ppxscal/embedding_network huggingface dataset:
Fast and accurate search for non-coding RNA pseudoknot structures in genomes
Authors: Zhibin Huang, Yong Wu, Joseph Robertson, Liang Feng, Russell L. Malmberg, Liming Cai
Venue: Bioinformatics (2008)

Motivation: Searching genomes for non-coding RNAs (ncRNAs) by their secondary structure has become an important goal for bioinformatics. For pseudoknot-free structures, ncRNA search can be effective based on the covariance model and CYK-type dynamic programming. However, the computational difficulty in aligning an RNA sequence to a pseudoknot has prohibited fast and accurate search of arbitrary RNA structures. Our previous work introduced a graph model for RNA pseudoknots and proposed to solve the structure–sequence alignment by graph optimization. Given k candidate regions in the target sequence for each of the n stems in the structure, we could compute a best alignment in time O(ktn) based upon a tree width t decomposition of the structure graph. However, to implement this method to programs that can routinely perform fast yet accurate RNA pseudoknot searches, we need novel heuristics to ensure that, without degrading the accuracy, only a small number of stem candidates need to be examined and a tree decomposition of a small tree width can always be found for the structure graph. Results: The current work builds on the previous one with newly developed preprocessing algorithms to reduce the values for parameters k and t and to implement the search method into a practical program, called RNATOPS, for RNA pseudoknot search. In particular, we introduce techniques, based on probabilistic profiling and distance penalty functions, which can identify for every stem just a small number k (e.g. k ≤ 10) of plausible regions in the target sequence to which the stem needs to align. We also devised a specialized tree decomposition algorithm that can yield tree decomposition of small tree width t (e.g. t ≤ 4) for almost all RNA structure graphs. Our experiments show that with RNATOPS it is possible to routinely search prokaryotic and eukaryotic genomes for specific RNA structures of medium to large sizes, including pseudoknots, with high sensitivity and high specificity, and in a reasonable amount of time. Availability: The source code in C++ for RNATOPS is available at www.uga.edu/RNA-Informatics/software/rnatops/ Contact: cai@cs.uga.edu Supplementary information: The online Supplementary Material contains all illustrative figures and tables referenced by this article.
W4A 2008: a review
Authors: David Sloan, Yeliz Yesilada
Venue: Issue 92 (September 2008) (2008)

The 5th annual International Cross-disciplinary Conference on Web Accessibility (W4A for short) took place alongside WWW 2008 in Beijing, in April 2008. The conference venue was Beijing's International Convention Centre, next door to the Bird's Nest Olympic Stadium, and given the closeness of the conference - in location and timing - to the world's most famous sporting event, it was fitting that the conference theme looked at how accessibility can be addressed as Web user become more active, as content creators. Our theme was "One World, One Web: Surfers become Designers?
Mining search engine query logs via suggestion sampling
Authors: Ziv Bar-Yossef, Maxim Gurevich
Venue: Proceedings of the VLDB Endowment (2008)

Many search engines and other web applications suggest auto-completions as the user types in a query. The suggestions are generated from hidden underlying databases, such as query logs, directories, and lexicons. These databases consist of interesting and useful information, but they are typically not directly accessible. In this paper we describe two algorithms for sampling suggestions using only the public suggestion interface. One of the algorithms samples suggestions uniformly at random and the other samples suggestions proportionally to their popularity. These algorithms can be used to mine the hidden suggestion databases. Example applications include comparison of popularity of given keywords within a search engine's query log, estimation of the volume of commercially-oriented queries in a query log, and evaluation of the extent to which a search engine exposes its users to negative content. Our algorithms employ Monte Carlo methods in order to obtain unbiased samples from the suggestion database. Empirical analysis using a publicly available query log demonstrates that our algorithms are efficient and accurate. Results of experiments on two major suggestion services are also provided.
ASP.NET MVC Framework Preview, 1 edition
Authors: Steven Sanderson
Venue: Firstpress (2008)

The ASP.NET MVC framework is the latest evolution of Microsofts ASP.NET web platform. It introduces a radically new highproductivity programming model, promotes cleaner code architecture, supports testdriven development, and provides powerful extensibility, combined with all the benefits of ASP.NET 3.5. ASP.NET MVC Framework Preview is a first look at this technologys main features, designed to give you a head start getting to grips with this powerful new technology. What youll learn A solid architectural background to ASP.NET MVC, including ModelViewController and REST concepts Who is this book for? This book is for web developers with a basic knowledge of ASP.NET and C#, who want, or need, to start using the new ASP.NET MVC framework.
HELIQUEST
Authors: Romain Gautier, Dominique Douguet, Bruno Antonny, Guillaume Drin
Venue: Bioinformatics (2008)

Summary: HELIQUEST calculates the physicochemical properties and amino acid composition of an α-helix and screens databank to identify protein segments possessing similar features. This server is also dedicated to mutating helices manually or automatically by genetic algorithm to design analogues of defined features. Availability: http://heliquest.ipmc.cnrs.fr Contact: gautier@ipmc.cnrs.fr
Activity index variance as an indicator of the number of signal sources
Authors: Rok Istenic, Damjan Zazula
Venue: WSEAS Transactions on Signal Processing (2008)

In this paper we introduce a novel technique that can be used as an indicator of the number of active signal sources in convolutive signal mixtures. The technique is designed so that the number of sources is estimated using only recorded signals and some marginal information, such as possible minimum and maximum triggering frequencies of sources, but no information on mixing matrix, other parameters of signal sources, etc. Our research is based on the convolution kernel compensation method (CKC), which is a blind source separation method. First, a correlation matrix of the recorded signals is estimated. Next, a measure of the global activity of the signal sources, called activity index, is introduced. The exact analytical model of the activity index variance was derived for the purpose of the estimation of the number of signal sources. Using the analytical model, the number of active signal sources can be estimated if some a priori marginal information is available. We evaluated these marginal parameter values in extensive simulations of compound signals. The number of sources, their lengths, signal-to-noise ratio, source triggerings, and the number of measurements were randomly combined in preselected ranges. By using the established marginal parameter values and increasing extension factors, the model of the activity index variance was deployed to estimate the number of signal sources. The estimation results using synthetic signal mixtures are very promising.
Dynamic packaging in e-retailing with stochastic demand over finite horizons: A Q-learning approach
Authors: Yan Cheng
Venue: Expert Systems with Applications: An International Journal (2009)

This paper investigates how intelligent an agent may utilize a Q-learning approach, a simulation-based stochastic technique, to make optimal dynamic packaging decision in e-retailing setting. When the practical application of dynamic packaging involves a large number of products, normal Q-learning approach would encounter two major problems due to excessively large state space. First, learning the Q-values in tabular form may be infeasible because of the excessive amount of memory needed to store the table. Second, rewards in the state space may be so sparse that with random exploration they will only be discovered extremely slowly. This paper first describes the state-dependent and event-driven nature of the dynamic packaging problem with a Markov decision process model, then proposes a states generalization approach based on distortion measure, and finally puts forward a heuristic based exploration/exploitation policy which is used to improve the convergence in Q-learning. We validate our approach in a simulated test.
New 500 m spatial resolution land cover map of the western insular Southeast Asia region
Authors: J. Miettinen, C. M. Wong, S. C. Liew
Venue: International Journal of Remote Sensing (2008)

This letter presents the methodology and accuracy assessment of a new 500 m spatial resolution land cover map of the western part of insular Southeast Asia. The map was produced using 250 Moderate Resolution Imaging Spectroradiometer (MODIS) images (acquired 1 January-2 July 2007), elevation information and peatland maps. The map covers the Malaysian Peninsula and the major islands of Sumatra, Java and Borneo, in addition to numerous smaller islands. The classification scheme of 12 classes reflects the special characteristics of land cover of insular Southeast Asia. With an overall accuracy of 82%, the map provides reliable new information on the current land cover distribution in this region, which is experiencing rapid land cover changes.
Dynamic question generation system for web-based testing using particle swarm optimization
Authors: Shu-Chen Cheng, Yen-Ting Lin, Yueh-Min Huang
Venue: Expert Systems with Applications: An International Journal (2009)

One aim of testing is to identify weaknesses in students' knowledge. Computerized tests are now one of the most important ways to judge learning, and, selecting tailored questions for each learner is a significant part of such tests. Therefore, one current trend is that computerized adaptive tests (CATs) not only assist teachers in estimating the learning performance of students, but also facilitate understanding of problems in their learning process. These tests, must effectively and efficiently select questions from a large-scale item bank, and to cope with this problem we propose a dynamic question generation system for web-based tests using the novel approach of particle swarm optimization (PSO). The dynamic question generation system is built to select tailored questions for each learner from the item bank to satisfy multiple assessment requirements. Furthermore, the proposed approach is able to efficiently generate near-optimal questions that satisfy multiple assessment criteria. With a series of experiments, we compare the efficiency and efficacy of the PSO approach with other approaches. The experimental results show that the PSO approach is suitable for the selection of near-optimal questions from large-scale item banks.
Fuzzy modeling for data cleaning in sensor networks
Authors: Alfredo Petrosino, Antonino Staiano
Venue: International Journal of Hybrid Intelligent Systems (2008)

Sensor networks have become an important source of data with numerous applications in monitoring various real-life phenomena as well as industrial applications and traffic control. Sensor data is subject to several sources of errors as the data captured from the physical world through these sensor devices tend to be incomplete, noisy, and unreliable. Such errors may seriously impact the answer to any query posed to the sensors yielding imprecise or even incorrect and misleading answers for critical decisions or activation of actuators. Play, thus, a fundamental role data cleaning procedures to overcome these problems. The most recent applications in this research field conceive the use of machine learning techniques. Machine learning approaches have assumed a prominent role in data analysis especially for their ability to deal with very large amount of noisy and incomplete data. In this paper, we propose the application of the well known ANFIS model for reducing the uncertainty associated with the data thus obtaining a more accurate estimate of sensor readings. The obtained cleaning results demonstrate its effectiveness if the cleaning model has to be implemented at sensor level rather than at base-station level.
Hopping on Even Ground and Up Stairs with a Single Articulated Leg
Authors: Q. Guo, C. J. Macnab, J. K. Pieper
Venue: Journal of Intelligent and Robotic Systems (2008)

This paper presents a method for generating gaits for a one-legged articulated hopping robot. A static optimization procedure produces the initial joint velocities for the flight phase, using the principle of conservation of angular momentum and assuming (nearly) passive flight. Two novel objective functions for this static optimization enable one to choose different gaits by simply changing a few parameters. A dynamic optimization procedure yields a solution for the flight trajectory that minimizes control effort. The stance phase (when the foot is touching the ground) becomes a standard two point boundary value problem, also solved with a dynamic optimization procedure. During the stance phase, the physical joint limitations, ground reaction forces, and the trajectory of the zero-moment point all constrain the solution. After these single-phase optimizations, a complete-cycle optimization procedure, incorporating both flight and stance phases, further reduces the control effort and balances the motion phases. In simulation, the leg hops on even ground and up stairs, exhibiting energy-efficient and intuitively satisfying gaits.
Modeling per-flow throughput and capturing starvation in CSMA multi-hop wireless networks
Authors: Michele Garetto, Theodoros Salonidis, Edward W. Knightly
Venue: IEEE/ACM Transactions on Networking (TON) (2008)

Multi-hop wireless networks employing random access protocols have been shown to incur large discrepancies in the throughputs achieved by the flows sharing the network. Indeed, flow throughputs can span orders of magnitude from near starvation to many times greater than the mean. In this paper, we address the foundations of this disparity. We show that the fundamental cause is not merely differences in the number of contending neighbors, but a generic coordination problem of CSMA-based random access in a multi-hop environment. We develop a new analytical model that incorporates this lack of coordination, identifies dominating and starving flows and accurately predicts per-flow throughput in a large-scale network.We then propose metrics that quantify throughput imbalances due to the MAC protocol operation. Our model and metrics provide a deeper understanding of the behavior of CSMA protocols in arbitrary topologies and can aid the design of effective protocol solutions to the starvation problem.
Development of a two-dimensional agent-based model for chronic chagasic cardiomyopathy after stem cell transplantation
Authors: Viviane Galvão, José Garcia Vivas Miranda, Ricardo Ribeiro-dos-Santos
Venue: Bioinformatics (2008)

Motivation: A significant issue in stem cell therapy is to understand the role of this type of cell in the tissue regeneration. To explain this mechanism, an experimental study has quantified that the bone marrow cell transplantation decreases the number of inflammatory cells and reduces the fibrosis area in chagasic mice. Using this experimental data, we have developed an agent-based computational model to investigate the regeneration of the chronic chagasic cardiomyopathy after bone marrow stem cell transplantation. Results: Our model includes six different types of agents: inflammatory cell, fibrosis area, cardiomyocyte, proinflammatory cytokine tumor necrosis factor-α, Trypanosoma cruzi parasite and bone marrow stem cell. This latter promotes apoptosis in inflammatory cells, reduction in the fibrosis area and can differentiate into cardiomyocyte. Proinflammatory cytokine tumor necrosis factor-α can increase the fibrosis area and T.cruzi can increase the number of inflammatory cells. Our results for both apoptosis of inflammatory cells and reduction in the fibrosis area were compared with experimental data. They suggest that the concentration pattern is the most important factor to characterize the kinetics of cardiac tissue regeneration after bone marrow stem cell transplantation. Availability: The source code of our software is available online at www.vivas.ufba.br/bone/bone.zip Contact: vivianegalvao@uefs.br Supplementaty information:Supplementary data are available at Bioinformatics online.
Parallel Programming with Transactional Memory
Authors: Ulrich Drepper
Venue: Queue (2008)

While sometimes even writing regular, single-threaded programs can be quite challenging, trying to split a program into multiple pieces that can be executed in parallel adds a whole dimension of additional problems. Drawing upon the transaction concept familiar to most programmers, transactional memory was designed to solve some of these problems and make parallel programming easier. Ulrich Drepper from Red Hat shows us how it's done.
Dynamic active probing of helpdesk databases
Authors: Shenghuo Zhu, Tao Li, Zhiyuan Chen, Dingding Wang, Yihong Gong
Venue: Proceedings of the VLDB Endowment (2008)

Helpdesk databases are used to store past interactions between customers and companies to improve customer service quality. One common scenario of using helpdesk database is to find whether recommendations exist given a new problem from a customer. However, customers often provide incomplete or even inaccurate information. Manually preparing a list of clarification questions does not work for large databases. This paper investigates the problem of automatic generation of a minimal number of questions to reach an appropriate recommendation. This paper proposes a novel dynamic active probing method. Compared to other alternatives such as decision tree and case-based reasoning, this method has two distinctive features. First, it actively probe the customer to get useful information to reach the recommendation, and the information provided by customer will be immediately used by the method to dynamically generate the next questions to probe. This feature ensures that all available information from the customer is used. Second, this method is based on a probabilistic model, and uses a data augmentation method which avoids overfitting when estimating the probabilities in the model. This feature ensures that the method is robust to databases that are incomplete or contain errors. Experimental results verify the effectiveness of our approach.
Fuzzy multicriteria R&D project selection with a real options valuation model
Authors: A. Çagri Tolga
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2008)

Real options valuation is a financial technique for evaluating investments under conditions of uncertainty, particularly uncertainty associated with market variables such as future product demand or the future value of an asset. The real option value of the investment opportunity is what a value-maximizing firm would pay the right to undertake the investment project with its inherent decision points. This paper proposes a fuzzy multi-criteria R&D project selection methodology based on the hierarchical fuzzy TOPSIS, which includes a fuzzy real options valuation model.
Duty Cycle Stabilization in Semi-mobile Wireless Networks
Authors: Jing Li, Anish Arora
Venue: Proceedings of the 10th International Symposium on Stabilization, Safety, and Security of Distributed Systems (2008)

Coordinating the duty cycles of nodes in low power wireless networks raises challenging stabilization issues. In this paper, we show how to maintain duty-cycle coordination across the partitions of a static network of nodes. The idea is to synchronize the wakeup times of the nodes based on information carried by mobile "token" nodes between the otherwise disconnected partitions; the stabilization challenge is to deal with the corruption of state in both the static nodes and the mobile tokens. Our basic protocol assumes zero or more token nodes traversing disconnected static nodes in a circular order without overtaking each other. Refinements of our protocol accommodate richer patterns of token traversal and speeds.
Supporting business intelligence by providing ontology-based end-user information self-service
Authors: Michael Spahn, Joachim Kleb, Stephan Grimm, Stefan Scheidl
Venue: Proceedings of the first international workshop on Ontology-supported business intelligence (2008)

Business users need to analyse changing sets of information to effectively support their working tasks. Due to the complexity of enterprise systems and available tools, especially technically unskilled users face considerable challenges when trying to flexibly retrieve needed data in an ad-hoc manner. As a consequence, available data is limited to information artefacts like queries or reports which have been predefined for them by IT experts. To improve information self-service capabilities of business users, we present an ontology-based architecture and end-user tool, enabling easy data access and query creation for business users. Our approach is based on a semantic middleware integrating data from heterogeneous information systems and providing a comprehensible data model in the form of a business level ontology (BO). We show how our end-user tool Semantic Query Designer (SQD) enables convenient navigation and query building upon the BO, and illustrate its usage and the processing of data over all layers of our system architecture in detail, using a comprehensible use case example. As flexible query creation is a crucial precondition of leveraging the usage of enterprise data, we contribute to the enablement of business users of making better informed decisions, thus increasing effectiveness and efficiency of business processes.
Towards red-edge positions less sensitive to canopy biophysical parameters for leaf chlorophyll estimation using properties optique spectrales des feuilles (PROSPECT) and scattering by arbitrarily inclined leaves (SAILH) simulated data
Authors: M. A. Cho, A. K. Skidmore, C. Atzberger
Venue: International Journal of Remote Sensing (2008)

Several methods for extracting the chlorophyll sensitive red-edge position (REP) from hyperspectral data are reported in literature. This study is a continuation of a recent paper published as 'A new technique for extracting the red edge position from hyperspectral data: the linear extrapolation method'. The method was validated experimentally for estimation of foliar nitrogen concentrations of rye, maize and mixed grass/herb. The objective of this study was to test the utility of the linear extrapolation method under different conditions including variable canopy biophysical parameters, solar zenith angle, sensor noise and spectral bandwidth. REPs were extracted from synthetic canopy spectra that were simulated using properties optique spectrales des feuilles (PROSPECT) and scattering by arbitrarily inclined leaves (SAILH) radiative transfer models. REPs extracted by the linear extrapolation method involving wavebands at 680, 694, 724 and 760 nm produced the highest correlation (R 2 = 0.75) with leaf chlorophyll content with minimal effects of leaf and canopy biophysical confounders (leaf area index, leaf inclination distribution and leaf dry matter content) compared to traditional techniques including the linear interpolation, inverted Gaussian modelling and polynomial fitting techniques. In addition, the new technique is insensitive to changes in solar zenith angle. However, the advantage of using the linear extrapolation method compared to the various alternative methods diminishes with increasing sensor noise and decreasing spectral resolution. In summary, the linear extrapolation technique confirms its high potential for leaf chlorophyll estimation. The efficacy of the technique under field conditions needs to be established.