ppxscal/embedding_network huggingface dataset:
A geometric nonuniform fast Fourier transform
Authors: Ian Sammis, John Strain
Venue: Journal of Computational Physics (2009)

An efficient algorithm is presented for the computation of Fourier coefficients of piecewise-polynomial densities on flat geometric objects in arbitrary dimension and codimension. Applications range from standard nonuniform FFTs of scattered point data, through line and surface potentials in two and three dimensions, to volumetric transforms in three dimensions. Input densities are smoothed with a B-spline kernel, sampled on a uniform grid, and transformed by a standard FFT, and the resulting coefficients are unsmoothed by division. Any specified accuracy can be achieved, and numerical experiments demonstrate the efficiency of the algorithm for a gallery of realistic examples.
Relationship between Emotional State and Pupil Diameter Variability under Various Types of Workload Stress
Authors: Kiyomi Sakamoto, Shoichi Aoyama, Shigeo Asahara, Haruki Mizushina, Hirohiko Kaneko
Venue: Proceedings of the International Conference on Ergonomics and Health Aspects of Work with Computers: Held as Part of HCI International 2009 (2009)

We carried out two experiments to explore the relationship between the frequency characteristic of pupil diameter variability and emotional state under various types of workload. The workload required the subjects to listen to spoken words and categorize them. The difficulty of the task was adjusted by changing the time interval of the stimulus presentation in Experiment 1 (time-based task) and the number of categories in Experiment 2 (cognitive-based task). Pupil diameter was monitored and recorded using an infrared video camera while observers were performing the tasks. In both experiments, a significant correlation was observed between the frequency characteristic of pupil diameter variability and emotional state. Our results indicated the frequency characteristic of pupil diameter variability to be a potentially useful index for evaluating mental stress.
From the EIC: Building and verifying hardware at a higher level of abstraction
Venue: IEEE Design Test (2009)

To manage design complexity and cost, the next-generation design methodology must enable the highest possible level of abstraction; hide, insofar as possible, implementation details from designers; allow efficient design reuse, including the reuse of IP blocks, underlying architectures, and a large portion of embedded software across multiple generations; and provide flexibility in the system architecture of computation, communications, and storage elements. High-level synthesis is necessary and critical in such a solution. Consequently, this issue of IEEE Design &#x0026; Test presents nine articles to review the progress of high-level synthesis research and which examine various aspects of this up-and-coming methodology.
Lessons from trying to develop a robust documentation exemplar
Authors: Lynn Robert Carter, Andreas Karatsolis
Venue: Proceedings of the 27th ACM international conference on Design of communication (2009)

Software system documentation has been an integral part of the development process since the first efforts to design and implement large and robust systems. However, the focus of this documentation typically has been limited to the production of discrete artifacts, despite the richness of data and genres that surround it. Efforts to develop a robust documentation exemplar - Della - have not been completely successful, mainly because the provided documentation was largely ignored by many students for simpler but less effective alternate designs. This paper will present, in addition to the lessons learned from the Della project, some insights into the direction software system documentation now should be taking in support of large and long-lived systems.
Precision and mathematical form in first and subsequent mentions of numerical facts and their relation to document structure
Authors: Sandra Williams, Richard Power
Venue: Proceedings of the 12th European Workshop on Natural Language Generation (2009)

In a corpus study we found that authors vary both mathematical form and precision when expressing numerical quantities. Indeed, within the same document, a quantity is often described vaguely in some places and more accurately in others. Vague descriptions tend to occur early in a document and to be expressed in simpler mathematical forms (e.g., fractions or ratios), whereas more accurate descriptions of the same proportions tend to occur later, often expressed in more complex forms (e.g., decimal percentages). Our results can be used in Natural Language Generation (1) to generate repeat descriptions within the same document, and (2) to generate descriptions of numerical quantities for different audiences according to mathematical ability.
Facial Expression Recognition Based on Wavelet Energy Distribution Feature and Neural Network Ensemble
Authors: Chen Feng-jun, Wang Zhi-liang, Xu Zheng-guang, Xiao Jiang
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

Facial expression recognition is necessary for designing any human-machine interfaces. A novel facial expression recognition method based on the Wavelet energy feature and neural network ensemble classifier is proposed in this paper. And six basic expressions – anger, disgust, surprise, happiness, fear and sadness are analyzed. Firstly, wavelet transform is used for static facial expression images and the wavelet energy is extracted from various sub-areas as facial expression features; Secondly, the neural network ensemble based on Bagging algorithm is used to offer the classifier trainings on facial expression recognition. Experiments results demonstrate an expression classification accuracy of 75.9% on the CMU-PITTSBURGH AU-Coded Face Expression Image Database, which conduct classification more accurately than other single neural network.
Smooth 3-D Reconstruction for 2-D Histological Images
Authors: Amalia Cifor, Tony Pridmore, Alain Pitiot
Venue: Proceedings of the 21st International Conference on Information Processing in Medical Imaging (2009)

We present an image driven approach to the reconstruction of 3-D volumes from stacks of 2-D post-mortem sections (histology, cryoimaging, autoradiography or immunohistochemistry) in the absence of any external information. We note that a desirable quality of the reconstructed volume is the smoothness of its notable structures (e.g. the gray/white matter surfaces in brain images). Here we propose to use smoothness as a means to drive the reconstruction process itself.From an initial rigid pair-wise reconstruction of the input 2-D sections, we extract the boundaries of structures of interest. Those are then evolved under a mean curvature flow modified to constrain the flow within 2-D planes. Sparse displacement fields are then computed, independently for each slice, from the resulting flow. A variety of transformations, from globally rigid to arbitrarily flexible ones, can then be estimated from those fields and applied to the individual input 2-D sections to form a smooth volume.We detail our method and discuss preliminary results on both real histological data and synthetic examples.
Sharing Good Practice through Mash-Up Personal Learning Environments
Authors: Felix Mödritscher, Fridolin Wild
Venue: Proceedings of the 8th International Conference on Advances in Web Based Learning (2009)

Personal learning environments (PLEs) require new ways to motivate and scaffold learners. In particular, practice sharing is of importance for learnercentric approaches in the scope of (technology-enhanced) lifelong learning, as it is an enabler for community building and sustaining. In this paper we elaborate prerequisites for `good practice sharing' and explain how we realized these aspects in our PLE solution named Mash-Up Personal Learning Environments (MUPPLE.org). Finally, we argue for the utility of our MUPPLE approach by highlighting two different strategies of good practice sharing and their benefits for learning and community building.
In Strangers We Trust? Findings of an Empirical Study of Distributed Teams
Authors: Ban Al-Ani, David Redmiles
Venue: Proceedings of the 2009 Fourth IEEE International Conference on Global Software Engineering (2009)

Trust has long been a contentious issue in human endeavours. It is not readily given nor gained, more so when strangers are involved. It often becomes an issue during distributed development where individuals are expected to interact with strangers they may not “meet” during the project lifetime. Trust was spontaneously raised by respondents in an empirical study of practices within distributed development and is reported in this paper. A qualitative analysis of study data suggests that trust typically becomes an issue in large teams when developers are to deliver an innovative product. We also found that it is more likely to be an issue the greater the diversity (of culture, language, time zone…etc.) within the team. Finally the data also suggests that developers more readily trust an authoritative team member (e.g. team leader), even if remote.Data suggests these factors can act as positive and negative forces to influence trust within distributed teams. These forces are reported in this paper together with proposed approaches that can promote equilibrium of the net forces.
A Scalable Noise Reduction Technique for Large Case-Based Systems
Authors: Nicola Segata, Enrico Blanzieri, Pádraig Cunningham
Venue: Proceedings of the 8th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2009)

Because case-based reasoning (CBR) is instance-based, it is vulnerable to noisy data. Other learning techniques such as support vector machines (SVMs) and decision trees have been developed to be noise-tolerant so a certain level of noise in the data can be condoned. By contrast, noisy data can have a big impact in CBR because inference is normally based on a small number of cases. So far, research on noise reduction has been based on a majority-rule strategy, cases that are out of line with their neighbors are removed. We depart from that strategy and use local SVMs to identify noisy cases. This is more powerful than a majority-rule strategy because it explicitly considers the decision boundary in the noise reduction process. In this paper we provide details on how such a local SVM strategy for noise reduction can be made scale to very large datasets (> 500,000 training samples). The technique is evaluated on nine very large datasets and shows excellent performance when compared with alternative techniques.
Collaborative learning through practices of group cognition
Authors: Gerry Stahl
Venue: Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 1 (2009)

While there is evidence that collaborative learning consists largely of group-level practices, there has been little analysis and description of these processes as such; learning has generally been studied at the individual unit of analysis. Our research, in contrast, focuses on describing the interactional small-group practices that take place in learning contexts. This paper considers these practices and how they work together to form the foundation for effective collaborative learning activities. It analyzes collaborative learning activities in a paradigmatic CSCL setting to discuss such small-group practices as: resolving cognitive conflict, pursuing inquiry, maintaining a group problem space and coordinating multiple modes of reasoning. These have broad implications for foundational issues of temporality, indexicality and group cognition.
Syntactic tree-based relation extraction using a generalization of Collins and Duffy convolution tree kernel
Authors: Mahdy Khayyamian, Seyed Abolghasem Mirroshandel, Hassan Abolhassani
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Student Research Workshop and Doctoral Consortium (2009)

Relation extraction is a challenging task in natural language processing. Syntactic features are recently shown to be quite effective for relation extraction. In this paper, we generalize the state of the art syntactic convolution tree kernel introduced by Collins and Duffy. The proposed generalized kernel is more flexible and customizable, and can be conveniently utilized for systematic generation of more effective application specific syntactic sub-kernels. Using the generalized kernel, we will also propose a number of novel syntactic sub-kernels for relation extraction. These kernels show a remarkable performance improvement over the original Collins and Duffy kernel in the extraction of ACE-2005 relation types.
A self-training approach to cost sensitive uncertainty sampling
Authors: Alexander Liu, Goo Jun, Joydeep Ghosh
Venue: Machine Learning (2009)

Uncertainty sampling is an effective method for performing active learning that is computationally efficient compared to other active learning methods such as loss-reduction methods. However, unlike loss-reduction methods, uncertainty sampling cannot minimize total misclassification costs when errors incur different costs. This paper introduces a method for performing cost-sensitive uncertainty sampling that makes use of self-training. We show that, even when misclassification costs are equal, this self-training approach results in faster reduction of loss as a function of number of points labeled and more reliable posterior probability estimates as compared to standard uncertainty sampling. We also show why other more naive methods of modifying uncertainty sampling to minimize total misclassification costs will not always work well.
Network Access Control Mechanism Based on Locator/Identifier Split
Authors: Tu Rui, Su Jinshu, Chen Feng
Venue: Proceedings of the 2009 IEEE International Conference on Networking, Architecture, and Storage (2009)

Legacy IP address-based access control has met many challenges, because the network nodes cannot be identified accurately based on their variable IP addresses. “Locator/Identifier Split” has made it possible to build a network access control mechanism based on the permanent identifier. With the support of “Locator/Identifier Split” routing and addressing concept, the Identifier-based Access Control (IBAC) makes network access control more accurate and efficient, and fits for mobile nodes’ access control quite well. Moreover, Self-verifying Identifier makes it possible for the receiver to verify the packet sender’s identity without the third part authentication, which greatly reduces the probability of “Identifier Spoofing”.
Internal Resistance Identification in Vehicle Power Lithium-Ion Battery and Application in Lifetime Evaluation
Authors: Xuezhe Wei, Bing Zhu, Wei Xu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

According to the characteristic analysis of lithium-ion power battery, battery accelerate life test is carried out to obtain the relevant conclusions such as the changing trend of battery ohmic resistance in different conditions. Battery ohmic resistance is consequently set up as the Evaluation Index of lifetime. Battery ohmic resistance equivalent model is established aiming at the real-time identification of lithium-ion battery ohmic resistance. Based on this model, the real-time identification is achieved by the experimental collected data and recursive least squares algorithm. The adoption of battery ohmic resistance identification algorithm can be applied to provide some useful reference for the battery life state estimation.
Research on the Architecture and the Components of Semantic Web Application Platform
Authors: Siwei Yu, Hui Dong, Ying Jiang
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

This paper introduces a domain-independent Semantic Web application platform named DOWL, on top of which ontology (OWL) based knowledge retrieval system can be easily set up for any domains. DOWL is an integrated domain Semantic Web solution that consists of several components. The overview of DOWL is presented first in this paper, followed by the introduction of design and realization of each component in DOWL. Finally, case study of the Chinese History domain is discussed, which successfully applies DOWL. DOWL is testified to be a realizable and applicable platform for Semantic Web applications, especially for small domains.
Locally Parallel Textures Modeling with Adapted Hilbert Spaces
Authors: Pierre Maurel, Jean-François Aujol, Gabriel Peyré
Venue: Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (2009)

This article presents a new adaptive texture model. Locally parallel oscillating patterns are modeled with a weighted Hilbert space defined over local Fourier coefficients. The weights on the local Fourier atoms are optimized to match the local orientation and frequency of the texture. We propose an adaptive method to decompose an image into a cartoon layer and a locally parallel texture layer using this model and a total variation cartoon model. This decomposition method is then used to denoise an image containing oscillating patterns. Finally we show how to take advantage of such a separation framework to simultaneously inpaint the structure and texture components of an image with missing parts. Numerical results show that our method improves state of the art algorithms for directional and complex textures.
A Method for Selecting ERP System Based on Fuzzy Set Theory and Analytical Hierarchy Process
Authors: Lan He, Congbo Li
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

Enterprise Resource Planning (ERP) system can significantly improve future competitiveness and performance of a company, but it is also a critical investment and has a high failure probability. Thus, selecting an appropriate ERP system is very important. A method for selecting ERP system is proposed based on fuzzy set theory and analytical hierarchy process (AHP). The evaluation criteria system, including vendor brand, quality, price and service, is constructed, a multi-criteria decision-making model is formulated and the solution process is introduced in detail, that is, AHP is used to identify the weights of the criteria and fuzzy set theory is used to deal with the fuzzification of the criteria. An application example of ERP system selection demonstrates the feasibility of the proposed method.
Web-Based Learning --- Yes We Can!
Authors: Ulrik Schroeder
Venue: Proceedings of the 8th International Conference on Advances in Web Based Learning (2009)

Web-based Learning has become a matter of fact at universities. We are now at the edge of new developments with Web 2.0 applications and social software is radically changing the way of how we communicate and share in social networks. Can we expect an analogous revolution for university education 2.0? I will give some arguments that I rather expect an incremental evolution than a radical change. First, I take a look at current eLearning implementations and organizational frameworks and give an example from RWTH Aachen University. Against the background of cognitive theories the utilization of Web 2.0 applications are promising to strengthen 21st century learning. But methods and tools must be adapted to the context of institutional learning as well as the formal regulations must be adjusted vice versa.
Deinterlacing with Motion-Compensated Anisotropic Diffusion
Authors: Matthias Ghodstinat, Andrés Bruhn, Joachim Weickert
Venue: Statistical and Geometrical Approaches to Visual Motion Analysis: International Dagstuhl Seminar, Dagstuhl Castle, Germany, July 13-18, 2008. Revised Papers (2009)

We present a novel deinterlacing scheme that makes consequent use of discontinuity-preserving partial differential equations (PDEs). It combines the accuracy of recent variational motion estimation techniques with the directional interpolation qualities of anisotropic diffusion filters. Our algorithm proceeds in three steps: First, we interpolate the interlaced images by means of a spatial edge enhancing diffusion process (EED). Then we apply the variational optic flow technique of Brox et al. (2004) in order to obtain a precise interframe registration. Finally we use a spatiotemporal generalisation of EED for motion-compensated inpainting of the missing data in the original sequence. Experiments demonstrate that the proposed method outperforms not only classical deinterlacing schemes, but also a recent PDE-based approach.
Interactivity for Museums: Designing and Comparing Sensor-Based Installations
Authors: Pedro Campos, André Dória, Magno Sousa
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

Technology today provides exciting new possibilities for creating more appealing museum experiences, since we can exploit the surprise factor of innovative interaction styles to create an engaging experience that facilitates the learning process. This research was based on extensive in-site observation as well as surveys conducted at the scene, and it relates to a cultural interactive exhibition titled "Cultural Tourism". The issues were organized around usability problems detected, social interaction and differences between interaction styles, all of which contribute to increasing our knowledge regarding the use of interactive technology as a means to reduce the distance between visitors and cultural heritage.
Coimagination Method: Communication Support System with Collected Images and Its Evaluation via Memory Task
Authors: Mihoko Otake, Motoichiro Kato, Toshihisa Takagi, Hajime Asama
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)

Prevention of dementia is a crucial issue in this aged society. We propose coimagination method for prevention of dementia through supporting interactive communication with images. Coimagination method aims to activate three cognitive functions: episode memory, division of attention, and planning function, which decline at mild cognitive impairment (MCI). Participants of the coimagination program bring images according to the theme and communicate with them. They share feeling rather than memory, which is a major difference between coimagination and reminiscence. They take memory task whether they remember the owner or theme of images after the series of sessions. We held coimagination program successfully at the welfare institution for elderly people in Kashiwa city, Japan. Each session was held one hour per week for five times. The result of the task indicates that the subjects showed empathy with each other. The effectiveness of the proposed method was validated through the experiment.
Context-free parsing through regular approximation
Authors: Mark-Jan Nederhof
Venue: Proceedings of the International Workshop on Finite State Methods in Natural Language Processing (1998)

We show that context-free parsing can be realised by a 2-phase process, relying on an approximated context-free grammar. In the first phase a finite transducer performs parsing according to the approximation. In the second phase, the approximated parses are refined according to the original grammar.