ppxscal/embedding_network huggingface dataset:
Subgroup coverings of some sporadic groups
Authors: P. E. Holmes
Venue: Journal of Combinatorial Theory Series A (2006)

A set of proper subgroups is a covering for a group if their union is the whole group. Determining the size of a smallest covering is an open problem for many simple groups. For some of the sporadic groups, we find subgroup coverings of minimal cardinality. For others we specify the isomorphism types of subgroups in a smallest covering and use graphs to calculate bounds for its size.
Information extraction, data mining and joint inference
Authors: Andrew McCallum
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

Although information extraction and data mining appear together in many applications, their interface in most current systems would better be described as serial juxtaposition than as tight integration. Information extraction populates slots in a database by identifying relevant subsequences of text, but is usually not aware of the emerging patterns and regularities in the database. Data mining methods begin from a populated database, and are often unaware of where the data came from, or its inherent uncertainties. The result is that the accuracy of both suffers, and accurate mining of complex text sources has been beyond reach.In this talk I will describe work in probabilistic models that perform joint inference across multiple components of an information processing pipeline in order to avoid the brittle accumulation of errors. After briefly introducing conditional random fields, I will describe recent work in information extraction leveraging factorial state representations, entity resolution, and transfer learning, as well as scalable methods of inference and learning. I'll close with some recent work on probabilistic models for social network analysis, and a demonstration of Rexa.info, a new research paper search engine.
Multi-Agent Coalition Formation for Long-Term Task or Mobile Network
Authors: Hsiu-Hui Lee, Chung-Hsien Chen
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

Coalition formation is a process to form a group and solve a problem via cooperation. Because of the rising of network, each computing device can communicate through network. We can integrate those resources and use them by coalition formation. In this paper, we propose a new architecture which integrates case-based reasoning, negotiation, and reinforcement learning to improve the coalition formation process. Coalitions of our architecture suit for executing longterm task or for accomplishing a task in high mobility networks. Our experiments also show the advantage of our architecture in these two different environments.
Outpatient clinic scheduling: a simulation approach
Authors: Ming Guo, Michael Wagner, Constance West
Venue: Proceedings of the 36th conference on Winter simulation (2004)

The process by which outpatients are scheduled for a doctor's visit is a crucial determinant of the overall efficiency of the patient flow. The problem at hand consists of determining prioritization (triage) rules so that adequate patient care is guaranteed, resources (provider schedules) are utilized efficiently and a service guarantee can be ensured. We present a simulation framework for the evaluation and optimization of scheduling rules. We outline the basic ingredients of our model, illustrate the kinds of analyses it has enabled us to perform and summarize our experience with a preliminary implementation for the Division of Pediatric Ophthalmology at Cincinnati Children's Hospital Medical Center. Challenges for adaptations to other settings are also outlined.
Multi-scaling sampling: an adaptive sampling method for discovering approximate association rules
Authors: Cai-Yan Jia, Xie-Ping Gao
Venue: Journal of Computer Science and Technology (2005)

One of the obstacles of the efficient association rule mining is the explosive expansion of data sets since it is costly or impossible to scan large databases, esp., for multiple times. A popular solution to improve the speed and scalability of the association rule mining is to do the algorithm on a random sample instead of the entire database. But how to effectively define and efficiently estimate the degree of error with respect to the outcome of the algorithm, and how to determine the sample size needed are entangling researches until now. In this paper, an effective and efficient algorithm is given based on the PAC (Probably Approximate Correct) learning theory to measure and estimate sample error. Then, a new adaptive, on-line, fast sampling strategy -- multi-scaling sampling -- is presented inspired by MRA (Multi-Resolution Analysis) and Shannon sampling theorem, for quickly obtaining acceptably approximate association rules at appropriate sample size. Both theoretical analysis and empirical study have showed that the sampling strategy can achieve a very good speed-accuracy trade-off.
Visual calibration and correction for ambient illumination
Authors: Kate Devlin, Alan Chalmers, Erik Reinhard
Venue: ACM Transactions on Applied Perception (TAP) (2006)

Many applications require that an image will appear the same regardless of where or how it is displayed. However, the conditions in which an image is displayed can adversely affect its appearance. Computer monitor screens not only emit light, but can also reflect extraneous light present in the viewing environment. This can cause images displayed on a monitor to appear faded by reducing their perceived contrast. Current approaches to this problem involve measuring this ambient illumination with specialized hardware and then altering the display device or changing the viewing conditions. This is not only impractical, but also costly and time consuming. For a user who does not have the equipment, expertise, or budget to control these facets, a practical alternative is sought. This paper presents a method whereby the display device itself can be used to determine the effect of ambient light on perceived contrast, thus enabling the viewers themselves to perform visual calibration. This method is grounded in established psychophysical experimentation and we present both an extensive procedure and an equivalent rapid procedure. Our work is extended by providing a novel method of contrast correction so that the contrast of an image viewed in bright conditions can be corrected to appear the same as an image viewed in a darkened room. This is verified through formal validation. These methods are easy to apply in practical settings, while accurate enough to be useful.
A Conic Section Classifier and its Application to Image Datasets
Authors: Arunava Banerjee, Santhosh Kodipaka, Baba C. Vemuri
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

Many problems in computer vision involving recognition and/or classification can be posed in the general framework of supervised learning. There is however one aspect of image datasets, the high-dimensionality of the data points, that makes the direct application of off-the-shelf learning techniques problematic. In this paper, we present a novel concept class and a companion tractable algorithm for learning a suitable classifier from a given labeled dataset, that is particularly suited to high-dimensional sparse datasets. Each member class in the dataset is represented by a prototype conic section in the feature space, and new data points are classified based on a distance measure to each such representative conic section that is parameterized by its focus, directrix and eccentricity. Learning is achieved by altering the parameters of the conic section descriptor for each class, so as to better represent the data. We demonstrate the efficacy of the technique by comparing it to several well known classifiers on multiple public domain datasets.
A constructive heuristic for the undirected rural postman problem
Authors: Gianpaolo Ghiani, Demetrio Laganà, Roberto Musmanno
Venue: Computers and Operations Research (2006)

This paper describes a constructive heuristic for the well-known Undirected Rural Postman Problem. At each iteration, the procedure inserts a connected component of the required edges and performs a local postoptimization. Computational results on a set of benchmark instances with up to 350 vertices show that the proposed procedure is competitive with the classical Frederickson procedure. Its use is recommended when a high-quality solution is needed in a short amount of time (e.g., in laser plotter applications).
Building conference proceedings requires adaptable workflow and content management
Authors: Jutta A. Mülle, Klemens Böhm, Nicolas Röper, Tobias Sünder
Venue: Proceedings of the 32nd international conference on Very large data bases (2006)

ProceedingsBuilder is a system that helps the proceedings chair of a scientific conference to carry out his chores. It has features of both workflow management systems (WFMS) and content management systems (CMS), in order to collect the material for the printed proceedings and other products. ProceedingsBuilder has been operational at several conferences, including VLDB 2005. When using Proceedings-Builder, we had a very intense lesson which kinds of work-flow adaptations may become necessary. Existing WFMS do not offer support for most of them. The concern of this article is to describe and classify these various requirements regarding adaptation. ProceedingsBuilder is an example of a broad class of systems, namely editorial systems that collect content in order to publish it. Our findings are of interest to a broader audience, not only to conference organizers.
A Real-time Secure Voice Communication System Based on Speech Recognition
Authors: Zongyuan Deng, Zhen Yang, Lixin Deng
Venue: Proceedings of the International Conference on Systems and Networks Communication (2006)

This paper proposes a scheme of real-time secure communication system based on information hiding and speech recognition. The algorithm uses speech recognition to reduce the bit-rate of secret speech greatly. Then we design an information hiding algorithm by adaptively choosing embedding locations and adopting the multi-nary modulation technique. Experimental results show that this algorithm has good imperceptibility and robustness against various interference (A-law/U-law compression, low-pass filtering, white noise, etc) when the speech is transmitted over the public switching telephone network (PSTN). This algorithm can be widely used in secure voice communication and fax systems.
Design space exploration using arithmetic-level hardware--software cosimulation for configurable multiprocessor platforms
Authors: Jingzhao Ou, Viktor K. Prasanna
Venue: ACM Transactions on Embedded Computing Systems (TECS) (2006)

Configurable multiprocessor platforms consist of multiple soft processors configured on FPGA devices. They have become an attractive choice for implementing many computing applications. In addition to the various ways of distributing software execution among the multiple soft processors, the application designer can customize soft processors and the connections between them in order to improve the performance of the applications running on the multiprocessor platform. State-of-the-art design tools rely on low-level simulation to explore the various design trade-offs offered by configurable multiprocessor platforms. These low-level simulation based exploration techniques are too time-consuming and can be a major bottleneck to efficient design space exploration on these platforms. We propose a design space exploration technique for configurable multiprocessor platforms using arithmetic-level cycle-accurate hardware--software cosimulation. Arithmetic-level abstractions of the hardware and software execution platforms are created within the proposed cosimulation environment. The configurable multiprocessor platforms are described using these arithmetic-level abstractions. Hardware and software simulators are tightly integrated to concurrently simulate the arithmetic behavior of the multiprocessor platform. The simulation within the integrated simulators are synchronized to provide cycle-accurate simulation results for the complete multiprocessor platform. By doing so, we significantly speed up the cosimulation process for configurable multiprocessor platforms. Exploration of the various hardware-software design trade-offs provided by configurable multiprocessor platforms can be performed within the proposed cycle-accurate cosimulation environment. After the final designs are identified, the corresponding low-level implementations with the desired cycle-accurate arithmetic behavior are generated automatically. For illustrative purposes, we provide an implementation of our approach based on MATLAB/Simulink. We show the cosimulation of two numerical computation applications and one image-processing application on a popular configurable multiprocessor platform within the MATLAB/Simulink-based cosimulation environment. For these three applications, our arithmetic-level cosimulation approach leads to speed-ups in simulation time of up to more than 800x compared with the low-level simulation approaches. The designs of these applications identified using our arithmetic-level cosimulation approach achieve execution time speed-ups up to 5.6x, compared with other designs considered in our experiments.
WebTelop: dynamic TV-content augmentation by using Web pages
Authors: Q. Ma, K. Tanaka
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

In this paper, we propose a method for dynamic integration of TV-program content and related Web content and demonstrate our prototype system called WebTelop. The primary source of information in WebTelop is the TV-program content. Web pages related to the TV-program content are retrieved automatically in real time and are used to augment the TV-program content in the form of captions. Our method enables: (1) real time integration of TV-program content with Web-page content, (2) information retrieval for TVprogram content augmentation based on the topic structures of the TV programs and Web pages, and (3) the use of a virtual character agent to help users navigate through the related Web pages of the TV programs.
Fuzzy Neural Network for Evaluating Sensor Task Priorities
Authors: Shucai Huang, Weimin Li, Wei Li
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

Sensor task priorities are the important foundation for sensors management. In this contribution a fuzzy management scheme is proposed to cope with the evaluation of multi-sensor task priorities in air surveillance applications. Based on all fused track and identified data, a fuzzy neural network determines the priority of each surveillance task to perform during the decision cycle. The structure of the fuzzy neural network is constructed first, the linguistic variables and terminology are defined, and the nodes function and the learning rules of the fuzzy neural network are designed then, finally a sensor task priorities evaluation example is given to demonstrate the validity of the fuzzy neural network evaluation approach in the sensor management application. Included results illustrate how the importance of the tasks, measured through their time-varying priorities, allows timely adapt sensor operation to changing situations.
Communication-Aware Job Placement Policies for the KOALA Grid Scheduler
Authors: Ozan Sonmez, Hashim Mohamed, Dick Epema
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

In multicluster systems, and more generally, in grids, parallel applications may require co-allocation, i.e., the simultaneous allocation of resources such as processors in multiple clusters. Although co-allocation enables the allocation of more processors than available on a single cluster, depending on the applications' communication characteristics, it has the potential disadvantage of increased execution times due to relatively slow wide-area communication. In this paper, we present two job placement policies, the Cluster Minimization and the Flexible Cluster Minimization policies which take into account the wide-area communication overhead when co-allocating applications across the clusters. We have implemented these policies in our grid scheduler called KOALA in order to serve different job request types. To assess the performance of the policies, we perform experiments in a real multicluster testbed using communication-intensive parallel applications.
Dynamic estimation of CPU demand of web traffic
Authors: Giovanni Pacifici, Wolfgang Segmuller, Mike Spreitzer, Asser Tantawi
Venue: Proceedings of the 1st international conference on Performance evaluation methodolgies and tools (2006)

Managing the resources in a large Web serving system requires knowledge of the resource needs for service request-s of various kinds, and these needs may change over time. Assessing resource needs is commonly performed using techniques such as offline profiling, application instrumentation, and kernel-based instrumentation. Little attention has been given to the dynamic estimation of dynamic resource needs, relying only on external and high-level measurements such as overall resource utilization and request rates. We consider the problem of dynamically estimating dynamic CPU demands of multiple kinds of requests using CPU utilization and throughput measurements. We formulate the problem as a linear regression problem and obtain its basic solution. However, in practice one is faced with issues such as insignificant flows, collinear flows, space and temporal variations, and background noise. In order to deal with such issues, we present several mechanisms such as data aging, flow rejection, flow combining, noise reduction, and smoothing. We implemented these techniques in a Work Profiler component that we delivered as part of a broader system management product. We present experimental results from using this component in scenarios inspired by real-world usage of that product; our technique produces estimates that are roughly within a factor of 2 of the right answer, for the request flows that draw significant CPU power.
On the equalization of keystroke timing histograms
Authors: Jugurta R. Montalvão Filho, Eduardo O. Freire
Venue: Pattern Recognition Letters (2006)

The effect of parametric equalization of time interval histograms (key down-down intervals) on the performance of keystroke-based user verification algorithms is analyzed. Three algorithms are used throughout this analysis: a classic one for static (structured) texts, a second one, also proposed in literature, for both static and arbitrary (free) text, and a new one for arbitrary text based verification. Their performances are reported before and after time interval histogram equalization, and the results corroborate with the hypothesis that the nonlinear memoryless time interval transform proposed here, despite its simplicity, can be a useful and almost costless building block in keystroke-based biometric systems.
Propositional satisfiability: techniques, algorithms and applications
Authors: Inês Lynce
Venue: AI Communications (2006)

Recent years have seen remarkable progress in propositional satisfiability (SAT). Despite the worst-case exponential run time of all known algorithms, SAT solvers can currently be used to solve hard benchmark problems.This PhD dissertation contributes to a better understanding of the techniques, the algorithms and the applications of propositional satisfiability. First, we introduce efficient lazy data structures that, though unable to determine exactly the dynamic size of a clause, are quite accurate at predicting the number of unassigned literals in a clause. In addition, we suggest the use of probing-based preprocessing techniques for manipulating propositional formulas. Furthermore, unrestricted backtracking is proposed as an algorithm that combines the advantages of local search and backtrack search. Finally, we relate hardness with hidden structure in unsatisfiable random 3-SAT formulas, where hardness is measured by the search effort and hidden structure is measured by unsatisfiable cores and strong backdoors.
RaSOSS - Remote Analysis System for Open Source Software
Authors: Timo Koponen
Venue: Proceedings of the International Conference on Software Engineering Advances (2006)

Open Source Software is becoming evermore important and widespread these days. However, their maintenance processes are commonly unknown even they are controlled with defect management and version management systems. These systems have been studied separately in earlier studies. Therefore, in this paper, we present a system, Remote Analysis System Open Source Software (RaSOSS), for analyzing maintenance process through both systems. The system retrieves data from the defect management and version management systems for analysis. Analysis provides attributes that evaluated generally project, defect management process and version management. We used Apache HTTP Server as a case study to explain results of provided analysis.