ppxscal/embedding_network huggingface dataset:
Implementing time-varying contour trees
Authors: Ajith Mascarenhas, Jack Snoeyink
Venue: Proceedings of the twenty-first annual symposium on Computational geometry (2005)

In this video, we describe our experiences in implementing an algo-rithm to compute time-varying contour trees and highlight the chal-lenges in applying this algorithm to real-world scientific datasets. For ease of illustration we restrict our explanations to contour trees of time-varying functions defined on the plane.
GUARD: Gossip Used for Autonomous Resource Detection
Authors: Sagnik Nandy, Larry Carter, Jeanne Ferrante
Venue: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01 (2005)

A growing trend in the development and deployent of grid computing systems is decentralization. Decentralizing these systems helps make the ore scalable and robust, but poses several challenges. In this paper we address one such proble - that of locating computing resources meeting specified requirements in a large scale heterogenous system. The heterogeneous and dynaic nature, coupled with the ultiple occurrences of these resources, makes the problem distinct from traditional data location problems found inthe context of content-sharing systems. We propose GUARD (Gossip Used for Autonomous Resource Detection), a protocol that uses gossiping between neighbors to propagate the current knowledge of distances from available resources. GUARD is autonomous (alldecisions are made locally, using knowledge based only on interaction with imediate neighbors) and does not make any assumptions about the underlying network topology. Our siulations show GUARD is ore efficient than other techniques such as random routing, history-based routing and frequency-based routing that have been used for similar purposes. We also show how GUARD can be odified to locateultiple categories of resources meeting multiple criteria.
Specific ergodicity: an informative indicator for invertible computational media
Authors: Tommaso Toffoli, Lev B. Levitin
Venue: Proceedings of the 2nd conference on Computing frontiers (2005)

Specific ergodicity asks, for an invertible cellular automaton, lattice gas, or similar indefinitely-extended computational medium, what fraction of the information needed to specify an individual state is still missing after one is told the computational trajectory to which that state belongs. While the well-known distinction between "ergodic" and "nonergodic" for a dynamical system is an all-or-nothing classification, specific ergodicity---with range in the [0,1] interval---provides a continuous parameter which may be interpreted as "degree of ergodicity." Moreover, while the property of a system's being ergodic can only refer to the system as a whole, specific ergodicity is an intensive quantity (ie it factors out the size of the system); thus, for a spatially-distributed, homogeneous computational system such as a cellular automaton or a lattice gas, in the limit of infinite system size this quantity reflects an intrinsic property of the material that makes up the computational medium, abstracting from its specific size or shapeWe provide the conceptual background, present theoretical and numerical results, and discuss the relevance of specific ergodicity to a number of concrete research questions.Values of specific ergodicity for a variety of systems of actual interest turn out to be well distributed over its entire range; in this sense, this quantity is an informative indicator. Indeed, besides representing a useful parameter in the classification of distributed computational media, specific ergodicity provides a "sense of direction" in issues such as protection from noise, design of self-organizing media, necessary conditions for the emergence and persistence of life, effectiveness of a parallel architecture as a "programmable medium," and a number of topics in nanotechnology
Linking Micro- to Macro-level Behavior in the Aggressor-Defender-Stalker Game
Authors: Carl Anderson
Venue: Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems (2004)

In many multiagent systems, small changes in individual-level rules may lead to very large changes at the group-level. This phenomenon is striking in the "aggressor-defender game," a simple participative game in which each participant randomly selects two others from the group (A and B). In the aggressor game, everyone tries to position themselves so that A is always between themselves and B. In the defender game everyone tries to position themselves between A and B. Despite these exceedingly simple rules and the seemingly small difference between them, the two games exhibit very different dynamics. The aggressor game produces a highly dynamic group that rapidly expands over time whereas the defender game quickly collapses to a tight knot. I analyze these games and provide some insight as to how these two group level behaviors arise, thereby linking the micro- and macro-levels. I also introduce and analyze a new, related and simpler game, the stalker game, in which each participant selects and pursues a single participant, and which also produces a collapsing group. It is suggested that such a geometrical analysis may be applicable for other multiagent systems such as insect societies and collective robotics.
Decision support queries on a tape-resident data warehouse
Authors: Damianos Chatziantoniou, Theodore Johnson
Venue: Information Systems (2005)

Data warehouses collect masses of operational data, allowing analysts to extract information by issuing decision support queries on the otherwise discarded data. In many application areas (e.g. telecommunications), the warehoused data sets are multiple terabytes in size. Parts of these data sets are stored on very large disk arrays, while the remainder is stored on tape-based tertiary storage (which is one to two orders of magnitude less expensive than on-line storage). However, the inherently sequential nature of access to tape-based tertiary storage makes the efficient access to tape-resident data difficult to accomplish through conventional databases.In this paper, we present a way to make access to a massive tape-resident data warehouse easy and efficient. Ad hoc decision support queries usually involve large scale and complex aggregation over the detail data. These queries are difficult to express in SQL, and frequently require self-joins on the detail data (which are prohibitively expensive on the disk-resident data and infeasible to compute on tape-resident data), or unnecessary multiple passes through the detail data. An extension to SQL, the extended multi feature SQL (EMF SQL) expresses complex aggregation computations in a clear manner without using self-joins. The detail data in a data warehouse usually represents a record of past activities, and therefore is temporal. We show that complex queries involving sequences can be easily expressed in EMF SQL. An EMF SQL query can be optimized to minimize the number of passes through the detail data required to evaluate the query, in many cases to only one pass. We describe an efficient query evaluation algorithm along with a query optimization algorithm that minimizes the number of passes through the detail data, and which minimizes the amount of main memory required to evaluate the query. These algorithms are useful not only in the context of tape-resident data warehouses but also in data stream systems which require similar processing techniques.
Using Facial Images to Diagnose Fetal Alcohol Syndrome (FAS)
Authors: Jeffrey Huang, Amit Jain, Shiaofen Fang, Edward P. Riley
Venue: Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02 (2005)

This paper proposes the methodology of classification architectures for FAS diagnosis tasks and shows their feasibility through experimental studies. We describe the automatic selection of features from an image training set using the theories of multidimensional discriminant analysis and the associated optimal linear projection. The method consists of two steps: projection of face image from the original vector space to a face subspace via PCA, and then use of LDA to obtain a linear classifier. This hybrid classifier using PCA and LDA provides an effective framework for classification of FAS images as FAS-positive and FAS-negative.
A Mobile Climbing Robot for High Precision Manufacture and Inspection of Aerostructures
Authors: T. S. White, R. Alexander, G. Callow, A. Cooke, S. Harris, J. Sargent
Venue: International Journal of Robotics Research (2005)

In this paper we describe the design, development, and experimental trials of a climbing robot for manufacturing and inspection applications within the aerospace industry. We describe the mechanical platform, which utilizes vacuum for attachment to vertical and overhanging surfaces, and a traction system that enables rapid movement of the robot over planar and curved surfaces of any orientation. The main applications considered during the research were the manufacturing processes for large external surface structures such as wings and the post-manufacturing and in-service inspection of such structures. The design of suitable tool packages for manufacturing and non-destructive testing is considered in the paper. The first tool package to be implemented and tested was a five-axis high precision drill, which is described. The control system is described within this paper along with the software architecture. The software architecture for the robot was generalized, allowing different robot configurations to be described and implemented rapidly through structured configuration files. Particular attention is paid to the robot's localization and navigation system, which provides tool point precision to aircraft manufacturing tolerances. The localization system uses data from several different types of sensors and combines these with information provided by a surface model to derive six-degrees-of-freedom position and orientation using an extended Kalman filter to fuse the state information from the different sources. Tool point position is calculated through direct kinematic transformations. Improvements to this work are described, which utilize one of the initial releases of Lieca's new six-degrees-of-freedom precision measurement instruments, the Lieca LTD-800. We also summarize the experimental trials and the initial performance in terms of tool point precision and climbing performance. The concept of application of the robot and details of the technologies included in the robot that are outlined in this paper are the subject of separate pending patent applications filed by BAE SYSTEMS plc.
Computer Vision for Music Identification
Authors: Yan Ke, Derek Hoiem, Rahul Sukthankar
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01 (2005)

We describe how certain tasks in the audio domain can be effectively addressed using computer vision approaches. This paper focuses on the problem of music identification, where the goal is to reliably identify a song given a few seconds of noisy audio. Our approach treats the spectrogram of each music clip as a 2-D image and transforms music identification into a corrupted sub-image retrieval problem. By employing pairwise boosting on a large set of Viola-Jones features, our system learns compact, discriminative, local descriptors that are amenable to efficient indexing. During the query phase, we retrieve the set of song snippets that locally match the noisy sample and employ geometric verification in conjunction with an EM-based "occlusion" model to identify the song that is most consistent with the observed signal. We have implemented our algorithm in a practical system that can quickly and accurately recognize music from short audio samples in the presence of distortions such as poor recording quality andsignificant ambient noise. Our experiments demonstrate that this approach significantly outperforms the current state-of-the-art in content-based music identification.
The affects of different queuing disciplines over FTP, video and VoIP performance
Authors: Mitko Gospodinov
Venue: Proceedings of the 5th international conference on Computer systems and technologies (2004)

The objective of the paper is presentation of research the affects of different queuing disciplines on packet delivery for three applications: FTP, Video and VoIP. For modelling, simulation and analysing on these applications is used OPNET (Optimised Network Engineering Tool) environment. In the paper is investigated how the choice of the queuing discipline can affect the applications and utilization of the network resources in the routers.
TCP Congestion Control Approach for Improving Network Services
Authors: A. M. Al-Naamany, H. Bourdoucen
Venue: Journal of Network and Systems Management (2005)

With the continuous increasing demand of Internet applications, networks are experiencing a serious congestion problem. This affects directly the networks' services and management due to large amounts of data loss and long transmission delays. The present work suggests an improved networking congestion control approach for TCP using fuzzy logic. Its main objective is to use packet drop information to improve network services by optimizing data throughput and smoothing data transfer profiles.
Parallel-hierarchical neural network for 3D object recognition
Authors: Noriaki Sato, Masafumi Hagiwara
Venue: Systems and Computers in Japan (2004)

In this paper, the authors propose a parallel-hierarchical neural network that can recognize multiple 3D objects from 2D projection images. The proposed network focuses on a parallel-hierarchical structure and memory-based recognition assistance, which are characteristics of the excellent vision systems that living organisms have, and refers to the neocognitron, which models the parallel-hierarchical structure of vision systems. The amount of calculations is reduced by deleting cells having a low degree of importance based on competition between cells and detecting features that differ for each cell. The network not only can recognize an object, but can also estimate its orientation at the same time. The memory-based recognition assistance is modeled by performing iterative processing during which the input image approaches a learning image based on the orientation estimation result. Weights are determined by sequentially presenting learning images, and no teaching signal is necessary. This is done in a short time since it is not an iterative learning method. The network performance was evaluated by using five objects from COIL-100. Images that were obtained by photographing each object after it was rotated 60&deg; at a time around the vertical axis were used for the learning images. The experiments checked the recognition rates for various 2D projection images that were obtained from the 3D objects. These results verified the effectiveness of the proposed neural network as a 3D object recognition technique. &copy; 2003 Wiley Periodicals, Inc. Syst Comp Jpn, 35(1): 1&ndash;12, 2004; Published online in Wiley InterScience (). DOI 10.1002&sol;scj.10579
Optimization objectives and models of variation for statistical gate sizing
Authors: Matthew R. Guthaus, Natesan Venkateswaran, Vladimir Zolotov, Dennis Sylvester, Richard B. Brown
Venue: Proceedings of the 15th ACM Great Lakes symposium on VLSI (2005)

This paper approaches statistical optimization by examining gate delay variation models and optimization objectives. Most previous work on statistical optimization has focused exclusively on the optimization algorithms without considering the effects of the variation models and objective functions. This work empirically derives a simple variation model that is then used to optimize for robustness. Optimal results from example circuits used to study the effect of the statistical objective function on parametric yield.
CLICKS: Mining Subspace Clusters in Categorical Data via K-Partite Maximal Cliques
Authors: Mohammed J. Zaki, Markus Peters
Venue: Proceedings of the 21st International Conference on Data Engineering (2005)

We present a novel algorithm called CLICKS, that finds clusters in categorical datasets based on a search for k-partite maximal cliques. Unlike previous methods, CLICKS mines subspace clusters. It uses a selective vertical method to guarantee complete search. CLICKS outperforms previous approaches by over an order of magnitude and scales better than any of the existing method for high-dimensional datasets. We demonstrate this improvement in an excerpt from our comprehensive performance studies.
Supporting and changing practices of nested and overlapping educational communities
Authors: Daniel Suthers, Violet Harada, Joyce Yukawa, Viil Lid
Venue: ACM SIGGROUP Bulletin (2003)

Applications of information technology to support systemic reform in public school systems have taken several forms. Instructional applications include attempts to more effectively convey information to students, to empower students' own agency in accessing information and constructing knowledge, and to aid teachers' classroom management, lesson preparation, and assessment. Technology has been proffered as a change agent in itself: teachers will need to change their practices in order to use technologies designed for doing authentic inquiry and communicating or collaborating with others [10]. Information technology can also support professional development through access to online courses, and enable participation in distributed communities of practice. The work reported in this paper has taken this latter strategy. Because today's school systems operate in an environment of constant change, professional development requires a paradigm shift from a scripted training approach to a more fluid approach that encourages the incorporation of networks, coalitions, and partnerships. The capacity to network with other professionals is essential to the notion of communities of practice. McLaughlin and Mitra argue that sustaining large-scale theory-based reform efforts "requires a community of practice to provide support, deflect challenges from the broader environment, and furnish the feedback and encouragement essential to going deeper" [7]. Barab defines a community that advances ongoing and open-ended professional development as a "persistent, sustained network of individuals who share and develop an overlapping knowledge base, set of beliefs, values, history and experiences focused on a common practice and/or mutual enterprise" [1]. These communities change the relationships among teachers, breaking the isolation that most teachers have found so confining.
Multi-Scale Analysis of Connectivity for Image Retrieval
Authors: Atul Sajjanhar, Guojun Lu, Dengsheng Zhang
Venue: Proceedings of the Third International Conference on Image and Graphics (2004)

Previously, we proposed the concept of connectivity to obtain discriminating shape descriptors. In this paper, we use connectivity to obtain superior distance histograms for multi-scale images. Experiments are performed to evaluate distance histograms, based on connectivity, for shape-based retrieval of multi-scale images. Item S8 within the MPEG-7 Still Images Content Set is used for performing experiments. Experimental results show that the proposed method enhances retrieval performance significantly.
Large-scale circuit placement
Authors: Jason Cong, Joseph R. Shinnerl, Min Xie, Tim Kong, Xin Yuan
Venue: ACM Transactions on Design Automation of Electronic Systems (TODAES) (2005)

Placement is one of the most important steps in the RTL-to-GDSII synthesis process, as it directly defines the interconnects, which have become the bottleneck in circuit and system performance in deep submicron technologies. The placement problem has been studied extensively in the past 30 years. However, recent studies show that existing placement solutions are surprisingly far from optimal. The first part of this tutorial summarizes results from recent optimality and scalability studies of existing placement tools. These studies show that the results of leading placement tools from both industry and academia may be up to 50&percent; to 150&percent; away from optimal in total wirelength. If such a gap can be closed, the corresponding performance improvement will be equivalent to several technology-generation advancements. The second part of the tutorial highlights the recent progress on large-scale circuit placement, including techniques for wirelength minimization, routability optimization, and performance optimization.
Book review: Combinatorics, Set Systems, Hypergraphs, Families of Vectors and Combinatorial Probability by B. Bollobas (Cambridge University Press)
Venue: Issue 101 (July 1987) (1987)

Can the distinct strengths of logic programming and functional programming be combined into a unified computational model? How can logic languages be extended to include functions and equations? The fourteen papers in this collection address these issues together with their underlying theory and semantics. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Interaction in 4-second bursts: the fragmented nature of attentional resources in mobile HCI
Authors: Antti Oulasvirta, Sakari Tamminen, Virpi Roto, Jaana Kuorelahti
Venue: Proceedings of the SIGCHI conference on Human factors in computing systems (2005)

When on the move, cognitive resources are reserved partly for passively monitoring and reacting to contexts and events, and partly for actively constructing them. The Re-source Competition Framework (RCF), building on the Multiple Resources Theory, explains how psychosocial tasks typical of mobile situations compete for cognitive resources and then suggests that this leads to the depletion of resources for task interaction and eventually results in the breakdown of fluent interaction. RCF predictions were tested in a semi-naturalistic field study measuring attention during the performance of assigned Web search tasks on mobile phone while moving through nine varied but typical urban situations. Notably, we discovered up to eight-fold differentials between micro-level measurements of atten-tional resource fragmentation, for example from spans of over 16 seconds in a laboratory condition dropping to bursts of just a few seconds in difficult mobile situations. By cali-brating perceptual sampling, reducing resources from tasks of secondary importance, and resisting the impulse to switch tasks before finalization, participants compensated for the resource depletion. The findings are compared to previous studies in office contexts. The work is valuable in many areas of HCI dealing with mobility.
Reason 3 Overdrive!
Authors: Christopher Lee Martin
Venue:  (2005)

Coverage includes- C.L. Martin, also known as Bodhisattva 13:20, is an award-winning electronic musician with several global releases and a full-length album. He is a composer and compiler for Truffle Records, and has provided tracks for two independent films. He runs an event-production crew, a monthly club, and is a full-time college student with a 4.0 GPA working toward a degree in Advanced Geology. "Cuts to the chase" and provides many helpful power tips for experienced users of the application. The author, an award-winning electronic musician and a Reason expert, offers his advanced knowledge to help readers get to the next step. As Reason is a cross-platform application, this is written to suit both PC and Mac users. The format's nonlinear approach means that readers don't have to sit down and read it from cover to cover in order to benefit from the book. They can dip in anywhere, pull out a nugget, and immediately apply it to their work...literally in just minutes. Companion Web site offers source files used in the book.