ppxscal/embedding_network huggingface dataset:
Measures of international collaboration in scientific literature: part II
Authors: Abraham Bookstein, Henk Moed, Moshe Yitzahki
Venue: Information Processing and Management: an International Journal (2006)

This paper continues the attempt of Part I to develop a coherent family of measures of influence between classes of documents, for example, language or nationality classes, as indicated by citation choice. In this paper we focus on situations in which there is some ambiguity as to how to assign items to a class. For simplicity, we change our focus from citations to co-authorship patterns, restricting most of our discussion to papers with two authors. Like the earlier paper, we propose very simple models of the citation decision, and base our measures on the parameters that appear in the model.
An Evolutionary-Based Approach for Outage Scheduling of Electrical Distribution Feeders
Authors: J. S. Wu, T. E. Lee, K. S. Lo
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

In this paper, an evolutionary-based approach for the outage scheduling of distribution feeders is proposed with considering multiple objectives. Heuristic rules and genetic algorithm (GA) is integrated to guide the evolutionary search for the problem. A straightforward hybrid coding technique is used for the genes in the GA. With the advantage of the hybrid solution, practical constraints are easily considered in the search process. A practical system is simulated to test the effectiveness of the proposed approach.
Clustering of 3D Spatial Points Using Maximum Likelihood Estimator over Voronoi Tessellations: Study of the Galaxy Distribution in Redshift Space
Authors: Daniel Pizarro, Luis E. Campusano, Roger G. Clowes, Patrizzio Virgili, Nancy Hitschfeld-Kahler, Ilona K. Sochting
Venue: Proceedings of the 3rd International Symposium on Voronoi Diagrams in Science and Engineering (2006)

This paper describes an algorithm based on the 2D approach of Allard & Fraley that uses Voronoi tessellation and a non-parametric maximum likelihood estimator. We have designed a 3D version of this algorithm which detects multiple clusters of points immersed in background noise; its application to the detection of galaxy clusters in redshift space, using the astronomical database of the 2-degree Field Galaxy Redshift Survey, is presented and discussed. Adopting as a benchmark a particular set of catalogued clusters of galaxies, we find that the proposed algorithm recognizes the location of ~ 67% of the clusters. Three variants of the algorithm were assessed to deal with the elongation of the clusters in the radial direction of observation introduced by the astronomical distance indicator; their merits and limitations are discussed. We address separately the detection of the galaxy cluster location and the detection of galaxy cluster members, both of them having an anisotropic space as their search domain. In the case of detection of galaxy cluster members, a second stage of detection was incorporated in order to improve the results.
Improved Anti-collision Scheme for High Speed Identification in RFID System
Authors: Tae-Wook Hwang, Byong-Gyo Lee, Young Soo Kim, Doug Young Suh, Jin Sang Kim
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 2 (2006)

Tag identification time is handled as an important factor because the performance of RFID system is decided by this factor dominantly. To improve this ability, many anti-collision algorithms have been applied on RFID system. ALOHA based anti-collision algorithms are simple and they have superior anticollision ability. But, it has disadvantage that the identification performance grows worse as the collision probability increases rapidly in case the reader recognize multiple tags. The improved framed slotted ALOHA is proposed to solve this problem. The collision probability is reduced and the tag identification speed increases with the proposed method. By the result, the proposed method offers the more efficient identification rate than that of the typical ALOHA method.
String-Matching and Update through Algebraic Signatures in Scalable Distributed Data Structures
Authors: Riad Mokadem, Witold Litwin
Venue: Proceedings of the 17th International Conference on Database and Expert Systems Applications (2006)

Scalable Distributed Data Structures (SDDSs) store large scalable files over a distributed RAM of nodes in a grid or a P2P network. The files scale transparently for the applications. The prototype system, designed by CERIA, experiments with this technology for Wintel multicomputers. The application may manipulate data much faster than on local disks. We present the functions we have put into the prototype we now call SDDS-2004. We improve the searches and updates of records in our SDDS files. An original property of these functions is the use of the algebraic signatures. This technique serves the distributed non-key record search. The search may concern the entire field or a (sub)string. The algebraic properties of the signatures act similarly to hash schemes in [KR87]. In particular, sending a few-byte signature of the searched string alone, suffices for the search. This makes the communication between the SDDS client and server more efficient. It is also more confidential, since the signature in an intercepted message does not disclose the searched string. On the other hand, we use the signatures for the update management. The clients do not need to then to send updates which in fact do not change the stored records. Finally, our signatures help managing the concurrency control. We present our architecture and design choices. Performance measures validate our implementation. It is now available for download in site of CERIA.
Enriching MPEG-7 User Models with Content Metadata
Authors: Harry Agius, Marios C. Angelides
Venue: Proceedings of the First International Workshop on Semantic Media Adaptation and Personalization (2006)

MPEG-7 is an XML-based standard that provides tools for creating rich and structured multimedia content metadata. However, only an extremely limited range of preferences can be specified for user models and multimedia content metadata created by other parts of the standard cannot be fully exploited. This results in a very incomplete mapping of user models to content models. We present an approach to address the problem by representing user models by means of existing MPEG-7 content description tools.
Distributed Mutual exlusion Counter for the Web Server
Authors: Seung Ju Jang
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02 (2006)

This paper suggests the Distributed Mutual Exclusion Counter (WMEC) algorithm and implements it to solve aproblem that is enrolled as a membership at a web system. We use the HTMLfljperText Markup Language) interface to design the web system. In order to connect wrth DB(Data Base), we use the ASP(Active Sewer Pages) inteface. Even though a customer is not a member for certain web sewer, he/she can obtain the same authority as that of a member in the web system. Unique identification is manually assigned to each nonmember customer by the DMEC algorithm. We present the DMEC algorithm for the web sever system. With the "guest" authority it is possible to buy goods as normal membership authority using the DMEC algorithm. The DMEC algorithm treats the counter value. We conduct experiment to conJim that the distributed counter is accurately assigned to each customer by the DMEC algorithm.
Architectural Knowledge in Product Line Engineering: An Industrial Case Stu
Authors: Deepak Dhungana, Rick Rabiser, Paul Grunbacher, Herbert Prahofer, Christian Federspiel, Klaus Lehner
Venue: Proceedings of the 32nd EUROMICRO Conference on Software Engineering and Advanced Applications (2006)

Capturing and sharing architectural knowledge is already a complex endeavor when dealing with conventional software systems for single customers. In product line engineering, however, the situation is even more difficult due to architectural variability and complex relationships between features and technical solution components. In this paper, we present our experiences and approaches taken in eliciting and sharing architectural knowledge for the software product line infrastructure of a company in the plant building domain. An important lesson learned is the necessity of capturing architectural knowledge and making this knowledge available appropriately to various stakeholders in the product line environment.
Improving the Performance of Asynchronous Communication in Long-Distance Delay-Sensitive Networks through the Development of Context-Aware Architectures
Authors: Cathryn Peoples, Gerard Parr, Bryan Scotney, Petre Dini
Venue: Proceedings of the International Conference on Autonomic and Autonomous Systems (2006)

Context-awareness is inherent in anticipated interplanetary missions. Swarm technologies [11] use context-awareness in short-haul networks between components, and long-distance networks allow communication with Earth. However, the propagation delays limit real-time communications, deep space being an environment in which the speed of light becomes a restriction. Therefore, the development of a protocol stack which is adaptive to application requirements and external influences will help to maximise communication synchronicity. As part of a first year doctorate research programme, this paper correlates current stack functionalities with interplanetary application requirements. A redesigned stack proposes to resolve this misalignment. Context-awareness is incorporated, enabling intelligent protocol selection using application layer knowledge and environmental information, with particular attention given to transport protocols. The paper concludes by considering transport protocol characteristics when deployed beside a context-aware layer, with the longterm aim being the development of a transport protocol suitable for deployment in the state-of-theart context-aware stack.
The Production Algorithm of Pseudo-Random Number Generator Based on Compound Non-Linear Chaos System
Authors: Xiao-jun Tong, Ming-gen Cui, Wei Jiang
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

Pseudo-random number generator designs based on the traditional characteristic polynomial and the register slow in speed, and short life cycle. This paper a compound chaos system is designed using the nonlinear Logistic mapping system and the partition mapping. A production algorithm of pseudo-random number generator based on the compound non-linear chaos system is introduced. Theoretical and experimental results show that the random sequences produced by this pseudo-random number generator has good cryptology performance, making the design an ideal pseudo-random number generator. A new chaos stream cipher encryption system is designed based on the algorithm. Experimental results show that this stream cipher is desirable in terms of security, costeffectiveness and pseudo-randomness .
Dominance Attributions Following Damage to the Ventromedial Prefrontal Cortex
Authors: Matthew S. Karafin, Daniel Tranel, Ralph Adolphs
Venue: Journal of Cognitive Neuroscience (2004)

Damage to the human ventromedial prefrontal cortex (VM) can result in dramatic and maladaptive changes in social behavior despite preservation of most other cognitive abilities. One important aspect of social cognition is the ability to detect social dominance, a process of attributing from particular social signals another person's relative standing in the social world. To test the role of the VM in making attributions of social dominance, we designed two experiments: one requiring dominance judgments from static pictures of faces, the second requiring dominance judgments from film clips. We tested three demographically matched groups of subjects: subjects with focal lesions in the VM (n = 15), brain-damaged comparison subjects with lesions excluding the VM (n = 11), and a reference group of normal individuals with no history of neurological disease (n = 32). Contrary to our expectation, we found that subjects with VM lesions gave dominance judgments on both tasks that did not differ significantly from those given by the other groups. Despite their grossly normal performance, however, subjects with VM lesions showed more subtle impairments specifically when judging static faces: They were less discriminative in their dominance judgments, and did not appear to make normal use of gender and age of the faces in forming their judgments. The findings suggest that, in the laboratory tasks we used, damage to the VM does not necessarily impair judgments of social dominance, although it appears to result in alterations in strategy that might translate into behavioral impairments in real life.
Collection-based compound noun segmentation for Korean information retrieval
Authors: In-Su Kang, Seung-Hoon Na, Jong-Hyeok Lee
Venue: Information Retrieval (2006)

Compound noun segmentation is a key first step in language processing for Korean. Thus far, most approaches require some form of human supervision, such as pre-existing dictionaries, segmented compound nouns, or heuristic rules. As a result, they suffer from the unknown word problem, which can be overcome by unsupervised approaches. However, previous unsupervised methods normally do not consider all possible segmentation candidates, and/or rely on character-based segmentation clues such as bi-grams or all-length n-grams. So, they are prone to falling into a local solution. To overcome the problem, this paper proposes an unsupervised segmentation algorithm that searches the most likely segmentation result from all possible segmentation candidates using a word-based segmentation context. As word-based segmentation clues, a dictionary is automatically generated from a corpus. Experiments using three test collections show that our segmentation algorithm is successfully applied to Korean information retrieval, improving a dictionary-based longest-matching algorithm.
Feature-level Fusion for Object Segmentation using Mutual Information
Authors: Vinay Sharma, James W. Davis
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

We present a new feature-level image fusion technique for object segmentation based on mutual information. Using object regions roughly detected from one sensor as input, the proposed technique extracts relevant information from another to complete the segmentation. First, a contourbased feature representation is presented that implicitly captures object shape. The notion of relevance across sensor modalities is then defined using mutual information computed based on the affinity between contour features. Finally a heuristic selection scheme is proposed to identify the set of contour features having the highest mutual information with the input object regions. The approach works directly from the input image pair without relying on a training phase. Results are presented for segmenting people from background, and quantitatively evaluated.
Rapid detection and suppression of multi-user interference in DS-CDMA
Authors: M. L. Honig
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

Minimum mean squared error (MMSE) detection has been proposed for direct sequence-code division multiple access (DS-CDMA) systems. The MMSE detectors are near-far resistant, and can be adapted with standard adaptive algorithms without knowledge of user parameters (i.e., spreading codes). These algorithms rely on a known training sequence for initial adaptation, and subsequently switch to a decision-directed mode. After the switch, the performance of the adaptive algorithm may degrade substantially if a strong interferer suddenly appears (i.e., if power control is relaxed). We present a "rescue" algorithm that monitors for sudden changes in the signal space, which may be caused by the appearance of a strong interferer. If a new interferer is detected, decision-directed adaptation is suspended, and an estimate of the optimal filter coefficients is obtained without a training sequence. It is shown that in the presence of low-level background noise, a good estimate can be obtained within a few symbol intervals. A numerical example is given which illustrates the performance of the rescue algorithm in a synchronous DS-CDMA system.
Database and Narratological Representation of Australian Aboriginal Knowledge as Information Visualisation using a Game Engine.
Authors: Malcolm Pumpa., Theodor G. Wyeld.
Venue: Proceedings of the conference on Information Visualization (2006)

Current database technologies do not support contextualised representations of multi-dimensional narratives. This paper outlines a new approach to this problem using a multi-dimensional database served in a 3D game environment. Preliminary results indicate it is a particularly efficient method for the types of contextualised narratives used by Australian Aboriginal peoples to tell their stories about their traditional landscapes and knowledge practices. We discuss the development of a tool that complements rather than supplants direct experience of these traditional knowledge practices.
A linear time algorithm for optimal tree sibling partitioning and approximation algorithms in Natix
Authors: Carl-Christian Kanne, Guido Moerkotte
Venue: Proceedings of the 32nd international conference on Very large data bases (2006)

Document insertion into a native XML Data Store (XDS) requires to partition the document tree into a number of storage units with limited capacity, such as records on disk pages. As intra partition navigation is much faster than navigation between partitions, minimizing the number of partitions has a beneficial effect on query performance.We present a linear time algorithm to optimally partition an ordered, labeled, weighted tree such that each partition does not exceed a fixed weight limit. Whereas traditionally tree partitioning algorithms only allow child nodes to share a partition with their parent node (i.e. a partition corresponds to a subtree), our algorithm also considers partitions containing several subtrees as long as their roots are adjacent siblings. We call this sibling partitioning.Based on our study of the optimal algorithm, we further introduce two novel, near-optimal heuristics. They are easier to implement, do not need to hold the whole document instance in memory, and require much less runtime than the optimal algorithm.Finally, we provide an experimental study comparing our novel and existing algorithms. One important finding is that compared to partitioning that exclusively considers parent-child partitions, including sibling partitioning as well can decrease the total number of partitions by more than 90%, and improve query performance by more than a factor of two.
The Role of Problem Classification in Online Meta-cognition
Authors: George Alexander, Anita Raja
Venue: Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology (2006)

Agents operating in open environments must be able to adapt their processing to available resources, deadlines, their goal criteria, and their current problem solving contexts. This paper describes the role of meta-cognition in this process; in particular, we define a meta-cognition framework that uses Naive Bayesian classification of the agent's current context in order to represent the meta-level control problem as a Markov Decision Process.
A software retrieval service based on adaptive knowledge-driven agents for wireless environments
Authors: Eduardo Mena, Arantza Illarramendi, Jose A. Royo, Alfredo GoñI
Venue: ACM Transactions on Autonomous and Adaptive Systems (TAAS) (2006)

The ability to retrieve software in an easy and efficient way confers competitive advantage on computer users in general and, even more especially, on users of wireless devices (like some laptops, PDAs, etc.). In this article, we present a software retrieval service that allows users to select and retrieve software in an easy and efficient way, anywhere and anytime. Two relevant components of this service are: 1) a software ontology (software catalog) which provides users with a semantic description of software elements, hiding the location and access method of various software repositories, and 2) a set of specialist agents that allow browsing of the software catalog (automatically customized for each user), and an efficient retrieval method for the selected software. These agents automatically adapt their behavior to different users and situations by considering the profile and preferences of the users and the network status.In summary, our software-obtaining process based on an ontology and autonomous and adaptive agents presents a qualitative advance with respect to existing solutions: our approach adapts to the features of users, relieving them from knowing the technical features of their devices and the location and access method of various remote software repositories.
A framework for visual data mining of structures
Authors: Hans-Jörg Schulz, Thomas Nocke, Heidrun Schumann
Venue: Proceedings of the 29th Australasian Computer Science Conference - Volume 48 (2006)

Visual data mining has been established to effectively analyze large, complex numerical data sets. Especially, the extraction and visualization of inherent structures such as hierarchies and networks has made a signi ffcant leap forward. However, it is still a challenging task for users to explore explicitly given large structures. In this paper, we approach this task by tightly coupling visualization and graph-theoretical methods. Therefore, we investigate if and how visualization can benefft from common graph-theoretical methods - mainly developed for the investigation of social networks - and vice versa. To accomplish this close integration, we introduce a design of a general framework for visual data mining of complex structures. Especially, this design includes an appropriate processing order of different mining and visualization algorithms and their mining results. Furthermore, we discuss some important implementation details of our framework to ensure fast structure processing. Finally, we examine the applicability of the framework for a large real-world data set.
Does more uniformly distributed sampling generally lead to more accurate prediction in computer experiments?
Authors: Longjun Liu, Wayne Wakeland
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Sampling uniformity is one of the central issues for computer experiments or metamodeling. Is it generally true that more uniformly distributed sampling leads to more accurate prediction? A study was conducted to compare four designs for computer experiments, based on simulation tests and statistical analysis. Maximin Latin hypercube design (LHMm) nearly always generated more uniform sampling in two- and three- dimensional cases than does random sampling (Rd), Latin hypercube design (LHD), or Minimized centered L2 discrepancy Latin hypercube design (LHCL2). But often there was no significant difference among the means of the prediction errors by employing LHMm versus the other designs. Occasionally, even the opposite was seen. More uniform sampling did not generally lead to more accurate prediction unless sampling included extremely nonuniform cases, especially when the sample size was relatively small.
Regularized extrapolation of noisy data with a wavelet signal model
Authors: Li-Chien Lin, C.-C. Jay Kuo
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

The bandlimited signal model has been widely used and bandlimited extrapolation has been extensively studied and applied in signal reconstruction. We examine a regularization technique for robust data extrapolation based on the wavelet representation. We first formulate the regularization problem and characterize the properties of its solution. Then, a practical iterative algorithm is proposed to achieve robust extrapolation.