ppxscal/embedding_network huggingface dataset:
How to Use SIFT Vectors to Analyze an Image with Database Templates
Authors: Adrien Auclair, Laurent D. Cohen, Nicole Vincent
Venue: Adaptive Multimedial Retrieval: Retrieval, User, and Semantics: 5th International Workshop, AMR 2007, Paris, France, July 5-6, 2007 Revised Selected Papers (2007)

During last years, local image descriptors have received much attention because of their efficiency for several computer vision tasks such as image retrieval, image comparison, features matching for 3D reconstruction... Recent surveys have shown that Scale Invariant Features Transform (SIFT) vectors are the most efficient for several criteria. In this article, we use these descriptors to analyze how a large input image can be decomposed by small template images contained in a database. Affine transformations from database images onto the input image are found as described in [16]. The large image is thus covered by small patches like a jigsaw puzzle. We introduce a filtering step to ensure that found images do not overlap themselves when warped on the input image. A typical new application is to retrieve which products are proposed on a supermarket shelf. This is achieved using only a large picture of the shelf and a database of all products available in the supermarket. Because the database can be large and the analysis should ideally be done in a few seconds, we compare the performances of two state of the art algorithms to search SIFT correspondences: Best-Bin-First algorithm on Kd-Tree and Locality Sensitive Hashing. We also introduce a modification in the LSH algorithm to adapt it to SIFT vectors.
Two Types of Generalized Variable Precision Formal Concepts
Authors: Hong-Zhi Yang, Ming-Wen Shao
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

In this paper, we introduce two pairs operators in fuzzy formal contexts. Based on the proposed operators, we present two types of generalized variable precision formal concepts, i.e. property oriented crisp-fuzzy concepts and object oriented fuzzy-crisp concepts. We have different level generalized formal concepts with different precision level. Last, we discuss the relationship between different precision level generalized concepts lattices in details.
A scalable parallel framework for analyzing terascale molecular dynamics simulation trajectories
Authors: Tiankai Tu, Charles A. Rendleman, David W. Borhani, Ron O. Dror, Justin Gullingsrud, Morten Ø. Jensen, John L. Klepeis, Paul Maragakis, Patrick Miller, Kate A. Stafford, David E. Shaw
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

As parallel algorithms and architectures drive the longest molecular dynamics (MD) simulations towards the millisecond scale, traditional sequential post-simulation data analysis methods are becoming increasingly untenable. Inspired by the programming interface of Google's MapReduce, we have built a new parallel analysis framework called HiMach, which allows users to write trajectory analysis programs sequentially, and carries out the parallel execution of the programs automatically. We introduce (1) a new MD trajectory data analysis model that is amenable to parallel processing, (2) a new interface for defining trajectories to be analyzed, (3) a novel method to make use of an existing sequential analysis tool called VMD, and (4) an extension to the original MapReduce model to support multiple rounds of analysis. Performance evaluations on up to 512 cores demonstrate the efficiency and scalability of the HiMach framework on a Linux cluster.
A numerical model for the simultaneous transport of oxygen and carbon dioxide in the systemic capillaries and surrounding tissue
Authors: Maithili Sharan, S. Selvakumar
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

A mathematical model is formulated for the simultaneous transport of oxygen (O$_{2}$) and carbon dioxide (CO$_{2}$) in the systemic capillaries and surrounding tissue. The model takes into account the molecular diffusion, convection and the consumption of O$_{2}$ and the production of CO$_{2}$ in the tissue due to metabolism. The interaction of O$_{2}$ and CO$_{2}$ in the blood is incorporated using non-linear functions to represent O$_{2}$ and CO$_{2}$ dissociation curves depending on both O$_{2}$ and CO$_{2}$ in the blood. The formulation leads to a coupled system of nonlinear partial differential equations. A finite difference technique of O((&Delta; r$_{1})^{2}$, (&Delta; r$_{2})^{2}$, &Delta; z) along with a line iterative approach is described to solve the governing equations of the model together with the physiologically relevant boundary conditions. It is shown that the interaction of O$_{2}$ and CO$_{2}$ in the blood plays an important role in the removal of CO$_{2}$ from the tissue whereas its effect is not significant on the delivery of O$_{2}$ to tissue. It is found that by considering the interaction of O$_{2}$ and CO$_{2}$ in the blood, the accumulation of the total CO$_{2}$ is reduced by about 44% of the total CO$_{2}$ exchanged in the tissue. The sensitivity analysis shows that the PO$_{2}$ (PCO$_{2}$) in the tissue decreases (increases) with the decrease of blood velocity and increase of metabolic rate.
On the interaction between localization and location verification for wireless sensor networks
Authors: Dawood Al-Abri, Janise McNair
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2008)

Secure wireless sensor networks (WSNs) must be able to associate a set of reported data with a valid location. Many algorithms exist for the localization service that determines a WSN node's location, and current research is developing for location verification, where the network must determine whether or not a node's claimed location is valid (or invalid). However, the interaction of these two services creates another challenge, since there is no method to distinguish between benign errors, e.g., errors that are inherent to the localization technique, and malicious errors, e.g., errors due to a node's deceptive location report. In this paper, we study the problem of inherent localization errors and their impact on the location verification service. We propose a localization and location verification (LLV) server model, and define categories of LLV schemes for discrete and continuous resolution. We then designate two metrics to measure the impact of inherent localization errors-the probability of verification (for the discrete location verification schemes) and the CDF of the deviation distance (for the continuous location verification schemes)-to analyze the performance of each LLV category. Numerical results show that a proper tuning mechanism is needed to tolerate even small inherited estimation errors, otherwise the location verification can result in the rejection of almost all nodes. In addition, we propose several location verification feedback (LV-FEED) algorithms to improve the localization accuracy. Analysis of these algorithms shows that a significant improvement in localization accuracy can be accomplished in a few iterations of executing the location verification feedback schemes.
A multivariate version of the Benjamini-Hochberg method
Authors: J. A. Ferreira, S. O. Nyangoma
Venue: Journal of Multivariate Analysis (2008)

We propose a multivariate method for combining results from independent studies about the same 'large scale' multiple testing problem. The method works asymptotically in the number of hypotheses and consists of applying the Benjamini-Hochberg procedure to the p-values of each study separately by determining the 'individual false discovery rates' which maximize power subject to a restriction on the (global) false discovery rate. We show how to obtain solutions to the associated optimization problem, provide both theoretical and numerical examples, and compare the method with univariate ones.
Representing and reasoning over a taxonomy of part-whole relations
Authors: C. Maria Keet, Alessandro Artale
Venue: Applied Ontology (2008)

Many types of part-whole relations have been proposed in the literature to aid the conceptual modeller to choose the most appropriate type, but many of those relations lack a formal specification to give clear and unambiguous semantics to them. To remedy this, a formal taxonomy of types of mereological and meronymic part-whole relations is presented that distinguishes between transitive and intransitive relations and the kind of entity types that are related. The demand to use it effectively brings afore new requirements for automated reasoning over a hierarchy of relations. To ensure logically and ontologically correct inferencing over both the class and role hierarchy, the new reasoning service RBox compatibility for Description Logics reasoners is introduced. The proposed combination of formal semantics and the new reasoning service will improve the representation of the application domain when using part-whole relations in conceptual models and ontologies.
Improved Bounds for Wireless Localization
Authors: Tobias Christ, Michael Hoffmann, Yoshio Okamoto, Takeaki Uno
Venue: Proceedings of the 11th Scandinavian workshop on Algorithm Theory (2008)

We consider a novel class of art gallery problems inspired by wireless localization. Given a simple polygon P, place and orient guards each of which broadcasts a unique key within a fixed angular range. Broadcasts are not blocked by the edges of P. The interior of the polygon must be described by a monotone Boolean formula composed from the keys. We improve both upper and lower bounds for the general setting by showing that the maximum number of guards to describe any simple polygon on n vertices is between roughly ${\frac{3}{5}}$n and $\frac{4}{5}$n. For the natural setting where guards may be placed aligned to one edge or two consecutive edges of P only, we prove that n ¿ 2 guards are always sufficient and sometimes necessary.
A Comparative Study on Data Smoothing Regularization for Local Factor Analysis
Authors: Shikui Tu, Lei Shi, Lei Xu
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

Selecting the cluster number and the hidden factor numbers of Local Factor Analysis (LFA) model is a typical model selection problem, which is difficult when the sample size is finite or small. Data smoothing is one of the three regularization techniques integrated in the statistical learning framework, Bayesian Ying-Yang (BYY) harmony learning theory, to improve parameter learning and model selection. In this paper, we will comparatively investigate the performance of five existing formulas to determine the hyper-parameter namely the smoothing parameter that controls the strength of data smoothing regularization. BYY learning algorithms on LFA using these formulas are evaluated by model selection accuracy on simulated data and classification accuracy on real world data. Two observations are obtained. First, learning with data smoothing works better than that without it especially when sample size is small. Second, the gradient method derived from imposing a sample set based improper prior on the smoothing parameter generally outperforms other methods such as the one from Gamma or Chi-square prior, and the one under the equal covariance principle.
Speech Enhancement System Based on Auditory System and Time-Delay Neural Network
Authors: Jae-Seung Choi, Seung-Jin Park
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

This paper proposes a speech enhancement system based on an auditory system for noise reduction in speech that is degraded by background noises. Accordingly, the proposed system adjusts frame by frame the coefficients for both lateral inhibition and amplitude component according to the detected sections for each input frame, then reduces the noise signal using a time-delay neural network. Based on measuring signal-to-noise ratios, experiments confirm that the proposed system is effective for speech that is degraded by various noises.
Solving Three-Objective Optimization Problems Using a New Hybrid Cellular Genetic Algorithm
Authors: Juan José Durillo, Antonio Jesús Nebro, Francisco Luna, Enrique Alba
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

In this work we present a new hybrid cellular genetic algorithm. We take MOCell as starting point, a multi-objective cellular genetic algorithm, and, instead of using the typical genetic crossover and mutation operators, they are replaced by the reproductive operators used in differential evolution. An external archive is used to store the nondominated solutions found during the search process and the SPEA2 density estimator is applied when the archive becomes full. We evaluate the resulting hybrid algorithm using a benchmark composed of three-objective test problems, and we compare the results with several state of the art multi-objective metaheuristics. The obtained results show that our proposal outperforms the other algorithms according to the two considered quality indicators.
Unconsciously Harmonized Online Communication Based on Uninterruptibility Estimation of Interaction Partners
Authors: Takahiro Tanaka, Kyouhei Matsumura, Kinya Fujita
Venue: Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008)

The current users of real-time online communication tools have a problem in recognizing the status of interaction partners. Therefore, the start of dialogue has a risk of unintended interruption of the partner. To overcome the problem, we focused on application-switching (AS) as a potential intelligent activity discontinuity for uninterruptibility estimation. The preliminary experiments revealed the uninterruptibility reduction effect of AS. Therefore, we developed an online communication system which allows users to naturally recognize the uninterruptibility of interaction partners, by estimating uninterruptibility using AS, keystroke, mouse click and presenting uninterruptibility as avatar posture and motion.
Towards the Use of XPDL as Planning and Scheduling Modeling Tool: The Workflow Patterns Approach
Authors: Arturo González-Ferrer, Juan Fdez-Olivares, Luis Castillo, Lluvia Morales
Venue: Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence (2008)

This paper presents a transformation from a business process model diagram stored in XPDL format, into a hierarchical extension of the PDDL planning language, using the concept of workflow patterns as base of the translation process. The proposed architecture is evaluated within a specific teamwork project management scenario: the allocation of human resources and web services for the cooperative development of on-line courses in an e-learning center.
?Designer? Logic And Symbols with Logic Cell Arrays
Authors: Steve Landry
Venue: IEEE Micro (1987)

Logic cell arrays allow ASIC designers to create new logic elements and to devise symbols for them that simplify logic schematics. 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
Effective Algorithm for Detecting Community Structure in Complex Networks Based on GA and Clustering
Authors: Xin Liu, Deyi Li, Shuliang Wang, Zhiwei Tao
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

The study of networked systems has experienced a particular surge of interest in the last decade. One issue that has received a considerable amount of attention is the detection and characterization of community structure in networks, meaning the appearance of densely connected groups of vertices, with only sparser connections between groups. In this paper, we present an approach for the problem of community detection using genetic algorithm (GA) in conjunction with the method of clustering. We demonstrate that our algorithms are highly effective at discovering community structure in both computer-generated and real-world network data, and show how they can be used to shed light on the sometimes daunting complex real-world systems of scale-free network structure.
Learning Multi-dimensional Functions: Gas Turbine Engine Modeling
Authors: Chris Drummond
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

This paper shows how multi-dimensional functions, describing the operation of complex equipment, can be learned. The functions are points in a shape space, each produced by morphing a prototypical function located at its origin. The prototypical function and the space's dimensions, which define morphological operations, are learned from a set of existing functions. New ones are generated by averaging the coordinates of similar functions and using these to morph the prototype appropriately. This paper discusses applying this approach to learning new functions for components of gas turbine engines. Experiments on a set of compressor maps, multi-dimensional functions relating the performance parameters of a compressor, show that it more accurately transforms old maps, into new ones, than existing methods.
Visual Analysis Tool for Bipartite Networks
Authors: Kazuo Misue
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

To find hidden features of co-authoring relationships, we focused on drawing techniques for bipartite graphs. We previously developed a drawing method called "anchored maps", which is used to depict bipartite graphs visually. In anchored maps, some nodes are restricted to certain positions, but others are left to be arranged freely. In this study, we used our method to depict co-authoring relationships as anchored maps. The maps revealed certain co-authoring relationships. Anchored maps can help us discover important features that we cannot find when using only bipartite graphs that have a free layout.
Web Behaviormetric User Profiling Concept
Authors: Peter Géczy, Noriaki Izumi, Shotaro Akaho, Kôiti Hasida
Venue: Proceedings of the 9th international conference on E-Commerce and Web Technologies (2008)

We present a concept for building behaviorally centered user profiles. The concept utilizes behavioral analytics of user interactions in web environments. User interactions are temporally segmented into elemental browsing units. The browsing segments permit identification of the essential navigational points as well as higher order abstractions. The profiles incorporate relevant metrics from three major domains: temporal, navigational, and abstractions. Temporal metrics focus on aspects of durations and delays between portions of human interactions. The navigational metrics target the initial, terminal, and single user actions. The abstraction metrics encompass elemental patterns of human browsing behavior and their interconnections. The profiling concept utilizes relatively simple analytic and statistical apparatus. It facilitates computational efficiency and scalability to large user domains.
Combining One-Class Classification Models Based on Diverse Biological Data for Prediction of Protein-Protein Interactions
Authors: José A. Reyes, David Gilbert
Venue: Proceedings of the 5th international workshop on Data Integration in the Life Sciences (2008)

This research addresses the problem of prediction of protein-protein interactions (PPI) when integrating diverse biological data. Gold Standard data sets frequently employed for this task contain a high proportion of instances related to ribosomal proteins. We demonstrate that this situation biases the classification results and additionally that the prediction of non-ribosomal based PPI is a much more difficult task. In order to improve the performance of this subtask we have integrated more biological data into the classification process, including data from mRNA expression experiments and protein secondary structure information. Furthermore we have investigated several strategies for combining diverse one-class classification (OCC) models generated from different subsets of biological data. The weighted average combination approach exhibits the best results, significantly improving the performance attained by any single classification model evaluated.
Automatic G1 Surface Reconstruction from Serial Cross-Sectional Images
Authors: Fatimah Yahya, Jamaludin Md Ali, Ahmad Abdul Majid, Arsmah Ibrahim
Venue: Proceedings of the 10th international conference on Visual Information Systems: Web-Based Visual Information Search and Management (2008)

Biomedical imaging facilities today like MRI, PET, CT scan and confocal microscopy produce sequentially parallel cross sectional images. Recon-structing trustworthy 3D explicit models which enable better understanding of the topology and shape of structure is crucial in facilitating diagnosis, improves surgical planning and aid in biological research.Our technique produce a surface from G1 cross sectional contour curves of images. Surface accuracy is controlled by a tolerance measure. Features can be isolated and identified for corresspondence.First the boundaries of the region of interest are extracted and corner points detected. G1 rational Bezier cubics, iteratively determined, are fitted piecewise between these corners and approximating the boundary. as close as need be. Adjacent contour curves are blended together to form the surface. Technique is fully automatic.
Homomorphic Encryption with CCA Security
Authors: Manoj Prabhakaran, Mike Rosulek
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part II (2008)

We address the problem of constructing public-key encryption schemes that meaningfully combine useful computability features with non-malleability. In particular, we investigate schemes in which anyone can change an encryption of an unknown message m into an encryption of T(m) (as a feature), for a specific set of allowed functions T, but the scheme is "non-malleable" with respect to all other operations. We formulate precise definitions that capture these intuitive requirements and also show relationships among our new definitions and other more standard ones (IND-CCA, gCCA, and RCCA). We further justify our definitions by showing their equivalence to a natural formulation of security in the Universally Composable framework. We also consider extending the definitions to features which combine multiple ciphertexts, and show that a natural definition is unattainable for a useful class of features. Finally, we describe a new family of encryption schemes that satisfy our definitions for a wide variety of allowed transformations T, and which are secure under the standard Decisional Diffie-Hellman (DDH) assumption.
Embodied Creative Agents: A Preliminary Social-Cognitive Framework
Authors: Stéphanie Buisine, Améziane Aoussat, Jean-Claude Martin
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

The goal of this paper is to open discussion about industrial creativity as a potential application field for Embodied Conversational Agents. We introduce the domain of creativity and especially focus on a collective creativity tool, the brainstorming: we present the related research in Psychology which has identified several key cognitive and social mechanisms that influence brainstorming process and outcome. However, some dimensions remain unexplored, such as the influence of the partners' personality or the facilitator's personality on idea generation. We propose to explore these issues, among others, using Embodied Conversational Agents. The idea seems original given that Embodied Agents were never included into brainstorming computer tools. We draw some hypotheses and a research program, and conclude on the potential benefits for the knowledge on creativity process on the one hand, and for the field of Embodied Conversational Agents on the other hand.