ppxscal/embedding_network huggingface dataset:
Distances between Data Sets Based on Summary Statistics
Authors: Nikolaj Tatti
Venue: The Journal of Machine Learning Research (2007)

The concepts of similarity and distance are crucial in data mining. We consider the problem of defining the distance between two data sets by comparing summary statistics computed from the data sets. The initial definition of our distance is based on geometrical notions of certain sets of distributions. We show that this distance can be computed in cubic time and that it has several intuitive properties. We also show that this distance is the unique Mahalanobis distance satisfying certain assumptions. We also demonstrate that if we are dealing with binary data sets, then the distance can be represented naturally by certain parity functions, and that it can be evaluated in linear time. Our empirical tests with real world data show that the distance works well.
A paradigmatic and methodological examination of knowledge management research: 2000 to 2004
Authors: Zining Guo, James Sheffield
Venue: Decision Support Systems (2008)

Knowledge management (KM) research has been evolving for more than a decade, yet little is known about KM theoretical perspectives, research paradigms, and research methods. This paper explores KM research in influential journals for the period 2000-2004. A total of 160 KM articles in ten top-tier information systems and management journals are analyzed. Articles that may serve as useful exemplars of KM research from positivist, interpretivist, and critical pluralist paradigms are selected. We find that KM research in information systems journals differs from that in management journals, but neither makes a balanced use of positivist and non-positivist research approaches.
Design and comparison of adaptive power system stabilizers based on neural fuzzy networks and genetic algorithms
Authors: Jesús Fraile-Ardanuy, P. J. Zufiria
Venue: Neurocomputing (2007)

This paper presents two different power system stabilizers (PSSs) which are designed making use of neural fuzzy network and genetic algorithms (GAs). In both cases, GAs tune a conventional PSS on different operating conditions and then, the relationship between these points and the PSS parameters is learned by the ANFIS. ANFIS will select the PSS parameters based on machine loading conditions. The first stabilizer is adjusted minimizing an objective function based on ITAE index, while second stabilizer is adjusted minimizing an objective function based on pole-placement technique. The proposed stabilizers have been tested by performing simulations of the overall nonlinear system. Preliminary experimental results are shown.
Robust estimation with sampling and approximate pre-aggregation
Authors: Christopher Jermaine
Venue: Proceedings of the 29th international conference on Very large data bases - Volume 29 (2003)

The majority of data reduction techniques for approximate query processing (such as wavelets, histograms, kernels, and so on) are not usually applicable to categorical data. There has been something of a disconnect between research in this area and the reality of data-base data; much recent research has focused on approximate query processing over ordered or numerical attributes, but arguably the majority of database attributes are categorical: country, state, job_title, color, sex, department, and so on. This paper considers the problem of approximation of aggregate functions over categorical data, or mixed categorical/numerical data. We propose a method based upon random sampling, called Approximate Pre-Aggregation (APA). The biggest drawback of sampling for aggregate function estimating is the sensitivity of sampling to attribute value skew, and APA uses several techniques to overcome this sensitivity. The increase in accuracy using APA compared to "plain vanilla" sampling is dramatic. For SUM and AVG queries, the relative error for random sampling alone is more than 700% greater than for sampling with APA. Even if stratified sampling techniques are used, the error is still between 28% and 175% greater than for APA.
A bio-inspired architecture for division of labour in SANETs
Authors: Thomas Halva Labella, Falko Dressler
Venue: Proceedings of the 1st international conference on Bio inspired models of network, information and computing systems (2006)

Division of labour is one of the possible strategies to efficiently exploit the resources of autonomous systems. It is also a phenomenon often observed in animal systems. We show an architecture that implements division of labour in Sensor/Actuator Networks. The way the nodes take their decisions is inspired by ants' foraging behaviour. The preliminary results show that the architecture and the bio-inspired mechanism successfully induce self-organised division of labour in the network. The experiments were run in simulation. We developed a new type of simulator for this purpose. Key features of our work are cross-layer design and exploitation if inter-node interactions. No explicit negotiation between the agents takes place.
The Application of Adaptive Immune Genetic Algorithm for Parameter Optimization in Soil Water Movement
Authors: Haiyan Sun, Quanjang Wang, Xiaobin Li
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

This paper introduces adaptive immune genetic algorithmAIGA. It based on genetic algorithm and immune principle. The algorithm defines selection, expansion and mutation operation. For improve searching ability of the global and local. The algorithm defines three new parameter as selection scale, expansion radius, mutation radius and adaptive adjusting parameters. A simulation test of soil water movement parameters optimization is done with AIGA. A good result is obtained from the model .
Breast MR segmentation and lesion detection with cellular neural networks and 3D template matching
Authors: Gökhan Ertaş, H.Özcan Gülçür, Onur Osman, Osman N. Uçan, Mehtap Tunacı, Memduh Dursun
Venue: Computers in Biology and Medicine (2008)

A novel fully automated system is introduced to facilitate lesion detection in dynamic contrast-enhanced, magnetic resonance mammography (DCE-MRM). The system extracts breast regions from pre-contrast images using a cellular neural network, generates normalized maximum intensity-time ratio (nMITR) maps and performs 3D template matching with three layers of 12x12 cells to detect lesions. A breast is considered to be properly segmented when relative overlap >0.85 and misclassification rate
XCentric: logic programming for XML processing
Authors: Jorge Coelho, Mario Florido
Venue: Proceedings of the 9th annual ACM international workshop on Web information and data management (2007)

Here we present the logic-programming language XCentric, discuss design issues, and show its adequacy for XML processing. Distinctive features of XCentric are a powerful unification algorithm for terms with functors of arbitrary arity (which correspond closely to XML documents) and a rich type language that uses operators such as repetition (*), alternation, etc, as types allowing a compact representation of terms with functors with an arbitrary number of arguments (closely related to standard type languages for XML). This new form of unification together with an appropriate use of types yields a substantial degree of flexibility in programming.
Domain-Based Decomposition Parallel Molecular Dynamics Algorithm on Computer Clusters
Authors: Jiu-ling Zhao, Jiu-fen Zhao
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

With MPI and C/C++, a parallel algorithm of molecular dynamics based on octal-tree domain decomposition method was implemented for micro canonical system (NVE), and run the code on a small cluster. The code speed-up was examined for a number of particles ranging from N = 192 to 10800 and for number of processors from P = 2 up to 8. As a result, the computing performance has been improved obviously, that is the computing speedup of the system can be three times or more than those computing on the single computer.
MSF: A Session-Oriented Adaptive Load Balancing Algorithm
Authors: Yijiao Chen, Xicheng Lu, Zhigang Sun
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

Some content-oriented applications, such as IDS and IPS; require keeping session integrality when scheduling the workload, otherwise, the semantic integrality of the session will be destroyed. The traditional load balancing algorithms focus on parallel processing and have less consideration for session integrality. In this paper, we proposed an adaptive load balancing algorithm named MSF (Minimum Sessions First). The algorithm integrates the static workload pre-distribution scheme based on flow table with adaptive scheduling scheme, can obtain the session level load balancing by dynamic scheduling the flow-bundles in which the session number are minimum. The simulation results show that the scheduler achieves significant improvement in session integrality disruption and has a fairly good load balance both in packets level and bits level. It's a sample algorithm and appropriate for the application of session-oriented load balancing.
Algorithm for Tracking of Fast Motion Objects with Adaptive Mean Shift
Authors: Guo-liang Wang, De-qun Liang, Yan-chun Wang, Zhao-hua Hu
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

The Classic Kernel-Based Object Tracking algorithm uses fixed kernel-bandwidth, which limits the performance when the object scale exceeds the size of the tracking window and the object fast motion. Therefor, a real-time object tracking algorithm is proposed, This algorithm gets the target's scale using automatic selection of kernel-bandwidth based on feature matching. Based on the analysis of similarity of object kernel-histogram by object center distance-weighting, gets the target's location by mean-shift Algorithm. Experimental results show that the proposed algorithm can track successfully fast moving objects of changing in size.
Class size and its impact on information technology instruction
Authors: Jack Purdum
Venue: Proceedings of the 8th ACM SIGITE conference on Information technology education (2007)

This paper provides a formal assessment of the impact of class size on teaching effectiveness using Analysis of Variance techniques.
Distributed set-expression cardinality estimation
Authors: Abhinandan Das, Sumit Ganguly, Minos Garofalakis, Rajeev Rastogi
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

We consider the problem of estimating set-expression cardinality in a distributed streaming environment where rapid update streams originating at remote sites are continually transmitted to a central processing system. At the core of our algorithmic solutions for answering set-expression cardinality queries are two novel techniques for lowering data communication costs without sacrificing answer precision. Our first technique exploits global knowledge of the distribution of certain frequently occurring stream elements to significantly reduce the transmission of element state information to the central site. Our second technical contribution involves a novel way of capturing the semantics of the input set expression in a boolean logic formula, and using models (of the formula) to determine whether an element state change at a remote site can affect the set expression result. Results of our experimental study with real-life as well as synthetic data sets indicate that our distributed set-expression cardinality estimation algorithms achieve substantial reductions in message traffic compared to naive approaches that provide the same accuracy guarantees.
Performance Analysis of CORBA Replication Models
Authors: Swapna S. Gokhale, B. Dasarathy
Venue: Proceedings of the Third IEEE International Symposium on Dependable, Autonomic and Secure Computing (2007)

Active and passive replication models constitute an effective way to achieve the availability objectives of distributed real-time (DRE) systems. These two models have different impacts on the application performance. Although these models have been commonly used in practical systems, a systematic quantitative evaluation of their influence on the application performance has not been conducted. In this paper we describe a methodology to analyze the application performance in the presence of active and passive replication models. For each one of these models, we obtain an analytical expression for the application response time in terms of the model parameters. Based on these analytical expressions, we derive the conditions under which one replication model has better performance over the other. Our results indicate that the superiority of one replication model over the other is governed not only by the model parameters but also by the application characteristics. We illustrate the value of the analytical expressions to assess the influence of the parameters of each model on the application response time and for a comparative analysis of the two models.
Periodic solutions of a discrete-time nonautonomous predator-prey system with the Beddington-Deangelis functional response
Authors: Binxiang Dai, Jiezhong Zou
Venue: Journal of Applied Mathematics and Computing (2007)

In this paper, we investigate a discrete-time nonautonomous predator-prey system with the Beddington-DeAngelis functional response. By using the coincidence degree and the related continuation theorem as well as some priori estimates, easily verifiable sufficient criteria are established for the existence of positive periodic solutions.
Quasiconvex Optimization for Robust Geometric Reconstruction
Authors: Qifa Ke, Takeo Kanade
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

Geometric reconstruction problems in computer vision are often solved by minimizing a cost function that combines the reprojection errors in the 2D images. In this paper, we show that, for various geometric reconstruction problems, their reprojection error functions share a common and quasiconvex formulation. Based on the quasiconvexity, we present a novel quasiconvex optimization framework in which the geometric reconstruction problems are formulated as a small number of small-scale convex programs that are ready to solve. Our final reconstruction algorithm is simple and has intuitive geometric interpretation. In contrast to existing local minimization approaches, our algorithm is deterministic and guarantees a predefined accuracy of the minimization result.The quasiconvexity also provides an intuitive method to handle directional uncertainties and outliers in measurements. When there are outliers in the measurements, our method provides a mechanism to locate the global minimum of a robust error function. For large scale problems and when computational resources are constrained, we provide an efficient approximation that gives a good upper bound (but not global minimum) on the reconstruction error. We demonstrate the effectiveness of our algorithm by experiments on both synthetic and real data.
Hypervisor-Based Efficient Proactive Recovery
Authors: Hans P. Reiser, Rudiger Kapitza
Venue: Proceedings of the 26th IEEE International Symposium on Reliable Distributed Systems (2007)

Proactive recovery is a promising approach for building fault and intrusion tolerant systems that tolerate an arbitrary number of faults during system lifetime. This paper investigates the benefits that a virtualization-based replication infrastructure can offer for implementing proactive recovery. Our approach uses the hypervisor to initialize a new replica in parallel to normal system execution and thus minimizes the time in which a proactive reboot interferes with system operation. As a consequence, the system maintains an equivalent degree of system availability without requiring more replicas than a traditional replication system. Furthermore, having the old replica available on the same physical host as the rejuvenated replica helps to optimize state transfer. The problem of remote transfer is reduced to remote validation of the state in the frequent case when the local replica has not been corrupted.
Cross-Layer Design of Wireless Multihop Backhaul Networks With Multiantenna Beamforming
Authors: Seung-Jun Kim, Xiaodong Wang, Mohammad Madihian
Venue: IEEE Transactions on Mobile Computing (2007)

A cross-layer design approach is considered for joint routing and resource allocation for the physical (PHY) and the medium access control (MAC) layers in multi-hop wireless backhaul networks. The access points (APs) are assumed to be equipped with multiple antennas capable of both transmit and receive beamforming. A nonlinear optimization problem is formulated that maximizes the fair throughput of the APs in the network under the routing and the PHY/MAC constraints. Dual decomposition is employed to decouple the original problem into smaller subproblems in different layers, which are coordinated by the dual prices. The network layer subproblem can be solved in a distributed manner, and the physical layer subproblem in a semi-distributed manner. To solve the physical layer subproblem, an iterative minimum mean square error (IMMSE) algorithm is used with the target link signal-to-interference-and-noiseratio (SINR) set dynamically based on the price generated from the upper layers. A scheduling heuristic is also developed, which improves the choice of the transmission sets over time. Simulation results illustrate the e±cacy of the proposed cross-layer design.
Modeling of vocal tract
Authors: Zygmunt Ciota, Małgorzata Napieralska, Andrzej Napieralski
Venue: Proceedings of the 1st international conference on Bio inspired models of network, information and computing systems (2006)

The most important features of vocal tract have been presented. The proposed model of the tract permits to obtain vocal tract transmittances and power spectrum of phonemes. The model can be also helpful for a voice synthesizer.
Efficient Techniques for Detecting False Origin Advertisements in Inter-domain Routing
Authors: Sophie Qiu, Fabian Monrose, Andreas Terzis, Patrick McDaniel
Venue: Proceedings of the 2006 2nd IEEE Workshop on Secure Network Protocols (2006)

The Border Gateway Protocol (BGP), and hence the Internet, remains critically vulnerable to a range of prefix forgery attacks. In this paper, we address these attacks by proposing a non-cryptographic, incrementally deployable mechanismto probabilistically detect forged BGP origin advertisements. Upon receiving an advertisement from a "suspicious" origin, the receiving domain intelligently probes other ASes about the received information. Any dissenting information indicates potential forgery or error, and is reported by the polled ASes to the true origin and processed appropriately. In this design, we exploit the fact that the highly connected AStopology makes it difficult to block the dissemination of information as it traverses the Internet. We evaluate the effectiveness of our probing mechanism via simulation on realistic Internet topologies. The experiments show that 98% of forgeries can be detected even when as few as 10% of the ASes participate in the protocol under a naïve polling stratagem. Moreover, we show that judicious node selection can further improve detection rates while minimizing the number of probes.
EulerView: a non-hierarchical visualization component
Authors: Rosario De Chiara, Andrew Fish
Venue: Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing (2007)

The Treeview control is the traditional way of visualizing hierarchical information in user interfaces, but in situations such as managing bookmarks in browsers, more general classifications may be more appropriate than hierarchies. We have developed a component called EulerView which is an extension of Treeview, with a similar look and feel, addressing migration, navigation and overspecificity issues amongst 2D or 3D visualisations of classifications. It has familiar characteristics, and an underlying model, based on Euler diagrams, enabling more general classifications. We found, via user testing, that users of EulerView appear to grasp a fairly accurate internal representation of Euler diagrams and that they could organise bookmarks well within in a given classification using EulerView.
Sight enhancement through video fusion in a surveillance system
Authors: Andrea Masini, Francesco Branchitta, Marco Diani, Giovanni Corsini
Venue: Proceedings of the 14th International Conference on Image Analysis and Processing (2007)

In this paper we consider the problem of fusing two video streams acquired by an RGB camera and a sensor operating in the Long Wave Infrared (LWIR). The application of interest is area surveillance and the fusion process aims at enhancing the human perception of the monitored scene. We propose a fusion procedure where the background and the moving objects are separated and fused by means of different strategies. With respect to standard video fusion techniques this approach has the advantage of reducing the computational load and mitigating the rapid brightness variations in the fused video. It is also less sensitive to the presence of noise. We discuss the experimental results obtained on a typical area surveillance scenario and demonstrate the effectiveness of the proposed method. For this purpose, the analysis is carried out both subjectively, in terms of visual quality of the fused video stream and objectively, in terms of standard image quality indexes. The computational load is also evaluated.
Advanced fade countermeasures for DVB-S2 systems in railway scenarios
Authors: Stefano Cioni, Cristina Párraga Niebla, Gonzalo Seco Granados, Sandro Scalise, Alessandro Vanelli-Coralli, María Angeles Vázquez Castro
Venue: EURASIP Journal on Wireless Communications and Networking (2007)

This paper deals with the analysis of advanced fade countermeasures for supporting DVB-S2 reception by mobile terminals mounted on high-speed trains. Recent market studies indicate this as a potential profitable market for satellite communications, provided that integration with wireless terrestrial networks can be implemented to bridge the satellite connectivity inside railway tunnels and large train stations. In turn, the satellite can typically offer the coverage of around 80% of the railway path with existing space infrastructure. This piece of work, representing the first step of a wider study, is focusing on the modifications which may be required in the DVB-S2 standard (to be employed in the forward link) in order to achieve reliable reception in a challenging environment such as the railway one. Modifications have been devised trying to minimize the impact on the existing air interface, standardized for fixed terminals.
Embedded noninteractive continuous bot detection
Authors: Roman V. Yampolskiy, Venu Govindaraju
Venue: Computers in Entertainment (CIE) (2008)

Multiplayer online computer games are quickly growing in popularity, with millions of players logging in every day. While most play in accordance with the rules set up by the game designers, some choose to utilize artificially intelligent assistant programs, a.k.a. bots, to gain an unfair advantage over other players. In this article we demonstrate how an embedded noninteractive test can be used to prevent automatic artificially intelligent players from illegally participating in online game-play. Our solution has numerous advantages over traditional tests, such as its nonobtrusive nature, continuous verification, and simple noninteractive and outsourcing-proof design.