ppxscal/embedding_network huggingface dataset:
Towards the Construction of Attack Resistant and Efficient Overlay Streaming Topologies
Authors: Thorsten Strufe, Jens Wildhagen, Günter Schäfer
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2007)

Even though overlay streaming is an inherently fault tolerant and stable system architecture, careful neighbor selection is a significant task. Inappropriate routing decisions can lead to an unstable topology with only a few very important nodes on which a large set of succeeding nodes depend. The presented algorithm selects streaming neighbors based on local information, passing knowledge to parent nodes only. Similar to SplitStream [Castro, M., P. Druschel, A. Kermarrec, A. Nandi, A. Rowstron and A. Singh, SplitStream: High-bandwidth content distribution in a cooperative environment, in: Proceedings of (IPTPS'03), 2003, pp. 298-313], it creates inner-node disjoint multicast trees. The created topologies are broad and have short paths, thus improving the resistance to node failure and intentional attacks. A malicious node can neither gain any knowledge about different regions of the topology other than its own successors nor deliberately move to a more important position in the hierarchy. The characteristics of the created topologies are revised in a static simulation study calculating the vertex connectivity and packet loss on node disconnections.
Mechanisms for multi-unit auctions
Authors: Shahar Dobzinski, Noam Nisan
Venue: Proceedings of the 8th ACM conference on Electronic commerce (2007)

We present an incentive-compatible polynomial-time approximation scheme for multi-unit auctions with general k-minded playervaluations. The mechanism fully optimizes over an appropriately chosen sub-range of possible allocations and then uses VCG payments over this sub-range. We show that obtaining a fully polynomial-time incentive-compatible approximation scheme, at least using VCG payments, is NP-hard. For the case of valuations given by black boxes, we give a polynomial-time incentive-compatible 2-approximation mechanism and show that no better is possible, at least using VCG payments.
Fast Ego-motion Estimation with Multi-rate Fusion of Inertial and Vision
Authors: Leopoldo Armesto, Josep Tornero, Markus Vincze
Venue: International Journal of Robotics Research (2007)

This paper presents a tracking system for ego-motion estimation which fuses vision and inertial measurements using EKF and UKF (Extended and Unscented Kalman Filters), where a comparison of their performance has been done. It also considers the multi-rate nature of the sensors: inertial sensing is sampled at a fast sampling frequency while the sampling frequency of vision is lower. the proposed approach uses a constant linear acceleration model and constant angular velocity model based on quaternions, which yields a non-linear model for states and a linear model in measurement equations. Results show that a significant improvement is obtained on the estimation when fusing both measurements with respect to just vision or just inertial measurements. It is also shown that the proposed system can estimate fast-motions even when vision system fails. Moreover, a study of the influence of the noise covariance is also performed, which aims to select their appropriate values at the tuning process. The setup is an end-effector mounted camera, which allow us to pre-define basic rotational and translational motions for validating results.
Optimum Design for Wireless Satellite Communication
Authors: Hong Liang
Venue: Proceedings of the International Multi-Conference on Computing in the Global Information Technology (2007)

Satellite wireless communication has following problems which are huge communication amount, atmosphere noise, long distance information transfer, and orbit and position control, etc. This paper proposes some methods for wireless satellite communication which can solve above problems. This paper creates a program control connection method for solving huge communication problem. This paper indicates a FM and FSMA method to purify the atmosphere noise and transfer high quality information flow. This paper shows a paraboloid antenna method for long distance information transference. This paper proposes light year test and adaptive control method to solve correct orbit and position control problems. All these methods are efficient and reliable which can improve the quality of wireless satellite communication significantly.
Optimal power loading for OFDM transmissions over underspread Rayleigh time-varying channels
Authors: A. Scaglione
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

OFDM renders multipath channels with finite memory equivalent to parallel flat fading subchannels, over which equalization amounts to simple phase compensation. If the channel status information is known at the transmitter side, optimal power loading across subchannels is possible. Users mobility, time and carrier asynchronism introduce variations in the equivalent channel impulse response setting the channel coherence time as a boundary for the OFDM symbol duration. Optimal design should incorporate such variations, possibly avoiding the overhead of frequent training. Most adaptive modulation schemes assume knowledge of the channel response and flat fading. Modeling the channel taps as correlated Gaussian random processes, we develop the optimal power/bit loading strategies for frequency selective fading, based on the knowledge of the channel past estimates and correlation. In practice the channel sample correlation are obtained as a by-product of channel estimation which, however, does not need to be performed on a block by block basis.
Evaluation of a warped linear predictive coding scheme
Authors: A. Harma
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02 (2000)

Basically all conventional digital signal processing techniques can be warped by introducing a simple modification to the system. In this paper, the focus is in warped linear predictive coding techniques with application to speech and audio coding. The performance of warped LPC is compared with a conventional LPC in listening tests and in terms of technical measures. This is done at various sampling rates as a function of the order of the LPC model.
A Scenario for Identity Management in Daidalos
Authors: Zhikui Chen
Venue: Proceedings of the Fifth Annual Conference on Communication Networks and Services Research (2007)

Digital Identity corresponds to the electronic information associated generally with an individual in a particular identity system. This is used by online service providers to authenticate and authorize users for services protected by access policies. Having good identity systems can enable individuals to use effectively and extensively electronic transactions in a secure yet privacy preserving manner. In order to match the above purpose, this paper introduces an identity scenario, a user-centric identity management, in terms of VID -- Virtual Identity, which concept is designed to protect a user's privacy and secure communication data, which contemplates the multitude of identities and roles we take on each time we turn on our computer, mobile phone or PDA.. Simultaneously, the associated identity management system with its related infrastructure is described. A key component, the ID broker, of the proposed infrastructure is also detailed including some interfaces and their related components. Furthermore, a method that allows a user to manage his/her service via the VID is introduced.
Pattern identification in dynamical systems via symbolic time series analysis
Authors: Venkatesh Rajagopalan, Asok Ray, Rohan Samsi, Jeffrey Mayer
Venue: Pattern Recognition (2007)

This paper presents symbolic time series analysis (STSA) of multi-dimensional measurement data for pattern identification in dynamical systems. The proposed methodology is built upon concepts derived from Information Theory and Automata Theory. The objective is not merely to classify the time series patterns but also to identify the variations therein. To achieve this goal, a symbol alphabet is constructed from raw data through partitioning of the data space. The maximum entropy method of partitioning is extended to multi-dimensional space. The resulting symbol sequences, generated from time series data, are used to model the dynamical information as finite state automata and the patterns are represented by the stationary state probability distributions. A novel procedure for determining the structure of the finite state automata, based on entropy rate, is introduced. The diversity among the observed patterns is quantified by a suitable measure. The efficacy of the STSA technique for pattern identification is demonstrated via laboratory experimentation on nonlinear systems.
A Clustering Technique for Early Detection of Dominant and Recessive Cross-Cutting Concerns
Authors: Chuan Duan, Jane Cleland-Huang
Venue: Proceedings of the Early Aspects at ICSE: Workshops in Aspect-Oriented Requirements Engineering and Architecture Design (2007)

This paper describes an approach for automating the detection of early aspects. Based on hierarchical clustering and an underlying probabilistic algorithm, the technique generates initial requirements clusters representing relatively homogenous feature sets, use cases and potential cross-cutting concerns. A second clustering phase is then applied in which dominant terms are identified and removed from each of the initial clusters, allowing new clusters to form around less dominant terms. This second phase enables previously inter-tangled aspects to be detected. Three metrics are introduced to differentiate potential cross-cutting concerns from other types of clusters. The approach is illustrated through an example based on the Public Health Watcher case study.
Esperanto, to aid education reform
Authors: A. C. Boschen
Venue: Proceedings of the Frontiers in Education Conference on 1995. Proceedings., 1995 vol 1. - Volume 01 (1995)

Amidst vast and intense social and economic dislocations and budget crises we agonize over ways to improve our education base-to ferret out deficiencies and bring it into step with the needs of the times (a strategy, furthermore, to check the further decline of society). Educational philosophies are under close scrutiny, as also the bare nuts and bolts. We suggest that these analyses go just a bit deeper than we are in the habit of doing on such matters, more in the manner of an engineering analysis. Something akin to a time and motion study is suggested, and in this vein a profound consideration of language itself as the lowest base of communication-and of education. How do the gross irregularities of language impact the learning process? In what ways and to what extent could a scientifically designed language aid the process? A close look at Esperanto is offered. It is the one such language that has stood the test of time, in continuous and extensive use by a worldwide speaking, reading, and writing community. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Parallel computing in problems that occur during mathematical simulation of radiation transfer
Authors: E. F. Lelikova, L. I. Rubina, O. N. Ul'Yanov, M. A. Chashchin
Venue: Automation and Remote Control (2007)

Possibilities of the application of parallel computing to solving problems that occur during mathematical simulation of radiation transfer are considered. Techniques of the radiation analytic representation method (RARM) and the Lagrange-Chebyshev polynomial method (LCPM) for radiation transfer numerical simulation in the nonuniform plane layer of finite thickness that contains single-or multicomponent mixture of substances are designed. The techniques include several sequential and parallel algorithms and programs that realize them; a part of them is joined into a program system with the user interface. Parallel programs are elaborated in MPI and DVM technologies of parallel programming.
Generalized second order identifiability condition and relevant testing technique
Authors: K. Abed-Meraim
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

This paper presents a generalized sufficient and necessary identifiability condition for second order statistics (SOS) based blind source separation (BSS). It is then shown that, even when this condition is not satisfied the sources are still partially identifiable (in blocks). Furthermore, although the identifiability condition depends on the autocorrelation coefficients of the unknown source signals, it can be tested directly from the observations. This issue is of prime importance to decide whether the sources have been well separated or else if further treatments are needed. Some simulation examples are given to assess our theoretical results.
Interactive presentation: Implementation of AES/Rijndael on a dynamically reconfigurable architecture
Authors: Claudio Mucci, Luca Vanzolini, Fabio Campi, Mario Toma
Venue: Proceedings of the conference on Design, automation and test in Europe (2007)

Reconfigurable architectures provide the user the capability to couple performance typical of hardware design with the flexibility of the software. In this paper, we present the design of AES/Rijndael on a dynamically reconfigurable architecture. We will show a performance improvement of three order of magnitude compared to the reference code and up to 24x speed-up figure wrt fast C implementations over a RISC processor. A maximum throughput of 546 Mbit/sec is achieved. Compared to prior art, we show better energy efficiency with respect to the other programmable solutions, obtaining up to 3 Mbit/sec/mW.
A new clustering evaluation function using Renyi's information potential
Authors: E. Gokcay
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06 (2000)

Clustering is an important unsupervised learning paradigm, but so far the traditional methodologies are mostly based on the minimization of the variance between the data and the cluster means. Here we propose a new evaluation function based on a previously developed information theoretic measure defined from Renyi's (1960) entropy. We show how to apply Renyi's entropy to clustering and analyze the resulting staircase nature of the performance function that can be expected during learning. We suggest simulated annealing as a possible optimization criterion.
A Probabilistic Ensemble Pruning Algorithm
Authors: Huanhuan Chen, Peter Tino, Xin Yao
Venue: Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (2006)

An ensemble is a group of learners that work together as a committee to solve a problem. However, the existing ensemble training algorithms sometimes generate unnecessary large ensembles, which consume extra computational resource and may degrade the performance. Ensemble pruning algorithm aims to find a good subset of ensemble members to constitute a small ensemble, which saves the computational resource and performs as well as, or better than, the non-pruned ensemble. This paper will introduce a probabilistic ensemble pruning algorithm by choosing a set of "sparse" combination weights, most of which are zero, to prune the large ensemble. In order to obtain the set of sparse combination weights and satisfy the non-negative restriction of the combination weights, a left-truncated, nonnegative, Gaussian prior is adopted over every combination weight. Expectation-Maximization algorithm is employed to obtain maximum a posterior (MAP) estimation of weight vector. Four benchmark regression problems and another four benchmark classification problems have been employed to demonstrate the effectiveness of the method.
Fuzzy Multi-object Linear Programming Application in Product-Mix Decision-Making
Authors: Sani Susanto, Neneng Tintin Rosmiyanti, Pandian Vasant, Arijit Bhattacharya
Venue: Proceedings of the First Asia International Conference on Modelling & Simulation (2007)

This paper focuses on optimizing product-mix problem using real-world data of a food processing industry. The extensively used LP model has been remodeled using fuzzy sets and applied to the real-world problem. The developed LP model is able to consider the fuzziness in the parameters and to tackle the presence of multiple objective functions. The degree of satisfaction of the product-mix decision-maker in terms of (i) the total profit obtained and (ii) the waste resulted, is at least 70%, which is encouraging.
A multichannel speech/silence detector based on time delay estimation and fuzzy classification
Authors: F. Bentelli
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01 (1999)

Discontinuous transmission based on speech/pause detection represents a valid solution to improve the spectral efficiency of new-generation wireless communication systems. In this context robust voice activity detection (VAD) algorithms are required, as traditional solutions present a high misclassification rate in the presence of the background noise typical of mobile environments. The fuzzy voice activity detector (FVAD) proposed by Beritelli, Casale, and Cavallaro (see Contribution ITU-T, Study Group 16, question 19/16, Washington, September 1997), shows that a valid alternative to deal with the problem of activity decision is to use methodologies like fuzzy logic. In this paper we propose a multichannel approach to activity detection using both fuzzy logic and time delay estimation. Objective and subjective tests confirm a significant improvement over traditional methods, above all in terms of a reduction in activity increase for nonstationary noise.
Circular Arc Path Method: A New 2-D Polygon Blending Algorithm
Authors: Baogang Bai, Zhongyue Li, Zhigeng Pan
Venue: Proceedings of the 16th International Conference on Artificial Reality and Telexistence--Workshops (2006)

2-D shape blending or morphing is the process of continuously transforming one polygon into another, which is widely studied in 2-D character animation, pattern matching, geometric modeling, virtual reality technologies and simulation, etc. ,and has found significant applications in those fields. Presents a new 2-D shape blending algorithm based on the vertex circular arc path.After controlling the vertex locus preferably, the user controls the morph by specifying the types of vertex correspondence as well as the feature correspondence between the source and target shapes. Some techniques are also provided to control the vertex path during the morphing process. The amount of user input required to produce a morph is directly proportional to the amount of controls the user wishes to impose on the process. The user may allow the system to automatically generate the morph as well. Our approach is totally geometry based and is easy and fast enough in fully interactive time. Experimental results show that the two polygons can be blended as user prescribed whilst keeping the feature correspondence and feature preservation. The result is satisfactory. Experimental results show the applicability, flexibility, and expandability of our approach.
Design tradeoffs in applying content addressable storage to enterprise-scale systems based on virtual machines
Authors: Partho Nath, Michael A. Kozuch, David R. O'Hallaron, Jan Harkes, M. Satyanarayanan, Niraj Tolia, Matt Toups
Venue: Proceedings of the annual conference on USENIX '06 Annual Technical Conference (2006)

This paper analyzes the usage data from a live deployment of an enterprise client management system based on virtual machine (VM) technology. Over a period of seven months, twenty-three volunteers used VM-based computing environments hosted by the system and created over 800 checkpoints of VM state, where each checkpoint included the virtual memory and disk states. Using this data, we study the design tradeoffs in applying content addressable storage (CAS) to such VM-based systems. In particular, we explore the impact on storage requirements and network load of different privacy properties and data granularities in the design of the underlying CAS system. The study clearly demonstrates that relaxing privacy can reduce the resource requirements of the system, and identifies designs that provide reasonable compromises between privacy and resource demands.
Dynamic compilation: the benefits of early investing
Authors: Prasad Kulkarni, Matthew Arnold, Michael Hind
Venue: Proceedings of the 3rd international conference on Virtual execution environments (2007)

Dynamic compilation is typically performed in a separate thread, asynchronously with the remaining application threads. This compilation thread is often scheduled for execution in a simple round-robin fashion either by the operating system or by the virtual machine itself. Despite the popularity of this approach in production virtual machines, it has a number of shortcomings that can lead to suboptimal performance. This paper explores a number of issues surrounding asynchronous dynamic compilation in a virtual machine. We begin by describing the shortcomings of current approaches and demonstrate their potential to perform poorly under certain conditions. We describe the importance of enforcing a minimum level of utilization for the compilation thread, and evaluate the performance implications of varying the utilization that is enforced. We observed surprisingly large speedups by increasing the priority of the compilation thread, averaging 18.2% improvement over a large benchmark suite. Finally, we discuss options for implementing these techniques in a VM and address relevant issues when moving from a single-processor to a multiprocessor machine.
A study on the modeling ability of the IDS method: A soft computing technique using pattern-based information processing
Authors: Masayuki Murakami, Nakaji Honda
Venue: International Journal of Approximate Reasoning (2007)

The ink drop spread (IDS) method is a modeling technique developed by algorithmically mimicking the information-handling processes of the human brain. This method has been proposed as a new approach to soft computing. IDS modeling is characterized by processing that uses intuitive pattern information instead of complex formulas, and it is capable of stable and fast convergences. This paper investigates the modeling ability of the IDS method based on three typical benchmarks. Experimental results demonstrated that the IDS method can handle various modeling targets, ranging from logic operations to complex nonlinear systems, and that its modeling performance is satisfactory in comparison with that of feedforward neural networks.