7815226
Peak Load Forecasting Using the Self-organizing Map
This paper aims to study the short-term load forecasting of electricity by using an extended self-organizing map. We first adopt a traditional Kohonen self-organizing map (SOM) to learn time-series load data with weather information as parameters. Then, in order to improve the accuracy of the prediction, an extension of SOM algorithm based on error-correction learning rule is used, and the estimation of the peak load is achieved by averaging the output of all the neurons. Finally, as an implementation example, data of electricity demand from New York Independent System Operator (ISO) are used to verify the effectiveness of the learning and prediction for the proposed methods.
8972258
Designing oscillators in synthetic gene networks based on multi-scale dynamics
Multistability, oscillations, and switching exist at various levels of biological processes and organizations and have been investigated on the basis of many theoretical models, such as circadian oscillations with the period protein (PER) and the timeless protein (TIM) in Drosophila, and multistable dynamics regulated by transcriptional factors. Considerable experimental evidence suggests that cellular processes are intrinsically rhythmic or periodic. Various periodic oscillations with different time scales ranging from less than a second to more than a year, which may allow for living organisms to adapt their behaviors to a periodically varying environment, have also been observed experimentally. On the other hand, in synthetic gene networks, both toggle switch and repressilator have been theoretically proposed and further confirmed by experiments. All of these works stress the importance of feedback regulation of transcriptional factors, which is a key in giving rise to oscillatory or multistable dynamical behaviors exhibited by biological genetic systems. In addition, it should be noted that many periodic behaviors do not simply oscillate smoothly; rather, they change rapidly or jump at certain states. In gene expression systems, many different time scales characterize the gene regulatory processes. For instance, the transcription and translation processes generally evolve on a time scale that is much slower than that of phosphorylation, dimerization or binding reactions of transcription factors. In genetic networks, the time scale for expression of some genes is much slower than that of others, depending on the length of the genes. We aim to design robust periodic oscillators in synthetic gene-protein systems by simple nonlinear models and to analyze the basic mechanism of limit cycles with jumping behaviors or relaxation oscillations by exploiting multiple time-scale properties [1, 2]. We show that periodic oscillations are mainly generated by nonlinear feedback loops in gene regulatory systems and the jumping dynamics caused by time scale differences among biochemical reactions. Moreover, effects of time delay are also examined. We show that time delay generally enlarges the stability region of oscillations, thereby making the oscillations more sustainable despite parameter changes or noise [1, 2]. The dynamics of the proposed models is robust in terms of stability and period length to the parameter perturbations or environment variations. Although we mainly analyze some specific models, the mechanisms identified in this work are likely to apply to a variety of genetic regulatory systems. These simple models may actually act as basic building block in synthetic gene-protein networks, such as genetic oscillators or switches because the dynamics is robust for parameter perturbations or environment variations. Several examples are also provided to demonstrate implementation of synthetic oscillators by using genes of the /spl lambda/ phage bacteria.
16730298
Efficient moving object segmentation algorithm using background registration technique
An efficient moving object segmentation algorithm suitable for real-time content-based multimedia communication systems is proposed in this paper. First, a background registration technique is used to construct a reliable background image from the accumulated frame difference information. The moving object region is then separated from the background region by comparing the current frame with the constructed background image. Finally, a post-processing step is applied on the obtained object mask to remove noise regions and to smooth the object boundary. In situations where object shadows appear in the background region, a pre-processing gradient filter is applied on the input image to reduce the shadow effect. In order to meet the real-time requirement, no computationally intensive operation is included in this method. Moreover, the implementation is optimized using parallel processing and a processing speed of 25 QCIF fps can be achieved on a personal computer with a 450-MHz Pentium III processor. Good segmentation performance is demonstrated by the simulation results.
31293594
Integrating mRNA Decay Information into Co-Regulation Study
Absolute or relative transcript amounts measured through high-throughput technologies (e.g., microarrays) are now commonly used in bioinformatics analysis, such as gene clustering and DNA binding motif finding. However, transcription rates that represent mRNA synthesis may be more relevant in these analyses. Because transcription rates are not equivalent to transcript amounts unless the mRNA degradation rates as well as other factors that affect transcript amount are identical across different genes, the use of transcription rates in bioinformatics analysis may lead to a better description of the relationships among genes and better identification of genomic signals. In this article, we propose to use experimentally measured mRNA decay rates and mRNA transcript amounts to jointly infer transcription rates, and then use the inferred transcription rates in downstream analyses. For gene expression similarity analysis, we find that there tends to be higher correlations among co-regulated genes when transcription-rate-based correlations are used compared to those based on transcript amounts. In the context of identifying DNA binding motifs, using inferred transcription rates leads to more significant findings than those based on transcript amounts. These analyses suggest that the incorporation of mRNA decay rates and the use of the inferred transcription rates can facilitate the study of gene regulations and the reconstruction of transcriptional regulatory networks.
206977606
Priority Based Overlay Multicast for Distributed Interactive Applications
Distributed Interactive Applications (DIAs) is different with other network-based applications, since the data should be delivered to the receiver node according to its priority. Among the existing overlay multicast protocols the "priority-based directed minimum spanning tree" (PST) is designed for DIAs. But in PST the available bandwidth (avail-bw) is used inefficiently and the system becomes unstable when its scale increases. This paper proposed a novel overlay multicast protocol named Priority Based Overlay Multicast (POM), which uses the entities’ priority, links’ delay and node’s avail-bw to build multicast tree. By using POM the nodes with high priority receive the data in short delay, while the nodes with low priority tolerate a long delay in order to balance the available bandwidth usage among the nodes. The simulation results show that POM uses the avail-bw efficiently and keeps the system stable when its scale increases. Keywords: DIAs; Priority; Available bandwidth.
4784687
SERF: ODMG-based generic re-structuring facility
The age of information management and with it the advent of increasingly sophisticated technologies have kindled a need in the database community and others to re-structure existing systems and move forward to make use of these new technologies. Legacy application systems are being transformed to newer state-of-the-art systems, information sources are being mapped from one data model to another, a diversity of data sources are being transformed to load, cleanse and consolidate data into modern data-warehouses [CR99].
Re-structuring is thus a critical task for a variety of applications. For this reason, most object-oriented database systems (OODB) today support some form of re-structuring support [Tec94, Obj93, BKKK87]. This existing support of current OODBs [BKKK87, Tec94, Obj93] is limited to a pre-defined taxonomy of simple fixed-semantic schema evolution operations. However, such simple changes, typically to individual types only, are not sufficient for many advanced applications [Bré96]. More radical changes, such as combining two types of redefining the relationship between two types, are either very difficult or even impossible to achieve with current commercial database technology [Tec94, Obj93]. In fact, most OODBs would typically require the user to write ad-hoc programs to accomplish such transformations. Research that has begun to look into the issue of complex changes [Bré96, Ler96] is still limited by providing a fixed set of some selected (even if now more complex) operations.
To address these limitations of the current restructuring technology, we have proposed the SERF framework which aims at providing a rich environment for doing complex user-defined transformations flexibly, easily and correctly [CJR98b]. The goal of our work is to increase the usability and utility of the SERF framework and its applicability to re-structuring problems beyond OODB evolution. Towards that end, we provide re-usable transformations via the notion of SERF Templates that can be packaged into libraries, thereby increasing the portability of these transformations. We also now have a first cut at providing an assurance of consistency for the users of this system, a semantic optimizer that provides some performance improvements via enhanced query optimization techniques with emphasis on the re-structuring primitives [CNR99]. In this demo we give an overview of the SERF framework, its current status and the enhancements that are planned for the future. We also present an example of the application of SERF to a domain other than schema evolution, i.e., the web restructuring.
44509988
A threshold criterion, auto-detection and its use in MST-based clustering
Clustering is to group data points into homogenous clusters so that data points within the same cluster are more similar than data points belonging to different clusters. There are many effective clustering algorithms for discovering arbitrary shaped clusters, but one common problem of many algorithms is the difficulty for users to decide appropriate parameters for these algorithms. To reduce the dependence of clustering performance on parameters, this paper proposes a threshold criterion for the single linkage cluster analysis and incorporates it into the Minimum Spanning Tree (MST) based clustering method. Since the threshold can be automatically decided according to the underlying data distributions, arbitrary shaped clusters can be discovered with little human intervention. The experimental results on spatial data are very encouraging.