Scalable algorithms for height field illumination

Global illumination algorithms are at the center of realistic image synthesis and account for non-trivial light transport and occlusion within scenes, such as indirect illumination, ambient occlusion, and environment lighting. Their computationally most difficult part is determining light source visibility at each visible scene point. Height fields, on the other hand, constitute an important special case of geometry and are mainly used to describe certain types of objects such as terrains and to map detailed geometry onto object surfaces. The geometry of an entire scene can also be approximated by treating the distance values of its camera projection as a screen-space height field. In order to shadow height fields from environment lights a horizon map is usually used to occlude incident light. We reduce the per-receiver time complexity of generating the horizon map on N N height fields from O(N) of the previous work to O(1) by using an algorithm that incrementally traverses the height field and reuses the information already gathered along the path of traversal. We also propose an accurate method to integrate the incident light within the limits given by the horizon map. Indirect illumination in height fields requires information about which other points are visible to each height field point. We present an algorithm to determine this intervisibility in a time complexity that matches the space complexity of the produced visibility information, which is in contrast to previous methods which scale in the height field size. As a result the amount of computation is reduced by two orders of magnitude in common use cases. Screen-space ambient obscurance methods approximate ambient obscurance from the depth bu er geometry and have been widely adopted by contemporary real-time applications. They work by sampling the screen-space geometry around each receiver point but have been previously limited to near- field effects because sampling a large radius quickly exceeds the render time budget. We present an algorithm that reduces the quadratic per-pixel complexity of previous methods to a linear complexity by line sweeping over the depth bu er and maintaining an internal representation of the processed geometry from which occluders can be efficiently queried. Another algorithm is presented to determine ambient obscurance from the entire depth bu er at each screen pixel. The algorithm scans the depth bu er in a quick pre-pass and locates important features in it, which are then used to evaluate the ambient obscurance integral accurately. We also propose an evaluation of the integral such that results within a few percent of the ray traced screen-space reference are obtained at real-time render times.

Virtual communities : a virtual treasure trove for end-user developers

End-user development is a very common but often largely overlooked phenomenon in information systems research and practice. End-user development means that regular people, the end-users of software, and not professional developers are doing software development. A large number of people are directly or indirectly impacted by the results of these non-professional development activities. The numbers of users performing end-user development activities are difficult to ascertain precisely. But it is very large, and still growing. Computer adoption is growing towards 100% and many new types of computational devices are continually introduced. In addition, other devices not previously programmable are becoming so. This means that, at this very moment, hundreds of millions of people are likely struggling with development problems. Furthermore, software itself is continually being adapted for more flexibility, enabling users to change the behaviour of their software themselves. New software and services are helping to transform users from consumers to producers. Much of this is now found on-line. The problem for the end-user developer is that little of this development is supported by anyone. Often organisations do not notice end-user development and consequently neither provide support for it, nor are equipped to be able to do so. Many end-user developers do not belong to any organisation at all. Also, the end-user development process may be aggravating the problem. End-users are usually not really committed to the development process, which tends to be more iterative and ad hoc. This means support becomes a distant third behind getting the job done and figuring out the development issues to get the job done. Sometimes the software itself may exacerbate the issue by simplifying the development process, deemphasising the difficulty of the task being undertaken. On-line support could be the lifeline the end-user developer needs. Going online one can find all the knowledge one could ever need. However, that does still not help the end-user apply this information or knowledge in practice. A virtual community, through its ability to adopt the end-user’s specific context, could surmount this final obstacle. This thesis explores the concept of end-user development and how it could be supported through on-line sources, in particular virtual communities, which it is argued here, seem to fit the end-user developer’s needs very well. The experiences of real end-user developers and prior literature were used in this process. Emphasis has been on those end-user developers, e.g. small business owners, who may have literally nowhere to turn to for support. Adopting the viewpoint of the end-user developer, the thesis examines the question of how an end-user could use a virtual community effectively, improving the results of the support process. Assuming the common situation where the demand for support outstrips the supply.

Design and validation of stateful composite RESTful web services

A web service is a software system that provides a machine-processable interface to the other machines over the network using different Internet protocols. They are being increasingly used in the industry in order to automate different tasks and offer services to a wider audience. The REST architectural style aims at producing scalable and extensible web services using technologies that play well with the existing tools and infrastructure of the web. It provides a uniform set of operation that can be used to invoke a CRUD interface (create, retrieve, update and delete) of a web service. The stateless behavior of the service interface requires that every request to a resource is independent of the previous ones facilitating scalability. Automated systems, e.g., hotel reservation systems, provide advanced scenarios for stateful services that require a certain sequence of requests that must be followed in order to fulfill the service goals. Designing and developing such services for advanced scenarios with REST constraints require rigorous approaches that are capable of creating web services that can be trusted for their behavior. Systems that can be trusted for their behavior can be termed as dependable systems. This thesis presents an integrated design, analysis and validation approach that facilitates the service developer to create dependable and stateful REST web services. The main contribution of this thesis is that we provide a novel model-driven methodology to design behavioral REST web service interfaces and their compositions. The behavioral interfaces provide information on what methods can be invoked on a service and the pre- and post-conditions of these methods. The methodology uses Unified Modeling Language (UML), as the modeling language, which has a wide user base and has mature tools that are continuously evolving. We have used UML class diagram and UML state machine diagram with additional design constraints to provide resource and behavioral models, respectively, for designing REST web service interfaces. These service design models serve as a specification document and the information presented in them have manifold applications. The service design models also contain information about the time and domain requirements of the service that can help in requirement traceability which is an important part of our approach. Requirement traceability helps in capturing faults in the design models and other elements of software development environment by tracing back and forth the unfulfilled requirements of the service. The information about service actors is also included in the design models which is required for authenticating the service requests by authorized actors since not all types of users have access to all the resources. In addition, following our design approach, the service developer can ensure that the designed web service interfaces will be REST compliant. The second contribution of this thesis is consistency analysis of the behavioral REST interfaces. To overcome the inconsistency problem and design errors in our service models, we have used semantic technologies. The REST interfaces are represented in web ontology language, OWL2, that can be part of the semantic web. These interfaces are used with OWL 2 reasoners to check unsatisfiable concepts which result in implementations that fail. This work is fully automated thanks to the implemented translation tool and the existing OWL 2 reasoners. The third contribution of this thesis is the verification and validation of REST web services. We have used model checking techniques with UPPAAL model checker for this purpose. The timed automata of UML based service design models are generated with our transformation tool that are verified for their basic characteristics like deadlock freedom, liveness, reachability and safety. The implementation of a web service is tested using a black-box testing approach. Test cases are generated from the UPPAAL timed automata and using the online testing tool, UPPAAL TRON, the service implementation is validated at runtime against its specifications. Requirement traceability is also addressed in our validation approach with which we can see what service goals are met and trace back the unfulfilled service goals to detect the faults in the design models. A final contribution of the thesis is an implementation of behavioral REST interfaces and service monitors from the service design models. The partial code generation tool creates code skeletons of REST web services with method pre and post-conditions. The preconditions of methods constrain the user to invoke the stateful REST service under the right conditions and the post condition constraint the service developer to implement the right functionality. The details of the methods can be manually inserted by the developer as required. We do not target complete automation because we focus only on the interface aspects of the web service. The applicability of the approach is demonstrated with a pedagogical example of a hotel room booking service and a relatively complex worked example of holiday booking service taken from the industrial context. The former example presents a simple explanation of the approach and the later worked example shows how stateful and timed web services offering complex scenarios and involving other web services can be constructed using our approach.

Computer programs for analysis of droplets sprayed on water sensitive papers

The use of water-sensitive papers is an important tool for assessing the quality of pesticide application on crops, but manual analysis is laborious and time-consuming. Thus, this study aimed to evaluate and compare the results obtained from four software programs for spray droplet analysis in different scanned images of water-sensitive papers. After spraying, papers with four droplet deposition patterns (varying droplet spectra and densities) were analyzed manually and by means of the following computer programs: CIR, e-Sprinkle, DepositScan and Conta-Gotas. The diameter of the volume and number medians and the number of droplets per target area were studied. There is a strong correlation between the values measured using the different programs and the manual analysis, but there is a great difference between the numerical values measured for the same paper. Thus, it is not advisable to compare results obtained from different programs.

Scheduling dynamic dataflow graphs with model checking

With the shift towards many-core computer architectures, dataflow programming has been proposed as one potential solution for producing software that scales to a varying number of processor cores. Programming for parallel architectures is considered difficult as the current popular programming languages are inherently sequential and introducing parallelism is typically up to the programmer. Dataflow, however, is inherently parallel, describing an application as a directed graph, where nodes represent calculations and edges represent a data dependency in form of a queue. These queues are the only allowed communication between the nodes, making the dependencies between the nodes explicit and thereby also the parallelism. Once a node have the su cient inputs available, the node can, independently of any other node, perform calculations, consume inputs, and produce outputs. Data ow models have existed for several decades and have become popular for describing signal processing applications as the graph representation is a very natural representation within this eld. Digital lters are typically described with boxes and arrows also in textbooks. Data ow is also becoming more interesting in other domains, and in principle, any application working on an information stream ts the dataflow paradigm. Such applications are, among others, network protocols, cryptography, and multimedia applications. As an example, the MPEG group standardized a dataflow language called RVC-CAL to be use within reconfigurable video coding. Describing a video coder as a data ow network instead of with conventional programming languages, makes the coder more readable as it describes how the video dataflows through the different coding tools. While dataflow provides an intuitive representation for many applications, it also introduces some new problems that need to be solved in order for data ow to be more widely used. The explicit parallelism of a dataflow program is descriptive and enables an improved utilization of available processing units, however, the independent nodes also implies that some kind of scheduling is required. The need for efficient scheduling becomes even more evident when the number of nodes is larger than the number of processing units and several nodes are running concurrently on one processor core. There exist several data ow models of computation, with different trade-offs between expressiveness and analyzability. These vary from rather restricted but statically schedulable, with minimal scheduling overhead, to dynamic where each ring requires a ring rule to evaluated. The model used in this work, namely RVC-CAL, is a very expressive language, and in the general case it requires dynamic scheduling, however, the strong encapsulation of dataflow nodes enables analysis and the scheduling overhead can be reduced by using quasi-static, or piecewise static, scheduling techniques. The scheduling problem is concerned with nding the few scheduling decisions that must be run-time, while most decisions are pre-calculated. The result is then an, as small as possible, set of static schedules that are dynamically scheduled. To identify these dynamic decisions and to find the concrete schedules, this thesis shows how quasi-static scheduling can be represented as a model checking problem. This involves identifying the relevant information to generate a minimal but complete model to be used for model checking. The model must describe everything that may affect scheduling of the application while omitting everything else in order to avoid state space explosion. This kind of simplification is necessary to make the state space analysis feasible. For the model checker to nd the actual schedules, a set of scheduling strategies are de ned which are able to produce quasi-static schedulers for a wide range of applications. The results of this work show that actor composition with quasi-static scheduling can be used to transform data ow programs to t many different computer architecture with different type and number of cores. This in turn, enables dataflow to provide a more platform independent representation as one application can be fitted to a specific processor architecture without changing the actual program representation. Instead, the program representation is in the context of design space exploration optimized by the development tools to fit the target platform. This work focuses on representing the dataflow scheduling problem as a model checking problem and is implemented as part of a compiler infrastructure. The thesis also presents experimental results as evidence of the usefulness of the approach.

On advancing business intelligence in the electricity retail market

In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.

Cost-efficient virtual machine management : provisioning, admission control, and consolidation

One of the main challenges in Software Engineering is to cope with the transition from an industry based on software as a product to software as a service. The field of Software Engineering should provide the necessary methods and tools to develop and deploy new cost-efficient and scalable digital services. In this thesis, we focus on deployment platforms to ensure cost-efficient scalability of multi-tier web applications and on-demand video transcoding service for different types of load conditions. Infrastructure as a Service (IaaS) clouds provide Virtual Machines (VMs) under the pay-per-use business model. Dynamically provisioning VMs on demand allows service providers to cope with fluctuations on the number of service users. However, VM provisioning must be done carefully, because over-provisioning results in an increased operational cost, while underprovisioning leads to a subpar service. Therefore, our main focus in this thesis is on cost-efficient VM provisioning for multi-tier web applications and on-demand video transcoding. Moreover, to prevent provisioned VMs from becoming overloaded, we augment VM provisioning with an admission control mechanism. Similarly, to ensure efficient use of provisioned VMs, web applications on the under-utilized VMs are consolidated periodically. Thus, the main problem that we address is cost-efficient VM provisioning augmented with server consolidation and admission control on the provisioned VMs. We seek solutions for two types of applications: multi-tier web applications that follow the request-response paradigm and on-demand video transcoding that is based on video streams with soft realtime constraints. Our first contribution is a cost-efficient VM provisioning approach for multi-tier web applications. The proposed approach comprises two subapproaches: a reactive VM provisioning approach called ARVUE and a hybrid reactive-proactive VM provisioning approach called Cost-efficient Resource Allocation for Multiple web applications with Proactive scaling. Our second contribution is a prediction-based VM provisioning approach for on-demand video transcoding in the cloud. Moreover, to prevent virtualized servers from becoming overloaded, the proposed VM provisioning approaches are augmented with admission control approaches. Therefore, our third contribution is a session-based admission control approach for multi-tier web applications called adaptive Admission Control for Virtualized Application Servers. Similarly, the fourth contribution in this thesis is a stream-based admission control and scheduling approach for on-demand video transcoding called Stream-Based Admission Control and Scheduling. Our fifth contribution is a computation and storage trade-o strategy for cost-efficient video transcoding in cloud computing. Finally, the sixth and the last contribution is a web application consolidation approach, which uses Ant Colony System to minimize the under-utilization of the virtualized application servers.

Design and evaluation of web interface signs to improve web usability : a semiotic framework

Technological innovations, the development of the internet, and globalization have increased the number and complexity of web applications. As a result, keeping web user interfaces understandable and usable (in terms of ease-of-use, effectiveness, and satisfaction) is a challenge. As part of this, designing userintuitive interface signs (i.e., the small elements of web user interface, e.g., navigational link, command buttons, icons, small images, thumbnails, etc.) is an issue for designers. Interface signs are key elements of web user interfaces because ‘interface signs’ act as a communication artefact to convey web content and system functionality, and because users interact with systems by means of interface signs. In the light of the above, applying semiotic (i.e., the study of signs) concepts on web interface signs will contribute to discover new and important perspectives on web user interface design and evaluation. The thesis mainly focuses on web interface signs and uses the theory of semiotic as a background theory. The underlying aim of this thesis is to provide valuable insights to design and evaluate web user interfaces from a semiotic perspective in order to improve overall web usability. The fundamental research question is formulated as What do practitioners and researchers need to be aware of from a semiotic perspective when designing or evaluating web user interfaces to improve web usability? From a methodological perspective, the thesis follows a design science research (DSR) approach. A systematic literature review and six empirical studies are carried out in this thesis. The empirical studies are carried out with a total of 74 participants in Finland. The steps of a design science research process are followed while the studies were designed and conducted; that includes (a) problem identification and motivation, (b) definition of objectives of a solution, (c) design and development, (d) demonstration, (e) evaluation, and (f) communication. The data is collected using observations in a usability testing lab, by analytical (expert) inspection, with questionnaires, and in structured and semi-structured interviews. User behaviour analysis, qualitative analysis and statistics are used to analyze the study data. The results are summarized as follows and have lead to the following contributions. Firstly, the results present the current status of semiotic research in UI design and evaluation and highlight the importance of considering semiotic concepts in UI design and evaluation. Secondly, the thesis explores interface sign ontologies (i.e., sets of concepts and skills that a user should know to interpret the meaning of interface signs) by providing a set of ontologies used to interpret the meaning of interface signs, and by providing a set of features related to ontology mapping in interpreting the meaning of interface signs. Thirdly, the thesis explores the value of integrating semiotic concepts in usability testing. Fourthly, the thesis proposes a semiotic framework (Semiotic Interface sign Design and Evaluation – SIDE) for interface sign design and evaluation in order to make them intuitive for end users and to improve web usability. The SIDE framework includes a set of determinants and attributes of user-intuitive interface signs, and a set of semiotic heuristics to design and evaluate interface signs. Finally, the thesis assesses (a) the quality of the SIDE framework in terms of performance metrics (e.g., thoroughness, validity, effectiveness, reliability, etc.) and (b) the contributions of the SIDE framework from the evaluators’ perspective.

Application of the differential display RT-PCR strategy for the identification of inflammation-related mouse genes

The inflammatory response elicited by various stimuli such as microbial products or cytokines is determined by differences in the pattern of cellular gene expression. We have used the differential display RT-PCR (DDRT-PCR) strategy to identify mRNAs that are differentially expressed in various murine cell types stimulated with pro-inflammatory cytokines, microbial products or anti-inflammatory drugs. Mouse embryonic fibroblasts (MEFs) were treated with IFNs, TNF, or sodium salicylate. Also, peritoneal macrophages from C3H/Hej mice were stimulated with T. cruzi-derived GPI-mucin and/or IFN-g. After DDRT-PCR, various cDNA fragments that were differentially represented on the sequencing gel were recovered, cloned and sequenced. Here, we describe a summary of several experiments and show that, when 16 of a total of 28 recovered fragments were tested for differential expression, 5 (31%) were found to represent mRNAs whose steady-state levels are indeed modulated by the original stimuli. Some of the identified cDNAs encode for known proteins that were not previously associated with the inflammatory process triggered by the original stimuli. Other cDNA fragments (8 of 21 sequences, or 38%) showed no significant homology with known sequences and represent new mouse genes whose characterization might contribute to our understanding of inflammation. In conclusion, DDRT-PCR has proven to be a potent technology that will allow us to identify genes that are differentially expressed when cells are subjected to changes in culture conditions or isolated from different organs.

VVER-440 Thermal Hydraulics as a Computer Code Validation Challenge

This thesis concentrates on the validation of a generic thermal hydraulic computer code TRACE under the challenges of the VVER-440 reactor type. The code capability to model the VVER-440 geometry and thermal hydraulic phenomena specific to this reactor design has been examined and demonstrated acceptable. The main challenge in VVER-440 thermal hydraulics appeared in the modelling of the horizontal steam generator. The major challenge here is not in the code physics or numerics but in the formulation of a representative nodalization structure. Another VVER-440 specialty, the hot leg loop seals, challenges the system codes functionally in general, but proved readily representable. Computer code models have to be validated against experiments to achieve confidence in code models. When new computer code is to be used for nuclear power plant safety analysis, it must first be validated against a large variety of different experiments. The validation process has to cover both the code itself and the code input. Uncertainties of different nature are identified in the different phases of the validation procedure and can even be quantified. This thesis presents a novel approach to the input model validation and uncertainty evaluation in the different stages of the computer code validation procedure. This thesis also demonstrates that in the safety analysis, there are inevitably significant uncertainties that are not statistically quantifiable; they need to be and can be addressed by other, less simplistic means, ultimately relying on the competence of the analysts and the capability of the community to support the experimental verification of analytical assumptions. This method completes essentially the commonly used uncertainty assessment methods, which are usually conducted using only statistical methods.

Rigorous development of safety-critical systems

Nowadays, computer-based systems tend to become more complex and control increasingly critical functions affecting different areas of human activities. Failures of such systems might result in loss of human lives as well as significant damage to the environment. Therefore, their safety needs to be ensured. However, the development of safety-critical systems is not a trivial exercise. Hence, to preclude design faults and guarantee the desired behaviour, different industrial standards prescribe the use of rigorous techniques for development and verification of such systems. The more critical the system is, the more rigorous approach should be undertaken. To ensure safety of a critical computer-based system, satisfaction of the safety requirements imposed on this system should be demonstrated. This task involves a number of activities. In particular, a set of the safety requirements is usually derived by conducting various safety analysis techniques. Strong assurance that the system satisfies the safety requirements can be provided by formal methods, i.e., mathematically-based techniques. At the same time, the evidence that the system under consideration meets the imposed safety requirements might be demonstrated by constructing safety cases. However, the overall safety assurance process of critical computerbased systems remains insufficiently defined due to the following reasons. Firstly, there are semantic differences between safety requirements and formal models. Informally represented safety requirements should be translated into the underlying formal language to enable further veri cation. Secondly, the development of formal models of complex systems can be labour-intensive and time consuming. Thirdly, there are only a few well-defined methods for integration of formal verification results into safety cases. This thesis proposes an integrated approach to the rigorous development and verification of safety-critical systems that (1) facilitates elicitation of safety requirements and their incorporation into formal models, (2) simplifies formal modelling and verification by proposing specification and refinement patterns, and (3) assists in the construction of safety cases from the artefacts generated by formal reasoning. Our chosen formal framework is Event-B. It allows us to tackle the complexity of safety-critical systems as well as to structure safety requirements by applying abstraction and stepwise refinement. The Rodin platform, a tool supporting Event-B, assists in automatic model transformations and proof-based verification of the desired system properties. The proposed approach has been validated by several case studies from different application domains.

Measurement of epidermal thickness in a patient with psoriasis by computer-supported image analysis

The aim of the present study was to measure full epidermal thickness, stratum corneum thickness, rete length, dermal papilla widening and suprapapillary epidermal thickness in psoriasis patients using a light microscope and computer-supported image analysis. The data obtained were analyzed in terms of patient age, type of psoriasis, total body surface area involvement, scalp and nail involvement, duration of psoriasis, and family history of the disease. The study was conducted on 64 patients and 57 controls whose skin biopsies were examined by light microscopy. The acquired microscopic images were transferred to a computer and measurements were made using image analysis. The skin biopsies, taken from different body areas, were examined for different parameters such as epidermal, corneal and suprapapillary epidermal thickness. The most prominent increase in thickness was detected in the palmar region. Corneal thickness was more pronounced in patients with scalp involvement than in patients without scalp involvement (t = -2.651, P = 0.008). The most prominent increase in rete length was observed in the knees (median: 491 µm, t = 10.117, P = 0.000). The difference in rete length between patients with a positive and a negative family history was significant (t = -3.334, P = 0.03), being 27% greater in psoriasis patients without a family history. The differences in dermal papilla distances among patients were very small. We conclude that microscope-supported thickness measurements provide objective results.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

Ureases display biological effects independent of enzymatic activity: Is there a connection to diseases caused by urease-producing bacteria?

Ureases are enzymes from plants, fungi and bacteria that catalyze the hydrolysis of urea to form ammonia and carbon dioxide. While fungal and plant ureases are homo-oligomers of 90-kDa subunits, bacterial ureases are multimers of two or three subunit complexes. We showed that some isoforms of jack bean urease, canatoxin and the classical urease, bind to glycoconjugates and induce platelet aggregation. Canatoxin also promotes release of histamine from mast cells, insulin from pancreatic cells and neurotransmitters from brain synaptosomes. In vivo it induces rat paw edema and neutrophil chemotaxis. These effects are independent of ureolytic activity and require activation of eicosanoid metabolism and calcium channels. Helicobacter pylori, a Gram-negative bacterium that colonizes the human stomach mucosa, causes gastric ulcers and cancer by a mechanism that is not understood. H. pylori produces factors that damage gastric epithelial cells, such as the vacuolating cytotoxin VacA, the cytotoxin-associated protein CagA, and a urease (up to 10% of bacterial protein) that neutralizes the acidic medium permitting its survival in the stomach. H. pylori whole cells or extracts of its water-soluble proteins promote inflammation, activate neutrophils and induce the release of cytokines. In this paper we review data from the literature suggesting that H. pylori urease displays many of the biological activities observed for jack bean ureases and show that bacterial ureases have a secretagogue effect modulated by eicosanoid metabolites through lipoxygenase pathways. These findings could be relevant to the elucidation of the role of urease in the pathogenesis of the gastrointestinal disease caused by H. pylori.

Visual analytics for behavioral and niche market segmentation

Companies require information in order to gain an improved understanding of their customers. Data concerning customers, their interests and behavior are collected through different loyalty programs. The amount of data stored in company data bases has increased exponentially over the years and become difficult to handle. This research area is the subject of much current interest, not only in academia but also in practice, as is shown by several magazines and blogs that are covering topics on how to get to know your customers, Big Data, information visualization, and data warehousing. In this Ph.D. thesis, the Self-Organizing Map and two extensions of it – the Weighted Self-Organizing Map (WSOM) and the Self-Organizing Time Map (SOTM) – are used as data mining methods for extracting information from large amounts of customer data. The thesis focuses on how data mining methods can be used to model and analyze customer data in order to gain an overview of the customer base, as well as, for analyzing niche-markets. The thesis uses real world customer data to create models for customer profiling. Evaluation of the built models is performed by CRM experts from the retailing industry. The experts considered the information gained with help of the models to be valuable and useful for decision making and for making strategic planning for the future.