907 resultados para computer-based diagnostics
Resumo:
Modern machine structures are often fabricated by welding. From a fatigue point of view, the structural details and especially, the welded details are the most prone to fatigue damage and failure. Design against fatigue requires information on the fatigue resistance of a structure’s critical details and the stress loads that act on each detail. Even though, dynamic simulation of flexible bodies is already current method for analyzing structures, obtaining the stress history of a structural detail during dynamic simulation is a challenging task; especially when the detail has a complex geometry. In particular, analyzing the stress history of every structural detail within a single finite element model can be overwhelming since the amount of nodal degrees of freedom needed in the model may require an impractical amount of computational effort. The purpose of computer simulation is to reduce amount of prototypes and speed up the product development process. Also, to take operator influence into account, real time models, i.e. simplified and computationally efficient models are required. This in turn, requires stress computation to be efficient if it will be performed during dynamic simulation. The research looks back at the theoretical background of multibody dynamic simulation and finite element method to find suitable parts to form a new approach for efficient stress calculation. This study proposes that, the problem of stress calculation during dynamic simulation can be greatly simplified by using a combination of floating frame of reference formulation with modal superposition and a sub-modeling approach. In practice, the proposed approach can be used to efficiently generate the relevant fatigue assessment stress history for a structural detail during or after dynamic simulation. In this work numerical examples are presented to demonstrate the proposed approach in practice. The results show that approach is applicable and can be used as proposed.
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This paper investigates defect detection methodologies for rolling element bearings through vibration analysis. Specifically, the utility of a new signal processing scheme combining the High Frequency Resonance Technique (HFRT) and Adaptive Line Enhancer (ALE) is investigated. The accelerometer is used to acquire data for this analysis, and experimental results have been obtained for outer race defects. Results show the potential effectiveness of the signal processing technique to determine both the severity and location of a defect. The HFRT utilizes the fact that much of the energy resulting from a defect impact manifests itself in the higher resonant frequencies of a system. Demodulation of these frequency bands through use of the envelope technique is then employed to gain further insight into the nature of the defect while further increasing the signal to noise ratio. If periodic, the defect frequency is then present in the spectra of the enveloped signal. The ALE is used to enhance the envelope spectrum by reducing the broadband noise. It provides an enhanced envelope spectrum with clear peaks at the harmonics of a characteristic defect frequency. It is implemented by using a delayed version of the signal and the signal itself to decorrelate the wideband noise. This noise is then rejected by the adaptive filter that is based upon the periodic information in the signal. Results have been obtained for outer race defects. They show the effectiveness of the methodology to determine both the severity and location of a defect. In two instances, a linear relationship between signal characteristics and defect size is indicated.
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In this paper a computer program to model and support product design is presented. The product is represented through a hierarchical structure that allows the user to navigate across the products components, and it aims at facilitating each step of the detail design process. A graphical interface was also developed, which shows visually to the user the contents of the product structure. Features are used as building blocks for the parts that compose the product, and object-oriented methodology was used as a means to implement the product structure. Finally, an expert system was also implemented, whose knowledge base rules help the user design a product that meets design and manufacturing requirements.
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Software plays an important role in our society and economy. Software development is an intricate process, and it comprises many different tasks: gathering requirements, designing new solutions that fulfill these requirements, as well as implementing these designs using a programming language into a working system. As a consequence, the development of high quality software is a core problem in software engineering. This thesis focuses on the validation of software designs. The issue of the analysis of designs is of great importance, since errors originating from designs may appear in the final system. It is considered economical to rectify the problems as early in the software development process as possible. Practitioners often create and visualize designs using modeling languages, one of the more popular being the Uni ed Modeling Language (UML). The analysis of the designs can be done manually, but in case of large systems, the need of mechanisms that automatically analyze these designs arises. In this thesis, we propose an automatic approach to analyze UML based designs using logic reasoners. This approach firstly proposes the translations of the UML based designs into a language understandable by reasoners in the form of logic facts, and secondly shows how to use the logic reasoners to infer the logical consequences of these logic facts. We have implemented the proposed translations in the form of a tool that can be used with any standard compliant UML modeling tool. Moreover, we authenticate the proposed approach by automatically validating hundreds of UML based designs that consist of thousands of model elements available in an online model repository. The proposed approach is limited in scope, but is fully automatic and does not require any expertise of logic languages from the user. We exemplify the proposed approach with two applications, which include the validation of domain specific languages and the validation of web service interfaces.
Resumo:
The number of molecular diagnostic assays has increased tremendously in recent years.Nucleic acid diagnostic assays have been developed, especially for the detection of human pathogenic microbes and genetic markers predisposing to certain diseases. Closed-tube methods are preferred because they are usually faster and easier to perform than heterogenous methods and in addition, target nucleic acids are commonly amplified leading to risk of contamination of the following reactions by the amplification product if the reactions are opened. The present study introduces a new closed-tube switchable complementation probes based PCR assay concept where two non-fluorescent probes form a fluorescent lanthanide chelate complex in the presence of the target DNA. In this dual-probe PCR assay method one oligonucleotide probe carries a non-fluorescent lanthanide chelate and another probe a light absorbing antenna ligand. The fluorescent lanthanide chelate complex is formed only when the non-fluorescent probes are hybridized to adjacent positions into the target DNA bringing the reporter moieties in close proximity. The complex is formed by self-assembled lanthanide chelate complementation where the antenna ligand is coordinated to the lanthanide ion captured in the chelate. The complementation probes based assays with time-resolved fluorescence measurement showed low background signal level and hence, relatively high nucleic acid detection sensitivity (low picomolar target concentration). Different lanthanide chelate structures were explored and a new cyclic seven dentate lanthanide chelate was found suitable for complementation probe method. It was also found to resist relatively high PCR reaction temperatures, which was essential for the PCR assay applications. A seven-dentate chelate with two unoccupied coordination sites must be used instead of a more stable eight- or nine-dentate chelate because the antenna ligand needs to be coordinated to the free coordination sites of the lanthanide ion. The previously used linear seven-dentate lanthanide chelate was found to be unstable in PCR conditions and hence, the new cyclic chelate was needed. The complementation probe PCR assay method showed high signal-to-background ratio up to 300 due to a low background fluorescence level and the results (threshold cycles) in real-time PCR were reached approximately 6 amplification cycles earlier compared to the commonly used FRET-based closed-tube PCR method. The suitability of the complementation probe method for different nucleic acid assay applications was studied. 1) A duplex complementation probe C. trachomatis PCR assay with a simple 10-minute urine sample preparation was developed to study suitability of the method for clinical diagnostics. The performance of the C. trachomatis assay was equal to the commercial C. trachomatis nucleic acid amplification assay containing more complex sample preparation based on DNA extraction. 2) A PCR assay for the detection of HLA-DQA1*05 allele, that is used to predict the risk of type 1 diabetes, was developed to study the performance of the method in genotyping. A simple blood sample preparation was used where the nucleic acids were released from dried blood sample punches using high temperature and alkaline reaction conditions. The complementation probe HLA-DQA1*05 PCR assay showed good genotyping performance correlating 100% with the routinely used heterogenous reference assay. 3) To study the suitability of the complementation probe method for direct measurement of the target organism, e.g., in the culture media, the complementation probes were applied to amplificationfree closed-tube bacteriophage quantification by measuring M13 bacteriophage ssDNA. A low picomolar bacteriophage concentration was detected in a rapid 20- minute assay. The assay provides a quick and reliable alternative to the commonly used and relatively unreliable UV-photometry and time-consuming culture based bacteriophage detection methods and indicates that the method could also be used for direct measurement of other micro-organisms. The complementation probe PCR method has a low background signal level leading to a high signal-to-background ratio and relatively sensitive nucleic acid detection. The method is compatible with simple sample preparation and it was shown to tolerate residues of urine, blood, bacteria and bacterial culture media. The common trend in nucleic acid diagnostics is to create easy-to-use assays suitable for rapid near patient analysis. The complementation probe PCR assays with a brief sample preparation should be relatively easy to automate and hence, would allow the development of highperformance nucleic acid amplification assays with a short overall assay time.
Resumo:
Conventional diagnostics tests and technologies typically allow only a single analysis and result per test. The aim of this study was to propose robust and multiplex array-inwell test platforms based on oligonucleotide and protein arrays combining the advantages of simple instrumentation and upconverting phosphor (UCP) reporter technology. The UCPs are luminescent lanthanide-doped crystals that have a unique capability to convert infrared radiation into visible light. No autofluorescence is produced from the sample under infrared excitation enabling the development of highly sensitive assays. In this study, an oligonucleotide array-in-well hybridization assay was developed for the detection and genotyping of human adenoviruses. The study provided a verification of the advantages and potential of the UCP-based reporter technology in multiplex assays as well as anti-Stokes photoluminescence detection with a new anti- Stokes photoluminescence imager. The developed assay was technically improved and used to detect and genotype adenovirus types from clinical specimens. Based on the results of the epidemiological study, an outbreak of adenovirus type B03 was observed in the autumn of 2010. A quantitative array-in-well immunoassay was developed for three target analytes (prostate specific antigen, thyroid stimulating hormone, and luteinizing hormone). In this study, quantitative results were obtained for each analyte and the analytical sensitivities in buffer were in clinically relevant range. Another protein-based array-inwell assay was developed for multiplex serodiagnostics. The developed assay was able to detect parvovirus B19 IgG and adenovirus IgG antibodies simultaneously from serum samples according to reference assays. The study demonstrated that the UCPtechnology is a robust detection method for diverse multiplex imaging-based array-inwell assays.
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The overall goal of the study was to describe nurses’ acceptance of an Internet-based support system in the care of adolescents with depression. The data were collected in four phases during the period 2006 – 2010 from nurses working in adolescent psychiatric outpatient clinics and from professionals working with adolescents in basic public services. In the first phase, the nurses’ anticipated perceptions of the usefulness of the Internet-based support system before its implementation was explored. In the second phase, the nurses’ perceived ease of computer and Internet use and attitudes toward it were explored. In the third phase, the features of the support system and its implementation process were described. In the fourth phase, the nurses’ experiences of behavioural intention and actual system use of the Internet-based support were described in psychiatric out-patient care after one year use. The Technology Acceptance Model (TAM) was used to structure the various research phases. Several benefits were identified from the nurses’ perspective in using the Internet-based support system in the care of adolescents with depression. The nurses’ technology skills were good and their attitudes towards computer use were positive. The support system was developed in various phases to meet the adolescents’ needs. Before the implementation of the information technology (IT)-based support system, it is important to pay attention to the nurses’ IT-training, technology support, resources, and safety as well as ethical issues related to the support system. After one year of using the system, the nurses perceived the Internet-based support system to be useful in the care of adolescents with depression. The adolescents’ independent work with the support system at home and the program’s systematic character were experienced as conducive from the point of view of the treatment. However, the Internet-based support system was integrated only partly into the nurseadolescent interaction even though the nurses’ perceptions of it were positive. The use of the IT-based system as part of the adolescents’ depression care was seen positively and its benefits were recognized. This serves as a good basis for future IT-based techniques. Successful implementations of IT-based support systems need a systematic implementation plan and commitment from the part of the organization and its managers. Supporting and evaluating the implementation of an IT-based system should pay attention to changing the nurses’ work styles. Health care organizations should be offered more flexible opportunities to utilize IT-based systems in direct patient care in the future.
Resumo:
The Saimaa ringed seal is one of the most endangered seals in the world. It is a symbol of Lake Saimaa and a lot of effort have been applied to save it. Traditional methods of seal monitoring include capturing the animals and installing sensors on their bodies. These invasive methods for identifying can be painful and affect the behavior of the animals. Automatic identification of seals using computer vision provides a more humane method for the monitoring. This Master's thesis focuses on automatic image-based identification of the Saimaa ringed seals. This consists of detection and segmentation of a seal in an image, analysis of its ring patterns, and identification of the detected seal based on the features of the ring patterns. The proposed algorithm is evaluated with a dataset of 131 individual seals. Based on the experiments with 363 images, 81\% of the images were successfully segmented automatically. Furthermore, a new approach for interactive identification of Saimaa ringed seals is proposed. The results of this research are a starting point for future research in the topic of seal photo-identification.
Resumo:
Due to various advantages such as flexibility, scalability and updatability, software intensive systems are increasingly embedded in everyday life. The constantly growing number of functions executed by these systems requires a high level of performance from the underlying platform. The main approach to incrementing performance has been the increase of operating frequency of a chip. However, this has led to the problem of power dissipation, which has shifted the focus of research to parallel and distributed computing. Parallel many-core platforms can provide the required level of computational power along with low power consumption. On the one hand, this enables parallel execution of highly intensive applications. With their computational power, these platforms are likely to be used in various application domains: from home use electronics (e.g., video processing) to complex critical control systems. On the other hand, the utilization of the resources has to be efficient in terms of performance and power consumption. However, the high level of on-chip integration results in the increase of the probability of various faults and creation of hotspots leading to thermal problems. Additionally, radiation, which is frequent in space but becomes an issue also at the ground level, can cause transient faults. This can eventually induce a faulty execution of applications. Therefore, it is crucial to develop methods that enable efficient as well as resilient execution of applications. The main objective of the thesis is to propose an approach to design agentbased systems for many-core platforms in a rigorous manner. When designing such a system, we explore and integrate various dynamic reconfiguration mechanisms into agents functionality. The use of these mechanisms enhances resilience of the underlying platform whilst maintaining performance at an acceptable level. The design of the system proceeds according to a formal refinement approach which allows us to ensure correct behaviour of the system with respect to postulated properties. To enable analysis of the proposed system in terms of area overhead as well as performance, we explore an approach, where the developed rigorous models are transformed into a high-level implementation language. Specifically, we investigate methods for deriving fault-free implementations from these models into, e.g., a hardware description language, namely VHDL.
Resumo:
Hur arbetar en framgångsrik programmerare? Uppgifterna att programmera datorspel och att programmera industriella, säkerhetskritiska system verkar tämligen olika. Genom en noggrann empirisk undersökning jämför och kontrasterar avhandlingen dessa två former av programmering och visar att programmering innefattar mer än teknisk förmåga. Med utgångspunkt i hermeneutisk och retorisk teori och med hjälp av både kulturvetenskap och datavetenskap visar avhandlingen att programmerarnas tradition och värderingar är grundläggande för deras arbete, och att båda sorter av programmering kan uppfattas och analyseras genom klassisk texttolkningstradition. Dessutom kan datorprogram betraktas och analyseras med hjälp av klassiska teorier om talproduktion i praktiken - program ses då i detta sammanhang som ett slags yttranden. Allt som allt förespråkar avhandlingen en återkomst till vetenskapens grunder, vilka innebär en ständig och oupphörlig cyklisk rörelse mellan att erfara och att förstå. Detta står i kontrast till en reduktionistisk syn på vetenskapen, som skiljer skarpt mellan subjektivt och objektivt, och på så sätt utgår från möjligheten att uppnå fullständigt vetande. Ofullständigt vetande är tolkandets och hermeneutikens domän. Syftet med avhandlingen är att med hjälp av exempel demonstrera programmeringens kulturella, hermeneutiska och retoriska natur.
Resumo:
In the field of molecular biology, scientists adopted for decades a reductionist perspective in their inquiries, being predominantly concerned with the intricate mechanistic details of subcellular regulatory systems. However, integrative thinking was still applied at a smaller scale in molecular biology to understand the underlying processes of cellular behaviour for at least half a century. It was not until the genomic revolution at the end of the previous century that we required model building to account for systemic properties of cellular activity. Our system-level understanding of cellular function is to this day hindered by drastic limitations in our capability of predicting cellular behaviour to reflect system dynamics and system structures. To this end, systems biology aims for a system-level understanding of functional intraand inter-cellular activity. Modern biology brings about a high volume of data, whose comprehension we cannot even aim for in the absence of computational support. Computational modelling, hence, bridges modern biology to computer science, enabling a number of assets, which prove to be invaluable in the analysis of complex biological systems, such as: a rigorous characterization of the system structure, simulation techniques, perturbations analysis, etc. Computational biomodels augmented in size considerably in the past years, major contributions being made towards the simulation and analysis of large-scale models, starting with signalling pathways and culminating with whole-cell models, tissue-level models, organ models and full-scale patient models. The simulation and analysis of models of such complexity very often requires, in fact, the integration of various sub-models, entwined at different levels of resolution and whose organization spans over several levels of hierarchy. This thesis revolves around the concept of quantitative model refinement in relation to the process of model building in computational systems biology. The thesis proposes a sound computational framework for the stepwise augmentation of a biomodel. One starts with an abstract, high-level representation of a biological phenomenon, which is materialised into an initial model that is validated against a set of existing data. Consequently, the model is refined to include more details regarding its species and/or reactions. The framework is employed in the development of two models, one for the heat shock response in eukaryotes and the second for the ErbB signalling pathway. The thesis spans over several formalisms used in computational systems biology, inherently quantitative: reaction-network models, rule-based models and Petri net models, as well as a recent formalism intrinsically qualitative: reaction systems. The choice of modelling formalism is, however, determined by the nature of the question the modeler aims to answer. Quantitative model refinement turns out to be not only essential in the model development cycle, but also beneficial for the compilation of large-scale models, whose development requires the integration of several sub-models across various levels of resolution and underlying formal representations.
Resumo:
The main objective of the present study was to upgrade a clinical gamma camera to obtain high resolution tomographic images of small animal organs. The system is based on a clinical gamma camera to which we have adapted a special-purpose pinhole collimator and a device for positioning and rotating the target based on a computer-controlled step motor. We developed a software tool to reconstruct the target’s three-dimensional distribution of emission from a set of planar projections, based on the maximum likelihood algorithm. We present details on the hardware and software implementation. We imaged phantoms and heart and kidneys of rats. When using pinhole collimators, the spatial resolution and sensitivity of the imaging system depend on parameters such as the detector-to-collimator and detector-to-target distances and pinhole diameter. In this study, we reached an object voxel size of 0.6 mm and spatial resolution better than 2.4 and 1.7 mm full width at half maximum when 1.5- and 1.0-mm diameter pinholes were used, respectively. Appropriate sensitivity to study the target of interest was attained in both cases. Additionally, we show that as few as 12 projections are sufficient to attain good quality reconstructions, a result that implies a significant reduction of acquisition time and opens the possibility for radiotracer dynamic studies. In conclusion, a high resolution single photon emission computed tomography (SPECT) system was developed using a commercial clinical gamma camera, allowing the acquisition of detailed volumetric images of small animal organs. This type of system has important implications for research areas such as Cardiology, Neurology or Oncology.
Resumo:
Software is a key component in many of our devices and products that we use every day. Most customers demand not only that their devices should function as expected but also that the software should be of high quality, reliable, fault tolerant, efficient, etc. In short, it is not enough that a calculator gives the correct result of a calculation, we want the result instantly, in the right form, with minimal use of battery, etc. One of the key aspects for succeeding in today's industry is delivering high quality. In most software development projects, high-quality software is achieved by rigorous testing and good quality assurance practices. However, today, customers are asking for these high quality software products at an ever-increasing pace. This leaves the companies with less time for development. Software testing is an expensive activity, because it requires much manual work. Testing, debugging, and verification are estimated to consume 50 to 75 per cent of the total development cost of complex software projects. Further, the most expensive software defects are those which have to be fixed after the product is released. One of the main challenges in software development is reducing the associated cost and time of software testing without sacrificing the quality of the developed software. It is often not enough to only demonstrate that a piece of software is functioning correctly. Usually, many other aspects of the software, such as performance, security, scalability, usability, etc., need also to be verified. Testing these aspects of the software is traditionally referred to as nonfunctional testing. One of the major challenges with non-functional testing is that it is usually carried out at the end of the software development process when most of the functionality is implemented. This is due to the fact that non-functional aspects, such as performance or security, apply to the software as a whole. In this thesis, we study the use of model-based testing. We present approaches to automatically generate tests from behavioral models for solving some of these challenges. We show that model-based testing is not only applicable to functional testing but also to non-functional testing. In its simplest form, performance testing is performed by executing multiple test sequences at once while observing the software in terms of responsiveness and stability, rather than the output. The main contribution of the thesis is a coherent model-based testing approach for testing functional and performance related issues in software systems. We show how we go from system models, expressed in the Unified Modeling Language, to test cases and back to models again. The system requirements are traced throughout the entire testing process. Requirements traceability facilitates finding faults in the design and implementation of the software. In the research field of model-based testing, many new proposed approaches suffer from poor or the lack of tool support. Therefore, the second contribution of this thesis is proper tool support for the proposed approach that is integrated with leading industry tools. We o er independent tools, tools that are integrated with other industry leading tools, and complete tool-chains when necessary. Many model-based testing approaches proposed by the research community suffer from poor empirical validation in an industrial context. In order to demonstrate the applicability of our proposed approach, we apply our research to several systems, including industrial ones.
Resumo:
Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.
Resumo:
Today, the user experience and usability in software application are becoming a major design issue due to the adaptation of many processes using new technologies. Therefore, the study of the user experience and usability might be included in every software development project and, thus, they should be tested to get traceable results. As a result of different testing methods to evaluate the concepts, a non-expert on the topic might have doubts on which option he/she should opt for and how to interpret the outcomes of the process. This work aims to create a process to ease the whole testing methodology based on the process created by Seffah et al. and a supporting software tool to follow the procedure of these testing methods for the user experience and usability.