Towards an algorithmic skeleton framework for programming the Intel R Xeon PhiTM processor

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.

Framework for the semantic alignment of enterprise’s domain knowledge

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.

Functional characterization and directed engineering of redox proteins for a rational improvement of Bioelectrochemical systems

In recent years, new methods of clean and environmentally friendly energy production have been the focus of intense research efforts. Microbial fuel cells (MFCs) are devices that utilize naturally occurring microorganisms that feed on organic matter, like waste water, while producing electrical energy. The natural habitats of bacteria thriving in microbial fuel cells are usually marine and freshwater sediments. These microorganisms are called dissimilatory metal reducing bacteria (DMRB), but in addition to metals like iron and manganese, they can use organic compounds like DMSO or TMAO, radionuclides and electrodes as terminal electron acceptors in their metabolic pathways.(...)

Methodological framework for detection of harmonisation breaking in service environments

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.

DYNAMOD – A dynamic agent based modelling framework for digital businesses

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.

Engineering of metal oxide nanoparticles for application in electrochemical devices

The growing demand for materials and devices with new functionalities led to the increased inter-est in the field of nanomaterials and nanotechnologies. Nanoparticles, not only present a reduced size as well as high reactivity, which allows the development of electronic and electrochemical devices with exclusive properties, when compared with thin films. This dissertation aims to explore the development of several nanostructured metal oxides by sol-vothermal synthesis and its application in different electrochemical devices. Within this broad theme, this study has a specific number of objectives: a) research of the influence of the synthesis parameters to the structure and morphology of the nanoparticles; b) improvement of the perfor-mance of the electrochromic devices with the application of the nanoparticles as electrode; c) application of the nanoparticles as probes to sensing devices; and d) production of solution-pro-cessed transistors with a nanostructured metal oxide semiconductor. Regarding the results, several conclusions can be exposed. Solvothermal synthesis shows to be a very versatile method to control the growth and morphology of the nanoparticles. The electrochromic device performance is influenced by the different structures and morphologies of WO3 nanoparticles, mainly due to the surface area and conductivity of the materials. The dep-osition of the electrochromic layer by inkjet printing allows the patterning of the electrodes without wasting material and without any additional steps. Nanostructured WO3 probes were produced by electrodeposition and drop casting and applied as pH sensor and biosensor, respectively. The good performance and sensitivity of the devices is explained by the high number of electrochemical reactions occurring at the surface of the na-noparticles. GIZO nanoparticles were deposited by spin coating and used in electrolyte-gated transistors, which promotes a good interface between the semiconductor and the dielectric. The produced transistors work at low potential and with improved ON-OFF current ratio, up to 6 orders of mag-nitude. To summarize, the low temperatures used in the production of the devices are compatible with flexible substrates and additionally, the low cost of the techniques involved can be adapted for disposable devices.

Knowledge management framework based on brain models and human physiology

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.

A marketing plan for O'Templus Organic Gin

The purpose of the project was to create a marketing plan for the Portuguese brand O’Templus Gin, owned and managed by Oficina de Espíritos in Évora, Portugal. Here O’Templus gin is marketed as an artisanal, organic gin for organic consumers. Information collected to understand the market was consistent with previous research, however there continues to be a lack of information on the organic alcoholic drinks market in Portugal. Identifying the needs of the organic consumer in Portugal, and gauging interest in the product itself, a marketing plan was developed to bring O’Templus to a wider audience.

The quest for growth in the German organic food retail market: Historical trends, current strategies, and future outlook

This paper aims to provide strategies for the organic supermarket chain “Alnatura” to shape the demand and its market share of the organic food & beverage (F&B) market in Germany within the next five years. Through the historic evolution and the current market assessment of Germany, compared to a benchmark country (US), as well as prospective trends in Germany, reasons and opportunities for market growth are evaluated. In addition, an industry attractiveness, competitor and company analysis is executed. Based on those findings and a conducted survey, suggestions to adjust Alnatura´s current business strategies are deduced and finally examined on its risk and feasibility.

Control of a white organic light emitting diode’s emission parameters using a single doped RGB active layer

White Color tuning is an attractive feature that Organic Light Emitting Diodes (OLEDs) offer. Up until now, there hasn’t been any report that mix both color tuning abilities with device stability. In this work, White OLEDs (W-OLEDs) based on a single RGB blend composed of a blue emitting N,N′-Di(1-naphthyl)-N,N′-diphenyl-(1,1′-biphenyl)-4,4′-diamine (NPB) doped with a green emitting Coumarin-153 and a red emitting 4-(Dicyanomethylene)-2-methyl-6-(4-dimethylaminostyryl)-4H-pyran (DCM1) dyes were produced. The final device structure was ITO/Blend/Bathocuproine (BCP)/ Tris(8-hydroxyquinolinato)aluminium (Alq3)/Al with an emission area of 0.25 cm2. The effects of the changing in DCM1’s concentration (from 0.5% to 1% wt.) allowed a tuning in the final white color resulting in devices capable of emitting a wide range of tunes – from cool to warm – while also keeping a low device complexity and a high stabilitty. Moreover, an explanation on the optoelectrical behavior of the device is presented. The best electroluminescense (EL) points toward 160 cd/m2 of brightness and 1.1 cd/A of efficiency, both prompted to being enhanced. An Impedance Spectroscopy (IS) analysis allowed to study both the effects of BCP as a Hole Blocking Layer and as an aging probe of the device. Finally, as a proof of concept, the emission was increased 9 and 64 times proving this structure can be effectively applied for general lighting.

Radiation damage in flexible TFTs and organic detectors

In this thesis was investigated the radiation hardness of the building blocks of a future flexible X-ray sensor system. The characterized building blocks for the pixel addressing and signal amplification electronics are high mobility semiconducting oxide transistors (HMSO-TFTs) and organic transistors (OTFTs), whereas the photonic detection system is based on organic semiconducting single crystals (OSSCs). TFT parameters such as mobility, threshold voltage and subthreshold slope were measured as function of cumulative X-ray dose. Instead for OSSCs conductivity and X-ray sensitivity were analysed after various radiation steps. The results show that ionizing radiation does not lead to degradation in HMSO-TFTs. Instead OTFTs show instability in mobility which is reduced up to 73% for doses of 1 kGy. OSSC demonstrate stable detector properties for the tested total dose range. As conclusion, HMSO-TFTs and OSSCs can be readily employed in the X-ray detector system allowing operation for total doses exceeding 1 kGy of ionizing radiation.

Magnetotransport properties of metal/LaAlO3/SrTiO3 heterostructures

The quasi two-dimensional electron gas (q2DEG) hosted in the interface of an epitaxially grown lanthanum aluminate (LaAlO3) thin film with a TiO2-termi-nated strontium titanate (SrTiO3) substrate (001) has been massively studied in the last few years. The confinement of mobile electrons to within a few nanome-ters from the interface, superconductive behavior at low temperatures and elec-tron mobility exceeding 1000 cm2/(V.s) make this system an interesting candi-date to explore the physics of spin injection and transport. However, due to the critical thickness for conduction of 4 unit cells (uc) of LaAlO3, a high tunneling resistance hampers electrical access to the q2DEG, preventing proper injection of spin polarized current. Recently, our group found that depositing a thin overlayer of Co on LaAlO3 reduces the critical thickness, enabling conduction with only 1 uc of LaAlO3. Two scenarios arise to explain this phenomenon: a pinning of the Fermi level in the metal, inducing charge transfer in the SrTiO3; the creation of oxygen vacancies at the interface between LaAlO3 and the metal, leading to an n-type doping of the SrTiO3. In this dissertation, we will report on magnetotransport of metal/LaAlO3/SrTiO3 (metal: Ti, Ta, Co, Py, Au, Pt, Pd) heterostructures with 2 uc of LaAlO3 studied at low temperatures (2 K) and high magnetic fields (9 T). We have analyzed the transport properties of the gas, namely, the carrier concen-tration, mobility and magnetotransport regime and we will discuss the results in the light of the two scenarios mentioned above.

Development of an experimental setup for metal cutting research

Analytical, numerical and experimental models have been developed over time to try to characterize and understand the metal cutting process by chip removal. A true knowledge of the cutting process by chip removal is required by the increasing production, by the quality requirements of the product and by the reduced production time, in the industries in which it is employed. In this thesis an experimental setup is developed to evaluate the forces and the temperature distribution in the tool according to the orthogonal cutting model conditions, in order to evaluate its performance and its possible adoption in future works. The experimental setup is developed in a CNC lathe and uses an orthogonal cutting configuration, in which thin discs fixed onto a mandrel are cut by the cutting insert. In this experimental setup, the forces are measured by a piezoelectric dynamometer while temperatures are measured by thermocouples placed juxtaposed to the side face of the cutting insert. Three different solutions are implemented and evaluated for the thermocouples attachment in the cutting insert: thermocouples embedded in thermal paste, thermocouples embedded in copper plate and thermocouples brazed in the cutting insert. From the tests performed in the experimental setup it is concluded that the adopted forces measurement technique shows a good performance. Regarding to the adopted temperatures measurement techniques, only the thermocouples brazed in the cutting insert solution shows a good performance for temperature measurement. The remaining solutions show contact problems between the thermocouple and the side face of the cutting insert, especially when the vibration phenomenon intensifies during the cut. It is concluded that the experimental setup does not present a sufficiently robust and reliable performance, and that it can only be used in future work after making improvements in the assembly of the thermocouples.

Coupling organic substrate removal to methane production in a fully biological microbial electrolysis cell

Microbial electrolysis cells (MECs) are an innovative and emerging technique based on the use of solid-state electrodes to stimulate microbial metabolism for wastewater treatment and simultaneous production of value-added compounds (such as methane). This research studied the performance of a two-chamber MEC in terms of organic matter oxidation (at the anode) and methane production (at the cathode). MEC‟s anode had been previously inoculated with an activated sludge, whereas the cathode chamber inoculum was an anaerobic sludge (containing methanogenic microorganisms). During the experimentation, the bioanode was continuously fed with synthetic solutions in anaerobic basal medium, at an organic load rate (OLR) of around 1 g L-1 d-1, referred to the chemical oxygen demand (COD). At the beginning (Run I), the feeding solution contained acetate and subsequently (Run II) it was replaced with a more complex solution containing soluble organic compounds other than acetate. For both conditions, the anode potential was controlled at -0.1 V vs. standard hydrogen electrode, by means of a potentiostat. During Run I, over 80% of the influent acetate was anaerobically oxidized at the anode, and the resulting electric current was recovered as methane at the cathode (with a cathode capture efficiency, CCE, accounting around 115 %). The average energy efficiency of the system (i.e., the energy captured into methane relative to the electrical energy input) under these conditions was over 170%. However, reactor‟s performance decreased over time during this run. Throughout Run II, a substrate oxidation over 60% (on COD basis) was observed. The electric current produced (57% of coulombic efficiency) was also recovered as methane, with a CCE of 90%. For this run the MEC‟s average energy efficiency accounted for almost 170 %. During all the experimentation, a very low biomass growth was observed at the anode whereas ammonium was transferred through the cationic membrane and concentrated at the cathode. Tracer experiments and scanning electron microscopy analyses were also carried out to gain a deeper insight into the reactor performance and also to investigate the possible reasons for partial loss of performance. In conclusion, this research suggests the great potential of MEC to successfully treat low-strength wastewaters, with high energy efficiency and very low sludge production.

The Beglocal framework applied to B2C E-commerce

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.