ppxscal/embedding_network huggingface dataset:
Batch process modelling with mixtures of Gaussian processes
Authors: Xiaoling Ou, Elaine Martin
Venue: Neural Computing and Applications (2008)

In recent years Gaussian processes have attracted a significant amount of interest with the particular focus being that of process modelling. This has primarily been a consequence of their good predictive performance and inherent analytical properties. Gaussian processes are a member of the family of non-parametric Bayesian regression models and can be derived from the perspective of neural networks. Their behaviour is controlled through the structure of the covariance function. However, when applied to batch processes, whose data exhibits different variance structures throughout the duration of the batch, a single Gaussian process may not be appropriate for the accurate modelling of its behaviour. Furthermore there are issues with respect to the computational costs of Gaussian processes. The implementation of a Gaussian process model requires the repeated computation of a matrix inverse whose order is the cubic of the number of training data points. This renders the algorithm impractical when dealing with large data sets. To address these two issues, a mixture model of Gaussian processes is proposed. The resulting prediction is attained as a weighted sum of the outputs from each Gaussian process component, with the weights determined by a Gaussian kernel gating network. The model is implemented through a Bayesian approach utilising Markov chain Monte Carlo algorithms. The proposed methodology is applied to data from a bench-mark batch simulation polymerization process, methyl methacrylate (MMA), and the results are compared with those from a single Gaussian process to illustrate the advantages of the proposed mixture model approach.
RIPS++ N-Dimensional Array Classes
Authors: A. G. Willis, M. P. Healey, B. E. Glendenning
Venue: Scientific Programming (1993)

This article describes a set of C++ classes developed for the AIPS++ project. These classes handle arrays having an arbitrary number of dimensions. We give an overview of the methods available in these classes and show some simple examples of their use. Finally we describe the use of these classes to develop a radio astronomy application and discuss some of the performance issues that must be considered when these classes are used.
Online and Offline Fingerprint Template Update Using Minutiae: An Experimental Comparison
Authors: Biagio Freni, Gian Luca Marcialis, Fabio Roli
Venue: Proceedings of the 5th international conference on Articulated Motion and Deformable Objects (2008)

Although the template fingerprint collected during the registration phase of personal verification systems can be considered in principle as representative of the subject identity, some recent works pointed out that it is not completely able to follow the intra-class variations of the fingerprint shape. Accordingly, making these systems adaptive to these variations is one of the most interesting problems, and is often called as the "template updating" problem. In this paper, two different approaches for fingerprint template updating are compared by experiments. The first one, already proposed in other works, relies on the concept of "online" template updating, that is, the fingerprint template is updated when the system is operating. As alternative, we propose the "offline" template update, which requires the collection of a representative batch of samples when the system is operating. They concur to the template updating when the system is offline, that is, it is not operating. Preliminary experiments carried out on the FVC data sets allow to point out some differences among the investigated approaches.
Methods for obtaining an operating point sufficiently small signal stable in power systems including wind parks
Authors: P. Ledesma, C. Gallardo
Venue: Proceedings of the 6th WSEAS International Conference on Applied Electromagnetics, Wireless and Optical (2008)

This paper shows a simple approach to obtain an operating point sufficiently small signal stable. In the case of a stable operating point with a poorly damped oscillatory mode, the objective is to increase the damping of that mode. That is, the power system linearization at the operating point is modified. Operator actions such as redispatch, varying load, varying reactive power (voltage) often modify the operating point to do this; the effect of this is that transients near enough to the operating point will decay more quickly. However, the analysis does not attempt the more difficult study of large signal transients. The existence of a stable operating point is of course necessary for system security, but there is no guarantee that large signal transients will result in operation at that operating point.
Discovering Communicable Models from Earth Science Data
Authors: Mark Schwabacher, Pat Langley, Christopher Potter, Steven Klooster, Alicia Torregrosa
Venue: Computational Discovery of Scientific Knowledge: Introduction, Techniques, and Applications in Environmental and Life Sciences (2007)

This chapter describes how we used regression rules to improve upon results previously published in the Earth science literature. In such a scientific application of machine learning, it is crucially important for the learned models to be understandable and communicable. We recount how we selected a learning algorithm to maximize communicability, and then describe two visualization techniques that we developed to aid in understanding the model by exploiting the spatial nature of the data. We also report how evaluating the learned models across time let us discover an error in the data.
Multi-layer Ensemble Classifiers on Protein Secondary Structure Prediction
Authors: Wei Li, Yuehui Chen, Yaou Zhao
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Protein secondary structure prediction is a bridge between amino acid sequence and tertiary prediction. Many methods have been used to improve the prediction accuracy and have a great development. Here a new method to predict the secondary structure is proposed by using classified database. The structure is similar with PSI-PRED method. But in the middle of the two neural network (NN) a neural ensemble is used to divided the initial database into two databases. Then the two databases are input into the next NN separately in order to predict the possible secondary structure. Experiments show that the proposed method achieves an average Q 3 score of 82% in CB396 database and 86% in CB513 database which produces the best prediction accuracy.
Expectation Propagation for Rating Players in Sports Competitions
Authors: Adriana Birlutiu, Tom Heskes
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

Rating players in sports competitions based on game results is one example of paired comparison data analysis. Since an exact Bayesian treatment is intractable, several techniques for approximate inference have been proposed in the literature. In this paper we compare several variants of expectation propagation (EP). EP generalizes assumed density filtering (ADF) by iteratively improving the approximations that are made in the filtering step of ADF. Furthermore, we distinguish between two variants of EP: EP-Correlated, which takes into account the correlations between the strengths of the players and EP-Independent, which ignores those correlations. We evaluate the different approaches on a large tennis dataset to find that EP does significantly better than ADF (iterative improvement indeed helps) and EP-Correlated does significantly better than EP-Independent (correlations do matter).
The Design of Blue Emitting Materials Based on Spirosilabifluorene Derivatives
Authors: Miao Sun, Ben Niu, Jingping Zhang
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

Ground state geometries and electronic properties of four experimentally reported spirosilabifluorene derivatives are calculated by HF(DFT)/6-31G* method. Their first excited state geometries are investigated using CIS/6-31G* method. The absorption and emission spectra are evaluated by TD-B3LYP/6-31G* and show an excellent agreement with the experimental data. The "CH"/N substituted spirosilabifluorene derivatives are also investigated. Compared to the pristine molecule, no significant change of the emission wavelengths are found for the "CH"/N substituted derivatives. Furthermore, we find that the performance and the optical properties of these derivatives can be improved through oligomerization or addition of a phenyl group.
Integrated Decision Algorithms for Auto-steered Electric Transmission System Asset Management
Authors: James Mccalley, Vasant Honavar, Sarah Ryan, William Meeker, Daji Qiao, Ron Roberts, Yuan Li, Jyotishman Pathak, Mujing Ye, Yili Hong
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

Electric power transmission systems are comprised of a large number of physical assets, including transmission lines, power transformers, and circuit breakers, that are capital-intensive, highly distributed, and may fail. Managing these assets under resource constraints requires equipment health monitoring integrated with system level decision-making to optimize a number of various operational, maintenance, and investment-related objectives. Industry processes to these ends have evolved ad-hoc over the years, and no systematic structures exist to coordinate the various decision problems. In this paper, we describe our progress in building a prototype structure for this purpose together with a software-hardware environment to deploy and test it. We particularly focus on the decision algorithms and the Benders approach we have taken to solve them in an integrated fashion.
Experience Report on the Effect of Software Development Characteristics on Change Distribution
Authors: Anita Gupta, Reidar Conradi, Forrest Shull, Daniela Cruzes, Christopher Ackermann, Harald Rønneberg, Einar Landre
Venue: Proceedings of the 9th international conference on Product-Focused Software Process Improvement (2008)

This paper reports on an industrial case study in a large Norwegian Oil and Gas company (StatoilHydro ASA) involving a reusable Java-class framework and an application that uses that framework. We analyzed software changes from three releases of the framework and the application. On the basis of our analysis of the data, we found that perfective and corrective changes account for the majority of changes in both the reusable framework and the non-reusable application. Although adaptive changes are more frequent and has longer active time in the reusable framework, it went through less refactoring compared to the non-reusable application. For the non-reusable application we saw preventive changes as more frequent and with longer active time. We also found that designing for reuse seems to lead to fewer changes, as well as we saw a positive effect on doing refactoring.
A Fuzzy-Based Handover System for Wireless Cellular Networks: A Case Study for Handover Enforcement
Authors: Leonard Barolli, Arjan Durresi, Fatos Xhafa, Akio Koyama
Venue: Proceedings of the 2nd international conference on Network-Based Information Systems (2008)

Presently, the wireless mobile networks and devices are becoming increasingly popular to provide users the access anytime and anywhere. The mobile systems are based on cellular approach and the area is covered by cells that overlap each other. Many handover algorithms are proposed in the literature. However, to make a better handover and keep the QoS in wireless networks is very difficult. In this paper, we propose a new handover system based on fuzzy logic. We consider the case of handover enforcement and verify that the proposed system makes the necessary handovers for all simulations.
Improving BTC image compression using a fuzzy complement edge operator
Authors: T. M. Amarunnishad, V. K. Govindan, Abraham T. Mathew
Venue: Signal Processing (2008)

A simple and easy to implement technique for improving block truncation coding (BTC) is proposed. The method is based on replacement of bit block obtained using the conventional BTC method with the fuzzy logical bit block (LBB) such that the sample mean and standard deviation in each image block are preserved. This fuzzy LBB is obtained from the fuzzy edge image by using the Yager involutive fuzzy complement edge operator (YIFCEO). The input image is encoded with the block mean and standard deviation and the fuzzy LBB. Experimental results show an improvement of visual quality of reconstructed images and peak signal-to-noise ratio (PSNR) when compared to the conventional BTC. The raggedness and jagged appearance and the ringing artifacts at sharp edges are greatly reduced in the reconstructed images. With the use of YIFCEO, the proposed method is shown to be more flexible to determine the visual quality of the reconstructed images.
Distributed Clustering of Autonomous Shipping Containers by Concept, Location, and Time
Authors: Arne Schuldt, Sven Werner
Venue: Proceedings of the 5th German conference on Multiagent System Technologies (2007)

Recent developments in logistics show an increasing trend towards autonomous control. Intelligent software agents, that represent logistic objects like shipping containers, plan and schedule their way through a logistic network. This paper addresses the aspect of cooperation. A special focus lies on the second step of the model for cooperation, namely team formation. The question is by which criteria shipping containers, or logistic objects and agents in general, can form clusters. Starting from the particular demands of the logistics domain this paper argues in favour of conceptual, spatial, and temporal properties. A framework that takes concept, location, and time into account is introduced and demonstrated by an example application.
Rotation Invariant Texture Classification Algorithm Based on DT-CWT and SVM
Authors: Shuzhen Chen, Yan Shang, Bingyi Mao, Qiusheng Lian
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

A rotation invariant texture classification algorithm based on dual-tree complex wavelet transform (DT-CWT) and support vector machines (SVM) is proposed. First, the texture image is transformed by Radon transform to convert the rotation to translation, the rotation invariant feature vector is composed of the energies of the subbands acquired by DT-CWT which is shift invariant to the transformed texture image, the SVM algorithm is used to the texture classification at last. This algorithm is compared with the classifier of probabilistic neural network (PNN) and other rotation invariant texture classification algorithm, the experiment results show that it can improve the classification rate effectively.
Functional-Logic Graph Parser Combinators
Authors: Steffen Mazanek, Mark Minas
Venue: Proceedings of the 19th international conference on Rewriting Techniques and Applications (2008)

Parser combinators are a popular technique among functional programmers for writing parsers. They allow the definition of parsers for string languages in a manner quite similar to BNF rules. In recent papers we have shown that the combinator approach is also beneficial for graph parsing. However, we have noted as well that certain graph languages are difficult to describe in a purely functional way.In this paper we demonstrate that functional-logic languages can be used to conveniently implement graph parsers. Therefore, we provide a direct mapping from hyperedge replacement grammars to graph parsers. As in the string setting, our combinators closely reflect the building blocks of this grammar formalism. Finally, we show by example that our framework is strictly more powerful than hyperedge replacement grammars.We make heavy use of key features of both the functional and the logic programming approach: Higher-order functions allow the treatment of parsers as first class citizens. Non-determinism and logical variables are beneficial for dealing with errors and incomplete information. Parsers can even be applied backwards and thus be used as generators or for graph completion.
Stacking Cost Sensitive Models
Authors: Sotiris Kotsiantis
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

A classifier induced from an imbalanced data set has, typically, a low error rate for the majority class and an unacceptable error rate for the minority class. This paper firstly provides a systematic study on the various methodologies that have tried to handle this problem. Finally, it presents an experimental study of these methodologies with a proposed stacking cost-sensitive ensemble and it concludes that such a framework can be a more effective solution to the problem.
On Second-Order Monadic Groupoidal Quantifiers
Authors: Juha Kontinen, Heribert Vollmer
Venue: Proceedings of the 15th international workshop on Logic, Language, Information and Computation (2008)

We study logics defined in terms of so-called second-order monadic groupoidal quantifiers. These are generalized quantifiers defined by groupoid word-problems or equivalently by context-free languages. We show that, over strings with built-in arithmetic, the extension of monadic second-order logic by all second-order monadic groupoidal quantifiers collapses to its fragment ${{\rm mon-}Q^1_{{\rm Grp}}}{\text{\rm FO}}$. We also show a variant of this collapse which holds without built-in arithmetic. Finally, we relate these results to an open question regarding the expressive power of finite leaf automata with context-free leaf languages.
Speaker Characteristics and Emotion Classification
Authors: Anton Batliner, Richard Huber
Venue: Speaker Classification I: Fundamentals, Features, and Methods (2007)

In this paper, we address the -- interrelated -- problems of speaker characteristics (personalization) and suboptimal performance of emotion classification in state-of-the-art modules from two different points of view: first, we focus on a specific phenomenon (irregular phonation or laryngealization) and argue that its inherent multi-functionality and speaker-dependency makes its use as feature in emotion classification less promising than one might expect. Second, we focus on a specific application of emotion recognition in a voice portal and argue that constraints on time and budget often prevent the implementation of an optimal emotion recognition module.
Dynamic Querying in Structured Peer-to-Peer Networks
Authors: Domenico Talia, Paolo Trunfio
Venue: Proceedings of the 19th IFIP/IEEE international workshop on Distributed Systems: Operations and Management: Managing Large-Scale Service Deployment (2008)

Dynamic Querying (DQ) is a technique adopted in unstructured Peer-to-Peer (P2P) networks to minimize the number of peers that is necessary to visit to reach the desired number of results. In this paper we introduce the use of the DQ technique in structured P2P networks. In particular, we present a P2P search algorithm, named DQ-DHT (Dynamic Querying over a Distributed Hash Table), to perform DQ-like searches over DHT-based overlays. The aim of DQ-DHT is two-fold: allowing arbitrary queries to be performed in structured P2P networks, and providing dynamic adaptation of the search according to the popularity of the resources to be located. This paper describes the DQ-DHT algorithm using Chord as basic overlay and analyzes its performance in comparison with DQ in unstructured networks.
IBM FORTRAN Exhibit and Film
Authors: Daniel N. Leeson
Venue: IEEE Annals of the History of Computing (1984)

The exhibit, which included the film, was intended to commemorate the 25th anniversary of FORTRAN. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A Fuzzy Optimization Method for Multi-criteria Decision-Making Problem Based on the Inclusion Degrees of Intuitionistic Fuzzy Sets
Authors: Changrui Yu, Yan Luo
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

This paper presents a fuzzy optimization method based on the inclusion degrees of intuitionistic fuzzy sets to solve multi-criteria decision making problems under fuzzy environments. First, the inclusion degree of intuitionistic fuzzy sets is defined and a series of specific formulas of inclusion degree are presented by means of the normal implication operators. Some formulas of inclusion degree of intuitionistic fuzzy sets are generalized by defining the cardinal number of intuitionistic fuzzy sets. Then, we give multi-criteria fuzzy decision-making method based on inclusion degree of intuitionistic fuzzy sets. Finally, we illustrate the effectiveness of the method proposed in this paper by an example.
Shape Analysis with Overcomplete Spherical Wavelets
Authors: B. T. Yeo, Peng Yu, P. Ellen Grant, Bruce Fischl, Polina Golland
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

In this paper, we explore the use of over-complete spherical wavelets in shape analysis of closed 2D surfaces. Previous work has demonstrated, theoretically and practically, the advantages of over-complete over bi-orthogonal spherical wavelets. Here we present a detailed formulation of over-complete wavelets, as well as shape analysis experiments of cortical folding development using them. Our experiments verify in a quantitative fashion existing qualitative theories of neuro-anatomical development. Furthermore, the experiments reveal novel insights into neuro-anatomical development not previously documented.
Advances in the Geometrical Study of Rotation-Invariant T-Norms
Authors: Koen C. Maes, Bernard Baets
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

T-norm properties for left-continuous, increasing [0,1]2¿[0,1] functions can be fully described in terms of contour lines. For a left-continuous t-norm T, the rotation-invariance property comes down to the continuity of its contour line C 0. However, contour lines are inadequate to investigate the geometrical structure of these rotation-invariant t-norms. Enforced with the companion and zooms it is possible to totally reconstruct T by means of its contour line C 0 and its β-zoom, with β the unique fixpoint of C 0.
Causal Errors in Distributed Systems
Authors: Nikki Lesley, Holly Hou, Joydeep Mitra
Venue: IEEE Distributed Systems Online (2003)

This article presents a project that analyzes the pattern of causal errors in distributed systems. It asks the question: how wrong could the system be if causal order is not enforced? Simulations of a stock-trading system show that the number of failed trades due to causal errors has minimal impact on the system.