ppxscal/embedding_network huggingface dataset:
Applying Dewey Encoding to Construct XML Index for Path and Keyword Query
Authors: Li Ying, Ma Jun, Sun Yuyin
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

Path and Keyword search in XML documents has recently become an active area of research, in which constructing an effective index is a key issue. Existing index structures and encoding schemes for XML query processing target the Parent-Child and Ancestor-Descendant relationships, however, they depend on large index space and complex algorithms used to process regular path expressions. In this paper, we first introduce an encoding scheme by which the relationship of two nodes on a DOM tree and the topology of n nodes of a tree can be calculated efficiently. Then, we propose a novel index approach which is separated into two parts. One, called path index, keeps the path information of XML documents. The other, called value index, stores the content. Experiments show that the approach is more effective than the traditional ones, namely DataGuide and XISS, in terms of running time and size of index space.
Three New Algorithms for Regular Language Enumeration
Authors: Margareta Ackerman, Erkki Mäkinen
Venue: Proceedings of the 15th Annual International Conference on Computing and Combinatorics (2009)

We present new and more efficient algorithms for regular language enumeration problems. The min-word problem is to find the lexicographically minimal word of length n accepted by a given NFA, the cross-section problem is to list all words of length n accepted by an NFA in lexicographical order, and the enumeration problem is to list the first m words accepted by an NFA according to length-lexicographic order. For the min-word and cross-section problems, we present algorithms with better asymptotic running times than previously known algorithms. Additionally, for each problem, we present algorithms with better practical running times than previously known algorithms.
The Design of Controller Based on Tendency Surface
Authors: Yucheng Li, Hongxing Li, Mushu Wang
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

This paper proposes the definition of the tendency curve with saturation line and gives the range of the parameters and the necessary and sufficient condition when the cubic polynomials satisfy the definitions, which is based on the method of tendency surface constructed by cubic polynomial (TSCP) proposed in our former paper. The simulation experiment results, compared with the general fuzzy control, are given, which verify the effectiveness of the given method.
An Acceptability Predictor for Websites
Authors: Ray Adams, Anthony White, Efe Ceylan
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services (2009)

User acceptance is a high priority for website design and implementation. Two significant, but largely separate, approaches to acceptability are: First, the Web Accessibility Initiative (WAI) has explored the measurement of technical features of a website to gauge its accessibility. Second, human judgments about acceptability are obtained from intended users or experts. The present work explores the important question of how best to combine these two methods. Experiment One required new users to explore automatic website evaluation systems. They found two of four systems difficult or impossible to use and system outputs difficult to understand. Experiment Two combines formal properties and user judgments, using an automatic system to predict user judgments from formal website properties. A simple system was able to predict user judgments within 91% accuracy. Clearly, user judgments about websites can be predicted reliably, a result of value to designers.
The hidden permutation model and location-based activity recognition
Authors: Hung H. Bui, Dinh Phung, Svetha Venkatesh, Hai Phan
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

Permutation modeling is challenging because of the combinatorial nature of the problem. However, such modeling is often required in many real-world applications, including activity recognition where subactivities are often permuted and partially ordered. This paper introduces a novel Hidden Permutation Model (HPM) that can learn the partial ordering constraints in permuted state sequences. The HPM is parameterized as an exponential family distribution and is flexible so that it can encode constraints via different feature functions. A chain-flipping Metropolis-Hastings Markov chain Monte Carlo (MCMC) is employed for inference to overcome the O(n!) complexity. Gradient-based maximum likelihood parameter learning is presented for two cases when the permutation is known and when it is hidden. The HPM is evaluated using both simulated and real data from a location-based activity recognition domain. Experimental results indicate that the HPM performs far better than other baseline models, including the naive Bayes classifier, the HMM classifier, and Kirshner's multinomial permutation model. Our presented HPM is generic and can potentially be utilized in any problem where the modeling of permuted states from noisy data is needed.
CoCQA: co-training over questions and answers with an application to predicting question subjectivity orientation
Authors: Baoli Li, Yandong Liu, Eugene Agichtein
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

An increasingly popular method for finding information online is via the Community Question Answering (CQA) portals such as Yahoo! Answers, Naver, and Baidu Knows. Searching the CQA archives, and ranking, filtering, and evaluating the submitted answers requires intelligent processing of the questions and answers posed by the users. One important task is automatically detecting the question's subjectivity orientation: namely, whether a user is searching for subjective or objective information. Unfortunately, real user questions are often vague, ill-posed, poorly stated. Furthermore, there has been little labeled training data available for real user questions. To address these problems, we present CoCQA, a co-training system that exploits the association between the questions and contributed answers for question analysis tasks. The co-training approach allows CoCQA to use the effectively unlimited amounts of unlabeled data readily available in CQA archives. In this paper we study the effectiveness of CoCQA for the question subjectivity classification task by experimenting over thousands of real users' questions.
Universal Learning over Related Distributions and Adaptive Graph Transduction
Authors: Erheng Zhong, Wei Fan, Jing Peng, Olivier Verscheure, Jiangtao Ren
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

The basis assumption that "training and test data drawn from the same distribution" is often violated in reality. In this paper, we propose one common solution to cover various scenarios of learning under "different but related distributions" in a single framework. Explicit examples include (a) sample selection bias between training and testing data, (b) transfer learning or no labeled data in target domain, and (c) noisy or uncertain training data. The main motivation is that one could ideally solve as many problems as possible with a single approach. The proposed solution extends graph transduction using the maximum margin principle over unlabeled data. The error of the proposed method is bounded under reasonable assumptions even when the training and testing distributions are different. Experiment results demonstrate that the proposed method improves the traditional graph transduction by as much as 15% in accuracy and AUC in all common situations of distribution difference. Most importantly, it outperforms, by up to 10% in accuracy, several state-of-art approaches proposed to solve specific category of distribution difference, i.e, BRSD [1] for sample selection bias, CDSC [2] for transfer learning, etc. The main claim is that the adaptive graph transduction is a general and competitive method to solve distribution differences implicitly without knowing and worrying about the exact type. These at least include sample selection bias, transfer learning, uncertainty mining, as well as those alike that are still not studied yet. The source code and datasets are available from the authors.
CharanisML: A Flexible Virtual Actor Control Interface
Authors: Sebastian A. Weiß, Florian Berger, Alexander Marbach, Wolfgang Müller
Venue: Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development (2009)

In this submission we present a first step for an author-centric interface to believable agents. Based on a number of approaches for the description of 3D content, we developed CharanisML, the Character Animation System Meta Language. It is applicable for controlling both 2D and 3D avatars. To demonstrate this, we implemented two different clients in 2D and 3D that are able to interpret CharanisML. Also, they can be adapted as animation engines for interactive digital storytelling engines like Scenejo, that are used in the fields of entertainment as well as game-based learning. Using CharanisML it is possible for an author to control characters independently from both storytelling engines and two- or three-dimensional representation.
HES-SPATO: An Online History Educational System Based on SCORM
Authors: Jia-Jiunn Lo, Chuen-Jung Chang, Hsiao-Han Tu, Shiou-Wen Yeh
Venue: Transactions on Edutainment II (2009)

Online learning has become popular in the delivery of history materials. However, not much of the history learning material that is available online has a high level of understandability. Furthermore, not all history course designers and teachers are good at information technologies. To this end, an online history educational system, HES-SPATO, was developed. HES-SPATO is based on SCORM (Sharable Content Object Reference Model) to ensure reusability, durability, accessibility, and interoperability of electronic material. SPATO (Spatio-Person-Attribute-Temporal Object), the backbone of HES-SPATO, is designed to integrate the indispensable elements of historical events such as space, person, action/attribute, and time to increase the understandability of online history learning materials. In HES-SPATO, history SCOs were formed by integrating SPATOs with the associated "Space", "Person", and "Action/Attribute" assets, stored in the Asset Pool. SCOs, then, formed other SCORM components such as lessons and courses accordingly. The authoring module of HES-SPATO can enhance the history teachers' ability for creating online materials in a few guided steps with flexibility. HES-SPATO applies temporal logic to reason the temporal relationships between historical events. By applying the GIS concept of information layers, the learning module of HES-SPATO allow students to select different features with different layers to visualize historical events more clearly according to their own needs, zoom in to see features at closer range, view a variety of supplementary learning material at the same time and view SCOs according to their own progress and learning paths. It can also present specific information directly related to the historical event only, as defined in SPATO, to reduce cognitive load. With these developed functionalities, HES-SPATO can effectively reduce the teacher's burden and increase the understandability of history learning materials. Three teachers, who had taught general college history courses to non-history majors for more than ten years, were invited to evaluate both the authoring and learning modules. After these history teachers using HES-SPATO, semi-structured interviews were conducted to acquire their feedbacks in terms of processes to prepare history learning materials, understandings for students' learning history, responses for the map functionalities, and suggestions of the content and the history learning material displaying methods. The results of this interview demonstrated the teachers' acceptance of HES-SPATO and confirmed its helpfulness in teachers' preparation of online learning materials and students' understanding of history learning.
Swept Volume Parameterization for Isogeometric Analysis
Authors: M. Aigner, C. Heinrich, B. Jüttler, E. Pilgerstorfer, B. Simeon, A. -V. Vuong
Venue: Proceedings of the 13th IMA International Conference on Mathematics of Surfaces XIII (2009)

Isogeometric Analysis uses NURBS representations of the domain for performing numerical simulations. The first part of this paper presents a variational framework for generating NURBS parameterizations of swept volumes. The class of these volumes covers a number of interesting free-form shapes, such as blades of turbines and propellers, ship hulls or wings of airplanes. The second part of the paper reports the results of isogeometric analysis which were obtained with the help of the generated NURBS volume parameterizations. In particular we discuss the influence of the chosen parameterization and the incorporation of boundary conditions.
Indoor aerial robot competition: challenges in search and rescue applications
Authors: Paul Y. Oh, William E. Green, Keith W. Sevcik
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 4 (2005)

Tasks like bomb-detection, search-and-rescue, and reconnaissance in near-Earth environments are time, cost and labor intensive. Aerial robots could assist in such missions and offset the demand in resources and personnel. However, flying in environments rich with obstacles presents many more challenges which have yet to be identified. For example, telephone wire is one obstacle that is known to be hard to detect in mid-flight. This paper describes how a blimp can be used in an aerial robot competition to identify other key challenges when flying in these cluttered environments.
Integrated Assessment of Environmental Quality Based Projection in Guangzhou, China, from 2003 to 2007
Authors: Zhongliang Yue
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

In this paper, measured values of annual indexes were directly utilized to assessment. By using projection, we make integrated assessment of environmental quality in Guangzhou City from 2003 to 2007. The order of annual environmental quality is obtained. The results show that the environmental quality in Guangzhou is worrying.
Authentication without Elision: Partially Specified Protocols, Associated Data, and Cryptographic Models Described by Code
Authors: Phillip Rogaway, Till Stegers
Venue: Proceedings of the 2009 22nd IEEE Computer Security Foundations Symposium (2009)

Specification documents for real-world authentication protocols typically mandate some aspects of a protocol's behavior but leave other features optional or undefined. In addition, real-world schemes often include parameter negotiations, authenticate associated data, and support a multiplicity of options. The cryptographic community has routinely elided such matters from our definitions, schemes, and proofs. We propose encompassing them by explicitly modeling the presence of unspecified protocol functionality. To demonstrate, we provide a new treatment for mutual authentication in the public-key setting, doing this in the computational cryptographic tradition. In our model, compactly described in pseudocode, a protocol core (PC) will call out to protocol details (PD), but, for defining security, such calls will be serviced by the adversary. Parties accepting an authentication exchange will output a string of associated data, the value of which may be determined by the PD calls. We illustrate the approach by re-proving security for the Needham-Schroeder-Lowe public-key protocol, but extended in a manner that would be typical were the mechanism embedded in a real-world standard.
A Study on Geological Image Segmentation
Authors: Du Cheng, Leng Biao
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

As different geological different image, almost no exactly the same geological images, making the division of geological image has become very difficult. Of the current image processing technology, most algorithms are based on specific digital image analysis and cannot be used under any circumstances. There is almost none for the digital image processing algorithms to the tunnel Headings; not to say what kind of image analysis and what kind of algorithms used for the specific tunnel Heading digital image. This article is the study of geology through the digital images using HSI color model in the amount of similarity of the cluster, using the image error square and guidelines function C means clustering segmentation. Clustering in automatically, at the same time completed the labeling of objects and give full play to non-supervision of the advantages of clustering algorithm to image geological feature extraction, measurement and analysis and a higher level of understanding possible.
Study on Fuzzy Control Algorithm for Magnetic Levitated Platform
Authors: Huachun Wu, Yefa Hu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

Magnetic Levitated Platform (MLP) which has no mechanical contact, no need of lubrication and other characteristics can solve the difficulties of traditional platform such as easy wear, hard machining environment and so on. Because it is a typical high order, nonlinear, strong coupling, multivariable time-varying system, the accurate mathematical model is difficult to establish. The traditional PID control can not adapt to the complex conditions of MLP. It is difficult to meet the needs of control precision and real-time position variation, and easy to bring about overshoot or oscillation phenomenon. Therefore, this paper takes the MLP system as the control object, adopt fuzzy control algorithm to overcome the above difficulties. The research is carried out by the combination of simulation using MATLAB fuzzy logic toolbox and experimental debug. The results show that this method can greatly improve the control precision and stability of the MLP, the performance is better than the optimal PID controller. It can effectively meet the MLP working demand, and has good robustness。
Combined Measurement System for the Evaluation of Multi Causal Strain
Authors: Holger Steiner, Dietmar Reinert, Norbert Jung
Venue: Proceedings of the International Conference on Ergonomics and Health Aspects of Work with Computers: Held as Part of HCI International 2009 (2009)

This work addresses the problem of measuring psychological strain in humans by the use of physiological data. The aim of the work is the research, development and evaluation of a measurement system for the acquisition of such data from humans and the differentiation of psychological and physical strain with the help of machine learning algorithms. The developed system records and analyzes the ECG, the EMG, as well as the skin conductance, and combines these physiological parameters with the subject's physical activity. The main purpose of this measurement system is to assess both types of strain in employees at their workplaces.
Mercury Ion Selective Thin Film Sensor Prepared by Pulsed Laser Deposition Technique
Authors: Hong Men, Zongnian Ge, Xiaozhe Zhu, Shanshan Zhang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

This paper presents a method for preparing mercury ion selective thin film sensor. Pulsed laser deposition (PLD) technique was used to prepare thin film on the surface of light-addressable potentiometric sensor (LAPS). Material sensitive to mercury ion was synthesized by two-step solid phase reaction and as target of PLD. After LAPS was prepared, the target material was ablated by PLD and deposited the surface of the LAPS. The deposited LAPS chip was cut and prepared thin film sensor (Hg-LAPS).A novel measuring unit including Hg-LAPS, reference electrode (RE) and LED was designed. The Hg-LAPS has a high sensitivity towards mercury (Ⅱ) ion and shows good repetition and stability. The detection limit of the thin film sensor is 3×10-6 mol/L and the response time is less than 2 min. interfering ions, pH, lifetime and hysteresis etc. are also investigated.
Word sense disambiguation using automatically translated sense examples
Authors: Xinglong Wang, David Martinez
Venue: Proceedings of the International Workshop on Cross-Language Knowledge Induction (2006)

We present an unsupervised approach to Word Sense Disambiguation (WSD). We automatically acquire English sense examples using an English-Chinese bilingual dictionary, Chinese monolingual corpora and Chinese-English machine translation software. We then train machine learning classifiers on these sense examples and test them on two gold standard English WSD datasets, one for binary and the other for fine-grained sense identification. On binary disambiguation, performance of our unsupervised system has approached that of the state-of-the-art supervised ones. On multi-way disambiguation, it has achieved a very good result that is competitive to other state-of-the-art unsupervised systems. Given the fact that our approach does not rely on manually annotated resources, such as sense-tagged data or parallel corpora, the results are very promising.
Semi-supervised training of a statistical parser from unlabeled partially-bracketed data
Authors: Rebecca Watson, Ted Briscoe, John Carroll
Venue: Proceedings of the 10th International Conference on Parsing Technologies (2007)

We compare the accuracy of a statistical parse ranking model trained from a fully-annotated portion of the Susanne treebank with one trained from unlabeled partially-bracketed sentences derived from this treebank and from the Penn Treebank. We demonstrate that confidence-based semi-supervised techniques similar to self-training outperform expectation maximization when both are constrained by partial bracketing. Both methods based on partially-bracketed training data outperform the fully supervised technique, and both can, in principle, be applied to any statistical parser whose output is consistent with such partial-bracketing. We also explore tuning the model to a different domain and the effect of in-domain data in the semi-supervised training processes.
Tapas: Theory Combinations and Practical Applications
Authors: Nikolaj Bjørner, Leonardo Moura
Venue: Proceedings of the 7th International Conference on Formal Modeling and Analysis of Timed Systems (2009)

Satisfiability Modulo Theories is about checking the satisfiability of logical formulas over one or more theories. We provide an appetizer of SMT solving, illustrate an application for test-case generation based on dynamic symbolic execution and summarize an array of existing applications, enabling features, challenges and future directions.