ppxscal/embedding_network huggingface dataset:
Surface Reconstruction of Bone from X-ray Images and Point Distribution Model Incorporating a Novel Method for 2D-3D Correspondence
Authors: Guoyan Zheng, Lutz-Peter Nolte
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

Surface reconstruction of bone from a few X-ray images and point distribution model (PDM) is discussed. We present a robust approach combining regularized morphing and shape deformation, and show its application to surface reconstruction of proximal femur. The robustness of the presented approach relies on the development of a novel method to establish correspondence between the X-ray images and the model estimated from the PDM. The correspondence is based on an iterative non-rigid twodimensional (2D) point matching process, which iteratively uses a symmetric injective nearest-neighbor mapping operator (SIN-MO) and 2D thin-plate splines (2D-TPS) based deformation to find a fraction of best matched 2D point pairs between edge points detected from the X-ray images and projections of the points on the apparent contours extracted from the estimated model. The advantages of this novel method include robustness with respect to outliers, and automatic exclusion of cross matching, which is an important property for preservation of topology. Initial quantitative and qualitative evaluation results are given which indicate the validity of our approach.
Dimension Reduction for Supervised Ordering
Authors: Toshihiro Kamishima, Shotaro Akaho
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results and best-seller lists. Techniques for processing such ordinal data are being developed, particularly methods for a supervised ordering task: i.e., learning functions used to sort objects from sample orders. In this article, we propose two dimension reduction methods specifically designed to improve prediction performance in a supervised ordering task.
CoMobile: Collaborative Learning with Mobile Devices
Authors: Duc Phuong Nguyen, Martin Guggisberg, Helmar Burkhart
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

One of the common tools that support collaborative learning is web-based forum. A web forum is a place where students can ask questions, exchange their ideas, learning materials, learning experiences, and so on. As mobile devices can be used to access information from anywhere and at anytime, it would be useful to integrate these devices into such learning activities. However, it is a challenge to adapt web applications to mobile devices because of the limitations of screen size and processing power. In this paper, we introduce a novel application using mobile phones for accessing multimedia contents efficiently. Our system, the Interactive Multimedia Forum for Mobile Users (CoMobile), supports collaborative learning with various devices such as PC, PDA, and mobile phones.
Establishing Moore's Law
Authors: Ethan Mollick
Venue: IEEE Annals of the History of Computing (2006)

Every field has brief formulas or relationships that are useful for back-of-the-envelopecalculations. Rarely do these maxims become popular knowledge; even more rarely do they become asubiquitous and influential as Moore's law, the 40-year-old prediction that the speed of computerswill double every year or two. Here, a look at the way in which the legendary law evolved into aself-fulfilling prophecy.
On the Challenge of Allocating Service Based Applications in a Grid Environment
Authors: Sharath Babu Musunoori, Geir Horn, Frank Eliassen, Alia Mourad
Venue: Proceedings of the International Conference on Autonomic and Autonomous Systems (2006)

The significant advancements in grid computing provide a promising platform for parallel and distributed systems. However, achieving acceptable application performance in the grid environment remains a difficult engineering challenge. In particular for applications composed of services requiring some quality requirements to be fulfilled in order to satisfy the users needs. There is a growing need to support these applications as they perform unacceptably if platform resources are scarce or if the deployment is not carefully configured and tuned for the anticipated load. The fundamental problem we have at hand is of partitioning application services on to a distributed environment such that all services involved in the composition get sufficient resources to allow them to deliver at least the minimum required quality to be useful for the application. A subsequent problem is how to re-partition (reconfigure) or even adapt the application's service set dynamically when the underlying resources of the grid environment change with time. In this paper we provide an overview of both service partitioning and reconfiguration and different elements that affect the search process and investigate the nature of the problem space. In addition, we also introduce a special type of evolutionary algorithms such as learning and other nature-inspired solution techniques that can handle the dynamic behaviour of such stochastic computational environment.
Working Memory for Complex Scenes: Age Differences in Frontal and Hippocampal Activations
Authors: Denise C. Park, Robert C. Welsh, Christy Marshuetz, Angela H. Gutchess, Joseph Mikels, Thad A. Polk, Douglas C. Noll, Stephan F. Taylor
Venue: Journal of Cognitive Neuroscience (2003)

Age differences in frontal and hippocampal activations in working memory were investigated during a maintenance and subsequent probe interval in an event-related fMRI design. Younger and older adults either viewed or maintained photographs of real-world scenes (extended visual or maintenance conditions) over a 4-sec interval before responding to a probe fragment from the studied picture. Behavioral accuracy was largely equivalent across age and conditions on the probe task, but underlying neural activations differed. Younger but not older adults showed increased left anterior hippocampal activations in the extended visual compared with the maintenance condition. On the subsequent probe interval, however, older adults showed more left and right inferior frontal activations than younger adults. The increased frontal activations at probe in older adults may have been compensatory for the decreased hippocampal activations during maintenance, but alternatively could have reflected the increased difficulty of the probe task for the older subjects. Thus, we demonstrate qualitatively different engagement of both frontal and hippocampal structures in older adults in a working memory task, despite behavioral equivalence.
A framework for analysis of dynamic social networks
Authors: Tanya Y. Berger-Wolf, Jared Saia
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

Finding patterns of social interaction within a population has wide-ranging applications including: disease modeling, cultural and information transmission, and behavioral ecology. Social interactions are often modeled with networks. A key characteristic of social interactions is their continual change. However, most past analyses of social networks are essentially static in that all information about the time that social interactions take place is discarded. In this paper, we propose a new mathematical and computational framework that enables analysis of dynamic social networks and that explicitly makes use of information about when social interactions occur.
BABAR Experience of Large Scale Production on the Grid
Authors: C. A. J. Brew, F. F. Wilson, G. Castelli, T. Adye, E. Luppi, D. Andreotti
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

The BABAR Collaboration, based at Stanford Linear Accelerator Center (SLAC), Stanford, US, has been performing simulation studies and data analysis for 7 years using a number of compute farms around the world. Recent developments in Grid technologies could provide a way to manage the distributed resources in a single coherent structure. We describe enhancements to the BABAR Experiment's distributed Monte Carlo generation system to make use of European and North American Grid resources and present the results with regard to BABAR's latest cycle of Monte Carlo production. We compare the benefits of a local and Grid-based systems, the ease with which the system is managed and the challenges of integrating the Grid with legacy software. We compare job success rates and manageability issues between Grid and non-Grid production and present an investigation into the efficiency costs of different methods of making input data, in the form of files and database information, available to the job in a distributed environment.
Invited Paper: Pattern Matching Using n-Gram Sampling of Cumulative Algebraic Signatures: Preliminary Results
Authors: Witold Litwin, Riad Mokadem, Philippe Rigaux, Schwarz Thomas
Venue: Proceedings of the 17th International Conference on Database and Expert Systems Applications (2006)

We propose a novel string (pattern) matching algorithm called n-gram search. We intend it for the records stored once and searched many times in a database or a file, especially those organized in a Scalable Distributed Data Structure, (SDDS), over a grid or a structured P2P net. We presume that the records are encoded into their cumulative algebraic signatures, providing incidental confidentiality of stored data. The search starts with pre-processing the pattern, calculating the logarithmic algebraic signature (LAS) of the pattern and the LASs of every n-gram in it. The value of n \geqslant 1 is a parameter that one may tune. The search attempts to match the LASs of n-grams in the pattern towards dynamically calculated LASs, sampled over n-grams in the records. A mismatch generates a shift of up to K-n symbols towards next sample, where K is the pattern length. The whole process is parallel over the SDDS servers and does not require any local decoding. For an M-symbol long record, the unsuccessful search, measured as number of match attempts, costs O ((M-K) / (Kn+ 1)). The 2-grams should typically suffice, leading to O ((M-K) / (K-1)). We show that the algorithm particularly efficient for larger strings and records, i.e., with e-documents or DNA data. Preliminary results show then the n-gram search about (K - n + 1) faster than our previous algorithms and among the fastest known, e.g., probably often faster than Boyer-Moore. % MathType!MTEF!2!1!+- % feaafiart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn % hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr % 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9 % vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x % fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeyyzImlaaa!37B3! \[\geqslant\]
Research on 3-D Reconstruction With a Series of Cross-Sectional Images
Authors: Lijie Gan, Zhong Qu
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

3-D reconstruction with cross-sectional images means to reconstruct the 3-D shape of the object with a series of cross-sectional images. The 3-D reconstruction method derived from industrial computed tomography images is focused in this paper. The original data comes from a large industrial computed tomography machine, which uses the 3rd generation fan-beam scan mode. Firstly, images are processed to remove air annulus. Then volume rendering is used to reconstruct the workpiece in Matlab environment. The cross section image resulted from the 2-D convolution projection reconstruction is the original image for 3-D reconstruction, which is image file. The noise caused by converting paper or film image into digital image is reduced in this way. Furthermore the additional step to match images is avoided by applying the fan-beam convolution projection algorithm that determines whether the images are matched.
Star-Structured High-Order Heterogeneous Data Co-clustering Based on Consistent Information Theory
Authors: Bin Gao, Tie-Yan Liu, Wei-Ying Ma
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Heterogeneous object co-clustering has become an important research topic in data mining. In early years of this research, people mainly worked on two types of heterogeneous data (denoted by pair-wise co-clustering); while recently more and more attention was paid to multiple types of heterogeneous data (denoted by highorder co-clustering). In this paper, we studied the highorder co-clustering of objects with star-structured interrelationship, i.e., there is a central type of objects that connects the other types of objects. Actually, this case could be a very good model for many real-world applications, such as the co-clustering of Web images, their low-level visual features, and the surrounding text. We used a tripartite graph to represent the interrelationships among different objects, and proposed a consistent information theory which generates an effective algorithm to obtain the co-clusters of different types of objects. Experiments on a Web image show that our proposed algorithm is a better choice compared with previous work on heterogeneous object co-clustering.
2005 Special Issue: The interaction of attention and emotion
Authors: John G. Taylor, Nickolaos F. Fragopanagos
Venue: Neural Networks (2005)

We analyse emotions from the viewpoint of how emotion and attention interact in the brain. Much has been learnt about the brain structures involved in attention, especially in vision. In particular the manner in which attention functions as a high-level control system, able to make cognitive processing so effective, has been studied both at a global level by brain imaging (fMRI, PET, MEG and EEG), at a local single cell level in monkeys and lower animals, and computationally by a variety of models. The manner in which emotions impinge on this attention control system is not so well analysed, although numerous new results are now emerging from using the same tools. Here we use an engineering control approach to attention to model it in a global manner but with relatively sure local foundations at singe neuron level. The manner in which emotional value (as coded in amygdale and orbito-frontal cortex) can interact with the attention control circuitry is analysed using results of various experimental paradigms. A general model of this interaction is first developed and tested against a list of paradigms, and then more detailed computations are performed using more specific features of the attention control system and the limbic value coding. These computations are completed by a simulation of the emotional attentional blink, a demanding paradigm for any model of attention alone, but made more so by the presence of emotional value codes for stimuli. We conclude the paper with a general discussion of further avenues of research.
Flame Feature Model Development and Its Application to Flame Detection
Authors: Tai-Fang Lu, Chien-Yuan Peng, Wen-Bing Horng, Jian-Wen Peng
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

In this study, both linear discriminant technique and logistic regression method are considered and compared to develop a flame feature model. Based on the comparison, the logistic regression method is chosen and plugged into a flame detection system for segmenting the fire regions. Some spurious fire-like regions are then removed by the image difference method and the invented color masking technique. Finally, a simple method is devised to estimate the burning degree of the fire flame so that users could be informed with a proper warning alarm. The proposed method is tested with twelve diverse fire flame video clips at the process speed of thirty frames per second. The proposed method can achieve more than 97% detection rate on the average. In addition, the system can correctly recognize fire flames within one second on the initial combustion from the test video clips, which seems very promising.
Coherent closed quasi-clique discovery from large dense graph databases
Authors: Zhiping Zeng, Jianyong Wang, Lizhu Zhou, George Karypis
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

Frequent coherent subgraphs can provide valuable knowledge about the underlying internal structure of a graph database, and mining frequently occurring coherent subgraphs from large dense graph databases has been witnessed several applications and received considerable attention in the graph mining community recently. In this paper, we study how to efficiently mine the complete set of coherent closed quasi-cliques from large dense graph databases, which is an especially challenging task due to the downward-closure property no longer holds. By fully exploring some properties of quasi-cliques, we propose several novel optimization techniques, which can prune the unpromising and redundant sub-search spaces effectively. Meanwhile, we devise an efficient closure checking scheme to facilitate the discovery of only closed quasi-cliques. We also develop a coherent closed quasi-clique mining algorithm, <B>Cocain</B>1 Thorough performance study shows that Cocain is very efficient and scalable for large dense graph databases.
Computing the Equilibria of Bimatrix Games Using Dominance Heuristics
Authors: Raghav Aras, Alain Dutech, Francois Charpillet
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

We propose a formulation of a general-sum bimatrix game as a bipartite directed graph with the objective of establishing a correspondence between the set of the relevant structures of the graph (in particular elementary cycles) and the set of the Nash equilibria of the game. We show that finding the set of elementary cycles of the graph permits the computation of the set of equilibria. For games whose graphs have a sparse adjacency matrix, this serves as a good heuristic for computing the set of equilibria. The heuristic also allows the discarding of sections of the support space that do not yield any equilibrium, thus serving as a useful preprocessing step for algorithms that compute the equilibria through support enumeration.
Distributed Data Mining in Peer-to-Peer Networks
Authors: Souptik Datta, Kanishka Bhaduri, Chris Giannella, Ran Wolff, Hillol Kargupta
Venue: IEEE Internet Computing (2006)

Peer-to-peer (P2P) networks are gaining popularity in many applications such as file sharing, e-commerce, and social networking, many of which deal with rich, distributed data sources that can benefit from data mining. P2P networks are, in fact,well-suited to distributed data mining (DDM), which deals with the problem of data analysis in environments with distributed data,computing nodes,and users. This article offers an overview of DDM applications and algorithms for P2P environments,focusing particularly on local algorithms that perform data analysis by using computing primitives with limited communication overhead. The authors describe both exact and approximate local P2P data mining algorithms that work in a decentralized and communication-efficient manner.
Relay Node Placement in Wireless Sensor Networks
Authors: Errol L. Lloyd, Guoliang Xue
Venue: IEEE Transactions on Computers (2007)

A wireless sensor network consists of many low-cost, low-power sensor nodes, which can perform sensing, simple computation, and transmission of sensed information. Long distance transmission by sensor nodes is not energy efficient since energy consumption is a superlinear function of the transmission distance. One approach to prolonging network lifetime while preserving network connectivity is to deploy a small number of costly, but more powerful, relay nodes whose main task is communication with other sensor or relay nodes. In this paper, we assume that sensor nodes have communication range r> 0, while relay nodes have communication range R\geq r, and we study two versions of relay node placement problems. In the first version, we want to deploy the minimum number of relay nodes so that, between each pair of sensor nodes, there is a connecting path consisting of relay and/or sensor nodes. In the second version, we want to deploy the minimum number of relay nodes so that, between each pair of sensor nodes, there is a connecting path consisting solely of relay nodes. We present a polynomial time 7-approximation algorithm for the first problem and a polynomial time (5 + \epsilon){\hbox{-}}\rm approximation algorithm for the second problem, where \epsilon> 0 can be any given constant.
An Agent-Based Approach to Grid Service Monitoring
Authors: Keith Rochford, Brian Coghlan, John Walsh
Venue: Proceedings of the Proceedings of The Fifth International Symposium on Parallel and Distributed Computing (2006)

The centralised management of distributed computing infrastructures presents a number of considerable challenges, not least of which is the effective monitoring of physical resources and middleware components to provide an accurate operational picture for use by administrative or management staff. The detection and presentation of real-time information pertaining to the performance and availability of computing resources is a difficult yet critical activity. This architecture is intended to enhance the service monitoring experience of a Grid operations team. We have designed and implemented an extensible agent-based architecture capable of detecting and aggregating status information using low-level sensors, functionality tests and existing information systems. To date it has been successfully deployed across eighteen Grid- Ireland sites.
Grasping the Intentions of Others: The Perceived Intentionality of an Action Influences Activity in the Superior Temporal Sulcus during Social Perception
Authors: Kevin A. Pelphrey, James P. Morris, Gregory Mccarthy
Venue: Journal of Cognitive Neuroscience (2004)

An explication of the neural substrates for social perception is an important component in the emerging field of social cognitive neuroscience and is relevant to the field of cognitive neuroscience as a whole. Prior studies from our laboratory have demonstrated that passive viewing of biological motion (Pelphrey, Mitchell, et al., 2003; Puce et al., 1998) activates the posterior superior temporal sulcus (STS ) region. Furthermore, recent evidence has shown that the perceived context of observed gaze shifts (Pelphrey, Singerman, et al., 2003; Pelphrey et al., 2004) modulates STS activity. Here, using event-related functional magnetic resonance imaging at 4 T, we investigated brain activity in response to passive viewing of goal- and nongoal-directed reaching-to-grasp movements. Participants viewed an animated character making reaching-to-grasp movements either toward (correct) or away (incorrect) from a blinking dial. Both conditions evoked significant posterior STS activity that was strongly right lateralized. By examining the time course of the blood oxygenation level-dependent response from areas of activation, we observed a functional dissociation. Incorrect trials evoked significantly greater activity in the STS than did correct trials, while an area posterior and inferior to the STS (likely corresponding to the MT/ V5 complex) responded equally to correct and incorrect movements. Parietal cortical regions, including the superior parietal lobule and the anterior intraparietal sulcus, also responded equally to correct and incorrect movements, but showed evidence for differential responding based on the hand and arm (left or right) of the animated character used to make the reaching-to-grasp movement. The results of this study further suggest that a region of the right posterior STS is involved in analyzing the intentions of other people's actions and that activity in this region is sensitive to the context of observed biological motions.