ppxscal/embedding_network huggingface dataset:
An objective approach to cluster validation
Authors: Mohamed Bouguessa, Shengrui Wang, Haojun Sun
Venue: Pattern Recognition Letters (2006)

Cluster validation is a major issue in cluster analysis. Many existing validity indices do not perform well when clusters overlap or there is significant variation in their covariance structure. The contribution of this paper is twofold. First, we propose a new validity index for fuzzy clustering. Second, we present a new approach for the objective evaluation of validity indices and clustering algorithms. Our validity index makes use of the covariance structure of clusters, while the evaluation approach utilizes a new concept of overlap rate that gives a formal measure of the difficulty of distinguishing between overlapping clusters. We have carried out experimental studies using data sets containing clusters of different shapes and densities and various overlap rates, in order to show how validity indices behave when clusters become less and less separable. Finally, the effectiveness of the new validity index is also demonstrated on a number of real-life data sets.
A robust variable step size LMS-type algorithm: analysis and simulations
Authors: K. Mayyas, T. Aboulnasr
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

The paper presents a robust variable step size LMS-type algorithm with the attractive property of achieving a small final misadjustment while providing fast convergence at early stages of adaptation. The performance of the algorithm is not affected by the presence of noise. Approximate analysis of convergence and steady state performance for zero-mean stationary Gaussian inputs and a nonstationary optimal weight vector is provided. Simulation results clearly indicate its superior performance for stationary cases. For the nonstationary environment, the algorithm provides performance equivalent to that of the regular LMS algorithm.
A novel ball detection framework for real soccer video
Authors: Xinguo Yu, Qi Tian
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

Despite a lot of research efforts in sports video analysis, soccer video indexing remains a challenging task due to the lack of structure in a soccer game that could help in structure analysis. In particular, little work was done in detecting and tracking the ball whose trajectory could play a crucial role for detecting key events. We propose a novel framework for accurately detecting the ball for broadcast soccer video. Our framework combines both direct and indirect insights to identify the ball rather than conventional simple template matching methods. It has three key components. First we infer the ball size range from the player size. Next non-ball objects are removed to reduce the possible ball candidates. Last but not least, a Kalman filer-based procedure mines candidate trajectories in candidate feature images. Then, a procedure selects the reliable ball trajectories from them. The experimental results on two 1000-frame sequences confirm that the proposed framework is very effective and obtain a better result than existing methods.
Adaptive line enhancement using a second-order IIR filter
Authors: H. J. W. Belt, A. C. den Brinker, F. P. A. Benders
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

A second-order IIR filter is considered as the basic component of an adaptive line enhancer (ALE). As a new feature, the bandwidth of the proposed ALE is adapted simultaneously with the center frequency. This leads to the possibility of combining the convergence speed and accuracy. The adaptation of the filter poles is controlled by a sign algorithm. The step sizes are chosen such that transients caused by the retuning of the filter are ensured to remain much smaller in amplitude than the response of the filter to the input signal. When the input signal consists of a sinusoid corrupted by wideband noise, an accurate frequency parameter estimate can be obtained with the algorithm given in the paper.
Towards an operation model for generated web applications
Authors: Mihály Jakob, Holger Schwarz, Fabian Kaiser, Bernhard Mitschang
Venue: Workshop proceedings of the sixth international conference on Web engineering (2006)

This paper describes a new approach for the development of data-intensive web applications that depend on non-trivial data manipulation. E-Commerce web sites, on-line auction systems and large enterprise web portals fall into this category, as they require comprehensive data access, data processing and data manipulation capabilities. However, existing methodologies mainly concentrate on modeling content, navigation and presentation aspects of read-only web sites. Approaches that consider modeling data operations incorporate them into existing models resulting in a less clear design. We argue that existing models are not sufficient to express complex operations that access or modify web application content. Therefore, we propose an additional Operation Model defining operations for data-intensive web applications. We also propose the utilization of a web application generator to create an Operation Layer based on this Operation Model.
Efficient importance sampling heuristics for the simulation of population overflow in Jackson networks
Authors: Victor F. Nicola, Tatiana S. Zaburnenko
Venue: Proceedings of the 37th conference on Winter simulation (2005)

In this paper we propose state-dependent importance sampling heuristics to estimate the probability of population overflow in Jackson networks with arbitrary routing. These heuristics approximate the "optimal" state-dependent change of measure without the need for costly optimization involved in other recently proposed adaptive algorithms. Experimental results on tandem, feed-forward and feed-back networks with a moderate number of nodes yield asymptotically efficient estimates (often with bounded relative error) where no other state-independent importance sampling techniques are known to be efficient.
Reconstruction of permittivity profile from boundary capacitance data
Authors: Weifu Fang
Venue: Applied Mathematics and Computation (2006)

We present numerical methods of reconstructing permittivity profile of material flow from data collected in electrical capacitance tomography (ECT). Based on a formula for the sensitivity maps from a partial differential equation model, we propose a unified framework of iterative algorithms using updated sensitivity maps to properly incorporate the non-linear nature of the problem and a regularization mechanism to address the ill-posedness. For two- and three-phase flows, the total variation (TV) regularization method is shown to be effective in reconstructing the permittivity profiles accurately in a few iterations, without any a priori knowledge of the unknown permittivity values.
Distributed problem-based learning at Southern Illinois University School of Medicine
Authors: Terri Cameron, Howard S. Barrows, Steven M. Crooks
Venue: Proceedings of the 1999 conference on Computer support for collaborative learning (1999)

SIU School of Medicine piloted a Distributed Problem-Based Learning (DPBL) project in Spring 1999 to support the authentic PBL method used in the curriculum. The pilot included face-to-face (FTF) tutor group sessions augmented by DPBL in which the group participated from distributed sites.The pilot provided a list of observations including: the changes in the role of the facilitator, the feeling by students that information presented during DPBL was more likely to be more well thought-out and articulated than in face-to-face sessions, the value of being able to review session transcripts and whiteboards from any time and place, and the feeling that all students could respond to queries.Technological issues include Internet Service Provider (ISP) responsibility, collaborative software functionality, presentation of the problem in a way that supports free inquiry, submission of resources to the web site, and data collection.Future plans include platform-independent software, a database for collection of data as information is entered on the whiteboard, a database that presents the problem in a more intuitive, responsive manner, and a web page that allows resource submission by group members.
Fast model-based penetration testing
Authors: Sankalp Singh, James Lyons, David M. Nicol
Venue: Proceedings of the 36th conference on Winter simulation (2004)

Traditional approaches to security evaluation have been based on penetration testing of real systems, or analysis of formal models of such systems. The former suffer from the problem that the security metrics are based on only a few of the possible paths through the system. The latter suffer from the inability to analyze detailed system descriptions due to the rapid explosion of state space sizes, which render the models intractable for tools such as model checkers. We propose an approach to obtain statistically valid estimates of security metrics by performing repeated penetration testing of detailed system models. We make use of importance sampling techniques to help reduce the variance of our estimates, and achieve relative error bounds quickly. We validate our approach by estimating security metrics of a large model with more than 21700 possible states.
Subspace estimation using unitary Schur-type methods
Authors: J. Gotze, M. Haardt, J. A. Nossek
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

This paper presents efficient Schur-type algorithms for estimating the column space (signal subspace) of a low rank data matrix corrupted by additive noise. Its computational structure and complexity are similar to that of an LQ-decomposition, except for the fact that plane and hyperbolic rotations are used. Therefore, they are well suited for a parallel (systolic) implementation. The required rank decision, i.e., an estimate of the number of signals, is automatic, and updating as well as downdating are straightforward. The new scheme computes a matrix of minimal rank which is /spl gamma/-close to the data matrix in the matrix 2-norm, where /spl gamma/ is a threshold that can be determined from the noise level. Since the resulting approximation error is not minimized, critical scenarios lead to a certain loss of accuracy compared to SVD-based methods. This loss of accuracy is compensated by using unitary ESPRIT in conjunction with the Schur-type subspace estimation scheme. Unitary ESPRIT represents a simple way to constrain the estimated phase factors to the unit circle and provides a new reliability test. Due to the special algebraic structure of the problem, all required factorizations can be transformed into decompositions of real-valued matrices of the same size. The advantages of unitary ESPRIT dramatically improve the resulting subspace estimates, such that the performance of unitary Schur ESPRIT is comparable to that of SVD-based methods, at a fraction of the computational cost. Compared to the original Schur method, unitary Schur ESPRIT yields improved subspace estimates with a reduced computational load, since it is formulated in terms of real-valued computations throughout.
The Oversea Investment Decision of a Horizontally Integrated Multinationals--A Research in View of the Monopolistic Competition Frame
Authors: Yan-bo Zhang, Yan-hui Wang
Venue: Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (2006)

This paper investigates the following factors: (1) population scale;(2) income level;(3) the expenditure proportion on industrial products;(3) wages level;(5) transaction costs;(6) elasticity of substitution;(7) marginal costs, which functions acted on the horizontal FDI scale of host country from developed country in a monopolistic competition model composed of the developed country enterprises and the host country enterprises. On this foundation trying to study whether the developing country can keep on to draw on more and more horizontal FDI. This paper mainly concludes the following: Horizontal FDI flows to the flourishing countries and regions which economic development levels reach to a certain stage from developed countries generally, but the change of transaction costs would influence the location to horizontal FDI. When the transaction cost is bigger, the horizontal FDI also may be thrown to comparatively less developed countries and regions. In a certain period, the market scale of the host country is an important factor to choose location for horizontal FDI. Under the conditions for horizontal FDI entering into, as long as the growth speed of market scale is bigger than it of production cost, the host country can draw on horizontal FDI constantly. Because of the diversified characteristics of the economic development stage, China should choose and arrange in pairs or groups effectively when China makes use of the special policy to draw on foreign direct investments. For eastern littoral it is good to adopt general foreign direct investment policy to attract horizontal FDI, but not to adopt encouraging preferential policies. For the Midwestern it is good to adopt special pertinent preferential policy to promote vertical FDI steps transfer to the Midwest from the eastern littoral.
Application of Social Network Analysis to Collaborative Team Formation
Authors: Michelle Cheatham, Kevin Cleereman
Venue: Proceedings of the International Symposium on Collaborative Technologies and Systems (2006)

Team formation is a challenging problem in many large organizations in which it is entirely possible for two individuals to work on similar projects without realizing it. By applying social network analysis to mappings of co-authors and to mappings of related research paper keywords, we are able to help generate teams of diverse individuals with similar interests and aptitudes.
Awareness as a vital ingredient of teamwork
Authors: Barbara Dunin-Kȩplicz, Rineke Verbrugge
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

For successful coordination and cooperation in a multiagent system, participants need to establish a sufficiently accurate awareness of the current situation. Awareness is understood here as a limited form of consciousness: in the minimal form, it refers to the state of an agent's beliefs about itself, about others and about the environment. When considered in the context of agents' mental states, this leads to distinguishing three levels of awareness: intra-personal (about the agent itself), inter-personal (about other agents as individuals), and group awareness.Problems in modeling agents' awareness on all three levels are analyzed. It turns out that both the communication medium and agents' cognitive and computational limitations make the achievement of awareness difficult. Cognitive science is used to analyze and explain problems in human awareness, based on the concept of bounded rationality. The BDI framework, originally designed to formally define agents' informational and motivational attitudes, turns out to be also fruitful both for precisely formulating the problems concerning agents' awareness, and, even more importantly, for formulating and comparing possible solutions. Thus, the two fields of cognitive science and MAS mutually benefit from each other's viewpoints, especially in the light of the currently growing need for teamwork in which both computational agents and humans are involved.In this paper, some possible avenues to solutions for defining and achieving appropriate levels of awareness are suggested. In some cases, these are concrete formal solutions, which have been adopted in our theory of collective motivational attitudes, presented in a number of conference and journal papers [5, 6, 7]. They give rise to more generic solutions that can be of use in any advanced BDI system, especially in those aiming to realize teamwork.
Efficient Fuzzy Rules For Classification
Authors: Myung Won Kim, Ara Khil, Joung Woo Ryu
Venue: Proceedings of the International Workshop on on Integrating AI and Data Mining (2006)

Fuzzy rules are suitable for describing uncertain phenomena and natural for human understanding and they are, in general, efficient for classification. In this paper, we propose an optimized fuzzy rule generation method for classification both in accuracy and comprehensibility (or rule complexity). We investigate the use of genetic algorithm to determine an optimal set of membership functions for quantitative data. In our method, for a given set of membership functions a fuzzy decision tree is constructed and its accuracy and rule complexity are evaluated, which are combined into the fitness function to be optimized. We have experimented our algorithm with several benchmark data sets. The experiment results show that our method is more efficient in performance and compactness of rules compared with the existing methods.
Optimistic Coarse-Grained Cache Semantics for Data Marts
Authors: Maik Thiele, Jens Albrecht, Wolfgang Lehner
Venue: Proceedings of the 18th International Conference on Scientific and Statistical Database Management (2006)

Data marts and caching are two closely related concepts in the domain of multi-dimensional data. Both store precomputed data to provide fast response times for complex OLAP queries, and for both it must be guaranteed that every query can be completely processed. However, they differ extremely in their update behaviour which we utilise to build a specific data mart extended by cache semantics. In this paper, we introduce a novel cache exploitation concept for data marts - coarse-grained caching - in which the containedness check for a multi-dimensional query is done through the comparison of the expected and the actual cardinalities. Therefore, we subdivide the multi-dimensional data into coarse partitions, the so called cubletets, which allow to specify the completeness criteria for incoming queries. We show that during query processing, the completeness check is done with no additional costs.
Tracing and Managing hazardous material in Sensor Networks
Authors: Ronny Fehling
Venue: Proceedings of the International Conference on Systems and Networks Communication (2006)

This paper will look at a real world project in the field of hazardous material management and how sensor networks can efficiently help to increase safety and security as well as autonomously enable sophisticated application integration. We will introduce a Sensor Data Model that is able to handle the avalanche of sensor data by organizing, analyzing and correlating sensor data by using Zones and complex event processing. The model uses state-awareness for a truly event driven architecture.
A hub covering model for cargo delivery systems
Authors: Pinar Z. Tan, Bahar Y. Kara
Venue: Networks (2007)

The hub location problem appears in a variety of applications including airline systems, cargo delivery systems, and telecommunication network design. When we analyze the application areas separately, we observe that each area has its own characteristics. In this research we focus on cargo delivery systems. Our interviews with various cargo delivery firms operating in Turkey enabled us to determine the constraints, requirements, and criteria of the hub location problem specific to the cargo delivery sector. We present integer programming formulations and large-scale implementations of the models within Turkey. The results are compared with the current structure of a cargo delivery firm operating in Turkey. &copy; 2006 Wiley Periodicals, Inc. NETWORKS, Vol. 49(1), 28&ndash;39 2007
Towards Effective Unbiased Automated Feature Selection
Authors: Kuncup Iswandy, Andreas Koenig
Venue: Proceedings of the Sixth International Conference on Hybrid Intelligent Systems (2006)

The selection of relevant and non-redundant features or variables from a larger set is an ubiquitous problem in many disciplines. Numerous automated methods have been introduced, however, the important issue of selection stability is still largely uncovered. It can be observed, that small changes in the data can lead to dramatic changes in the selection. This compromises both statistical reliability and recognition rates as well as knowledge extraction. In our work, we pursue an approach employing data sampling techniques, e.g., leave-one-out method, and generate statistics of selection to determine a stability factor and identify stable features. In this paper, we introduce improved selection techniques from first and second order statistics and demonstrate their effectiveness for three benchmark problems of increasing complexity.
Simulation-based pricing of mortgage-backed securities
Authors: Jian Chen
Venue: Proceedings of the 36th conference on Winter simulation (2004)

Mortgage-Backed-Securities (MBS), as the largest investment class of fixed income securities, have always been hard to price. Because of the following reasons, normal numerical methods like lattice methods, or finite difference method for solving PDEs are hard to apply: 1) the path dependence of mortgage pool cash flows. 2) the embedded American call option to prepay. 3) the American put option to default. 4) the fact that mortgage borrower do not/cannot exercise these option optimally. And those reasons make Monte Carlo simulation the best approach to price MBS. A standard MBS pricing framework would consists the following parts: 1) Interest Rate model. 2) Prepayment model, which consists house turnover model and refinance model. 3) OAS model, which captures risk factors from the market price. Those factors are not accounted for in the previous two models. In order to hedge MBS efficiently and effectively, we need to calculate hedging measures quickly and correct. Chen and Fu (2001, 2002, 2003) has developed some efficient hedging algorithm in the past to perform this task.
Automatic Synchronization between Lyrics and Music CD Recordings Based on Viterbi Alignment of Segregated Vocal Signals
Authors: Hiromasa Fujihara, Masataka Goto, Jun Ogata, Kazunori Komatani, Tetsuya Ogata, Hiroshi G. Okuno
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

This paper describes a system that can automatically synchronize between polyphonic musical audio signals and corresponding lyrics. Although there were methods that can synchronize between monophonic speech signals and corresponding text transcriptions by using Viterbi alignment techniques, they cannot be applied to vocals in CD recordings because accompaniment sounds often overlap with vocals. To align lyrics with such vocals, we therefore developed three methods: a method for segregating vocals from polyphonic sound mixtures, a method for detecting vocal sections, and a method for adapting a speech-recognizer phone model to segregated vocal signals. Experimental results for 10 Japanese popular-music songs showed that our system can synchronize between music and lyrics with satisfactory accuracy for 8 songs.
Service Oriented Design Methodologies for Mobile Applications
Authors: I. T. Hawryszkiewycz, R. Steele
Venue: Proceedings of the International Conference on Mobile Business (2006)

There is an increase in the use of mobile devices in business applications. However, mobile support services in such applications generally are usually not strongly integrated with business functions and mobility is often seen as an add-on capability. Consequently the use of mobile devices is often ad-hoc in nature and not closely integrated into the application. This paper describes a way to identify reusable services to support mobility in business applications. It emphasis that integration must support mobility within the application context and concentrates on setting up context sensitive communications in mobile environments.