ppxscal/embedding_network huggingface dataset:
A new method to forecast of Escherichia coli promoter gene sequences: Integrating feature selection and Fuzzy-AIRS classifier system
Authors: Kemal Polat, Salih Güneş
Venue: Expert Systems with Applications: An International Journal (2009)

We have investigated the real-world task of recognizing biological concepts in DNA sequences in this work. Recognizing promoters in strings that represent nucleotides (one of A, G, T, or C) has been performed using a novel approach based on feature selection (FS) and Artificial Immune Recognition System (AIRS) with Fuzzy resource allocation mechanism (Fuzzy-AIRS), which is first proposed by us. The aim of this study is to improve the prediction accuracy of Escherichia coli promoter gene sequences using a novel system based on FS and Fuzzy-AIRS. The E. coli promoter gene sequences dataset has 57 attributes and 106 samples including 53 promoters and 53 non-promoters. The proposed system consists of two parts. Firstly, we have reduced the dimension of E. coli promoter gene sequences dataset from 57 attributes to 4 attributes by means of FS process. Second, Fuzzy-AIRS classifier algorithm has been run to predict the E. coli promoter gene sequences. The robustness of the proposed method is examined using prediction accuracy, sensitivity and specificity analysis, k-fold cross-validation method and confusion matrix. Whilst only Fuzzy-AIRS classifier has obtained 50% prediction accuracy using 10-fold cross-validation, the proposed system has obtained 90% prediction accuracy in the same conditions. These obtained results have indicated that the proposed system obtain the success rate in recognizing promoters in strings that represent nucleotides.
Powerful fusion
Authors: Dariusz Przybylski, Burkhard Rost
Venue: Bioinformatics (2008)

Motivation: A typical PSI-BLAST search consists of iterative scanning and alignment of a large sequence database during which a scoring profile is progressively built and refined. Such a profile can also be stored and used to search against a different database of sequences. Using it to search against a database of consensus rather than native sequences is a simple add-on that boosts performance surprisingly well. The improvement comes at a price: we hypothesized that random alignment score statistics would differ between native and consensus sequences. Thus PSI-BLAST-based profile searches against consensus sequences might incorrectly estimate statistical significance of alignment scores. In addition, iterative searches against consensus databases may fail. Here, we addressed these challenges in an attempt to harness the full power of the combination of PSI-BLAST and consensus sequences. Results: We studied alignment score statistics for various types of consensus sequences. In general, the score distribution parameters of profile-based consensus sequence alignments differed significantly from those derived for the native sequences. PSI-BLAST partially compensated for the parameter variation. We have identified a protocol for building specialized consensus sequences that significantly improved search sensitivity and preserved score distribution parameters. As a result, PSI-BLAST profiles can be used to search specialized consensus sequences without sacrificing estimates of statistical significance. We also provided results indicating that iterative PSI-BLAST searches against consensus sequences could work very well. Overall, we showed how a very popular and effective method could be used to identify significantly more relevant similarities among protein sequences. Availability: http://www.rostlab.org/services/consensus/ Contact: dariusz@mit.edu
An integrated decision making approach for ERP system selection
Authors: E. Ertugrul Karsak, C. Okan Özogul
Venue: Expert Systems with Applications: An International Journal (2009)

Enterprise resource planning (ERP) systems have gained major prominence by enabling companies to streamline their operations, leverage and integrate business data process. In order to implement an ERP project successfully, it is necessary to select an ERP system which can be aligned with the needs of the company. Thus, a robust decision making approach for ERP software selection requires both company needs and characteristics of the ERP system and their interactions to be taken into account. This paper develops a novel decision framework for ERP software selection based on quality function deployment (QFD), fuzzy linear regression and zero-one goal programming. The proposed framework enables both company demands and ERP system characteristics to be considered, and provides the means for incorporating not only the relationships between company demands and ERP system characteristics but also the interactions between ERP system characteristics through adopting the QFD principles. The presented methodology appears as a sound investment decision making tool for ERP systems as well as other information systems. The potential use of the proposed decision framework is illustrated through an application.
Using Laplace and angular measures for Feature Selection in Text Categorisation
Authors: Elena Montanes, Pedro Alonso, Elias F. Combarro, Irene Diaz, Raquel Cortina, Jose Ranilla
Venue: International Journal of Advanced Intelligence Paradigms (2008)

Text Categorisation (TC) consists of automatically assigning documents to a set of prefixed categories. It usually involves the management of a huge number of features. Some of them are irrelevant or noisy which mislead the classifiers. Thus, they are reduced to increase the efficiency and effectiveness of the classification. In this paper we propose to select relevant features using two different families of filtering measures, which are simpler than other usual measures applied for this purpose. The experiments over three corpora show that, in general, the proposed measures perform equal or better than the existing ones, sometimes allowing greater reductions.
One-handed mobile video browsing
Authors: Wolfgang Hürst, Philipp Merkle
Venue: Proceeding of the 1st international conference on Designing interactive user experiences for TV and video (2008)

Various situations exist in which people want to use just one hand when interacting with their mobile phones or PDAs. However, most of the few advanced video browsing approaches for such devices only support two handed operation. In this paper, we present an interface design for one-handed mobile video browsing. Using a PDA with touch screen, users can interactively scroll through a list of thumbnails representing the video's content. Thumbnail sizes can be manipulated in order to provide easier access to relevant information. Two evaluations are presented which motivate the design and verify the usability of our solution.
Introducing dynamic diversity into a discrete particle swarm optimization
Authors: Alberto García-Villoria, Rafael Pastor
Venue: Computers and Operations Research (2009)

Particle swarm optimization (PSO) is an evolutionary metaheuristic inspired by the flocking behaviour of birds, which has successfully been used to solve several kinds of problems, although there are few studies aimed at solving discrete optimization problems. One disadvantage of PSO is the risk of a premature search convergence. To prevent this, we propose to introduce diversity into a discrete PSO by adding a random velocity. The degree of the introduced diversity is not static (i.e. preset before running PSO) but instead changes dynamically according to the heterogeneity of the population (i.e. if the search has converged or not). We solve the response time variability problem (RTVP) to test these two new ideas. The RTVP is an NP-hard combinatorial scheduling problem that has recently appeared in the literature. It occurs whenever products, clients or jobs need to be sequenced in such a way that the variability in the time between the instants at which they receive the necessary resources is minimized. The most efficient algorithm for solving non-small instances of the RTVP published to date is a classical PSO algorithm, referred to by the authors as PSO-M1F. In this paper, we propose 10 discrete PSO algorithms for solving the RTVP: one based on the ideas described above (PSO-c"3dyn) and nine based on strategies proposed in the literature and adapted for solving a discrete optimization problem such as the RTVP. We compare all 11 PSO algorithms and the computational experiment shows that, on average, the best results obtained are due to our proposal of dynamic control mechanism for introducing diversity.
Nonuniform bilateral filtering for point sets and surface attributes
Authors: Hongxing Qin, Jie Yang, Yuemin Zhu
Venue: The Visual Computer: International Journal of Computer Graphics (2008)

With the proliferation of three-dimensional (3D) scanning tools and the popularity of point sets in geometry processing and rendering, there is a need for developing smoothing techniques for the point sets and surface attributes defined at these points. In this paper, we present a nonuniform bilateral filtering (NBF) method for point sets and surface attributes based on local geometry feature. In order to adapt the algorithm to irregular sampling, local sampling density is introduced to traditional bilateral filtering, and a global approach for volume preservation is proposed. Experiments show that our approach is stable, effective and easy to use.
Hermite-Birkhoff-Obrechkoff four-stage four-step ODE solver of order 14 with quantized step size
Authors: Truong Nguyen-Ba, Philip W. Sharp, Rémi Vaillancourt
Venue: Journal of Computational and Applied Mathematics (2008)

A four-stage Hermite-Birkhoff-Obrechkoff method of order 14 with four quantized variable steps, denoted by HBOQ(14)4, is constructed for solving non-stiff systems of first-order differential equations of the form y^'=f(t,y) with initial conditions y(t"0)=y"0. Its formula uses y^', y^'' and y^@? as in Obrechkoff methods. Forcing a Taylor expansion of the numerical solution to agree with an expansion of the true solution leads to multistep- and Runge-Kutta-type order conditions which are reorganized into linear Vandermonde-type systems. To reduce overhead, simple formulae are derived only once to obtain the values of Hermite-Birkhoff interpolation polynomials in terms of Lagrange basis functions for 16 quantized step size ratios. The step size is controlled by a local error estimator. When programmed in C ++, HBOQ(14)4 is superior to the Dormand-Prince Runge-Kutta pair DP(8,7)13M of order 8 in solving several problems often used to test higher order ODE solvers at stringent tolerances. When programmed in Matlab, it is superior to ode113 in solving costly problems, on the basis of the number of steps, CPU time, and maximum global error. The code is available on the URL www.site.uottawa.ca/~remi.
Fuzzy mode enhancement and detection for color image segmentation
Authors: Olivier Losson, Claudine Botte-Lecocq, Ludovic Macaire
Venue: Journal on Image and Video Processing (2008)

This work lies within the scope of color image segmentation by pixel classification. The classes of pixels are constructed by detecting the modes of the spatial-color compactness function, which characterizes the image by taking into account both the distribution of colors in the color space and their spatial location in the image plane. A fuzzy transformation of this function is performed, based on fuzzy morphological operators specifically designed formode detection. Experimental segmentation results, using several synthetic and benchmark images, show the interest of the proposed method.
Pattern Identification and Classification in the Translation from BPMN to BPEL
Authors: Luciano García-Bañuelos
Venue: Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part I on On the Move to Meaningful Internet Systems: (2008)

BPMN is a notation for business process modeling. Process models can be complex, for instance, with unstructured (cyclic) topologies. BPEL, on the other hand, is the choice for web service orchestration. This paper presents an approach to systematically identifying and classifying subgraphs in a BPMN model that may be translated to BPEL code. Most of existing methods rely on exhaustive search. In contrast, we partition the BPMN model into single-entry single-exit regions which are then classified according to control flow information. This information is gathered by using a reachability analysis based on dataflow equations.
Optimal control and filtering of weakly coupled linear discrete stochastic systems by the eigenvector approach
Authors: Naser Prljaca, Zoran Gajic
Venue: WSEAS Transactions on Systems and Control (2007)

In this paper the regulator and filter algebraic Riccati equations, corresponding to the steady state optimal control and filtering of weakly coupled linear discrete stochastic systems are solved in terms of reduced-order sub problems by using the eigenvector approach. The eigenvector method outperforms iterative methods (fixed point iterations, Newton method) of solutions to reduced-order sub problems in case of higher level of coupling between subsystems. In such cases the iterative methods could fail to produce solutions of the corresponding algebraic Riccati equations.
End-to-end support for joins in large-scale publish/subscribe systems
Authors: Badrish Chandramouli, Jun Yang
Venue: Proceedings of the VLDB Endowment (2008)

We address the problem of supporting a large number of select-join subscriptions for wide-area publish/subscribe. Subscriptions are joins over different tables, with varying interests expressed as range selection conditions over table attributes. Naive schemes, such as computing and sending join results from a server, are inefficient because they produce redundant data, and are unable to share dissemination costs across subscribers and events. We propose a novel, scalable scheme that group-processes and disseminates a general mix of multi-way select-join subscriptions. We also propose a simple and application-agnostic extension to content-driven networks (CN), which further improves sharing of dissemination costs. Experimental evaluations show that our schemes can generate orders of magnitude lower network traffic at very low processing cost. Our extension to CN can further reduce traffic by another order of magnitude, with almost no increase in notification latency.
Efficient network aware search in collaborative tagging sites
Authors: Sihem Amer Yahia, Michael Benedikt, Laks V. S. Lakshmanan, Julia Stoyanovich
Venue: Proceedings of the VLDB Endowment (2008)

The popularity of collaborative tagging sites presents a unique opportunity to explore keyword search in a context where query results are determined by the opinion of a network of taggers related to a seeker. In this paper, we present the first in-depth study of network-aware search. We investigate efficient top-k processing when the score of an answer is computed as its popularity among members of a seeker's network. We argue that obvious adaptations of top-k algorithms are too space-intensive, due to the dependence of scores on the seeker's network. We therefore develop algorithms based on maintaining score upper-bounds. The global upper-bound approach maintains a single score upper-bound for every pair of item and tag, over the entire collection of users. The resulting bounds are very coarse. We thus investigate clustering seekers based on similar behavior of their networks. We show that finding the optimal clustering of seekers is intractable, but we provide heuristic methods that give substantial time improvements. We then give an optimization that can benefit smaller populations of seekers based on clustering of taggers. Our results are supported by extensive experiments on del.icio.us datasets.
A comparative study on the measurement of toughness of stacks containing low-k dielectric films
Authors: Z. W. Zheng, I. Sridhar, S. Balakumar
Venue: Microelectronic Engineering (2008)

Good adhesion strength of thin film stack is desirable for the integrated circuits (IC) manufacturing stage such as chemical mechanical planarisation (CMP). The scratch test and four-point bending test are two most commonly used methods to find the adhesion properties of thin film because of their simplicity and quantifiability. In this research, scratch test is used to find the practical adhesion energy (W"p"a) of thin film stack and four-point bending test is used to find the critical strain energy release rate (G"c). The comparison of W"p"a from scratch test and G"c from four-point bend test reveals that, for the same thin film stack, W"p"a value is comparatively higher than G"c. The scratch test is semi-quantitative, in that the normal load at which a predefined failure event or delamination occurs is defined as a measure of adhesion. However, the four-point bending test is more quantitative in finding the adhesion properties. Thus, for practical application, such as CMP process, the G"c measurements from four-point bending test are recommended as references.
A Computer Simulation Laboratory for Social Theories
Authors: Joseph M. Whitmeyer, Moutaz Khouja, Ted Carmichael, Amar Saric, Chris Eichelberger, Min Sun, Mirsad Hadzikadic
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02 (2008)

We present an agent-based model that allows the user to employ different social theories to try to explain and predict social changes. The model is set in the context of an armed insurgency in a developing country. We demonstrate the capabilities of the model by showing how it simulates a news report-based scenario under different theories and combinations of theories.
Optimal routing for end-to-end guarantees using Network Calculus
Authors: Anne Bouillard, Bruno Gaujal, Sébastien Lagrange, íric Thierry
Venue: Performance Evaluation (2008)

In this paper we show how Network Calculus can be used to compute the optimal route for a flow (w.r.t. end-to-end guarantees on the delay or the backlog) in a network in the presence of cross-traffic. When cross-traffic is independent, the computation is shown to boil down to a functional shortest path problem. Under usual assumptions (concave arrival curves and convex service curves), a simple min-max lemma enables us to solve the problem in polynomial time by a sequence of classical shortest path computations. When cross-traffic perturbs the main flow over more than one node and under blind multiplexing, one can take into account the ''Pay Multiplexing Only Once'' (PMOO) phenomenon identified in [J.B. Schmitt, F.A. Zdarsky, The disco network calculator: A toolbox for worst case analysis. in: Proceedings of Valuetools'06, 2006; J.B. Schmitt, F.A. Zdarsky, I. Martinovic, Performance bounds in feed-forward networks under blind multiplexing. Technical Report 349/06, University of Kaiserslautern, Germany, 2006.]. It enables us to improve bounds on delays and backlogs, but it makes the computation more involved. We provide a formula which gives a service curve for a path with PMOO conditions. It introduces a new multi-dimensional Network Calculus operator and it generalizes a formula in the above reference. Moreover, when arrival (resp. service) curves are affine (resp. convex), we describe an efficient algorithm to compute this formula. We finally show how to adapt our routing algorithms to have optimal end-to-end guarantees for these new bounds on delays and backlogs which take into account PMOO.
Forwarding capacity of an infinite wireless network
Authors: Jarno Nousiainen, Jorma Virtamo, Pasi Lassila
Venue: Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems (2008)

We study the maximal forwarding capacity of a massively dense wireless multi-hop network where a typical path consists of a vast number of hops. In such a network, the macroscopic level, corresponding to the scale of an end-to-end path, and the microscopic level, corresponding to the scale of a single hop, can be separated. At the macroscopic level the task is that of routing, while at the microscopic level the packets are forwarded based on the information received from the macroscopic level. We give a formulation for the forwarding problem and devise simulation algorithms based on an augmentation of the max-flow min-cut theorem for obtaining upper bounds for the maximal forwarding capacity. We compare the upper bounds with feasible forwarding methods and find out that the tightest bound is about three times the highest achieved performance.
A Utility-Based Web Content Sensitivity Mining Approach
Authors: Cheng Wang, Ying Liu, Liheng Jian, Peng Zhang
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03 (2008)

Abnormal remarks on World Wide Web, such as violence, threat, superstition, etc. may disturb the social order and public morality. Most traditional methods filter a page as long as it contains a keyword in a predefined blacklist. Such methods cannot provide a quantitative measure of how sensitive the content is. In this paper, we propose a utility-based Web content sensitivity mining approach. Utility is viewed as the measure of how sensitive a page is. It allows the Internet regulators to take different operations according to different sensitivity values. We apply our approach on a real-world Web dataset. It identified a number of sensitive Web pages that traditional frequency-based methods failed to find. By varying the sensitive values of the keywords, different sets of high sensitivity keywords were discovered.
ELM-Based Agents for Grid Resource Selection
Authors: Guopeng Zhao, Zhiqi Shen, Ailiya, Chunyan Miao
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02 (2008)

Resource selection in Grid involves great dynamics and uncertainties inherited from tasks and resources. The optimal selection of a resource against a task requires fast and intelligent services. Intelligent agent with fast learning capability is promising to resource selection problem in Grid. This paper proposes an Extreme Learning Machine (ELM)-based agent, in which an ELM connectionist module is embedded in an extended Belief-Desire-Intention (BDI) architecture. ELM empowers the agent with fast training and learning speed in the Grid environment. To improve generalization performance a cooperative learning among a group of ELM-based agents is proposed, for which the group decision is summarized upon individual decisions. The experiment results show that ELM-based agents are able to provide intelligent resource selection services, and the proposed cooperative learning outperforms the individual one.