ppxscal/embedding_network huggingface dataset:
Online FCMAC-BYY Model with Sliding Window
Authors: Jiacai Fu, Thi Tra Dang, Minh Nhut Nguyen, Daming Shi
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

The online Bayesian Ying Yang (BYY) learning using clustering algorithm has been recently applied to Fuzzy CMAC in order to find the optimal centroids and widths of the fuzzy clusters. However, this BYY model is based on wholly-database, in which each data has a uniform contribution in forecasting future value, but it is not suitable for online applications in which the recent data are considered as more relevant. This research aims to propose an online learning algorithm for FCMAC-BYY based on sliding window. The experimental results show that the proposed model outperforms the existing representative techniques.
Foundations of Systems Biology: Using Cell Illustrator and Pathway Databases, 1st edition
Authors: Masao Nagasaki, Ayumu Saito, Atsushi Doi, Hiroshi Matsuno, Satoru Miyano
Venue: Computational Biology (2009)

Navigating safely through a wealth of genome, protein and metabolite information, as well as a host of information processing tools, without getting lost is crucial for successful research in and teaching of - molecular biology. This concise, easy-to-follow textbook/guide serves as a valuable introduction to contemporary cell biology for readers and offers insight into the key research directions in the field. It begins with an overview of existing tools for finding, designing and investigating metabolic, genetic, signalling and other network databases. This practical guide then introduces Cell Illustrator, a software tool for biological pathway modelling and simulation, developed by the authors. In-depth discussion reveals how this tool can be used for creating, analysing and simulating biological models, thereby explicating and testing current understanding of basic biological processes. Readers do not require prior knowledge of differential equations or programming. Features: Provides many helpful learning aids, such as detailed examples throughout, and exercises and solutions Designed and structured to be part of a semester-long course Discusses the computational functionalities required for Systems Biology Addresses practical issues surrounding software tools Introduces the current big bio-databases such as TRANSPATH by Biobase, and explains why and how they can be used to develop and support systems biology research Includes a CDrom containing Cell Illustrator that allows readers to create highly complex pathways and simulations Explains important pathway databases and software tools, together with their related concepts Guides the reader to model pathways in a step-by-step and clear manner Contains a Foreword written by Professor Andreas Dress, Director CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences Written for undergraduates, this reader-friendly introduction to the field of Systems Biology offers insight and teaches sound expertise in the subject. It will also prove valuable to graduate students and professionals wishing to develop and support their systems-biology research.
Semantic Activity Recognition
Authors: Monique Thonnat
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Extracting automatically the semantics from visual data is a real challenge. We describe in this paper how recent work in cognitive vision leads to significative results in activity recognition for visualsurveillance and video monitoring. In particular we present work performed in the domain of video understanding in our PULSAR team at INRIA in Sophia Antipolis. Our main objective is to analyse in real-time video streams captured by static video cameras and to recognize their semantic content. We present a cognitive vision approach mixing 4D computer vision techniques and activity recognition based on a priori knowledge. Applications in visualsurveillance and healthcare monitoring are shown. We conclude by current issues in cognitive vision for activity recognition.
Gas Concentration Forecasting Based on Support Vector Regression in Correlation Space via KPCA
Authors: Jian Cheng, Jian-Sheng Qian, Guang-Dong Niu, Yi-Nan Guo
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

Gas concentration is one of key factors which influence safe production of coal mine, and it is very important to forecast gas concentration accurately for ensuring the coal mine safety. A novel approach is presented to forecast gas concentration based on support vector regression (SVR) in correlation space reconstructed by kernel principal component analysis (KPCA). A two-stage architecture is proposed to improve its prediction accuracy and generalization performance for gas concentration forecasting. In the first stage, KPCA is adopted to extract features and obtain kernel principal components, so the correlation space of gas concentration is reconstructed according to the accumulative contribution ratio. Then, in the second stage, support vector regression (SVR) is employed for forecasting gas concentration, which hyperparameters are selected by adaptive chaotic cultural algorithm (ACCA). The approach is compared with the forecasting model in whole space of gas concentration. The simulation shows that SVR model in correlation space using KPCA performs much better than that without correlation analysis.
Unified detection and recognition for reading text in scene images
Authors: Allen R. Hanson, Erik G. Learned-Miller
Venue:  (2008)

Although an automated reader for the blind first appeared nearly two-hundred years ago, computers can currently "read" document text about as well as a seven-year-old. Scene text recognition brings many new challenges. A central limitation of current approaches is a feed-forward, bottom-up, pipelined architecture that isolates the many tasks and information involved in reading. The result is a system that commits errors from which it cannot recover and has components that lack access to relevant information. We propose a system for scene text reading that in its design, training, and operation is more integrated. First, we present a simple contextual model for text detection that is ignorant of any recognition. Through the use of special features and data context, this model performs well on the detection task, but limitations remain due to the lack of interpretation. We then introduce a recognition model that integrates several information sources, including font consistency and a lexicon, and compare it to approaches using pipelined architectures with similar information. Next we examine a more unified detection and recognition framework where features are selected based on the joint task of detection and recognition, rather than each task individually. This approach yields better results with fewer features. Finally, we demonstrate a model that incorporates segmentation and recognition at both the character and word levels. Text with difficult layouts and low resolution are more accurately recognized by this integrated approach. By more tightly coupling several aspects of detection and recognition, we hope to establish a new unified way of approaching the problem that will lead to improved performance. We would like computers to become accomplished grammar-school level readers.
Newton interpolation of the absolute value function
Authors: Plamen Simeonov
Venue: Proceedings of the 15th american conference on Applied mathematics (2009)

We find a sequence of points {xn} in the interval [-1, 1] for which the corresponding sequence of Lagrange interpolation polynomials to the function |x| converges to |x| uniformly on the interval [-1, 1]. We also estimate the rate of convergence.
A priori error estimation for the dual mixed finite element method of the elastodynamic problem in a polygonal domain, I
Authors: L. Boulaajine, M. Farhloul, L. Paquet
Venue: Journal of Computational and Applied Mathematics (2009)

In this paper we analyze a new dual mixed formulation of the elastodynamic system in polygonal domains. In this formulation the symmetry of the strain tensor is relaxed by the rotation of the displacement. For the time discretization of this new dual mixed formulation, we use an explicit scheme. After the analysis of stability of the fully discrete scheme, L^~ in time, L^2 in space a priori error estimates are derived for the approximation of the displacement, the strain, the pressure and the rotation. Numerical experiments confirm our theoretical predictions.
The effect of thermal radiation on the flow of a second grade fluid
Authors: T. Hayat, M. Nawaz, M. Sajid, S. Asghar
Venue: Computers Mathematics with Applications (2009)

This paper reports the magnetohydrodynamic (MHD) flow and heat transfer characteristics of a second grade fluid in a channel. Analytic technique namely the homotopy analysis method (HAM) is used to solve the momentum and energy equations. The important findings in this paper are the effects of second grade parameter, Hartmann number, Reynolds number, thermal radiation parameter, Prandtl and local Eckert numbers on the velocity, temperature, skin friction coefficient and Nusselt number.
Using structural information for identifying similar Chinese characters
Authors: Chao-Lin Liu, Jen-Hsiang Lin
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

Chinese characters that are similar in their pronunciations or in their internal structures are useful for computer-assisted language learning and for psycholinguistic studies. Although it is possible for us to employ image-based methods to identify visually similar characters, the resulting computational costs can be very high. We propose methods for identifying visually similar Chinese characters by adopting and extending the basic concepts of a proven Chinese input method--Cangjie. We present the methods, illustrate how they work, and discuss their weakness in this paper.
Freiman's theorem in finite fields via extremal set theory
Authors: Ben Green, Terence Tao
Venue: Combinatorics, Probability and Computing (2009)

Using various results from extremal set theory (interpreted in the language of additive combinatorics), we prove an asymptotically sharp version of Freiman's theorem in <inline-graphic mime-subtype="gif" xlink="S0963548309009821_inline1"><alt-text>$\F_2^n$</alt-text></inline-graphic>: if <inline-graphic mime-subtype="gif" xlink="S0963548309009821_inline2"><alt-text>$A \subseteq \F_2^n$</alt-text></inline-graphic> is a set for which |A + A| ≤ K|A| then A is contained in a subspace of size <inline-graphic mime-subtype="gif" xlink="S0963548309009821_inline4"><alt-text>$2^{2K + O(\sqrt{K}\log K)}|A|$</alt-text></inline-graphic>; except for the <inline-graphic mime-subtype="gif" xlink="S0963548309009821_inline5"><alt-text>$O(\sqrt{K} \log K)$</alt-text></inline-graphic> error, this is best possible. If in addition we assume that A is a downset, then we can also cover A by O(K46) translates of a coordinate subspace of size at most |A|, thereby verifying the so-called polynomial Freiman–Ruzsa conjecture in this case. A common theme in the arguments is the use of compression techniques. These have long been familiar in extremal set theory, but have been used only rarely in the additive combinatorics literature.
A two-step approach to building bilateral consensus between agents based on relationship learning theory
Authors: Ohbyung Kwon
Venue: Expert Systems with Applications: An International Journal (2009)

Researchers are increasingly focusing on the agent based approach to transaction support in ubiquitous commerce. These agents work autonomously to maximize utility on the user's behalf. In the case of a cooperative game, rather than a win-lose zero-sum game, agents may negotiate with each other or have a negotiating agent provide a suggestion that can be reasonably accepted by the dyad to build a consensus. In this paper we propose a novel methodology that increases agent performance in terms of costs associated with building consensus and successful negotiation rates. To do so, we develop a two-step approach: joint learning and negotiation to consensus building. We also conduct an experimental study to show the feasibility of the methodology.
Searching High-Dimensional Neighbours: CPU-Based Tailored Data-Structures Versus GPU-Based Brute-Force Method
Authors: Vincent Garcia, Frank Nielsen
Venue: Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques (2009)

Many image processing algorithms rely on nearest neighbor (NN) or on the k nearest neighbor (kNN) search problem. Several methods have been proposed to reduce the computation time, for instance using space partitionning. However, these methods are very slow in high dimensional space. In this paper, we propose a fast implementation of the brute-force algorithm using GPU (Graphics Processing Units) programming. We show that our implementation is up to 150 times faster than the classical approaches on synthetic data, and up to 75 times faster on real image processing algorithms (finding similar patches in images and texture synthesis).
Explicit Time Stepping Methods with High Stage Order and Monotonicity Properties
Authors: Emil Constantinescu, Adrian Sandu
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

This paper introduces a three and a four order explicit time stepping method. These methods have high stage order and favorable monotonicity properties. The proposed methods are based on multistage-multistep (MM) schemes that belong to the broader class of general linear methods, which are generalizations of both Runge-Kutta and linear multistep methods. Methods with high stage order alleviate the order reduction occurring in explicit multistage methods due to non-homogeneous boundary/source terms. Furthermore, the MM schemes presented in this paper can be expressed as convex combinations of Euler steps. Consequently, they have the same monotonicity properties as the forward Euler method. This property makes these schemes well suited for problems with discontinuous solutions.
Googlization of Libraries
Authors: William Miller, Rita Pellen
Venue:  (2009)

This book includes a variety of articles which look critically and judiciously at Google and its products, with a focus on Google Scholar and Google Book Search.
Eye Tracking and Gaze Based Interaction within Immersive Virtual Environments
Authors: Adrian Haffegee, Russell Barrow
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

Our eyes are input sensors which provide our brains with streams of visual data. They have evolved to be extremely efficient, and they will constantly dart to-and-fro to rapidly build up a picture of the salient entities in a viewed scene. These actions are almost subconscious. However, they can provide telling signs of how the brain is decoding the visuals, and can indicate emotional responses, prior to the viewer becoming aware of them.In this paper we discuss a method of tracking a user's eye movements, and use these to calculate their gaze within an immersive virtual environment. We investigate how these gaze patterns can be captured and used to identify viewed virtual objects, and discuss how this can be used as a natural method of interacting with the Virtual Environment. We describe a flexible tool that has been developed to achieve this, and detail initial validating applications that prove the concept.
Evaluation of OAI-ORE via large-scale information topology visualization
Authors: Robert Sanderson, Clare Llewellyn, Richard Jones
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

This poster evaluates the OAI-ORE specifications through experiments providing access to the JSTOR digital archive and the Flickr website. A browser-based dynamic graph visualization tool was designed and tested to determine if making the topology of the information available would provide end-user benefits in terms of navigation and discovery.
Mastering Applications in the Real World: Discipline-Specific Projects for Microsoft Office 2007, Introductory, 2nd edition
Authors: Course Technology
Venue:  (2007)

This project book is designed to enhance your Microsoft Office 2007 class. Mastering Applications in the Real World: Discipline-Specific Projects, Introductory gives you the opportunity to apply the skills you've learned to real-world projects and prepare for the future. These in-depth capstone projects enable you to take your knowledge of the four main Office 2007 applicationsWord, Excel, Access, and PowerPointto a new level. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Frankl&#x2019;s Conjecture and the Dual Covering Property
Authors: R. S. Shewale, Vinayak Joshi, V. S. Kharat
Venue: Graphs and Combinatorics (2009)

We have proved that the Frankl&#x2019;s Conjecture is true for the class of finite posets satisfying the dual covering property.
A Concept Lattice-Based Kernel for SVM Text Classification
Authors: Claudio Carpineto, Carla Michini, Raffaele Nicolussi
Venue: Proceedings of the 7th International Conference on Formal Concept Analysis (2009)

Standard Support Vector Machines (SVM) text classification relies on bag-of-words kernel to express the similarity between documents. We show that a document lattice can be used to define a valid kernel function that takes into account the relations between different terms. Such a kernel is based on the notion of conceptual proximity between pairs of terms, as encoded in the document lattice. We describe a method to perform SVM text classification with concept lattice-based kernel, which consists of text pre-processing, feature selection, lattice construction, computation of pairwise term similarity and kernel matrix, and SVM classification in the transformed feature space. We tested the accuracy of the proposed method on the 20NewsGroup database: the results show an improvement over the standard SVM when very little training data are available.
A New Practical Method on Hydrological Calculation
Authors: Lihua Feng, Xingcai Zhang
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

Artificial Neural Networks (ANN) deal with information through interactions among neurons (or nodes), approximating the mapping between inputs and outputs based on non-linear functional composition. They have the advantages of self-learning, self-organizing, and self-adapting. It is practical to use ANN technology to carry out hydrologic calculations. To this end, this note has fundamentally set up a system of calculation and analysis based on ANN technology, given an example of application with good results. It shows that ANN technology is a relatively effective way of solving problems in hydrologic calculation.
Towards implementation of photogrammetry based product re-realization
Authors: Jiacai Wang, Lirong Wang, Ichiro Hagiwara
Venue: Proceedings of the 9th WSEAS international conference on Robotics, control and manufacturing technology (2009)

This study presents a simple test procedure of reverse engineering system for rapid modeling and manufacturing of products with complex freeform surfaces. Its ultimate purpose is to explore a fast, efficient, economical and experimental route to reproduction of existing physical objects with digital camera and CNC machine tools for small and medium-sized manufacturers on a P2P-based multimedia collaborative environment. This paper focuses on developing a prototype of a photogrammetry based 3D digitization, B-spline surface model reconstruction, and tool path generation based on Open CASCADE kernel. Experiments show that the method is applicable for reverse modeling of freeform objects with moderate accuracy requirements. Therefore, the presented schema is a valid alternative to laser scanning techniques and coded light-based triangulation approaches with an important reduction of the hardware costs.
Searching for fair joint gains in agent-based negotiation
Authors: Minyi Li, Quoc Bao Vo, Ryszard Kowalczyk
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

In multi-issue negotiations, autonomous agents can act cooperatively to benefit from mutually preferred agreements. However, empirical evidence suggests that they often fail to search for joint gains and end up with inefficient results. To address this problem, this paper proposes a novel mediated negotiation procedure to support the negotiation agents in reaching an efficient and fair agreement in bilateral multi-issue negotiation. At each stage of negotiation, the mediator searches for the compromise direction based on a new EDD (Equal Directional Derivative) approach and computes the new tentative agreement. The numerical analysis presented in this paper demonstrates that the proposed approach not only guarantees Pareto efficiency, but also produces fairer improvements for two negotiating agents compared with other existing methods.
A Novel Approach to Cell Formation
Authors: Radim Belohlavek, Niranjan Kulkarni, Vilem Vychodil
Venue: Proceedings of the 7th International Conference on Formal Concept Analysis (2009)

We present an approach to the cell formation problem, known from group technology, which is inspired by formal concept analysis. The cell formation problem consists in allocating parts (objects) to machines (attributes), based on the machine-part matrix. This can be viewed as forming groups consisting of a set of parts and a set of machines. Such groups resemble formal concepts in the input data. Due to the specific nature of the performance assessment in the cell formation problem, good groups can be thought of as rectangles which, unlike those corresponding to formal concepts, contain a few blanks, i.e. which are not full of crosses in terms of formal concept analysis. Moreover, such groups need to be disjoint both in terms of objects and attributes. In this paper, we present an algorithm for the cell formation problem, experimental results, and a comparison to some methods proposed in the literature.
Explainable Artificial Intelligence for Training and Tutoring
Authors: H. Chad Lane, Mark G. Core, Michael van Lent, Steve Solomon, Dave Gomboc
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

This paper describes an Explainable Artificial Intelligence (XAI) tool that allows entities to answer questions about their activities within a tactical simulation. We show how XAI can be used to provide more meaningful after-action reviews and discuss ongoing work to integrate an intelligent tutor into the XAI framework.