ppxscal/embedding_network huggingface dataset:
Semantic feedback for interactive image retrieval
Authors: Changbo Yang, Ming Dong, Farshad Fotouhi
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

In this paper we present a semantic image retrieval system with integrated feedback mechanism. In our system, we propose a novel feedback solution for semantic retrieval: semantic feedback, which allows our system to interact with users directly at the semantic level. The learning process of the semantic feedback substantially improves the image retrieval performance of the proposed system. We demonstrate the effectiveness of our approach with experiments using 5,000 images from Corel database.
On Reducing Classifier Granularity in Mining Concept-Drifting Data Streams
Authors: Peng Wang, Haixun Wang, Xiaochen Wu, Wei Wang, Baile Shi
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

Many applications use classification models on streaming data to detect actionable alerts. Due to concept drifts in the underlying data, how to maintain a model's up-to-dateness has become one of the most challenging tasks in mining data streams. State of the art approaches, including both the incrementally updated classifiers and the ensemble classifiers, have proved that model update is a very costly process. In this paper, we introduce the concept of model granularity. We show that reducing model granularity will reduce model update cost. Indeed, models of fine granularity enable us to efficiently pinpoint local components in the model that are affected by the concept drift. It also enables us to derive new components that can easily integrate with the model to reflect the current data distribution, thus avoiding expensive updates on a global scale. Experiments on real and synthetic data show that our approach is able to maintain good prediction accuracy at a fraction of model updating cost of state of the art approaches.
Network sensitivity to intradomain routing changes
Authors: Renata Teixeira
Venue:  (2005)

The Internet's routing architecture was designed to have a clean separation between the intradomain and interdomain routing protocols. However, the appropriate &ldquo;division of labor&rdquo; between these two tiers becomes unclear when an Autonomous System (AS) has interdomain routes to a destination through multiple border routers&mdash;a situation that is extremely common today because neighboring domains often connect in several locations. Unfortunately, this evolution in Internet structure has made it increasingly susceptible to unforeseen interactions between the two routing protocols. We believe that the current mechanism of early-exit or hot potato routing&mdash;where each router in an AS directs traffic to the &ldquo;closest&rdquo; border router based on the intradomain distances&mdash;is convoluted, restrictive, and sometimes quite disruptive. This thesis improves the robustness of IP networks by revisiting the interaction between intradomain and interdomain routing protocols. First, it analyzes the influence of intradomain routing changes on BGP routing (the interdomain routing in the Internet today). We found that some intradomain routing changes trigger a significant number of BGP updates. In fact, these BGP routing changes are responsible for the largest traffic variations. Applications such as voice over IP, streaming, and gaming are particularly sensitive to these instabilities. As a result, the development of guidelines and tools for the design and configuration of networks that minimize the impact on BGP are important tasks for achieving network robustness. We address these challenges using an analytic model of routing interaction that incorporates metrics to evaluate network sensitivity to intradomain changes. Our model identifies vulnerabilities in the network and can be used by network administrators to engineer more robust networks. Finally, we propose a simple change to router's BGP decision logic to implement a flexible mechanism for selecting egress points for traffic. This mechanism allows network administrators to satisfy diverse goals, such as traffic engineering and robustness to equipment failures. We present two example optimization problems that use integer-programming and multicommodity-flow techniques, respectively, to tune our mechanism to satisfy network-wide objectives. Experiments with traffic, topology, and routing data from two backbone networks demonstrate that our solution is both simple (for the routers) and expressive (for the network administrators).
Dependency Algebra: A Tool for Designing Robust Real-Time Systems
Authors: Hui Ding, Lui Sha
Venue: Proceedings of the 26th IEEE International Real-Time Systems Symposium (2005)

A robust system is one that can ensure essential services in spite of faults and failures in useful but non-essential components. Unless we can ensure that critical services can only USE but not depend on less critical components, a seemingly minor fault can propagate along complex and implicit dependency chains and bring down the system. Modern real time systems are often developed concurrently by multiple teams. A team typically only knows the dependency relations between their components and neighboring components. In addition, dependency relations will change as software components and their interactions are being modified. Therefore, how to automatically track and analyze the system wide dependency from local information is important for the development of robust real time systems. This paper presents dependency algebra - a unified theoretical framework plus a prototype toolkit for dependency management in real-time systems.
Algebraic Temporal Specifications with Extended TUS. Hierarchical Granular Terms and Their Applications
Authors: Maroua Bouzid, A. Ligeza
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

Specification and efficient handling of temporal knowledge is an important issue in design and implementation of contemporary information systems, such as databases, knowledge-based systems or decision support systems. This paper re-explores TUS, the Time Unit System being an algebraic tool for constructing simple yet powerful temporal specifications. In particular, an extended version of TUS, to be called XTUS is introduced and its basic operations and properties are shown.
Guest Editors' Introduction: Research in the Digital Government Realm
Authors: Judy Cushing, Theresa Pardo
Venue: Computer (2005)

As they focus on the challenges that those who implement digital government face, computer science researchers practice nearly the entire spectrum of their discipline, working in collaboration with scientists from other disciplines in pursuit of answers to questions about information management, policy, and technology in government.Sidebar, p. 27. An IT View of Emergency ManagementJosé H. Canós, Technical University of Valencia, SpainMarcos R.S. Borges, Federal University of Rio de Janeiro, Brazil Gustavo Alonso, Swiss Federal Institute of Technology Zurich (ETHZ), SwitzerlandAn emergency plan provides guidelines that government agencies can use for making management decisions promptly and efficiently when a critical emergency occurs.Sidebar, p. 28.Public Safety and Cross-Boundary Data Sharing: Lessons from the CapWin ProjectChristine B. Williams, Janis L. Gogan, and Jane Fedorowicz, Bentley CollegeThe CapWIN project represents one of the first integrated multistate transportation and public safety wireless networks in the US, enabling data interoperability for first responders wherever they are.Sidebar, p. 29.In the Real World of Digital Government: Successes and Challenges of E-RulemakingNeil Eisner, US Department of TransportationThe government currently uses electronic technology in all aspects of the e-rulemaking process, and it is working to develop additional methods that will help the public provide good data to use in making governmental decisions. Sidebar, p. 30.Research Issues in Healthcare InformaticsSylvia J. Spengler, US National Science FoundationAddressing both citizen needs and professional interests, which will be critical to gaining acceptance of a multifaceted approach to healthcare informatics, requires the kind of multifaceted approach that has been a hallmark of the NSF digital government program.
Text Classification with Evolving Label-Sets
Authors: Shantanu Godbole, Ganesh Ramakrishnan, Sunita Sarawagi
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

We introduce the evolving label-set problem encountered in building real-world text classification systems. This problem arises when a text classification system trained on a label-set encounters documents of unseen classes at deployment time. We design a Class-Detector module that monitors unlabeled data, detects new classes, and suggests them to the administrator for inclusion in the label-set. We propose abstractions that group together tokens under human understandable concepts and provide a mechanism of assigning importance to unseen terms. We present generative algorithms leveraging the notion of support of documents in a model for (1) selecting documents of proposed new classes, and (2) automatically triggering detection of new classes. Experiments on three real world taxonomies show that our methods select new class documents with high precision, and trigger emergence of new classes with low false-positive and false-negative rates.
Automated modeling and nonlinear axis scaling
Authors: Leejay Wu
Venue:  (2005)

This thesis examines nonlinear axis scaling and its impact on the modeling of inter-attribute relationships. Through automated methods, the described system identifies possible scaling methods; decides which attributes serve as inputs or outputs; and builds regression trees that quantify these relationships. While the experiments focus on the accuracy and complexity of these models, both of which one can attempt to quantitatively examine, the results also consider applicability towards the inherently more qualitative task of rule-based outlier or anomaly detection. The results demonstrate that the use of nonlinear axis scaling, even in an automated system, can provide significantly more accurate models compared to the unscaled case without proportionally higher complexity costs; and also can help reveal unusual tuples in which what is unusual is not any individual value, but the combination thereof.
Testing Embedded Sequential Cores in Parallel Using Spectrum-Based BIST
Authors: Xiaoding Chen, Michael S. Hsiao
Venue: IEEE Transactions on Computers (2006)

We present a new BIST (built-in-self-test) architecture for system-on-a-chip (SOC), which can test a cluster of embedded sequential cores simultaneously. The compressed spectrum for a cluster of cores under test is computed by performing spectral analysis individually on all cores. Because there is no need to combine the cores to extract the spectrum for the entire cluster, the computation complexity is greatly reduced. For each individual core, we propose an interleaved state relaxation on the compacted test sequence for its characteristic fault set, leading to a partially specified, interleaved sequence which can be merged in a much easier way. A delay network and a switching network are added selectively to allow for more aggressive merging of spectra. Experimental results show that the same level of fault coverage can be achieved for each individual core with negligible hardware overhead, while the test application time for testing the entire cluster can be reduced by up to four times and the test data storage requirement is reduced by up to 42 percent.
Contention resolution and memory load balancing algorithms on distributed shared memory multiprocessors
Authors: Constantine Katsinis
Venue:  (2005)

It is well known that contention is one of the factors that limit the performance of high performance parallel computing systems that implement distributed shared memory (DSM). On cache-coherent DSM multiprocessors, one of the most intrusive forms of contention is the one that occurs at the network interface of a node, due to simultaneous requests for remote memory accesses. This thesis focuses on the issue of resolving remote memory access contention on hardware DSM systems, and on the performance impact of implementing contention resolution algorithms. The Simultaneous Optical Multiprocessor Exchange Bus (SOME-Bus) is a low-latency, high-bandwidth, fiber-optic interconnection network supporting DSM with a unique feature that every processor is connected to the other processor through a dedicated output channel. The thesis presents simple but effective contention resolution algorithms that rely on the information of average channel utilization, average channel waiting time, number of messages in the channel queue or short-term average channel waiting time reported by each node, and uses simulation to examine the performance of the algorithms on the SOME-Bus multiprocessor. The algorithms detect potential hot spots and resolve contention using dynamic block migration, which is a novel approach for migrating home nodes on a block-level basis and balancing remote memory accesses across the nodes of the system. The algorithms require minimal support from the operating system and all the necessary message transactions happen on the hardware level. Experiments with eight parallel codes on a 64-processor SOME-Bus show that algorithms yield significant performance improvements such as reduction in the execution times, number of remote memory accesses, average channel waiting times and average network latencies. Modified contention resolution algorithms are developed with the addition of data-acknowledge message multicasting. Application of the modified algorithms yields more performance improvements in some codes. Architectural enhancements to the network interface and directory of the SOME-Bus multiprocessor to support the contention resolution algorithms are also presented.
Proto-value functions: developmental reinforcement learning
Authors: Sridhar Mahadevan
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

This paper presents a novel framework called proto-reinforcement learning (PRL), based on a mathematical model of a proto-value function: these are task-independent basis functions that form the building blocks of all value functions on a given state space manifold. Proto-value functions are learned not from rewards, but instead from analyzing the topology of the state space. Formally, proto-value functions are Fourier eigenfunctions of the Laplace-Beltrami diffusion operator on the state space manifold. Proto-value functions facilitate structural decomposition of large state spaces, and form geodesically smooth orthonormal basis functions for approximating any value function. The theoretical basis for proto-value functions combines insights from spectral graph theory, harmonic analysis, and Riemannian manifolds. Proto-value functions enable a novel generation of algorithms called representation policy iteration, unifying the learning of representation and behavior.
Towards Continuous Usage Control on Grid Computational Services
Authors: Fabio Martinelli, Paolo Mori, Anna Vaccarelli
Venue: Proceedings of the Joint International Conference on Autonomic and Autonomous Systems and International Conference on Networking and Services (2005)

Security in the grid environment is a challenging issue, because this environment instantiates interactions among a set of possibly unknown entities where no trust relationships may exist a priori, or when such relationships are not strong enough for specific applications. In this paper we propose to integrate a local monitor into the grid computational service architecture, to control the behavior of applications executed on behalf of grid users. Our approach is inspired to the concept of continuous usage control rather then simply access control to monitor the security relevant interactions of these applications with the requested services. We also describe the prototype of computational service monitor we have developed and its integration within the Globus framework.
OGSI.NET: OGSI-compliance on the .NET framework
Authors: G. Wasson, N. Beekwilder, M. Morgan, M. Humphrey
Venue: Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid (2004)

The Open Grid Service Infrastructure (OGSI) has been designed to facilitate the creation of multiple, interoperable Grid service hosting environments, but to date only one fully OGSI-compliant hosting environment exists, Globus Toolkit version 3 (GT3). This paper describes the design and implementation of OGSI.NET, which is the second, independent hosting environment that is fully compliant with the OGSI specification. While the Microsoft suite of Visual Studio, Internet Information Services (IIS), and the Web Services Enhancements (WSE) provide a robust foundation upon which we implemented OGSI.NET, the challenges included constructing the Grid service container, parsing OGSI WSDL ("gwsdl"), and supporting Grid service handles (GSH). By describing our approach to these challenges, and by describing the unique Grid attribute programming. model we are developing as part of OGSI.NET, we contribute an early evaluation of OGSI and the broader Open Grid Services Architecture (OGSA).
Color in information display principles, perception, and models
Authors: Maureen C. Stone
Venue: ACM SIGGRAPH 2004 Course Notes (2004)

Color is a key component of information display that is easy to use badly. As a result, Edward Tufte's key principle for color design is "do no harm." While inspired color design is an art, the principles that underlie good color design have their roots in human perception and a deep understanding of the color properties of different media. Over the last decade, there has been significant progress towards providing computational models for color perception. Similarly, there has been substantial research and engineering work that has made it easier to predict and control color in digital media. Taken together, these provide a foundation that should enable the algorithmic application of color that is robust and effective, if still not "inspired."This course will survey the topics that support such a goal, and will provide pointers for further in-depth exploration. Topics include: Principles for the use of color in information display; principles of color design and color harmony, ways to numerically define and transform color, including visual, perceptual, aesthetic, and media-specific "color spaces;" color management systems and their application; color appearance fundamentals. The course will include an overview of some relevant research, including: automatic generation of color scales, algorithms for mapping names to colors, models for color blindness, and computational models for color appearance.
Data Dissemination based on Mobile Agent in Wireless Sensor Networks
Authors: Min Chen, Taekyoung Kwon, Yanghee Choi
Venue: Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary (2005)

Recently, mobile agents have been proposed for efficient data dissemination in sensor networks [1-6]. In the traditional client/server-based computing architecture, data at multiple sources is transferred to a destination; whereas, a task-specific executable code traverses the relevant sources to gather data in the mobile-agent based computing paradigm. As described in [1], many inherent advantages (e.g. scalability, extensibility, energy awareness, reliability) of the mobile agent architecture make it more suitable for sensor networks than the client/server architecture. In this paper, a mobile agent is exploited in three levels (e.g. node level, task level, and combined task level) to reduce the information redundancy and communication
Fuzzy Modeling Based on Ordinary Fuzzy Partitions and Nearest Neighbor Clustering
Authors: George E. Tsekouras
Venue: Journal of Intelligent and Robotic Systems (2005)

In this paper a novel algorithm is proposed to train fuzzy models. The novelty of the contribution lies on the development of a nearest neighbor-clustering scheme, which is able to perform the structure identification and the model parameter estimation without taking into account any random initial guesses. This nearest neighbor-clustering search is based on defining ordinary fuzzy partitions in the input space, and produces a number of spherical-shaped fuzzy clusters. The number of these clusters provides the number of rules of the fuzzy model. The premise model parameters are obtained by projecting the spherical clusters on each axe. Relationally, the consequent model parameters are determined by applying the orthogonal least-squares algorithm. Finally, the above model parameters are fine tuned by using the gradient descent method. The whole scheme requires one-pass through the data set and therefore it is a fast procedure that is easy to implement. Simulation experiments verify the algorithm's efficiency with respect to its prediction performance, its initialization capabilities, and its speed.
Entropic Discretization of a Quantum Drift-Diffusion Model
Authors: Samy Gallego, Florian Méhats
Venue: SIAM Journal on Numerical Analysis (2005)

This paper is devoted to the discretization and numerical simulation of a new quantum drift-diffusion model that was recently derived. In a first step, we introduce an implicit semi-discretization in time which possesses some interesting properties: this system is well-posed, it preserves the positivity of the density, the total charge is conserved, and it is entropic (a free energy is dissipated). Then, after a discretization of the space variable, we define a numerical scheme which has the same properties and is equivalent to a convex minimization problem. These results are illustrated by some numerical simulations.
Preemptible Atomic Regions for Real-Time Java
Authors: Jeremy Manson, Jason Baker, Antonio Cunei, Suresh Jagannathan, Marek Prochazka, Bin Xin, Jan Vitek
Venue: Proceedings of the 26th IEEE International Real-Time Systems Symposium (2005)

We present a new concurrency control abstraction for real-time systems called preemptible atomic regions (PARs). PARs a transactional mechanism that improves upon lock-based mutual exclusion in several ways. First, and foremost, PARs provide strong correctness guarantees. Any sequence of operations declared atomic will not suffer interference from other threads, even in the presence of programmer errors. In spite of this, PARs can be preempted by high priority tasks; this is essential to the minimization of blocking times. We have implemented PARs in a uniprocessor real-time Java virtual machine and evaluated their utility on a number of programs. The results suggest that programs that use PARs, depending on their semantics, can run faster and experience less jitter than those that use locks.
Generating Diverse Compound Critiques
Authors: Kevin Mccarthy, James Reilly, Barry Smyth, Lorraine Mcginty
Venue: Artificial Intelligence Review (2005)

Critiquing is a powerful form of feedback often used by conversational recommender systems. There are two main types of critiquing; unit and compound. Unit critiques allow the user to provide limited feedback at the feature-level by constraining a single feature's value space. Compound critiques, on the other hand, allow the user to manipulate multiple features simultaneously and therefore can help the user to locate the product they are looking for more efficiently. However, the usefulness of the compound critiquing approach is compromised when all the options that are presented to the user are very similar to each-other. In this paper we propose the idea of presenting diverse compound critiques, and evaluate the effectiveness of two alternative approaches in terms of their recommendation performance. Specifically, we look at the degree to which critique diversity can be improved, the effect this may have on user interaction, and its expected impact on recommendation efficiency and quality