联营电力市场中需求侧的直接参与

在现有的允许需求侧竞标的日前联营市场中，每当某个时段的市场清算电价高于投标报价时，需求侧的兆瓦级购电竞标就被拒绝。由于用户不参与通过削减供电量来牟利的商业运作，因此未得到满足的用户需求只能从平衡市场中在更接近于预期用电的时段中获得。这就使用户遭受更大的不能以所希望的价格来满足其对电能的需要的风险。文章介绍了一种新的市场概念，它能在日前市场对需求侧的竞标者关闭后，以合并拍卖规则中需求移动机制的方法来降低其需求不平衡的风险。     

Forecasting Economic Data with Neural Networks

Studies in recent years have attempted to forecast macroeconomic phenomena with neural networks reporting mixed results. This work represents an investigation of this problem using U.S. Real Gross Domestic Production and Industrial Production as case studies. This work is based on a coefficient of determination which accurately measures the ability of linear or nonlinear models to forecast economic data. The significance of our work is twofold: (1) It confirms recent work that neural networks significantly outperform linear regression due to nonlinearities inherent in the data sets, and (2) it provides a systematic approach that guarantees to find the maximum correlation between input(s) and output of interest. JEL Classification: C45, C52, C53, C67,     

Large-Eddy Simulation of the Lid-Driven Cubic Cavity Flow by the Spectral Element Method

This paper presents the large-eddy simulation of the lid-driven cubic cavity flow by the spectral element method (SEM) using the dynamic model. Two spectral filtering techniques suitable for these simulations have been implemented. Numerical results for Reynolds number Re=12,000 are showing very good agreement with other experimental and DNS results found in the literature.     

A model of (en)action to approach embodiment: a cornerstone for the design of virtual environments for learning

This paper presents a model of (en)action from a conceptual and theoretical point of view. This model is used to provide solid bases to overcome the complexity of designing virtual environments for learning (VEL). It provides a common grounding for trans-disciplinary collaborations where embodiment can be perceived as the cornerstone of the project. Where virtual environments are concerned, both computer scientists and educationalists have to deal with the learner/user’s body; therefore the model provides tools with which to approach both human actions and learning processes within a threefold model. It is mainly based on neuroscientific research, including enaction and the neurophysiology of action.     

Quantum Malware

When quantum communication networks proliferate they will likely be subject to a new type of attack by hackers, virus makers, and other malicious intruders. Here we introduce the concept of “quantum malware” to describe such human-made intrusions. We offer a simple solution for storage of quantum information in a manner, which protects quantum networks from quantum malware. This solution involves swapping the quantum information at random times between the network and isolated, distributed ancillas. It applies to arbitrary attack types, provided the protective operations are themselves not compromised.     

Smart Cars on Smart Roads: An IEEE Intelligent Transportation Systems Society Update

To promote tighter collaboration between the IEEE Intelligent Transportation Systems Society and the pervasive computing research community, the authors introduce the ITS Society and present several pervasive computing-related research topics that ITS Society researchers are working on. This department is part of a special issue on Intelligent Transportation.     

Free viewpoint action recognition using motion history volumes

Action recognition is an important and challenging topic in computer vision, with many important applications including video surveillance, automated cinematography and understanding of social interaction. Yet, most current work in gesture or action interpretation remains rooted in view-dependent representations. This paper introduces Motion History Volumes (MHV) as a free-viewpoint representation for human actions in the case of multiple calibrated, and background-subtracted, video cameras. We present algorithms for computing, aligning and comparing MHVs of different actions performed by different people in a variety of viewpoints. Alignment and comparisons are performed efficiently using Fourier transforms in cylindrical coordinates around the vertical axis. Results indicate that this representation can be used to learn and recognize basic human action classes, independently of gender, body size and viewpoint.     

Attribute value reordering for efficient hybrid OLAP

The normalization of a data cube is the ordering of the attribute values. For large multidimensional arrays where dense and sparse chunks are stored differently, proper normalization can lead to improved storage efficiency. We show that it is NP-hard to compute an optimal normalization even for 1 × 3 chunks, although we find an exact algorithm for 1 × 2 chunks. When dimensions are nearly statistically independent, we show that dimension-wise attribute frequency sorting is an optimal normalization and takes time O(dn log(n)) for data cubes of size n^d. When dimensions are not independent, we propose and evaluate a several heuristics. The hybrid OLAP (HOLAP) storage mechanism is already 19-30% more efficient than ROLAP, but normalization can improve it further by 9-13% for a total gain of 29-44% over ROLAP.     

A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms

Stereo matching is one of the most active research areas in computer vision. While a large number of algorithms for stereo correspondence have been developed, relatively little work has been done on characterizing their performance. In this paper, we present a taxonomy of dense, two-frame stereo methods. Our taxonomy is designed to assess the different components and design decisions made in individual stereo algorithms. Using this taxonomy, we compare existing stereo methods and present experiments evaluating the performance of many different variants. In order to establish a common software platform and a collection of data sets for easy evaluation, we have designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can easily be extended to include new algorithms. We have also produced several new multi-frame stereo data sets with ground truth and are making both the code and data sets available on the Web. Finally, we include a comparative evaluation of a large set of today's best-performing stereo algorithms.     

Disk drive control: The early years

One of the persistently exciting control applications is that of disk drive servos. From the start in the early 1950s to the massive capacity commodity drives of the early 2000s, the problem of accessing data on rotating disk media has provided a wealth of control challenges to be solved. This survey paper traces the early history of disk drive control from the first disk drive in 1956 to the first commercial drive with Magneto-Resistive heads in 1990. Rather than the approach used in (Abramovitch and Franklin, 2002a) in which the histories of the components were outlined first, we will focus on the feedback loop itself in those early days. The paper will survey the different areas of the disk drive control problem and how they evolved.