ppxscal/embedding_network huggingface dataset:
An Online Theme-Based Collaborative Learning System
Authors: Yonggu Wang, Kedong Li
Venue: Proceedings of the 7th international conference on Advances in Web Based Learning (2008)

In this paper, an online theme-based collaborative learning model (OTBCL model) is proposed. Unlike the current approaches, the model takes into account the two aspects in learning: interpersonal socialization and mental internalization, and joins them with learning portfolios in learning activities of themes. Then, the architecture, user interfaces and learning portfolio module of OTBCL system are elaborately presented, some useful principles are summarized which guide the process of developing learning systems. Finally, a case study was introduced, which explains how to intuitively analyze the participation in group lifecycle with statistical diagrams automatically generated by the system.
Secure Data Flow in a Calculus for Context Awareness
Authors: Doina Bucur, Mogens Nielsen
Venue: Concurrency, Graphs and Models: Essays Dedicated to Ugo Montanari on the Occasion of His 65th Birthday (2008)

We present a Mobile-Ambients-based process calculus to describe context-aware computing in an infrastructure-based Ubiquitous Computing setting. In our calculus, computing agents can provide and discover contextual information and are owners of security policies. Simple access control to contextual information is not sufficient to insure confidentiality in Global Computing, therefore our security policies regulate agents' rights to the provision and discovery of contextual information over distributed flows of actions. A type system enforcing security policies by a combination of static and dynamic checking of mobile agents is provided, together with its type soundness.
Towards Brazilian Portuguese automatic text simplification systems
Authors: Sandra M. Aluísio, Lucia Specia, Thiago A.S. Pardo, Erick G. Maziero, Renata P.M. Fortes
Venue: Proceeding of the eighth ACM symposium on Document engineering (2008)

In this paper we investigate the main linguistic phenomena that can make texts complex and how they could be simplified. We focus on a corpus analysis of simple account texts available on the web for Brazilian Portuguese and propose simplification strategies for this language. This study illustrates the need for text simplification to facilitate accessibility to information by poor literacy readers and potentially by people with other cognitive disabilities. It also highlights characteristics of simplification for Portuguese, which may differ from other languages. Such study consists of the first step towards building Brazilian Portuguese text simplification systems. One of the scenarios in which these systems could be used is that of reading electronic texts produced, e.g., by the Brazilian government or by relevant news agencies.
A modular neural network applied to image transformation and mental images
Authors: Manuel Carcenac
Venue: Neural Computing and Applications (2008)

This paper presents an original modular neural network architecture whose modules are multilayer perceptrons. The modules&#x2019; inputs are external inputs or hidden layers of other modules, thereby allowing them to be connected in a general manner. Based on this flexible architecture, networks with high numbers of inputs and outputs can be elaborated and properly trained. A suitable application is image transformation, i.e. the transformation of many input pixels into as many output pixels. Some architectural variations are presented; first the localization over a fraction of the network of a specific transformation&#x2019;s training, and then the merging of two input images into a single output image. As a case study, we use the modular network to model mental images and their transformations (mental rotation, mental assemblage). It should eventually prove to be a valuable tool for image processing applications, such as super-resolution, or for the elaboration of complex cognitive systems.
The Developer's Guide to Debugging, 1 edition
Authors: Thorsten Grtker, Ulrich Holtmann, Holger Keding, Markus Wloka
Venue:  (2008)

Software has bugs. Period. That's true, unfortunately. Even the good old "hello, world" program, known to virtually every C and C++ programmer in the world, can be considered to be buggy. Developing software means having to deal with defects; old ones, new ones, ones you created yourself, and those that others brought to life. Software developers debug programs for a living. Hence, good debugging skills are a must-have. That said, it is regrettable that debugging is hardly taught in engineering schools. That's how the idea for this book was born. The Developer's Guide to Debugging is a book for both professional software developers seeking to broaden their skills and students that want to learn the tricks of the trade from the ground up. With small examples and exercises it is well suited to accompany a CS course or lecture. At the same time it can be used as a reference guide to address problems as the need arises. This book goes beyond the level of simple source code debugging scenarios. In addition, it covers the most frequent real-world problems from the areas of program linking, memory access, parallel processing and performance analysis. The picture is completed by chapters covering static checkers and techniques to write code that leans well towards debugging. While the focus lies on C and C++, the workhorses of the software industry, one can apply many techniques described in The Developer's Guide to Debugging to programs written in other languages.
Fatigue based structural design optimization implementing a generalized Frost-Dugdale crack growth law
Authors: K. Krishnapillai, R. Jones, D. Peng
Venue: Proceedings of the 10th WSEAS International Conference on Mathematical Methods and Computational Techniques in Electrical Engineering (2008)

The structural optimisation procedure proposed integrates 3D geometrical modelling, structural analysis and optimization into one complete and automated computer-aided design process. This approach includes the implementation of the generalised Frost-Dugdale model, in which recent observation has revealed a near log-linear relationship between natural log of the crack length and the fatigue life for crack growth lengths as small as a few microns. Consequently, design against fatigue failure can include the analysis of near-threshold crack propagation, i.e. growth in the low-to-mid stress intensity factor range. The research presented here uses the generalised Frost-Dugdale model in a 3D numerical fatigue based optimisation study of a 7050-T7451 Aluminium structure. Two types of optimisation techniques were considered for this investigation; a gradient-less based and an enumeration scheme. The enumeration scheme takes advantage of a cluster computer architecture to produce a solution space. As a result, this procedure illustrates that for the design of light weight structures, a fatigue based optimisation used in conjunction with visualisation of the solution space may provide a viable design methodology. Furthermore, the possibility of the application of the Generalised Frost-Dugdale model in design optimisation has been demonstrated. This procedure has the potential to be applied to structures with complex structural configurations taking into account crack propagation in the near-threshold region.
Multi-focus Image Fusion with the Double-Density Dual-Tree DWT
Authors: A-Chuan Wang, Peng Zhao
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

This paper presents a novel multi-focus image fusion based on a double-density dual-tree discrete wavelet transform. The original image is decomposed into the 16-subband image pyramid by this wavelet. The image fusion process is performed by the direction value and the region standard deviation to get the fused 16-subband image pyramid. The final fused image is formed with the 16-subband image reconstruction. The fusion experiments indicate this image fusion is superior to the traditional image fusion based on the contrast pyramid or the wavelet decomposition.
Work Distribution and Resource Management in BPEL4People: Capabilities and Opportunities
Authors: Nick Russell, Wil M. Aalst
Venue: Proceedings of the 20th international conference on Advanced Information Systems Engineering (2008)

The BPEL4People and WS-HumanTask extensions to the BPEL proposal define the state of the art in resource management and work distribution in business process execution languages. In this paper, we use the workflow resource patterns as an evaluation framework to assess the capabilities of BPEL4People and WS-HumanTask and identify several areas where there is opportunity for further improvement.
Software connectors for highly distributed and voluminous data-intensive systems
Authors: Nenad Medvidovic
Venue:  (2007)

Data-intensive systems and applications transfer large volumes of data and metadata to highly distributed users separated by geographic distance and organizational boundaries. A dominating factor in these large volume data transfers is the selection of the appropriate software connector that satisfies user constraints on the required data distribution scenarios. This task is typically accomplished by consulting &ldquo;gurus'&rdquo; who rely on their intuitions, at best backed by anecdotal evidence. In this dissertation we motivate, present and evaluate a software architecture-based systematic framework for selecting software connectors based on eight key dimensions of data distribution that we use to represent the data distribution scenarios. Our framework, dubbed DISCO, accurately, efficiently, and reliably captures a guru's domain knowledge and allows a user to automatically leverage that knowledge to drive connector selection. In addition, DISCO affords a user the ability to validate a guru's domain knowledge against actual performance measurements of the connectors in the areas of efficiency, scalability, dependability and consistency. We provide a set of models, algorithms, techniques and tools to represent data distribution scenarios, classify and select connectors and explore the trade off space when architecting large scale data distribution systems. To date, 13 real-world connectors across four connector families have been explored using our framework. We validate our framework empirically and qualitatively, employing 30 data distribution scenarios gleaned from three real-world projects spanning planetary science, cancer research and earth science at NASA's Jet Propulsion Laboratory. We use a number of measures of accuracy including precision, recall and error rate. We also provide theoretical performance analysis of our connector selection algorithms. We report empirical performance measurements of the 13 connectors and use the data to revise and validate our precision measurements. In addition to our validation, we have integrated DISCO as a &ldquo;plug-in&rdquo; piece to an independently-developed COTS interoperability assessment framework, providing more feedback for a second use-case of the tool. We conclude the dissertation with a set of open research questions that will frame our future work.
Optimization Algorithms to Find Most Similar Deductive Consequences (MSDC)
Authors: Babak Mougouie
Venue: Proceedings of the 9th European conference on Advances in Case-Based Reasoning (2008)

Finding most similar deductive consequences, MSDC, is a new approach which builds a unified framework to integrate similarity-based and deductive reasoning. In this paper we introduce a new formulation $\mathcal{OP}$-MSDC(q) of MSDC which is a mixed integer optimization problem. Although mixed integer optimization problems are exponentially solvable in general, our experimental results show that $\mathcal{OP}$-MSDC(q) is surprisingly solved faster than previous heuristic algorithms. Based on this observation we expand our approach and propose optimization algorithms to find the k most similar deductive consequences k-MSDC.
Tiling Slideshow: An Audiovisual Presentation Method for Consumer Photos
Authors: Wei-Ta Chu, Jun-Cheng Chen, Ja-Ling Wu
Venue: IEEE MultiMedia (2007)

The Tiling Slideshow system automatically organizes consumer photos and provides a novel audiovisual presentation. Displaying at the same pace as user-selected music, photos are elaborately manipulated and displayed to mold a novel browsing experience. In contrast to conventional photo slideshows, the proposed presentation provides tighter audiovisual coordination, and offers a more lively viewing experience.
Formal Translation Directed by Parallel LLP Parsing
Authors: Ladislav Vagner, Bořivoj Melichar
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

Formal translation directed by parallel LLP parsing is presented here. The translator follows the traditional translation scheme --- the input grammar is extended by output symbols that are added into appropriate right-hand sides of grammar rules. The translation algorithm is based on the intermediate results provided by the parallel LLP parser. The correct sequence of output symbols is obtained from the intermediate results using the parallel prefix sum, the segmented parallel prefix sum, and parallel sorting steps. The translation algorithm presented here is suitable for all translations with LLP(q,k) input grammars. The asymptotical parallel time of the translation algorithm is ${\mathcal O}(\log^2(n))$.
Acquisition of Telephone Data from Radio Broadcasts with Applications to Language Recognition
Authors: Oldřich Plchot, Valiantsina Hubeika, Lukáš Burget, Petr Schwarz, Pavel Matějka
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

This paper presents a procedure of acquiring linguistic data from the broadcast media and its use in language recognition. The goal of this work is to answer the question whether the automatically obtained data from broadcasts can replace or augment to the continuous telephone speech. The main challenges are channel compensation issues and great portion of unspontaneous speech in broadcasts. The experimental results are obtained on NIST LRE 2007 evaluation system, using both NIST provided training data and data, obtained from broadcasts.
Data management and data analysis techniques for wireless sensor networks
Authors: Dimitrios Gunopulos
Venue:  (2007)

Fast developments in microelectronics and wireless technologies have made feasible the development of wireless sensor networks (WSN) composed of large numbers of small and smart sensors. Though cheap and small, the sensor devices have many resource limitations that introduce new challenges to the data management in sensor networks. Among all these limitations, energy is usually the primary concern when designing a sensor network algorithm. This dissertation presents two efficient approaches, data compression and data sampling, to minimize the energy consumption of the sensor networks. More specifically, it presents and evaluates an efficient data compression technique&mdash;the ALVQ (Adaptive Learning Vector Quantization) algorithm to compress the historical information in sensor networks with high accuracy. It shows how the ALVQ algorithm can be extended to compress multi-dimensional information and how the compressed data are transmitted in a sensor network while maximizing the precision. In addition, it proposes an efficient online sampling algorithm, Region Sampling, to retrieve a small fraction of the sensor data from the network while approximate the aggregate queries accurately. It demonstrates how a sensor network can be segmented into partitions of non-overlapping regions and how to use sampling energy cost rate and sampling statistics to compute the optimal sampling plan in different regions. In addition to energy-efficient data transmission, rapid developments in flash memories have made possible the ability to store large amounts of data within individual sensors. This dissertation presents two index structures, MicroHash and MicroGF, for efficient retrieval of one dimensional and multi-dimensional sensor data stored in the flash memory of a sensor device. It shows how to exploit the asymmetric read/write and wear characteristics of flash memory in order to offer high performance indexing and searching capabilities. Finally it considers a typical sensor network application, distributed spatio-temporal similarity search , and shows how to combine local computations of lower and upper bounds in order to find the trajectories that are most similar to the query.
Efficient Distributed Third-Party Data Authentication for Tree Hierarchies
Authors: Hao Yuan, Mikhail J. Atallah
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

In the third-party model for the distribution of data, the trusted data creator or owner provides an untrusted distributor D with integrity verification (IV) items that are stored at D in addition to the n data items. When a user U has a subset of n' of those n data items and needs to verify their integrity, U is provided by D with a number of IV items that U uses to verify its data's integrity. The model forbids U from receiving any information about the n-n' data items that the user is not authorized to access, and assumes that D has no signature authority (it stores only pre-signed IVs). Most of the published work in this area uses the Merkle tree or variants thereof, and typically requires D to store a linear or close to linear (in n) number s(n) of IV items that are pre-signed by the trusted authority. Moreover, most of the existing schemes impose on D a non-constant amount of computation work t(n) (typically logarithmic in n) in order to provide U with the IV items that enable U to verify the integrity of its data; we call h(n) the number of such IV items. The h(n) values found in the literature are non-constant, i.e., they actually do depend on the number of data items. The main contribution of this paper is to achieve linear s(n), constant h(n) and constant or logarithmic t(n) when the n data items are organized in a tree hierarchy T, and the user's subset of n' items form a subtree T'. The cases of T' considered are when T' is (i) rooted at a node v and of depth k below v; and (ii) reachable in k hops from v going both up and down in T.
On-Line Video Summarization Based on Signature-Based Junk and Redundancy Filtering
Authors: Víctor Valdés, José M. Martínez
Venue: Proceedings of the 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services (2008)

The huge amount of video content and the increasing rate in which new content is being created makes video summarization a necessary tool for the efficient access and management of video repositories. Nevertheless, the huge amount of data and the complexity of current techniques make the implantation of the summarization systems a difficult or non practical task. This paper presents current advances in the development of a novel algorithm for on-line video summarization, which can be easily used also as a video retrieval tool, aimed to combine summarization quality with high computational efficiency providing a system that can be practical for both commercial and home environments.
Iteratively Reweighted Fitting for Reduced Multivariate Polynomial Model
Authors: Wangmeng Zuo, Kuanquan Wang, David Zhang, Feng Yue
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Recently a class of reduced multivariate polynomial models (RM) has been proposed that performs well in classification tasks involving few features and many training data. The RM method, however, adopts a ridge least-square estimator, overlooking the fact that least square error usually does not correspond to minimum classification error. In this paper, we propose an iteratively reweighted regression method and two novel weight functions for fitting the RM model (IRF-RM). The IRF-RM method iteratively increases the weights of samples prone to misclassification and decreases the weights of samples far from the decision boundary, making the IRF-RM model more suitable for efficient pattern classification. A number of benchmark data sets are used to evaluate the IRF-RM method. Experimental results indicate that IRF-RM achieves a higher or comparable classification accuracy compared with RM and several state-of-the-art classification approaches.
Symbolic Classification of General Two-Player Games
Authors: Stefan Edelkamp, Peter Kissmann
Venue: Proceedings of the 31st annual German conference on Advances in Artificial Intelligence (2008)

In this paper we present a new symbolic algorithm for the classification, i. e. the calculation of the rewards for both players in case of optimal play, of two-player games with general rewards according to the Game Description Language. We will show that it classifies all states using a linear number of images concerning the depth of the game graph. We also present an extension that uses this algorithm to create symbolic endgame databases and then performs UCT to find an estimate for the classification of the game.
Blossoming and curvatures of surface patches
Authors: Przemysław Kiciak, Renata Kiełbiewska
Venue: Computer Aided Geometric Design (2008)

The ratio of curvatures of a polynomial curve p of degree n and its blossom curve of degree k at a given point u is a constant depending only on n and k. In this paper analogous properties of polynomial and rational patches (in triangular and tensor Bezier representations) are searched.
Evolving Connectionist Systems for Adaptive Sport Coaching
Authors: Boris Bacic, Nikola Kasabov, Stephen Macdonell, Shaoning Pang
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

Contemporary computer assisted coaching software operates either on a particular sub-space of the wider problem or requires expert(s) to operate and provide explanations and recommendations. This paper introduces a novel motion data processing methodology oriented to the provision of future generation sports coaching software. The main focus of investigation is the development of techniques that facilitate processing automation, incremental learning from initially small data sets, and robustness of architecture with a degree of interpretation on individual sport performers' motion techniques. Findings from a case study using tennis motion data verify the prospect of building similar models and architectures for other sports or entertainment areas in which the aims are to improve human motion efficacy and to prevent injury. A central feature is the decoupling of the high-level analytical architecture from the low-level processing of motion data acquisition hardware, meaning that the system will continue to work with future motion acquisition devices.
Refreshable tactile graphics applied to schoolbook illustrations for students with visual impairment
Authors: Grégory Petit, Aude Dufresne, Vincent Levesque, Vincent Hayward, Nicole Trudeau
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

This article presents research on making schoolbook illustrations accessible for students with visual impairment. The MaskGen system was developed to interactively transpose illustrations of schoolbooks into tactile graphics. A methodology was designed to transpose the graphics and prepare them to be displayed on the STReSS2, a refreshable tactile device. We experimented different associations of tactile rendering and audio feedbacks to find a model that children with visual impairment could use. We experimented with three scientific graphics (diagram, bar-chart and map) with forty participants: twenty sighted adults, ten adults with visual impairment, and ten children with visual impairment. Results show that the participants with visual impairment liked the tactile graphics and could use them to explore illustrations and answer questions about their content.