ppxscal/embedding_network huggingface dataset:
Genetic modification of flux for flux prediction of mutants
Authors: Quanyu Zhao, Hiroyuki Kurata
Venue: Bioinformatics (2009)

Motivation: Gene deletion and overexpression are critical technologies for designing or improving the metabolic flux distribution of microbes. Some algorithms including flux balance analysis (FBA) and minimization of metabolic adjustment (MOMA) predict a flux distribution from a stoichiometric matrix in the mutants in which some metabolic genes are deleted or non-functional, but there are few algorithms that predict how a broad range of genetic modifications, such as over-and underexpression of metabolic genes, alters the phenotypes of the mutants at the metabolic flux level. Results: To overcome such existing limitations, we develop a novel algorithm that predicts the flux distribution of the mutants with a broad range of genetic modification, based on elementary mode analysis. It is denoted as genetic modification of flux (GMF), which couples two algorithms that we have developed: modified control effective flux (mCEF) and enzyme control flux (ECF). mCEF is proposed based on CEF to estimate the gene expression patterns in genetically modified mutants in terms of specific biological functions. GMF is demonstrated to predict the flux distribution of not only gene deletion mutants, but also the mutants with underexpressed and overexpressed genes in Escherichia coli and Corynebacterium glutamicum. This achieves breakthrough in the a priori flux prediction of a broad range of genetically modified mutants. Contact: kurata@bio.kyutech.ac.jp Supplementary information: Supplementary file and programs are available at Bioinformatics online or http://www.cadlive.jp.
Reasoning with spatial plans on the semantic web
Authors: Rinke Hoekstra, Radboud Winkels, Erik Hupkes
Venue: Proceedings of the 12th International Conference on Artificial Intelligence and Law (2009)

There are several reasons why citizens, businesses and civil servants need access to regulations. Unfortunately, traditional approaches that aim to provide this access fall short, especially in the area of spatial planning. Fairly straight-forward questions such as "where will I be able to perform this kind of activity" or "is this activity allowed here" are not answered automatically by current systems. There are many attempts to create one-stop-shop front-ends to eGovernment, but these are seldom built from the perspective of the user. This paper describes our work on what we call a 'Legal Atlas'. Using various Semantic Web technologies we combine distributed geospatial data, textual data and controlled vocabularies in order to support users in answering questions such as those mentioned above.
Characterizing fault tolerance in genetic programming
Authors: Daniel Lombraña González, Francisco Fernández de Vega, Henri Casanova
Venue: Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems (2009)

Evolutionary Algorithms (EAs), and particularly Genetic Programming (GP), are techniques frequently employed to solve difficult real-life problems, which can require up to days or months of computation. One approach to reduce the time to solution is to use parallel computing on distributed platforms. Distributed platforms are prone to failures, and when these platforms are large and/or low-cost, failures are expected events rather than catastrophic exceptions. Therefore, fault tolerance and recovery techniques often become necessary. It turns out that Parallel GP (PGP) applications have an inherent ability to tolerate failures. This ability is quantified via simulation experiments performed using failure traces from real-world distributed platforms, namely, desktop grids (DGs), for two well-known GP problems. A simple technique is then proposed by which PGP applications can better tolerate the different, and often high, failures rates seen in different platforms.
Interactive and Dynamic Graphics for Data Analysis With R and GGobi, 1st edition
Authors: Dianne Cook, Deborah F. Swayne
Venue:  (2007)

This richly illustrated book describes the use of interactive and dynamic graphics as part of multidimensional data analysis. Chapters include clustering, supervised classification, and working with missing values. A variety of plots and interaction methods are used in each analysis, often starting with brushing linked low-dimensional views and working up to manual manipulation of tours of several variables. The role of graphical methods is shown at each step of the analysis, not only in the early exploratory phase, but in the later stages, too, when comparing and evaluating models. All examples are based on freely available software: GGobi for interactive graphics and R for static graphics, modeling, and programming. The printed book is augmented by a wealth of material on the web, encouraging readers follow the examples themselves. The web site has all the data and code necessary to reproduce the analyses in the book, along with movies demonstrating the examples. The book may be used as a text in a class on statistical graphics or exploratory data analysis, for example, or as a guide for the independent learner. Each chapter ends with a set of exercises. The authors are both Fellows of the American Statistical Association, past chairs of the Section on Statistical Graphics, and co-authors of the GGobi software. Dianne Cook is Professor of Statistics at Iowa State University. Deborah Swayne is a member of the Statistics Research Department at AT&T Labs.
Object discovery in high-resolution remote sensing images: a semantic perspective
Authors: Dihua Guo, Hui Xiong, Vijayalakshmi Atluri, Nabil R. Adam
Venue: Knowledge and Information Systems (2009)

Given its importance, the problem of object discovery in high-resolution remote-sensing (HRRS) imagery has received a lot of attention in the literature. Despite the vast amount of expert endeavor spent on this problem, more efforts have been expected to discover and utilize hidden semantics of images for object detection. To that end, in this paper, we address this problem from two semantic perspectives. First, we propose a semantic-aware two-stage image segmentation approach, which preserves the semantics of real-world objects during the segmentation process. Second, to better capture semantic features for object discovery, we exploit a hyperclique pattern discovery method to find complex objects that consist of several co-existing individual objects that usually form a unique semantic concept. We consider the identified groups of co-existing objects as new feature sets and feed them into the learning model for better performance of image retrieval. Experiments with real-world datasets show that, with reliable segmentation and new semantic features as starting points, we can improve the performance of object discovery in terms of various external criteria.
Temporal mining for interactive workflow data analysis
Authors: Michele Berlingerio, Fabio Pinelli, Mirco Nanni, Fosca Giannotti
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

In the past few years there has been an increasing interest in the analysis of process logs. Several proposed techniques, such as workflow mining, are aimed at automatically deriving the underlying workflow models. However, current approaches only pay little attention on an important piece of information contained in process logs: the timestamps, which are used to define a sequential ordering of the performed tasks. In this work we try to overcome these limitations by explicitly including time in the extracted knowledge, thus making the temporal information a first-class citizen of the analysis process. This makes it possible to discern between apparently identical process executions that are performed with different transition times between consecutive tasks. This paper proposes a framework for the user-interactive exploration of a condensed representation of groups of executions of a given process. The framework is based on the use of an existing mining paradigm: Temporally-Annotated Sequences (TAS). These are aimed at extracting sequential patterns where each transition between two events is annotated with a typical transition time that emerges from input data. With the extracted TAS, which represent sets of possible frequent executions with their typical transition times, a few factorizing operators are built. These operators condense such executions according to possible parallel or possible mutual exclusive executions. Lastly, such condensed representation is rendered to the user via the exploration graph, namely the Temporally-Annotated Graph (TAG). The user, the domain expert, is allowed to explore the different and alternative factorizations corresponding to different interpretations of the actual executions. According to the user choices, the system discards or retains certain hypotheses on actual executions and shows the consequent scenarios resulting from the coresponding re-aggregation of the actual data.
HxH: a hop-by-hop transport protocol for multi-hop wireless networks
Authors: Daniel Scofield, Lei Wang, Daniel Zappala
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

TCP can perform poorly in multi-hop wireless networks due to problems that arise with contention and mobility. End-to-end protocols are at an inherent disadvantage in trying to solve these problems because their feedback loop operates over multiple wireless hops, which makes it difficult to diagnose problems that occur several hops away and hinders their ability to adapt to changing network conditions. In this paper, we design HxH, a hop-by-hop transport protocol that uses credit-based congestion control and reverse ACKs to solve many of the problems observed with TCP. We use a simulation study to demonstrate that our hop-by-hop approach allows HxH to respond quickly to changing network conditions and to exploit the unique characteristics of wireless networks to reduce overhead. We show that HxH greatly increases throughput and improves fairness, as compared to several end-to-end protocols, in both mesh and mobile ad hoc networks.
Combining feature spaces for classification
Authors: Theodoros Damoulas, Mark A. Girolami
Venue: Pattern Recognition (2009)

In this paper we offer a variational Bayes approximation to the multinomial probit model for basis expansion and kernel combination. Our model is well-founded within a hierarchical Bayesian framework and is able to instructively combine available sources of information for multinomial classification. The proposed framework enables informative integration of possibly heterogeneous sources in a multitude of ways, from the simple summation of feature expansions to weighted product of kernels, and it is shown to match and in certain cases outperform the well-known ensemble learning approaches of combining individual classifiers. At the same time the approximation reduces considerably the CPU time and resources required with respect to both the ensemble learning methods and the full Markov chain Monte Carlo, Metropolis-Hastings within Gibbs solution of our model. We present our proposed framework together with extensive experimental studies on synthetic and benchmark datasets and also for the first time report a comparison between summation and product of individual kernels as possible different methods for constructing the composite kernel matrix.
Mixing behaviour-dependent and -independent tactics in multi-issue negotiation
Authors: Jan Richter, Ryszard Kowalczyk
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

We present mechanisms for the creation of strategies by mixing behaviour-dependent and -independent tactics in multi-issue negotiation. The traditional linear weighted combination of tactics may generate non-monotonic utilities over time even in the case of a monotonic series of opponent's offers. The proposed methods guarantee monotonic utilities, which can improve negotiation outcomes in many scenarios.
Compressing terrain elevation datasets
Authors: Wm. Randolph Franklin
Venue:  (2008)

A novel compression scheme named Overdetermined Compression (ODETCOM) for 16 bit Digital Elevation Models (DEMs) is proposed. We achieve excellent lossless compression ratios, surpassing the competing image compression algorithms like variants of JPEG (JPEG-LS and JPEG 2000). We also achieve a very competitive near-lossless (lossy with error bounds) compression, often surpassing the compression of JPEG-LS by a large margin.ODETCOM is based on a causal template model. We use a novel approach to train our model. An overdetermined system of linear equations is used to compute our model's parameters. We minimize the second norm of the residual to strike a balance between the conflicting predictor requirements. The error between the prediction and the sample value is compressed. Using our method we manage to achieve compression rates consistently better than the lossless JPEG variants.
Tracking and Segmentation of Highway Vehicles in Cluttered and Crowded Scenes
Authors: Goo Jun, J. K. Aggarwal, Muhittin Gokmen
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

Monitoring highway traffic is an important application of computer vision research. In this paper, we analyze congested highway situations where it is difficult to track individual vehicles in heavy traffic because vehicles either occlude each other or are connected together by shadow. Moreover, scenes from traffic monitoring videos are usually noisy due to weather conditions and/or video compression. We present a method that can separate occluded vehicles by tracking movements of feature points and assigning over-segmented image fragments to the motion vector that best represents the fragment's movement. Experiments were conducted on traffic videos taken from highways in Turkey, and the proposed method can successfully separate vehicles in overpopulated and cluttered scenes.
Clustering constrained symbolic data
Authors: Francisco de A. T. de Carvalho, Marc Csernel, Yves Lechevallier
Venue: Pattern Recognition Letters (2009)

Dealing with multi-valued data has become quite common in both the framework of databases as well as data analysis. Such data can be constrained by domain knowledge provided by relations between the variables and these relations are expressed by rules. However, such knowledge can introduce a combinatorial increase in the computation time depending on the number of rules. In this paper, we present a way to cluster such data in polynomial time. The method is based on the following: a decomposition of the data according to the rules, a suitable dissimilarity function and a clustering algorithm based on dissimilarities.
Web Services-Based Parallel Replicated Discrete Event Simulation for Large-Scale Simulation Optimization
Authors: Taejong Yoo, Hyunbo Cho, Enver Yücesan
Venue: Simulation (2009)

The exciting developments in the World Wide Web (WWW) have revived interest in computer simulation for modeling, particularly for conceiving simulation languages and building model libraries that can be assembled and executed over the Internet, and for analysis, particularly for developing simulation optimization algorithms for parallel experimentation. This paper contributes to this second stream of research by introducing a framework for Optimization via Simulation (OvS) through Parallel Replicated Discrete Event Simulation (PRDES). In particular, we combine Nested Partitions (NP) and Extended Optimal Computing Budget Allocation (EOCBA) to provide an efficient framework for PRDES experiments. The number of candidate alternatives to be evaluated can be reduced by the application of NP. EOCBA, a modification of the Optimal Computing Budget Allocation (OCBA) for PRDES, minimizes the number of simulation replications required to evaluate a particular alternative by allocating computing resources to potentially critical alternatives. We deploy web services technologies based on the Java Axis and .NET framework to create a viable infrastructure for heterogeneous PRDES systems. This approach, which receives increasing attention under the banners of `grid computing' and `cloud computing,' further promotes reusability, scalability, and interoperability. Experimental results with a prototype implementation not only furnish a proof of concept but also illustrate significant gains in simulation efficiency with PRDES. The proposed concept and techniques can also be applied to simulation models that require coordination and interoperation in heterogeneous environments, such as decentralized supply chains.
An Algorithm for Unrestored Flow Optimization in Survivable Networks Based on p-Cycles
Authors: Adam Smutnicki
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

This paper provides compound algorithm for Unrestorable Flow Optimisation (UFO) problem formulated for computer networks protected by p-cycles, created on the base of mathematical model and solution approaches proposed in our complementary paper [1]. Components of the algorithm have been selected carefully and then experimentally tested in order to compose the best final algorithm. Results of the wide computer tests on common benchmarks have been also presented as well as some practical conclusions following from the research made.
Introduction to Part III
Authors: Heiner Stuckenschmidt, Christine Parent, Stefano Spaccapietra
Venue: Modular Ontologies: Concepts, Theories and Techniques for Knowledge Modularization (2009)

Another valid view on modularity is ontologies that differs from the one taken in part II of the book is the idea that modules are not created by splitting up a large ontology into smaller parts but by composing a number of small ontologies that have been created independently of each other into a larger model. In this scenario that was investigated in more detail in chapter 4 the original ontologies become modules in a large modular ontology. The advantage of this scenario is not easier maintenance and analysis of the overall system - in fact integrating different ontologies normally makes both more complicated compared to the individual models. The rationale for this approach is the benefit of being able to reuse knowledge that has been created by other people as well as the Data that might be associated with the ontologies to be integrated. This scenario is much closer to the original vision of the semantic web, where information sources describe their information using ontologies and information is found and reused by linking it on the level of ontologies thus creating a system of interlinked ontologies in which information can be interpreted in a uniform way.
Empirical examination of effects of web assurance seals on perceived level of assurance and price tolerance with a focus being placed on cpa-associated seals
Authors: Richard A. Rivers
Venue:  (2008)

Since the beginning of e-commerce, trustworthiness of commercial web sites has been a constant issue, and, very likely, it will continue to be. Soon after the start of e-commerce, website assurance seal services emerged on the market, for the purpose of addressing online trust issues. As of 2008, web assurance seals have been around for more than ten years in B2C e-commerce. This study tested if multiple displays of web assurance seals had an incremental effect on perceived assurance levels, and if accounting-associated seals had any distinguishing effect compared with non-accounting-associated seals. Further, the relationship between perceived assurance levels and the maximum prices that online consumers were willing to pay was tested. The results of the study showed that multiple displays of assurance seals increased perceived assurance levels significantly, but only by a marginal amount, and that there was little relationship between level of perceived assurance and maximum price. Accounting-associated assurance seals turned out to share very similar results with non-accounting-associated seals. However, it was found that accounting-associated seals had similar results at significantly higher levels than non-accounting-associated seals; namely, compared with non-accounting-associated seals, accounting-associated seals raised perceived assurance levels higher and maximum tolerable prices higher than non-accounting-associated seals. Key words: e-commerce, B2C, online trust, website assurance seals, multiple displays, assurance level, perception, accounting-associated, CPA-associated, and price tolerance.
Electrochromism and Electrochromic Devices, 1st edition
Authors: Paul Monk, Roger Mortimer, David Rosseinsky
Venue:  (2007)

Electrochromic materials, both organic and inorganic, have widespread applications in light-attenuation, displays and analysis. Written in an accessible manner, this book provides a comprehensive treatment of all types of electrochromic systems and their many applications. Coverage develops from electrochromic scope and history to new searching presentations of optical quantification and theoretical mechanistic models. Non-electrode electrochromism and photo-electrochromism are summarised, with updated comprehensive reviews of electrochromic oxides (tungsten-trioxide particularly), metal co-ordination complexes and metal-cyanometallates, viologens and other organics; and more recent exotics such as fullerenes, hydrides, and conjugated electroactive polymers are also covered. The book concludes by examining device construction and durability. With an extensive bibliography, recent advances in the field, modern applications and a step-by-step development from simple examples to sophisticated theories, this book is ideal for researchers in materials science, polymer science, electrical engineering, physics, chemistry, bioscience and (applied) optoelectronics.
Linear control design under phase constraints
Authors: D. V. Balandin, M. M. Kogan
Venue: Automation and Remote Control (2009)

A new design method is proposed for linear stabilizing controllers which satisfy the given constraints on the phase variables and control input and minimize the upper bound on the maximum deviation of the plant output. The method is based on the apparatus of linear matrix inequalities; the theory is exemplified via the linear shock absorber design.
Learning to Select Object Recognition Methods for Autonomous Mobile Robots
Authors: Reinaldo A. C. Bianchi, Arnau Ramisa, Ramón López de Mántaras
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Selecting which algorithms should be used by a mobile robot computer vision system is a decision that is usually made a priori by the system developer, based on past experience and intuition, not systematically taking into account information that can be found in the images and in the visual process itself to learn which algorithm should be used, in execution time. This paper presents a method that uses Reinforcement Learning to decide which algorithm should be used to recognize objects seen by a mobile robot in an indoor environment, based on simple attributes extracted on-line from the images, such as mean intensity and intensity deviation. Two state-of-the-art object recognition algorithms can be selected: the constellation method proposed by Lowe together with its interest point detector and descriptor, the Scale-Invariant Feature Transform and a bag of features approach. A set of empirical evaluations was conducted using a household mobile robots image database, and results obtained shows that the approach adopted here is very promising.