ppxscal/embedding_network huggingface dataset:
COPACC: An Architecture of Cooperative Proxy-Client Caching System for On-Demand Media Streaming
Authors: Alan T. S. Ip, Jiangchuan Liu, John Chi-Shing Lui
Venue: IEEE Transactions on Parallel and Distributed Systems (2007)

Proxy caching is a key technique to reduce transmission cost for on-demand multimedia streaming. The effectiveness of current caching schemes, however, is limited by the insufficient storage space and weak cooperations among proxies and their clients, particularly considering the high bandwidth demands from media objects. In this paper, we propose COPACC, a cooperative proxy-and-client caching system that addresses the above deficiencies. This innovative approach combines the advantages of both proxy caching and peer-to-peer client communications. It leverages the client-side caching to amplify the aggregated cache space and rely on dedicated proxies to effectively coordinate the communications. We propose a comprehensive suite of distributed protocols to facilitate the interactions among different network entities in COPACC. It also realizes a smart and cost-effective cache indexing, searching, and verifying scheme. Furthermore, we develop an efficient cache allocation algorithm for distributing video segments among the proxies and clients. The algorithm not only minimizes the aggregated transmission cost of the whole system, but also accommodates heterogeneous computation and storage constraints of proxies and clients. We have extensively evaluated the performance of COPACC under various network and end-system configurations. The results demonstrate that it achieves remarkably lower transmission cost as compared to pure proxy-based caching with limited storage space. On the other hand, it is much more robust than a pure peer-to-peer communication system in the presence of node failures. Meanwhile, its computation and control overheads are both kept in low levels.
On the efficiency of adaptive MCMC algorithms
Authors: Christophe Andrieu, Y. F. Atchadé
Venue: Proceedings of the 1st international conference on Performance evaluation methodolgies and tools (2006)

We study a class of adaptive Markov Chain Monte Carlo (MCMC) processes which aim at behaving as an "optimal" target process via a learning procedure. We show, under appropriate conditions, that the adaptive process and "optimal" (nonadaptive) MCMC algorithm share identical asymptotic properties. The special case of adaptive MCMC algorithms governed by stochastic approximation is considered in details and we apply our results to the adaptive Metropolis algorithm of [1]. We also propose a new class of adaptive MCMC algorithms, called quasi-perfect adaptive MCMC which possesses appealing theoretical and practical properties, as demonstrated through numerical simulations.
Similarity search in high-dimensional datasets
Authors: Raghu Ramakrishnan, Jonathan Goldstein, Uri Shaft
Venue: Proceedings of the 2nd international workshop on Computer vision meets databases (2005)

The problem of finding "similar" multimedia objects is a central one, and a popular approach is to represent objects as vectors in a high-dimensional space, and to build a spatial index over a collection of such vectors in order to retrieve the "nearest neighbors" of a query object. There are some fundamental assumptions involved here. First, that the user's notion of similarity can be captured by distance in the space that the vectors are embedded, and second, that nearest neighbors can be efficiently retrieved. In this talk, we discuss these assumptions, based on our experience with the PiQ image database project, carried out at the University of Wisconsin-Madison, and some subsequent work.We will first present a brief overview of the PiQ system and its goal of identifying the DBMS infrastructure required to support image databases, and discuss the role of similarity and nearest-neighbor queries in content-based querying. Next, we consider when the notion of "nearest neighbor" is well-defined in high-dimensional spaces, and when efficient indexing is feasible. The goal is not to suggest that indexing high-dimensional data is impossible, although our results here are mainly negative. Rather, we seek to identify the conditions under which effective indexing and retrieval techniques are feasible, and to identify the key difficulties that must be overcome. Finally, we present some indexing techniques to retrieve nearest neighbors under appropriate conditions, highlighting the role played by redundancy and approximation.
Tight bounds for shared memory systems accessed by Byzantine processes
Authors: Noga Alon, Michael Merritt, Omer Reingold, Gadi Taubenfeld, Rebecca N. Wright
Venue: Distributed Computing (2005)

We provide efficient constructions and tight bounds for shared memory systems accessed by n processes, up to t of which may exhibit Byzantine failures, in a model previously explored by Malkhi et al. [21]. We show that sticky bits are universal in the Byzantine failure model for n ≥ 3t + 1, an improvement over the previous result requiring n ≥ (2t + 1) (t + 1). Our result follows from a new strong consensus construction that uses sticky bits and tolerates t Byzantine failures among n processes for any n ≥ 3t + 1, the best possible bound on n for strong consensus. We also present tight bounds on the efficiency of implementations of strong consensus objects from sticky bits and similar primitive objects.
Arithmetic integration of decision procedures
Authors: Zohar Manna
Venue:  (2006)

Decision procedures are algorithms that can determine validity or satisfiability of first-order formulas in a given decidable theory. They can efficiently discharge a large number of formulas in specific theories without any user guidance. Therefore they are at the heart of virtually every verification system, reasoning about the system behaviors, proving their safety or finding situations that could lead to bugs. This thesis offers novel solutions to an important class of decision problems, the mixed constraints on data structures and their quantitative properties. It includes three major contributions. (1) Decision Procedures for Term Algebras with Integer Arithmetic. Term Algebras can model a variety of tree-like data types such as records, lists, stacks, etc., which are essential constructs in programming languages. We developed the basic reduction technique, namely, extraction of accurate integer constraints from data constraints. From the construction of accurate integer constraints that precisely characterize data constraints, we can derive decision procedures for combined constraints by utilizing decision procedures for data structures and decision procedures for integer arithmetic. (2) Decision Procedures for Queues with Integer Arithmetic. Queue is a typical data type of linear structure and is widely used in programming languages and forms the basis for many concurrent algorithms and communication protocols. As a queue can grow at both ends, it does not fall in the category of recursive data structures, which can be modeled as term algebras. For this reason, we have further improved the reduction technique and developed new normalization procedures to handle the distinguished properties of queues. (3) Decision Procedures for Knuth-Bendix Order. Using quantifier elimination and the reduction technique developed for solving the combined constraints of term algebras and integer arithmetic, we proved the decidability of the first-order theory of Knuth-Bendix Order, thereby solving a long-standing open problem in term rewriting (officially listed as RTA open problem 99 since 2000). Knuth-Bendix order is widely used in term rewriting and theorem proving, along with lexicographic path order. Unfortunately, the first-order theory of lexicographic path order is undecidable. Therefore, our result on the decidability of Knuth-Bendix order may greatly benefit future algorithm design in term rewriting and theorem proving.
Program generation for the all-pairs shortest path problem
Authors: Sung-Chul Han, Franz Franchetti, Markus Püschel
Venue: Proceedings of the 15th international conference on Parallel architectures and compilation techniques (2006)

A recent trend in computing are domain-specific program generators, designed to alleviate the effort of porting and reoptimizing libraries for fast-changing and increasingly complex computing platforms. Examples include ATLAS, SPIRAL, and the codelet generator in FFTW. Each of these generators produces highly optimized source code directly from a problem specification. In this paper, we extend this list by a program generator for the well-known Floyd-Warshall (FW) algorithm that solves the all-pairs shortest path problem, which is important in a wide range of engineering applications.As the first contribution, we derive variants of the FW algorithm that make it possible to apply many of the optimization techniques developed for matrix-matrix multiplication. The second contribution is the actual program generator, which uses tiling, loop unrolling, and SIMD vectorization combined with a hill climbing search to produce the best code (float or integer) for a given platform.Using the program generator, we demonstrate a speedup over a straightforward single-precision implementation of up to a factor of 1.3 on Pentium 4 and 1.8 on Athlon 64. Use of 4-way vectorization further improves the performance by another factor of up to 5.7 on Pentium 4 and 3.0 on Athlon 64. For data type short integers, 8-way vectorization provides a speed-up of up to 4.6 on Pentium 4 and 5.0 on Athlon 64 over the best scalar code.
How to Break Access Control in a Controlled Manner
Authors: A Ferreira, R Cruz-Correia, L Antunes, P Farinha, E Oliveira-Palhares, D W. Chadwick, A Costa-Pereira
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

The Electronic Medical Record (EMR) integrates heterogeneous information within a Healthcare Institution stressing the need for security and access control. The Biostatistics and Medical Informatics Department from Porto Faculty of Medicine has recently implemented a Virtual EMR (VEMR) in order to integrate patient information and clinical reports within a university hospital. With more than 500 medical doctors using the system on a daily basis, an access control policy and model were implemented. However, the healthcare environment has unanticipated situations (i.e. emergency situations) where access to information is essential. Most traditional policies do not allow for overriding. A policy that allows for "Break-The-Glass (BTG)" was implemented in order to override access control whilst providing for non-repudiation mechanisms for its usage. The policy was easily integrated within the model confirming its modularity and the fact that user intervention in defining security procedures is crucial to its successful implementation and use.
Using Grid Computing to Enable Distributed Radar Data Retrieval and Processing
Authors: Diego Arias, Wilson Rivera
Venue: Proceedings of the Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (2006)

We describe a tool that implements a set of services to manipulate and store data from a radar network in a transparent way to end users. A major requirement of this system is data availability and reliability. Consequently, we have implemented a redundancy schema based on the Information Dispersal Algorithm (IDA). Preliminary results show that the IDA based replication provides better reliability and less storage spending than traditional replication.
Exploiting Mobile and Wireless Technologies in Vocational Training
Authors: Demetrios Sampson
Venue: Proceedings of the Fourth IEEE International Workshop on Wireless, Mobile and Ubiquitous Technology in Education (2006)

This paper presents the progress of the SMILE (Supporting Vocational Education and Training through Mobile Learning Environments) Project which is funded partly by the Leonardo da Vinci (LdV) Programme. The SMILE project (www.ask.iti.gr/smile) addresses the needs of the emerging mobile training services to support the new working paradigm, the mobile knowledge worker, at European and national level, by investigating some common questions about mobile training.
An Analysis of Linear and Non-Linear Interpolation Techniques for Three-Dimensional Rendering
Authors: Ekta Walia, Chandan Singh
Venue: Proceedings of the conference on Geometric Modeling and Imaging: New Trends (2006)

Many research papers indicate the use of various linear and non-linear interpolation techniques for the shading of three-dimensional objects. This paper presents a comparative study of the linear and non-linear interpolation techniques for the shading of threedimensional objects. It presents an analysis of different linear and non-linear interpolation techniques with respect to various parameters of shading. It analyses the affect of variation in specular highlight exponent on the quality of shading when the objects are shaded with linear and nonlinear interpolation techniques. The impact of varying the number of triangles in the underlying mesh on the shading quality obtained by these techniques is also compared. The interpolation schemes have also been analyzed for the Mach Band Effect when the intensity is interpolated across an underlying polygon. Finally, the cost of few non-linear interpolation algorithms that give good visual results has been compared to identify better and cost effective shading solutions for different situations like shading on handheld devices.
Scalable Monocular SLAM
Authors: Ethan Eade, Tom Drummond
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

Localization and mapping in unknown environments becomes more difficult as the complexity of the environment increases. With conventional techniques, the cost of maintaining estimates rises rapidly with the number of landmarks mapped. We present a monocular SLAM system that employs a particle filter and top-down search to allow realtime performance while mapping large numbers of landmarks. To our knowledge, we are the first to apply this FastSLAM-type particle filter to single-camera SLAM. We also introduce a novel partial initialization procedure that efficiently determines the depth of new landmarks. Moreover, we use information available in observations of new landmarks to improve camera pose estimates. Results show the system operating in real-time on a standard workstation while mapping hundreds of landmarks.
Incorporating Semantic Constraints into a Discriminative Categorization and Labelling Model.
Authors: Ariadna Quattoni, Michael Collins, Trevor Darrell
Venue: Proceedings of the Tenth IEEE International Conference on Computer Vision Workshops (2005)

This paper describes an approach to incorporate semantic knowledge sources within a discriminative learning framework. We consider a joint scene categorization and region labelling task and assume that some semantic knowledge is available. For example we might know what objects are allowed to appear in a given scene. Our goal is to use this knowledge to minimize the number of fully labelled examples (i.e. data for which each region in the image is labelled) required for learning. For each scene category the probability of a given labelling of image regions is modelled by a Conditional Random Field (CRF). Our model extends the CRF framework by incorporating hidden variables and combining class conditional CRFs into a joint framework for scene categorization and region labelling. We integrate semantic knowledge into the model by constraining the configurations that the latent region label variable can take, i.e. by constraining the possible region labelling for a given scene category. In a series of synthetic experiments, designed to illustrate the feasibility of the approach, adding semantic constraints about object entailment increased the region labelling accuracy given a fixed amount of fully labelled data.
Topic maps: fundamentalism meets pragmatism
Authors: Robert Barta
Venue: Proceedings of the 2005 Australasian Ontology Workshop - Volume 58 (2005)

After years of development, the Topic Maps community is in the process of consolidating its standards landscape. This work tries to outline an integrated scenario and sketches how the individual pieces may fit together. This is mostly achieved by a mathematical formalization for Topic Maps. It serves as basis for high-level data models and also for a query language.
Architecture for Development of WBES Based on Components and Agents
Authors: Alejandro Canales Cruz, Ruben Peredo Valderrama, Oscar Fabela Cano, Humberto Sossa A.
Venue: Proceedings of the 15th International Conference on Computing (2006)

A new Agents and Components Oriented Architecture for the development of Web-Based Education Systems (WBES) is presented. This architecture is based on the IEEE 1484 LTSA (Learning Technology System Architecture) specification and the software development pattern of the Intelligent Reusable Learning Components Object Oriented (IRLCOO). IRLCOO are a special type of Sharable Content Object (SCO) according to the Sharable Content Object Reference Model (SCORM). SCORM is used to create reusable and interoperable learning content. The architecture, communication model (based on LMS API, Web Services, AJAX, and Struts Framework) and Semantic Web Platform (SWP) that are described in this paper are used to develop authoring and evaluation tools with the integration of a digital library.
Learning Places from Views: Variation in Scene Processing as a Function of Experience and Navigational Ability
Authors: Russell A. Epstein, J. Stephen Higgins, Sharon L. Thompson-schill
Venue: Journal of Cognitive Neuroscience (2005)

Humans and animals use information obtained from different viewpoints to form representations of the spatial structure of the world. We used functional magnetic resonance imaging (fMRI) adaptation to investigate the neural basis of this learning process and to show how the concomitant representations vary across individuals as a function of navigational ability. In particular, we examined the effect of repeating viewpoint and/ or place information over both short (within-trial) and long (across-scan) intervals on the neural response in scene processing regions. Short-term fMRI adaptation effects in the parahippocampal cortex were initially highly viewpoint-specific but became less so over time. Long-term fMRI repetition effects included a significant viewpoint-invariant component. When individual differences in navigational ability were considered, a significant correlation between the strength of these effects and self-reported navigational competence was observed. In particular, good navigators encoded representations that differed between new and old views and new and old places, whereas bad navigators did not. These results suggest that cortical scene representations evolve over time to become more viewpoint-invariant and that the quality of these representations directly impacts navigational ability.
Low-Power Multiplierless 2-D DWT and IDWT Architectures Using 4-tap Daubechies Filters
Authors: Tze-Yun Sung, Yaw-Shih Shieh, Chun-Wang Yu, Hsi-Chin Hsin
Venue: Proceedings of the Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (2006)

This paper proposes two architectures of 2-D discrete wavelet transform (DWT) and inverse DWT (IDWT). The first high-efficiency architecture comprises a transform module, an address sequencer, and a RAM module. The transform module has uniform and regular structure, simple control flow, and local communication. The significant advantages of the single transform module are full hardware-utilization and low-power. The second architecture features parallel and pipelined computation and high throughput. Both architectures are very suitable for VLSI implementation of new-generation image coding/decoding systems, such as JPEG-2000. In the realization of 2-D DWT/IDWT, we focus on a FPGA and VLSI implementation using 4-tap Daubechies filters, which saves power and reduces chip area.
A Model for Interoperability in Computer Supported Collaborative Learning
Authors: Georgios Kahrimanis, Andreas Papasalouros, Nikolaos Avouris, Simeon Retalis
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Computer Supported Collaborative Learning activities involve combination of complex software tools that often need to interoperate in a wider context of learning. This paper proposes a data model that accommodates requirements of typical collaborative learning situations and facilitates interoperability of tools and interchange of products of collaboration and evaluation data. The model has been tested against various typical tools used for both synchronous and asynchronous collaboration of groups of students.
Endoscope Tracking Using Wavelet-Gravitation Network Incorporated with Kalman Filter
Authors: V. Spinko, D. Shi, W. S. Ng
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

Inspired by the movement of comet under gravitational interaction with planets and stars, we propose a novel wavelet-gravitation network (WGN) for endoscope optical tracking. We substitute the world gravitation law with interaction described by radial wavelet function. The WGN is trained based on the energy conservation law. The prediction of target image position is made with movement described by the second Newton's law. The WGN is incorporated with Kalman filtering framework. Our experiments show that WGN performs especially well for nonlinear movement tracking. As the movement of surgical tools is handdriven, it is mostly nonlinear and affected by both tangential and normal accelerations. Our proposed methodology has been successfully applied to endoscope tracking for image guided surgery.
Learning erasing pattern languages with queries
Authors: Jochen Nessel, Steffen Lange
Venue: Theoretical Computer Science (2005)

A pattern is a finite string of constant and variable symbols. The non-erasing language generated by a pattern is the set of all strings of constant symbols that can be obtained by substituting non-empty strings for variables. In order to build the erasing language generated by a pattern, it is also admissible to substitute the empty string.The present paper deals with the problem of learning erasing pattern languages within Angluin's model of learning with queries. Moreover, the learnability of erasing pattern languages with queries is studied when additional information is available. The results obtained are compared with previously known results in case non-erasing pattern languages have to be learned.First, when regular pattern languages have to be learned, it is shown that the learnability results for the non-erasing case remain valid, if the proper superclass of all erasing regular pattern languages is the object of learning. Second, in the general case, serious differences have been observed. For instance, it turns out that arbitrary erasing pattern languages cannot be learned in settings in which, in the non-erasing case, even polynomially many queries will suffice.