ppxscal/embedding_network huggingface dataset:
Crossing-Optimal Acyclic HP-Completion for Outerplanar st-Digraphs
Authors: Tamara Mchedlidze, Antonios Symvonis
Venue: Proceedings of the 15th Annual International Conference on Computing and Combinatorics (2009)

Given an embedded planar acyclic digraph G, the acyclic hamiltonian path completion with crossing minimization (Acyclic- HPCCM) problem is to determine a hamiltonian path completion set of edges such that, when these edges are embedded on G, they create the smallest possible number of edge crossings and turn G to a hamiltonian acyclic digraph. In this paper, we present a linear time algorithm which solves the Acyclic-HPCCM problem on any outerplanar st-digraph G. The algorithm is based on properties of the optimal solution and an st-polygon decomposition of G. As a consequence of our result, we can obtain for the class of outerplanar st-digraphs upward topological 2-page book embeddings with minimum number of spine crossings.
Detecting Frontal EEG Activities with Forehead Electrodes
Authors: Jeng-Ren Duann, Po-Chuan Chen, Li-Wei Ko, Ruey-Song Huang, Tzyy-Ping Jung, Chin-Teng Lin
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

This study demonstrates the acquisitions of EEG signals from non-hairy forehead sites and tested the feasibility of using the forehead EEG in detecting drowsiness-related brain activities. A custom-made 15-channel forehead EEG-electrode patch and 28 scalp electrodes placed according to the International 10-20 system were used to simultaneously record EEG signals from the forehead and whole-head regions, respectively. A total of five subjects were instructed to perform a night-time long-haul driving task for an hour in a virtual-reality based driving simulator comprising a real car mounted on a 6 degree-of-freedom Steward motion platform and a immersive VR environment with 360 degree projection scenes. Separate independent component analyses were applied to the forehead and whole-head EEG data for each individual subject. For the whole-head independent component (IC) set, the frontal central midline (FCM) IC with an equivalent dipole source located in the anterior cingulate cortex was selected for further analysis. For the forehead IC set, the IC with its theta power changes highly correlated with subject's driving performance was selected. The EEG power changes of the selected forehead ICs were then used to predict driving performance based on a linear regression model. The results of this study showed that it is feasible to accurately estimate quantitatively the changing level of driving performance using the EEG features obtained from the forehead non-hairy channels, and the estimation accuracy was comparable to that using the EEG features of the whole-head recordings.
Modeling and Management of Information Supporting Functional Dimension of Collaborative Networks
Authors: Hamideh Afsarmanesh, Ekaterina Ermilova, Simon S. Msanjila, Luis M. Camarinha-Matos
Venue: Transactions on Large-Scale Data- and Knowledge-Centered Systems I (2009)

Fluent creation of opportunity-based short-term Collaborative Networks (CNs) among organizations or individuals requires the availability of a variety of up-to-date information. A pre-established properly administrated strategic-alliance Collaborative Network (CN) can act as the breeding environment for creation/operation of opportunity-based CNs, and effectively addressing the complexity, dynamism, and scalability of their actors and domains. Administration of these environments however requires effective set of functionalities, founded on top of strong information management. The paper introduces main challenges of CNs and their management of information, and focuses on the Virtual organizations Breeding Environment (VBE), which represents a specific form of strategic-alliances. It then focuses on the needed functionalities for effective administration/management of VBEs, and exemplifies information management challenges for three of their subsystems handling the Ontology, the profiles and competencies, and the rational trust.
Modeling annotators: a generative approach to learning from annotator rationales
Authors: Omar F. Zaidan, Jason Eisner
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one exploit this side information to better learn the desired parameters &theta;? We present a generative model of how a given annotator, knowing the true &theta;, stochastically chooses rationales. Thus, observing the rationales helps us infer the true &theta;. We collect substring rationales for a sentiment classification task (Pang and Lee, 2004) and use them to obtain significant accuracy improvements for each annotator. Our new generative approach exploits the rationales more effectively than our previous "masking SVM" approach. It is also more principled, and could be adapted to help learn other kinds of probabilistic classifiers for quite different tasks.
Designing a feedback component of an intelligent tutoring system for foreign language
Authors: Anita Ferreira, John Atkinson
Venue: Knowledge-Based Systems (2009)

In this paper, we provide a model of corrective feedback generation for an intelligent tutoring system for Spanish as a foreign language. We have studied two kind of strategies: (1) Giving-Answer Strategies (GAS), where the teacher directly gives the desired target form or indicates the location of the error and (2) Prompting-Answer Strategies (PAS), where the teacher pushes the student less directly to notice and repair their own error. Based on different experimental settings and comparisons with face-to-face tutoring mode, we propose the design of a component of effective teaching strategies into ITS for Spanish as a foreign language.
Research on Three-dimensional Cartilage Thickness Measurement of Femoral Head in Magnetic Resonance Images
Authors: Cao Yu, Zhao Jie, Cheng Yuanzhi
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

Measuring the thickness of articular cartilage in three-dimensional (3D) magnetic resonance (MR) images is an important diagnostic procedure. A 3D measuring method was proposed to determine the femoral cartilage thickness in this paper. The cartilage thickness was defined as the distance between the two sides of the edges, which are the zero-crossing points of the second directional derivatives combined with Gaussian blurring along the normal direction of the cartilage surface. The spherical constraint of the femoral shape was utilized to confirm the normal direction. The zero-crossing method was demonstrated by mathematical simulation. Experiments were conducted using a resected femoral head to validate the method. The anatomical thickness data were proved to be well correlated with the zero-crossing thickness data.
Smooth Modules
Authors: Chuan-yu Xu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

Although smooth groups and smooth rings were presented, however the important method that smooth ring acts on smooth group has not been seen in report. In order to solve the problem, this paper defines smooth modulus, smooth homomorphism and smooth quotient modulus by the action. In order to compare two smooth modulus, this paper proves the fundamental theorem of smooth homomorphism of smooth modulus. This paper is different from the classical modulus. The former is based on smooth binary operation and fuzzy equality, and the latter is based on classical binary operation and crisp equality. This paper is different from YUAN fuzzy groups. The former is based on fuzzy equality, and the latter is based on crisp equality. The work of this paper further develops algebraic structures of fuzzy sets.
Book Review: A physical-design picture book
Authors: Igor Markov
Venue: IEEE Design Test (2009)

This is a review of Practical Problems in VLSI Physical Design Automation (by Sung Kyu Lim). The book, which grew out of a graduate-level course, focuses on helping readers grasp the essence of each algorithm presented and then to develop relevant algorithmic skills. Numerous illustrations make the examples fun and help readily convey the intracies of fairly sophisticated algorithms.
For Your Eyes Only: Controlling 3D Online Games by Eye-Gaze
Authors: Howell Istance, Aulikki Hyrskykari, Stephen Vickers, Thiago Chaves
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

Massively multiplayer online role-playing games, such as World of Warcraft, have become the most widespread 3D graphical environments with millions of active subscribers worldwide. People with severe motor impairments should be able to take part in these games without the extent of their disability being apparent to others online. Eye gaze is a high bandwidth modality that can support this. We have developed a software device that uses gaze input in different modes for emulating mouse and keyboard events appropriate for interacting with on-line games. We report an evaluation study that investigated gaze-based interaction with World of Warcraft using the device. We have found that it is feasible to carry out tasks representative of game play at a beginners skill level using gaze alone. The results from the locomotion task part of the study show similar performance for gaze-based interaction compared with a keyboard and mouse. We discuss the usability issues that arose when completing three types of tasks in the game and the implications of these for playing of this type of game using gaze as the only input modality.
TNT: Touch `n' Tangibles on LC-Displays
Authors: Ramon Hofer, Andreas Kunz
Venue: Proceedings of the 8th International Conference on Entertainment Computing (2009)

In this paper, we present TNT (Touch `n' Tangibles) - a new combination of several existing hardware technologies, which are integrated into an LC-display. TNT enables users to interact using finger touch and tangible user interfaces at the same time on an active flat panel screen, while maintaining precise identification of all interactive objects and fingers. TNT can accurately distinguish between touch and Tangible User Interfaces input by assigning different time slots to each interactive object using the same sensing technology for both methods. TNT's tracking is not affected by objects on the screen other than fingers and active Tangibles User Interfaces, which makes it ideal for use in brainstorming applications.
Design of Collaborative Learning in Cyber-Schools
Authors: Wu Junqi, Zhengbing Hu, Yang Zongkai, Liu Yumei
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

With the development of computer network and modern instructional theory, collaborative learning has become an important instructional strategy in the environment of cyber-schools, and it can help develop many important characters of learners, such as creativity, collaboration with people and so on, which are valued highly in modern society. This paper firstly introduces collaborative learning and the instructional procedures of collaborative learning in network environment, and then lists designs of some practical and useful collaborative learning cases that are carried out in LAMS platform, finally it gives some suggestions of collaborative learning in cyber-schools.
Improving the efficiency of inductive logic programming through the use of query packs
Authors: Hendrik Blockeel, Luc Dehaspe, Bart Demoen, Gerda Janssens, Jan Ramon, Henk Vandecasteele
Venue: Journal of Artificial Intelligence Research (2002)

Inductive logic programming, or relational learning, is a powerful paradigm for machine learning or data mining. However, in order for ILP to become practically useful, the efficiency of ILP systems must improve substantially. To this end, the notion of a query pack is introduced: it structures sets of similar queries. Furthermore, a mechanism is described for executing such query packs. A complexity analysis shows that considerable efficiency improvements can be achieved through the use of this query pack execution mechanism. This claim is supported by empirical results obtained by incorporating support for query pack execution in two existing learning systems.
Recursive Dual-Net: A New Universal Network for Supercomputers of the Next Generation
Authors: Yamin Li, Shietung Peng, Wanming Chu
Venue: Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing (2009)

In this paper, we propose a new universal network, called recursive dual-net (RDN), as a potential candidate for the interconnection network of supercomputers with very large scale. The recursive dual-net is based on a recursive dual-construction of a base network. A k-level dual-construction for k > 0 creates a network containing $(2m)^{2^k}/2$ nodes with node-degree d + k, where m and d are the number of nodes and the node-degree, respectively, of the base network. The recursive dual-net is node and edge symmetric and can contain huge number of nodes with small node-degree and short diameter. For example, we can construct a symmetric RDN connecting more than 3-million nodes with only 6 links per node and a diameter of 22. We investigate the topological properties of the recursive dual-net and compare it to that of other networks including 3D torus, WK-recursive network, hypercube, cube-connected-cycle, and dual-cube. We also establish the basic routing and broadcasting algorithms for the proposed recursive dual-net.
COBRA - mining web for COrporate Brand and Reputation Analysis
Authors: Scott Spangler, Ying Chen, Larry Proctor, Ana Lelescu, Amit Behal, Bin He, Thomas D. Griffin, Anna Liu, Brad Wade, Trevor Davis
Venue: Web Intelligence and Agent Systems (2009)

Corporations are extremely sensitive to issues such as brand stewardship and product reputation. Traditional brand image and reputation tracking is limited to news wires and contact centre analysis. However, with the emergence of web, Consumer Generated Media (CGM), such as blogs, news forums, message boards, and web pages/sites, is rapidly becoming the &ldquo;voice of the people&rdquo;. Effectively leveraging such readily available and massive amount of CGM content for brand and reputation insights can be extremely valuable to corporations. Yet the existing solutions in this space are commonly limited to keyword search based technologies that often result in excessive amount of information for users to digest manually. Some text mining based technologies exist for mining the web. However, they often target very narrow problems such as web page classification instead of looking at the overall stack of technologies required for web mining. This paper describes a holistically integrated brand and reputation analysis solution that mines CGM contents for insights, called COBRA (COrporate Brand and Reputation Analysis). COBRA contains a flexible ETL (Extract, Transform, and Load) engine that processes diverse sets of structured and unstructured information, a suite of analytical capabilities that mines CGM content to extract semantic entities and insights out of the data, and an alerting mechanism that utilizes a technique called &ldquo;orthogonal filtering&rdquo; to accurately generate brand and reputation alerts by filtering through orthogonal dimensions of information. We use a set of real-world case studies to demonstrate the effectiveness of our overall approach. We show that by applying such analytics techniques, we significantly improved the accuracy of alert identification by 10-200 times when compared to the popular keyword-search based techniques in today's alerting systems.
Generative conversations in game-based learning
Authors: Lai Har Judy Lee, Yam San Chee
Venue: Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 1 (2009)

This study examines a secondary level game-based learning curriculum centered on a multi-player 3D game, in which students collaboratively make sense of phenomena related to the behavior of charged particles in electric and magnetic fields. We study the interaction among the students while they enlist resources in the form of the game and curriculum materials that serve as scaffolds for sense-making. Through the consideration of coordination of the perception-conception of resources with actions related to scientific inquiry processes, potential sites for generative conversations were identified. We suggest future directions for the design and study of game-based learning curriculum to foster generative conversations that better shape students' sense-making trajectories.
Fast motion deblurring
Authors: Sunghyun Cho, Seungyong Lee
Venue: ACM SIGGRAPH Asia 2009 papers (2009)

This paper presents a fast deblurring method that produces a deblurring result from a single image of moderate size in a few seconds. We accelerate both latent image estimation and kernel estimation in an iterative deblurring process by introducing a novel prediction step and working with image derivatives rather than pixel values. In the prediction step, we use simple image processing techniques to predict strong edges from an estimated latent image, which will be solely used for kernel estimation. With this approach, a computationally efficient Gaussian prior becomes sufficient for deconvolution to estimate the latent image, as small deconvolution artifacts can be suppressed in the prediction. For kernel estimation, we formulate the optimization function using image derivatives, and accelerate the numerical process by reducing the number of Fourier transforms needed for a conjugate gradient method. We also show that the formulation results in a smaller condition number of the numerical system than the use of pixel values, which gives faster convergence. Experimental results demonstrate that our method runs an order of magnitude faster than previous work, while the deblurring quality is comparable. GPU implementation facilitates further speed-up, making our method fast enough for practical use.
Integration of routing and time synchronization protocols for wireless sensor networks
Authors: João B. Borges Neto, Francisco Milton Mendes Neto, Danielo G. Gomes, Pedro Fernandes Ribeiro Neto, Rossana M. C. Andrade
Venue: Proceedings of the 2008 Euro American Conference on Telematics and Information Systems (2008)

When dealing with Wireless Sensor Networks (WSN) applications that demand a high level cooperation of the sensor nodes, time synchronization is necessary to provide the correctness required for their results. In this work, we show that common issues between routing and time synchronization processes make their integration possible and, thus, can solve the problems of the resources consumption and time spent to acquire the synchronization. Two proposals for integrating them are presented.
Markov blanket feature selection for support vector machines
Authors: Jianqiang Shen, Lida Li, Weng-Keen Wong
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery approach for support vector machines and propose to discover Markov blankets by performing a fast heuristic Bayesian network structure learning. We give a sufficient condition that our approach will improve the performance. Two major factors that make it prohibitive for learning Bayesian networks from high-dimensional data sets are the large search space and the expensive cycle detection operations. We propose to restrict the search space by only considering the promising candidates and detect cycles using an online topological sorting method. Experimental results show that we can efficiently reduce the feature dimensionality while preserving a high degree of classification accuracy.
Research and Simulation of MIMO-OFDM Wireless Communication System
Authors: Jiang Xuehua, Chen Peijiang
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

A simple MIMO-OFDM wireless communication system is constructed based on the analysis of the technical principles and the system models of the MIMO technology and the OFDM technology. The system combines the MIMO system and the OFDM system together, space-time coding is done in the transmitter firstly, the signal is launched after OFDM modulated, and the process of the receiver is the inverse process of the transmitter. The system performance is simulated by using the software MATLAB, the experimental result shows that the MIMO-OFDM wireless communication system has better performance when the antenna number is very large and the other conditions are identical, but the system performance will reduce if the carrier number increases.
A reconfigurable ferromagnetic input device
Authors: Jonathan Hook, Stuart Taylor, Alex Butler, Nicolas Villar, Shahram Izadi
Venue: Proceedings of the 22nd annual ACM symposium on User interface software and technology (2009)

We present a novel hardware device based on ferromagnetic sensing, capable of detecting the presence, position and deformation of any ferrous object placed on or near its surface. These objects can include ball bearings, magnets, iron filings, and soft malleable bladders filled with ferrofluid. Our technology can be used to build reconfigurable input devices -- where the physical form of the input device can be assembled using combinations of such ferrous objects. This allows users to rapidly construct new forms of input device, such as a trackball-style device based on a single large ball bearing, tangible mixers based on a collection of sliders and buttons with ferrous components, and multi-touch malleable surfaces using a ferrofluid bladder. We discuss the implementation of our technology, its strengths and limitations, and potential application scenarios.
Intelligent finite element method: An evolutionary approach to constitutive modeling
Authors: A. A. Javadi, M. Rezania
Venue: Advanced Engineering Informatics (2009)

In this paper, a new approach is presented, for constitutive modeling of materials in finite element analysis, with potential applications in different engineering disciplines. The proposed approach provides a unified framework for modeling of complex materials, using evolutionary polynomial regression-based constitutive model (EPRCM), integrated in finite element analysis. Evolutionary polynomial regression (EPR) is a computing technique that generates a transparent and structured representation of the system being studied. The main advantage of EPRCM over conventional constitutive models is that it provides the optimum structure for the material constitutive model representation, as well as its parameters, directly from raw experimental (or field) data. The proposed algorithm provides a transparent relationship for the constitutive material model that can readily be incorporated in a finite element model (FEM). The incorporation of EPRCM into FEM will be presented and the application of the resulting methodology for material modeling in finite element analysis will be illustrated through two examples.