https://www.mdu.se/

Experience is one of the most valuable assets technicians and engineer have and may have been collected during many years and both from successful solutions as well as from very costly mistakes. Unfortunately industry rarely uses a systematic approach for experience reuse. This may be caused by the lack of efficient tools facilitating experience distribution and reuse. We propose a case-based approach and tool to facilitate experience reuse more systematically in industry. It is important that such a tool allows the technicians to give the problem case in a flexible way to increase acceptance and use. The proposed tool enables more structured handling of experience and is flexible and can be adapted to different situations and problems. The user is able to input text in a structured way and possibly in combination with other numeric or symbolic features. The system is able to identify and retrieve relevant similar experiences for reuse.

Industry has to adjust quickly to changes in their surroundings, for example reducing staff during recession and increasing staff when the market demands it. These factors may cause rapid loss of experience, collected during many years, or require experienced staff to spend considerable resources in training new staff, instead of focusing on production. This is recognised as very costly for companies and organisations today and also reduces competitiveness and productivity. Condition Monitoring, diagnostics and selection of efficient preventive or corrective actions is a task that often requires a high degree of expertise. This expertise is often gained through sometimes very expensive mistakes and can take many years to acquire leading to a few skilled experts. When they are not available due to changes in staff or retirements the company often faces serious problems that may be very expensive, e.g. leading to a reduced productivity.

If some deviation occurs in a machine, a fault report is often written; an engineer makes a diagnosis and may order spare parts to repair the machine. Fault report, spare parts, required time and statistics on performance after repair are often stored in different databases but so far not systematically reused. In this paper we present a Case-Based experience sharing system that enables reuse of experience in a more efficient way compared with what is mostly practiced in industry today. The system uses Case-Based-Reasoning (CBR) and limited Natural Language Processing. An important aspect of the experience management tool is that it is user-friendly and web-based to promote efficient experience sharing. The system should be able to handle both experiences that are only in house as well as sharing experience with other industries when there is no conflicting interest. Such a CBR based tool enables efficient experience gathering, management and reuse in production industries. The tool will facilitate the users with an interactive environment to communicate with each other for sharing their experiences. Depend on the user; the security level of the system will be varied to share knowledge among the collaborating companies.

The system identifies the most relevant experiences to assess and resolve the current situation. The experience is stored and retrieved as a case in the collaborative space where experience from various companies may have been stored under many years. Reusing experience and avoiding expensive mistakes will increase the participating companies' competitiveness and also transfer valuable experience to their employees. One of the benefits is also the opportunity and facility to identify people with similar tasks and problems at different companies and enable them to share their experience, e.g. if a technician has solved a similar problem recently and is in the near, the most efficient solution may be to call the expert and ask for assistance. In future, one may access this tool through his/her mobile device via wireless or mobile communications using Global Positioning System, GPS, enables the system to suggest experts nearby, willing and able to share the knowledge and quickly assist in resolve the problem.

A decision support system (DSS) was implemented based on a fuzzy logic inference system (FIS) to provide assistance in dose alteration of Duodopa infusion in patients with advanced Parkinson's disease, using data from motor state assessments and dosage. Three-tier architecture with an object oriented approach was used. The DSS has a web enabled graphical user interface that presents alerts indicating non optimal dosage and states, new recommendations, namely typical advice with typical dose and statistical measurements. One data set was used for design and tuning of the FIS and another data set was used for evaluating performance compared with actual given dose. Overall goodness-of-fit for the new patients (design data) was 0.65 and for the ongoing patients (evaluation data) 0.98. User evaluation is now ongoing. The system could work as an assistant to clinical staff for Duodopa treatment in advanced Parkinson's disease.

Scheduling theory generally assumes that real-time systems are mostly composed of activities with hard real-time requirements. Many systems are built today by composing different applications or components in the same system, leading to a mixture of many different kinds of requirements with small parts of the system having hard real-time requirements and other larger parts with requirements for more flexible scheduling and for quality of service. Hard real-time scheduling techniques are extremely pessimistic for the latter part of the application, and consequently it is necessary to use techniques that let the system resources be fully utilized to achieve the highest possible quality. This paper presents a framework for a scheduling architecture that provides the ability to compose several applications or components into the system, and to flexibly schedule the available resources while guaranteeing hard real-time requirements. The framework (called FSF) is independent of the underlying implementation, and can run on different underlying scheduling strategies. It is based on establishing service contracts that represent the complex and flexible requirements of the applications, and which are managed by the underlying system to provide the required level of service.

Software components need to be evaluated at several points during their life cycle, by different actors and for different purposes. Besides the quality assurance performed by component developers, there are two main activities which include evaluation of components: component selection (i.e. evaluation performed by the system developer in order to select the best fit component to use in a system) and an envisioned component certification (i.e. evaluation made by an independent actor in order to increase the trust in the component). This paper examines the fundamental similarities and differences between these two types of component evaluations and elaborates how these fit in the overall process views of component-based development for both COTS-based development and software product line development.

A modeling process is presented for extracting timingaccurate simulation models from complex embedded real-time systems. The process is supported by two complementary methods for tool-supported model extraction, Model Synthesis and Hybrid Model Extraction. The generated models enable impact analysis for complex real-time systems with respect to dynamic system properties, such as timing and resource usage. This can make software maintenance more predictable with respect to time-to-market and development costs, since timing errors can be identified early and avoided. The contribution of the paper is the modeling process, the Hybrid Model Extraction method and an interactive modeling tool, MASS, designed to support Hybrid Model Extraction of large implementations in C.

A problem in common of many complex software systems embedded in industrial

products is the absence of analyzability as formal models of the system

behavior does not exist. When performing maintenance of such systems it is

hard to predict how changes will impact specific system properties related to

timing and resource utilization and there is therefore a significant risk of running

into problems with unexpected side-effects of the changes made, which

increases development time required and costs.

In this paper we present the ART Framework, a set of methods and tools

that enable behavior impact analysis for existing industrial real-time systems.

The ART Framework enables developers of complex software systems to identify

problematic side-effects of a proposed design before vast resources have

been invested in implementation and testing. This reduces the risk of expensive

and time-consuming problems discovered late in a development project

and also reduces the risk releasing software containing latent critical errors.

The phase-noise theory and design of a differential CMOS LC-tank VCO with double switch pair is presented. A formula for the minimum achievable phase noise in the 1/f2 region is derived. The 2.15 to 2.35GHz 0.3μm CMOS VCO has a phase noise of -143.9dBc/Hz at 3MHz offset and draws 4mA from a 2.5V supply.

This paper presents a study of phase noise in CMOS Colpitts and LC-tank oscillators. Closed-form symbolic formulas for the 1/f² phase-noiseregion are derived for both the Colpitts oscillator (either single-ended or differential) and the LC-tank oscillator, yielding highly accurate results under very general assumptions. A comparison between the differential Colpitts and the LC-tank oscillator is also carried out, which shows that the latter is capable of a 2-dB lower phase-noise flgure-of-merit (FoM) when simplified oscillator designs and ideal MOS models are adopted. Several prototypesof both Colpitts and LC-tank oscillators have been implemented in a 0.35-μm CMOS process. The best performance of the LC-tank oscillatorsshows a phase noise of - 142 dBc/Hz at 3-MHz offset frequency from a 2.9-GHz carrier with a 16-mW power consumption, resulting in an excellent FoM of ∼189 dBc/Hz. For the same oscillation frequency, the FoM displayed by the differential Colpitts oscillators is ∼5 dB lower.

The aim of this study is to design and develop a low-power wireless A/D-converter that should be easy to integrate with other technologies or infrastructures at a low cost. This transmitting unit should be able to replace many of the signal wires between biomedical sensors connecting the patient and the sampling unit or supervision equipment. The model of today is an embedded hardware solution with two processors (FPGA and Bluetooth). A twelve bit ADC with a 1 kHz-sampling rate then converts an analogue signal that simulates an ECG-signal with typical frequencies. The communication between the ADC and Bluetooth™ is serial and controlled by the FPGA. The remote PC runs a simple software that controls the Bluetooth™ and processes the received data. The results indicate that it is possible to continuously transmit an ECG-signal without loosing data.

In this paper, some of the factors that affect classification performance of EEG based Brain-Computer Interfaces (BCI) is studied. Study is specified on P300 speller system which is also an EEG based BCI system. P300 is a physiological signal that represents a response of brain to a given stimulus which occurs right 300ms afier the stimulus onset. When this signal occurs, it changes the continuous EEG some micro volts. Since this is not a very distinguished change, some other physiological signals (movement of muscles and heart, blinking or other neural activities) may distort this signal. In order to understand if there is really a P300 component in the signal, consecutive P300 epochs are averaged over trials. In this study, we have been tried two different multi channel data handling methods with two different frequency windows. Resulted data have been classified using Support Vector Machines (SVM). It has been shown that proposed method has a better classification performance.

This paper discusses how the early phases of developing embedded electronic systems can be improved by enhanced modelling of cost and performance that includes explicithandling of uncertainties. The approach is to add cost information to existing UML models,capture uncertainties using probability distributions, and use Monte Carlo simulation to analyze the risk of not reaching the cost targets. It is demonstrated how the information obtained can be used when evaluating different architecture alternatives, while including both development and product cost as well as risk in the trade-off

In this paper, we present a general framework which allows the designer to specify a wide range of criteria for allocation. Major factors considered as part of our framework are mixed criticalities of tasks, schedulability, power consumption, fault-tolerance, and dependability requirements in addition to typical functional aspects such as memory constraints. This being a global optimization problem, we are forced to use meta-heuristic algorithms, and we were able to represent these requirements in a very intuitive manner by the usage of energy functions in simulated annealing. We envision the proposed methodology as a quite simple, scalable, as well as computationally effective solution covering a wide range of system architectures and solution spaces. 

Real-time systems typically have to satisfy complex requirements mapped to the timing attributes of the tasks that are eventually guaranteed by the underlying scheduler. These systems consist of a mix of hard and soft tasks with varying criticalities as well as associated fault tolerance (FT) requirements. Often time redundancy techniques are preferred in many embedded applications and hence it is extremely important to devise appropriate methodologies for scheduling real-time tasks under fault assumptions. Additionally, the relative criticality of tasks could undergo changes during the evolution of the system. Hence scheduling decisions under fault assumptions have to reflect all these important factors in addition to the resource constraints.

In this paper we propose a framework for 'FTfeasibility', i.e., to provide a priori guarantees that all critical tasks in the system will meet their deadlines even in case of faults. Our main objective here is to ensure FTfeasibility of all critical tasks in the system and do so with minimal costs and without any fundamental changes in the scheduling paradigm. We demonstrate its applicability in scenarios where the FT strategy employed is re-execution of the affected tasks or an alternate action upon occurrence of transient faults or software design faults. We analyse a feasible set of tasks and propose methods to adapt it to varying FT requirements without modifications to the underlying scheduler. We do so by reassigning task attributes to achieve FT-feasibility while keeping the costs minimised.

A prerequisite for creating a safe and predictable real time computer system is to have knowledge about its

timing behavior during operation. The Worst Case Execution Time (WCET) is one of the key values to

consider when predicting this timing behavior, since it ensures that every task meets its deadline in the

system. A missed deadline in systems with critical tasks can lead to severe consequences.

Dynamic WCET analysis is a widely used method to derive WCET value in the industry today. The

method is based on using simulation and measurement techniques. The WCET value is derived by

performing a set of automatic tests on the system and measure its execution time. To ensure that a safe

WCET value is derived the automatic tests must cover the worst case scenario, which is tough to find when

the systems increase in size and complexity.

Static WCET analysis is an alternative method, where it is guaranteed that an overestimated WCET value is

obtained. The method uses mathematical models of the system hard and software to calculate WCET.

Therefore, this method has been the main research subject for many research groups. One of the key

components in making a safe and tight WCET value, using static WCET analysis technique, is program

flow information.

The information describes the possible program flows through the program; this information can be either

provided to the WCET analyzer manually, by user, or automatically, by a flow analyzer. Deriving flow

information manually is done by:

• Studying and analyzing the program source code, and manually calculating loop bounds,

detecting infeasible paths and making recursion bounds.

• Providing the information to a WCET analyzer, usually by writing them in form of

annotations in a program language supported by the analyzer.

The steps above are time consuming and unsafe when the program complexity increases, that makes it

preferable to use flow analysis to provide flow information. This has been shown in a previous study at

Volvo Construction Equipment, where the WCET analysis tool aiT has been used. This work will complete

the study by evaluating an automatic method, using flow analyzers to derive flow information for the

analyzed code.

Flow analyzers use mathematical methods to model and derive flow information of program source code.

This flow information makes deriving WCET estimates safe, simple and requires no or minimum user

interaction. Therefore, Volvo CE is interested in the development of static WCET analysis tools where the

flow information is obtained automatically.

This work evaluated SWEdish Execution time Tool (SWEET), a prototype WCET analysis tool built by a

research group from Malardalens University (MDH). The results are compared to the ones obtained in

previous work using aiT, where the flow information is derived manually.

We have found that SWEET derived the same flow information that was derived manually, but since it is a

prototype tool a lot of manual work was needed. The manual work consisted mainly of adapting the Volvo

CE application to the SWEET analysis environment. This work has also contributed in development of

SWEET, adding new functionality and making it more users friendly.

A static Worst-Case Execution Time (WCET) analysis derives upper bounds for the execution times of programs. Such analysts requires information about the possible program flows. The current practice is to provide this information manually, which can be laborious and error-prone. An alternative is to derive this information through an automated flow analysis. In this article, we present a case study where an automatic flowanalysis method was tested on industrial real-time system code. The same code was the subject of an earlier WCET case study, where it was analysed using manual annotations for the flow information. The purpose of the current study was to see to which extent the same flow information could be found automatically. The results show that for the most part this is indeed possible, and we could derive comparable WCET estimates using the automatically generated flow information. In addition, valuable insights were gained on what is needed to make flow analysis methods work on real production code. 

Increased exposure to stress may cause serious health problems leading to long term sick leave if undiagnosed and untreated. The practice amongst clinicians' to use a standardized procedure measuring blood pressure, ECG, finger temperature, breathing speed etc. to make a reliable diagnosis of stress and stress sensitivity is increasing. But even with these measurements it is still difficult to diagnose due to large individual variations. A computer-based system as a second option for the assessment and diagnosis of individual stress level is valuable in this domain.

A combined approach based on a calibration phase and case-based reasoning is proposed exploiting data from finger temperature sensor readings from 24 individuals. In calibration phase, a standard clinical procedure with six different steps helps to establish a person's stress profile and set up a number of individual parameters. When acquiring a new case, patients are also asked to provide a fuzzy evaluation on how reliable was the procedure to define the case itself. Such a reliability "level" could be used to further discriminate among similar cases. The system extracts key features from the signal and classifies individual sensitivity to stress. These features are stored into a case library and similarity measurements are taken to assess the degrees of matching and create a ranked list containing the most similar cases retrieved by using the nearest-neighbor algorithm.

A current case (CC) is compared with two other stored cases (C_92 and C_115) in the case library. The global similarity between the case CC and case C_92 is 67% and case CC and case C_115 is 80% shown by the system. So the case C_115 has ranked higher than the case C_92 and is more similar to current case CC. If necessary, the solution for the best matching case can be revised by the clinician to fit the new patient. The current problem with confirmed solution is then retained as a new case and added to the case library for future use.

The system allows us to utilize previous experience and at the same time diagnose stress along with a stress sensitivity profile. This information enables the clinician to make a more informed decision of treatment plan for the patients. Such a system may also be used to actively notify a person's stress levels even in the home environment.

Increased exposure to stress may cause health problems. An experi-enced clinician is able to diagnose a person's stress level based on sensor read-ings. Large individual variations and absence of general rules make it difficult to diagnose stress and the risk of stress-related health problems. A decision sup-port system providing clinicians with a second opinion would be valuable. We propose a novel solution combining case-based reasoning and fuzzy logic along with a calibration phase to diagnose individual stress. During calibration a num-ber of individual parameters are established. The system also considers the feedback from the patient on how well the test was performed. The system uses fuzzy logic to incorporating the imprecise characteristics of the domain. The cases are also used for the individual treatment process and transfer experience between clinicians. The validation of the approach is based on close collabora-tion with experts and measurements from 24 persons used as reference.

Diagnosing stress is difficult even for experts due to large individual variations. Clinician's use today manual test procedures where they measure blood pressure, ECG, finger temperature and breathing speed during a number of exercises. An experienced clinician makes diagnosis on different readings shown in a computer screen. There are only very few experts who are able to diagnose and predict stress-related problems. In this paper we have proposed a combined approach based on a calibration phase and case-based reasoning to provide assistance in diagnosing stress, using data from the finger temperature sensor readings. The calibration phase helps to establish a number of individual parameters. The system uses a case-based reasoning approach and also feedback on how well the patient succeeded with the different test, used for giving similar cases reliability estimates.

The increasing use of digital patient records in hospital saves both time and reduces risks wrong treatments caused by lack of information. Digital patient records also enable efficient spread and transfer of experience gained from diagnosis and treatment of individual patient. This is today mostly manual (speaking with col-leagues) and rarely aided by computerized system. Most of the content in patient re-cords is semi-structured textual information. In this paper we propose a hybrid tex-tual case-based reasoning system promoting experience reuse based on structured or unstructured patient records, case-based reasoning and similarity measurement based on cosine similarity metric improved by a domain specific ontology and the nearest neighbor method. Not only new cases are learned, hospital staff can also add comments to existing cases and the approach enables prototypical cases.

In the medical literature there are a number of physiological reactions related to cognitive activities. Psychosocial and psychophysiological stress is such activities reflected in physiological reactions. Stress related symptoms are highly individual, but decreased hands temperature is the common for most individuals. A clinician learns with experience how to interpret the different symptoms but there is no adaptive diagnostic system for diagnosing stress. Decision support systems (DSS) diagnosing stress would be valuable both for junior clinicians and as second opinion for experts. Due to the large individual variations and no general set of rules, DSS are difficult to build for this task. The proposed solution combines a calibration phase with case-based reason¬ing approach and fuzzification of cases. During the calibration phase a number of individual parameters and case specific fuzzy membership functions are es-tablishes. This case-based approach may help the clinician to make a diagnosis, classification and treatment plan. The case may also be used to follow the treat-ment progress. This may be done using the proposed system. Initial tests show promising results. The individual cases including calibration and fuzzy mem-bership functions may also be used in an autonomous system in home environ-ment for treatment programs for individuals often under high stress.

This paper presents a methodology to formulate natural language rules for an adaptive neuro-fuzzy system based on discovered knowledge, supported by prior knowledge and statistical modeling. These rules could be improved using statistical methods and neural nets. This gives clinicians a valuable tool to explore the importance of different variables and their relations in a disease and could aid treatment selection. A prototype using the proposed methodology has been used to induce an Adaptive Neuro Fuzzy Inference Model that has been used to "discover" relationships between fluctuation, treatment and disease severity in Parkinson. Preliminary results from this project are promising and show that Neuro-fuzzy techniques in combination with statistical methods may offer medical research and medical applications a useful combination of methods.

Real-time control algorithms are designed based on the

characteristics of the controlled plants and they require good

performance without delays. However, digital control implementation

typically introduces delays and jitters due to insufficient CPU

processing power and the limitations of the real-time scheduling

method used. This can degrade the system performance or even make it

unstable.

In this paper we propose an integrated approach for control design

and real-time scheduling, suitable for both discrete-time and

continuous-time controllers. It guarantees system performance by

accepting a certain minimum value of jitter for control tasks and

feasibly schedules them together with other tasks in the system.

Results from comparison with other approaches from real-time and

control theory domains underline the effectiveness of our method.

Real-time control algorithms are designed based on the characteristics of the controlled plants and they require good performance without delays. However, digital control implementation typically introduces delays and jitters due to insufficient CPU processing power and the limitations of the real-time scheduling method used. This can degrade the system performance or even make it unstable. In this paper we propose an integrated approach for control design and real-time scheduling, suitable for both discrete-time and continuous-time controllers. It guarantees system performance by accepting a certain minimum value of jitter for control tasks and feasibly schedules them together with other tasks in the system. Results from comparison with other approaches from real-time and control theory domains underline the effectiveness of our method.

Independent subsystem abstraction allows subsystems to be developed and validated separately and supports an easier subsystem integration. In particular, this approach is desirable in open systems, since it does not require knowledge of temporal behaviour of other subsystems. However, independent

abstraction, assuming the worst-case CPU supply pattern, requires extra CPU allocations. We present our work in progress on dynamic slack reclamation, which keeps track of such extra CPU allocations at run time. We are also investigating how to utilize those extra resources for supporting soft real-time tasks.

We present our ongoing work to support the difficult, time consuming, and error-prone process of subsystem integration in the real-time domain. Our work will result in methods where independently developed subsystems, including both hard real-time and soft real-time functions, can be easily integrated without resulting unpredictable timing behaviour. The methods will also facilitate subsystem reuse, since a subsystem can easily be integrated in a new environment. Related research and methods are presented, together with our ongoing work in the area.

This paper presents a protocol for resource sharing in a hierarchical real-time scheduling framework. Together, the protocol and the scheduling framework significantly reduce the efforts and errors associated with integrating multiple semi-independent subsystems on a single processor. Thus, our proposed techniques facilitate modern software development processes, where subsystems are developed by independent teams (or subcontractors) and at a later stage integrated into a single product. Using our solution, a subsystem need not know, and is not dependent on, the timing behaviour of other subsystems; even though they share mutually exclusive resources. In this paper we also prove the correctness of our approach and evaluate its efficiency.

Engineers of embedded software systems rely on efficient design techniques and tools along with efficient run-time support. In the design of complex embedded real-time systems, the Hierarchical Scheduling Framework (HSF) has been introduced as a design-time framework enabling compositional schedulability analysis of embedded software systems with real-time properties. Moreover, the HSF provides a run-time framework guaranteeing that these non-functional requirements are met. In this paper a system consists of a number of semi-independent components called subsystems, and these subsystems are allowed to share logical resources. The HSF makes sure that the individual subsystems respect their allocated CPU budgets. However, as semi-independent sub-systems share logical resources, extra complexity is introduced. Specifically, the contribution of this paper is a novel method to allow for budget overruns; a common scenario when a subsystem utilizes shared logical resources. This proposed method is not only more resource efficient than existing methods, but it is also more appropriate for supporting composability of independently developed real-time subsystems.

The gender question in computer science is often presented as: "Why are there so few women in computer science and what can be done about that?"This question usually focuses on women. Sometimes "men" or "gender" enter the discussions. However, it is not common that the second part of the sentence - computer science - is considered.The papers in this thesis challenge, in different ways, how the gender question is usually perceived and discussed within the community of computer scientists, and where solutions are looked for.The approach taken is to move focus from women/gender to the discipline of computer science itself. This means the question is raised towards a more general level,towards "the science question", discussing the discipline, its paradigms and knowledge processes.Theories and methodologies from gender research, used within computer science, offer new possibilities to develop broader and more complex understandings of "the gender question in computer science".

In this thesis I explore feminist technoscience strategies in computer science, starting in “the gender question in computer science”, and ending up in communication and translation between feminist technoscience research and computer science educational practice. Necessary parts in this work concern issues of boundary crossings between disciplines, and focusing on the foundations of computer science: what it means to “know computer science”. The point of departure is in computer science (CS), in particular CS education. There are at this starting point two intertwined issues: the gender question in computer science (often formulated as “what to do about the situation of women in computer science?”) and the foundation question: “what does it mean to know computer science?”. These are not primarily questions looking for answers; they are calls for action, for change and transformation. The main focus and goal of this thesis concerns how to broaden the meaning of “knowing computer science”; to accommodate epistemological pluralism and diversity within the practices and among the practitioners of CS. I have identified translation as fundamental, to make feminist research and epistemological perspectives communicable into the community of computer science practitioners. In this, questions of knowledge and how knowledge is perceived and talked about are central. Communication and translation also depend on the ability and willingness to cross boundaries, to engage in “world-travelling” (Lugones). Additional issues of importance are asking questions open enough to invite to dialogues, and upholding critical (self) reflection. An important goal for feminist research is transformation. Because of this, interventions have been part of my research, interventions in which I myself am implicated. The work has been based in feminist epistemological thinking, where the concepts of positioning and partial perspectives (Haraway) have been of particular importance.

In this paper, we present our ongoing work on shared stack analysis for hybrid (static and dynamic) scheduled fixed priority systems. We present two methods that extend our previous work to support stack analysis for the general tasks model with offsets where several transactions can share a common run-time stack. The aim of this work is to support stack analysis of a wider range of systems. 

Abstract Interpretation is a well known formal framework for abstracting programming language semantics. It provides a systematic way of building static analyses which can be used for optimisation and debugging purposes. Different semantic properties can be captured by so-called abstract domains which then easily can be combined in various ways to yield more precise analyses. The most known abstract domain is probably the one of intervals. An analysis using the interval domain yields bindings of each integer-valued program variable to an interval at each program point. The interval is the smallest interval that contains the set of integers possible for that particular variable to assume at that program point during execution. Abstract interpretation can be used in many contexts, such as in debugging, program transformation, correctness proving, Worst Case Execution Time analysis etc.

In 1989 Philippe Granger introduced a static analysis of arithmetical congruences. The analysis is formulated as an abstract interpretation computing the smallest (wrt. inclusion) congruence (residue) class that includes the set of possible values that that variable may assume during execution. The result of the analysis is a binding of each integer-valued variable at each program point to a congruence class. Applications for this analysis include automatic vectorisation, pointer analysis (for determining pointer strides) and loop-bound analysis (for detecting loops with non-unit strides). However, in the original presentation, the analysis is not well suited to use on realistic low-level code. By low-level code we mean either compiled and linked object code where high-level constructions has been replaced with target-specific assembly code, or code in a higher-level language written in a fashion close to the hardware. A good example of low-level code is code written for embedded systems which often is using advantages of the target hardware and/or using a lot of bit-level operations. Code for embedded systems is an increasingly important target for analysis, since it is often safety-critical. The reason that the congruence domain in its original presentation is not suitable for low-level code is mainly due to the three following properties of low-level code: A) Bit-level operations are commonly used in low-level code. Programs that contain bit-operations are not supported in the original presentation. For any computation of an expression which contain operations that has not been defined in the analysis, it has to assume that nothing is known about the result and assign the result to the largest congruence class (equal to Z). This can potentially lead to very imprecise analysis results.

B) The interpretation of the values of integer-valued variables is not obvious (e.g. they can be signed or unsigned), the original presentation assumes that values has unambiguous representations. C) The value-domain is limited by its representation (integers are often represented by a fixed number of bits). In Grangers presentation integer-valued variables are assumed to take values in the infinite set of integers. Our contribution is to extend the theory of the analysis of arithmetical congruences to be able to handle low-level or assembly code, still in the framework of abstract interpretation.

This paper provides accurate definitions to the abstract bit-operations AND,NOT,XOR, left- and right shifting and truncation for the congruence domain in order to make the domain support these operations. We provide definitions for the operations together with proofs of their correctness. In these definitions care has been taken to the finite, fixed representation of integers as well as their sometimes ambiguous interpretations as signed or unsigned. With these definitions, congruence analysis can efficiently be performed on low-level code. The paper illustrates the usefulness of the new analysis by an example which shows that variables keep important parity information after executing a XOR-swap.

Events play an important role in many computer systems, from small reactive embedded applications to large distributed systems. Many applications react to events generated by a graphical user interface or by external sensors that monitor the system environment, and other systems use events for communication and synchronisation between independent subsystems. In some applications, however, individual event occurrences are not the main point of concern. Instead, the system should respond to certain event patterns, such as "the start button being pushed, followed by a temperature alarm within two seconds". One way to specify such event patterns is by means of an event algebra with operators for combining the simple events of a system into specifications of complex patterns.

This thesis presents an event algebra with two important characteristics. First, it complies with a number of algebraic laws, which shows that the algebra operators behave as expected. Second, any pattern represented by an expression in this algebra can be efficiently detected with bounded resources in terms of memory and time, which is particularly important when event pattern detection is used in embedded systems, where resource efficiency and predictability are crucial.

In addition to the formal algebra semantics and an efficient detection algorithm, the thesis describes how event pattern detection can be used in real-time systems without support from the underlying operating system, and presents schedulability theory for such systems. It also describes how the event algebra can be combined with a component model for embedded system, to support high level design of systems that react to event patterns.

This paper describes a novel Bluetooth(TM)-based wireless solution for industrial sensor monitoring. The solution enables wireless monitoring systems improving earlier Bluetooth(TM) implementations where mobility is not supported A distributed wireless sensor network is described with the sensor wireless interface, the architecture, protocols and algorithms used. Achieved results are: (1) Multi mobile wireless sensor monitoring with Bluelooth(TM). (2) Deployment of a distributed architecture for wireless sensors with global access.

In a component-based development process the selection of components is an activity that takes place over multiple lifecycle phases that span from requirement specifications through design to implementation-integration. Automated tool support for component selection would be very helpful in each phase. In this paper we introduce a framework that supports the selection of COTS componentsin the requirements phase. The framework lays on a tool that builds and solves an optimization model, whose solution provides the optimal COTS component selection. The selection criterion is based on cost minimization of the whole system while assuring a certain degree of satisfaction of the system requirements. The output of the model solution indicates the optimal combination of single COTScomponents and assemblies of COTS that satisfy the requirements while minimizing costs. 

Component-based development (CBD) is established as a standard approach in many domains. The most attractive parts of CBD come from its business side: increasing reuse and development efficiency. On other side many technical aspects are still remaining as challenges. This is in particular true in domains of embedded and dependable systems. The seminar will give the basic characteristics of component-based software development, then challenges and current practice and research directions.

In the research, education and in everyday practice, a need for and general understanding and a holistic approach is becoming more and more important. Still in concrete cases such approaches meet many challenges, mostly in form of misunderstanding between involved partners experts from different disciplines. Edu-cation in general does not provide training for such approach. This paper describes a case - a course which goal was to transfer knowledge from one area to another: A software Engineer-ing and management of software development projects was taught to students of management and economy. In addition to this the course pro-vided new teaching methods that students were not used to. Finally the course has been taught as a distance course, using internet-based tech-nology. All this elements made the course very challenging. The paper gives an overview of the case, identifies the challenges and discusses the lessons learned.

The process of component- and component-based system development differs in many significant ways from the "classical" development process of software systems. The main difference is in the separation of the development process of components from the development process of systems. This fact has a significant impact on the development process. Since the component-basedapproach is a relatively young approach in software engineering, the main emphasis in the area has been in development of technologies, while process modeling is still an unexplored area. This paper analyses the basic characteristics of the component-based approach and its impact on the development process and lifecycle models. The generic lifecycle of component-based systems and thelifecycle of components are discussed, and the different types of development processes are discussed in detail: architecture-driven component development, productline development and COTS-based development. Finally a short case study illustrates the principles and specifics of component-based processes. 

Component-Based Development (CBD) is established in many application domains. There is a strong trend in applying the same approach in different domains of dependable systems. However, a precondition of a successful use of CBD in these domains is the utilization of theories, methods and technologies to predict and evaluate dependability attributes. This tutorial gives an analysis of current methodologies of attribute-specific evaluation methods for dependable component-based systems. We identify limitations of the current technologies, discusses existing and possible new solutions to overcome these limitations both from a esearch-oriented and practical perspective.

One of the main objectives of developing component-based software systems is to enable efficient building of systems through the integration of components. All component models define some form of component inter-face standard that facilitates the programmatic integration of components, but they do not facilitate or provide theories for the prediction of the quality attributes of the component compositions. This decreases significantly the value of the component-based approach to building dependable systems. If it is not possible to predict the value of a particular attribute of a system prior to integration and deployment to the target environment the system must be subjected to other procedures, often costly, to determine this value empirically. For this reason one of the challenges of the component-based approach is to obtain means for the "composition" of quality attributes. This challenge poses a very difficult task because the diverse types of quality attributes do not have the same underlying conceptual characteristics, since many factors, in addition to component properties, influence the system properties. This paper analyses the relation between the quality attributes of components and those of their compositions. The types of relations are classified according to the possibility of predicting properties of compositions from the properties of the components and according to the influences of other factors such as software architecture or system environment. The classification is exemplified with particular cases of compositions of quality attributes, and its relation to dependability is discussed. Such a classification can indicate the efforts that would be required to predict the system attributes which are essential for system dependability and in this way, the feasibility of the component-based approach in developing dependable systems.

In recent years new paradigms of software development have emerged in many industrial and application domains: component-based and service-based software engineering.Component-based software engineering (CBSE) provides support for building systems through the composition and assembly of software components. CBSE is an established approach in many engineering domains, such as distributed and web based systems, desktop and graphical applications and recently in embedded systems domains. CBSE technologies facilitate effective management of complexity, significantly increase reusability and shorten time-to-market. On the other hand, the growing demands for Internet computing and emerging network-based business applications and systems are the driving forces for the evolvement of service-oriented software engineering (SOSE) . SOSE utilizes services as fundamental elements for developing applications and software solutions. SOSE technologies offer great feasibility in integrating distributed systems that are built on various platforms and technologies and further push focus on reusability and development efficiency.CBSE and SOSE are similar paradigms; they use similar approaches and technologies. Both CBSE and SOSE have a common source: Software Architecture with its basic concept that have been further developed and specialized. SOSE has evolved from CBSE frameworks and object oriented computing to face the challenges of open environments. Still CBSE and SOSE have continued developing in parallel, keeping different foci, which also has resulted in confusion in developing and applying similar concepts, or the same concepts designated differently. For example there is a general misunderstanding in what a component and a service are. This leads to less efficient utilization and combination of these approaches. For this reason, it is important to bring these worlds together and make researchers and practitioners aware of both sides; how can we take advantages of the strengths of these two paradigms, how can we adapt and integrate the component-based and service oriented technologies, concepts and their strengths to overcome the weaknesses in each separate technology.The aim of this tutorial is to show an integrated approach in utilization of CBSE and SOSE. The tutorial will start with providing an overview of software architecture with emphasis on architecture modeling and analysis, including CBSE and SOSE techniques from software architecture perspective. Subsequently, the tutorial will present analyses of the two techniques from multiple perspectives, such as their correlation from software architecture perspective, quality attribute analysis in respective technique, advantages and disadvantages of the two techniques, the possible directions in the adaptation of the two techniques and an indication on how to combine the strengths of both techniques. During the tutorial, some industrial context examples will be presented to illustrate CBSE and SOSE approaches and their integration.

Ny datormodell visar hur hjärnan behandlar information

Baran Çürüklüs forskning handlar om att förstå hur syncentret i hjärnan fungerar. Detta är viktigt för forskningen inom neurovetenskap och artificiell intelligens.

Under de senaste decennierna har hjärnforskningen visat att olika centra av hjärnbarken hos en och samma art har liknande struktur och att det finns stora likheter mellan olika arters hjärnbark. Dessa resultat tyder också på att nerv cellerna använder ett universellt språk när de kommunicerar med varandra. Dessutom verkar det finns generella regler som kan förklara hur hjärnan utvecklas och får sin slutliga form. En direkt konsekvens av dessa hypoteser är att Baran Çürüklüs forskning på syncentret kan ha stor inverkan på forskning på andra delar av hjärnan.

Syncentret är den del av hjärnbarken som tar emot de inkommande signaler från ögat. Syncentret är en mycket viktig del av hjärnan och innehåller uppskattningsvis 40 % av hjärnbarkens nerv celler. Baran Çürüklü har i detalj kartlagt svarsegenskaperna hos nerv cellerna i den primära visuella hjärnbarken under hjärnans utvecklingsförlopp. Detta arbete bygger på upptäckten av Hubel och Wiesel om att nerv cellerna i den primära visuella hjärnbarken reagerar på kontrastkanter. Deras forskning har resulterat i feedforward modellen som är en viktig del av arbetet som har gett dem Nobelpriset i fysiologi/medicin (1981).

Trots att denna modell har varit den mest refererade modellen i litteraturen så återstår fortfarande mycket forskning för att förstå nerv cellernas svarsegenskaper. Baran Çürüklüs modell kompletterar feedforward-modellen genom att bl.a. förklara hur hjärnan kan känna igen former under olika kontrastförhållanden. Modellen visar också hur omgivningen inverkar på syncentrets utvecklingsförlopp.

We propose a developmental model of the summation pools within the layer 4. The model is based on the modular structure of the neocortex and captures some of the known properties of layer 4. Connections between the orientation minicolumns are developed during exposure to visual input. Excitatory local connections are dense and biased towards the iso-orientation domain. Excitatory long-range connections are sparse and target all orientation domains equally. Inhibition is local. The summation pools are elongated along the orientation axis. These summation pools can facilitate weak and poorly tuned LGN input and explain improved visibility as an effect of enlargement of a stimulus.

An abstract model of a cortical hypercolumn is presented. This model could replicate experimental findings relating to the orientation tuning mechanism in the primary visual cortex. Properties of the orientation selective cells in the primary visual cortex like, contrast-invariance and response saturation were demonstrated in simulations. We hypothesize that broadly tuned inhibition and local excitatory connections are sufficient for achieving this behavior. We have shown that the local intracortical connectivity of the model is to some extent biologically plausible.