ppxscal/embedding_network huggingface dataset:
The Design of Talking Music Web Browser for Teaching Learning-Disabled Children: A Scaffolding Strategy to Aural Skills
Authors: Yu-Ting Huang, Chi Nung Chu, Yao-Ming Yeh, Pei-Luen Tsai
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

The goal of this study is to find an efficient solution on the World Wide Web that would promote aural skills for the learning-disabled children through scaffolding strategy. For the abstract mental model building of pitch recognition and rhythm, there is a significance level for the learning effect from traditional class learning with Talking Music Web Browser. The design of Talking Music Web Browser with Vygotsky's concept of zone of proximal development is developed according to the scaffolds of Chevé system, music notation, solmization and melody to inspire the learning-disabled children to get aural skills. The Talking Music Web Browser can recover the learning-disabled children from a difficult position of no instruments to play or out of tune in learning music. They can acquire a lot of learning supports which comes in extremely handy.
FPGA-Based Quadrature Mirror Filters for DSP Applications
Authors: Ali Al-Haj
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

One of the most efficient multi-rate digital signal decomposition structures is the quadrature mirror filter (QMF) bank.It has been used successfully to implement subband coding applications such as speech coding and image compression. In this paper, we report on several efficient FPGA-based implementations of the basic quadrature mirror filter bank. The implementations are based on transforming the basic filter bank structure using ployphase decomposition and distributed arithmetic techniques. The two techniques reduce computational time dramatically by enabling maximum exploitation of the ample parallelism inherent in the filter bank. Performance results demonstrate the effectiveness of FPGA implementations of ployphase and distributed arithmetic quadrature mirror filter bank.
A Translation from the HTML DTD into a Regular Hedge Grammar
Authors: Takuya Nishiyama, Yasuhiko Minamide
Venue: Proceedings of the 13th international conference on Implementation and Applications of Automata (2008)

The PHP string analyzer developed by the second author approximates the string output of a program with a context-free grammar. By developing a procedure to decide inclusion between context-free and regular hedge languages, Minamide and Tozawa applied this analysis to checking the validity of dynamically generated XHTML documents. In this paper, we consider the problem of checking the validity of dynamically generated HTML documents instead of XHTML documents.HTML is not specified by an XML schema language, but by an SGML DTD, and we can omit several kinds of tags in HTML documents. We formalize a subclass of SGML DTDs and develop a translation into regular hedge grammars. Thus we can validate dynamically generated HTML documents. We have implemented this translation and incorporated it in the PHP string analyzer. The experimental results show that the validation through this translation works well in practice.
The Uber-Assumption Family
Authors: Xavier Boyen
Venue: Proceedings of the 2nd international conference on Pairing-Based Cryptography (2008)

We offer an exposition of Boneh, Boyen, and Goh's "uber-assumption" family for analyzing the validity and strength of pairing assumptions in the generic-group model, and augment the original BBG framework with a few simple but useful extensions.
Risk Classification of Mammograms Using Anatomical Linear Structure and Density Information
Authors: Edward M. Hadley, Erika R. Denton, Josep Pont, Elsa Pérez, Reyer Zwiggelaar
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

Mammographic risk assessment is concerned with the probability of a woman developing breast cancer. Recently, it has been suggested that the density of linear structures is related to risk. For 321 images from the MIAS database, the images were segmented in to dense and non-dense tissue using a method described by Sivaramakrishna, et al. In addition, a measure of line strength was obtained for each pixel using the Line Operator method. The above-threshold linearity was calculated in dense and non-dense tissue for each image and the images were then classified by BIRADS class using linear discriminant analysis. The results show a marked improvement when both density and linear structure information is used in classification over density information alone.
Enabling the legally blind in classroom note-taking
Authors: David Hayden, Dirk Colbry, John A. Black,  Jr., Sethuraman Panchanathan
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

Classroom note-taking has been shown to be beneficial, even if the student never reviews his/her own notes. Students that are legally blind are thus at a disadvantage because they face significant barriers to note-taking in the classroom. This presentation demonstrates a working prototype of the CUbiC Note Taker, which is a highly portable device that allows students who are legally blind to take their own notes in class without any special in-classroom accommodations, and without requiring lecturers to adapt their presentation in any way.
Top-k Retrieval in Description Logic Programs Under Vagueness for the Semantic Web
Authors: Thomas Lukasiewicz, Umberto Straccia
Venue: Proceedings of the 1st international conference on Scalable Uncertainty Management (2007)

Description logics (DLs) and logic programs (LPs) are important representation languages for the Semantic Web. In this paper, we address an emerging problem in such languages, namely, the problem of evaluating ranked top-k queries. Specifically, we show how to compute the top-k answers in a data-complexity tractable combination of DLs and LPs under vagueness.
The Effect of Haptic Feedback on Basic Social Interaction within Shared Virtual Environments
Authors: Elias Giannopoulos, Victor Eslava, María Oyarzabal, Teresa Hierro, Laura González, Manuel Ferre, Mel Slater
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

This paper describes an experiment that studies the effect of basic haptic feedback in creating a sense of social interaction within a shared virtual environment (SVE). Although there have been a number of studies investigating the effect of haptic feedback on collaborative task performance, they do not address the effect it has in inducing social presence. The purpose of this experiment is to show that haptic feedback enhances the sense of social presence within a mediated environment. An experiment was carried out using a shared desktop based virtual environment where 20 remotely located couples who did not know one another had to solve a puzzle together. In 10 groups they had shared haptic communication through their hands, and in another group they did not. Hence the haptic feedback was not used for completing the task itself, but rather as a means of social interacting --- communicating with the other participant. The results suggest that basic haptic feedback increases the sense of social presence within the shared VE.
Some thoughts on the underlying logic and process underpinning Electronic Identity (e-ID)
Authors: Tony Collings
Venue: Information Security Tech. Report (2008)

This article I have outlined the fundamental issues that underpin any Identity or e-ID Scheme and any attempt to turn them into an automated e-ID delivery. The significance of Identity has almost gone un-noticed as our highly complex and interdependent technological society has evolved. It is only with the debate surrounding ID card systems and the rise of internet and electronic fraud that there is any awakening and understanding of the real issues that underpin identity and its impact upon society. The article examines why Identity matters by comparing what goes into the underlying logic and process underpinning electronic identity. The European Commission national ID Card scheme and other international perspectives are compared with what the USA is doing in this area and with what the UK is proposing with its national ID Card scheme. A discusses the basics components of identity, identity crime and some unintended consequences of electronic identity schemes.
An Image Authentication Scheme with Localization and Recovery
Authors: Chuanmu Li, Lili Liu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

A block-wise and content-based image authentication scheme with location and recovery is presented. In this scheme, the watermark of each block is an encrypted form of its content-feature, which is embeded in another block which selected by an ergodic matrix of a chaotic sequence. The randomicity of selected block can robust the VQ attack. The encryption further strengthens the security. That all security parameters are user dependent and can be computed at both ends individually based on Diffie-Hellman key exchange method makes the scheme not only robust against collage attack but also truly oblivious. The experiments demonstrate that the proposed scheme can detect and localize any tampering of size 8x8 pixels and above and can recover a 40% damaged image to an intelligible one.
Soft IP Customisation Model Based on Metaprogramming Techniques
Authors: Vytautas Štuikys, Robertas Damaševičius
Venue: Informatica (2004)

We propose a layered Soft IP Customisation (SIPC) model for specifying and implementing system-level soft IP design processes such as wrapping and customisation. The SIPC model has three layers: (1) Specification Layer for specification of a customisation process using UML class diagrams, (2) Generalisation Layer for representation of a customisation process using the metaprogramming techniques, and (3) Generation Layer for generation of the customised soft IP instances from metaspecifications. UML allows us to specify customisation of soft IPs at a high level of abstraction. Metaprogramming allows us to manage variability in a domain, develop generic domain components, and describe generation of customised component instances. The usage of the SIPC model eases and accelerates reuse, adaptation and integration of the pre-designed soft IPs into new hardware designs.
Different Structural Patterns Created by Short Range Variations of Internal Parameters
Authors: Flavia Doboga
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

This papers presents properties of spatial linear systems described by a certain physical quantity generated by a differential equation. This quantity can be represented by internal electric or magnetic field inside the material, by concentration or by similar physical or chemical quantities. A specific differential equation generates this quantity considering as input the spatial alternating variations of an internal parameter. As a consequence, specific spatial linear variations of the observable output physical quantity appear. It is shown that in case of very short range variations of this internal parameters, systems described by a differential equation able to generate a practical test-function exhibit an output which appears to an external observer under the form of two distinct envelopes. These can be considered as two distinct structural patterns located in the same material along a certain linear axis.
Combination of Natural and Numerical Optimization Methods at the Example of an Internal Gas Turbine Cooling Channel
Authors: Helga Steinbrück, Sebastian Zehner, Bernhard Weigand, Sven Olaf Neumann
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

Iceformation phenomena can be observed in many natural and technical processes. A naturally grown ice layer aspires in steady state to a minimum of energy dissipation. Driven by this goal, this phenomena can be used to optimize complex geometric configurations in a natural manner. But since this state of minimum energy dissipation is seldom the desired goal function in technical applications, this natural experimental optimization method is combined with a subsequent classical numerical optimization using evolutionary algorithms at the example of an internal cooling channel of a gas turbine blade.
HSBH Algorithm Based on Chaotic Map
Authors: Jian Zhang, Yu Chen, Ji-feng Guo
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

LSB is a classical algorithm of information hiding in the spatial domain. Although it has high capacity of information hiding, the robustness is weakening. Considering the robustness and security of information hiding, a new spatial domain image information hiding algorithm (HSBH) is proposed, the algorithm improves robust and security by interval set and chaos located. Experimental results indicate that the algorithm can extract the whole secret information from the camouflage-image which was overlapped random noise. When r=4, the value of gray is 46.9% of the total value of gray.
iSky: Efficient and Progressive Skyline Computing in a Structured P2P Network
Authors: Lijiang Chen, Bin Cui, Hua Lu, Linhao Xu, Quanqing Xu
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

An interesting problem in peer-based data management is efficient support for skyline queries within a multiattribute space. A skyline query retrieves from a set of multidimensional data points a subset of interesting points, compared to which no other points are better. Skyline queries play an important role in multi-criteria decision making and user preference applications. In this paper, we address the skyline computing problem in a structured P2P network. We exploit the iMinMax(θ) transformation to map high-dimensional data points to 1-dimensional values. All transformed data points are then distributed on a structured P2P network called BATON, where all peers are virtually organized as a balanced binary search tree. Subsequently, a progressive algorithm is proposed to compute skyline in the distributed P2P network. Further, we propose an adaptive skyline filtering technique to reduce both processing cost and communication cost during distributed skyline computing. Our performance study, with both synthetic and real datasets, shows that the proposed approach can dramatically reduce transferred data volume and gain quick response time.
Domain Ontology-Based Generative Component Design Using Feature Diagrams and Meta-programming Techniques
Authors: Robertas Damaševičius, Vytautas Štuikys, Jevgenijus Toldinas
Venue: Proceedings of the 2nd European conference on Software Architecture (2008)

In domains, where great variability of requirements and products exists such as embedded system design domain, a product line (PL) approach is emerging as the most promising design paradigm. The key for the PL implementation is the use of domain analysis and domain modelling methods. We propose to represent domain variability using feature models enriched with lightweight domain ontology. We transform such models into generative component specifications using meta-programming techniques. We suggest: 1) to use domain analysis methods from two perspectives, software engineering and cognitive science; 2) to enrich domain variability models explicitly by contextualization and repurposing (i.e., by lightweight domain ontology); 3) to represent the model using the enriched feature diagrams (EFDs); 4) to encode EFDs using heterogeneous meta-programming.
Synthesis of the Supervising Agent in MAS
Authors: František Čapkovič
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

The systematic approach to the synthesis of the agent-supervisor supervising a group of agents is presented. It is based on results of the DES (discrete event systems) control theory. The agents as well as the agent-supervisor are understood to be DES and they are modelled by Petri nets (PN). The method based on PN place invariants is used in order to synthetise the supervisor. The illustrative example is introduced to explain the elementary steps of the proposed technique. A counter-example illustrating the limits of the approach is introduced too.
The Future of Train Signaling
Authors: Andreas Svendsen, Gøran K. Olsen, Jan Endresen, Thomas Moen, Erik Carlson, Kjell-Joar Alme, Øystein Haugen
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

Producing the source code for a railway interlocking system based on the description of a station has traditionally been a multistage manual process. We show how this process can be automated and made less error-prone by introducing model-driven development (MDD). This paper addresses the experience of developing a Domain Specific Language (DSL) to describe railway stations, Train Control Language (TCL), and tools to support this language. In the railroad domain where there are extreme safety requirements, it is essential to show that consistency and completeness can be assured. We address how the model is used to generate several different representations for different purposes. We look at advantages and challenges with our approach, and we discuss improvements to existing technologies to support our case better.
Kernel Matrix Learning for One-Class Classification
Authors: Chengqun Wang, Jiangang Lu, Chonghai Hu, Youxian Sun
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

Kernel-based one-class classification is a special type of classification problem, and is widely used as the outlier detection and novelty detection technique. One of the most commonly used method is the support vector dada description (SVDD). However, the performance is mostly affected by which kernel is used. A promising way is to learn the kernel from the data automatically. In this paper, we focus on the problem of choosing the optimal kernel from a kernel convex hull for the given one-class classification task, and propose a new approach. Kernel methods work by nonlinearly mapping the data into an embedding feature space, and then searching the relations among this space, however this mapping is implicitly performed by the kernel function. How to choose a suitable kernel is a difficult problem. In our method, we first transform the data points linearly so that we obtain a new set whose variances equal unity. Then we choose the minimum embedding ball as the criterion to learn the optimal kernel matrix over the kernel convex hull. It leads to the convex quadratically constrained quadratic programming (QCQP). Experiments results on a collection of benchmark data sets demonstrated the effectiveness of the proposed method.
A Virtual and Real HCI System Based on Artificial Immune System
Authors: Ming Chen, Yimin Chen, Zhengwei Yao
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

This paper researches and implements a virtual and real moving objects interaction system in augmented reality (AR) environment based on artificial immune system. A custom artificial immune algorithm is applied in this paper in order to solve the collision detection problems with virtual and real objects. System mainly realized a fast collision detection algorithm to detect the process of actual moving hands and virtual objects, collision. System implements mainly processes as follows: The segmentation of hand images and identification of gestures; the process of transformation coordinate system; rough collision detection process; accurate collision detection; the reactive moving images response. The design of immune algorithm are described and implemented as follows: The identification of antigens aims at solving problems in data input; the initial generation of antibodies; the measurement of antibodies; the selection of concentration; the generation of memory cells; the promotion and suppressor of the antibodies.
Agent-Based Framework for Affective Intelligent Tutoring Systems
Authors: Mahmoud Neji, Mohamed Ben Ammar, Adel. M Alimi, Guy Gouardères
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

Affective Computing is a new Artificial Intelligence area that deals with the possibility of making computers able to recognize human emotions in different ways. This paper represents a study about the integration of this new area in the intelligent tutoring system. The main goal is to analyses learner facial expressions and show how Affective Computing could contribute for this interaction, being part of the development of computer systems where information about learner' emotion would be helpful.
Data Set Homeomorphism Transformation Based Meta-clustering
Authors: Xianchao Zhang, Yu Zong, He Jiang, Xinyue Liu
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Clustering analysis is an important data mining technique with a variety of applications. In this paper, the data set is treated in a dynamic way and a Data Set Homeomorphism Transformation Based Meta-Clustering algorithm (DSHTBMC) is proposed. DSHTBMC decomposes the task of clustering into multiple stages. It firstly constructs a series of homeomorphous data sets ranging from high regularity to low, and then iteratively clusters each homeomorphism data set based on the clustering result of the preceding homeomorphism data set. Since data sets of high regularities are easier to be clustered, and the clustering result of each homeomorphism data set can be used to induce high quality clusters in the following-up homeomorphism data set, in this way, the hardness of the problem is decreased. Two strategies (i.e., Displacement and Noising) for data set homeomorphism transformation are proposed, with classical hierarchical divisive method---Bisecting k-means as DSHTBMC's subordinate clustering algorithm, two new clustering algorithms---HD-DSHTBMC-D and HD-DSHTBMC-N are obtained. Experimental results indicate that the new clustering algorithms are remarkably better than Bisecting k-means algorithm in terms of clustering quality.
Differential Algebra and System Modeling in Cellular Biology
Authors: François Boulier, François Lemaire
Venue: Proceedings of the 3rd international conference on Algebraic Biology (2008)

Among all the modeling approaches dedicated to cellular biology, differential algebra is particularly related to the well-established one based on nonlinear differential equations. In this paper, it is shown that differential algebra makes one of the model reduction methods both simple and algorithmic: the quasi-steady state approximation theory, in the particular setting of generalized chemical reactions systems. This recent breakthrough may suggest some evolution of modeling techniques based on nonlinear differential equations, by incorporating the reduction hypotheses in the models. Potential improvements of parameters fitting methods are discussed too.
Solving Simple Stochastic Games
Authors: Hugo Gimbert, Florian Horn
Venue: Proceedings of the 4th conference on Computability in Europe: Logic and Theory of Algorithms (2008)

We present a new algorithm for solving Simple Stochastic Games (SSGs), which is fixed parameter tractable when parametrized with the number of random vertices. This algorithm is based on an exhaustive search of a special kind of positional optimal strategies, the f-strategies. The running time is , where and are respectively the number of vertices, random vertices and edges, and the maximum bit-length of a transition probability. Our algorithm improves existing algorithms for solving SSGs in three aspects. First, our algorithm performs well on SSGs with few random vertices, second it does not rely on linear or quadratic programming, third it applies to all SSGs, not only stopping SSGs.