When developing products, reliability is an important factor that has to be considered. For safety critical systems it is important to know the probability that an item will perform a required function without failure under stated conditions for a stated period of time. The main goal of a reliability prediction analysis is to predict the rate at which the product of a system will fail. To perform this prediction there are a number of methodologies available. This Master Thesis proposes a model-based approach for reliability prediction calculations based on the physics of failure and supported by analysis of test-data field returns and physical models provided by the FIDES methodology. FIDES based reliability models have been integrated into a model-based diagnosis environment for seamless integration with other safety assessment analysis. The model-based diagnosis environment used in this thesis is model-based reasoner RODON developed by Uptime Solutions AB. Components that uses the FIDES methodology have been developed in RODON, where components can be combined to systems by drag and drop method. Usage profiles that are defined according to the FIDES methodology in RODON are not system specific, which makes them reusable in other systems. The developed library of components and usage profiles makes it easy to model complex systems and perform reliability predictions according to the FIDES methodology.

Failure detection and isolation (FDI) is essential for reliable operations of complex autonomous systems or other systems where continuous observation or maintenance thereof is either very costly or for any other reason not easily accessible. Beneficial for the model based FDI is that there is no need for fault data to detect and isolate a fault in contrary to design by data clustering. However, it is limited by the accuracy and complexity of the model used. As models grow more complex, or have multiple interconnections, problems with the traditional methods for FDI emerge. The main objective of this thesis is to utilise the automated methodology presented in [Svärd, 2012] to create a model based FDI system for the Columbus air loop. A small but crucial part of the life support on board the European space laboratory Columbus. The process of creating a model based FDI, from creation of the model equations, validation thereof to the design of residuals, test quantities and evaluation logic is handled in this work. Although the latter parts only briefly which leaves room for future work. This work indicate that the methodology presented is capable to create quite decent model based FDI systems even with poor sensor placement and limited information of the actual design. [] Carl Svärd. Methods for Automated Design of Fault Detection and Isolation Systems with Automotive Applications. PhD thesis, Linköping University, Vehicular Systems, The Institute of Technology, 2012

In this thesis we present a language and technique to facilitate model-based testing. The core of our approach is an xUnit-like language that allows tests to refer to model entities such as associations. This language can be used by developers to describe tests based on an existing UML model. The tests might even be written before creating a UML model, and be based on requirements. The testing language, including its parser and generators, is written entirely in Umple, an open-source textual modeling tool with semantics closely based on UML, and which generates Java, PHP and several other target languages. Tests in our language can be embedded in Umple or in standalone files. The test language compiler converts our abstract testing language into JUnit, PHPUnit and other domain-language testing environments. In addition to allowing developers to write tests manually, we have created generators that create abstract tests for any Umple model. These generators can be used to verify the Umple compiler and to give Umple users extra confidence in their models. User-defined tests can be standalone or embedded in methods; they can be generic, referring to metamodel elements. Tests can also be located in traits or mixsets to allow testing of separate concerns or product lines. To test our language and the tests written in it, we have created an extensive test suite. We have also implemented mutation testing, that enables varying of features of the models to ensure that runs of the pre-mutation tests then fail.

abstract: Understanding intratumor heterogeneity and their driver genes is critical to designing personalized treatments and improving clinical outcomes of cancers. Such investigations require accurate delineation of the subclonal composition of a tumor, which to date can only be reliably inferred from deep-sequencing data (>300x depth). The resulting algorithm from the work presented here, incorporates an adaptive error model into statistical decomposition of mixed populations, which corrects the mean-variance dependency of sequencing data at the subclonal level and enables accurate subclonal discovery in tumors sequenced at standard depths (30-50x). Tested on extensive computer simulations and real-world data, this new method, named model-based adaptive grouping of subclones (MAGOS), consistently outperforms existing methods on minimum sequencing depth, decomposition accuracy and computation efficiency. MAGOS supports subclone analysis using single nucleotide variants and copy number variants from one or more samples of an individual tumor. GUST algorithm, on the other hand is a novel method in detecting the cancer type specific driver genes. Combination of MAGOS and GUST results can provide insights into cancer progression. Applications of MAGOS and GUST to whole-exome sequencing data of 33 different cancer types’ samples discovered a significant association between subclonal diversity and their drivers and patient overall survival. / Dissertation/Thesis / Doctoral Dissertation Biomedical Informatics 2019

An interactive activation model for picture naming was used to guide treatment of a semantic-level deficit in 4 individuals with aphasia and severe picture-naming problems. Participants exhibited a profile consistent with Broca's aphasia with severe naming deficits, part of which was attributable to a semantic impairment based on testing of the lexical system. A semantic-based treatment was used to train naming of nouns in two semantic categories using a single-participant multiple baseline across behaviors and participants. Additional treatment, which included orthographic and phonological information about target words, then was applied. Treatment responses and error patterns demonstrated that semantic treatment resulted in improved naming of both trained and untrained items for 2 of 4 participants. Two participants did not show improved naming until treatment emphasizing the phonological form of the word was provided. This study demonstrates the utility of using an interactive activation model to plan treatment based on levels of disruption in the lexical processing system.

Det finns en omfattande litteratur kring modellbaserad testning (MBT) men med få tecken på att metoden har fått något större genomslag i industrin. Målet med studien är att identifiera exempel där MBT används som testmetod inom industrin och eventuella hinder som finns i MBT-processen. För att genomföra detta används en mixed-methods ansats bestående av en systematisk litteraturstudie följt av en utforskande fallstudie. I fallstudien tillämpas MBT med hjälp av verktyget Modbat på ett mjukvarusystem. Endast ett fåtal industriella tillämpningar av MBT identifieras i litteraturstudien. Totalt sju studier kvarstår efter fulltextgranskningen. Studierna finns primärt inom mjukvaruindustrin och flygindustrin men innehåller även exempel från hälso- sjukvård och bilindustrin. Den utforskande fallstudien indikerar tre typer av hinder. Det första är mängden arbete med, samt bristande användarvänlighet hos verktygen. Den andra är svårigheten med att skriva ett adaptionslager som integrerar systemet med verktyget och modellen för att göra testfallen körbara. Det sista hindret är det kraftiga beroendet på att modellen utformas korrekt och stämmer med systemets tilltänkta beteende. Dessa tre hinder pekas även ut i verken från litteraturstudien. Vidare pekas bland annat även icke-tekniska svårigheter ut under litteraturstudien i form av att hela arbetsgruppen och ledningen behöver engageras för att införa ett nytt arbetssätt. Med en begränsad fallstudie och ett enkelt system bekräftas tre hinder i MBT-processen som även identifieras i litteraturgenomgången. MBT framstår som ett primärt akademiskt område med ett fåtal exempel på användning inom industrin. / There is extensive literature concerning model-based testing (MBT) but few signs that the method have had any major breakthrough in the industry. The goal of this study is to identify examples of MBT being used in the industry and any challenges faced during the MBT-process. The study is conducted using a mixed methods approach, consisting of a systematic literature review followed by an exploratory case-study. The case-study applies MBT to a software system using the MBT-tool Modbat.Only seven studies remain after the fulltext review is performed. The studies are primarily from the software and aerospace industries but also include examples from the healthcare and automotive industries. The exploratory case-study identifies three challenges. The first one is the amount of work and lacking usability related to the MBT-tools. The second challenge is implementing the adaption layer, integrating the system under test with the tool and model to make test cases executable. The final challenge is the dependency on a correct model representing the systems expected behaviour. These three challenges are also identified in the systematic literature review. Other challenges from the literature review include non-technical difficulties concerning training and the need to motivate staff and management.Using a limited case-study and a simple system three challenges, which are also identified in the literature review, throughout the MBT process are confirmed. MBT appears primarily as an academic subject with some examples of use in the industry.

Det finns en omfattande litteratur kring modellbaserad testning (MBT) men med få tecken på att metoden har fått något större genomslag i industrin. Målet med studien är att identifiera exempel där MBT används som testmetod inom industrin och eventuella hinder som finns i MBT-processen. För att genomföra detta används en mixed-methods ansats bestående av en systematisk litteraturstudie följt av en utforskande fallstudie. I fallstudien tillämpas MBT med hjälp av verktyget Modbat på ett mjukvarusystem. Endast ett fåtal industriella tillämpningar av MBT identifieras i litteraturstudien. Totalt sju studier kvarstår efter fulltextgranskningen. Studierna finns primärt inom mjukvaruindustrin och flygindustrin men innehåller även exempel från hälso- sjukvård och bilindustrin. Den utforskande fallstudien indikerar tre typer av hinder. Det första är mängden arbete med, samt bristande användarvänlighet hos verktygen. Den andra är svårigheten med att skriva ett adaptionslager som integrerar systemet med verktyget och modellen för att göra testfallen körbara. Det sista hindret är det kraftiga beroendet på att modellen utformas korrekt och stämmer med systemets tilltänkta beteende. Dessa tre hinder pekas även ut i verken från litteraturstudien. Vidare pekas bland annat även icke-tekniska svårigheter ut under litteraturstudien i form av att hela arbetsgruppen och ledningen behöver engageras för att införa ett nytt arbetssätt. Med en begränsad fallstudie och ett enkelt system bekräftas tre hinder i MBT-processen som även identifieras i litteraturgenomgången. MBT framstår som ett primärt akademiskt område med ett fåtal exempel på användning inom industrin. / There is extensive literature concerning model-based testing (MBT) but few signs that the method have had any major breakthrough in the industry. The goal of this study is to identify examples of MBT being used in the industry and any challenges faced during the MBT-process. The study is conducted using a mixed methods approach, consisting of a systematic literature review followed by an exploratory case-study. The case-study applies MBT to a software system using the MBT-tool Modbat.Only seven studies remain after the fulltext review is performed. The studies are primarily from the software and aerospace industries but also include examples from the healthcare and automotive industries. The exploratory case-study identifies three challenges. The first one is the amount of work and lacking usability related to the MBT-tools. The second challenge is implementing the adaption layer, integrating the system under test with the tool and model to make test cases executable. The final challenge is the dependency on a correct model representing the systems expected behaviour. These three challenges are also identified in the systematic literature review. Other challenges from the literature review include non-technical difficulties concerning training and the need to motivate staff and management.Using a limited case-study and a simple system three challenges, which are also identified in the literature review, throughout the MBT process are confirmed. MBT appears primarily as an academic subject with some examples of use in the industry.

The recent development of Integrated Power Systems (IPS) for shipboard application has opened the horizon to introduce new technologies that address the increasing power demand along with the associated performance specifications. Similarly, the Shipboard Power System (SPS) features system components with multiple dynamic characteristics and require stringent regulations, leveraging a challenge for an efficient system level management. The shipboard power management needs to support the survivability, reliability, autonomy, and economy as the key features for design consideration. To address these multiple issues for an increasing system load and to embrace future technologies, an autonomic power management framework is required to maintain the system level objectives. To address the lack of the efficient management scheme, a generic model-based holistic power management framework is developed for naval SPS applications. The relationship between the system parameters are introduced in the form of models to be used by the model-based predictive controller for achieving the various power management goals. An intelligent diagnostic support system is developed to support the decision making capabilities of the main framework. Naïve Bayes’ theorem is used to classify the status of SPS to help dispatch the appropriate controls. A voltage control module is developed and implemented on a real-time test bed to verify the computation time. Variants of the limited look-ahead controls (LLC) are used throughout the dissertation to support the management framework design. Additionally, the ARIMA prediction is embedded in the approach to forecast the environmental variables in the system design. The developed generic framework binds the multiple functionalities in the form of overall system modules. Finally, the dissertation develops the distributed controller using the Interaction Balance Principle to solve the interconnected subsystem optimization problem. The LLC approach is used at the local level, and the conjugate gradient method coordinates all the lower level controllers to achieve the overall optimal solution. This novel approach provides better computing performance, more flexibility in design, and improved fault handling. The case-study demonstrates the applicability of the method and compares with the centralized approach. In addition, several measures to characterize the performance of the distributed controls approach are studied.

We all have access to large collections of digital text documents, which are useful only if we can make sense of them all and distill important information from them. Good document clustering algorithms that organize such information automatically in meaningful ways can make a difference in how effective we are at using that information. In this paper we use model-based document clustering algorithms as a base for bisecting methods in order to identify increasingly cohesive clusters from larger, more diverse clusters. We specifically use the EM algorithm and Gibbs Sampling on a mixture of multinomials as the base clustering algorithms on three data sets. Additionally, we apply a refinement step, using EM, to the final output of each clustering technique. Our results show improved agreement with human annotated document classes when compared to the existing base clustering algorithms, with marked improvement in two out of three data sets.

Yes / Bayesian Network (BN)-based methods are increasingly used in system reliability analysis. While BNs enable to perform multiple analyses based on a single model, the construction of robust BN models relies either on the conversion from other intermediate system model structures or direct analyst-led development based on experts input, both requiring significant human effort. This article proposes an architecture model-based approach for the direct generation of a BN model. Given the architectural model of a system, a systematic bottom-up approach is suggested, underpinned by failure behaviour models of components composed based on interaction models to create a system-level failure behaviour model. Interoperability and reusability of models are supported by a library of component failure models. The approach was illustrated with application to a case study of a steam boiler system. / The full text will be available at the end of the publisher's embargo: 18th Nov 2023