ppxscal/embedding_network huggingface dataset:
Universal single-qubit quantum controller-observers
Authors: S. Lloyd, A. J. Landahl
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 3 (2003)

A feedback loop consists of three dynamical systems: an observer, a controller, and the system to be manipulated. Because of back-action in quantum systems, quantum controllers can act. as quantum observers and vice-versa. We demonstrate that under very general conditions, a single quantum bit can serve as both a full controller and full observer of a quantum system for a feedback loop. By similar techniques, we show that a qubit can be harnessed to serve as a quantum communication channel between two systems, and that multiple systems call be connected together to create all efficient universal quantum computer. We propose experimental realizations of our approach, and explore the implications for controllability, observability, and quantum information processing.
Feature-driven requirement dependency analysis and high-level software design
Authors: Wei Zhang, Hong Mei, Haiyan Zhao
Venue: Requirements Engineering (2006)

In this paper, we introduce four kinds of dependency between features, namely refinement, constraint, influence and interaction, partly based on the observation of feature operationalization and assignment of responsibilities. Then, we explore three kinds of connection between these dependencies, that is, connections between refinement and constraint, between constraint and interaction, and between influence and interaction. We further show how to use the constraint dependencies to facilitate the customization-based reuse of requirements, and how to employ the result of feature dependency analysis to design high-level software architecture. A simple document editor and an email-client are used as running examples to illustrate the ideas introduced in this paper.
Satin++: Divide-and-Share on the Grid
Authors: Gosia Wrzesinska, Jason Maassen, Kees Verstoep, Henri E. Bal
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

Divide-and-conquer is a popular and effective paradigm for writing grid-enabled applications. I t has been shown to perform well i n environments wtth high network latencies and dynamically changing numbers of processors. However, an important disadvantage of the divide-and-conquer paradigm is its limited applicability due to the lack of a shared data abstraction. W e propose a divide-and-share model: the divide-andconquer model extended with shared objects. Shared objects implement a relaxed consistency model called guard consistency. W e have implemented Satin++: a framework for writing divide-and-share applications. With Satin++ we implemented a number of applications including VLSI routing, N-body simulation and a S A T solver. W e evaluate the performance of our model on a cluster supercomputer and on the heterogeneous, wide-area Grid15000 testbed and demonstrate that our applications can achieve high eficiencies on the Grid.
E-commerce today and tomorrow: a truly generalized and active framework for the definition of electronic commerce
Authors: Yewsiang Poong, Khaliq-Ul Zaman, Mohammad Talha
Venue: Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet (2006)

E-commerce can be viewed from different perspectives by different people. Existing e-commerce frameworks consist of rigid and specific fundamental components of e-commerce. E-commerce field is constantly facing new challenges and new situations. To deal with these challenges, an Active E-commerce Framework is being proposed. This framework consists of six important e-commerce components each composed of several instances. The components and instances of the framework are subject to the rule of Component Flexibility (CF) and Instance Flexibility (IF) respectively. The user perspective is considered as the most important and vital component in this model. By using the user perspective component as the guiding ground, different e-commerce definitions can be constructed. This paper aims at providing an e-commerce framework that can cater for different views of e-commerce as well as assist a person in constructing e-commerce definition from his own perspective.
Wavelet Kernel Construction for Kernel Discriminant Analysis on Face Recognition
Authors: Wen-Sheng Chen, Pong Chi Yuen, Jian Huang, Jianghuang Lai
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

Kernel Discriminant Analysis (KDA) has been shown to be one of the promising approaches to handle the pose and illumination problem in face recognition. However, empirical results show that the performance for KDA on face recognition is sensitive to the kernel function and its parameters. Instead of following existing KDA methods in selecting popular kernel function, this paper proposes a new approach for constructing kernel using wavelet. By virtue of cubic B spline function, wavelet kernel function is constructed. A wavelet kernel based subspace linear discriminant (WKSLDA) algorithm is then developed for face recognition. Two human face databases, namely FERET and CMU PIE databases, are selected for evaluation. The results are encouraging. Comparing with the existing state-of-the-art RBF kernel based LDA methods, the proposed method gives superior resu
Using Generic Services for Document Life Cycle Management
Authors: Markus Aleksy, Michael Schwind
Venue: Proceedings of the 10th IEEE on International Enterprise Distributed Object Computing Conference Workshops (2006)

In order to support internal and external information demands, enterprises have to manage a multitude of heterogeneous information resources, typically in the guise of structured or unstructured documents. Enterprise content management systems (ECMS) are currently state of the art for storing and retrieving weakly structured documents. A challenge such systems are often faced with is the management of different document life cycles which can be determined by a variety of influence factors. In this paper we discuss some of these factors and propose the use of generic services to flexibly manage document life cycles in a platform independent manner, considering their inherent advantages and disadvantages.
The role of assessment infrastructures in crafting project based science classrooms
Authors: Laura D'Amico
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

Teachers in the midst of reforming their classroom environments need to make radical changes to the teaching and learning activities of themselves and their students. As teachers involved in the Learning through Collaborative Visualization (CoVis) Project [Pea, 1993] have discovered, classroom assessment is one of the most vital tools they have for shaping such changes. In general, teachers' assessment practices are key to structuring classroom activity and communicating expectations to students. In essence, assessment forms an infrastructure that both students and teachers rely upon as a mediational tool for classroom activity and communications. When teachers wish to change their pedagogical practices, they need to make concurrent changes in their classroom assessment infrastructure that will support and guide students in their new learning environment. The dissertation described here explores how classroom assessment infrastructures are used by four experienced, reform minded science teachers as a tool for crafting project based science classrooms.
An anelastic allspeed projection method for gravitationally stratified flows
Authors: Caroline Gatti-Bono, Phillip Colella
Venue: Journal of Computational Physics (2006)

This paper looks at gravitationally stratified atmospheric flows at low Mach and Froude numbers and proposes a new algorithm to solve the compressible Euler equations, in which the asymptotic limits are recovered numerically and the boundary conditions for block-structured local refinement methods are well-posed.The model is non-hydrostatic and the numerical algorithm uses a splitting to separate the fast acoustic dynamics from the slower anelastic dynamics. The acoustic waves are treated implicitly while the anelastic dynamics is treated semi-implicitly and an embedded-boundary method is used to represent orography. We present an example that verifies our asymptotic analysis and a set of results that compares very well with the classical gravity wave results presented by Durran.
Convergence of a first order scheme for a non-local Eikonal equation
Authors: O. Alvarez, E. Carlini, R. Monneau, E. Rouy
Venue: Applied Numerical Mathematics (2006)

We prove the convergence of a first order finite difference scheme approximating a non-local eikonal Hamilton-Jacobi equation. The non-local character of the problem makes the scheme not monotone in general. However, by using in a convenient manner the convergence result for monotone scheme of Crandall-Lions, we obtain the same bound √|ΔX|+Δt for the rate of convergence.
ASR: Adaptive Selective Replication for CMP Caches
Authors: Bradford M. Beckmann, Michael R. Marty, David A. Wood
Venue: Proceedings of the 39th Annual IEEE/ACM International Symposium on Microarchitecture (2006)

The large working sets of commercial and scientific workloads stress the L2 caches of Chip Multiprocessors (CMPs). Some CMPs use a shared L2 cache to maximize the on-chip cache capacity and minimize off-chip misses. Others use private L2 caches, replicating data to limit the delay due to global wires and minimize cache access time. Recent hybrid proposals use selective replication to balance latency and capacity, but their static replication rules result in performance degradation for some combinations of workloads and system configurations. This paper proposes Adaptive Selective Replication (ASR), a mechanism that dynamically monitors workload behavior to control replication. ASR replicates cache blocks only when it estimates the benefit of replication (lower L2 hit latency) exceeds the cost (more L2 misses). Full-system simulations of 8-processor CMPs show that ASR provides robust performance: improving performance by as much as 29% versus shared caches, 19% versus private caches, and 12% versus CMP-NuRapid [9] and Victim Replication [41]. Furthermore, while ASR does not improve the performance of all workloads, it provides performance stability by always performing at least comparably to the best alternative including Cooperative Caching [8].
The Watermarking Model for Relational Database Based on Watermarking Sharing
Authors: Cong Jin, Yu Fu, Feng Tao
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

In this paper we propose a conceptual framework for relational database based on secret sharing technology. We offer a technique to break the main secret into multiple parts and hide them individually in a relational database. The Lagrange Interpolating Polynomial method is used to recover the shared secret. The (k, n) threshold scheme is used to decide the minimum number of parts required to recover the secret data completely. Through deep data analysis, experimental results show how the proposed scheme can offer robust mechanism to protect data loss especially for the tuples deleting.
Properties of the Second Type of Covering-Based Rough Sets
Authors: William Zhu
Venue: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (2006)

To deal with the vagueness and granularity in information systems, researchers proposed several methods such as fuzzy theory and rough set theory. This paper studies a class of covering-based generalized rough sets. In this setting, a covering can generate a lower approximation operation and an upper approximation operation, but some of common properties of classical lower and upper approximation operations are no longer satisfied. We investigate conditions for a covering under which these properties hold for the second type of covering-based lower and upper approximation operations.
Cognitive agents based simulation for decisions regarding human team composition
Authors: Bruno Gonçalves, António Lopes, Sofia Esteves, Luís Botelho
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

This paper proposes to use cognitive multi-agent based simulation to facilitate human team formation decision processes. The models of organizational actors are acquired by a data-gathering monitoring system that stores all the interactions that take place in the selected cooperative task. In this knowledge acquisition process, only a relatively small number of team compositions are monitored. The extracted models are used in the agent-based simulation of all the possible team compositions. Simulated team compositions are evaluated and only a small set of the most promising ones is submitted to the human decision maker. An emergence model overrides the multi-agent based simulation in localized situations for which the involved set of agents should not be trusted. The model of the simulation agents is a motivated case-based reasoning system, in which the regular functioning of the CBR is biased to fulfil the agent's motives. The motivation model includes individual motivation and social influence.
A meta-mining approach to discovering regularities, differences, and changes in databases
Authors: Keith Chan
Venue:  (2006)

We propose to mine a set of rules from a collection of rule sets, each rule being discovered in a data set using a data mining algorithm. These meta-rules, rules about rules, represent the kind of knowledge that few existing data mining algorithms have been developed to mine for. In this study, we define problems in discovering the underlying regularities, differences, and changes hidden in rule sets and propose a new approach, meta-mining, which mines previous data mining results to discover these underlying regularities, differences, and changes. The purpose of meta-mining for regularities and for differences in rule sets is to discover association relationships. Meta-mining for regularities seeks to discover association relationships supported by a sufficiently large number of rules contained in just a few records in many data sets. Meta-mining for differences seeks to discover association relationships supported by a sufficiently small number of rules contained in many records in a small number of data sets. It would not be possible to distinguish between these two kinds of association relationships if the data sets were concatenated into a single data set. The associations that a large number of data sets have in common can be discovered in the form of rules. Their rule sets will contain a correspondingly large number of rules that support the associations. As these rules govern regular characteristics in the data sets, we refer to the rules for these rules as regular meta-rules. In contrast, the rules for some associations will be found in just a few data sets and their rule sets will contain a correspondingly smaller number of rules that support the associations. As these associations contribute to distinguishing or differentiating the data sets which contain them, we refer to the rules for these rules as differential meta-rules. Meta-mining can also be used to reveal changes in rule sets and this information can be used to discover change meta-rules, regularities governing how rules change over time. Change meta-rules can be used to predict how the rules will change in the future, freeing users from dependence on the historical data, allowing better planning, and making it possible to obviate or delay undesirable change. A meta-mining approach to the discovery of regular, differential, and change meta-rules should be able to (1) automatically generate fuzzy sets from data; (2) use linguistic variables and linguistic terms to represent regularities, differences, and changes; (3) exploit the scalability of parallel computer systems; (4) group and select a subset of attributes; and (5) enable the mining of association relationships involving attributes that were not originally contained in the data. (Abstract shortened by UMI.)
Characterization of a Connectivity Measure for Sparse Wireless Multi-hop Networks
Authors: Srinath Perur, Sridhar Iyer
Venue: Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems (2006)

The extent to which a wireless multi-hop network is connected is usually measured by the probability that all the nodes form a single connected component. We jind this measure, called connectivity, unsuitable for use with sparse networks since it is not indicative of the actual communication capability of the network, and can be unresponsive to changes in network parameters. An alternate connectivity measure that wejnd useful in sparse networks is the fraction of node pairs in the network that are connected. We call this term reachability and claim that it is more intuitive and expressive than connectivity when dealing with sparse networks. We identify reachability as growing according to the logistic growth model and present a regression model for reachability in terms of number of nodes and normalized transmission range. This can be used by a network designer to estimate the tradeoff between how connected the network is, the number of nodes, the area of operation, and transmission range of nodes.
Transmodal Sensorimotor Networks during Action Observation in Professional Pianists
Authors: B. Haslinger, P. Erhard, E. Altenmüller, U. Schroeder, H. Boecker, A. O. Ceballos-Baumann
Venue: Journal of Cognitive Neuroscience (2005)

Audiovisual perception and imitation are essential for musical learning and skill acquisition. We compared professional pianists to musically naive controls with fMRI while observing piano playing finger&ndash;hand movements and serial finger&ndash;thumb opposition movements both with and without synchronous piano sound. Pianists showed stronger activations within a fronto-parieto-temporal network while observing piano playing compared to controls and contrasted to perception of serial finger&ndash;thumb opposition movements. Observation of silent piano playing additionally recruited auditory areas in pianists. Perception of piano sounds coupled with serial finger&ndash;thumb opposition movements evoked increased activation within the sensorimotor network. This indicates specialization of multimodal auditory&ndash;sensorimotor systems within a fronto-parieto-temporal network by professional musical training. Musical ''language,'' which is acquired by observation and imitation, seems to be tightly coupled to this network in accord with an observation&ndash;execution system linking visual and auditory perception to motor performance.
Design at high level of a robust 8-bit microprocessor to soft errors by using only standard gates
Authors: Rodrigo Possamai Bastos, Fernanda Lima Kastensmidt, Ricardo Reis
Venue: Proceedings of the 19th annual symposium on Integrated circuits and systems design (2006)

This work presents a fault-tolerant IC version of a mass-produced 8-bit microprocessor from the M68HC11 family. It is able to tolerate Single Event Transients (SETs) and Single Event Upsets (SEUs). Based on the Triple Modular Redundancy (TMR) and Time Redundancy (TR) fault tolerance techniques, a protection scheme was designed and implemented at high level in the target microprocessor by using only standard logic gates. A typical IC design flow was developed by means of commercial CAD tools. Functional testing and fault injection simulations through benchmark executions were performed as a design verification testing. Furthermore, fault-tolerant IC design issues and results in area, performance and power were compared with a non-protected microprocessor version.
Impact of the Columbia Supercomputer on NASA Space and Exploration Missions
Authors: Rupak Biswas, Dochan Kwak, Cetin Kiris, Scott Lawrence
Venue: Proceedings of the 2nd IEEE International Conference on Space Mission Challenges for Information Technology (2006)

NASA's 10,240-processor Columbia supercomputer gained worldwide recognition in 2004 for increasing the space agency's computing capability ten-fold, and enabling U.S. scientists and engineers to perform significant, breakthrough simulations. Columbia has amply demonstrated its capability to accelerate NASA's key missions in space operations, exploration systems, science, and aeronautics. Columbia is part of an integrated high-end computing (HEC) environment comprised of massive storage and archive systems, highspeed networking, high-fidelity modeling and simulation tools, application performance optimization, and advanced data analysis and visualization. In this paper, we illustrate the impact Columbia is having on NASA's numerous space and exploration applications, such as the development of the Crew Exploration and Launch Vehicles (CEV/CLV), effects of long-duration human presence in space, and damage assessment and repair recommendations for remaining shuttle flights. We conclude by discussing HEC challenges that must be overcome to solve space-related science problems in the future.
Frequent subgraph mining in outerplanar graphs
Authors: Tamás Horváth, Jan Ramon, Stefan Wrobel
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

In recent years there has been an increased interest in algorithms that can perform frequent pattern discovery in large databases of graph structured objects. While the frequent connected subgraph mining problem for tree datasets can be solved in incremental polynomial time, it becomes intractable for arbitrary graph databases. Existing approaches have therefore resorted to various heuristic strategies and restrictions of the search space, but have not identified a practically relevant tractable graph class beyond trees. In this paper, we define the class of so called tenuous outerplanar graphs, a strict generalization of trees, develop a frequent subgraph mining algorithm for tenuous outerplanar graphs that works in incremental polynomial time, and evaluate the algorithm empirically on the NCI molecular graph dataset.
Application of Maximum Entropy-Based Image Resizing to Biomedical Imaging
Authors: Pingli Billy Kao, Brian Nutter
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

Subsampling algorithms are applied to resize digital images to a lower resolution for display and transmission applications where the pixel count of the display mechanism is lower than the pixel count of the image acquisition method. Unfortunately, interpolation-based resizing methods change the color information and attenuate a specific range of highfrequency components from which the human visual system derives significant response. The described maximum entropy algorithm (MEA) provides that, as an image goes through subsampling, locally informative pixels are retained by analyzing the pixel neighboringhoods. The selected pixels are inserted directly in the output image, and color information is therefore preserved. From subjective observation and object evaluation using the entropy, contrast, and PSNR, MEA effectively maintains important features and color information and demonstrates better resizing performance than interpolation-based methods for some applications. Furthermore, the computational expense is suitable for real-time implementation.