11:00 in the morning. I also bring into another concept—connection ratio. This concept is significant because it can evaluate whether the VoIP call is good when it use IMS network. By comparing the traffic model with other one’s models, we found the different results from them, both the accuracy and the busy hour. From the contract, we got the advantages of our traffic models.

An Analysis of the Telecommunications Business in China by Linear Regression

In this paper, we study the influence of the National Telecom Business Volume by the data in 2008 that have been published in China Statistical Yearbook of Statistics. We illustrate the procedure of modeling “National Telecom Business Volume” on the following eight variables, GDP, Consumption Levels, Retail Sales of Social Consumer Goods Total Renovation Investment, the Local Telephone Exchange Capacity, Mobile Telephone Exchange Capacity, Mobile Phone End Users, and the Local Telephone End Users. The testing of heteroscedasticity and multicollinearity for model evaluation is included. We also consider AIC and BIC criterion to select independent variables, and conclude the result of the factors which are the optimal regression model for the amount of telecommunications business and the relation between independent variables and dependent variable. Based on the final results, we propose several recommendations about how to improve telecommunication services and promote the economic development.

Förutsättningar för distanskommunikation mellan reklambyråer och kunder : En intervju- och enkätundersökning

Små reklambyråer har, i skuggan av den ekonomiska krisen, fått konkurrens om sina kunder av större reklambyråer och tryckerier. En lösning kan vara att skapa relationer till företag utanför närområdet. Internetbaserade verktyg för distanskommunikation skulle i sådana fall kunna erbjuda ett bra komplement till det fysiska mötet. Distanskommunikation är effektivt eftersom det bland annat ger minskad tidsåtgång för möten och minskade resekostnader. Denna typ av kommunikation kan dock innebära större risk för missförstånd, och färre tillfällen att bygga en personlig relation till kunden. Användningen av internetbaserade verktyg för att kommunicera på distans förväntas dock bli allt vanligare i framtiden, i takt med att utbudet av kommunikationsverktyg ökar. Huvudmålet med denna studie har därför varit att undersöka förutsättningarna för distanskommunikation mellan reklambyrå och kund. Syftet har varit att ta reda på hur för- och nackdelar med distanskommunikation värderas av respektive parter, samt vilket kommunikationssätt som de anser lämpar sig bäst vid olika arbetssteg. Detta undersöktes genom enkätundersökning till utvalda företag samt intervjuer med fyra mindre reklambyråer i Dalarna. Studiens resultat, visade tydligt att det personliga mötet är mycket viktigt, och att det inte kan ersättas av någon form av distanskommunikation. Däremot ansåg både företag och reklambyråer att verktyg för distanskommunikation kan användas vid arbetsmöten.