ppxscal/embedding_network huggingface dataset:
New results on web caching with request reordering
Authors: Susanne Albers
Venue: Proceedings of the sixteenth annual ACM symposium on Parallelism in algorithms and architectures (2004)

We study web caching with request reordering. The goal is to maintain a cache of web documents so that a sequence of requests can be served at low cost. To improve cache hit rates, a limited reordering of requests is allowed. Feder et al. [6], who recently introduced this problem, considered caches of size 1, i.e. a cache can store one document. They presented an offline algorithm based on dynamic programming as well as online algorithms that achieve constant factor competitive ratios. For arbitrary cache sizes, Feder et al. [7] gave online strategies that have nearly optimal competitive ratios in several cost models.In this paper we first present a deterministic online algorithm that achieves an optimal competitiveness, for the most general cost model and all cache sizes. We then investigate the offline problem, which is NP-hard in general. We develop the first polynomial time algorithms that can manage arbitrary cache sizes. Our strategies achieve small constant factor approximation ratios. The algorithms are based on a general technique that reduces web caching with request reordering to a problem of computing batched service schedules.Our approximation result for the Fault Model also improves upon the best previous approximation guarantee known for web caching without request reordering.
Exploring gradient-based face navigation interfaces
Authors: Tzu-Pei Grace Chen, Sidney Fels
Venue: Proceedings of Graphics Interface 2004 (2004)

We have created a gradient-based face navigation interface that allows users to explore a large face space based on an eigenface technique. This approach to synthesizing faces contrasts with more typical techniques for forming composite faces based on the blending of facial features. We compare three ways of moving through the face space, using two types of sliders and a face-wheel. These are adapted from typical color space interfaces since they are commonly used. However, eigenface dimensions do not have meaningful text labels, unlike primary colors, necessitating the use of faces themselves for the labels of the navigation axes. Results suggest that users can navigate with face-labelled axes. They find slider interfaces best suited to finding the neighborhood of a target face, but that the face-wheel is better for refinement once inside the neighborhood.
Identifying similarities, periodicities and bursts for online search queries
Authors: Michail Vlachos, Christopher Meek Zografoula Vagena, Dimitrios Gunopulos
Venue: Proceedings of the 2004 ACM SIGMOD international conference on Management of data (2004)

We present several methods for mining knowledge from the query logs of the MSN search engine. Using the query logs, we build a time series for each query word or phrase (e.g., 'Thanksgiving' or 'Christmas gifts') where the elements of the time series are the number of times that a query is issued on a day. All of the methods we describe use sequences of this form and can be applied to time series data generally. Our primary goal is the discovery of semantically similar queries and we do so by identifying queries with similar demand patterns. Utilizing the best Fourier coefficients and the energy of the omitted components, we improve upon the state-of-the-art in time-series similarity matching. The extracted sequence features are then organized in an efficient metric tree index structure. We also demonstrate how to efficiently and accurately discover the important periods in a time-series. Finally we propose a simple but effective method for identification of bursts (long or short-term). Using the burst information extracted from a sequence, we are able to efficiently perform 'query-by-burst' on the database of time-series. We conclude the presentation with the description of a tool that uses the described methods, and serves as an interactive exploratory data discovery tool for the MSN query database.
On the optimal choice of quality metric in image compression: a soft computing approach
Authors: O. Kosheleva
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2004)

Images take lot of computer space; in many practical situations, we cannot store all original images, we have to use compression. Moreover, in many such situations, compression ratio provided by even the best lossless compression is not sufficient, so we have to use lossy compression. In a lossy compression, the reconstructed image &#x0128; is, in general, different from the original image I. There exist many different lossy compression methods, and most of these methods have several tunable parameters. In different situations, different methods lead to different quality reconstruction, so it is important to select, in each situation, the best compression method. A natural idea is to select the compression method for which the average value of some metric d(I,&#x0128;) is the smallest possible. The question is then: which quality metric should we choose? In this paper, we show that under certain reasonable symmetry conditions, Lp metrics d(I,&#x0128;)=&#x222b;|I(x)&#x2212;&#x0128;(x)|pdx are the best, and that the optimal value of p can be selected depending on the expected relative size r of the informative part of the image.
Learning Rates for Q-learning
Authors: Eyal Even-Dar, Yishay Mansour
Venue: The Journal of Machine Learning Research (2004)

In this paper we derive convergence rates for Q-learning. We show an interesting relationship between the convergence rate and the learning rate used in Q-learning. For a polynomial learning rate, one which is 1/t&omega; at time t where &omega;&isin;(1/2,1), we show that the convergence rate is polynomial in 1/(1-&gamma;), where &gamma; is the discount factor. In contrast we show that for a linear learning rate, one which is 1/t at time t, the convergence rate has an exponential dependence on 1/(1-&gamma;). In addition we show a simple example that proves this exponential behavior is inherent for linear learning rates.
A Hybrid Parameterization Method for NURBS
Authors: Siti Mariyam Hj. Shamsuddin, Mahmoud Ali Ahmed
Venue: Proceedings of the International Conference on Computer Graphics, Imaging and Visualization (2004)

The problem of the parameterization of data points in NURBS curve/surface has been considered by amount of researchers. In this study, a new parameterization method considered as hybrid parameterization method is proposed. Like universal method, this method uses the property of "at each span index, there is exactly one maximum value of the rational B-spline basis function". By taking the maximum rational B-spline basis functions as initial values, the centripetal method is applied to generate the parameter values of hybrid parameterization. This approach inherits the advantages of universal and centripetal methods such as allowing having multiple knots value. The proposed method gives better object shaped relevant to the other methods. The results on two simple data sets for both curves and surfaces show that this method is capable of generating smooth and fair object shape.
RT-Frontier: A Real-Time Operating System for Practical Imprecise Computation
Venue: Proceedings of the 10th IEEE Real-Time and Embedded Technology and Applications Symposium (2004)

Imprecise computation is known as an effective techniquefor dynamically resolving trade-offs between theamount of resources and the quality of the result. However,its implementation and operating system supportmethods have not been exploited enough from a practicalpoint of view. This paper presents a new approachtaken in the RT-Frontier operating system to support imprecisecomputation. Applications that allow imprecisecomputation are first transformed to tasks composedof three parts based on an extended imprecise computationmodel. All tasks are then uniformly scheduled accordingto a novel scheduling algorithm called Slack Stealerfor Optional Parts (SS-OP). The SS-OP algorithm is designedto handle imprecise computations with small overhead,which is at a comparable level of that of the EarliestDeadline First (EDF) algorithm. The results of experimentsshow that the presented approach is cost-effectiveenough to be considered as a practical basis for embeddedreal-time systems.
Workshop on formal verification: (VERkshop)
Venue: ACM SIGSOFT Software Engineering Notes (1980)

There has been significant progress in the formal verification of system designs and of programs in the last few years, but there are many problems remaining. In an effort to assess the state of the art on the practical side of formal verification, a workshop (VERkshop) was held in April at SRI, co-organized by Peter Neumann and Steve Walker (DoD). There were about 50 attendees, essentially all of whom contributed on-line informal written statements (research summaries, position statements, etc.) in advance.In order to share the conclusions of the VERkshop with a wider audience, we are including most of the a priori VERkshop contribution in this issue (although some have been abridged). In addition, a posteriori statements are included that summarize the three days' activities. Some trivial corrections and formatting have been added, but otherwise the material is essentially as received. The included items have page numbers as indicated.
A New Method in Multi-Issue Negotiation
Authors: Ning Zhang, Lei Wang, Jie Yang
Venue: Proceedings of the E-Commerce Technology for Dynamic E-Business, IEEE International Conference (2004)

In this paper we describe a mechanism for automated negotiation in which artificial agents can deal with a multi-issue negotiation in a one-to-many way based on some strategies. The negotiation process are governed dynamically by some strategies that emphasize on the diverse processing methods under the considering of different commodity attributes, including dynamic delayed evaluation and response to the received offers, generation of offer group with the same utility. Our analysis shows that the mechanism ensures that bargaining agents could reach a better agreement automatically. We also implement a prototype system to verify the advantages of our mechanism.
A classification of s-lines in a closed s-manifold
Authors: Howard Iseri
Venue: Smarandache Notions Journal (2004)

In Smarandache Manifolds [1], it is shown that the s-sphere has both closed and open s-lines. It is shown here that this is true for any closed s-manifold. This would make each closed s-manifold a Smarandache geometry relative to the axiom requiring each line to be extendable to infinity, since each closed s-line would have finite length.Furthermore, it is shown that whether a particular s-line is closed or not is determined locally, and it is determined precisely which s-lines are closed and which are open.
Knowledge-Based Automation of Web-Based Learning Materials Using Semantic Web Technologies
Authors: Yukari Shirota
Venue: Proceedings of the Second International Conference on Creating, Connecting and Collaborating through Computing (2004)

Today, an increasing number of junior and senior high schools,and universities use computer-network-based distance learningsystems. However, teachers face a cost problem whendeveloping learning materials for such systems. It takes muchtime, practice, and devotion to design and develop learningmaterials from scratch. The cost is particularly high whenteachers try to create distance learning systems to help studentsinteractively and naturally. I believe that we can leverageknowledge bases and Semantic Web technologies for most ofthis work, and thereby largely relinquish it to computers. Tojustify this belief, we have developed a prototype system thatcan automate Web-based learning materials. The targetproblem is a mathematical optimization problem. This paperoutlines the system and provides a concrete description of theautomation process.
Using interactive technology in a short java course: an experience report
Authors: Roberto E. Lopez-Herrejon, Morrie Schulman
Venue: Proceedings of the 9th annual SIGCSE conference on Innovation and technology in computer science education (2004)

Keeping students alert and responsive during lectures is a challenge even for experienced teachers in small group settings. Research has shown the importance of student participation and involvement in the learning process. Many ideas and strategies have been proposed to promote these two vital education elements [5]. Among them is the use of interactive technology where the instructor asks a question to the class and each student answers individually. These answers are tallied and the professor can get immediate, quantitative, and real-time feedback information that can be used to detect and address comprehension problems and to adapt the lecture plan accordingly. In this paper we report our experiences using a wireless interactive system named the Classroom Performance System (CPS) [9] in a fast-paced, short but comprehensive Java programming course. We present the challenges we faced and the lessons we learned in designing and delivering lectures using this type of technology.
Online QoS Optimization Using Service Classes in Surveillance Radar Systems
Authors: Chang-Gun Lee, Chi-Sheng Shih, Lui Sha
Venue: Real-Time Systems (2004)

Many application level qualities are functions of available computation resources. Recent studies have handled the computation resource allocation problem to maximize the overall application quality. However, such QoS problems are fundamentally multi-dimensional optimization problems that require extensive computation. Therefore, online usage of optimization procedures may significantly reduce the computation resource available for applications. This raises the question of how to best use the optimization procedures for dynamic real-time task sets. In dynamic real-time systems, it is important to improve the performance by re-allocating the resources adapting to dynamic situations. However, the overhead of changing task parameters (i.e., algorithms and frequencies) for resource re-allocation is non-negligible in many applications. Thus, too frequent change of resource allocation may not be desirable. This paper proposes a method called service classes configuration to address the QoS problem with dynamic arrival and departure of tasks. The method avoids online usage of optimization procedures by offline designing templates (called service classes) of resource allocation, which will be adaptively used depending on online situations. The service classes are designed by best trading-off the accuracy of dynamic adaptation against the overhead of resource re-allocation. A simplified radar application is used as an illustrative example.
A fuzzy controller with evolving structure
Authors: Plamen Angelov
Venue: Information Sciences&mdash;Informatics and Computer Science: An International Journal (2004)

An approach to on-line design of fuzzy controllers of Takagi-Sugeno type with gradually evolving structure is treated in the paper. Fuzzy rules, representing the structure of the controller are generated based on data collected during the process of control using newly introduced technique for on-line identification of Takagi-Sugeno systems. The output of the plant under control (including its dynamic) and the respective control signal has been memorised and stored in on-line mode. These data has been used to train in a non-iterative, recursive way the fuzzy controller. The indirect adaptive control approach has been used in combination with the novel on-line identification technique. This approach exploits the quasi-linear nature of Takagi-Sugeno models and builds-up the control rule-base structure and adapts it in on-line mode with recursive, non-iterative learning. The method is illustrated with an example from air-conditioning systems, though it has wider potential applications.
Fault-Tolerant Techniques for Ambient Intelligent Distributed Systems
Authors: Diana Marculescu, Nicholas H. Zamora, Phillip Stanley-Marbell, Radu Marculescu
Venue: Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design (2003)

Ambient Intelligent Systems provide an unexplored hardware platformfor executing distributed applications under strict energy constraints.These systems must respond quickly to changes in userbehavior or environmental conditions and must provide high availabilityand fault-tolerance under given quality constraints. Thesesystems will necessitate fault-tolerance to be built into applications.One way to provide such fault-tolerance is to employ the use of redundancy.Hundreds of computational devices will be available indeeply networked ambient intelligent systems, providing opportunitiesto exploit node redundancy to increase application lifetime orimprove quality of results if it drops below a threshold. Pre-copyingwith remote execution is proposed as a novel, alternative techniqueof code migration to enhance system lifetime for ambient intelligentsystems. Self-management of the system is considered in two differentscenarios: applications that tolerate graceful quality degradationand applications with single-point failures. The proposed techniquecan be part of a design methodology for prolonging the lifetime ofa wide range of applications under various types of faults, despitescarce energy resources.
What global sourcing means for U.S. IT workers and for the U.S. economy
Authors: Catherine L. Mann
Venue: Communications of the ACM (2004)

The result is likely to be increased IT employment diffused throughout the U.S. economy, especially in non-tech industrial sectors.
Effective use of block-level sampling in statistics estimation
Authors: Surajit Chaudhuri, Gautam Das, Utkarsh Srivastava
Venue: Proceedings of the 2004 ACM SIGMOD international conference on Management of data (2004)

Block-level sampling is far more efficient than true uniform-random sampling over a large database, but prone to significant errors if used to create database statistics. In this paper, we develop principled approaches to overcome this limitation of block-level sampling for histograms as well as distinct-value estimations. For histogram construction, we give a novel two-phase adaptive method in which the sample size required to reach a desired accuracy is decided based on a first phase sample. This method is significantly faster than previous iterative methods proposed for the same problem. For distinct-value estimation, we show that existing estimators designed for uniform-random samples may perform very poorly if used directly on block-level samples. We present a key technique that computes an appropriate subset of a block-level sample that is suitable for use with most existing estimators. This, to the best of our knowledge, is the first principled method for distinct-value estimation with block-level samples. We provide extensive experimental results validating our methods.
Word translation disambiguation using bilingual bootstrapping
Authors: Hang Li, Cong Li
Venue: Computational Linguistics (2004)

This article proposes a new method for word translation disambiguation, one that uses a machine-learning technique called bilingual bootstrapping. In learning to disambiguate words to be translated, bilingual bootstrapping makes use of a small amount of classified data and a large amount of unclassified data in both the source and the target languages. It repeatedly constructs classifiers in the two languages in parallel and boosts the performance of the classifiers by classifying unclassified data in the two languages and by exchanging information regarding classified data between the two languages. Experimental results indicate that word translation disambiguation based on bilingual bootstrapping consistently and significantly outperforms existing methods that are based on monolingual bootstrapping.
Maximizing the Use of Computational Resources in Multi-Camera Feedback Control
Venue: Proceedings of the 10th IEEE Real-Time and Embedded Technology and Applications Symposium (2004)

In vision-based feedback control systems, the time to obtainsensor information is usually non-negligible, and thesesystems thereby possess fundamentally different timing behaviorcompared to standard real-time control applications.For many image-based tracking algorithms, however, it ispossible to trade-off the computational time versus the accuracyof the produced position/orientation estimates.This paper presents a method for optimizing the use ofcomputational resources in a multi-camera based positioningsystem. A simplified equation for the covariance of theposition estimation error is calculated, which depends onthe set of cameras used and the number of edge detectionpoints in each image. An efficient algorithm for selectionof a suitable subset of the available cameras is presented,which attempts to minimize the estimation covariance givena desired, pre-specified maximum input-output latency ofthe feedback control loop.Simulations have been performed that capture the real-timeproperties of the vision-based tracking algorithm andthe effects of the timing on the performance of the controlsystem. The suggested strategy has been compared withheuristic algorithms, and it obtains large improvements inestimation accuracy and performance for objects both infree motion and under closed-loop position control.
Image Analysis Techniques for the Automated Evaluation of Subaxial Subluxation in Cervical Spine X-ray Images
Authors: R. Joe Stanley, Santhosh Seetharaman, L. Rodney Long, Sameer Antani, George Thoma, Edward Downey
Venue: Proceedings of the 17th IEEE Symposium on Computer-Based Medical Systems (2004)

Rheumatoid arthritis is a chronic inflammatory disease affecting synovial joints of the body,especially the hands and feet, spine, knees and hips. For many patients, the cervical spine isassociated with rheumatoid arthritis. Subluxation is the abnormal movement of one of thebones that comprise a joint. In this research, image analysis techniques have been investigated for the recognition of cervical spine x-ray images with one or more instances of subaxial subluxation. Receiver operating characteristic curve results are presented, showing potential for subaxial subluxation discrimination on an image-by-image basis.
A Dichotomous Algorithm for Association Rule Mining
Authors: T.-Y. Jen, R. Taouil, D. Laurent
Venue: Proceedings of the Database and Expert Systems Applications, 15th International Workshop (2004)

The analysis of large amounts of data requires important computing resources that may not be available, even in current environment, and there are traditionally two main ways for solving this problem. The first is to use multi-processor machines, and the second is to use computer clusters. The main drawbacks of these solutions are the expensive cost of machines and their specific utilization. In order to avoid these drawbacks, distributed algorithms for mining association rules have been proposed. However, these algorithms either run high-synchronous methods or lack flexibility to be adapted to machines with limited available resources. In this paper, a distributed dichotomous algorithm (DDA) is proposed for association rule mining. The main features of DDA are that this algorithm does not require a high level of synchronization and that it does not process data replication and redundant calculations. In addition, DDA can partition recursively the tasks and the data set so as to be processed by machines with limited available resources.