ppxscal/embedding_network huggingface dataset:
Adaptive Line Tracking with Multiple Hypotheses for Augmented Reality
Authors: Harald Wuest, Florent Vial, Didier Stricker
Venue: Proceedings of the 4th IEEE/ACM International Symposium on Mixed and Augmented Reality (2005)

We present a real-time model-based line tracking approach with adaptive learning of image edge features that can handle partial occlusion and illumination changes. A CAD (VRML) model of the object to track is needed. First, the visible edges of the model with respect to the camera pose estimate are sorted out by a visibility test performed on standard graphics hardware. For every sample point of every projected visible 3D model line a search for gradient maxima in the image is then carried out in a direction perpendicular to that line. Multiple hypotheses of these maxima are considered as putative matches. The camera pose is updated by minimizing the distances between the projection of all sample points of the visible 3D model lines and the most likely matches found in the image. The state of every edge's visual properties is updated after each successful camera pose estimation.We evaluated the algorithm and showed the improvements compared to other tracking approaches.
Coevolving Predator and Prey Robots: Do "Arms Races" Arise in Artificial Evolution?
Authors: Stefano Nolfi, Dario Floreano
Venue: Artificial Life (1998)

Coevolution (i.e., the evolution of two or more competing populations with coupled fitness) has several features that may potentially enhance the power of adaptation of artificial evolution. In particular, as discussed by Dawkins and Krebs, competing populations may reciprocally drive one another to increasing levels of complexity by producing an evolutionary "arms race." In this article we will investigate the role of coevolution in the context of evolutionary robotics. In particular, we will try to understand in what conditions coevolution can lead to "arms races." Moreover, we will show that in some cases artificial coevolution has a higher adaptive power than simple evolution. Finally, by analyzing the dynamics of coevolved populations, we will show that in some circumstances well-adapted individuals would be better advised to adopt simple but easily modifiable strategies suited for the current competitor strategies rather than incorporate complex and general strategies that may be effective against a wide range of opposing counter-strategies.
Classification of Proteomic Data with Logistic Kernel Partial Least Squares Algorithm
Authors: Zhenqiu Liu, Dechang Chen, Jianjun Tian
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03 (2005)

In this paper we introduce the logistic kernel partial least squares (LKPLS) algorithm for classi?cation of health vs. cancer using mass spectrometry (MS). Wavelet decomposition is proposed for feature selection and data preprocessing. LKPLS combines the logistic regression with the kernel partial least squares algorithm. The method is applied to real life cancer samples. Experimental comparisons show that LKPLS outperforms other methods in the analysis of MS data.
Evolutionary algorithms for medical simulations: a case study in minimally-invasive vascular interventions
Authors: Peter A. N. Bosman, Tanja Alderliesten
Venue: Proceedings of the 2005 workshops on Genetic and evolutionary computation (2005)

To obtain the expertise to correctly perform minimally-invasive vascular interventions thorough training is required. Training using simulation systems are increasingly becoming an accepted methodology. Recently, a minimally--invasive vascular intervention simulation (MIVIS) system has been developed. At the heart of this system lies an optimization problem to be solved repeatedly. In this paper, we investigate the advantages and disadvantages of using an evolutionary algorithm (EA) to solve the optimization problem instead of a problem--specific first--order analytical approximation algorithm. The results show that the use of the EA as optimization algorithm is favorable. A substantial reduction in time can be obtained while the RMS error associated with the simulation result differs only slightly.
Teaching cryptography to undergraduate students in small liberal art schools
Authors: Wen-Jung Hsin
Venue: Proceedings of the 2nd annual conference on Information security curriculum development (2005)

Teaching the concept of cryptography to undergraduate students in small traditional liberal art schools is important, but a challenging task. It is important because cryptography is the theoretical basis of computer and network security. It is challenging because with heavy mandatory liberal art class requirements, there is no room to accommodate an entire course or two on advanced topics such as cryptography in Computer Science curriculum. Thus, the concept of cryptography is sprinkled in different courses such as Operating Systems, Computer Networking, and Discrete Mathematics.Depending on time allowance, the author has taught this subject in one-class period to two-week period. Regardless of the length of time, students generally would like to know how to apply the cryptography in actual applications. Recently, the author along with a colleague has devised a model of "On-line/Off-line Signature Scheme with Two Signers" of which many applications (such as e-Traveler's Check [3], e-Check [4], and Proxy Signature) can build on top. The e-Traveler's Check [3] is the first ever electronic version of a paper Traveler's Check. By carefully selecting a set of important, representative cryptography components, along with the devised model and diverse applications, students get a coherent sense and appreciation of cryptography and more importantly many students express interest in going on pursuing cryptography in graduate schools or professional fields.
A Denial-of-Service Resistant Quality-of-Service Signaling Protocol for Mobile Ad Hoc Networks
Authors: Marek Hejmo, Brian L. Mark, Charikleia Zouridaki, Roshan K. Thomas
Venue: Proceedings of the Second International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks (2005)

Quality-of-service (QoS) signaling protocols for mobile ad hoc networks (MANETs) are highly vulnerable to attacks. In particular, a class of Denial-of-service (DoS) attacks can severely cripple network performance with relatively little effort expended by the attacker. We propose a distributed QoS signaling protocol that is resistant to a large class of DoS attacks. The key elements of the scheme are: sensing of available bandwidth, traffic policing, and rate monitoring. The proposed signaling scheme provides QoS for real-time traffic and achieves a compromise between signaling protocols that require the maintenance of per-flow state and those that are completely stateless. The signaling scheme scales gracefully in terms of the number of nodes and/or traffic flows in the MANET. We analyze the key security properties of the protocol and present simulation results to demonstrate its resistance to DoS attacks.
Prototype Implementation and Performance Evaluation of a QoS-based Web Server
Authors: Zhiguang Shan, Chuang Lin, Yaya Wei
Venue: Proceedings of the IEEE International Workshop (2005)

With the evolvement of the E-commerce, the Internet is undergoing substantial changes from a communication and browsing infrastructure to a medium for conducting business and selling services. These changes place the Web server at the center of the E-commerce infrastructure with increasing requirements for providing service differentiation and performance assurance. To that end, Web servers must have mechanisms and policies for establishing and supporting Quality of Service (QoS).In this paper, a Web server prototype with priority-based QoS control mechanisms, called QoS Apache, is implemented. A performance testing platform is established, and the performance measurement software httperf is used to test the popular Apache and the QoS Apache. The performance evaluation results show that the QoS Apache server can provide different types of requests with differentiated Web QoS, in comparison with the popular QoS-unaware Apache.
Towards a formal framework for Choreography
Authors: Nadia Busi, Roberto Gorrieri, Claudio Guidi, Roberto Lucchi, Gianluigi Zavattaro
Venue: Proceedings of the 14th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprise (2005)

One of the main challenges in the area of Service Oriented Computing, in general, and of Web services technology, in particular, is the definition of languages and models for the description of choreographies . A choreography defines the collaborations between interacting services: more precisely, it specifies a contract containing a "global" definition of the common ordering conditions and constraints under which messages are exchanged in a services conversation. In this paper, starting from the analysis of the main aspects of Web services technology, we propose a simple choreography language, equipped with a formal semantics, which is intended as the starting point for the development of a framework for the design and analysis of choreographies in Service Oriented Computing.
Automatic model-based 3D object recognition by combining feature matching with tracking
Authors: Sungho Kim, So Kweon
Venue: Machine Vision and Applications (2005)

We propose a vision-based robust automatic 3D object recognition, which provides object identification and 3D pose information by combining feature matching with tracking. For object identification, we propose a robust visual feature and a probabilistic voting scheme. An initial object pose is estimated using correlations between the model image and the 3D CAD model, which are predefined, and the homography, byproduct of the identification. In tracking, a Lie group formalism is used for robust and fast motion computation. Experimental results show that object recognition by the proposed method improves the recognition range considerably.
Relational discovery in sequentially-connected data streams: efficient algorithms for lossless pattern discovery and change detection
Authors: Jeffrey Allen Coble
Venue:  (2005)

We are developing relational data mining techniques that discover structural patterns consisting of complex relationships between entities. Our research is particularly applicable to domains in which the data is event driven, such as counter-terrorism intelligence analysis. Such analytical tasks require discovery of relational patterns between events and actors so that these patterns can be exploited for prediction and action. An additional complexity of these event-driven problems is that they are often continuous, with data streaming in over a long period of time or even indefinitely. This presents the need for discovery algorithms to repeatedly assimilate new data into the discovery process. However, reprocessing the accumulated data after receiving each new increment is often an intractable task because of the computational demands of most relational discovery methods. We have developed an algorithm to mine relational data streams by summarizing discoveries from previous data increments so that the globally-best patterns can be computed by examining only the new data increment and isolated sets of sequentially-connected data that spans increment boundaries. Our algorithm will find pattern instances that span increment boundaries by using a targeted, localized search, based on the set of globally-best substructures, and an efficient graph exploration technique that restricts the range of the graph that must be explored. Many continuous problems are also dynamic in nature, requiring discovery algorithms to be capable of recognizing and adapting to change over time. We introduce an algorithm with which we are able to use a measure of central tendency for a set of graphs, used to compute a representative point in graph space. We use these points, along with a distance metric, to measure change in sequential sets of the best patterns discovered from successive data increments. The objective of this work is to enable a method for measuring pattern drift in relational data streams, where the salient patterns may change in prevalence and structure over time. With a measure of central tendency for graph data, along with a method for calculating graph distance, we have a framework with which we can begin to adapt time-series techniques to relational data streams.
Discovery of Gene Expression Patterns across Multiple Cancer Types
Authors: Cheryl Chan, Parvin Mousavi
Venue: Proceedings of the Fifth IEEE Symposium on Bioinformatics and Bioengineering (2005)

In this paper, we investigate the underlying common gene expression signatures in related cancer types. Shared expression signatures are investigated in breast and ovarian cancers specifically through the definition of four progressively more difficult classification problems. SHEBA, a stochastic Bayesian inference approach, is introduced to identify highly predictive gene sets in the defined classification problems. The heuristics reduce the computation time required to identify the most informative groups of features in the gene space, while providing a good approximation of comparable exhaustive approaches. The breast and ovarian cancer class could be distinguished well from the other classes of cancers using SHEBA in three of the four classificationproblems, suggesting the existence of a commonality between their gene expressions. Extensive statistical validation and preliminary biological review of the most predictive gene sets demonstrate their robustness and specificity.
Reengineering C++ Component Models via Automatic Program Transformation
Authors: Robert L. Akers, Ira D. Baxter, Michael Mehlich, Brian J. Ellis, Kenn R. Luecke
Venue: Proceedings of the 12th Working Conference on Reverse Engineering (2005)

Automated program transformation holds promise for a variety of software life cycle endeavors, particularly where the size of legacy systems makes code analysis, re-engineering, and evolution difficult and expensive. But constructing highly scalable transformation tools supporting modern languages in full generality is itself a painstaking and expensive process. This cost can be managed by developing a common transformation system infrastructure reuseable by derived tools that each address specific tasks, thus leveraging the infrastructure costs. This paper describes the Design Maintenance System (DMS1), a practical, commercial program analysis and transformation system, and discusses how it was employed to construct a custom modernization tool being applied to a large C++ industrial avionics system. The tool transforms components developed in a 1990's-era component style to a more modern CORBA-like component framework, preserving functionality.
Anaphora and Discourse Structure
Authors: Bonnie Webber, Matthew Stone, Aravind Joshi, Alistair Knott
Venue: Computational Linguistics (2003)

We argue in this article that many common adverbial phrases generally taken to signal a discourse relation between syntactically connected units within discourse structure instead work anaphorically to contribute relational meaning, with only indirect dependence on discourse structure. This allows a simpler discourse structure to provide scaffolding for compositional semantics and reveals multiple ways in which the relational meaning conveyed by adverbial connectives can interact with that associated with discourse structure. We conclude by sketching out a lexicalized grammar for discourse that facilitates discourse interpretation as a product of compositional rules, anaphor resolution, and inference.
Global Segmentation and Curvature Analysis of Volumetric Data Sets Using Trivariate B-Spline Functions
Authors: Octavian Soldea Gershon Elber, Ehud Rivlin
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

This paper presents a method to globally segment volumetric images into regions that contain convex or concave (elliptic) iso-surfaces, planar or cylindrical (parabolic) iso-surfaces, and volumetric regions with saddle-like (hyperbolic) iso-surfaces, regardless of the value of the iso-surface level. The proposed scheme relies on a novel approach to globally compute, bound, and analyze the Gaussian and mean curvatures of an entire volumetric data set, using a trivariate B-spline volumetric representation. This scheme derives a new differential scalar field for a given volumetric scalar field, which could easily be adapted to other differential properties. Moreover, this scheme can set the basis for more precise and accurate segmentation of data sets targeting the identification of primitive parts. Since the proposed scheme employs piecewise continuous functions, it is precise and insensitive to aliasing.
ReflecTS: a flexible transaction service framework
Authors: Anna-Brith Arntsen, Randi Karlsen
Venue: Proceedings of the 4th workshop on Reflective and adaptive middleware systems (2005)

Transactional requirements, from applications and execution environments, are varying and may exceed traditional ACID properties. We believe that transactional middleware platforms must be flexible in order to adapt to these requirements. Present systems are, however, inflexible with respect to such adaptations. ReflecTS is a flexible transaction processing platform maintaining an extensible number of concurrently running transaction services. This paper presents the architecture and the first prototype of ReflecTS, which focuses on a transaction service selection procedure. The selection procedure is based on XML-specifications of transactional requirements and transaction service descriptions-making the platform adjustable to varying requirements.
Optimal Routing with Multiple Traffic Matrices Tradeoff between Average andWorst Case Performance
Authors: Chun Zhanga, Jim Kurosea, Don Towsley, Zihui Ge, Yong Liu
Venue: Proceedings of the 13TH IEEE International Conference on Network Protocols (2005)

In this paper, we consider the problem of finding an "efficient" and "robust" set of routes in the face of changing/ uncertain traffic. The changes/uncertainty in exogenous traffic are characterized by multiple traffic matrices. Our goal is to find a set of routes that results in good average case performance over the set of traffic matrices, while avoiding bad worst case performance for any single traffic matrix. With multiple traffic matrices, previous work aims solely to optimize the average case performance [1], or the worst case performance [2]. For a given set of traffic matrices, different sets of routes offer a different tradeoff between the average case and the worst case performance. In this paper, we quantify the performance of a routing configuration at both network level and link level. We propose a simple metric - a weighted sum of the average case and the worst case performance - to control the tradeoff between these two considerations. Despite of its simple form, this metric is very effective. We prove that optimizing routing using this metric has desirable properties, such as the average case performance being a decreasing, convex and differentiable function to the worst case performance. By extending previous work [1][3], we derive methods to find the optimal routes with respect to the proposed metric for two classes of intradomain routing protocols: MPLS and OSPF/IS-IS. We evaluate our approach with data collected from an operational tier-1 ISP. For MPLS, we find that there exists significant tradeoff (e.g., 15% - 23% difference) between optimizing solely on the average case performance and solely on the worst case performance. Our approach can identify solutions that can dramatically improve the worst case performance (13% - 15%) while only slightly sacrificing the average case performance (2.2% - 3%), in comparison to that by optimizing solely on the average case performance. For OSPF/IS-IS, we still find a significant difference between the two optimization objectives, however, a fine-grained tradeoff is difficult to achieve due to the limited control that OSPF/ISIS provide.
Reactive information displays to augment comprehension and problem solving performance
Authors: Daesub Yoon
Venue:  (2005)

In recent years, interactive systems have increasingly become a part of people's daily lives. People want to use new systems without having to spend a lot of time learning its commands. So interface design is rapidly moving from a technology-centered approach to a human-centered approach. However, even human-centered design is not a perfect solution because people still need to give explicit commands to activate and control a system. An even more novel and useful way of interacting with a system will be one that avoids the need for explicit commands. One particular strand of research in this direction addresses the question of how an interface can actively assist the user in information processing tasks such as decision making, planning and problem solving. In this context, the focus of our research is the design and evaluation of adaptive interfaces that are designed to help people in problem solving activities. These interfaces adapt the information they present to the user in response to his or her eye movements, and are called Reactive Information Displays. Our research also tackled the problem of providing software to support the development of such interfaces. We developed Reactive Information Displays that employ various strategies to assist users based on a cognitive model of problem solving proposed by Narayanan and Hegarty (2002). The design and operating principles of these displays are presented here. We evaluated these displays with several users. From these empirical studies, described herein, we have strong evidence that Reactive Information Displays can increase multiple aspects of users' problem solving performance. The display designs and evaluation studies form two of the three major parts of this dissertation. Since an eye tracker produces a very large amount of raw eye movement data, it is impossible to analyze the data manually. Therefore, we developed automatic analysis tools to extract useful information from raw eye movement data. Also, for the various reactive strategies that we investigated, we developed software design toolkits to implement the corresponding displays semi-automatically. The third part of this dissertation consists of architectural specifications of the analysis tools and design toolkits.
The Zotob Storm
Authors: Bruce Schneier
Venue: IEEE Security and Privacy (2005)

Using Zotob worm outbreak as an example, Schneier discusses patches and security processes for preventing more worm outbreaks. Given that it's impossible to know what's coming beforehand, how you respond to an actual worm largely determines your defense's effectiveness.
Stratified type inference for generalized algebraic data types
Authors: François Pottier, Yann Régis-Gianas
Venue: Conference record of the 33rd ACM SIGPLAN-SIGACT symposium on Principles of programming languages (2006)

Stratified type inference for generalized algebraic data types.
Formal certification of a compiler back-end or: programming a compiler with a proof assistant
Authors: Xavier Leroy
Venue: Conference record of the 33rd ACM SIGPLAN-SIGACT symposium on Principles of programming languages (2006)

This paper reports on the development and formal certification (proof of semantic preservation) of a compiler from Cminor (a C-like imperative language) to PowerPC assembly code, using the Coq proof assistant both for programming the compiler and for proving its correctness. Such a certified compiler is useful in the context of formal methods applied to the certification of critical software: the certification of the compiler guarantees that the safety properties proved on the source code hold for the executable compiled code as well.