983 resultados para unified framework


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RESUMO: Os circuitos fronto-estriatais constituem um sistema em ansa fechada que une diversas regiões do lobo frontal aos gânglios da base, participando, com outras áreas cerebrais, no controlo do movimento, cognição e comportamento. As Distonias Primárias, a Doença de Parkinson e a Hidrocefalia de Pressão Normal, são doenças do movimento caracterizadas por disfunção do circuito fronto-estriatal motor. A conectividade funcional entre as diversas ansas do sistema fronto-estriatal, permite prever que as doenças do movimento possam também acompanhar-se de sintomas da esfera cognitiva e comportamental, cuja avaliação seria importante no manejo diagnóstico e terapêutico dos doentes. Objectivos Os nossos objectivos foram avaliar, por estudos clínicos, a relação entre sintomas motores, cognitivos e comportamentais em três doenças do movimento com fisiopatologias diversas - distonias Primárias, Doença de Parkinson e Hidrocefalia de Pressão Normal - analisando os dados sob a perspectiva teórica fornecida pelo conhecimentos dos vários circuitos frontoestriatais. Os nossos objectivos específicos para cada doença foram: a) Distonias Primárias: avaliação de disfunção executiva em doentes com Distonia Primária e relação com a gravidade dos sintomas motores b) Doença de Parkinson: 1. avaliação breve das funções mentais nas fases iniciais da doença, incluindo análise longitudinal para determinação de factores preditivos para declínio cognitivo; 2. relação entre a função motora e cognitiva e a Perturbação do Comportamento do sono REM, incluindo análise longitudinal; 3.avaliação de sintomas psiquiátricos, de um ponto de vista global e especificamente com incidência sobre as Perturbações do Controlo do Impulso (PCI). c) Hidrocefalia de Pressão Normal: 1. caracterização das alterações da marcha, incluindo comparação com a Doença de Parkinson; 2. caracterização das alterações cognitivas e da relação entre estas e a disfunção da marcha; 3. estudo evolutivo das alterações da marcha e cognitiva em doentes submetido a cirurgia e doentes não submetidos a cirurgia. Métodos: A Distonia Primária, a Doença de Parkinson e a Hidrocefalia de Pressão Normal foram diagnosticadas segundo critérios clínicos validados. Sempre que justificado, foram recrutados grupos de controlo, com indivíduos sem doença, emparelhados para idade, sexo e grau de escolaridade. Os doentes foram avaliados com instrumentos de aplicação clinica directa, incluindo escalas de função motora, testes neuropsicológicos globais e dirigidos às funções executivas e escalas de avaliação psiquiátrica. Testes aplicados nas Distonias Primárias: Unified Dystonia Rating Scale, Wisconsin Card Sorting Test, teste de Stroop, teste de cubos da WAIS, Teste de Retenção Visual de Benton; na Doença de Parkinson: Unified Parkinson's Disease Rating Scale, Frontal Assessment Battery (FAB), Mini-Mental State Examination (MMSE), REM-sleep behaviour disorder Questionnaire; Symptom Chek-list 90-R, Brief Psychiatric Rating Scale, FAS (fluência verbal lexical) Nomeação de Animais (Fluência verbal semântica), prova de repetição de dígitos (WAIS), Rey auditory verbal learning test, teste de Stroop, matrizes progressivas de Raven, Questionnaire for Impulsive-Compulsive Disorders; na HPN: prova cronometrada de marcha,MMSE, prova de memória imediata da WAIS, prova de repetição de dígitos (WAIS), FAB, desenho complexo de Rey, teste de Stroop, cancelamento de letras, teste Grooved Pegboard. Os doentes com HPN foram também submetidos a estudo imagiológico. A avaliação estatística foi adaptada às características de cada um dos estudos.Resultados Distonias Primárias: encontrámos défices de função executiva, envolvendo dificuldade na mudança entre sets cognitivos, bem como correlação significativa entre as pontuações nos testes cronometrados e a gravidade dos sintomas motores. Doença de Parkinson: os doentes com DP obtiveram pontuações significativamente inferiores na FAB e em sub-testes do MMSE (memória e função visuo-espacial). A pontuação no MMSE encontrava-se significativamente correlacionada com itens da função motora não relacionados com o tremor. A disfunção da marcha, a disartria, o fenótipo não tremorígeno, a presença de alucinações e pontuação abaixo do ponto de corte na MMSE, foram factores preditivos de demência na avaliação longitudinal. A rigidez e a disartria foram factores preditivos de declínio nas funções frontais. A disfunção frontal foi factor preditivo de declínio na pontuação do MMSE. Encontrámos uma prevalência elevada de RBD nas fases iniciais da DP, que o estudo longitudinal mostrou ser factor preditivo de declínio motor, nomeadamente por agravamento da bradicinésia. Encontrámos também uma prevalência elevada de sintomas psiquiátricos, nomeadamente psicose, depressão, ansiedade, somatização e sintomas obsessivo-compulsivos. As PCI não se encontravam relacionadas com o fenótipo motor, com as complicações motoras do tratamento dopaminérgico ou com a disfunção cognitiva. HPN: os doentes com HPN e os DP apresentaram um padrão disfunção da marcha semelhante, caraterizado por passos curtos, lentidão e dificuldades de equilíbrio, sendo os sintomas mais graves na HPN. Os doentes de Parkinson com maior duração de doença, maior dose de dopaminérgicos e fenótipo motor acinético-rígido apresentaram um padrão de disfunção da marcha de gravidade semelhante ao encontrado na HPN. As alterações vasculares da substância branca, em particular as encontradas na região frontal, encontravam-se negativamente correlacionadas com a melhoria da marcha após PL. O estudo das funções cognitivas mostrou um padrão de atingimento global, com valores mais baixos na cópia do desenho complexo de Rey. Os resultados nas provas de função cognitiva não se encontravam significativamente correlacionados com os resultados na prova da marcha. A progressão na disfunção da marcha encontrava-se relacionada com o tratamento não cirúrgico, idade superior na primeira avaliação, presença de lesões da substância branca, e presença de factores de risco vascular, ao passo que não foram encontrados factores que predissessem de modo significativo o agravamento da função cognitiva. Conclusões: Os resultados dos diversos estudos, evidenciam a presença de alterações cognitivas e comportamentais nas três doenças de movimento. O padrão destas alterações e o modo como estas se relacionaram com os sintomas motores variou de doença para doença. Nas Distonias primárias, a perseveração cognitiva poderá ser o sintoma correspondente à perseveração motora própria da doença, sugerindo disfunção no circuito dorso-lateral frontoestriatal. A correlação entre a gravidade motora da doença e o resultado nos testes cognitivos cronometrados, poderá ser o efeito da relação entre bradicinésia e bradifrenia. Na Doença de Parkinson, o espectro de alterações é mais acentuado, espelhando a disseminação do processo degenerativo no SNC. Para além dos sintomas de disfunção executiva, sugerindo disfunção das tês ansas não motoras, existem sinais de disfunção cognitiva global, estas com uma influência mais significativa no desenvolvimento da demência. A relação entre os diferentes sintomas motores e cognitivos é também complexa, embora se evidencie uma dissociação significativa entre o tremor, sem relação com os sintomas não motores, e os sintomas motores não tremorígenos, relacionados com o declínio cognitivo. Enquanto que a presença de RBD parece ser um factor preditivo de agravamento motor, os sintomas psiquiátricos, também muito frequentes, apresentam uma relação menos clara com a função motora. Destes, os sintomas obsessivo-compulsivos são aqueles que com mais frequência se atribuem a disfunção do sistema fronto-estriatal, nomeadamente da ansa orbito-frontal. As PCI também não mostraram ter relação com os sintomas motores ou cognitivos. Na HPN, é patente o carácter fronto-estriatal das alterações da marcha, demonstrado tanto na sua caracterização quanto no efeito deletério das lesões vasculares da substância branca do lobo frontal na recuperação da marcha após PL. As alterações cognitivas parecem ter um padrão mais difuso, o que talvez explique a falta de correlação com os sintomas motores - esta dissociação pode ser causada quer por diferença nos mecanismos fisiopatológicos quer por presença de comorbilidades cognitivas. --------- ABSTRACT: Fronto-striatal circuits constitute a closed loop system which connects different parts of the frontal lobes to the basal ganglia. They are engaged in motor, cognitive and behavioural control. Primary Dystonia, Parkinson's Disease and Normal-Pressure Hydrocephalus are movement disorders caused by disturbance of the motor fronto-striatal circuit. The existence of cognitive and behavioural dysfunction in these movement disorders is predictable, given the functional connectivity between the several distinct loops of the circuit. Evaluation of cognitive and behavioural dysfunction in these three disorders is thus both of clinical and theoretical relevance. Objectives Our objectives were to evaluate, by clinical means, the relation between motor, cognitive and behavioural symptoms in three movement disorders with different pathophysiological backgrounds - Primary Dystonia, Parkinson's Disease and Normal-Pressure Hydrocephalus - and to analyse the study results under the theoretical framework formed by present knowledge of the fronto-estriatal system. Specific objectives: a) Primary Dystonia: executive dysfunction assessment and correlation analysis with motor dysfunction severity; b) Parkinson's Disease: 1. brief cognitive assessment in the early stages of disease, including a longitudinal analysis for determination of predictive factors for cognitive decline; 2. to investigate the relation between RBD and cognitive and motor dysfunction, including a longitudinal analysis; 3. psychiatric symptom assessment, with particular incidence on Impulse Control Disorders; c) Normal-Pressure Hydrocephalus: 1. gait dysfunction characterization and comparison with Parkinson's Disease patients; 2. determination of cognitive dysfunction profile and its relation with gait dysfunction; 3. follow-up study of cognitive and motor outcome in patients submitted and not submitted to shunt surgery. Methods: Primary Dystonia, Parkinson's Disease and Normal Pressure Hydrocephalus were diagnosed according to clinically validate criteria. Where warranted, we recruited control groups formed by healthy individuals, matched for age, sex and educational level. Patients were evaluated with instruments of direct clinical application, including motor function scales, neuropsychological tests aimed at global and executive functions and psychiatric rating scales. Tests used in Primary Dystonia: Unified Dystonia Rating Scale, Wisconsin Card Sorting Test, Stroop Test, Cube Assembly test (WAIS), Benton’s Visual Retention Test; in Parkinson's Disease: Unified Parkinson's Disease Rating Scale, Frontal Assessment Battery (FAB) , Mini-mental State Examination (MMSE), REM-sleep behavior disorder Questionnaire, Symptom Check-list 90- R, Brief Psychiatric Rating Scale, FAS (phonetic verbal fluency), semantic verbal fluency test, digit span test (WAIS), auditory verbal learning test,Stroop test, Raven's progressive Matrices, Questionnaire for Impulsive-Compulsive Disorders; in NPH: timed walking test, MMSE, immediate memory task (WAIS), digit span test (WAIS), FAB, Rey’s Complex Figure test, Stroop test, letter cancellation test, Perdue Pegboard test. NPH patients were also subjected to an imaging study. Statistics were adapted to the characteristics of each study.Results: Primary Dystonia: we found set-shifting deficits as well as significant correlation between timed neuropsychological tests and dystonia severity. Parkinson's Disease: PD patients had significantly lower scores on the FAB and on the memory and visuo-spatial tests of the MMSE; MMSE scores were significantly correlated to non-tremor motor scores; gait dysfunction and speech scores, non-tremor motor phenotype, hallucinations and scores bellow cut-off on the MMSE were predictive of dementia at follow-up; speech and rigidity scores were predictive of frontal type decline; frontal dysfunction was predictivy of decline in MMSE scores; RBD bradykinesia worsening; psychiatric symptoms were prevalent, particularly Psychosis, Depression, Anxiety, Somatisation and Obsessive-Compulsive Symptoms; Impulse Control Disorders were unrelated to motor phenotype,motor side effects of dopamine treatment and executive function; NPH: gait dysfunction was worse in NPH when compared to PD patients, although the pattern was similarly characterized by slowness, short steps and disequilibrium; PD patients whose gait disturbance was as severe as that of NPH patients were characterized by longer disease duration, predominance of non-tremor motor scores, more advanced disease stage and higher dopamine dose; frontal white matter lesions correlated negatively with improvement after LP; cognitive function assessment revealed wide spread deficits, with lower results on the drawing of the complex figure of Rey, which were not significantly correlated to gait dysfunction; older age, white matter lesions and the presence of vascular risk factors were predictive factors for motor but not cognitive function worsening. Conclusion: Results from our studies highlight the presence of cognitive and behavioural dysfunction in all three movement disorders. Symptom pattern and the relation with ovement derangement varied according to the disease. In Primary Dystonia, set-shifting difficulties could be the cognitive counterpart of motor perseveration characteristic of this disorder, suggesting dysfunction of the dorso-lateral circuit. The relation between timed tests and dystonia severity could suggest a relation between bradyphrenia and bradykinesia in Primary Dystonia. In Parkinson's Disease patients, the spectrum of non-motor symptoms is wider, probably reflecting the spread of neurodegeneration beyond the fronto-striatal circuits. While frontal type deficits predominate, suggestive of dorso-lateral and orbito-frontal dysfunction, non-frontal deficits were also apparent in the initial stages of disease, and were predictive of dementia at follow-up. The relationship between cognitive and motor symptoms is complex, although the results strongly suggest a dissociation between tremor symptoms, which bore no relation with non-motor symptoms, and non-tremor symptoms,whichwas frequent, and a predictive factor for which were related with cognitive decline. While RBD was found to be a predictive factor for bradykinesia worsening, psychiatric symptoms, which were also frequent, showed no apparent relation with motor dysfunction. Relevant to our theoretical consideration was the high prevalence of OCS, which have been attributed to orbito-frontal dysfunction. As to the particular case of ICD, we found no relation either with motor or cognitive dysfunction. The fronto-striatal nature of gait dysfunction in NPH is suggest by the clinical characterization study and by the effects of frontal white matter lesions on gait recovery after LP, whereas cognitive dysfunction presented a more diffuse pattern, which could explain the lack or relation with gait assessment results and also the different outcome on the longitudinal study - this dissociation could be caused by a real difference in pathophysiological mechanisms or, in alternative, be due to the existence of cognitive comorbidities.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies

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Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de Computadores

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The Graphics Processing Unit (GPU) is present in almost every modern day personal computer. Despite its specific purpose design, they have been increasingly used for general computations with very good results. Hence, there is a growing effort from the community to seamlessly integrate this kind of devices in everyday computing. However, to fully exploit the potential of a system comprising GPUs and CPUs, these devices should be presented to the programmer as a single platform. The efficient combination of the power of CPU and GPU devices is highly dependent on each device’s characteristics, resulting in platform specific applications that cannot be ported to different systems. Also, the most efficient work balance among devices is highly dependable on the computations to be performed and respective data sizes. In this work, we propose a solution for heterogeneous environments based on the abstraction level provided by algorithmic skeletons. Our goal is to take full advantage of the power of all CPU and GPU devices present in a system, without the need for different kernel implementations nor explicit work-distribution.To that end, we extended Marrow, an algorithmic skeleton framework for multi-GPUs, to support CPU computations and efficiently balance the work-load between devices. Our approach is based on an offline training execution that identifies the ideal work balance and platform configurations for a given application and input data size. The evaluation of this work shows that the combination of CPU and GPU devices can significantly boost the performance of our benchmarks in the tested environments, when compared to GPU-only executions.

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The reported productivity gains while using models and model transformations to develop entire systems, after almost a decade of experience applying model-driven approaches for system development, are already undeniable benefits of this approach. However, the slowness of higher-level, rule based model transformation languages hinders the applicability of this approach to industrial scales. Lower-level, and efficient, languages can be used but productivity and easy maintenance seize to exist. The abstraction penalty problem is not new, it also exists for high-level, object oriented languages but everyone is using them now. Why is not everyone using rule based model transformation languages then? In this thesis, we propose a framework, comprised of a language and its respective environment, designed to tackle the most performance critical operation of high-level model transformation languages: the pattern matching. This framework shows that it is possible to mitigate the performance penalty while still using high-level model transformation languages.

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Cloud computing has been one of the most important topics in Information Technology which aims to assure scalable and reliable on-demand services over the Internet. The expansion of the application scope of cloud services would require cooperation between clouds from different providers that have heterogeneous functionalities. This collaboration between different cloud vendors can provide better Quality of Services (QoS) at the lower price. However, current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability to enable collaboration between cloud service providers. Hence, the PhD work is motivated to address interoperability issue between cloud providers as a challenging research objective. This thesis proposes a new framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Analysing different methodologies that have been applied to resolve various problem scenarios related to interoperability lead us to exploit Model Driven Architecture (MDA) and Service Oriented Architecture (SOA) methods as appropriate approaches for our inter-cloud framework. Moreover, since distributing the operations in a cloud-based environment is a nondeterministic polynomial time (NP-complete) problem, a Genetic Algorithm (GA) based job scheduler proposed as a part of interoperability framework, offering workload migration with the best performance at the least cost. A new Agent Based Simulation (ABS) approach is proposed to model the inter-cloud environment with three types of agents: Cloud Subscriber agent, Cloud Provider agent, and Job agent. The ABS model is proposed to evaluate the proposed framework.

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The Intel R Xeon PhiTM is the first processor based on Intel’s MIC (Many Integrated Cores) architecture. It is a co-processor specially tailored for data-parallel computations, whose basic architectural design is similar to the ones of GPUs (Graphics Processing Units), leveraging the use of many integrated low computational cores to perform parallel computations. The main novelty of the MIC architecture, relatively to GPUs, is its compatibility with the Intel x86 architecture. This enables the use of many of the tools commonly available for the parallel programming of x86-based architectures, which may lead to a smaller learning curve. However, programming the Xeon Phi still entails aspects intrinsic to accelerator-based computing, in general, and to the MIC architecture, in particular. In this thesis we advocate the use of algorithmic skeletons for programming the Xeon Phi. Algorithmic skeletons abstract the complexity inherent to parallel programming, hiding details such as resource management, parallel decomposition, inter-execution flow communication, thus removing these concerns from the programmer’s mind. In this context, the goal of the thesis is to lay the foundations for the development of a simple but powerful and efficient skeleton framework for the programming of the Xeon Phi processor. For this purpose we build upon Marrow, an existing framework for the orchestration of OpenCLTM computations in multi-GPU and CPU environments. We extend Marrow to execute both OpenCL and C++ parallel computations on the Xeon Phi. We evaluate the newly developed framework, several well-known benchmarks, like Saxpy and N-Body, will be used to compare, not only its performance to the existing framework when executing on the co-processor, but also to assess the performance on the Xeon Phi versus a multi-GPU environment.

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Nowadays, the consumption of goods and services on the Internet are increasing in a constant motion. Small and Medium Enterprises (SMEs) mostly from the traditional industry sectors are usually make business in weak and fragile market sectors, where customized products and services prevail. To survive and compete in the actual markets they have to readjust their business strategies by creating new manufacturing processes and establishing new business networks through new technological approaches. In order to compete with big enterprises, these partnerships aim the sharing of resources, knowledge and strategies to boost the sector’s business consolidation through the creation of dynamic manufacturing networks. To facilitate such demand, it is proposed the development of a centralized information system, which allows enterprises to select and create dynamic manufacturing networks that would have the capability to monitor all the manufacturing process, including the assembly, packaging and distribution phases. Even the networking partners that come from the same area have multi and heterogeneous representations of the same knowledge, denoting their own view of the domain. Thus, different conceptual, semantic, and consequently, diverse lexically knowledge representations may occur in the network, causing non-transparent sharing of information and interoperability inconsistencies. The creation of a framework supported by a tool that in a flexible way would enable the identification, classification and resolution of such semantic heterogeneities is required. This tool will support the network in the semantic mapping establishments, to facilitate the various enterprises information systems integration.

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As the complexity of markets and the dynamicity of systems evolve, the need for interoperable systems capable of strengthening enterprise communication effectiveness increases. This is particularly significant when it comes to collaborative enterprise networks, like manufacturing supply chains, where several companies work, communicate, and depend on each other, in order to achieve a specific goal. Once interoperability is achieved, that is once all network parties are able to communicate with and understand each other, organisations are able to exchange information along a stable environment that follows agreed laws. However, as markets adapt to new requirements and demands, an evolutionary behaviour is triggered giving space to interoperability problems, thus disrupting the sustainability of interoperability and raising the need to develop monitoring activities capable of detecting and preventing unexpected behaviour. This work seeks to contribute to the development of monitoring techniques for interoperable SOA-based enterprise networks. It focuses on the automatic detection of harmonisation breaking events during real-time communications, and strives to develop and propose a methodological approach to handle these disruptions with minimal or no human intervention, hence providing existing service-based networks with the ability to detect and promptly react to interoperability issues.

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Digital Businesses have become a major driver for economic growth and have seen an explosion of new startups. At the same time, it also includes mature enterprises that have become global giants in a relatively short period of time. Digital Businesses have unique characteristics that make the running and management of a Digital Business much different from traditional offline businesses. Digital businesses respond to online users who are highly interconnected and networked. This enables a rapid flow of word of mouth, at a pace far greater than ever envisioned when dealing with traditional products and services. The relatively low cost of incremental user addition has led to a variety of innovation in pricing of digital products, including various forms of free and freemium pricing models. This thesis explores the unique characteristics and complexities of Digital Businesses and its implications on the design of Digital Business Models and Revenue Models. The thesis proposes an Agent Based Modeling Framework that can be used to develop Simulation Models that simulate the complex dynamics of Digital Businesses and the user interactions between users of a digital product. Such Simulation models can be used for a variety of purposes such as simple forecasting, analysing the impact of market disturbances, analysing the impact of changes in pricing models and optimising the pricing for maximum revenue generation or a balance between growth in usage and revenue generation. These models can be developed for a mature enterprise with a large historical record of user growth rate as well as for early stage enterprises without much historical data. Through three case studies, the thesis demonstrates the applicability of the Framework and its potential applications.

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The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.

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This case-study examined the use of the BeGloCal Framework applied to B2C E-commerce, for a fast moving consumer goods European manufacturing firm. It explains how the framework supported the team within the company to identify the right local market as to where to start the project, the problem for the company was to find the most appealing area to invest resources. By going through all the steps of the framework the findings led the company to London (Kensington and Chelsea). It shows how managers should act when they have to find a trade-off between standardization and adaptation.

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The purpose of this work is to develop a practicable approach for Telecom firms to manage the credit risk exposition to their commercial agents’ network. Particularly it will try to approach the problem of credit concession to clients’ from a corporation perspective and explore the particular scenario of agents that are part of the commercial chain of the corporation and therefore are not end-users. The agents’ network that served as a model for the presented study is composed by companies that, at the same time, are both clients and suppliers of the Telecommunication Company. In that sense the credit exposition analysis must took into consideration all financial fluxes, both inbound and outbound. The current strain on the Financial Sector in Portugal, and other peripheral European economies, combined with the high leverage situation of most companies, generates an environment prone to credit default risk. Due to these circumstances managing credit risk exposure is becoming increasingly a critical function for every company Financial Department. The approach designed in the current study combined two traditional risk monitoring tools: credit risk scoring and credit limitation policies. The objective was to design a new credit monitoring framework that is more flexible, uses both external and internal relationship history to assess risk and takes into consideration commercial objectives inside the agents’ network. Although not explored at length, the blueprint of a Credit Governance model was created for implementing the new credit monitoring framework inside the telecom firm. The Telecom Company that served as a model for the present work decided to implement the new Credit Monitoring framework after this was presented to its Executive Commission.

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This project is based on the theme of capacity-building in social organisations to improve their impact readiness, which is the predictability of delivering intended outcomes. All organisations which have a social mission, non-profit or for-profit, will be considered to fall within the social sector for the purpose of this work. The thesis will look at (i) what is impact readiness and what are the considerations for building impact readiness in social organisations, (ii) what is the international benchmark in measuring and building impact readiness, (iii) understand the impact readiness of Portuguese social organisations and the supply of capacity building for social impact in Portugal currently, and (iv) provide recommendations on the design of a framework for capacity building for impact readiness adapted to the Portuguese context. This work is of particular relevance to the Social Investment Laboratory, which is a sponsor of this project, in its policy work as part of the Portuguese Social Investment Taskforce (the “Taskforce”). This in turn will inform its contribution to the set-up of Portugal Inovação Social, a wholesaler catalyst entity of social innovation and social investment in the country, launched in early 2015. Whilst the output of this work will be set a recommendations for wider application for capacity-building programmes in Portugal, Portugal Inovação Social will also clearly have a role in coordinating the efforts of market players – foundations, corporations, public sector and social organisations – in implementing these recommendations. In addition, the findings of this report could have relevance to other countries seeking to design capacity building frameworks in their local markets and to any impact-driven organisations with an interest in enhancing the delivery of impact within their work.