ppxscal/embedding_network huggingface dataset:
Spatially-Variant Morpho-Hessian Filter: Efficient Implementation and Application
Authors: Olena Tankyevych, Hugues Talbot, Petr Dokladál, Nicolas Passat
Venue: Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing (2009)

Elongated objects are more difficult to filter than more isotropic ones because they locally comprise fewer pixels. For thin linear objects, this problem is compounded because there is only a restricted set of directions that can be used for filtering, and finding this local direction is not a simple problem. In addition, disconnections can easily appear due to noise. In this paper we tackle both issues by combining a linear filter for direction finding and a morphological one for filtering. More specifically, we use the eigen-analysis of the Hessian for detecting thin, linear objects, and a spatially-variant opening or closing for their enhancement and reconnection. We discuss the theory of spatially-variant morphological filters and present an efficient algorithm. The resulting spatially-variant morphological filter is shown to successfully enhance directions in 2D and 3D examples illustrated with a brain blood vessel segmentation problem.
Human Factor's in Telemedicine: Training Surgeons by Telementoring
Authors: Dina Notte, Rym Mimouna, Guy-Bernard Cadiere, Jean Bruyns, Michel Degueldre, Pierre Mols
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

This study aim at evaluating several cases and communication options between a surgeon-mentor and a surgeon-mentoree within a telementoring context. The simulation proved that surgical telementoring was technically feasible with a satellite link simulated at 384 Kb/s, 512 Kb/s, and 768 Kb/s and with a transmission delay of 700 ms. Results show the limitations of image communication and its acceptability for telementoring and point out an important learning process for the mentoree. This seems to indicate a more efficient learning curve than with the standard training techniques (live surgical demonstration by companionship or videoconferencing), or with the use of laparoscopic simulator and surgical robots.
Afforded actions as a behavioral assessment of physical presence in virtual environments
Authors: Jean-Claude Lepecq, Lionel Bringoux, Jean-Marie Pergandi, Thelma Coyle, Daniel Mestre
Venue: Virtual Reality (2009)

A particular affordance was used as a potential candidate for behavioral assessment of physical presence in virtual environments. The subjects&#x2019; task was to walk through a virtual aperture of variable widths. In the case of presence, the subjects&#x2019; body orientation, while walking, was hypothesized to be adapted to the width of the aperture and to their own shoulder width. Results show that most subjects adapted their behavior to both their body architecture and the virtual width constraints. These subjects exhibited a behavioral transition from frontal walking to body rotation while walking through broad to narrow apertures. The same behavioral transition has already been documented in real environments (Warren and Whang in J Exp Psychol Human Percept Perform 13(3):371&#x2013;383, 1987). This behavioral adjustment is thus assumed to be an objective indication of presence. Beyond these results, the present study suggests that every afforded action could be a potential tool for sensorimotor assessment of physical presence.
Content-Based Clustering for Tag Cloud Visualization
Authors: Arkaitz Zubiaga, Alberto P. García-Plaza, Víctor Fresno, Raquel Martínez
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

Social tagging systems are becoming an interesting way to retrieve web information from previously annotated data. These sites present a tag cloud made up by the most popular tags, where neither tag grouping nor their corresponding content is considered. We present a methodology to obtain and visualize a cloud of related tags based on the use of self-organizing maps, and where the relations among tags are established taking into account the textual content of tagged documents. Each map unit can be represented by the most relevant terms of the tags it contains, so that it is possible to study and analyze the groups as well as to visualize and navigate through the relevant terms and tags.
Lane Mark Detection with Active Contour for Gradient Domain
Authors: Bibo Lu, Chunli Miao, Hui Wang
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

The extraction of lane mark is an essential step for several vision-based systems in intelligent transportation applications. In this paper, we propose a novel method for lane detection using a new active contour model. The new model is a modified version of the classical C-V model in gradient domain. The initial level set curve can be anywhere in the image without changing the segmentation result. To select the lane mark contour, moment invariant is utilized to make shape analysis. The experiment results on real scene image show that the proposed algorithm could detect lane mark accurately.
An Improved Algorithm of PRI Transform
Authors: Yan Mao, Jun Han, Guohua Guo, Xu Qing
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

It is a difficult problem to deinterleave radar radiating source in the electronic countermeasure field at present, the pulse repetition interval (PRI) constant and PRI jitter pulse sequence can be deinterleaved by PRI transform algorithm, but it has some disadvantages. The deinterleaving right rate is affected by the range of PRI value, and the PRI transform algorithm is not useful to PRI stagger pulse sequence. In order to resolve the two problems, an improved algorithm is proposed in this paper, and simulation results show that this improved algorithm is effective.
Combining Symmetry Breaking and Global Constraints
Authors: George Katsirelos, Nina Narodytska, Toby Walsh
Venue: Recent Advances in Constraints: 13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008, Rome, Italy, June 18-20, 2008, Revised Selected Papers (2009)

We propose a new family of constraints which combine together lexicographical ordering constraints for symmetry breaking with other common global constraints. We give a general purpose propagator for this family of constraints, and show how to improve its complexity by exploiting properties of the included global constraints.
A Designed Edge Marking Fill Algorithm for Elongated Polygon
Authors: Guodong Ye, Gui Lin, Changqing Zhu
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

To fill an elongated polygon, traditional Edge Marking Fill Algorithm can not deal properly. Basing on it, this paper especially presents a designed Edge Marking Fill algorithm aiming at elongated polygon. The idea is to design an algorithm, which signs out the pixel activated double times, then bounce out the function of edge marking fill algorithm and fill it with polygon pixel value. It solves the shortage that Edge Marking Fill Algorithm can not pick up the couple pixels for single point in the case of elongated polygon. The experimental results show that the new designed algorithm can be carried out easily and efficiently.
Large Margin Feature Weighting Method via Linear Programming
Authors: Bo Chen, Hongwei Liu, Jing Chai, Zheng Bao
Venue: IEEE Transactions on Knowledge and Data Engineering (2009)

The problem of feature selection is a difficult combinatorial task in machine learning and of high practical relevance. In this paper, we consider feature selection method for multimodally distributed data, and present a large margin feature weighting method for k-nearest neighbor (kNN) classifiers. The method learns the feature weighting factors by minimizing a cost function, which aims at separating different classes by large local margins and pulling closer together points from the same class, based on using as few features as possible. The consequent optimization problem can be efficiently solved by Linear Programming. Finally, the proposed approach is assessed through a series of experiments with UCI and microarray data sets, as well as a more specific and challenging task, namely, radar high-resolution range profiles (HRRP) automatic target recognition (ATR). The experimental results demonstrate the effectiveness of the proposed algorithms.
Fingerprint Skeleton Extraction Based on Improved Principal Curve
Authors: Chi Ma, Hongyun Zhang, Duoqian Miao, XueDong Zhang
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

In the fingerprint recognition system, skeleton extraction for low quality fingerprint images is an emphasis and difficulty task. Traditional methods are, however, susceptible to noise. In view of this, we propose a principal curves-based approach to alleviate this difficulty. In the paper, according to some characteristics of the fingerprint dataset, we improve the original principal graph algorithm proposed by Kégl to obtain principal curves, which can be served as the skeleton of a fingerprint. Experimental results show that our improved principal curve algorithm is better in efficiency and quality than the original algorithm. Our algorithm contains more information quantity and is proved to be more accurate and anti-noisy than thinning algorithm.
Case-Based Reasoning in Transfer Learning
Authors: David W. Aha, Matthew Molineaux, Gita Sukthankar
Venue: Proceedings of the 8th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2009)

Positive transfer learning (TL) occurs when, after gaining experience from learning how to solve a (source) task, the same learner can exploit this experience to improve performance and/or learning on a different (target) task. TL methods are typically complex, and case-based reasoning can support them in multiple ways. We introduce a method for recognizing intent in a source task, and then applying that knowledge to improve the performance of a case-based reinforcement learner in a target task. We report on its ability to significantly outperform baseline approaches for a control task in a simulated game of American football. We also compare our approach to an alternative approach where source and target task learning occur concurrently, and discuss the tradeoffs between them.
Better informed training of latent syntactic features
Authors: Markus Dreyer, Jason Eisner
Venue: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (2006)

We study unsupervised methods for learning refinements of the nonterminals in a treebank. Following Matsuzaki et al. (2005) and Prescher (2005), we may for example split NP without supervision into NP[0] and NP[1], which behave differently. We first propose to learn a PCFG that adds such features to nonterminals in such a way that they respect patterns of linguistic feature passing: each node's nonterminal features are either identical to, or independent of, those of its parent. This linguistic constraint reduces runtime and the number of parameters to be learned. However, it did not yield improvements when training on the Penn Treebank. An orthogonal strategy was more successful: to improve the performance of the EM learner by treebank preprocessing and by annealing methods that split nonterminals selectively. Using these methods, we can maintain high parsing accuracy while dramatically reducing the model size.
One Eighth Rule in N-queens Problem Based on Group Theory and Morphological Gene Combinations
Authors: Zhang Dakun
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

After analyzed the feasible Solutions of N-queens problem, this paper brought forward the concept of morphological gene and rules to extract morphological genes. It connected dihedral group, morphological gene combination with equivalence class of queens position of N-queens problem, summarized the one eighth rule of N-queens problem, then analyzed the causes for attenuate of one eighth rule from two aspects of Group and symmetry of morphological gene combination. It provided a new mentality for further deep research of N-queens problem, and is of reference value for studying highly effective algorithm for N-queens problem.
Database Technologies for RDF
Authors: Souripriya Das, Jagannathan Srinivasan
Venue: Reasoning Web. Semantic Technologies for Information Systems: 5th International Summer School 2009, Brixen-Bressanone, Italy, August 30 - September 4, 2009, Tutorial Lectures (2009)

Efficient and scalable support for RDF/OWL data storage, loading, inferencing and querying, in conjunction with already available support for enterprise level data and operations reliability requirements, can make databases suitable to act as enterprise-level RDF/OWL repository and hence become a viable platform for building semantic applications for the enterprise environments.This tutorial outlines the requirements for supporting semantic technologies in databases including bulk load and data manipulation operations, inference based on RDFS, OWL and user-defined rules, and support for SPARQL queries. It also discusses the design choices for handling issues that arise in implementing support for storage and operations on large scale RDF/OWL data, and in general, touches upon the practical aspects related to RDF/OWL support that become important in enterprise environments. Semantic technologies support in Oracle Database is used as a case study to illustrate with concrete examples the key requirements and design issues.
Towards Content-Oriented Integration for Process-Centric Knowledge Management Systems
Authors: Ming Gao, Jichen Jiang
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

Workﬂow Management System (WfMS) which focuses on controlling, monitoring, optimizing and supporting business processes management is extensively used in Knowledge Management Systems (KMS). But traditional WfMS only work with complete processes on the basis of process models and therefore fail to support a large class of knowledge intensive business processes such as content-oriented integration. In this paper, a service-oriented framework supporting effective content-oriented integration for process-centric KMS is proposed. This framework uses a hybrid process-driven navigation mechanism including content-oriented high-level process and content fragments-oriented micro process. Representational State Transfer (REST) based interface is used to interact with outer entities to increase flexibility and extensibility in constructing complex knowledge intensive applications. A content-oriented services activation and composition meta-data model is given to map relationships among processes, services and related content and its fragments which is used to activate corresponding processes and transform service context into message exchange objects transmitted in enterprise service bus. Finally, the overview, design and implementation of the prototype system are illustrated.
A Novel Revolutionary Surgical Device for TransOral Incisionless Surgery: EsophyX Used for Endoluminal Fundoplication (ELF) in Patients Suffering of Reflux Disease
Authors: Adrian Lobontiu, Daniel Loisance
Venue: Proceedings of the 2009 Advanced Technologies for Enhanced Quality of Life (2009)

The novel Endoluminal Fundoplication (ELF) technique using a Trans-Oral Incisionless and fastener-deploying device (EsophyX™, EndoGastric Solutions) was developed and evaluated for feasibility, safety and the treatment of Gastro-Esophageal Reflux Disease (GERD) in a series of animal and human (phase 1, phase 2) studies.
Extractors for Low-Weight Affine Sources
Authors: Anup Rao
Venue: Proceedings of the 2009 24th Annual IEEE Conference on Computational Complexity (2009)

We give polynomial time computable extractors for \emph{low-weight affince sources}. A distribution is affine if it samples a randompoints from some unknown low dimensional subspace of $\mathbb{F}_2^n$. A distribution is low weight affine if the corresponding linear spacehas a basis of low-weight vectors. Low-weight affine sources are thus a generalization of the well studied models of bit-fixing sources (which are just weight $1$ affine sources). For universal constants $c,\epsilon$, our extractors can extract almost allthe entropy from weight $k^{\epsilon}$ affine sources of dimension $k$, as long as $k > \log ^c n$, with error $2^{-k^{\Omega(1)}}$. In particular, our results give new extractors for low entropy bit-fixing sources, with exponentially small error, a parameter that is important for the application of these extractors to cryptography. Our techniques involve constructing new \emph{condensers} for \emph{affine somewhere random sources}.
Genome-wide maps of mono-and di-nucleosomes of Aspergillus fumigatus
Authors: Hiromi Nishida, Takayuki Motoyama, Shogo Yamamoto, Hiroyuki Aburatani, Hiroyuki Osada
Venue: Bioinformatics (2009)

We identified 5 975 567 mono-and 6 995 122 di-nucleosome positions of the fungus Aspergillus fumigatus, which was detected at high resolution based on the DNA sequence data obtained from both mono-and di-nucleosomal DNA fragments. We show that the distribution of lengths of the mono-nucleosomal DNA fragments has two peaks at 135 and 150 nt, whereas the distribution of di-nucleosomal DNA fragment lengths has a single peak at 285 nt. Although the gene bodies of the active and inactive genes and the inactive gene promoters had the two peaks of the mono-nucleosomal DNA fragment lengths, the active gene promoter lost the longer peak at 150 nt. Our findings strongly suggest that the nucleosomes protecting longer DNA fragments against MNase at the promoters, thereby inhibiting high gene expression. Contact: hnishida@iu.a.u-tokyo.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online.
The Social Factor: Innovate, Ignite, and Win through Mass Collaboration and Social Networking, 1st edition
Authors: Maria Azua
Venue:  (2009)

Harness the Power of Social Networking to Promote Innovation and Drive Growth A treasure trove of strategic and tactical insights for the business leader Provides relevant experience from a host of powerful case studies and compelling business scenarios Secrets for avoiding costly mistakes that can cripple a social networking initiative Millions of people use social networking sites, and companies are increasingly turning to social networking to build relationships with customers. But companies routinely miss the best opportunities to create value and promote innovationby using social networking to build thriving communities of employees, partners, and customers. Business leaders and strategists can drive immense value from social networking inside the firewall. Drawing on her unsurpassed experience deploying innovative social networking systems within IBM and for customers, Maria Azua demonstrates how to establish social networking communities, and then leverage those communities to drive extraordinary levels of innovation. Azua offers specific techniques for promoting mass collaboration in the enterprise and strategies to monetize social networking to generate new business opportunities. Whatever your industry, youll learn how to choose and implement the right social networking solutions for your unique challenges...how to avoid false starts and wasted time...and how to evaluate and make the most of todays most promising social technologiesfrom wikis and blogs to knowledge clouds.
Spatial Encoding Scheme for Protein Supporting Structure Discovery
Authors: Yu-Feng Huang, Chia-Jui Yang, Yi-Wei Yang, Chien-Kang Huang
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

Protein function is highly correlated with its three dimensional conformation in order to interact with others proteins, ligands, substrates, inhibitors, etc. Studies on binding site and protein function have been investigated to understand the mechanism of protein activity; therefore, protein stability and flexibility play different roles on protein functions. In this work, we propose a framework to discover protein supporting structures, which employs the signatures of local structures and mines the rigid regions form the same/similar proteins.Through experiments and discussions, we heuristically determined the effective encoding method. Further we apply this encoding method in discovering protein supporting structure by identifying stable regions. Our results reveal that supporting structure can be discovered in selected enzyme families. Moreover, the reasons for supporting structure existence vary between protein families.
These Lives Will Not Be Lost in Vain: Organizational Learning from Disaster in U.S. Coal Mining
Authors: Peter M. Madsen
Venue: Organization Science (2009)

The stated purpose of the investigations that invariably follow industrial, transportation, and mining disasters is to learn from those tragedies to prevent future tragedies. But does prior experience with disaster make organizations more capable of preventing future disasters? Do organizations learn from disasters experienced by other organizations? Do organizations learn differently from rare disasters than they do from common minor accidents? In its present state, the organizational safety literature is poorly equipped to answer these questions. The present work begins to address this gap by empirically examining how prior organizational experience with disaster affects the likelihood that organizations will experience future disasters. It approaches the issue in the context of fatal U.S. coal mining accidents from 1983 to 2006. The analysis demonstrates that organizations do learn to prevent future disasters through both direct and vicarious experience with disaster. It also indicates that the mechanisms through which organizations learn from disasters differ from those through which they learn from minor accidents.
Textile-Based Wearable Sensors for Assisting Sports Performance
Authors: Shirley Coyle, Deirdre Morris, King-Tong Lau, Dermot Diamond, Niall Moyna
Venue: Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks (2009)

There is a need for wearable sensors to assess physiological signals and body kinematics during exercise. Such sensors need to be straightforward to use, and ideally the complete system integrated fully within a garment. This would allow wearers to monitor their progress as they undergo an exercise training programme without the need to attach external devices. This takes physiological monitoring into a more natural setting. By developing textile sensors the intelligence is integrated into a sports garment in an innocuous manner.A number of textile based sensors are presented here that have been integrated into garments for various sports applications.
A Prize-Collecting Steiner Tree Approach for Transduction Network Inference
Authors: Marc Bailly-Bechet, Alfredo Braunstein, Riccardo Zecchina
Venue: Proceedings of the 7th International Conference on Computational Methods in Systems Biology (2009)

Into the cell, information from the environment is mainly propagated via signaling pathways which form a transduction network. Here we propose a new algorithm to infer transduction networks from heterogeneous data, using both the protein interaction network and expression datasets. We formulate the inference problem as an optimization task, and develop a message-passing, probabilistic and distributed formalism to solve it. We apply our algorithm to the pheromone response in the baker's yeast S. cerevisiae. We are able to find the backbone of the known structure of the MAPK cascade of pheromone response, validating our algorithm. More importantly, we make biological predictions about some proteins whose role could be at the interface between pheromone response and other cellular functions.