ppxscal/embedding_network huggingface dataset:
Knowledge-Based Road Extraction from High Resolution Remotely Sensed Imagery
Authors: Jing Shen, Xiangguo Lin, Yunfei Shi, Cheng Wong
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Road tracking is a promising technique to increase the efficiency of road mapping. In this paper, a new road tracker, angular texture signature, is proposed based on the knowledge of the roads on high resolution imagery. The tracker uses parabola to model the road trajectory and predict the position of next road centreline point. It employs angular texture signature to get the moving direction of current road centreline point, and move forward one preset step along the direction to reach a new position, and then use curvature change of the parabola to verify the new added road point whether right enough. We also build compactness of angular texture signature polygon to check whether the angular texture signature is suitable for tracking. Extensive experiments demonstrate that our tracker is robust enough to be used to track road on high resolution imagery.
Scientific application-based performance comparison of SGI Altix 4700, IBM POWER5+, and SGI ICE 8200 supercomputers
Authors: Subhash Saini, Dale Talcott, Dennis Jespersen, Jahed Djomehri, Haoqiang Jin, Rupak Biswas
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

The suitability of next-generation high-performance computing systems for petascale simulations will depend on various performance factors attributable to processor, memory, local and global network, and input/output characteristics. In this paper, we evaluate performance of new dual-core SGI Altix 4700, quad-core SGI Altix ICE 8200, and dual-core IBM POWER5+ systems. To measure performance, we used micro-benchmarks from High Performance Computing Challenge (HPCC), NAS Parallel Benchmarks (NPB), and four real-world applications---three from computational fluid dynamics (CFD) and one from climate modeling. We used the micro-benchmarks to develop a controlled understanding of individual system components, then analyzed and interpreted performance of the NPBs and applications. We also explored the hybrid programming model (MPI+OpenMP) using multi-zone NPBs and the CFD application OVERFLOW-2. Achievable application performance is compared across the systems. For the ICE platform, we also investigated the effect of memory bandwidth on performance by testing 1, 2, 4, and 8 cores per node.
Artificial Neural Networks Application to Calculate Parameter Values in the Magnetotelluric Method
Authors: Andrzej Bielecki, Tomasz Danek, Janusz Jagodziński, Marek Wojdyła
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

In this paper a possibility of neural network application to data processing in magnetotelluric method is studied. The modular neural system, consisting of three multi-layer neural networks, is used for obtaining geoelectric model of lithosphere basing on amplitude and phase MT curves. Cases of two and three flat lithosphere layers are considered.
Data Assimilation in Multiscale Chemical Transport Models
Authors: Lin Zhang, Adrian Sandu
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

In this paper we discuss variational data assimilation using the STEM atmospheric Chemical Transport Model. STEM is a multiscale model and can perform air quality simulations and predictions over spatial and temporal scales of different orders of magnitude. To improve the accuracy of model predictions we construct a dynamic data driven application system (DDDAS) by integrating data assimilation techniques with STEM. We illustrate the improvements in STEM field predictions before and after data assimilation. We also compare three popular optimization methods for data assimilation and conclude that L-BFGS method is the best for our model because it requires fewer model runs to recover optimal initial conditions.
Client-Centric Performance Analysis of a High-Availability Cluster
Authors: Jesper Grønbæk, Hans-Peter Frejek, Thibault Renier, Hans-Peter Schwefel
Venue: Proceedings of the 4th international symposium on Service Availability (2007)

High-Availability as provided by fault-tolerance mechanisms comes at the price of increased overhead due to additional processing and communication, which may be a limiting factor to service performance as perceived by the clients. In order to quantify this impact and to understand the underlying mechanisms for performance degradation, this paper presents an approach for the analysis of client-centric performance metrics in cluster-based service deployment scenarios using High-Availability Middleware. The approach is based on a combination of measurement based empiric analysis under synthetically generated load patterns and simple queueing models, that allow for the extrapolation of empiric results and are used to gain insights into the underlying causes of the empiric performance behavior. The empiric and numerical results in the paper are based on an abstracted SIP-like call control service as deployed in future version of IP-based cellular networks, running on a two-node cluster system.
The Effect of LSI Technology on the Theory of Modular Computer Design
Authors: A. D. Friedman
Venue: Computer (1978)

Logic-oriented and computation-oriented approaches to design offer insights into the problems of modularity.
Construction and Application of PSO-SVM Model for Personal Credit Scoring
Authors: Ming-Hui Jiang, Xu-Chuan Yuan
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

The parameters of support vector machine (SVM) are crucial to the model's classification performance. Aiming at the randomicity of selecting the parameters in SVM, this paper constructed a PSO-SVM model by using particle swarm optimization (PSO) to search the parameters of SVM. The model was used for personal credit scoring in commercial banks and particles' fitness function was used to control the type II error which costs huger loss to commercial banks. Compared with BP NN, the application results indicate that PSO-SVM gets higher classification accuracy with lower type II error rate and the model shows stronger robustness, which presents more applicable for commercial banks to control personal credit risks.
A Hybrid Simulated-Annealing Algorithm for Two-Dimensional Strip Packing Problem
Authors: Türkay Dereli, Gülesin Sena Daş
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

This paper presents a hybrid simulated-annealing (SA) algorithm for two-dimensional strip packing problem (2D SPP) where a set of small rectangular items has to be allocated on a larger stock rectangle in order to find a minimum height. A new recursive placement procedure is proposed and the procedure is combined with the SA algorithm. The hybrid-SA algorithm was tested on a set of benchmark problems taken from the literature. The computational results have validated the quality of the solutions and usefulness of the proposed hybrid-SA algorithm.
Speedup Analysis for Parallel Implementation of Model of Response Accuracy and Response Time in Computerized Testing
Authors: Tianyou Wang, Jun Ni
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Recently, computerized testing has revolutionized the testing industry by offering an array of benefits for both the examinees and the test users. It potentially enhances the quality of education at all levels. Computerized testing also makes available new types of data such as item-response time and human response at the individual item level. However, the present models of these responses demand much computing time. This paper presents an analysis for a parallel implementation of the models by estimating parallel speedup and efficiency. The model provides an insight into the success of advanced computerized testing study using high performance computing (HPC) technology.
Policy Gradients with Parameter-Based Exploration for Control
Authors: Frank Sehnke, Christian Osendorfer, Thomas Rückstieß, Alex Graves, Jan Peters, Jürgen Schmidhuber
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in parameter space, which leads to lower variance gradient estimates than those obtained by policy gradient methods such as REINFORCE. For several complex control tasks, including robust standing with a humanoid robot, we show that our method outperforms well-known algorithms from the fields of policy gradients, finite difference methods and population based heuristics. We also provide a detailed analysis of the differences between our method and the other algorithms.
Early fault detection using a novel spectrum enhancement method for motor current signature analysis
Authors: Niaoqing Hu, Yue Zhang, Fengshou Gu, Guojun Qin, Andrew Ball
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

This paper develops a novel spectrum enhancement method to simplify the spectrum representation. It uses a forward synchronous transform to convert three phase current signals into the two current signals in the synchronous reference frame. The spectrum obtained by applying Fast Fourier Transform (FFT) to one of the transformed current signals is then maximized by varying the initial phase in the synchronous transform. The enhanced spectrum is a much concise representation of the fault signal because it not only eliminates the supply frequency but also enlarges the magnitudes of fault components. The capabilities in enhancing the fault signals and controlling the noise are highlighted through both theoretical analysis and numerical simulation. In addition, two common motor fault cases: a broken rotor bar and a small rotor eccentricity are also tested to evaluate the performance of the enhanced spectrum in detecting these incipient motor faults.
Probing Queries in Wireless Sensor Networks
Authors: Liqiang Pan, Jizhou Luo, Jianzhong Li
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

For queries in wireless sensor networks, empty sets may be returned as query results which could confuse users a lot and users obtain no useful information about the monitored objects from the empty sets. To solve the problem, this paper proposes methods to provide users with approximate answer sets in the case where no sensing data satisfies the query conditions. The approximate answer sets can be used not only to answer the query approximately but also to guide users to modify their queries for further probing the monitored objects. The distance between sensing data and a query and the dominating relationship between sensing data are first defined. Then, three algorithms for processing probing queries are proposed, which compute the best approximate answer sets that consist of the sensing data with the smallest distance from given queries. All the algorithms utilize the dominating relationship to reduce the amount of data transmitted in sensor networks by filtering out the unnecessary data. Experimental results on real and synthetic data sets show that the proposed algorithms have high performance and energy efficiency.
Evaluation of the throughput of a multiple-picker order picking system with congestion consideration
Authors: Jason Chao-Hsien Pan, Po-Hsun Shih
Venue: Computers and Industrial Engineering (2008)

This study investigates an order picking system involving multiple pickers in a warehouse. Travel distance or travel time has usually been employed to measure order picking efficiency, since most previous studies assumed an order picking system only undertakes single-picker operations. However, multiple pickers frequently work in the same area concurrently in an actual warehouse system and congestion inevitably takes place and the traditional travel distance or travel time might not be a proper measure for the system efficiency. Consequently, this study proposes a throughput model for the determination of the picking operation performance for such multiple-picker environment to consider a trade-off between the picking distance and the blocking-caused delay for the storage assignment. The proposed model is first validated by a simulation experiment and then used to compare the throughput of the warehouse under two popular storage assignment strategies with different demand distributions of stock keep units in the order picking system.
Converting an existing communication system into SCA compliant SDR
Authors: Usman Shahid Khan, Shoab Ahmed Khan
Venue: Proceedings of the 7th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications (2008)

This paper presents an implementation of converting an existing Digital Communication System which uses Commercial Off The Shelf (COTS) components and any standard interface like PCI, USB, or Ethernet, to an SCA compliant SDR. Since the initiation of Joint Tactical Radio System (JTRS) program, the concept of Software Defined Radio (SDR) has received considerable attention. Converting the existing Commercial receivers into SCA compliant Receiver requires special consideration as it needs direct hardware interfacing. This paper presents a general implementation that uses drivers and system level calls to build a glue layer to make an existing communication system SCA compliant. The paper uses Open Source SCA Implementation Embedded (OSSIE) for demonstration.
The InfoPhase Method or How to Read Neurons with Neurons
Authors: Raul C. Mureşan, Wolf Singer, Danko Nikolić
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

We present a novel method that can be used to characterize the dynamics of a source neuronal population. A set of readout, regular spiking neurons, is connected to the population in such a way as to facilitate coding of information about the source in the relative firing phase of the readouts. We show that such a strategy is useful in revealing temporally structured processes in the firing of source neurons, which have been recorded from cat visual cortex. We also suggest extensions of the method to allow for the direct identification of temporal firing patterns in the source population.
Challenges in Satisfiability Modulo Theories
Authors: Robert Nieuwenhuis, Albert Oliveras, Enric Rodríguez-Carbonell, Albert Rubio
Venue: Proceedings of the 18th international conference on Term Rewriting and Applications (2007)

Here we give a short overview of the DPLL(T) approach to Satisfiability Modulo Theories (SMT), which is at the basis of current state-of-the-art SMT systems. After that, we provide a documented list of theoretical and practical current challenges related to SMT, including some new ideas to exploit SAT techniques in Constraint Programming.
VSB: The Visual Semantic Browser
Authors: Ismael Navas-Delgado, Amine Kerzazi, Othmane Chniber, José F. Aldana-Montes
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

The Semantic Web not only covers ontology definitions, but also their relationships and instances. This paper describes an adaptable tool for the visualization of all these Semantic Web elements. The tool includes a set of interfaces to enable the inclusion of different visualization tools as plug-ins. Thus, it is divided into four views: ontology groups, ontology mappings, ontologies and instances. Some algorithms are included but we are planning to develop new ones to improve the tool capabilities (the current version is available at http://khaos.uma.es/VSB where new plug-ins will be made public). The tool has also been successfully applied to develop a graphical query interface that takes advantage of the ontology and instance levels.
Implementing Organisations in JADE
Authors: Cristián Madrigal-Mora, Esteban León-Soto, Klaus Fischer
Venue: Proceedings of the 6th German conference on Multiagent System Technologies (2008)

The representation of an agent organisation using a concrete computational entity is a frequently missing feature in platforms for multiagent systems, and it is normally left as a result of the emergent behaviour of interacting agents. This is also the case for JADE, one of the most used multiagent system platforms. This paper proposes an extension to JADE that addresses this missing concept, without disrupting the compatibility with previously developed systems nor the availability of JADE's platform services.
Brief paper: Robust high-order repetitive control: Optimal performance trade-offs
Authors: Goele Pipeleers, Bram Demeulenaere, Joris De Schutter, Jan Swevers
Venue: Automatica (Journal of IFAC) (2008)

High-order repetitive control has previously been introduced to either improve the robustness for period-time uncertainty or reduce the sensitivity for non-periodic inputs of standard repetitive control schemes. This paper presents a systematic, semidefinite programming based approach to compute high-order repetitive controllers that yield an optimal trade-off between these two performance criteria. The methodology is numerically illustrated through trade-off curves for various controller orders and levels of period-time uncertainty. Moreover, existing high-order repetitive control approaches are shown to correspond to specific points on these curves.
EMBRACE: emulating biologically-inspired architectures on hardware
Authors: L. McDaid, J. Harkin, S. Hall, T. Dowrick, Y. Chen, J. Marsland
Venue: Proceedings of the 9th WSEAS International Conference on Neural Networks (2008)

This paper highlights and discusses the current challenges in the implementation of large scale Spiking Neural Networks (SNNs) in hardware. A mixed-mode approach to realising scalable SNNs on a reconfigurable hardware platform is presented. The approach uses compact low power analogue spiking neuron cells, with a weight storage capability, interconnected using Network on Chip (NoC) routers. Results presented show that this route to hardware implementation is promising.
An Integrated Neuro-mechanical Model of C. elegans Forward Locomotion
Authors: Jordan H. Boyle, John Bryden, Netta Cohen
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

One of the most tractable organisms for the study of nervous systems is the nematode Caenorhabditis elegans, whose locomotion in particular has been the subject of a number of models. In this paper we present a first integrated neuro-mechanical model of forward locomotion. We find that a previous neural model is robust to the addition of a body with mechanical properties, and that the integrated model produces oscillations with a more realistic frequency and waveform than the neural model alone. We conclude that the body and environment are likely to be important components of the worm's locomotion subsystem.
Maximizing a Submodular Set Function Subject to a Matroid Constraint (Extended Abstract)
Authors: Gruia Calinescu, Chandra Chekuri, Martin Pál, Jan Vondrák
Venue: Proceedings of the 12th international conference on Integer Programming and Combinatorial Optimization (2007)

Let $f:2^{N} \rightarrow \cal R^{+}$ be a non-decreasing submodular set function, and let $(N,\cal I)$ be a matroid. We consider the problem $\max_{S \in \cal I} f(S)$. It is known that the greedy algorithm yields a 1/2-approximation [9] for this problem. It is also known, via a reduction from the max-k-cover problem, that there is no (1 ¿ 1/e + ¿)-approximation for any constant ¿> 0, unless P = NP [6]. In this paper, we improve the 1/2-approximation to a (1 ¿ 1/e)-approximation, when f is a sum of weighted rank functions of matroids. This class of functions captures a number of interesting problems including set coverage type problems. Our main tools are the pipage rounding technique of Ageev and Sviridenko [1] and a probabilistic lemma on monotone submodular functions that might be of independent interest.We show that the generalized assignment problem (GAP) is a special case of our problem; although the reduction requires |N| to be exponential in the original problem size, we are able to interpret the recent (1 ¿ 1/e)-approximation for GAP by Fleischer et al. [10] in our framework. This enables us to obtain a (1 ¿ 1/e)-approximation for variants of GAP with more complex constraints.
A Hybrid Method for Automatic and Highly Precise VHD Background Removal
Authors: Chen Ding, Yankui Sun, Xiaolin Tian, Zesheng Tang
Venue: Medical Imaging and Informatics: 2nd International Conference, MIMI 2007, Beijing, China, August 14-16, 2007 Revised Selected Papers (2008)

Background removal is a critical step in Visible Human Data (VHD) processing, which is the basic of all other researches. In this paper, a new segmentation algorithm based on the hybrid method for VHD background removal has been proposed, which combines a feature based segmentation method with a contour based one. The algorithm first determines the background part and the interested parts of an image at a coarse level by using its colour features, and then obtains a fine segmentation by using a Gradient Vector Flow (GVF) Snake model on the previous initial contour. Our test results on Chinese VHD show that the new algorithm is more robust and accurate than the previous methods.
Auditing Business Process Compliance
Authors: Aditya Ghose, George Koliadis
Venue: Proceedings of the 5th international conference on Service-Oriented Computing (2007)

Compliance issues impose significant management and reporting requirements upon organizations. We present an approach to enhance business process modeling notations with the capability to detect and resolve many broad compliance related issues. We provide a semantic characterization of a minimal revision strategy that helps us obtain compliant process models from models that might be initially non-compliant, in a manner that accommodates the structural and semantic dimensions of parsimoniously annotated process models. We also provide a heuristic approach to compliance resolution using a notion of compliance patterns. This allows us to partially automate compliance resolution, leading to reduced levels of analyst involvement and improved decision support.
Fundamental Analysis of a Digital Spiking Neuron for Its Spike-Based Coding
Authors: Hiroyuki Torikai
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

A digital spiking neuron (DSN) is a wired system of shift registers. By adjusting the parameters (e.g., number of registers and wiring pattern), the DSN can generate spike-trains having various inter-spike-intervals. In this paper we present some basic relations between parameters of the DSN and characteristics of the spike-train. We also discuss that the presented results will be fundamental to consider ISI-based coding abilities of the DSN.