Optimization of breast tomosynthesis image reconstruction using parallel computing

Breast cancer is the most common cancer among women, being a major public health problem. Worldwide, X-ray mammography is the current gold-standard for medical imaging of breast cancer. However, it has associated some well-known limitations. The false-negative rates, up to 66% in symptomatic women, and the false-positive rates, up to 60%, are a continued source of concern and debate. These drawbacks prompt the development of other imaging techniques for breast cancer detection, in which Digital Breast Tomosynthesis (DBT) is included. DBT is a 3D radiographic technique that reduces the obscuring effect of tissue overlap and appears to address both issues of false-negative and false-positive rates. The 3D images in DBT are only achieved through image reconstruction methods. These methods play an important role in a clinical setting since there is a need to implement a reconstruction process that is both accurate and fast. This dissertation deals with the optimization of iterative algorithms, with parallel computing through an implementation on Graphics Processing Units (GPUs) to make the 3D reconstruction faster using Compute Unified Device Architecture (CUDA). Iterative algorithms have shown to produce the highest quality DBT images, but since they are computationally intensive, their clinical use is currently rejected. These algorithms have the potential to reduce patient dose in DBT scans. A method of integrating CUDA in Interactive Data Language (IDL) is proposed in order to accelerate the DBT image reconstructions. This method has never been attempted before for DBT. In this work the system matrix calculation, the most computationally expensive part of iterative algorithms, is accelerated. A speedup of 1.6 is achieved proving the fact that GPUs can accelerate the IDL implementation.

A new MDA-SOA based framework for intercloud interoperability

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.

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.

Efficiency optimization of the transportation supply chain activity: the maritime option for Volkswagen Autoeuropa

Field Lab of Entrepreneurial Innovative Ventures

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.

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.

Cost-to-serve customers’ optimization: Macro project Unilever – Jerónimo Martins

The objective of this work project is to analyse and discuss the importance of the “Cost to Serve” as a differentiation key factor, by accessing cost to serve customers of a Portuguese subsidiary of a multinational company, which is operating in the sector of fast moving consumer goods (FMCG) – Unilever – Jerónimo Martins (UJM). I will also suggest and quantify key proposals to decrease costs and increase customers’ value. Hence, the scope of this work project is focused on logistics and distribution processes of the company supply chain.

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.

Optimization of export support systems: How to promote exports from Portugal to Germany in the area of information technology and electronics

This work project focuses on developing new approaches which enhance Portuguese exports towards a defined German industry sector within the information technology and electronics fields. Firstly and foremost, information was collected and a set of expert and top managers’ interviews were performed in order to acknowledge the demand of the German market while identifying compatible Portuguese supply capabilities. Among the main findings, Industry 4.0 presents itself as a valuable opportunity in the German market for Portuguese medium sized companies in the embedded systems area of expertise for machinery and equipment companies. In order to achieve the purpose of the work project, an embedded systems platform targeting machinery and equipment companies was suggested as well as it was developed several recommendations on how to implement it. An alternative approach for this platform was also considered within the German market namely the eHealth sector having the purpose of enhancing the current healthcare service provision.

Optimization of export support systems

The present paper is a personal reflection on a work project carried out to promote exports from Portugal to Germany in the IT area, under consideration of the deliverables required by the clients CCILA and Anetie. The project outcome approaches the fact that the majority of the Portuguese market players has disadvantages in size and does rarely coordinate activities among each other, which hinders them to export successfully on a broad scale. To bring together Portuguese delivery potential and German market demand, expert interviews were conducted. Based on the findings, a concept was developed to overcome the domestic collaboration issues in order to strengthen the national exports in the identified sector - embedded systems implementation services for machinery and equipment companies.

Shrinking shrinkage:How and why is fruit shrinkage being caused in Sonaemc's convenience stores? Finding opportunities of improvement envisioning its optimization

This work project regards a challenge presented by a Portuguese organization on the retail sector, SONAEMC, which is a case study of how and why fruit shrinkage occurs in the fruit supply chain within their convenience stores. A qualitative research methodology enabled to infer in which stages throughout the chain shrinkage’s causes occur and, to conclude that internal rules for procedures and processes are not always followed and whose compliance would be enough to reduce fruit shrinkage. The key conclusion is that if fruit stock loss is reduced by as much as 15% the category’s profitability could increase about 8%.

Technical optimization of the synthesis of flavours

The goal of this thesis is the investigation and optimization of the synthesis of potential fragrances. This work is projected as collaboration between the University of Applied Sciences in Merseburg and the company Miltitz Aromatics GmbH in Bitterfeld‐Wolfen (Germany). Flavoured compounds can be synthesized in different ways and by various methods. In this work, methods like the phase transfer catalysis and the Cope‐rearrangement were investigated and applied, for getting a high yield and quantity of the desired substances and without any by‐products or side reactions. This involved the study of syntheses with different process parameters such as temperature, solvent, pressure and reaction time. The main focus was on Cope‐rearrangement, which is a common method in the synthesis of new potential fragrance compounds. The substances synthesized in this work have a hepta‐1,5‐diene‐structure and that is why they can easily undergo this [3,3]‐sigma tropic rearrangement. The lead compound of all research was 2,5‐dimethyl‐2‐vinyl‐4‐hexenenitrile (Neronil). Neronil is synthesized by an alkylation of 2‐methyl‐3‐butenenitrile with prenylchloride under basic conditions in a phase‐transfer system. In this work the yield of isolated Neronil is improved from about 35% to 46% by according to the execution conditions of the reaction. Additionally the amount of side product was decreased. This synthesized hexenenitrile involved not only the aforementioned 1,5‐diene‐structure, but also a cyano group, that makes this structure a suitable base for the synthesis of new potential fragrance compounds. It was observed that Neronil can be transferred into 2,5‐dimethyl‐2‐vinyl‐4‐hexenoic acid by a hydrolysis under basic conditions. After five hours the acid can be obtained with a yield of 96%. The following esterification is realized with isobutanol to produce 2,5‐dimethyl‐2‐vinyl‐4‐hexenoic acid isobutyl ester with quantitative conversion. It was observed that the Neronil and the corresponding ester can be converted into the corresponding Cope‐product, with a conversion of 30 % and 80%. Implementing the Cope‐rearrangement, the acid was heated and an unexpected decarboxylated product is formed. To achieve the best verification of reaction development and structure, scrupulous analyses were done using GC‐MS, 1H‐NMR and 13C‐ NMR.

Optimization of the electrodialytic phosphorus recovery from sewage sludge ash

Phosphorus (P) is becoming a scarce element due to the decreasing availability of primary sources. Therefore, recover P from secondary sources, e.g. waste streams, have become extremely important. Sewage sludge ash (SSA) is a reliable secondary source of P. The use of SSAs as a direct fertilizer has very restricted legislation due to the presence of inorganic contaminants. Furthermore, the P present in SSAs is not in a plant-available form. The electrodialytic (ED) process is one of the methods under development to recover P and simultaneously remove heavy metals. The present work aimed to optimize the P recovery through a 2 compartment electrodialytic cell. The research was divided in three independent phases. In the first phase, ED experiments were carried out for two SSAs from different seasons, varying the duration of the ED process (2, 4, 6 and 9 days). During the ED treatment the SSA was suspended in distilled water in the anolyte, which was separated from the catholyte by a cation exchange membrane. From both ashes 90% of P was successfully extracted after 6 days of treatment. Regarding the heavy metals removal, one of the SSAs had a better removal than the other. Therefore, it was possible to conclude that SSAs from different seasons can be submitted to ED process under the same parameters. In the second phase, the two SSAs were exposed to humidity and air prior to ED, in order to carbonate them. Although this procedure was not successful, ED experiments were carried out varying the duration of the treatment (2 and 6 days) and the period of air exposure that SSAs were submitted to (7, 14 and 30 days). After 6 days of treatment and 30 days of air exposure, 90% of phosphorus was successfully extracted from both ashes. No differences were identified between carbonated and non-carbonated SSAs. Thus, SSAs that were exposed to the air and humidity, e.g. SSAs stored for 30 days in an open deposit, can be treated under the same parameters as the SSAs directly collected from the incineration process. In the third phase, ED experiments were carried out during 6 days varying the stirring time (0, 1, 2 and 4 h/day) in order to investigate if energy can be saved on the stirring process. After 6 days of treatment and 4 h/day stirring, 80% and 90% of P was successfully extracted from SSA-A and SSA-B, respectively. This value is very similar to the one obtained for 6 days of treatment stirring 24 h/day.

Optimization of production of anti-cancer vaccines based on dendritic cells

Cancer remains as one of the top killing diseases in first world countries. It’s not a single, but a set of various diseases for which different treatment approaches have been taken over the years. Cancer immunotherapy comes as a “new” breath on cancer treatment, taking use of the patients’ immune system to induce anti-cancer responses. Dendritic Cell (DC) vaccines use the extraordinary capacity of DCs’ antigen presentation so that specific T cell responses may be generated against cancer. In this work, we report the ex vivo generation of DCs from precursors isolated from clinical-grade cryopreserved umbilical cord blood (UCB) samples. After the thawing protocol for cryopreserved samples was optimized, the generation of DCs from CD14+ monocytes, i.e., moDCs, or CD34+ hematopoietic stem cells (HSCs), i.e, CD34-derived DCs, was followed and their phenotype and function evaluated. Functional testing included the ability to respond to maturation stimuli (including enzymatic removal of surface sialic acids), Ovalbumin-FITC endocytic capacity, cytokine secretion and T cell priming ability. In order to evaluate the feasibility of using DCs derived from UCB precursors to induce immune responses, they were compared to peripheral blood (PB) moDCs. We observed an increased endocytosis capacity after moDCs were differentiated from monocyte precursors, but almost 10-fold lower than that of PB moDCs. Maturation markers were absent, low levels of inflammatory cytokines were seen and T cell stimulatory capacity was reduced. Sialidase enzymatic treatment was able to mature these cells, diminishing endocytosis and promoting higher T cell stimulation. CD34-derived DCs showed higher capacity for both maturation and endocytic capacity than moDCs. Although much more information was acquired from moDCs than from CD34-derived DCs, we conclude the last as probably the best suited for generating an immune response against cancer, but of course much more research has to be performed.