ppxscal/embedding_network huggingface dataset:
Physically Consistent Variational Denoising of Image Fluid Flow Estimates
Authors: Andrey Vlasenko, Christoph Schnörr
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

High-speed image measurements of fluid flows define an important field of research in experimental fluid mechanics and the related industry. Numerous competing methods have been developed for both 2D and 3D measurements. Estimates of fluid flow velocity fields are often corrupted, however, due to various deficiencies of the imaging process, making the physical interpretation of the measurements questionable. We present an algorithm that accepts vector field estimates from any method and returns a physically plausible denoised version of it. Our approach enforces the physical structure and does not rely on particular noise models. Accordingly, the algorithm performs well for different types of noise and estimation errors. The computational steps are sufficiently simple to scale up to large 3D problems in the near future.
Categorical Data Clustering Using the Combinations of Attribute Values
Authors: Hee-Jung Do, Jae-Yearn Kim
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

Clustering is an important technique for exploratory data analysis. While most of the earlier clustering algorithms focused on numerical data, real-world problems and data mining applications frequently involve categorical data. Here, we propose a new clustering algorithm for categorical data that is based on the frequency of attribute value combinations. Our algorithm finds all the combinations of attribute values in a record, which represent a subset of all the attribute values, and then groups the records using the frequency of these combinations. As our algorithm considers all the subsets of attribute values in a record, records in a cluster have not only similar attribute value sets but also strongly associated attribute values. We evaluated our algorithm with real and synthetic data sets, and the experimental results demonstrate the effectiveness of our algorithm.
Various Speaker Recognition Techniques Using a Special Nonlinear Metric
Authors: Tudor Barbu, Mihaela Costin
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

In this paper we compare voice recognition techniques using a special nonlinear metric. We describe text-dependent and text-independent speaker recognition methods based on a mel-cepstral analysis in the feature extraction stage and a supervised classification. The Hausdorff-based metric proposed by us is able to measure the distance between different sized speech feature vectors resulted from the mel-cepstral featuring process. Then, a minimum mean distance classifier uses this new distance to identify the speakers.
Recovering the Long-Range Links in Augmented Graphs
Authors: Pierre Fraigniaud, Emmanuelle Lebhar, Zvi Lotker
Venue: Proceedings of the 15th international colloquium on Structural Information and Communication Complexity (2008)

The augmented graph model, as introduced by Kleinberg (STOC 2000), is an appealing model for analyzing navigability in social networks. Informally, this model is defined by a pair (H,φ), where H is a graph in which inter-node distances are supposed to be easy to compute or at least easy to estimate. This graph is "augmented" by links, called long-range links, which are selected according to the probability distribution φ. The augmented graph model enables the analysis of greedy routing in augmented graphs G ¿ (H,φ). In greedy routing, each intermediate node handling a message for a target t selects among all its neighbors in G the one that is the closest to t in H and forwards the message to it.This paper addresses the problem of checking whether a given graph G is an augmented graph. It answers part of the questions raised by Kleinberg in his Problem 9 (Int. Congress of Math. 2006). More precisely, given G ¿ (H,φ), we aim at extracting the base graph H and the long-range links R out of G. We prove that if H has high clustering coefficient and H has bounded doubling dimension, then a simple local maximum likelihood algorithm enables to partition the edges of G into two sets H¿ and R¿ such that E(H) ¿ H¿ and the edges in H¿ ¿ E(H) are of small stretch, i.e., the map H is not perturbed too greatly by undetected long-range links remaining in H¿. The perturbation is actually so small that we can prove that the expected performances of greedy routing in G using the distances in H¿ are close to the expected performances of greedy routing using the distances in H. Although this latter result may appear intuitively straightforward, since H¿ ¿ E(H), it is not, as we also show that routing with a map more precise than H may actually damage greedy routing significantly. Finally, we show that in absence of a hypothesis regarding the high clustering coefficient, any local maximum likelihood algorithm extracting the long-range links can miss the detection of at least ¿(n 5¿ /logn) long-range links of stretch at least ¿(n 1/5 ¿ ¿ ) for any 0 < ¿< 1/5, and thus the map H cannot be recovered with good accuracy.
An improved shading cache for modern GPUs
Authors: Pitchaya Sitthi-amorn, Jason Lawrence, Lei Yang, Pedro V. Sander, Diego Nehab
Venue: Proceedings of the 23rd ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware (2008)

Several recently proposed techniques based on the principle of data reprojection allow reusing shading information generated in one frame to accelerate the calculation of the shading in the following frame. This strategy can significantly reduce the average rendering cost for many important real-time effects at an acceptable level of approximation error. This paper analyzes the overhead associated with incorporating temporal data reprojection on modern GPUs. Based on this analysis, we propose an alternative algorithm to those previously described in the literature and measure its efficiency for multiple scenes and hardware platforms.
Flexible Conversations Using Social Commitments and a Performatives Hierarchy
Authors: Rob Kremer, Roberto A. Flores
Venue: Agent Communication II: International Workshops on Agent Communication, AC 2005 and AC 2006, Utrecht, Netherlands, July 25, 2005, and Hakodate, Japan, May 9, 2006, Selected and Revised Papers (2006)

In this research, we re-arrange FIPA's ACL performatives to form a subsumption lattice (ontology) and apply a theory of social commitments to achieve a simplified and observable model of agent behaviour. Using this model, we have implemented agent interaction through social commitments (or obligations) based solely on observation of messages passed between the agents (such observation is supported by the cooperation domain mechanism in our agent infrastructure system). Moreover, because the performatives are in a subsumption lattice, it is relatively easy for an observer to infer social commitment relationships even if the observer does not understand the details of messages or even the exact performatives used (so long as the observer has access to the performatives ontology).Our social commitment model can be used in agent implementation to simplify the specification and observation of agent behaviour even if the agents themselves are not implemented using social commitments. This is accomplished through the use of commitment operators attached to the performatives (as policies) in the subsumption lattice.In this work, we show how FIPA's performatives can be interpreted in a theory of social commitment to allow observable social behaviour and conformance to social norms.
Experience with Feedback Control Mechanisms in Self-replicating Multi-Agent Systems
Authors: Sebnem Bora, Oguz Dikenelli
Venue: Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V (2007)

In this paper, we present an approach for adaptive replication to support fault tolerance. This approach uses a feedback control theory methodology within an adaptive replication infrastructure to determine replication degrees of replica groups. We implemented this approach in a multi-agent system to survive Byzantine failures. At the end of the paper, we also provide some experimental results to show the effectiveness of our approach.
Using Similarity Metrics for Matching Lifelong Learners
Authors: Nicolas Labeke, Alexandra Poulovassilis, George Magoulas
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

The L4All system provides an environment for the lifelong learner to access information about courses, personal development plans, recommendation of learning pathways, personalised support for planning of learning, and reflecting on learning. Designed as a web-based application, it offers lifelong learners the possibility to define and share their own timeline (a chronological record of their relevant life episodes) in order to foster collaborative elaboration of future goals and aspirations. A keystone for delivering such functionalities is the possibility for learner to search for `people like me'. Addressing the fact that such a definition of `people like me' is ambiguous and subjective, this paper explores the use of similarity metrics as a flexible mechanism for comparing and ranking lifelong learners' timelines.
Reconstruction of 3D Structures From Protein Contact Maps
Authors: Marco Vassura, Luciano Margara, Pietro Di Lena, Filippo Medri, Piero Fariselli, Rita Casadio
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2008)

The prediction of the protein tertiary structure from solely its residue sequence (the so called Protein Folding Problem) is one of the most challenging problems in Structural Bioinformatics. We focus on the protein residue contact map. When this map is assigned it is possible to reconstruct the 3D structure of the protein backbone. The general problem of recovering a set of 3D coordinates consistent with some given contact map is known as a unit-disk-graph realization problem and it has been recently proven to be NP-Hard. In this paper we describe a heuristic method (COMAR) that is able to reconstruct with an unprecedented rate (3-15 seconds) a 3D model that exactly matches the target contact map of a protein. Working with a non-redundant set of 1760 proteins, we find that the scoring efficiency of finding a 3D model very close to the protein native structure depends on the threshold value adopted to compute the protein residue contact map. Contact maps whose threshold values range from 10 to 18 &#x00C5;ngstroms allow reconstructing 3D models that are very similar to the proteins native structure.
An Integer Linear Programming for Container Stowage Problem
Authors: Feng Li, Chunhua Tian, Rongzeng Cao, Wei Ding
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

So far most stowage planning only consider the stowage of single type containers or do not consider the stability of the containership. Here a 0-1 linear programming model for this problem is proposed. The objective is to maximize space utilization while minimize the operation cost from upload and download of different types containers at each port of a multi-port journey, with vessel stability, industry regulations and customized rules as the constraints. Based on experiments by adopting branch cut algorithm from COIN-OR(Common Optimization Interface for Operations Research) to such model. Successively, a simulation system is developed to verify the feasibility and practicability of the model. By using the branch and cut algorithm of COIN-OR, the simulation system has shown that our model is efficient and robust.
Modelling of Transport and Traffic Problems
Authors: Andreas Schadschneider
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

The Asymmetric Simple Exclusion Process (ASEP) is the simplest cellular automaton which captures the essential aspects of most transport and traffic phenomena. It describes the directed motion of particles obeying an exclusion principle. For specific applications, however, various generalizations of the ASEP are necessary. These are discussed for the case of highway traffic, ant trails, pedestrian dynamics and intracellular transport.
Using Decision Models for the Adaptive Generation of Learning Spaces
Authors: Eric Ras, Dimitri Ilin
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

This paper presents an approach that uses a decision model for resolving variations in a so-called learning space, which aim is to enhance the reuse of explicitly documented experiences by providing context-aware learning content. Decision models promise a better possibility to separate the variabilities in e-learning content, and address the problem of closed corpus of adaptive hypermedia systems. Adaptation is not coupled to a fixed set of learning resources, but to types of learning space concepts. The system adapts and personalizes the learning space to the learner's situation. A controlled experiment provides first statistically significant results, which show an experience package reuse improvement regarding knowledge acquisition and application efficiency. Further, it provides a baseline for future evaluations of different adaptation methods and techniques.
A First Approach to Birth Weight Prediction Using RBFNNs
Authors: A. Guillén, I. Rojas, J. González, H. Pomares, L. J. Herrera
Venue: Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks (2007)

This paper presents a first approach to try to determine the weight of a newborn using a set of variables determined uniquely by the mother. The proposed model to approximate the weight is a Radial Basis Function Neural Network (RBFNN) because it has been successfully applied to many real world problems. The problem of determining the weight of a newborn could be very useful by the time of diagnosing the gestational diabetes mellitus, since it can be a risk factor, and also to determine if the newborn is macrosomic. However, the design of RBFNNs is another issue which still remains as a challenge since there is no perfect methodology to design an RBFNN using a reduced data set, keeping the generalization capabilities of the network. Within the many design techniques existing in the literature, the use of clustering algorithms as a first initialization step for the RBF centers is a quite common solution and many approaches have been proposed. The following work presents a comparative of RBFNNs generated using several algorithms recently developed concluding that, although RBFNNs that can approximate a training data set with an acceptable error, further work must be done in order to adapt RBFNN to large dimensional spaces where the generalization capabilities might be lost.
A Framework for an Integrated Network Management System Base on Enhanced Telecom Operation Map (eTOM)
Authors: A. R. Yari, S. H. Fesharaki
Venue: Proceedings of the 10th Asia-Pacific Network Operations and Management Symposium on Managing Next Generation Networks and Services (2007)

This paper provides a summary of development process for the conceptual design of an integrated network management system (NMS) platform for incumbent with a huge legacy system. Based on proven international standards such as Enhanced Telecom Operation Map (eTOM) [1] and New Generation Operations System and Software (NGOSS) [2] framework an approach has been develop to address the current situation of incumbent as well as to make provision for NGN. In other world, the solution has been developed in a way that a relatively smooth transformation/ development of the existing fragmented management landscape towards an integrated NMS is possible. A service centric concept has been deployed for our conceptual design.
Upper Bounds for Set Systems with the Identifiable Parent Property
Authors: Michael J. Collins
Venue: Proceedings of the 3rd international conference on Information Theoretic Security (2008)

We derive upper bounds on the size of set systems having the c-identifiable parent property (c-IPP) and the c-traceability property (c-TA).
Hindi to English and Marathi to English Cross Language Information Retrieval Evaluation
Authors: Manoj Kumar Chinnakotla, Sagar Ranadive, Om P. Damani, Pushpak Bhattacharyya
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

In this paper, we present our Hindi to English and Marathi to English CLIR systems developed as part of our participation in the CLEF 2007 Ad-Hoc Bilingual task. We take a query translation based approach using bi-lingual dictionaries. Query words not found in the dictionary are transliterated using a simple rule based transliteration approach. The resultant transliteration is then compared with the unique words of the corpus to return the `k' words most similar to the transliterated word. The resulting multiple translation/transliteration choices for each query word are disambiguated using an iterative page-rank style algorithm which, based on term-term co-occurrence statistics, produces the final translated query. Using the above approach, for Hindi, we achieve a Mean Average Precision (MAP) of 0.2366 using title and a MAP of 0.2952 using title and description. For Marathi, we achieve a MAP of 0.2163 using title.
Split local absorbing conditions for one-dimensional nonlinear Klein-Gordon equation on unbounded domain
Authors: Houde Han, Zhiwen Zhang
Venue: Journal of Computational Physics (2008)

The numerical solution of the one-dimensional nonlinear Klein-Gordon equation on an unbounded domain is studied in this paper. Split local absorbing boundary (SLAB) conditions are obtained by the operator splitting method, then the original problem is reduced to an initial boundary value problem on a bounded computational domain, which can be solved by the finite difference method. Several numerical examples are provided to show the advantages and effectiveness of the given method, and some interesting collision behaviors are also observed.
A Virtual Environment for Core Skills Training in Vascular Interventional Radiology
Authors: Vincent Luboz, James Lai, Rafal Blazewski, Derek Gould, Fernando Bello
Venue: Proceedings of the 4th international symposium on Biomedical Simulation (2008)

We present a prototype for a new virtual environment aiming at training interventional radiologists in the core skills involved in using catheters or guidewires. The instrument is modelled as a hybrid mass-spring particle system while the vasculature is a rigid triangulated surface mesh. A specially designed commercial haptic device allows the trainee to use real instruments to guide the simulation through synthetically generated vasculature with different degrees of complexity. Open source libraries are used for the visualisation and collision detection. Preliminary results show reasonable behaviour.
Evaluating the Effect of Open Student Models on Self-Assessment
Authors: Antonija Mitrovic, Brent Martin
Venue: International Journal of Artificial Intelligence in Education (2007)

This paper discusses the simple open student models used in two of our constraint-based tutors, SQL-Tutor and KERMIT, and their effects on self-assessment. The systems present a high-level abstraction of the detailed information contained in the student model, in terms of skill meters representing the student's progress on domain concepts. SQL-Tutor presents the open student model when the student requires it, or when selecting new problems. KERMIT, on the other hand, continuously displays a high-level summary of the student's progress, while more detailed information is available on request. Our results show that even simple open student models can have important positive effects on learning and students' meta-cognitive skills. Students appreciated having access to their models, and they felt this feature contributed to their understanding of the domain. Performance of less able students becomes significantly better than that of their peers of similar abilities without access to their models. We have also seen that open student models can help students learn to select better problems.
Hiding Frequent Patterns under Multiple Sensitive Thresholds
Authors: Ya-Ping Kuo, Pai-Yu Lin, Bi-Ru Dai
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

Frequent pattern mining is a popular topic in data mining. With the advance of this technique, privacy issues attract more and more attention in recent years. In this field, previous works based hiding sensitive information on a uniform support threshold or a disclosure threshold. However, in practical applications, we probably need to apply different support thresholds to different itemsets for reflecting their significance. In this paper, we propose a new hiding strategy to protect sensitive frequent patterns with multiple sensitive thresholds. Based on different sensitive thresholds, the sanitized dataset is able to highly fulfill user requirements in real applications, while preserving more information of the original dataset. Empirical studies show that our approach can protect sensitive knowledge well not only under multiple thresholds, but also under a uniform threshold. Moreover, the quality of the sanitized dataset can be maintained.