ppxscal/embedding_network huggingface dataset:
Hamiltonian Connectedness of the Faulty WK-Recursive Network
Authors: Jung-Sheng Fu
Venue: Proceedings of the Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (2006)

Much research on the WK-recursive network has been published during the past few years due to its many favorable properties. We use K(d, t) to denote a WK-recursive network of level t, each of whose basic modules is a d-node complete graph, where d > 1 and t \geqslant 1. Let F denote the set of faulty nodes in K(d, t). In this study, we show that K(d, t) - F is Hamiltonian connected when |F|d \leqslant - 4. Therefore, K(d, t) - F can embed the longest linear array between any two distinct nodes with dilation, congestion, load, and expansion all equal to one. In addition, since the connectivity of K(d, t) is d - 1, the result is optimal.
Learning Association Fields from Natural Images
Authors: Francesco Orabona, Giorgio Metta, Giulio Sandini
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

Previous studies have shown that it is possible to learn certain properties of the responses of the neurons of the visual cortex, as for example the receptive fields of complex and simple cells, through the analysis of the statistics of natural images and by employing principles of efficient signal encoding from information theory. Here we want to go further and consider how the output signals of 'complex cells' are correlated and which information is likely to be grouped together. We want to learn 'association fields', which are a mechanism to integrate the output of filters with different preferred orientation, in particular to link together and enhance contours. We used static natural images as training set and the tensor notation to express the learned fields. Finally we tested these association fields in a computer model to measure their performance.
Improved Privacy-Preserving Bayesian Network Parameter Learning on Vertically Partitioned Data
Authors: Zhiqiang Yang, Rebecca N. Wright
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

Privacy concerns often prevent different parties from sharing their data in order to carry out data mining applications on their joint data. Privacy-preserving data mining seeks to address this by enabling parties to jointly compute a data mining algorithm on distributed data without sharing their data. In this paper, we address a particular data mining problem, that of learning the parameters of Bayesian network on a vertically partitioned database. We provide a simple privacy-preserving protocol for learning the parameters of Bayesian network on vertically partitioned databases. In comparison to the previously known solution for this problem (Meng, Sivakumar, and Kargupta, 2004), our solution provides better performance, full privacy, and complete accuracy. In combination with our previous work on privacy-preserving learning of Bayesian network structure on vertically partitioned databases, this work provides a complete privacy-preserving protocol for learning Bayesian networks (both structure and parameters) on vertically partitioned data, with very little overhead beyond computing the structure alone.
Design and Implementation of SCORM Content Conversion System for DiTV
Authors: SeungHyun Im, SiHwa Lee, XiaoLi Wu, ManHyoung Lee, DaeHoon Hwang
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02 (2006)

Recently, the main topic in e-learning domain and industry is called digital convergence whose core demand is OSMU (One Source Multi Use). However, there exists so many learning contents in Web, and with the development of new learning content which must adapt the new learning environment, the problem about cost and time appears. So in this paper we design and implement a JAVA based content conversion system which has the ability of interoperability, reuse and highly-use to convert the SCORM-based learning content into MHP-based DiTV content in order to adapt t-learning environment using DiTV. Using this system, the problem about the e-learning content which has been mentioned above can be solved well. Moreover, it is possible for a person who is not familiar with computer to study using DiTV but not PC.
A unified load generator based on formal load specification and load transformation
Authors: Jing Cong, Bernd E. Wolfinger
Venue: Proceedings of the 1st international conference on Performance evaluation methodolgies and tools (2006)

Optimizing the performance of existing networks often demands realistic and valid load generation tools. As the network loads observed may vary significantly over time, there is a strong need to develop flexible and extensible load generators which can reproduce these loads accurately. This paper presents a unified methodology for artificial load generating at different interfaces within the protocol hierarchy of computer networks. A unified load generator which is based on a formal load specification technique and a new approach to load modeling combined with load transformation is established. The methodology of constructing the unified load generator is validated by means of implementing a prototype of such a load generator (UniLoG) which is capable of producing network traffic with different characteristics in a very simple and flexible manner. We present the architectural design, some implementation aspects and investigate the limits of applicability of our prototype. Recent performance evaluation studies with UniLoG indicate that this load generator is a valid tool for QoS studies in computer networks, and can indeed produce some predefined traffic accurately.
Maturation of White Matter is Associated with the Development of Cognitive Functions during Childhood
Authors: Zoltan Nagy, Helena Westerberg, Torkel Klingberg
Venue: Journal of Cognitive Neuroscience (2004)

In the human brain, myelination of axons continues until early adulthood and is thought to be important for the development of cognitive functions during childhood. We used diffusion tensor MR imaging and calculated fractional anisotropy, an indicator of myelination and axonal thickness, in children aged between 8 and 18 years. Development of working memory capacity was positively correlated with fractional anisotropy in two regions in the left frontal lobe, including a region between the superior frontal and parietal cortices. Reading ability, on the other hand, was only correlated with fractional anisotropy in the left temporal lobe, in the same white matter region where adults with reading disability are known to have lower fractional anisotropy. Both the temporal and the frontal regions were also correlated with age. These results show that maturation of white matter is an important part of brain maturation during childhood, and that maturation of relatively restricted regions of white matter is correlated with development of specific cognitive functions.
Weierstrass semi-rational expansion method and new doubly periodic solutions of the generalized Hirota-Satsuma coupled KdV system
Authors: Yong Chen, Zhenya Yan
Venue: Applied Mathematics and Computation (2006)

In the paper, with the aid of symbolic computation, we investigate the generalized Hirota-Satsuma coupled KdV system via our Weierstrass semi-rational expansion method presented recently using the rational expansion of Weierstrass elliptic function and its first-order derivative. As a consequence, three families of new Weierstrass elliptic function solutions via Weierstrass elliptic function P(Ξ;g2,g3) and its first-order derivative P'(Ξ;g2, g3). Moreover, the corresponding new Jacobi elliptic function solutions and solitary wave solutions are also presented, and when Ξ; → ∞, these solitary wave solutions approach to some constants.
Experimental designs for 2-colour cDNA microarray experiments: Research Articles
Authors: Nam-Ky Nguyen, E. R. Williams
Venue: Applied Stochastic Models in Business and Industry (2006)

Kerr and Churchill (Biostatistics 2001; 2:183&ndash;201) showed how varieties (e.g. type of tissues, drug treatments, etc.) are paired onto arrays by a catalogue of A-optimal incomplete block designs (IBDs) for 6&ndash;10 varieties (v), and number of blocks of size 2 between v and $ \left(v \atop 2 \right)$. These A-optimal IBDs were obtained by (i) generating all non-isomorphic connected graphs on v vertices using Brendan McKay's, MAKEG program () and (ii) comparing all designs of the same size on the basis of A-optimality to obtain the best ones.In this paper we will give a quick overview on IBDs and describe an algorithmic approach to extend the mentioned catalogue. We aim at IBDs with up to 100 varieties with equal as well as unequal replications. A catalogue of 2007 IBDs is given. We will also extend the concept of even designs in Kerr and Churchill (Biostatistics 2001; 2:183&ndash;201) to row-orthogonal designs. Copyright &copy; 2006 John Wiley & Sons, Ltd.
Characterizing the quality of second-graders' observations and explanations to inform the design of educative curriculum materials
Authors: Carrie Beyer, Elizabeth A. Davis
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

Recording observations and constructing evidence-based explanations are key aspects of inquiry-oriented science teaching and are essential to learning authentic science. However, little is known about the kinds of observations and explanations early elementary school students can make and the ways educative curriculum materials can support students' and teachers' learning about these inquiry practices. In this study, we describe the quality of second graders' drawings and descriptions of their observations and the explanations they construct from their observations during an inquiry-based unit. Our results show that despite some success in making drawings, descriptions, and explanations, children still face many difficulties when engaged in these inquiry tasks. These findings suggest specific areas in which scaffolding for students may be warranted. The findings also point to areas where it may be important to provide additional guidance for teachers. We make recommendations for these student and teacher supports.
Dynamic gain changes during attentional modulation
Authors: Arun P. Sripati, Kenneth O. Johnson
Venue: Neural Computation (2006)

Attention causes a multiplicative effect on firing rates of cortical neurons without affecting their selectivity (Motter, 1993; McAdams & Maunsell, 1999a) or the relationship between the spike count mean and variance (McAdams & Maunsell, 1999b). We analyzed attentional modulation of the firing rates of 144 neurons in the secondary somatosensory cortex (SII) of two monkeys trained to switch their attention between a tactile pattern recognition task and a visual task. We found that neurons in SII cortex also undergo a predominantly multiplicative modulation in firing rates without affecting the ratio of variance to mean firing rate (i.e., the Fano factor). Furthermore, both additive and multiplicative components of attentional modulation varied dynamically during the stimulus presentation.We then used a standard conductance-based integrate-and-fire model neuron to ascertain which mechanisms might account for a multiplicative increase in firing rate without affecting the Fano factor. Six mechanisms were identified as biophysically plausible ways that attention could modify the firing rate: spike threshold, firing rate adaptation, excitatory input synchrony, synchrony between all inputs, membrane leak resistance, and reset potential. Of these, only a change in spike threshold or in firing rate adaptation affected model firing rates in a manner compatible with the observed neural data. The results indicate that only a limited number of biophysical mechanisms can account for observed attentional modulation.
Counting All Possible Ancestral Configurations of Sample Sequences in Population Genetics
Authors: Yun S. Song, Rune Lyngso, Jotun Hein
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2006)

Given a set D of input sequences, a genealogy for D can be constructed backward in time using such evolutionary events as mutation, coalescent, and recombination. An ancestral configuration (AC) can be regarded as the multiset of all sequences present at a particular point in time in a possible genealogy for D. The complexity of computing the likelihood of observing D depends heavily on the total number of distinct ACs of D and, therefore, it is of interest to estimate that number. For D consisting of binary sequences of finite length, we consider the problem of enumerating exactly all distinct ACs. We assume that the root sequence type is known and that the mutation process is governed by the infinite-sites model. When there is no recombination, we construct a general method of obtaining closed-form formulas for the total number of ACs. The enumeration problem becomes much more complicated when recombination is involved. In that case, we devise a method of enumeration based on counting contingency tables and construct a dynamic programming algorithm for the approach. Last, we describe a method of counting the number of ACs that can appear in genealogies with less than or equal to a given number R of recombinations. Of particular interest is the case in which R is close to the minimum number of recombinations for D.
A comparison between mechanisms for sequential compute resource auctions
Authors: Andrew Byde
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

This paper describes simulations designed to test the relative efficiency of two different sequential auction mechanisms for allocating compute resources between users in a shared data-center. For each of two possible auction types we apply a genetic algorithm to a broad class of bidding strategies to determine a near-optimal bidding strategy for a specified auction type, and use statistics of the performance of these strategies to determine the most suitable auction type for this domain.
Statistic Analysis for the Tiancalli Agents on TAC SCM 2005 and 2006
Authors: Daniel Macias Galindo, Darnes Vilarino Ayala, Fabiola Lopez y Lopez
Venue: Proceedings of the 15th International Conference on Computing (2006)

During the last two years we have developed the Tiancalli Project. This project includes the construction of TAC SCM compliant agents. The TAC SCM is a contest about different software agents competing in a simulated market that has been organized for four years by Trading Agent Research Group. In order to find the strenghtness and weaknessof our agent, we have made a statistic research with both 2005 and 2006 game results. The objective of this article is to present the results obtained in this comparison. Also it is important to discuss a more concrete basis about factors that must be modified, such as the ones which should be kept on the TAC SCM 2007.
Personalized document retrieval in multi-party environments with the Semantic Desktop
Authors: Mark Siebert, Pierre Smits, Leo Sauermann, Andreas Dengel
Venue: Proceedings of the 10th IEEE on International Enterprise Distributed Object Computing Conference Workshops (2006)

Multi-party environments, like account communities, struggle with organizationally pre-defined information structures in corporate document repositories. Different roles work in different information structures according to their tasks and perspectives. The Semantic Desktop increases retrieval quality respecting personal information models, such as individual folder structures. The paper illustrates impact of different roles and document settings. The findings foster the discussion on integration of semantic technologies in document management enabling support of multi-party environments.
SyncWUF: An Ultra Low-Power MAC Protocol for Wireless Sensor Networks
Authors: Xiaolei Shi, Guido Stromberg
Venue: IEEE Transactions on Mobile Computing (2007)

In wireless sensor networks, power consumption is one of the key design issues because a large number of sensor nodes are powered by cheap batteries. Switching the RF transceiver, which is one of the biggest power consumers in a sensor node, to low-power sleep mode as much as possible has been proven to be a very efficient way to save power with a factor of tens or even hundreds. So far, several schemes have been proposed to reduce the duty cycle of the RF transceiver by MAC layer scheduling. Among them, the Wake-Up-Frame scheme and the WiseMAC are two very efficient protocols based on the so-called preamble sampling technology. This paper proposes combining these two schemes to obtain a further optimized low-power MAC protocol, called SyncWUF, for low-traffic wireless sensor network. Analytical and simulation results prove that our proposal achieves significant battery lifetime gain in different application cases without negatively affecting other important system parameters such as channel capacity and latency.
An improved algorithm for approximating the chromatic number of Gn,p
Authors: Amin Coja-Oghlan, Lars Kuhtz
Venue: Information Processing Letters (2006)

Answering a question of Krivelevich and Vu [M. Krivelevich, V.H. Vu, Approximating the independence number and the chromatic number in expected polynomial time, J. Combin. Optimization 6 (2002) 143-155], we present an algorithm for approximating the chromatic number of random graphs Gn, p within a factor of O(√np/ln(np)) in polynomial expected time. The algorithm applies to edge probabilities c0/n ≤ p ≤ 0.99, where c0 > 0 is a certain constant.
Mining long-term search history to improve search accuracy
Authors: Bin Tan, Xuehua Shen, ChengXiang Zhai
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

Long-term search history contains rich information about a user's search preferences, which can be used as search context to improve retrieval performance. In this paper, we study statistical language modeling based methods to mine contextual information from long-term search history and exploit it for a more accurate estimate of the query language model. Experiments on real web search data show that the algorithms are effective in improving search accuracy for both fresh and recurring queries. The best performance is achieved when using clickthrough data of past searches that are related to the current query.
Transparent Decision Support Using Statistical Reasoning and Fuzzy Inference
Authors: Andrew Hamilton-Wright, Daniel W. Stashuk
Venue: IEEE Transactions on Knowledge and Data Engineering (2006)

A framework for the development of a decision support system (DSS) that exhibits uncommonly transparent rule-based inference logic is introduced. A DSS is constructed by marrying a statistically based fuzzy inference system (FIS) with a user interface, allowing drill-down exploration of the underlying statistical support, providing transparent access to both the rule-based inference as well as the underlying statistical basis for the rules. The FIS is constructed through a "Pattern Discovery” based analysis of training data. Such an analysis yields a rule base characterized by simple explanations for any rule or data division in the extracted knowledge base. The reliability of a fuzzy inference is well predicted by a confidence measure that determines the probability of a correct suggestion by examination of values produced within the inference calculation. The combination of these components provides a means of constructing decision support systems that exhibit a degree of transparency beyond that commonly observed in supervised-learning-based methods. A prototype DSS is analyzed in terms of its workflow and usability, outlining the insight derived through use of the framework. This is demonstrated by considering a simple synthetic data example and a more interesting real-world example application with the goal of characterizing patients with respect to risk of heart disease. Specific input data samples and corresponding output suggestions created by the system are presented and discussed. The means by which the suggestions made by the system may be used in a larger decision context is evaluated.
A Model-Driven Aspect Framework for Grid Service Development
Authors: Wen-jun Li, Chu-wei Huang, Qiang-chao Chen, Hui Bian
Venue: Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (2006)

Service-Oriented Architecture (SOA) plays an important role in the next generation computing models for scientific and commercial applications. But difficulties in the development and maintenance of Grid services slow down the spread of service-based applications. A Model- Driven Aspect Framework (MDAF) is proposed in this paper to facilitate the development of Grid services, which benefits from the combination of Model-Driven Architecture and Aspect-Oriented Programming. The UML output in XMI format derived from a CASE tool is used as the input of the framework to generate a suite of source code files and related settings. The design and implementation of MDAF are built on AspectJ along with several open source toolkits, including Eclipse, Velocity and Ant. Finally a case study of a full text search application developed with MDAF is presented to demonstrate the advantages of Grid service development with MDAF. MDAF enables a better separation of business logic and Grid specific details at both model and code levels, which makes it easy to develop, test and maintain Grid service based applications.
Adaptive Negotiation with On-Line Prediction of Opponent Behaviour in Agent-Based Negotiations
Authors: Jakub Brzostowski, Ryszard Kowalczyk
Venue: Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology (2006)

We propose an adaptive approach in agent-based negotiation involving on-line prediction of the opponent behaviour based on the parametric non-linear regression analysis. The predictive decision-making mechanism for the negotiation agent is based on the history of offers in the current negotiation encounter. In comparison to the related work the proposed approach allows the negotiation agents to predict more complex behaviour of the negotiation opponent in terms of mixture of its time-dependant and behaviour-dependant tactics. We perform experiments in order to validate the proposed approach. The results show that the predictive decision-making gives better results in terms of the utility gains for the adaptive negotiation agent as compared with a range of non-predictive negotiation strategies.
Improved ZigBee Connection Method for Healthcare Device
Authors: JY Jung, JW Lee
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 01 (2006)

Generally speaking, bio signal devices for measuring a human bio signal and PDA for collecting bio signals may be personalized in the ubiquitous healthcare system. Therefore, specific bio signal devices will connect with the same PDA all the time. And if there are several PDAs in same WPAN region, the bio signal devices may receive beacon messages from multi PDAs and should connect with the exact PDA. We propose the zigbee connection algorithm appropriated to the ubiquitous healthcare system. Simulation results indicate that the scanning time in the proposed algorithm is faster than the Wireless MAC and PHY specifications for LR-WPANs.