Variability has become an important aspect of modern software-intensive products and systems. In order to reach new markets and utilize existing resources through reuse, it is necessary to have effective management of variants, configurations, and reusable functionality. The topic of this thesis is the construction of feature models that document and describe variability and commonality. The work aims to contribute to methods for creating feature models that are of high quality, suitable for their intended purpose, correct, and usable. The thesis suggests an approach, complementing existing feature modeling methodologies, that contributes to arriving at a satisfactory modeling result. The approach is based on existing practices to raise quality from other research areas, and targets shortcomings in existing feature modeling methods. The requirements for such an approach were derived from an industrial survey and a case study in the automotive domain. The approach was refined and tested in a second case study in the mobile applications domain. The main contributions of the thesis are a quality model for feature models, procedures for prioritizing and evaluating quality in feature models, and an initial set of empirically grounded development principles for reaching certain qualities in feature models. The principal findings of the thesis are that feature models exhibit different qualities, depending on certain characteristics and properties of the model. Such properties can be identified, formalized, and influenced in order to guide development of feature models, and thereby promote certain quality factors of feature models.

QC 20100506

The focus throughout this thesis is on the fatigue characteristics of core materials used insandwich structures. Three sandwich configurations are investigated, two with cellular foamsand one with honeycomb core material These corresponds to typical materials and dimensionsused in the marine and aeronautical industry.A modified four-point bending rig, which enables reversed loading, is successfully used forconstant amplitude fatigue tests of all material configurations. The core materials are tested asused in composite sandwich beams and through the design of the specimens the desiredfailure is in shear of the core. Analyses and inspections during and after the tests supports thetheory that the fracture initiation and fatigue failure occurs in a large zone of the core withwell distributed micro cracks rather than a single propagating crack. The fatigue test resultsare plotted in stress life diagrams including a Weibull type function which provides a goodaccuracy curve fit to the results. The fatigue life of the core materials is found to be reducedwith a increased load ratio, R.The influence on the strength and fatigue performance on sandwich beams with two types ofcore damages, an interfacial disbond and a flawed butt-joint, are experimentally investigated.The fatigue failure initiates at the stress intensity locations which are present due to the predamage.The specimens with flawed butt-joints display a fatigue crack propagation in theinterface between the core and face of the sandwich while the crack propagates through thethickness of the beams where an initial interface flaw is present. A fatigue failure predictionmodel is suggested which utilises the fatigue performance of undamaged beams and thestrength reduction due to the damages. The approach is correlated with results from fatiguetesting and satisfactory correlation is found.A uni-axial fatigue tests method is developed which simplifies the rig and specimenscompared to the four point bend method. A comparison between the results from uni-axialtension/compression fatigue tests and shear fatigue tests shows good correlation, although theR-dependency differs in some cases.The fatigue crack propagation rates are investigated for two configurations: crackspropagating in pure foam core material and cracks propagating in the core material near andalong a sandwich face/core interface. The rate at which a crack propagates stable in the socalled Paris’ regime is extracted for both Mode I and Mode II loading. The agreement betweenthe Mode I crack propagation rate in the pure foam and in the core/face sandwich interfacelayer supports the theory that the crack actually propagates in the sandwich core beneath astiffened resin rich layer present in the face/core interface. The stress intensity thresholds andthe limits at which the crack growth becomes unstable are further established.Acoustic Emission (AE) is used to monitor crack initiation and growth in the core, duringboth static and fatigue loading. It is found that the approximate location of AE-hits can bedetermined which demonstrates that AE has a potential both as an non destructive testing tooland to study the failure process of non-visible sub-surface damages in sandwich structures. / QC 20100520

This thesis studies the problems of feature tracking and motion estimation and presents an application of these concepts to human-computer interaction. The presentation is divided into three parts. The first part addresses feature tracking in a multi-scale context. Features in an image appear at different scales, and these scales can be expected to change over time due to the size variations that occur when objects move relative to the camera. A scheme for feature tracking is presented, which incorporates a mechanism for automatic scale selection and it is argued that such a mechanism is necessary to handle size variations over time. Experiments demonstrate how the proposed scheme is robust to size variations in situations where a traditional fixed scale tracker fails. This leads to extended feature trajectories, which are valuable for motion and structure estimation. It is also shown how an object representation suitable for tracking can be built in a conceptually simple way as a multi-scale feature hierarchy with qualitative relations between features at different scales. Experiments illustrate the capability of the proposed hierarchy to handle occlusions and semirigid objects. The second part of the thesis develops a geometric framework for computing estimates of 3D structure and motion from sparse feature correspondences in monocular sequences. A tool is presented, called the centered affine trifocal tensor, for motion estimation from three affine views. Moreover, a factorization approach is developed which simultaneously handles point and line correspondences in multiple affine views. Experiments show the influence of several factors on the accuracy of the structure and motion estimates, including noise in the feature localization, perspective effects and the number of feature correspondences. This motion estimation framework is also applied to feature correspondences obtained from the abovementioned feature tracker. The last part integrates the functionalities from the first two parts into a pre-prototype system which explores new principles for human-computer interaction. The idea is to transfer 3D orientation to a computer using no other equipment than the operator’s hand. / QC 20100519

The high complexity of modern electronic systems has resulted in a substantial increase in the time-to-market as well as in the cost of design, production, and testing. Recently, in order to reduce the design cost, many electronic systems have employed a core-based system-on-chip (SoC) implementation technique, which integrates pre-defined and pre-verified intellectual property cores into a single silicon die. Accordingly, the testing of manufactured SoCs adopts a modular approach in which test patterns are generated for individual cores and are applied to the corresponding cores separately. Among many techniques that reduce the cost of modular SoC testing, test scheduling is widely adopted to reduce the test application time. This thesis addresses the problem of minimizing the test application time for modular SoC tests with considerations on three critical issues: high testing temperature, temperature-dependent failures, and defect probabilities. High temperature occurs in testing modern SoCs and it may cause damages to the cores under test. We address the temperature-aware test scheduling problem aiming to minimize the test application time and to avoid the temperature of the cores under test exceeding a certain limit. We have developed a test set partitioning and interleaving technique and a set of test scheduling algorithms to solve the addressed problem. Complicated temperature dependences and defect-induced parametric failures are more and more visible in SoCs manufactured with nanometer technology. In order to detect the temperature-dependent defects, a chip should be tested at different temperature levels. We address the SoC multi-temperature testing issue where tests are applied to a core only when the temperature of that core is within a given temperature interval. We have developed test scheduling algorithms for multi-temperature testing of SoCs. Volume production tests often employ an abort-on-first-fail (AOFF) approach which terminates the chip test as soon as the first fault is detected. Defect probabilities of individual cores in SoCs can be used to compute the expected test application time of modular SoC tests using the AOFF approach. We address the defect-probability driven SoC test scheduling problem aiming to minimize the expected test application time with a power constraint. We have proposed techniques which utilize the defect probability to generate efficient test schedules. Extensive experiments based on benchmark designs have been performed to demonstrate the efficiency and applicability of the developed techniques.

This thesis is concerned with modeling of driver behavior based on data collected from real traffic using an advanced instrumented vehicle. In particular, the focus is on driver-following behavior (often called car-following in transport science) for microscopic simulation of road traffic systems. In addition, the modeling methodology developed can be applied for the design of human-centered control algorithms in adaptive cruise control (ACC) and other longitudinal active-safety technologies. Driver behavior is a constant research topic in the modeling of traffic systems and Intelligent Transportation Systems (ITS), which could be traced back to the work of GeneralMotor (GM) Co. in 1950’s. In the early time, researchers were only interested in the development of driver models fulfilling basic physical properties and producing reasonable flow dynamics on a macroscopic level. With the booming interest on driver modeling on a microscopic level and needs in ITS developments, researchers now emphasize modeling using microscopic data acquired from real world. To follow this research trend, a methodological framework on car-following data acquisition, analysis and modeling has been developed step by step in this thesis, and the basic idea is to build a computational model for car-following behavior by exploration of collected data. To carry out the work, different techniques within the field of modern Artificial Intelligence (AI), namely Computational Intelligence (CI)1, have been applied in the research subtasks e.g. information estimation, behavioral regime classification, regime model integration and model estimation. Therefore, a preliminary introduction of the CI methods being used in this thesis work is included in the text. / QC 20100602

This thesis concerns the estimation and description of curvature for computer vision applications. Different types of multi-dimensional data are considered: images (2D); volumes (3D); time sequences of images (3D); and time sequences of volumes (4D). The methods are based on local Fourier domain models and use local operations such as filtering. A hierarchical approach is used. Firstly, the local orientation is estimated and represented with a vector field equivalent description. Secondly, the local curvature is estimated from the orientation description. The curvature algorithms are closely related to the orientation estimation algorithms and the methods as a whole give a unified approach to the estimation and description of orientation and curvature. In addition, the methodology avoids thresholding and premature decision making. Results on both synthetic and real world data are presented to illustrate the algorithms performance with respect to accuracy and noise insensitivity. Examples illustrating the use of the curvature estimates for tasks such as image enhancement are also included.

The extraction of features is necessary for all aspects of image processing and analysis such as classification, segmentation, enhancement and coding. In the course of developing models to describe images, a need arises for description of more complex structures than lines. This need does not reject the importance of line structures but indicates the need to complement and utilize them in a more systematic way. In this thesis, some new methods for extraction of local symmetry features as well as experimental results and applications are presented. The local images are expanded in terms of orthogonal functions with iso-value curves being harmonic functions. Circular, linear, hyperbolic and parabolic structures are studied in particular and some two-step algorithms involving only convolutions are given for detection purposes. Confidence measures with a reliability verified by both theoretical and experimental studies, are proposed. The method is extended to symmetric patterns fulfilling certain general conditions. It is shown that in the general case the resulting algorithms are implementable through the same computing schemes used for detection of linear structures except for a use of different filters. Multidimensional linear symmetry is studied and an application problem in 3-D or in particular, optical flow, and the solution proposed by this general framework is presented. The solution results in a closed form algorithm consisting of two steps, in which spatio-temporal gradient and Gaussian filtering are performed. The result consists of an optical flow estimate minimizing the linear symmetry criterion and a confidence measure based on the minimum error. The frequency band sensitivity of the obtained results is found to be possible to control. Experimental results are presented.

Large-scale networked systems, such as the Internet and server clusters, are omnipresent today. They increasingly deliver services that are critical to both businesses and the society at large, and therefore their continuous and correct operation must be guaranteed. Achieving this requires the realization of adaptive management systems, which continuously reconfigure such large-scale dynamic systems, in order to maintain their state near a desired operating point, despite changes in the networking conditions.The focus of this thesis is continuous real-time monitoring, which is essential for the realization of adaptive management systems in large-scale dynamic environments. Real-time monitoring provides the necessary input to the decision-making process of network management, enabling management systems to perform self-configuration and self-healing tasks.We have developed, implemented, and evaluated a design for real-time continuous monitoring of global metrics with performance objectives, such as monitoring overhead and estimation accuracy. Global metrics describe the state of the system as a whole, in contrast to local metrics, such as device counters or local protocol states, which capture the state of a local entity. Global metrics are computed from local metrics using aggregation functions, such as SUM, AVERAGE and MAX.Our approach is based on in-network aggregation, where global metrics are incrementally computed using spanning trees. Performance objectives are achieved through filtering updates to local metrics that are sent along that tree. A key part in the design is a model for the distributed monitoring process that relates performance metrics to parameters that tune the behavior of a monitoring protocol. The model allows us to describe the behavior of individual nodes in the spanning tree in their steady state. The model has been instrumental in designing a monitoring protocol that is controllable and achieves given performance objectives.We have evaluated our protocol, called A-GAP, experimentally, through simulation and testbed implementation. It has proved to be effective in meeting performance objectives, efficient, adaptive to changes in the networking conditions, controllable along different performance dimensions, and scalable. We have implemented a prototype on a testbed of commercial routers. The testbed measurements are consistent with simulation studies we performed for different topologies and network sizes. This proves the feasibility of the design, and, more generally, the feasibility of effective and efficient real-time monitoring in large network environments. / QC 20100727

In recent years the end-of-life phase has come into focus. European Union directives have been issued regulating certain product groups and producer responsibility. Vehicles and electronic products are the first to be identified and targeted. EU environmental legislation acts as a driver for increased reuse, recycling and recovery. The overall aim of the presented activities has been to increase the effectiveness of current recycling practices, both in terms of design changes and end-of-life treatment process suggestions. A “pre-step” operation has been suggested, in order to either salvage valuable (or toxic) material or to remove diluting bulk material. As this thesis is focused on the recycling of white-goods specifically dishwashers the suggested prestep would be removal of valuable copper prior to shredding. A life cycle assessment (LCA) study has been conducted. The purpose of this study was to determine if using a pre-step is beneficial from an environmental point of view or not. Furthermore, an experiment on the usability of recycled polymers from waste electrical and electronic equipment (WEEE) has been performed. Based on this work polymer recycling process suggestions are presented. Based on research in the fields of design for recycling, design for disassembly and EcoDesign the material hygiene (MH) concept of design for recycling is formulated. This concept is tested on a disassembly field study carried out at a waste collection facility and a polymer recycling experiment at a refrigerator fragmentation plant. Five MH factors are suggested: MH Mix, MH Identification, MH Resources, and MH Weight and MH Map. Additionally, a MH mind-set is presented. / QC 20100816