ppxscal/embedding_network huggingface dataset:
SSW: A Small-World-Based Overlay for Peer-to-Peer Search
Authors: Mei Li, Wang-Chien Lee, Anand Sivasubramaniam, Jing Zhao
Venue: IEEE Transactions on Parallel and Distributed Systems (2008)

Peer-to-peer (P2P) systems have become a popular platform for sharing and exchanging voluminous information among thousands or even millions of users. The massive amount of information shared in such systems mandates efficient semantic based search instead of key-based search. This paper presents the design of an overlay network, namely semantic small world (SSW), that facilitates efficient semantic based search in P2P systems. SSW achieves the efficiency based on the following four ideas: 1) semantic clustering: peers with similar semantics organize into peer clusters; 2) dimension reduction: to address the high maintenance overhead associated with capturing high-dimensional data semantics in the overlay, peer clusters are adaptively mapped to a one-dimensional naming space; 3) small world network: peer clusters form into a one-dimensional small world network, which is search efficient with low maintenance overhead; 4) efficient search algorithms: peers perform efficient semantic based search, including approximate point query and range query, in the proposed overlay. Extensive experiments using both synthetic data and real data demonstrate that SSW is superior to the state-of-the-art on various aspects, including scalability, maintenance overhead, adaptivity to distribution of data and locality of interest, resilience to peer failures, load balancing, and efficiency in support of various types of queries on data objects with high dimensions.
Near-optimal algorithms for shared filter evaluation in data stream systems
Authors: Zhen Liu, Srinivasan Parthasarathy, Anand Ranganathan, Hao Yang
Venue: Proceedings of the 2008 ACM SIGMOD international conference on Management of data (2008)

We consider the problem of evaluating multiple overlapping queries defined on data streams, where each query is a conjunction of multiple filters and each filter may be shared across multiple queries. Efficient support for overlapping queries is a critical issue in the emerging data stream systems, and this is particularly the case when filters are expensive in terms of their computational complexity and processing time. This problem generalizes other well-known problems such as pipelined filter ordering and set cover, and is not only NP-Hard but also hard to approximate within a factor of o(log n) from the optimum, where n is the number of queries. In this paper, we present two near-optimal approximation lgorithms with provably-good performance guarantees for the evaluation of overlapping queries. We present an edge-coverage based Greedy algorithm which achieves an approximation ratio of (1 + log(n) + log(α)), where n is the number of queries and α is the average number of filters in a query. We also present a randomized, fast and easily parallelizable Harmonic algorithm which achieves an approximation ratio of 2β, where β is the maximum number of filters in a query. We have implemented these algorithms in a prototype system, and evaluated their performance using extensive experiments in the context of multimedia stream analysis. The results show that our Greedy algorithm consistently outperforms other known algorithms under various settings and scales well as the numbers of queries and filters increase.
Unified eigen analysis on multivariate Gaussian based estimation of distribution algorithms
Authors: Weishan Dong, Xin Yao
Venue: Information Sciences: an International Journal (2008)

Multivariate Gaussian models are widely adopted in continuous estimation of distribution algorithms (EDAs), and covariance matrix plays the essential role in guiding the evolution. In this paper, we propose a new framework for multivariate Gaussian based EDAs (MGEDAs), named eigen decomposition EDA (ED-EDA). Unlike classical EDAs, ED-EDA focuses on eigen analysis of the covariance matrix, and it explicitly tunes the eigenvalues. All existing MGEDAs can be unified within our ED-EDA framework by applying three different eigenvalue tuning strategies. The effects of eigenvalue on influencing the evolution are investigated through combining maximum likelihood estimates of Gaussian model with each of the eigenvalue tuning strategies in ED-EDA. In our experiments, proper eigenvalue tunings show high efficiency in solving problems with small population sizes, which are difficult for classical MGEDA adopting maximum likelihood estimates alone. Previously developed covariance matrix repairing (CMR) methods focusing on repairing computational errors of covariance matrix can be seen as a special eigenvalue tuning strategy. By using the ED-EDA framework, the computational time of CMR methods can be reduced from cubic to linear. Two new efficient CMR methods are proposed. Through explicitly tuning eigenvalues, ED-EDA provides a new approach to develop more efficient Gaussian based EDAs.
Adaptive Hybrid Model for Long Term Load Prediction in Computational Grid
Authors: Yulai Yuan, Yongwei Wu, Guangwen Yang, Weimin Zheng
Venue: Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (2008)

Long term load prediction can assist task scheduling and load balancing greatly in distributed environment such as computational grid. Due to the dynamic property of grid environment, fixed-parameter prediction model can not exert its forecast capability completely. In this paper we first observe and analyze parameters’ impact on prediction accuracy for our previous long term load prediction hybrid model (HModel) in detail. And then, a parameter-level adaptive method based on previous analysis is proposed in order to make HModel adapt to the time-varying characteristics of load in computational grid. The results of the experiments demonstrate that our adaptive hybrid model (AHModel) outperforms the widely used autoregressive (AR) model in long term load prediction significantly, and it also achieves obvious reduction in prediction mean square error comparing with HModel which uses fixed parameter value.
Toward Noise Modelling in Urban Areas
Authors: Stjepan Lakusic, Vesna Dragcevic
Venue: Proceedings of the 2008 Second Asia International Conference on Modelling & Simulation (AMS) (2008)

Noise field measurements are the only precise method of estimating environment pollution. They are long-term and expensive and are not applicable in case of prediction of conditions caused by the new intervention in space. Independent of the bases of available data, which are sometimes very limited, and of the choice of calculation method for reliable prediction of environmental conditions, making the calculation model is an important segment. In that process it is necessary to consider specific features of the location as well as of the model of behavior of all elements in the process of noise emergence (vehicle, traffic surface, machines, devices), significantly influenced by socioeconomic and economic conditions in the country. This paper provides the calculation model for the prediction of environmental noise for three relevant locations in business and residential areas of Zagreb (Croatia) and their verification was done with regard to field measurements.
Efficient Complex Event Processing over RFID Data Stream
Authors: Xingyi Jin, Xiaodong Lee, Ning Kong, Baoping Yan
Venue: Proceedings of the Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008) (2008)

RFID technology holds the promise of real-time identifying, locating and monitoring physical objects. To achieve these goals, RFID events need to be collected efficiently and composed expressively. Furthermore, these events have unique characteristics, such as locomotive, temporal and history oriented which should be considered and integrated into an event engine model. The diversity of RFID applications poses further challenges to a generalized framework for RFID events processing. In this paper, the Expressive Stream Language is utilized to collect vast number of primitive events efficiently. Moreover, we introduce a novel semantics to meet requirement of expressive event composition. At last, we use Timed Petri Net to model our newly RFID complex event engine. By introducing typical applications scenarios, we evaluate the validity and effectiveness of our RFID event processing system.
Composable context-aware architectural connectors
Authors: Christine Julien, Dewayne Perry
Venue: Proceedings of the 1st international workshop on Software architectures and mobility (2008)

In mobile and pervasive computing systems, the ability of an application to adapt its behavior in response to a changing environment is essential. In this paper we propose a new class of context-aware architectural connectors that enable software designers to incorporate context-aware aspects into a software architecture design. These context-aware connectors must also be composable to allow multiple types of context to be applied to a single architectural connection. We introduce our notion of context-aware connectors and describe some intended uses.
Application Level QoS in Multimedia Peer-to-Peer (P2P) Networks
Authors: Alireza Goudarzi Nemati, Makoto Takizawa
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

In peer-to-peer (P2P) overlay networks, each peer process (peer) can play a role of not only client but also server. Here, multimedia contents are in nature distributed in peersby downloading and caching. A peer may have a full replica and another peer may have only a part, even less qualified version of a multimedia content like monochromatic version of a fully colored movie. Here, a peer which transmits multimedia contents and a peer which receives the contents are referred to as source and receiver peers, respectively. In addition, a peer on a mobile computer is moving in the network. This means, not only receiver peers but also source peers are moving. In this paper, we would like to discuss how source peers efficiently deliver multimedia contents to receiver peers in a streaming model, where quality of service (QoS) supported by the peers and communication channels are dynamically changing, possibly according to the movements of the peers. It is critical to support a receiver peer with enough QoS to satisfy the receiver’s requirements, e.g. play a fully colored video movie in the streaming service in change of QoS of networks and peers. In this paper, we discuss a multi-source streaming protocol where a receiver peer can receive packets of a multimedia content from a source peer which can support enough QoS out of multiple source peers. If a current source peer which supports the receiver peer is expected to support less QoS, another source peer takes over the source peer and starts sending packets of the multimedia content.
Nonextensive entropic kernels
Authors: André F. T. Martins, Mário A. T. Figueiredo, Pedro M. Q. Aguiar, Noah A. Smith, Eric P. Xing
Venue: Proceedings of the 25th international conference on Machine learning (2008)

Positive definite kernels on probability measures have been recently applied in structured data classification problems. Some of these kernels are related to classic information theoretic quantities, such as mutual information and the Jensen-Shannon divergence. Meanwhile, driven by recent advances in Tsallis statistics, nonextensive generalizations of Shannon's information theory have been proposed. This paper bridges these two trends. We introduce the Jensen-Tsallis q-difference, a generalization of the Jensen-Shannon divergence. We then define a new family of nonextensive mutual information kernels, which allow weights to be assigned to their arguments, and which includes the Boolean, Jensen-Shannon, and linear kernels as particular cases. We illustrate the performance of these kernels on text categorization tasks.
The random Tukey depth
Authors: J. A. Cuesta-Albertos, A. Nieto-Reyes
Venue: Computational Statistics Data Analysis (2008)

The computation of the Tukey depth, also called halfspace depth, is very demanding, even in low dimensional spaces, because it requires that all possible one-dimensional projections be considered. A random depth which approximates the Tukey depth is proposed. It only takes into account a finite number of one-dimensional projections which are chosen at random. Thus, this random depth requires a reasonable computation time even in high dimensional spaces. Moreover, it is easily extended to cover the functional framework. Some simulations indicating how many projections should be considered depending on the kind of problem, sample size and dimension of the sample space among others are presented. It is noteworthy that the random depth, based on a very low number of projections, obtains results very similar to those obtained with the Tukey depth.
Realization of an Adaptive Distributed Sound System Based on Global-Time-Based Coordination and Listener Localization
Authors: Emmanuel Henrich, Juan A. Colmenares, Keizo Fujiwara, Chansik Im, K. H. (Kane) Kim, Liangchen Zheng
Venue: Proceedings of the 2008 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing (2008)

This paper discusses the benefits of exploiting 1) the principle of global-time-based coordination of distributed computing actions (TCoDA) and 2) a high-level component-/object-based programming approach in developing real-time embedded computing software. The benefits are discussed in the context of a concrete case study. A new major type of distributed multimedia processing applications, called Adaptive Distributed Sound Systems (ADSSs), is presented here to show the compelling nature of the TCoDA exploitation. High-quality ADSSs impose stringent real-time distributed computing requirements. They require a global-time base with precision better than 100 μs. For efficient implementation, the TMO programming scheme and associated tools are shown to be highly useful. In addition, a prototype TMO-based ADSS has been developed and its most important quality attributes have been empirically evaluated. The prototype ADSS has also turned out to be a cost-effective tool for assessing the quality of service of a TMO execution engine.
Logsonomy - social information retrieval with logdata
Authors: Beate Krause, Robert Jäschke, Andreas Hotho, Gerd Stumme
Venue: Proceedings of the nineteenth ACM conference on Hypertext and hypermedia (2008)

Social bookmarking systems constitute an established part of the Web 2.0. In such systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Today's search engines represent the gateway to retrieve information from the World Wide Web. Short queries typically consisting of two to three words describe a user's information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. This clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. The resulting network structure, which we will term logsonomy is very similar to the one of folksonomies. In order to find out about its properties, we analyze the topological characteristics of the tripartite hypergraph of queries, users and bookmarks on a large snapshot of del.icio.us and on query logs of two large search engines. All of the three datasets show small world properties. The tagging behavior of users, which is explained by preferential attachment of the tags in social bookmark systems, is reflected in the distribution of single query words in search engines. We can conclude that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of social bookmarking users is driven by similar dynamics.
An on-line algorithm for improving performance in navigation
Authors: A. Blum
Venue: Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science (1993)

Recent papers have shown optimally-competitive on-line strategies for a robot traveling from a point s to a point t in certain unknown geometric environments. We consider the question: Having gained some partial information about the scene on its first trip from s to t, can the robot improve its performance on subsequent trips it might make? This is a type of on-line problem where a strategy must exploit partial information about the future (e.g., about obstacles that lie ahead). For scenes with axis-parallel rectangular obstacles where the Euclidean distance between s and t is n, we present a deterministic algorithm whose average trip length after t trips, k/spl les/n, is O(/spl radic/n/k) times the length of the shortest s-t path in the scene. We also show that this is the best a deterministic strategy can do. This algorithm can be thought of as performing an optimal tradeoff between search effort and the goodness of the path found. We improve this algorithm so that for every i/spl les/n, the robot's ith trip length is O(/spl radic/n/t) times the shortest s-t path length. A key idea of the paper is that a tree structure can be defined in the scene, where the nodes are portions of certain obstacles and the edges are "short" paths from a node to its children. The core of our algorithms is an on-line strategy for traversing this tree optimally.
Design issues related to pie menus for 5-way joysticks
Authors: Tuomas Vaittinen, Timo-Pekka Viljamaa, Petri Piippo
Venue: Proceedings of the 4th international conference on mobile technology, applications, and systems and the 1st international symposium on Computer human interaction in mobile technology (2007)

Although linear textual menus are a widely adopted solution in the mobile phone user interfaces, alternatives that would take smaller amount of screen real estate exist, e.g. toolbars and pie menus. Pie menus also provide access to functions with fewer key presses than traditional Options menu but are best suited for expert users. We compared toolbars and pie menus as a way to access most often used functions of a mobile media player. Based on user test results, we selected pie menus for implementation into a prototype and made another user test to see what kind of design considerations are related to pie menus for digital joysticks. The user feedback was positive and six design issues were identified.
A Stroll through Domain-Driven Development with Naked Objects
Authors: Konstantin Läufer
Venue: Computing in Science and Engineering (2008)

With the help of domain-driven development frameworks such as Naked Objects for Java, changes to an application's core functionality propagate automatically to the user interface and persistence layers.
Hierarchical Co-evolution of Cooperating Agents Acting in the Brain-Arena
Authors: Michail Maniadakis, Panos Trahanias
Venue: Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems (2008)

Recently, many brain-inspired models have been used in attempts to support the cognitive abilities of artificial organisms. In this article, we introduce a computational framework to facilitate these efforts, emphasizing the cooperative performance of brain substructures. Specifically, we introduce an agent-based representation of brain areas, together with a hierarchical cooperative co-evolutionary design mechanism. The proposed methodology is capable of designing biologically inspired cognitive systems, considering both the specialties of brain areas and their cooperative performance. The effectiveness of the proposed approach is demonstrated by designing a brain-inspired model of working memory usage. The co-evolutionary scheme enforces the cooperation of agents representing the involved brain areas, facilitating the accomplishment of two different tasks by the same model. Furthermore, we investigate the performance of the model in lesion conditions, highlighting the distinct roles of agents representing brain areas. The implemented model is embedded in a simulated robotic platform to support its cognitive and behavioral capabilities.
End-user programming and the intrinsic complexity of networked artefacts
Authors: Joëlle Coutaz
Venue: Proceedings of the 4th international workshop on End-user software engineering (2008)

In this article, we propose a model for networked artifacts inspired from molecular chemistry. It demonstrates the intrinsic complexity of the domain illustrated with unsolved problems such as mastering the semantics of networked artefacts. Based on this model, we identify similarities with the service-oriented computing paradigm and suggest possible avenues for collaboration between Software Engineering and researchers in EUD including: semantic alignment between end-user programming languages and service descriptions, and human-service interaction as a transversal issue in software design.
Developing an Intelligent Table Tennis Umpiring System: Identifying the Ball from the Scene
Authors: Patrick Kam Cheung Wong
Venue: Proceedings of the 2008 Second Asia International Conference on Modelling & Simulation (AMS) (2008)

This paper reports further development of an intelligent table tennis umpiring system, of which the idea and plan was previously published at this conference in 2007. Briefly, table tennis is a fast sport. A service usually takes a few seconds to complete but an umpire needs to make many observations and makes a judgment before or soon after the service is complete. This is a complex task and the author believes the employment of videography, image processing and artificial intelligence (AI) technologies could help evaluating the service. The aim of this research is to develop an intelligent system which is able to identify and track the location of the ball from live video images and evaluate the service according to the service rules. In this paper, the techniques of identifying a table tennis ball from the scene is described and discussed. A number of image processing techniques have been employed to identify and measure the characteristics of the ball. Artificial neural networks have been applied as a classifier. It classifies whether the detected object is not-a- ball, a ball on the palm or a ball in mid air. The system has been tested on 21 still images which contain pictures of ball-like objects, balls on the palm and in mid air. The preliminary results are very promising. Out of 83 objects, 82 have been correctly classified. The system will be further tested on video images once the video is captured and processed.This paper also discusses the idea of implementing the final system as a multi-agent system, which the author believes it is appropriate for this application because multiple cameras will have to be employed to obtain accurate results.
Integrating ARC grid middleware with Taverna workflows
Authors: Hajo N. Krabbenhöft, Steffen Möller, Daniel Bayer
Venue: Bioinformatics (2008)

Summary: This work presents two independent approaches for a seamless integration of computational grids with the bioinformatics workflow suite Taverna. These are supported by a unique relational database to link applications with grid resources and presents those as workflow elements. A web portal facilitates its collaborative maintenance. The first approach implements a gateway service to handle authentication certificates and all communication with the grid. It reads the database to spawn web services for workflow elements which are in turn used by Taverna. The second approach lets Taverna communicate with the grid on its own, by means of a newly developed plug-in. It reads the database and executes the needed tasks directly on the grid. While the gateway service is non-intrusive, the plug-in has technical advantages, e.g. by allowing data to remain on the grid while being passed between workflow elements. Availability: http://grid.inb.uni-luebeck.de/ Contact: bayer@inb.uni-luebeck.de