ppxscal/embedding_network huggingface dataset:
Information Overload and FP7 Funding Opportunities in 2009-10
Authors: Stefano Bertolo
Venue: Proceedings of the 18th international conference on Inductive Logic Programming (2008)

Physical tools like the lever and the loom amplify human strength and dexterity and are often introduced, as in the case of the agricultural harvester, because a sudden abundance of one quantity of interest (wheat fields) introduces scarcity in other related quantities (the human labor needed to harvest them). The rate at which digital information is becoming available (both to organisations and individuals) is creating a similar scarcity in our ability to interpret it to make decisions that benefit us. In this talk I will describe funding opportunities that the EU will make available through its Framework Programme 7 to tackle this scarcity. I will discuss several trends that make the ILP community ideally placed to contribute to these efforts, together with some general patterns that have proved very effective in the engineering of successful proposals in the recent past.
Multi-agent Positioning Mechanism in the Dynamic Environment
Authors: Hidehisa Akiyama, Itsuki Noda
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

In this paper, we propose a novel agent positioning mechanism for the dynamic environments. In many problems of the real-world multi-agent/robot domain, a position of each agent is an important factor to affect agents' performance. Because the real-world problem is generally dynamic, a suitable positions for each agent should be determined according to the current status of the environment. We formalize this issue as a map from a focal point like a ball position in a soccer field to a desirable positioning of each player agent, and propose a method to approximate the map using Delaunay Triangulation. This method is simple, fast and accurate, so that it can be implemented for real-time and scalable problems like RoboCup Soccer. The performance of the method is evaluated in RoboCup Soccer Simulation environment compared with other function approximation method like Normalized Gaussian Network. The result of the evaluation tells us that the proposal method is robust to uneven sample distribution so that we can easily to maintain the mapping.
Extracting Information from Flexible Receptor-Flexible Ligand Docking Experiments
Authors: Karina S. Machado, Evelyn K. Schroeder, Duncan D. Ruiz, Ana Wink, Osmar Norberto De Souza
Venue: Proceedings of the 3rd Brazilian symposium on Bioinformatics: Advances in Bioinformatics and Computational Biology (2008)

Recent progress in structural biology and bioinformatics contributed to the increased amount of data that need to be stored and analyzed. Advances in data mining research have allowed the development of efficient methods to find interesting patterns in large databases. In this context, this work proposes a method to automatically extract detailed information from molecular docking experiments. Completely flexible molecular docking studies (including ligand and receptor explicit flexibilities) of the InhA enzyme from Mycobacterium tuberculosis in complex with NADH were performed with AutoDock3.05 using receptor snapshots generated by nanosecond molecular dynamics simulations. To analyze the results we applied our data mining method which was capable of identifying important information about intermolecular interactions and association rules. The method allowed a fast and concise analysis which led to identification of relevant residues and conformations essential to ligand binding.
Partition-Based Parallel Constructing-Density-Tree Clustering
Authors: Yunpeng Zhang, Zhengjun Zhai, Lu Zhang, Yifei Bao, Weidi Dai, Fei Zuo
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

A Parallel Constructing-Density-Tree Clustering Algorithm based on Data Partitioning (PCAP) was presented. The PCAP automatically partitioned global data space into load-balanced subspaces, which were distributed to different processors to complete subspaces’ clustering. The clustering result of global data space was achieved by merging those strong-association clusters though checking the association-intensity of leaves’ similarity. The detailed method of computing the association-intensity between clusters was described. Finally, the relevancy of the speedup and the amount of processors were discussed. The experiment results on artificial and real datasets show PCAP realizes the parallel of constructing-density-tree clustering algorithm and improves the clustering speed efficiently under preserving enough clustering precision. This approach is more suitable for dealing with great amounts of datasets.
Performance of complete and nearly complete binary search trees
Authors: Ahmed Tarek
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

Binary Search Trees are frequently used data structure for rapid access to the stored data. Data structures like arrays, vectors and linked lists are limited by the trade-off between the ability to perform a fast search and resize easily. They are an alternative that is both dynamic in size and easily searchable. This paper addresses the performance analysis and measurement, collectively known as the Performance in complete and nearly complete binary search trees. Performance measurement in complete and nearly complete binary search trees is equally important aside from performance analysis to learn deviation from the optimality. To estimate this deviation, new performance criteria are introduced. A multi-key search algorithm is proposed and the related analysis has followed. The algorithm is capable of searching for multiple key elements in the same execution. This helps in pruning a subtree structure out of a given tree for further processing.
ANN Classification of OMIS Hyperspectral Remotely Sensed Imagery: Experiments and Analysis
Authors: Peijun Du, Kun Tan, Wei Zhang, Zhigang Yan
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

In order to experiment the performance of some popular ANN algorithms to OMIS (Operational Modular Imaging Spectrometer) hyperspectral image, three widely used ANNs, including Back Propagation Neural Network (BPNN), Radial Basis Function Neural Network (RBFNN), Fuzzy ARTMAP network and their improvements, are employed and compared. It is concluded that ANN classifiers perform much better than traditional classifiers such as SAM, MLC and MDC, and RBFNN outperforms BPNN and Fuzzy ARTMAP in terms of classification accuracy. It is also concluded that dimensionality reduction by PCA can be effectively used to feature extraction for hyperspectral image classification.
Helping Teachers Build ITS with Domain Schema
Authors: Brent Martin, Antonija Mitrovic
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

Authoring ITS domain models is a difficult task requiring many skills. Tools such as ASPIRE that model domains using ontology reduce the problem by allowing the author to work at a higher level of abstraction (and thus avoid low-level code writing), but such tools tend to be complex and the task is not intuitive for many people. To overcome this problem we have developed a framework for domain schema: high-level abstractions that describe the semantics of the domain model for a class of domains. Using domain schema reduces the authoring effort to one of describing only those aspects that are unique to this particular domain; the schema provides the rest of the model. We describe the framework we have implemented and give some examples of domain types for which schema have been built.
Performance of reimbursement schemes in valuation of technologies: The example of Magnetic Resonance Imaging
Authors: R. Blankart, J. Schreyögg, R. Busse
Venue: Technology and Health Care (2008)

Different reimbursement schemes for health care providers have been developed worldwide. They have evolved over time and have been influenced by politics, costs, patient needs and technological progress. Different methods in the valuation of technologies and their reflection in outpatient reimbursement schemes are analyzed. Using Magnetic Resonance Imaging (MRI) as an example, five different reimbursement schemes from four countries are compared according to defined performance criteria. Major differences in the structure and valuation of internationally used reimbursement schemes are presented; Prices for Neurocranium MRI scans vary from \psfig{figure=eur.eps,width=1.7mm}98 to \psfig{figure=eur.eps,width=1.7mm}462 and large discrepancies can even be found within the same country. There are politically driven reimbursement schemes like the German Geb&uuml;hrenordnung f&uuml;r 'A'rzte, while others such as the Swiss TARMED are primarily based on actual costs.
Evaluating the Foot Electromyogram Signal as a Noise Reference for a Bathroom Scale Ballistocardiogram Recorder
Authors: Omer T. Inan, Mozziyar Etemadi, Richard M. Wiard, Laurent Giovangrandi, Gregory T. A. Kovacs
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

A bathroom scale ballistocardiogram (BCG) recorder has been developed in our group as a potential home monitor for heart failure outpatients. While the signal quality obtained by this device is as high as elaborate table- and bed-based BCG systems discussed previously in the literature, the standing posture required by this system may lead to undesired motion induced noise in the signal, particularly for elderly patients. Electromyogram (EMG) signals from the feet are proposed as a noise reference for the standing BCG measurement. The correlation between these signals and the BCG noise is quantified for a case with low (eyes open) and higher (eyes closed) involuntary movement on the scale. For the six subjects considered in this trial, the foot EMG appears to be a valuable reference for BCG movement noise estimation. Additionally, the fact that many bathroom scales have electrodes on the feet for various body fat percentage estimates makes the measurement highly practical for future implementations.
Time Series Classification Using Gaussian Mixture Models of Reconstructed Phase Spaces
Authors: Richard J. Povinelli, Michael T. Johnson, Andrew C. Lindgren, Jinjin Ye
Venue: IEEE Transactions on Knowledge and Data Engineering (2004)

A new signal classification approach is presented that is based upon modeling the dynamics of a system as they are captured in a reconstructed phase space. The modeling is done using full covariance Gaussian Mixture Models of time domain signatures, in contrast with current and previous work in signal classification that is typically focused on either linear systems analysis using frequency content or simple nonlinear machine learning models such as artificial neural networks. The proposed approach has strong theoretical foundations based on dynamical systems and topological theorems, resulting in a signal reconstruction, which is asymptotically guaranteed to be a complete representation of the underlying system, given properly chosen parameters. The algorithm automatically calculates these parameters to form appropriate reconstructed phase spaces, requiring only the number of mixtures, the signals, and their class labels as input. Three separate data sets are used for validation, including motor current simulations, electrocardiogram recordings, and speech waveforms. The results show that the proposed method is robust across these diverse domains, significantly outperforming the time delay neural network used as a baseline.
A Communication-Aware Topological Mapping Technique for NoCs
Authors: Rafael Tornero, Juan M. Orduña, Maurizio Palesi, José Duato
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

Networks---on---Chip (NoCs) have been proposed as a promising solution to the complex on-chip communication problems derived from the increasing number of processor cores. The design of NoCs involves several key issues, being the topological mapping (the mapping of the Intellectual Properties (IPs) to network nodes) one of them. Several proposals have been focused on topological mapping last years, but they require the experimental validation of each mapping considered.In this paper, we propose a communication-aware topological mapping technique for NoCs. This technique is based on the experimental correlation of the network model with the actual network performance, thus avoiding the need to experimentally evaluate each mapping explored. The evaluation results show that the proposed technique can provide better performance than the currently existing techniques (in terms of both network latency and energy consumption). Additionally, it can be used for both regular and irregular topologies.
Correspondence Analysis for Exploring the Fulfillment of Coach Systems for Small and Medium Enterprises in Taiwan
Authors: Hua-Kai Chiou, Tse-Jung Chen, Yen-Wen Wang
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

From the economy trace of Taiwan, Small and Medium Enterprises (SMEs) encompassed 98% of all Taiwanese enterprises. In order to help transform, modernize, and encourage innovation for SMEs, the government provides many coach systems, such as start-up and incubation system, to support them to expand the market opportunities and enhance their competitiveness. In this study we try to assess the fulfillment of coach systems which supported by government for improving industry upgrade. Here we employ Delphi process to converge 27 critical indicators with respect to three key-link stages for evaluation. We also utilize correspondence analysis to exploring the implementation of coach programs and conduct some meaningful suggestions of the policy direction from these empirical cases. Through this study we successfully demonstrate that correspondence analysis is a suitable and easy to readable approach for evaluation the projects achievement of public divisions.
Fine-Grained Task Scheduling Using Adaptive Data Structures
Authors: Ralf Hoffmann, Thomas Rauber
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

Task pools have been shown to provide efficient load balancing for irregular applications on heterogeneous platforms. Often, distributed data structures are used to store the tasks and the actual load balancing is achieved by task stealing where an idle processor accesses tasks from another processor. In this paper we extent the concept of task pools to adaptive task pools which are able to adapt the number of tasks moved between the processor to the specific execution scenario, thus reducing the overhead for task stealing significantly. We present runtime experiments for different applications on two execution platforms.
Multi-view Ear Shape Feature Extraction and Reconstruction
Authors: Heng Liu, Jingqi Yan
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

Due to ear's complex structure, particular position, and preferable stability, ear biometrics has attracted increasingly attention recently. In this paper, we present a new multi-view based ear feature extraction strategy. We utilize not only front view ear image but backside view ear image to extract 2D ear shape four kinds of rich features for ear recognition. In addition, we utilize multi-view ear images to reconstruct 3D ear shape, and a neural network 3D ear registration method is introduced also. Experimental results and comparison analysis show our multi-view based strategy will be a promising approach for ear biometrics.
A family of root-finding methods with accelerated convergence
Authors: M. S. Petkovi, L. Z. Rani
Venue: Computers Mathematics with Applications (2006)

A parametric family of iterative methods for the simultaneous determination of simple complex zeros of a polynomial is considered. The convergence of the basic method of the fourth order is accelerated using Newton's and Halley's corrections thus generating total-step methods of orders five and six. Further improvements are obtained by applying the Gauss-Seidel approach. Accelerated convergence of all proposed methods is attained at the cost of a negligible number of additional operations. Detailed convergence analysis and two numerical examples are given.
A Tableau Method for Public Announcement Logics
Authors: Philippe Balbiani, Hans Ditmarsch, Andreas Herzig, Tiago Lima
Venue: Proceedings of the 16th international conference on Automated Reasoning with Analytic Tableaux and Related Methods (2007)

Public announcement logic is an extension of multi-agent epistemic logic with dynamic operators to model the informational consequences of announcements to the entire group of agents. We propose a labelled tableau-calculus for this logic. We also present an extension of the calculus for a logic of arbitrary announcements.
Fast Fourier transform of frequency hopping spread spectrum in noisy environment
Authors: Abid Yahya, Othman Sidek, Mohd Fadzli Mohd Salleh
Venue: Proceedings of the 6th WSEAS International Conference on Applied Electromagnetics, Wireless and Optical (2008)

Frequency hopping spread spectrum (FHSS) systems have traditionally been applied in low data rate applications where the received signal can be considered narrow band. In this paper we have discussed a synchronous coherently detected FHSS/BPSK system. Pseudonoise sequence generator has been implemented to select the frequencies for transmission or reception. We have investigated the spectral characteristics of both spread and nonspread BPSK waveforms. We have analyzed and simulated these systems with several variations by taking the Fast Fourier Transform (FFT) of FHSS with original binary sequence and with noisy signal. The simulated results have shown that a signal lingering at a predefined frequency for a short period of time limits the possibility of interference from another signal source generating radiated power at a specific hop frequency.
Performance of a Propagation Delay Tolerant ALOHA Protocol for Underwater Wireless Networks
Authors: Joon Ahn, Bhaskar Krishnamachari
Venue: Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems (2008)

Underwater wireless networks have recently gained a great deal of attention as a topic of research. Although there have been several recent studies on the performance of medium access control (MAC) protocols for such networks, they are mainly based on simulations, which can be insufficient for understanding the fundamental behavior of systems. In this work we show a way to analyze mathematically the performance of an underwater MAC protocol. We particularly analyze a propagation delay tolerant ALOHA (PDT-ALOHA) protocol proposed recently [1]. In this scheme, guard bands are introduced at each time slot to reduce collisions between senders with different distances to the receiver, which have a great impact on acoustic transmissions. We prove several interesting properties concerning the performance of this protocol. We also show that the maximum throughput decreases as the maximum propagation delay increases, identifying which protocol parameter values realize the maximum throughput approximately. Although it turns out that exact expression for the maximum throughput of PDT-ALOHA can be quite complicated, we propose a useful simple expression which is shown numerically to be a very good approximation. Our result can be interpreted to mean that the throughput of PDT-ALOHA protocol can be 17-100% higher than the conventional slotted ALOHA, with proper protocol parameter values
Paradise: a two-stage DSL embedded in Haskell
Authors: Lennart Augustsson, Howard Mansell, Ganesh Sittampalam
Venue: ACM SIGPLAN Notices (2008)

We have implemented a two-stage language, Paradise, for building reusable components which are used to price financial products. Paradise is embedded in Haskell and makes heavy use of type-class based overloading, allowing the second stage to be compiled into a variety of backend platforms. Paradise has enabled us to begin moving away from implementation directly in monolithic Excel spreadsheets and towards a more modular and retargetable approach.
An Improved Approach of Adaptive Control for Time-Delay Systems Based on Observer
Authors: Lin Chai, Shumin Fei
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

This paper is concerned with the problem of observer-based stabilization for time-delay systems. Both the state delay and input delay under consideration are assumed to be a constant time-delays, but not known exactly. A new design method is proposed for an observer-based controller with adaptation to the time-delays. The designed controller simultaneously contains both the current state and the past information of systems. The design for adaptation law to delay constants is more concise than the existing conclusions. The controller can be derived by solving a set of linear matrix inequalities (LMIs).
An Approach to Theory of Fuzzy Discrete Signals
Authors: Bohdan S. Butkiewicz
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

The paper presents an approach to description of fuzzy discrete functions and Fourier transform of such functions taking in consideration their uncertainty. Conventional approach to uncertainty employs probabilistic description. Here, fuzzy logic theory is applied to describe this uncertainty. A definition of transform, called later Discrete Fuzzy Fourier Transform and definition of Inverse Discrete Fuzzy Fourier Transform are proposed. Some properties of such transformations and examples of applications and comparison with conventional approach are shown.
Stress recovery procedure for discontinuous deformation analysis
Authors: Zhiye Zhao, Jiong Gu
Venue: Advances in Engineering Software (2009)

The discontinuous deformation analysis (DDA) has been widely applied for rock engineering problems due to its special features in modeling the discontinuous rock mass. A linear polynomial function is often used in the standard DDA to ease the complex contact determination between the blocks. This linear displacement function generates a constant stress field within a block, which cannot be effectively used to model the stress variation within a block and across the block interface, especially in the region with a large stress gradient. In this paper, a stress recovery procedure is proposed for those DDA blocks which are glued together. Such a procedure can improve the stress accuracy along the block interface, and can be used for more accurate contact determination. Two numerical examples are presented to study the stress accuracy of the proposed method, and the results show that the proposed stress recovery method provides a better accuracy than the direct DDA and the averaging method.
Guided Forest Edit Distance: Better Structure Comparisons by Using Domain-knowledge
Authors: Zeshan Peng, Hing-Fung Ting
Venue: Proceedings of the 18th annual symposium on Combinatorial Pattern Matching (2007)

We introduce the guided forest edit distance problem, which measures the similarity of two forests under the guidance of a third forest. We give an efficient algorithm for the problem. Our problem is a natural generalization of many important structure comparison problems such as the forest edit distance problem, constrained sequence alignment problem and the longest constrained common subsequence problem. Our algorithm matches the performance of the best known algorithms for these problems.