ppxscal/embedding_network huggingface dataset:
Function-based classification from 3D data via generic and symbolic models
Authors: Michael Pechuk, Octavian Soldea, Ehud Rivlin
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

We propose a novel scheme for function-based classification of objects in 3D images. The classification process calls for constructing a generic multi-level hierarchical description of object classes in terms of functional components. Functionality is derived from a large set of geometric attributes and relationships between object parts. Initially, the input range data describing each object instance is segmented, each object part is labeled as one of a few possible primitives, and each group of primitive parts is tagged by a functional symbol. Connections between primitive parts and functional parts at the same level in the hierarchy are labeled as well. Then, the generic multi-level hierarchical description of object classes is built using the functionalities of a number of object instances. During classification, a search through a finite graph using a probabilistic fitness measure is performed to find the best assignment of object parts to the functional structures of each class. An object is assigned to a class providing the highest fitness value. The scheme does not require a-priori knowledge about any class. We tested the proposed scheme on a database of about one thousand different 3D objects. The results show high accuracy in classification.
Severity Analyses of Single-Vehicle Crashes Based on Rough Set Theory
Authors: Chaozhong Wu, Hu Lei, Ming Ma, Xinping Yan
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

A single-vehicle crash is a typical pattern of traffic accidents and tends to cause heavy loss. The purpose of this study is to identify the factors significantly influencing single-vehicle crash injury severity, using a data selected from Beijing city for a 4-year period. Rough set theory was applied to complete the injury severity analysis, and followed by applying cross-validation method to estimate the prediction accuracy of extraction rules. Results show that it is effective for analyzing the severity of Single-vehicle crashes with rough set theory.
Trajectory Control Strategies for the Underwater Glider
Authors: Yanhui Wang, Hongwei Zhang, Shuxin Wang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

The Linear-quadratic regulator for the underwater glider is designed, and the motion path of the feedback control system in ocean vertical plane is studied. First, changes of the trajectory path when the glider is in steady moving are tested in this paper. Then, according to the fact that the glider needs sharp turning, two kinds of control strategies are studied. From the contrastive analysis, we choose a better strategy for the glider. Simulation result shows that, the control strategy can improve the moving performance of the underwater glider.
Phrase-based query degradation modeling for vocabulary-independent ranked utterance retrieval
Authors: J. Scott Olsson, Douglas W. Oard
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (2009)

This paper introduces a new approach to ranking speech utterances by a system's confidence that they contain a spoken word. Multiple alternate pronunciations, or degradations, of a query word's phoneme sequence are hypothesized and incorporated into the ranking function. We consider two methods for hypothesizing these degradations, the best of which is constructed using factored phrase-based statistical machine translation. We show that this approach is able to significantly improve upon a state-of-the-art baseline technique in an evaluation on held-out speech. We evaluate our systems using three different methods for indexing the speech utterances (using phoneme, phoneme multigram, and word recognition), and find that degradation modeling shows particular promise for locating out-of-vocabulary words when the underlying indexing system is constructed with standard word-based speech recognition.
Knowledge discovery from imbalanced and noisy data
Authors: Jason Van Hulse, Taghi Khoshgoftaar
Venue: Data Knowledge Engineering (2009)

Class imbalance and labeling errors present significant challenges to data mining and knowledge discovery applications. Some previous work has discussed these important topics, however the relationship between these two issues has not received enough attention. Further, much of the previous work in this domain is fragmented and contradictory, leading to serious questions regarding the reliability and validity of the empirical conclusions. In response to these issues, we present a comprehensive suite of experiments carefully designed to provide conclusive, reliable, and significant results on the problem of learning from noisy and imbalanced data. Noise is shown to significantly impact all of the learners considered in this work, and a particularly important factor is the class in which the noise is located (which, as discussed throughout this work, has very important implications to noise handling). The impacts of noise, however, vary dramatically depending on the learning algorithm and simple algorithms such as naive Bayes and nearest neighbor learners are often more robust than more complex learners such as support vector machines or random forests. Sampling techniques, which are often used to alleviate the adverse impacts of imbalanced data, are shown to improve the performance of learners built from noisy and imbalanced data. In particular, simple sampling techniques such as random undersampling are generally the most effective.
Meaning and the mental lexicon
Authors: Will Lowe
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

This paper presents a network model of the mental lexicon and its formation. Models of word meaning typically postulate a network of nodes with connection strengths, or distances, that reflect semantic similarity, but seldom explain how the network is formed or how it could be represented in the brain. The model presented here is an attempt to address these questions. The network organizes semantically similar words into clusters when exposed to sequentially presented text. Lexical co-occurrence information is calculated and used to create a hierarchical semantic representation. The output is similar to semantic networks first described by [Collins and Loftus, 1975], but is created automatically.
Improving Translation of Live Sequence Charts to Temporal Logic
Authors: Rahul Kumar, Eric G. Mercer, Annette Bunker
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

An efficient and mathematically rigorous translation from Live Sequence Charts (LSCs) to temporal logic is essential to providing an end-to-end specification and verification method for System on Chip (SoC) protocols. Without mathematical rigor, no translation can be trusted to completely represent the LSC specification, while inefficiency renders even provably sound translations useless in verifying the correctness of industrial-strength protocols. Previous work shows that the LSC-to-temporal logic and LSC-to-automata translations can be automated and formalized for the LSC language. In the LSC-to-temporal logic translation, the extraordinary size of the resulting formula limits the scalability of the charts that can be translated and verified. Our work, on the other hand, leverages intuitive temporal logic reductions to generate a formula that is at most quadratic in the size of the chart and demonstrates the benefits of the improved translation on several examples.
Research on Gas Stations Automation Management System Based on Neural Network
Authors: Zhao Meihong, Li Yun
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

The present main problems are that volume list of oil tank are not exact commonly and volume of oil tank can’t be probed visually. Aiming at domestic gas stations’ status, the gas station automation management system is establishedbased on neural networks. This paper puts forward the method of using linear interpolation algorithm to calculate the volume of oil tank at real time. It has improved the calculating accuracy greatly and can monitor administrant at real-time to make correct judgments electronic.
Idea generation and material consolidation: tool use and intermediate artefacts in journalistic writing
Authors: Simon Attfield, Sarah Fegan, Ann Blandford
Venue: Cognition, Technology and Work (2009)

We report an in-depth, longitudinal study of a freelance music journalist writing a feature article. Our analysis attends to the participant&#x2019;s activities from initiation to completion, and the ways in which she established structure using tools and artefacts to support cognitive effort. We observed five work stages: establishing an initial idea; preparing for an interview; interviewing; planning the article; and writing. Each resulted in the production of a working document embodying ideas and commitments which provided a key resource for the next stage. Stages began with phases of idea generation during which ideas were spontaneously triggered through intense engagement with information resources. They finished with phases of material consolidation when intermediate artifacts were configured to facilitate generation during the next stage. We examine these in detail and use our findings to motivate a discussion of working document overview representations and specific requirements related to idea generation and material consolidation.
A Table-Driven Programming Paradigm for Context-Aware Application Development
Authors: Zhang Junbin, Qi Yong, Hou Di, Li Ming
Venue: Proceedings of the 2009 Ninth Annual International Symposium on Applications and the Internet (2009)

Context-aware application should behave suitably according to the changing context of the pervasive computing environment. Several programming paradigms and languages have been proposed to facilitate development of context-aware application, but they are either lack of sufficient flexibility or somewhat complex to program. A table-driven programming paradigm is proposed in this paper to overcome shortcomings of those approaches. Virtual tables constructed and maintained by system connect knowledge of both developer and space manager while separate dependency between context and application logic from base program. Validation and evaluation show that the paradigm is easy to be implemented and deployed, meanwhile brings better usability and adaptability.
Nonlinear Diffusion Filters without Parameters for Image Segmentation
Authors: Carlos Platero, Javier Sanguino, Olga Velasco
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

Nonlinear diffusion filtering seeks to improve images qualitatively by removing noise while preserving details and even enhancing edges. However, well known implementations are sensitive to parameters which are necessarily tuned to sharpen a narrow range of edge slopes. In this work, we have selected a nonlinear diffusion filter without control parameters. It has been guided searching the optimum balance between time performance and resulting quality suitable for automatic segmentation tasks. Using a semi-implicit numerical scheme, we have determined the relationship between the slope range to sharpen and the diffusion time. It has also been selected the diffusivity with optimum performances. Several diffusion filters have been applied to noisy computed tomography images and evaluated for their suitability to the medical image segmentation. Experimental results show that our proposal of filter performs quite well in relation to others.
Unsupervised multilingual word sense disambiguation via an interlingua
Authors: Kornél Markó, Stefan Schulz, Udo Hahn
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

We present an unsupervised method for resolving word sense ambiguities in one language by using statistical evidence assembled from other languages. It is crucial for this approach that texts are mapped into a language-independent interlingual representation. We also show that the coverage and accuracy resulting from multilingual sources outperform analyses where only monolingual training data is taken into account.
Proactive Uniform Data Replication by Density Estimation in Apollonian P2P Networks
Authors: Nicolas Bonnel, Gildas Ménier, Pierre-François Marteau
Venue: Proceedings of the 2nd International Conference on Data Management in Grid and Peer-to-Peer Systems (2009)

We propose a data replication scheme on a random apollonian P2P overlay that benefits from the small world and scale free properties. The proposed algorithm features a replica density estimation and a space filling mechanism designed to avoid redundant messages. Not only it provides uniform replication of the data stored into the network but it also improves on classical flooding approaches by removing any redundancy. This last property is obtained at the cost of maintaining a random apollonian overlay. Thanks to the small world and scale free properties of the random apollonian P2P overlay, the search efficiency of the space filling tree algorithm we propose has comparable performances with the classical flooding algorithm on a random network.
Insertable Surgical Imaging Device with Pan, Tilt, Zoom, and Lighting
Authors: Tie Hu, Peter K. Allen, Nancy J. Hogle, Dennis L. Fowler
Venue: International Journal of Robotics Research (2009)

In this paper we describe work we have done in developing an insertable surgical imaging device with multiple degrees of freedom for minimally invasive surgery. The device is fully insertable into the abdomen using standard 12 mm trocars. It consists of a modular camera and lens system which has pan and tilt capability provided by two small DC servo motors. It also has its own integrated lighting system that is part of the camera assembly. Once the camera is inserted into the abdomen, the insertion port is available for additional tooling, motivating the idea of single-port surgery. A third zoom axis has been designed for the camera as well, allowing close-up and far-away imaging of surgical sites with a single camera unit. In animal tests with the device we have performed surgical procedures including cholecystectomy, appendectomy, running (measuring) the bowel, suturing, and nephrectomy. Preliminary tests suggest that the new device may have advantages over a standard laparoscope including the following. â¢ Low-cost and simple design. â¢ Easier and more intuitive to use than a standard laparoscope. â¢ Joystick operation requires no specialized operator training. â¢ Pan/tilt functions provide a large imaging volume not restricted by the fulcrum point of standard laparoscope. â¢ Time to perform procedures was better than or equivalent to a standard laparoscope. We believe these insertable platforms will be an integral part of future surgical systems. The platforms can be used with tooling as well as imaging devices, allowing many surgical procedures to be performed using such a system.
Learning combination features with L1 regularization
Authors: Daisuke Okanohara, Jun'ichi Tsujii
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers (2009)

When linear classifiers cannot successfully classify data, we often add combination features, which are products of several original features. The searching for effective combination features, namely feature engineering, requires domain-specific knowledge and hard work. We present herein an efficient algorithm for learning an L1 regularized logistic regression model with combination features. We propose to use the grafting algorithm with efficient computation of gradients. This enables us to find optimal weights efficiently without enumerating all combination features. By using L1 regularization, the result we obtain is very compact and achieves very efficient inference. In experiments with NLP tasks, we show that the proposed method can extract effective combination features, and achieve high performance with very few features.
Cultural Aspect of Interaction Design beyond Human-Computer Interaction
Authors: Rungtai Lin, Po-Hsien Lin, Wen-Shin Shiao, Su-Huei Lin
Venue: Proceedings of the 3rd International Conference on Internationalization, Design and Global Development: Held as Part of HCI International 2009 (2009)

Over the past several decades, we have made many efforts to understand Human-Computer Interaction (HCI). But beyond HCI, we need a better understanding of Human-Culture Interaction not just for taking part in the cultural context, but also for developing the interactive experience of users. Therefore we propose a general framework for cultural product experience that applies to the mental models of designer and user and which can be experienced in Human-Culture Interaction. Then, based on the interactive experience of users with an aboriginal cultural object, the Linnak (a twin drinking cup), a modern Linnak was proposed to demonstrate how to design a successful cultural product using the human-culture interaction framework. The intended purpose of this paper is to provide a framework for examining the way designers interact across cultures and the interactive experience of users in the design process.
Theoretical Analysis of Stochastic Parallel Gradient Descent Control Algorithm in Adaptive Optics
Authors: Huizhen Yang, Xinyang Li
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

We generalize the convergence, the stability and the averaged converging rate of stochastic parallel gradient descent algorithm when it is used as control algorithm for adaptive optics system in theory. Analysis results show the adaptive optics system can obtain convergence, stability and a factor ofn /square root (n is the number of control parameters) speeding compared with sequential gradient descent techniques on making use of stochastic parallel gradient descent to control adaptive optics systems.
Caring and Curing by Mixing Information and Emotions in Orphan Diseases Websites: A Twofold Analysis
Authors: Maria Cristina Caratozzolo, Enrica Marchigiani, Oronzo Parlangeli, Marcella Zaccariello
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

The study reported in this article was structured as a first step in planning guidelines to design effective internet sites for Associations dealing with rare diseases.The Authors used a two-stage analysis: first, they carried out an analysis of the websites of a sample of Italian Associations on rare diseases and then they did an interview survey to identify the objectives and needs of those organizations. Results indicate that two different kinds of organizations do exist and suggest possibilities for developing guidelines aimed at improving their websites.
An Iris detector for tumoral masses identification in mammograms
Authors: Arianna Mencattini, Giulia Rabottino, Marcello Salmeri, Roberto Lojacono
Venue: Proceedings of the 2009 IEEE International Workshop on Medical Measurements and Applications (2009)

Radiologists that analyze screening mammographic images miss the 10–20% of the diagnosis since this kind of images are very difficult to interpret. In this paper, we present the first step of a CADx (Computer Aided Diagnosis) system that, from the original mammogram, extracts suspicious regions on which the radiologists have to focus their attention. The procedure often successes also in case of very low contrast, because it depends only on the orientation of the gradient vectors in the image but not on their amplitude.
Control Strategies for the Regulation of the Eukaryotic Heat Shock Response
Authors: Elena Czeizler, Eugen Czeizler, Ralph-Johan Back, Ion Petre
Venue: Proceedings of the 7th International Conference on Computational Methods in Systems Biology (2009)

Elevated temperatures cause proteins in living cells to misfold. They start forming larger and larger aggregates that can eventually lead to the cell's death. The heat shock response is an evolutionary well conserved cellular response to massive protein misfolding and it is driven by the need to keep the level of misfolded proteins under control. We consider in this paper a recently proposed new molecular model for the heat shock response in eukaryotes, consisting of a temperature-induced activation mechanism, chaperoning of misfolded proteins and self-regulation of the chaperon synthesis. We take in this paper a control driven approach to studying this regulatory network. We modularize the network by identifying its main functional modules. We distinguish three main feedback loops. The main question we are addressing is why is this level of complexity needed for implementing what could in principle also be achieved with an open-loop design. We answer the question by comparing the numerical behavior of various knockdown mutants where one or more feedback loops are missing. We also discuss a new approach for a biologically-unbiased model comparison.
Video Gaming for Blind Learners School Integration in Science Classes
Authors: Jaime Sánchez, Mauricio Sáenz
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

In this study we evaluate how the use of audio-based technology can facilitate school integration of blind learners through the interaction with a science videogame. This experience consisted of designing and implementing The Natomy's Journey Game to be played by blind and sighted middle school students. The use of the videogame and its impact on the integration of blind learners into mainstream schools was also evaluated, through the participation of both teachers and learners. In the end, the goal was for blind learners to be able to interact and become socially integrated through active science video gaming and the application of specific science content. The results of this study provide initial data and evidence that the use of video games such as The Natomy's Journey Game can improve the process for the school integration of learners with visual disabilities.
The Forecast of Tornado Variety Based on Function S-rough Sets
Authors: Zhao Jiang, Qiu Taorong, Nie Bin, Li Wen, Wang Weili
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

The Tornado speed is estimated according to its path length and width, but sometimes from the information detected by the Dopper radar, we found that the path length and the width of the Tornado did not have intersection in wind speed ranks. Although the forecast of the wind speed rank is accurate, the wind speed may change owing to other unknown factors. Because it, these information is rough from its character which could not to express in accurate math's methods. We choose the max of the wind speed from any possibility in wind speed estimation, and forecast the wind speed possible change in the variational condition based on function singular rough sets[1]. It was proved to be feasible and effective after tested.