550060
Automatic categorization of figures in scientific documents
Figures are very important non-textual information contained in scientific documents. Current digital libraries do not provide users tools to retrieve documents based on the information available within the figures. We propose architecture for retrieving documents by integrating figures and other information. The initial step in enabling integrated document search is to categorize figures into a set of pre-defined types. We propose several categories of figures based on their functionalities in scholarly articles. We have developed a machine-learning-based approach for automatic categorization of figures. Both global features, such as texture, and part features, such as lines, are utilized in the architecture for discriminating among figure categories. The proposed approach has been evaluated on a testbed document set collected from the CiteSeer scientific literature digital library. Experimental evaluation has demonstrated that our algorithms can produce acceptable results for real- world use. Our tools can be integrated into a scientific-document digital library
14843520
Deriving knowledge from figures for digital libraries
Figures in digital documents contain important information. Current digital libraries do not summarize and index information available within figures for document retrieval. We present our system on automatic categorization of figures and extraction of data from 2-D plots. A machine-learning based method is used to categorize figures into a set of predefined types based on image features. An automated algorithm is designed to extract data values from solid line curves in 2-D plots. The semantic type of figures and extracted data values from 2-D plots can be integrated with textual information within documents to provide more effective document retrieval services for digital library users. Experimental evaluation has demonstrated that our system can produce results suitable for real-world use.
2511396
An architecture for creating collaborative semantically capable scientific data sharing infrastructures
Increasingly, scientists are seeking to collaborate and share data among themselves. Such sharing is can be readily done by publishing data on the World-Wide Web. Meaningful querying and searching on such data depends upon the availability of accurate and adequate metadata that describes the data and the sources of the data. In this paper, we outline the architecture of an implemented cyber-infrastructure for chemistry that provides tools for users to upload datasets and their metadata to a database. Our proposal combines a two level metadata system with a centralized database repository and analysis tools to create an effective and capable data sharing infrastructure. Our infrastructure is extensible in that it can handle data in different formats and allows different analytic tools to be plugged in.
10201400
RF/sup */IPF: a weighting scheme for multimedia information retrieval
The region-based approach has become a popular research trend in the field of multimedia database retrieval. We present the Region Frequency and Inverse Picture Frequency (RF/sup */IPF) weighting, a measure developed to unify region-based multimedia retrieval systems with text-based information retrieval systems. The weighting measure gives the highest weight to regions that occur often in a small number of images in the database. These regions are considered discriminators. With this weighting measure, we can blend image retrieval techniques with TF/sup */IDF-based text retrieval techniques for large-scale Web applications. The RF/sup */IPF weighting has been implemented as a part of our experimental SIMPLIcity image retrieval system and tested on a database of about 200000 general-purpose images. Experiments have shown that this technique is effective in discriminating images of different semantics. Additionally, the overall similarity approach enables a simple querying interface for multimedia information retrieval systems.
1791876
A Region-Based Fuzzy Feature Matching Approach to Content-Based Image Retrieval
This paper proposes a fuzzy logic approach, UFM (unified feature matching), for region-based image retrieval. In our retrieval system, an image is represented by a set of segmented regions, each of which is characterized by a fuzzy feature (fuzzy set) reflecting color, texture, and shape properties. As a result, an image is associated with a family of fuzzy features corresponding to regions. Fuzzy features naturally characterize the gradual transition between regions (blurry boundaries) within an image and incorporate the segmentation-related uncertainties into the retrieval algorithm. The resemblance of two images is then defined as the overall similarity between two families of fuzzy features and quantified by a similarity measure, UFM measure, which integrates properties of all the regions in the images. Compared with similarity measures based on individual regions and on all regions with crisp-valued feature representations, the UFM measure greatly reduces the influence of inaccurate segmentation and provides a very intuitive quantification. The UFM has been implemented as a part of our experimental SIMPLIcity image retrieval system. The performance of the system is illustrated using examples from an image database of about 60,000 general-purpose images.
2269151
Content-based image indexing and searching using Daubechies' wavelets
Abstract. This paper describes WBIIS (Wavelet-Based Image Indexing and Searching), a new image indexing and retrieval algorithm with partial sketch image searching capability for large image databases. The algorithm characterizes the color variations over the spatial extent of the image in a manner that provides semantically meaningful image comparisons. The indexing algorithm applies a Daubechies' wavelet transform for each of the three opponent color components. The wavelet coefficients in the lowest few frequency bands, and their variances, are stored as feature vectors. To speed up retrieval, a two-step procedure is used that first does a crude selection based on the variances, and then refines the search by performing a feature vector match between the selected images and the query. For better accuracy in searching, two-level multiresolution matching may also be used. Masks are used for partial-sketch queries. This technique performs much better in capturing coherence of image, object granularity, local color/texture, and bias avoidance than traditional color layout algorithms. WBIIS is much faster and more accurate than traditional algorithms. When tested on a database of more than 10 000 general-purpose images, the best 100 matches were found in 3.3 seconds.
7128221
TAPHS: thermal-aware unified physical-level and high-level synthesis
Thermal effects are becoming increasingly important during integrated circuit design. Thermal characteristics influence reliability, power consumption, cooling costs, and performance. It is necessary to consider thermal effects during all levels of the design process, from the architectural level to the physical level. However, design-time temperature prediction requires access to block placement, wire models, power profile, and a chip-package thermal model. Thermal-aware design and synthesis necessarily couple architectural-level design decisions (e.g., scheduling) with physical design (e.g., floorplanning) and modeling (e.g., wire and thermal modeling). This article proposes an efficient and accurate thermal-aware floor-planning high-level synthesis system that makes use of integrated high-level and physical-level thermal optimization techniques. Voltage islands are automatically generated via novel slack distribution and voltage partitioning algorithms in order to reduce the design's power consumption and peak temperature. A new thermal-aware floorplanning technique is proposed to balance chip thermal profile, thereby further reducing peak temperature. The proposed system was used to synthesize a number of benchmarks, yielding numerous designs that trade off peak temperature, integrated circuit area, and power consumption. The proposed techniques reduces peak temperature by 12.5degC on average. When used to minimize peak temperature with a fixed area, peak temperature reductions are common. Under a constraint on peak temperature, integrated circuit area is reduced by 9.9% on average
32133517
Information Extraction from the Structured Part of Office Documents
The contents of office documents can be divided into structured and unstructured parts. In this paper, we present a sample-based approach to analyzing a document to form its layout and conceptual structures, and then extracting information from the structured part of the office documents. We represent a document's layout structure as an ordered labeled tree structure using nested segmentation, and its conceptual structure as a set of attribute type pairs. The layout similarities between the document to be processed and samples are identified by employing an approximate tree matching method. The conceptual similarities are identified by analyzing document and sample contents, and by measuring the degree of conceptual closeness. Finally, the information is extracted by instantiating the attributes specified in the conceptual structure based on the result of document structure analysis.
2052176
Structural matching and discovery in document databases
Structural matching and discovery in documents such as SGML and HTML is important for data warehousing [6], version management [7, 11], hypertext authoring, digital libraries [4] and Internet databases. As an example, a user of the World Wide Web may be interested in knowing changes in an HTML document [2, 5, 10]. Such changes can be detected by comparing the old and new version of the document (referred to as structural matching of documents). As another example, in hypertext authoring, a user may wish to find the common portions in the history list of a document or in a database of documents (referred to as structural discovery of documents). In SIGMOD 95 demo sessions, we exhibited a software package, called TreeDiff [13], for comparing two latex documents and showing their differences. Given two documents, the tool represents the documents as ordered labeled trees and finds an optimal sequence of edit operations to transform one document (tree) to the other. An edit operation could be an insert, delete, or change of a node in the trees. The tool is so named because documents are represented and compared using approximate tree matching techniques [9, 12, 14].
15717973
Effective hidden Markov models for detecting splicing junction sites in DNA sequences
Abstract Identification or prediction of coding sequences from within genomic DNA has been a major rate-limiting step in the pursuit of genes. Programs currently available are far from being powerful enough to elucidate the gene structure completely. In this paper, we develop effective hidden Markov models (HMMs) to represent the consensus and degeneracy features of splicing junction sites in eukaryotic genes. Our HMM system based on the developed HMMs is fully trained using an expectation maximization (EM) algorithm and the system performance is evaluated using a 10-way cross-validation method. Experimental results show that the proposed HMM system can correctly detect 92% of the true donor sites and 91.5% of the true acceptor sites in the test data set containing real vertebrate gene sequences. These results suggest that our approach provide a useful tool in discovering the splicing junction sites in eukaryotic genes.
29234559
Quasi-abelian cayley graphs and parsons graphs
LetGbe a finite group, andSa subset ofGwith 1?SandS-1=S.IfSis a union of conjugacy classes ofG,then the Cayley graphX=Cay(G, S)onGwith respect toSis calledquasi-abelian.In this paper we prove that any connected quasi-abelian Cayley graph is hamiltonian (Theorem 2). As a consequence, we prove that Zaks' three conjectures on Parsons graphs are true, with one exception.