ppxscal/embedding_network huggingface dataset:
Managing highly correlated semi-structured data: architectural aspects of a digital archive
Authors: Alf-Christian Schering, Holger Meyer, Andreas Heuer
Venue: Proceedings of the ACM first Ph.D. workshop in CIKM (2007)

XML techniques are well suited to describe, manage, store, and exchange hierarchical, semi-structured data. Information represented beyond hierarchical structures can still be described and exchanged in XML format employing additional concepts such as ID/IDREF or XLink. However, retrieval, manipulation, and storage mechanisms are far away from being the ideal solution for such data. Query languages do not perform efficiently in these cases. Especially in scenarios, such as the Digital Wossidlo Archive (WossiDiA), a project dealing with a huge number of arbitrarily correlated data units, XML query evaluation and retrieval techniques face problems, such as intricate querying and bad efficiency. At this point a solution to manage these data efficiently needs to be devised. This paper introduces a first approach which attempts to find such a solution for the WossiDiA information system.
MPEG-7 tools for universal multimedia access
Authors: José M. Martínez
Venue: Journal of the American Society for Information Science and Technology (2007)

Universal Multimedia Access (UMA) deals with seamless access to once-only-created content via any kind of terminal and any kind of network connectivity, which implies that the content should be adapted in order to fit a variety of terminal and network characteristics, as well as user preferences. The MPEG-7 standard offers some support for UMA within its section on Multimedia Description Schemes (MDS). Within the standard, several groups of tools serve this purpose. For instance, the Navigation and Access Tools provide some Description Schemes that allow the description of adapted content variations and summaries and allow for preprocessed content versions. Some support is also found in the Content Metadata Tools (Media and Usage Tools), for real-time ease in creation of online content versions and in limited support for session description, which is completed in MPEG-21.
Visualization of Pareto-Sets in Evolutionary Multi-Objective Optimization
Authors: Mario Koppen, Kaori Yoshida
Venue: Proceedings of the 7th International Conference on Hybrid Intelligent Systems (2007)

In this paper, a method for the visualization of the population of an evolutionary multi-objective optimization (EMO) algorithm is presented. The main characteristic of this approach is the preservation of Paretodominance relations among the individuals as good as possible. It will be shown that in general, a Paretodominance preserving mapping from higher- to lowerdimensional spaces does not exist. Thus, the demand is to find a mapping with as few wrongly indicated dominance relations as possible, which gives one more objective in addition to other mapping objectives like preserving nearest neighbor relations. Therefore, such a mapping poses a multi-objective optimization problem by itself, which is also handled by an EMO algorithm (NSGA-II in this case). The resulting mappings are shown for the run of a NSGA-II version on the 15 objective DTLZ2 problem as an example. From such plots, some insights into evolutionary dynamics can be obtained.
Nested Transactions in Distributed Systems
Authors: D. R. Ries
Venue: IEEE Transactions on Software Engineering (1982)

In database management systems and operating systems, transactions are used as units of consistency, serializability, recovery, and for deadlock control. Normally, the transactions for each of these systems are considered independently. In this paper we describe nested transactions where the transactions from one system interact with the transactions from another system. Such nested transactions can expect to become more important with the introduction of network operating systems and heterogeneous distributed database systems.
An experimental study of the impact of information extraction accuracy on semantic search performance
Authors: Jennifer Chu-Carroll, John Prager
Venue: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (2007)

Researchers have shown that various natural language processing techniques can be used in document analysis to impact search performance. For the most part, they examined how an analysis system with certain performance characteristics can be leveraged to improve document and/or passage search results. We have previously shown that semantic queries which utilize named entity and relation information extracted from the corpus can lead to significant improvement in search performance. In this paper, we extend our previous efforts and examine how search performance degrades in the face of imperfect named entity and relation extraction. Our study was carried out by developing gold standard annotated corpora and applying different error models to the gold standard annotations to simulate errors made by automatic recognizers. We identify automatic recognizer characteristics that make them more amenable to our search tasks, show that recognizer recall has more significant impact on semantic search performance than its precision, and demonstrate that significant improvement in both MAP and Exact Precision scores can be achieved by adopting automatic named entity and relation recognizers with near state-of-the-art performance.
Queueing Analysis of Global Locking Synchronization Schemes for Multicopy Databases
Authors: Chin-Hwa Lee
Venue: IEEE Transactions on Computers (1980)

Locking is a simple scheme to synchronize multiple updates in a multicopy distributed database system. Various schemes were proposed before to maintain the consistency of the distributed database. But these schemes were compared to each other mostly on heuristic base. In this paper, three analytic queueing models for the Network Semaphore scheme, Hopping Permit scheme, and Adaptive Hopping Permit scheme are developed. Incorporating special waiting stages allows the latter two control schemes to he modeled as M/G/1 queueing systems. Shown in this paper are various performance measures of the models, which can provide much insight into these schemes. The validity of these models is verified by the simulation results.
Parametric and nonparametric Bayesian model specification: A case study involving models for count data
Authors: Milovan Krnjajić, Athanasios Kottas, David Draper
Venue: Computational Statistics Data Analysis (2008)

In this paper we present the results of a simulation study to explore the ability of Bayesian parametric and nonparametric models to provide an adequate fit to count data of the type that would routinely be analyzed parametrically either through fixed-effects or random-effects Poisson models. The context of the study is a randomized controlled trial with two groups (treatment and control). Our nonparametric approach uses several modeling formulations based on Dirichlet process priors. We find that the nonparametric models are able to flexibly adapt to the data, to offer rich posterior inference, and to provide, in a variety of settings, more accurate predictive inference than parametric models.
Data-Dependent Kernel Machines for Microarray Data Classification
Authors: Huilin Xiong, Ya Zhang, Xue-Wen Chen
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2007)

One important application of gene expression analysis is to classify tissue samples according to their gene expression levels. Gene expression data are typically characterized by high dimensionality and small sample size, which makes the classification task quite challenging. In this paper, we present a data-dependent kernel for microarray data classification. This kernel function is engineered so that the class separability of the training data is maximized. A bootstrapping-based resampling scheme is introduced to reduce the possible training bias. The effectiveness of this adaptive kernel for microarray data classification is illustrated with a k-Nearest Neighbor (KNN) classifier. Our experimental study shows that the data-dependent kernel leads to a significant improvement in the accuracy of KNN classifiers. Furthermore, this kernel-based KNN scheme has been demonstrated to be competitive to, if not better than, more sophisticated classifiers such as Support Vector Machines (SVMs) and the Uncorrelated Linear Discriminant Analysis (ULDA) for classifying gene expression data.
Risk of malignant brain tumors and cell phone use
Authors: James C. Lin
Venue: ACM SIGMOBILE Mobile Computing and Communications Review (2007)

It has been estimated that there are about 2 billion users of cellular mobile telephones worldwide. The popularity of cellular telephones is beyond any debate. It's a good guess that most, if not all users, would prefer no links between cellular telephone and health effect, let alone cell-phone use and cancer.
ECO-system: Embracing the Change in Placement
Authors: Jarrod A. Roy, Igor L. Markov
Venue: Proceedings of the 2007 Asia and South Pacific Design Automation Conference (2007)

In a realistic design flow, circuit and system optimizations must interact with physical aspects of the design. For example, improvements in timing and power may require replacing large modules with variants that have different power/delay trade-off, shape and connectivity. New logic may be added late in the design flow, subject to interconnect optimization. To support such flexibility in design flows we develop a robust system for performing Engineering Change Orders (ECOs). In contrast with existing stand-alone tools that offer poor interfaces to the design flow and cannot handle a full range of modern VLSI layouts, our ECO-system reliably handles fixed objects and movable macros in instances with widely varying amounts of whitespace. It detects geometric regions and sections of the netlist that require modification and applies an adequate amount of change in each case. Given a reasonable initial placement, it applies minimal changes, but is capable of re-placing large regions to handle pathological cases. ECO-system can be used in the range from high-level synthesis, to physical synthesis and detail placement.
A New Algorithm for Generating Prime Implicants
Authors: J. R. Slagle, Chin-Liang Chang, R. C. T. Lee
Venue: IEEE Transactions on Computers (1970)

This paper describes an algorithm which will generate all the prime implicants of a Boolean function. The algorithm is different from those previously given in the literature, and in many cases it is more efficient. It is proved that the algorithm will find all the prime implicants. The algorithm may possibly generate some nonprime implicants. However, using frequency orderings on literals, the experiments with the algorithm show that it usually generates very few ( possibly none) nonprime implicants. Furthermore, the algorithm may be used to find the minimal sums of a Boolean function. The algorithm is implemented by a computer program in the LISP language.
Using the influence model to recognize functional roles in meetings
Authors: Wen Dong, Bruno Lepri, Alessandro Cappelletti, Alex Sandy Pentland, Fabio Pianesi, Massimo Zancanaro
Venue: Proceedings of the 9th international conference on Multimodal interfaces (2007)

In this paper, an influence model is used to recognize functional roles played during meetings. Previous works on the same corpus demonstrated a high recognition accuracy using SVMs with RBF kernels. In this paper, we discuss the problems of that approach, mainly over-fitting, the curse of dimensionality and the inability to generalize to different group configurations. We present results obtained with an influence modeling method that avoid these problems and ensures both greater robustness and generalization capability.
Bootstrap variants of the Akaike information criterion for mixed model selection
Authors: Junfeng Shang, Joseph E. Cavanaugh
Venue: Computational Statistics Data Analysis (2008)

Two bootstrap-corrected variants of the Akaike information criterion are proposed for the purpose of small-sample mixed model selection. These two variants are asymptotically equivalent, and provide asymptotically unbiased estimators of the expected Kullback-Leibler discrepancy between the true model and a fitted candidate model. The performance of the criteria is investigated in a simulation study where the random effects and the errors for the true model are generated from a Gaussian distribution. The parametric bootstrap is employed. The simulation results suggest that both criteria provide effective tools for choosing a mixed model with an appropriate mean and covariance structure. A theoretical asymptotic justification for the variants is presented in the Appendix.
Active-Matrix Liquid Crystal Displays Using Amorphous Silicon Thin-Film Transistors
Authors: R. Flasck, S. Holmberg
Venue: IEEE Computer Graphics and Applications (1984)

The major challenge facing the portable computer industry is the development of cost-effective, low-power, full-screen, flat panel displays. Here is a technology that can help.
Archer: a history-driven global routing algorithm
Authors: Muhammet Mustafa Ozdal, Martin D. F. Wong
Venue: Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design (2007)

Global routing is an important step in the physical design process. In this paper, we propose a new global routing algorithm Archer, which resolves some of the most common problems with the state-of-the-art global routers. It is known that concurrent global routing algorithms are typically too expensive to be applied on today's large designs, which may contain up to a million nets. On the other hand, iterative rip-up and reroute (RNR) based algorithms are susceptible to getting stuck in local optimal solutions. In this paper, we propose an RNR-based global routing algorithm that guides the routing iterations out of local optima through effective usage of congestion histories. We also focus on the problem of how to enable a smooth trade-off between seemingly conflicting objectives of overflow and wirelength minimization. Furthermore, we propose a Lagrangian relaxation based bounded-length min-cost topology improvement algorithm that enables Steiner trees to change dynamically for the purpose of congestion optimization. Our experiments show that Archer obtains congestion-free solutions for all circuits in the standard ISPD98 benchmarks, which is the best result published so far. Furthermore, it produces better results than the best results reported in the ISPD-07 Global Routing Contest in terms of routability. Compared to FastRoute [18, 19], which is the state-of-the-art RNR-based global routing algorithm, Archer improves routability by 30%, and reduces the wirelengths by 32% on the average on ISPD07 benchmarks.
A novel approach to revealing positive and negative co-regulated genes
Authors: Yu-Hai Zhao, Guo-Ren Wang, Ying Yin, Guang-Yu Xu
Venue: Journal of Computer Science and Technology (2007)

As explored by biologists, there is a real and emerging need to identify co-regulated gene clusters, which include both positive and negative regulated gene clusters. However, the existing pattern-based and tendency-based clustering approaches are only designed for finding positive regulated gene clusters. In this paper, a new subspace clustering model called g-Cluster is proposed for gene expression data. The proposed model has the following advantages: 1) find both positive and negative co-regulated genes in a shot, 2) get away from the restriction of magnitude transformation relationship among co-regulated genes, and 3) guarantee quality of clusters and significance of regulations using a novel similarity measurement gCode and a user-specified regulation threshold δ, respectively. No previous work measures up to the task which has been set. Moreover, MDL technique is introduced to avoid insignificant g-Clusters generated. A tree structure, namely GS-tree, is also designed, and two algorithms combined with efficient pruning and optimization strategies to identify all qualified g-Clusters. Extensive experiments are conducted on real and synthetic datasets. The experimental results show that 1) the algorithm is able to find an amount of co-regulated gene clusters missed by previous models, which are potentially of high biological significance, and 2) the algorithms are effective and efficient, and outperform the existing approaches.
The Binary Tree as an Interconnection Network: Applications to Multiprocessor Systems and VLSI
Authors: E. Horowitz
Venue: IEEE Transactions on Computers (1981)

The binary tree is a natural way to organize complex computations by a computer. For problems that can be naturally divided into a tree structure, a great deal of parallelism may be employed. In this paper we examine several aspects of the binary tree structure as it relates to both multiprocessor systems and to VISI circuit design. First, we present an algorithm for mapping an arbitrary binary tree onto the plane. An analysis shows the density of this mapping. Second, we consider the problem of routing messages within a binary tree under the assumption that certain nodes may be faulty. Finally, we analyze the binary tree's capacity to transfer information between nodes and we compare it to the capacity of the linear array and the grid.
The effect of &ldquo;open access&rdquo; on citation impact: An analysis of ArXiv's condensed matter section
Authors: Henk F. Moed
Venue: Journal of the American Society for Information Science and Technology (2007)

This article statistically analyzes how the citation impact of articles deposited in the Condensed Matter section of the preprint server ArXiv (hosted by Cornell University), and subsequently published in a scientific journal, compares to that of articles in the same journal that were not deposited in the archive. Its principal aim is to further illustrate and roughly estimate the effect of two factors, &ldquo;early view&rdquo; and &ldquo;quality bias,&rdquo; on differences in citation impact between these two sets of papers, using citation data from Thomson Scientific's Web of Science. It presents estimates for a number of journals in the field of condensed matter physics. To discriminate between an &ldquo;open access&rdquo; effect and an early view effect, longitudinal citation data were analyzed covering a time period as long as 7 years. Quality bias was measured by calculating ArXiv citation impact differentials at the level of individual authors publishing in a journal, taking into account coauthorship. The analysis provided evidence of a strong quality bias and early view effect. Correcting for these effects, there is in a sample of six condensed matter physics journals studied in detail no sign of a general &ldquo;open access advantage&rdquo; of papers deposited in ArXiv. The study does provide evidence that ArXiv accelerates citation due to the fact that ArXiv makes papers available earlier rather than makes them freely available. &copy; 2007 Wiley Periodicals, Inc.
Empirical likelihood inference for censored median regression model via nonparametric kernel estimation
Authors: Yichuan Zhao, Feiming Chen
Venue: Journal of Multivariate Analysis (2008)

An alternative to the accelerated failure time model is to regress the median of the failure time on the covariates. In the recent years, censored median regression models have been shown to be useful for analyzing a variety of censored survival data with the robustness property. Based on missing information principle, a semiparametric inference procedure for regression parameter has been developed when censoring variable depends on continuous covariate. In order to improve the low coverage accuracy of such procedure, we apply an empirical likelihood ratio method (EL) to the model and derive the limiting distributions of the estimated and adjusted empirical likelihood ratios for the vector of regression parameter. Two kinds of EL confidence regions for the unknown vector of regression parameters are obtained accordingly. We conduct an extensive simulation study to compare the performance of the proposed methods with that normal approximation based method. The simulation results suggest that the EL methods outperform the normal approximation based method in terms of coverage probability. Finally, we make some discussions about our methods.
Component Based Legacy Program Executing over Grid
Authors: Le Du, Yongwei Wu, Chunlu Wang
Venue: Proceedings of the Sixth International Conference on Grid and Cooperative Computing (2007)

Executing the legacy program over grid is very important and necessary. To reuse the legacy program, we developed a method based on Component for executing the legacy code. We can deploy the legacy program as a Component without re-engineering the code, or even requiring access to the source files. This approach is based on the Grid Component Model (GCM). In this paper, we describe the GCM and the model of the legacy program Component including the Legacy Program Interface Description, the File Transfer Mechanism, the Adopter and the Execution Management. Then it introduces the implement of this model and presents the performance evaluation through the example of Bioinformatics. The experiments demonstrate that it has the better performance and provides the characters of reliability, interoperability and flexibility.
Topology Discovery in Dynamic and Decentralized Networks with Mobile Agents and Swarm Intelligence
Authors: Bogdan T. Nassu, Takashi Nanya, Elias P. Duarte
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

Topology discovery is a key task for several compu- ter network applications such as diagnosis, routing and network management. Traditional approaches for topology discovery cannot always be used in dynamic and decentra- lized networks, such as unstructured peer-to-peer networks and wireless ad hoc networks. This paper introduces a stra- tegy based on mobile agents and swarm intelligence for to- pology discovery in such environments. The proposed stra- tegy is inspired by ant colonies, employing simple agents that disseminate information about the topology and com- municate through stigmergy. Experimental results show that the nodes obtain descriptions which are very close to the real network topology. It is also shown that the stigmergy-based method for the selection of agent destina- tions produces better results than a random selection, and that the number of agents can be dynamically adjusted as the size of the network changes.
Surface Simplification Using multi-edge mesh collapse
Authors: Hua-hong Chen, Xiao-nan Luo, Ruo-tian Ling
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

In computer graphics, object are often represented by triangle meshes. Iterative collapse of geometric elements is an important way to simplify the meshes. This paper presents a method for dividing the triangle mesh into certain kind of multi-edge mesh and puts forward a new mesh simplification algorithm based on the multi-edge mesh collapse. The algorithm utilizes iterative collapse of multi-edge mesh to simplify meshes and the surface error approximations are maintained using quadric error metrics. A multi-edge mesh containing n exterior edges, and during every simplification, 2(n-1) faces are collapsed. so much less collapses are need when n becomes bigger. In many cases, the time of the simplification process can be reduced.