ppxscal/embedding_network huggingface dataset:
Interschema correspondence establishment in a cooperative OWL-based multi-information server grid environment
Authors: A. R. Tawil, M. Montebello, R. Bahsoon, W. A. Gray, N. J. Fiddian
Venue: Information Sciences: an International Journal (2008)

Establishing interschema semantic knowledge between corresponding elements in a cooperating OWL-based multi-information server grid environment requires deep knowledge, not only about the structure of the data represented in each server, but also about the commonly occurring differences in the intended semantics of this data. The same information could be represented in various incompatible structures, and more importantly the same structure could be used to represent data with many diverse and incompatible semantics. In a grid environment interschema semantic knowledge can only be detected if both the structural and semantic properties of the schemas of the cooperating servers are made explicit and formally represented in a way that a computer system can process. Unfortunately, very often there is lack of such knowledge and the underlying grid information servers (ISs) schemas, being semantically weak as a consequence of the limited expressiveness of traditional data models, do not help the acquisition of this knowledge. The solution to overcome this limitation is primarily to upgrade the semantic level of the IS local schemas through a semantic enrichment process by augmenting the local schemas of grid ISs to semantically enriched schema models, then to use these models in detecting and representing correspondences between classes belonging to different schemas. In this paper, we investigate the possibility of using OWL-based domain ontologies both for building semantically rich schema models, and for expressing interschema knowledge and reasoning about it. We believe that the use of OWL/RDF in this setting has two important advantages. On the one hand, it enables a semantic approach for interschema knowledge specification, by concentrating on expressing conceptual and semantic correspondences between both the conceptual (intensional) definition and the set of instances (extension) of classes represented in different schemas. On the other hand, it is exactly this semantic nature of our approach that allows us to devise reasoning mechanisms for discovering and reusing interschema knowledge when the need arises to compare and combine it.
Cosegmentation for Image Sequences
Authors: Dong Seon Cheng, Mario A. T. Figueiredo
Venue: Proceedings of the 14th International Conference on Image Analysis and Processing (2007)

We present a generative model to perform cosegmentation on an arbitrary number of images, where cosegmentation has been defined as the task of segmenting simultaneously the common parts between a pair of images. We build upon a previous work that introduced a new approach to model-based clustering under prior knowledge, and exploit its simplicity and flexibility to solve the problem of cosegmentation. We show experiments performed with datasets as diverse as slices of an MRI scan, frames from a video sequence, images in a database of objects, and with a set of 3D range images.
Multicasting with selective delivery: a SafetyNet for vertical handoffs
Authors: Henrik Petander, Eranga Perera, Aruna Seneviratne
Venue: Wireless Personal Communications: An International Journal (2007)

In the future, mobility support will require handling roaming in heterogeneous access networks. In order to enable seamless roaming it is necessary to minimize the impact of the vertical handoffs. Localized mobility management schemes such as Fast Handovers for Mobile IPv6 (FMIPv6) and Hierarchical Mobile IPv6 do not provide sufficient handoff performance, since they have been designed for horizontal handoffs. In this paper, we propose the SafetyNet protocol, which allows a Mobile Node to perform seamless vertical handoffs. Further, we propose the SafetyNet handoff timing algorithm, to enable a Mobile Node to delay or even completely avoid upward vertical handoffs. We implement the SafetyNet protocol and compare its performance with the FMIPv6 protocol in our wireless test bed and analyze the results. The experimental results indicate that the proposed SafetyNet protocol can provide an improvement of up to 95% for TCP performance in vertical handoffs, when compared with FMIPv6 and an improvement of 64% over FMIPv6 with bicasting. We use numerical analysis of the protocol to show that its over the air signaling and data transmission overhead is comparable to FMIPv6 and significantly smaller than that of FMIPv6 with bicasting.
Using Permuted States and Validated Simulation to Analyze Conflict Rates in Optimistic Replication
Authors: An-I Andy Wang, Geoff Kuenning, Peter Reiher
Venue: Simulation (2007)

Optimistic replication provides high data availability in the presence of network outages. Although widely deployed, this relaXed consistency model introduces concurrent updates, whose behavior is poorly understood due to the vast state space. This paper introduces the notion of permuted states to eliminate system states that are redundant and unreachable, which can constitute the majority of states (4069 out of 4096 for four replicas). With the aid of permuted states, we are for the first time able to construct analytical models beyond the two-replica case. By eXamining the analysis for 2 to 4 replicas, we can demystify the process of forming identical conflicts&#x2014;the most common conflict type at high replication factors. Additionally, we have automated and optimized the generation of permuted states, which allows us to eXplore higher replication factors (up to 10 replicas) using hybrid techniques. It also allows us to validate our results with eXisting simulations based on actual replication mechanisms, which previously were analytically validated with only one pair of replicas. Finally, we have discovered that update locality and bimodal access patterns are the primary factors contributing to the formation of identical conflicts.
Grid With a View: Optimal Texturing for Perception of Layered Surface Shape
Authors: Alethea Bair Donald House
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

We present the results of two controlled studies comparing layered surface visualizations under various texture conditions. The task was to estimate surface normals, measured by accuracy of a hand-set surface normal probe. A single surface visualization was compared with the two-surfaces case under conditions of no texture and with projected grid textures. Variations in relative texture spacing on top and bottom surfaces were compared, as well as opacity of the top surface. Significant improvements are found for the textured cases over non-textured surfaces. Either larger or thinner top-surface textures, and lower top surface opacities are shown to give less bottom surface error. Top surface error appears to be highly resilient to changes in texture. Given the results we also present an example of how appropriate textures might be useful in volume visualization.
A Hybrid Image Segmentation Approach Using Watershed Transform and FCM
Authors: Yifei Zhang, Shuang Wu, Ge Yu, Daling Wang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

Medical image segmentation is an essential step for most subsequent image analysis tasks. In this paper a hybrid image segmentation algorithm is proposed, which combines the morphological method of watershed and fuzzy c-means (FCM) clustering. A dilation-erosion contrast enhancement approach is used as a preprocessing stage in order to obtain an accurate estimation of the image borders. Then an initial partitioning of the image into primitive regions is produced by applying the maker-controlled watershed transform. After edge post-processing, the regions' statistical characters are inputted to a FCM clustering process for the final segmentation. Merging the watershed regions through the FCM clustering obtains a better initial setting from the preceding steps, accelerates convergence speed, and improves the accuracy of segmentation. The hybrid algorithm is applied to lung extraction in Computerized Tomography (CT) images. The experiments show that the algorithm is more effective for medical image segmentation than FCM and watershed algorithm.
Service configuration and user profiling in 4G terminals
Authors: Artemis A. Koutsorodi, Evgenia F. Adamopoulou, Konstantinos P. Demestichas, Michael E. Theologou
Venue: Wireless Personal Communications: An International Journal (2007)

This paper presents a middleware platform for managing devices that operate in heterogeneous environments. The proposed management framework supports terminal-controlled, preference-based access network selection. Two separate problems are identified in this domain: one involving the computation of optimal allocations of services to access networks and quality levels (service configuration), and one concerning the dynamic inference of the user's preferences, according to the usage context (user profiling). This paper includes an approach to the definition, mathematical formulation and solution of both these problems. Indicative results of the proposed solution methods are presented in the context of a real-life scenario simulating a day in the life of an ordinary user.
Internet Applications Usage Accounting Based on Flow
Authors: Zhenqi Wang, Jin Liu
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

Due to the highly dynamic nature of the development and the use of the Internet applications, traditional traffic identification methods based on wellknown port numbers are not appropriate for the identification of new type of Internet application. This paper proposes methodologies for application traffic analysis, such as signature inspection, dynamic port identification. We have incorporated our methodologies into a system, to analyze Internet traffic between our university network and the Internet, and characterize all in/out Internet traffic.
Performance analysis of adaptive multipath load balancing in WDM-LOBS networks
Authors: Miguel A. González-Ortega, José C. López-Ardao, Raúl F. Rodríguez-Rubio, Cándido López-García, Manuel Fernández-Veiga, Andrés Suárez-González
Venue: Computer Communications (2007)

The rapid advances in optical transmission technology have led to a wide deployment of WDM-based networks, and OBS is considered as a promising switching technology in the optical domain. A major problem in OBS is undoubtedly burst contention. Different mechanisms to reduce burst loss probability have been proposed, but multipath routing has many advantages and it is a relatively little explored alternative in the scope of OBS networks. Two interesting adaptive multipath mechanisms for OBS (AARA and GPMR) have been proposed in the literature, but both of them assume that all the interfaces have total wavelength conversion capacity. However, it is expected this feature to be gradually introduced, giving rise to heterogeneous scenarios where different types of interfaces coexist. Although AARA is applicable to heterogeneous scenarios, GPMR must be slightly modified. We propose this modification and an interesting practical implementation for GPMR. Finally, it is shown that both solutions work satisfactorily well for homogeneous scenarios, but the modified GPMR works clearly better than AARA for heterogeneous scenarios. On the other hand, by means of a general traffic model at the burst level, and through exhaustive simulation experiments, we study the effect of the correlation structure and of the marginal distribution of the traffic arrival pattern on the burst losses.
Business and IT Alignment with SEAM for Enterprise Architecture
Authors: Alain Wegmann, Gil Regev, Irina Rychkova, Lam-Son Le, Philippe Julia
Venue: Proceedings of the 11th IEEE International Enterprise Distributed Object Computing Conference (2007)

To align an IT system with an organization's needs, it is necessary to understand the organization's position within its environment as well as its internal configuration. In SEAM for Enterprise Architecture the organization is considered as a hierarchy of systems that span from business down to IT. The alignment process addresses the complete hierarchy. We illustrate the use of SEAM for Enterprise Architecture with an example in which a new hiring process and an IT system are developed. With this approach it is possible to train new engineers in the design of business and IT alignment. It is also possible to scope projects in a way that integrate both business and IT strategies. This enables the consideration of IT developments in an enterprise-wide context.
A linear fit gets the correct monotonicity directions
Authors: Malik Magdon-Ismail, Joseph Sill
Venue: Machine Learning (2008)

Let f be a function on ¿ d that is monotonic in every variable. There are 2 d possible assignments to the directions of monotonicity (two per variable). We provide sufficient conditions under which the optimal linear model obtained from a least squares regression on f will identify the monotonicity directions correctly. We show that when the input dimensions are independent, the linear fit correctly identifies the monotonicity directions. We provide an example to illustrate that in the general case, when the input dimensions are not independent, the linear fit may not identify the directions correctly. However, when the inputs are jointly Gaussian, as is often assumed in practice, the linear fit will correctly identify the monotonicity directions, even if the input dimensions are dependent. Gaussian densities are a special case of a more general class of densities (Mahalanobis densities) for which the result holds. Our results hold when f is a classification or regression function. If a finite data set is sampled from the function, we show that if the exact linear regression would have yielded the correct monotonicity directions, then the sample regression will also do so asymptotically (in a probabilistic sense). This result holds even if the data are noisy.
Advances of Research in Fuzzy Integral for Classifiers' fusion
Authors: Zhizhou Kong, Zixing Cai
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

Fuzzy Integral is compared with other two methods which are hot in studying of classifiers' fusion. The standard model of Fuzzy Integral and its general solution are introduced. Then, the state of the art and the challenge problems in Fuzzy Integral research field are discussed. The algorithms for standard and extended Fuzzy Integral models are briefly analyzed. Finally, the open areas of theoretic and applied research in Fuzzy Integral are brought forward.
A novel technique for incremental analysis of on-chip power distribution networks
Authors: Yuhong Fu, Rajendran Panda, Ben Reschke, Savithri Sundareswaran, Min Zhao
Venue: Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design (2007)

We propose a novel and efficient incremental analysis technique for 'what-if analysis of on-chip power distribution networks (PDN). Effect of local modifications to a PDN, including local topology changes, can be quickly analyzed without need for very expensive re-analysis of the entire modified network. We borrow ideas from a fictitious domain method that has been successfully used in solving partial differential equations arising from inhomogeneous problems in mechanics. The effect of local wiring modifications in several PDN regions is mimicked by applying fictitious currents at the boundaries of these regions in the original unmodified network. The fictitious currents are calculated from component sub-problems in a low-computation iterative procedure. The practicality of this method for use in what-if analysis is demonstrated with several large power networks from actual industrial designs. It analyzes a modified network with few million changes in a fraction of time it would take for a complete re-analysis.
GM(1,1) Model - Ameliorated Based on Genetic Algorithm and Its Application
Authors: Junfeng Li, Wenzhan Dai, Haipeng Pan
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

In this paper, first, the method of enhancing smooth degree of original data sequence by function transformation is studied and some transformation functions are presented. Second, original data sequence is transformed by means of function transformation. Third, The mechanism of GM(1,1)- ameliorated model based on adaptive genetic algorithm (AGA) is proposed and the steps of modeling is explained in detail . At last, the method is applied in building the model of Chinese country per-capita housing areas. The results of example show the effectiveness of the proposed approach.
Critical Load Factors in Two-Processor Distributed Systems
Authors: H. S. Stone
Venue: IEEE Transactions on Software Engineering (1978)

In a two-processor distributed computer network, prior research showed that a maximum flow algorithm can be used to find optimal program-module-to-processor assignments to maximize the performance of distributed programs. This paper examines the sequence of optimal assignments found as the load on one processor is held fixed and the load on the other is varied. For every program module M there exists a critical load factor fM such that when the load on the processor with variable load is below fM, M is assigned to that processor by an optimal assignment, and is otherwise assigned to the other processor. This characteristic opens the possibility of doing optimal dynamic assignments in real-time.
Researching your institution's computer past
Authors: Russell McMahon
Venue: Proceedings of the 8th ACM SIGITE conference on Information technology education (2007)

The history of computing in educational institutions is relatively young, but quickly forgotten as computing students today have no concept of what it was like to use a computer back in the 1950-1990 time period. However, preserving one's own institution's computer past should be more than just a history lesson. It can be a way to connect present day students with their institution's own achievements and it can be a mechanism for recruiting young people into your institution. In any case telling the story of the people whose achievements may only be known by a few or even forgotten is something that needs to be preserved. This project spans both academic and administrative computing as well as the people involved including alumni, faculty, and staff. It is both an oral history and a documented history as it covers university events and the university's own internal use of computing. Presented in this paper are the methods of research used as well as ideas on how one might go about such a task at their institution. The final goals of this research are to produce a book with a companion website and host a computing history symposium. specific permission and/or a fee.
Efficient sampling in approximate dynamic programming algorithms
Authors: Cristiano Cervellera, Marco Muselli
Venue: Computational Optimization and Applications (2007)

Dynamic Programming (DP) is known to be a standard optimization tool for solving Stochastic Optimal Control (SOC) problems, either over a finite or an infinite horizon of stages. Under very general assumptions, commonly employed numerical algorithms are based on approximations of the cost-to-go functions, by means of suitable parametric models built from a set of sampling points in the d-dimensional state space. Here the problem of sample complexity, i.e., how "fast" the number of points must grow with the input dimension in order to have an accurate estimate of the cost-to-go functions in typical DP approaches such as value iteration and policy iteration, is discussed. It is shown that a choice of the sampling based on low-discrepancy sequences, commonly used for efficient numerical integration, permits to achieve, under suitable hypotheses, an almost linear sample complexity, thus contributing to mitigate the curse of dimensionality of the approximate DP procedure.
Model Checking of Consensus Algorit
Authors: Tatsuhiro Tsuchiya, Andre Schiper
Venue: Proceedings of the 26th IEEE International Symposium on Reliable Distributed Systems (2007)

We show for the first time that standard model checking allows one to completely verify asynchronous algorithms for solving consensus, a fundamental problem in fault-tolerant distributed computing. Model checking is a powerful verification methodology based on state exploration. However it has rarely been applied to consensus algorithms, because these algorithms induce huge, often infinite state spaces. Here we focus on consensus algorithms based on the Heard-Of model, a new computation model for distributed computing. By making use of the high abstraction level provided by this computation model and by devising a finite representation of unbounded timestamps, we develop a methodology for verifying consensus algorithms in every possible state by model checking.
Computing Length-Preserved Free Boundary for Quasi-Developable Mesh Segmentation
Authors: Charlie Wang
Venue: IEEE Transactions on Visualization and Computer Graphics (2008)

Stretch-free surface flattening has been requested by a variety of applications. At present, the most difficult problem is how to segment a given model into nearly developable atlases so that a nearly stretch-free flattening can be computed. The criterion for segmentation is needed to evaluate the possibility of flattening a given surface patch, which should be fast computed. In this paper, we present a method to compute the length-preserved free boundary (LPFB) of a mesh patch which speeds up the mesh parameterization. The distortion on parameterization can then be employed as the criterion in a trial-and-error algorithm for segmenting a given model into nearly developable atlases. The computation of LPFB is formulated as a numerical optimization problem in the angle space, where we are trying to optimize the angle excesses on the boundary while preserving the constraints derived from the closed-path theorem and the length preservation.
Orthogonal Neighborhood Preserving Projections: A Projection-Based Dimensionality Reduction Technique
Authors: Effrosyni Kokiopoulou, Yousef Saad
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

This paper considers the problem of dimensionality reduction by orthogonal projection techniques. The main feature of the proposed techniques is that they attempt to preserve both the intrinsic neighborhood geometry of the data samples and the global geometry. In particular we propose a method, named Orthogonal Neighborhood Preserving Projections, which works by first building an “affinity” graph for the data, in a way that is similar to the method of Locally Linear Embedding (LLE). However, in contrast with the standard LLE where the mapping between the input and the reduced spaces is implicit, ONPP employs an explicit linear mapping between the two. As a result, handling new data samples becomes straightforward, as this amounts to a simple linear transformation.We show how to define kernel variants of ONPP, as well as how to apply the method in a supervised setting. Numerical experiments are reported to illustrate the performance of ONPP and to compare it with a few competing methods.