ppxscal/embedding_network huggingface dataset:
Pixel Coverage Segmentation for Improved Feature Estimation
Authors: Nataša Sladoje, Joakim Lindblad
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

By utilizing intensity information available in images, partial coverage of pixels at object borders can be estimated. Such information can, in turn, provide more precise feature estimates. We present a pixel coverage segmentation method which assigns pixel values corresponding to the area of a pixel that is covered by the imaged object(s). Starting from any suitable crisp segmentation, we extract a one-pixel thin 4-connected boundary between the observed image components where a local linear mixture model is used for estimating fractional pixel coverage values. We evaluate the presented segmentation method, as well as its usefulness for subsequent precise feature estimation, on synthetic test objects with increasing levels of noise added. We conclude that for reasonable noise levels the presented method outperforms the achievable results of a perfect crisp segmentation. Finally, we illustrate the application of the suggested method on a real histological colour image.
Adaptive control for autonomous underwater vehicles
Authors: Conor McGann, Frederic Py, Kanna Rajan, John Ryan, Richard Henthorn
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

We describe a novel integration of Planning with Probabilistic State Estimation and Execution. The resulting system is a unified representational and computational framework based on declarative models and constraint-based temporal plans. The work is motivated by the need to explore the oceans more cost-effectively through the use of Autonomous Underwater Vehicles (AUV), requiring them to be goal-directed, perceptive, adaptive and robust in the context of dynamic and uncertain conditions. The novelty of our approach is in integrating deliberation and reaction over different temporal and functional scopes within a single model, and in breaking new ground in oceanography by allowing for precise sampling within a feature of interest using an autonomous robot. The system is general-purpose and adaptable to other ocean going and terrestrial platforms.
A Reduction Theorem for the Verification of Round-Based Distributed Algorithms
Authors: Mouna Chaouch-Saad, Bernadette Charron-Bost, Stephan Merz
Venue: Proceedings of the 3rd International Workshop on Reachability Problems (2009)

We consider the verification of algorithms expressed in the Heard-Of Model, a round-based computational model for fault-tolerant distributed computing. Rounds in this model are communication-closed, and we show that every execution recording individual events corresponds to a coarser-grained execution based on global rounds such that the local views of all processes are identical in the two executions. This result helps us to substantially mitigate state-space explosion and verify Consensus algorithms using standard model checking techniques.
Patterns, Movement and Clinical Diagnosis of Abdominal Adhesions
Authors: Benjamin Wright, John Fenner, Richard Gillott, Paul Spencer, Patricia Lawford, Karna Dev Bardhan
Venue: Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics (2009)

Patterns in normal abdominal movement captured with medical imaging can be recognised by a trained radiologist but the process is time consuming. Abdominal adhesions present a diagnostic problem in which the radiologist is asked to detect abnormal movement that may be indicative of pathology. This paper postulates that the use of image analysis can augment the diagnostic abilities of the radiologist in respect of adhesions. Proof of concept experiments were conducted in-silico to explore the effectiveness of the technique. The results indicate that trained participants are accurate in their assessment of abnormalities when supplied with additional information from image analysis techniques. However without the additional information, participants made incorrect diagnoses on many occasions. ROC methods were used to quantify the outcomes of the in-silico experiment.
Automatic Building Detection Using Airborne LIDAR Data
Authors: Zhang Hao, Zhang Yongsheng, Liu Jun, Ji Song
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

A method automatically extracting buildings from LIDAR data is presented. LIDAR point clouds are re-sampled into regular grid DSM, and a filtering processing which filters out non-ground points on the DSM surface is carried out simultaneously, acquiring a DEM with only ground points. An nDSM is obtained by subtracting DEM from DSM, and the building candidate regions are identified by using some thresholds to the nDSM. For these building candidates, we extract texture features in each candidate region, that is image texture based on Gray Level Co-occurrence Matrix (GLCM). Unsupervised clustering method is used with these features to separate building candidates from trees and vegetations. The workflow is presented in this paper and an example for a test site in Glenville approves it.
Joule expansion imaging techniques on microlectronic devices
Authors: Stéphane Grauby, Luis-David Patino Lopez, Amine Salhi, Etienne Puyoo, Jean-Michel Rampnoux, Wilfrid Claeys, Stefan Dilhaire
Venue: Microelectronics Journal (2009)

We have studied the electrically induced off-plane surface displacement on two microelectronic devices using scanning Joule expansion microscopy (SJEM). We present the experimental method and surface displacement results. We show that they can be successfully compared with surface displacement images obtained using an optical interferometry method. We also present thermal images using scanning thermal microscopy (SThM) technique to underline that SJEM is more adapted to higher frequency measurements. The performances of the three methods are compared.
Learning Model Complexity in an Online Environment
Authors: Dan Levi, Shimon Ullman
Venue: Proceedings of the 2009 Canadian Conference on Computer and Robot Vision (2009)

In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification problems in the visual domain (such as recognizing handwriting, faces and human-body images) often require a large number of training examples, which may become available over a long training period. This motivates the development of scalable and adaptive systems which are able to continue learning at any stage and which can efficiently learn from large amounts of data, in an on-line manner. Previous approaches to on-line learning in visual classification have used a fixed parametric model, and focused on continuously improving the model parameters as more data becomes available. Here we propose a new framework which enables online learning algorithms to adjust the complexity of the learned model to the amount of the training data as more examples become available. Since in online learning the training set expands over time, it is natural to allow the learned model to become more complex during the course of learning instead of confining the model to a fixed family of a bounded complexity. Formally, we use a set of parametric classifiers y = hαθ (x) where y is the class and x the observed data. The parameter α controls the complexity of the model family. For a fixed α, the training examples are used for the optimal setting of θ. When the amount of data becomes sufficiently large, the value of α is increased, and a more complex model family is used. For evaluation of the proposed approach, we implement an online Support Vector Machine with increasing complexity, and evaluate in a task of handwritten character recognition on the MNIST database.
Fuzzy Control of Air-Suction Seeding Device Based on SPCE061A
Authors: Gao Lin, Wang Nai-kang, Li Wen-bin, Zhang Jun-mei
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

In order to make sure the seeding quality of air-suction seeding device, it is very important to control the vacuum degree of sowing drum. In this paper, the structure and principles of air-suction seeding device was introduced briefly and a fuzzy control system to control vacuum degree based on SPCE061A was presented. According to the features of SPCE061A and control demands of seeding device in the seedling production line, a new control technique combining speech control with fuzzy control was proposed to control seeding device. A layout about two-dimensional fuzzy controller was described. The dynamical simulation was carried out by using the MATLAB fuzzy toolbox. The result of simulation demonstrated that it was feasible to adopt the method of fuzzy control to control the vacuum degree of sowing drum in air-suction seeding device.
Software Calibration of Wirelessly Networked Sensors
Authors: Bernard Tourancheau, Yannis Mazzer, Valentin Gavan, Frédéric Kuznik, Gérard Krauss
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

This paper introduces our work on the communication stack of wireless sensor networks. We present the IPv6 approach for wireless sensor networks called 6LoWPAN in its IETF charter. We then compare the different implementations of 6LoWPAN subsets for several sensor nodes platforms. This paper presents our work with Wireless Sensor Networks for the calibration of the embedded sensor chips located in each Wireless Sensor Networks node. We propose a software compensation applied on data sources for each devices. We implement such a calibration process at the initialization of the Wireless Sensor Networks and we propose a software module on each node to regularly improve the measurement accuracy. The results shows the temperature measurements improvements for our energy efficiency in building testbed.
Performance Evaluation for Multistage Interconnection Networks Servicing Multicast Traffic
Authors: John Garofalakis, Eleftherios Stergiou
Venue: Proceedings of the 2009 First International Conference on Advances in Future Internet (2009)

Multistage Interconnection Networks (MINs) provide efficient communication resources between network components in an ap¬pealing cost/performance relation. Consequently, they have been widely used on Internet connections such as ATM and gigabit Ethernet switches, terabit routers as well as for interconnecting parallel systems. In this paper a novel analytical method for providing performance evaluation on MINs is presented under multicast environment. The proposed analysis was applied on various network size MINs constructed by variable buffer-length Switching Elements (SEs) per network stage, supporting mixed traffic patterns such as unicast and multicast, under various offered loads in uniform traffic conditions.The applied multicasting policy, where a packet is copied and transmitted when only both destina¬tion buffers are available has not been considered insofar by former models. This mechanism, which is called "full-multicast" was employed by all SEs using the "Cell Replication While Routing" (CRWR) technique.The proposed architecture, which is thoroughly analyzed by our novel analytical model, can be also useful in performance study and development of other internet communication links supporting multicast traffic.
A New Sensorless Design for PMLSM Servo Control System
Authors: Zhili Liu, Xingcheng Huang, Shuwang Du, Mingxuan Sun
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

In this paper a new method to inspect the speed and position of linear motor is presented. We find the mathematical model of PMLSM in the rotationary dq coordinate contains the nonlinear term and it satisfies Lipschitz conditions. So we introduce an observer design method for Lipschitz nonlinear systems in the presence of bounded disturbances and give the stability condition of the observer with the form of LMI. Based on this method we estimate the speed of the linear motor, the result of which can be used to calculate the position of motor’s magnetic pole together with formulae. To support the theoretical concepts, we set up a sensorless linear servo control system for PMLSM. The simulation results prove the feasibility of the proposed method.
Discussion of Max-limited Speed for Work Zone of Highway Based on Information Processing
Authors: Yihu Wu, Xiaomei Yin, Dan Yu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

Set a reasonable value of max-limited speed is an important part of traffic control. On the basis of systematically analyzing the information processing mode of driver and considered the performance differences of different vehicles, each kind of traffic information in work zone is classified and quantified and a calculation method of different vehicles’ max-limited speed for work zone of highway is discussed according to drivers’ information processing ability. Considered there are large and small two kinds of vehicles in the case, samples of different width and length of work zone are given to testify the max-limited speed value, which is changed along with the geometrical shape of work zone. And result of the max-limited speed value of different vehicles is dissimilar, thus the method of max-limited speed based on information processing is feasible.
The achilles' heel of QBF
Authors: Carlos Ansotegui, Carla P. Gomes, Bart Selman
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

In recent years we have seen significant progress in the area of Boolean satisfiability (SAT) solving and its applications. As a new challenge, the community is now moving to investigate whether similar advances can be made in the use of Quantified Boolean Formulas (QBF). QBF provides a natural framework for capturing problem solving and planning in multi-agent settings. However, contrarily to single-agent planning, which can be effectively formulated as SAT, we show that a QBF approach to planning in a multi-agent setting leads to significant unexpected computational difficulties. We identify as a key difficulty of the QBF approach the fact that QBF solvers often end up exploring a much larger search space than the natural search space of the original problem. This is in contrast to the experience with SAT approaches. We also show how one can alleviate these problems by introducing two special QBF formulations and a new QBF solution strategy. We present experiments that show the effectiveness of our approach in terms of a significant improvement in performance compared to earlier work in this area. Our work also provides a general methodology for formulating adversarial scenarios in QBF.
Affectively Intelligent User Interfaces for Enhanced E-Learning Applications
Authors: Fatma Nasoz, Mehmet Bayburt
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

In this article we describe a new approach for electronic learning applications to interact with their users. First we discuss our motivation to build affectively intelligent user interfaces that can recognize learning related emotions and adapt to these through user modeling. In the remainder of the paper we describe the experiment we designed to elicit learning related emotions from students in order collect their physiological signals while they are experiencing those emotions and to classify those physiological signals into emotional states with pattern recognition algorithms.
AFPL2, an Abstract Language for Firewall ACLs with NAT Support
Authors: S. Pozo, A. J. Varela-Vaca, R. M. Gasca
Venue: Proceedings of the 2009 Second International Conference on Dependability (2009)

The design and management of firewall ACLs is a very hard and error-prone task. Part of this complexity comes from the fact that each firewall platform has its own low-level language with a different functionality, syntax, and development environment. Although high-level languages have been proposed to model firewall ACLs, none of them has been widely adopted by the industry due to a combination of factors: high complexity, no support of important features of firewalls, etc. In this paper the most important access control policy languages are reviewed, with special focus on the development of firewall ACLs. Based on this analysis, a new domain specific language for firewall ACLs (AFPL2) is proposed, supporting more features that other languages do not cover (e.g. NAT). As the result of our design methodology, AFPL2 is very lightweight and easy to use. AFPL2 can be translated to existing low-level firewall languages, or be directly interpreted by firewall platforms, and is an extension to a previously developed language.
Representing and Reasoning about Different Viewpoints: An Agronomy Application
Authors: Madalina Croitoru, Rallou Thomopoulos
Venue: Proceedings of the 17th International Conference on Conceptual Structures: Conceptual Structures: Leveraging Semantic Technologies (2009)

Real-world applications are often complex systems where several ways of analysing a given situation can be expressed, depending on actors' viewpoints. This paper proposes a semantically sound syntactic extension to Conceptual Graphs, namely Conceptual Graph Assemblies (CGAs), that allows the representation of multiple viewpoints on the same situation. Several reasoning mechanisms, based on the projection operation, corresponding to different strength levels and adapted to multi-viewpoints situations are then demonstrated. Several modelling scenarios are then proposed and our work is put in the context of real world examples from the agri-food domain.
Housing: Socioeconomic, Availability and Development Issues
Authors: Vitaly I. Voloshin
Venue:  (2009)

This book is for math and computer science majors, for students and representatives of many other disciplines (like bioinformatics, for example) taking courses in graph theory, discrete mathematics, data structures, algorithms. It is also for anyone who wants to understand the basics of graph theory, or just is curious. No previous knowledge in graph theory or any other significant mathematics is required. The very basic facts from set theory, proof techniques and algorithms are sufficient to understand it; but even those are explained in the text. Structurally, the text is divided into two parts where Part II is the generalization of Part I.The first part discusses the key concepts of graph theory with emphasis on trees, bipartite graphs, cycles, chordal graphs, planar graphs and graph coloring. The second part considers generalizations of Part I and discusses hypertrees, bipartite hyper graphs, hyper cycles, chordal hyper graphs, planar hyper graphs and hyper graph coloring. There is an interaction between the parts and within the parts to show how ideas of generalizations work. The main point is to exhibit the ways of generalizations and interactions of mathematical concepts from the very simple to the most advanced. One of the features of this text is the duality of hyper graphs.This fundamental concept is missing in graph theory (and in its introductory teaching) because dual graphs are not properly graphs, they are hyper graphs. However, as Part II shows, the duality is a very powerful tool in understanding, simplifying and unifying many combinatorial relations; it is basically a look at the same structure from the opposite (vertices versus edges) point of view. 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
Parameter Estimation for Marked Point Processes. Application to Object Extraction from Remote Sensing Images
Authors: Florent Chatelain, Xavier Descombes, Josiane Zerubia
Venue: Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (2009)

This communication addresses the problem of estimating the parameters of a family of marked point processes. These processes are of interest in extraction of object networks from remote sensing images. They are defined from a combination of several energy terms. First, a data energy term controls the localization of the objects with respect to the data. Second, prior information is given by intern energy terms corresponding to geometrical constraints on the configuration to be detected. An estimation procedure of the weight associated with these energies is studied. The application to unsupervised detection of objects is finally discussed.
Complex Diffusion on Scalar and Vector Valued Image Graphs
Authors: Dohyung Seo, Baba C. Vemuri
Venue: Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (2009)

Complex diffusion was introduced in the image processing literature as a means to achieve simultaneous denoising and enhancement of scalar valued images. In this paper, we present a novel geometric framework to achieve complex diffusion for color images represented by image graphs. In this framework, we develop a novel variational formulation that involves a modified harmonic map functional and is quite distinct from the Polyakov action described by Sochen et al. Our formulation provides a novel framework for simultaneous feature preserving denoising and enhancement. We also develop a quaternionic diffusion that can be applied to color image data represented by a quaternion in the image graph framework. In this framework, the real and imaginary parts can be interpreted as low and high-pass filtered data respectively. Finally, we suggest novel ways to use the imaginary part of complex diffusion toward image reconstruction. We present results of comparison between the complex diffusion, quaternionic diffusion and the well known Beltrami flow in the image graph framework.
Assessing and improving the performance of speech recognition for incremental systems
Authors: Timo Baumann, Michaela Atterer, David Schlangen
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (2009)

In incremental spoken dialogue systems, partial hypotheses about what was said are required even while the utterance is still ongoing. We define measures for evaluating the quality of incremental ASR components with respect to the relative correctness of the partial hypotheses compared to hypotheses that can optimize over the complete input, the timing of hypothesis formation relative to the portion of the input they are about, and hypothesis stability, defined as the number of times they are revised. We show that simple incremental post-processing can improve stability dramatically, at the cost of timeliness (from 90 % of edits of hypotheses being spurious down to 10 % at a lag of 320 ms). The measures are not independent, and we show how system designers can find a desired operating point for their ASR. To our knowledge, we are the first to suggest and examine a variety of measures for assessing incremental ASR and improve performance on this basis.
A Thai speech translation system for medical dialogs
Authors: Tanja Schultz, Dorcas Alexander, Alan W. Black, Kay Peterson, Sinaporn Suebvisai, Alex Waibel
Venue: Demonstration Papers at HLT-NAACL 2004 on XX (2004)

In this paper we present our activities towards a Thai Speech-to-Speech translation system. We investigated in the design and implementation of a prototype system. For this purpose we carried out research on bootstrapping a Thai speech recognition system, developing a translation component, and building an initial Thai synthesis system using our existing tools.