ppxscal/embedding_network huggingface dataset:
Bayesian separation and recovery of convolutively mixed autoregressive sources
Authors: S. J. Godsill
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

In this paper we address the problem of the separation and recovery of convolutively mixed autoregressive processes in a Bayesian framework. Solving this problem requires the ability to solve integration and/or optimization problems of complicated posterior distributions. We thus propose efficient stochastic algorithms based on Markov chain Monte Carlo (MCMC) methods. We present three algorithms. The first one is a classical Gibbs sampler that generates samples from the posterior distribution. The two other algorithms are stochastic optimization algorithms that allow to optimize either the marginal distribution of the sources, or the marginal distribution of the parameters of the sources and mixing filters, conditional upon the observation. Simulations are presented.
Markovian high resolution spectral analysis
Authors: P. Ciuciu
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

When short data records are available, spectral analysis is basically an undetermined linear inverse problem. One usually considers the theoretical setting of regularization to solve such ill-posed problems. In this paper, we first show that "nonparametric" and "high resolution" are not incompatible in the field of spectral analysis. To this end, we introduce non-quadratic convex penalization functions, like in low level image processing. The spectral amplitudes estimate is then defined as the unique minimizer of a compound convex criterion. An original scheme of regularization to simultaneously retrieve narrow-band and wide-band spectral features is finally proposed.
Automatic Construction of N-ary Tree Based Taxonomies
Authors: Kunal Punera, Suju Rajan, Joydeep Ghosh
Venue: Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (2006)

Hierarchies are an intuitive and effective organization paradigm for data. Of late there has been considerable research on automatically learning hierarchical organizations of data. In this paper, we explore the problem of learning nary tree based hierarchies of categories with no user-defined parameters. We propose a framework that characterizes a "good" taxonomy and also provide an algorithm to find it. This algorithm works completely automatically (with no user input) and is significantly less greedy than existing algorithms in literature. We evaluate our approach on multiple real life datasets from diverse domains, such as text mining, hyper-spectral analysis, written character recognition etc. Our experimental results show that not only are n-ary trees based taxonomies more "natural", but also the output space decompositions induced by these taxonomies for many datasets yield better classification accuracies as opposed to classification on binary tree based taxonomies.
Provenance-aware storage systems
Authors: Kiran-Kumar Muniswamy-Reddy, David A. Holland, Uri Braun, Margo Seltzer
Venue: Proceedings of the annual conference on USENIX '06 Annual Technical Conference (2006)

A Provenance-Aware Storage System (PASS) is a storage system that automatically collects and maintains provenance or lineage, the complete history or ancestry of an item. We discuss the advantages of treating provenance as meta-data collected and maintained by the storage system, rather than as manual annotations stored in a separately administered database. We describe a PASS implementation, discussing the challenges it presents, performance cost it incurs, and the new functionality it enables. We show that with reasonable overhead, we can provide useful functionality not available in today's file systems or provenance management systems.
Centralized security policy support for virtual machine
Authors: Nguyen Anh Quynh, Ruo Ando, Yoshiyasu Takefuji
Venue: Proceedings of the 20th conference on Large Installation System Administration (2006)

For decades, researchers have pointed out that Mandatory Access Control (MAC) is an effective method to protect computer systems from being misused. Unfortunately, MAC is still not widely deployed because of its complexity. The problem is even worse in a virtual machine environment, because the current architecture is not designed to support MAC in a site-wide manner: machines with multiple virtual hosts needs to have multiple MAC security policies, and each of these policies must be updated and managed separately inside each virtual host. In order to ease the burden on administrators when deploying security policies in a virtual environment, this paper proposes an architecture named Virtual Mandatory Access Control (VMAC) to centralize security policies, so that all policy management can easily be done from a central machine. VMAC securely centralizes the security logging information from all virtual hosts into a central machine so intrusion detection analysis on the logging data is straightforward. To arrive at the architecture presented here, we have investigated various popular MAC schemes, and implemented several schemes with VMAC on the Xen Virtual Machine. This paper presents our experiences in the development process.
Extracting Number-Selective Responses from Coherent Oscillations in a Computer Model
Authors: Jeremy A. Miller, Garrett T. Kenyon
Venue: Neural Computation (2007)

Cortical neurons selective for numerosity may underlie an innate number sense in both animals and humans. We hypothesize that the number- selective responses of cortical neurons may in part be extracted from coherent, object-specific oscillations . Here, indirect evidence for this hypothesis is obtained by analyzing the numerosity information encoded by coherent oscillations in artificially generated spikes trains. Several experiments report that gamma-band oscillations evoked by the same object remain coherent, whereas oscillations evoked by separate objects are uncorrelated. Because the oscillations arising from separate objects would add in random phase to the total power summed across all stimulated neurons, we postulated that the total gamma activity, normalized by the number of spikes, should fall roughly as the square root of the number of objects in the scene, thereby implicitly encoding numerosity. To test the hypothesis, we examined the normalized gamma activity in multiunit spike trains, 50 to 1000 msec in duration, produced by a model feedback circuit previously shown to generate realistic coherent oscillations. In response to images containing different numbers of objects, regardless of their shape, size, or shading, the normalized gamma activity followed a square-root-of-n rule as long as the separation between objects was sufficiently large and their relative size and contrast differences were not too great. Arrays of winner-take-all numerosity detectors, each responding to normalized gamma activity within a particular band, exhibited tuning curves consistent with behavioral data. We conclude that coherent oscillations in principle could contribute to the number-selective responses of cortical neurons, although many critical issues await experimental resolution.
Metis: a thin-client application framework
Authors: Deborra J. Zukowski, Apratim Purakayastha, Ajay Mohindra, Murthy Devarakonda
Venue: Proceedings of the 3rd conference on USENIX Conference on Object-Oriented Technologies (COOTS) - Volume 3 (1997)

This paper introduces a thin-client programming model and then presents an object-oriented framework for developing applications using the model. The programming model and the framework have evolved from interactions with developers and users of commercial applications. The key aspects of the thin-client programming model are that the client downloads application front ends from the network; that these applications rely only on services found on network servers; that the services are bound as late as possible; and that the applications interact with each other within the confines of a workspace. We implemented the framework using Java Beans and JDK 1.1, and developed several sample applications using the framework.
Somatic solidarity, Magical Realism and Animating Popular Gods: Place-Hampi "where intensities are felt"
Authors: Sarah Kenderdine
Venue: Proceedings of the 11th International Conference Information Visualization (2007)

Place-Hampi is an embodied theatre of participation in the drama of Hindu mythology focused at the most significant archaeological, historical and sacred locations of the World Heritage site Vijayanagara (Hampi), South India. The research described in this paper examines a history of several scopic regimes observable in Indian aesthetic traditions (principally those associated with chromolithography) and their socio-cultural implications to articulate the somatic engagement inherent to encounters with the mythological deities in image form. Information derived from the examination of diverse scopic regimes has been used to guide the decisions in symbolic logic and high level cognitive programming of computer graphic characters that help co-evolve the narrative engagement between intangible heritage of "place' and participants. Place- Hampi investigates experiences of encounter as tangible knowledge that has implications for immersive heritage visualizations for diverse cultural audiences.
Facilitating Interdisciplinary Modelling of Complex Problems
Authors: Igor Nikolic, Pieter J. Beers, Gerard P. J. Dijkema
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

In this paper the system-decomposition method is presented, which facilitates the process of modelling of complex systems by multidisciplinary teams. Such modelling is non-trivial, because these teams must codtfy knowledge~omd zflerent scientific disciplines in order to create models that exhibit realistic behaviour. The system-decomposition method has been developed to facilitate the creation of a standard inte$ace for and between researchers, model parts and computer model code. The method was applied to three dzfferent complex system modelling eflorts. The results demonstrate that it reduces modelling costs, improves model quality and enables the integration of knowledge in multidisciplinary teams, the models they produce and the actual written computer code.
Garbage collection-aware utility accrual scheduling
Authors: Shahrooz Feizabadi, Godmar Back
Venue: Real-Time Systems (2007)

The convenience and robustness of automatic memory management have long been exploited by modern systems that use type-safe programming languages such as Java. The timeliness requirements of real-time systems, however, impose specific demands on the operational parameters of the garbage collector. The memory requirements of real-time tasks must be accommodated with a predictable impact on the time-line and under the purview of the scheduler. Utility Accrual is a method of dynamic overload scheduling that is designed to respond to overload conditions by producing a schedule that heuristically maximizes a pre-defined metric of utility. Traditionally, UA schedulers have focused primarily on CPU overload. We explore memory overload conditions in which the memory demands exceed the system's available memory bandwidth. This paper presents a utility accrual algorithm for uniprocessor CPU and garbage collection scheduling that addresses such memory overload conditions. By tightly linking CPU and memory allocation, the scheduler can appropriately respond to overload along both dimensions. This scheduler is the first of its kind to enable the use of automatic memory management in a utility accrual system. Experimental results based on actual Java application profiles indicate the benefits of our model when compared to memory-unaware scheduling.
Impact of different link cost metrics on the performance of routing algorithms for traffic-engineered MPLS networks
Authors: A. Halimi, K. Hendling, B. Statovci-Halimi, K. Bengi
Venue: Proceedings of the The 8th International Conference on Communication Systems - Volume 01 (2002)

This paper assesses the influence of different link cost metrics on the overall performance of routing algorithms, which are suitable for realizing traffic engineering in IP networks by means of MPLS (Multiprotocol Label Switching). The performance evaluation is conducted by means of extensive network simulations for a partially meshed network and three distributed routing algorithms, while the average end-to-end delay, total network throughput, and the total packet drop probability are taken as performance measures. It is shown that the link cost metric selection affects the performance of the considered routing algorithms in terms of the typical traffic engineering goals.
An architecture for developing behavioral history
Authors: Mark Allman, Ethan Blanton, Vern Paxson
Venue: Proceedings of the Steps to Reducing Unwanted Traffic on the Internet on Steps to Reducing Unwanted Traffic on the Internet Workshop (2005)

We present an architecture for large-scale sharing of past behavioral patterns about network actors (e.g., hosts or email addresses) in an effort to inform policy decisions about how to treat future interactions. In our system, entities can submit reports of certain observed behavior (particularly attacks) to a distributed database. When deciding whether to provide services to a given actor, users can then consult the database to obtain a global history of the actor's past activity. Three key elements of our system are: (i) we do not require a hard-and-fast notion of identity, (ii) we presume that users make local decisions regarding the reputations developed by the contributors to the system as the basis of the trust to place in the information, (iii) we envision enabling witnesses to attest that certain activity was observed without requiring the witness to agree as to the behavioral meaning of the activity. We sketch an architecture for such a system that we believe the community could benefit from and collectively build.
On Embeddings of Rectangles into Optimal Squares
Authors: Shou-Hsuan S. Huang, Hongfei Liu, Rakesh M. Verma
Venue: Proceedings of the 1993 International Conference on Parallel Processing - Volume 03 (1993)

Let G = h x w be a rectangular grid and H = s x s be the optimal sqaure grid for G, i.e., the least square grid which is no less than G in size. In this paper, an embedding scheme is presented for embedding G into H such that the dilation cost is at most 6. The significance of this result is that optimal expansion is always achieved, regardless of the aspect ratio of the rectangle, while keeping the dilation constant.
Refinement preserving approximations for the design and verification of heterogeneous systems
Authors: Roberto Passerone, Jerry R. Burch, Alberto L. Sangiovanni-Vincentelli
Venue: Formal Methods in System Design (2007)

Embedded systems are electronic devices that function in the context of a real environment, by sensing and reacting to a set of stimuli. Because of their close interaction with the environment, and to simplify their design, different parts of an embedded system are best described using different notations and different techniques. In this case, we say that the system is heterogeneous. We informally refer to the notation and the rules that are used to specify and verify the elements of heterogeneous systems and their collective behavior as a model of computation. In this paper, we consider different classes of relationships between models of computation and discuss their preservation properties with respect to the model's refinement relation and composition operator. In particular, we focus on abstraction and refinement relationships in the form of abstract interpretations and introduce the notion of conservative approximation. We show that, unlike abstract interpretations, conservative approximations preserve refinement verification results from an abstract to a concrete model while avoiding false positives. We also characterize the relationship between abstract interpretations and conservative approximations, and derive necessary and sufficient conditions to obtain a conservative approximation from a pair of abstract interpretations. In addition, we use the inverse of a conservative approximation to identify components that can be used indifferently in several models, thus enabling reuse across models of computation. The concepts described in this paper are illustrated with examples from continuous time and discrete time models of computation.
Portfolio assessment in aerodynamics [engineering education]
Authors: N. J. Mourtos
Venue: Proceedings of the Frontiers in Education Conference,1997. on 27th Annual Conference. Teaching and Learning in an Era of Change. - Volume 01 (1997)

This paper discusses a new way of assessing student learning in an "aerodynamics" course through the use of portfolios. The approach is general enough so that it can be used in any engineering course, perhaps with a few modifications depending on content. The main idea is allowing the students more responsibility for their own learning. Instead of having all the students in the class perform identical activities (homework, experiments, tests, etc.), a cadre of assignments is made available to them and they may choose and perform (within reason) the ones that suit them better in terms of their own strengths and learning styles. The ultimate goal is for each student to demonstrate a minimum level of competence in all basic skills (analytical, computational, experimental, design, and communication) while pursuing excellence in at least one of them. The paper describes the various assignments and options the students have for achieving their learning objectives. It also discusses my observations on the effects of this approach to student learning as well as the response of the students. 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
Exploiting Platform Heterogeneity for Power Efficient Data Centers
Authors: Ripal Nathuji, Canturk Isci, Eugene Gorbatov
Venue: Proceedings of the Fourth International Conference on Autonomic Computing (2007)

It has recently become clear that power management is of critical importance in modern enterprise computing environments. The traditional drive for higher performance has influenced trends towards consolidation and higher densities, artifacts enabled by virtualization and new small form factor server blades. The resulting effect has been increased power and cooling requirements in data centers which elevate ownership costs and put more pressure on rack and enclosure densities. To address these issues, in this paper, we enable power-efficient management of enterprise workloads by exploiting a fundamental characteristic of data centers: "platform heterogeneity". This heterogeneity stems from the architectural and management-capability variations of the underlying platforms. We define an intelligent workload allocation method that leverages heterogeneity characteristics and efficiently maps workloads to the best fitting platforms, significantly improving the power efficiency of the whole data center. We perform this allocation by employing a novel analytical prediction layer that accurately predicts workload power/performance across different platform architectures and power management capabilities. This prediction infrastructure relies upon platform and workload descriptors that we define as part of our work. Our allocation scheme achieves on average 20% improvements in power efficiency for representative heterogeneous data center configurations, highlighting the significant potential of heterogeneity-aware management.
Selecting Requirements Engineering Techniques Based on Project Attributes--A Case Study
Authors: Li Jiang, Armin Eberlein
Venue: Proceedings of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (2007)

Selection of the most appropriate RE techniques for a software project based on the project's characteristics is a non-trivial process and a common challenge faced by software developers. In order to facilitate RE techniques selection, we propose a model for RE Technique Suitability Assessment (RETSA) based on project attributes. This model was developed based on surveys and interviews of experienced software developers and experts from industry and academia. RETSA was applied to an industrial project. This case study shows the help this model provided during the selection of RE techniques for a software project.
A perceptive evaluation of volume rendering techniques
Authors: Christian Boucheny, Georges-Pierre Bonneau, Jacques Droulez, Guillaume Thibault, Stéphane Ploix
Venue: Proceedings of the 4th symposium on Applied perception in graphics and visualization (2007)

The display of space filling data is still a challenge for the community of visualization. Direct Volume Rendering (DVR) is one of the most important techniques developed to achieve direct perception of such volumetric data. It is based on semi-transparent representations, where the data are accumulated in a depth-dependent order. However, it produces images that may be difficult to understand, and thus several techniques have been proposed so as to improve its effectiveness, using for instance lighting models or simpler representations (e.g. Maximum Intensity Projection). In this paper we present two perceptual studies that question how DVR meets its goals, in either static or dynamic context. We show that a static representation is highly ambiguous, even in simple cases, but this can be counterbalanced by use of dynamic cues, i.e. motion parallax, provided that the rendering parameters are correctly tuned.
Automatic identification of pro and con reasons in online reviews
Authors: Soo-Min Kim, Eduard Hovy
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

In this paper, we present a system that automatically extracts the pros and cons from online reviews. Although many approaches have been developed for extracting opinions from text, our focus here is on extracting the reasons of the opinions, which may themselves be in the form of either fact or opinion. Leveraging online review sites with author-generated pros and cons, we propose a system for aligning the pros and cons to their sentences in review texts. A maximum entropy model is then trained on the resulting labeled set to subsequently extract pros and cons from online review sites that do not explicitly provide them. Our experimental results show that our resulting system identifies pros and cons with 66% precision and 76% recall.
Expressing Sensor Network Interaction Patterns Using Data-Driven Macroprogramming
Authors: Animesh Pathak, Luca Mottola, Amol Bakshi, Viktor K. Prasanna, Gian Pietro Picco
Venue: Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications Workshops (2007)

Wireless Sensor Networks (WSNs) are increasingly being employed as a key building block of pervasive computing infrastructures, owing to their ability to be embedded within the real world. So far, pervasive applications for WSNs have been developed in an ad-hoc manner using node-centric programming models, focusing on the behavior of single nodes. Instead, macro-programming models provide much higher levels of abstractions, allowing developers to reason on the sensor network as a whole. In this paper, we demonstrate how a wide range of interaction patterns commonly found in pervasive, embedded applications can be expressed using ATaG, a data-driven macro-programming language. To support this, we showcase real-world applications developed in ATaG, and consider both homogeneous, sense-only scenarios, and heterogeneous settings involving actuation on the environment under control.