ppxscal/embedding_network huggingface dataset:
A Semantic Context Service for Smart Offices
Authors: A. Coronato, G. De Pietro, M. Esposito
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02 (2006)

Smart Home environments aim to integrate physical devices, human beings and computing entities in homes and buildings. They have to support characteristics coming from mobile computing, ubiquitous computing and sensor networking in order to provide intelligent, context-aware and pro-active applications. In this vision, "context" plays a central role; but, the raw context data, obtained by various data sources, are represented in heterogeneous formats and thus it's not possible to understand their meanings without a prior knowledge of the particular context information model. Therefore, data sources are not able to produce high-level context information, but provide only raw information. Such low-level information should be combined in order to generate higher-level context information. In this paper we propose a Semantic Context Service, that exploits Semantic Web technologies to support Smart Offices. In particular, this service relies on ontologies and rules to classify several typologies of entities, which can be involved in smart homes and offices, and to infer higher-level context information from low-level information coming from positioning systems and sensors in the physical environments.
Law of large numbers for increasing subsequences of random permutations
Authors: Ross G. Pinsky
Venue: Random Structures Algorithms (2006)

Let the random variable Zn,k denote the number of increasing subsequences of length k in a random permutation from Sn, the symmetric group of permutations of &lcub;1,&hellip;,n&rcub;. We show that Var(Zn,kn) = o((EZn,kn)2) as n &rarr; &infin; if and only if $k_n=o(n^{{2\over 5}})$. In particular then, the weak law of large numbers holds for Zn,kn if $k_n=o(n^{{2\over 5}})$; that is, $$\lim_{n\rightarrow\infty}{{Z_{n,k_n}}\over {EZ_{n,k_n}}}=1,\ \hbox{in probability}.$$ We also show the following approximation result for the uniform measure Un on Sn. Define the probability measure &mu;n;kn on Sn by $$\mu_{n;k_n}={{1}\over{{n\choose {k_n}}}}\sum_{x_1 < x_2 < \cdots < x_{k_n}} U_{n;x_1,x_2,\ldots,x_{k_n}},$$ where Un;x1,x2,&hellip;,xkn denotes the uniform measure on the subset of permutations that contain the increasing subsequence &lcub;x1,x2,&hellip;,xkn&rcub;. Then the weak law of large numbers holds for Zn,kn if and only if $$\lim_{n\rightarrow\infty}||\mu_{n;k_n}-U_n||=0,\eqno(^{\ast})$$ where &mid;&mid;&dot;&mid;&mid; denotes the total variation norm. In particular then, (&ast;) holds if $k_n=o(n^{{2\over 5}})$.In order to evaluate the asymptotic behavior of the second moment, we need to analyze occupation times of certain conditioned two-dimensional random walks. &copy; 2005 Wiley Periodicals, Inc. Random Struct. Alg., 2006
How to cite curated databases and how to make them citable
Authors: Peter Buneman
Venue: Proceedings of the 18th International Conference on Scientific and Statistical Database Management (2006)

Curated scientific databases such as the IUPHAR database resemble conventional publications such as reference manuals in that they represent the work of a large number of people who both create and revise their contents. The difference is that curated databases have more internal structure and that they change more for supporting citation of data: there are few standards, there is little supporting technology, and the requirements above, if they are met at all, are met in an ad hoc fashion.
Practical Needs and Wants for Silicon Debug and Diagnosis
Authors: Fidel Muradali
Venue: Proceedings of the 15th Asian Test Symposium (2006)

New and efficient solutions for silicon debug and diagnosis will have a highly visible impact on productivity. From prototype turn-on to volume production, sources of difficulty can include, circuit complexity, packaging, physical access, schedule, missing tool capability and the traditional infrastructure development for just go/no-go testing. The goal of this panel is to identify precise topics to drive academic research and industrial development. It is a unique continuation of an IEEE Test Technology Committee effort to examine Silicon Debug & Diagnosis. As an initial step, the focus of the Silicon Debug and Diagnosis Workshop 2006 will be to generate a template cross-industry & cross-academia list of topics. This will be summarized and, with ATS audience participation, built upon.
Access methods for xml query optimization
Authors: Attila Barta
Venue:  (2006)

An ever increasing number of organizations store their data using the XML data model. In this respect, the XML data model is used as encoding for information exchange, e-commerce messaging and complex data formats such as genome and protein data. These XML encoded data are stored in XML documents and a collection of XML documents is know as an XML database. In a simplified model, an XML document can be modeled as a tree. A challenge to the current database research is how to query these tree-encoded databases. The de facto XML query language is XQuery and there are many XQuery implementations ranging from simple XQuery prototypes to complex implementations that are part of database systems that provide XML support. The common denominator of these XQuery implementations is the immaturity of the XML query optimizer. The query optimization techniques proved to be the foundation of success for the object/relational database systems. We believe that without a sound query optimization technique querying large XML databases will not be feasible. In this thesis we present query optimization techniques for XML databases. These query optimization techniques are based on an original query optimization paradigm that we call two-level query optimization and in the context of this paradigm we introduce two novel optimization strategies, namely holistic path summary pruning and access-order selection. Furthermore, we propose the usage of path summaries (a concise representation of an XML instance) in the query optimizer as system catalogs. The query optimization techniques that we propose are employed at the access method selection level. An access method is a query operator that accesses a data sources. In this thesis we present three access methods: ToXStream, which works on streamed documents, TwigStackScan and ToXinScan that employ path summaries. The soundness of the optimization techniques that we propose are verified through experiments on XML query benchmarks. The experimental results suggest that, when applicable, these optimization techniques induce performance improvements up to two orders of magnitude over the state-of-the-art.
The PageRank Vector: Properties, Computation, Approximation, and Acceleration
Authors: Claude Brezinski, Michela Redivo-Zaglia
Venue: SIAM Journal on Matrix Analysis and Applications (2006)

An important problem in Web search is determining the importance of each page. After introducing the main characteristics of this problem, we will see that, from the mathematical point of view, it could be solved by computing the left principal eigenvector (the PageRank vector) of a matrix related to the structure of the Web by using the power method. We will give expressions of the PageRank vector and study the mathematical properties of the power method. Various Padé-style approximations of the PageRank vector will be given. Since the convergence of the power method is slow, it has to be accelerated. This problem will be discussed. Recently, several acceleration methods were proposed. We will give a theoretical justification for these methods. In particular, we will generalize the recently proposed Quadratic Extrapolation, and we interpret it on the basis of the method of moments of Vorobyev, and as a Krylov subspace method. Acceleration results are given for the various epsilon-algorithms, and for the E-algorithm. Other algorithms for this problem are also discussed.
Machine Learning in Value-Based Software Test Data Generation
Authors: Du Zhang
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

Software engineering research and practice thus far are primarily conducted in a value-neutral setting where each artifact in software development such as requirement, use case, test case, and defect, is treated as equally important during a software system development process. There are a number of shortcomings of such value-neutral software engineering. Value-based software engineering is to integrate value considerations into the full range of existing and emerging software engineering principles and practices. Machine learning has been playing an increasingly important role in helping develop and maintain large and complex software systems. However, machine learning applications to software engineering have been largely confined to the value-neutral software engineering setting. In this paper, we advocate a shift to applying machine learning methods to value-based software engineering. We propose a framework for value-based software test data generation. The proposed framework incorporates some general principles in value-based software testing and can help improve return on investment.
On-line optimization of FPGA power-dissipation by exploiting run-time adaption of communication primitives
Authors: K. Paulsson, M. Hübner, J. Becker
Venue: Proceedings of the 19th annual symposium on Integrated circuits and systems design (2006)

The flexibility of reconfigurable hardware can be exploited to adapt to requirements of applications while run-time. Hardware described functions can be configured dynamically when required, which leads to better usage of chip resources due to reduction of chip area and therefore reduced power consumption. Unfortunately the many restrictions of available run-time reconfigurable hardware architectures has until now limited the integration of such systems in real applications. Also, the high power consumption of reconfigurable architectures makes them suitable for mostly very high performance requiring applications such as signal processing tasks or multimedia applications. In this paper a method for 2D reconfiguration is described, which also enables on-line routing of communication primitives. In order to decrease the power consumption, we also propose a method for adapting signal routing according to power and performance. We demonstrate that there is a trade-off between the power and performance of on-chip signal lines, which can be exploited for on-line adaptation.
Adaptive control of quantum computing systems
Authors: R. L. Kosut, H. Rabitz
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 3 (2003)

In this paper we promote the use of adaptive control for deducing the external control fields required to make a quantum computer behave as desired in an uncertain environment. Adaptive systems can be classified as indirect or direct. In an indirect adaptive control system, data is used to first. determine parameters in a system model. Then the model is used to determine the control parameters in order to achieve a desired goal.
Learning Ambiguities Using Bayesian Mixture of Experts
Authors: Atul Kanaujia, Dimitris Metaxas
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

Mixture of Experts(ME) is an ensemble of function approximators that fit the clustered data set locally rather than globally. ME provides a useful tool to learn multi-valued mappings(ambiguities) in the data set. Mixture of Experts training involve learning a multi-category classifier for the gates distribution and fitting a regressor within each of the clusters. The learning of ME is based on divide and conquer which is known to increase the error due to variance. In order to avoid overfitting several researchers have proposed using linear experts. However in the absence of any knowledge of non-linearities existing in the data set, it is not clear how many linear experts could accurately model the data. In this work we propose a bayesian learning framework for learning Mixture of Experts. Bayesian learning intrinsically embodies regularization and model selection using Occam's razor. In the past Bayesian learning methods have been applied to classification and regression in order to avoid scale sensitivity and orthodox model selection procedure of cross validation. Although true Bayesian learning is computationally intractable, approximations do result in sparser and more compact models.
My Computational Education
Authors: Charles Day
Venue: Computing in Science and Engineering (2006)

I peaked as a computational scientist in 1986. At that time, two years from finishing my PhD, I was trying to account for an aspect of the x-ray emission from a pulsar known as Hercules X-1.
Permanence and global attractivity of a delayed periodic logistic equation
Authors: Fengde Chen, Xiangdong Xie, Xiaoxing Chen
Venue: Applied Mathematics and Computation (2006)

In this paper, we consider the delayed periodic logistic equation N(t) = N(t)[a(t) - b(t)NP(t -σ(t)) - c(t)Nq(t - τ(t))], which describes the evolution of a single species. Sufficient conditions which guarantee the permanence and the globally attractivity of the system are obtained.
Bounds based on lumpable matrices for partially ordered state space
Authors: Ana Bušić, Jean-Michel Fourneau
Venue: Proceeding from the 2006 workshop on Tools for solving structured Markov chains (2006)

We consider the strong stochastic ("st") ordering on Markov chains whose states are naturally endowed with a partial order and we present an algorithmic derivation of lumpable upper bounding matrix.The comparison of Markov chains relies on the monotonicity property even if it is only sufficient. When the model is not monotone, we must build a monotone upper bound. Quite often the natural partial order of the model makes the problem monotone with this order. However, if we use a total order consistent with the partial one the model is often not monotone anymore for the total order. Furthermore, the monotonicity property for total order adds a lot of constraints which are irrelevant and make the bound less accurate.Here we assume that the model is monotone for the natural partial order and we must build a matrix which is larger in the strong stochastic sense and easier to solve. We build a lumpable bound and we store the lumped version to be analyzed.Lumpable upper bounding matrices may also be useful when they are associated to a total order. We can derive a bound of the Markov chain with a two phase algorithm: first we derive a lumpable upper bound from the specifications, we store the lumped version and we make this lumped matrix monotone in a second phase.
Design and tuning of importance-based fuzzy logic controller for a flexible-link manipulator
Authors: Linda Z. Shi, Mohamed B. Trabia
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2006)

Fuzzy logic control presents a computationally efficient and robust alternative to conventional controllers for many systems. This paper presents a distributed fuzzy logic controller (FLC) structure for a flexible-link manipulator based on evaluating the importance degrees of the output variables of the system. The two velocity variables, which have higher importance degrees, are grouped together as the inputs of the Velocity FLC. The two displacement variables, which have lower importance degrees, are used as the inputs of the Displacement FLC. The outputs of those two FLCs are summed up to control the joint of the flexible link. The fuzzy rules of the distributed importance-based FLCs are written based on the expert knowledge, and the parameters of the membership functions of the two FLCs are tuned using nonlinear programming. The distributed importance-based FLC structure is further compared with two other commonly used structures: a Linear Quadratic Regulator and a distributed PD-like FLC. The robustness of the three controllers are tested and compared under various conditions.
The Fourth Amendment and Emerging Communications Technologies
Authors: Patricia L. Bellia
Venue: IEEE Security and Privacy (2006)

The key US Supreme Court case that addresses the constitutionality of government surveillance is nearly four decades old, but Congress hasn't substantially revised surveillance statutes in nearly two decades. This overview considers how technological developments have strained the prevailing legal framework and highlights areas for reform.
A New EAAODV Routing Protocol based on Mobile Agent
Authors: ZHAO Chenchen, YANG Zhen
Venue: Proceedings of the International Conference on Systems and Networks Communication (2006)

This paper proposes a new routing scheme for mobile Ad hoc networks .. EAAODV (Energy-Aware AODV), which combines the on-demand routing capability of Ad hoc On-Demand Distance Vector routing protocol with a distributed topology discovery mechanism - mobile agents. Utilizing the interior characteristics of the mobile agent technology, EAAODV obtains the dynamic energy distribution in the network, thus reaching the balance condition. EAAODV eliminates the problem of low efficiency and link breaking in routing due to the energy exhaustion of some nodes, which exists in the traditional protocols. This paper analyzes the scheme by means of both mathematics and simulation technologies. Results show that EAAODV hybrid protocol proposed in this paper is able to achieve a longer surviving network duration and a larger throughput compared to the traditional AODV protocols.
Bio-Inspired Control Approach to Multiple Spacecraft Formation Flying
Authors: Liguo Weng, Wenchan Cai, Ran Zhang, Y. D. Song
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

This work addresses the problem of formation control for multiple spacecraft in a Planetary Orbital Environment (POE). Due to the diverse interferences and uncertainties in outer space, traditional control methods encounter great difficulties in this area. A new control approach inspired by human memory system is proposed, which is shown to be capable of learning from past control experience and current behavior to improve its performance and demands much less system dynamic information as compared with traditional controls. Both theoretical analysis and computer simulation verify its effectiveness.
An array of Au nanoparticles on the nanopatterned Si(100)
Authors: Sung Koo Kang, Younghun Kim, Inhee Choi, Jinwon Lee, Jongheop Yi
Venue: Microelectronic Engineering (2005)

1-D arrays of Au nanoparticles (AuNPs) were fabricated on a silicon wafer. The silicon oxide patterns were prepared on the OTS-derivatized Si(110) by AFM anodic oxidation. After modifying the patterned area with APTES (aminopropyltriethoxylsilane) and MPTMS ((3-mercaptopropyl)trimethoxysilane) via a selective self-assembly technique, colloidal AuNPs were immobilized on the patterned regions of the silicon substrate. This assembled substrate was immersed in a growth solution for additional growth of the AuNPs. As a result, continuously linked 1-D arrays of nanoparticles are formed without any significant increase in line width.
How Elementary School Students Contribute to Different Computer Mediated Collaborative Tasks
Authors: Chiung-Hui Chiu, Hsiao-Yun Yang
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

This paper reports a study which investigated how elementary school students contributed differently to accomplish computer mediated collaborative tasks with different difficulty levels. One hundred and forty-five sixth grade students participated in this study. Three experimental activities were arranged. Each activity required the students in three-member groups to perform a collaborative task. The first activity required a hard task, the second one required an easy task, and the third one required a medium task. A collaborative learning system was adopted to support the activities. Students' textual discussions showed that students in accomplishing the easy collaborative task exhibited less desirable interaction with their partners.
The FRACTAL component model and its support in Java: Experiences with Auto-adaptive and Reconfigurable Systems
Authors: Eric Bruneton, Thierry Coupaye, Matthieu Leclercq, Vivien Quéma, Jean-Bernard Stefani
Venue: Software&mdash;Practice Experience (2006)

This paper presents F RACTAL, a hierarchical and reflective component model with sharing. Components in this model can be endowed with arbitrary reflective capabilities, from plain black-box objects to components that allow a fine-grained manipulation of their internal structure. The paper describes J ULIA, a Java implementation of the model, a small but efficient runtime framework, which relies on a combination of interceptors and mixins for the programming of reflective features of components. The paper presents a qualitative and quantitative evaluation of this implementation, showing that component-based programming in F RACTAL can be made very efficient. Copyright &copy; 2006 John Wiley & Sons, Ltd.
A Coevolution Approach for Database Schemas and Related Ontologies
Authors: Andreas Kupfer, Silke Eckstein, Karl Neumann, Brigitte Mathiak
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

Ontologies are one of the key technologies for data integration and meta-databases, by connecting databases on a semantical level. Still, everything fails when one of the database schemas changes: specific parts of the ontology have to be reconstructed by hand. We propose an approach that allows the database schema and the ontology to change and evolve, without ever losing their connection to each other. We call that "coevolution". Coevolution cannot be completely automated, as data definition languages do not define the change of semantical concepts, but only technical schema changes. In this paper we present our mapping of database schemas to ontologies, describe how these ontologies can be enriched by semantical information and show our approach to transfer schema changes to the ontology
Smoothly adjustable denoising using a priori knowledge
Authors: Patrick Celka, Elly Gysels
Venue: Signal Processing (2006)

Assuming a signal is composed of information and noise, this paper presents a generic approach to denoising by mapping the noisy signal using a priori information about the signal to be retrieved. The method is based on a subspace decomposition of both the a priori information at disposal and the noisy signal, followed by shrinkage of both subspace coefficients and smooth mapping of first onto the second space. Our method propose 3 different ways of building the a priori knowledge: A model-base, averaging-based and recursive-based. The proposed method is particularly suited for low signal to noise ratio. The denoising methods are validated on synthetic electrocardiogram (ECG) signals and further assessed on real life ECG and visual brain evoked potentials using the wavelet transform.