ppxscal/embedding_network huggingface dataset:
A Kernel-Based Reinforcement Learning Approach to Dynamic Behavior Modeling of Intrusion Detection
Authors: Xin Xu, Yirong Luo
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

As an important active defense technique for computer networks, intrusion detection has received lots of attention in recent years. However, the performance of current intrusion detection systems (IDSs) is far from being satisfactory due to the increasing number of complex sequential attacks. Aiming at the above problem, in this paper, a novel kernel-based reinforcement learning method for sequential behavior modeling in host-based IDSs is proposed. Based on Markov process modeling of host-based intrusion detection using sequences of system calls, the performance optimization of IDSs is transformed to a sequential prediction problem using evaluative reward signals. By using the kernel-based learning prediction algorithm, i.e., the kernel least-squares temporal-difference (kernel LS-TD) algorithm, which implements LS-TD learning in a kernel-induced feature space, the nonlinear modeling and prediction problem for sequential behaviors in IDSs is efficiently solved. Experiments on system call data from the University of New Mexico illustrate that the proposed kernel-based RL approach can achieve better detection accuracy than previous sequential behavior modeling methods including Hidden Markov Models (HMMs) and linear TD algorithms.
Reliability of Components
Authors: Jay W. Forrester
Venue: IEEE Annals of the History of Computing (1983)

Because this issue of the Annals focuses on the SAGE system, the following excerpt from Christopher Evans's 1975 interview with Jay W. Forrester is timely. Editor's Note: Jay Forrester is one of the great pioneers of the computer business: director of Digital Computer Laboratory at MIT, builder of Whirlwind, inventor of core memory, and chief engineer for SAGE. His accomplishments are too numerous to mention, but this brief excerpt from an interview shows us something of his attitude toward design.
Improving the Learning Speed in 2-Layered LSTM Network by Estimating the Configuration of Hidden Units and Optimizing Weights Initialization
Authors: Débora C. Corrêa, Alexandre L. Levada, José H. Saito
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

This paper describes a method to initialize the LSTM network weights and estimate the configuration of hidden units in order to improve training time for function approximation tasks. The motivation of this method is based on the behavior of the hidden units and the complexity of the function to be approximated. The results obtained for 1-D and 2-D functions show that the proposed methodology improves the network performance, stabilizing the training phase.
A Semantics-Based Aspect Language for Interactions with the Arbitrary Events Symbol
Authors: Roy Grønmo, Fredrik Sørensen, Birger Møller-Pedersen, Stein Krogdahl
Venue: Proceedings of the 4th European conference on Model Driven Architecture: Foundations and Applications (2008)

In this paper we introduce an aspect language that can define cross-cutting effects on a set of UML 2.0 sequence diagrams. The aspects and sequence diagrams are woven at the model level. By basing the weaving upon a formal trace model for sequence diagrams, we ensure that the weaving is semantics-based. We propose the arbitrary events symbol as a wildcard mechanism to express zero or more events on a sequence diagram lifeline. The approach is explained by a real-life example, and a weaving tool partially implements the approach.
A Mathematical Tool to Extend 2D Spatial Operations to Higher Dimensions
Authors: Farid Karimipour, Mahmoud R. Delavar, Andrew U. Frank
Venue: Proceeding sof the international conference on Computational Science and Its Applications, Part I (2008)

3D and temporal objects must be included in GIS to handle real world phenomena. Many have studied extension of spatial operations to these multi-dimensional spaces and suggested technical solutions to extend a spatial operation to a new multi-dimensional space. These technical approaches have led to developments which can not be generalized. One technique used to extend a spatial operation from 2D to a multi-dimensional space is not likely usable for another spatial operation, nor to extend the same spatial operation to another multi-dimensional space. This paper suggested studying spatial operations via their dimension-independent properties. It intends to construct a mathematical framework to integrate spatial operations of different multi-dimensional spaces (3D and time) a GIS should support. The framework will be independent of the space in which the operations are applied using algebraic structures - and more specifically category theory - that ignore those properties of operations which depend on the objects they are applied to. Implementations for some case studies for spatial operations of moving points are presented.
The Effect of Entity Generalization on Software Functional Sizing: A Case Study
Authors: Oktay Turetken, Onur Demirors, Cigdem Gencel, Ozden Ozcan Top, Baris Ozkan
Venue: Proceedings of the 9th international conference on Product-Focused Software Process Improvement (2008)

In this paper we discuss a specific result derived from a multiple case study. The case study involved implementation of IFPUG Function Point Analysis and COSMIC Functional Size Measurement methods in an innovative military software development project by different groups of experts. Application of these methods in a case that provides a number of size measurement challenges enabled us to observe significant improvement opportunities for the methodologies. In this paper, we depict the utilization of the entity generalization concept in two FSM methods and based on our observations we discuss the effects of different interpretations of the concept for measuring the software functional size.
Ontology-based inference for causal explanation
Authors: Ph. Besnard, M.-O. Cordier, Y. Moinard
Venue: Integrated Computer-Aided Engineering (2008)

We define an inference system to capture explanations based on causal statements, using an ontology in the form of an IS-A hierarchy. We first introduce a simple logical language which makes it possible to express that a fact causes another fact and that a fact explains another fact. We present a set of formal inference patterns from causal statements to explanation statements. We introduce an elementary ontology which gives greater expressiveness to the system while staying close to propositional reasoning. We provide an inference system that captures the patterns discussed, firstly in a purely propositional framework, then in a datalog (limited predicate) framework.
Healthcare Information Management System in Home Environment
Authors: Chang Won Jeong, Chung Sub Lee, Su Chong Joo
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

In this paper, we suggested a healthcare information management system for supporting healthcare home services. Our researching focus in this paper is how to design system and how to use constructed database on the framework for supporting healthcare home services. The healthcare database constructed by using this information for the purpose of healthcare home services is divided into the base information with real schemes and the context based information with view schemes. Finally, for verifying the practical use of healthcare information constructed in this paper, we show an example of healthcare home monitoring service using information, emergency call, home appliance control, and we describes the results of the experimental evaluation between the base and context based information in terms of execution service time for healthcare home applications.
Mobile 2.0 Leads to a Transformation in mLearning
Authors: Shudong Wang, Michael Higgins
Venue: Proceedings of the 1st international conference on Hybrid Learning and Education (2008)

This paper aims to delineate the impact of Mobile 2.0 on mobile learning (mLearning). Based on a thorough analysis on numerous Mobile 2.0 applications which can be used or are being used for learning purposes, the paper concludes that Mobile 2.0 brings a revolution to learning and will eventually lead to a transformation in the style of learning. The background for this conclusion includes introduction of the concept and technology of Mobile 2.0, its relationship to Web 2.0, empirical research, and actual use of Mobile 2.0 applications in education. The paper also offers a sneak peek at the future of Web 3.0 assisted learning. This Japan and China based research is also applied to other countries.
Enriching Ontology for Deep Web Search
Authors: Yoo Jung An, Soon Ae Chun, Kuo-Chuan Huang, James Geller
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

This paper addresses the problems of extracting instances from the Deep Web, enriching a domain specific ontology with those instances, and using this ontology to improve Web search. Extending an existing ontology with a large number of instances extracted from the Deep Web is an important process for making the ontology more usable for indexing of Deep Web sites. We demonstrate how instances extracted from the Deep Web are used to enhance a domain ontology. We show the contribution of the enriched ontology to Web search effectiveness. This is done by comparing the number of relevant Web sites returned by a search engine with a user's search terms only, with the Web sites found when using additional ontology-based search terms. Experiments suggest that the ontology plus instances approach results in more relevant Web sites among the first 100 hits.
Interactive office documents: a new face for web 2.0 applications
Authors: John M. Boyer
Venue: Proceeding of the eighth ACM symposium on Document engineering (2008)

As the world wide web transforms from a vehicle of information dissemination and e-commerce transactions into a writable nexus of human collaboration, the Web 2.0 technologies at the forefront of the tranformation may be seen as special cases of a more general shift in the conceptual application model of the web. This paper recognizes the conceptual transition and explores the connections to a new class of interactive office documents that become possible by tighter integration of the Open Document Format with the W3C's next generation web forms technology (XForms). The connections transcend simple provisioning of office document editing and persistence capabilities on the web. Rather, the advantages of office documents as self-contained entities that flow through a collaborative network or business process are combined with web application qualities such as intelligent behavioral interaction, in-process web service access, and control of server submission content. An office document mashup called 'Dual Forms' is presented to demonstrate the feasibility of office document centric web applications.
Software Integration and Framework Development
Authors: Th. Haase, P. Klein, M. Nagl
Venue: Collaborative and Distributed Chemical Engineering. From Understanding to Substantial Design Process Support: Results of the IMPROVE Project (2008)

The a-posteriori integration of heterogeneous engineering tools, where tools are supplied by different vendors, constitutes a challenging task. In particular, this applies to an integration approach where existing engineering tools are extended by new functionality which, again, can be integrated synergistically. Responding to these challenges, an approach to tool integration is described which puts strong emphasis on software architecture and model-driven development.Starting from an abstract description for an integration software architecture, this architecture is gradually refined down to the implementation level. To integrate heterogeneous engineering tools, wrappers are constructed, abstracting from technical details and providing homogenized data access. This approach to tool integration is supported by a collection of tools for software architecture design and model-driven wrapper development, all based on formal graph models and transformation rules. This collection of tools considerably leverages the problem of composing a tightly integrated development environment from a set of heterogeneous engineering tools. So, we give specific architecture tools for the problem of tool integration following an a-posteriori approach.
Dependence of neuronal correlations on filter characteristics and marginal spike train statistics
Authors: Tom Tetzlaff, Stefan Rotter, Eran Stark, Moshe Abeles, Ad Aertsen, Markus Diesmann
Venue: Neural Computation (2008)

Correlated neural activity has been observed at various signal levels (e.g., spike count, membrane potential, local field potential, EEG, fMRI BOLD). Most of these signals can be considered as superpositions of spike trains filtered by components of the neural system (synapses, membranes) and the measurement process. It is largely unknown how the spike train correlation structure is altered by this filtering and what the consequences for the dynamics of the system and for the interpretation of measured correlations are. In this study, we focus on linearly filtered spike trains and particularly consider correlations caused by overlapping presynaptic neuron populations. We demonstrate that correlation functions and statistical second-order measures like the variance, the covariance, and the correlation coefficient generally exhibit a complex dependence on the filter properties and the statistics of the presynaptic spike trains. We point out that both contributions can play a significant role in modulating the interaction strength between neurons or neuron populations. In many applications, the coherence allows a filter-independent quantification of correlated activity. In different network models, we discuss the estimation of network connectivity from the high-frequency coherence of simultaneous intracellular recordings of pairs of neurons.
Optimising Predictive Control Based on Neural Models
Authors: Maciej Ławryńczuk
Venue: Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications (2008)

This paper presents a Model Predictive Control (MPC) algorithm for on-line economic optimisation of nonlinear technological processes. The economic profit is explicitly expressed in the minimised objective function. The algorithm uses only one dynamic neural model, which is linearised on-line. As a result, an easy to solve on-line quadratic programming problem is formulated. In contrast to the classical multilayer control system structure, the necessity of repeating two nonlinear optimisation problems at each sampling instant is avoided.
A complex network-based approach for boundary shape analysis
Authors: André Ricardo Backes, Dalcimar Casanova, Odemir Martinez Bruno
Venue: Pattern Recognition (2009)

This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has an efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, curvature, Zernike moments and multiscale fractal dimension).
Topic 4 High-Performance Architectures and Compilers
Authors: Michael O'Boyle, François Bodin, Jose Gonzalez, Lucian Vintan
Venue: Proceedings of the 13th European international conference on Parallel Processing (2007)

Parallelism is now a central concern for architecture designers and compiler writers. Instruction-level parallelism and increasingly multi-cores are present in all contemporary processors. Furthermore, we are witnessing a convergence of interests with architects and compiler writers addressing large scale parallel machines, general-purpose platforms and specialised hardware designs such as graphic coprocessors or low-power embedded systems. Modern systems require system software and hardware to be designed in tandem, hence this topic is concerned with architecture design and compilation. Twenty-four papers were submitted to the track of which five were accepted split over two sessions.
Let Robots Play Soccer under More Natural Conditions: Experience-Based Collaborative Localization in Four-Legged League
Authors: Qining Wang, Yan Huang, Guangming Xie, Long Wang
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

This paper presents an experience-based collaborative approach for a group of autonomous robots to localize in asymmetric, dynamic environments. To help robots play soccer under more natural conditions, we propose a Markov localization based hybrid method with integration of environment experience construction and dynamic reference object based multi-robot localization. By using this method, the robot can estimate and correct its position perception more accurately and effectively among a group of autonomous robots, taking the odometry error and other negative influence into consideration. Satisfactory results are obtained in the RoboCup Four-Legged League environment.
Local Spatial Properties Based Image Interpolation Using Neural Network
Authors: Liyong Ma, Yi Shen, Jiachen Ma
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

A neural network based interpolation scheme using the local spatial properties of the source image for image enlargement is proposed. The local spatial properties that are used for neural network training include the neighbor pixels gray values, the average value and the gray value variations between neighbor pixels in the selected region. Gaussian radial basis function neural network is used for image local spatial properties pattern learning and regression estimation for image interpolation. The trained neural network is used to estimate the gray values of unknown pixels using the known neighbor pixels and local spatial properties information. Some interpolation experiments demonstrate that the proposed approach is superior to linear, cubic and other neural network and support vector machines based interpolation approaches.
Learning of Regular ω-Tree Languages
Authors: M. Jayasrirani, M. H. Begam, D. G. Thomas
Venue: Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications (2008)

We introduce two subclasses of regular &omega;-tree languages called local &omega;-tree languages and Buchi local &omega;-tree languages. Automata characterization for these &omega;-tree languages is given. For these subclasses and &omega;-regular tree languages learning algorithms are given.
Simplified Planar Coresets for Data Streams
Authors: John Hershberger, Subhash Suri
Venue: Proceedings of the 11th Scandinavian workshop on Algorithm Theory (2008)

We propose a simple, optimal-space algorithm for maintaining an extent coreset for a data stream of points in the plane. For a given parameter r, the coreset consists of a sample of ¿(r) points from the stream seen so far. The coreset property is that for any slab (defined by two parallel lines) that encloses the sample, a (1 + ¿) expansion of the slab encloses all the stream points seen so far, for ¿ = O(1/r 2). The coreset can be maintained in O(logr) amortized time per point of the stream.
Numerical Study and Optimal Blade Design of a Centrifugal Pump by Evolutionary Algorithms
Authors: Vasilis Grapsas, Fotis Stamatelos, John Anagnostopoulos, Dimitris Papantonis
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

A numerical methodology for hydrodynamic design in centrifugal pumps is developed and tested, considering the possibility to increase the hydraulic efficiency of the pump impeller by improving the blades shape. The simulation and analysis of the incompressible turbulent flow through the test impeller is performed with a commercial CFD code, and the numerical results are in agreement with the corresponding measurements in a laboratory pump impeller. A parametric study is carried out to examine the influence of some blade design parameters on the performance and the efficiency of the impeller, like the blade length, the inlet height, and the leading edge inclination. The values of the above parameters that maximize the hydraulic efficiency of the impeller are then derived by a multiparametric optimization methodology, using a stochastic evolutionary algorithm software. The optimal impeller design exhibits a remarkable efficiency increase compared to the initial impeller design.
Using Laplacian Spectra to Analyze Project Based Services
Authors: Yi Yang, Zhi-Cong Fang, Yan Yang, Hong Cai
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

In this paper, we use Laplacian spectral analysis to study the characteristics of complex service project networks by observing their marked signatures in theLaplacian eigenvalues and eigenvectors. Based on that, we also depict other representations of the complexity of those project complex networks including inverse participation ratio (IPR), degree expectation value (DEV). Compared with using adjacency matrix or coupling matrix only, we find that those extended spectral analysis methods do provide interesting features like lens to observe the intrinsic properties of the complex network representing the organizational structure of project based services.
An empirical investigation of scenarios gained and lost in architecture evaluation meetings
Authors: Dietmar Winkler, Stefan Biffl, Muhammad Ali Babar
Venue: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement (2008)

Studying the effectiveness of scenario development meetings in the software architecture process is important to improve meeting effectiveness. This paper reports initial findings from analyzing the data collected in a controlled experiment aimed at studying the effectiveness of meetings in terms of gained and lost scenarios of individuals, real and nominal (non-communicating) teams. Our findings question the effectiveness of holding meetings since more important scenarios were lost than gained in these meetings. In the study nominal teams performed better than individuals and real teams.
How Anonymous Is k-Anonymous? Look at Your Quasi-ID
Authors: Claudio Bettini, X. Sean Wang, Sushil Jajodia
Venue: Proceedings of the 5th VLDB workshop on Secure Data Management (2008)

The concept of quasi-ID (QI) is fundamental to the notion of k-anonymity that has gained popularity recently as a privacy-preserving method in microdata publication. This paper shows that it is important to provide QI with a formal underpinning, which, surprisingly, has been generally absent in the literature. The study presented in this paper provides a first look at the correct and incorrect uses of QI in k-anonymization processes and exposes the implicit conservative assumptions when QI is used correctly. The original notions introduced in this paper include (1) k-anonymity under the assumption of a formally defined external information source, independent of the QI notion, and (2) k-QI, which is an extension of the traditional QI and is shown to be a necessary refinement. The concept of k-anonymity defined in a world without using QI is an interesting artifact itself, but more importantly, it provides a sound framework to gauge the use of QI for k-anonymization.