The meet up between data, processes and structural knowledge in modeling complex enterprise systems is a challenging task that has led to the study of combining formalisms from knowledge representation, database theory, and process management. Moreover, to ensure system correctness, formal verification also comes into play as a promising approach that offers well-established techniques. In line with this, significant results have been obtained within the research on data-aware business processes, which studies the marriage between static and dynamic aspects of a system within a unified framework. However, several limitations are still present. Various formalisms for data-aware processes that have been studied typically use a simple mechanism for specifying the system dynamics. The majority of works also assume a rather simple treatment of inconsistency (i.e., reject inconsistent system states). Many researches in this area that consider structural domain knowledge typically also assume that such knowledge remains fixed along the system evolution (context-independent), and this might be too restrictive. Moreover, the information model of data-aware processes sometimes relies on relatively simple structures. This situation might cause an abstraction gap between the high-level conceptual view that business stakeholders have, and the low-level representation of information. When it comes to verification, taking into account all of the aspects above makes the problem more challenging. In this thesis, we investigate the verification of data-aware processes in the presence of ontologies while at the same time addressing all limitations above. Specifically, we provide the following contributions: (1) We propose a formal framework called Golog-KABs (GKABs), by leveraging on the state of the art formalisms for data-aware processes equipped with ontologies. GKABs enable us to specify semantically-rich data-aware business processes, where the system dynamics are specified using a high-level action language inspired by the Golog programming language. (2) We propose a parametric execution semantics for GKABs that is able to elegantly accommodate a plethora of inconsistency-aware semantics based on the well-known notion of repair, and this leads us to consider several variants of inconsistency-aware GKABs. (3) We enhance GKABs towards context-sensitive GKABs that take into account the contextual information during the system evolution. (4) We marry these two settings and introduce inconsistency-aware context-sensitive GKABs. (5) We introduce the so-called Alternating-GKABs that allow for a more fine-grained analysis over the evolution of inconsistency-aware context-sensitive systems. (6) In addition to GKABs, we introduce a novel framework called Semantically-Enhanced Data-Aware Processes (SEDAPs) that, by utilizing ontologies, enable us to have a high-level conceptual view over the evolution of the underlying system. We provide not only theoretical results, but have also implemented this concept of SEDAPs. We also provide numerous reductions for the verification of sophisticated first-order temporal properties over all of the settings above, and show that verification can be addressed using existing techniques developed for Data-Centric Dynamic Systems (which is a well-established data-aware processes framework), under suitable boundedness assumptions for the number of objects freshly introduced in the system while it evolves. Notably, all proposed GKAB extensions have no negative impact on computational complexity.

Context-aware computing aims at making mobile devices sensitive to the social and physical settings in which they are used. A necessary requirement to achieve this goal is to enable those devices to establish a shared understanding of the desired settings. Establishing a shared understanding entails the need to manipulate sensed data in order to capture a real world situation wholly, conceptually, and meaningfully. Quite often, however, the data acquired from sensors can be inexact, incomplete, and/or uncertain. Inexact sensing arises mostly due to the inherent limitation of sensors to capture a real world phenomenon precisely. Incompleteness is caused by the absence of a mechanism to capture certain real-world aspects; and uncertainty stems from the lack of knowledge about the reliability of the sensing sources, such as their sensing range, accuracy, and resolution. The thesis identifies a set of criteria for a context-aware system to capture dynamic real-world situations. On the basis of these criteria, a distributed architecture is designed, implemented and tested. The architecture consists of Primitive Context Servers, which abstract the acquisition of primitive contexts from physical sensors; Aggregators, to minimise error caused by inconsistent sensing, and to gather correlated primitive contexts pertaining to a particular entity or situation; a Knowledge Base and an Empirical Ambient Knowledge Component, to model dynamic properties of entities with facts and beliefs; and a Composer, to reason about dynamic real-world situations on the basis of sensed data. Two additional components, namely, the Event Handler and the Rule Organiser, are responsible for dynamically generating context rules by associating decision events ? signifying a user?s activity ? with the context in which those decision events are produced. Context-rules are essential elements with which the behaviour of mobile devices can be controlled and useful services can be provided. Four estimation and recognition schemes, namely, Fuzzy Logic, Hidden Markov Models, Dempster-Schafer Theory of Evidence, and Bayesian Networks, are investigated, and their suitability for the implementation of the components of the architecture of the thesis is studied. Subsequently, fuzzy sets are chosen to model dynamic properties of entities. Dempster-Schafer?s combination theory is chosen for aggregating primitive contexts; and Bayesian Networks are chosen to reason about a higher-level context, which is an abstraction of a real-world situation. A Bayesian Composer is implemented to demonstrate the capability of the architecture in dealing with uncertainty, in revising the belief of the Empirical Ambient Knowledge Component, in dealing with the dynamics of primitive contexts and in dynamically defining contextual states. The Composer could be able to reason about the whereabouts of a person in the absence of any localisation sensor. Thermal, relative humidity, light intensity properties of a place as well as time information were employed to model and reason about a place. Consequently, depending on the variety and reliability of the sensors employed, the Composer could be able to discriminate between rooms, corridors, a building, or an outdoor place with different degrees of uncertainty. The Context-Aware E-Pad (CAEP) application is designed and implemented to demonstrate how applications can employ a higher-level context without the need to directly deal with its composition, and how a context rule can be generated by associating the activities (decision events) of a mobile user with the context in which the decision events are produced.

In modern Mobile Ad hoc Networks (MANETs), service discovery is a major component for mobile devices to exchange data and find available services. However, service discovery architectures developed and adopted by the industry either are not appropriate for MANETs or cannot provide security and privacy protection to clients. Service discovery architectures could be either directory-based or directory-less. Both of the two types of architectures suffer from certain security or privacy issues: The directory-based architecture requires a directory server to facilitate communication between service providers and users, which makes the directory server a single point of failure and may harm users’ privacy if the directory server is honestbut- curious; the directory-less architecture solves these two problems but without a trusted directory, the Denial of Service (DoS) attacks can be easily performed on all entities in the system since the mutual authentication between entities consumes significant computational resource. Wi-Fi Aware, a recently introduced Wi-Fi-based connectivity, allows MANETs nodes to discover and connect directly to each other without any infrastructure. Moreover, the size of the message transmitted in this process is large enough (around 255 bytes) for security and privacy protection. So in this thesis, we implemented a Wi-Fi Aware-based decentralized secure service discovery system that allows the clients to directly discover nearby service providers and provide mutual authentication between them without a directory server. In our system we leverage several schemes, including bloom filter, Timed Efficient Stream Loss- Tolerant Authentication (TESLA), and client puzzle. A set of experiments are carried out for the evaluation of the implemented system. The evaluation results show that our system meets most of the security requirements of service discovery architectures with acceptable processing delays. / I moderna moblie ad hoc -nätverk (MANETs) är service discovery en huvudkomponent för noder för att utbyta data och hitta andras tjänster. Men serviceupptäcktsarkitekturerna som utvecklats och antagits av branschen är antingen inte lämpliga i MANET eller kan inte ge kunderna säkerhet och integritetsskydd. service discovery-arkitekturer är katalogbaserade eller kataloglösa. Båda de två arkitekturerna lider av vissa säkerhetseller sekretessproblem: Den katalogbaserade arkitekturen kräver att katalogservern underlättar kommunikationen mellan tjänsteleverantörer och användare, vilket gör katalogservern till en enda felpunkt och kan skada användarnas integritet om katalogservern är ärlig-men-nyfiken; Den kataloglösa arkitekturen löser dessa två problem men utan en pålitlig katalog kan Denial of Service (DoS) -attacker enkelt utföras på alla enheter i systemet eftersom den ömsesidiga autentiseringen mellan enheter förbrukar massor av beräkningsresurser. Nyligen, med den nyaWi-Fi-funktionen som kallas WiFi-Aware cite wifiaware, kan MANET-noder upptäcka och ansluta direkt till varandra utan någon annan typ av anslutning mellan dem . Dessutom är storleken på meddelandet som överförs i denna process tillräckligt stor (cirka 255 byte) för säkerhetsautentisering. Så i denna avhandling implementerade vi ett Wi-Fi Aware-baserat Decentralized Secure service discovery-system som gör att klienterna direkt kan upptäcka närliggande tjänsteleverantörer och tillhandahålla ömsesidig autentisering mellan dem utan en katalogserver. I vårt system används flera system för att skydda vårt system från ovanstående säkerhets- och integritetsfrågor, bland annat blomfilter, Timed Efficient Stream Loss-Tolerant Authentication (TESLA) och klientpussel. En uppsättning utvärderingsförsök utförs för det implementerade systemet. Utvärderingsresultaten visar att vårt system uppfyller de flesta säkerhetskraven för service discovery -arkitekturer med en acceptabel bearbetningsfördröjning.

Wireless Sensor Networks (WSNs) consist of Sensor Nodes (SNs) spatially removed from one another, that can monitor a variety of environmental conditions. SNs then collaboratively communicate the collected information to a central location, by passing along the data in a multi-hop fashion. SN energy resources are limited and energy monitoring and preservation in WSNs are therefore very important. Since multi-hop communication takes place, the routing protocol used may have a significant effect on the balanced use and preservation of energy in the WSN. A significant amount of research has been performed on energy efficient routing in WSNs, but the majority of these studies were only implemented in simulation. The simulation engines used to perform these studies do not take into account all of the relevant environmental factors affecting energy efficiency. In order to comment on the feasibility of a routing protocol meant to improve the energy efficiency of a WSN, it is important to test the routing scheme in a realistic environment. In this study, a SN specifically designed to be used in an energy consumption ascertaining WSN testbed was developed. This SN has a unique set of features which makes it ideal for this application. Each SN is capable of recording its own power consumption. The design also features a lithium battery charging circuit which improves the reusability of the SN. Each node has a detachable sensor module and transceiver module which enables the researcher to conduct experiments using various transceivers and sensors. Twenty of these SNs were then used to form an energy consumption ascertaining WSN testbed. This testbed was used to compare the energy consumption of a Minimum Total Transmission Power Routing (MTTPR) scheme to a shortest hop path routing scheme. The results show that each SN’s transmission power setting dependant efficiency has a significant effect on the overall performance of the MTTPR scheme. The MTTPR scheme might in some cases use more energy than a shortest hop path routing scheme because the transmission power setting dependant efficiency of the transceiver is not taken into account. The MTTPR scheme as well as other similar routing schemes can be improved by taking the transceiver efficiency at different transmission power settings into account. Simulation environments used to evaluate these routing schemes can also be improved by considering the transceiver efficiency at different transmission power settings. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2014

Wireless Sensor Networks (WSNs) consist of Sensor Nodes (SNs) spatially removed from one another, that can monitor a variety of environmental conditions. SNs then collaboratively communicate the collected information to a central location, by passing along the data in a multi-hop fashion. SN energy resources are limited and energy monitoring and preservation in WSNs are therefore very important. Since multi-hop communication takes place, the routing protocol used may have a significant effect on the balanced use and preservation of energy in the WSN. A significant amount of research has been performed on energy efficient routing in WSNs, but the majority of these studies were only implemented in simulation. The simulation engines used to perform these studies do not take into account all of the relevant environmental factors affecting energy efficiency. In order to comment on the feasibility of a routing protocol meant to improve the energy efficiency of a WSN, it is important to test the routing scheme in a realistic environment. In this study, a SN specifically designed to be used in an energy consumption ascertaining WSN testbed was developed. This SN has a unique set of features which makes it ideal for this application. Each SN is capable of recording its own power consumption. The design also features a lithium battery charging circuit which improves the reusability of the SN. Each node has a detachable sensor module and transceiver module which enables the researcher to conduct experiments using various transceivers and sensors. Twenty of these SNs were then used to form an energy consumption ascertaining WSN testbed. This testbed was used to compare the energy consumption of a Minimum Total Transmission Power Routing (MTTPR) scheme to a shortest hop path routing scheme. The results show that each SN’s transmission power setting dependant efficiency has a significant effect on the overall performance of the MTTPR scheme. The MTTPR scheme might in some cases use more energy than a shortest hop path routing scheme because the transmission power setting dependant efficiency of the transceiver is not taken into account. The MTTPR scheme as well as other similar routing schemes can be improved by taking the transceiver efficiency at different transmission power settings into account. Simulation environments used to evaluate these routing schemes can also be improved by considering the transceiver efficiency at different transmission power settings. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2014

This thesis proposed solutions to some shortcomings to current eLearning architectures. The proposed DeLC architecture supports context-aware and adaptable provision of eLearning services and electronic content. The architecture is fully distributed and integrates service-oriented development with agent technology. Central to this architecture is that a node is our unit of computation (known as eLearning node) which can have purely service-oriented architecture, agent-oriented architecture or mixed architecture. Three eLeaerning Nodes have been implemented in order to demonstrate the vitality of the DeLC concept. The Mobile eLearning Node uses a three-level communication network, called InfoStations network, supporting mobile service provision. The services, displayed on this node, are to be aware of its context, gather required learning material and adapted to the learner request. This is supported trough a multi-layered hybrid (service- and agent-oriented) architecture whose kernel is implemented as middleware. For testing of the middleware a simulation environment has been developed. In addition, the DeLC development approach is proposed. The second eLearning node has been implemented as Education Portal. The architecture of this node is poorly service-oriented and it adopts a client-server architecture. In the education portal, there are incorporated education services and system services, called engines. The electronic content is kept in Digital Libraries. Furthermore, in order to facilitate content creators in DeLC, the environment Selbo2 was developed. The environment allows for creating new content, editing available content, as well as generating educational units out of preexisting standardized elements. In the last two years, the portal is used in actual education at the Faculty of Mathematics and Informatics, University of Plovdiv. The third eLearning node, known as Agent Village, exhibits a purely agent-oriented architecture. The purpose of this node is to provide intelligent assistance to the services deployed on the Education Pportal. Currently, two kinds of assistants are implemented in the node - eTesting Assistants and Refactoring eLearning Environment (ReLE). A more complex architecture, known as Education Cluster, is presented in this thesis as well. The Education Cluster incorporates two eLearning nodes, namely the Education Portal and the Agent Village. eLearning services and intelligent agents interact in the cluster.

Recent studies of non-conscious processing have indicated that visually processed non-conscious informationcan be used to influence behaviour after as much as 5000 ms. This study further explores the possibilities of nonconsciousvisual working memory retention. Twelve participants were in this study instructed to memorizemasked faces and then make decisions based on what they believe they saw or guess intuitively. Results indicatethat increased working memory load only affected conscious trials, suggesting non-conscious stimulus remainedunperceived. Since no consciousness effect was observed when measuring response times of congruent trials thisstudy do not support non-conscious working memory retention. / Nya studier av undermedvetet processande har indikerat att visuellt behandlad undermedveten information kananvändas för att påverka beteende efter så mycket som 5000 ms. Denna studie undersöker även möjligheternavad gäller undermedveten inlagring i det visuella arbetsminnet. Tolv deltagare fick i denna studie i uppdrag attmemorera maskade ansikten och sedan fatta beslut utifrån vad de tror att de såg eller gissa intuitivt. Resultatentyder på att ökad belastning av arbetsminnet påverkar endast medvetna försöksomgångarna, vilket tyder på ickemedvetnastimuli förblev osedda. Eftersom ingen medvetandeeffekt observerades vid svarstiderna underkongruenta försök stöder inte denna studien undermedveten lagring av arbetsminnet.

Tragically, traffic accidents involving drivers, motorcyclists and pedestrians result in thousands of fatalities worldwide each year. For this reason, making improvements to road safety and saving people's lives is an international priority. In recent years, this aim has been supported by Intelligent Transport Systems, offering safety systems and providing an intelligent driving environment. The development of wireless communications and mobile ad hoc networks has led to improvements in intelligent transportation systems heightening these systems' safety. Vehicular ad hoc Networks comprise an important technology; included within intelligent transportation systems, they use dedicated short-range communications to assist vehicles to communicate with one another, or with those roadside units in range. This form of communication can reduce road accidents and provide a safer driving environment. A major challenge has been to design an ideal system to filter relevant contextual information from the surrounding environment, taking into consideration the contributory factors necessary to predict the likelihood of a crash with different levels of severity. Designing an accurate and effective pre-crash system to avoid front and back crashes or mitigate their severity is the most important goal of intelligent transportation systems, as it can save people's lives. Furthermore, in order to improve crash prediction, context-aware systems can be used to collect and analyse contextual information regarding contributory factors. The crash likelihood in this study is considered to operate within an uncertain context, and is defined according to the dynamic interaction between the driver, the vehicle and the environment, meaning it is affected by contributory factors and develops over time. As a crash likelihood is considered to be an uncertain context and develops over time, any usable technology must overcome this uncertainty in order to accurately predict crashes. This thesis presents a context-aware pre-crash collision prediction system, which captures information from the surrounding environment, the driver and other vehicles on the road. It utilises a Dynamic Bayesian Network as a reasoning model to predict crash likelihood and severity level, whether any crash will be fatal, serious, or slight. This is achieved by combining the above mentioned information and performing probabilistic reasoning over time. The thesis introduces novel context aware on-board unit architecture for crash prediction. The architecture is divided into three phases: the physical, the thinking and the application phase; these which represent the three main subsystems of a context-aware system: sensing, reasoning and acting. In the thinking phase, a novel Dynamic Bayesian Network framework is introduced to predict crash likelihood. The framework is able to perform probabilistic reasoning to predict uncertainty, in order to accurately predict a crash. It divides crash severity levels according to the UK department for transport, into fatal, serious and slight. GeNIe version 2.0 software was used to implement and verify the Dynamic Bayesian Network model. This model has been verified using both syntactical and real data provided by the UK department for transport in order to demonstrate the prediction accuracy of the proposed model and to demonstrate the importance of including a large amount of contextual information in the prediction process. The evaluation of the proposed system delivered high-fidelity results, when predicting crashes and their severity. This was judged by inputting different sensor readings and performing several experiments. The findings of this study has helped to predict the probability of a crash at different severity levels, accounting for factors that may be involved in causing a crash, thereby representing a valuable step towards creating a safer traffic network.

Recent advances in sensor technologies and the growing interest in context- aware applications, such as targeted advertising and location-based services, have led to a demand for understanding human behavior patterns from sensor data. People engage in routine behaviors. Automatic routine discovery goes beyond low-level activity recognition such as sitting or standing and analyzes human behaviors at a higher level (e.g., commuting to work). The goal of the research presented in this thesis is to automatically discover high-level semantic human routines from low-level sensor streams. One recent line of research is to mine human routines from sensor data using parametric topic models. The main shortcoming of parametric models is that they assume a fixed, pre-specified parameter regardless of the data. Choosing an appropriate parameter usually requires an inefficient trial-and-error model selection process. Furthermore, it is even more difficult to find optimal parameter values in advance for personalized applications. The research presented in this thesis offers a novel nonparametric framework for human routine discovery that can infer high-level routines without knowing the number of latent low-level activities beforehand. More specifically, the frame-work automatically finds the size of the low-level feature vocabulary from sensor feature vectors at the vocabulary extraction phase. At the routine discovery phase, the framework further automatically selects the appropriate number of latent low-level activities and discovers latent routines. Moreover, we propose a new generative graphical model to incorporate multimodal sensor streams for the human activity discovery task. The hypothesis and approaches presented in this thesis are evaluated on public datasets in two routine domains: two daily-activity datasets and a transportation mode dataset. Experimental results show that our nonparametric framework can automatically learn the appropriate model parameters from multimodal sensor data without any form of manual model selection procedure and can outperform traditional parametric approaches for human routine discovery tasks.

Database systems research is an old and well-established field in computer science. Many of the key concepts appeared as early as the 60s, while the core of relational databases, which have dominated the database world for a while now, was solidified during the 80s. However, the underlying hardware has not displayed such stability in the same period, which means that a lot of assumptions that were made about the hardware by early database systems are not necessarily true for modern computer architectures. In particular, over the last few decades there have been two notable consistent trends in the evolution of computer hardware. The first is that the memory hierarchy of mainstream computer systems has been getting deeper, with its different levels moving away from each other, and new levels being added in between as a result, in particular cache memories. The second is that, when it comes to data transfers between any two adjacent levels of the memory hierarchy, access latencies have not been keeping up with transfer rates. The challenge is therefore to adapt database index structures so that they become immune to these two trends. The latter is addressed by gradually increasing the size of the data transfer unit; the former, by organizing the data so that it exhibits good locality for memory transfers across multiple memory boundaries. We have developed novel structures that facilitate both of these strategies. We started our investigation with the venerable B+-tree, which is the cornerstone order-preserving index of any database system, and we have developed a novel pointer-free tree structure for its pages that optimizes its cache performance and makes it immune to the page size. We then adapted our approach to the R-tree and the GiST, making it applicable to multi-dimensional data indexes as well as generalized indexes for any abstract data type. Finally, we have investigated our structure in the context of main memory alone, and have demonstrated its superiority over the established approaches in that setting too. While our research has its roots in data structures and algorithms theory, we have conducted it with a strong experimental focus, as the complex interactions within the memory hierarchy of a modern computer system can be quite challenging to model and theorize about effectively. Our findings are therefore backed by solid experimental results that verify our hypotheses and prove the superiority of our structures over competing approaches.