ppxscal/embedding_network huggingface dataset:
Statistical Machine Translation of Broadcast News from Spanish to Portuguese
Authors: Raquel Sánchez Martínez, João Paulo Silva Neto, Diamantino António Caseiro
Venue: Proceedings of the 8th international conference on Computational Processing of the Portuguese Language (2008)

In this paper we describe the work carried out to develop an automatic system for translation of broadcast news from Spanish to Portuguese. Two challenging topics of speech and language processing were involved: Automatic Speech Recognition (ASR) of the Spanish News and Statistical Machine Translation (SMT) of the results to the Portuguese language. ASR of broadcast news is based on the AUDIMUS.MEDIA system, a hybrid ANN/HMM system with multiple stream decoding. A 22.08% Word Error Rate (WER) was achieved in a Spanish Broadcast News task, which is comparable to other international state of the art systems. Parallel normalized texts from European Parliament database were used to train the SMT system from Spanish to Portuguese. Preliminary non-exhaustive human evaluation showed a fluency of 3.74 and sufficiency of 4.23.
Practical Rails Plugins
Authors: Nick Plante, David Berube
Venue: Practical (2008)

The Rails framework empowers developers with unprecedented levels of productivity by embracing principles such as convention over configuration and dont repeat yourself. This paradigm is even apparent at the community level, where developers regularly share their custom framework extensions by way of Rails plugins feature. Plugins offer a way for developers to extend the core Rails framework with their own custom features, allowing for rapid integration of features such as authentication, user ratings, and search. Practical Rails Plugins shows you how to capitalize upon the wide variety of plugins at your disposal by guiding you through their integration into a number of interesting projects. Youll learn how to rapidly augment projects involving asynchronous video transcoding, geocoding and mapping, content management, community ratings, and PDF generation. Youll also learn how to create and distribute your own plugins. The ultimate guide to building powerful web sites faster using Rails plugins Demonstrates how to use popular plugins within a number of practical (and fully functional) projects and miniapplications Shows you how to create and distribute your own plugins What youll learn Install and manage your plugin collection. Effectively manage the development process using plugins for browser testing, model augmentation, and data validation. Use plugins to expand your applications abilities, adding features such as OpenID authentication, file attachment handling, graphing and charting, and full text search. Create and distribute your own plugins for use by other community members! Who is this book for? Rails developers interested in taking advantage of plugins to streamline application development.
Fast Computation of Point-to-Point Paths on Time-Dependent Road Networks
Authors: Giacomo Nannicini, Philippe Baptiste, Daniel Krob, Leo Liberti
Venue: Proceedings of the 2nd international conference on Combinatorial Optimization and Applications (2008)

We propose an algorithm for the point-to-point time-dependent shortest path problem, using which good solutions may be found in a short time; our method provides an upper bound to the number of settled nodes for each shortest path computation, which is highly desirable in some industrial applications. In particular, we address a typical server scenario, where we have to compute point-to-point shortest paths in road networks where arc costs (travelling times) are time-dependent, and where each request has to be provided within an allotted time frame.
Tactor Localization at the Wrist
Authors: Hsiang-Yu Chen, Joseph Santos, Matthew Graves, Kwangtaek Kim, Hong Z. Tan
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

The present study examined our ability to identify the location of a single vibration delivered to the dorsal and/or volar side of the forearm near the wrist. Three participants took part in three absolute identification experiments. In Exps. I and II, a 3-by-3 tactor array was placed on the dorsal and volar side of the wrist, respectively. In Exp. III, two 3-by-3 tactor arrays were placed on both sides of the wrist. Prior to each experiment, the intensities of the tactors were adjusted to be equally loud. Each participant completed a total of 405, 405 and 810 trials for Exps. I, II and III, respectively. The results indicate that on average, only 2 tactor locations can be correctly identified on either the dorsal or the volar side of the wrist, and 4 locations on both sides. The implications of our results for the design of mobile devices are discussed.
Cross-Curriculum Search for Intergeo
Authors: Paul Libbrecht, Cyrille Desmoulins, Christian Mercat, Colette Laborde, Michael Dietrich, Maxim Hendriks
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

Intergeo is a European project dedicated to the sharing of interactive geometry constructions. This project is setting up an annotation and search web platform which will offer and provide access to thousands of interactive geometry constructions and resources using them. The search platform should cross the boundaries of the curriculum standards of Europe. A topics and competency based approach to retrieval for interactive geometry with designation of the semantic entities has been adopted: it requests the contributor of an interactive geometry resource to input the competencies and topics involved in a construction, and allows the searcher to find it by the input of competencies and topics close to them; both rely on plain-text-input.This paper describes the current prototypes, the input-methods, the workflows used, and the integration into the Intergeo platform.
Average misbelief criterion in the minimal fuzzy covering problem
Authors: Anna Sikharulidze, Gia Sirbiladze
Venue: Proceedings of the 9th WSEAS International Conference on Fuzzy Systems (2008)

A new criterion is introduced for a minimal fuzzy covering which is a minimal value of average misbelief in possible alternatives. A bicriterion problem is obtained using the new criterion and the criterion of covering price minimization. The proposed approach is illustrated by a concrete example.
GA-Based Neural Network to Identification of Nonlinear Structural Systems
Authors: Grace S. Wang, Fu-Kuo Huang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

The initial weights of neural network (NN) are randomly selected and thus the optimization algorithm used in the training of NN may get stuck in the local minimal. Genetic algorithm (GA) is a parallel and global search technique that searches multiple points, so it is more likely to obtain a global solution. In this regard, a new algorithm of combining GA and NN is proposed here. The GA is employed to exploit the initial weights and the NN is to obtain the network topology. Through the iterative process of selection, reproduction, cross over and mutation, the optimal weights can then be obtained. The proposed new algorithm is applied to the Duffing's oscillator and Wen's degrading nonlinear systems. Finally, the accuracy of this method is illustrated by comparing the results of the predicted response with the measured one.
Opinion Analysis Across Languages: An Overview of and Observations from the NTCIR6 Opinion Analysis Pilot Task
Authors: David Kirk Evans, Lun-Wei Ku, Yohei Seki, Hsin-Hsi Chen, Noriko Kando
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

In this paper we introduce the NTCIR6 Opinion Analysis Pilot Task, information about the Chinese, Japanese, and English data, plans for future opinion analysis tasks at NTCIR, and a brief overview of the evaluation results. This pilot task is a sentence-level opinion identification and polarity detection task run over data from a comparable corpus in three languages: Chinese, English, and Japanese. We have manually annotated documents for this task in each language, producing what we believe to be the first multilingual opinion analysis data set over comparable data. Six participants submitted Chinese system results, three Japanese, and six English for this pilot task. We plan to release the data to the research community, and hope to spur further research into cross-lingual opinion analysis and its use in other NLP tasks. In particular, we look forward to researchers using this data to investigate cross-cultural perspective differences based on automatic sentiment analysis.
An Influence of Nonlinearities to Storage Capacity of Neural Networks
Authors: Algis Garliauskas
Venue: Informatica (2005)

The more realistic neural soma and synaptic nonlinear relations and an alternative mean field theory (MFT) approach relevant for strongly interconnected systems as a cortical matter are considered. The general procedure of averaging the quenched random states in the fully-connected networks for MFT, as usually, is based on the Boltzmann Machine learning. But this approach requires an unrealistically large number of samples to provide a reliable performance. We suppose an alternative MFT with deterministic features instead of stochastic nature of searching a solution a set of large number equations. Of course, this alternative theory will not be strictly valid for infinite number of elements. Another property of generalization is an inclusion of the additional member in the effective Hamiltonian allowing to improve the stochastic hill-climbing search of the solution not dropping into local minima of the energy function. Especially, we pay attention to increasing of neural networks retrieval capability transforming the replica-symmetry model by including of different nonlinear elements. Some results of numerical modeling as well as the wide discussion of neural systems storage capacity are presented.
Evaluating usability of a commercial electronic health record: A case study
Authors: Paula J. Edwards, Kevin P. Moloney, Julie A. Jacko, François Sainfort
Venue: International Journal of Human-Computer Studies (2008)

Electronic health records (EHR) are increasingly being implemented by care providers in order to streamline processes and improve quality of care. Due to EHRs' complexity, the usability of these systems is crucial to ensure safety and to enable clinicians (users) to focus on their patients rather than the technology. This case study presents experiences from the implementation of a commercial EHR in a large pediatric hospital system. This case discusses how a predictive evaluation method, Heuristic Walkthrough, was used to evaluate and improve the usability of the EHR system. Outcomes from the evaluation resulted in immediate changes in the system configuration and training materials, which helped to avoid usability problems at rollout, as well as change requests to the vendor to improve overall system usability in the long term. Design trade-offs and lessons learned for future EHR implementations and other healthcare applications are discussed.
A Hybrid Particle Swarm Optimization for Manipulator Inverse Kinematics Control
Authors: Xiulan Wen, Danghong Sheng, Jiacai Huang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

A very important problem usually encountered in the study of robot manipulators is the inverse kinematics problem. The inverse kinematics control of a robotic manipulator requires solving non-linear equations having transcendental functions and involving time-consuming calculations. In this paper, a hybrid particle swarm optimization based on the behaviour of insect swarms and natural selection mechanism is firstly presented to optimize neural network (HPSONN) for manipulator inverse kinematics. Compared with the results of the fast back propagation learning algorithm (FBP), conventional genetic algorithm (GA) based elitist reservation (EGA), improved GA (IGA) and immune evolutionary computation (IEC), the simulation results verify the hybrid particle swarm optimization is more effective for manipulator inverse kinematics control than above most methods.
The Object-Oriented Protocol for Data Exchange and Control in Computational-Diverse Embedded Systems
Authors: Bogusław Cyganek
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

One of the key functionality of embedded-computer systems is control and data exchange among its building modules. Different size terminal sensors, microprocessor sub-systems, specialized devices, etc. should be able to smoothly exchange data and control notifications. This is often a difficult and time consuming task for a designer, mostly due to diversity of components. Usually the protocols and their realizations have to be implemented separately for each specific case. Therefore it would be desirable to have a definition of a protocol for data exchange and control that fits a certain class of such systems. In this paper we propose a solution to this problem which can be easily applied to different computer platforms. We start with the definition of the proposed DXC protocol. Then we present its object-oriented implementation. This way our proposition can be re-used on different platforms. The presented solution was employed with success to the suite of embedded systems for communication measurements and showed robustness and flexibility.
Text-Based Clustering of the ImageCLEFphoto Collection for Augmenting the Retrieved Results
Authors: Osama Demerdash, Leila Kosseim, Sabine Bergler
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

We present our participation in the 2007 ImageCLEF photographic ad-hoc retrieval task. Our first participation in this year's ImageCLEF comprised six runs. The main purpose of three of these runs was to evaluate the text and visual retrieval tools as well as their combination in the context of the given task. The other purpose of our participation was to experiment with applying clustering techniques to this task, which has not been done frequently in previous editions of the ImageCLEF Ad hoc task. We used the preclustered collection to augment the search results of the retrieval engines. For retrieval, we used two publicly available libraries; Apache Lucene for text and LIRE for visual retrieval. The clustered-augmented results reduced slightly the precision of the initial runs. While the aspired results have not yet been achieved, we note that the task is useful in assessing the validity of the clusters.
Vehicle Classification at Nighttime Using Eigenspaces and Support Vector Machine
Authors: Tuan Hue Thi, Kostia Robert, Sijun Lu, Jian Zhang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 2 - Volume 02 (2008)

A robust framework to classify vehicles in nighttime traffic using vehicle eigenspaces and support vector machine is presented. In this paper, a systematic approach has been proposed and implemented to classify vehicles from roadside camera video sequences. Collections of vehicle images are analyzed to obtain their representative eigenspaces. The model Support Vector Machine (SVM) built from those vehicle spaces will then become a reliable classifier for any unknown vehicle images. This approach has been implemented and proven to be robust in both speed and accuracy for vehicle classification at night.
One Exercise --- Various Tutorial Strategies
Authors: George Goguadze, Erica Melis
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

Narciss' theoretical framework for informative tutorial feedback (ITF) suggests to adapt the feedback along the dimensions: content, procedure, form, and presentation according to the task, the learner's response and to the learner's characteristics and particular situation. As prerequisites for the adaptations we devised a knowledge representation for exercises to which various tutorial and presentation strategies can be applied. We also developed techniques for generating the procedure, form and presentation of feedback.
Does Help Help? Introducing the Bayesian Evaluation and Assessment Methodology
Authors: Joseph E. Beck, Kai-Min Chang, Jack Mostow, Albert Corbett
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

Most ITS have a means of providing assistance to the student, either on student request or when the tutor determines it would be effective. Presumably, such assistance is included by the ITS designers since they feel it benefits the students. However, whether--and how--help helps students has not been a well studied problem in the ITS community. In this paper we present three approaches for evaluating the efficacy of the Reading Tutor's help: creating experimental trials from data, learning decomposition, and Bayesian Evaluation and Assessment, an approach that uses dynamic Bayesian networks. We have found that experimental trials and learning decomposition both find a negative benefit for help---that is, help hurts! However, the Bayesian Evaluation and Assessment framework finds that help both promotes student long-term learning and provides additional scaffolding on the current problem. We discuss why these approaches give divergent results, and suggest that the Bayesian Evaluation and Assessment framework is the strongest of the three. In addition to introducing Bayesian Evaluation and Assessment, a method for simultaneously assessing students and evaluating tutorial interventions, this paper describes how help can both scaffold the current problem attempt as well as teach the student knowledge that will transfer to later problems.
DC Motor Damping: A Strategy to Increase Passive Stiffness of Haptic Devices
Authors: Manohar B. Srikanth, Hari Vasudevan, Manivannan Muniyandi
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

Physically dissipative damping can increase the range of passive stiffness that can be rendered by a haptic device. Unlike simulated damping it does not introduce noise into the haptic control system. A DC motor can generate such damping if it's terminals are shorted. We employ a configuration of the H-bridge which can cause this damping to impart stability to our haptic device. This results in an increase in passive wall stiffness of about 33.3% at a sampling rate of 100Hz and 16.6% at 1kHz over the performance of an undamped DC motor. We have also attempted to implement the system on the hybrid haptic control system [1], it was seen that a perceivable change in the performance of this system was not observed by the use of DC motor damping.
An Analysis of Constructed Categories for Textual Classification Using Fuzzy Similarity and Agglomerative Hierarchical Methods
Authors: Marcus Vinicius C. Guelpeli, Ana Cristina Bicharra Garcia
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

Ambiguity is a challenge faced by systems that handle natural language. To assuage the issue of linguistic ambiguities found in text classification, this work proposes a text categorizer using the methodology of Fuzzy Similarity. The grouping algorithms Stars and Cliques are adopted in the Agglomerative Hierarchical method and they identify the groups of texts by specifying some time of relationship rule to create categories based on the similarity analysis of the textual terms. The proposal is that based on the methodology suggested, categories can be created from the analysis of the degree of similarity of the texts to be classified, without needing to determine the number of initial categories. The combination of techniques proposed in the categorizer’s phases brought satisfactory results, proving to be efficient in textual classification.
Merging ontologies requires interlocking institutional worlds
Authors: Robert M. Colomb, Mohammad Nazir Ahmad
Venue: Applied Ontology (2007)

Merging of ontologies is a frequently addressed problem in the ontology literature. This paper argues that in general two even very similar ontologies cannot be merged. Further, where two ontologies can be merged their conceptualizations are special. They are systems of institutional facts which are interlocking. The argument is based on the literature of the federated database problem and on the concepts of speech act and institutional fact.
Topic Signature Language Models for Ad hoc Retrieval
Authors: Xiaohua Zhou, Xiaohua Hu, Xiaodan Zhang
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

Semantic smoothing, which incorporates synonym and sense information into the language models, is effective and potentially significant to improve retrieval performance. The previously implemented semantic smoothing models, such as the translation model, have shown good experimental results. However, these models are unable to incorporate contextual information. To overcome this limitation, we propose a novel context-sensitive semantic smoothing method that decomposes a document into a set of weighted context-sensitive topic signatures and then translate those topic signatures into query terms. The language model with such a context-sensitive semantic smoothing is referred to as the topic signature language model. In detail, we implement two types of topic signatures depending on whether ontology exists in the application domain. One is the ontology-based concept and the other the multiword phrase. The translation probabilities from each topic signature to individual terms are estimated through the EM algorithm. Document models based on topic signature translation are then derived. The new smoothing method is evaluated on TREC 2004/2005 Genomics Track with ontology-based concepts, and TREC Ad hoc Track (Disk 1, 2 and 3) with multiword phrases. Both experiments show significant improvements over the two-stage language model as well as the language model with context-insensitive semantic smoothing.
Synchronization of Chaotic Systems Via the Laguerre---Polynomials-Based Neural Network
Authors: Hongwei Wang, Hong Gu
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

In recent years, chaos synchronization has attracted many researchers' interests. For a class of chaotic synchronization systems with unknown uncertainties caused by both model variations and external disturbances, an orthogonal function neural network is utilized to realize the synchronization of chaotic systems. The basis functions of orthogonal function neural network are Laguerre polynomials. First of all, the orthogonal function neural network is trained to learn the uncertain information. Then, the parameters of Laguerre orthogonal neural network are adjusted to accomplish the synchronization of two chaotic systems with the perturbation by Lyapunov steady theorem. At last, the result of numerical example is shown to illustrate the validity of the proposed method.