L'objet de la présente thèse est d'analyser l'incidence des politiques menées dans le cadre des systèmes d'éducation et de formation grec et italien afin de se conformer aux exigences de la stratégie de Lisbonne 2000. Le niveau d'influence de la politique de l'UE sur les structures des deux pays et ses effets sur les réformes nationales sont liés à la relation, entre structures nationales et internationales en ce qui concerne les politiques d'éducation et de formation. Les réformes ne sont pas nécessairement le résultat de la politique de l'Union européenne ; elles peuvent également être le résultat de la voie nationale suivie et intervenir indépendamment des politiques européennes. Cela permet de se demander si le changement de la politique nationale est lié aux directives internationales ou s'il est le résultat indépendant de l'évolution de l'État. / The present thesis attempts a policy impact analysis through the Greek and Italian education and training policies undertaken to respond to the Lisbon's Strategy 2000 requirements. The level of influence of the EU policy within the domestic structure of both countries and its dynamic on national reforms is related to the relationship, - level of influence-, between national and international structure as concerns the educational and training policies. Reforms are not necessarily results of the European's Community policy, but they can be results of the national pathway and they would have taken place in any case. The above hypothesis leads to the query if national policy change is linked to the international directives or it is the independent result of the State's development.

<h4>A generalized physics-based modeling framework is presented to analyze: (a) the effects of temperature on identified degradation mechanisms, (b) interfacial debonding processes, including deterministic and stochastic mechanisms, and (c) establishing model performance benchmarks of electrochemical porous electrode theory models, as a necessary stepping stone to perform valid battery degradation analyses and designs. Specifically, the effects of temperature were incorporated into a physics-based, reduced-order model and extended for a LiCoO₂ -graphite 18650 cell. Three dimensionless driving forces were identified, controlling the temperature-dependent reversible charge capacity. The identified temperature-dependent irreversible mechanisms include homogeneous SEI, at moderate to high temperatures, and the chemomechanical degradation of the cathode at low temperatures. Also, debonding of a statistically representative electrochemically active particle from the surrounding binder-electrolyte matrix in a porous electrode was modeled analytically, for the first time. The proposed framework enables to determine the space of C-Rates and electrode particle radii that suppresses or enhances debonding and is graphically summarized into performance–microstructure maps where four debonding mechanisms were identified, and condensed into power-law relations with respect to the particle radius. Finally, in order to incorporate existing or emerging degradation models into porous electrode theory (PET) implementations, a set of benchmarks were proposed to establish a common basis to assess their physical reaches, limitations, and accuracy. Three open source models: dualfoil, MPET, and LIONSIMBA were compared, exhibiting significant qualitative differences, despite showing the same macroscopic voltage response, leading the user to different conclusions regarding the battery performance and possible degradation mechanisms of the analyzed system.</h4>

Within the worldwide business community, many analysis tools and techniques have evolved to assist in the evaluation and encouragement of financial health and fiscal viability. However, in the educational community, such analysis is uncommon. It has long been argued that educational institutions bear little resemblance to, and should not be treated like, businesses. This research identifies an educational environment where educational institutions are, indeed, businesses, and may greatly benefit from the use of business analyses. The worldwide effort of Education for All (EFA) has focused on primary education, particularly in less developed countries (LDCs). In Sub-Saharan Africa, Uganda increased its primary school enrollments from 2.7 million in 1996 to 7.6 million in 2003. This rapid primary school expansion substantially increased the demand for secondary education. Limited government funding for secondary schools created an educational bottleneck. In response to this demand, laws were passed to allow the establishment of private secondary schools, operated and taxed as businesses. Revenue reports, filed by individual private schools with the Uganda Revenue Authority, formed the database for the financial analysis portion of this research. These reports, required of all profitable businesses in Uganda, are similar to audited corporate financial statements. Survey data and national examination (UNEB) scores were also utilized. This research explored standard business financial analysis tools, including financial statement ratio analysis, and evaluated the applicability of each to this LDC educational environment. A model for financial assessment was developed and industry averages were calculated for private secondary schools in the Mukono District of Uganda. Industry averages can be used by individual schools as benchmarks in assessing their own financial health. Substantial deviations from the norms signal areas of potential concern. Schools may take appropriate corrective action, leading to sustainable fiscal viability. An example of such analysis is provided. Finally, school financial health, defined by eight financial measures, was compared with quality of education, defined by UNEB scores. Worldwide, much attention is given to education and its role in development. This research, with its model for financial assessment of private LDC schools, offers a new and pragmatic perspective.

Multi functional health monitoring wearable devices are quite prominent these days. Usually these devices are battery-operated and consequently are limited by their battery life (from few hours to a few weeks depending on the application). Of late, it was realized that these devices, which are currently being operated at fixed voltage and frequency, are capable of operating at multiple voltages and frequencies. By switching these voltages and frequencies to lower values based upon power requirements, these devices can achieve tremendous benefits in the form of energy savings. Dynamic Voltage and Frequency Scaling (DVFS) techniques have proven to be handy in this situation for an efficient trade-off between energy and timely behavior. Within imec, wearable devices make use of the indigenously developed MUSEIC v2 (Multi Sensor Integrated circuit version 2.0). This system is optimized for efficient and accurate collection, processing, and transfer of data from multiple (health) sensors. MUSEIC v2 has limited means in controlling the voltage and frequency dynamically. In this thesis we explore how traditional DVFS techniques can be applied to the MUSEIC v2. Experiments were conducted to find out the optimum power modes to efficiently operate and also to scale up-down the supply voltage and frequency. Considering the overhead caused when switching voltage and frequency, transition analysis was also done. Real-time and non real-time benchmarks were implemented based on these techniques and their performance results were obtained and analyzed. In this process, several state of the art scheduling algorithms and scaling techniques were reviewed in identifying a suitable technique. Using our proposed scaling technique implementation, we have achieved 86.95% power reduction in average, in contrast to the conventional way of the MUSEIC v2 chip’s processor operating at a fixed voltage and frequency. Techniques that include light sleep and deep sleep mode were also studied and implemented, which tested the system’s capability in accommodating Dynamic Power Management (DPM) techniques that can achieve greater benefits. A novel approach for implementing the deep sleep mechanism was also proposed and found that it can obtain up to 71.54% power savings, when compared to a traditional way of executing deep sleep mode. / Nuförtiden så har multifunktionella bärbara hälsoenheter fått en betydande roll. Dessa enheter drivs vanligtvis av batterier och är därför begränsade av batteritiden (från ett par timmar till ett par veckor beroende på tillämpningen). På senaste tiden har det framkommit att dessa enheter som används vid en fast spänning och frekvens kan användas vid flera spänningar och frekvenser. Genom att byta till lägre spänning och frekvens på grund av effektbehov så kan enheterna få enorma fördelar när det kommer till energibesparing. Dynamisk skalning av spänning och frekvens-tekniker (såkallad Dynamic Voltage and Frequency Scaling, DVFS) har visat sig vara användbara i detta sammanhang för en effektiv avvägning mellan energi och beteende. Hos Imec så använder sig bärbara enheter av den internt utvecklade MUSEIC v2 (Multi Sensor Integrated circuit version 2.0). Systemet är optimerat för effektiv och korrekt insamling, bearbetning och överföring av data från flera (hälso) sensorer. MUSEIC v2 har begränsad möjlighet att styra spänningen och frekvensen dynamiskt. I detta examensarbete undersöker vi hur traditionella DVFS-tekniker kan appliceras på MUSEIC v2. Experiment utfördes för att ta reda på de optimala effektlägena och för att effektivt kunna styra och även skala upp matningsspänningen och frekvensen. Eftersom att ”overhead” skapades vid växling av spänning och frekvens gjordes också en övergångsanalys. Realtidsoch icke-realtidskalkyler genomfördes baserat på dessa tekniker och resultaten sammanställdes och analyserades. I denna process granskades flera toppmoderna schemaläggningsalgoritmer och skalningstekniker för att hitta en lämplig teknik. Genom att använda vår föreslagna skalningsteknikimplementering har vi uppnått 86,95% effektreduktion i jämförelse med det konventionella sättet att MUSEIC v2-chipets processor arbetar med en fast spänning och frekvens. Tekniker som inkluderar lätt sömn och djupt sömnläge studerades och implementerades, vilket testade systemets förmåga att tillgodose DPM-tekniker (Dynamic Power Management) som kan uppnå ännu större fördelar. En ny metod för att genomföra den djupa sömnmekanismen föreslogs också och enligt erhållna resultat så kan den ge upp till 71,54% lägre energiförbrukning jämfört med det traditionella sättet att implementera djupt sömnläge.