ppxscal/embedding_network huggingface dataset:
Using N-gram based features for machine translation system combination
Authors: Yong Zhao, Xiaodong He
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)

Conventional confusion network based system combination for machine translation (MT) heavily relies on features that are based on the measure of agreement of words in different translation hypotheses. This paper presents two new features that consider agreement of n-grams in different hypotheses to improve the performance of system combination. The first one is based on a sentence specific online n-gram language model, and the second one is based on n-gram voting. Experiments on a large scale Chinese-to-English MT task show that both features yield significant improvements on the translation performance, and a combination of them produces even better translation results.
Key Techniques of Eye Gaze Tracking Based on Pupil Corneal Reflection
Authors: Chi Jian-nan, Zhang Peng-yi, Zheng Si-yi, Zhang Chuang, Huang Ying
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

Eye Gaze Tracking (EGT) is a kind of techniques that can estimate gaze direction of a person via various methods such as optics, electronics, mechanics etc. Pupil corneal reflection is one of those methods that using the vector from Purkinje image center location to pupil center location to estimate the gaze direction. A review on key techniques of EGT based on pupil corneal reflection is given in three aspects of eye feature detection, mapping model from gaze parameters to gaze direction and face pose estimation. The characteristics of two kind mapping models are analyzed and the detection method of gaze direction based on stereovision is discussed. According to a large number of recent references, we propose some major problems and their possible solutions in EGT techniques as well as its research orientation in future.
Content Quality Assessment Related Frameworks for Social Media
Authors: Kevin Chai, Vidyasagar Potdar, Tharam Dillon
Venue: Proceedings of the International Conference on Computational Science and Its Applications: Part II (2009)

The assessment of content quality (CQ) in social media adds a layer of complexity over traditional information quality assessment frameworks. Challenges arise in accurately evaluating the quality of content that has been created by users from different backgrounds, for different domains and consumed by users with different requirements. This paper presents a comprehensive review of 19 existing CQ assessment related frameworks for social media in addition to proposing directions for framework improvements.
DL-lite in the light of first-order logic
Authors: A. Artale, D. Calvanese, R. Kontchakov, M. Zakharyaschev
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

The use of ontologies in various application domains, such as Data Integration, the Semantic Web, or ontology-based data management, where ontologies provide the access to large amounts of data, is posing challenging requirements w.r.t. a trade-off between expressive power of a DL and efficiency of reasoning. The logics of the DL-Lite family were specifically designed to meet such requirements and optimized w.r.t. the data complexity of answering complex types of queries. In this paper we propose DL-Litebool, an extension of DL-Lite with full Booleans and number restrictions, and study the complexity of reasoning in DL-Litebool and its significant sub-logics. We obtain our results, together with useful insights into the properties of the studied logics, by a novel reduction to the one-variable fragment of first-order logic. We study the computational complexity of satisfiability and subsumption, and the data complexity of answering positive existential queries (which extend unions of conjunctive queries). Notably, we extend the LOGSPACE upper bound for the data complexity of answering unions of conjunctive queries in DL-Lite to positive queries and to the possibility of expressing also number restrictions, and hence local functionality in the TBox.
Application Research of Image Matching Based on Morphology Description Matrix and Genetic algorithm
Authors: Yang Wenli, Zeng Zhiyuan
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

In this paper, an image matching algorithm based on morphology description matrix and genetic algorithm is proposed to improve matching efficiency. For the non-ergodic search characteristic of genetic algorithm is utilized, the global optimization is improved rapidly. Moreover, a shape matching algorithm based on the similarity of morphology description matrix is used in this paper. The calculation of matching search is reduced and the accuracy of matching results are improved by using the similarity of morphology description matrix as the fitness function of genetic algorithm. Experimental results show that the new algorithm can satisfy the real-time and
Logic in Access Control (Tutorial Notes)
Authors: Martín Abadi
Venue: Foundations of Security Analysis and Design V: FOSAD 2007/2008/2009 Tutorial Lectures (2009)

Access control is central to security in computer systems. Over the years, there have been many efforts to explain and to improve access control, sometimes with logical ideas and tools. This paper is a partial survey and discussion of the role of logic in access control. It considers logical foundations for access control and their applications, in particular in languages for security policies. It focuses on some specific logics and their properties. It is intended as a written counterpart to a tutorial given at the 2009 International School on Foundations of Security Analysis and Design.
Radio interferometric Quasi Doppler bearing estimation
Authors: Janos Sallai, Peter Volgyesi, Akos Ledeczi
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

The paper introduces a novel technique for the bearing estimation of radio sources that can be used for the precise localization and/or tracking of RF tags such as wireless sensor nodes. It is well known that the bearing to a radio source can be estimated by an array of antennas typically arranged in a circular manner. The method is often referred to as Quasi-Doppler measurement. The disadvantage of the existing method is that the receiver is relatively large because of the multiple antennas (typically 8 or 16) and it is computationally intensive to process the high frequency radio signals. Thus, it cannot be done on small, inexpensive radio tags. Instead, we propose to use the array on the transmitter side utilizing as few as three antennas. We use a radio interferometric technique to transform the useful phase information from the high frequency radio signal to a low frequency signal (≪ 1 kHz) that can be processed on low-cost hardware. Utilizing three anchors nodes with small antenna arrays, any number of low cost wireless nodes with single antennas can be accurately localized.
Executing multicellular differentiation
Authors: Nicola Bonzanni, Elzbieta Krepska, K. Anton Feenstra, Wan Fokkink, Thilo Kielmann, Henri Bal, Jaap Heringa
Venue: Bioinformatics (2009)

Motivation: Understanding the processes involved in multi-cellular pattern formation is a central problem of developmental biology, hopefully leading to many new insights, e.g. in the treatment of various diseases. Defining suitable computational techniques for development modelling, able to perform in silico simulation experiments, is an open and challenging problem. Results: Previously, we proposed a coarse-grained, quantitative approach based on the basic Petri net formalism, to mimic the behaviour of the biological processes during multicellular differentiation. Here, we apply our modelling approach to the well-studied process of Caenorhabditis elegans vulval development. We show that our model correctly reproduces a large set of in vivo experiments with statistical accuracy. It also generates gene expression time series in accordance with recent biological evidence. Finally, we modelled the role of microRNA mir-61 during vulval development and predict its contribution in stabilizing cell pattern formation. Contact: feenstra@few.vu.nl Supplementary information: Supplementary data are available at Bioinformatics online.
RapidMesh: declarative toolkit for rapid experimentation of wireless mesh networks
Authors: Shivkumar C. Muthukumar, Xiaozhou Li, Changbin Liu, Joseph B. Kopena, Mihai Oprea, Ricardo Correa, Boon Thau Loo, Prithwish Basu
Venue: Proceedings of the 4th ACM international workshop on Experimental evaluation and characterization (2009)

We present the RapidMesh toolkit for rapid protocol simulation, implementation and experimentation of wireless mesh networks. RapidMesh utilizes declarative networking, a declarative, database-inspired extensible infrastructure that uses query languages to specify behavior. RapidMesh integrates a declarative networking engine with the emerging ns-3 network simulator. The same declarative specifications can also be used as actual implementations using the ns-3 network emulator, hence providing a bridge between simulation and testbed-based experimentation. We demonstrate that RapidMesh enables a variety of wireless routing protocols and neighbor discovery protocols can be synthesized via compact declarative specifications. We experimentally validate declarative MANET routing protocols in dynamic settings within RapidMesh operating in ns-3 simulation environment and on the ORBIT wireless testbed.
A Graph-Based Approach for Shape Skeleton Analysis
Authors: André R. Backes, Odemir M. Bruno
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

This paper presents a novel methodology to shape characterization, where a shape skeleton is modeled as a dynamic graph, and degree measurements are computed to compose a set of shape descriptors. The proposed approach is evaluated in a classification experiment which considers a generic set of shapes. A comparison with traditional shape analysis methods, such as Fourier descriptors, Curvature, Zernike moments and Multi-scale Fractal Dimension, is also performed. Results show that the method is efficient for shape characterization tasks, in spite of the reduced amount of information present in the shape skeleton.
One translation per discourse
Authors: Marine Carpuat
Venue: Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions (2009)

We revisit the one sense per discourse hypothesis of Gale et al. in the context of machine translation. Since a given sense can be lexicalized differently in translation, do we observe one translation per discourse? Analysis of manual translations reveals that the hypothesis still holds when using translations in parallel text as sense annotation, thus confirming that translational differences represent useful sense distinctions. Analysis of Statistical Machine Translation (SMT) output showed that despite ignoring document structure, the one translation per discourse hypothesis is strongly supported in part because of the low variability in SMT lexical choice. More interestingly, cases where the hypothesis does not hold can reveal lexical choice errors. A preliminary study showed that enforcing the one translation per discourse constraint in SMT can potentially improve translation quality, and that SMT systems might benefit from translating sentences within their entire document context.
What Have the Neighbours Ever Done for Us? A Collaborative Filtering Perspective
Authors: Rachael Rafter, Michael P. O'Mahony, Neil J. Hurley, Barry Smyth
Venue: Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH (2009)

Collaborative filtering (CF) techniques have proved to be a powerful and popular component of modern recommender systems. Common approaches such as user-based and item-based methods generate predictions from the past ratings of users by combining two separate ratings components: a base estimate, generally based on the average rating of the target user or item, and a neighbourhood estimate, generally based on the ratings of similar users or items. The common assumption is that the neighbourhood estimate gives CF techniques a considerable edge over simpler average-rating techniques. In this paper we examine this assumption more carefully and demonstrate that the influence of neighbours can be surprisingly minor in CF algorithms, and we show how this has been disguised by traditional approaches to evaluation, which, we argue, have limited progress in the field.
Dense and Deformable Motion Segmentation for Wide Baseline Images
Authors: Juho Kannala, Esa Rahtu, Sami S. Brandt, Janne Heikkilä
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

In this paper we describe a dense motion segmentation method for wide baseline image pairs. Unlike many previous methods our approach is able to deal with deforming motions and large illumination changes by using a bottom-up segmentation strategy. The method starts from a sparse set of seed matches between the two images and then proceeds to quasi-dense matching which expands the initial seed regions by using local propagation. Then, the quasi-dense matches are grouped into coherently moving segments by using local bending energy as the grouping criterion. The resulting segments are used to initialize the motion layers for the final dense segmentation stage, where the geometric and photometric transformations of the layers are iteratively refined together with the segmentation, which is based on graph cuts. Our approach provides a wider range of applicability than the previous approaches which typically require a rigid planar motion model or motion with small disparity. In addition, we model the photometric transformations in a spatially varying manner. Our experiments demonstrate the performance of the method with real images involving deforming motion and large changes in viewpoint, scale and illumination.
Desynchronisation Technique Using Petri Nets
Authors: Sohini Dasgupta, Alex Yakovlev
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

In this paper we consider the problem of desynchronising modular synchronous specifications for their realisation into GALS architectures and obtaining simple wrappers that are efficiently synthesisable using existing synthesis tools. The systems are modeled using Petri nets (PN) and the desynchronisation technique is based on the theory of PN Localities. The firing semantics of a globally synchronous system is characterised by maximal firing of input and output transitions. The partitioning of a synchronous system is achieved by unbundling the input transitions and allowing the output transitions to fire in maximal steps, in order to enable asynchronous communication in a distributed environment. Our model satisfies the two essential correctness properties, namely, semantics preservation and deadlock prevention, during the shift from maximal firing semantics, followed by synchronous systems, to standard interleaving semantics for input transitions and maximal step firing semantics for output transitions, followed by GALS architectures. The formation of localities is supported by adding internal signals which are necessary for building wrappers in the localities that will generate local clock enables. These wrappers can be subsequently synthesised using PN based synthesis tools.
Annotated Contraction Kernels for Interactive Image Segmentation
Authors: Hans Meine
Venue: Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition (2009)

This article shows how the interactive segmentation tool termed "Active Paintbrush" and a fully automatic region merging can both be based on the theoretical framework of contraction kernels within irregular pyramids instead of their own, specialized data structures. We introduce "continous pyramids" in which we purposely drop the common requirement of a fixed reduction factor between successive levels, and we show how contraction kernels can be annotated for a fast navigation of such pyramids. Finally, we use these concepts for improving the integration of the automatic region merging and the interactive tool.
Combining Multidimensional Scaling and Computational Intelligence for Industrial Monitoring
Authors: António Dourado, Sara Silva, Lara Aires, João Araújo
Venue: Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects (2009)

Large industrial complexes with hundreds of variables must be tightly monitored for safety, quality and resources optimization. Multidimensional scaling and computational intelligence are proposed in this work as effective tools for building classifiers of the operating state of the industrial process into normal / abnormal working regions. The VisRed, Visualization by Data Reduction computational framework, is extended with techniques from computational intelligence, such as neural networks (several architectures), support vector machines and neuro-fuzzy systems (in an evolving adaptive implementation) to build such classifiers. The Visbreaker plant of an oil refinery is taken as case study and some scenarios show the potentiality of the combined approach.
Exploiting image descriptions for the generation of referring expressions
Authors: Knut Hartmann, Jochen Schöpp
Venue: Referring Phenomena in a Multimedia Context and their Computational Treatment (1997)

Intelligent multimedia representation systems (e.g. (Wahlster et al., 1993), (Andr&eacute; et al., 1996), (Feiner and McKeown, 1993)) have to select appropriate expressions in different modes (texts, graphics and animations) and to coordinate them 1. For both tasks, an explicit representation of the content of the multimodal expressions is required. An important aspect of the media coordination is to ensure the cohesion of the resulting multimodal presentation.
Trade-offs between Agility and Reliability of Predictions in Dynamic Social Networks Used to Model Risk of Microbial Contamination of Food
Authors: Artur Dubrawski, Purnamrita Sarkar, Lujie Chen
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

This paper evaluates trade-offs between agility and reliability of predictions arising due to sparseness of data modeled with dynamic social networks. We use real field data from food safety domain to illustrate the discussion. We model food production facilities as one type of entities in a social network evolving in time. Another type of entities denotes various specific strains of Salmonella. Two entities are linked in the graph if a microbial test of food sample conducted at the specific food facility over specific period of time turns out positive for the particular pathogen. We use a computationally efficient latent space model to predict future occurrences of pathogens in individual facilities. Empirical results indicate predictive utility of the proposed representation. However, sparseness of data limits the attainable agility of predictions. We identify exploiting recency of data and using the known patterns in it, such as seasonality, as plausible means of battling the challenge of sparseness.
An Energy Reporting Aggregation Method Based on EAFM and DTRM in WSN
Authors: Sheng Zhang, Ping Zhou, Jian Shu
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

Analyzed the energy consumption disciplinarian of the nodes in WSN, the node’s Energy Attenuation Forecast Model(EAFM) can be established. A Difference-threshold Reporting Mechanism (DTRM) is used to report the residual energy of nodes. The energy collection mechanism based on EAFM and DTRM can reduce energy data reporting times significantly,improve the efficient of energy data collection, save the node's energy at the same time. The experiments in the platform of telosb nodes show that the predicable rate is between 70% and85%, and this method can extend the node’s life by 1% ~ 4.5%.
A High-Performance Significand BCD Adder with IEEE 754-2008 Decimal Rounding
Authors: Álvaro Vazquez, Elisardo Antelo
Venue: Proceedings of the 2009 19th IEEE Symposium on Computer Arithmetic (2009)

We present a new method and architecture to merge efficiently IEEE 754 -2008 decimal rounding with significand BCD addition and subtraction. This is a key component to improve several decimal floating-point operations such as addition, multiplication and fused multiply-add. The decimal rounding unit is based on a direct implementation of the IEEE 754 2008 round ing modes. We show that the resultant implementations for IEEE 754-2008 Decimal64 (16 precision digits) and Decimal128 (34 precision digits) formats reduce significantly the area and latency required for significand BCD addition/subtraction and decimal rounding in previous high-performance decimal floating-point adders.
Approximation to the k-th derivatives by multiquadric quasi-interpolation method
Authors: Limin Ma, Zongmin Wu
Venue: Journal of Computational and Applied Mathematics (2009)

Quasi-interpolation is very useful in the study of approximation theory and its applications, since it can yield solutions directly without the need to solve any linear system of equations. Based on the good performance (simple to evaluate) of multiquadric functions, the advantages (approximation order, convexity and monotonlcity preserving) of multiquadric quasi-interpolation have been widely discussed. However, it is usually only for the approximation properties of the function itself and the good properties for derivatives, whereas the high order derivatives have been largely ignored. In this paper, we go further into the approximation properties to the k-th derivatives by using multiquadric quasi-interpolation. Furthermore, we develop two kinds of multiquadric quasi-interpolation schemes on bounded interval [x"0,x"N], whose derivatives converge to the corresponding derivatives of the approximated functions. Finally, the numerical experiments are presented to confirm the accuracy of the presented scheme. Both theoretical results and numerical examples show this scheme provides good accuracy even if the data points in [x"0,x"N] are irregularly distributed.
Implementing the maximum of monotone algorithms
Authors: Liad Blumrosen
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

Running several sub-optimal algorithms and choosing the optimal one is a common procedure in computer science, most notably in the design of approximation algorithms. This paper deals with one significant flaw of this technique in environments where the inputs are provided by selfish agents: such protocols are not necessarily incentive compatible even when the underlying algorithms are. We characterize sufficient and necessary conditions for such best-outcome protocols to be incentive compatible in a general model for agents with one-dimensional private data. We show how our techniques apply in several settings.