ppxscal/embedding_network huggingface dataset:
A calendar based Internet content pre-caching agent for small computing devices
Authors: Andreas Komninos, Mark D. Dunlop
Venue: Personal and Ubiquitous Computing (2008)

We described in earlier publications the principles of a system where Internet content would be pre-cached, based on contextual information obtained from a user's electronic calendar. The model for such a system envisioned a set of cooperating agents, distributed on a user's desktop and mobile device, which would be responsible for making decisions on the context and preferences of the user, and downloading the relevant internet content through a land-based broadband connection and storing it on the mobile device. This paper presents and discusses established pre-caching techniques and their suitability for use on mobile information access scenarios. It proceeds in describing the implementation details of an alternative approach, a calendar-based pre-caching system and presents the findings of tests that were made with human subjects on such a system.
The Quest for Multi-headed Worms
Authors: Van-Hau Pham, Marc Dacier, Guillaume Urvoy-Keller, Taoufik En-Najjary
Venue: Proceedings of the 5th international conference on Detection of Intrusions and Malware, and Vulnerability Assessment (2008)

In [6], Pouget et al. have conjectured the existence of so-called multi-headed worms and found a couple of them on attack traces collected on a single honeypot. These worms take advantage of several distinct attack techniques to propagate but they use only one of them against a given target. From a victim's viewpoint, they are therefore indistinguishable from the other classical worms that always propagate using the same attack vector or same sequence of attack vectors. This paper aims at confirming the existence of these worms by studying a very large dataset. The validation process led to three important contributions. First, we establish the existence and assess the importance of three distinct classes of attacks seen in the wild. Second, we propose a new method to correlate attack traces time series and apply it to search for multi-headed worms. Third, we offer and discuss results of the analysis of 15 months of data gathered over 28 different platforms located all over the world.
Regularized Discriminative Direction for Shape Difference Analysis
Authors: Luping Zhou, Richard Hartley, Lei Wang, Paulette Lieby, Nick Barnes
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

The "discriminative direction" has been proven useful to reveal the subtle difference between two anatomical shape classes. When a shape moves along this direction, its deformation will best manifest the class difference detected by a kernel classifier. However, we observe that such a direction cannot maintain a shape's "anatomical" correctness, introducing spurious difference. To overcome this drawback, we develop a regularized discriminative direction by requiring a shape to conform to its population distribution when it deforms along the discriminative direction. Instead of iterative optimization, an analytic solution is provided to directly work out this direction. Experimental study shows its superior performance in detecting and localizing the difference of hippocampal shapes for sex. The result is supported by other independent research in the same domain.
On Selecting an Algorithm for Fuzzy Optimization
Authors: Elizabeth Untiedt, Weldon Lodwick
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

Formulations for fuzzy and possibilistic optimization abound in the literature, but few are implemented in practice. This paper investigates the theory, semantics, and efficacy of a selection of significant fuzzy and possibilistic optimization algorithms via their application to a well-known large-scale problem: the radiation therapy planning problem. The algorithms are compared, critiqued, and organized with the following objective in mind: to guide a decision maker in the selection and implementation of a fuzzy or possibilistic optimization algorithm.
A Fast 2-Approximation Algorithm for the Minimum Manhattan Network Problem
Authors: Zeyu Guo, He Sun, Hong Zhu
Venue: Proceedings of the 4th international conference on Algorithmic Aspects in Information and Management (2008)

Given a set T of n points in ¿2, a Manhattan Network G is a network with all its edges horizontal or vertical segments, such that for all p,q ¿ T, in G there exists a path (named a Manhattan path) of the length exactly the Manhattan distance between p and q. The Minimum Manhattan Network (MMN) problem is to find a Manhattan network of the minimum length, i.e., the total length of the segments of the network is to be minimized. In this paper we present a 2-approximation algorithm with time complexity O(n 2), which improves the 2-approximation algorithm with time complexity ¿(n 8), proposed by Chepoi, Nouioua et al.. To the best of our knowledge, this is the best result on this problem.
Ontology Guided Evolution of Complex Embedded Systems Projects in the Direction of MDA
Authors: Lars Pareto, Miroslaw Staron, Peter Eriksson
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

Implementation of MDA in large, product developing organizations involves changing processes, practices, tools, and communication infrastructures. The paper presents a case study, in which modeling related needs of a unit within Ericsson were compared to features of current and envisioned MDA tools, using qualitative methods. The paper's main contribution is an ontology defining areas and sub-areas of improvement associated with the introduction of MDA in complex embedded systems projects. The ontology is grounded in interviews with senior modellers at Ericsson and in survey publications from within the field of MDA. It identifies 26 improvement areas concerned with model content, modeling activities, and the management of modeling projects. The ontology has been presented to stakeholders within the unit studied, with positive feedback: appreciated were its groundedness, traceability, holistic scope, and potential as platform and checklist for several recurrent analysis and communication tasks related to software process improvement within Ericsson.
A Qualitative Analysis on Collaborative Learning Experience of Student Journalists Using Wiki
Authors: Will Wai Ma, Allan Hoi Yuen
Venue: Proceedings of the 1st international conference on Hybrid Learning and Education (2008)

Education in journalism emphasizes internships, apprenticeships, and other opportunities to learn journalism by doing journalism; however, most computer-mediated communication tools do not have such a provision. The fully open structure of Wiki matches the principles of learning journalism while, from a technical point of view, Wiki provides a very easy way for users to report, write and edit. In a case study, a group of undergraduate journalism students were exposed to a student-written Wiki to jointly compose news reporting. Analysis of student journalists' responses to the open-ended questions revealed revision as the core processing capability of Wiki. The motivational factors to revision include accuracy (fact checking), story enrichment, and personal interest toward the news topic. In addition, learners are also affected by the social interactions among the community users within Wiki. The qualitative data shows students both value the process and face challenges in managing the complexity of shared editing.
Autonomous underwater vehicle (auv) path planning and adaptive on-board routing for adaptive rapid environmental assessment
Authors: Henrik Schmidt, Pierre Lermusiaux
Venue:  (2007)

In shallow water, a large part of underwater acoustic prediction uncertainties are induced by sub-meso-to-small scale oceanographic variabilities. Conventional oceanographic measurements for capturing such ocean-acoustic environmental variabilities face the classical conflict between resolution and coverage. The Adaptive Rapid Environmental Assessment (AREA) project was proposed to resolve this conflict by optimizing the location of in-situ measurements in an adaptive manner. In this thesis, ideas, concepts and performance limits in AREA are clarified. Both an engineering and a mathematical model for AREA are developed. A modularized AREA simulator was developed and implemented in C++. Philosophies in AREA are discussed. Presumptions about the ocean are made to bridge the gap between the viewpoint in the oceanography community, where the ocean environment is considered to be a deterministic but very complicated system, and that of the underwater acoustic community, where the ocean environment is treated as a random system. At present, how to optimally locate the in-situ measurements made by a single AUV carrying a CTD (conductivity, temperature and depth) sensor is considered in AREA. In this thesis, the AUV path planning is modeled as a Shortest Path problem. However, due to the sound velocity correlation effect, the size of tins problem can be very large. A method is developed to simplify the graph for a fast solution. As a significant step, a linear approximation for acoustic Transmission Loss (TL) is investigated numerically and analytically. In addition to following a predetermined path, an AUV can also adaptively generate its path on-board. This adaptive on-board AUV routing problem is modeled using Dynamic Programming (DP) in this thesis. A method based on an optimized predetermined path is developed to reduce the size of the DP problem and approximately yet efficiently solve it using Pattern Recognition. As a special case, a thermocline-oriented AUV yoyo control and control parameter optimization methods for AREA are also developed. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Person Identification Based on Barefoot 3D Sole Shape
Authors: Michael Hild
Venue: Proceedings of the 2nd international workshop on Computational Forensics (2008)

In this paper we report on person identification based on the three-dimensional shape of the human foot sole. After acquisition of 3D foot sole data with a laser scanner, data normalization is performed and person identification is carried out using principal component analysis (PCA) and linear discriminant analysis (LDA) in conjunction with 1---NN classification, and support vector machines (SVM) in conjunction with output value thresholding. The obtained high identification and rejection rates indicate that the 3D foot sole shape of the human bare foot is adequate for person identification.
An Incremental Learning Algorithm Based on Rough Set Theory
Authors: Yinghong Ma, Yehong Han
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

A decision table is a pair S = (U,A), where U and A are nonempty finite sets called the universe and primitive attributes respectively. In order to computing the minimal rule sets on the decision table in which a new instance is added, a classification of the new instances and a criteria for the minimum recalculation are given, an incremental learning algorithm is presented and this algorithm is proved that can be used to the consistent and the inconsistent decision tables. The complexity of this algorithm is also obtained.
Nature Inspired Methods in the Radial Basis Function Network Learning Process
Authors: Miroslav Burša, Lenka Lhotská
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

In present we benefit from the use of nature processes which provide us with highly effective heuristics for solving various problems. Their advantages are mainly prominent in hybrid approach. This paper evaluates several approaches for learning neural network based on Radial Basis Function (RBF) for distinguishing different sets in $\mathcal{R}^{L}$. RBF networks use one layer of hidden RBF units and the number of RBF units is kept constatnt. In the paper we evaluate the ACO$_\mathcal{R}$ (Ant Colony Approach for Real domain) approach inspired by ant behavior and the PSO (Particle Swarm Optimization) algorithm inspired by behavior of flock of birds or fish in the nature. Nature inspired and classical algorithms are compared and evaluated.
Rational QR-iteration without inversion
Authors: Raf Vandebril, Marc Van Barel, Nicola Mastronardi
Venue: Numerische Mathematik (2008)

In this manuscript a new method will be presented for performing a QR-iteration with (A&#x00a0;&#x2212; &#x03c3; I)(A&#x00a0;&#x2212; &#x03ba; I)&#x2212;1&#x00a0;=&#x00a0;QR without explicit inversion of the factor (A&#x00a0;&#x2212; &#x03ba; I)&#x2212;1. A QR-method driven by a rational function is attractive since convergence can occur at both sides of the matrix. Each step of this new iteration consists of two substeps. In the explicit version, first an RQ-factorization of the initial matrix A&#x00a0;&#x2212; &#x03ba; I&#x00a0;=&#x00a0;RQ will be computed, followed by a QR-factorization of the matrix (A&#x00a0;&#x2212; &#x03c3; I)Q H . The factorization of (A&#x00a0;&#x2212; &#x03c3; I)Q H can be computed in an intelligent manner, exploiting properties of the already known RQ-factorization of A&#x00a0;&#x2212; &#x03ba; I. The similarity transformation yielding the QR-step is defined by the unitary factor Q in the QR-factorization of the transformed matrix (A&#x00a0;&#x2212; &#x03c3; I)Q H . Examples will be given, illustrating how to efficiently compute the factorization for some specific classes of matrices. The novelties of this approach with respect to these matrix classes will be discussed.
Comparison of Pixel and Subpixel Retinal Vessel Tree Segmentation Using a Deformable Contour Model
Authors: L. Espona, M. J. Carreira, M. G. Penedo, M. Ortega
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

This paper presents a comparison of pixel and subpixel performance of the snake-based system designed to detect the vessel tree in eye fundus images. The automatic analysis of the retinal vessel tree facilitates the computation of the arteriovenous index, which is essential for the diagnosis and evolution of several eye diseases. A high accuracy is required to correctly assess the clinicians and it is insufficient when working at a pixel level. The developed model is inspired in the classical snake but incorporating domain specific knowledge and profits from the automatic localization of the optic disc and from the extraction of vascular tree centerlines previously developed in our research group [1]. The efficiency and accuracy of the detection of arteriovenous structures are evaluated using the publicly available DRIVE database and an equivalent system configuration for pixel and subpixel results. Results demonstrate that, although more time consuming, subpixel retinal vessel extraction is much more reliable, keeping relatively low values of computing time.
A Technique for Displaying Presence Information on a Live Camera Image Using 3-D Mask Objects
Authors: Jun Higuchi, Shin Takahashi, Jiro Tanaka
Venue: Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008)

Installing a live camera in an office or laboratory can provide reliable high-quality communication among collaborators who are physically separated, but may also lead to privacy concerns. We propose a technique for displaying presence information using a three-dimensional object as a mask that covers the image of people in the live camera system. Our technique enables information to be shared partially, enabling sufficient communication while alleviating the discomfort of feeling monitored by the camera. The system also clarifies less-visible activities such as typing text using a keyboard or moving a mouse of people in the camera image. We implemented the Koka-ComeCam system using our proposed technique.
Coordination and Agreement in Multi-Agent Systems
Authors: Sascha Ossowski
Venue: Proceedings of the 12th international workshop on Cooperative Information Agents XII (2008)

It is commonly accepted that coordination is a key characteristic of multi-agent systems and that, in turn, the capability of coordinating with others constitutes a centrepiece of agenthood. However, the key elements of coordination models, mechanisms, and languages for multi-agent systems are still subject to considerable debate. This paper provides a brief overview of different approaches to coordination in multi-agent systems. It will then show how these approaches relate to current efforts working towards a paradigm for smart, next-generation distributed systems, where coordination is based on the concept of agreement between computational agents.
Designing Persuasive Health Behaviour Change Dialogs
Authors: Hien Nguyen
Venue: Proceedings of the 11th international conference on User Modeling (2007)

Using theories of behaviour change, argumentation theory, and findings in social psychology, our research explores new methods to raise the persuasiveness of adaptive dialog-based systems using tailored arguments and onscreen characters to enhance the system's credibility and trustworthiness. Initial results revealed the existence of individual preferences for arguments, types of communication, and appearance of onscreen characters. In the future, we will explore methods to learn these preferences through interactions with the user, and to utilize them to maximize the persuasion effect of the system. The final outcome of the research will be a persuasion model that is capable of modelling the user's cognitive and affective state and generating tailored arguments to move the user in the desired direction. 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
Rough Sets in the Interpretation of Statistical Tests Outcomes for Genes Under Hypothetical Balancing Selection
Authors: Krzysztof Cyran
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

Detection of natural selection at the molecular level is one of the crucial problems in contemporary population genetics. There exists a number of statistical tests designed for it, however, the interpretation of the outcomes is often obscure, because of the existence of factors like population growth, migration and recombination. In his earlier work, the author has proposed the multi-null methodology, and he applied it for four genes implicated in human familial cancer: ATM, RECQL, WRN and BLM. Because of high computational effort required for estimating critical values under nonclassical nulls, mentioned methodology is not appropriate for selection screening. In the current paper, the author presents novel, rough set based methodology, helpful in the interpretation of tests outcomes applied versus only classical nulls. This method does not require long-lasting simulations and, as it is shown in the paper, it gives reliable results.
New Challenges in Petascale Scientific Databases
Authors: Alexander Szalay
Venue: Proceedings of the 20th international conference on Scientific and Statistical Database Management (2008)

Scientific data is doubling every year. Virtual Observatories are established over every scale of the physical world: from elementary particles to materials, biological systems, environmental observatories, remote sensing, and the universe. These collaborations collect increasing amounts of data, often close to a rate of petabytes per year. Many scientists will soon obtain most of their data from large scientific repositories of data, often stored in the form of databases. The talk will discuss the different requirements for such databases, and discuss user behavior in a few concrete examples taken from astronomy, in particular from the 6 year usage of the Sloan Digital Sky Survey database. Interesting query patterns are emerging, where users create custom "crawlers" to break large queries into many repetitive ones. The trial-and-error behavior of many exploratory projects will be also discussed. The talk will also present various scalable alternatives to large scientific analysis facilities.
The Average Radius of Attraction Basin of Hopfield Neural Networks
Authors: Fan Zhang, Xinhong Zhang
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

This paper introduces a derivation of the attraction basin to the Hopfield neural networks and obtains an average radius of the attraction basin, which is a expression of Hamming distance. The average radius of the attraction basin is (N ¿ 1) / 2P. If the average of Hamming distance between the probe pattern and a stored pattern is less than (N ¿ 1) / 2P, the neural network will converge to the stored pattern.
Introduction to Part I Issues in Introductory Programming Courses
Authors: Jens Bennedsen
Venue: Reflections on the Teaching of Programming: Methods and Implementations (2008)

Learning to program is notoriously difficult. Since the early 1970s, teaching programming to novices has been considered a big challenge and --according to the number of people attending conferences on programming-- it still seems to be [Dijkstra, 1969; Gries, 1974; McCracken et al., 2001; Robins et al., 2003; Soloway and Spohrer, 1988; Wegner et al.,1996]. Indeed, it is considered one of seven grand challenges in computing education [Mcgettrick et al., 2005]. Teaching introductory programming at university level has been the basis for many lively discussions among computer science teachers [Astrachan et al., 2005; Bailie et al., 2003; Bruce, 2005; SIGCSE-members, 2005], and for a substantial number of articles (e.g., searching "CS1" at ACM's digital library gives 1402 hits and searching "introductory programming" gives 62,654 --[search done December 20, 2007]). More official approaches to the design of computing curricula have also been taken --the most well know and influential being the series of curricula recommendations made by the ACM (American Association for the Computing Machinery ) and IEEE (Institute of Electrical and Electronics Engineers, Inc).
A Numerical Abstract Domain Based on Expression Abstraction and Max Operator with Application in Timing Analysis
Authors: Bhargav S. Gulavani, Sumit Gulwani
Venue: Proceedings of the 20th international conference on Computer Aided Verification (2008)

This paper describes a precise numerical abstract domain for use in timing analysis. The numerical abstract domain is parameterized by a linear abstract domain and is constructed by means of two domain lifting operations. One domain lifting operation is based on the principle of expression abstraction (which involves defining a set of expressions and specifying their semantics using a collection of directed inference rules) and has a more general applicability. It lifts any given abstract domain to include reasoning about a given set of expressions whose semantics is abstracted using a set of axioms. The other domain lifting operation incorporates disjunctive reasoning into a given linear relational abstract domain via introduction of max expressions. We present experimental results demonstrating the potential of the new numerical abstract domain to discover a wide variety of timing bounds (including polynomial, disjunctive, logarithmic, exponential, etc.) for small C programs.