Evaluation of the predictability of real-time crash risk models

The primary objective of the present study was to investigate the predictability of crash risk models that were developed using high-resolution real-time traffic data. More specifically the present study sought answers to the following questions: (a) how to evaluate the predictability of a real-time crash risk model; and (b) how to improve the predictability of a real-time crash risk model. The predictability is defined as the crash probability given the crash precursor identified by the crash risk model. An equation was derived based on the Bayes’ theorem for estimating approximately the predictability of crash risk models. The estimated predictability was then used to quantitatively evaluate the effects of the threshold of crash precursors, the matched and unmatched case-control design, and the control-to-case ratio on the predictability of crash risk models. It was found that: (a) the predictability of a crash risk model can be measured as the product of prior crash probability and the ratio between sensitivity and false alarm rate; (b) there is a trade-off between the predictability and sensitivity of a real-time crash risk model; (c) for a given level of sensitivity, the predictability of the crash risk model that is developed using the unmatched case-controlled sample is always better than that of the model developed using the matched case-controlled sample; and (d) when the control-to-case ratio is beyond 4:1, the increase in control-to-case ratio does not lead to clear improvements in predictability.     

A comparison of the predictability of batch flotation kinetic models

Batch flotation test data of a mixture of pyrite and calcite were used to compare regression parameters of four kinetic model structures. The work included the use of unoxidized or a mixture of partially oxidized pyrite (by microwave irradiation). The objective of floating oxidized pyrite was to have mineral particles with different floatability, closer to a real situation. The models considered include: single rate constant, distributed rate constants (i.e. rectangular and gamma distributions), and a recently introduced approach based on fractional calculus. Such models were selected due to their good tradeoff between simplicity and accuracy. The regressions were performed (1) taking all the data points and comparing the mean square error (MSE) and adjusted correlation factor $\left(R_{\mathit{Adj}}^2\right)$ as indicators of the goodness of fit; and (2) taking the first data points while neglecting the last ones (from 1 to 3) and observing the variability of the model parameters and the prediction of maximum recovery (R_∞). For the latter regression scheme, besides MSE and $R_{\mathit{Adj}}^2$, a predictive factor, E, was defined by subtracting the final measured recovery from the calculation obtained by the model. This allowed to measure the ability of each model to extrapolate the omitted points on the recovery vs. time curve.Results from this study showed that the single constant model had a satisfactory performance with the advantage of having the least parameters compared to the other structures. The gamma model was effective and robust. The rectangular model gave an acceptable goodness of fit but overestimated the maximum and final recovery. Finally, the fractional calculus approach gave the best goodness of fit, overall, but failed in predicting the maximum recovery, which occurred when the derivative order was greater than 1.     

Circular causality and indeterminism in machines for design

Presenting a hard-to-predict typography-varying system predicated on Nazi-era cryptography, the Enigma cipher machine, this paper illustrates conditions under which unrepeatable phenomena can arise, even from straight-forward mechanisms. Such conditions arise where systems are observed from outside of boundaries that arise through their observation, and where such systems refer to themselves in a circular fashion. It argues that the Enigma cipher machine is isomorphous with Heinz von Foersters portrayals of non-triviality in his non-trivial machine (NTM), but not with surprising human behaviour, and it demonstrates that the NTM does not account for spontaneity as it is observed in humans in general.     

Investigation of the Biopharmaceutical Behavior of Theophylline Hydrophilic Matrix Tablets Using USP Methods and an Artificial Digestive System

This work aimed to investigate the biopharmaceutical behavior of hydrophilic matrix tablets of theophylline using different in vitro methods: USP II, USP IV, and a novel in vitro system simulating the gastrointestinal tract in man called the artificial digestive system (ADS). The potentiality of each method was evaluated by establishing in vitro/in vivo correlation. Using USP methods, the drug release was pH-independent and dependent on agitation intensity. Level A IVIVCs could be established using the different in vitro methods but one to one correlation was established only when the ADS method was used. For the prediction of in vivo drug dosage form behavior based on in vitro methods, the ADS showed a high predictability when compared to USP in vitro methods.     

Meaningful Multicollinearity Measures

Problems of multicollinearity in regression analysis are considered and numerical measures established to assess the extent of multicollinearity in a set of regression data with respect to parameter confidence regions and tests of hypotheses, the effective sample size, and predictability.     

Timing predictability of cache replacement policies

Hard real-time systems must obey strict timing constraints. Therefore, one needs to derive guarantees on the worst-case execution times of a system’s tasks. In this context, predictable behavior of system components is crucial for the derivation of tight and thus useful bounds. This paper presents results about the predictability of common cache replacement policies. To this end, we introduce three metrics, evict, fill, and mls that capture aspects of cache-state predictability. A thorough analysis of the LRU, FIFO, MRU, and PLRU policies yields the respective values under these metrics. To the best of our knowledge, this work presents the first quantitative, analytical results for the predictability of replacement policies. Our results support empirical evidence in static cache analysis.

Time in ergonomics research

Abstract

The mastering of dynamic situations by human operators is a recurring theme in ergonomics. In order to paint an up-date picture of research a heuristic approach has been adopted by taking an interest in temporal errors and in ergonomical solutions. A temporal error in a dynamic situation is taken to mean an undesired adjustment of the evolution of this situation—whether or not this adjustment is the object of temporal reasoning. The errors have to do with order relationships, durations and temporal perspectives and they have been looked at from four different angles: (1) as shifts in relation to a norm, (2) as stemming from characteristics of the situation, (3) as resulting from an inadequacy or from a conflict of temporal reference systems, and (4) as the products of an inferential reasoning. Each time, the ergonomical implications of these options will be discussed.     

On detecting predictability of one-sided sequences

We consider predicting and predictability for discrete time processes in a pathwise setting where only a sole one-sided semi-infinite sequence of past values is available, and where statistical properties of the ensemble of the paths are unknown. We obtain some sufficient conditions of predictability in the terms of degeneracy of frequency characteristics representing one-sided modifications of the Z-transform. These characteristics are defined for one-sided semi-infinite sequences representing of the past values. Some predictors are discussed.     

Predictivity of system delays shortens human response time

System delays considerably affect users' experience and performance. Research on the psychological effects of system delays has focused on delay length and variability. We introduce delay predictivity as a new factor profoundly affecting user performance. A system delay is predictive when its duration is informative about the nature of consecutive interaction events. We report an experiment (N=122) where short delays were differently distributed across two alternative target stimuli in a choice response task. We manipulated variability and predictivity of delays. For one group of participants the delays were of constant duration. For three other groups the delays were variable, but differed in predictivity. They were either non-predictive, probabilistically predictive (they predicted the targets with a probability of 0.8), or deterministically predictive. Performance with constant delays was superior to performance with variable non-predictive or with probabilistically predictive delays. Surprisingly, participants with deterministically predictive delays outperformed participants in all other groups. This has important implications for interface design, whenever there is some degree of freedom in scheduling system delays. Best performance is achieved with predictive delays, but only when deterministic predictivity can be achieved. Otherwise, constant delays are to be preferred over variable ones.