ppxscal/embedding_network huggingface dataset:
(1 + ρ)-Approximation for Selected-Internal Steiner Minimum Tree
Authors: Xianyue Li, Yaochun Huang, Feng Zou, Donghyun Kim, Weili Wu
Venue: Proceedings of the 14th annual international conference on Computing and Combinatorics (2008)

Selected-internal Steiner minimum tree problem is a generalization of original Steiner minimum tree problem. Given a weighted complete graph G = (V,E) with weight function c, and two subsets $R^{'}\subsetneq R\subseteq V$ with |R ¿ R ¿| ¿ 2, selected-internal Steiner minimum tree problem is to find a Steiner minimum tree T of G spanning R such that any leaf of T does not belong to R ¿. In this paper, suppose c is metric, we obtain a (1 + ρ)-approximation algorithm for this problem, where ρ is the best-known approximation ratio for the Steiner minimum tree problem.
Vis-OOMPI: Visual Tool for Automatic Code Generation Based on C++/OOMPI
Authors: Chantana Phongpensri (Chantrapornchai), Thanarat Rungthong
Venue: Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2008)

This work proposes a visual tool called , Vis-OOMPI, which targets to help programmers to write parallel programs. The platform OOMPI is considered in the tool. Since MPI is one of popular APIs in C which are used in parallel programs for message passing, the object concept is incorporated and then becomes OOMPI [5]. The tool helps the beginners in message passing programming and includes some additional concepts with OO supports which is exhibited in OOMPI.
Extended Homeostatic Adaptation: Improving the Link between Internal and Behavioural Stability
Authors: Hiroyuki Iizuka, Ezequiel A. Paolo
Venue: Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats (2008)

This study presents an extended model of homeostatic adaptation designed to exploit the internal dynamics of a neural network in the absence of sensory input. In order to avoid typical convergence to asymptotic states under these conditions plastic changes in the network are induced in evolved neurocontrollers leading to a renewal of dynamics that may favour sensorimotor adaptation. Other measures are taken to avoid loss of internal variability (as caused, for instance, by synaptic strength saturation). The method allows the generation of reliable adaptation to morphological disruptions in a simple simulated vehicle using a homeostatic neurocontroller that has been selected to behave homeostatically while performing the desired behaviour but non-homeostatically in other circumstances. The performance is compared with simple homeostatic neural controllers that have only been selected for a positive link between internal and behavioural stability. The extended homeostatic networks perform much better and are more adaptive to morphological disruptions that have never been experienced before by the agents.
SCTP Performance Issue on Path Delay Differential
Authors: Yuansong Qiao, Enda Fallon, Liam Murphy, John Murphy, Austin Hanley, Xiaosong Zhu, Adrian Matthews, Eoghan Conway, Gregory Hayes
Venue: Proceedings of the 5th international conference on Wired/Wireless Internet Communications (2007)

This paper studies the effect of path delay on SCTP performance. It focuses on the SCTP fast retransmit algorithm and demonstrates that the performance in the current retransmission strategy will degrade acutely when the secondary path delay is less than the primary path delay at a certain level. The performance degradation is due to the disordered SACKs and constant congestion window size during the fast retransmit phase. Some modifications aimed at these problems are proposed and evaluated. This paper also identifies that the cause of the performance degradation in SCTP is a result of the single path configuration oriented design of the current fast retransmit algorithm. Several fast retransmission strategies are evaluated for different path delay and bandwidth configurations.
Structural collapse simulation under consideration of uncertainty - Improvement of numerical efficiency
Authors: Bernd Möller, Martin Liebscher, Karl Schweizerhof, Steffen Mattern, Gunther Blankenhorn
Venue: Computers and Structures (2008)

The focus in this paper is set on the improvement of the numerical efficiency of a fuzzy stochastic structural collapse simulation. The deterministic computation is performed with an FE-model taking into account large deformations, contact phenomena and non-linear behavior of the material. Structural parameters have to be specified on the basis of rare, vague and imprecise information. This is taken into account with the aid of uncertainty model fuzzy randomness. A substantial reduction of the computational effort is achieved by approximating structural responses with a neural network following the response surface methodology. The improved fuzzy stochastic analysis of a structural collapse is demonstrated by a moderate complex structural collapse example.
Developing Motivating Collaborative Learning Through Participatory Simulations
Authors: Gustavo Zurita, Nelson Baloian, Felipe Baytelman, Antonio Farias
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

Participatory simulations are collaborative group learning activities whose goals are to improve teaching and learning, increasing motivation inside the classroom by engaging the learner in games simulating a certain system they have to learn about. It has been already applied to students of primary and secondary educational levels, however there are still not experiences reported with higher level students, although there are many learning subjects to which this technique can be applied. This paper presents the implementation of a framework-like tool for supporting learning activities in a business school with undergraduate students using mobile devices over an ad-hoc network.
Creating and Testing Textbooks for Secondary Schools
Authors: Karin Freiermuth, Juraj Hromkovič, Björn Steffen
Venue: Proceedings of the 3rd international conference on Informatics in Secondary Schools - Evolution and Perspectives: Informatics Education - Supporting Computational Thinking (2008)

The main goal of this paper is to present our approach for writing textbooks that are self-contained and available for individual learning. These texts are written in the language of the corresponding pupils and are not restricted by any length limitations. This allows us to write as clearly and thoroughly as possible. Minimizing the time for mastering the subject instead of minimizing the presentation length is the main goal. The detailed lecture notes provide a safety net for the teacher and the pupils alike. They do not restrict teachers in their interaction with the class or in the freedom of choosing alternative ways in approaching the subject. On the contrary, the freedom of designing the content of the lesson increases because pupils have the certainty to be able to learn from the lecture notes if something was not fully understood.Here some general rules for writing learning aids are presented and then applied for an introductory course about programming in LOGO. Finally, we summarize our teaching experience in different classes with the produced learning aids.
Extended Formula Normalization for ε-Retrieval and Sharing of Mathematical Knowledge
Authors: Immanuel Normann, Michael Kohlhase
Venue: Proceedings of the 14th symposium on Towards Mechanized Mathematical Assistants: 6th International Conference (2007)

Even though only a tiny fraction of mathematical knowledge is available digitally (e.g in theorem prover or computer algebra libraries, in documents with content-markup), our current retrieval methods are already inadequate. With further increase in digitalization of mathematics the situation will get worse without significant advances.When searching a formula, we often want to find not only structurally identical occurrences, but also all (logically) equivalent ones. Furthermore, we want to retrieve whole mathematical theories (i.e. objects with prescribed properties), and we want to find them irrespective of the nomenclature chosen in the respective formalization.In this paper, we propose a normalization-based approach to mathematical formula and theory retrieval modulo an equivalence theory and concept renaming, and apply the proposed algorithm to end-user querying and knowledge sharing. We test the implementation by applying it to a first-order translation of the Mizar library.
Hiding I/O latency with pre-execution prefetching for parallel applications
Authors: Yong Chen, Surendra Byna, Xian-He Sun, Rajeev Thakur, William Gropp
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

Parallel applications are usually able to achieve high computational performance but suffer from large latency in I/O accesses. I/O prefetching is an effective solution for masking the latency. Most of existing I/O prefetching techniques, however, are conservative and their effectiveness is limited by low accuracy and coverage. As the processor-I/O performance gap has been increasing rapidly, data-access delay has become a dominant performance bottleneck. We argue that it is time to revisit the "I/O wall" problem and trade the excessive computing power with data-access speed. We propose a novel pre-execution approach for masking I/O latency. We describe the pre-execution I/O prefetching framework, the pre-execution thread construction methodology, the underlying library support, and the prototype implementation in the ROMIO MPI-IO implementation in MPICH2. Preliminary experiments show that the pre-execution approach is promising in reducing I/O access latency and has real potential.
A hardware processing unit for point sets
Authors: Simon Heinzle, Gaël Guennebaud, Mario Botsch, Markus Gross
Venue: Proceedings of the 23rd ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware (2008)

We present a hardware architecture and processing unit for point sampled data. Our design is focused on fundamental and computationally expensive operations on point sets including k-nearest neighbors search, moving least squares approximation, and others. Our architecture includes a configurable processing module allowing users to implement custom operators and to run them directly on the chip. A key component of our design is the spatial search unit based on a kd-tree performing both kNN and &epsilon;N searches. It utilizes stack recursions and features a novel advanced caching mechanism allowing direct reuse of previously computed neighborhoods for spatially coherent queries. In our FPGA prototype, both modules are multi-threaded, exploit full hardware parallelism, and utilize a fixed-function data path and control logic for maximum throughput and minimum chip surface. A detailed analysis demonstrates the performance and versatility of our design.
Image Guidance for Robotic Minimally Invasive Coronary Artery Bypass
Authors: Michael Figl, Daniel Rueckert, David Hawkes, Roberto Casula, Mingxing Hu, Ose Pedro, Dong Ping Zhang, Graeme Penney, Fernando Bello, Philip Edwards
Venue: Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality (2008)

A novel system for image guidance in totally endoscopic coronary artery bypass (TECAB) is presented. Key requirement is the availability of 2D-3D registration techniques that can deal with non-rigid motion and deformation. Image guidance for TECAB is mainly required before the mechanical stabilization of the heart, thus the most dominant source of non-rigid deformation is the motion of the beating heart.To augment the images in the endoscope of the da Vinci robot, we have to find the transformation from the coordinate system of the preoperative imaging modality to the system of the endoscopic cameras.In a first step we build a 4D motion model of the beating heart. Intraoperatively we can use the ECG or video processing to determine the phase of the cardiac cycle. We can then take the heart surface from the motion model and register it to the stereo-endoscopic images of the da Vinci robot using 2D-3D registration methods. We are investigating robust feature tracking and intensity-based methods for this purpose.Images of the vessels available in the preoperative coordinate system can then be transformed to the camera system and projected into the calibrated endoscope view using two video mixers with chroma keying. It is hoped that the augmented view can improve the efficiency of TECAB surgery and reduce the conversion rate to more conventional procedures.
Evaluation of QoS-Based Web Service Matchmaking Algorithms
Authors: Kyriakos Kritikos, Dimitris Plexousakis
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

Web Service (WS) discovery is a prerequisite for achieving WS composition and orchestration. Although a lot of research has been conducted on the functional discovery of WSs, the proposed techniques fall short when faced with the foreseen increase in the number of (potentially functionally-equivalent) WSs. The above situation can be resolved with the addition of non-functional (Quality of Service (QoS)) discovery mechanisms to WS discovery engines. QoS-based WS matchmaking algorithms have been devised for this reason. However, they are either slow - as they are based on ontology reasoners - or produce inaccurate results. Inaccuracy is caused both by the syntactic matching of QoS concepts and by wrong matchmaking metrics. In this paper, we present two Constraint Programming (CP) QoS-based WS discovery algorithms for unary constrained WS specifications that produce accurate results with good performance. We also evaluate these algorithms on matchmaking time, precision and recall in different settings in order to demonstrate their efficiency and accuracy.
The University of Manchester computing machine
Authors: F. C. Williams, T. Kilburn
Venue: Papers and discussions presented at the Dec. 10-12, 1951, joint AIEE-IRE computer conference: Review of electronic digital computers (1951)

The computing machine which now is operating at the University of Manchester, represents the culmination of a research project of several years' standing. It seems appropriate to outline the various steps in the development of this project, since these have given the final machine its major characteristics.
From Pixels to Semantic Spaces: Advances in Content-Based Image Retrieval
Authors: Nuno Vasconcelos
Venue: Computer (2007)

The image retrieval paradigm has evolved from low-level image representations to semantic concept models to higher-level semantic inferences. UCSD's Statistical Visual Computing Laboratory has developed effective techniques for each paradigm that equate retrieval with classification and strive for minimum-probability-of-error optimality.
An In-Field-Maintenance Framework for Wireless Sensor Networks
Authors: Qiuhua Cao, John A. Stankovic
Venue: Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems (2008)

This paper introduces a framework for in-field-maintenance services for wireless sensor networks. The motivation of this work is driven by an observation that many applications using wireless sensor networks require one-time deployment and will be largely unattended. It is also desirable for the applications to have a long system lifetime. However, the performance of many individual protocols and the overall performance of the system deteriorate over time. The framework we present here allows the system or each individual node in the network to identify the performance degradation, and to act to bring the system back to a desirable coherent state. We implement and apply our framework to a case study for a real system, called VigilNet [5]. The performance evaluation demonstrates that our framework is effective and efficient.
A Rough Set Based Map Granule
Authors: Sumalee Sonamthiang, Nick Cercone, Kanlaya Naruedomkul
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

Data in an information system are usually represented and stored in a flat and unconnected structure as in a table. Underlying the data structure, there is a domain concept that is an understandable description for humans and supports other machine learning techniques. In this work, Map Granule (MG) construction is introduced. A MG comprises of multilevel granules with their hierarchy relations. We propose a rough set based granular computing to induce approximation of a domain concept hierarchy of an information system. An algorithm is proposed to select a sequence of attribute subsets which is necessary to partition a granularity hierarchically. In each level of granulation, reducts and core are applied to retain the specific concepts of a granule whereas common attributes are applied to exclude the common knowledge and generate a more general concept. The information granule relations are represented by a tree structure in which the relation strengths are defined by a rough ratio of specificness/coarseness.
Multivariate distribution of returns in financial time series
Authors: M. I. Krivoruchenko, E. Alessio, V. Frappietro, L. J. Streckert
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

Multivariate probability density functions of returns are constructed in order to model the empirical behavior of returns in a financial time series. They describe the well-established deviations from the Gaussian random walk, such as an approximate scaling and heavy tails of the return distributions, long-ranged volatility-volatility correlations (volatility clustering) and return-volatility correlations (leverage effect). Free parameters of the model are fixed over the long term by fitting 100+ years of daily prices of the Dow Jones 30 Industrial Average. The multivariate probability density functions which we have constructed can be used for pricing derivative securities and risk management.
Reflective Middleware: From Your Desk to Your Hand
Authors: Manuel Roman, Fabio Kon, Roy H. Campbell
Venue: IEEE Distributed Systems Online (2001)

Middleware has emerged as an important architectural component in modern distributedsystems. Its role is to offer users a high-level, platform-independent programming model(object-oriented or component-based) and to hide problems of distribution. Examples of keymiddleware platforms include CORBA, DCOM, .NET, and the Java-based series of technologies (RMI, Jini, and EJB).
The Computer Aversion, Attitudes, and Familiarity Index (CAAFI): A validity study
Authors: Stefan E. Schulenberg, Amanda M. A. Melton
Venue: Computers in Human Behavior (2008)

This study's purpose was to provide additional psychometric data on the Computer Aversion, Attitudes, and Familiarity Index (CAAFI). The CAAFI is comprised of 40 items, yielding a total score and four factor scores with 10 items each (one familiarity, one attitudes, two aversion). The measure was administered to a sample of undergraduate psychology students (N=293) along with the Computer Understanding and Experience Scale, the Computer Attitude Scale, and the Computer Aversion Scale. The factor structure of the CAAFI was supported via confirmatory factor analytic procedures and analysis of internal consistency reliability coefficients. In relation to the other measures of computer-related constructs, the strongest validity support was found for the CAAFI total score and Factors 1 (computer familiarity) and 3 (computer aversion-discomfort), followed by Factor 2 (computer attitudes). With regard to Factor 4 (computer aversion-fear), given the results of the analyses the decision was made to remove these items from the CAAFI in order to enhance the measure's psychometric properties and practical utility.
Solving the Problem of Trans-Genomic Query with Alignment Tables
Authors: Douglass Stott Parker, Ruey-Lung Hsiao, Yi Xing, Alissa M. Resch, Christopher J. Lee
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2008)

The trans-genomic query (TGQ) problem -- enabling the free query of biological information, even across genomes -- is a central challenge facing bioinformatics. Solutions to this problem can alter the nature of the field, moving it beyond the jungle of data integration and expanding the number and scope of questions that can be answered.An alignment table is a binary relationship on locations (sequence segments). An important special case of alignment tables are hit tables ? tables of pairs of highly similar segments produced by alignment tools like BLAST. However, alignment tables also include general binary relationships, and can represent any useful connection between sequence locations. They can be curated, and provide a high-quality queryable backbone of connections between biological information. Alignment tables thus can be a natural foundation for TGQ, as they permit a central part of the TGQ problem to be reduced to purely technical problems involving tables of locations.Key challenges in implementing alignment tables include efficient representation and indexing of sequence locations. We define a location datatype that can be incorporated naturally into common off-the-shelf database systems. We also describe an implementation of alignment tables in BLASTGRES, an extension of the open-source POSTGRESQL database system that provides indexing and operators on locations required for querying alignment tables.This paper also reviews several successful large-scale applications of alignment tables for Trans-Genomic Query. Tables with millions of alignments have been used in queries about alternative splicing, an area of genomic analysis concerning the way in which a single gene can yield multiple transcripts. Comparative genomics is a large potential application area for TGQ and alignment tables.
On Computing Mobile Agent Routes for Data Fusion in Distributed Sensor Networks
Authors: Qishi Wu, Nageswara S. V. Rao, Jacob Barhen, S. Sitharama Iyengar, Vijay K. Vaishnavi, Hairong Qi, Krishnendu Chakrabarty
Venue: IEEE Transactions on Knowledge and Data Engineering (2004)

The problem of computing a route for a mobile agent that incrementally fuses the data as it visits the nodes in a distributed sensor network is considered. The order of nodes visited along the route has a significant impact on the quality and cost of fused data, which, in turn, impacts the main objective of the sensor network, such as target classification or tracking. We present a simplified analytical model for a distributed sensor network and formulate the route computation problem in terms of maximizing an objective function, which is directly proportional to the received signal strength and inversely proportional to the path loss and energy consumption. We show this problem to be NP-complete and propose a genetic algorithm to compute an approximate solution by suitably employing a two-level encoding scheme and genetic operators tailored to the objective function. We present simulation results for networks with different node sizes and sensor distributions, which demonstrate the superior performance of our algorithm over two existing heuristics, namely, local closest first and global closest first methods.