ppxscal/embedding_network huggingface dataset:
iThaiSTAR --- A Low Cost Humanoid Robot for Entertainment and Teaching Thai Dances
Authors: Chun Che Fung, Thitipong Nandhabiwat, Arnold Depickere
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

Development of humanoid and dance robots has improved greatly due to rapid advancement of electronics, computer, mechatronics and control technologies. While humanoid robots such as Honda ASIMO, Fujita HOAP-3 and Sony QRIO have dazed the public with their amazing capabilities, such robots are in very limited supply and they are also extremely expensive. On the other hand, the low cost toy robot, WowWee's Robosapien (RS), has become very popular. It has also expanded its functionalities in later models since its line of products were first launched in 2004. The most important aspect of such robot is its cost is only a fraction of the highly sophisticated robots. This study investigates the feasibility of using low cost robots such as RS for the purposes of entertainment and teaching Thai dances. Informal feedbacks and comments have shown a high degree of acceptance and keen interest. This demonstrates the potential of low cost robots for training, entertainment and edutainment purposes.
Similarity Measures between Connection Numbers of Set Pair Analysis
Authors: Junjie Yang, Jianzhong Zhou, Li Liu, Yinghai Li, Zhengjia Wu
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

The Set Pair Analysis (SPA) is a new system analysis approach and uncertainty theory. The similarity measure between connection numbers is the key to applications of SPA in multi-attribute decision-making, pattern recognition, artificial intelligent. However, it is difficult to accurately depict similarity degree between connection numbers. The distance between connection numbers, a group of checking criterions and the similarity degree functions of connection numbers in SPA are presented in this paper to measure the similarity between connection numbers, and the rationality of such measurement is also explained by the well-designed criterions. The result shows the effectiveness of the proposed similarity measures.
On Medial Representations
Authors: Gabriella Sanniti Di Baja
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

During the last half century, medial representations of objects have been involved in many biological and physical theories, and computer scientists have designed suitable algorithms for their computation. Aim of this paper is to provide a short, non-comprehensive, survey of the most common medial representation systems.
Evaluation of Quality Retaining Diagnostic Credibility for Surgery Video Recordings
Authors: Mariusz Duplaga, Mikołaj Leszczuk, Zdzisław Papir, Artur Przelaskowski
Venue: Proceedings of the 10th international conference on Visual Information Systems: Web-Based Visual Information Search and Management (2008)

The paper proves that it is possible to meet contradictory requirements of effective compression and diagnostic credibility, for long-lasting and low motion bronchoscopic recordings at compression ratios close to 100. As the main supporting assumption, it has been accepted that the content can be compressed as far as clinicians are not able to sense a loss of video diagnostic fidelity. Different market codecs were inspected by means of the combined subjective and objective tests.
The SPARQL Query Graph Model for Query Optimization
Authors: Olaf Hartig, Ralf Heese
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

The Semantic Web community has proposed several query languages for RDF before the World Wide Web Consortium started to standardize SPARQL. Due to the declarative nature of the query language, a query engine should be responsible to choose an efficient evaluation strategy. Although all RDF repositories provide query capabilities, some of them require manual interaction to reduce query execution time by several orders of magnitude.In this paper, we propose the SPARQL query graph model (SQGM) supporting all phases of query processing. On top of the SQGM we defined transformations rules to simplify and to rewrite a query. Based on these rules we developed heuristics to achieve an efficient query execution plan. Experiments illustrate the potential of our approach.
Supervised grayscale thresholding based on transition regions
Authors: Qingmao Hu, Suhuai Luo, Yu Qiao, Guoyu Qian
Venue: Image and Vision Computing (2008)

A new thresholding framework is proposed which is transition region based, and consists of deriving the transition region with the help of supervision and calculating the threshold from the transition region. Four ways of supervision are studied: picking up an object and a background pixel, from other clustering or segmentation results, based on sample statistics, and exploration of background proportions. The approach has been validated both quantitatively and qualitatively. It is found that the proposed approach: (1) is more robust, consistent and reliable than the conventional transition-region-based thresholding methods; and (2) is easier to implement and has wider applicability than existing supervised thresholding methods. The approach is especially useful for segmenting difficult images with multiple objects and/or serious imaging artifacts.
The LENUS Master Patient Index: Combining Hospital Content Management with a Healthcare Service Bus
Authors: Dirk Krechel, Markus Hartbauer
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

The LENUS master patient index in combination with the electronic patient record and a healthcare service bus enables the implementation of a small lean reference system for patient management. Via a modern client all ADT functionalities can be applied without a leading administrative software system. Based on service oriented architecture the index is used in combination with a preconfigured open source healthcare bus. It uses the association based search engine of the LENUS HCM software suite to reach a high re-identification rate of existing patients. Only few cases must be processed manually in the LENUS clearing component.
A study on drag reduction of a rotationally oscillating circular cylinder at low Reynolds number
Authors: N. Fujisawa, M. Ugata, T. Suzuki
Venue: Journal of Visualization (2005)

The flow field around a rotationally oscillating circular cylinder in a uniform flow is studied by using a particle image velocimetry to understand the mechanism of drag reduction and the corresponding suppression of vortex shedding in the cylinder wake at low Reynolds number. Experiments are conducted on the flow around the circular cylinder under rotational oscillation at forcing Strouhal number 1, rotational amplitude 2 and Reynolds number 2,000. It is found from the flow measurement by PIV that the width of the wake is narrowed and the velocity fluctuations are reduced by the rotational oscillation of the cylinder, which results in the drag reduction rate of 30%. The mechanism of drag reduction is studied by phase-averaged PIV measurement, which indicates the formation of periodic small-scale vortices from both sides of the cylinder. It is found from the cross-correlation measurement between the velocity fluctuations that the large-scale structure of vortex shedding is almost removed in the cylinder wake, when the small-scale vortices are generated at the unstable frequency of shear layer by the influence of rotational oscillation.
On Using Energy Signatures in Protein Structure Similarity Searching
Authors: Bożena Małysiak, Alina Momot, Stanisław Kozielski, Dariusz Mrozek
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

The analysis of small molecular substructures (like enzyme active sites) in the whole protein structure can be supported by using methods of similarity searching. These methods allow to search the 3D structural patterns in a database of protein structures. However, the well-known methods of fold similarity searching like VAST or DALI are not appropriate for this task. Methods that benefit from a dependency between a spatial conformation and potential energy of protein structure seem to be more supportive. In the paper, we present a new version of the EAST (Energy Alignment Search Tool) algorithm that uses energy signatures in the process of similarity searching. This makes the algorithm not only more sensitive, but also eliminates disadvantages of previous implementations of our EAST method.
A Novel Elliptical Basis Function Neural Networks Model Based on a Hybrid Learning Algorithm
Authors: Ji-Xiang Du, Guo-Jun Zhang, Zeng-Fu Wang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

In this paper, a novel elliptical basis function neural networks model (EBFNN) based on a hybrid learning algorithm (HLA) is proposed. Firstly, a geometry analytic algorithm is applied to construct the hyper-ellipsoid units of hidden layer of the EBFNN, i.e., initial the structure of the EBFNN. Then, the hybrid learning algorithm (HLA) is further applied to adjust the centers and the shape parameters. The experimental results demonstrated the proposed hybrid learning algorithm for the EBFNN model is feasible and efficient, and the EBFNN is not only parsimonious but also has better generalization performance than the RBFNN.
Generalizing Data in Natural Language
Authors: Ryszard S. Michalski, Janusz Wojtusiak
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

This paper concerns the development of a new direction in machine learning, called natural induction, which requires from computer-generated knowledge not only to have high predictive accuracy, but also to be in human-oriented forms, such as natural language descriptions and/or graphical representations. Such forms facilitate understanding and acceptance of the learned knowledge, and making mental models that are useful for decision making. An initial version of the AQ21-NI program for natural induction and its several novel features are briefly described. The performance of the program is illustrated by an example of deriving medical diagnostic rules from micro-array data.
Evolution and complexity: The double-edged sword
Authors: Thomas Miconi
Venue: Artificial Life (2008)

We attempt to provide a comprehensive answer to the question of whether, and when, an arrow of complexity emerges in Darwinian evolution. We note that this expression can be interpreted in different ways, including a passive, incidental growth, or a pervasive bias towards complexification. We argue at length that an arrow of complexity does indeed occur in evolution, which can be most reasonably interpreted as the result of a passive trend rather than a driven one. What, then, is the role of evolution in the creation of this trend, and under which conditions will it emerge? In the later sections of this article we point out that when certain proper conditions (which we attempt to formulate in a concise form) are met, Darwinian evolution predictably creates a sustained trend of increase in maximum complexity (that is, an arrow of complexity) that would not be possible without it; but if they are not, evolution will not only fail to produce an arrow of complexity, but may actually prevent any increase in complexity altogether. We conclude that, with regard to the growth of complexity, evolution is very much a double-edged sword.
Snap: A time critical decision-making framework for MOUT simulations
Authors: Shang-Ping Ting, Suiping Zhou
Venue: Computer Animation and Virtual Worlds (2008)

Deliberative reasoning based on the rational analysis of various alternatives often requires too much information and may be too slow in time critical situations. In these situations, humans rely mainly on their intuitions rather than some structured decision-making processes. An important and challenging problem in Military Operations on Urban Terrain (MOUT) simulations is how to generate realistic tactical behaviors for the non-player characters (also known as bots), as these bots often need to make quick decisions in time-critical and uncertain situations. In this paper, we describe our work on Snap, a time critical decision-making framework for the bots in MOUT simulations. The novel features of Snap include case-based reasoning (CBR) and thin slicing. CBR is used to make quick decisions by comparing the current situation with past experience cases. Thin slicing is used to model human's ability to quickly form up situation awareness under uncertain and complex situations using key cues from partial information. To assess the effectiveness of Snap, we have integrated it into Twilight City, a virtual environment for MOUT simulations. Experimental results show that Snap is very effective in generating quick decisions during time critical situations for MOUT simulations. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Monte Carlo Numerical Treatment of Large Linear Algebra Problems
Authors: Ivan Dimov, Vassil Alexandrov, Rumyana Papancheva, Christian Weihrauch
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

In this paper we deal with performance analysis of Monte Carlo algorithm for large linear algebra problems. We consider applicability and efficiency of the Markov chain Monte Carlo for large problems, i.e., problems involving matrices with a number of non-zero elements ranging between one million and one billion. We are concentrating on analysis of the almost Optimal Monte Carlo (MAO) algorithm for evaluating bilinear forms of matrix powers since they form the so-called Krylov subspaces.Results are presented comparing the performance of the Robust and Non-robust Monte Carlo algorithms. The algorithms are tested on large dense matrices as well as on large unstructured sparse matrices.
Research of CT / MRI Tumor Image Registration Based on Least Square Support Vector Machines
Authors: Zeqing Yang, Libing Liu, Weiling Liu, Weidong Yang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

In view of the characteristics of the local nonlinear distortion about medical CT and MRI tumor image registration, the method of Least Square Support Vector Machines (LS-SVM) was used to register the images. The verge point of tumor was marked using vector machine weights in this algorithm, and the eigenvalues of tumor images were obtained. The difference of corresponding feature points between CT and MRI tumor image was eliminated adopting the least square algorithm, which not only can effectively remove geometric deformation of the images, but also can be adaptive correct the errors caused by the positioning of feature points. Finally, we had experimented on the Matlab platform, the results show that the algorithm has higher registration accuracy and can meet medical tumor registration requirements. It also play guidance role in image fusion and tumor targeted therapy, which has important application in clinical medicine.
Smart Actuator-Based Fault-Tolerant Control for Networked Safety-Critical Embedded Systems
Authors: Inseok Yang, Donggil Kim, Kyungmin Kang, Dongik Lee, Kyungsik Yoon
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

In this paper, a fault-tolerant control method is presented with an application to steer-by-wire (SBW) system. SBW is a network-based vehicle steering system in which the mechanical linkage and hydraulics are replaced by electrical motors and fieldbus networks. Since failure of a steering system may result in a catastrophic accident, SBW can be considered as a safety-critical embedded system for which very high level of dependability must be satisfied. This paper proposes an effective control strategy to tolerate faulty actuators. The proposed method has a simple structure to be implemented on low cost embedded processors. The reconfiguration strategy consists of two fold: i) a smart actuator of which embedded microprocessor provides the fast and accurate diagnostic information through a time-triggered fieldbus, and ii) an IMC-PID controller which is capable of tolerating the effect of faults based on the diagnostic information being sent from the smart actuator. Simulation results with a SBW model show that the proposed method can enhance the system dependability in the presence of faults without using any redundant actuators.
HMM-Based Acoustic Event Detection with AdaBoost Feature Selection
Authors: Xi Zhou, Xiaodan Zhuang, Ming Liu, Hao Tang, Mark Hasegawa-Johnson, Thomas Huang
Venue: Multimodal Technologies for Perception of Humans: International Evaluation Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8-11, 2007, Revised Selected Papers (2008)

Because of the spectral difference between speech and acous- tic events, we propose using Kullback-Leibler distance to quantify the discriminant capability of all speech feature components in acoustic event detection. Based on these distances, we use AdaBoost to select a discriminant feature set and demonstrate that this feature set outperforms classical speech feature set such as MFCC in one-pass HMM-based acoustic event detection. We implement an HMM-based acoustic events detection system with lattice rescoring using a feature set selected by the above AdaBoost based approach.
Cooperative 3-Robot Passing and Shooting in the RoboCup Small Size League
Authors: Ryota Nakanishi, James Bruce, Kazuhito Murakami, Tadashi Naruse, Manuela Veloso
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

This paper describes a method for cooperative play among 3 robots in order to score a goal in the RoboCup Small Size League. In RoboCup 2005 Osaka, our team introduced a new attacking play, where one robot kicks a ball and the other receives and immediately shoots the ball on goal. However, due to the relatively slow kicking speed of the robot, top opponent teams could prevent successful passing between robots. This motivates the need for more complex play, such as passing around to several robots to avoid the opponents' passing defense. In this paper we propose a method to realize such a play, i.e. a combination play among 3 robots. We discuss the technical issues to achieve this combination play, especially for a pass-and-shoot combination play. Experimental results on real robots are provided. They indicate that the success rate of the play depends strongly on the arrangement of the robots, and ranges from 20 % to 90 % in tests with an opponent goalkeeper which stands still.
Virtual Artistic Paper-Cut
Authors: Hanwen Guo, Minyong Shi, Zhiguo Hong, Rui Yang, Li Zhang
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

This paper presents some algorithms for a novel simulation of the folding and cut crafts in Chinese Paper-cut. All algorithms in simulation are designed by consideration of the real Paper-cut's whole process. We applies area filling algorithm, polygon clipping algorithm, contour extraction algorithm and subdivision curve algorithm, with the proper improvement that meets the technique of the art in the nature, to yield some vivid Paper-cut works. Our approach is feasible to anyone with the desire, due to Paper-cut illumines itself in 2D and all the operations are also in 2D.Moverover, recent compelling graphic systems, such as Flash, Photoshop, Maya and 3DMax, did not provide a similar interface for paper's fold and decorative pattern which are primary elements in Paper-cut. However, our approach not only meets the interest of the Paper-cut, but also holds an interface for these compelling systems because of measuring up the SVG.
Synchronization
Authors: Helmut Jürgensen
Venue: Information and Computation (2008)

Synchronization of a system can be achieved by applying an input sequence which causes the system to enter a known state. We survey synchronization issues from the points of view of automaton and coding theory. A connection between properties of codes and synchronizing words is established which may offer a new view of Cerny's conjecture.
Restaurant Recommendation for Group of People in Mobile Environments Using Probabilistic Multi-criteria Decision Making
Authors: Moon-Hee Park, Han-Saem Park, Sung-Bae Cho
Venue: Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008)

Since 1990s, with an advancement of network technology and the popularization of the Internet, information that people can access has proliferated, thus information recommendation has been investigated as an important issue. Because preference to information recommendation can be different as context that the users are related to, we should consider this context to provide a good service. This paper proposes the recommendation system that considers the preferences of group users in mobile environment and applied the system to recommendation of restaurants. Since mobile environment has plenty of uncertainty, our system have used Bayesian network which showed reliable performance with uncertain input to model individual user's preference. Also, restaurant recommendation mostly considers the preference of group users, so we have used AHP (Analytic Hierarchy Process) of multi-criteria decision making method to get the preference of group users from individual users' preferences. For experiments, we have assumed 10 different situations and compared the proposed method with random recommendation and simple rule-based recommendation. Finally, we have confirmed that the proposed system provides high usability with SUS (System Usability Scale).
Discovering Knowledge from Local Patterns with Global Constraints
Authors: Bruno Crémilleux, Arnaud Soulet
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

It is well known that local patterns are at the core of a lot of knowledge which may be discovered from data. Nevertheless, use of local patterns is limited by their huge number and computational costs. Several approaches (e.g., condensed representations, pattern set discovery) aim at selecting or grouping local patterns to provide a global view of the data. In this paper, we propose the idea of global constraints to write queries addressing global patterns as sets of local patterns. Usefulness of global constraints is to take into account relationships between local patterns, such relations expressing a user bias according to its expectation (e.g., search of exceptions, top-k patterns). We think that global constraints are a powerful way to get meaningful patterns. We propose the generic Approximate-and-Push approach to mine patterns under global constraints and we give a method for the case of the top-k patterns w.r.t. any measure. Experiments show its efficiency since it was not feasible to mine such patterns beforehand.