Control algorithms for large scale adaptive optics

In this dissertation, the problem of creating effective large scale Adaptive Optics (AO) systems control algorithms for the new generation of giant optical telescopes is addressed. The effectiveness of AO control algorithms is evaluated in several respects, such as computational complexity, compensation error rejection and robustness, i.e. reasonable insensitivity to the system imperfections. The results of this research are summarized as follows: 1. Robustness study of Sparse Minimum Variance Pseudo Open Loop Controller (POLC) for multi-conjugate adaptive optics (MCAO). The AO system model that accounts for various system errors has been developed and applied to check the stability and performance of the POLC algorithm, which is one of the most promising approaches for the future AO systems control. It has been shown through numerous simulations that, despite the initial assumption that the exact system knowledge is necessary for the POLC algorithm to work, it is highly robust against various system errors. 2. Predictive Kalman Filter (KF) and Minimum Variance (MV) control algorithms for MCAO. The limiting performance of the non-dynamic Minimum Variance and dynamic KF-based phase estimation algorithms for MCAO has been evaluated by doing Monte-Carlo simulations. The validity of simple near-Markov autoregressive phase dynamics model has been tested and its adequate ability to predict the turbulence phase has been demonstrated both for single- and multiconjugate AO. It has also been shown that there is no performance improvement gained from the use of the more complicated KF approach in comparison to the much simpler MV algorithm in the case of MCAO. 3. Sparse predictive Minimum Variance control algorithm for MCAO. The temporal prediction stage has been added to the non-dynamic MV control algorithm in such a way that no additional computational burden is introduced. It has been confirmed through simulations that the use of phase prediction makes it possible to significantly reduce the system sampling rate and thus overall computational complexity while both maintaining the system stable and effectively compensating for the measurement and control latencies.

A comparison of pixel and object-based land cover classification. A case study of the Asmara region, Eritrea

In this paper we compare the performance of two image classification paradigms (object- and pixel-based) for creating a land cover map of Asmara, the capital of Eritrea and its surrounding areas using a Landsat ETM+ imagery acquired in January 2000. The image classification methods used were maximum likelihood for the pixel-based approach and Bhattacharyya distance for the object-oriented approach available in, respectively, ArcGIS and SPRING software packages. Advantages and limitations of both approaches are presented and discussed. Classifications outputs were assessed using overall accuracy and Kappa indices. Pixel- and object-based classification methods result in an overall accuracy of 78% and 85%, respectively. The Kappa coefficient for pixel- and object-based approaches was 0.74 and 0.82, respectively. Although pixel-based approach is the most commonly used method, assessment and visual interpretation of the results clearly reveal that the object-oriented approach has advantages for this specific case-study.

Test Blueprints - Exposing Side Effects in Execution Traces to Support Writing Unit Tests

Writing unit tests for legacy systems is a key maintenance task. When writing tests for object-oriented programs, objects need to be set up and the expected effects of executing the unit under test need to be verified. If developers lack internal knowledge of a system, the task of writing tests is non-trivial. To address this problem, we propose an approach that exposes side effects detected in example runs of the system and uses these side effects to guide the developer when writing tests. We introduce a visualization called Test Blueprint, through which we identify what the required fixture is and what assertions are needed to verify the correct behavior of a unit under test. The dynamic analysis technique that underlies our approach is based on both tracing method executions and on tracking the flow of objects at runtime. To demonstrate the usefulness of our approach we present results from two case studies.

Exploiting Runtime Information in the IDE

Developers rely on the mechanisms provided by their IDE to browse and navigate a large software system. These mechanisms are usually based purely on a system's static source code. The static perspective, however, is not enough to understand an object-oriented program's behavior, in particular if implemented in a dynamic language. We propose to enhance IDEs with a program's runtime information (eg. message sends and type information) to support program comprehension through precise navigation and informative browsing. To precisely specify the type and amount of runtime data to gather about a system under development, dynamically and on demand, we adopt a technique known as partial behavioral reflection. We implemented navigation and browsing enhancements to an IDE that exploit this runtime information in a prototype called Hermion. We present preliminary validation of our experimental enhanced IDE by asking developers to assess its usefulness to understand an unfamiliar software system.

Augmenting Static Source Views in IDEs with Dynamic Metrics

Mainstream IDEs such as Eclipse support developers in managing software projects mainly by offering static views of the source code. Such a static perspective neglects any information about runtime behavior. However, object-oriented programs heavily rely on polymorphism and late-binding, which makes them difficult to understand just based on their static structure. Developers thus resort to debuggers or profilers to study the system's dynamics. However, the information provided by these tools is volatile and hence cannot be exploited to ease the navigation of the source space. In this paper we present an approach to augment the static source perspective with dynamic metrics such as precise runtime type information, or memory and object allocation statistics. Dynamic metrics can leverage the understanding for the behavior and structure of a system. We rely on dynamic data gathering based on aspects to analyze running Java systems. By solving concrete use cases we illustrate how dynamic metrics directly available in the IDE are useful. We also comprehensively report on the efficiency of our approach to gather dynamic metrics.

A reliable, traffic-adaptive and energy-efficient link layer for wireless sensor networks

The paper presents a link layer stack for wireless sensor networks, which consists of the Burst-aware Energy-efficient Adaptive Medium access control (BEAM) and the Hop-to-Hop Reliability (H2HR) protocol. BEAM can operate with short beacons to announce data transmissions or include data within the beacons. Duty cycles can be adapted by a traffic prediction mechanism indicating pending packets destined for a node and by estimating its wake-up times. H2HR takes advantage of information provided by BEAM such as neighbour information and transmission information to perform per-hop congestion control. We justify the design decisions by measurements in a real-world wireless sensor network testbed and compare the performance with other link layer protocols.

Assimilation of Compliance Software in Highly Regulated Industries: An Empirical Multitheoretical Investigation

In this paper we follow a theory-based approach to study the assimilation of compliance software in highly regulated multinational enterprises. These relatively new software products support the automation of controls which are associated with mandatory compliance requirements. We use institutional and success factor theories to explain the assimilation of compliance software. A framework for analyzing the assimilation of Access Control Systems (ACS), a special type of compliance software, is developed and used to reflect the experiences obtained in four in-depth case studies. One result is that coercive, mimetic, and normative pressures significantly effect ACS assimilation. On the other hand, quality aspects have only a moderate impact at the beginning of the assimilation process, in later phases the impact may increase if performance and improvement objectives become more relevant. In addition, it turns out that position of the enterprises and compatibility heavily influence the assimilation process.

NextServe Framework: Supporting Services Over Content-Centric Networking

The future Internet architecture aims to reformulate the way the content/service is requested to make it location-independent. Information-Centric Networking is a new network paradigm, which tries to achieve this goal by making content objects identified and requested by name instead of address. In this paper, we extend Information-Centric Networking architecture to support services in order to be requested and invoked by names. We present NextServe framework, which is a service framework with a human-readable self-explanatory naming scheme. NextServe is inspired by the object-oriented programming paradigm and is applicable with real-world scenarios.

Towards cheap, accurate polymorphism detection

Polymorphism, along with inheritance, is one of the most important features in object-oriented languages, but it is also one of the biggest obstacles to source code comprehension. Depending on the run-time type of the receiver of a message, any one of a number of possible methods may be invoked. Several algorithms for creating accurate call-graphs using static analysis already exist, however, they consume significant time and memory resources. We propose an approach that will combine static and dynamic analysis and yield the best possible precision with a minimal trade-off between used resources and accuracy.

An initiative for participatory monitoring of large scale acquisitions: Opportunities and results thus far

Increasing commercial pressures on land are provoking fundamental and far-reaching changes in the relationships between people and land. Much knowledge on land-oriented investments projects currently comes from the media. Although this provides a good starting point, lack of transparency and rapidly changing contexts mean that this is often unreliable. The International Land Coalition, in partnership with Oxfam Novib, Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), University of Pretoria, Centre for Development and Environment of the University of Bern (CDE), and GIZ, started to compile an inventory of land-related investments. This project aims to better understand the extent, trends and impacts of land-related investments by supporting an ongoing and systematic stocktaking exercise of the various investment projects currently taking place worldwide. It involves a large number of organizations and individuals working in areas where land transactions are being made, and able to provide details of such investments. The project monitors land transactions in rural areas that imply a transformation of land use rights from communities and smallholders to commercial use, and are made both by domestic and foreign investors (private actors, governments, government-back private investors). The focus is on investments for food or agrofuel production, timber extraction, carbon trading, mineral extraction, conservation and tourism. A novel way of using ITC to document land acquisitions in a spatially explicit way and by using an approach called “crowdsourcing” is being developed. This approach will allow actors to share information and knowledge directly and at any time on a public platform, where it will be scrutinized in terms of reliability and cross checked with other sources. Up to now, over 1200 deals have been recorded across 96 countries. Details of such transactions have been classified in a matrix and distributed to over 350 contacts worldwide for verification. The verified information has been geo-referenced and represented in two global maps. This is an open database enabling a continued monitoring exercise and the improvement of data accuracy. More information will be released over time. The opportunities arise from overcoming constraints by incomplete information by proposing a new way of collecting, enhancing and sharing information and knowledge in a more democratic and transparent manner. The intention is to develop interactive knowledge platform where any interested person can share and access information on land deals, their link to involved stakeholders, and their embedding into a geographical context. By making use of new ICT technologies that are more and more in the reach of local stakeholders, as well as open access and web-based spatial information systems, it will become possible to create a dynamic database containing spatial explicit data. Feeding in data by a large number of stakeholders, increasingly also by means of new mobile ITC technologies, will open up new opportunities to analyse, monitor and assess highly dynamic trends of land acquisition and rural transformation.

A Demonstration of Mobility Prediction as a Service in Cloudified LTE Networks

Location prediction has attracted a significant amount of research effort. Being able to predict users’ movement benefits a wide range of communication systems, including location-based service/applications, mobile access control, mobile QoS provision, and resource management for mobile computation and storage management. In this demo, we present MOBaaS, which is a cloudified Mobility and Bandwidth prediction services that can be instantiated, deployed, and disposed on-demand. Mobility prediction of MOBaaS provides location predictions of a single/group user equipments (UEs) in a future moment. This information can be used for self-adaptation procedures and optimal network function configuration during run-time operations. We demonstrate an example of real-time mobility prediction service deployment running on OpenStack platform, and the potential benefits it bring to other invoking services.