A SOA-based Framework for Multi-Devices and Multi-Platform User Interfaces

This thesis reports investigations on applying the Service Oriented Architecture (SOA) approach in the engineering of multi-platform and multi-devices user interfaces. This study has three goals: (1) analyze the present frameworks for developing multi-platform and multi-devices applications, (2) extend the principles of SOA for implementing a multi-platform and multi-devices architectural framework (SOA-MDUI), (3) applying and validating the proposed framework in the context of a specific application. One of the problems addressed in this ongoing research is the large amount of combinations for possible implementations of applications on different types of devices. Usually it is necessary to take into account the operating system (OS), user interface (UI) including the appearance, programming language (PL) and architectural style (AS). Our proposed approach extended the principles of SOA using patterns-oriented design and model-driven engineering approaches. Synthesizing the present work done in these domains, this research built and tested an engineering framework linking Model-driven Architecture (MDA) and SOA approaches to developing of UI. This study advances general understanding of engineering, deploying and managing multi-platform and multi-devices user interfaces as a service.

Agent-based management systems for many-core platforms : rigorous design and efficient implementation

Due to various advantages such as flexibility, scalability and updatability, software intensive systems are increasingly embedded in everyday life. The constantly growing number of functions executed by these systems requires a high level of performance from the underlying platform. The main approach to incrementing performance has been the increase of operating frequency of a chip. However, this has led to the problem of power dissipation, which has shifted the focus of research to parallel and distributed computing. Parallel many-core platforms can provide the required level of computational power along with low power consumption. On the one hand, this enables parallel execution of highly intensive applications. With their computational power, these platforms are likely to be used in various application domains: from home use electronics (e.g., video processing) to complex critical control systems. On the other hand, the utilization of the resources has to be efficient in terms of performance and power consumption. However, the high level of on-chip integration results in the increase of the probability of various faults and creation of hotspots leading to thermal problems. Additionally, radiation, which is frequent in space but becomes an issue also at the ground level, can cause transient faults. This can eventually induce a faulty execution of applications. Therefore, it is crucial to develop methods that enable efficient as well as resilient execution of applications. The main objective of the thesis is to propose an approach to design agentbased systems for many-core platforms in a rigorous manner. When designing such a system, we explore and integrate various dynamic reconfiguration mechanisms into agents functionality. The use of these mechanisms enhances resilience of the underlying platform whilst maintaining performance at an acceptable level. The design of the system proceeds according to a formal refinement approach which allows us to ensure correct behaviour of the system with respect to postulated properties. To enable analysis of the proposed system in terms of area overhead as well as performance, we explore an approach, where the developed rigorous models are transformed into a high-level implementation language. Specifically, we investigate methods for deriving fault-free implementations from these models into, e.g., a hardware description language, namely VHDL.

User Experience of Geocaching and Its Application to Tourism and Education

Advances in technology have provided new ways of using entertainment and game technology to foster human interaction. Games and playing with games have always been an important part of people’s everyday lives. Traditionally, human-computer interaction (HCI) research was seen as a psychological cognitive science focused on human factors, with engineering sciences as the computer science part of it. Although cognitive science has made significant progress over the past decade, the influence of people’s emotions on design networks is increasingly important, especially when the primary goal is to challenge and entertain users (Norman 2002). Game developers have explored the key issues in game design and identified that the driving force in the success of games is user experience. User-centered design integrates knowledge of users’ activity practices, needs, and preferences into the design process. Geocaching is a location-based treasure hunt game created by a community of players. Players use GPS (Global Position System) technology to find “treasures” and create their own geocaches; the game can be developed when the players invent caches and used more imagination to creations the caches. This doctoral dissertation explores user experience of geocaching and its applications in tourism and education. Globally, based on the Geocaching.com webpage, geocaching has been played about 180 countries and there are more than 10 million registered geocachers worldwide (Geocaching.com, 25.11.2014). This dissertation develops and presents an interaction model called the GameFlow Experience model that can be used to support the design of treasure hunt applications in tourism and education contexts. The GameFlow Model presents and clarifies various experiences; it provides such experiences in a real-life context, offers desirable design targets to be utilized in service design, and offers a perspective to consider when evaluating the success of adventure game concepts. User-centered game designs have adapted to human factor research in mainstream computing science. For many years, the user-centered design approach has been the most important research field in software development. Research has been focusing on user-centered design in software development such as office programs, but the same ideas and theories that will reflect the needs of a user-centered research are now also being applied to game design (Charles et al. 2005.) For several years, we have seen a growing interest in user experience design. Digital games are experience providers, and game developers need tools to better understand the user experience related to products and services they have created. This thesis aims to present what the user experience is in geocaching and treasure hunt games and how it can be used to develop new concepts for the treasure hunt. Engineers, designers, and researchers should have a clear understanding of what user experience is, what its parts are, and most importantly, how we can influence user satisfaction. In addition, we need to understand how users interact with electronic products and people, and how different elements synergize their experiences. This doctoral dissertation represents pioneering work on the user experience of geocaching and treasure hunt games in the context of tourism and education. The research also provides a model for game developers who are planning treasure hunt concepts.

Death switch for gene therapy: application to erythropoietin transgene expression

The effectiveness of the caspase-9-based artificial "death switch" as a safety measure for gene therapy based on the erythropoietin (Epo) hormone was tested in vitro and in vivo using the chemical inducer of dimerization, AP20187. Plasmids encoding the dimeric murine Epo, the tetracycline-controlled transactivator and inducible caspase 9 (ptet-mEpoD, ptet-tTAk and pSH1/Sn-E-Fv’-Fvls-casp9-E, respectively) were used in this study. AP20187 induced apoptosis of iCasp9-modified C2C12 myoblasts. In vivo, two groups of male C57BI/6 mice, 8-12 weeks old, were injected intramuscularly with 5 µg/50 g ptet-mEpoD and 0.5 µg/50 g ptet-tTAk. There were 20 animals in group 1 and 36 animals in group 2. Animals from group 2 were also injected with the 6 µg/50 g iCasp9 plasmid. Seventy percent of the animals showed an increase in hematocrit of more than 65% for more than 15 weeks. AP20187 administration significantly reduced hematocrit and plasma Epo levels in 30% of the animals belonging to group 2. TUNEL-positive cells were detected in the muscle of at least 50% of the animals treated with AP20187. Doxycycline administration was efficient in controlling Epo secretion in both groups. We conclude that inducible caspase 9 did not interfere with gene transfer, gene expression or tetracycline control and may be used as a safety mechanism for gene therapy. However, more studies are necessary to improve the efficacy of this technique, for example, the use of lentivirus vector.

Poly(3-hydroxybutyrate-co-3-hydroxyhexanoate)-based scaffolds for tissue engineering

Development and selection of an ideal scaffold is of importance for tissue engineering. Poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (PHBHHx) is a biocompatible bioresorbable copolymer that belongs to the polyhydroxyalkanoate family. Because of its good biocompatibility, PHBHHx has been widely used as a cell scaffold for tissue engineering. This review focuses on the utilization of PHBHHx-based scaffolds in tissue engineering. Advances in the preparation, modification, and application of PHBHHx scaffolds are discussed.

Enthalpy-entropy compensation based on isotherms of mango

Moisture equilibrium data of mango pulp were determined using the static gravimetric method. Adsorption and desorption isotherms were obtained in the range of 30-70 ºC, to water activities (a w) from 0.02 to 0.97. The application of the GAB model to the experimental results, using direct nonlinear regression analysis, provided agreement between experimental and calculated values. The net isosteric heat of sorption was estimated from equilibrium sorption data, using the Clausius-Clapeyron equation. Isosteric heats of sorption were found to increase with increasing temperature and could be well adjusted by an exponential relationship. The enthalpy-entropy compensation theory was applied to sorption isotherms and plots of deltaH versus deltaS provided the isokinetic temperatures, indicating an enthalpy controlled sorption process.

Load balancing in P2P smartphone based distributed IoT systems

With the new age of Internet of Things (IoT), object of everyday such as mobile smart devices start to be equipped with cheap sensors and low energy wireless communication capability. Nowadays mobile smart devices (phones, tablets) have become an ubiquitous device with everyone having access to at least one device. There is an opportunity to build innovative applications and services by exploiting these devices’ untapped rechargeable energy, sensing and processing capabilities. In this thesis, we propose, develop, implement and evaluate LoadIoT a peer-to-peer load balancing scheme that can distribute tasks among plethora of mobile smart devices in the IoT world. We develop and demonstrate an android-based proof of concept load-balancing application. We also present a model of the system which is used to validate the efficiency of the load balancing approach under varying application scenarios. Load balancing concepts can be apply to IoT scenario linked to smart devices. It is able to reduce the traffic send to the Cloud and the energy consumption of the devices. The data acquired from the experimental outcomes enable us to determine the feasibility and cost-effectiveness of a load balanced P2P smart phone-based applications.

Power Consumption Measurement and Scenario Based Energy Model in Wearable Computing Applications

The power is still today an issue in wearable computing applications. The aim of the present paper is to raise awareness of the power consumption of wearable computing devices in specific scenarios to be able in the future to design energy efficient wireless sensors for context recognition in wearable computing applications. The approach is based on a hardware study. The objective of this paper is to analyze and compare the total power consumption of three representative wearable computing devices in realistic scenarios such as Display, Speaker, Camera and microphone, Transfer by Wi-Fi, Monitoring outdoor physical activity and Pedometer. A scenario based energy model is also developed. The Samsung Galaxy Nexus I9250 smartphone, the Vuzix M100 Smart Glasses and the SimValley Smartwatch AW-420.RX are the three devices representative of their form factors. The power consumption is measured using PowerTutor, an android energy profiler application with logging option and using unknown parameters so it is adjusted with the USB meter. The result shows that the screen size is the main parameter influencing the power consumption. The power consumption for an identical scenario varies depending on the wearable devices meaning that others components, parameters or processes might impact on the power consumption and further study is needed to explain these variations. This paper also shows that different inputs (touchscreen is more efficient than buttons controls) and outputs (speaker sensor is more efficient than display sensor) impact the energy consumption in different way. This paper gives recommendations to reduce the energy consumption in healthcare wearable computing application using the energy model.

Sensor communication in Smart cities and regions: An efficient IoT-based remote health monitoring system

Recent advances in Information and Communication Technology (ICT), especially those related to the Internet of Things (IoT), are facilitating smart regions. Among many services that a smart region can offer, remote health monitoring is a typical application of IoT paradigm. It offers the ability to continuously monitor and collect health-related data from a person, and transmit the data to a remote entity (for example, a healthcare service provider) for further processing and knowledge extraction. An IoT-based remote health monitoring system can be beneficial in rural areas belonging to the smart region where people have limited access to regular healthcare services. The same system can be beneficial in urban areas where hospitals can be overcrowded and where it may take substantial time to avail healthcare. However, this system may generate a large amount of data. In order to realize an efficient IoT-based remote health monitoring system, it is imperative to study the network communication needs of such a system; in particular the bandwidth requirements and the volume of generated data. The thesis studies a commercial product for remote health monitoring in Skellefteå, Sweden. Based on the results obtained via the commercial product, the thesis identified the key network-related requirements of a typical remote health monitoring system in terms of real-time event update, bandwidth requirements and data generation. Furthermore, the thesis has proposed an architecture called IReHMo - an IoT-based remote health monitoring architecture. This architecture allows users to incorporate several types of IoT devices to extend the sensing capabilities of the system. Using IReHMo, several IoT communication protocols such as HTTP, MQTT and CoAP has been evaluated and compared against each other. Results showed that CoAP is the most efficient protocol to transmit small size healthcare data to the remote servers. The combination of IReHMo and CoAP significantly reduced the required bandwidth as well as the volume of generated data (up to 56 percent) compared to the commercial product. Finally, the thesis conducted a scalability analysis, to determine the feasibility of deploying the combination of IReHMo and CoAP in large numbers in regions in north Sweden.

Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

Implementation of Quantitative Reaction-based Model Refinement

Building a computational model for complex biological systems is an iterative process. It starts from an abstraction of the process and then incorporates more details regarding the specific biochemical reactions which results in the change of the model fit. Meanwhile, the model’s numerical properties such as its numerical fit and validation should be preserved. However, refitting the model after each refinement iteration is computationally expensive resource-wise. There is an alternative approach which ensures the model fit preservation without the need to refit the model after each refinement iteration. And this approach is known as quantitative model refinement. The aim of this thesis is to develop and implement a tool called ModelRef which does the quantitative model refinement automatically. It is both implemented as a stand-alone Java application and as one of Anduril framework components. ModelRef performs data refinement of a model and generates the results in two different well known formats (SBML and CPS formats). The development of this tool successfully reduces the time and resource needed and the errors generated as well by traditional reiteration of the whole model to perform the fitting procedure.

Development of 3D super-resolution tomographic STED microscopy and its application to studies on bone resorption

In this doctoral thesis, a tomographic STED microscopy technique for 3D super-resolution imaging was developed and utilized to observebone remodeling processes. To improve upon existing methods, wehave used a tomographic approach using a commercially available stimulated emission depletion (STED) microscope. A certain region of interest (ROI) was observed at two oblique angles: one at a standard inverted configuration from below (bottom view) and another from the side (side view) via a micro-mirror positioned close to the ROI. The two viewing angles were reconstructed into a final tomogram. The technique, named as tomographic STED microscopy, was able to achieve an axial resolution of approximately 70 nm on microtubule structures in a fixed biological specimen. High resolution imaging of osteoclasts (OCs) that are actively resorbing bone was achieved by creating an optically transparent coating on a microscope coverglass that imitates a fractured bone surface. 2D super-resolution STED microscopy on the bone layer showed approximately 60 nm of lateral resolution on a resorption associated organelle allowing these structures to be imaged with super-resolution microscopy for the first time. The developed tomographic STED microscopy technique was further applied to study resorption mechanisms of OCs cultured on the bone coating. The technique revealed actin cytoskeleton with specific structures, comet-tails, some of which were facing upwards and some others were facing downwards. This, in our opinion, indicated that during bone resorption, an involvement of the actin cytoskeleton in vesicular exocytosis and endocytosis is present. The application of tomographic STED microscopy in bone biology demonstrated that 3D super-resolution techniques can provide new insights into biological 3D nano-structures that are beyond the diffraction-limit when the optical constraints of super-resolution imaging are carefully taken into account.

Production of magnesium carbonates from serpentinites for CO2 mineral sequestration : optimisation towards industrial application

Global warming is one of the most alarming problems of this century. Initial scepticism concerning its validity is currently dwarfed by the intensification of extreme weather events whilst the gradual arising level of anthropogenic CO2 is pointed out as its main driver. Most of the greenhouse gas (GHG) emissions come from large point sources (heat and power production and industrial processes) and the continued use of fossil fuels requires quick and effective measures to meet the world’s energy demand whilst (at least) stabilizing CO2 atmospheric levels. The framework known as Carbon Capture and Storage (CCS) – or Carbon Capture Utilization and Storage (CCUS) – comprises a portfolio of technologies applicable to large‐scale GHG sources for preventing CO2 from entering the atmosphere. Amongst them, CO2 capture and mineralisation (CCM) presents the highest potential for CO2 sequestration as the predicted carbon storage capacity (as mineral carbonates) far exceeds the estimated levels of the worldwide identified fossil fuel reserves. The work presented in this thesis aims at taking a step forward to the deployment of an energy/cost effective process for simultaneous capture and storage of CO2 in the form of thermodynamically stable and environmentally friendly solid carbonates. R&D work on the process considered here began in 2007 at Åbo Akademi University in Finland. It involves the processing of magnesium silicate minerals with recyclable ammonium salts for extraction of magnesium at ambient pressure and 400‐440⁰C, followed by aqueous precipitation of magnesium in the form of hydroxide, Mg(OH)2, and finally Mg(OH)2 carbonation in a pressurised fluidized bed reactor at ~510⁰C and ~20 bar PCO2 to produce high purity MgCO3. Rock material taken from the Hitura nickel mine, Finland, and serpentinite collected from Bragança, Portugal, were tested for magnesium extraction with both ammonium sulphate and bisulphate (AS and ABS) for determination of optimal operation parameters, primarily: reaction time, reactor type and presence of moisture. Typical efficiencies range from 50 to 80% of magnesium extraction at 350‐450⁰C. In general ABS performs better than AS showing comparable efficiencies at lower temperature and reaction times. The best experimental results so far obtained include 80% magnesium extraction with ABS at 450⁰C in a laboratory scale rotary kiln and 70% Mg(OH)2 carbonation in the PFB at 500⁰C, 20 bar CO2 pressure for 15 minutes. The extraction reaction with ammonium salts is not at all selective towards magnesium. Other elements like iron, nickel, chromium, copper, etc., are also co‐extracted. Their separation, recovery and valorisation are addressed as well and found to be of great importance. The assessment of the exergetic performance of the process was carried out using Aspen Plus® software and pinch analysis technology. The choice of fluxing agent and its recovery method have a decisive sway in the performance of the process: AS is recovered by crystallisation and in general the whole process requires more exergy (2.48–5.09 GJ/tCO2sequestered) than ABS (2.48–4.47 GJ/tCO2sequestered) when ABS is recovered by thermal decomposition. However, the corrosive nature of molten ABS and operational problems inherent to thermal regeneration of ABS prohibit this route. Regeneration of ABS through addition of H2SO4 to AS (followed by crystallisation) results in an overall negative exergy balance (mainly at the expense of low grade heat) but will flood the system with sulphates. Although the ÅA route is still energy intensive, its performance is comparable to conventional CO2 capture methods using alkanolamine solvents. An energy‐neutral process is dependent on the availability and quality of nearby waste heat and economic viability might be achieved with: magnesium extraction and carbonation levels ≥ 90%, the processing of CO2‐containing flue gases (eliminating the expensive capture step) and production of marketable products.

PERFORMANCE ANALYSIS OF A TACTICAL ASSET ALLOCATION – Evidence from the Black–Litterman model based fixed income portfolio

Over time the demand for quantitative portfolio management has increased among financial institutions but there is still a lack of practical tools. In 2008 EDHEC Risk and Asset Management Research Centre conducted a survey of European investment practices. It revealed that the majority of asset or fund management companies, pension funds and institutional investors do not use more sophisticated models to compensate the flaws of the Markowitz mean-variance portfolio optimization. Furthermore, tactical asset allocation managers employ a variety of methods to estimate return and risk of assets, but also need sophisticated portfolio management models to outperform their benchmarks. Recent development in portfolio management suggests that new innovations are slowly gaining ground, but still need to be studied carefully. This thesis tries to provide a practical tactical asset allocation (TAA) application to the Black–Litterman (B–L) approach and unbiased evaluation of B–L models’ qualities. Mean-variance framework, issues related to asset allocation decisions and return forecasting are examined carefully to uncover issues effecting active portfolio management. European fixed income data is employed in an empirical study that tries to reveal whether a B–L model based TAA portfolio is able outperform its strategic benchmark. The tactical asset allocation utilizes Vector Autoregressive (VAR) model to create return forecasts from lagged values of asset classes as well as economic variables. Sample data (31.12.1999–31.12.2012) is divided into two. In-sample data is used for calibrating a strategic portfolio and the out-of-sample period is for testing the tactical portfolio against the strategic benchmark. Results show that B–L model based tactical asset allocation outperforms the benchmark portfolio in terms of risk-adjusted return and mean excess return. The VAR-model is able to pick up the change in investor sentiment and the B–L model adjusts portfolio weights in a controlled manner. TAA portfolio shows promise especially in moderately shifting allocation to more risky assets while market is turning bullish, but without overweighting investments with high beta. Based on findings in thesis, Black–Litterman model offers a good platform for active asset managers to quantify their views on investments and implement their strategies. B–L model shows potential and offers interesting research avenues. However, success of tactical asset allocation is still highly dependent on the quality of input estimates.

Hydrogen Sensor Application of Anodic Titanium Oxide Nanostructures

Hydrogen (H2) fuel cells have been considered a promising renewable energy source. The recent growth of H2 economy has required highly sensitive, micro-sized and cost-effective H2 sensor for monitoring concentrations and alerting to leakages due to the flammability and explosiveness of H2 Titanium dioxide (TiO2) made by electrochemical anodic oxidation has shown great potential as a H2 sensing material. The aim of this thesis is to develop highly sensitive H2 sensor using anodized TiO2. The sensor enables mass production and integration with microelectronics by preparing the oxide layer on suitable substrate. Morphology, elemental composition, crystal phase, electrical properties and H2 sensing properties of TiO2 nanostructures prepared on Ti foil, Si and SiO2/Si substrates were characterized. Initially, vertically oriented TiO2 nanotubes as the sensing material were obtained by anodizing Ti foil. The morphological properties of tubes could be tailored by varying the applied voltages of the anodization. The transparent oxide layer creates an interference color phenomena with white light illumination on the oxide surface. This coloration effect can be used to predict the morphological properties of the TiO2 nanostructures. The crystal phase transition from amorphous to anatase or rutile, or the mixture of anatase and rutile was observed with varying heat treatment temperatures. However, the H2 sensing properties of TiO2 nanotubes at room temperature were insufficient. H2 sensors using TiO2 nanostructures formed on Si and SiO2/Si substrates were demonstrated. In both cases, a Ti layer deposited on the substrates by a DC magnetron sputtering method was successfully anodized. A mesoporous TiO2 layer obtained on Si by anodization in an aqueous electrolyte at 5°C showed diode behavior, which was influenced by the work function difference of Pt metal electrodes and the oxide layer. The sensor enabled the detection of H2 (20-1000 ppm) at low operating temperatures (50–140°C) in ambient air. A Pd decorated tubular TiO2 layer was prepared on metal electrodes patterned SiO2/Si wafer by anodization in an organic electrolyte at 5°C. The sensor showed significantly enhanced H2 sensing properties, and detected hydrogen in the range of a few ppm with fast response/recovery time. The metal electrodes placed under the oxide layer also enhanced the mechanical tolerance of the sensor. The concept of TiO2 nanostructures on alternative substrates could be a prospect for microelectronic applications and mass production of gas sensors. The gas sensor properties can be further improved by modifying material morphologies and decorating it with catalytic materials.