ppxscal/embedding_network huggingface dataset:
"Playing with" museum exhibits: designing educational games mediated by mobile technology
Authors: Nikoleta Yiannoutsou, Ioanna Papadimitriou, Vassilis Komis, Nikolaos Avouris
Venue: Proceedings of the 8th International Conference on Interaction Design and Children (2009)

In this paper, we describe two educational games mediated by mobile technology which were designed for use in the context of a traditional historical museum by young children. Our analysis focuses on the principles of the educational design, on the use of mobile technology and on the envisaged interaction between the exhibits and the children. The main argument of the paper is that mobile technology can support the play with the exhibits of a museum -instead of just viewing them in the more traditional way--and in this context the spectrum of children interaction with the exhibits can be broadened and enriched.
Detecting high-level gene function and inferring genetic pathway relationships using machine learning methods
Authors: Lenore Cowen
Venue:  (2008)

My thesis looks at two different problems related to predicting gene function. In the first project, we try to predict GO annotations for genes, using a fast SVM method that models frequency profiles of super-short subsequences (of 2-4 amino acid residues in length). We postulate that the success of our method comes from the fact that we are somehow capturing the remaining sequence signal of very remote homology. (However, since there's no order inherent in the frequency profiles we use and since the subsequences involved are extremely short, it's possible that the signatures we're detecting can't really be meaningfully considered to be "homology" at all.) Previous SVM methods for gene function prediction are either outperformed by our method, or (unlike our method) are too complex and computationally intensive to be able to be run in a high-throughput fashion on a genome-wide scale. In addition, we show that our results are significantly non-overlapping with results returned by BLAST, still the most popular single method for predicting gene function, and are of superior accuracy to those returned by PSI-BLAST. Thus we are capturing something quite different from global sequence homology.
Control network programming: static search control with system options
Authors: Kostadin Kratchanov, Tzanko Golemanov, Emilia Golemanova
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

Control Network Programming (CNP) is a programming paradigm that is especially convenient for representing problems with a natural graph-like description. This description is often of nondeterministic nature. The report continues the discussion from [1] on how a CN program is interpreted and executed. The basic algorithm of the interpreter is presented. It is followed by a discussion of the so called system options - these are powerful means for user control of the execution process.
Robust cascaded nonlinear predictive control of a permanent magnet synchronous motor
Authors: R. Errouissi, M. Ouhrouche
Venue: Proceedings of the 2009 IEEE International Conference on Industrial Technology (2009)

This paper presents a cascaded nonlinear predictive control of a permanent magnet synchronous motor (PMSM) drive. The Taylor series expansion is used to carry out the prediction defined on a finite horizon. However, it's well-known that this control strategy cannot remove completely the steady state error under mismatched parameters and load torque. Then, the full knowledge of machine parameters and operating conditions must be used to compute the control law. For that reason, a disturbance observer is designed for the estimation of the offset caused by the parameters uncertainties and external disturbance. By taking into account the offset observer in the global control system design, an equivalent cascaded proportional integration (PI) action is obtained. The performances of the proposed control strategy are analysed by simulation. The obtained results show the effectiveness of the proposed control strategy regarding trajectory tracking and
Applying an agricultural ontology to web-based applications
Authors: Michael T. Maliappis
Venue: International Journal of Metadata, Semantics and Ontologies (2009)

Despite the growing number of ontologies available online, their range of application in real-world projects is comparatively limited. This paper describes the construction of an ontology concerning the horticultural domain of agriculture, and examines its usage in particular application areas. The proposed ontology is used: as a refining and classification tool facilitating indexing and searching processes in a repository environment; as a domain model for a rule knowledge-base construction. A prototype web application has been developed to investigate the usefulness of ontology and examine several software development tools.
Mixtures of Classifiers for Recognizing Standing and Running Pedestrians
Authors: Raluca Borca-Mureşan, Sergiu Nedevschi, Florin Măguran
Venue: Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers (2008)

Recognizing pedestrians in traffic scenarios is an important task for any smart vehicle application. Within the context of a real-time stereo based driving assistance system, this paper presents a novel method for recognizing pedestrians. We have designed a meta- classification scheme composed of a mixture of Bayesian and boosted classifiers that learn the discriminant features of a pedestrian space partitioned into attitudes like pedestrian standing and pedestrian running. Our experiments show that the mixture of classifiers proposed outperforms a single classifier trained on the whole un-partitioned object space. For classification we have used a probabilistic approach based on Bayesian Networks and Adaptive Boosting. Two types of features were extracted from the image: anisotropic gaussians and histograms of gradient orientations (HOG).
Using realistic simulation for performance analysis of mapreduce setups
Authors: Guanying Wang, Ali R. Butt, Prashant Pandey, Karan Gupta
Venue: Proceedings of the 1st ACM workshop on Large-Scale system and application performance (2009)

Recently, there has been a huge growth in the amount of data processed by enterprises and the scientific computing community. Two promising trends ensure that applications will be able to deal with ever increasing data volumes: First, the emergence of cloud computing, which provides transparent access to a large number of compute, storage and networking resources; and second, the development of the MapReduce programming model, which provides a high-level abstraction for data-intensive computing. However, the design space of these systems has not been explored in detail. Specifically, the impact of various design choices and run-time parameters of a MapReduce system on application performance remains an open question. To this end, we embarked on systematically understanding the performance of MapReduce systems, but soon realized that understanding effects of parameter tweaking in a large-scale setup with many variables was impractical. Consequently, in this paper, we present the design of an accurate MapReduce simulator, MRPerf, for facilitating exploration of MapReduce design space. MRPerf captures various aspects of a MapReduce setup, and uses this information to predict expected application performance. In essence, MRPerf can serve as a design tool for MapReduce infrastructure, and as a planning tool for making MapReduce deployment far easier via reduction in the number of parameters that currently have to be hand-tuned using rules of thumb. Our validation of MRPerf using data from medium-scale production clusters shows that it is able to predict application performance accurately, and thus can be a useful tool in enabling cloud computing. Moreover, an initial application of MRPerf to our test clusters running Hadoop, revealed a performance bottleneck, fixing which resulted in up to 28.05% performance improvement.
Quantum mechanical designing of the optoelectronic yield for intersubband laser nanoheterostructures
Authors: E. A. Anagnostakis
Venue: Proceedings of the 1st WSEAS international conference on Nanotechnology (2009)

A novel LASER action nanoheterostructure of the intersubband, midinfrared functionality type is designed on the basis of optically pumped dual resonant tunnelling of conductivity electrons within an appropriately energetically determined scheme of five subbands hosted by two communicating asymmetric approximately rectangular quantum wells (QWs). The upper LASER action level employed is the second excited subband of the nanostructure back, wider QW and is being provided with electrons via resonant tunnelling from the first excited subband of the nanostructure front QW being populated through remotely ignited optical pumping out of the local fundamental subband. As the lower LASER action level, on the other hand, functions the first excited back QW subband, directly delivering the received electrons to the local fundamental subband - via a fast vertical longitudinal optical phonon scattering-, wherefrom they are being recycled back to the nanostructure front QW fundamental subband by virtue of a second - reverse sense - resonant tunnelling - mediated normal charge transport mechanism. LASER action level population inversion and intersubbad transition (ISBT) effective dipole lengths are critically monitored in connexion to the pertinent ISBT oscillator strengths and device stimulated optical gain achievable.
Identifying suspicious URLs: an application of large-scale online learning
Authors: Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

This paper explores online learning approaches for detecting malicious Web sites (those involved in criminal scams) using lexical and host-based features of the associated URLs. We show that this application is particularly appropriate for online algorithms as the size of the training data is larger than can be efficiently processed in batch and because the distribution of features that typify malicious URLs is changing continuously. Using a real-time system we developed for gathering URL features, combined with a real-time source of labeled URLs from a large Web mail provider, we demonstrate that recently-developed online algorithms can be as accurate as batch techniques, achieving classification accuracies up to 99% over a balanced data set.
Models for association rules based on clustering and correlation
Authors: Carlos Ordonez
Venue: Intelligent Data Analysis (2009)

Association rules require models to understand their relationship to statistical properties of the data set. In this work, we study mathematical relationships between association rules and two fundamental techniques: clustering and correlation. Each cluster represents an important itemset. We show the sufficient statistics for clustering and correlation on binary data sets are the linear sum of points and the quadratic sum of points, respectively. We prove itemset support can be bounded and approximated from both models. Support bounds and support estimation obey the set downward closure property for fast bottom-up search for frequent itemsets. Both models can be efficiently computed with sparse matrix computations. Experiments with real and synthetic data sets evaluate model accuracy and speed. The clustering model is accurate to estimate support, given a sufficiently large number of clusters and it is more accurate than correlation, except for sets of two items. Accuracy increases as the number of clusters grows, but decreases as the minimum support threshold decreases. Once built, the clustering model represents a faster alternative than the traditional A-priori algorithm and the correlation model to mine associations. The correlation model is faster to compute than clustering, but it is less accurate. Time complexity to compute both models is linear on data set size, whereas dimensionality marginally impacts time when analyzing large transaction data sets.
A data compression method for impulse response deformation model
Authors: Kazuyoshi Tagawa, Koichi Hirota, Michitaka Hirose
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

As an approach to real-time simulation of haptic interaction with deformable objects, we proposed a record-reproduction method called ‘impulse response deformation model’ (IRDM), in which the deformation of an object shape is computed by convolving temporal sequence of interaction force with a pre-computed response of model to impulse force. Although, IRDM has an advantage that its computation cost of interaction force is independent of model complexity, it requires a huge amount of memory to store impulse response data corresponding to the combination of all input and output degrees of freedom. This paper discusses an approach to solve this problem by compressing the impulse response data. The key idea is to substitute similar impulse response waveforms by modification of a smaller number of representative waveforms. In our prototype implementation, a correlation coefficient was used as an index of the similarity. By this proposed approach the experimental implementation performance proved that the amount of storage was reduced to 1.1% of the original data size in cases where the threshold correlation coefficient value was 0.8.
Using swamps to improve optimal pathfinding
Authors: Nir Pochter, Aviv Zohar, Jeffrey S. Rosenschein
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

We address the problem of quickly finding shortest paths in known graphs. We propose a method that relies on identifying areas that tend to be searched needlessly (areas we call swamps), and exploits this knowledge to improve search. The method requires relatively little memory, and reduces search cost drastically, while still finding optimal paths. Our method is independent of the heuristics used in the search, and of the search algorithm. We present experimental results that support our claims, and provide an anytime algorithm for the pre-processing stage that identifies swamps.
Extracting and predicting the communication behaviour of parallel applications
Authors: Rodrigo Fernandes de Mello, Evgueni Dodonov, Ricardo Bertagna, Luciano Jose Senger
Venue: International Journal of Parallel, Emergent and Distributed Systems (2009)

This paper presents a model to extract and predict the communication behaviour of parallel applications. The behaviour was extracted by introducing system calls in the Linux kernel to obtain the communication information about application tasks. The extracted information is organised as time series of the number of bytes transmitted and received during the task's execution time. The dimension of these time series is reduced by using a self-organising neural network architecture that detects common resource usage states and compacts communication events. This reduction simplifies the design of the prediction model as it does not need to consider too many different communication characteristics. The reduced information is submitted to a time-delay neural network that allows to predict the volume of future data transfers. The resulting predictions may be used in scheduling algorithms, allowing to define the best resources to be allocated according to communication events. If there is no communication it is possible to distribute processes just considering CPU capacity, otherwise it is necessary to evaluate when and how many bytes are transferred to allocate tasks in neighbour networks.
A modified semi-implicit method for a hyperbolic two-fluid model
Authors: Moon-Sun Chung, Sung-Jae Lee
Venue: Applied Numerical Mathematics (2009)

By introducing the interfacial pressure jump terms based on a surface tension into the momentum equations of a two-phase two-fluid model, the mathematical property of the governing equations is changed to a hyperbolic type. Then the eigenvalues of the equation system always become always real values representing the void wave and the pressure wave propagation speeds as shown in the present author's former article: Numerical Heat Transfer - Part B (40) (2001) 83-97. To solve the interfacial pressure jump terms with void fraction gradients implicitly, the conventional semi-implicit method should be modified by inserting an intermediate calculation process for a void fraction at a fractional time step. This modified semi-implicit method then becomes stable without conventional additive terms. Consequently, by including the interfacial pressure jump terms with the modified semi-implicit method, the numerical calculations of the void discontinuity propagation and water faucet problems can become more stable and sound than those calculated by using virtual mass terms.
Graph Spanners in the Streaming Model: An&#x00a0;Experimental Study
Authors: Giorgio Ausiello, Camil Demetrescu, Paolo G. Franciosa, Giuseppe F. Italiano, Andrea Ribichini
Venue: Algorithmica (2009)

This article reports the results of an extensive experimental analysis of efficient algorithms for computing graph spanners in the data streaming model, where an (&#x03b1;,&#x03b2;)-spanner of a graph G is a subgraph S&#x2286;G such that for each pair of vertices the distance in S is at most &#x03b1; times the distance in G plus &#x03b2;. To the best of our knowledge, this is the first computational study of graph spanner algorithms in a streaming setting. We compare experimentally the randomized algorithms proposed by Baswana (http://www.citebase.org/abstract?id=oai:arXiv.org:cs/0611023) and by Elkin (In: Proceedings of the 34th International Colloquium on Automata, Languages and Programming (ICALP 2007), Wroclaw, Poland, pp.&#x00a0;716&#x2013;727, 9&#x2013;13 July 2007) for general stretch factors with the deterministic algorithm presented by Ausiello et&#x00a0;al. (In: Proceedings of the 15th Annual European Symposium on Algorithms (ESA 2007), Engineering and Applications Track, Eilat, Israel, 8&#x2013;10 October 2007. LNCS, vol.&#x00a0;4698, pp. 605&#x2013;617, 2007), designed for building small stretch spanners. All the algorithms we implemented work in a data streaming model where the input graph is given as a stream of edges in arbitrary order, and all of them need a single pass over the data. Differently from the algorithm in Ausiello et&#x00a0;al., the algorithms in Baswana (http://www.citebase.org/abstract?id=oai:arXiv.org:cs/0611023) and Elkin (In: Proceedings of the 34th International Colloquium on Automata, Languages and Programming (ICALP 2007), Wroclaw, Poland, pp.&#x00a0;716&#x2013;727, 9&#x2013;13 July 2007) need to know in advance the number of vertices in the graph. The results of our experimental investigation on several input families confirm that all these algorithms are very efficient in practice, finding spanners with stretch and size much smaller than the theoretical bounds and comparable to those obtainable by off-line algorithms. Moreover, our experimental findings confirm that small values of the stretch factor are the case of interest in practice, and that the algorithm by Ausiello et&#x00a0;al. tends to produce spanners of better quality than the algorithms by Baswana and Elkin, while still using a comparable amount of time and space resources.
Composing Miners to Develop an Intrusion Detection Solution
Authors: Marcello Castellano, Giuseppe Mastronardi, Luca Pisciotta, Gianfranco Tarricone
Venue: Privacy, Security, and Trust in KDD: Second ACM SIGKDD International Workshop, PinKDD 2008, Las Vegas, NV, USA, August 24, 2008, Revised Selected Papers (2009)

Today, security is of strategic importance for many computer science applications. Unfortunately, an optimal solution does not exist and often system administrators are faced with new security problems when trying to protect computing resources within a reasonable time. Security applications that seem effective at first, could actually be unsuitable. This paper introduces a way of developing flexible computer security solutions which can allow system administrators to intervene rapidly on systems by adapting not only existing solutions but new ones as well. To this end, the study suggests considering the problem of intrusion detection as a Knowledge Discovery process and to describe it in terms of both e-services and miner building blocks. In addition, a definition of an intrusion detection process using Web content analysis generated by users is presented.
Robert Milne --Mountain Writing & Scottish Mountaineering Publications Work
Authors: Ken Crocket
Venue: Proceeding of the 2006 conference on Rob Milne: A Tribute to a Pioneering AI Scientist, Entrepreneur and Mountaineer (2006)

This article takes a slightly unusual approach to Rob Milne's writing as it is inextricably bound up with the subject matter --exploratory mountaineering. The latter is peculiarly intensive and demanding, especially in winter, and as a result has often induced exciting writing from its practitioners. For those not involved in this aspect of mountaineering therefore, a little background is often helpful. This cannot be an exhaustive list; Rob may have penned articles for local magazines or journals which are rarely indexed. Article excerpts are in italics.
Fault-tolerate Multiparty Electronic Contract Signing Protocol
Authors: Dongyao Ji, Dengguo Feng
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

We present a general fault-tolerate multiparty contract signing protocol that uses verifiable signature sharing technique, the protocol works in the asynchronous network environment and realizes multiparty contract signing within a fixed expected number of computational rounds. The correctness of the protocol is proved in theory.
Fast Set Bounds Propagation using BDDs
Authors: Graeme Gange, Vitaly Lagoon, Peter J. Stuckey
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Set bounds propagation is the most popular approach to solving constraint satisfaction problems (CSPs) involving set variables. The use of reduced ordered Binary Decision Diagrams (BDDs) to represent and solve set CSPs is well understood and brings the advantage that propagators for arbitrary set constraints can be built. This can substantially improve solving. The disadvantages of BDDs is that creating and manipulating BDDs can be expensive. In this paper we show how we can perform set bounds propagation using BDDs in a much more efficient manner by generically creating set constraint predicates, and using a marking approach to propagation. The resulting system can be significantly faster than competing approaches to set bounds propagation.
Chemical education using feelable molecules
Authors: R. Andrew Davies, James S. Maskery, Nigel W. John
Venue: Proceedings of the 14th International Conference on 3D Web Technology (2009)

Two different approaches for the preparation of novel cost-effective molecular haptic applications (Figure 1) are described. The former utilises Perl scripting within a commercial molecular modelling package to generate static / animated H3D scene graphs for haptic CPK space-filling atomic perception. Within the second approach, key chemical concepts such as reactivity, aciditity and periodicity can be investigated using prototype H3D user interfaces.