Logistic regression for simulating damage occurrence on a fruit grading line

Many factors influence the incidence of mechanical damage in fruit handled on a grading line. This makes it difficult to address damage estimation from an analytical point of view. During fruit transfer from one element of a grading line to another, damage occurs as a combined effect of machinery roughness and the intrinsic susceptibility of fruit. This paper describes a method to estimate bruise probability by means of logistic regression, using data yielded by specific laboratory tests. Model accuracy was measured via the statistical significance of its parameters and its classification ability. The prediction model was then linked to a simulation model through which impacts and load levels, similar to those of real grading lines, could be generated. The simulation output sample size was determined to yield reliable estimations. The process makes it possible to derive a suitable line design and the type of fruit that should be handled to maintain bruise levels within European Union (EU) Standards. A real example with peaches was carried out with the aid of the software implementation SIMLIN®, developed by the authors and registered by Madrid Technical University. This kind of tool has been demanded by inter-professional associations and grading lines designers in recent year

Evaluating Prediction Rules for t-Year Survivors With Censored Regression Models

Suppose that we are interested in establishing simple, but reliable rules for predicting future t-year survivors via censored regression models. In this article, we present inference procedures for evaluating such binary classification rules based on various prediction precision measures quantified by the overall misclassification rate, sensitivity and specificity, and positive and negative predictive values. Specifically, under various working models we derive consistent estimators for the above measures via substitution and cross validation estimation procedures. Furthermore, we provide large sample approximations to the distributions of these nonsmooth estimators without assuming that the working model is correctly specified. Confidence intervals, for example, for the difference of the precision measures between two competing rules can then be constructed. All the proposals are illustrated with two real examples and their finite sample properties are evaluated via a simulation study

Direct certification of a class of quantum simulations

One of the main challenges in the field of quantum simulation and computation is to identify ways to certify the correct functioning of a device when a classical efficient simulation is not available. Important cases are situations in which one cannot classically calculate local expectation values of state preparations efficiently. In this work, we develop weak-membership formulations of the certification of ground state preparations. We provide a non-interactive protocol for certifying ground states of frustration-free Hamiltonians based on simple energy measurements of local Hamiltonian terms. This certification protocol can be applied to classically intractable analog quantum simulations: For example, using Feynman-Kitaev Hamiltonians, one can encode universal quantum computation in such ground states. Moreover, our certification protocol is applicable to ground states encodings of IQP circuits demonstration of quantum supremacy. These can be certified efficiently when the error is polynomially bounded.Comment: 10 pages, corrected a small error in Eqs. (2) and (5

Cluster mass estimation through Fair Galaxies

We analyse a catalogue of simulated clusters within the theoretical framework of the Spherical Collapse Model (SCM), and demonstrate that the relation between the infall velocity of member galaxies and the cluster matter overdensity can be used to estimate the mass profile of clusters, even though we do not know the full dynamics of all the member galaxies. In fact, we are able to identify a limited subset of member galaxies, the 'fair galaxies', which are suitable for this purpose. The fair galaxies are identified within a particular region of the galaxy distribution in the redshift (line-of-sight velocity versus sky-plane distance from the cluster centre). This 'fair region' is unambiguously defined through statistical and geometrical assumptions based on the SCM. These results are used to develop a new technique for estimating the mass profiles of observed clusters and subsequently their masses. We tested our technique on a sample of simulated clusters; the mass profiles estimates are proved to be efficient from 1 up to 7 virialization radii, within a typical uncertainty factor of 1.5, for more than 90 per cent of the clusters considered. Moreover, as an example, we used our technique to estimate the mass profiles and the masses of some observed clusters of the Cluster Infall Regions in the Sloan Digital Sky Survey catalogue. The technique is shown to be reliable also when it is applied to sparse populated clusters. These characteristics make our technique suitable to be used in clusters of large observational catalogues.Comment: 11 pages, 11 figures, 5 tables - Slightly revised to match the version published on MNRAS; abstract update

On general systems with network-enhanced complexities

In recent years, the study of networked control systems (NCSs) has gradually become an active research area due to the advantages of using networked media in many aspects such as the ease of maintenance and installation, the large flexibility and the low cost. It is well known that the devices in networks are mutually connected via communication cables that are of limited capacity. Therefore, some network-induced phenomena have inevitably emerged in the areas of signal processing and control engineering. These phenomena include, but are not limited to, network-induced communication delays, missing data, signal quantization, saturations, and channel fading. It is of great importance to understand how these phenomena influence the closed-loop stability and performance properties

Estimation of Collision Multiplicities in IEEE 802.11-based WLANs

Abstract—Estimating the collision multiplicity (CM), i.e. the number of users involved in a collision, is a key task in multipacket reception (MPR) approaches and in collision resolution (CR) techniques. A new technique is proposed for IEEE 802.11 networks. The technique is based on recent advances in random matrix theory and rely on eigenvalue statistics. Provided that the eigenvalues of the covariance matrix of the observations are above a given threshold, signal eigenvalues can be separated from noise eigenvalues since their respective probability density functions are converging toward two different laws: a Gaussian law for the signal eigenvalues and a Tracy-Widom law for the noise eigenvalues. The proposed technique outperforms current estimation techniques in terms of underestimation rate. Moreover, this paper reveals that, contrary to what is generally assumed in current MPR techniques, a single observation of the colliding signals is far from being sufficient to perform a reliable CM estimation