Experiences in applying data‐driven modelling technology to steelmaking processes

Experience has shown that data‐driven modelling methods are useful for improving steelmaking processes. In particular, principal components analysis and partial least squares are well‐suited for industrial implementation because they address practical issues such as colinearity and missing data. In the course of applying these multivariate methods on‐line, a need for a flexible computer infrastructure to better support data handling and model implementation was identified and met with an internally developed software calculation platform. Multivariate methods have been found useful for monitoring and for prediction and can also be applied as a foundation for other methods such as optimization.     

Improving branch prediction accuracy by reducing pattern history table interference

A deeply pipelined superscalar processor needs an accurate branch predictor in order to approach its performance potential. The 2-level branch predictors have been shown to achieve high prediction accuracy, yet they still suffer a significant number of mispredictions. It has been shown that a number of these mispredictions are due to interference in the pattern history tables. This paper details a method for reducing the amount of pattern history table interference by dynamically identifying some easily predictable branches and inhibiting the pattern history table update for these branches. We show that inhibiting the update in this manner reduces the amount of destructive interference in the global history variation of the 2-level branch predictor, resulting in significantly improved branch prediction accuracy for the SPEC 95 benchmarks. For example, for a 2 K Byte gshare predictor, we eliminate 38% of the mispredictions for the gcc benchmark.     

An event-based analysis of the coordination of early infant vocalizations and facial actions.

This study used an event-based approach to provide empirical evidence regarding the nature of coordination in 3- and 6-month-old infants. Vocalizations and facial actions of 12 normally developing infants interacting with their caregivers were coded. Coded vocalizations and facial actions were considered coordinated when they temporally overlapped. Results indicate that infants coordinated their vocalizations and facial actions more than expected by chance. Coordinated events were governed by 2 sequence patterns. When 2 communicative events were temporally associated across modalities, 1 event tended to be completely embedded within the other, and vocalizations tended to end before facial actions. This study provides new information about how infant communication is structured, confirms results from other coordination studies, and describes a new method for analysis of event-based data. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Power-of-two policies for single-warehouse multi-retailer inventory systems with order frequency discounts

This paper presents power-of-two policies for a single-warehouse multi-retailer system. In this system, discounts on the purchasing cost based on order frequency are given to the warehouse. Models with assumptions analogous to the EOQ environment are discussed for all-unit and incremental order frequency discounts. 94%-effective power-of-two policies are developed for both models. For incremental discounts, a 98%-effective power-of-two policy for a variable base planning period is also derived. For each model, a computational study shows every test problem considered has a power-of-two policy that is over 96% effective. An extension to holding costs that are dependent on the purchasing price is also provided.     

Results analysis for trust constrained real-time optimization

In real-time optimization (RTO), results analysis is used to ensure that RTO predictions can be implemented and are not the result of the unnecessary variance transmission around the RTO loop. Miletic and Marlin [2] proposed a statistical framework for analyzing RTO results; however, their method cannot effectively deal with inequality constraints. Many industrial RTO implementations include bounds on the changes that the RTO system can make to the process operation (i.e. trust-region constraints). Such trust-region constraints can seriously degrade the performance of existing results analysis methods. In this paper, a results analysis procedure is proposed that incorporates statistical testing on both the primal and dual variables of the optimization problem to effectively analyze steady-state RTO results in the presence of trust-region constraints. The proposed method is illustrated using two small case studies, one of which is the same Williams and Otto [11] reactor example used in [2].     

Performance Analysis of Perturbation‐Based Methods for Real‐Time Optimization

This paper provides a comprehensive performance analysis approach for Real‐Time Optimization (RTO) technologies, which incorporates systematic approaches to estimating bounds on the convergence behaviour and performance effects of on‐line experiments used by a given RTO approach. The performance analysis method is illustrated by an investigation of the conventional two‐phase approach and representative techniques drawn from the three main classes of perturbation‐based RTO methods which attempt to directly compensate for plant/model mismatch through adaptation. The proposed approach is applied to two simulation‐based case studies: a heat exchanger system and a continuous bioreactor.     

基于稳态模型的常压蒸馏塔在线优化控制

在深入探讨在线代化概念的基础上，提出了一种基于过程稳态模型的常压蒸馏塔在线优化策略，构造了包括代化层、控制层在内的多级优化控制系统。重点介绍了稳态优化器的设计以及在线优化系统的实施，并给出了常压加热炉出口温度在线优化与常压蒸馏增轻油收率在线优化两个成功的应用实例，获得了良好的经济效益。     

A Price-Directed Approach to Real-Time Scheduling of Production Operations

Most past approaches to job shop scheduling are either highly myopic, or they are unable to adapt effectively to the stream of unforeseen disruptions that characterizes almost all manufacturing systems. We propose a two-module scheduling system that is both robust and non-myopic. Periodically a Planning Module develops a global view of what is likely to happen in die facility over the next one to four weeks. It then passes information down to the Dispatching Module. The Dispatching Module is based on microprocessors that are located on the factory floor. Whenever a machine is about to become idle, a fast optimization algorithm is run on the closest microprocessor to decide which job should be done next. The data provided by the Planning Module allows this decision to be made in a non-myopic manner.     

陆相伸展性盆地二级层序的厘定

对二级层序的界面、内部沉积演化及其与构造活动、盆地沉降史的耦合关系进行了分析,系统阐述了厘定陆相伸展性盆地二级层序的依据。我国东部新生代盆地古近系可划分为4～5个二级层序,层序界面普遍为一个区域性角度不整合面,界面上、下古生物组合及沉积特征存在明显变化;层序内部表现为一个大尺度的水进-水退的充填序列,层序底部发育大型低位扇体。二级层序对应于盆地的幕式构造演化阶段,其底界面的形成与构造反转、断块掀斜旋转、岩浆侵入和火山喷发、构造应立场转变等构造事件密切相关。因此,陆相伸展性盆地二级层序受控于区域性构造活动,与构造活动的耦合关系也是厘定该级别层序的关键所在。     

Using Predicated Execution to Improve the Performance of a Dynamically Scheduled Machine with Speculative Execution

Conditional branches incur a severe performance penalty in wide-issue, deeply pipelined processors. Speculative execution^{(1, 2)} and predicated execution^(3–9) are two mechanisms that have been proposed for reducing this penalty. Speculative execution can completely eliminate the penalty associated with a particular branch, but requires accurate branch prediction to be effective. Predicated execution does not require accurate branch prediction to eliminate the branch penalty, but is not applicable to all branches and can increase the latencies within the program. This paper examines the performance benefit of using both mechanisms to reduce the branch execution penalty. Predicated execution is used to handle the hard-to-predict branches and speculative execution is used to handle the remaining branches. The hard-to-predict branches within the program are determined by profiling. We show that this approach can significantly reduce the branch execution penalty suffered by wide-issue processors.