ppxscal/embedding_network huggingface dataset:
A two-dimensional matrix Padé-type approximation in the inner product space
Authors: Youtian Tao, Chuanqing Gu
Venue: Journal of Computational and Applied Mathematics (2009)

By introducing a bivariate matrix-valued linear functional on the scalar polynomial space, a general two-dimensional (2-D) matrix Pade-type approximant (BMPTA) in the inner product space is defined in this paper. The coefficients of its denominator polynomials are determined by taking the direct inner product of matrices. The remainder formula is developed and an algorithm for the numerator polynomials is presented when the generating polynomials are given in advance. By means of the Hankel-like coefficient matrix, a determinantal expression of BMPTA is presented. Moreover, to avoid the computation of the determinants, two efficient recursive algorithms are proposed. At the end the method of BMPTA is applied to partial realization problems of 2-D linear systems.
Linear offset-free Model Predictive Control
Authors: Urban Maeder, Francesco Borrelli, Manfred Morari
Venue: Automatica (Journal of IFAC) (2009)

This work addresses the problem of offset-free Model Predictive Control (MPC) when tracking an asymptotically constant reference. In the first part, compact and intuitive conditions for offset-free MPC control are introduced by using the arguments of the internal model principle. In the second part, we study the case where the number of measured variables is larger than the number of tracked variables. The plant model is augmented only by as many states as there are tracked variables, and an algorithm which guarantees offset-free tracking is presented. In the last part, offset-free tracking properties for special implementations of MPC schemes are briefly discussed.
Investigations into Particle Swarm Optimization for Multi-class Shape Recognition
Authors: Ee Lee Ng, Mei Kuan Lim, Tomás Maul, Weng Kin Lai
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

There has been a significant drop in the cost as well as an increase in the quality of imaging sensors due to stiff competition as well as production improvements. Consequently, real-time surveillance of private or public spaces which relies on such equipment is gaining wider acceptance. While the human brain is very good at image analysis, fatigue and boredom may contribute to a less-than-optimum level of monitoring performance. Clearly, it would be good if highly accurate vision systems could complement the role of humans in round-the-clock video surveillance. This paper addresses an image analysis problem for video surveillance based on the particle swarm computing paradigm. In this study three separate datasets were used. The overall finding of the paper suggests that clustering using Particle Swarm Optimization leads to better and more consistent results, in terms of both cluster characteristics and subsequent recognition, as compared to traditional techniques such as K-Means.
0˝-Categorical Completely Decomposable Torsion-Free Abelian Groups
Authors: Alexander G. Melnikov
Venue: Proceedings of the 5th Conference on Computability in Europe: Mathematical Theory and Computational Practice (2009)

We show that every homogeneous completely decomposable torsion-free abelian group is 0˝-categorical. We give a description of effective categoricity for some natural class of torsion-free abelian groups. In particular, we give examples of 0˝-categorical but not 0˝-categorical torsion-free abelian groups.
A Proactive Secret Sharing Scheme in matrix projection method
Authors: Li Bai, XuKai Zou
Venue: International Journal of Security and Networks (2009)

Proactive Secret Sharing (PSS) scheme is a method to periodically renew n secret shares in a (k, n) threshold-based Secret Sharing Scheme (SSS) without modifying the secret, or reconstructing the secret to reproduce new shares. Traditionally, PSS schemes are developed for the Shamir's SSS which is a single SSS. Bai (2006) developed a multiple-secret sharing scheme using matrix projection. This paper presents a distributed PSS method for the matrix projection SSS. Once the new shares are updated, adversaries cannot discover the secrets from k shares which are mixed with past and present shares.
Detection of Security and Dependability Threats: A Belief Based Reasoning Approach
Authors: Davide Lorenzoli, George Spanoudakis
Venue: Proceedings of the 2009 Third International Conference on Emerging Security Information, Systems and Technologies (2009)

Monitoring the preservation of security and dependability (S&D) properties during the operation of systems at runtime is an important verification measure that can increase system resilience. However it does not always provide sufficient scope for taking control actions against violations as it only detects problems after they occur. In this paper, we describe a proactive monitoring approach that detects potential violations of S&D properties, called ““threats”, and discuss the results of an initial evaluation of it.
Intelligent Advertising for User Generated Content through Sentiment Analysis
Authors: Guang Qiu, Jiajun Bu, Chun Chen, Feng Zhang
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

The tradeoff between revenue and market share triggers the emergence of targeted advertising. However, all previous related work only focuses on the topical relevance of ads and does not concern the attitudes of consumers. In our paper, we propose a novel advertising strategy DASA (Dissatisfaction-oriented Advertising based on Sentiment Analysis) which takes the attitudes of consumers into consideration and promotes ads according to what consumers are unsatisfied with. Our work is most suitable for User Generated Content which contains plenty of consumers’ opinionated information. The experiments show encouraging results.
Power-Efficient Pipelined Reconfigurable Fixed-Width Baugh-Wooley Multipliers
Authors: Jin-Hao Tu, Lan-Da Van
Venue: IEEE Transactions on Computers (2009)

In this paper, we propose a pipelined reconfigurable fixed-width Baugh-Wooley multiplier design framework that provides four configuration modes (CMs): n \times n fixed-width multiplier, two n/2 \times n/2 fixed-width multipliers, n/2 \times n/2 full-precision multiplier, and two n/4 \times n/4 full-precision multipliers. Furthermore, low-power schemes including gated clock and zero input techniques are employed to achieve the power-efficient pipelined reconfigurable design. The presented power-efficient pipelined reconfigurable fixed-width multiplier design not only generates a family of widely used multipliers but also leads to 10.59, 21.7, 28.84, and 31.58 percent power saving, on average, for n = 8, 16, 24, and 32, respectively, compared with that of the pipelined reconfigurable fixed-width multiplier without using the low-power schemes. On the other hand, compared with non-reconfigurable pipelined multiplier, we can save 0.81, 12.46, 17.93, and 23.2 percent power consumption, respectively, for n = 8, 16, 24, and 32.
Overview of Behaviour Characteristics of High and Low Literacy Users: Information Seeking of an Online Social Service System
Authors: Neesha Kodagoda, B. L. Wong, Nawaz Kahan
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

We investigated the differences in information seeking behaviours between low and high literacy users on an on-line social service system called the "Adviseguide" website. Ten volunteers participated in the study. Using the UK's National Skills for Life Survey, five were classified as high literate; five as low literate. Participants had four information search tasks that vary in difficulty: easy, medium and difficult. Observations, video recording, and a semi structured interview technique were used. The data were analysed using Grounded Theory and Emergent Themes Analysis approach. We identified eight information seeking behaviour characteristics; Reading/ Scanning, Focus, Satisfied, Verification, Recovery, Trajectories, Representation and Abandon. Results showed that low and high literacy users demonstrated critically different characteristics.
Social Network Discovery Based on Sensitivity Analysis
Authors: Tarik Crnovrsanin, Carlos D. Correa, Kwan-Liu Ma
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

This paper presents a novel methodology for social network discovery based on the sensitivity coefficients of importance metrics, namely the Markov centrality of a node, a metric based on random walks. Analogous to node importance, which ranks the important nodes in a social network, the sensitivity analysis of this metric provides a ranking of the relationships between nodes. The sensitivity parameter of the importance of a node with respect to another measures the direct or indirect impact of a node. We show that these relationships help discover hidden links between nodes and highlight meaningful links between seemingly disparate sub-networks in a social structure. We introduce the notion of implicit links, which represent an indirect relationship between nodes not connected by edges, seen as hidden connections in complex networks. We demonstrate our methodology on two social network data sets and use sensitivity-guided visualizations to highlight our findings. Our results show that this analytic tool, when coupled with visualization, is an effective mechanism for discovering social networks.
Automated Analysis of e-Participation Data by Utilizing Associative Networks, Spreading Activation and Unsupervised Learning
Authors: Peter Teufl, Udo Payer, Peter Parycek
Venue: Proceedings of the 1st International Conference on Electronic Participation (2009)

According to [1], the term e-participation is defined as "the use of information and communication technologies to broaden and deepen political participation by enabling citizens to connect with one another and with their elected representatives". This definition sounds quite simple and logical, but when considering the implementation of such a service in a real world scenario, it is obvious that it is not possible to evaluate messages, which are generated by thousands of citizens, by hand. Such documents need to be read and analyzed by experts with the required in-depth domain knowledge. In order to enable this analysis process and thereby to increase the number of possible e-particpation applications, we need to provide these experts with automated analysis tools that cluster, pre-screen and pre-evaluate public opinions and public contributions. In this paper we present a framework based on Machine Learning-(ML) and Artificial Intelligence-(AI) techniques that are capable of various analysis mechanisms such as unsupervised clustering of yet unread documents, searching for related concepts within documents and the description of relations between terms. To finish, we show how the proposed framework can be applied to real world data taken from the Austrian e-participation platform mitmachen.at.
Real-time alert correlation using stream data mining techniques
Authors: Reza Sadoddin, Ali A. Ghorbani
Venue: Proceedings of the 20th national conference on Innovative applications of artificial intelligence - Volume 3 (2008)

With the large volume of alerts produced by low-level detectors, management of intrusion alerts is becoming more challenging. Alert Correlation addresses this issue by providing a condensed, yet more useful view of the network from the intrusion standpoint. In this paper, we propose a new framework for real-time alert correlation that incorporates novel techniques for aggregating alerts into structured patterns and incremental mining of frequent structured patterns. In the proposed framework, time-sensitive statistical relationships between alerts are maintained in an efficient data structure and are updated incrementally to reflect the latest trends of patterns. The results of experiments with synthetic and real-world datasets demonstrate the efficiency of the proposed techniques. Our Frequent Structure Mining algorithm scales linearly with the size of the dataset and the proposed framework can cope with the throughput of a large-scale network. The ability to answer time-sensitive queries about patterns is another advantage of this work compared to other methods.
A log-extended Weibull regression model
Authors: Giovana O. Silva, Edwin M. M. Ortega, Gauss M. Cordeiro
Venue: Computational Statistics Data Analysis (2009)

A bathtub-shaped failure rate function is very useful in survival analysis and reliability studies. The well-known lifetime distributions do not have this property. For the first time, we propose a location-scale regression model based on the logarithm of an extended Weibull distribution which has the ability to deal with bathtub-shaped failure rate functions. We use the method of maximum likelihood to estimate the model parameters and some inferential procedures are presented. We reanalyze a real data set under the new model and the log-modified Weibull regression model. We perform a model check based on martingale-type residuals and generated envelopes and the statistics AIC and BIC to select appropriate models.
Countermeasures of Agricultural E-commerce Development
Authors: Cheng-hua Shi, Zhan-ping Hou, Fei Zhao
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

With the information technology wave sweeping through the world, agricultural e-commerce becomes an Important Way to promote agricultural production and management and improve agricultural competitiveness. This paper evaluates the significance of agricultural e-commerce for agricultural development, analyzes the problems in development of China's agricultural e-commerce currently, and explores countermeasures of agricultural e-commerce development at last.
An Analysis of Fire Frame Processing and Video Dynamic Features
Authors: Lin Shi, Xinyu Liu, Pei Liu
Venue: Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing (2009)

In this paper, RGB to gray, binaryzation and morphological close operation are used for fire flame images processing. The area, mean gray, circularity between fire flame and interference image are analyzed then. It is found in the experimental data that the differences among the autocorrelation function of the area sequence, the variance of the mean gray sequence, the mean v and autocorrelation function of the circularity sequence of the fire flame and these of interferences is sensible. On this basis, using of these four video dynamic features as fire identification parameters is proposed. It shows in the experimental results that the image processing method and fire dynamic featuresdescribed in this paper can identify fire flame correctly, reducing false alarm rate and false dismissal rate.
A Bayesian Local Linear Wavelet Neural Network
Authors: Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

In general, wavelet neural networks have a problem on the curse of dimensionality, i.e. the number of hidden units to be required are exponentially rose with increasing an input dimension. To solve the above problem, a wavelet neural network incorporating a local linear model has already been proposed. On their network design, however, the number of hidden units is empirically determined and fixed during learning. In the present paper, a design method based on Bayesian method is proposed for the local linear wavelet neural network. The performance of the proposed method is evaluated through computer simulation.
Fusion of Claude Bernard's Experiments for Scientific Discovery Reasoning
Authors: Claire Laudy, Bassel Habib, Jean-Gabriel Ganascia
Venue: Proceedings of the 17th International Conference on Conceptual Structures: Conceptual Structures: Leveraging Semantic Technologies (2009)

We are interested in using a fusion process to complete information prior to the reasoning process about scientific discoveries. In particular, using fusion to complete the set of experiments used as the source of information of the process that led Claude Bernard to his discovery about the effects of curare. Our reconstruction of the discovery process is based on his experiments as they are illustrated in his notebooks. Our main problem is the lack of some important information in his notebooks containing descriptions of his set of experiments. In order to fill in the gaps in his set of experiments, we propose to use fusion between experiments. Prior to fusion, we must ensure that the experiments are compatible according to some similarity measures and depending on the objectives of the fusion. The paper presents our domain-independent approach for similarity checking and fusion, including similarity and fusion strategies.
Hierarchical Web Categorization Model Based on Fuzzy Cognitive Maps
Authors: Jingxiu Lee, Weijuan Zhang
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

Text categorization is an important direction of information processing, and now there are many methods of text categorization, such as Bayesian probabilistic models, Vector Space Model, K-Nearest Neighbor and so on. And now most of information of web is in form of text. Therefore, this paper proposed a Hierarchical model of web categorization based on Fuzzy Cognitive Maps, namely, using Fuzzy Cognitive Maps (FCMs) and the thoughts of decomposition to realize hierarchical web categorization. In that way, it can largely decrease scale and complexity, and increase categorization efficiency.
Study on Dynamic Change of Land Utilization in Wuhan Metropolitan Area
Authors: Lilan Su, Xiaoyong Gao, Yanfang Liu
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

The paper takes individual 9 units of the 1 plus 8 cities in Wuhan Metropolitan Area as the researchzone, through a consecutive time sequence of 10 years period just before and after the Wuhan Metropolitan Area project (1996-2005) and intercept the year 1996 and 2005 as two time node for analysis. The land use relative change rate (R) and Information entropy values of land use structure (H) are presented here as primary indicators to value land use structure transformations of the research zone and also features of different individual units within the metropolitan area since they aggregation as a whole. The outcomes indicated that Wuhan as the core of Wuhan Metropolitan Area far superiority other units, an integrative regional development still needs to be improved; Huangshi, Xianning, Ezhou have already form the second group, the comparatively advantages are initially notable, and such units perform as active intergrades for city radiation from Wuhan; territorial differentiation in Wuhan Metropolitan Area is evident: the east part betters the west, and the longitude rapids the latitude.
New Advances in Intelligent Decision Technologies: Results of the First KES International Symposium IDT'09, 1st edition
Authors: Kazumi Nakamatsu, Gloria Phillips-Wren, Lakhmi C. Jain, Robert J. Howlett
Venue:  (2009)

IDT (Intelligent Decision Technologies) seeks an interchange of research on intelligent systems and intelligent technologies which enhance or improve decision making in industry, government and academia. The focus is interdisciplinary in nature, and includes research on all aspects of intelligent decision technologies, from fundamental development to the applied system. It constitutes a great honor and pleasure for us to publish the works and new research results of scholars from the First KES International Symposium on Intelligent Decision Technologies (KES IDT'09), hosted and organized by University of Hyogo in conjunction with KES International (Himeji, Japan, April, 2009). The symposium was concerned with theory, design, development, implementation, testing and evaluation of intelligent decision systems. Its topics included intelligent agents, fuzzy logic, multi-agent systems, artificial neural networks, genetic algorithms, expert systems, intelligent decision making support systems, information retrieval systems, geographic information systems and knowledge management systems. These technologies have the potential to support decision making in many areas of management, international business, finance, accounting, marketing, healthcare, military applications, production, networks, traffic management, crisis response and human interfaces.
Connectivity of cognitive radio networks: proximity vs. opportunity
Authors: Wei Ren, Qing Zhao, Ananthram Swami
Venue: Proceedings of the 2009 ACM workshop on Cognitive radio networks (2009)

We address the connectivity of large-scale ad hoc cognitive radio networks, where secondary users exploit channels temporarily and locally unused by primary users and the existence of a communication link between two secondary users depends not only on the distance between them but also on the transmitting and receiving activities of nearby primary users. We introduce the concept of connectivity region defined as the set of density pairs -- the density of the secondary users and the density of the primary transmitters -- under which the secondary network is connected. Using theories and techniques from continuum percolation, we analytically characterize the connectivity region of the secondary network by showing its three basic properties and analyzing its two critical parameters. Furthermore, we reveal the tradeoff between proximity (the number of neighbors) and the occurrence of spectrum opportunities by studying the impact of secondary users' transmission power on the connectivity region of the secondary network, and design the transmission power of the secondary users to maximize their tolerance to the primary traffic load.
Discrete-Event Modeling and Simulation: A Practitioner's Approach, 1st edition
Authors: Gabriel A. Wainer
Venue: Computational Analysis, Synthesis, And Design Of Dynamic Models (2009)

Complex artificial dynamic systems require advanced modeling techniques that can accommodate their asynchronous, concurrent, and highly non-linear nature. Discrete Event systems Specification (DEVS) provides a formal framework for hierarchical construction of discrete-event models in a modular manner, allowing for model re-use and reduced development time.Discrete Event Modeling and Simulation presents a practical approach focused on the creation of discrete-event applications. The book introduces the CD++ tool, an open-source framework that enables the simulation of discrete-event models. After setting up the basic theory of DEVS and Cell-DEVS, the author focuses on how to use the CD++ tool to define a variety of models in biology, physics, chemistry, and artificial systems. They also demonstrate how to map different modeling techniques, such as Finite State Machines and VHDL, to DEVS. The in-depth coverage elaborates on the creation of simulation software for DEVS models and the 3D visualization environments associated with these tools.A much-needed practical approach to creating discrete-event applications, this book offers world-class instruction on the fields most useful modeling tools.