ppxscal/embedding_network huggingface dataset:
Managing Complex Augmented Reality Models
Authors: Dieter Schmalstieg, Gerhard Schall, Daniel Wagner, Istvan Barakonyi, Gerhard Reitmayr, Joseph Newman, Florian Ledermann
Venue: IEEE Computer Graphics and Applications (2007)

Mobile augmented reality requires georeferenced data to present world-registered overlays. To cover a wide area and all artifacts and activities, a database containing this information must be created, stored, maintained, delivered, and finally used by the client application. We present a data model and a family of techniques to address these needs.
Adaptive Training of a Kernel-Based Representative and Discriminative Nonlinear Classifier
Authors: Benyong Liu, Jing Zhang, Xiaowei Chen
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Adaptive training of a classifier is necessary when feature selection and sparse representation are considered. Previously, we proposed a kernel-based nonlinear classifier for simultaneous representation and discrimination of pattern features. Its batch training has a closed-form solution. In this paper we implement an adaptive training algorithm using an incremental learning procedure that exactly retains the generalization ability of batch training. It naturally yields a sparse representation. The feasibility of the presented methods is illustrated by experimental results on handwritten digit classification.
A Hybrid Evolutionary Algorithm for Mixed-Integer Nonlinear Bilevel Programming Problems
Authors: Hong Li, Yong-Chang Jiao
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

This paper presents a hybrid evolutionary algorithm to solve mixed-integer nonlinear bilevel programming problems, in which integer decision variables are controlled by an upper-level decision maker and real-value (continuous) decision variables are controlled by a lower-level decision maker. This hybrid evolutionary algorithm contains the mutation operator used in thedifferential evolution, the crossover operator as which theorthogonal experimental design serves, and the migration operator to keep the population's diversity. Simulation results show that the proposed algorithm can find global optimal solutions with less computation burden.
Interactive Fault Localization Techniques in a Spreadsheet Environment
Authors: Joseph R. Ruthruff, Margaret Burnett, Gregg Rothermel
Venue: IEEE Transactions on Software Engineering (2006)

End-user programmers develop more software than any other group of programmers, using software authoring devices such as multimedia simulation builders, e-mail filtering editors, by-demonstration macro builders, and spreadsheet environments. Despite this, there has been only a little research on finding ways to help these programmers with the dependability of the software they create. We have been working to address this problem in several ways, one of which includes supporting end-user debugging activities through interactive fault localization techniques. This paper investigates fault localization techniques in the spreadsheet domain, the most common type of end-user programming environment. We investigate a technique previously described in the research literature and two new techniques. We present the results of an empirical study to examine the impact of two individual factors on the effectiveness of fault localization techniques. Our results reveal several insights into the contributions such techniques can make to the end-user debugging process and highlight key issues of interest to researchers and practitioners who may design and evaluate future fault localization techniques.
EU Assesses Adequacy of US Safe Harbor Privacy Compliance
Authors: Staff
Venue: I-WAYS - The Journal of E-Government Policy and Regulation (2005)

In October 1995 the European Commission approved a Directive (95/46/EC) on the protection of individuals with regard to the processing of personal data and on the free movement of such data. It restricts transfers of personal data from EU Member States to other countries outside the EU where the legal regime does not ensure an adequate level of privacy protection for natural persons. The Commission in July 2000 adopted a Decision (520/2000/EC) that allows transfers of personal data between Europe and the United States. This recognized the Safe Harbor Privacy Principles and Frequently Asked Questions that had been issued by the US Department of Commerce as "providing adequate protection for the purposes of personal data transfers from the EU." As a result, data transfers from EU Member States to US organizations that subscribe to the Principles can take place lawfully insofar as the recipient organizations are deemed to provide an adequate level of privacy protection. This report presents excerpts from the Commission Staff Working Document (SEC (2004) 1323) of October 10, 2004 on the implementation of the Safe Harbor Decision. The full text should be consulted for extensive footnotes. 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
Gathering Precise Patient Medical History with an Ontology-Driven Adaptive Questionnaire
Authors: Matt-Mouley Bouamrane, Alan Rector, Martin Hurrell
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

A thorough documentation of a patient's medical history is widely recognised as providing good indicators of potential intraoperative and postoperative complications. As~preoperative assessment can be time consuming, computer-based Information Collection Systems (ICS) can help free up precious and limited resources, leaving clinicians with more time to fulfil their primary mission of administrating medical care. In addition, medical histories collected by ICSs have proved to be more accurate than traditional pen-and-paper questionnaires or face-to-face interviews. A~challenge remains however in designing questionnaires which are general enough to suit a majority of patients, while at the same time, being able to capture critical individual information. In this paper, we propose a solution to this dilemma with a context-sensitive adaptive information collection system. The proposed method permits to iteratively capture finer-grained information with each successive step, should this information be relevant according to a questionnaire ontology. We argue that the method is robust, scalable and highly configurable. It results in questionnaires which are coherent and well structured and are able to capture enhanced patients' medical histories.
Learning Context-Sensitive Languages from Linear Structural Information
Authors: José M. Sempere
Venue: Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications (2008)

In this work we propose a method to infer context-sensitive languages from positive structural examples produced by linear grammars. Our approach is based on a representation theorem induced by two operations over strings: duplication and reversal. The inference method produces an acceptor device which is an unconventional model of computation based on biomolecules (DNA computing). We prove that a subclass of context-sensitive languages can be inferred by using the representation result in combination with reductions from linear languages to k-testable in the strict sense regular languages.
System and methods for detecting unwanted voice calls
Authors: Ram Dantu
Venue:  (2007)

Voice over IP (VoIP) is a key enabling technology for the migration of circuit-switched PSTN architectures to packet-based IP networks. However, this migration is successful only if the present problems in IP networks are addressed before deploying VoIP infrastructure on a large scale. One of the important issues that the present VoIP networks face is the problem of unwanted calls commonly referred to as SPIT (spam over Internet telephony). Mostly, these SPIT calls are from unknown callers who broadcast unwanted calls. There may be unwanted calls from legitimate and known people too. In this case, the unwantedness depends on social proximity of the communicating parties. For detecting these unwanted calls, I propose a framework that analyzes incoming calls for unwanted behavior. The framework includes a VoIP spam detector (VSD) that analyzes incoming VoIP calls for spam behavior using trust and reputation techniques. The framework also includes a nuisance detector (ND) that proactively infers the nuisance (or reluctance of the end user) to receive incoming calls. This inference is based on past mutual behavior between the calling and the called party (i.e., caller and callee), the callee's presence (mood or state of mind) and tolerance in receiving voice calls from the caller, and the social closeness between the caller and the callee. The VSD and ND learn the behavior of callers over time and estimate the possibility of the call to be unwanted based on predetermined thresholds configured by the callee (or the filter administrators). These threshold values have to be automatically updated for integrating dynamic behavioral changes of the communicating parties. For updating these threshold values, I propose an automatic calibration mechanism using receiver operating characteristics curves (ROC). The VSD and ND use this mechanism for dynamically updating thresholds for optimizing their accuracy of detection.In addition to unwanted calls to the callees in a VoIP network, there can be unwanted traffic coming into a VoIP network that attempts to compromise VoIP network devices. Intelligent hackers can create malicious VoIP traffic for disrupting network activities. Hence, there is a need to frequently monitor the risk levels of critical network infrastructure. Towards realizing this objective, I describe a network level risk management mechanism that prioritizes resources in a VoIP network. The prioritization scheme involves an adaptive re-computation model of risk levels using attack graphs and Bayesian inference techniques. All the above techniques collectively account for a domain-level VoIP security solution.
Patterns for agile development practice part 3 (version 4)
Authors: Joseph Bergin
Venue: Proceedings of the 2006 conference on Pattern languages of programs (2006)

This set of ten patterns is intended to complement the standard wisdom that can be gleaned from the Agile Development literature such as Kent Beck's Extreme Programming Explained[1]. It is directed primarily at those who are starting out with Extreme Programming or another agile methodology and might miss some subtle ideas. Once a team gains experience these patterns will become obvious, but initially some of them are counter intuitive. While this study began in Extreme Programming practice, most of the advice applies to agile development in general. The ten patterns here extend the work of 2004--2006 on the same topic ([3] and [4]). This paper contains some of the standard practices of Extreme Programming as detailed in [1]. We consider XP to be a pattern language in which the practices are the basis of the patterns. They have the characteristics of a true Pattern Language in that they are synergistic and generative. The dozen or so practices detailed in Beck and elsewhere, such as "Do the simplest thing that could possibly work" and "Yesterday's Weather", form a subset of this language. As this "language" is in its early stages of development, there is no significance to the current ordering of the patterns here. This paper presents ten of the one hundred or so patterns developed so far. Many of these patterns are listed briefly in the Thumbnail section at the end.
Gaussian-shaped circularly-symmetric 2D filter banks
Authors: Radu Matei
Venue: Proceedings of the 7th WSEAS International Conference on Signal Processing, Robotics and Automation (2008)

In this paper we propose a class of 2D circularly-symmetric filter banks based on a 1D IIR Gaussian prototype. We approach two cases, namely dyadic and uniform filter banks. The Gaussian prototype is obtained using an efficient rational approximation, namely the Chebyshev-Padé approximation. Then, using a frequency transformation, the corresponding 2D filters with circular symmetry are derived. These filters can be implemented both as digital filters, or in the analog version, using for instance the concept of cellular neural networks, which is detailed in the paper.
Theory-Driven Group Formation through Ontologies
Authors: Seiji Isotani, Riichiro Mizoguchi
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

Group formation plays a critical role in collaborative learning (CL). It affects the acceptance of group activities by learners and the success of the collaborative learning process. Nevertheless, proposing an effective and pedagogically sound group formation is a very complex issue due to the multiple factors that influence group arrangement. The main goal of this paper is to present an ontology that works as a framework based on learning theories that facilitates group formation and CL design. To validate the usefulness and effectiveness of this ontology we present a method to use it and the results of an experiment carried out with four instructors and twenty participants. The results suggest that our ontology can be used adequately and the concepts represented on it can positively affect the performance of individuals during group learning.
The Diffusion of Mobile Data Services in the United States and Korea
Authors: Elizabeth Fife, Francis Pereira, Andrea Vladar, Chung Kim
Venue: Proceedings of the 2008 7th International Conference on Mobile Business (2008)

This paper examines the adoption of mobile data services in the United States and Korea. We use the Global Acceptance of Technology model to analyze consumer behavior according to cultural and sociodemographicfactors, mediated by the influence of technology-related factors. Using primary data collected from a recent survey of U.S. and Korean users, we find that higher rates of usage for a variety of mobile data services in Korea compared to usage in the United States can be partiallyexplained by social and cultural differences between the two countries. Interestingly, despite identifiable differences in cultural and social norms we find many similarities in perceptions and preferences for mobile data services in the two markets. From this data we also analyze willingness to pay for mobile data services andagain find marked similarities between U.S. and Korean consumers.
Roles of a Talking Head in a Cooperative Human-Robot Dialogue System
Authors: Mary Ellen Foster
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

The JAST human-robot dialogue system [1] is designed as a platform to integrate empirical findings on cognition and cooperative dialogue with research on autonomous robots by supporting multimodal human-robot collaboration on a construction task. The robot consists of a pair of mechanical arms with grippers, mounted in a position to resemble human arms, and a Philips iCat animatronic talking head [2]. The user and the robot work together to assemble construction toys on a common work area, coordinating their actions through speech, gestures, and facial displays.
Using BlueJ to Introduce Programming
Authors: Michael Kölling
Venue: Reflections on the Teaching of Programming: Methods and Implementations (2008)

This chapter describes the BlueJ system. The discussion includes both the software tool aspects of BlueJ, as well as pedagogical approaches that should be considered when teaching with BlueJ. Pedagogical changes that have been suggested go deeper than merely introducing a new software tool: they include changes to a more software-engineering-oriented course, removal of considerable chunks of traditional material, and the introduction of new skills and approaches. We discuss experiences of using the system over eight years at various institutions, and discuss successes and failures as seen retrospectively today.
Magneto-thermal-stress analysis of induction heating devices
Authors: Ion Cârstea, Daniela Cârstea, Alexandru Adrian Cârstea
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

In analysis of the induction heating devices a coupled model is used for an accurate numerical simulation. The magnetic field, eddy currents, temperature change and stress are phenomena that coexist in the same geometry and interact so that the mathematical models for these fields must be solved simultaneously. The stresses are determined by the sum of magnetic stress caused by Lorentz force and thermal stress caused by eddy current loss. A numerical model based on the finite element method is presented. As target example we consider a conducting solid circular hollow cylinder. Assuming that a coil generates a sinusoidal magnetic field, we analyse the interaction of the magnetic and mechanical behaviour of the device with emphasis on numerical algorithms for the numerical simulation of the induction devices.
Noise-Insensitive Digital BIST for any PLL or DLL
Authors: Stephen Sunter, Aubin Roy
Venue: Journal of Electronic Testing: Theory and Applications (2008)

PLLs are the heart of most SoCs, so their performance affects many tests. Practical, published PLL BIST approaches cannot measure <10 ps RMS jitter or >1 GHz. This paper describes how a SerDes undersampling DFT technique was adapted to test multiple PLLs and DLLs for jitter, phase error, output frequency, duty cycle, lock time, and lock range. Two techniques for cancelling random and systematic noise are also described. The multi-GHz range, sub-picosecond jitter noise floor, and minimal silicon area are better than for any previous silicon-proven DFT or BIST that needs no calibration or analog circuitry. FPGA implementation results are provided.
Preservation of Evidence in Case of Online Gaming Crime
Authors: Patrick S. Chen, Cheng-Yu Hung, Chiao-Hsin Ko, Ying-Chieh Chen
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

Along with the rapid growth of network applications and digital contents, online gaming has become a very successful industry in recent years. It not only brings tremendous business opportunities but also attracts marvelous customers to be online players. However, due to the lack of virtual property protection and related information security schemes, more and more players have violated the law because of its real world profit. Unfortunately, online gaming crime has turned out one of the most serious cybercrimes in many countries, such as in Taiwan, South Korea, China, and so on. In order to solve this judicial problem and effectively protect virtual property, we propose a Virtual Property Description Language (VPDL) as the syntax to record and express virtual property. There are six models, including Identity Model, Ownership Model, Trading Model, Content Model, Revocation Model, and Security Model. It can effectively protect virtual property and strengthen the competence of digital evidence by recording the legal source, ownership, trading track, and handling of virtual properties so as to lower the cases of online gaming crime. The online gaming companies may use it in the aspects of virtual property management, tracing historic records and collecting legal digital evidence, while the existing system mechanism of online game doesn't need to be changed.
Symbolic Memory of Motion Patterns by an Associative Memory Dynamics with Self-organizing Nonmonotonicity
Authors: Hideki Kadone, Yoshihiko Nakamura
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

We previously proposed a memory system of motion patterns [4] using an assotiative memory model. It forms symbolic representations of motion patterns based on correlations by utilizing bifurcations of attractors depending on the parameter of activation nonmonotonicity. But the parameter had to be chosen appropreately to some degree by manual. We propose here a way to provide the paremeter with self-organizing dynamics along with the retrieval of the associative momory. Attractors of the parameter are discrete states representing the hierarchical correlations of the stored motion patterns.
A Unified View of Objective Interestingness Measures
Authors: Céline Hébert, Bruno Crémilleux
Venue: Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition (2007)

Association rule mining often results in an overwhelming number of rules. In practice, it is difficult for the final user to select the most relevant rules. In order to tackle this problem, various interestingness measures were proposed. Nevertheless, the choice of an appropriate measure remains a hard task and the use of several measures may lead to conflicting information. In this paper, we give a unified view of objective interestingness measures. We define a new framework embedding a large set of measures called SBMs and we prove that the SBMs have a similar behavior. Furthermore, we identify the whole collection of the rules simultaneously optimizing all the SBMs. We provide an algorithm to efficiently mine a reduced set of rules among the rules optimizing all the SBMs. Experiments on real datasets highlight the characteristics of such rules.
Numerical Analysis and Risk Assessment on Face Stability of Large-Diameter Tunnels
Authors: Qunfang Hu, Hongwei Huang
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

For the two types of shield tunneling such as Slurry and EPB shield the stability of tunnel face depends on the prevailing support pressure. The support pressure at the tunnel face has to be applied to a value that gives as well sufficient safety against a collapse of the tunnel face as the against uplifting. The paper aims at a better understanding of the mechanics of face failure for those lager-diameter tunnels. And some different determination methods of the applied support pressure are compared and given a risk assessment, which are illustrated their application by numerical analysis in the Yangtze River Tunnel of Shanghai.
Secure and efficient beaconing for vehicular networks
Authors: Frank Kargl, Elmar Schoch, Björn Wiedersheim, Tim Leinmüller
Venue: Proceedings of the fifth ACM international workshop on VehiculAr Inter-NETworking (2008)

The basis for many VANET applications are periodic beacons carrying information like location, heading and speed. In order to secure beaconing, messages should be signed and carry a certificate to attest valid network participants. In order to reduce the significant communication and computational overhead created by this, we propose to skip signatures or certificates in certain situations.
Praise, Blame, Obligation, and Beyond: Toward a Framework for Classical Supererogation and Kin
Authors: Paul Mcnamara
Venue: Proceedings of the 9th international conference on Deontic Logic in Computer Science (2008)

Continuing prior work ([1, 2]), I integrate a simple system for personal obligation with a system for aretaic (agent-evaluative) appraisal. I then explore various relationships between definable aretaic statuses such as praiseworthiness and blameworthiness and deontic statuses such as obligatoriness and impermissibility. I focus on partitions of the normative statuses generated (cf. "normative positions" but without explicit representation of agency). In addition to representing and exploring traditional questions in ethical theory about the connection between blame, praise, permissibility and obligation, this allows me to carefully represent schemes for supererogation and kin. These controversial concepts have provided challenges to both ethical theory and deontic logic, and are among deontic logic's test cases.