Constructing Confidence Intervals for Spearman’s Rank Correlation with Ordinal Data: A Simulation Study Comparing Analytic and Bootstrap Methods

Research shows good probability coverage using analytic confidence intervals (CIs) for Spearman’s rho with continuous data, but poorer coverage with ordinal data. A simulation study examining the latter case replicated prior results and revealed that coverage of bootstrap CIs was usually as good or better than coverage of analytic CIs

Towards maintainer script modernization in FOSS distributions

Free and Open Source Software (FOSS) distributions are complex software systems, made of thousands packages that evolve rapidly, independently, and without centralized coordination. During packages upgrades, corner case failures can be encountered and are hard to deal with, especially when they are due to misbehaving maintainer scripts: executable code snippets used to finalize package configuration. In this paper we report a software modernization experience, the process of representing existing legacy systems in terms of models, applied to FOSS distributions. We present a process to define meta-models that enable dealing with upgrade failures and help rolling back from them, taking into account maintainer scripts. The process has been applied to widely used FOSS distributions and we report about such experiences

Calibration of pipeline ADC with pruned Volterra kernels

A Volterra model is used to calibrate a pipeline ADC simulated in Cadence Virtuoso using the STMicroelectronics CMOS 45 nm process. The ADC was designed to work at 50 MSps, but it is simulated at up to 125 MSps, proving that calibration using a Volterra model can significantly increase sampling frequency. Equivalent number of bits (ENOB) improves by 1-2.5 bits (6-15 dB) with 37101 model parameters. The complexity of the calibration algorithm is reduced using different lengths for each Volterra kernels and performing iterative pruning. System identification is performed by least squares techniques with a set of sinusoids at different frequencies spanning the whole Nyquist band. A comparison with simplified Volterra models proposed in the literature shows better performance for the pruned Volterra model with comparable complexity, improving linearity by as much as 1.5 bits more than the other techniques

Closed and Open Loop Subspace System Identification of the Kalman Filter

Some methods for consistent closed loop subspace system identification presented in the literature are analyzed and compared to a recently published subspace algorithm for both open as well as for closed loop data, the DSR_e algorithm. Some new variants of this algorithm are presented and discussed. Simulation experiments are included in order to illustrate if the algorithms are variance efficient or not

Improvement of BepiColombo's radio science experiment through an innovative Doppler noise reduction technique

The Mercury Orbiter Radio science Experiment (MORE), onboard the ESA/JAXA BepiColombo mission to Mercury, is designed to estimate Mercury’s gravity field, its rotational state, and to perform tests of relativistic gravity. The state-of-the-art onboard and ground instrumentations involved in the MORE experiment will enable to establish simultaneous X/X, X/Ka and Ka/Ka-band links, providing a range rate accuracy of 3 µm/s (at 1000 s integration time) and a range accuracy of 20 cm. The purpose of this work is to show the improvement achievable on MORE’s performance by means of the Time-Delay Mechanical Noise Cancellation (TDMC) technique. The TDMC consists in a combination of Doppler measurements collected (at different times) at the two-way antenna and at an additional, smaller and stiffer, receive-only antenna that should be located in a site with favorable tropospheric conditions. This configuration could reduce the leading noises in a Ka-band two-way link, such as those caused by troposphere and ground antenna mechanical vibrations. We present the results of end-to-end simulations and estimation of Mercury’s gravity field and rotational state considering the TDMC technique. We compare results for a two-way link from NASA’s DSS-25 (in Goldstone, CA) or from ESA’s DSA-3 (in Malargue, Argentina), while we assume APEX as the receive-only antenna. We show that in best-case noise conditions, the TDMC technique allows to obtain a factor-of-two accuracy gain on both global and local parameters, considering DSA-3 as two-way antenna. Such improvement in the scientific objectives of MORE is of geophysical interest as it could provide a constraint on the interior structure of Mercury

Investigating the effects of odour integration in reading and learning experiences

Books are the tools used for reading novels and stories, but also for educational purposes. Conventional books have undergone a radical transformation in recent years due to the use of new technologies. However, even today the technological devices used for reading e-books are still poorly exploited, despite the fact that they represent a fundamental tool to make the reading experience more immersive by using a complete multisensory approach. In this perspective, one sense that represents an important element of human perception is the sense of smell. Consequently, authors make the hypothesis that the introduction of odours during reading sessions could increase the user experience and the learning performances. In order to demonstrate these hypotheses, the authors have defined and carried out several experimental testing sessions. The analysis of the collected data proved that the introduction of odour does not disturb the reader during reading activities but, on the contrary, can actually make the experience more immersive. Similarly, odours do not disturb studying activities, but they can instead increase the level of concentration and people's learning performance

Extending AMMA for Supporting Dynamic Semantics Specifications of DSLs

Over the last years, Model Driven Engineering platforms evolved from fixed metamodel tools to systems with variable metamodels. This enables dealing with a variety of Domain Specific Languages (DSLs). These generic platforms are increasingly adopted to solve problems like code generation. However, these environments are often limited to syntax definitions. The AMMA platform conceives DSLs as collections of coordinated models defined using a set of core DSLs. For broadening the approach to semantics definition, AMMA should thus be extended. The paper presents an extension of the core DSLs of AMMA to specify the dynamic semantics of a range of DSLs by means of Abstract State Machines. Thus, DSLs can be defined not only according to their abstract and concrete syntaxes but also to their semantics in a uniform and systematic way. The approach is validated by means of the semantic bootstrap of the ATL transformation language

Platelet activating factor (1-O-alkyl-2-O-acetyl-sn-glycero-3-phosphocholine) Activity of analogs lacking oxygen at the 2-position

In mission-critical Internet of Things systems, applications require not only high availability, reliability, safety, and security but also regulatory compliance, scalability, and serviceability. In addition, they\u27re exposed to uncertainty and variability. Model-driven engineering is a candidate for meeting these challenges