Generating a Performance Stochastic Model from UML Specifications

Since its initiation by Connie Smith, the process of Software Performance Engineering (SPE) is becoming a growing concern. The idea is to bring performance evaluation into the software design process. This suitable methodology allows software designers to determine the performance of software during design. Several approaches have been proposed to provide such techniques. Some of them propose to derive from a UML (Unified Modeling Language) model a performance model such as Stochastic Petri Net (SPN) or Stochastic process Algebra (SPA) models. Our work belongs to the same category. We propose to derive from a UML model a Stochastic Automata Network (SAN) in order to obtain performance predictions. Our approach is more flexible due to the SAN modularity and its high resemblance to UML' state-chart diagram

On the Robustness of Randomized Ensembles to Adversarial Perturbations

Randomized ensemble classifiers (RECs), where one classifier is randomly selected during inference, have emerged as an attractive alternative to traditional ensembling methods for realizing adversarially robust classifiers with limited compute requirements. However, recent works have shown that existing methods for constructing RECs are more vulnerable than initially claimed, casting major doubts on their efficacy and prompting fundamental questions such as: "When are RECs useful?", "What are their limits?", and "How do we train them?". In this work, we first demystify RECs as we derive fundamental results regarding their theoretical limits, necessary and sufficient conditions for them to be useful, and more. Leveraging this new understanding, we propose a new boosting algorithm (BARRE) for training robust RECs, and empirically demonstrate its effectiveness at defending against strong $\ell_\infty$ norm-bounded adversaries across various network architectures and datasets. Our code can be found at https://github.com/hsndbk4/BARRE.Comment: Published as a conference paper in ICML 202

Stroke prediction context-aware health care system

This paper proposes a prediction framework based on ontology and Bayesian Belief Networks BBN to support a medical teams in every daily. We propose a Stroke Prediction System (SPS), a new software component to handle the uncertainty of having a stroke disease by determining the risk score level. This is composed of four layers: acquisition of data, aggregation, reasoning and application. SPS senses, collects, and analyzes data of a patient, then uses wearable sensors and the mobile application to interact with the patient and staffs. When the risk reaches critical limits, SPS notifies all concerned parties, the patient, the doctor, and the emergency department. The patient profile is also updated to reflect this urgent intervention requirement. A Bayesian model is designed and implemented using the Netica tool to prove its efficiency i) by handling patient context remotely and verifying its changes locally and ii) on predicting missing probabilities and calculate the probability of high risk level for emergency cases. The SPS system improves the accuracy of decision making and uses a new ontology of stroke disease inspired from our Parkinson ontology already developed

Increase of reactive oxygen species contributes to growth inhibition by fluconazole in \u3cem\u3eCryptococcus neoformans\u3c/em\u3e

Background Cryptococcus neoformans, a basidiomycetous yeast, is a fungal pathogen that can colonize the lungs of humans causing pneumonia and fungal meningitis in severely immunocompromised individuals. Recent studies have implied that the antifungal drug fluconazole (FLC) can induce oxidative stress in C. neoformans by increasing the production of reactive oxygen species (ROS), as presence of the antioxidant ascorbic acid (AA) could reverse the inhibitory effects of FLC on C. neoformans. However, in Candida albicans, AA has been shown to stimulate the expression of genes essential for ergosterol biosynthesis. Hence, the contribution of ROS in FLC-mediated growth inhibition remains unclear. Results In order to determine whether counteracting ROS generated by FLC in C. neoformans can contribute to diminishing inhibitory effects of FLC, we tested three other antioxidants in addition to AA, namely, pyrrolidine dithiocarbamate (PDTC), retinoic acid (RA), and glutathione (GSH). Our data confirm that there is an increase in ROS in the presence of FLC in C. neoformans. Importantly, all four antioxidants reversed FLC-mediated growth inhibition of C. neoformans to various extents. We further verified the involvement of increased ROS in FLC-mediated growth inhibition by determining that ROS-scavenging proteins, metallothioneins (CMT1 and CMT2), contribute to growth recovery by PDTC and AA during treatment with FLC. Conclusion Our study suggests that ROS contributes to FLC-mediated growth inhibition and points to a complex nature of antioxidant-mediated growth rescue in the presence of FLC

Reliable bounding zones and inconsistency measures for GPS positioning using geometrical constraints

Reliable confidence domains for positioning with Global Navigation Satellite System (GNSS) and inconsistency measures for the observations are of great importance for any navigation system, especially for safety critical applications. In this work, deterministic error bounds are introduced in form of intervals to assess remaining observation errors. The intervals can be determined based on expert knowledge or - as in our case - based on a sensitivity analysis of the measurement correction process. Using convex optimization, bounding zones are computed for GPS positioning, which satisfy the geometrical constraints imposed by the observation intervals. The bounding zone is a convex polytope. When exploiting only the navigation geometry, a confidence domain is computed in form of a zonotope. We show that the relative volume between the polytope and the zonotope can be considered as an inconsistency measure. A small polytope volume indicates bad consistency of the observations. In extreme cases, empty sets are obtained which indicates large outliers. We explain how shape and volume of the polytopes are related to the positioning geometry. Furthermore, we propose a new concept of Minimum Detectable Biases. Using the example of the Klobuchar ionospheric model and Saastamoinen tropospheric model, we show how observation intervals can be determined via sensitivity analysis of these correction models for a real measurement campaign. Taking GPS code data from simulations and real experiments, a comparison analysis between the proposed deterministic bounding method and the classical least-squares adjustment has been conducted in terms of accuracy and reliability. It shows that the computed polytopes always enclose the reference trajectory. In case of large outliers, large position deviations persist in the least-squares solution while the polytope algorithm yields empty sets and thus successfully detects the cases with outliers

3D-Printed Hermetic Alumina Housings

Ceramics are repeatedly investigated as packaging materials because of their gas tightness, e.g., as hermetic implantable housing. Recent advances also make it possible to print the established aluminum oxide in a Fused Filament Fabrication process, creating new possibilities for manufacturing personalized devices with complex shapes. This study was able to achieve integration of channels with a diameter of 500 m (pre-sintered) with a nozzle size of 250 m (layer thickness 100 m) and even closed hemispheres were printed without support structures. During sintering, the weightbearing feedstock shrinks by 16.7%, resulting in a relative material density of 96.6%. The well-known challenges of the technology such as surface roughness (Ra = 15–20 m) and integrated cavities remain. However, it could be shown that the hollow structures in bulk do not represent a mechanical weak point and that the material can be gas-tight (<1012 mbar s1). For verification, a volume-free helium leak test device was developed and validated. Finally, platinum coatings with high adhesion examined the functionalization of the ceramic. All the prerequisites for hermetic housings with integrated metal structures are given, with a new level of complexity of ceramic shapes available