ppxscal/embedding_network huggingface dataset:
Top-Down Induction of Relational Model Trees in Multi-instance Learning
Authors: Annalisa Appice, Michelangelo Ceci, Donato Malerba
Venue: Proceedings of the 18th international conference on Inductive Logic Programming (2008)

(Multi-)relational regression consists of predicting continuous response of target objects called reference objects by taking into account interactions with other objects called task-relevant objects. In relational databases, reference objects and task-relevant objects are stored in distinct data relations. Interactions between objects are expressed by means of (many-to-one) foreign key constraints which may allow linking explanatory variables of a task-relevant object in several alternative ways to the response variable. By materializing multiple assignments in distinct attribute-value vectors, a reference object is represented as a bag of multiple instances, although there is only one response value for the entire bag. This works points out the same assumption of multi-instance learning that is a primary instance is responsible for the observed response value of a reference object. We propose a top-down induction multi-relational model tree system which navigates foreign key constraints according to a divide-and-conquer strategy, derives a representation of reference objects as bags of attribute-value vectors and then, for each bag, constructs a primary instance as main responsible of the response value. Coefficients of local hyperplane are estimated in an EM implementation of the stepwise least square regression. Experiments confirm the improved accuracy of our proposal with respect to traditional attribute-value and relational model tree learners.
Theories and Ordinals: Ordinal Analysis
Authors: Michael Rathjen
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

How do ordinals gauge the strength and computational power of theories and what kind of information can be extracted from this correlation? This will be the guiding question of this talk. The connection between ordinal representation systems and theories is established in ordinal analysis, a central area of proof theory. The origins of proof theory can be traced back to the second problem on Hilbert's famous list of problems, which called for a proof of consistency of the arithmetical axioms of the reals.
Are all american women making progress online? african--americans and latinas
Authors: Caroline Tolbert, Karen Mossberger, Bridgett King, Gena L. Miller
Venue: Information Technologies and International Development (2008)

Although the gender gap online has narrowed in the United States, little research on technology access and use has examined the different experiences of women---particularly the interaction between gender, race/ethnicity, and poverty. Using the most recent comprehensive survey of technology use and access, the 2003 Current Population Survey, we find new evidence of diminishing gender disparities overall, differences between African--American women and Latinas in the factors that influence technology access and use, and some indications that minority women outpace their male peers online. However, substantial disadvantages for minority women remain, driven by inequalities in education and income. We find evidence that while there is virtually no gender gap in technology access between White men and women, there is a gender divide among minority populations, but women are not unilaterally disadvantaged.
Heterogeneity and Endogenous Nonlinearity in an Artificial Stock Model
Authors: Hongquan Li, Wei Shang, Shouyang Wang
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

We present a nonlinear structural stock market model which is a nonlinear deterministic process buffeted by dynamic noise. The market is composed of two typical trader types, the rational fundamentalists believing that the price of an asset is determined solely by its fundamental value and the boundedly rational noise traders governed by greed and fear. The interaction among heterogeneous investors determines the dynamics and the statistical properties of the system. We find the model is able to generate time series that exhibit dynamical and statistical properties closely resembling those of the S P500 index, such as volatility clustering, fat tails (leptokurtosis), autocorrelation in square and absolute return, larger amplitude, crashes and bubbles. We also investigate the nonlinear dependence structure in our data. The results indicate that the GARCH-type model cannot completely account for all nonlinearity in our simulated market, which is thus consistent with the results from real markets. It seems that the nonlinear structural model is more powerful to give a satisfied explanation to market behavior than the traditional stochastic approach.
Collisions for Round-Reduced LAKE
Authors: Florian Mendel, Martin Schläffer
Venue: Proceedings of the 13th Australasian conference on Information Security and Privacy (2008)

LAKE is a family of cryptographic hash functions presented at FSE 2008. It is an iterated hash function and defines two main instances with a 256 bit and 512 bit hash value. In this paper, we present the first security analysis of LAKE. We show how collision attacks, exploiting the non-bijectiveness of the internal compression function of LAKE, can be mounted on reduced variants of LAKE. We show an efficient attack on the 256 bit hash function LAKE-256 reduced to 3 rounds and present an actual colliding message pair. Furthermore, we present a theoretical attack on LAKE-256 reduced to 4 rounds with a complexity of 2109. By using more sophisticated message modification techniques we expect that the attack can be extended to 5 rounds. However, for the moment our approach does not appear to be applicable to the full LAKE-256 hash function (with all 8 rounds).
Advancing public sector performance analysis
Authors: Carolyn J. Heinrich
Venue: Applied Stochastic Models in Business and Industry (2008)

Recent reforms intended to promote more accountable and responsive government have increased public attention to performance analysis and accelerated the production and use of information on agency performance and public program outcomes. Drawing from cases and empirical studies, this presentation considers questions about what should count as evidence, how it should be communicated, who should judge the quality and reliability of evidence and performance information, and how to achieve a balance between processes that produce rigorous information for decision making and those that foster democratic governance and accountability. Promising directions are suggested for efforts to improve government effectiveness through the use of more rigorous information in decision making, along with acknowledgment of the limitations and risks associated with such efforts. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Prediction of a Go/No-go Decision from Single-Trial Activities of Multiple Neurons in Monkey Superior Colliculus
Authors: Ryohei P. Hasegawa, Yukako T. Hasegawa, Mark A. Segraves
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

The purpose of this study was to develop an algorithm capable of transforming neural activity to correctly report behavioral outcome during a cognitive task. We recorded from small groups of 2-5 neurons in the superior colliculus (SC) while monkeys performed a go/no-go task. Depending upon the color of a peripheral stimulus, the monkey was required to either make a saccade to the stimulus (go) or maintain fixation (no-go). In order to replicate the progress of the decision-making process and generate a virtual decision function (VDF), we performed a multiple regression analysis, with 1 msec resolution, on neuron activity during individual trials. Post hoc analyses by VDF predicted the monkey's choice with nearly 90% accuracy. These results suggest that monitoring of a limited number of SC neurons has sufficient capacity to predict go/no-go decisions on a trial-by-trial basis, and serves as an ideal candidate for a cognitive brain-machine interface (BMI).
Dimensionality Reduction for Classification
Authors: Frank Plastria, Steven Bruyne, Emilio Carrizosa
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

We investigate the effects of dimensionality reduction using different techniques and different dimensions on six two-class data sets with numerical attributes as pre-processing for two classification algorithms. Besides reducing the dimensionality with the use of principal components and linear discriminants, we also introduce four new techniques. After this dimensionality reduction two algorithms are applied. The first algorithm takes advantage of the reduced dimensionality itself while the second one directly exploits the dimensional ranking. We observe that neither a single superior dimensionality reduction technique nor a straightforward way to select the optimal dimension can be identified. On the other hand we show that a good choice of technique and dimension can have a major impact on the classification power, generating classifiers that can rival industry standards. We conclude that dimensionality reduction should not only be used for visualisation or as pre-processing on very high dimensional data, but also as a general pre-processing technique on numerical data to raise the classification power. The difficult choice of both the dimensionality reduction technique and the reduced dimension however, should be directly based on the effects on the classification power.
Numerical study of two problems in fluid flow: cavitation and cerebral circulation
Authors: Pierre A. Gremaud
Venue:  (2008)

Two different computational models of fluid flow are considered. First, the possibility of cavitation is investigated numerically in two and three dimensions for the spherically symmetric, barotropic, Navier-Stokes equations. A splitting method is derived in order to allow the use of known solutions to the corresponding inviscid Euler equations. Results indicate cavitation is possible in the presence of high Mach numbers. This work is intended to be a stepping off point in the search for analytic solutions showing cavitation in multi-dimensional compressible flows. Second, a blood flow model for circulation in the Circle of Willis (CoW) is derived. It is calibrated using ensemble Kalman filtering and validated against clinical data. The resulting model is then used to predict the effects of common anatomical variations within the CoW on blood perfusion in the brain, both under normal circumstances and in the event of a stroke.
JEOPARD: Java environment for parallel real-time development
Authors: Fridtjof Siebert
Venue: Proceedings of the 6th international workshop on Java technologies for real-time and embedded systems (2008)

Multicore systems have become standard for desktop computers today and current operating systems and software development tools provide straightforward means to use the additional computing power. However, a more fundamental change in the design and development of software is required to fully exploit the power of multicore systems. Furthermore, the fast growing market of embedded systems is currently largely unaffected by the introduction of multicore systems. This will change quickly in the future, which will mean that there will be a demand on efficient development of reliable embedded software that can give real-time guarantees and exploit the available power on multicore systems. The JEOPARD project addresses this demand by developing software tools to exploit multicore power while ensuring correctness and predictable timing.
Use of Protein Ontology to Enable Data Exchange for Complex Proteomic Experiments
Authors: Amandeep S. Sidhu, Tharam S. Dillon, Elizabeth Chang
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Ontologies and controlled vocabularies are being established by many groups to provide roadmaps through the confused mass of data currently being generated from increasingly large-scale experimental biological experiments. The world of protein chemistry is no exception to this rule, with Protein Ontology (PO) having lead the field by providing a framework in which individual molecules and complexes can be defined by their structure, function and cellular location. PO performs searches across the protein databases using a standard nomenclature consistent to all entries.
FTTH-Enhanced Mini-System m TBCP-Based Overlay Construction and Evaluation
Authors: Mi-Young Kang, Omar F. Hamad, Choung-Ung Pom, Ji-Seung Nam
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

For better performance and to avoid member service annoyance that results due to joining-clients' waiting durations and time-outs when there are more than one clients wanting to join concurrently for FTTH-based Broadcasting Mini-system's service, this paper proposes a more efficient and better performing Overlay Tree Building Control Protocol by modifying and extending the basic mechanisms building the conventional TBCP. The modified-TBCP (mTBCP) proposed is performance-effective mechanism since it considers the case of how fast will children, concurrently, find and join new parents when paths to existing parents are broken. Besides utilizing partial topology information, mTBCP also does a LAN-out-degree-check. If the selected child-parent-pair falls under the same LAN, that selected parent does not change the out-degree status. The performance comparison, in terms of Overlay-Connection-Count and Latency against Group-Size-Growth, between the proposed mTBCP and the traditional TBCP is done through simulations and the results conclude in favour of the proposed mTBCP.
Blended GIS Studies Model the Work of a Forest Expert
Authors: Markus Holopainen, Teppo Hujala, Juhana Nieminen
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

Geoinformatics is a science involved with spatial data and spatial geographic information systems (GIS). At the Helsinki University Faculty of Agriculture and Forestry geoinformatics is widely practised in both the forest and agricultural sciences. Opportunities offered by the Web and the principles of research-orientated tuition have constituted the basis on which the planning and implementation of geoinformatics curricula have been carried out. The concept of blended tuition provides the means to combine these views in a consistent guideline. Tuition strives for pedagogical appropriateness by integrating local, remote and mobile studies into the learning environment, as well as activities resulting in research information. Here we present those blended tuition components and accumulative phases currently found in geoinformatics curricula. Our case further highlights activities for increasing student and tutor motivation and commitment to apply blended studies.
Fourier Spectral Solver for the Incompressible Navier-Stokes Equations with Volume-Penalization
Authors: G. H. Keetels, H. J. Clercx, G. J. Heijst
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

In this study we use a fast Fourier spectral technique to simulate the Navier-Stokes equations with no-slip boundary conditions. This is enforced by an immersed boundary technique called volume-penalization. The approach has been justified by analytical proofs of the convergence with respect to the penalization parameter. However, the solution of the penalized Navier-Stokes equations is not smooth on the surface of the penalized volume. Therefore, it is not a priori known whether it is possible to actually perform accurate fast Fourier spectral computations. Convergence checks are reported using a recently revived, and unexpectedly difficult dipole-wall collision as a test case. It is found that Gibbs oscillations have a negligible effect on the flow evolution. This allows higher-order recovery of the accuracy on a Fourier basis by means of a post-processing procedure.
Effects of performance feedback on users' evaluations of an interactive IR system
Authors: Diane Kelly, Chirag Shah, Cassidy R. Sugimoto, Earl W. Bailey, Rachael A. Clemens, Ann K. Irvine, Nicholas A. Johnson, Weimao Ke, Sanghee Oh, Anezka Poljakova, Marcos A. Rodriguez, Megan G. van Noord, Yan Zhang
Venue: Proceedings of the second international symposium on Information interaction in context (2008)

In this study, we seek to understand how providing feedback to users about their performances with an interactive information retrieval (IIR) system impacts their evaluations of that system. Sixty subjects completed three recall-based searching tasks with an experimental IIR system and were asked to evaluate the system after each task and after finishing all three tasks. Before completing the final evaluation, three-fourths of the subjects were provided with feedback about their performances. Subjects were assigned randomly to one of four feedback conditions: a baseline condition where no feedback was provided; an actual feedback condition where subjects were provided with their real performances; and two conditions where subjects were deceived and told that they performed very well or very poorly. Results show that the type of feedback provided significantly affected subjects' system evaluations; most importantly there was a significant difference in subjects' satisfaction ratings before and after feedback was provided in the actual feedback condition.
A Novel Vehicle Tracking and Recognition System Based on Edge Line Segment Set Matching
Authors: Tan Liu, Mei Xie
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 2 - Volume 02 (2008)

Image line segment feature is sparse and directional, and can facilitate the analysis of some specific geometric features and patterns. A novel vehicle target motion estimation and recognition method based on target edge line segment feature is introduced. This method includes a series of algorithms using segments as the basic elements of calculation. At first the definition of the similarities of the segment sets is presented. Then the motion estimation and target recognition algorithms are introduced. The key idea of the method is to use the similarity of segment sets as the measurement of target matching. Experimental results show significant advantages of this method, including improved efficiency, less memory requirement and better adaptiveness, over some traditional pixel-value-based algorithms in some situations.
Electric field-enhanced metal-induced lateral crystallization and P-channel poly-Si TFTs fabricated by it
Authors: Xiangbin Zeng, Huijuan Wang, Xiaowei Sun, Junfeng Li
Venue: Microelectronics Journal (2008)

The poly-Si thin film was obtained by electric field-enhanced metal-induced lateral crystallization technique at low temperature. Raman spectra, X-ray diffraction (XRD) and scan electron microscope (SEM) were used to analyze the crystallization state, crystal structure and surface morphology of the poly-Si thin film. Results show that the poly-Si has good crystallinity, and the electric field has the effect of enhancing the crystallization when DC electric voltage is added to the film during annealing. Secondary ion mass spectroscopy (SIMS) shows that the metal Ni improves the crystallization by diffusing into the a-Si thin film, so the crystallization of the lateral diffused region of Ni is the best. The p-channel poly-Si thin film transistors (TFTs) were fabricated by this large-size grain technique. The I"D"S-V"D"S and the transfer characteristics of the TFTs were measured, from which, the hole mobility of TFTs was 65cm^2/Vs, the on and off current ratio was 5x10^6. It is a promising method to fabricate high-performance poly-Si TFTs at low temperature for applications in AMLCD and AMOLED.
Information Retrieval and Filtering over Self-organising Digital Libraries
Authors: Paraskevi Raftopoulou, Euripides G. Petrakis, Christos Tryfonopoulos, Gerhard Weikum
Venue: Proceedings of the 12th European conference on Research and Advanced Technology for Digital Libraries (2008)

We present iClusterDL, a self-organising overlay network that supports information retrieval and filtering functionality in a digital library environment. iClusterDL is able to handle huge amounts of data provided by digital libraries in a distributed and self-organising way. The two-tier architecture and the use of semantic overlay networks provide an infrastructure for creating large networks of digital libraries that require minimum administration, yet offer a rich set of tools to the end-user. We present the main components of our architecture, the protocols that regulate peer interactions, and an experimental evaluation that shows the efficiency, and the retrieval and filtering effectiveness of our approach.
Operational Semantics of Framed Temporal Logic Programs
Authors: Xiaoxiao Yang, Zhenhua Duan
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

This paper investigates the operational semantics of framed temporal logic programs. To this end, a framed temporal logic programming language called Framed Tempura is employed. The evaluation rules for both the arithmetic and boolean expressions are defined. The semantic equivalence rules for the reduction of a program within a state is formalized. Furthermore, the congruence and transition rules between configurations for the reduction of programs are also specified. Thus, the executable behavior of framed programs can be captured in an operational way. In addition, the consistency of the operational semantics and the minimal model semantics based on model theory is proved.
Predictive Indexing for Position Data of Moving Objects in the Real World
Authors: Yutaka Yanagisawa
Venue: Proceeding sof the international conference on Computational Science and Its Applications, Part I (2008)

We propose a spatial-temporal indexing method for moving objects based on a prediction technique using motion patterns extracted from practical data, such as trajectories of pedestrians. To build an efficient index structure, we conducted an experiment to analyze practical moving objects, such as people walking in a hall. As a result, we found that any moving objects can be classified into just three types of motion characteristics: 1) staying, 2) straight-moving, 3) random walking. Indexing systems can predict highly accurate future positions of each object based on our found characteristics; moreover, the indexing system can build efficient MBRs in the spatial-temporal data structure. To show the advantage of our prediction method over previous works, we conducted an experiment to evaluate the performance of each prediction method.
eGovernment Project Evaluation: An Integrated Framework
Authors: Jianwei Liu, Zsofia Derzsi, Marta Raus, Alexander Kipp
Venue: Proceedings of the 7th international conference on Electronic Government (2008)

Recently, the EU government has put a lot of effort into modernizing its public sectors using advanced information and communication technology (ICT). Together with various universities and research institutes all over the EU, a number of e-government projects are now undertaken under the 6th/7th Research Framework Programme One of the critical issues faced by both researchers and the EU government is how to evaluate and assess the successfulness of such projects. The traditional value assessment methods existing in the business field are not good enough to cope with the issue, as business and government hold different value perspectives and have different concerns. In this paper we present a comparative study of six value assessment frameworks and introduce an integrated value assessment framework that may better serve the purpose. A "value cube" and a "step-by-step" method design are generated for supporting the assessment and a real-life case (the Beer Living Lab) for applying the framework in practice is given.