ppxscal/embedding_network huggingface dataset:
Bipartite Biotokens: Definition, Implementation, and Analysis
Authors: W. J. Scheirer, T. E. Boult
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Cryptographic transactions form the basis of many common security systems found throughout computer networks. Supporting these transactions with biometrics is very desirable, as stronger non-repudiation is introduced, along with enhanced ease-of-use. In order to support such transactions, some sort of secure template construct is required that, when re-encoded, can release session specific data. The construct we propose for this task is the bipartite biotoken. In this paper, we define the bipartite biotoken, describe its implementation for fingerprints, and present an analysis of its security. No other technology exists with the critical reissue and secure embedding properties of the bipartite biotoken. Experimental results for matching accuracy are presented for the FVC 2002 data set and imposter testing on 750 Million matches.
A Mechano-Chemical Model of a Solid Tumor for Therapy Outcome Predictions
Authors: Sven Hirsch, Dominik Szczerba, Bryn Lloyd, Michael Bajka, Niels Kuster, Gábor Székely
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

Experimental investigations of tumors often result in data reflecting very complex underlying mechanisms. Computer models of such phenomena enable their analysis and may lead to novel and more efficient therapy strategies. We present a generalized finite element mechano-chemical model of a solid tumor and assess its suitability for predicting therapy outcome. The model includes hosting tissue, tumor cells (vital and necrotic), nutrient, blood vessels and a growth inhibitor. At a certain time instant of the tumor development virtual therapies are performed and their outcomes are presented. The model is initiated with parameters either obtained directly from the available literature or estimated using multi-scale modeling. First results indicate the usefulness of multi-physics tumor models for predicting therapy response. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Mobility, Skills, and the Michigan Non-Compete Experiment
Authors: Matt Marx, Deborah Strumsky, Lee Fleming
Venue: Management Science (2009)

Whereas a number of studies have considered the implications of employee mobility, comparatively little research has considered institutional factors governing the ability of employees to move from one firm to another. This paper explores a legal constraint on mobility---employee non-compete agreements---by exploiting Michigan's apparently inadvertent 1985 reversal of its non-compete enforcement policy as a natural experiment. Using a differences-in-differences approach, and controlling for changes in the auto industry central to Michigan's economy, we find that the enforcement of non-competes indeed attenuates mobility. Moreover, non-compete enforcement decreases mobility more sharply for inventors with firm-specific skills and for those who specialize in narrow technical fields. The results speak to the literature on employee mobility while offering a credibly exogenous source of variation that can extend previous research on the implications of such mobility.
How are web characteristics evolving?
Authors: João Miranda, Daniel Gomes
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

The Web is a hypertextual environment in permanent evolution. There are new technologies and Web publishing behaviors emerging everyday. This study presents trends on the evolution of the Web, derived from the comparison of two characterizations of a web portion performed within a 5 year interval. The Portuguese Web was used as a case study. Several metrics regarding content and site characteristics were analyzed.
Introduction to computational advertising
Authors: Evgeniy Gabrilovich, Vanja Josifovski, Bo Pang
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Tutorial Abstracts (2008)

Web advertising is the primary driving force behind many Web activities, including Internet search as well as publishing of online content by third-party providers. Even though the notion of online advertising barely existed a decade ago, the topic is so complex that it attracts attention of a variety of established scientific disciplines, including computational linguistics, computer science, economics, psychology, and sociology, to name but a few. Consequently, a new discipline --- Computational Advertising --- has emerged, which studies the process of advertising on the Internet from a variety of angles. A successful advertising campaign should be relevant to the immediate user's information need as well as more generally to user's background and personalized interest profile, be economically worthwhile to the advertiser and the intermediaries (e.g., the search engine), as well as be aesthetically pleasant and not detrimental to user experience.
Hybrid Learning Enhancement of RBF Network Based on Particle Swarm Optimization
Authors: Sultan Noman Qasem, Siti Mariyam Shamsuddin
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

This study proposes RBF Network hybrid learning with Particle Swarm Optimization for better convergence, error rates and classification results. In conventional RBF Network structure, different layers perform different tasks. Hence, it is useful to split the optimization process of hidden layer and output layer of the network accordingly. RBF Network hybrid learning involves two phases. The first phase is a structure identification, in which unsupervised learning is exploited to determine the RBF centers and widths. The second phase is parameters estimation, in which supervised learning is implemented to establish the connections of weights between the hidden layer and the output layer. The incorporation of PSO in RBF Network hybrid learning is accomplished by optimizing the centers, the widths and the weights of RBF Network. The results for training, testing and validation on dataset illustrate the effectiveness of PSO in enhancing RBF Network learning.
The Flood, the Channels and the Dykes: Managing Legal Information in a Globalized and Digital World
Authors: Joost Breuker, Pompeu Casanovas, Michel C. A. Klein, Enrico Francesconi
Venue: Proceeding of the 2009 conference on Law, Ontologies and the Semantic Web: Channelling the Legal Information Flood (2009)

Information search and retrieval are part of daily routines of the legal profession. Lawyers, judges, prosecutors, and legal clerks usually access a number of electronic resources to browse, search, select, or update legal contents. Legal databases have currently become large digital libraries where the tasks related to information-seeking may sometimes be cumbersome. Adding semantics to support information search may provide significant results in terms of efficiency, efficacy, and user satisfaction. Semantic technologies may be able to improve legal information search in the judicial and lawyers' domains. However, legal professionals sometimes prefer following routines than changing their information search behavior. New trends in legal ontologies and Semantic Web technologies may help to improve both professional and laymen's skills.
Storage class memory: technology, systems and applications
Authors: Richard F. Freitas
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

Storage Class Memory (SCM) is the term used to describe a new class of solid-state, nonvolatile memory technologies. There are several (≥10) such technologies currently under active research and development that are vying to become the SCM of choice. As a group, their performance is nearer memory than storage while their cost is nearer storage than memory. In the systems designer's eye, these performance and cost characteristics blur the historic distinction between memory and storage. Exploiting SCM will require significant changes in the design of memory and storage systems. These changes at the system level will force or enable changes at the application level as well as opening up new application opportunities. In this talk we will discuss several of today's leading SCM technologies, discuss their potential impact on the design of memory and storage systems, consider the changes that might be needed to existing applications and explore some of the potential opportunities for future applications.
A Minimal Contouring Approach to the Computation of the Reeb Graph
Authors: Giuseppe Patanè, Michela Spagnuolo, Bianca Falcidieno
Venue: IEEE Transactions on Visualization and Computer Graphics (2009)

Given a manifold surface {\cal M} and a continuous scalar function f:{\cal M}\rightarrow {\hbox{\rlap{I}\kern 2.0pt{\hbox{R}}}}, the Reeb graph of ({\cal M},f) is a widely used high-level descriptor of {\cal M} and its usefulness has been demonstrated for a variety of applications, which range from shape parameterization and abstraction to deformation and comparison. In this context, we propose a novel contouring algorithm for the construction of a discrete Reeb graph with a minimal number of nodes, which correspond to the critical points of f (i.e., minima, maxima, and saddle points) and its level sets passing through the saddle points. In this way, we do not need to sample, sweep, or increasingly sort the f-values. Since most of the computation uses only local information on the mesh connectivity, equipped with the f-values at the surface vertices, the proposed approach is insensitive to noise and requires a small-memory footprint and temporary data structures. Furthermore, we maintain the parametric nature of the Reeb graph with respect to the input scalar function and we efficiently extract the Reeb graph of time-varying maps. Indicating with n and s the number of vertices of {\cal M} and saddle points of f, the overall computational cost O(sn) is competitive with respect to the O(n\,\log \,n) cost of previous work. This cost becomes optimal if {\cal M} is highly sampled or s\le \log n, as it happens for Laplacian eigenfunctions, harmonic maps, and one-forms.
Semisupervised Multitask Learning
Authors: Qiuhua Liu, Xuejun Liao, Hui Li Carin, Jason R. Stack, Lawrence Carin
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

Context plays an important role when performing classification, and in this paper we examine context from two perspectives. First, the classification of items within a single task is placed within the context of distinct concurrent or previous classification tasks (multiple distinct data collections). This is referred to as multi-task learning (MTL), and is implemented here in a statistical manner, using a simplified form of the Dirichlet process. In addition, when performing many classification tasks one has simultaneous access to all unlabeled data that must be classified, and therefore there is an opportunity to place the classification of any one feature vector within the context of all unlabeled feature vectors; this is referred to as semi-supervised learning. In this paper we integrate MTL and semi-supervised learning into a single framework, thereby exploiting two forms of contextual information. Example results are presented on a "toy" example, to demonstrate the concept, and the algorithm is also applied to three real data sets.
Can we learn a template-independent wrapper for news article extraction from a single training site?
Authors: Junfeng Wang, Chun Chen, Can Wang, Jian Pei, Jiajun Bu, Ziyu Guan, Wei Vivian Zhang
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Automatic news extraction from news pages is important in many Web applications such as news aggregation. However, the existing news extraction methods based on template-level wrapper induction have three serious limitations. First, the existing methods cannot correctly extract pages belonging to an unseen template. Second, it is costly to maintain up-to-date wrappers for a large amount of news websites, because any change of a template may invalidate the corresponding wrapper. Last, the existing methods can merely extract unformatted plain texts, and thus are not user friendly. In this paper, we tackle the problem of template-independent Web news extraction in a user-friendly way. We formalize Web news extraction as a machine learning problem and learn a template-independent wrapper using a very small number of labeled news pages from a single site. Novel features dedicated to news titles and bodies are developed. Correlations between news titles and news bodies are exploited. Our template-independent wrapper can extract news pages from different sites regardless of templates. Moreover, our approach can extract not only texts, but also images and animates within the news bodies and the extracted news articles are in the same visual style as in the original pages. In our experiments, a wrapper learned from 40 pages from a single news site achieved an accuracy of 98.1% on 3,973 news pages from 12 news sites.
Estimation of dynamic parameters of cardiac ventricles
Authors: YiQiang Xu, Qiu Guan, S. Y. Chen
Venue: Proceedings of the 10th WSEAS international conference on Mathematics and computers in biology and chemistry (2009)

This paper presents an approach to quantitative analysis of cardiac ventricular motions, which defines a new parameter named movement extents of myocardium, based on the point distribution model, to describe local cardiac motions. The algorithm finds the motion path of key points in a cardiac cycle via spline interpolation and the result is used to estimate their velocity and acceleration. Therefore, movement of key points is recovered throughout the cardiac cycle between time intervals to estimate the parameters of heart (including radial velocity, radial acceleration and cardiac stress and strain). We estimate these parameters by experiments to judge whether the motion area is driven with the other area. If the motion of the area is larger than adjacent area or less than the others, this area can be distinguished from normal ones.
Domain-Dependent View of Multiple Robots Path Planning
Authors: Pavel Surynek
Venue: Proceeding of the 2008 conference on STAIRS 2008: Proceedings of the Fourth Starting AI Researchers' Symposium (2008)

We study a problem of path planning for a group of robots in this paper. The problem is stated as a finding of spatial-temporal paths through which the robots can go from their initial locations to the given goal locations in a certain environment. The robots must subordinate to a variety of physical constraints. The most important constraints from our point of view are that the robots must avoid obstacles and they must avoid each other. Both of these two constraints can be captured by a model where the environment is modeled as an undirected graph. Vertices of this graph represent possible locations for the robots and edges represent possible transitions between locations. The robots are located in the vertices of the graph. Each vertex can be occupied by at most one robot. A robot can move to the neighboring unoccupied vertex. The main result of the paper is the description of a class of the problem for which a polynomial time solving algorithm exists. We also present an experimental evaluation in which we tested the ability of several state-of-the-art planners to solve the problem.
Short-Term Capital Flows in China: Trend, Determinants and Policy Implications
Authors: Haizhen Yang, Yanping Zhao, Yujing Ze
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

The volatility of international capital flows have further increased both in volume and speed since the outbreak of subprime crisis originating from America. Orientation of international capital flows blurred because of the downward expectation on the growth rate in main countries. Since the short-term capital flow has gradually become an important part of international capital flow in China in decade, the volatility of short-term capital flows may affect the development of Chinese economy severely. A structural model-VECM was build to explore the determinants of net flows of short-term capital in China. The conclusions of this study were that net flows in China are largely determined by estate price, circulated stock value, expectation on exchange rate and interest rate. On that basis, some policy suggestions were proposed.
Fabrication and characterization of surface micromachined stacked transformer on glass substrate
Authors: Jumril Yunas, Azrul Azlan Hamzah, Burhanuddin Yeop Majlis
Venue: Microelectronic Engineering (2009)

On-chip micro-transformer with square interwinding coil has been developed. The transformer consists of stacked spiral coil which is fabricated on high resistive glass substrate using MEMS technology. The device is fabricated using simple surface micromachining process including an additional bonding process for integration purpose. The performance of the micro-transformer is illustrated through low and high frequency measurements and compared with conventional Si-based micro-transformer. The results show that the RF performance of the glass-based transformer is improved compared to that of silicon-based transformer highlighting a good prospect for the future 3-dimensional RF-MEMS device application.
Sun Seeking: Interactive Story-Reading Through Different Media
Authors: Hilary Smith, Rose Luckin, Danaë Stanton Fraser, Lisa Williams, Andreas Duenser, Eva Hornecker, Adrian Woolard, Brendan Lancaster
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

This poster introduces two pilot studies on children's story reading and retelling using interactive media that move beyond familiar keyboard and mouse interaction. These studies formed a subset of investigations into the potential for Augmented Reality (AR) story books to engage and motivate story reading using familiar and easy to set-up technologies. We contrasted AR with two other media and report initial findings that point towards the memorability and potential for engagement of these different media, concluding with our further research questions.
CellMigration System
Authors: Lynda Dib, Zahia Guessoum, Mohamed T. Laskri
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

The migration of cells is an abnormal behaviour conditioned by the detection of certain factors in the environment that lead to the dissociation of the cellular links (communicating junctions).This behaviour drives to a migratory state of cells which can lead to cancer. We have thus developed a new agent-based tool for modelling and studying the emergent behaviour resulting from the interaction of cells in their tissue. This tool (named CellMigration) is realized under a multi-agent platform (named DIMA). CellMigration allows to model and to simulate the safe behaviour, the tumoral behaviour and the migratory behaviour. We first describe CellMigration. Results are then presented to validate and analysed to validate the realized simulations.
A global model for virtual educational system
Authors: Daniel Hunyadi, Iulian Pah, Dan Chiribuca
Venue: WSEAS Transactions on Information Science and Applications (2009)

This paper present a virtual educational environment model which makes learning easier by using collaboration (and extension, team-research model) as a form of social interplay. The model represents a universe where human agents interact with artificial agents (software agents). Considering the vision of the system, it can be classified among advanced systems for it is client-oriented (student) and provides value added educational services, due to the collaborative learning attribute. The model proposes an original architecture where elements of the socio-cultural theory of collaborative learning are assigned to the artificial intelligence components (the multi-agent system). The expected results are: conceptual models (agents, learning and teaching strategies, student profiles and group profiles, communication between agents, negotiation strategies and coalition formation), software entities, and a methodology to evaluate the performance of eLearning systems.
Measurement of Airflow of Air-Conditioning in a Car with PIV
Authors: J. H. Yang, S. Kato, H. Nagano
Venue: Journal of Visualization (2009)

In the present study, a model experiment is performed in order to clarify the airflow characteristics of a car cabin. In addition, this study provides high precision data for a benchmark test using the CFD (Computational Fluid Dynamics) analysis method. Initially, the study focuses on the ventilation mode that describes the flow field in the car cabin obtained from an experiment with PIV. The car cabin model is made of transparent acrylic resin and measures 1,450 mm &times; 700 mm &times; 900 mm, almost half the size of a real car, and was installed in a thermostatic chamber. In the experiment, the cabin model was controlled by an orifice tube and a pressure gauge in order to confirm the airflow rate. The PIV measurement was performed at a total of 18 regions within the section. The analyzed PIV data provides the mean velocity profile, the standard deviation distribution and the turbulence intensity distribution at each region.
New method for wastewater pre-treatment in the sewage system
Authors: Diana Robescu, Raluca Mocanu, Dan Robescu
Venue: Proceedings of the 10th WSEAS international conference on Mathematics and computers in biology and chemistry (2009)

The paper presents a new method, currently unused, for the practical application of the sewage network as a wastewater pre-treatment stage. This can be achieved by using alternative aeration systems along the sewage system, which lead to alternative aerobic and anaerobic areas and allow the development of the biological processes. The microorganisms that occurred partially decompose the organic pollutants from the wastewater in the sewage system. Besides the rationally and efficiently used of the sewage system for facilitating the operation of the wastewater treatment plant, another important advantage is the modified gaseous medium that lead to quickly and safety interventions of the operators in the sewage network, without danger. In this paper the mathematical model and numerically simulations are presented, which were done to obtain the optimum horizontally distribution of aeration equipment in aerobic zones and the optimum length of aerobic and anaerobic zones. It was found that the removing of the organic substances was around 15-17% using this method on 10 kilometers of the sewage system.
Normative Systems: the meeting point between Jurisprudence and Information Technology?A position paper
Authors: Luigi Logrippo
Venue: Proceeding of the 2007 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the sixth SoMeT_07 (2007)

It is argued that there are many concepts and methods in common between policy systems used in Information Technology and Jurisprudence, i.e. legal theory. These concepts are found in the research area of 'normative systems' which encompasses them and provides a framework for unifying research. It is further argued that advantages can be accrued to both research areas by favoring interchanges of methods and principles in this unifying framework. A distinction is made between norms in rule style and norms in requirements style. Issues of completeness, consistency and conflicts are considered. Concepts that are useful in this research area include defeasible logic and ontologies. Useful tools are theorem provers and model checkers.