A probabilistic approach to assess hydrate formation and design preventive measures

Formation of hydrates is one of the major flow assurance problems faced by the oil and gas industry. Hydrates tend to form in natural gas pipelines with the presence of water and favorable temperature and pressure conditions, generally low temperatures and corresponding high pressures. Agglomeration of hydrates can result in blockage of flowlines and equipment, which can be time consuming to remove in subsea equipment and cause safety issues. Natural gas pipelines are more susceptible to burst and explosion owing to hydrate plugging. Therefore, a rigorous risk-assessment related to hydrate formation is required, which assists in preventing hydrate blockage and ensuring equipment integrity. This thesis presents a novel methodology to assess the probability of hydrate formation and presents a risk-based approach to determine the parameters of winterization schemes to avoid hydrate formation in natural gas pipelines operating in Arctic conditions. It also presents a lab-scale multiphase flow loop to study the effects of geometric and hydrodynamic parameters on hydrate formation and discusses the effects of geometric and hydrodynamic parameters on multiphase development length of a pipeline. Therefore, this study substantially contributes to the assessment of probability of hydrate formation and the decision making process of winterization strategies to prevent hydrate formation in Arctic conditions.

Design, fabrication and characterization of resonant waveguide grating based optical biosensors

The absence of rapid, low cost and highly sensitive biodetection platform has hindered the implementation of next generation cheap and early stage clinical or home based point-of-care diagnostics. Label-free optical biosensing with high sensitivity, throughput, compactness, and low cost, plays an important role to resolve these diagnostic challenges and pushes the detection limit down to single molecule. Optical nanostructures, specifically the resonant waveguide grating (RWG) and nano-ribbon cavity based biodetection are promising in this context. The main element of this dissertation is design, fabrication and characterization of RWG sensors for different spectral regions (e.g. visible, near infrared) for use in label-free optical biosensing and also to explore different RWG parameters to maximize sensitivity and increase detection accuracy. Design and fabrication of the waveguide embedded resonant nano-cavity are also studied. Multi-parametric analyses were done using customized optical simulator to understand the operational principle of these sensors and more important the relationship between the physical design parameters and sensor sensitivities. Silicon nitride (SixNy) is a useful waveguide material because of its wide transparency across the whole infrared, visible and part of UV spectrum, and comparatively higher refractive index than glass substrate. SixNy based RWGs on glass substrate are designed and fabricated applying both electron beam lithography and low cost nano-imprint lithography techniques. A Chromium hard mask aided nano-fabrication technique is developed for making very high aspect ratio optical nano-structure on glass substrate. An aspect ratio of 10 for very narrow (~60 nm wide) grating lines is achieved which is the highest presented so far. The fabricated RWG sensors are characterized for both bulk (183.3 nm/RIU) and surface sensitivity (0.21nm/nm-layer), and then used for successful detection of Immunoglobulin-G (IgG) antibodies and antigen (~1μg/ml) both in buffer and serum. Widely used optical biosensors like surface plasmon resonance and optical microcavities are limited in the separation of bulk response from the surface binding events which is crucial for ultralow biosensing application with thermal or other perturbations. A RWG based dual resonance approach is proposed and verified by controlled experiments for separating the response of bulk and surface sensitivity. The dual resonance approach gives sensitivity ratio of 9.4 whereas the competitive polarization based approach can offer only 2.5. The improved performance of the dual resonance approach would help reducing probability of false reading in precise bio-assay experiments where thermal variations are probable like portable diagnostics.

Telescoped approach to aryl hydroxymethylation in the synthesis of a key pharmaceutical intermediate

An efficient synthetic approach leading to introduction of the hydroxymethyl group to an aryl moiety via combination of the Bouveault formylation and hydride reduction has been optimized using a rational, mechanistic-based approach. This approach enabled telescoping of the two steps into a single efficient process, readily amenable to scaleup.

Collection of aboveground community and species-specific plant biomass from the Jena Experiment (time series since 2002).

This data set comprises time series of aboveground community plant biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of several experiments at the field site of a large grassland biodiversity experiment (the Jena Experiment; see further details below). Aboveground community biomass was normally harvested twice a year just prior to mowing (during peak standing biomass twice a year, generally in May and August; in 2002 only once in September) on all experimental plots in the Jena Experiment. This was done by clipping the vegetation at 3 cm above ground in up to four rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned by random selection of new coordinates every year within the core area of the plots. The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship. The following series of datasets are contained in this collection: 1. Plant biomass form the Main Experiment: In the Main Experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). 2. Plant biomass from the Dominance Experiment: In the Dominance Experiment, 206 grassland plots of 3.5 x 3.5 m were established from a pool of 9 species that can be dominant in semi-natural grassland communities of the study region. In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 3, 4, 6, and 9 species). 3. Plant biomass from the monoculture plots: In the monoculture plots the sown plant community contains only a single species per plot and this species is a different one for each plot. Which species has been sown in which plot is stated in the plot information table for monocultures (see further details below). The monoculture plots of 3.5 x 3.5 m were established for all of the 60 plant species of the Jena Experiment species pool with two replicates per species like the other experiments in May 2002. All plots were maintained by bi-annual weeding and mowing.

Assisting End-users in Filling Out Web Services

With the quick advance of web service technologies, end-users can conduct various on-line tasks, such as shopping on-line. Usually, end-users compose a set of services to accomplish a task, and need to enter values to services to invoke the composite services. Quite often, users re-visit websites and use services to perform re-occurring tasks. The users are required to enter the same information into various web services to accomplish such re-occurring tasks. However, repetitively typing the same information into services is a tedious job for end-users. It can negatively impact user experience when an end-user needs to type the re-occurring information repetitively into web services. Recent studies have proposed several approaches to help users fill in values to services automatically. However, prior studies mainly suffer the following drawbacks: (1) limited support of collecting and analyzing user inputs; (2) poor accuracy of filling values to services; (3) not designed for service composition. To overcome the aforementioned drawbacks, we need maximize the reuse of previous user inputs across services and end-users. In this thesis, we introduce our approaches that prevent end-users from entering the same information into repetitive on-line tasks. More specifically, we improve the process of filling out services in the following 4 aspects: First, we investigate the characteristics of input parameters. We propose an ontology-based approach to automatically categorize parameters and fill values to the categorized input parameters. Second, we propose a comprehensive framework that leverages user contexts and usage patterns into the process of filling values to services. Third, we propose an approach for maximizing the value propagation among services and end-users by linking a set of semantically related parameters together and similar end-users. Last, we propose a ranking-based framework that ranks a list of previous user inputs for an input parameter to save a user from unnecessary data entries. Our framework learns and analyzes interactions of user inputs and input parameters to rank user inputs for input parameters under different contexts.

Reputation performance: a portfolio selection approach

This paper introduces a normative view on corporate reputation strategic management. Reputation performance is conceptualised as the outcome of complex processes and social interactions and the lack of a holistic reputation performance management framework is identified. In an attempt to fill this gap, a portfolio-based approach is put forward. Drawing on the foundations of modern portfolio theory we create a portfolio-based reputation management algorithmic model where reputation components and priorities are weighted by decision makers and shape organisational change in an attempt to formulate a corporate reputation strategy. The rationale of this paper is based on the foundational consideration of organisations as choosing he optimal strategy by seeking to maximise their reputation performance while maintaining organisational stability and minimising organisational risk.

Reputation Performance: a portfolio selection approach

This paper introduces a normative view on corporate reputation management; an algorithmic model for reputation-driven strategic decision making is proposed and corporate reputation is conceptualized as influenced by a selection among organizational priorities. A portfolio-based approach is put forward; we draw on the foundations of portfolio theory and we create a portfolio-based reputation management model where reputation components and priorities are weighted by decision makers and shape organizational change in an attempt to formulate a corporate reputation strategy. The rationale of this paper is based on the foundational consideration of organizations as choosing the optimal strategy by seeking to maximize performance on corporate reputation capital while maintaining organizational stability and minimizing organizational risk.

Introducing Corporate Reputation Continuity to Support Organizational Resilience Against Crises

As Corporate Reputation (CR) evolves into an important asset for organizations, crises and disasters stand as threats to the preservation of the reputation capital since they usually result to negative projections to their audiences and to problematic evaluations by their stakeholders. Viewing CR as the accumulated trust and positive evaluations of the stakeholders, this paper proposes a conceptual and normative framework for Reputation Continuity, which enhances the ability of organizations to preserve their reputation, instead of working for its recovery in the post-crisis period. In our approach, we propose a process of maintaining trusted links, instead of restoring them and establishing a reputation resilient organization, instead of one struggling to recover from reputation losses, after the crisis has emerged. Working closely with stakeholders during the crisis, injecting a sense of normality continuity through effective leadership and mitigating image problems are seen as critical concerns, alongside a set of managerial practices to be followed. Ultimately, it is argued that, the value-based and strategically integrated view of Business Continuity must be enhanced and supported by Reputation Continuity activities.

Dynamic Distance-Based Shape Features for Gait Recognition

We propose a novel skeleton-based approach to gait recognition using our Skeleton Variance Image. The core of our approach consists of employing the screened Poisson equation to construct a family of smooth distance functions associated with a given shape. The screened Poisson distance function approximation nicely absorbs and is relatively stable to shape boundary perturbations which allows us to define a rough shape skeleton. We demonstrate how our Skeleton Variance Image is a powerful gait cycle descriptor leading to a significant improvement over the existing state of the art gait recognition rate.

Modular approach to select bacteriophages targeting Pseudomonas aeruginosa for their application to children suffering with cystic fibrosis

This review discusses the potential application of bacterial viruses (phage therapy) towards the eradication of antibiotic resistant Pseudomonas aeruginosa in children with cystic fibrosis (CF). In this regard, several potential relationships between bacteria and their bacteriophages are considered. The most important aspect that must be addressed with respect to phage therapy of bacterial infections in the lungs of CF patients is in ensuring the continuity of treatment in light of the continual occurrence of resistant bacteria. This depends on the ability to rapidly select phages exhibiting an enhanced spectrum of lytic activity among several well-studied phage groups of proven safety. We propose a modular based approach, utilizing both mono-species and hetero-species phage mixtures. With an approach involving the visual recognition of characteristics exhibited by phages of well studied phage groups on lawns of the standard P. aeruginosa PAO1 strain, the simple and rapid enhancement of the lytic spectrum of cocktails is permitted, allowing the development of tailored preparations for patients capable of circumventing problems associated with phage resistant bacterial mutants.

Sentiment classification with case-base approach

L’augmentation de la croissance des réseaux, des blogs et des utilisateurs des sites d’examen sociaux font d’Internet une énorme source de données, en particulier sur la façon dont les gens pensent, sentent et agissent envers différentes questions. Ces jours-ci, les opinions des gens jouent un rôle important dans la politique, l’industrie, l’éducation, etc. Alors, les gouvernements, les grandes et petites industries, les instituts universitaires, les entreprises et les individus cherchent à étudier des techniques automatiques fin d’extraire les informations dont ils ont besoin dans les larges volumes de données. L’analyse des sentiments est une véritable réponse à ce besoin. Elle est une application de traitement du langage naturel et linguistique informatique qui se compose de techniques de pointe telles que l’apprentissage machine et les modèles de langue pour capturer les évaluations positives, négatives ou neutre, avec ou sans leur force, dans des texte brut. Dans ce mémoire, nous étudions une approche basée sur les cas pour l’analyse des sentiments au niveau des documents. Notre approche basée sur les cas génère un classificateur binaire qui utilise un ensemble de documents classifies, et cinq lexiques de sentiments différents pour extraire la polarité sur les scores correspondants aux commentaires. Puisque l’analyse des sentiments est en soi une tâche dépendante du domaine qui rend le travail difficile et coûteux, nous appliquons une approche «cross domain» en basant notre classificateur sur les six différents domaines au lieu de le limiter à un seul domaine. Pour améliorer la précision de la classification, nous ajoutons la détection de la négation comme une partie de notre algorithme. En outre, pour améliorer la performance de notre approche, quelques modifications innovantes sont appliquées. Il est intéressant de mentionner que notre approche ouvre la voie à nouveaux développements en ajoutant plus de lexiques de sentiment et ensembles de données à l’avenir.

Laadun ja oikean tiedon varmistaminen pk-yrityksen tilaus-toimitusketjussa

Oikean tiedon siirtyminen oikeaan aikaan, sekä laadukkaan työn tekeminen yrityksen tilaus-toimitusketjun jokaisessa vaiheessa, ovat avaintekijöitä arvolupauksen ja laadun täyttämiseen asiakkaalle. Diplomityön tavoite on kehittää pk-yritykselle työkalut parempaan tiedon hallintaan ja laadukkaan työn tekemiseen toiminnanohjausjärjestelmässä. Tutkimusmenetelmänä diplomityössä käytettiin toimintatutkimusta, jossa diplomityön tekijä osallistui kohdeyrityksen päivittäiseen työn tekemiseen neljän kuukauden ajan. Tutkimuksen tiedon keräämisessä käytettiin myös puolistrukturoitua haastattelua, sekä kyselytutkimuksella. Tutkimusote työssä on kvalitatiivinen eli laadullinen tutkimusote. Työ koostuu teoriaosasta sekä soveltavasta osasta, jonka jälkeen työn tulokset esitetään tiivistetysti johtopäätöksissä ja yhteenvedossa. Toiminnanohjausjärjestelmät keräävät ja tallentavat tietoa, jota työntekijät ja yrityksen rajapinnoilla työskentelevät ihmiset siihen syöttävät. Onkin äärimmäisen tärkeää, että yrityksellä on kuvatut yhtenäiset toimintamallit prosesseille, joita he käyttävät tiedon tallentamisessa järjestelmiin. Tässä diplomityössä tutkitaan pk-yrityksen nykyiset toimintamallit tiedon tallentamisesta toiminnanohjausjärjestelmään, jonka jälkeen kehitetään yhtenäiset ohjeet toiminnanohjausjärjestelmään syötetystä myyntitilaussopimuksesta. Teoriaosuudessa esitetään laatu eri näkökulmista ja mitä laadunhallintajärjestelmät ovat ja kuinka niitä kehitetään. Teoriaosassa myös avataan tilausohjautuvan tuotannon periaatteet, sekä toiminnanohjausjärjestelmän merkitys liiketoiminnalle. Teoriaosuudella pohjustetaan soveltavaa osuutta, jossa ongelma-analyysin jälkeen kehitetään yritykseen oma laadunhallintajärjestelmä, sekä uudet työmallit tiedonvaihtoon ja sen tallentamiseen. Tuloksena on myös toiminnanohjausjärjestelmän käytön tehostuminen ohjelmistotoimittajan tekemänä. Ohjelmasta karsittiin turhat nimikkeistöt ja sen konfigurointia tehostettiin. Työn tuloksena saatiin työohjeet ydinprosessien suorittamiseen, sekä oma laadunhallintajärjestelmä tukemaan yrityksen ydin- ja tukiprosesseja, sekä tiedonhallintaa.

From global advocacy to local resistance. Benin's experience of competency-based school curriculum

In the vein of the "Education for All" campaign to promote access to education, a wave of curriculum revision along the competency-based approach has swept francophone countries in sub-Sahara Africa, thus Benin. The current study documents local actors' various interactions with the curricular reform in the course of its implementation. Secondary data supplemented with qualitative research techniques such as semi-structured interviews with teachers, and focus group discussions with parents enable to relate the patterns of change, the challenges and resistance to change. The actors spectrum generated illustrates advocacy on one hand and resistance on the other. Advocacy of local actors reflects the global optimistic discourse on education and resistance is favoured by disappointing policy outcomes as well as contextual constraints. (DIPF/Orig.)

Attack simulation based software protection assessment method

Software protection is an essential aspect of information security to withstand malicious activities on software, and preserving software assets. However, software developers still lacks a methodology for the assessment of the deployed protections. To solve these issues, we present a novel attack simulation based software protection assessment method to assess and compare various protection solutions. Our solution relies on Petri Nets to specify and visualize attack models, and we developed a Monte Carlo based approach to simulate attacking processes and to deal with uncertainty. Then, based on this simulation and estimation, a novel protection comparison model is proposed to compare different protection solutions. Lastly, our attack simulation based software protection assessment method is presented. We illustrate our method by means of a software protection assessment process to demonstrate that our approach can provide a suitable software protection assessment for developers and software companies.

Proactive Marketing – Concept Development and Empirical Analysis

In this thesis, proactive marketing is suggested to be a broader concept than existing research assumes. Although the concept has been mentioned in the context of competitive advantage in previous research, it has not been comprehensively described. This thesis shows that proactive marketing is more than investing in marketing communications of a company. Proactive marketing is described as a three-phased process that contains different customer value identification, creation, and delivery activities. The purpose of proactive marketing is essentially to anticipate and pursue market opportunities that bring value to the company’s stakeholders. Ultimately, proactive marketing aims at acting first on the market, shaping the markets, and thus reaching competitive advantage. The proactive marketing process is supported by the structures of an organization. Suitable structures for proactive marketing are identified in the thesis based on existing research and through an empirical analysis. Moreover, proactive marketing is related to two management theories: the dynamic capabilities framework and the empowerment of employees. A dynamic environment requires companies that pursue proactive marketing to change continuously. Dynamic capabilities are considered as tools of the management, which enable companies to create suitable conditions for the constant change. Empowerment of employees is a management practice that creates proactive behaviors in individuals. The empirical analysis is conducted in an online company operating in the rapidly changing marketplace of the Internet. Through the empirical analysis, the thesis identifies in practice how proactiveness manifests in the marketing process of a company, how organizational structures facilitate proactive marketing, and how proactive marketing is managed. The theoretical contribution of this thesis consist of defining the proactive marketing concept comprehensively and providing further research suggestions related to proactive marketing.