ppxscal/embedding_network huggingface dataset:
Longitudinal nominal data analysis using marginalized models
Authors: Keunbaik Lee, Donald Mercante
Venue: Computational Statistics Data Analysis (2010)

Recently, marginalized transition models have become popular for the analysis of longitudinal data. Heagerty (2002) and Lee and Daniels (2007) proposed marginalized transition models for the analysis of longitudinal binary data and ordinal data, respectively. In this paper, we extend their work to accommodate longitudinal nominal data using a Markovian dependence structure. A Fisher-scoring algorithm is developed for estimation. Methods are illustrated with a real dataset and are compared with other standard methods.
Measuring Similarities between XML Documents Based on Content and Structure
Authors: Xiaoling Xia, Yongming Guo, Jiajin Le
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

Extended Marked-up Language (XML) has become a de facto standard for information representation and data exchange over the Web. As a result, large amounts of XML documents emerge in many application areas, such as Digital library, patent retrieval and Intranet search. Effectively measuring similarities between XML documents plays an important role in these application areas. However, most of current research work focus on measuring the structural similarities between XML documents, and not or less taking into account the content of the documents and links between documents. This paper develops a novel similarity measure model which is based on Extended Vector Space Model. This model can effectively measure similarities between XML documents by combining content, structure and links. In order to evaluate this similarity measure model, we adopt k-means algorithm to cluster XML documents. Experiments show that this model gains better clustering quality compared to the classical vector space model.
Speech-enabled card games for language learners
Authors: Ian McGraw, Stephanie Seneff
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

This paper debuts a novel application of speech recognition to foreign language learning. We present a generic framework for developing user-customizable card games designed to aid learners in the difficult task of vocabulary acquisition. We also describe a prototype game built on this framework that, using a Mandarin speech recognizer, provides a student of Chinese with opportunities to speak vocabulary items in a meaningful context. The system dynamically loads only the necessary vocabulary for each game in an effort to maintain robust recognition performance without limiting the lexical domain. To assess the Sentence Error Rate (SER) of our prototype, we asked college-age students from various universities in the United States and beyond to participate in a Web-based user study. The three central concepts in the game were recognized with a SER of 16.02%, illustrating the feasibility of deploying this system in a university curriculum via the Internet. Finally, to ensure that our recognizer is behaving appropriately with regard to learner speech, we perform a rigorous analysis of the recognition errors to determine their underlying causes.
Improved Arterial Inner Wall Detection Using Generalized Median Computation
Authors: Da-Chuan Cheng, Arno Schmidt-Trucksäss, Shing-Hong Liu, Xiaoyi Jiang
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

In this paper, we propose a novel method for automatic detection of the lumen diameter and intima-media thickness from dynamic B-mode sonographic image sequences with and without plaques. There are two phases in this algorithm. In the first phase a dual dynamic programming (DDP) is applied to detect the far wall IMT and near wall IMT. The general median curves are then calculated. In the second phase, the DDP is applied again using the median curves as the knowledge to obtain a more informed search and to potentially correct errors from the first phase. All results are visually controlled by professional physicians. Based on our experiments, this system can replace the experts' manual work, which is time-consuming and not repeatable. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
An OWL Ontology for Fuzzy OWL 2
Authors: Fernando Bobillo, Umberto Straccia
Venue: Proceedings of the 18th International Symposium on Foundations of Intelligent Systems (2009)

The need to deal with vague information in Semantic Web languages is rising in importance and, thus, calls for a standard way to represent such information. We may address this issue by either extending current Semantic Web languages to cope with vagueness, or by providing an ontology describing how to represent such information within Semantic Web languages. In this work, we follow the latter approach and propose and discuss an OWL ontology to represent important features of fuzzy OWL 2 statements.
4D MAP Image Reconstruction Incorporating Organ Motion
Authors: Jacob Hinkle, P. Thomas Fletcher, Brian Wang, Bill Salter, Sarang Joshi
Venue: Proceedings of the 21st International Conference on Information Processing in Medical Imaging (2009)

Four-dimensional respiratory correlated computed tomography (4D RCCT) has been widely used for studying organ motion. Most current algorithms use binning techniques which introduce artifacts that can seriously hamper quantitative motion analysis. In this paper, we develop an algorithm for tracking organ motion which uses raw time-stamped data and simultaneously reconstructs images and estimates deformations in anatomy. This results in a reduction of artifacts and an increase in signal-to-noise ratio (SNR). In the case of CT, the increased SNR enables a reduction in dose to the patient during scanning. This framework also facilitates the incorporation of fundamental physical properties of organ motion, such as the conservation of local tissue volume. We show in this paper that this approach is accurate and robust against noise and irregular breathing for tracking organ motion. A detailed phantom study is presented, demonstrating accuracy and robustness of the algorithm. An example of applying this algorithm to real patient image data is also presented, demonstrating the utility of the algorithm in reducing artifacts.
PRESTO: feedback-driven data management in sensor networks
Authors: Ming Li, Deepak Ganesan, Prashant Shenoy
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

This paper presents PRESTO, a novel two-tier sensor data management architecture comprising proxies and sensors that cooperate with one another for acquiring data and processing queries. PRESTO proxies construct time-series models of observed trends in the sensor data and transmit the parameters of the model to sensors. Sensors check sensed data with model-predicted values and transmit only deviations from the predictions back to the proxy. Such a model-driven push approach is energy-efficient, while ensuring that anomalous data trends are never missed. In addition to supporting queries on current data, PRESTO also supports queries on historical data using interpolation and local archival at sensors. PRESTO can adapt model and system parameters to data and query dynamics to further extract energy savings. We have implemented PRESTO on a sensor testbed comprising Intel Stargates and Telos Motes. Our experiments show that in a temperature monitoring application, PRESTO yields one to two orders of magnitude reduction in energy requirements over on-demand, proactive or model-driven pull approaches. PRESTO also results in an order of magnitude reduction in query latency in a 1% duty-cycled five hop sensor network over a system that forwards all queries to remote sensor nodes.
Shape and Structure Features Based Chinese Wine Classification
Authors: Yi Wan, Xingbo Sun, Rong Guo
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

Chinese wines can be classification or graded by the micrographs. Micrographs of Chinese wines show floccule,stick and granule of variant shape and size. Different wines have variant microstructure and micrographs, we study the classification of Chinese wines based on the micrographs. Shape and structure of wines’ particles in microstructure is the most important feature for recognition and classification of wines. So we introduce a new feature extraction method which can describe the structure and region shape of micrograph efficiently. First, the micrographs are enhanced using total variation denoising, and segmented using relative entropy thresholding. Then features are extracted using proposed method in the paper based on area, perimeter and traditional shape feature. Eight kinds total 26 features are selected. Finally, Chinese wine classification system based on micrograph using combination of shape and structure features and BP neural network have been presented. We compare the recognition results for different choices of features (traditional shape features or proposed features). The experimental results show that the better classification rate have been achieved using the combinational features proposed in this paper.
Quantitative Analysis of Endodontic Treatment for Periapical Lesions in Intraoral Radiographs
Authors: Taeju Lee, Hyekyung Jeong, Desok Kim, Byung-Do Lee
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

Intraoral radiographs have been taken to diagnose periapical lesions. Subsequent endodontic treatment needs to be evaluated quantitatively, that is often difficult due to various imaging factors as well as subjective visual interpretation. Therefore, we sought to establish an image analysis based quantitative model to evaluate endodontic treatments (40 effective and 43 noneffective cases). To normalize an image, the dentin area and the background were used as references. In each pair of images representing before and after treatment, the lesion area was manually selected by experts and segmented by tophat operation. Numerous features representing the effective bone healing were calculated. Using relative differences of selected features, an evaluation model was derived by logistic regression analysis. Gray level intensity and textural differences obtained from lesions significantly increased in the effectively treated cases. The model provided the accuracy of 80.7%. Our quantitative model may be helpful to evaluate endodontic treatment in clinical settings and in animal studies.
Blind Separation Algorithm with Improved Learning Rule for Audio Signal
Authors: Dahui Li, Ying Zheng, Jinku Han
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

In this paper, the separation model for audio signal is built, at the same time, separable assumption conditions and separation criteria are assumed. Improved learning rule is proposed, on the basis of the separation effect with two learning rules, and it is applied in the adaptive algorithm to realize blind separation for audio signals. Experiment shows that the performance improved algorithm is better in the speed of convergence is fast, stability of separation signals and separation effect than the two original learning rules. Moreover it eliminates the phenomenon that the step decreases too late or too early.
A Localized Algorithm for Target Monitoring in Wireless Sensor Networks
Authors: Kamrul Islam, Selim G. Akl
Venue: Proceedings of the 8th International Conference on Ad-Hoc, Mobile and Wireless Networks (2009)

We consider the following target monitoring problem: Given a set of stationary targets T = {t 1, ¿ ,t m } and a set V = {v 1, ¿ ,v n } of sensors, the target monitoring problem asks for generating a family of subsets of sensors V 1, ¿ ,V s called the monitoring sets, such that each V i monitors all targets. In doing so, the objective of this problem is to maximize z = s/k, where k=max$_{v_j\in V}|\{i:v_j\in V_i\}|$. Maximizing z has direct impact in prolonging the lifetime of sensor networks. For this problem, we present a simple localized algorithm which requires each node to know only its 2-hop neighborhood. Nodes do not need to know their geographic positions. It is shown that the algorithm achieves an optimum result in special cases. We prove that the size of a monitoring set is at most a constant times the size of a minimum monitoring set when the number of targets is a constant. We present extensive simulation results to evaluate the performance of the algorithm.
Influence and Impact Relationship between GIS Users and GIS Interfaces
Authors: Hongmei Wang
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

A Geographic Information System (GIS) is a computer-based system for managing and processing geospatial data. GIS has been an important tool in science, government agencies, private agencies and the public since the 1960s. To make GIS more usable and useful to GIS users, the GIS community has paid increasing attention to GIS interfaces. This paper provides an individual level analysis of influence and impact relationship between GIS users and GIS interfaces based on the level analysis framework developed by Korpela et al. The analysis results show that, on one hand, different physical and mental characteristics of the end GIS users have influenced design of GIS interfaces; on the other hand, technologies developed in GIS interfaces have impacted how the GIS users understand and use the GIS in different ways.
Teaching Me Softly: Experiences and Reflections on Informal Educational Game Design
Authors: Ulrich Wechselberger
Venue: Transactions on Edutainment II (2009)

Video games are highly engaging environments. Therefore, there is a growing interest in harnessing their motivational potential via game-based learning. However, putting curricular content into digital games is not trivial. Many educational games fail to combine teaching and gameplay in a subtle way, thereby suffer from low-grade design and fail to utilise the motivational potential of video games.This article explicates some main issues of educational games and reflects on an approach to a more informal and harmonic design for educational games. Furthermore, it describes the "Eduventure II", a research project investigating and testing these methods. The game developed in this prototype links the curriculum to narrative, simulation and game play layers. The here presented text describes the theoretical background, issues, concept and implementation of the prototype, as well as the lessons learnt from a pedagogical perspective.
Study Urban Extension Spatial Differentiation Based on Multi-temporal Satellite Remote Sensing Images
Authors: Yunjun Zhan, Haiwei Yang
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

Taking Yiwu city for example, dividing the urban region into 4 spatial units that is northeast, northwest, southeast and southwest. Using multi-temporal satellite remote sensing Images and geography information system, the space clustering and historical shape for the city land use expanding from 1970 to 2004 were studied in this paper. The results indicated the spatial differentiation law and the driving force of land using extension. Before 1991, the urban extension driving force is the commodity market agglutination. From 1991 to 1997, market irradiation appeared with the urban area agglutination, the construction of specialty markets prompted the laminated plate extension of the city. After 1997, the burst Yiwu city urban extension was driven by construction of new dwellings, construction of new public facilities and the outmigration of public facilities. The research in this paper indicated that the driving force of commerce was important in the process of Yiwu urbanization.
Research on Railway Passenger Traffic Volume Forecasting Method
Authors: Zeng Changqing, Long Chengzhi
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

Railway passenger traffic volume forecasting is an important responsibity of the railway transportation management departments, railway passenger traffic volumes are influenced by multiple factors, and the action mechanisms of these factors are usually unable to be described by accurate mathematical linguistic forms, so the theory and method of railway passenger traffic forecasting remain a focus in research all the time. The paper analyzes data using rough set theory. Combining rough set theory and the characteristics of railway passenger traffic volume data, we bring forward a forecasting model of railway passenger traffic volume using rough set theory. Through setting up, hybrid clustering method of discretization and reduction decision table, a rule Set concerning forecasting of railway passenger traffic volumes is achieved——rough set forecasting model.
Evaluation Model of Rubber Planting Suitability Based on Cloud Theory, Rough Set and Fuzzy Neural Network
Authors: Cao Yang, Song Weidong
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

The new rubber planting suitability evaluation model based on the cloud theory, rough set and fuzzy neural network has been put forward according to the lack of influencing factors samples on rubber growth. Qualitative description of the rubber planting rules can be converted into quantitative rubber planting influencing factors sample data by the forward cloud generator of the evaluation model. Moreover, rough set is used to reduce the sample data. Then, the membership of each evaluation element is obtained via the fuzzy neural network. Finally, the evaluation grade is calculated though evaluation element membership. The preliminary research indicates that the model, which combines spatial clustering analysis, can scientifically and fleetly divide the study area into the most suitable area, suitable area, the less suitable area and unsuitable area.
Studying Point-Select-Drag Interaction Techniques for Older People with Cognitive Impairment
Authors: Nadine Vigouroux, Pierre Rumeau, Frédéric Vella, Bruno Vellas
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Addressing Diversity. Part I: Held as Part of HCI International 2009 (2009)

Graphical user interfaces and interactions that involve pointing to items and dragging them are becoming more common in rehabilitation and assistive technologies. We are currently investigating interaction techniques to understand point-select-drag interactions for older people with cognitive impairment. In particular, this study reports how older perform such tasks. Significant differences in behavior between all of the interaction techniques are observed and the reasons for these differences are discussed according the cognitive impairment.
Ordered inference using observed confidence levels
Authors: Alan M. Polansky
Venue: Computational Statistics Data Analysis (2010)

Statistical inference on the ordering of the elements of a mean vector is an important issue in many applied problems, particularly in biostatistical applications. Some common ordering models include simple, tree and umbrella orderings. Many statistical methods have been developed to detect these orderings within the normal model, and outside the normal model using nonparametric methods. Estimates as well as confidence regions have also been developed for the mean vector under constraints imposed by these ordering models. In order to attempt to distinguish between ordered models, multiple testing procedures are usually required to control the overall error rate of the sequence of tests. This paper shows how observed confidence levels allow for the exploration of very general ordering models without the need for specialized asymptotic theory or multiple testing methods. The proposed methods are applied to several examples.
Psi-calculi: Mobile Processes, Nominal Data, and Logic
Authors: Jesper Bengtson, Magnus Johansson, Joachim Parrow, Björn Victor
Venue: Proceedings of the 2009 24th Annual IEEE Symposium on Logic In Computer Science (2009)

A psi-calculus is an extension of the pi-calculus with nominal data types for data structures and for logical assertions representing facts about data. These can be transmitted between processes and their names can be statically scoped using the standard pi-calculus mechanism to allow for scope migrations. Other proposed extensions of the pi-calculus can be formulated as psi-calculi; examples include the applied pi-calculus, the spi-calculus, the fusion calculus, the concurrent constraint pi-calculus, and calculi with polyadic communication channels or pattern matching. Psi-calculi can be even more general, for example by allowing structured channels, higher-order formalisms such as the lambda calculus for data structures, and a predicate logic for assertions. Our labelled operational semantics and definition of bisimulation is straightforward, without a structural congruence. We establish minimal requirements on the nominal data and logic in order to prove general algebraic properties of psi-calculi. The proofs have been checked in the interactive proof checker Isabelle. We are the first to formulate a truly compositional labelled operational semantics for calculi of this calibre. Expressiveness and therefore modelling convenience significantly exceeds that of other formalisms, while the purity of the semantics is on par with the original pi-calculus.
Optimization Model of Industrial Structure Based on the Bearing Capacity of Resources and Environment
Authors: Changrong Zhang, Huifeng Xue
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

Considering making a region to achieve the sustainable utilization of natural resources, the sustainable improvement of ecological environment, and the sustainable development of economy, this paper builds a multi-objective optimization model of industrial scale structure based on the bearing capacity of regional natural resources and environment. And this model was used to optimize the industrial scale structure of 2010 for Yulin City of Shaanxi Province.
Secure Distributed Multiplication of Two Polynomially Shared Values: Enhancing the Efficiency of the Protocol
Authors: Peter Lory
Venue: Proceedings of the 2009 Third International Conference on Emerging Security Information, Systems and Technologies (2009)

In view of practical applications, it is a high priority to optimize the efficiency of methods for secure multiparty computations. These techniques enable, for instance, truly practical double auctions and distributed signatures. The multiplication protocol for the secure multiparty multiplication of two polynomially shared values over Z_q with a public prime number q is an important module in these computations. The protocol of Gennaro, Rabin and Rabin (1998) is a well known and efficient protocol for this purpose. It requires one round of communication and O(n^2 k \log n + n k^2) bit-operations per player, where k is the bit size of the prime q and n is the number of players. In a previous paper (2007), the author has presented a modification of this protocol, that reduces its complexity to O(n^2k + nk^2). The present paper reduces this complexity further to O(n^2 k). This reduction is profitable in situations where n is smaller than k. The new protocol requires the same amount of communication as the original one and is unconditionally secure, as well.