NN-based Prediction Interval for Nonlinear Processes Controller

Neural networks (NNs) are extensively used in modelling, optimization, and control of nonlinear plants. NN-based inverse type point prediction models are commonly used for nonlinear process control. However, prediction errors (root mean square error (RMSE), mean absolute percentage error (MAPE) etc.) significantly increase in the presence of disturbances and uncertainties. In contrast to point forecast, prediction interval (PI)-based forecast bears extra information such as the prediction accuracy. The PI provides tighter upper and lower bounds with considering uncertainties due to the model mismatch and time dependent or time independent noises for a given confidence level. The use of PIs in the NN controller (NNC) as additional inputs can improve the controller performance. In the present work, the PIs are utilized in control applications, in particular PIs are integrated in the NN internal model-based control framework. A PI-based model that developed using lower upper bound estimation method (LUBE) is used as an online estimator of PIs for the proposed PI-based controller (PIC). PIs along with other inputs for a traditional NN are used to train the PIC to predict the control signal. The proposed controller is tested for two case studies. These include, a chemical reactor, which is a continuous stirred tank reactor (case 1) and a numerical nonlinear plant model (case 2). Simulation results reveal that the tracking performance of the proposed controller is superior to the traditional NNC in terms of setpoint tracking and disturbance rejections. More precisely, 36% and 15% improvements can be achieved using the proposed PIC over the NNC in terms of IAE for case 1 and case 2, respectively for setpoint tracking with step changes.

     

EDITORIAL

The process undertaken by an information seeker, in order to form relevance decisions regarding documents, is defined as “Document Triage.” To better facilitate users’ needs in their triage activities, interactive interfaces have begun to evolve within on-line academic repositories. In order to complement current work on interface design and interaction, and produce custom guidelines to inform the creation of triage interfaces, we examine how interfaces that alter the document presentation and structure affect information seekers’ visual and navigational attention. We present a set of heuristics for both creating and evaluating such interfaces.     

Interval or moments: which carry more information?

In many practical situations, we do not have enough observations to uniquely determine the corresponding probability distribution, we only have enough observations to estimate two parameters of this distribution. In such cases, the traditional statistical approach is to estimate the mean and the standard deviation. Alternatively, we can estimate the two bounds that form the range of the corresponding variable and thus, generate an interval. Which of these two approaches should we select? A natural idea is to select the most informative approach, i.e., an approach in which we need the smallest amount of additional information (in Shannon’s sense) to obtain the full information about the situation. In this paper, we follow this idea and come up with the following conclusion: in practical situations in which a 95 % confidence level is sufficient, interval bounds are more informative; however, in situations in which we need higher confidence, the moments approach is more informative.     

Taking science education beyond schooling

Abstract

The shape and content of science education has always been articulated from the scientist's perspective. Recently, an increasing number of science educators have recognized the serious limitations of this perspective and have proposed to define scientific literacy from societal or citizenship perspectives. In this article, I argue that these alternatives will remain as limited as their predecessors unless the very structures of schooling are called into question. Furthermore, I argue that alternatives cannot be designed at the drawing board by theoreticians, but have to be grounded in praxis, thereby providing concrete trajectories along which science education can actually change.     

故障自动防护微机械角速度传感器

微机械角速度传感器是目前市场上能够进行批量生产的最复杂的传感器之一。它由在真空中做复杂运动的惯性质量块和驱动该设备、分析其响应的多种复杂电路组成,并集中于一个在极狭小的空间内。本文介绍了由奥地利SensorDynamics公司成功研制的一种MEMS角速率传感器,可以满足现代应用的全部要求,尤其是汽车工业所要求的小尺寸、坚固的机械结构、长期稳定性、不受限制的故障自动防护性和AEC-Q100认证。     

The weak aggregating algorithm and weak mixability

This paper resolves the problem of predicting as well as the best expert up to an additive term of the order o(n), where n is the length of a sequence of letters from a finite alphabet. We call the games that permit this weakly mixable and give a geometrical characterisation of the class of weakly mixable games. Weak mixability turns out to be equivalent to convexity of the finite part of the set of superpredictions. For bounded games we introduce the Weak Aggregating Algorithm that allows us to obtain additive terms of the form .     

Radiometric normalization and image mosaic generation of ASTER thermal infrared data: An application to extensive sand sheets and dune fields

Data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) have a significant advantage over previous datasets because of the combination of high spatial resolution (15-90 m) and enhanced multispectral capabilities, particularly in the thermal infrared (TIR) atmospheric window (8-12 μm) of the Earth where common silicate minerals are more easily identified. However, the 60 km swath width of ASTER can limit the effectiveness of accurately tracing large-scale features, such as eolian sediment transport pathways, over long distances. The primary goal of this paper is to describe a method for generating a seamless and radiometrically accurate ASTER TIR mosaic of atmospherically corrected radiance and from that, extract surface emissivity for arid lands, specifically, sand seas. The Gran Desierto in northern Sonora, Mexico was used as a test location for the radiometric normalization technique because of past remote sensing studies of the region, its compositional diversity, and its size. A linear approach was taken to transform adjacent image swaths into a direct linear relationship between image acquisition dates. Pseudo-invariant features (PIFs) were selected using a threshold of correlation between radiance values, and change-pixels were excluded from the linear regression used to determine correction factors. The degree of spectral correlation between overlapping pixels is directly related to the amount of surface change over time; therefore, the gain and offsets between scenes were based only on regions of high spectral correlation. The result was a series of radiometrically normalized radiance-at-surface images that were combined with a minimum of image edge seams present. These edges were subsequently blended to create the final mosaic. The advantages of this approach for TIR radiance (as opposed to emissivity) data include the ability to: (1) analyze data acquired on different dates (with potentially very different surface temperatures) as one seamless compositional dataset; (2) perform decorrelation stretches (DCS) on the entire dataset in order to identify and discriminate compositional units; and (3) separate brightness temperature from surface emissivity for quantitative compositional analysis of the surface, reducing seam-line error in the emissivity mosaic. The approach presented here is valid for any ASTER-related study of large geographic regions where numerous images spanning different temporal and atmospheric conditions are encountered.     

Using physical memorabilia as opportunities to move into collocated digital photo-sharing

The uptake of digital photos vs. print photos has altered the practice of photo-sharing. Print photos are easy to share within the home, but much harder to share outside of it. The opposite is true of digital photos. People easily share digital photos outside the home, e.g., to family and friends by e-mail gift-giving, and to social networks and the broader public by web publishing. Yet within the home, collocated digital photo-sharing is harder, primarily because digital photos are typically stored on personal accounts in desktop computers located in home offices. This leads to several consequences. (1) The invisibility of digital photos implies few opportunities for serendipitous photo-sharing. (2) Access control and navigation issues inhibit family members from retrieving photo collections. (3) Photo viewing is compromised as digital photos are displayed on small screens in an uncomfortable viewing setting.To mitigate some of these difficulties, we explore how physical memorabilia collected by family members can create opportunities that encourage social and collocated digital photo-sharing. First, we studied (via contextual interviews with 20 households) how families currently practice photo-sharing and how they keep memorabilia. We identified classes of memorabilia that can serve as memory triggers to family events, trips, and times when people took photos. Second, we designed Souvenirs, a photo-viewing system that exploits memorabilia as a social instrument. Using Souvenirs, a family member can meaningfully associate physical memorabilia with particular photo-sets. Later, any family member can begin their story-telling with others through the physical memento, and then enrich the story by displaying its associated photos simply by moving the memento close to the home's large-format television screen. Third, we re-examined our design premises by evoking household reactions to an early version of Souvenirs. Based on these interviews, we redesigned Souvenirs to better reflect the preferences and real practices of photo and memorabilia use in the home.