ppxscal/embedding_network huggingface dataset:
Transfer of learning in virtual environments: a new challenge?
Authors: Cyril Bossard, Gilles Kermarrec, C&#x00e9;dric Buche, Jacques Tisseau
Venue: Virtual Reality (2008)

The aim of all education is to apply what we learn in different contexts and to recognise and extend this learning to new situations. Virtual learning environments can be used to build skills. Recent research in cognitive psychology and education has shown that acquisitions are linked to the initial context. This provides a challenge for virtual reality in education or training. A brief overview of transfer issues highlights five main ideas: (1) the type of transfer enables the virtual environment (VE) to be classified according to what is learned; (2) the transfer process can create conditions within the VE to facilitate transfer of learning; (3) specific features of VR must match and comply with transfer of learning; (4) transfer can be used to assess a VE&#x2019;s effectiveness; and (5) future research on transfer of learning must examine the singular context of learning. This paper discusses how new perspectives in cognitive psychology influence and promote transfer of learning through the use of VEs.
Static polarizability of molecular materials: Environmental and vibrational contributions
Authors: Francesca Terenziani, Anna Painelli, Zoltan G. Soos
Venue: Journal of Computational Methods in Sciences and Engineering (2004)

Modeling the dielectric behavior of molecular materials made up of large &pi;-conjugated molecules is an interesting and complex task. Here we address linear polarizabilities, and the related dielectric constant, of molecular crystals and aggregates made up of closed-shell &pi;-conjugated molecules with either a non-polar or largely polar ground-state, and also examine the behavior of mixed-valence (or charge-transfer) organic salts. We recognize important collective phenomena due to supramolecular interactions in materials with large molecular polarizabilities, and underline large vibrational contributions to the polarizability in materials with largely delocalized electrons.
Knowledge Cartography: Software Tools and Mapping Techniques, 1 edition
Authors: Alexandra Okada, Simon J. Buckingham Shum, Tony Sherborne
Venue: Advanced Information And Knowledge Processing (2008)

Knowledge Cartography is the discipline of mapping intellectual landscapes. The focus of this book is on the process by which manually crafting interactive, hypertextual maps clarifies ones own understanding, as well as communicating it. The authors see mapping software as a set of visual tools for reading and writing in a networked age. In an information ocean, the primary challenge is to find meaningful patterns around which we can weave plausible narratives. Maps of concepts, discussions and arguments make the connections between ideas tangible and disputable. With 17 chapters from the leading researchers and practitioners, the reader will find the current stateof-the-art in the field. Part 1 focuses on educational applications in schools and universities, before Part 2 turns to applications in professional communities, but with many cross-cutting themes: conceptual frameworks for understanding knowledge cartography visual languages, many of which work on both paper and with software specialist software, much of it freely available and open source case studies reflecting on successes and failures ways in which maps can be used both effectively and ineffectively examples of how to evaluate maps visit the website for updates on the field, and extra resources for each chapter: www.kmi.open.ac.uk/books/knowledge-cartography Knowledge Cartography will be of interest to learners, educators, and researchers in all disciplines, as well as policy analysts, scenario planners, knowledge managers and team facilitators. Practitioners will find new perspectives and tools to expand their repertoire, while researchers will find rich enough conceptual grounding for further scholarship.
A View from the Engine Room: Computational Support for Symbolic Model Checking
Authors: Randal E. Bryant
Venue: 25 Years of Model Checking: History, Achievements, Perspectives (2008)

Symbolic model checking owes much of its success to powerful methods for reasoning about Boolean functions. The first symbolic model checkers used Ordered Binary Decision Diagrams (OBDDs) [1] to represent system transition relations and sets of system states [9]. All of the steps required for checking a model can be expressed as a series of operations on these representations, without ever enumerating individual states or transitions. More recently, bounded [3] and unbounded [10,11] model checkers have been devised that use Boolean satisfiability (SAT) solvers as their core computational engines. Methods having a SAT solver work on a detailed system model and OBDDs operate on an abstracted model have shown that the combination of these two reasoning techniques can be more powerful than either operating on its own [4]. Boolean methods have enabled model checkers to scale to handle some of the complex verification problems arising from real-world hardware and software designs.Given the importance of Boolean reasoning in symbolic checking, we take this opportunity to examine the capabilities of SAT solvers and BDD packages.We use several simple experimental evaluations to illustrate some strengths and weaknesses of current approaches, and suggest directions for future research.
Adaptive Sparse Grid Classification Using Grid Environments
Authors: Dirk Pflüger, Ioan Lucian Muntean, Hans-Joachim Bungartz
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

Common techniques tackling the task of classification in data mining employ ansatz functions associated to training data points to fit the data as well as possible. Instead, the feature space can be discretized and ansatz functions centered on grid points can be used. This allows for classification algorithms scaling only linearly in the number of training data points, enabling to learn from data sets with millions of data points. As the curse of dimensionality prohibits the use of standard grids, sparse grids have to be used.Adaptive sparse grids allow to get a trade-off between both worlds by refining in rough regions of the target function rather than in smooth ones. We present new results for some typical classification tasks and show first observations of dimension adaptivity. As the study of the critical parameters during development involves many computations for different parameter values, we used a grid environment which we present.
IT Direction in Thailand: Cultivating an E-Society
Authors: Pattarasinee Bhattarakosol
Venue: IT Professional (2003)

Thailand's new, long-term plans aim to bring technologies to the peopleand to nurture a generation to produce IT for the world market.
Limitations of Hardness vs. Randomness under Uniform Reductions
Authors: Dan Gutfreund, Salil Vadhan
Venue: Proceedings of the 11th international workshop, APPROX 2008, and 12th international workshop, RANDOM 2008 on Approximation, Randomization and Combinatorial Optimization: Algorithms and Techniques (2008)

We consider (uniform) reductions from computing a function f to the task of distinguishing the output of some pseudorandom generator G from uniform. Impagliazzo and Wigderson [10] and Trevisan and Vadhan [24] exhibited such reductions for every function f in PSPACE. Moreover, their reductions are "black box," showing how to use any distinguisher T, given as oracle, in order to compute f (regardless of the complexity of T). The reductions are also adaptive, but with the restriction that queries of the same length do not occur in different levels of adaptivity. Impagliazzo and Wigderson [10] also exhibited such reductions for every function f in EXP, but those reductions are not black-box, because they only work when the oracle T is computable by small circuits.Our main results are that: Nonadaptive black-box reductions as above can only exist for functions f in BPPNP (and thus are unlikely to exist for all of PSPACE). Adaptive black-box reductions, with the same restriction on the adaptivity as above, can only exist for functions f in PSPACE (and thus are unlikely to exist for all of EXP). Beyond shedding light on proof techniques in the area of hardness vs. randomness, our results (together with [10,24]) can be viewed in a more general context as identifying techniques that overcome limitations of black-box reductions, which may be useful elsewhere in complexity theory (and the foundations of cryptography).
Virtual Memory and the MC68010
Authors: Douglas MacGregor, David Mothersole
Venue: IEEE Micro (1983)

The designers of this microprocessor used the continuation method to provide an elegant general solution to the problem of virtual memory support.
Single global lock semantics in a weakly atomic STM
Authors: Vijay Menon, Steven Balensiefer, Tatiana Shpeisman, Ali-Reza Adl-Tabatabai, Richard L. Hudson, Bratin Saha, Adam Welc
Venue: ACM SIGPLAN Notices (2008)

As memory transactions have been proposed as a language-level replacement for locks, there is growing need for well-defined semantics. In contrast to database transactions, transaction memory (TM) semantics are complicated by the fact that programs may access the same memory locations both inside and outside transactions. Strongly atomic semantics, where non-transactional accesses are treated as implicit single-operation transactions, remain difficult to provide without specialized hardware support and/or significant performance overhead. As an alternative, many in the community have informally proposed that a single global lock semantics [16, 9], where transaction semantics are mapped to those of regions protected by a single global lock, provide an intuitive and efficiently implementable model for programmers. In this paper, we explore the implementation and performance implications of single global lock semantics in a weakly atomic STM from the perspective of Java, and we discuss why even recent STM implementations fall short of these semantics. We describe a new weakly atomic Java STM implementation that provides single global lock semantics while permitting concurrent execution, but we show that this comes at a significant performance cost. We also propose and implement various alternative semantics that loosen single lock requirements while still providing strong guarantees. We compare our new implementations to previous ones, including a strongly atomic STM. [22]
Behavioural Theory at Work: Program Transformations in a Service-Centred Calculus
Authors: Luís Cruz-Filipe, Ivan Lanese, Francisco Martins, António Ravara, Vasco T. Vasconcelos
Venue: Proceedings of the 10th IFIP WG 6.1 international conference on Formal Methods for Open Object-Based Distributed Systems (2008)

We analyse the relationship between object-oriented modelling and session-based, service-oriented modelling, starting from a typical UML Sequence Diagram and providing a program transformation into a service-oriented model. We also provide a similar transformation from session-based specifications into request-response specifications. All transformations are specified in SSCC--a process calculus for modelling and analysing service-oriented systems--and proved correct with respect to a suitable form of behavioural equivalence (full weak bisimilarity). Since the equivalence is proved to be compositional, results remain valid in arbitrary contexts.
Bifurcations in Discrete-Time Delayed Hopfield Neural Networks of Two Neurons
Authors: Eva Kaslik, Stefan Balint
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

This paper is devoted to the bifurcation analysis of a two-dimensional discrete-time delayed Hopfield-type neural network. In the most general framework considered so far in the known literature, the stability domain of the null solution and the bifurcations occurring at its boundary are described in terms of two characteristic parameters. By applying the center manifold theorem and the normal form theory, the direction and stability of the existing bifurcations are analyzed.
Unsupervised Anomaly Detection Using HDG-Clustering Algorithm
Authors: Cheng-Fa Tsai, Chia-Chen Yen
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

As intrusion posing a serious security threat in network environments, many network intrusion detection schemes have been proposed in recent years. Most such methods employ signature-based or data-mining based techniques that rely on labeled training data, but cannot detect new types of attacks. Anomaly detection techniques can be adopted to solve this problem with purely normal data. However, extracting these data is a very costly task. Unlike the approaches that rely on labeled data or purely normal data, unsupervised anomaly detection can discover "unseen" attacks by unlabeled data. This investigation presents a new mixed clustering algorithm named HDG-Clustering for unsupervised anomaly detection. The proposed algorithm is evaluated using the 1999 KDD Cup data set. Experimental results indicate that the proposed approach outperforms several existing techniques.
Spherical Demons: Fast Surface Registration
Authors: B. T. Yeo, Mert Sabuncu, Tom Vercauteren, Nicholas Ayache, Bruce Fischl, Polina Golland
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

We present the fast Spherical Demons algorithm for registering two spherical images. By exploiting spherical vector spline interpolation theory, we show that a large class of regularizers for the modified demons objective function can be efficiently implemented on the sphere using convolution. Based on the one parameter subgroups of diffeomorphisms, the resulting registration is diffeomorphic and fast --- registration of two cortical mesh models with more than 100k nodes takes less than 5 minutes, comparable to the fastest surface registration algorithms. Moreover, the accuracy of our method compares favorably to the popular FreeSurfer registration algorithm. We validate the technique in two different settings: (1) parcellation in a set of in-vivo cortical surfaces and (2) Brodmann area localization in ex-vivo cortical surfaces.
MultiMatch --- Multilingual/Multimedia Access to Cultural Heritage
Authors: Giuseppe Amato, Juan Cigarrán, Julio Gonzalo, Carol Peters, Pasquale Savino
Venue: Proceedings of the 11th European conference on Research and Advanced Technology for Digital Libraries (2007)

Cultural heritage content is everywhere on the web, in contexts such as digital libraries, audiovisual archives, and portals of museums or galleries, in multiple languages and multiple media. MultiMatch, a 30 month specific targeted research project under the Sixth Framework Programme, plans to develop a multilingual search engine designed specifically for the access, organisation and personalised presentation of cultural heritage digital objects.
Simplicial Complexes of Networks and Their Statistical Properties
Authors: Slobodan Maletić, Milan Rajković, Danijela Vasiljević
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

Topological, algebraic and combinatorial properties of simplicial complexes which are constructed from networks (graphs) are examined from the statistical point of view. We show that basic statistical features of scale free networks are preserved by topological invariants of simplicial complexes and similarly statistical properties pertaining to topological invariants of other types of networks are preserved as well. Implications and advantages of such an approach to various research areas involving network concepts are discussed.
Study on Speaker Adaptation Methods in the Broadcast News Transcription Task
Authors: Petr Červa, Jindřich Ždánský, Jan Silovský, Jan Nouza
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

This paper deals with the use of speaker adaptation methods in the broadcast news transcription task, which is very difficult from speaker adaptation point of view. It is because in typical broadcast news, speakers change frequently and their identity is not known in the time when the given program is being transcribed. Due to this fact, it is often necessary to use some unconventional speaker adaptation methods here which can operate without the knowledge of speaker's identity and/or in an unsupervised mode too. In this paper, we compare and propose several such methods that can operate both in on-line and off-line modes in addition and we show their performance in a real broadcast news transcription system.
A Novel Description of Multifractal Phenomenon of Network Traffic Based on Generalized Cauchy Process
Authors: Ming Li, S. C. Lim, Huamin Feng
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Let D(n) and H(n) be the fractal dimension and the Hurst parameter of traffic in the nth interval, respectively. Thus, this paper gives the experimental variance analysis of D(n) and H(n) of network traffic based on the generalized Cauchy (GC) process on an interval-by-interval basis. We experimentally infer that traffic has the phenomenon Var[D(n)] > Var[H(n)]. This suggests a new way to describe the multifractal phenomenon of traffic. That is, traffic has local high-variability and global robustness. Verifications of that inequality are demonstrated with real traffic.
Measuring Architectural Vulnerability Factors
Authors: Shubhendu S. Mukherjee, Christopher T. Weaver, Joel Emer, Steven K. Reinhardt, Todd Austin
Venue: IEEE Micro (2003)

Processor designers need accurate estimates of soft-error rates early in the design cycle to make appropriate cost-reliability tradeoffs. Here, the authors present a method for estimating the architectural vulnerability factor—the probability that a fault in a particular structure will result in an error.
The Semantic Web: What, Why, How, and When
Authors: Frank van Harmelen
Venue: IEEE Distributed Systems Online (2004)

The Semantic Web aims to enrich the Web with a layer of machine-interpretable metadata so that computer programs can predictably derive new information. This goal will require the development of metadata syntax and vocabularies, and the creation of metadata for lots of Web pages.
Neural Network-Based Position Sensorless Control for Transverse Flux Linear SRM
Authors: Zhongsong Chen, Baoming Ge, Aníbal T. Almeida
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

The purpose of this paper is to present a sensorless control method for transverse flux linear switched reluctance motor (TFLSRM) based on position estimation by employing a public back propagation neural network (BPNN). The system characterizes with that only one public BPNN is needed to transform the winding current and flux linkage of each phase into each segmental position signal, then final total position is obtained by combining each segmental position signal. The starting position is derived from the comparison of the calculated position values based on currents and flux linkages of all phases. A TFLSRM with three phases is used to verify the validity of the proposed method, the established position sensorless control system with a BPNN is simulated. The results illustrate the excellent performance of the BPNN-based position sensorless control system.
Multi-agent geosimulation in support to "what if" courses of action analysis
Authors: Hedi Haddad, Bernard Moulin
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

In this paper we propose an approach to support "what-if" analysis in the context of COA evaluation. Our approach consists in using multiagent geosimulation to simulate the execution of COAs in a Virtual Geographic Environment (VGE) which can change during the simulation, and then allowing the user to explore various assumptions and to analyse their outcomes. We identify the requirements to support this approach and we present how we implement them in the MAGS-COA software. We also illustrate our approach on an example and we present future works.
Signal estimation based on covariance information from observations featuring correlated uncertainty and coming from multiple sensors
Authors: J. D. Jiménez-López, J. Linares-Pérez, S. Nakamori, R. Caballero-Águila, A. Hermoso-Carazo
Venue: Signal Processing (2008)

The linear least-squares estimation problem of signals from observations coming from multiple sensors is addressed when there is a non-zero probability that each observation does not contain the signal to be estimated (uncertain observations). At each sensor, this uncertainty in the observations is modeled by a sequence of Bernoulli random variables correlated at consecutive sampling times. To estimate the signal, recursive filtering and (fixed-point and fixed-interval) smoothing algorithms are derived without requiring the knowledge of the signal state-space model but only the means and covariance functions of the processes involved in the observation equations, the uncertainty probabilities and the correlation between the variables modeling the uncertainty. To measure the estimation accuracy, recursive expressions for the estimation error covariance matrices are also proposed. The theoretical results are illustrated by a numerical simulation example where a signal is estimated from observations featuring correlated uncertainty and coming from two sensors with different uncertainty characteristics.
A framework for semantic grouping in P2P databases
Authors: Verena Kantere, Dimitrios Tsoumakos, Timos Sellis
Venue: Information Systems (2008)

Sharing of structured data in decentralized environments is a challenging problem, especially in the absence of a global schema. Social network structures map network links to semantic relations between participants in order to assist in efficient resource discovery and information exchange. In this work, we propose a scheme that automates the process of creating schema synopses from semantic clusters of peers which own autonomous relational databases. The resulting mediated schemas can be used as global interfaces for relevant queries. Active nodes are able to initiate the group schema creation process, which produces a mediated schema representative of nodes with similar semantics. Group schemas are then propagated in the overlay and used as a single interface for relevant queries. This increases both the quality and the quantity of the retrieved answers and allows for fast discovery of interest groups by joining peers. As our experimental evaluations show, this method increases both the quality and the quantity of the retrieved answers and allows for faster discovery of semantic groups by joining peers.
Negotiation Constellations --- Method Selection Framework for Requirements Negotiation
Authors: Samuel Fricker, Paul Grünbacher
Venue: Proceedings of the 14th international conference on Requirements Engineering: Foundation for Software Quality (2008)

Customers, product managers, project leaders, architects, engineers, and other stakeholders are negotiating requirements throughout the software lifecycle. Even-though fundamental for understanding requirements engineer-ing, negotiation has not been as thoroughly studied as other facets of this engineering discipline. This paper casts requirements engineering into the landscape of negotiation by describing a framework for selecting tactics and methods for various negotiation constellations that can be encountered in a software organization. The framework opens perspectives that are essential for understanding the behavior of people involved in development projects, for understanding how development teams and stakeholders create mutually satisfactory solutions, and for giving tactical advice to practitioners.