ppxscal/embedding_network huggingface dataset:
Real-Time Registration Based on Planar Template Tracking for AR System
Authors: Kun Zeng, Ke Yang, Leyuan Liu, Qing Yang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

In this paper, it is presented that a markerless registration method, for an augmented reality system, is based on minimizing the sum of squared difference (SSD) between the stored image of patch previously and the current one in real time. In the proposed algorithm, the correspondences between frames are obtained in the process of fixed region tracking and the homograph of the region can be computed with the motion on projective transformation. By combined with the intrinsic parameters of camera, the position and orientation of region can be achieved in 3D registration for system. A markerless AR system based on the proposed algorithm can be improved to run stably in case of the illumination continuously linear changes or the patch partly covered.
Modeling Inlay/Onlay Prostheses with Mesh Deformation Techniques
Authors: Kwan-Hee Yoo, Jong-Sung Ha, Jae-Soo Yoo
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

This paper presents a method for effectively modeling the outer surfaces of inlay/onlay prostheses restoring teeth that are partially destroyed. We exploit 3D mesh deformation techniques: direct manipulation free-form deformation (DMFFD) [9] and multiple wires deformation (MWD) [10] with three kinds of information: standard teeth models, scanned mesh data from the plaster cast of a patient's tooth, functionally guided plane (FGP) measuring the occlusion of the patients' teeth. Our implementation can design inlay/onlay prostheses by setting up various parameters required in dentistry during visualizing the generated mesh models.
The Changing Face of Web Search
Authors: Prabhakar Raghavan
Venue: Proceedings of the 19th annual symposium on Combinatorial Pattern Matching (2008)

Web search has come to dominate our consciousness as a convenience we take for granted, as a medium for connecting advertisers and buyers, and as a fast-growing revenue source for the companies that provide this service. Following a brief overview of the state of the art and how we got there, this talk covers a spectrum of technical challenges arising in web search - ranging from spam detection to auction mechanisms.
Generic XML-based framework for metadata portals
Authors: Uwe Schindler, Michael Diepenbroek
Venue: Computers Geosciences (2008)

We present a generic and flexible framework for building geoscientific metadata portals independent of content standards for metadata and protocols. Data can be harvested with commonly used protocols (e.g., Open Archives Initiative Protocol for Metadata Harvesting) and metadata standards like DIF or ISO 19115. The new Java-based portal software supports any XML encoding and makes metadata searchable through Apache Lucene. Software administrators are free to define searchable fields independent of their type using XPath. In addition, by extending the full-text search engine (FTS) Apache Lucene, we have significantly improved queries for numerical and date/time ranges by supplying a new trie-based algorithm, thus, enabling high-performance space/time retrievals in FTS-based geo portals. The harvested metadata are stored in separate indexes, which makes it possible to combine these into different portals. The portal-specific Java API and web service interface is highly flexible and supports custom front-ends for users, provides automatic query completion (AJAX), and dynamic visualization with conventional mapping tools. The software has been made freely available through the open source concept.
Structure identification of Boolean relations and plain bases for co-clones
Authors: Nadia Creignou, Phokion Kolaitis, Bruno Zanuttini
Venue: Journal of Computer and System Sciences (2008)

We give a quadratic algorithm for the following structure identification problem: given a Boolean relation R and a finite set S of Boolean relations, can the relation R be expressed as a conjunctive query over the relations in the set S? Our algorithm is derived by first introducing the concept of a plain basis for a co-clone and then identifying natural plain bases for every co-clone in Post's lattice. In the process, we also give a quadratic algorithm for the problem of finding the smallest co-clone containing a Boolean relation.
Dynamic Tracking of Facial Expressions Using Adaptive, Overlapping Subspaces
Authors: Dimitris Metaxas, Atul Kanaujia, Zhiguo Li
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear subspaces. The learned subspaces adaptively adjust to the subject by tracking the shapes independently using Kanade Lucas Tomasi(KLT) point tracker. The novelty of our approach is that the tracking of feature points is used to generate independent training examples for updating the learned shape manifold and the appearance model. We use landmark based shape analysis to train a Gaussian mixture model over the aligned shapes and learn a Point Distribution Model(PDM) for each of the mixture components. The target 2D shape is searched by first maximizing the mixture probability density for the local feature intensity profiles along the normal followed by constraining the global shape using the most probable PDM cluster. The feature shapes are robustly tracked across multiple frames by dynamically switching between the PDMs. The tracked 2D facial features are used deform the 3D face mask.The main advantage of the 3D deformable face models is the reduced dimensionality. The smaller number of degree of freedom makes the system more robust and enables capturing subtle facial expressions as change of only a few parameters. We demonstrate the results on tracking facial features and provide several empirical results to validate our approach. Our framework runs close to real time at 25 frames per second.
Prescribed Learning of R.E. Classes
Authors: Sanjay Jain, Frank Stephan, Nan Ye
Venue: Proceedings of the 18th international conference on Algorithmic Learning Theory (2007)

This work extends studies of Angluin, Lange and Zeugmann on the dependence of learning on the hypotheses space chosen for the class. In subsequent investigations, uniformly recursively enumerable hypotheses spaces have been considered. In the present work, the following four types of learning are distinguished: class-comprising (where the learner can choose a uniformly recursively enumerable superclass as hypotheses space), class-preserving (where the learner has to choose a uniformly recursively enumerable hypotheses space of the same class), prescribed (where there must be a learner for every uniformly recursively enumerable hypotheses space of the same class) and uniform (like prescribed, but the learner has to be synthesized effectively from an index of the hypothesis space). While for explanatory learning, these four types of learnability coincide, some or all are different for other learning criteria. For example, for conservative learning, all four types are different. Several results are obtained for vacillatory and behaviourally correct learning; three of the four types can be separated, however the relation between prescribed and uniform learning remains open. It is also shown that every (not necessarily uniformly recursively enumerable) behaviourally correct learnable class has a prudent learner, that is, a learner using a hypotheses space such that it learns every set in the hypotheses space. Moreover the prudent learner can be effectively built from any learner for the class.
Generalized Non-Interactive Oblivious Transfer Using Count-Limited Objects with Applications to Secure Mobile Agents
Authors: Vandana Gunupudi, Stephen R. Tate
Venue: Financial Cryptography and Data Security: 12th International Conference, FC 2008, Cozumel, Mexico, January 28-31, 2008. Revised Selected Papers (2008)

Oblivious transfer (OT) is a fundamental primitive used in many cryptographic protocols, including general secure function evaluation (SFE) protocols. However, interaction is a primary feature of any OT protocol. In this paper, we show how to remove the interaction requirement in an OT protocol when parties participating in the protocol have access to slightly modified Trusted Platform Modules, as defined by Sarmenta et al. in proposing the notion of count-limited objects (clobs) [8]. Specifically, we construct a new cryptographic primitive called "generalized non-interactive oblivious transfer"(GNIOT). While it is possible to perform GNIOT using clobs in a straightforward manner, with multiple clobs, we show how to perform this efficiently, by using a single clob regardless of the number of values that need to be exchanged in an oblivious manner. Additionally, we provide clear definitions and a formal proof of the security of our construction. We apply this primitive to mobile agent applications and outline a new secure agent protocol called the GTX protocol which provides the same security guarantees as existing agent protocols while removing the need for interaction, thus improving efficiency.
Relative Principle Component and Relative Principle Component Analysis Algorithm
Authors: Cheng-Lin Wen, Jing Hu, Tian-Zhen Wang
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Aiming at the problems happened in the practical application of traditional Principle Component Analysis (PCA), the concept of Relative Principle Component (RPC) and method of Relative Principle Component Analysis (RPCA) are put forward. Meanwhile, some concepts such as Relative Transform (RT), "Rotundity" Scatter and so on are introduced. The new algorithm can overcome some disadvantages of traditional PCA for compressing data when data is "Rotundity" Scatter. A simulation has been used to demonstrate the effectiveness and practicability of the algorithm proposed. The RPCs selected by RPCA are more representative, and the way to choose RPCs is more flexible, so that the application of the new algorithm will be very extensive.
Correlation Integral Decomposition for Classification
Authors: Marcel Jiřina, Marcel Jiřina,  Jr.
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

In this paper we show that the correlation integral can be decomposed into functions each related to a particular point of data space. For these functions, one can use similar polynomial approximations as used in the correlation integral. The essential difference is that the value of the exponent, which would correspond to the correlation dimension, differs in accordance to the position of the point in question. Moreover, we show that the multiplicative constant represents the probability density estimation at that point. This finding is used for the construction of a classifier. Tests with some data sets from the Machine Learning Repository show that this classifier can be very effective.
Complex Effects Simulation Based Large Particles System on GPU
Authors: Xingquan Cai, Jinhong Li, Zhitong Su
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

In this paper, we present a new method to implement complex effects simulation based large particles system on GPU. Our method could be used in 3D games to simulate the photorealist effects. Our particles system is a state-preserving simulation system. We update the dynamic attributes and render the particles in batches on GPU. The most important is that we handle the collisions between particles and other models on GPU. We also compare with the CPU particles system method and implement complex effects on GPU. Finally, we give the implementation results.
An Efficient Multiple Faces Tracking System
Authors: Shuhan Shen, Yuncai Liu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

A multiple faces tracking system was presented based on Relevance Vector Machine (RVM) and Boosting learning. In this system, a face detector based on Boosting learning is used to detect faces at the first frame, and the face motion model and color model are created. In the tracking process different tracking methods are used according to different states of faces, and the states are changed according to the tracking results. When the full image search condition is satisfied, a full image search is started in order to find new coming faces and former occluded faces. In the full image search and local search, the similarity matrix is introduced to help matching faces efficiently. Experimental results demonstrate the capability and efficiency of the proposed system.
Plenary lecture II: local deformations and singular linear system theory. Bifurcation diagrams
Authors: Maria I. Garcia-Planas
Venue: Proceedings of the WSEAS International Conference on Applied Computing Conference (2008)

In this work we consider differentiable families of triples of matrices ϕ(ξ) = (E(ξ), A(ξ), B(ξ) with the parameter vector ξ ∈ Rk, representing families of singular linear time invariant systems in the form E(ξ)x(t) = A(ξ)x(t)+B(ξ)u(t), with E(ξ), A(ξ) ∈ Mn(C), B(ξ) ∈ Mn×m(C) for each ξ. In this paper, we show that we can reduce locally the family to a special typically more simple form, called the versal deformation by a smooth change of parameters and a proportional and derivative feedback equivalence transformation. As an application, this procedure is applied to the analysis to the neighborhood of a fixed system, showing bifurcation diagrams of critical points.
Fuzzy control of parallel induction motors drive
Authors: Sakrawee Raweekul, Thanatchai Kulworawanichpong, Sarawut Sujitjorn
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

This article presents the design of a fuzzy controller for a drive system. The drive consists of three single-phase induction motors (fractional hp) in parallel connection, and fed by a single PWM inverter. The fuzzy controller is self-organizing and capable of dealing with high torque disturbances. Simulation results are presented.
ZoomLinux: A Research Result Providing a Tangible Response to the Needs of Low Vision Students
Authors: Giovanni Paolo Caruso, Silvia Dini, Lucia Ferlino
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

This paper addresses the needs of low-vision students by examining the development of ZoomLinux, a DVD containing specially selected open source educational software products. The DVD was created in 2008 by a group of researchers and professionals who have gained extensive experience in visual impairment through studies conducted over many years. ZoomLinux differs from similar products devoted to people with special needs by being "especially normal": the software applications and the platform itself are readily usable by each and every student in the classroom, thus satisfying the most important requirement of e-inclusion. This approach offers new opportunities for educational and methodological settings: the teacher can customize system and software options in order to meet different special needs. For each educational software, the DVD provides detailed informations about strengths, weaknesses regarding use with low vision students, accessibility analysis and notes explaining how teachers can customize the interface.
An efficient parallel approach for identifying protein families in large-scale metagenomic data sets
Authors: Changjun Wu, Ananth Kalyanaraman
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

Metagenomics is the study of environmental microbial communities using state-of-the-art genomic tools. Recent advancements in high-throughput technologies have enabled the accumulation of large volumes of metagenomic data that was until a couple of years back was deemed impractical for generation. A primary bottleneck, however, is in the lack of scalable algorithms and open source software for large-scale data processing. In this paper, we present the design and implementation of a novel parallel approach to identify protein families from large-scale metagenomic data. Given a set of peptide sequences we reduce the problem to one of detecting arbitrarily-sized dense subgraphs from bipartite graphs. Our approach efficiently parallelizes this task on a distributed memory machine through a combination of divide-and-conquer and combinatorial pattern matching heuristic techniques. We present performance and quality results of extensively testing our implementation on 160K randomly sampled sequences from the CAMERA environmental sequence database using 512 nodes of a BlueGene/L supercomputer.
Joint routing and admission control problem under statistical delay and jitter constraints in MPLS networks
Authors: Hichem Ayed Harhira, Samuel Pierre
Venue: Computer Communications (2008)

Admission control algorithms are crucial for ensuring a near optimal resource allocation while guaranteeing the required Quality of Service (QoS) constraints. In this paper, a new routing and Admission Control mechanism in multi-protocol label switching (MPLS) based networks is proposed. The proposed mechanism relies on the packets' delay distributions that are empirically built on every link, to make adequate admission decisions. As a new connection request arrives, the admission control mechanism computes a feasible path, satisfying the connection's statistical QoS constraints (the maximum end-to-end delay, jitter and the QoS violation probability). For that, we formulate this problem as an Integer Linear Programming (ILP) model that is solved to optimality using the CPLEX mathematical programming tool for real-size networks. Simulation results show that the new admission control mechanism allows for low blocking rates while statistically satisfying the QoS constraints for both the new and the ongoing connections.
The Design of Colossus (foreword by Howard Campaigne)
Authors: Thomas H. Flowers
Venue: IEEE Annals of the History of Computing (1983)

This article describes the construction and operation of the Colossus machines. The machines had most if not all of the essential features of a modern computer, except that variable programming was provided not by memory store but by hard-wired function units selected and interconnected by switches operated by the mathematician-programmers.
Privacy Recovery with Disposable Email Addresses
Authors: Jean-Marc Seigneur, Christian Damsgaard Jensen
Venue: IEEE Security and Privacy (2003)

Solutions for privacy protection exhibit five role categories: prevention, detection, awareness, response, and recovery. Few recovery tools are available, though, especially for private data linked to permanent real-world facts (such as a user's birthday). Generally, once private data is revealed, second use cannot be controlled. In the case of email addresses, we argue that recovery-like tools do exist: Disposable Email Addresses (DEAs) can be closed when they are compromised by spam, because there is generally no requirement for email address to become permanent private data. In this article, we investigate the use and cost-benefit of DEAs as a mechanism for privacy recovery.
Using context to improve query formulation and entry from mobile phones
Authors: Maryam Kamvar
Venue:  (2008)

The goal of this thesis is to improve the query formulation and entry step of the web search process from mobile phones. We achieve this by providing query recommendations (queries displayed to the user before she has begun query input) and query predictions (queries displayed to the user as she is entering the query) as part of the mobile search interface. We derived the motivation for our research from a comprehensive overview of the state of mobile web search. After analyzing millions of requests made to the Google mobile search interface, we were able to identify areas for improvement. We discovered that the first step of the search process&mdash;formulating and entering the query&mdash;is time-consuming and cumbersome for mobile users. To address this, we present two approaches for improving mobile query formulation and entry: relevant query recommendations and accurate query predictions. We build recommendation and prediction models that consider a user's context when she is interacting with the search interface. We restrict context to the set of circumstances captured in the Google search logs at the time of query. We find that the two contextual signals that make the biggest impact in improving the accuracy of predictions, thus reducing the number of key presses needed to enter a query, are knowledge of the application being used (in this case a search engine), and of the location of the user. Although knowledge of the day-of-week did not significantly impact the prediction model, it improves the quality of the recommendations. Knowledge of the time-of-day did not significantly improve either model. The query recommendation and prediction models presented in this thesis are general and can be used in conjunction with any search interface. However, we focus our research on search interfaces for mobile phones, where we believe the greatest need for improvement exists. We design, implement, and evaluate interfaces for the prediction and recommendation models in order to improve the mobile search experience. Our findings can be easily incorporated in existing mobile search systems.
Summarizing spatial data streams using ClusterHulls
Authors: John Hershberger, Nisheeth Shrivastava, Subhash Suri
Venue: Journal of Experimental Algorithmics (JEA) (2009)

We consider the following problem: given an on-line, possibly unbounded stream of two-dimensional (2D) points, how can we summarize its spatial distribution or shape using a small, bounded amount of memory&quest; We propose a novel scheme, called ClusterHull, which represents the shape of the stream as a dynamic collection of convex hulls, with a total of at most m vertices, where m is the size of the memory. The algorithm dynamically adjusts both the number of hulls and the number of vertices in each hull to best represent the stream using its fixed-memory budget. This algorithm addresses a problem whose importance is increasingly recognized, namely, the problem of summarizing real-time data streams to enable on-line analytical processing. As a motivating example, consider habitat monitoring using wireless sensor networks. The sensors produce a steady stream of geographic data, namely, the locations of objects being tracked. In order to conserve their limited resources (power, bandwidth, and storage), the sensors can compute, store, and exchange ClusterHull summaries of their data, without losing important geometric information. We are not aware of other schemes specifically designed for capturing shape information in geometric data streams and so we compare ClusterHull with some of the best general-purpose clustering schemes, such as CURE, k-medians, and LSEARCH. We show through experiments that ClusterHull is able to represent the shape of two-dimensional data streams more faithfully and flexibly than the stream versions of these clustering algorithms.