ppxscal/embedding_network huggingface dataset:
Multi-value Classification of Very Short Texts
Authors: Andreas Heß, Philipp Dopichaj, Christian Maaß
Venue: Proceedings of the 31st annual German conference on Advances in Artificial Intelligence (2008)

We introduce a new stacking-like approach for multi-value classification. We apply this classification scheme using Naive Bayes, Rocchio and kNN classifiers on the well-known Reuters dataset. We use part-of-speech tagging for stopword removal. We show that our setup performs almost as well as other approaches that use the full article text even though we only classify headlines. Finally, we apply a Rocchio classifier on a dataset from a Web 2.0 site and show that it is suitable for semi-automated labelling (often called tagging) of short texts and is faster than other approaches.
An Integrated System Perspective for Multimedia Communication
Authors: Zhihai He
Venue: IEEE MultiMedia (2004)

Reviewed:K.R. Rao, Z.S. Bojkovic, and D.A. Milovanovic, Multimedia Communication Systems: Techniques, Standards, and Networks, Prentice Hall, 2002, $69, 576 pp., ISBN 013031398X. One primary accomplishment of this book is that it presents readers with a clear picture ofmultimedia communication and demystifies the various technologies developed in theinternational standards and research literature.
Case-Based Support for Library Reference Services
Authors: Yen Bui
Venue: Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2007)

This paper reports on the results of the first phase of the development of a knowledge management system that provides assistance to reference librarians. This system would employ the parallel use of expert knowledge and case-based retrieval of similar existing question/answer (QA) pairs. CBR is used to store, organize, and represent these QAs in such a way that they could be offered as suggested solutions. The first phase involves testing the possibility of categorizing reference questions in the knowledge base into case-groups and combining attribute matching with text similarity in the similarity measure. Here, CBR is used in a new field which is not domain-specific, and where the level of variability among the potentially high volume of textual cases can be both major and minor. Questions are used in the similarity measure, and the solutions are the paired answers of the retrieved questions.
Context Visualization for Visual Data Mining
Authors: Mao Lin Huang, Quang Vinh Nguyen
Venue: Visual Data Mining: Theory, Techniques and Tools for Visual Analytics (2008)

Context and history visualization plays an important role in visual data mining especially in the visual exploration of large and complex data sets. The preservation of context and history information in the visualization can improve user comprehension of the exploration process as well as enhance the reusability of mining techniques and parameters to archive the desired results. This chapter presents methodology and various interactive visualization techniques supporting visual data mining in general as well as for visual preservation of context and history information. Algorithms are also described in supporting such methodology for visual data mining in real time.
Fuzzy control of a swells canal system
Authors: Taieb Ben Romdhane, Raouf Ketata, Sofiene Hermi
Venue: Applied Soft Computing (2008)

This work forms a part of the research undertaken on the maritime developments behaviour submitted to the action of sea waves. To succeed in this objective, we have conceived and achieved a system of artificial wave generation in a swells channel (channel of 37.5m of length, 1m of width and 1m of depth). Indeed, the simulation of swells on scale model has many advantages. We can mention the construction of dykes for the protection of ports, the didactic interest of conception and generation of new models of waves and the construction of boat shells. The installed canal has to achieve tests of developments stability in the domain of the maritime hydraulics. Every work or scale model is constituted of several layers of ripraps of shapes and well-determined relative density. Thus, the survey of stability consists in reproducing in similitude (scale 1/20) in the swells canal to observe their effects on the holding of riprap (accumulation of boulder) or the artificial blocks of the scale model. Otherwise, the modelling of the process of swell generation is described by complicated physical laws and requires important means of computation. To solve this problem, we have conceived a system based on fuzzy logic permitting to assure the generation of coherent command data with the statistical parameters characterizing the oceanic waves, and to guarantee its conformity to the model of Pierson Moskowich spectrum.
Finding Total and Partial Orders from Data for Seriation
Authors: Heikki Mannila
Venue: Proceedings of the 19th international conference on Algorithmic Learning Theory (2008)

Ordering and ranking items of different types (observations, web pages, etc.) are important tasks in various applications, such as query processing and scientific data mining. We consider different problems of inferring total or partial orders from data, with special emphasis on applications to the seriation problem in paleontology. Seriation can be viewed as the task of ordering rows of a 0-1 matrix so that certain conditions hold. We review different approaches to this task, including spectral ordering methods, techniques for finding partial orders, and probabilistic models using MCMC methods.Joint work with Antti Ukkonen, Aris Gionis, Mikael Fortelius, Kai Puolamäki, and Jukka Jernvall.
Self-assembly of Decidable Sets
Authors: Matthew J. Patitz, Scott M. Summers
Venue: Proceedings of the 7th international conference on Unconventional Computing (2008)

The theme of this paper is computation in Winfree's Abstract Tile Assembly Model (TAM). We first review a simple, well-known tile assembly system (the "wedge construction") that is capable of universal computation. We then extend the wedge construction to prove the following result: if a set of natural numbers is decidable, then it and its complement's canonical two-dimensional representation self-assemble. This leads to a novel characterization of decidable sets of natural numbers in terms of self-assembly. Finally, we prove that our construction is, in some "natural" sense, optimal with respect to the amount of space it uses.
Can "Something You Know" Be Saved?
Authors: Baris Coskun, Cormac Herley
Venue: Proceedings of the 11th international conference on Information Security (2008)

"Something you know," in the form of passwords, has been the cornerstone of authentication for some time; however the inability to survive replay attack threatens this state of affairs. While "something you know" may always be used in addition to "something you have" we examine whether it can be salvaged as the solo factor for authentication. A recent surge of interest in Challenge Response authentication schemes raises the question whether a secret shared between the user and the server can allow secure access even in the presence of spyware.Our conclusion is negative. Assuming only a limit on the amount that a user can remember and calculate we find that any scheme likely to be usable is too easily brute forced if the attacker observes several logins. This is true irrespective of the details of the scheme. The vital parameter is the number of bits of the secret involved in each bit of the response. When this number is too low the scheme is easily brute-forced, but making it high makes the scheme unworkable for the user. Our conclusion is that single factor "something you know" schemes have a fundamental weakness unless the number of logins the attacker observes can be restricted.
Evaluation of the Growth of Real Estate Financial System Based on BP Neural Network
Authors: Hu Nai-Peng, Tian Jin-Xin
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

Currently, there is little quantitative research on macroscopic real estate finance at home and abroad. Seen from the whole system of real estate finance, this paper chooses 14 main indexes to compose an evaluation index system. Based on the evaluation index system, an error -back-propagation BP network model is built to evaluate the growth of real estate finance. Data of real estate financial system from 1997-2005 are used as train and test samples of BP neural network. After training, the BP neural network is used to evaluate and forecast by simulation. Through the good accuracy of evaluation and forecasting, the model is proved to be very efficient. By comparing the growing difference of two adjacent years and analyzing the related macro financial policies in related years, the running effect of related real estate financial policies in related years is gained. So by using the evaluation model of this paper, decision makers can decide to use what kind of macro adjusting and controlling policies to gain anticipated aim of real estate finance in the future.
Accuracy of higher-order lattice Boltzmann methods for microscale flows with finite Knudsen numbers
Authors: Seung Hyun Kim, Heinz Pitsch, Iain D. Boyd
Venue: Journal of Computational Physics (2008)

Accuracy of the lattice Boltzmann (LB) method for microscale flows with finite Knudsen numbers is investigated. We employ up to the eleventh-order Gauss-Hermite quadrature for the lattice velocities and diffuse-scattering boundary condition for fluid-wall interactions. Detailed comparisons with the direct simulation Monte Carlo (DSMC) method and the linearized Boltzmann equation are made for planar Couette and Poiseuille flows. All higher-order LB methods considered here give improved results as compared with the standard LB method. The accuracy of the LB hierarchy, however, does not monotonically increase with the order of the Gauss-Hermite quadrature at moderate and large Knudsen numbers. The results also show the sensitivity to a quadrature chosen, even when the Gauss-Hermite quadratures have the same order of formal accuracy. Among the schemes investigated here, D2Q16 is the most efficient method and offers a quantitative prediction in the slip and transition regimes. The higher-order LB methods predict the Knudsen layer up to Kn=O(0.1). The Knudsen layer, however, rapidly disappears when the Knudsen number approaches unity due to a finite number of the lattice velocities, while it is still present for Kn=O(1) in the Boltzmann equation. It is also found that the higher-order LB methods adopted here do not capture the asymptotic behavior of the Boltzmann equation at large Knudsen numbers.
An Evolutionary Programming Based SVM Ensemble Model for Corporate Failure Prediction
Authors: Lean Yu, Kin Keung Lai, Shouyang Wang
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

In this study, a multistage evolutionary programming (EP) based support vector machine (SVM) ensemble model is proposed for designing a corporate bankruptcy prediction system to discriminate healthful firms from bad ones. In the proposed model, a bagging sampling technique is first used to generate different training sets. Based on the different training sets, some different SVM models with different parameters are then trained to formulate different classifiers. Finally, these different SVM classifiers are aggregated into an ensemble output using an EP approach. For illustration, the proposed SVM ensemble model is applied to a real-world corporate failure prediction problem.
Simplified Hand Configuration for Object Manipulation
Authors: Salvador Cobos, Manuel Ferre, Javier Ortego, Miguel Angel Sanchéz-Urán
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

This work is focused on obtaining realistic human hand models that are suitable for manipulation tasks. Firstly, a 24 DOF kinematic model of the human hand is defined. This model is based on the human skeleton. Intra-finger and inter-finger constraints have been included in order to improve the movement realism. Secondly, two simplified hand descriptions (9 and 6 DOF) have been developed according to the constraints predefined. These simplified models involve some errors in reconstructing the hand posture. These errors are calculated with respect to the 24 DOF model and evaluated according to the hand gestures. Finally, some criteria are defined by which to select the hand description best suited to the features of the manipulation task.
Lateral Excitation between Dissimilar Orientation Columns for Ongoing Subthreshold Membrane Oscillations in Primary Visual Cortex
Authors: Yuto Nakamura, Kazuhiro Tsuboi, Osamu Hoshino
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

Primary visual cortex (V1) is the first stage of visual information processing; detection of particularly oriented bars. These elemental visual features are sent to higher visual regions including V2, in which their combinations such as "corners" and "junctions" are processed. A recent study has demonstrated that corners and T-junctions could be processed even at the early visual stage (V1), raising the question of why the binding of bars by V1 is necessary. We simulated a V1 neural network model, in which the so-called "orientation-columns" were connected through both excitatory and inhibitory synapses. The lateral excitatory connections contributed not only to binding paired bars constituting corners but also to making membrane oscillations near firing-threshold during ongoing (spontaneous) neuronal activity periods. This ongoing subthreshold neuronal state led to accelerating the reaction speed of neurons to paired bar-stimuli. The lateral inhibitory connections effectively enhanced the selective responsiveness of neurons to the stimuli. We suggest that coordinated lateral excitation and inhibition between orientation-columns in V1 could send angular information such as corners and junctions, presented to retina, rapidly to the next stage V2 for its full and precise analyses.
From Napier to Lucas: The Use of Napier's Bones in Calculating Instruments
Authors: M. R. Williams
Venue: IEEE Annals of the History of Computing (1983)

The paper surveys the development of different types of calculating machines that have used the idea of John Napier's "bones. " After showing how to use the bones, the paper discusses the machines of such mathematicians as Wilhelm Schickard, Samuel Morland, Gaspard Schott, Athanasius Kircher, Edouard Lucas, and Henri Genaille. A newly discovered manuscript by Rene Grillet (from the late seventeenth century) provided the base for a study of Grillet's work and a remarkable arithmetic instrument he invented in 1678, using the idea of Napier's bones.
Efficient Algorithms for SNP Haplotype Block Selection Problems
Authors: Yaw-Ling Lin
Venue: Proceedings of the 14th annual international conference on Computing and Combinatorics (2008)

Global patterns of human DNA sequence variation (haplotypes) defined by common single nucleotide polymorphisms (SNPs) have important implications for identifying disease associations and human traits. Recent genetics research reveals that SNPs within certain haplotype blocks induce only a few distinct common haplotypes in the majority of the population. The existence of haplotype block structure has serious implications for association-based methods for the mapping of disease genes. Our ultimate goal is to select haplotype block designations that best capture the structure within the data.Here in this paper we propose several efficient combinatorial algorithms related to selecting interesting haplotype blocks under different diversity functions that generalizes many previous results in the literatures. In particular, given an m×n haplotype matrix A, we show linear time algorithms for finding all interval diversities, farthest sites, and the longest block within A. For selecting the multiple long blocks with diversity constraint, we show that selecting k blocks with longest total length can be be found in O(nk) time. We also propose linear time algorithms in calculating the all intra-longest-blocks and all intra-k-longest-blocks.
Simulated Emotion in Affective Embodied Agents
Authors: Chris Creed, Russell Beale
Venue: Affect and Emotion in Human-Computer Interaction: From Theory to Applications (2008)

An important strand of research that is often neglected in the field of affective computing is that of how users respond to simulated displays of emotion. We present an overview of the few studies that have explicitly investigated this space and discuss a number of issues related to simulated emotion research. An overview of our own work in this area is then provided, along with forthcoming studies that we plan to conduct. We conclude with a number of suggestions of where future research in this space should focus.
Efficient Adaptive In-Place Radix Sorting
Authors: Amer Al-Badarneh, Fouad El-Aker
Venue: Informatica (2004)

This paper presents a new in-place pseudo linear radix sorting algorithm. The proposed algorithm, called MSL (Map Shuffle Loop) is an improvement over ARL (Maus, 2002). The ARL algorithm uses an in-place permutation loop of linear complexity in terms of input size. MSL uses a faster permutation loop searching for the next element to permute group by group, instead of element by element. The algorithm and its runtime behavior are discussed in detail. The performance of MSL is compared with quicksort and the fastest variant of radix sorting algorithms, which is the Least Significant Digit (LSD) radix sorting algorithm (Sedgewick, 2003).
Structural Analysis of Promoter Sequences Using Grammar Inference and Support Vector Machine
Authors: Robertas Damaševičius
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

Promoters are short regulatory DNA sequences located upstream of a gene. Structural analysis of promoter sequences is important for successful gene prediction. Promoters can be recognized by certain patterns that are conserved within a species, but there are many exceptions which makes the structural analysis of promoters a complex problem. Grammar rules can be used for describing the structure of promoter sequences; however, derivation of such rules is not trivial. In this paper, stochastic L-grammar rules are derived automatically from known drosophila and vertebrate promoter and non-promoter sequences using genetic programming. The fitness of grammar rules is evaluated using a machine learning technique, called Support Vector Machine (SVM). SVM is trained on the known promoter sequences to obtain a discriminating function which serves as a means of evaluating a candidate grammar (a set of rules) by determining the percentage of generated sequences that are classified correctly. The combination of SVM and grammar rule inference can mitigate the lack of structural insight in machine learning approaches such as SVM.
Temporal coding: Assembly formation through constructive interference
Authors: Thomas Burwick
Venue: Neural Computation (2008)

Temporal coding is studied for an oscillatory neural network model with synchronization and acceleration. The latter mechanism refers to increasing (decreasing) the phase velocity of each unit for stronger (weaker) or more coherent (decoherent) input from the other units. It has been demonstrated that acceleration generates the desynchronization that is needed for self-organized segmentation of two overlapping patterns. In this letter, we continue the discussion of this remarkable feature, giving also an example with several overlapping patterns. Due to acceleration, Hebbian memory implies a frequency spectrum for pure pattern states, defined as coherent patterns with decoherent overlapping patterns. With reference to this frequency spectrum and related frequency bands, the process of pattern retrieval, corresponding to the formation of temporal coding assemblies, is described as resulting from constructive interference (with frequency differences due to acceleration) and phase locking (due to synchronization).
Towards a Multicultural ECA Tour Guide System
Authors: Aleksandra Cerekovic, Hung-Hsuan Huang, Igor S. Pandzic, Yukiko Nakano, Toyoaki Nishida
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

In this article we present an ongoing project in our research group, an ECA based multicultural tour guide system. Tour guide ECA agent provides information about the city of Dubrovnik and dynamically changes its behaviors among Japanese, Croatian and general western cultures speaking in English.
Increasing Interpretations
Authors: Harald Zankl, Aart Middeldorp
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

The paper at hand introduces a refinement of interpretation based termination criteria for term rewrite systems in the dependency pair setting. Traditional methods share the property that--in order to be successful--all rewrite rules must (weakly) decrease with respect to some measure. The novelty of our approach is that we allow some rules to increase the interpreted value. These rules are found by simultaneously searching for adequate polynomial interpretations while considering the information of the dependency graph. We prove that our method extends the termination proving power of linear natural interpretations. Furthermore, this generalization perfectly fits the recursive SCC decomposition algorithm which is implemented in virtually every termination prover dealing with term rewrite systems.
The influence of slip condition on thin film flow of a fourth grade fluid by the homotopy analysis method
Authors: M. Sajid, M. Awais, S. Nadeem, T. Hayat
Venue: Computers Mathematics with Applications (2008)

This paper provides an investigation regarding slip effects on thin film flow of a fourth grade fluid down a vertical cylinder. The nonlinear problem that arises is solved for both exact and HAM (homotopy analysis method) solutions. Exact and HAM solutions are also compared. Finally we briefly describe the flow characteristics to include the effects of emerging parameters.
Applications Demand Class-Specific Optimizations: The C++ Compiler Can Do More
Authors: Ian G. Angus
Venue: Scientific Programming (1993)

So far C++ has made few inroads into the realm of scientific computing, which is still largely dominated by Fortran. Of the few attempts that have been made to apply C++ to numerically intensive codes, the results have often suffered from severe performance problems. A careful examination of these problems indicates that they are unlikely to be solved by incremental improvements in compiler optimization technology. The flow of this article will: motivate the discussion by describing a common efficiency problem that arises when numerical codes are programmed in C++; discuss some potential solution strategies that we believe are viable in the near term, but not over the long term; introduce a mechanism by which a compiler can load domain-specific and class-specific optimizations on an as needed basis. A simple interface that will enable this feature will be presented. Althoug our immediate motivation is that of numerically intensive codes, our approach is applicable to all application domains.