Look-ahead-window-based interval adaptive feedrate scheduling for long five-axis spline toolpaths under axial drive constraints

Scheduling of the five-axis spline toolpath feedrate is of great significance for high-quality and high-efficiency machining using five-axis machine tools. Due to the fact that there exists nonlinear relationship between the Cartesian space of the cutting tool and the joint space of the five feed axes, it is a challenging task to schedule the five-axis feedrate under axial drive constraints. Most existing methods are researched for routine short spline toolpaths, however, the five-axis feedrate scheduling method expressed for long spline toolpaths is limited. This article proposes an interval adaptive feedrate scheduling method based on a dynamic moving look-ahead window, so as to generate smooth feedrate for long five-axis toolpath in a piecewise manner without using the integral toolpath geometry. First, the length of the look-ahead window which equals to that of the toolpath interval is determined in case of abrupt braking at the end of the toolpath. Then, the interval permissible tangential feed parameters in terms of the velocity, acceleration, and jerk are determined according to the axial drive constraints at each toolpath interval. At the same time, the end velocity of the current interval is obtained through looking ahead the next interval. Using the start and end velocities and the permissible feed parameters of each interval, the five-axis motion feedrate is scheduled via an interval adaptive manner. Thus, the feedrate scheduling task for long five-axis toolpath is partitioned into a series of extremely short toolpaths, which realizes the efficient scheduling of long spline toolpath feedrate. Experimental results on two representative five-axis spline toolpaths demonstrate the feasibility of the proposed approach, especially for long toolpaths.

Temporal context actively shapes EEG signatures of time perception

Our subjective perception of time is optimized to temporal regularities in the environment. This is illustrated by the central tendency effect: when estimating a range of intervals, short intervals are overestimated whereas long intervals are underestimated to reduce the overall estimation error. Most models of interval timing ascribe this effect to the weighting of the current interval with previous memory traces after the interval has been perceived. Alternatively, the perception of the duration could already be flexibly tuned to its temporal context. We investigated this hypothesis using an interval reproduction task with a shorter and longer interval range. As expected, reproductions were biased towards the subjective mean of each presented range. EEG analysis showed that temporal context affected neural dynamics during the perception phase. Specifically, longer previous durations decreased CNV and P2 amplitude and increased beta power. In addition, multivariate pattern analysis showed that it is possible to decode context from the transient EEG signal quickly after the onset and offset of the perception phase. Together, these results suggest that temporal context creates dynamic expectations which actively affect the perception of duration.Significance StatementThe subjective sense of duration does not arise in isolation, but is informed by previous experiences. This is demonstrated by abundant evidence showing that duration estimates are biased towards previously perceived time intervals. However, it is yet unknown whether this temporal context actively affects perception or asserts its influence in later, post-perceptual stages as proposed by most current formal models of this task. Using an interval reproduction task, we here show that EEG signatures flexibly adapt to the temporal context during perceptual encoding. Furthermore, interval history could be decoded from the transient EEG signal even when the current duration was identical. All in all, our results suggest that context actively influences perception.

Dynamic Emulation of a PEM Electrolyzer by Time Constant Based Exponential Model

The main objective of this paper is to develop a dynamic emulator of a proton exchange membrane (PEM) electrolyzer (EL) through an equivalent electrical model. Experimental investigations have highlighted the capacitive effect of EL when subjecting to dynamic current profiles, which so far has not been reported in the literature. Thanks to a thorough experimental study, the electrical domain of a PEM EL composed of 3 cells has been modeled under dynamic operating conditions. The dynamic emulator is based on an equivalent electrical scheme that takes into consideration the dynamic behavior of the EL in cases of sudden variation in the supply current. The model parameters were identified for a suitable current interval to consider them as constant and then tested with experimental data. The obtained results through the developed dynamic emulator have demonstrated its ability to accurately replicate the dynamic behavior of a PEM EL.

An Iterative Dimension-Wise Approach to the Structural Analysis with Interval Uncertainties

The structural analysis is inevitably surrounded with uncertainties and the interval analysis is a favorable method if insufficient data is available on uncertainties. The accuracy of current interval analysis methods including the interval perturbation method (IPM), subinterval perturbation method (SIPM) and dimension-wise approach (DWA) depends on a reference point (RP), e.g., the expansion point in IPM, for some problems due to ignoring the co-operative effects of multiple interval inputs on the response. To this end, an iterative dimension-wise approach (IDWA) is proposed. Either the minimal or maximal input vector of the response is identified as an RP by a global update in which a novel RP is dimension-wisely assembled by the minimal or maximal points of all sectional curves of the response surface at a previous RP through a local update. The interval response is calculated by deterministic solvers at the minimal and maximal input vectors. An acoustic analysis problem is studied eventually to validate the effectiveness of the proposed method, from which conclusions are drawn.

Blink Number Forecasting Based on Improved Bayesian Fusion Algorithm for Fatigue Driving Detection

An improved Bayesian fusion algorithm (BFA) is proposed for forecasting the blink number in a continuous video. It assumes that, at one prediction interval, the blink number is correlated with the blink numbers of only a few previous intervals. With this assumption, the weights of the component predictors in the improved BFA are calculated according to their prediction performance only from a few intervals rather than from all intervals. Therefore, compared with the conventional BFA, the improved BFA is more sensitive to the disturbed condition of the component predictors for adjusting their weights more rapidly. To determine the most relevant intervals, the grey relation entropy-based analysis (GREBA) method is proposed, which can be used analyze the relevancy between the historical data flows of blink number and the data flow at the current interval. Three single predictors, that is, the autoregressive integrated moving average (ARIMA), radial basis function neural network (RBFNN), and Kalman filter (KF), are designed and incorporated linearly into the BFA. Experimental results demonstrate that the improved BFA obviously outperforms the conventional BFA in both accuracy and stability; also fatigue driving can be accurately warned against in advance based on the blink number forecasted by the improved BFA.

Development of Nitinol Stents: Electropolishing Experiments

As a result of the collective efforts of engineers and physicians modern medicine is one of the most developed discipline nowadays. The invention of stents is one of the most important result of these works. With development of stents artery narrowing, which can often lead to death, can be efficiently treated. The stent is a biocompatible mesh, which is inserted into the narrowed section of the artery to dilate and prop up its wall hereby it ensures continuous blood flow. The bio-and haemocompatibility of stents have to be sufficient to avoid significant recurrent stenosis (restenosis). Better biocompatibility can be achieved using surface treatments such as chemical etching, electropolishing and coatings. In our research we developed self-expandable stents made of shape memory Ni-Ti alloy called nitinol. In this article the present stage of our work, the electropolishing experiments are summarized. A new electropolishing cell was worked out by using special stent holder to lead the current to the stent, which made possible the even electropolishing of the stent surface. The electrolyte, which was applied, contains less than 5% of perchloric acid. A current interval was determined which will be sufficient to determine the optimal polishing parameters, such as polishing time and current density with further researches.

ON BEGINS, MEETS AND BEFORE

Interval temporal logics (ITLs) are logics for reasoning about temporal statements expressed over intervals, i.e., periods of time. The most famous temporal logic for intervals studied so far is probably Halpern and Shoham's HS, which is the logic of the thirteen Allen's interval relations. Unfortunately, HS and most of its fragments are undecidable. This discouraged the research in this area until recently, when a number non-trivial decidable ITLs have been discovered. This paper is a contribution towards the complete classification of all different fragments of HS. We consider here different combinations of the interval relations begins (B), meets (A), later (L) and their inverses [Formula: see text], [Formula: see text] and [Formula: see text]. We know from previous work that the combination [Formula: see text] is decidable only when finite domains are considered (and undecidable elsewhere), and that [Formula: see text] is decidable over the natural numbers. In the present paper we show that, over strongly discrete linear models (e.g. finite orders, the naturals, the integers), decidability of [Formula: see text] can be further extended to capture the language [Formula: see text], which lies strictly in between [Formula: see text] and [Formula: see text]. The logic [Formula: see text] turns out to be maximal w.r.t decidability over the considered classes, and its satisfiability problem is EXPSPACE-complete. In this paper we also provide an optimal non-deterministic decision procedure, and we show that the language is powerful enough to polynomially encode metric constraints on the length of the current interval.

Phase-rectified signal averaging as a sensitive index of autonomic changes with aging

Standard heart rate variability (HRV) techniques have been questioned in the sleep and autonomic fields as imprecise measures of sympathetic and parasympathetic activity. A new technique has emerged, known as phase-rectified signal averaging (PRSA). PRSA is used to quantify the quasi-periodic accelerations and decelerations in short-term heart rate, an effect that is normally masked by artifacts and noise. When applied to a signal of peak-to-peak (RR) time intervals, these quasiperiodicities can be used to estimate overall vagal activity, quantified as deceleration capacity (DC) and acceleration capacity (AC). We applied the PRSA analysis to a healthy cohort (ages 21–60 yr) enrolled in a clinical sleep trial, in which ECG data during wakefulness and sleep were available. We found that DC and AC were significantly attenuated with increasing age: a 0.27 ms/yr decrease in DC and a 0.29 ms/yr increase in AC ( P < 0.001). However, even in the older subjects, DC values were higher then previously found in people post-myocardial infarction. We also found a drop in percentage of normal-to-normal intervals where the current interval deviated >50 ms from the previous interval with age, with a decrease of 0.84%/yr. We did not find any differences between younger and older subjects with traditional HRV techniques, such as low-frequency or high-frequency power. Overall, the study provides normative PRSA data and suggests that PRSA is more sensitive than other HRV measurements. We propose that the decrease in DC and AC may be a sensitive marker for autonomic changes with aging. Further work will be required to determine whether the observed changes predict poorer cardiac health prognosis.

A rate signal interpreter

A simple, on-the-line device is described for converting an electrical pulse pattern into a continuous voltage output proportional to the instantaneous pulse rate. The special purpose circuit and an analog computer version are both given. Pulse rates varying by 30:1 are adequately measured. Multiple ranges are provided. A special feature is that a falling rate is followed as soon as the current interval exceeds the last completed interval. The circuit is stable and components are not critical. impulse rate; rate measurement; instrumentation; interval measurement Submitted on November 16, 1964