ppxscal/embedding_network huggingface dataset:
Application of Adaptive Genetic Algorithm in Inversion Analysis of Permeability Coefficients
Authors: Xianghui Deng
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

Permeability coefficients of dam foundation are inversed on the base of real water heads. Otherwise, simple genetic algorithm has the disadvantages in determining the optimal probability values of the crossover and mutation, computation quantity is great and premature phenomena easily appears. Adaptive genetic algorithm is proposed to overcome the disadvantages which simple genetic algorithm has. At same time, adaptive genetic algorithm is used to identify the permeability coefficients of Er Tan dam foundation. The result shows that the method is effective in improving the computational convergence and overcoming the premature phenomena. So adaptive genetic algorithm is efficient and feasible in back analysis for permeability coefficients of dam.
Constructing a know-how repository of advices and warnings from procedural texts
Authors: Lionel Fontan, Patrick Saint-Dizier
Venue: Proceeding of the eighth ACM symposium on Document engineering (2008)

In this paper, we show how a domain dependent know-how textual database of advices and warnings can be constructed from procedural texts. We show how arguments of type warnings and advices can be annotated and extracted from procedural texts, and propose a format and a strategy to automatically generate a know-how textual database.
Entertainment Modeling in Physical Play Through Physiology Beyond Heart-Rate
Authors: Georgios N. Yannakakis, John Hallam
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

An investigation into capturing the relation of physiology, beyond heart rate recording, to expressed preferences of entertainment in children's physical gameplay is presented in this paper. An exploratory survey experiment raises the difficulties of isolating elements derived (solely) from heart rate recordings attributed to reported entertainment and a control experiment for surmounting those difficulties is proposed. Then a survey experiment on a larger scale is devised where more physiological signals (Blood Volume Pulse and Skin Conductance) are collected and analyzed. Given effective data collection a set of numerical features is extracted from the child's physiological state. A preference learning mechanism based on neuro-evolution is used to construct a function of single physiological features that models the players' notion of `fun' for the games under investigation. Performance of the model is evaluated by the degree to which the preferences predicted by the model match those expressed by the children. Results indicate that there appears to be increased mental/emotional effort in preferred games of children.
Exploiting adaptation in a java virtual machine to enable both programmer productivity and performance for heterogeneous devices
Authors: Chandra Krintz
Venue:  (2007)

Computer systems with which we interact on a daily basis consist of a vast diversity of devices. At the low end, battery-powered, handheld devices with limited resources, e.g., personal digital assistants (PDAs), smartphones, etc., are common and extremely popular. At the high end, powerful, multi- and many-core processor systems are increasingly ubiquitous in the laptops, deskside computers, workstations, and clusters that we use. The pervasiveness of heterogeneous systems requires that there be programming languages for application development, that are easy to learn and use, portable across diverse systems, and that facilitate extraction of high performance from the underlying, available device technology. The Java programming language offers many of these characteristics. Its architecture-independent program transfer format and extant virtual machine technology for a wide variety of devices, provides programmers with a write once and run anywhere (WORA) model. Moreover, its object-orientation, robust library support, and high-level syntax, make Java easy to learn and develop applications with. Finally, modern virtual machine (VM) technology offers powerful adaptive services that combine program profiling and optimization, to extract high performance from applications with frequently executed code regions (hot spots). However, the Java language and its VM technology to date have not targeted device-specific opportunities that have the potential for enabling both programmer productivity and scalable high performance. In this dissertation, we investigate potential opportunities for devices at the two ends of the performance spectrum: battery-powered, handheld PDAs and parallel processing systems. Our thesis question asks whether we can employ adaptive JVM technologies to improve the performance of programs in resource-constrained devices and to facilitate efficient and scalable parallel programming in multi-core systems. We address each question with a specific and novel solution: (1) adaptive compiled code management for low end devices, and (2) adaptive code parallelization for high end, multiprocessing systems. The goal of our work is to extract high performance from the underlying device technology through novel JVM extensions while maintaining the ease-of-use of the Java programming language. We describe each of our foci in detail and present empirical evidence of its efficacy and potential.
Selecting strategies using empirical game models: an experimental analysis of meta-strategies
Authors: Christopher Kiekintveld, Michael P. Wellman
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

In many complex multi-agent domains it is impractical to compute exact analytic solutions. An alternate means of analysis applies computational tools to derive and analyze empirical game models. These models are noisy approximations, which raises questions about how to account for uncertainty when analyzing the model. We develop a novel experimental framework and apply it to benchmark meta-strategies -- general algorithms for selecting strategies based on empirical game models. We demonstrate that modeling noise is important; a na&iuml;ve approach that disregards noise and plays according to Nash equilibrium yields poor choices. We introduce three parameterized algorithms that factor noise into the analysis by predicting distributions of opponent play. As observation noise increases, rational players generally make less specific outcome predictions. Our comparison of the algorithms identifies logit equilibrium as the best method for making these predictions. Logit equilibrium incorporates a form of noisy decision-making by players. Our evidence shows that this is a robust method for approximating the effects of uncertainty in many contexts. This result has practical relevance for guiding analysis of empirical game models. It also offers an intriguing rationale for behavioral findings that logit equilibrium is a better predictor of human behavior than Nash equilibrium.
A Stepwise Dimension Reduction Approach to Evolutionary Design of Relative Large Combinational Logic Circuits
Authors: Zhifang Li, Wenjian Luo, Xufa Wang
Venue: Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware (2008)

In this paper, a stepwise dimension reduction (SDR) approach to evolutionary design of relatively large combinational logic circuits is proposed. The proposed method divides the whole circuit into several layers. As for a circuit with one output, the number of input combinations is expected to be reduced layer-by-layer. The current layer's outputs are the next layer's inputs. All layers are evolved separately one after another, and assembled to form a final solution. The experimental results of SDR on parities, multipliers and circuits taken from MCNC library are comparable with those of GDD. Especially, the 19-parity circuit can be evolved successfully.
Complexity of Topological Properties of Regular ω-Languages
Authors: Victor L. Selivanov, Klaus W. Wagner
Venue: Proceedings of the 12th international conference on Developments in Language Theory (2008)

We determine the complexity of topological properties of regular &omega;-languages (i.e., classes of &omega;-languages closed under inverse continuous functions). We show that they are typically NL-complete (PSPACE-complete) for the deterministic Muller, Mostowski and B&uuml;chi automata (respectively, for the nondeterministic Rabin, Muller, Mostowski and B&uuml;chi automata). For the deterministic Rabin and Streett automata and for the nondeterministic Streett automata upper and lower complexity bounds for the topological properties are established.
Artificial Neural Network Based Automatic Face Model Generation System from Only One Fingerprint
Authors: Seref Sagiroglu, Necla Ozkaya
Venue: Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition (2008)

Biometrics technology has received increasingly more attention during the last three decades. Since the performance of biometric systems has reached a satisfactory level for applications, a number of biometric features have been deeply studied, tested and successfully deployed in applications. Relationships among biometric features have not been studied so far. This study focuses on analysing the existence of any relationships among fingerprints and faces. For doing that an intelligent system based on artificial neural networks for generating face models including eyes, nose, mouth, ears andface border from only one fingerprint with the errors among 2.0-12.9 % was developed. Experimental results have shown that there are close realitionships among fingerprints and faces and it is possible to generate faces from only one fingerprint image without knowing any information about faces. Although the proposed system is an initial study and it is still under development, the results are very encouraging and promising for the future developments and applications.
A one-parameter family of interpolating kernels for smoothed particle hydrodynamics studies
Authors: Rubén M. Cabezón, Domingo García-Senz, Antonio Relaño
Venue: Journal of Computational Physics (2008)

A set of interpolating functions of the type f(v)={sin@p2v/@p2v}^n is analyzed in the context of the smoothed-particle hydrodynamics (SPH) technique. The behaviour of these kernels for several values of the parameter n has been studied either analytically as well as numerically in connection with several tests carried out in two-dimensions. The main advantage of this kernel relies in its flexibility because for n=3 it is similar to the standard widely used cubic-spline, whereas for n>3 the interpolating function becomes more centrally condensed, being well suited to track discontinuities such as shock fronts and thermal waves.
Control-oriented approaches to dynamic decision making
Authors: S. Y. Xu, Z. P. Jiang, L. Huang, D. W. Repperger
Venue: Proceedings of the 8th WSEAS International Conference on Robotics, Control and Manufacturing Technology (2008)

In this paper, an approach of learning in dynamic decision making tasks is first developed based on the application of feedback control theory to the case study of the Sugar Factory (SF) task. The SF task is a simple individual dynamic decision-making task in which decision makers are expected to learn from experience. Previously there have been some experimental models (e.g. the D&F model and the W model) focusing on this task, however, they are not robust to workload change and require a large amount of information to be stored. The control model presented here not only avoids such shortcomings, but also significantly enhances the system efficiency, adaptivity and robustness. Through the demonstration of simulation, this new model presents a fairly good estimation of automation control capability to participants, that is, the capacity of automation in a SF supervisory control system. In a supervisory control system, both of the operators' trust in automation and self-confidence in manual control could be described by a dynamic approach, which provides a basis for understanding the factors that guide operators' allocation strategy. As trust and self-confidence are closely associated with the capacity of automation and manual control separately, it behooves us to improve existing models to let the operator have a better understanding of capacities. A modified EDFT model as well as the theoretical analysis are then proposed to present a more accurate description of reliance on automation. Simulation results on a Sugar Factory supervisory control system are derived to show that operators' reliance on automation has been greatly enhanced.
Argument Dependencies in Tukang Besi
Authors: Alastair Butler, Mark Donohue
Venue: Logic, Language, and Computation: 6th International Tbilisi Symposium on Logic, Language, and Computation,TbiLLC 2005 Batumi, Georgia, September 12-16, 2005. Revised Selected Papers (2007)

This paper uses standard syntactic scoping properties (as found with lambda calculus and predicate logic) to account for linking dependencies in Tukang Besi, an Austronesian language of Indonesia. Basic argument dependencies are established with a combination of verbal agreement, case marking and constituent order. If taken alone, no one of these is sufficient to determine the grammatical relations in the clause. Rather these different factors operate in combination to yield unambiguous clauses. What is shown is that scope taking options determine which combinations are possible and which are impossible.
Autonomous Objects and Bottom-Up Composition in ZOO Applied to a Case Study of Biological Reactivity
Authors: Nuno Amálio, Fiona Polack, Jing Zhang
Venue: Proceedings of the 1st international conference on Abstract State Machines, B and Z (2008)

As part of our work on the formal analysis of object-oriented models, we turn to systems where many autonomous individuals interact to give rise to complex collective behaviour. We adapt our ZOO [1,2] structuring and apply it to a case study based on a published model of part of the immune system [3]. The formalisation calls for a bottom-up solution with no central control over individual units, and includes an approach to represent feedback channels enabling broadcast communication between individuals and across levels.
Phosphorous doped SOG as a pre-metal-dielectric for sub-50nm technology nodes
Authors: Arabinda Das, Momtchil Stavrev, Heike Prenz, Markus Schardin, Ines Uhlig, Werner Graf, Hans-Peter Sperlich
Venue: Microelectronic Engineering (2008)

The goal of this work is to find a substitute for chemically-vapour-deposited (CVD) Borophosphosilicate glass (BPSG), which is currently used as a pre-metal dielectric (PMD) for sub 50nm. Two spin-on candidates are considered, out of which one contains four weight percent (wt.%) of phosphor. First, their material properties are discussed and then their integration challenges are presented. Particularly, issues like thermal budget, direct CMP capability and compatibility to wet-cleans are explored. Then the suitable candidate is tested electrically.
Measure the Thickness of the Thin-Film Single-Slice-Capacitor
Authors: Liu Changhui, Xu Chunmei, Liu Le, He Huahui
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

According to wave-absorbing material's electricity characteristic, this text created a kind of new high-performance, low-cost capacitance type absorbing-wave coat's thickness measuring system. Carry out a research of thin film measurement which from nm-level to micron-level. According to the theory which capacitor working in electric field, it design a special single-piece capacitance sensor. This system can carry on a measurement to the thickness of thin film from nm-level to micron-level. Pass to adopt a kind of new capacitance signal to collect the framework type integration chip(Frame ASIC) CAV424 and shield measure and low price position RISC microcontroller, it carry out a method combine with the difference technique and three-signals-inspect technique. The system can automatically adjust null, correct and remove a great deal of errors. Because the microcontroller have inside place 10 position A/D conversion and driver of LCD, the CAV424 output's differential voltage signal can directly with the ADC connection, link in the microcontroller, and the structure of system is very simple.
Modality-Independent Determination of Vertebral Position and Rotation in 3D
Authors: Tomaž Vrtovec
Venue: Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality (2008)

The determination of the position and rotation of vertebrae is important for the understanding of normal and pathological spine anatomy. Existing techniques, however, estimate the position and rotation parameters from two-dimensional (2D) planar cross-sections, are relatively complex and require a relatively large amount of manual interaction. We have developed an automated and modality-independent method for the determination of the position and rotation of vertebrae in three dimensions (3D) that is based on registration of image intensity gradients, extracted in 3D from symmetrical vertebral parts. The method was evaluated on 52 vertebrae; 26 were acquired by computed tomography (CT) and 26 by magnetic resonance (MR). The results show that by the proposed gradient-based registration of symmetrical vertebral parts, the position and rotation of vertebrae in 3D can be successfully determined in both CT and MR spine images. As the position and rotation of vertebrae in 3D are among the most important spine parameters, the proposed method may provide valuable support in the evaluation of deformities and disease processes that affect the spine.
Firing Pattern Estimation of Biological Neuron Models by Adaptive Observer
Authors: Kouichi Mitsunaga, Yusuke Totoki, Takami Matsuo
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

In this paper, we present three adaptive observers with the membrane potential measurement under the assumption that some of parameters in HR neuron are known. Using the Strictly Positive Realness and Yu's stability criterion, we can show the asymptotic stability of the error systems. The estimators allow us to recover the internal states and to distinguish the firing patterns with early-time dynamic behaviors.
Discrete and Hybrid Stochastic State Estimation Algorithms for Networked Control Systems
Authors: S. Cairano, K. H. Johansson, A. Bemporad, R. M. Murray
Venue: Proceedings of the 11th international workshop on Hybrid Systems: Computation and Control (2008)

Networked control systems enable for flexible systems operation and reduce cost of installation and maintenance, potentially at the price of increasing the uncertainty due to information exchange over the network. We focus on the problem of information loss in terms of packet drops, which are modelled as stochastic events that depend on the current state of the network. To design reliable control systems the state of the network must be estimated online, together with the state of the controlled process. This paper proposes various approaches to discrete and hybrid stochastic estimation of network and process states, where the network is modelled as a Markov chain and the packet drop probability depends on the states of the Markov chain. The proposed techniques are evaluated on simulations and experimental data.
Multisensor Real-Time Risk Assessment Using Continuous-Time Hidden Markov Models
Authors: Kjetil Haslum, Andr Årnes
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

The use of tools for monitoring the security state of assets in a network is an essential part of network management. Traditional risk assessment methodologies provide a framework for manually determining the risks of assets, and intrusion detection systems can provide alerts regarding security incidents, but these approaches do not provide a real-time high level overview of the risk level of assets. In this paper we further extend a previously proposed real-time risk assessment method to facilitate more flexible modeling with support for a wide range of sensors. Specifically, the paper develops a method for handling continuous-time sensor data and for determining a weighted aggregate of multisensor input.
Graph based image segmentation
Authors: Long Quan
Venue:  (2007)

Image segmentation refers to a process of dividing the image into disjoint regions that were meaningful. This process is fundamental in computer vision in that many applications, such as image retrieval, visual summary, image based modeling, and others, can benefit from it. This process is also challenging because segmentation is usually subjective and computation is highly costly. Recently graph based image segmentation has attracted growing interest. In this thesis, we investigate different graph structures and priors based on them for image segmentation from three perspectives. First, we investigate the pairwise graph based prior. We design a joint prior in the joint segmentation for 3D clustering and 2D image segmentation. This problem makes good use of the current states of the art in both unbiased and biased graph partitioning. Second, we generalize the pairwise graph to the hypergraph that can model multiple-wise relation among the data points. We propose a biased hypergraph partitioning approach, called Linear Neighborhood Propagation, which leads to a linear system with an efficient solution. Finally, we degrade the cyclic graph to a connected acyclic graph, i.e. tree. We propose a tree partitioning method based on the normalized cut criterion, called Normalized Tree Partitioning. It runs in linear time, and can potentially get superior performance over spectral graph partitioning due to less approximation.
A model-driven, agent-based approach for the integration of services into a collaborative business process
Authors: Ingo Zinnikus, Christian Hahn, Klaus Fischer
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

In cross-organisational business interactions, the most desirable solution for integrating different partners would suggest to integrate their processes and data on a rather low level. However, the internal processes and interfaces of the participating partners are often pre-existing and have to be taken as given. Furthermore, in cross-organisational scenarios partners are typically very sensitive about their product data and the algorithms that process it. In many cases, private processes are only partially visible and hidden behind public interface descriptions. This imposes restrictions on the possible solutions for the problems which occur when partner processes are integrated. In this paper, we describe a solution which supports rapid prototyping by combining a model-driven framework for cross-organisational business processes with an agent-based approach for flexible process execution. We show how the model-driven approach can be combined with semantic service discovery for flexible service composition.