ppxscal/embedding_network huggingface dataset:
1st international workshop on ambient media delivery and interactive television
Authors: Maria Luisa Sapino
Venue: Proceedings of the 2008 Ambi-Sys workshop on Ambient media delivery and interactive television (2008)

Through new interactive features, television is becoming a central hub for entertainment, communication, and sharing. Instead of old, push-based broadcasting to set-top-boxes, new pull-based, interactive services and tighter integration with other audio/visual entertainment devices enable ambient access to tv programming. Thus, with the steering committee members, Marina Geymonat (Telecom Italia, Italy) and Roberto Rossetto (RAI-Teche, Italy), we have envisioned and organized the Ambient Media Delivery and Interactive Television workshop, AMDIT 2008, focusing on the data management challenges associated with the design of ambient media delivery and user aware interactive television systems, to make television programmes available and easily accessible in multiple contexts, through diverse media devices. Below, I provide an overview of the contributions to the workshop.
Study of Image Splicing Detection
Authors: Zhen Zhang, Ying Zhou, Jiquan Kang, Yuan Ren
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

With the advent of digital technology, digital image has gradually taken the place of the original analog photograph, and the forgery of digital image has become more and more easy and indiscoverable. Image splicing is a commonly used technique in image tampering. In this paper, we simply introduce the definition of image splicing and some methods of image splicing detection, mainly including the detection based on steganalysis model, the detection based on Hilbert-Huang transform (HHT) and moments of characteristic functions (CF) with wavelet decomposition. We focus on discussing our proposed approach based on image quality metrics (IQMs) and moment features. Especially we analyze the model creation and the extraction of features in digital image. In addition, we compare these approaches and analyze the future works of digital image forensics.
Using Global Optimization to Explore Multiple Solutions of Clustering Problems
Authors: Ida Bifulco, Loredana Murino, Francesco Napolitano, Giancarlo Raiconi, Roberto Tagliaferri
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

A classical approach to clustering consists in running an algorithm aimed to minimize the distortion. Apart from very limited and simple cases such problem cannot be solved by a local search algorithm because of multiple local minima. In this paper a Global Optimization (GO) algorithm is used to overcome such difficulty. The proposed algorithm (Controlled Random Search) iterates by maintaining a population of solutions which tends to concentrate around the most "promising" areas. From Data Mining point of view such an approach enables to infer deep information about the underlying structure of data. Collecting and presenting such information in a human understandable manner can help the choice between several possible alternatives. Numerical experiments are carried out on a real dataset, showing that GO produces solutions with much better distortion values than the classical approach, while graphical representation of the whole solution set can be useful to data exploration.
Uncovering the Deep Web: Transferring Relational Database Content and Metadata to OWL Ontologies
Authors: Damir Jurić, Marko Banek, Zoran Skočir
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

Organizing the publicly available Web content into highly systematized domain ontologies is a necessary step in the evolvement of the Semantic Web. A large portion of that content called the deep Web is stored in relational databases and it is not accessible to Web search engines. Incorporation of the deep Web data results in domain ontologies richer both in content and in semantic relations. In this paper we introduce a framework for an automatic mapping of relational database metadata and content to domain ontologies written in OWL. Relational constructs: relations, attributes and primary-foreign key associations are translated to OWL classes, datatype properties and object properties. Database tuples become ontology instances. In order to define reference points for integration with other ontologies the constructed ontologies are further enriched with additional semantics from the WordNet lexical database using word sense disambiguation mechanisms. A software implementation of the approach has been developed and evaluated on case study examples.
Splitting the Control Flow with Boolean Flags
Authors: Axel Simon
Venue: Proceedings of the 15th international symposium on Static Analysis (2008)

Tools for proving the absence of run-time errors often deploy a numeric domain that approximates the possible values of a variable using linear inequalities. These abstractions are adequate since the correct program state is often convex. For instance, if the upper and lower bound of an index lie within the bounds of an array, then so do all the indices inbetween. In certain cases, for example when analysing a division operation, the correct program state is not convex. In this case correctness can be shown by splitting the control flow path, that is, by partitioning the set of execution traces which is normally implemented by analysing a path several times. We show that adding a Boolean flag to the numeric domain has the same effect. The paper discusses prerequisites, limitations and presents an improved points-to analysis using Boolean flags.
Qospl: a quality of service-driven software product line engineering framework for design and analysis of component-based distributed real-time and embedded systems
Authors: Barrett R. Bryant
Venue:  (2007)

Software complexity may be reduced and productivity may be increased by the synergy of Component-Based Software Engineering and Software Product Line Engineering. The synergistic techniques decrease complexity by uplifting software artifacts to a higher abstraction level, namely the component level, and defining the interfaces, interactions, and contexts of such artifacts for composing software systems. Such synergistic techniques also facilitate productivity increase by promoting feature reusability, leveraging component replacement and offering selectivity among product variants. When applied to Distributed Real-time and Embedded (DRE) systems, however, these technologies must fulfill such systems' time-critical missions and numerous functional and Quality of Service (QoS) requirements. New critical challenges to be solved are QoS sensitivity that influences functional validity and performance quality, tangled requirements that increase the complexity of requirements evaluation and abundant unsatisfactory design artifacts that introduce unnecessary development workload. With an aim to answer the QoS sensitivity problem and alleviate the requirements evaluation complexity and development workload in the analysis and design workflows of a DRE software product line construction, this dissertation introduces a Quality of Service-driven software Product Line engineering framework (QoSPL). Such a framework consists of domain engineering, application engineering and quantitative analysis processes. The domain engineering process analyzes QoS requirements, represented as the execution flows of application-specific and functionality-determined tasks, and their common and variable features by means of a grammar-oriented specification language. The application engineering process models a set of execution flows to describe the behavioral characteristics of a DRE system by means of formalism with concurrent and asynchronous behaviors in a timely manner. A DRE software product line can be realized by varying different components and/or execution flows. The quantitative analysis process utilizes evolutionary algorithms to simulate the influence factors of the deployment environment and to search the optimal simulation results. Less probable design artifacts in terms of their QoS requirements can be eliminated by means of programs written in a domain-specific language. Adaptive approaches written in the domain-specific language hasten the convergence rates and/or obtain better optimal results for the quantitative analysis process. This dissertation provides two case studies and a number of experimental results to show the benefits of using QoSPL for a DRE software product line construction.
Digital Divide in eGovernment: The eInclusion Gap Model
Authors: Jörg Becker, Björn Niehaves, Philipp Bergener, Michael Räckers
Venue: Proceedings of the 7th international conference on Electronic Government (2008)

The Digital Divide is a matter of fact in most countries. For instance, senior citizens, citizens without employment, or citizens with low education utilise online services in a distinct way, often to a lesser extent. Within this paper, we examine how such digital divide groups make use of different online services. Here, four types on services are taken into account and contrasted with each other: Internet usage, E-Commerce usage, E-Government for Information and E-Government for Transaction. As a result, we develop the E-Inclusion-Gap Model which addresses gaps between such service-specific usage and we discuss possible reasons behind them.
Deformation Measurement of the Large Flexible Surface by Improved RBFNN Algorithm and BPNN Algorithm
Authors: Xiyuan Chen
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

The Radial Basis Function (RBF) Neural Network (NN) is one of the approaches which has shown a great promise in this sort of problems because of its faster learning capacity. This paper presents the information fusion method based on improved RBFNN to deduce the deformation information of the whole flexible surface considering the complexity of the deformation of the large flexible structure. A distributed Strapdown Inertial Units (SIU) information fusion model for deformation measurement of the large flexible structure is presented. Comparing with the modeling results by improved RBFNN and back propagation (BP) NN, the simulation on a simple thin plate model shows that the information fusion based on improved RBFNN is effective and has higher precision than based on BPNN.
Object matching in disjoint cameras using a color transfer approach
Authors: Kideog Jeong, Christopher Jaynes
Venue: Machine Vision and Applications (2008)

Object appearance models are a consequence of illumination, viewing direction, camera intrinsics, and other conditions that are specific to a particular camera. As a result, a model acquired in one view is often inappropriate for use in other viewpoints. In this work we treat this appearance model distortion between two non-overlapping cameras as one in which some unknown color transfer function warps a known appearance model from one view to another. We demonstrate how to recover this function in the case where the distortion function is approximated as general affine and object appearance is represented as a mixture of Gaussians. Appearance models are brought into correspondence by searching for a bijection function that best minimizes an entropic metric for model dissimilarity. These correspondences lead to a solution for the transfer function that brings the parameters of the models into alignment in the UV chromaticity plane. Finally, a set of these transfer functions acquired from a collection of object pairs are generalized to a single camera-pair-specific transfer function via robust fitting. We demonstrate the method in the context of a video surveillance network and show that recognition of subjects in disjoint views can be significantly improved using the new color transfer approach.
Ubiquitous Advertising Challenges
Authors: Carina Ihlström Eriksson, Maria Åkesson
Venue: Proceedings of the 2008 7th International Conference on Mobile Business (2008)

The aim of this paper is to further explore new issues on advertising in ubiquitous information environments by theoretically and empirically discussing challenges of ubiquitous advertising. We have performed 15 interviews and 9 workshops with publishers and advertisers from the media industry. Our findings confirm previous research but also point out several additional challenging issues. We contribute to theory and practice by suggesting additional challenges for ubiquitous advertising regarding: 1) dynamic data exploitation, 2) real-time advertising adjustment (and channeling) to user behavior and preferences, 3) context adaptation and 4) user-advertiser relations.
Knowledge Processing with Interval and Soft Computing, 1 edition
Authors: Chenyi Hu, R. Baker Kearfott, Andre de Korvin, Vladik Kreinovich
Venue: Advanced Information And Knowledge Processing (2008)

Interval computing combined with fuzzy logic has become an emerging tool in studying artificial intelligence and knowledge processing (AIKP) applications since it models uncertainties frequently raised in the field. This book provides introductions for both interval and fuzzy computing in a very accessible style. Application algorithms covered in this book include quantitative and qualitative data mining with interval valued datasets, decision making systems with interval valued parameters, interval valued Nash games and interval weighted graphs. Successful applications in studying finance and economics, etc are also included. This book can serve as a handbook or a text for readers interested in applying interval and soft computing for AIKP.
Learning Smooth, Human-Like Turntaking in Realtime Dialogue
Authors: Gudny Ragna Jonsdottir, Kristinn R. Thorisson, Eric Nivel
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

Giving synthetic agents human-like realtime turntaking skills is a challenging task. Attempts have been made to manually construct such skills, with systematic categorization of silences, prosody and other candidate turn-giving signals, and to use analysis of corpora to produce static decision trees for this purpose. However, for general-purpose turntaking skills which vary between individuals and cultures, a system that can learn them on-the-job would be best. We are exploring ways to use machine learning to have an agent learn proper turntaking during interaction. We have implemented a talking agent that continuously adjusts its turntaking behavior to its interlocutors based on realtime analysis of the other party's prosody. Initial results from experiments on collaborative, content-free dialogue show that, for a given subset of turn-taking conditions, our modular reinforcement learning techniques allow the system to learn to take turns in an efficient, human-like manner.
Metamodel Matching for Automatic Model Transformation Generation
Authors: Jean-Rémy Falleri, Marianne Huchard, Mathieu Lafourcade, Clémentine Nebut
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

Applying Model-Driven Engineering (MDE) leads to the creation of a large number of metamodels, since MDE recommends an intensive use of models defined by metamodels. Metamodels with similar objectives are then inescapably created. A recurrent issue is thus to turn compatible models conforming to similar metamodels, for example to use them in the same tool. The issue is classically solved developing ad hoc model transformations. In this paper, we propose an approach that automatically detects mappings between two metamodels and uses them to generate an alignment between those metamodels. This alignment needs to be manually checked and can then be used to generate a model transformation. Our approach is built on the Similarity Flooding algorithm used in the fields of schema matching and ontology alignment. Experimental results comparing the effectiveness of the application of various implementations of this approach on real-world metamodels are given.
An Unsupervised Learning Algorithm for Rank Aggregation
Authors: Alexandre Klementiev, Dan Roth, Kevin Small
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

Many applications in information retrieval, natural language processing, data mining, and related fields require a ranking of instances with respect to a specified criteria as opposed to a classification. Furthermore, for many such problems, multiple established ranking models have been well studied and it is desirable to combine their results into a joint ranking, a formalism denoted as rank aggregation. This work presents a novel unsupervised learning algorithm for rank aggregation (ULARA) which returns a linear combination of the individual ranking functions based on the principle of rewarding ordering agreement between the rankers. In addition to presenting ULARA, we demonstrate its effectiveness on a data fusion task across ad hoc retrieval systems.
On the error probability of quasi-orthogonal space&ndash;time block codes
Authors: Jae-Dong Yang, Xianglan Jin, Jong-Seon No, Dong-Joon Shin
Venue: International Journal of Communication Systems (2008)

In this paper, we derive the exact pairwise error probabilities (PEPs) of various quasi-orthogonal space&ndash;time block codes (QO-STBCs) using the moment generating function. By classifying the exact PEPs of QO-STBCs into three types, we derive the closed-form expression for each type of PEP. Based on these closed-form expressions, we obtain the union bounds on the symbol error probability and bit error probability for QPSK modulation. Through simulation, it is shown that these union bounds are quite tight. Copyright &copy; 2008 John Wiley & Sons, Ltd.
The Joy of String Diagrams
Authors: Pierre-Louis Curien
Venue: Proceedings of the 22nd international workshop on Computer Science Logic (2008)

In the past recent years, I have been using string diagrams to teach basic category theory (adjunctions, Kan extensions, but also limits and Yoneda embedding). Using graphical notations is undoubtedly joyful, and brings us close to other graphical syntaxes of circuits, interaction nets, etc... It saves us from laborious verifications of naturality, which is built-in in string diagrams. On the other hand, the language of string diagrams is more demanding in terms of typing: one may need to introduce explicit coercions for equalities of functors, or for distinguishing a morphism from a point in the corresponding internal homset. So that in some sense, string diagrams look more like a language "à la Church", while the usual mathematics of, say, Mac Lane's "Categories for the working mathematician" are more "à la Curry".
Assertion-Based Verification: Industry Myths to Realities (Invited Tutorial)
Authors: Harry Foster
Venue: Proceedings of the 20th international conference on Computer Aided Verification (2008)

Debugging, on average, has grown to consume more than 60% of today's ASIC and SoC verification effort. Clearly, this is a topic the industry must address, and some organizations have done just that. Those that have adopted an assertion-based verification (ABV) methodology have seen significant reduction in simulation debugging time (as much as 50% [1]) due to improved observability. Furthermore, organizations that have embraced an ABV methodology are able to take advantage of more advanced verification techniques, such as formal verification, thus improving their overall verification quality and results. Nonetheless, even with multiple published industry case studies from various early adopters--each touting the benefits of applying ABV--the industry as a whole has resisted adopting assertion-based techniques. This tutorial provides an industry survey of today's ABV landscape, ranging from myths to realities. Emerging challenges and possible research opportunities are discussed. The following extended abstract provides a reference on which the tutorial builds.
An Efficient and Sensitive Decision Tree Approach to Mining Concept-Drifting Data Streams
Authors: Cheng-Jung Tsai, Chien-I Lee, Wei-Pang Yang
Venue: Informatica (2008)

Data stream mining has become a novel research topic of growing interest in knowledge discovery. Most proposed algorithms for data stream mining assume that each data block is basically a random sample from a stationary distribution, but many databases available violate this assumption. That is, the class of an instance may change over time, known as concept drift. In this paper, we propose a Sensitive Concept Drift Probing Decision Tree algorithm (SCRIPT), which is based on the statistical X 2 test, to handle the concept drift problem on data streams. Compared with the proposed methods, the advantages of SCRIPT include: a) it can avoid unnecessary system cost for stable data streams; b) it can immediately and efficiently corrects original classifier while data streams are instable; c) it is more suitable to the applications in which a sensitive detection of concept drift is required.
Towards Haptic Performance Analysis Using K-Metrics
Authors: Richard Hall, Hemang Rathod, Mauro Maiorca, Ioanna Ioannou, Edmund Kazmierczak, Stephen O'Leary, Peter Harris
Venue: Proceedings of the 3rd international workshop on Haptic and Audio Interaction Design (2008)

It is desirable to automatically classify data samples for the assessment of quantitative performance of users of haptic devices as the haptic data volume may be much higher than is feasible to manually annotate. In this paper we compare the use of three k-metrics for automated classifaction of human motion: cosine, extrinsic curvature and symmetric centroid deviation. Such classification algorithms make predictions about data attributes, whose quality we assess via three mathematical methods of comparison: root mean square deviation, sensitivity error and entropy correlation coefficient. Our assessment suggests that k-cosine might be more promising at analysing haptic motion than our two other metrics.
ENABLE --- A View on User's Needs
Authors: Stefan Parker, Gerhard Nussbaum, Helmut Sonntag, Franz Pühretmair, Veronika Williams, Rachel Mccrindle, Christina Victor, David Oliver, Martin Maguire, Peter Mayer, Georg Edelmayer, Paul Panek
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

The ENABLE project, which is partly funded by the European Commission, aims to assist elderly people to live well, independently and at ease. In this project a wrist unit with both integrated and external sensors, and with a radio frequency link to a mobile phone, will be developed. ENABLE will provide a number of services for elderly people, among them also a remote control service for the home environment. This paper briefly describes the project in general and then focuses on the initial user needs investigation which was carried out in early 2007 in six different European countries. The provisional findings are discussed and an outlook on the ongoing and future project work is given. A special focus of this paper is on the environmental control service.