ppxscal/embedding_network huggingface dataset:
User Value Based Product Adaptation: A Case of Mobile Products for Chinese Urban Elderly People
Authors: Jikun Liu, Xin Liu
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

Mobile user experience in Asia is far from optimal. User interfaces and interactions are just copies of those for Western users. Product designers are not clear about the needs of many user segments in Asia. Products lack creative solutions specific for the Asian market, driving researchers to study users in Asia and create new concepts to improve the mobile user experience. Based upon the Industrial Design Value Innovation Theory developed in the Industrial Design Department of Tsinghua University, this project sponsored by the Nokia Research Center targets the market segment of urban elderly people in China, conducts the user research and concept design for proper mobile products or service systems, and hopes to contribute to the corporate future design strategies and market development plans.
Designing International Enterprise Software
Authors: Janaki Kumar, Dan Rosenberg, Paul Hofmann, Michael Arent
Venue: Proceedings of the Symposium on Human Interface 2009 on ConferenceUniversal Access in Human-Computer Interaction. Part I: Held as Part of HCI International 2009 (2009)

This paper provides a framework to understand the various aspects of creating international enterprise software. These aspects could be used to evaluate and prioritize a software product's investment in internationalization. The intended audiences for this paper are user experience designers, product managers and other members of the software development product team, interested in creating world ready enterprise software.
Research of Grid-Similarity-Based Clustering Algorithm
Authors: Chun-jiang Pang
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

Aim at the limitations of traditional measurement method on similitude between objects, we put forward Grid-Similarity-based Clustering Algorithm (GSCA), it brings in a new criterion to measure the similitude between objects. It applies on the grid clustering and disposes the density threshold of grid by the method of density threshold that improves the precision of clustering. Besides, the GSCA algorithm disposes the very high dimension datasets by the technique of entropy. The algorithm appears its advantages in the comparative experiments with some traditional clustering algorithm.
Integrated NLP evaluation system for pluggable evaluation metrics with extensive interoperable toolkit
Authors: Yoshinobu Kano, Luke McCrohon, Sophia Ananiadou, Jun'ichi Tsujii
Venue: Proceedings of the Workshop on Software Engineering, Testing, and Quality Assurance for Natural Language Processing (2009)

To understand the key characteristics of NLP tools, evaluation and comparison against different tools is important. And as NLP applications tend to consist of multiple semi-independent sub-components, it is not always enough to just evaluate complete systems, a fine grained evaluation of underlying components is also often worthwhile. Standardization of NLP components and resources is not only significant for reusability, but also in that it allows the comparison of individual components in terms of reliability and robustness in a wider range of target domains. But as many evaluation metrics exist in even a single domain, any system seeking to aid inter-domain evaluation needs not just predefined metrics, but must also support pluggable user-defined metrics. Such a system would of course need to be based on an open standard to allow a large number of components to be compared, and would ideally include visualization of the differences between components. We have developed a pluggable evaluation system based on the UIMA framework, which provides visualization useful in error analysis. It is a single integrated system which includes a large ready-to-use, fully interoperable library of NLP tools.
S3: A Spectral and Spatial Sharpness Measure
Authors: Cuong T. Vu, Damon M. Chandler
Venue: Proceedings of the 2009 First International Conference on Advances in Multimedia (2009)

This paper presents a block-based algorithm designed to measure the local perceived sharpness in an image. Our method utilizes both spectral and spatial properties of the image: For each block, we measure the slope of the magnitude spectrum and the total spatial variation. These measures are then adjusted to account for visual perception, and then the adjusted measures are combined via a weighted geometric mean. The resulting measure, S3 (Spectral and Spatial Sharpness), yields a perceived sharpness map in which greater values denote perceptually sharper regions. This map can be collapsed into a single index which quantifies the overall perceived sharpness of the whole image. We demonstrate the utility of the S3 measure for within-image and across-image sharpness prediction, for global blur estimation, and for no-reference image quality assessment of blurred images.
Opportunistic flooding in low-duty-cycle wireless sensor networks with unreliable links
Authors: Shuo Guo, Yu Gu, Bo Jiang, Tian He
Venue: Proceedings of the 15th annual international conference on Mobile computing and networking (2009)

Intended for network-wide dissemination of commands, configurations and code binaries, flooding has been investigated extensively in wireless networks. However, little work has yet been done on low-duty-cycle wireless sensor networks in which nodes stay asleep most of time and wake up asynchronously. In this type of network, a broadcasting packet is rarely received by multiple nodes simultaneously, a unique constraining feature that makes existing solutions unsuitable. Combined with unreliable links, flooding in low-duty-cycle networks is a new challenging issue. In this paper, we introduce Opportunistic Flooding, a novel design tailored for low-duty-cycle networks with unreliable wireless links and predetermined working schedules. The key idea is to make probabilistic forwarding decisions at a sender based on the delay distribution of next-hop nodes. Only opportunistically early packets are forwarded using links outside the energy optimal tree to reduce the flooding delay and redundancy in transmission. To improve performance further, we propose a forwarder selection method to alleviate the hidden terminal problem and a link-quality-based backoff method to resolve simultaneous forwarding operations. We evaluate Opportunistic Flooding with extensive simulation and a test-bed implementation consisting of 30 MicaZ nodes. Evaluation shows our design is close to the optimal performance achievable by oracle flooding designs. Compared with improved traditional flooding, our design achieves significantly shorter flooding delay while consuming only 20% ~ 60% of the transmission energy in various low-duty-cycle network settings.
Research on Relationship between Fractal Parameters and Compressive Stress of Metallic Gaskets
Authors: Xiu Feng, Long Wei, Feng Lu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

Metallic gasket seals are widely used in pressure vessels and piping. The failure of sealing systems is mostly caused not by the strength of flanges or bolts but by the leakage of the connections. The topography of sealing surface has a major influence on the leakage of the bolted flange connections. Based on the fractal geometry theory, the fractal characterization of the sealing surface topography of metallic gaskets was studied. The profile curves of metallic gasket surface under different compressive stresses were measured by the AF-LI type stylus profilometer. The fractal dimension, scale coefficient and characteristic length scale of surface profiles were calculated by structure function method. The influence of the compressive stress on the fractal parameters was also analyzed. It’s found that the sealing surfaces of metallic gaskets were fractal, and the fractal dimension and the scale coefficient can be used to characterize the sealing surface topography of metallic gaskets under various compressive stresses. The formulae expressing the relationship between the fractal parameters and the compressive stress were obtained by the regression analysis of the test results. The results are helpful for the study on the sealing performance of metallic gaskets.
Evaluation of Non-photorealistic 3D Urban Models for Mobile Device Navigation
Authors: Christos Gatzidis, Vesna Brujic-Okretic, Maria Mastroyanni
Venue: Proceedings of the 3rd International Conference on Virtual and Mixed Reality: Held as Part of HCI International 2009 (2009)

This research presents a user evaluation study examining the effect different rendering styles of 3D virtual city models, as intended for navigational purposes, could potentially have on users with emphasis on non-photorealistically rendered (NPR) stylizations. The purpose of this experiment is to establish whether, particularly for the application area mentioned above, non-photorealistic, expressive rendering could provide alternative, more effective visual styles than the photorealistic representations of urban areas usually opted for by developers today. 50 participants were exposed to a predominably questionnaire-based study assessing various parameters by observation of the models on a UMPC (Ultra Mobile PC). The results of this research could potentially have significant implications on how future pedestrian navigational software should be visualized in the future.
Examining the Usage and Impact of Transformational M-Banking in Kenya
Authors: Olga Morawczynski
Venue: Proceedings of the 3rd International Conference on Internationalization, Design and Global Development: Held as Part of HCI International 2009 (2009)

Since its introduction in March of 2007, the M-PESA application has acquired a user base of over five million, and an agent network of over five thousand. Because of its rapid growth, the application has received a significant amount of attention. There have been assertions that it can engender transformational benefits by providing the unbanked with new opportunities to access financial services. There is, however, very little discussion of what these transformational benefits are and how they are engendered. This paper will contribute to filling this gap in the literature. It will draw from ethnographic fieldwork that was deployed over a period of fourteen months in two locations--an informal settlement near Nairobi and a farming village in Western Kenya. It will show that the M-PESA application was utilized for the cultivation of livelihood strategies. Such strategies helped residents to cope with (temporarily adjust) and recover from (longer term shifts in livelihood strategies) stresses and shocks. The outcomes of these strategies will also be discussed.
Semi-Lagrangian Runge-Kutta Exponential Integrators for Convection Dominated Problems
Authors: Elena Celledoni, Bawfeh Kingsley Kometa
Venue: Journal of Scientific Computing (2009)

In this paper we consider the case of nonlinear convection-diffusion problems with a dominating convection term and we propose exponential integrators based on the composition of exact pure convection flows. These methods can be applied to the numerical integration of the considered PDEs in a semi-Lagrangian fashion. Semi-Lagrangian methods perform well on convection dominated problems (Pironneau in Numer. Math. 38:309---332, 1982; Hockney and Eastwood in Computer simulations using particles. McGraw-Hill, New York, 1981; Rees and Morton in SIAM J. Sci. Stat. Comput. 12(3):547---572, 1991; Baines in Moving finite elements. Monographs on numerical analysis. Clarendon Press, Oxford, 1994).In these methods linear convective terms can be integrated exactly by first computing the characteristics corresponding to the gridpoints of the adopted discretization, and then producing the numerical approximation via an interpolation procedure.
Dependency parsing by belief propagation
Authors: David A. Smith, Jason Eisner
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

We formulate dependency parsing as a graphical model with the novel ingredient of global constraints. We show how to apply loopy belief propagation (BP), a simple and effective tool for approximate learning and inference. As a parsing algorithm, BP is both asymptotically and empirically efficient. Even with second-order features or latent variables, which would make exact parsing considerably slower or NP-hard, BP needs only O(n3) time with a small constant factor. Furthermore, such features significantly improve parse accuracy over exact first-order methods. Incorporating additional features would increase the runtime additively rather than multiplicatively.
Automatic Image Classification Using the Classification Ant-Colony Algorithm
Authors: Wei-jiu Zhang, Li Mao, Wen-bo Xu
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

To enhance the versatility, robustness, and convergence rate of automatic classification of images, an ant-colony-based classification model is proposed in this paper. According to the characteristics of the image classification, this model adopts and improves the traditional Ant-Colony algorithm. It defines two types of ants that have different search strategies and refreshing mechanisms. The stochastic ants identify new categories, construct the category tables and determine the clustering center of each category. The Intellectual ants classify the image pixels using their search advancing strategies, with the guidance of the information provided by stochastic ants. Comparing with the traditional ant colony algorithms, this algorithm provides a more effective and accurate approach for automatic image classification.
Virtual Sport System for Optimum Exercising Based on a User Model
Authors: Kazumoto Tanaka, Takayuki Kataoka, Makoto Hasegawa
Venue: Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development (2009)

It is said that improving movement habits is effective to solve the problem of obesity. In this paper, we describe a physically interactive computer game system that can control a game mode to let a user maintain an appropriate exercise load based on an estimation of the user's heart rate state. We propose a Bayesian network model that can estimate heart rate states. The model calculates probability distribution of a heart rate state using user's motion features. We also describe an experimental validation of the system.
Semi-supervised Categorization of Wikipedia Collection by Label Expansion
Authors: Boris Chidlovskii
Venue: Advances in Focused Retrieval: 7th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2008, Dagstuhl Castle, Germany, December 15-18, 2008. Revised and Selected Papers (2009)

We address the problem of categorizing a large set of linked documents with important content and structure aspects, for example, from Wikipedia collection proposed at the INEX XML Mining track. We cope with the case where there is a small number of labeled pages and a very large number of unlabeled ones. Due to the sparsity of the link based structure of Wikipedia, we apply the spectral and graph-based techniques developed in the semi-supervised machine learning. We use the content and structure views of Wikipedia collection to build a transductive categorizer for the unlabeled pages. We report evaluation results obtained with the label propagation function which ensures a good scalability on sparse graphs.
Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs
Authors: Huyen Do, Alexandros Kalousis, Melanie Hilario
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

The Support Vector Machine error bound is a function of the margin and radius. Standard SVM algorithms maximize the margin within a given feature space, therefore the radius is fixed and thus ignored in the optimization.We propose an extension of the standard SVM optimization in which we also account for the radius in order to produce an even tighter error bound than what we get by controlling only for the margin.We use a second set of parameters, μ, that control the radius introducing like that an explicit feature weighting mechanism in the SVM algorithm. We impose an l 1 constraint on μ which results in a sparse vector, thus performing feature selection. Our original formulation is not convex, we give a convex approximation and show how to solve it. We experiment with real world datasets and report very good predictive performance compared to standard SVM.
Effects of silver oxalate additions on the physical characteristics of low-temperature-curing MOD silver paste for thick-film applications
Authors: Hong-Ching Lin, Pang Lin, Chun-An Lu, Sea-Fue Wang
Venue: Microelectronic Engineering (2009)

In this paper, the effect of silver oxalate addition on physical characteristics of metallo-organic-decomposition (MOD) silver screen-printable paste for thick film technology was investigated. The addition of silver oxalate in the paste not only produces fresh fine silver particles after curing, but also reduces the decomposition temperature of the lubricant coated on the silver flakes. This is an effective route to provide fine silver particles to the paste without significantly changing the rheological behavior. At the curing temperature of 225^oC, the resistivity decreases from 180.1 to 31.9 @m@W-cm, as the silver oxalate content increases from 0 to 10wt%. This is due to the fact that active silver catalysts produced increase the packing density of silver flakes, and also the removal of lubricant from the surface of silver flakes enhances the electrical conductivity, thereby decreasing the resistance of film.
OutlinAR: an assisted interactive model building system with reduced computational effort
Authors: Pished Bunnun, Walterio W. Mayol-Cuevas
Venue: Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality (2008)

This paper presents a system that allows online building of 3D wire-frame models through a combination of user interaction and automated methods from a handheld camera-mouse. Crucially, the model being built is used to concurrently compute camera pose, permitting extendable tracking while enabling the user to edit the model interactively. In contrast to other model building methods that are either off-line and/or automated but computationally intensive, the aim here is to have a system that has low computational requirements and that enables the user to define what is relevant (and what is not) at the time the model is being built. OutlinAR hardware is also developed which simply consists of the combination of a camera with a wide field of view lens and a wheeled computer mouse.
Highly Oscillatory Problems, 1st edition
Authors: Bjorn Engquist, Athanasios Fokas, Ernst Hairer, Arieh Iserles
Venue: London Mathematical Society Lecture Note Series (2009)

The first book to approach high oscillation as a subject of its own, Highly Oscillatory Problems begins a new dialog and lays the groundwork for future research. It ensues from the six-month program held at the Newton Institute of Mathematical Sciences, which was the first time that different specialists in highly oscillatory research, from diverse areas of mathematics and applications, had been brought together for a single intellectual agenda. This ground-breaking volume consists of eight review papers by leading experts in subject areas of active research, with an emphasis on computation: numerical Hamiltonian problems, highly oscillatory quadrature, rapid approximation of functions, high frequency wave propagation, numerical homogenization, discretization of the wave equation, high frequency scattering and the solution of elliptic boundary value problems.
A Large Margin Classifier with Additional Features
Authors: Xinwang Liu, Jianping Yin, En Zhu, Guomin Zhang, Yubin Zhan, Miaomiao Li
Venue: Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition (2009)

We consider the problem of learning classifiers from samples which have additional features that are absent due to noise or corruption of measurement. The common approach for handling missing features in discriminative models is first to complete their unknown values, and then a standard classification algorithm is employed over the completed data. In this paper, an algorithm which aims to maximize the margin of each sample in its own relevant subspace is proposed. We show how incomplete data can be classified directly without completing any missing features in a large-margin learning framework. Moreover, according to the theory of optimal kernel function, we proposed an optimal kernel function which is a convex composition of a set of linear kernel function to measure the similarity between additional features of each two samples. Based on the geometric interpretation of the margin, we formulate an objective function to maximize the margin of each sample in its own relevant subspace. In this formulation, we make use of the structural parameters trained from existing features and optimize the structural parameters trained from additional features only. A two-step iterative procedure for solving the objective function is proposed. By avoiding the pre-processing phase in which the data is completed, our algorithm could offer considerable computational saving. We demonstrate our results on a large number of standard benchmarks from UCI and the results show that our algorithm can achieve better or comparable classification accuracy compared to the existing algorithms.
Computability of Analytic Functions with Analytic Machines
Authors: Tobias Gärtner, Günter Hotz
Venue: Proceedings of the 5th Conference on Computability in Europe: Mathematical Theory and Computational Practice (2009)

We present results concerning analytic machines, a model of real computation introduced by Hotz which extends the well known Blum, Shub and Smale machines by infinite converging computations. We use the machine model to define computability of complex analytic (i.e. holomorphic) functions and examine in particular the class of analytic functions which have analytically computable power series expansions. We show that this class is closed under the basic analytic operations composition, local inversion and analytic continuation.
Efficient Multiplication of Polynomials on Graphics Hardware
Authors: Pavel Emeliyanenko
Venue: Proceedings of the 8th International Symposium on Advanced Parallel Processing Technologies (2009)

We present the algorithm to multiply univariate polynomials with integer coefficients efficiently using the Number Theoretic transform (NTT) on Graphics Processing Units (GPU). The same approach can be used to multiply large integers encoded as polynomials. Our algorithm exploits fused multiply-add capabilities of the graphics hardware. NTT multiplications are executed in parallel for a set of distinct primes followed by reconstruction using the Chinese Remainder theorem (CRT) on the GPU. Our benchmarking experiences show the NTT multiplication performance up to 77 GMul/s. We compared our approach with CPU-based implementations of polynomial and large integer multiplication provided by NTL and GMP libraries.