Model-based Decentralized Embedded Diagnosis inside Vehicles: Application to Smart Distance Keeping Function

International audienceAbstract—In this paper, the deployment of a fault diagnosis strategy in the Smart Distance Keeping (SDK) system with a decentralized architecture is presented. The SDK system is an advanced version of the Adaptive Cruise Control (ACC) system, implemented in a Renault-Volvo Trucks vehicle. The main goal of this work is to analyze measurements, issued from the SDK elements, in order to detect, to localize and to identify some faults that may be produced. Our main contribution is the proposition of a decentralized approach permitting to carry out an on-line diagnosis without computing the global model and to deploy it on several control units. This paper explains the model-based decentralized solution and its application to the embedded diagnosis of the SDK system inside truck with five control units connected via a CAN-bus using ”Hardware In the Loop” (HIL) technique. We also discuss the constraints that must be fulfilled

Smart distance keeping: modeling and perspectives for embedded diagnosis

International audienceThis paper presents a detailed description of an advanced Adaptive Cruise Control (ACC) system implemented on a Renault-Volvo Trucks vehicle. One of the main differences between this new system, which is called the Smart Distance Keeping (SDK), and the classical ACC is the choice of the safe distance. This later is the distance between the vehicle (with the ACC or the SDK system) and the front obstacle (which may be a vehicle). It is supposed fix in the case of the ACC, while variable in the case of the SDK. The variation of this distance (in the case of SDK) depends essentially on the relative velocity between the vehicle and the front obstacle. The choice of this distance influences the velocity regulation. The main contribution of this work is on the SDK system architecture, the design of its environment model, and the proposition of a detection and isolation strategy for some of the possible faults that may be produced on the system

An observational, prospective, multicenter, natural history study of patients with mucopolysaccharidosis type IIIA

Mucopolysaccharidosis type IIIA (MPS IIIA, also known as Sanfilippo syndrome) is a rare genetic lysosomal storage disease characterized by early and progressive neurodegeneration resulting in a rapid decline in cognitive function affecting speech and language, adaptive behavior, and motor skills. We carried out a prospective observational study to assess the natural history of patients with MPS IIIA, using both standardized tests and patientcentric measures to determine the course of disease progression over a 2-year period. A cohort of 23 patients (7 girls, 16 boys; mean age 28–105 months at baseline) with a confirmed diagnosis of MPS IIIA were assessed and followed up at intervals of 3–6 months; cognitive function was measured using Bayley Scales of Infant and Toddler Development 3rd edition (BSID-III) to derive cognitive development quotients (DQ). Daily living, speech/ language development and motor skills were measured using the Vineland Adaptive Behavior Scale (VABS-II). Sleep–wake patterns, behavior and quality-of-life questionnaires were also reported at each visit using parent/ caregiver reported outcome tools. All patients had early onset severe MPS IIIA, were diagnosed before 74 months of age, and had cognitive scores below normal developmental levels at baseline. Patients less than 40 months of age at baseline were more likely to continue developing new skills over the first 6–12 months of follow-up. There was a high variability in cognitive developmental age (DA) in patients between 40 and 70 months of age; twothirds of these patients already had profound cognitive decline, with a DA ≤10 months. The highest cognitive DA achieved in the full study cohort was 34 months. Post hoc, patients were divided into two groups based on baseline cognitive DQ (DQ ≥50 or <50). Cognitive DQ decreased linearly over time, with a decrease from baseline of 30.1 and 9.0 points in patients with cognitive DQ ≥50 at baseline and cognitive DQ <50 at baseline, respectively. Over the 2-year study, VABS-II language scores declined progressively. Motor skills, including walking, declined over time, although significantly later than cognitive decline. No clear pattern of sleep disturbance was observed, but night waking was common in younger patients. Pain scores, as measured on the quality-of-life questionnaire, increased over the study period. The findings of this study strengthen the natural history data on cognitive decline in MPS IIIA and importantly provide additional data on endpoints, validated by the patient community as important to treat, that may form the basis of a multidomain endpoint capturing the disease complexity

Clinical reappraisal of SHORT syndrome with PIK3R1 mutations: towards recommendation for molecular testing and management

International audienceSHORT syndrome has historically been defined by its acronym: short stature (S), hyperextensibility of joints and/or inguinal hernia (H), ocular depression (O), Rieger abnormality (R) and teething delay (T). More recently several research groups have identified PIK3R1 mutations as responsible for SHORT syndrome. Knowledge of the molecular etiology of SHORT syndrome has permitted a reassessment of the clinical phenotype. The detailed phenotypes of 32 individuals with SHORT syndrome and PIK3R1 mutation, including eight newly ascertained individuals, were studied to fully define the syndrome and the indications for PIK3R1 testing. The major features described in the SHORT acronym were not universally seen and only half (52%) had 4 or more of the classic features. The commonly observed clinical features of SHORT syndrome seen in the cohort included IUGR \textless 10(th) percentile, postnatal growth restriction, lipoatrophy and the characteristic facial gestalt. Anterior chamber defects and insulin resistance or diabetes were also observed but were not as prevalent. The less specific, or minor features of SHORT syndrome include teething delay, thin wrinkled skin, speech delay, sensorineural deafness, hyperextensibility of joints and inguinal hernia. Given the high risk of diabetes mellitus, regular monitoring of glucose metabolism is warranted. An echocardiogram, ophthalmological and hearing assessments are also recommended

Effects of eight neuropsychiatric copy number variants on human brain structure

Many copy number variants (CNVs) confer risk for the same range of neurodevelopmental symptoms and psychiatric conditions including autism and schizophrenia. Yet, to date neuroimaging studies have typically been carried out one mutation at a time, showing that CNVs have large effects on brain anatomy. Here, we aimed to characterize and quantify the distinct brain morphometry effects and latent dimensions across 8 neuropsychiatric CNVs. We analyzed T1-weighted MRI data from clinically and non-clinically ascertained CNV carriers (deletion/duplication) at the 1q21.1 (n = 39/28), 16p11.2 (n = 87/78), 22q11.2 (n = 75/30), and 15q11.2 (n = 72/76) loci as well as 1296 non-carriers (controls). Case-control contrasts of all examined genomic loci demonstrated effects on brain anatomy, with deletions and duplications showing mirror effects at the global and regional levels. Although CNVs mainly showed distinct brain patterns, principal component analysis (PCA) loaded subsets of CNVs on two latent brain dimensions, which explained 32 and 29% of the variance of the 8 Cohen’s d maps. The cingulate gyrus, insula, supplementary motor cortex, and cerebellum were identified by PCA and multi-view pattern learning as top regions contributing to latent dimension shared across subsets of CNVs. The large proportion of distinct CNV effects on brain morphology may explain the small neuroimaging effect sizes reported in polygenic psychiatric conditions. Nevertheless, latent gene brain morphology dimensions will help subgroup the rapidly expanding landscape of neuropsychiatric variants and dissect the heterogeneity of idiopathic conditions

Smart distance keeping: modeling and perspectives for embedded diagnosis

International audienceThis paper presents a detailed description of an advanced Adaptive Cruise Control (ACC) system implemented on a Renault-Volvo Trucks vehicle. One of the main differences between this new system, which is called the Smart Distance Keeping (SDK), and the classical ACC is the choice of the safe distance. This later is the distance between the vehicle (with the ACC or the SDK system) and the front obstacle (which may be a vehicle). It is supposed fix in the case of the ACC, while variable in the case of the SDK. The variation of this distance (in the case of SDK) depends essentially on the relative velocity between the vehicle and the front obstacle. The choice of this distance influences the velocity regulation. The main contribution of this work is on the SDK system architecture, the design of its environment model, and the proposition of a detection and isolation strategy for some of the possible faults that may be produced on the system

ON THE RELIABILITY EVALUATION OF SRAM-BASED FPGA DESIGNS †

Benefits of Field Programmable Gate Arrays (FPGAs) have lead to a spectrum of use ranging from consumer products to astronautics. This diversity necessitates the need to evaluate the reliability of the FPGA, because of their high susceptibility to soft errors, which are due to the high density of embedded SRAM cells. Reliability evaluation is an important step in designing highly reliable systems, which results in a strong competitive advantage in today&apos;s marketplace. This paper proposes a mathematical model able to evaluate and therefore help to improve the reliability of SRAM-based FPGAs. 1

An Efficient BIST Architecture for Delay Faults in the Logic Cells of Symmetrical SRAM-Based FPGAs

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Towards on-line estimation of BTI/HCI-induced frequency degradation

International audienceThis work proposes a new bottom-up approach for on-line estimation of circuit performance loss due to BTI/HCI effects. Built on the top of device-level models, it takes into account all factors that impact global circuit aging, namely, process, topology, workload, voltage and temperature variations. The proposed model is fed by voltage and temperature monitors that on-line track dynamic variations. This allows an accurate assessment of the evolution of the circuit critical path delays during its operation. Its accuracy is evaluated here on two circuits implemented in 28nm FD-SOI technology