| 1. |
- Abbaspour Asadollah, Sara
(författare)
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Concurrency Bugs : Characterization, Debugging and Runtime Verification
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Concurrent software has been increasingly adopted in recent years, mainly due to the introduction of multicore platforms. However, concurrency bugs are still difficult to test and debug due to their complex interactions involving multiple threads (or tasks). Typically, real world concurrent software has huge state spaces. Thus, testing techniques and handling of concurrency bugs need to focus on exposing the bugs in this large space. However, existing solutions typically do not provide debugging information to developers (and testers) for understanding the bugs.Our work focuses on improving concurrent software reliability via three contributions: 1) An investigation of concurrent software challenges with the aim to help developers (and testers) to better understand concurrency bugs. We propose a classification of concurrency bugs and discuss observable properties of each type of bug. In addition, we identify a number of gaps in the body of knowledge on concurrent software bugs and their debugging. 2) Exploring concurrency related bugs in real-world software with respect to the reproducibility of bugs, severity of their consequence and effort required to fix them. Our findings here is that concurrency bugs are different from other bugs in terms of their fixing time and severity, while they are similar in terms of reproducibility. 3) A model for monitoring concurrency bugs and the implementation and evaluation of a related runtime verification tool to detect the bugs. In general, runtime verification techniques are used to (a) dynamically verify that the observed behaviour matches specified properties and (b) explicitly recognize understandable behaviors in the considered software. Our implemented tool is used to detect concurrency bugs in embedded software and is in its current form tailored for the FreeRTOS operating system. It helps developers and testers to automatically identify concurrency bugs and subsequently helps to reduce their finding and fixing time.
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| 2. |
- Abbaspour, Sara, 1984-
(författare)
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Electromyogram Signal Enhancement and Upper-Limb Myoelectric Pattern Recognition
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Losing a limb causes difficulties in our daily life. To regain the ability to live an independent life, artificial limbs have been developed. Hand prostheses belong to a group of artificial limbs that can be controlled by the user through the activity of the remnant muscles above the amputation. Electromyogram (EMG) is one of the sources that can be used for control methods for hand prostheses. Surface EMGs are powerful, non-invasive tools that provide information about neuromuscular activity of the subjected muscle, which has been essential to its use as a source of control for prosthetic limbs. However, the complexity of this signal introduces a big challenge to its applications. EMG pattern recognition to decode different limb movements is an important advancement regarding the control of powered prostheses. It has the potential to enable the control of powered prostheses using the generated EMG by muscular contractions as an input. However, its use has yet to be transitioned into wide clinical use. Different algorithms have been developed in state of the art to decode different movements; however, the challenge still lies in different stages of a successful hand gesture recognition and improvements in these areas could potentially increase the functionality of powered prostheses. This thesis firstly focuses on improving the EMG signal’s quality by proposing novel and advanced filtering techniques. Four efficient approaches (adaptive neuro-fuzzy inference system-wavelet, artificial neural network-wavelet, adaptive subtraction and automated independent component analysis-wavelet) are proposed to improve the filtering process of surface EMG signals and effectively eliminate ECG interferences. Then, the offline performance of different EMG-based recognition algorithms for classifying different hand movements are evaluated with the aim of obtaining new myoelectric control configurations that improves the recognition stage. Afterwards, to gain proper insight on the implementation of myoelectric pattern recognition, a wide range of myoelectric pattern recognition algorithms are investigated in real time. The experimental result on 15 healthy volunteers suggests that linear discriminant analysis (LDA) and maximum likelihood estimation (MLE) outperform other classifiers. The real-time investigation illustrates that in addition to the LDA and MLE, multilayer perceptron also outperforms the other algorithms when compared using classification accuracy and completion rate.
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| 3. |
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| 4. |
- Abola, Benard
(författare)
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Perturbed Markov Chains with Damping Component and Information Networks
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis brings together three thematic topics, PageRank of evolving tree graphs, stopping criteria for ranks and perturbed Markov chains with damping component. The commonality in these topics is their focus on ranking problems in information networks. In the fields of science and engineering, information networks are interesting from both practical and theoretical perspectives. The fascinating property of networks is their applicability in analysing broad spectrum of problems and well established mathematical objects. One of the most common algorithms in networks' analysis is PageRank. It was developed for web pages’ ranking and now serves as a tool for identifying important vertices as well as studying characteristics of real-world systems in several areas of applications. Despite numerous successes of the algorithm in real life, the analysis of information networks is still challenging. Specifically, when the system experiences changes in vertices /edges or it is not strongly connected or when a damping stochastic matrix and a damping factor are added to an information matrix. For these reasons, extending existing or developing methods to understand such complex networks is necessary.Chapter 2 of this thesis focuses on information networks with no bidirectional interaction. They are commonly encountered in ecological systems, number theory and security systems. We consider certain specific changes in a network and describe how the corresponding information matrix can be updated as well as PageRank scores. Specifically, we consider the graph partitioned into levels of vertices and describe how PageRank is updated as the network evolves.In Chapter 3, we review different stopping criteria used in solving a linear system of equations and investigate each stopping criterion against some classical iterative methods. Also, we explore whether clustering algorithms may be used as stopping criteria.Chapter 4 focuses on perturbed Markov chains commonly used for the description of information networks. In such models, the transition matrix of an information Markov chain is usually regularised and approximated by a stochastic (Google type) matrix. Stationary distribution of the stochastic matrix is equivalent to PageRank, which is very important for ranking of vertices in information networks. Determining stationary probabilities and related characteristics of singularly perturbed Markov chains is complicated; leave alone the choice of regularisation parameter. We use the procedure of artificial regeneration for the perturbed Markov chain with the matrix of transition probabilities and coupling methods. We obtain ergodic theorems, in the form of asymptotic relations. We also derive explicit upper bounds for the rate of convergence in ergodic relations. Finally, we illustrate these results with numerical examples.
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| 5. |
- Abrahamsson, Henrik
(författare)
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Network overload avoidance by traffic engineering and content caching
- 2012
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The Internet traffic volume continues to grow at a great rate, now driven by video and TV distribution. For network operators it is important to avoid congestion in the network, and to meet service level agreements with their customers. This thesis presents work on two methods operators can use to reduce links loads in their networks: traffic engineering and content caching.This thesis studies access patterns for TV and video and the potential for caching. The investigation is done both using simulation and by analysis of logs from a large TV-on-Demand system over four months.The results show that there is a small set of programs that account for a large fraction of the requests and that a comparatively small local cache can be used to significantly reduce the peak link loads during prime time. The investigation also demonstrates how the popularity of programs changes over time and shows that the access pattern in a TV-on-Demand system very much depends on the content type.For traffic engineering the objective is to avoid congestion in the network and to make better use of available resources by adapting the routing to the current traffic situation. The main challenge for traffic engineering in IP networks is to cope with the dynamics of Internet traffic demands.This thesis proposes L-balanced routings that route the traffic on the shortest paths possible but make sure that no link is utilised to more than a given level L. L-balanced routing gives efficient routing of traffic and controlled spare capacity to handle unpredictable changes in traffic. We present an L-balanced routing algorithm and a heuristic search method for finding L-balanced weight settings for the legacy routing protocols OSPF and IS-IS. We show that the search and the resulting weight settings work well in real network scenarios.
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| 6. |
- Afshar, Sara
(författare)
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Lock-Based Resource Sharing for Real-Time Multiprocessors
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Embedded systems are widely used in the industry and are typically resource constrained, i.e., resources such as processors, I/O devices, shared buffers or shared memory might be limited in the system. Hence, techniques that can enable an efficient usage of processor bandwidths in such systems are of great importance. Locked-based resource sharing protocols are proposed as a solution to overcome resource limitation by allowing the available resources in the system to be safely shared. In recent years, due to a dramatic enhancement in the functionality of systems, a shift from single-core processors to multi-core processors has become inevitable from an industrial perspective to tackle the raised challenges due to increased system complexity. However, the resource sharing protocols are not fully mature for multi-core processors. The two classical multi-core processor resource sharing protocols, spin-based and suspension-based protocols, although providing mutually exclusive access to resources, can introduce long blocking delays to tasks, which may be unacceptable for many industrial applications. In this thesis we enhance the performance of resource sharing protocols for partitioned scheduling, which is the de-facto scheduling standard for industrial real-time multi-core processor systems such as in AUTOSAR, in terms of timing and memory requirements. A new scheduling approach uses a resource efficient hybrid approach combining both partitioned and global scheduling where the partitioned scheduling is used to schedule the major number of tasks in the system. In such a scheduling approach applications with critical task sets use partitioned scheduling to achieve higher level of predictability. Then the unused bandwidth on each core that is remained from partitioning is used to schedule less critical task sets using global scheduling to achieve higher system utilization. These scheduling schema however lacks a proper resource sharing protocol since the existing protocols designed for partitioned and global scheduling cannot be directly applied due to the complex hybrid structure of these scheduling frameworks. In this thesis we propose a resource sharing solution for such a complex structure. Further, we provide the blocking bounds incurred to tasks under the proposed protocols and enhance the schedulability analysis, which is an essential requirement for real-time systems, with the provided blocking bounds.
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| 7. |
- Ahlberg, Carl
(författare)
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Embedded high-resolution stereo-vision of high frame-rate and low latency through FPGA-acceleration
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Autonomous agents rely on information from the surrounding environment to act upon. In the array of sensors available, the image sensor is perhaps the most versatile, allowing for detection of colour, size, shape, and depth. For the latter, in a dynamic environment, assuming no a priori knowledge, stereo vision is a commonly adopted technique. How to interpret images, and extract relevant information, is referred to as computer vision. Computer vision, and specifically stereo-vision algorithms, are complex and computationally expensive, already considering a single stereo pair, with results that are, in terms of accuracy, qualitatively difficult to compare. Adding to the challenge is a continuous stream of images, of a high frame rate, and the race of ever increasing image resolutions. In the context of autonomous agents, considerations regarding real-time requirements, embedded/resource limited processing platforms, power consumption, and physical size, further add up to an unarguably challenging problem.This thesis aims to achieve embedded high-resolution stereo-vision of high frame-rate and low latency, by approaching the problem from two different angles, hardware and algorithmic development, in a symbiotic relationship. The first contributions of the thesis are the GIMME and GIMME2 embedded vision platforms, which offer hardware accelerated processing through FGPAs, specifically targeting stereo vision, contrary to available COTS systems at the time. The second contribution, toward stereo vision algorithms, is twofold. Firstly, the problem of scalability and the associated disparity range is addressed by proposing a segment-based stereo algorithm. In segment space, matching is independent of image scale, and similarly, disparity range is measured in terms of segments, indicating relatively few hypotheses to cover the entire range of the scene. Secondly, more in line with the conventional stereo correspondence for FPGAs, the Census Transform (CT) has been identified as a recurring cost metric. This thesis proposes an optimisation of the CT through a Genetic Algorithm (GA) - the Genetic Algorithm Census Transform (GACT). The GACT shows promising results for benchmark datasets, compared to established CT methods, while being resource efficient.
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| 8. |
- Ahlskog, Mats, 1970-
(författare)
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The fuzzy front end of manufacturing technology development : Exploring the link between the known and the unknown
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- It is well known that a way of competing on a global market is through the introduction of new manufacturing technologies in the production system that can improve product quality as well as contribute to reducing manufacturing time, reduced product price and in the end increased profits. Manufacturing companies that develop and introduce new manufacturing technologies can differentiate themselves from others and thus achieve increased competitiveness.The fuzzy front end of manufacturing technology development is characterized by a high degree of technology uncertainty and challenges due to the lack of access to relevant knowledge, lack of a structured development process, and enough resources that are working with development of new manufacturing technologies.In the literature only a few empirical studies that explore the fuzzy front end of manufacturing technology development can be found. Prior research highlights that little is actually known about what should be done in the fuzzy front end of manufacturing technology development projects, and thus more research is needed. Supporting the fuzzy front end of manufacturing technology development is important to facilitate a successful introduction of new manufacturing technologies, fast time-to-volume and long-term production system development.Based on the above-mentioned importance of developing new manufacturing technology, the objective of the research presented in this thesis is to explore the fuzzy front end of manufacturing technology development. In order to fulfil the objective, empirical data were collected from five case studies conducted in the manufacturing industry. During the empirical studies four important parts were studied: organising, knowledge development, collaboration and the development process.The main findings revealed that development of new manufacturing technology is often conducted in collaboration with external partners and many ad hoc decisions are taken due to lack of a predefined development process for the fuzzy front end of manufacturing technology development. In addition, in the fuzzy front end access to relevant manufacturing knowledge is important and knowledge needs to be developed in order to reduce technology uncertainty.In order to support the fuzzy front end of manufacturing technology development projects, a supporting framework has been developed. The proposed framework is an elaboration of results from the research questions addressed and can be used as a guideline to overcome the challenges observed in the fuzzy front end of manufacturing technology development projects. The framework is built on two important dimensions for innovations, degree of technology uncertainty and degree of novelty. The critical factors identified in the analysis are embedded in the proposed framework as central parts in the fuzzy front end of manufacturing technology development.
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| 9. |
- Ahmed, Mobyen Uddin, 1976-
(författare)
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A Multimodal Approach for Clinical Diagnosis and Treatment
- 2011
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- A computer-aided Clinical Decision Support System (CDSS) for diagnosis and treatment often plays a vital role and brings essential benefits for clinicians. Such a CDSS could function as an expert for a less experienced clinician or as a second option/opinion of an experienced clinician to their decision making task. Nevertheless, it has been a real challenge to design and develop such a functional system where accuracy of the system performance is an important issue. This research work focuses on development of intelligent CDSS based on a multimodal approach for diagnosis, classification and treatment in medical domains i.e. stress and post-operative pain management domains. Several Artificial Intelligence (AI) techniques such as Case-Based Reasoning (CBR), textual Information Retrieval (IR), Rule-Based Reasoning (RBR), Fuzzy Logic and clustering approaches have been investigated in this thesis work. Patient’s data i.e. their stress and pain related information are collected from complex data sources for instance, finger temperature measurements through sensor signals, pain measurements using a Numerical Visual Analogue Scale (NVAS), patient’s information from text and multiple choice questionnaires. The proposed approach considers multimedia data management to be able to use them in CDSSs for both the domains. The functionalities and performance of the systems have been evaluated based on close collaboration with experts and clinicians of the domains. In stress management, 68 measurements from 46 subjects and 1572 patients’ cases out of ≈4000 in post-operative pain have been used to design, develop and validate the systems. In the stress management domain, besides the 68 measurement cases, three trainees and one senior clinician also have been involved in order to conduct the experimental work. The result from the evaluation shows that the system reaches a level of performance close to the expert and better than the senior and trainee clinicians. Thus, the proposed CDSS could be used as an expert for a less experienced clinician (i.e. trainee) or as a second option/opinion for an experienced clinician (i.e. senior) to their decision making process in stress management. In post-operative pain treatment, the CDSS retrieves and presents most similar cases (e.g. both rare and regular) with their outcomes to assist physicians. Moreover, an automatic approach is presented in order to identify rare cases and 18% of cases from the whole cases library i.e. 276 out of 1572 are identified as rare cases by the approach. Again, among the rare cases (i.e. 276), around 57.25% of the cases are classified as ‘unusually bad’ i.e. the average pain outcome value is greater or equal to 5 on the NVAS scale 0 to 10. Identification of rear cases is an important part of the PAIN OUT project and can be used to improve the quality of individual pain treatment.
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| 10. |
- Akan, Batu, 1981-
(författare)
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Planning and Sequencing Through Multimodal Interaction for Robot Programming
- 2014
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Over the past few decades the use of industrial robots has increased the efficiency as well as the competitiveness of several sectors. Despite this fact, in many cases robot automation investments are considered to be technically challenging. In addition, for most small and medium-sized enterprises (SMEs) this process is associated with high costs. Due to their continuously changing product lines, reprogramming costs are likely to exceed installation costs by a large margin. Furthermore, traditional programming methods of industrial robots are too complex for most technicians or manufacturing engineers, and thus assistance from a robot programming expert is often needed. The hypothesis is that in order to make the use of industrial robots more common within the SME sector, the robots should be reprogrammable by technicians or manufacturing engineers rather than robot programming experts. In this thesis, a novel system for task-level programming is proposed. The user interacts with an industrial robot by giving instructions in a structured natural language and by selecting objects through an augmented reality interface. The proposed system consists of two parts: (i) a multimodal framework that provides a natural language interface for the user to interact in which the framework performs modality fusion and semantic analysis, (ii) a symbolic planner, POPStar, to create a time-efficient plan based on the user's instructions. The ultimate goal of this work in this thesis is to bring robot programming to a stage where it is as easy as working together with a colleague.This thesis mainly addresses two issues. The first issue is a general framework for designing and developing multimodal interfaces. The general framework proposed in this thesis is designed to perform natural language understanding, multimodal integration and semantic analysis with an incremental pipeline. The framework also includes a novel multimodal grammar language, which is used for multimodal presentation and semantic meaning generation. Such a framework helps us to make interaction with a robot easier and more natural. The proposed language architecture makes it possible to manipulate, pick or place objects in a scene through high-level commands. Interaction with simple voice commands and gestures enables the manufacturing engineer to focus on the task itself, rather than the programming issues of the robot. The second issue addressed is due to inherent characteristics of communication with the use of natural language; instructions given by a user are often vague and may require other actions to be taken before the conditions for applying the user's instructions are met. In order to solve this problem a symbolic planner, POPStar, based on a partial order planner (POP) is proposed. The system takes landmarks extracted from user instructions as input, and creates a sequence of actions to operate the robotic cell with minimal makespan. The proposed planner takes advantage of the partial order capabilities of POP to execute actions in parallel and employs a best-first search algorithm to seek the series of actions that lead to a minimal makespan. The proposed planner can also handle robots with multiple grippers, parallel machines as well as scheduling for multiple product types.
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