ppxscal/embedding_network huggingface dataset:
Improving interactive machine translation via mouse actions
Authors: Germán Sanchis-Trilles, Daniel Ortiz-Martínez, Jorge Civera, Francisco Casacuberta, Enrique Vidal, Hieu Hoang
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

Although Machine Translation (MT) is a very active research field which is receiving an increasing amount of attention from the research community, the results that current MT systems are capable of producing are still quite far away from perfection. Because of this, and in order to build systems that yield correct translations, human knowledge must be integrated into the translation process, which will be carried out in our case in an Interactive-Predictive (IP) framework. In this paper, we show that considering Mouse Actions as a significant information source for the underlying system improves the productivity of the human translator involved. In addition, we also show that the initial translations that the MT system provides can be quickly improved by an expert by only performing additional Mouse Actions. In this work, we will be using word graphs as an efficient interface between a phrase-based MT system and the IP engine.
Unique Stressors of Cross-Cultural Collaboration through ICTs in Virtual Teams
Authors: Niina Nurmi
Venue: Proceedings of the International Conference on Ergonomics and Health Aspects of Work with Computers: Held as Part of HCI International 2009 (2009)

Geographically distributed virtual teams are increasingly prevalent in global organizations. Despite the growing attention to virtual teams, there is limited understanding of how cross-cultural collaboration and electronic dependence in communication affect virtual workers' psychological reactions and well-being. This qualitative multi-case study aims at understanding the different causes of stress in cross-cultural collaboration. An overarching analysis across seven case studies revealed that globally distributed team members experienced job stressors such as language challenges in English, or lingua franca, misunderstandings, and conflicts due to different mindsets, communication and behavior styles, and work-leisure orientations. Without adequate skills in lingua franca, or proper cultural and local awareness of distant team sites, coping was not successful, thereby stressors lead to distress.
A variational characterisation of spherical designs
Authors: Ian H. Sloan, Robert S. Womersley
Venue: Journal of Approximation Theory (2009)

In this paper we first establish a new variational characterisation of spherical designs: it is shown that a set X"N={x"1,...,x"N}@?S^d, where S^d:={x@?R^d^+^1:@?"j"="1^dx"j^2=1}, is a spherical L-design if and only if a certain non-negative quantity A"L","N(X"N) vanishes. By combining this result with a known ''sampling theorem'' for the sphere, we obtain the main result, which is that if X"N@?S^d is a stationary point set of A"L","N whose ''mesh norm'' satisfies h"X"""N
Description logic-ground knowledge integration and management
Authors: Joseph B. Kopena
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 4 (2005)

This abstract describes ongoing work in developing large-scale knowledge repositories. The project addresses three primary aspects of such systems: integration of knowledge sources; access and retrieval of stored knowledge; scalable, effective repositories. Previous results have shown the effectiveness of description logic-based representations in integrating knowledge sources and the role of non-standard inferences in supporting repository reasoning tasks. Current efforts include developing general-purpose mechanisms for adapting reasoning algorithms for optimized inference under known domain structure and effective use of database technology as a large-scale knowledge base backend.
Coders at Work, 1st edition
Authors: Peter Seibel
Venue:  (2009)

Peter Seibel interviews 15 of the most interesting computer programmers alive today in Coders at Work, offering a brand-new companion volume to Apresss highly acclaimed best-seller Founders at Work by Jessica Livingston. As the words at work suggest, Peter Seibel focuses on how his interviewees tackle the day-to-day work of programming, while revealing much more, like how they became great programmers, how they recognize programming talent in others, and what kinds of problems they find most interesting. Hundreds of people have suggested names of programmers to interview on the Coders at Work web site: www.codersatwork.com. The complete list was 284 names. Having digested everyones feedback, we selected 15 folks whove been kind enough to agree to be interviewed: Frances Allen: Pioneer in optimizing compilers, first woman to win the Turing Award (2006) and first female IBM fellow Joe Armstrong: Inventor of Erlang Joshua Bloch: Author of the Java collections framework, now at Google Bernie Cosell: One of the main software guys behind the original ARPANET IMPs and a master debugger Douglas Crockford: JSON founder, JavaScript architect at Yahoo! L. Peter Deutsch: Author of Ghostscript, implementer of Smalltalk-80 at Xerox PARC and Lisp 1.5 on PDP-1 Brendan Eich: Inventor of JavaScript, CTO of the Mozilla Corporation Brad Fitzpatrick: Writer of LiveJournal, OpenID, memcached, and Perlbal Dan Ingalls: Smalltalk implementor and designer Simon Peyton Jones: Coinventor of Haskell and lead designer of Glasgow Haskell Compiler Donald Knuth: Author of The Art of Computer Programming and creator of TeX Peter Norvig: Director of Research at Google and author of the standard text on AI Guy Steele: Coinventor of Scheme and part of the Common Lisp Gang of Five, currently working on Fortress Ken Thompson: Inventor of UNIX Jamie Zawinski: Author of XEmacs and early Netscape/Mozilla hacker What youll learn How the best programmers in the world do their job Who is this book for? Programmers interested in the point of view of leaders in the field. Programmers looking for approaches that work for some of these outstanding programmers.
PDA: Passive distributed assertions for sensor networks
Authors: Kay Romer, Junyan Ma
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

Sensor networks are prone to failures and are hard to debug. This is particularely true for failures caused by incorrect interaction of multiple nodes. We propose a mechanism called passive distributed assertions (PDA) that allows developers to detect such failures and provides hints on possible causes. PDA allow a programmer to formulate assertions over distributed node states using a simple declarative language, causing the sensor network to emit information that can be passively collected (e.g., using packet sniffing) and evaluated to verify that assertions hold. This passive approach allows us to minimize the interference between the application and assertion verification. Further, our system provides mechanisms to deal with inaccurate traces that result from message loss and synchronization inaccuracies. We implement PDA on the BTnode platform and evaluate it using an extensive case study.
Subspace Regularization: A New Semi-supervised Learning Method
Authors: Yan-Ming Zhang, Xinwen Hou, Shiming Xiang, Cheng-Lin Liu
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, though works well in many cases, has some limitations. To overcome this problems, we introduce into semi-supervised learning the classic low-dimensionality embedding assumption, stating that most geometric information of high dimensional data is embedded in a low dimensional manifold. Based on this, we formulate the problem of semi-supervised learning as a task of finding a subspace and a decision function on the subspace such that the projected data are well separated and the original geometric information is preserved as much as possible. Under this framework, the optimal subspace and decision function are iteratively found via a projection pursuit procedure. The low computational complexity of the proposed method lends it to applications on large scale data sets. Experimental comparison with some previous semi-supervised learning methods demonstrates the effectiveness of our method.
Spatial Navigation in a Virtual Multilevel Building: The Role of Exocentric View in Acquiring Survey Knowledge
Authors: Zhiqiang Luo, Henry Been-Lirn Duh, I-Ming Chen, Wenshu Luo
Venue: Proceedings of the 3rd International Conference on Virtual and Mixed Reality: Held as Part of HCI International 2009 (2009)

The present study aimed to test the function of the exocentric view on the acquisition of survey knowledge during spatial navigation in a virtual multilevel building. Subjects navigated a virtual three-level building in three conditions. In the first condition, subjects navigated the building without any aid. In the second condition, subjects navigated the building with the aid of a three-dimensional (3D) floor map which illustrated the spatial layout on each level from one exocentric perspective. In the third condition, subjects could watch the spatial layout on each level from the exocentric perspective when traveling to another level by an elevator. After navigation, all subjects made the judgment of spatial relative direction. The analyses of the accuracy of spatial judgments showed that the accuracy of judgment of spatial horizontal direction was significantly improved when subjects observed the exocentric views of levels in the last two conditions; the judgment of spatial vertical direction was significantly worse in the 3D floor map condition than in other two conditions. Furthermore, the accuracy of judgment of both spatial horizontal and vertical directions was best in the direction faced by subjects when they first enter each level. The results suggested that the content of exocentric view should be carefully designed to improve the acquisition of survey knowledge. The application of the findings included the design of 3D map for the navigation in the virtual multilevel building.
Interaction Based Functional Clustering of Genomic Data
Authors: Ritesh Krishna, Chang-Tsun Li, Vicky Buchanan-Wollaston
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

We present the first report on Granger causality based detection of functional modules from temporal gene expression data. The approach uses temporal causal relationships shared between pair of genes to derive a connection matrix, which is further analyzed using graph-theoretic techniques. The approach is evaluated against a synthesized dataset and a real biological dataset obtained for Arabidopsis thaliana. We show the effectiveness of our approach by analyzing the results using the existing biological literature.
Automatic Music Genre Classification Using a Hierarchical Clustering and a Language Model Approach
Authors: Thibault Langlois, Gonçalo Marques
Venue: Proceedings of the 2009 First International Conference on Advances in Multimedia (2009)

Automatic music genre classification has received a lot of attention from the Music Information Retrieval (MIR) community in the past years. Systems capable of discriminating music genres are essential for managing music databases. This paper presents a method for music genre classification based solely on the audio contents of the signal. The method relies on a language modeling approach and takes in account the temporal information of the music signals for genre classification. First, the music data is transformed into a sequence of symbols, and a model is derived for each genre by estimating n-grams from the training data. As a term o comparison, HMMs models for each musical genre were also implemented. Tests on different audio sets show that the proposed approach performs very well, and outperforms HMMs based methods.
Comparisons of 6LoWPAN Implementations on Wireless Sensor Networks
Authors: Yannis Mazzer, Bernard Tourancheau
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

This paper introduces our work on the communication stack of wireless sensor networks. We present the IPv6 approach for wireless sensor networks called 6LoWPAN in its IETF charter. We then compare the different implementations of 6LoWPAN subsets for several sensor nodes platforms. We present our approach for the 6LoWPAN implementation which aims to preserve the advantages of modularity while keeping a small memory footprint and a good efficiency.
Web 2.0 project-based learning in higher education: some preliminary evidence
Authors: Francesca Grippa, Giustina Secundo
Venue: International Journal of Web Based Communities (2009)

This paper develops an understanding of how Web 2.0 applications can be utilised to support a Project-Based Learning (PBL) approach. Creating communities in the classroom has been the traditional method of engaging students. Web 2.0 technologies are changing the way dispersed learning communities interact. To provide preliminary evidence on this, we have designed a Social Computing Environment (SCE) to support a community of students coming from Morocco, Tunisia, Egypt and Jordan and involved in an International Master's Programme in e-Business Management (IMeBM). This study suggests that Web 2.0 tools enhance learning effectiveness in terms of learners' satisfaction, knowledge creation and learning performance. The preliminary results suggest that learners prefer to utilise wikis more than blogs to collaborate with peers, tutors and mentors.
A novel iris segmentation using radial-suppression edge detection
Authors: Jing Huang, Xinge You, Yuan Yan Tang, Liang Du, Yuan Yuan
Venue: Signal Processing (2009)

Iris segmentation is a key step in the iris recognition system. The conventional methods of iris segmentation are based on the assumption that the inner and outer boundaries of an iris can be taken as circles. The region of the iris is segmented by detecting the circular inner and outer boundaries. However, we investigate the iris boundaries in the CASIA-IrisV3 database, and find that the actual iris boundaries are not always circular. In order to solve this problem, a new approach for iris segmentation based on radial-suppression edge detection is proposed in this paper. In the radial-suppression edge detection, a non-separable wavelet transform is used to extract the wavelet transform modulus of the iris image. Then, a new method of radial non-maxima suppression is proposed to retain the annular edges and simultaneously remove the radial edges. Next, a thresholding operation is utilized to remove the isolated edges and produce the final binary edge map. Based on the binary edge map, a self-adaptive method of iris boundary detection is proposed to produce final iris boundaries. Experimental results demonstrate that the proposed iris segmentation is desirable.
Multiagent System Simulations of Signal Averaging in English Auctions with Two-Dimensional Value Signals
Authors: Alan Mehlenbacher
Venue: Computational Economics (2009)

Computational experiments with a multiagent system show that bidders use signal averaging to avoid the winner's curse in English auctions. The results vary with the percent of common value in a two-dimensional value signal, information levels, uncertainty, and the number of bidders. The complexity introduced by the combinations of these factors affects the bidding strategies and auction outcomes in interesting ways--usually nonlinearly and sometimes non-monotonically. Of main concern to a seller is the effect of these factors on revenue. I find that revenue increases with the percent of common value in the two-dimensional value signal, decreases with uncertainty, and increases with the number of bidders. There is very little impact of information level on revenue when values are pure private and pure common. However, for the intermediate cases of two-dimensional value signals, revenue decreases with increased information.
Preference grammars: softening syntactic constraints to improve statistical machine translation
Authors: Ashish Venugopal, Andreas Zollmann, Noah A. Smith, Stephan Vogel
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (2009)

We propose a novel probabilistic synchoronous context-free grammar formalism for statistical machine translation, in which syntactic nonterminal labels are represented as "soft" preferences rather than as "hard" matching constraints. This formalism allows us to efficiently score unlabeled synchronous derivations without forgoing traditional syntactic constraints. Using this score as a feature in a log-linear model, we are able to approximate the selection of the most likely unlabeled derivation. This helps reduce fragmentation of probability across differently labeled derivations of the same translation. It also allows the importance of syntactic preferences to be learned alongside other features (e.g., the language model) and for particular labeling procedures. We show improvements in translation quality on small and medium sized Chinese-to-English translation tasks.
Cellulase Activity in Physically Isolated Fractions of a Paddy Soil
Authors: Jinlong Yan, Genxing Pan, Lianqing Li, Guixiang Quan
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

Speciﬁc location of extracellular enzymes within the soil matrix was related to soil organic matter (SOM) quality and carbon turnover. A physical fractionation procedure was used to investigate whether soil carbon was spatially isolated from degradative enzymes in a paddy soil. In POM fractions of this study, high C concentrations are found because they are derived from inputs of recent plant materials with high C-to-N ratios and low mineral content. Total nitrogen was highest in the clay-sized fraction and lowest in the silt-sized fraction. The C-to-N ratios were decreased with decreasing particle size, lowest in the clay-sized fraction, greatest in the POM fractions, and inter-mediate in the bulk soil and silt-sized fractions. Different distribution trend in physically isolated fractions indicated that there was fundamental difference in the factors determining their location. The absolute activity of carboxymethyl cellulase activity was greatest in coarse POM fractions and generally decreased from the coarse POM fractions to the silt-size fraction, following a decrease of Corg as well as an increase in biostability of the organic material, as indicated by a decrease in the C-to-N ratio.
Key Issues in Planning and Making Sense of International Field Research
Authors: Susan M. Dray, David A. Siegel
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II (2009)

More and more companies are doing international research as they design products and services for people around the world. These studies are particularly complex and challenging however, and there are, to date, relatively few resources to guide the people doing them. This tutorial uses scenarios and discussion to help practitioners learn how to approach, plan, manage, and interpret international field studies.
Towards system-mediated car passenger communication
Authors: Angela Mahr, Margarita Pentcheva, Christian Müller
Venue: Proceedings of the 1st International Conference on Automotive User Interfaces and Interactive Vehicular Applications (2009)

In this paper, we outline a system that supports the communication between passengers by transmitting speech (and maybe also video) of the communication partners back and forth. A study is presented that addresses the questions: 1. Is listening to noisy speech coming from the backseat really distracting the driver? Subjects are rating the truth of common-sense statements played from the back of the car (clear, noisy) while driving with a drive simulator. NOISY is rated significantly more distracting than CLEAR while objective driving performance only degrades for men but not for women.
A Machine Learning Based Framework for Adaptive Mobile Learning
Authors: Ahmed Al-Hmouz, Jun Shen, Jun Yan
Venue: Proceedings of the 8th International Conference on Advances in Web Based Learning (2009)

Advances in wireless technology and handheld devices have created significant interest in mobile learning (m-learning) in recent years. Students nowadays are able to learn anywhere and at any time. Mobile learning environments must also cater for different user preferences and various devices with limited capability, where not all of the information is relevant and critical to each learning environment. To address this issue, this paper presents a framework that depicts the process of adapting learning content to satisfy individual learner characteristics by taking into consideration his/her learning style. We use a machine learning based algorithm for acquiring, representing, storing, reasoning and updating each learner acquired profile.
Implicit proposal filtering in multi-party consensus-building conversations
Authors: Yasuhiro Katagiri, Yasuharu Den, Masato Ishizaki, Yosuke Matsusaka, Mika Enomoto, Katsuya Takanashi
Venue: Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue (2008)

An attempt was made to statistically estimate proposals which survived the discussion to be incorporated in the final agreement in an instance of a Japanese design conversation. Low level speech and vision features of hearer behaviors corresponding to aiduti, noddings and gaze were found to be a positive predictor of survival. The result suggests that non-linguistic hearer responses work as implicit proposal filters in consensus building, and could provide promising candidate features for the purpose of recognition and summarization of meeting events.
A Novel Scheme of Robust and Blind Video Watermarking
Authors: Li Jing
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

A novel video watermarking scheme is proposed, in which the watermark is embedded into DCT coefficients of luminance component of the video. Firstly, geometric features of one frame is extracted by Harris detection, then the watermark composed of information part and symbol part is embedded to the subsequent video frames at the same time. Information watermark is divided into several segments which were embedded to frames separately. Every segment was embedded into direct current coefficients of certain blocks of each frame; while the symbol watermark was embedded to low frequency coefficients of the other blocks. To extract the watermark, the geometric attacks are rectified firstly with the aid of geometric features, then the frames with watermark were found by detecting the symbol watermark, so that, the information watermark will be extracted correctly. Experimental results show that the watermark is invisible and the scheme is robust to various attacks such as rotation, scaling, frame dropping, insertion, regrouping and MPEG, The scheme can satisfy real-time requirement and the watermark can be extracted blindly.