ppxscal/embedding_network huggingface dataset:
Fast Generalized Belief Propagation for MAP Estimation on 2D and 3D Grid-Like Markov Random Fields
Authors: Kersten Petersen, Janis Fehr, Hans Burkhardt
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

In this paper, we present two novel speed-up techniques for deterministic inference on Markov random fields (MRF) via generalized belief propagation (GBP). Both methods require the MRF to have a grid-like graph structure, as it is generally encountered in 2D and 3D image processing applications, e.g. in image filtering, restoration or segmentation. First, we propose a caching method that significantly reduces the number of multiplications during GBP inference. And second, we introduce a speed-up for computing the MAP estimate of GBP cluster messages by presorting its factors and limiting the number of possible combinations. Experimental results suggest that the first technique improves the GBP complexity by roughly factor 10, whereas the acceleration for the second technique is linear in the number of possible labels. Both techniques can be used simultaneously.
Currents: Trends, People, Projects
Authors: Greg Goth, Dave Dorenbos, Virginia Dorenbos
Venue: IEEE Software (2007)

The first news story, "Will the Semantic Web Quietly Revolutionize Software Engineering?" looks at attempts to leverage Semantic Web technology to improve software development. The second news story, "The Possible Futures of Service Software," reports on the conference The New Software Industry: Forces at Play, Business in Motion.
Sacrificing a little coverage can substantially increase network lifetime
Authors: Limin Wang, Sandeep S. Kulkarni
Venue: Ad Hoc Networks (2008)

We present a simple, local protocol, pCover, which provides partial (but high) coverage in sensor networks. Through pCover, we demonstrate that it is feasible to maintain a high coverage (~90%) while significantly increasing coverage duration when compared with protocols that provide full coverage. In particular, we show that we are able to maintain 94% coverage for a duration that is 2.3-7 times the duration for which existing protocols maintain full coverage. Through simulations, we show that our protocol provides load balancing, i.e., the desired level of coverage is maintained (almost) until the point where all sensors deplete their batteries. We also show that pCover handles failure of sensors, different coverage areas, different node densities, and different topologies, and can be used for dynamically changing the level of coverage.
Categorical Representation of Evolving Structure of an Ontology for Clinical Fungus
Authors: Arash Shaban-Nejad, Volker Haarslev
Venue: Proceedings of the 11th conference on Artificial Intelligence in Medicine (2007)

With increasing popularity of using ontologies, many industrial and clinical applications have employed ontologies as their conceptual backbone. Ontologies try to capture knowledge from a domain of interest and when the knowledge changes, the definitions will be altered. We study change management in the FungalWeb Ontology, which is the result of integrating numerous biological databases and web accessible textual resources. The fungal taxonomy is currently unstable and evolves over time. This evolution can be seen in both nomenclature and the taxonomic structure. In an experiment we have focused on changes in medical species of fungus which can potentially alter the related disease name and description in an integrated clinical system. In order to address certain aspects of representation of changes in an ontology driven clinical application we propose a methodology based on category theory as a mathematical notation, which is independent of a specific choice of ontology language and any particular implementation.
Building Quality-Based Views of the Web
Authors: Enrico Triolo, Nicola Polettini, Diego Sona, Paolo Avesani
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

Due to the fast growing of the information available on the Web, the retrieval of relevant content is increasingly hard. The complexity of the task is concerned both with the semantics of contents and with the filtering of quality-based sources. A recent strategy addressing the overwhelming amount of information is to focus the search on a snapshot of internet, namely a Web view. In this paper, we present a system supporting the creation of a quality-based view of the Web. We give a brief overview of the software and of its functional architecture. More emphasis is on the role of AI in supporting the organization of Web resources in a hierarchical structure of categories. We survey our recent works on document classifiers dealing with a twofold challenge. On one side, the task is to recommend classifications of Web resources when the taxonomy does not provide examples of classification, which usually happens when taxonomies are built from scratch. On the other side, even when taxonomies are populated, classifiers are trained with few examples since usually when a category achieves a certain amount of Web resources the organization policy suggests a refinement of the taxonomy. The paper includes a short description of a couple of case studies where the system has been deployed for real world applications.
Model-based functional size measurement
Authors: Luigi A. Lavazza, Vieri del Bianco, Carla Garavaglia
Venue: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement (2008)

Function Point Analysis (FPA) is the most widely used method for measuring the size of software requirements, usually for the purpose of cost estimation. Unfortunately, FPA is affected by several drawbacks: it must be performed by specifically skilled personnel, it is expensive, and the resulting measures are subject to high variability. In order to solve - at least partially - these problems, researchers have proposed to base FP counting on UML models. However, models built without having FPA in mind hardly provide the required information at the proper detail level, so that the measures of the models tend to vary accordingly. On the contrary, building models that are suitable for FPA generally requires additional notations, skills and effort, thus partly spoiling the advantages of the approach. This paper illustrates a technique for building FPA-oriented UML models that do not need to include more information than usually required by the development process, and are easy to measure. As a result, FPA can be performed in a seamless way, while yielding reliable results. The proposed technique was validated by means of a controlled experiment and a set of pilot applications, which are also briefly described in the paper.
Thermal model for dc characteristics of algan/gan hemts including self-heating effect and non-linear polarization
Authors: Manju K. Chattopadhyay, Sanjiv Tokekar
Venue: Microelectronics Journal (2008)

A thermal model based on the polynomial relationship of n"s and E"F is presented. The effect of temperature rise due to self-heating is studied on various parameters viz. polarization, electron mobility, velocity saturation, low-field mobility and thermal conductivity of substrate. Parasitic resistances and channel length modulation were also taken into consideration. The relationship between self-heating effect and device parameters was studied. The model is based on closed-form expressions and does not require elaborate computation. After including self-heating effect in calculations of current-voltage characteristics, our results agreed well with published experimental data.
A self-adaptive query service for pervasive environments
Authors: Hocine Grine, Thierry Delot, Sylvain Lecomte
Venue: Proceedings of the 8th international conference on New technologies in distributed systems (2008)

The query service is the key element enabling users to identify and access data or services. If the growth of mobility in recent years makes it necessary to support different types of queries (continuous, location dependent, spatio-temporal, etc.,), it has also resulted in the emergence of new and specifique evaluation and optimization techniques. These different types of queries or techniques are useful and efficient depending on the usage conditions in which the user is located. Today, it is necessary to have, in pervasive environments, a query service that adapts to context changes (application constraints, user preferences, connectivity profile mobility, etc.). In this paper we propose an architecture of a query service dynamically adaptable to the context. This adaptability is managed and controled by an adaptation manager by use of rules. Our solution not only allows the addition and removal of new features dynamically, it also allows the change of used evaluation techniques in order to use the adapted one to the environment.
A scalable, commodity data center network architecture
Authors: Mohammad Al-Fares, Alexander Loukissas, Amin Vahdat
Venue: Proceedings of the ACM SIGCOMM 2008 conference on Data communication (2008)

Today's data centers may contain tens of thousands of computers with significant aggregate bandwidth requirements. The network architecture typically consists of a tree of routing and switching elements with progressively more specialized and expensive equipment moving up the network hierarchy. Unfortunately, even when deploying the highest-end IP switches/routers, resulting topologies may only support 50% of the aggregate bandwidth available at the edge of the network, while still incurring tremendous cost. Non-uniform bandwidth among data center nodes complicates application design and limits overall system performance. In this paper, we show how to leverage largely commodity Ethernet switches to support the full aggregate bandwidth of clusters consisting of tens of thousands of elements. Similar to how clusters of commodity computers have largely replaced more specialized SMPs and MPPs, we argue that appropriately architected and interconnected commodity switches may deliver more performance at less cost than available from today's higher-end solutions. Our approach requires no modifications to the end host network interface, operating system, or applications; critically, it is fully backward compatible with Ethernet, IP, and TCP.
Privacy Preserving Market Basket Data Analysis
Authors: Ling Guo, Songtao Guo, Xintao Wu
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

Randomized Response techniques have been empirically investigated in privacy preserving association rule mining. However, previous research on privacy preserving market basket data analysis was solely focused on support/ confidence framework. Since there are inherent problems with the concept of finding rules based on their support and confidence measures, many other measures (e.g., correlation, lift, etc.) for the general market basket data analysis have been studied. How those measures are affected due to distortion is not clear in the privacy preserving analysis scenario.In this paper, we investigate the accuracy (in terms of bias and variance of estimates) of estimates of various rules derived from the randomized market basket data and present a general framework which can conduct theoretical analysis on how the randomization process affects the accuracy of various measures adopted in market basket data analysis. We also show several measures (e.g., correlation) have monotonic property, i.e., the values calculated directly from the randomized data are always less or equal than those original ones. Hence, some market basket data analysis tasks can be executed on the randomized data directly without the release of distortion probabilities, which can better protect data privacy.
Computer Algebra: A `Classical' Path to Explore Decoherence and Entanglement Phenomena in Quantum Information Theory
Authors: Stephan Fritzsche
Venue: Proceedings of the 10th international workshop on Computer Algebra in Scientific Computing (2007)

During the past decade, quantum information theory has attracted a lot of interest because of its promise for solving problems that are intractable otherwise. Despite of the recent advancements in understanding the basic principles of quantum information systems, however, there are still a large number of difficulties to be resolved. One of the great challenges concerns for instance the decoherence in quantum systems and how entanglement is lost or transfered between the subsystems, if they are coupled to their enviroment. -- To overcome these difficulties, several schemes for studying the decay of quantum states and their interaction with an environment have been developed during recent years, including a large variety of separability and entanglement measures, decoherence-free subspaces as well as (quantum) error correction codes.To support the investigation of entanglement and decoherence phenomena in general N ¿qubit quantum systems, we recently developed the Feynman program [1], a computer-algebraic approach within the framework of Maple, which facilitates the symbolic and numerical manipulation of quantum registers and quantum transformations. This program has been designed for studying the dynamics of quantum registers owing to their interaction with external fields and perturbations. In a recent addition to this program [2], moreover, we now implemented also various noise models as well as a number of entanglement measures (and related quantities). In this lecture, I shall display the interactive use of the program by a number of simple but intuitive examples.To make quantum information theory alive, an active (re-) search has been initiated during the past decade to find and explore physical systems that are suitable to produce and control the entanglement in course of their time evolution. In atomic photoionization, for instance, we have shown how the polarization can be transfered from the incoming photons to the emitted photoelectrons, giving rise to a (spin-spin) entanglement between the photoelectron and the remaining (photo-) ion. Detailed computations on the entanglement as function of the energy and polarization of the incoming light have been carried out along various isoelectronic sequences [3]. For the two-photon decay of atomic hydrogen, moreover, we analyzed the geometrical control of the polarization entanglement of the emitted photons. 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
Usability Evaluation in Task Orientated Collaborative Environments
Authors: Florian Urmetzer, Vassil Alexandrov
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

An evaluation of the usability is often neglected in the software development cycle, even that it was shown in the past that a careful look at the usability of a software product has impact on its adoption. With the recent arising of software supporting collaboration between multiple users, it is obvious that usability testing will get more complex because of the multiplication of user interfaces and their physical distribution. The need for new usability testing methodologies and tools for their support under these circumstances is one consequence. This paper widens the methodologies of usability evaluation to computing systems supporting the solving of a collaborative work task. Additionally details of a distributed screen recording tool are described that can be used to support usability evaluation in a collaborative context.
MAP-Inference for Highly-Connected Graphs with DC-Programming
Authors: Jörg Kappes, Christoph Schnörr
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-functions, and highly-connected structures of the underlying graph render this problem particularly difficult. Established techniques that work well for sparsely connected grid-graphs used for image labeling, degrade for non-sparse models used for object recognition.In this context, we present a new class of mathematically sound algorithms that can be flexibly applied to this problem class with a guarantee to converge to a critical point of the objective function. The resulting iterative algorithms can be interpreted as simple message passing algorithms that converge by construction, in contrast to other message passing algorithms.Numerical experiments demonstrate its performance in comparison with established techniques.
Perspectives in Optical Computing
Authors: H. John Caulfield
Venue: Computer (1998)

Optical computing is dead only if we foolishly define it as the attempt to supplant electronics. The hope for optics lies in doing things that are provably impossible for electronics.
Intelligent GPS-Based Vehicle Control for Improved Fuel Consumption and Reduced Emissions
Authors: S. H. Lee, S. D. Walters, R. J. Howlett
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

The development of in-vehicle control systems such as Global Positioning Systems (GPS) provides static and dynamic road information. This widely accessible technology can be used to develop an auxiliary control sub-system to reduce vehicle fuel consumption as well as improve road safety and comfort. The raw GPS data from the receiver were processed and integrated with the past trajectory using a Neuro-fuzzy technique. The system essentially used a fuzzy logic derived relief map of the test route and this was further validated and corrected based on the past trajectory from the GPS sensor. The information was then processed and translated in order to estimate the future elevation of the vehicle. Experimental results demonstrated the feasibility and robustness of the system for potential application in vehicle control for reduced fuel consumption and emissions.
K-Means with Large and Noisy Constraint Sets
Authors: Dan Pelleg, Dorit Baras
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

We focus on the problem of clustering with soft instance-level constraints. Recently, the CVQE algorithm was proposed in this context. It modifies the objective function of traditional K-means to include penalties for violated constraints. CVQE was shown to efficiently produce high-quality clustering of UCI data. In this work, we examine the properties of CVQE and propose a modification that results in a more intuitive objective function, with lower computational complexity. We present our extensive experimentation, which provides insight into CVQE and shows that our new variant can dramatically improve clustering quality while reducing run time. We show its superiority in a large-scale surveillance scenario with noisy constraints.
A survey of dynamic service composition approaches for ambient systems
Authors: Aitor Urbieta, Guillermo Barrutieta, Jorge Parra, Aitor Uribarren
Venue: Proceedings of the 2008 Ambi-Sys workshop on Software Organisation and MonIToring of Ambient Systems (2008)

Ambient systems are populated by autonomous devices interconnected to one another that supply a variety of functionality that is eventually used by the users. One of the biggest challenges in this research area is to establish automatic mechanisms to compose, in a dynamic way, services on demand. The objective of the composition is to satisfy user needs combining the existing services, when there is not a service in the environment that can perform it. The aim of this research work is, firstly, to have a look at and analyze the state of the art regarding service composition in ubiquitous environments and, secondly, to propose a set of properties and characteristics that can be applied to this type of systems to allow their classification and ultimately their scientific comparison.
Machinery Vibration Signals Analysis and Monitoring for Fault Diagnosis and Process Control
Authors: Juan Dai, C. L. Chen, Xiao-Yan Xu, Ying Huang, Peng Hu, Chi-Ping Hu, Tao Wu
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

The vibration signals contain a wealth of complex information that characterizes the dynamic behavior of the machinery. Monitoring rotating machinery is often accomplished with the aid of vibration sensors. Transforming this information into useful knowledge about the health of the machine can be challenging due to the presence of extraneous noise sources and variations in the vibration signal itself. This paper describes applying vibration theory to detect machinery fault, via the measurement of vibration and voice monitoring machinery working condition, also proposes a useful way of vibration analysis and source identification in complex machinery. An actual experiment case study has been conducted on a mill machine. The experiment results indicate that fewer sensors and less measurement and analysis time can achieve condition monitoring, fault diagnosis, and damage forecasting. Further applications allow feedback to the process control on production line.
Predicting future locations using prediction-by-partial-match
Authors: Ingrid Burbey, Thomas L. Martin
Venue: Proceedings of the first ACM international workshop on Mobile entity localization and tracking in GPS-less environments (2008)

We implemented the Prediction-by-Partial-Match data compression algorithm as a predictor of future locations. Positioning was done using IEEE 802.11 wireless access logs. Several experiments were run to determine how to divide the data for training and testing and how to best represent the data as a string of symbols. Our test data consisted of 198 datasets containing over 28,000
A Decision-Tree-Based Online Speaker Clustering
Authors: Wei Wang, Ping Lv, Qingwei Zhao, Yonghong Yan
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I (2007)

When performing online speaker clustering, it is common to make clustering decision as soon as an audio segment is received. When the wrong decision is made, the error can propagate the posterior clustering. This paper describes a decision-tree-based online speaker clustering algorithm. Unlike typical online clustering approaches, the proposed method constructs a decision tree when an audio segment is received. A pruning strategy for candidate-elimination is also applied. Experiments indicate that the algorithm achieves good performance on both precision and speed. Finally, we discuss the relation between the performance and the width of the decision tree beam.