ppxscal/embedding_network huggingface dataset:
A martingale framework for concept change detection in time-varying data streams
Authors: Shen-Shyang Ho
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

In a data streaming setting, data points are observed one by one. The concepts to be learned from the data points may change infinitely often as the data is streaming. In this paper, we extend the idea of testing exchangeability online (Vovk et al., 2003) to a martingale framework to detect concept changes in time-varying data streams. Two martingale tests are developed to detect concept changes using: (i) martingale values, a direct consequence of the Doob's Maximal Inequality, and (ii) the martingale difference, justified using the Hoeffding-Azuma Inequality. Under some assumptions, the second test theoretically has a lower probability than the first test of rejecting the null hypothesis, "no concept change in the data stream", when it is in fact correct. Experiments show that both martingale tests are effective in detecting concept changes in time-varying data streams simulated using two synthetic data sets and three benchmark data sets.
Level 2 Fusion: Situational Assessment Composition Fusion with Uncertain Classification
Authors: Stephen C. Stubberud, Kathleen A. Kramer
Venue: Proceedings of the 18th International Conference on Systems Engineering (2005)

A Level 2 fusion approach to composition estimation with uncertain classification is described. The technique is based upon Markov chain estimation of composition that allows for measurements of class that are uncertain. For this approach, Bayesian taxonomy is used to represent the uncertainty. While previous work has address composition estimation under conditions where the detection of objects in a group is uncertain, composition when there is uncertainty of classification is a much more difficult problem to address. The Markov chain, while straightforward in its implementation, contains a significant complexity in its transition matrices that would be difficult to model in other standard approaches to estimation theory, such as the Kalman filter.
Visual motion analysis without correspondence
Authors: Sherif M. Elshafei
Venue:  (2004)

A system that handles two computer-vision tasks related to motion analysis is presented. Using a pair of grey-level images as input, the system computes: (1) an approximation of the 2-D visual velocity field of a temporally changing scene, and (2) detects motion boundaries. The proposed algorithm uses motion blur in a novel way. It exploits a new image acquisition method that acquires two images simultaneously, in which one image is a temporal extension of the other. This avoids the need to estimate temporal derivatives, essential for algorithms that are based on the gradient constraint equation. Not being based on image sequences, the algorithm also avoids the need to follow image features from one frame to the next. This elegantly avoids the correspondence problem that is associated with almost all visual-motion estimation techniques. Through experiments, it is demonstrated that appropriate analysis of motion blur results in an unbiased estimator for the orthogonal component of the 2-D image velocity vector. It is also shown that the algorithm is able to segment objects in motion without the need to solve for the optical flow field. The algorithm exploits integral operations in almost all of its computational sub-processes to reduce the effects of noise. All computations are performed in the spatial domain for ease of future implementation in analog VLSI. The success of the method comes in large part from its ability to integrate effectively motion blur as a raw source of information with a simple, local non-iterative procedure to find displacements of moving edges.
Empirical Study of Hybrid Particle Swarm Optimizers with the Simplex Method Operator
Authors: Fang Wang, Yuhui Qiu
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

A novel hybrid simplex method and particle swarm optimization (HSMPSO) algorithm is presented in this article. Computational experiments on variety of benchmark functions indicate this SM-PSO hybrid is a promising way for locating global optima of continuous multimodal functions. Although very easy to be implemented, the hybrid method yields competitive results in both reliability and efficiency compared to other published algorithms. We provide an extensive analysis of the impact of the parameters of our hybrid algorithm on its performance as well.
Negotiating the hybrid: art, theory and genetic technologies
Authors: Caroline Seck Langill
Venue: AI Society (2005)

Over the past decade artists have increasingly turned to science in order to investigate technology&#x2019;s effect. The move from hardware-based technologies to live organisms as media, raises ethical issues that the broader art community is addressing. This paper tracks the history of instrumental disengagement to determine when and how the gradual codification of life contributed to the eventual use of live organisms in art practice.
Applying AspectJ to J2EE Application Development
Authors: Nicholas Lesiecki
Venue: IEEE Software (2006)

This article focuses on the application of AspectJ to the development of a Java 2 Enterprise Edition Web application for Video Monitoring Services of America (VMS). The project used aspects to cleanly modularize concerns ranging in scope from auxiliary (error handling) to application-specific (shopping basket price calculation) to framework-level (object relationship management). VMS saw benefits resulting from the aspect-oriented implementation of these concerns in the areas of code size, understandability, and reduced defects. This article details specific areas to which AspectJ was applied, the development team's reaction to the new technology, strategies used to ease adoption, and some of the pitfalls encountered when using the development tools.
MaGMA: mobility and group management architecture for real-time collaborative applications: Research Articles
Authors: Nadav Lavi, Israel Cidon, Idit Keidar
Venue: Wireless Communications Mobile Computing (2005)

We introduce MaGMA, a mobility and group management architecture, enabling real-time collaborative group applications such as push-to-talk (PTT) for mobile users. MaGMA provides, for the first time, a comprehensive and scalable solution for group management, seamless mobility, and quality-of-service (QoS). MaGMA is a distributed IP-based architecture consisting of an overlay server network deployed as part of the service infrastructure. MaGMA's architecture consists of a collection of mobile group managers (MGMs), which manage group membership and may also implement a multicast overlay for data delivery. The architecture is very flexible, and can co-exist with current as well as emerging wireless network technologies. We see such services as essential components in beyond-3G (B3G) networks. We propose two group management approaches in the context of MaGMA. We devise protocols for both approaches, evaluate both solutions using simulations, and validate the results through mathematical analysis. Finally, we present a proof-of-concept prototype implementation. Copyright &copy; 2005 John Wiley & Sons, Ltd.Preliminary version of this paper appears in Proceedings of the Sixth IEEE IFIP Conference on Mobile and Wireless Communication Networks (MWCN), Paris, October 2004.
Safety and QoS-Aware Management of Heterogeneous Sensor Networks
Authors: Mohamed Younis, Waleed Youssef, Mohamed Eltoweissy, Stephan Olariu
Venue: Proceedings of the 8th International Symposium on Parallel Architectures,Algorithms and Networks (2005)

Recently, we have proposed ANSWER: AutoNomouS Wireless sEnsor netwoRk as a service platform whose mission is to provide dependable information services to in-situ mobile users while satisfying their quality-of-service (QoS) requirements. Alongside with the stationary tiny sensors, the network employs more powerful mobile devices referred to as aggregation and forwarding nodes (AFNs). ANSWER exploits AFN mobility to support QoS requirements. However, as an AFN moves closer to an event (e.g., a hazardous spill), it may be at risk (e.g., due to potential damage). In this paper, we present a quantitative analysis of the interplay and balance between QoS support and asset safety. We propose a new scheme, called SAFER (for SAFEty-aware Relocation), which pursues relocation of the AFN in order to boost network performance without unnecessarily compromising AFN safety. SAFER uses historical data on detected events and employs an evolutionary neural network to assess the risk involved and predict good quality new position(s).
Mixtures of factor analyzers: an extension with covariates
Authors: Ernest Fokoué
Venue: Journal of Multivariate Analysis (2005)

This paper examines the analysis of an extended finite mixture of factor analyzers (MFA) where both the continuous latent variable (common factor) and the categorical latent variable (component label) are assumed to be influenced by the effects of fixed observed covariates. A polytomous logistic regression model is used to link the categorical latent variable to its corresponding covariate, while a traditional linear model with normal noise is used to model the effect of the covariate on the continuous latent variable. The proposed model turns out be in various ways an extension of many existing related models, and as such offers the potential to address some of the issues not fully handled by those previous models. A detailed derivation of an EM algorithm is proposed for parameter estimation, and latent variable estimates are obtained as by-products of the overall estimation procedure.
Generic Quantum Markov Semigroups: the Fock Case
Authors: L. Accardi, S. Hachicha, H. Ouerdiane
Venue: Open Systems Information Dynamics (2005)

We introduce the class of generic quantum Markov semigroups. Within this class we study the class corresponding to the Fock case which is further split into four subclasses each of which contains both bounded and unbounded generators, depending on some global characteristics of the intensities of jumps. For the first two of these classes we find an explicit solution which reduces the problem of finding the quantum semigroup to the calculation of two classical semigroups, one of which is diagonal (in a suitable basis) and the other one is triangular (in the same basis). In the bounded case our formula gives the unique solution. In the unbounded case it gives one solution, which we conjecture to be the minimal one.
Clockless Pipelining for Coarse Grain Datapaths
Authors: Abdelhalim Alsharqawi, Abdel Ejnioui
Venue: Proceedings of the 19th International Conference on VLSI Design held jointly with 5th International Conference on Embedded Systems Design (2006)

In this paper, we present two novel synchronization approaches to support data flow in clockless designs using single-rail encoding. Both approaches are based on self-resetting stage logic in which a pipeline stage resets itself before starting the next execution cycle. As such, a stage goes through a reset and an evaluate phase to complete a single period. While in the first approach synchronization is controlled between neighboring stages, the last stage of the pipeline in the second approach controls the synchronization of all the stages in the pipeline. Concept designs of both pipelines are presented to illustrate the inner workings of self-resetting stage logic and its data-flow synchronization mechanism. Implementation results show that both pipelines can reach throughputs up to 1.4 Giga outputs per second.
Distinguishing between Learning, Growth and Evolution
Authors: Nigel Phillips, Sue Black
Venue: Proceedings of the IEEE International Workshop on Software Evolvability (2005)

Systems are not expected to stay the same over many versions; if there were no change at all there would be no improvement or continued satisfaction with a system. Lehman's laws of software evolution look at how a system changes over time. The current set of laws are now accepted as fundamental to the teaching and understanding of software engineering. This paper describes the terms "learning", "growth" and "evolution" from a biological perspective with a view to using and applying these ideas to an initial framework for the categorisation of software. The purpose is to classify software systems and thus understand more about their behaviour and characteristics.
Performance Analysis of Adaptive Path Selective Decorrelating Detector with Channel Estimation Errors
Authors: Ali Hakan Ulusoy, Ahmet Rizaner, Kadri Hacioĝlu, Hasan Amca
Venue: Wireless Personal Communications: An International Journal (2005)

The system complexity and noise enhancement due to the use of Multipath Decorrelating Detector (MDD) can be reduced by employing adaptive path selection technique. Adaptive Path Selective Decorrelating Detector (APSDD) requires knowledge of the channel coefficients for path selection. Generally, the channel coefficients are assumed to be known at the receiver. However, this is not realistic and the channel coefficients should be estimated. In this paper, we extend the Bit Error Rate (BER) analysis of the path selective receiver to include channel estimation errors.
Smart Archive: a Component-based Data Mining Application Framework
Authors: Perttu Laurinen, Lauri Tuovinen, Juha Roning
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

Implementation of data mining applications is a challenging and complicated task, and the applications are often built from scratch. In this paper, a component-based application framework, called Smart Archive (SA) designed for implementing data mining applications, is presented. SA provides functionality common to most data mining applications and components for utilizing history information. Using SA, it is possible to build high-quality applications with shorter development times by configuring the framework to process application-specific data. The architecture, the components, the implementation and the design principles of the framework are presented. The advantages of a framework-based implementation are demonstrated by presenting a case study which compares the framework approach to implementing a real-world application with the option of building an equivalent application from scratch. In conclusion, the paper presents a lucid framework for creating data mining applications and illustrates the importance and advantages of using the presented approach.
Schemes for locating, collaboration, and management of net-centric services
Authors: Wei-Tek Tsai
Venue:  (2005)

As service-oriented computing paradigm and technologies become increasingly important and in demand, they have emerged as key enablers for flexible and scalable Internet and Web application solutions. Effective locating of services and efficient metadata management are an important and integral part of the service-oriented paradigm of computing. However, there are limitations on dealing with service functional properties matching and also uncertainties caused by service semantics matching. Mobile service collaboration and domain-specific service locating are yet insufficient. In this thesis, we present a virtual service ontology model as the fundamental approach, to address and tackle large-scale net-centric services locating and management issues. These issues include service functional properties matching, distributed service metadata management in repositories, and mobile services collaboration. Within the virtual service ontology model, we use facets-based service ontological taxonomies to organize and manage service metadata in distributed repositories. This approach offers an operational framework for interactive and automated service locating tasks. We develop and provide a new location-transparent naming and routing algorithm for mobile services collaboration and interaction. With facets-based service ontological descriptions, we propose and give a progressive method for the dynamic formation of domain-specific ontological taxonomies of services. The soundness of this approach and the developed algorithms and mechanisms are validated through analytic reasoning with the schemes, experiments, and prototype. The contributions of this dissertation include the following. At the framework level, we present a data model of faceted service ontologies for service metadata management and service locating. Facets-based multiform taxonomic hierarchies of service ontologies characterize the modeling. Extended from the model, a location transparent routing and naming algorithm is developed for effective collaboration and interaction of mobile services. A novel approach to the dynamic formation of service ontological taxonomies is given; this optimizes domain-specific service locating and management by using constraint satisfaction for adaptive and dynamic formation of service ontology representations. By providing an operational prototype, we combine interactive and automated services locating as a means of reducing uncertainties of service semantics matching.
Hedged learning: regret-minimization with learning experts
Authors: Yu-Han Chang, Leslie Pack Kaelbling
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

In non-cooperative multi-agent situations, there cannot exist a globally optimal, yet opponent-independent learning algorithm. Regret-minimization over a set of strategies optimized for potential opponent models is proposed as a good framework for deciding how to behave in such situations. Using longer playing horizons and experts that learn as they play, the regret-minimization framework can be extended to overcome several shortcomings of earlier approaches to the problem of multi-agent learning.
Partial Ensemble Classifiers Selection for Better Ranking
Authors: Jin Huang, Charles X. Ling
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

Ranking is an important task in data mining and knowledge discovery. We propose a novel approach called PECS algorithm to improve the overall ranking performance of a given ensemble. We formally analyse the sufficient and necessary condition under whichPECS algorithm can effectively improve ensemble ranking performance. The experiments with real-world data sets show that this new approach achieves significant improvements in ranking over the original Bagging and Adaboost ensembles.
Two-scale image retrieval with significant meta-information feedback
Authors: Jia Li
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

A two-scale image retrieval system is developed to provide efficient search in large-scale databases as well as flexibility for users to incorporate ubjective preferences during retrieval. A new clustering method is developed for images each characterized by a varying number of weighted feature vectors. Furthermore, significant meta-information is mined within every cluster. A scanning mode of retrieval is created using cluster centers, which serve as a low scale version of a database in contrast to original images. In particular, users are presented with representative images of highly ranked clusters along with prominent meta-information. This retrieval approach enables users to quickly examine a large and diverse portion of a database surrounding a query and to learn about hidden connections between visual patterns and non-imagery types of data. The clusters formed also facilitate fast search in the case of individual image-based retrieval by filtering out images whose cluster centers are far from the query. The two-scale retrieval system has been implemented on a fine art painting database. Advantages of the system have been demonstrated by quantitative evaluation of the retrieval performance.
Create free-form digital shapes with hands
Authors: Monica Bordegoni, Umberto Cugini
Venue: Proceedings of the 3rd international conference on Computer graphics and interactive techniques in Australasia and South East Asia (2005)

Current tools aimed at supporting the conceptual phase of product design are not intuitive to use, and do not exploit designers' skill and creativity. This paper presents the results of a research work aiming at integrating user-friendly and effective ways of interaction based on ad-hoc haptic interfaces into free-form shape modeling systems.
Power-Conscious Design of the CELL Processor's Synergistic Processor Element
Authors: Osamu Takahashi, Scott Cottier, Sang H. Dhong, Brian Flachs, Joel Silberman
Venue: IEEE Micro (2005)

The authors describe the low-power design of the synergistic processor element (SPE) of CELL processor developed by SONY, Toshiba and IBM. CMOS static gates implement most of the logic, and dynamic circuits are used in critical areas. Tight coupling of the instruction set architecture, microarchitecture, and physical implementation achieves a compact, power-efficient design.
Enhanced ontologies for video annotation and retrieval
Authors: Marco Bertini, Alberto Del Bimbo, Carlo Torniai
Venue: Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval (2005)

A typical way to perform video annotation requires to classify video elements (e.g. events and objects) according to some pre-defined ontology of the video content domain. Ontologies are defined by establishing relationships between linguistic terms that specify domain concepts at different abstraction levels. However, although linguistic terms are appropriate to distinguish event and object categories, they are inadequate when they must describe specific or complex patterns of events or video entities. Instead, in these cases, pattern specifications can be better expressed using visual prototypes, either images or video clips, that capture the essence of the event or entity. Therefore enhanced ontologies, that include both visual and linguistic concepts, can be useful to support video annotation up to the level of detail of pattern specification.This paper presents algorithms and techniques that employ enriched ontologies for video annotation and retrieval, and discusses a solution for their implementation for the soccer video domain. An unsupervised clustering method is proposed in order to create pictorially enriched ontologies by defining visual prototypes that represent specific patterns of highlights and adding them as visual concepts to the ontology.Two algorithms that use pictorially enriched ontologies to perform automatic soccer video annotation are proposed and results for typical highlights are presented. Annotation is performed associating occurrences of events, or entities, to higher level concepts by checking their similarity to visual concepts that are hierarchically linked to higher level semantics, using a dynamic programming approach.Usage of reasoning on the ontology is shown, to perform higher-level annotation of the clips using the domain knowledge and to create complex queries that comprise visual prototypes of actions, their temporal evolution and relations.