366,682 research outputs found

    Maintenance Testing of Mixed-Signal Boards

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    In the context of maintenance and diagnosis of faulty boards, we introduce a functional FSM-based model for mixed-signal circuits. We target effi cient test sequences generation for ATE based on a high-level, functional modeling of components assemblies. The approach is flexible, allows to handle digital as well as analog and mixed-signal components in a similar way. A primary prototype has been developped, and two industrial cases partially processed

    Epilepsy attacks recognition based on 1D octal pattern, wavelet transform and EEG signals

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    Electroencephalogram (EEG) signals have been generally utilized for diagnostic systems. Nowadays artificial intelligence-based systems have been proposed to classify EEG signals to ease diagnosis process. However, machine learning models have generally been used deep learning based classification model to reach high classification accuracies. This work focuses classification epilepsy attacks using EEG signals with a lightweight and simple classification model. Hence, an automated EEG classification model is presented. The used phases of the presented automated EEG classification model are (i) multileveled feature generation using one-dimensional (1D) octal-pattern (OP) and discrete wavelet transform (DWT). Here, main feature generation function is the presented octal-pattern. DWT is employed for level creation. By employing DWT frequency coefficients of the EEG signal is obtained and octal-pattern generates texture features from raw EEG signal and wavelet coefficients. This DWT and octal-pattern based feature generator extracts 128 × 8 = 1024 (Octal-pattern generates 128 features from a signal, 8 signal are used in the feature generation 1 raw EEG and 7 wavelet low-pass filter coefficients). (ii) To select the most useful features, neighborhood component analysis (NCA) is deployed and 128 features are selected. (iii) The selected features are feed to k nearest neighborhood classifier. To test this model, an epilepsy seizure dataset is used and 96.0% accuracy is attained for five categories. The results clearly denoted the success of the presented octal-pattern based epilepsy classification model

    Using LNT Formal Descriptions for Model-Based Diagnosis

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    International audienceProviding models for model-based diagnosis has always been a challenging task. There has never been an agreement on an underlying modeling language, making it almost impossible to share models within our community. In addition, there are other domains like formal methods or model-based testing relying on system models for formal verification and automated test case generation. Although, there we face the situation of different modeling languages as well, the question remains whether it is possible to re-use these models in the context of model-based diagnosis. In this paper , we elaborate on this question and show how models written in LNT can be used for fault local-ization only requiring simple modification. This allows re-using formal method's models for diagnosis directly. Besides discussing the underlying principles, we also present a use case showing the applicability of the methods

    Diagnosing Errors in DbC Programs Using Constraint Programming

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    Model-Based Diagnosis allows to determine why a correctly designed system does not work as it was expected. In this paper, we propose a methodology for software diagnosis which is based on the combination of Design by Contract, Model-Based Diagnosis and Constraint Programming. The contracts are specified by assertions embedded in the source code. These assertions and an abstraction of the source code are transformed into constraints, in order to obtain the model of the system. Afterwards, a goal function is created for detecting which assertions or source code statements are incorrect. The application of this methodology is automatic and is based on Constraint Programming techniques. The originality of this work stems from the transformation of contracts and source code into constraints, in order to determine which assertions and source code statements are not consistent with the specification.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0

    MISSED: an environment for mixed-signal microsystem testing and diagnosis

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    A tight link between design and test data is proposed for speeding up test-pattern generation and diagnosis during mixed-signal prototype verification. Test requirements are already incorporated at the behavioral level and specified with increased detail at lower hierarchical levels. A strict distinction between generic routines and implementation data makes reuse of software possible. A testability-analysis tool and test and DFT libraries support the designer to guarantee testability. Hierarchical backtrace procedures in combination with an expert system and fault libraries assist the designer during mixed-signal chip debuggin

    Improving the cost effectiveness equation of cascade testing for Familial Hypercholesterolaemia (FH)

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    Purpose of Review : Many International recommendations for the management of Familial Hypercholesterolaemia (FH) propose the use of Cascade Testing (CT) using the family mutation to unambiguously identify affected relatives. In the current economic climate DNA information is often regarded as too expensive. Here we review the literature and suggest strategies to improve cost effectiveness of CT. Recent findings : Advances in next generation sequencing have both speeded up the time taken for a genetic diagnosis and reduced costs. Also, it is now clear that, in the majority of patients with a clinical diagnosis of FH where no mutation can be found, the most likely cause of their elevated LDL-cholesterol (LDL-C) is because they have inherited a greater number than average of common LDL-C raising variants in many different genes. The major cost driver for CT is not DNA testing but of treatment over the remaining lifetime of the identified relative. With potent statins now off-patent, the overall cost has reduced considerably, and combining these three factors, a FH service based around DNA-CT is now less than 25% of that estimated by NICE in 2009. Summary : While all patients with a clinical diagnosis of FH need to have their LDL-C lowered, CT should be focused on those with the monogenic form and not the polygenic form
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