ppxscal/embedding_network huggingface dataset:
Good Continuation in Layers: Shading flows, color flows, surfaces and shadows
Authors: Ohad Ben-Shahar, Andreas Glaser, Steven W. Zucker
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

We extend the concept of good continuation in a uniform fashion from boundaries to shading, hue, and texture. Each has the property that local measurements yield an orientation, which we explicitly establish for hue using geometric harmonic techniques. Good continuation arises in a geometric sense, because these orientations all vary smoothly in an appropriate sense. Thus they correspond to flows. Taken together they define a layered set of flows, in the sense the "horizontal" computations within each flow provide global consistency while "vertical" computations across flows enable the identification of shading and shadowing and different types of edges. Evidence is reviewed that primate visual systems enjoy such an organization.
Efficient Margin Maximizing with Boosting
Authors: Gunnar Rätsch, Manfred K. Warmuth
Venue: The Journal of Machine Learning Research (2005)

AdaBoost produces a linear combination of base hypotheses and predicts with the sign of this linear combination. The linear combination may be viewed as a hyperplane in feature space where the base hypotheses form the features. It has been observed that the generalization error of the algorithm continues to improve even after all examples are on the correct side of the current hyperplane. The improvement is attributed to the experimental observation that the distances (margins) of the examples to the separating hyperplane are increasing even after all examples are on the correct side.We introduce a new version of AdaBoost, called AdaBoost*ν, that explicitly maximizes the minimum margin of the examples up to a given precision. The algorithm incorporates a current estimate of the achievable margin into its calculation of the linear coefficients of the base hypotheses. The bound on the number of iterations needed by the new algorithms is the same as the number needed by a known version of AdaBoost that must have an explicit estimate of the achievable margin as a parameter. We also illustrate experimentally that our algorithm requires considerably fewer iterations than other algorithms that aim to maximize the margin.
Solving the Wiener-Hopf equation with a probabilistic kernel
Authors: V. I. Norkin
Venue: Cybernetics and Systems Analysis (2006)

Inhomogeneous Wiener-Hopf equations on a halfline with probabilistic kernels are considered. They are analyzed using the theory of isotonic and contraction operators. Necessary and sufficient conditions of existence and general sufficient conditions of uniqueness for the solutions of these equations are established. The conditions for and the rate of convergence of successive approximations of the solution are found.
End-to-end techniques for network resource management
Authors: Paul Francis
Venue:  (2006)

Network-based applications have evolved from simple web browsing to complex commercial transactions. This evolution has made a clear case for network QoS mechanisms, since the delays seen on the network often form the major component of an end-user's perceived delay. The key challenge in providing network QoS is the distributed and decentralized nature of the network resource. In this thesis, we have attempted to develop techniques for exposing the network as a managed resource to applications without requiring any explicit support from the network elements like routers, gateways, ISPs, etc. As part of this broad initiative, we have developed two key components: MPAT (used to control the network from end-hosts), and Netmapper (used to monitor the network from end-hosts). MPAT is the first truly scalable algorithm for providing differential services to a group of TCP flows that share the same bottleneck link. The challenge is to hold the cumulative fair share of all flows, while being fair to the background traffic. Our system can give more bandwidth to one TCP flow at the expense of lower bandwidth to another flow, in such a way that the sum total of the bandwidth that the two flows get is same as the fair share of two TCP flows. Using experiments on the real Internet, we show that our system can share congestion state across more than 100 TCP flows with throughput differentials of 95:1. We also developed a network mapping and annotation service (called Netmapper) for distributed applications sensitive to bandwidth availability, latency, or loss. The system exposes internal network state (e.g. bandwidth available at links, location of bottleneck links) using only end-to-end measurements that are TCP-friendly. Our novel scheme to identify the location of bottleneck links improves upon existing methods for bottleneck identification, which detect incorrect bottleneck link if the bottleneck is due to transient network congestion. We built Netmapper, and show, using experiments on the real Internet, that the system consumes very small amount of bandwidth, and converges even with dynamically varying network state.
An Effective Test Pattern Generation for Testing Signal Integrity
Authors: Yongjoon Kim, Myung-Hoon Yang, Youngkyu Park, DaeYeal Lee, Sungho Kang
Venue: Proceedings of the 15th Asian Test Symposium (2006)

As more cores are integrated in a single chip with sophisticated process like nano technology, testing signal integrity between the cores needs much effort due to complicate coupling effects. In this paper, we propose a novel test pattern generation method for testing signal integrity. Using this method, short and effective test patterns are generated with low hardware overhead. It can be used for self-test scheme and experimental results show the effectiveness of the proposed scheme.
Parameter estimation for periodic discrete event processes
Authors: D. A. Gray, B. J. Slocumb, S. D. Elton
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

Methods for estimating the pulse repetition interval and the pulse time-of-arrival jitter variance of a periodic pulse train (PT) are given. The estimators operate on data comprising a set of pulse time-of-arrival measurements which are corrupted by additive noise (timing jitter). Parameter estimators are formulated using two jitter models common to PT applications. The estimators include a closed-form maximum likelihood approach, recursive least squares estimation, and a Kalman filter approach that incorporates both jitter models. Comparison with Cramer-Rao lower bounds shows the estimators to be statistically efficient for a correct choice of jitter model. The estimator performance penalty for using the incorrect jitter model is also presented. Finally, the utility of the estimators is demonstrated using PT measurements from an operational radar.
Neural Mechanisms of Involuntary Attention to Acoustic Novelty and Change
Authors: Carles Escera, Kimmo Alho, István Winkler, Risto Näätänen
Venue: Journal of Cognitive Neuroscience (1998)

Behavioral and event-related brain potential (ERP) measures were used to elucidate the neural mechanisms of involuntary engagement of attention by novelty and change in the acoustic environment. The behavioral measures consisted of the reaction time (RT) and performance accuracy (hit rate) in a forcedchoice visual RT task where subjects were to discriminate between odd and even numbers. Each visual stimulus was preceded by an irrelevant auditory stimulus, which was randomly either a "standard" tone (80%), a slightly, higher "deviant" tone (10%), or a natural, "novel" sound (10%). Novel sounds prolonged the RT to successive visual stimuli by 17 msec as compared with the RT to visual stimuli that followed standard tones. Deviant tones, in turn, decreased the hit rate but did not significantly affect the RT. In the ERPs to deviant tones, the mismatch negativity (MMN), peaking at 150 msec, and a second negativity, peaking at 400 msec, could be observed. Novel sounds elicited an enhanced N1, with a probable overlap by the MMN, and a large positive P3a response with two different subcomponents: an early centrally dominant P3a, peaking at 230 msec, and a late P3a, peaking at 315 msec with a right-frontal scalp maximum. The present results suggest the involvement of two different neural mechanisms in triggering involuntary attention to acoustic novelty and change: a transient-detector mechanism activated by novel sounds and reflected in the N1 and a stimulus-change detector mechanism activated by deviant tones and novel sounds and reflected in the MMN. The observed differential distracting effects by slightly deviant tones and widely deviant novel sounds support the notion of two separate mechanisms of involuntary attention.
Kernel projection classifiers with suppressing features of other classes
Authors: Yoshikazu Washizawa, Yukihiko Yamashita
Venue: Neural Computation (2006)

We propose a new classification method based on a kernel technique called suppressed kernel sample space projection classifier (SKSP), which is extended from kernel sample space projection classifier (KSP).In kernel methods, samples are classified after they are mapped from an input space to a high-dimensional space called a feature space. The space that is spanned by samples of a class in a feature space is defined as a kernel sample space. In KSP, an unknown input vector is classified to the class of which projection norm onto the kernel sample space is maximized. KSP can be interpreted as a special type of kernel principal component analysis (KPCA). KPCA is also used in classification problems. However, KSP has more useful properties compared with KPCA, and its accuracy is almost the same as or better than that of KPCA classifier.Since KSP is a single-class classifier, it uses only self-class samples for learning. Thus, for a multiclass classification problem, even though there are very many classes, the computational cost does not change for each class. However, we expect that more useful features can be obtained for classification if samples from other classes are used. By extending KSP to SKSP, the effects of other classes are suppressed, and useful features can be extracted with an oblique projection.Experiments on two-class classification problems, indicate that SKSP shows high accuracy in many classification problems.
A Survey of Unit Testing Practices
Authors: Per Runeson
Venue: IEEE Software (2006)

Most companies and testing books use the term unit testing, but its semantics varies widely in different organizations. Lund University researchers launched a survey in a company network to explore this variation. The survey, which involved companies in focus-group discussions and a questionnaire, focused on defining unit testing, discussing its practices, and evaluating a company's strengths and weaknesses. The results indicate a common understanding of unit testing's scope, although the aim and practices vary across companies. Practitioners can use the survey instruments as a baseline for measuring their unit testing practices and to start improvement initiatives.This article is part of a special issue on Software Testing.
Time-varying higher-order cumulant spectra: application to the analysis of composite FM signals in multiplicative and additive noise
Authors: B. Boashash, B. Ristic
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

Time-varying higher-order spectra (TV-HOS), have recently been proposed for (poly)spectral analysis of non-stationary signals. Two new results are presented here. First, the cumulant TV-HOS (in particular, cumulant Wigner-Ville trispectrum (WVT)), is shown to preserve the essential properties of cumulant higher-order spectra (e.g. eliminate Gaussian additive noise) and at the same time characterise time-variations of the signal's frequency content. Second, when dealing with composite FM signals, a special kind of "non-oscillating cross-terms" is shown to appear in the moment TV-HOS time-frequency subspace. We show that these cross-terms cannot be eliminated by smoothing the WVT, but rather by an appropriate projection from the full time-multi-frequency space to a time-frequency subspace.
Virtually Pipelined Network Memory
Authors: Banit Agrawal, Timothy Sherwood
Venue: Proceedings of the 39th Annual IEEE/ACM International Symposium on Microarchitecture (2006)

We introduce virtually-pipelined memory, an architectural technique that efficiently supports high-bandwidth, uniform latency memory accesses, and high-confidence throughput even under adversarial conditions. We apply this technique to the network processing domain where memory hierarchy design is an increasingly challenging problem as network bandwidth increases. Virtual pipelining provides a simple to analyze programing model of a deep pipeline (deterministic latencies) with a completely different physical implementation (a memory system with banks and probabilistic mapping). This allows designers to effectively decouple the analysis of their algorithms and data structures from the analysis of the memory buses and banks. Unlike specialized hardware customized for a specific data-plane algorithm, our system makes no assumption about the memory access patterns. In the domain of network processors this will be of growing importance as the size of the routing tables, the complexity of the packet classification rules, and the amount of packet buffering required, all continue to grow at a staggering rate. We present a mathematical argument for our system's ability to provably provide bandwidth with high confidence and demonstrate its functionality and area overhead through a synthesizable design. We further show that, even though our scheme is general purpose to support new applications such as packet reassembly, it outperforms the state of the art in specialized packet buffering architectures.
Formal Models of Appeal and Its Evaluation in Argumentation-based Negotiation of Agent
Authors: Wu Jinghua, Jiang Guorui, Huang Tiyun
Venue: Proceedings of the International Multi-Conference on Computing in the Global Information Technology (2006)

Argumentation-based negotiation of agent has been well known and widely studied for it can make agent who received the argumentation change its preferences or goals and make the negotiators find a well compromise quickly in the end. But few can effectively and formally model and evaluate with appeal, which is the most important kind of argumentation. The goals of this paper are to formally model with appeal and its evaluation, and then analyze its strength through the simulated calculation of it, which can make the negotiator appealed make a right choice and accomplish the cooperation with its opponent.
Application-Level Resource Provisioning on the Grid
Authors: Gurmeet Singh, Carl Kesselman, Ewa Deelman
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

In this paper, we present algorithms for Grid resource provisioning that employ agreement-based resource management. These algorithms allow userlevel resource allocation and scheduling of applications that are structured as a precedenceconstrained set of tasks. We present a provisioning model where the resource availability in the Grid can be enumerated as a set of slots. A slot is defined as a number of processors available from a certain start time for a certain duration at a certain cost. Using a cost model that combines the cost of resource allocation and the expected application runtime, we evaluate the performance of the Min-Min and of the Genetic algorithm (GA)-based heuristics for a range of synthetic applications. We show that the GA paired with a list scheduling algorithm can obtain significantly better solutions than the Min-Min heuristic alone.
Combining Bayesian Networks and Decision Trees to Predict Drosophila melanogaster Protein-Protein Interactions
Authors: Jingkai Yu, Farshad Fotouhi, Russell L. Jr. Finley
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

Protein-protein interactions are important in many aspects of cellular processes. Discovery of protein interactions that take place within a cell can provide a starting point for understanding biological regulatory pathways. High-throughput experimental screens developed so far show high error rates in terms of false positives and false negatives. There is thus a great need for new computational approaches to enable the prediction of new protein-protein interactions and to enhance the reliability of experimentally derived interaction maps. Many of the computational approaches developed thus far are based on strong biological assumptions, resulting in biases towards certain types of predictions. As a first step towards a more complete and accurate interaction map, we propose to predict protein-protein interactions using existing experimental data combined with the Gene Ontology (GO) annotations of proteins. We do not use strong prior rules about GO patterns and proteinprotein interactions and thus avoid biases associated with various assumptions. We show that GO annotations can be a useful predictor for proteinprotein interactions and that prediction performance can be improved by combining the results from both decision trees and Bayesian networks.
Analysis of multi-server queue with a single vacation (e, d)-policy
Authors: Xiuli Xu, Zhe George Zhang
Venue: Performance Evaluation (2006)

In this paper, we consider a Markovian multi-server queue with a single vacation (e,d)-policy. In an M/M/c system with such a policy, when d (<c) servers become idle at a service completion (or a customer departure) instant, e(≤d) idle servers take a single vacation. After the vacation is completed, these servers return to attend the queue (either serve or stay idle) until the vacation condition is satisfied again. This model is more appropriate for the service or manufacturing systems with servers' maintenance performed during their idle time. We formulate the system as a quasi-birth-and-death (QBD) process and develop the various stationary performance measures for this system. In addition, we also prove several conditional stochastic decomposition properties.
Optimization in a Health Care System: a Liver Transplantation Example
Authors: Gustavo da Gama Torres, Ricardo Poley Martins Ferreira, Henrique Pacca Loureiro Luna
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

This text presents a study in modeling a waiting list of liver transplantation, and the use of the resources that affects the system efficiency. The approach uses the graph theory to modeling the system as a workflow. The objective is to know how the system is, and how it will work after changing some parameters. The focus is the planning and the system management. The work encloses aspects of knowledge representation and optimization. An experiment is described and some conclusions are extracted.
On equations with partial derivatives which correspond to invariant manifolds of mechanical systems
Authors: V. D. Irtegov
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 4 (2003)

The paper discusses the relationships between the equations of disturbed motion in the neighborhood of invariant manifolds of conservative systems and the systems of equations with partial derivatives, which have one and the same main part. The properties, which are common for the considered systems, are indicated. Some examples of application of such a relationship to the case of equations of rigid body dynamics are given.
Memory Lost and Regained Following Bilateral Hippocampal Damage
Authors: Katharina Henke, Neal E. A. Kroll, Hamraz Behniea, David G. Amaral, Michael B. Miller, Robert Rafal, Michael S. Gazzaniga
Venue: Journal of Cognitive Neuroscience (1999)

We present a longitudinal neuropsychological study (31 examinations over a period of 18 months) of patient DF. DF demonstrated bilateral atrophy of the hippocampal formation and globus pallidus resulting from carbon monoxide poisoning. Eighteen months after the event, the volume of the hippocampal formation was reduced by 42% on the left side and 28% on the right. The patient initially presented with a severe global amnesia. Then, he showed a gradual, yet selective recovery of episodic memory function. Verbal free recall and spatial mem ory performance remained reduced, whereas immediate word recall and recognition memory, as well as picture learning and memory, improved to levels at the lower range of normal performance. Interestingly, nonspatial associative learning was never much impaired and recovered completely by the end of testing. These data are taken as evidence that the human hippocampal formation does not equally support different forms of episodic memory.
A Statistical Digital Equalizer for Loopback-based Linearity Test of Data Converters
Authors: Hongjoong Shin, Jiseon Park, Jacob A. Abraham
Venue: Proceedings of the 15th Asian Test Symposium (2006)

This paper presents a new Built-in Self Test (BIST) method based on efficient digital equalization and spectral prediction techniques. The method enables accurate built-in characterization of the static performance parameters of data converters, and thus test and calibration costs can be significantly alleviated. Based on recent work on dynamic performance parameter characterization using a loopback test, the transfer function of a DAC in loopback mode is estimated with a spectral prediction technique and Chebyshev polynomials. A digital equalizer is designed to compensate for the nonlinearity of the DAC in the pre-conversion stage, hence the ADC can be tested with the digitally calibrated analog signals. The digital equalizer overcomes accuracy limitations encountered in a traditional compensation technique, and thus a standard histogram test which may suffer from INL masking problems can be successfully applied. Simulation results are presented to validate the technique.
Hierarchical topic segmentation of websites
Authors: Ravi Kumar, Kunal Punera, Andrew Tomkins
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

In this paper, we consider the problem of identifying and segmenting topically cohesive regions in the URL tree of a large website. Each page of the website is assumed to have a topic label or a distribution on topic labels generated using a standard classifier. We develop a set of cost measures characterizing the benefit accrued by introducing a segmentation of the site based on the topic labels. We propose a general framework to use these measures for describing the quality of a segmentation; we also provide an efficient algorithm to find the best segmentation in this framework. Extensive experiments on human-labeled data confirm the soundness of our framework and suggest that a judicious choice of cost measures allows the algorithm to perform surprisingly accurate topical segmentations.