ppxscal/embedding_network huggingface dataset:
Using Case Provenance to Propagate Feedback to Cases and Adaptations
Authors: David Leake, Scott A. Dial
Venue: Proceedings of the 9th European conference on Advances in Case-Based Reasoning (2008)

Case provenance concerns how cases came into being in a case-based reasoning system. Case provenance information has been proposed as a resource to exploit for tasks such as guiding case-based maintenance and estimating case confidence [1]. The paper presents a new bidirectional provenance-based method for propagating case confidence, examines when provenance-based maintenance is likely to be useful, and expands the application of provenance-based methods to a new task: assessing the quality of adaptation rules. The paper demonstrates the application of the resulting quality estimates to rule maintenance and prediction of solution quality.
A Tree-Based Approach for Computing Double-Base Chains
Authors: Christophe Doche, Laurent Habsieger
Venue: Proceedings of the 13th Australasian conference on Information Security and Privacy (2008)

We introduce a tree-based method to find short Double-Base chains. As compared to the classical greedy approach, this new method is not only simpler to implement and faster, experimentally it also returns shorter chains on average. The complexity analysis shows that the average length of a chain returned by this tree-based approach is $\frac{\log_2 n }{4.6419}\cdotp$ This tends to suggest that the average length of DB-chains generated by the greedy approach is not O(logn/loglogn). We also discuss generalizations of this method, namely to compute Step Multi-Base Representation chains involving more than 2 bases and extended DB-chains having nontrivial coefficients.
Towards an Open Source Screen Reader: Screenreader Usability Extensions (SUE)
Authors: Andrea Gaal, Gerhard Jaworek, Joachim Klaus, Martina Weicht, Frank Zenker, Ilvio Bruder, Antje Düsterhöft, Andreas Heuer
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

More and more educational institutions, authorities, and companies adopt open source software, especially Linux. Unfortunately, at the moment, no Linux based screen reader provides adequate and sufficient functionality as the ones of Windows. This means that visually impaired people are disadvantaged in the labour market. The focus of the project is the development of a screen reader for the graphical interface using Linux. The screen reader will allow the visually impaired to work with Linux for typical office tasks and the desktop (GNOME) itself. A special training course will instruct teachers and pupils at institutions for the blind and the partially sighted in using the screen reader. The content of the programme is based on the 7 modules of the ECDL (European Computer Driving Licence).
Local Movement Control with Neural Networks in the Small Size League
Authors: Steffen Prüter, Ralf Salomon, Frank Golatowski
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

In the RoboCup small-size league, most teams calculate the robots' positions by means of a camera that is mounted above the field as well as different kinds of artificial intelligence methods that run on an additional PC. This processing loop induces various time delays, which require forecasting routines, if more accurate behaviors are desired. This paper shows that by utilizing a combination of a neural network and local sensors, the robot is able to estimates its actual position quite accurately. This paper furthermore shows that the learning procedure is also able to compensate for slip and friction effects that cannot be observed by the local sensors.
Texture and strain in narrow copper damascene interconnect lines: An X-ray diffraction analysis
Authors: B. Kaouache, S. Labat, O. Thomas, S. Maitrejean, V. Carreau
Venue: Microelectronic Engineering (2008)

The behaviour of submicron damascene copper lines raises a number of fundamental issues such as grain growth in narrow trenches, thermomechanical properties of copper in these confined geometries, etc. This experimental study is aimed at evaluating the influence of annealing, polishing and line width on the room temperature strain and texture of narrow copper damascene lines. X-ray diffraction has been performed on arrays of lines with widths ranging between 3@mm and 0.09@mm. Two annealing conditions (150^oC and 400^oC) have been used either prior or after Chemical Mechanical Polishing (CMP). A clear influence of the Cu overburden on the in-line microstructure is evidenced. X-ray diffraction analysis shows that strains in line longitudinal direction are higher in those annealed at 400^oC and decrease with the width of the lines. Effect of CMP on structure and relationship between both texture and strain and temperature of thermal treatments is discussed in light of these observations.
Human Touching Behavior Recognition Based on Neural Networks
Authors: Joung Woo Ryu, Cheonshu Park, Joo-Chan Sohn
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Of the possible interactions between human and robot, touch is an important means of providing human beings with emotional relief. However, most previous studies have focused on interactions based on voice and images. In this paper, a method of recognizing human touching behaviors is proposed for developing a robot that can naturally interact with humans through touch. In this method, the recognition process is divided into pre-process phase and recognition phase. In the pre-process phase, recognizable characteristics are calculated from the data generated by the touch detector which was fabricated using force sensors. The force sensor used an FSR (force sensing register). The recognition phase classifies human touching behaviors using a multi-layer perceptron which is a neural network model. We measured three different human touching behaviors for six men. The human touching behaviors are `hitting,' 'stroking,' and `tickling'. In the test conducted with recognizers generated for each user, the average recognition rate was 93.8%, while the test conducted with a single recognizer showed a 79.8% average recognition rate. These results show the feasibility of the proposed human touching behavior recognition method.
Efficient One-Round Key Exchange in the Standard Model
Authors: Colin Boyd, Yvonne Cliff, Juan Gonzalez Nieto, Kenneth G. Paterson
Venue: Proceedings of the 13th Australasian conference on Information Security and Privacy (2008)

We consider one-round key exchange protocols secure in the standard model. The security analysis uses the powerful security model of Canetti and Krawczyk and a natural extension of it to the ID-based setting. It is shown how KEMs can be used in a generic way to obtain two different protocol designs with progressively stronger security guarantees. A detailed analysis of the performance of the protocols is included; surprisingly, when instantiated with specific KEM constructions, the resulting protocols are competitive with the best previous schemes that have proofs only in the random oracle model.
Towards More Integrated Implementation of Healthcare Information Systems: Using the 3LGM2 for Modeling the IHE-Scheduled Workflow Integration Profile
Authors: Rada Hussein, Alfred Winter
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

In today's healthcare enterprises, data from many sources are needed to make optimal healthcare decisions. Therefore, the Integrating the Healthcare Enterprise (IHE) concept emerged to solve the interoperability problems by collaborative professional organizations representing both buyers and vendors. The goal of this work is to model and analyze the IHE-scheduled workflow integration profile in order to facilitate the adoption of the IHE concepts. This is achieved by creating the 3-layer model of this integration profile utilizing the 3LGM2 tool. The created model has been able to provide support for structured and comprehensive analysis of the scheduled workflow integration profile in all its aspects: processes, information, applications and organization.
Family of Energy Conserving Glossy Reflection Models
Authors: Michal Radziszewski, Witold Alda
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

We present an improved reflection model optimized for global illumination. The model produces visually plausible images, is symmetric and has improved energy preserving capabilities compared to previous approaches which satisfies these requirements. Having an efficient sampling routine, the model is ready to use in Monte Carlo rendering. Presented model is phenomenological, i.e. it has intuitive glossiness parameter that affects its appearance. Moreover it can be used as a set of basis functions designed to fit material reflection to measured data.
Fuzzy Similarity of Facial Expressions of Embodied Agents
Authors: Radosław Niewiadomski, Catherine Pelachaud
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

In this paper we propose an algorithm based on fuzzy similarity which models the concept of resemblance between facial expressions of an Embodied Conversational Agent (ECA). The algorithm measures the degree of visual resemblance between any two facial expressions. We also present an evaluation study in which we compared the users' perception of similarity of facial expressions. Finally we describe an application of this algorithm to generate complex facial expressions of an ECA.
Cross-Layer Distributed Diversity for Heterogeneous Wireless Networks
Authors: H. Javaheri, G. Noubir, Y. Wang
Venue: Proceedings of the 5th international conference on Wired/Wireless Internet Communications (2007)

In this paper, we introduce a cross-layer diversity framework for multi-air interface wireless communication devices. As an initial step, we focus on devices, of the cellular phones type, that have both long-range relatively low-rate communication air-interface (e.g., GSM) and short-range high-rate communication air-interface (e.g., IEEE802.11). The devices can cooperate through the energy-efficient high-rate interface to improve the performance of the long-range interface. Within this framework we propose a distributed signal-combining technique that accounts for the limited bandwidth of the short-range communication: Threshold Maximum Ratio Combining. We analytically derive the probability distribution function of the signal to noise ratio (SNR) of the combined signals as a function of the number of involved devices and show that significant improvement of the SNR is achievable which translates into a reduction of the overall system outage probability.
Information Conveyed by the Neural Network Systems and its Applied Significance
Authors: Algis Garliauskas
Venue: Informatica (2007)

In this paper, the information theory interpreted as the neural network systems of the brain is considered for information conveying and storing. Using the probability theory and specific properties of the neural systems, some foundations are presented. The neural network model proposed and computational experiments allow us to draw a conclusion that such an approach can be applied in storing, coding, and transmission of information.
An Evolutionary RBFNN Learning Algorithm for Complex Classzification Problems
Authors: Jin Tian, Minqiang Li, Fuzan Chen
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

A self-optimizing approach for complex classifications is proposed in this paper to construct dynamical radial basis function neural network (RBFNN) models based on a specially designed genetic algorithm (GA). The algorithm adopts a matrix-form mixed encoding and specifically designed genetic operators to optimize the decayed-radius selected clustering (DRSC) process by co-evolving all of the parameters of the network's layout. The individual fitness is evaluated as a multi-objective optimization task and the weights between the hidden layer and the output layer are calculated by the pseudo-inverse algorithm. Experimental results on eight UCI datasets show that the GA-RBFNN can produce a higher accuracy of classification with a much simpler network structure and outperform those models of neural network based on other training methods.
A Modular Reference Architecture Framework for Electronic Cross-Organizational Interoperation
Authors: Christoph Schroth, Beat Schmid
Venue: Proceedings of the 7th international conference on Electronic Government (2008)

The organization of value creation has changed fundamentally in numerous industries during the last years. Rather than being part of hard-wired value chains, today's companies increasingly establish loosely coupled, adaptive business networks. However, seamless interoperation across corporate boundaries still faces significant managerial as well as technological challenges. In this work, we propose a reference architecture framework for electronic business media that overcome the drawbacks of today's business-to-business (B2B) solutions. Based on the St. Gallen Media Reference Model this reference framework builds on the design principle of modularity which proved critical for the success of numerous "artefacts" in other, more mature industries. On the basis of a case study in the field of public administration in Switzerland, we show its real-world applicability and its improvement potential.
Attention-Based Environment Perception in Autonomous Robotics
Authors: Antonio Chella, Irene Macaluso, Lorenzo Riano
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

This paper describes a robotic architecture that uses visual attention mechanisms for autonomous navigation in unknown indoor environments. A foveation mechanism based on classical bottom-up gaze shifts allows the robot to autonomously select landmarks, defined as salient points in the camera images. Landmarks are memorized in a behavioral fashion, coupling sensing and acting to achieve a representation view and scale independent. Selected landmarks are stored in a topological map; during the navigation a top-down mechanism controls the attention system to achieve robot localization. Experiments and results show that our system is robust to noise and odometric errors, being at the same time adaptable to different environments and acting conditions.
Modal Abstractions of Concurrent Behaviour
Authors: Sebastian Nanz, Flemming Nielson, Hanne Riis Nielson
Venue: Proceedings of the 15th international symposium on Static Analysis (2008)

We present a novel algorithm for the automatic construction of modal transition systems as abstractions of concurrent processes. Modal transition systems are recognised as valuable abstractions for model checking because they allow for the deduction of safety as well as liveness properties. However, the issue of effectively creating these abstractions from specification languages such as process algebras is a missing link that prevents their more widespread usage for model checking of concurrent systems. Our algorithm is based on static analysis and uses a lattice of intervals to express simultaneous over- and under-approximations to the set of process actions available in a particular state. We obtain an abstraction that is 3-valued in both states and transitions and that naturally integrates with model checking approaches for modal transition systems.
Effective Learning with Heterogeneous Neural Networks
Authors: Lluís A. Belanche-Muñoz
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

This paper introduces a class of neuron models accepting heterogeneous inputs and weights. The neuron model computes a user- defined similarity function between inputs and weights. The neuron transfer function is formed by composition of an adapted logistic function with the power mean of the partial input-weight similarities. The resulting neuron model is capable of dealing directly with mixtures of continuous quantities (crisp or fuzzy) and discrete quantities (ordinal, integer, binary or nominal). There is also provision for missing values. An artificial neural network using these neuron models is trained using a breeder genetic algorithm until convergence. A number of experiments are carried out using several real-world benchmarking problems. The network is compared to a standard radial basis function network and to a multi-layer perceptron and shown to learn from non-trivial data sets with superior generalization ability in most cases, at a comparable computational cost. A further advantage is the interpretability of the learned weights.
A Fuzzy Extension of Some Classical Concordance Measures and an Efficient Algorithm for Their Computation
Authors: Michele Ceccarelli, Antonio Maratea
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

Many indexes have been proposed in literature for the comparison of two crisp data partitions, as resulting from two different classifications attempts, two different clustering solutions or the comparison of a predicted vs. a true labeling. Most of these indexes implementations have a computational cost of O(N 2) (where N is the number of data points) and this fact may limit their usage in very big datasets or their integration in computational-intensive validation strategies. Furthermore, their extension to fuzzy partitions is not obvious. In this paper we analyze efficient algorithms to compute many classical indexes (most notably the Jaccard coefficient and the Rand index) in O(d 2 + N) (where d is the number of different classes/clusters) and propose a straightforward procedure to extend their computation to fuzzy partitions. The fuzzy extension is based on a pseudo-count concept and provides a natural framework for including memberships in computation of binary similarity indexes, not limited to the ones here revised. Results on simulated data using the Jaccard coefficient highlight a higher consistence of its proposed fuzzy extension with respect to its crisp counterpart.
Robust Statistics Meets SDC: New Disclosure Risk Measures for Continuous Microdata Masking
Authors: Matthias Templ, Bernhard Meindl
Venue: Proceedings of the UNESCO Chair in data privacy international conference on Privacy in Statistical Databases (2008)

The aim of this study is to evaluate the risk of re-identification related to distance-based disclosure risk measures for numerical variables. First, we overview different - already proposed - disclosure risk measures. Unfortunately, all these measures do not account for outliers. We assume that outliers must be protected more than observations near the center of the data cloud. Therefore, we propose a weighting scheme for each observation based on the concept of robust Mahalanobis distances. We also consider the peculiarities of different protection methods and adapt our measures to be able to give realistic measures for each method. In order to test our proposed distance based disclosure risk measures we run a simulation study with different amounts of data contamination. The results of the simulation study shows the usefulness of the proposed measures and gives deeper insights into how the risk of quantitative data can be measured successfully. All the methods proposed and all the protection methods plus measures used in this paper are implemented in R-package sdcMicro which is freely available on the comprehensive R archive network (http://cran.r-project.org).
Fundamentals of Distributed Computing: A Practical Tour of Vector Clock Systems
Authors: Roberto Baldoni, Matthias Klusch
Venue: IEEE Distributed Systems Online (2002)

A distributed computation consists of a set of processes that cooperate to achieve a common goal. A main characteristic of these computations is that the processes do not already share a common global memory and that they communicate only by exchanging messages over a communication network. Moreover, message transfer delays are finite yet unpredictable. This computation model defines what is known as the asynchronous distributed system model, which includes systems that span large geographic areas and are subject to unpredictable loads.
A Term Distribution Visualization Approach to Digital Forensic String Search
Authors: Moses Schwartz, L. M. Liebrock
Venue: Proceedings of the 5th international workshop on Visualization for Computer Security (2008)

Digital forensic string search is vital to the forensic discovery process, but there has been little research on improving tools or methods for this task. We propose the use of term distribution visualizations to aid digital forensic string search tasks. Our visualization model enables an analyst to quickly identify relevant sections of a text and provides brushing and drilling-down capabilities to support analysis of large datasets. Initial user study results suggest that the visualizations are useful for information retrieval tasks, but further studies must be performed to obtain statistically significant results and to determine specific utility in digital forensic investigations.
Modelling the natural gas consumption in a changing environment
Authors: F. A. Batzias, N. P. Nikolaou, A. S. Kakos
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

A composite function was used successfully for modelling the Natural Gas (NG) consumption in 16 European energy markets. Background of the model is a logistic function where the upper limit is also a logistic function of time, with secondary parameters determined either endogenously together with the rest primary parameters or exogenously in a sample space of the energy market. Fitting of this 'double logistic' dynamic model to NG consumption data of the period 1980-2000 gave better Standard Errors of Estimate (SEEs) for ten energy markets in comparison with the linear, the exponential/asymptotic and the static logistic model. Supplementary results obtained by statistical analysis of answers selected by circulating a questionnaire in the wider area of Attica in Greece, led to the conclusion that income/welfare, residential place and information play an important role as regards the intention of inhabitants to adopt the NG alternative. These results can be used for policy making as regards incentives offered to potential consumers (that constitute a dynamic market share rather than a static one) to accelerate the adoption of NG technology.