Slow Time-Varying Batch Process Quality Prediction Based on Batch Augmentation Analysis

In this paper, focusing on the slow time-varying characteristics, a series of works have been conducted to implement an accurate quality prediction for batch processes. To deal with the time-varying characteristics along the batch direction, sliding windows can be constructed. Then, the start-up process is identified and the whole process is divided into two modes according to the steady-state identification. In the most important mode, the process data matrix, used to establish the regression model of the current batch, is expanded to involve the process data of previous batches, which is called batch augmentation. Thus, the process data of previous batches, which have an important influence on the quality of the current batch, will be identified and form a new batch augmentation matrix for modeling using the partial least squares (PLS) method. Moreover, considering the multiphase characteristic, batch augmentation analysis and modeling is conducted within each phase. Finally, the proposed method is applied to a typical batch process, the injection molding process. The quality prediction results are compared with those of the traditional quality prediction method based on PLS and the ridge regression method under the proposed batch augmentation analysis framework. The conclusion is obtained that the proposed method based on the batch augmentation analysis is superior.

Dynamics of KPI lumps

A family of nonsingular rational solutions of the Kadomtsev-Petviashvili (KP) I equation are investigated. These solutions have multiple peaks whose heights are time-dependent and the peak trajectories in the xy-plane are altered after collision. Thus they differ from the standard multi-peaked KPI simple n-lump solutions whose peak heights as well as peak trajectories remain unchanged after interaction.The anomalous scattering occurs due to a non-trivial internal dynamics among the peaks in a slow time scale. This phenomena is explained by relating the peak locations to the roots of complex heat polynomials. It follows from the long time asymptotics of the solutions that the peak trajectories separate as O(√|t|) as |t| → ∞, and all the peak heights approach the same constant value corresponding to that of the simple 1-lump solution. Consequently, a multi-peaked n-lump solution evolves to a superposition of n 1-lump solutions asymptotically as |t| →∞.

Fast-time and slow-time processing of the pseudorandom amplitude-phase-shift keyed signals

The two-dimensional raw data structure is used for modern pulse-Doppler radars. Fast-time and slow-time processing of radar return signals is performed. The matched filter compresses each received pulse in fast time. The FFT-based spectral processing of the compressed pulses is then performed in slow time. The two-dimensional structure of raw data has specific features in radars with the transmission and reception of pseudorandom amplitude-phase-shift keyed (APSK) signals to a common aerial. It is formed when the coherent processing interval of the APSK signal is divided into subintervals. The article describes the fast-time and slow-time processing of the APSK signal subintervals. The structure of the signal in the subintervals is also analyzed. The choice of the subinterval duration is discussed. The possible energy losses during the processing of the reflected signals are estimated. The results of the processing modeling of the additive sum of APSK signals with different Doppler frequencies are presented.

A Method for Reducing Timing Jitter’s Impact in Through-Wall Human Detection by Ultra-Wideband Impulse Radar

Ultra-wideband (UWB) impulse radar is widely used for through-wall human respiration detection due to its high range resolution and high penetration capability. UWB impulse radar emits very narrow time pulses, which can directly obtain the impulse response of the target. However, the time interval between successive pulses emitted is not ideally fixed because of timing jitter. This results in the impulse response position of the same target not being fixed, but it is related to slow-time. The clutter scattered by the stationary target becomes non-stationary clutter, which affects the accurate extraction of the human respiration signal. In this paper, we propose a method for reducing timing jitter’s impact in through-wall human detection by UWB impulse radar. After the received signal is processed by the Fast Fourier transform (FFT) in slow-time, we model the range-frequency matrix in the frequency domain as a superposition of the low-rank representation of jitter-induced clutter data and the sparse representation of human respiratory data. By only extracting the sparse component, the impact of timing jitter in human respiration detection can be reduced. Both numerical simulated data and experimental data demonstrate that our proposed method can effectively remove non-stationary clutter induced by timing jitter and improve the accuracy of the human target signal extraction.

Slow-Time Code Design for Space-Time Adaptive Processing in Airborne Radar

Space-time adaptive processing (STAP) techniques have been motivated as a key enabling technology for advanced airborne radar applications. In this paper, a slow-time code design is considered for the STAP technique in airborne radar, and the principle for improving signal-to-clutter and noise ratio (SCNR) based on slow-time coding is given. We present two algorithms for the optimization of transmitted codes under the energy constraint on a predefined area of spatial-frequency and Doppler-frequency plane. The proposed algorithms are constructed based on convex optimization (CVX) and alternating direction (AD), respectively. Several criteria regarding parameter selection are also given for the optimization process. Numerical examples show the feasibility and effectiveness of the proposed methods.

Searching for Intimacy, Searching for Deleuze

In this article, the author is in Paris searching for Gilles Deleuze. She wants to become more intimate with him, spending slow time exploring his work. In her search for intimacy with Deleuze, she follows a map that she buys at a bouquiniste, and she chooses to take the roads toward an ontological conception of love, to an intimacy that blurs boundaries between public and private and between love and politics. Through this exploration, she develops an understanding of a diasporic intimacy that leads her further away from the structures of intimacy often found in the Oedipal home, to an intimacy that is more transient but not less significant. She finds that there is intimacy in the passing smile of a child, in the telling of a philosopher’s secret and from the offering of a paw from a stray dog. In these intimate gestures, she finds a strange and productive tenderness capable of redirecting becomings.

Long range correlations and slow time scales in a boundary driven granular model

We consider a velocity field with linear viscous interactions defined on a one dimensional lattice. Brownian baths with different parameters can be coupled to the boundary sites and to the bulk sites, determining different kinds of non-equilibrium steady states or free-cooling dynamics. Analytical results for spatial and temporal correlations are provided by analytical diagonalisation of the system’s equations in the infinite size limit. We demonstrate that spatial correlations are scale-free and time-scales become exceedingly long when the system is driven only at the boundaries. On the contrary, in the case a bath is coupled to the bulk sites too, an exponential correlation decay is found with a finite characteristic length. This is also true in the free cooling regime, but in this case the correlation length grows diffusively in time. We discuss the crucial role of boundary driving for long-range correlations and slow time-scales, proposing an analogy between this simplified dynamical model and dense vibro-fluidized granular materials. Several generalizations and connections with the statistical physics of active matter are also suggested.