ppxscal/embedding_network huggingface dataset:
Dot Detection of Optical Braille Images for Braille Cells Recognition
Authors: Amany Al-Saleh, Ali El-Zaart, Abdulmalik Alsalman
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

Braille is a tactile format of written communication for people with low vision and blindness worldwide. Optical Braille Recognition (OBR) offers many benefits to Braille users and people who work with them. This paper presents a new algorithm for detecting dots composing Braille characters in an image of embossed Braille material obtained by an optical scanner. We assume that a mixture of Beta distributions can model the histogram of a scanned Braille document. The core of the proposed method is the use of stability of thresholding with Beta distribution to initiate the process of thresholds estimation. Segmented Braille image is then used to form a grid that contains recto dots and another one that contains verso dots. Using segmented image, Braille dots composing characters on both single-sided and double-sided documents are automatically identified from those grids with excellent accuracy.
Implement Web Learning System Based on Genetic Algorithm and Pervasive Agent Ontology
Authors: Qinglin Guo, Ming Zhang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

For a web-based dynamic learning environment, personalized support for learners becomes more important. In order to achieve optimal efficiency in a learning process, individual learner's cognitive learning style should be taken into account. It is necessary to provide learners with an individualized learning support system. In this paper, a framework of web learning system based on genetic algorithm and Pervasive Agent Ontology is presented. The proposed framework utilizes genetic algorithm for representing and extracting a dynamic learning process and learning pattern to support students' deep learning in web-based learning environment. Aiming at the problems in current Web environment, we put forward the information integration method of Semantic Web based on Pervasive Agent Ontology (SWPAO method), which will integrate, analyze and process enormous web information and extract answers for students on the basis of semantics. And experiments do prove that it is feasible to use the method to develop an individual Web-based learning system, which is valuable for further study in more depth.
Self-Organizing Clustering with Map of Nonlinear Varieties Representing Variation in One Class
Authors: Hideaki Kawano, Hiroshi Maeda, Norikazu Ikoma
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

Adaptive Subspace Self-Organizing Map (ASSOM) is an evolution of Self-Organizing Map, where each computational unit defines a linear subspace. Recently, its modified version, where each unit defines an linear manifold instead of the linear subspace, has been proposed. The linear manifold in a unit is represented by a mean vector and a set of basis vectors. After training, these units result in a set of linear variety detectors. In another point of view, we can consider the AMSOM represents the latent commonality of data as linear structures. In numerous cases, however, these are not enough to describe the latent commonality of data because of its linearity. In this paper, the nonlinear variety is considered in order to represent a diversity of data in a class. The effectiveness of the proposed method is verified by applying it to some simple classification problems.
Mapping Heavy Communication Grid-Based Workflows Onto Grid Resources Within an SLA Context Using Metaheuristics
Authors: Dang Minh Quan, D. Frank Hsu
Venue: International Journal of High Performance Computing Applications (2008)

Service Level Agreements (SLAs) are currently one of the major research topics in grid computing. Among many system components for SLA-related grid jobs, the SLA mapping mechanism has received widespread attention. It is responsible for assigning sub-jobs of a workflow to a variety of grid resources in a way that meets the user's deadline and costs as little as possible. With the distinguished workload and resource characteristics, mapping a heavy communication workflow within an SLA context gives rise to a complicated combinatorial optimization problem. This paper presents the application of various metaheuristics and suggests a possible approach to solving this problem. Performance measurements deliver evaluation results on the quality and efficiency of each method.
Predicting Future User Behaviour in Interactive Live TV
Authors: Martin Gude, Stefan M. Grünvogel, Andreas Pütz
Venue: Proceedings of the 6th European conference on Changing Television Environments (2008)

Recommender systems are a means of personalisation providing their users with personalised recommendations of items that would possibly suit the users needs. They are used in a broad area of contexts where items are somehow linked to users. The creation of recommendations of interactive live TV suffers from several inherent problems, e.g. the impossibility to foresee the contents of the next items or the reactions of the user to the changing programme.This paper proposes an algorithm for building personalised streams within interactive live TV. The development of the algorithm comprises a basic model for users and media items. A first preliminary evaluation of the alogithm is executed and the results discussed.
Quantization Error and Accuracy-Performance Tradeoffs for Embedded Data Mining Workloads
Authors: Ramanathan Narayanan, Berkin Özışkyılmaz, Gokhan Memik, Alok Choudhary, Joseph Zambreno
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Data mining is the process of automatically finding implicit, previously unknown and potentially useful information from large volumes of data. Embedded systems are increasingly used for sophisticated data mining algorithms to make intelligent decisions while storing and analyzing data. Since data mining applications are designed and implemented considering the resources available on a conventional computing platform, their performance degrades when executed on an embedded system. In this paper, we analyze the bottlenecks faced in implementing these algorithms in an embedded environment and explore their portability to the embedded systems domain. Particularly, we analyze the floating point computation in these applications and convert them into fixed point operations. Our results reveal that the execution time of five representative applications can be reduced by as much as 11.5× and 5.2× on average, without a significant impact on accuracy.
Particle Swarm Optimization for Bézier Surface Reconstruction
Authors: Akemi Gálvez, Angel Cobo, Jaime Puig-Pey, Andrés Iglesias
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

This work concerns the issue of surface reconstruction, that is, the generation of a surface from a given cloud of data points. Our approach is based on a metaheuristic algorithm, the so-called Particle Swarm Optimization. The paper describes its application to the case of Bézier surface reconstruction, for which the problem of obtaining a suitable parameterization of the data points has to be properly addressed. A simple but illustrative example is used to discuss the performance of the proposed method. An empirical discussion about the choice of the social and cognitive parameters for the PSO algorithm is also given.
Simulation Analysis of High Speed Underwater Acoustic Communication Based on a Statistical Channel Model
Authors: Guoqing Zhou, Taebo Shim
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

Underwater acoustic channel (UACh) requires robust techniques to get high speed data transmission for reliable communication. This paper presents the adaptive transmission technique in conjunction with the maximal ratio combining (MRC) diversity technique to adapt the UACh fluctuation based on a statistical channel model. Simulation analysis shows that we can optimize the data rate allowing the transmit power to vary with SNR, subject to an average power constraint, and also shows that data rate can be increased under adaptive technique in conjunction with two branch diversity. Under the optimum data rate, the Matlab simulink of UACh QPSK communication system gives a benchmark for the future real experiment in the ocean.
Cortical dynamics of anticipatory mechanisms in interception: A neuromagnetic study
Authors: Patrice Senot, Sylvain Baillet, Bernard Renault, Alain Berthoz
Venue: Journal of Cognitive Neuroscience (2008)

Humans demonstrate an amazing ability for intercepting and catching moving targets, most noticeably in fast-speed ball games. However, the few studies exploring the neural bases of interception in humans and the classical studies on visual motion processing and visuomotor interactions have reported rather long latencies of cortical activations that cannot explain the performances observed in most natural interceptive actions. The aim of our experiment was twofold: (1) describe the spatio-temporal unfolding of cortical activations involved in catching a moving target and (2) provide evidence that fast cortical responses can be elicited by a visuomotor task with high temporal constraints and decide if these responses are task or stimulus dependent. Neuromagnetic brain activity was recorded with whole-head coverage while subjects were asked to catch a free-falling ball or simply pay attention to the ball trajectory. A fast, likely stimulus-dependent, propagation of neural activity was observed along the dorsal visual pathway in both tasks. Evaluation of latencies of activations in the main cortical regions involved in the tasks revealed that this entire network of regions was activated within 40 msec. Moreover, comparison of experimental conditions revealed similar patterns of activation except in contralateral sensorimotor regions where common and catch-specific activations were differentiated.
An efficient algorithm for attention-driven image interpretation from segments
Authors: Hong Fu, Zheru Chi, Dagan Feng
Venue: Pattern Recognition (2009)

In the attention-driven image interpretation process, an image is interpreted as containing several perceptually attended objects as well as the background. The process benefits greatly a content-based image retrieval task with attentively important objects identified and emphasized. An important issue to be addressed in an attention-driven image interpretation is to reconstruct several attentive objects iteratively from the segments of an image by maximizing a global attention function. The object reconstruction is a combinational optimization problem with a complexity of 2^N which is computationally very expensive when the number of segments N is large. In this paper, we formulate the attention-driven image interpretation process by a matrix representation. An efficient algorithm based on the elementary transformation of matrix is proposed to reduce the computational complexity to 3@wN(N-1)^2/2, where @w is the number of runs. Experimental results on both the synthetic and real data show a significantly improved processing speed with an acceptable degradation to the accuracy of object formulation.
Sound propagation model for sound source localization in area of observation of an audio robot
Authors: Snejana Pleshkova, Alexander Bekiarski
Venue: Proceedings of the 9th WSEAS International Conference on Neural Networks (2008)

An audio robot uses sound information to localize the subjects or persons in area of observation. The main problem in this case is to recover the sound direction and to localize the position of the talker. This problem is similar to the ability of human hearing system for sound localization. The attempt in this article is to model the sound propagation and to use this model to determine the sound direction and to do sound localization.
Compressing Very Large Database Workloads for Continuous Online Index Selection
Authors: Piotr Kołaczkowski
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

The paper presents a novel method for compressing large database workloads for purpose of autonomic, continuous index selection. The compressed workload contains a small subset of representative queries from the original workload. A single pass clustering algorithm with a simple and elegant selectivity based query distance metric guarantees low memory and time complexity. Experiments on two real-world database workloads show the method achieves high compression ratio without decreasing the quality of the index selection problem solutions.
An efficient low cost approach for on-line signature recognition based on length normalization and fractional distances
Authors: Carlos Vivaracho-Pascual, Marcos Faundez-Zanuy, Juan M. Pascual
Venue: Pattern Recognition (2009)

This work presents a new proposal for an efficient on-line signature recognition system with very low computational load and storage requirements, suitable to be used in resource-limited systems like smart-cards. The novelty of the proposal is in both the feature extraction and classification stages, since it is based on the use of size normalized signatures, which allows for similarity estimation, usually based on dynamic time warping (DTW) or hidden Markov models (HMMs), to be performed by an easy distance calculation between vectors, which is computed using fractional distance, instead of the more typical Euclidean one, so as to overcome the concentration phenomenon that appears when data are high dimensional. Verification and identification tasks have been carried out using the MCYT database, achieving an EER (common threshold) of 6.6% and 1.8% with skilled and random forgeries, respectively, in the first task and 3.6% of error in the second. The proposed system outperforms DTW-based and HMM-based ones, even though these have proved to be very efficient in on-line signature recognition, with storage requirements between 9 and 90 times lesser and a processing speed between 181 and 713 times greater than the DTW-based systems.
Apartness, compactness and nearness
Authors: Douglas Bridges, Hajime Ishihara, Peter M. Schuster, Luminia Vî
Venue: Theoretical Computer Science (2008)

We investigate constructively a pre-apartness structure that is classically important in the characterisation of compact proximity spaces, and that may help identify a good constructive notion of compactness for not-necessarily-uniform apartness spaces. In addition, we produce what may be the right notion of ''nearness'' in the theory of apartness spaces.
Smart Environment Vectorization
Authors: Alejandro Fernández-Montes, Juan A. Ortega, Luis González, Juan A. Álvarez, Manuel D. Cruz
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

The automation of smart environment systems is one of the main goals of smart home researching. This paper focus on learning user lighting preference, considering a working field like a standard office. A review of the smart environment and devices setup is done, showing a real configuration for test purposes. Suitable learning machine techniques are exposed in order to learn these preferences, and suggest the actions the smart environment should execute to satisfy the user preferences. Learning machine techniques proposed are fed with a database, so a proposal for the vectorization of data is described and analyzed.
Business Value Chains in Real-Time On-Line Interactive Applications
Authors: Justin Ferris, Mike Surridge, E. Rowland Watkins
Venue: Proceedings of the 5th international workshop on Grid Economics and Business Models (2008)

Grid infrastructure are already being used in the on-line gaming sector to provide large-scale game hosting in a business context. However, the game platforms and infrastructures used do not take advantage of the potential for rich business networks to support indefinite scaling within single game instances, or to simplify the problem of managing the quality of experience and access rights for end customers. The European edutain@grid research project is developing an infrastructure for realising such business networks using bipartite Service Level Agreements. This paper describes the analysis of business value chains and SLA terms for the initial implementation, and provides insights into how these should be formulated, and what challenges this presents to Grid infrastructure implementers.
Real-Time Data Stream Management System for Large Volume of RFID Events
Authors: So Young Choi, Ho Min Jung, Ki Seok Bang, Wan Yeon Lee, Young Woong Ko
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

A data stream management system (DSMS) for the real-time processing of a large volume of RFID events is proposed herein. It allows the real-time scheduling of groups of operators, the components of a query, to process user queries of various kinds within the time limit. It also creates user-level threads consisting of operators, and the DSMS scheduler schedules the threads of a query, depending on the priority. A prototype of the proposed system was built, and the scheduling of a large volume of RFID events was shown through experiments
An Elastoplastic Hydro-mechanical Model for Unsaturated Soils
Authors: De'An Sun, Li Xiang
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

This paper presents a coupled elastoplastic constitutive model for predicting the hydraulic and stress-strain-strength behaviour of unsaturated soils. Hydraulic hysteresis in the water-retention behaviour is modeled as an elastoplastic process with the elastic region of the saturation degree. The effect of change in degree of saturation on the stress-strain-strength behaviour and the effect of change in void ratio on the water-retention behaviour are taken into consideration in the model, in addition to the effect of suction on the hydraulic and mechanical behaviour. Model predictions of the stress-strain and water-retention behaviour are compared with those obtained from triaxial tests on unsaturated soil along isotropic compression, triaxial stress paths with or without variation in suction.
A Collaborative Model for Wireless Sensor Networks Applied to Museums' Environmental Monitoring
Authors: Lina M. Brito, Laura M. Rodríguez Peralta
Venue: Proceedings of the 5th international conference on Cooperative Design, Visualization, and Engineering (2008)

The major functions of the Wireless Sensor Networks (WSNs) cannot be accomplished without collaboration among sensor nodes. However, most of the work found in literature only focuses on a specific type of collaboration, associated with the accomplishment of a certain task, such as: sensing, signal processing, computing, routing, etc. In this paper, we present a graph-based model of collaborative work for WSNs. This model is called Wireless Sensor Networks Supported Cooperative Work (WSNSCW) and was created for the specific case of WSNs. We also present the formalization of some of the entities of the model and of its properties. This is a generic model that is being used as a basis for the development of a 3D web-based awareness tool for WSNs. In this paper, the model is applied to the specific case of a WSN created in a museum for artwork conservation.
Using Translation Heuristics to Improve a Multimodal and Multilingual Information Retrieval System
Authors: Miguel Ángel García-Cumbreras, Maria Teresa Martín-Valdivia, Luis Alfonso Ureña-López, Manuel Carlos Díaz-Galiano, Arturo Montejo-Ráez
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

Nowadays, the multimodal nature of the World Wide Web is an evidence. Web sites which include video files, pictures, music and text have become widespread. Furthermore, multimodal collections in several languages demand to apply multilingual information retrieval strategies. This paper describes a new retrieval technique applied on a multimodal and multilingual system that have been tested on two different multilingual image collections. The system applies several machine translators and implements some novel heuristics. These heuristics explore a variety of ways to combine the translations obtained from the given set of translators, and the configuration of the retrieval model by using different weighting functions, and also studying the effect of pseudo-relevance feedback (PRF) on this domain. Our results show interesting effects by these variations, allowing the determination of the parameters for the best retrieval model on this data and reporting the loss in performance on each language.
Provenance Provisioning in Mobile Agent-Based Distributed Job Workflow Execution
Authors: Yuhong Feng, Wentong Cai
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

Job workflow systems automate the execution of scientific applications, however they may hide how the results are achieved (i.e., the provenance information of the job workflow execution). This paper describes the development and evaluation of a decentralized recording and collection scheme for job workflow provenance in mobile agent-based distributed job workflow execution. A performance study was conducted to evaluate our approach against the one using a centralized provenance server. The results are discussed in the paper.
Existence of solutions for first order PBVPs with impulses on time scales
Authors: Zongyi Wang, Peixuan Weng
Venue: Computers Mathematics with Applications (2008)

In this paper, we consider some kind of nonlinear periodic differential equation with impulses on time scales, and give some new criteria for the existence of at least one solution by using differential inequalities and fixed point theorems.
Automatic Generation of User Adapted Learning Designs: An AI-Planning Proposal
Authors: Lluvia Morales, Luis Castillo, Juan Fernandez-Olivares, Arturo Gonzalez-Ferrer
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

A Learning Design(LD) definition under the IMS-LD standard is a complex task for the instructor because it requires a lot of time, effort and previous knowledge of the students group over which will be defined the knowledge objectives. That is why, taking advantage from diffusion of learning objects(LO) labeling using IMS-MD standard, we have proposed to realize a knowledge engineering process, represented as an algorithm, over LO labels and user profiles to automaticaly define a domain that will be used by an intelligent planner to build a LD. This LD will be finally implemented in the ILIAS Learning Management System(LMS).