ppxscal/embedding_network huggingface dataset:
Knowledge Publishing and Access on the Semantic Web: A Sociotechnological Analysis
Authors: Enrico Motta
Venue: IEEE Intelligent Systems (2006)

The Semantic Web extends the current Web with a semantic layer, which can be reasoned upon by semantic-aware agents. The idea is that this semantic layer will enable a greater degree of task automation and user support than is possible with the current Web. Here, the author speculates on the Semantic Web's implications for knowledge publishing and access, which will be brought about by the existence of massive amounts of semantic data on the Web. In particular, the author considers how an ontology-driven world might lead to the imposition of conceptual viewpoints on formal knowledge production, which might threaten the democratic nature of knowledge publishing on the Web. However, he also argues that this risk can be avoided if researchers exploit the inherent flexibility and "smartness" associated with semantic technologies and succeed in connecting the process of constructing the Semantic Web to the social dynamics shaping the current Web.This article is part of a special issue on the Future of AI.
Between classical and ideal: enhancing wildland fire prediction using cluster computing
Authors: Baker Abdalhaq, Ana Cortés, Tomàs Margalef, Germán Bianchini, Emilio Luque
Venue: Cluster Computing (2006)

One of the challenges still open to wildland fire simulators is the capacity of working under real-time constrains with the aim of providing fire spread predictions that could be useful in fire mitigation interventions. We propose going one step beyond the classical wildland fire prediction by linking evolutionary optimization strategies to the traditional scheme with the aim of emulating an "ideal" fire propagation model as much as possible. In order to accelerate the fire prediction, this enhanced prediction scheme has been developed in a fashion on a Linux cluster using MPI. Furthermore, a sensitivity analysis has been carried out to determine the input parameters that we can fix to their typical values in order to reduce the search-space involved in the optimization process and, therefore, accelerates the whole prediction strategy.
Simulation based performance modeling for a warfighter in the loop minefield detection system
Authors: Abhilash Rajagopal, Sanjeev Agarwal, Sreeram Ramakrishnan
Venue: Proceedings of the 37th conference on Winter simulation (2005)

There has been significant recent interest in airborne reconnaissance for target detection using high resolution airborne images collected from an Unmanned Aerial Vehicle (UAV). Even if Automatic Target Recognition (ATR) algorithms are able to produce satisfactory results in terms of probability of detection for certain false alarm rate, there is a need for a Warfighter-in-the-Loop (WIL) to reduce false alarms further and verify and validate detections to attain the operational performance requirements. We develop a simulation model to assess effectiveness of the warfighter in decision loop for airborne minefield detection. The war-fighter effectiveness is measured in terms of average waiting-time, number of minefield segments in queue, and the expected false alarms, and missed detection. Various parameters which potentially affect the warfighter performance were identified with the help of prior studies with human operator in laboratory settings. Simulation trials were conducted to evaluate the dependence of these parameters on warfighter performance.
RDFS(FA): Connecting RDF(S) and OWL DL
Authors: Jeff Z. Pan, Ian Horrocks
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

Semantic Web (SW) languages are supposed to be compatible with each other in a meaningful way, so as to facilitate machine understanding. Recent research, however, shows that the semantics of the standard SW annotation language RDF (as well as its ontological extension RDFS) and that of the standard SW ontology language OWL DL are not compatible with each other. This paper investigates some issues behind this incompatibility and proposes a novel modification of RDF(S) as a firm semantic foundation for many of the latest Description Logics-based SW ontology languages, including OWL DL. Furthermore, the bidirectional one-to-one mapping between RDFS(FA) axioms in strata 0-2 and OWL DL axioms has been established, which enables RDFS(FA)-agents and OWL DL-agents to communicate with each other more easily. As a result, the introduction of RDFS(FA) clarifies the vision of the Semantic Web and solidifies RDF(S)'s proposed role as the base of the Semantic Web.
The Design of High-Level Features for Photo Quality Assessment
Authors: Yan Ke, Xiaoou Tang, Feng Jing
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

We propose a principled method for designing high level features forphoto quality assessment. Our resulting system can classify between high quality professional photos and low quality snapshots. Instead of using the bag of low-level features approach, we first determine the perceptual factors that distinguish between professional photos and snapshots. Then, we design high level semantic features to measure the perceptual differences. We test our features on a large and diverse dataset and our system is able to achieve a classification rate of 72% on this difficult task. Since our system is able to achieve a precision of over 90% in low recall scenarios, we show excellent results in a web image search application.
Using Prior Knowledge to Improve Distributed Hill Climbing
Authors: Roger Mailler
Venue: Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology (2006)

The Distributed Probabilistic Protocol (DPP) is a new, approximate algorithm for solving Distributed Constraint Satisfaction Problems (DCSPs) that exploits prior knowledge to improve the algorithm's convergence speed and efficiency. This protocol can most easily be thought of as a hybrid between the Distributed Breakout Algorithm (DBA) and the Distributed Stochastic Algorithm (DSA), because like DBA, agents exchange "improve" messages to control the search process, but like DSA, actually change their values based on a random probability. DPP improves upon these algorithms by having the agents exchange probability distributions that describe the likelihood of having particular "improve" values. These distributions can then be used by an agent to estimate the probability of having the best improve value among its neighbors or to compute the error caused by not informing other agents of changes to its improve value. This causes the protocol to use considerably fewer messages than both DBA and DSA, does not require a user to choose a randomness parameter like DSA, and allows DPP to more quickly converge onto good solutions. Overall, this protocol is empirically shown to be very competitive with both DSA and DBA.
Automatic Generation of Functional Programs from CASL Specifications
Authors: Agnes Arnould, Laurent Fuchs, Marc Aiguier, Thibaud Brunet
Venue: Proceedings of the International Conference on Software Engineering Advances (2006)

In this paper, we present a code generator transforming a class of CASL specifications into O'Caml programs. This code generator is dedicated to rapid prototyping of CASL specifications especially in the area of geometric modeling where algebraic formalisms have been used since the last decade. A large class of constructive equational specifications is handled by this generator while insuring the correctness of generated O'Caml programs. In particular, CASL specifications with many interpretation models (i.e. incomplete) are automatically supplemented in order to produce a program that implements one of them. Underlying properties, such as termination, completeness and confluence hold when equations satisfy some syntactic criteria given in the paper.
Multiple Neuronal Networks Mediate Sustained Attention
Authors: Natalia S. Lawrence, Thomas J. Ross, Ray Hoffmann, Hugh Garavan, Elliot A. Stein
Venue: Journal of Cognitive Neuroscience (2003)

Sustained attention deficits occur in several neuropsychiatric disorders. However, the underlying neurobiological mechanisms are still incompletely understood. To that end, functional MRI was used to investigate the neural substrates of sustained attention (vigilance) using the rapid visual information processing (RVIP) task in 25 healthy volunteers. In order to better understand the neural networks underlying attentional abilities, brain regions where task-induced activation correlated with task performance were identified. Performance of the RVIP task activated a network of frontal, parietal, occipital, thalamic, and cerebellar regions. Deactivation during task performance was seen in the anterior and posterior cingulate, insula, and the left temporal and parahippocampal gyrus. Good task performance, as defined by better detection of target stimuli, was correlated with enhanced activation in predominantly right fronto-parietal regions and with decreased activation in predominantly left temporo-limbic and cingulate areas. Factor analysis revealed that these performance-correlated regions were grouped into two separate networks comprised of positively activated and negatively activated intercorrelated regions. Poor performers failed to significantly activate or deactivate these networks, whereas good performers either activated the positive or deactivated the negative network, or did both. The fact that both increased activation of task-specific areas and increased deactivation of task-irrelevant areas mediate cognitive functions underlying good RVIP task performance suggests two independent circuits, presumably reflecting different cognitive strategies, can be recruited to perform this vigilance task.
Face recognition using multi-feature and radial basis function network
Authors: Su Hongtao, David Dagan Feng, Zhao Rong-chun
Venue: Selected papers from the 2002 Pan-Sydney workshop on Visualisation - Volume 22 (2003)

In this paper, a face recognition algorithm using multi feature and Radial basis Function Network (RBFN) is proposed. The algorithm consists of three steps. In the first step, a coarse classification is performed using Fourier frequency spectrum feature, and only the first k gallery images with minimum Euclidean distance to the probe image are retained. In the second step, the Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) features of frequency spectrum are extracted, which will be taken as the input of the RBFN in the third step. In the last step, the classification is carried out by using RBFN. The proposed approach has been tested on ORL face database and Shimon database. The experimental results have demonstrated that the performance of this algorithm is much superior to the other algorithms on the same database.
Three architectures for trusted data dissemination in edge computing
Authors: Shen-Tat Goh, HweeHwa Pang, Robert H. Deng, Feng Bao
Venue: Data Knowledge Engineering (2006)

Edge computing pushes application logic and the underlying data to the edge of the network, with the aim of improving availability and scalability. As the edge servers are not necessarily secure, there must be provisions for users to validate the results--that values in the result tuples are not tampered with, that no qualifying data are left out, that no spurious tuples are introduced, and that a query result is not actually the output from a different query. This paper aims to address the challenges of ensuring data integrity in edge computing. We study three schemes that enable users to check the correctness of query results produced by the edge servers. Two of the schemes are our original contributions, while the third is an adaptation of existing work. Our study shows that each scheme offers different security features, and imposes different demands on the edge servers, user machines, and interconnecting network. In other words, all three schemes are useful for different application requirements and resource configurations.
Zero Cost Test Point Insertion Technique to Reduce Test Set Size and Test Generation Time for Structured ASICs
Authors: Rajamani Sethuram, Seongmoon Wang, Srimat T. Chakradhar, Michael L. Bushnell
Venue: Proceedings of the 15th Asian Test Symposium (2006)

Since structured application specific integrated chip (ASIC) products require very short turn around time, long automatic test pattern generation (ATPG) run time is undesirable. Large structured ASICs often require a large number of test patterns to achieve the desired fault coverage. This paper presents the first test point insertion technique for structured ASICs that can reduce test set sizes and ATPG run time. Only unused flip-flops in the structured ASIC design are used to implement test points, so the proposed technique does not incur any hardware overhead. Since test points are inserted during a post-layout step, considering both timing and layout information, hence test points can be inserted without changing the existing layout or routing. Novel gain functions are defined that specifically quantify the reduction in test volume and test time to select the best signal lines for inserting test points. The gain function described in this paper is also applicable to regular cell based ASICs. The proposed test point insertion technique can be used in conjunction with any compression technique [19] to further reduce the test volume. Experimental results clearly demonstrate the effectiveness and scalability of the proposed technique. Using less than 1% of extra flip-flops and very little run time for test point insertion, we reduced test generation time by up 42.9% and test data volume by up to 25.9% while also achieving a near 100% fault efficiency for very large industrial (400K-5M signal lines) designs.
Estimation of intrinsic processes affected by additive fractal noise
Authors: Rosaura Fernández-Pascual, María D. Ruiz-Medina, José M. Angulo
Venue: Journal of Multivariate Analysis (2006)

Fractal Gaussian models have been widely used to represent the singular behavior of phenomena arising in different applied fields; for example, fractional Brownian motion and fractional Gaussian noise are considered as monofractal models in subsurface hydrology and geophysical studies Mandelbrot [The Fractal Geometry of Nature, Freeman Press, San Francisco, 1982 [13]]. In this paper, we address the problem of least-squares linear estimation of an intrinsic fractal input random field from the observation of an output random field affected by fractal noise (see Angulo et al. [Estimation and filtering of fractional generalised random fields, J. Austral. Math. Soc. A 69 (2000) 1-26 [2]], Ruiz-Medina et al. [Fractional generalized random fields on bounded domains, Stochastic Anal. Appl. 21 (2003a) 465-492], Ruiz-Medina et al. [Fractional-order regularization and wavelet approximation to the inverse estimation problem for random fields, J. Multivariate Anal. 85 (2003b) 192-216]. Conditions on the fractality order of the additive noise are studied to obtain a bounded inversion of the associated Wiener-Hopf equation. A stable solution is then obtained in terms of orthogonal bases of the reproducing kernel Hilbert spaces associated with the random fields involved. Such bases are constructed from orthonormal wavelet bases (see Angulo and Ruiz-Medina [Multiresolution approximation to the stochastic inverse problem, Adv. in Appl. Probab. 31 (1999) 1039-1057], Angulo et al. [Wavelet-based orthogonal expansions of fractional generalized random fields on bounded domains, Theoret. Probab. Math. Stat. (2004), in press]). A simulation study is carried out to illustrate the influence of the fractality orders of the output random field and the fractal additive noise on the stability of the solution derived.
Unsupervised Bayesian Detection of Independent Motion in Crowds
Authors: Gabriel J. Brostow, Roberto Cipolla
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

While crowds of various subjects may offer applicationspecific cues to detect individuals, we demonstrate that for the general case, motion itself contains more information than previously exploited. This paper describes an unsupervised data driven Bayesian clustering algorithm which has detection of individual entities as its primary goal. We track simple image features and probabilistically group them into clusters representing independently moving entities. The numbers of clusters and the grouping of constituent features are determined without supervised learning or any subject-specific model. The new approach is instead, that space-time proximity and trajectory coherence through image space are used as the only probabilistic criteria for clustering. An important contribution of this work is how these criteria are used to perform a one-shot data association without iterating through combinatorial hypotheses of cluster assignments. Our proposed general detection algorithm can be augmented with subject-specific filtering, but is shown to already be effective at detecting individual entities in crowds of people, insects, and animals. This paper and the associated video examine the implementation and experiments of our motion clustering framework.
A design method using darwinian principles for Collaborative Problem-Solving Environments (CPSEs)
Authors: Zann Gill
Venue: Proceedings of the 1999 conference on Computer support for collaborative learning (1999)

Distributed computational CPSEs (Collaborative Problem-Solving Environments) offer a petri dish where we can keep records and track creative path-finding as never before. CPSEs will enable us to test hypotheses about the dynamics of creative problem-solving that could not be tested until now.This paper argues that Darwin's method, a daring break from the rationalistic straitjacket of his time, offers eight lessons for designers and users of CPSEs. By applying these eight lessons, CPSEs can more effectively support large scale, long-lived multi-Center and multi-project enterprises such as Mars research and mission planning. Web-based knowledge management, interactive visualization and collaborative control capabilities can evolve incrementally, transitioning into CPSEs, which will support scientists and designers to work in new ways.My hypothesis is that CPSEs will support a new scientific revolution that could change the paradigm for "scientific method." If this hypothesis is correct, then CPSEs could drive a paradigm change in the community of practice regarding what constitutes acceptable "scientific method" and "engineering design." I suggest that CPSE design itself may also require a new synthesis, a new way of looking at scientific and engineering problems.
Active Graph Cuts
Authors: Olivier Juan, Yuri Boykov
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

This paper adds a number of novel concepts into global s/t cut methods improving their efficiency and making them relevant for a wider class of applications in vision where algorithms should ideally run in real-time. Our new Active Cuts (AC) method can effectively use a good approximate solution (initial cut) that is often available in dynamic, hierarchical, and multi-label optimization problems in vision. In many problems AC works faster than the state-of-the-art max-flow methods [2] even if initial cut is far from the optimal one. Moreover, empirical speed improves several folds when initial cut is spatially close to the optima. Before converging to a global minima, Active Cuts outputs a multitude of intermediate solutions (intermediate cuts) that, for example, can be used be accelerate iterative learning-based methods or to improve visual perception of graph cuts realtime performance when large volumetric data is segmented. Finally, it can also be combined with many previous methods for accelerating graph cuts.
Visualizing locations of off-screen objects on mobile devices: a comparative evaluation of three approaches
Authors: Stefano Burigat, Luca Chittaro, Silvia Gabrielli
Venue: Proceedings of the 8th conference on Human-computer interaction with mobile devices and services (2006)

Browsing large information spaces such as maps on the limited screen of mobile devices often requires people to perform panning and zooming operations that move relevant display content off-screen. This makes it difficult to perform spatial tasks such as finding the location of Points Of Interest (POIs) in a city. Visualizing the location of off-screen objects can mitigate this problem: in this paper, we present a user study comparing the Halo [2] approach with two other techniques based on arrows. Halo surrounds off-screen objects with circles that reach the display window, so that users can derive the location and distance of objects by observing the visible portion of the corresponding circles. In the two arrow-based techniques, arrows point at objects and their size and body length, respectively, inform about the distance of objects. Our study involved four tasks requiring users to identify and compare off-screen objects locations, and also investigated the effectiveness of the three techniques with respect to the number of off-screen objects. Arrows allowed users to order off-screen objects faster and more accurately according to their distance, while Halo allowed users to better identify the correct location of off-screen objects. Implications of these results for mobile map-based applications are also discussed.
Denoising Images using Wiener Filter in Directionalet Domain
Authors: Zhenjian Wang, Changwen Qu, Lei Cui
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

An algorithm for denoising image based on directionalet is proposed, and in each high-frequency subbands, adaptive Wiener filtering (window size 1× 25 ) is performed. Then, the denoised image is obtained by reconstruction from the filtered coefficients. At last, all directional sub-images are averaged.. The experiments results showed that this method outperforms Wiener filtering in standard 2-D wavelet domain. The SNR is improved 1~3d
Using log files to track students' model-based inquiry
Authors: Barbara C. Buckley, Janice D. Gobert, Paul Horwitz
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

We report on the Modeling Across the Curriculum Project (mac.concord.org), a 5-year study funded by the IERI program (IERI # 0115699). In this project we are using qualitative model-based tools for inquiry in three science domains (Genetics, Gas Laws, & Newtonian Mechanics) to promote scientific literacy on a broad scale, namely, content knowledge, process skills, and epistemologies of science (Perkins, 1986). The process skills we focus on in this project are model-based inquiry skills; epistemological constructs of interest here are students' epistemologies of models as a subset of epistemology of science (Gobert & Discenna, 1997; Schwartz & White, 1999). Our technological infrastructure, Pedagogica&trade; (Horwitz & Burke, 2002) logs all students' interactions with our hypermodels (Horwitz & Christie, 1999). We use students' log files as performance assessments of model-based inquiry on inquiry tasks called "hot spots" and track changes in inquiry skills over time both within and across domains.