Quality Control for Scalable Media Processing Applications

Many media processing applications create a load that varies significantly over time. Hence, if such an application is assigned a lower processing-time budget than needed in its worst-case load situation, deadline misses are likely to occur. This problem can be dealt with by designing media processing applications in a scalable fashion. A scalable media processing application can run in multiple qualities, leading to correspondingly different resource demands. The problem we consider is to find an accompanying quality control strategy, which minimizes both the number of deadline misses and the number of quality changes, while maximizing the quality of processing. We present an initial approach to the above problem by modeling it as a Markov decision process (MDP). Our model is based on measuring relative progress at milestones. Solving the MDP results in a quality control strategy that can be applied during runtime with only little overhead. We evaluate our approach by means of a practical example, which concerns a scalable MPEG-2 decoder.     

On a large-gain theorem

The aim of this paper is to give a general quantitative requirement which the loop gain must satisfy in order to stabilize a given unstable (possibly nonlinear and time-varying) plant, namely that the gain must exceed one.     

压缩式致冷设备的电子宽温域多功能控制

设计并研制了一种用于压缩式致冷设备的电子式定温域多功能控制装置。它除具有控温范围宽、精度高、控温参数易调等优点外，还实现了低成本的温度显示、半自动除霜控制、加电延时保护、过欠压保护等功能。全部采用无触点控制方式，有良好的性能／价格比。     

H∞-control with measurement-feedback for Pritchard-Salamon systems

In this paper we extend the finite-dimensional results for the H_∞-control problem with measurement-feedback to a large class of infinite-dimensional systems, allowing for a certain type of unboundedness in the input and output operators (the Pritchard-Salamon class). The main result of the paper relates the solvability to the suboptimal H_∞-control problem to the existence of stabilizing solutions to certain operator Riccati equations. Furthermore, a characterization of all suboptimal controllers is given.     

An explicit finite difference method for finite-time observers

In this paper we present a numerical method for estimating the current state of a nonlinear control system. We use finite differences to discretize a modified version of the finite-time observer equations in James. The discretized equations are simple and easily programmed. The convergence and accuracy of the scheme is proved, and the scheme enjoys a number of important properties: availability of rate of convergence estimates, good robustness characteristics, and the ability to handle certain types of discontinuities in the observations. The major disadvantage is that the number of grid points required increases exponentially with the number of state dimensions.     

Management of multidimensional discrete data

Spatial database management involves two main categories of data: vector and raster data. The former has received a lot of in-depth investigation; the latter still lacks a sound framework. Current DBMSs either regard raster data as pure byte sequences where the DBMS has no knowledge about the underlying semantics, or they do not complement array structures with storage mechanisms suitable for huge arrays, or they are designed as specialized systems with sophisticated imaging functionality, but no general database capabilities (e.g., a query language). Many types of array data will require database support in the future, notably 2-D images, audio data and general signal-time series (1-D), animations (3-D), static or time-variant voxel fields (3-D and 4-D), and the ISO/IEC PIKS (Programmer's Imaging Kernel System) BasicImage type (5-D). In this article, we propose a comprehensive support ofmultidimensional discrete data (MDD) in databases, including operations on arrays of arbitrary size over arbitrary data types. A set of requirements is developed, a small set of language constructs is proposed (based on a formal algebraic semantics), and a novel MDD architecture is outlined to provide the basis for efficient MDD query evaluation.     

An Effective Software Pipelining Algorithm for Clustered Embedded VLIW Processors

This paper proposes a software pipelining framework, CALiBeR (ClusterAware Load Balancing Retiming Algorithm), suitable for compilers targetingclustered embedded VLIW processors. CALiBeR can be used by embedded systemdesigners to explore different code optimization alternatives, that is, high-qualitycustomized retiming solutions for desired throughput and program memory sizerequirements, while minimizing register pressure. An extensive set of experimentalresults is presented, demonstrating that our algorithm compares favorablywith one of the best state-of-the-art algorithms, achieving up to 50% improvementin performance and up to 47% improvement in register requirements. In orderto empirically assess the effectiveness of clustering for high ILP applications,additional experiments are presented contrasting the performance achievedby software pipelined kernels executing on clustered and on centralized machines.     

Information systems and uncertainty: a conspiracy of misplaced confidence

Abstract. Information technology is becoming an increasingly important factor in contemporary management. Information systems are being set up in business explicitly to accommodate the new opportunities of this technology, and these are having a lasting effect on managerial practice. The full implications of this technology-driven development have not been appreciated by organizations, which in absorbing technological systems, are tolerating a great drain on their resources.
The efficacy of computers is predicated on the acceptance of some very specific perspectives. A growing discontent and disappointment with their limited achievements is our reason for advocating a different point of view. We will discuss how a shift in perspective, particularly in respect to the perception of uncertainty, will affect thinking and practice in the field of management support systems. We will render our view of the application of computerized decision support systems (DSS), and especially, we will focus on the beliefs and assumptions that have shaped this technology thus far. To this end we will discuss the concept of uncertainty, by juxtaposing current thinking and practice with our understanding of the context of its application. Finally, we will place our understanding of uncertainty in a managerial context and explain the implications this would have for strategists.