ppxscal/embedding_network huggingface dataset:
Points with Type-2 Operations
Authors: Carol L. Walker, Elbert A. Walker
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

The algebra of truth values for fuzzy sets of type-2, due to Zadeh, contains as subalgebras those of type-1 and of interval-valued fuzzy sets. It also contains many other interesting subalgebras, some of which could possibly serve as a basis of a useful fuzzy set theory. This paper is about one such subalgebra which we call the subalgebra of points, and which generalizes type-1. We investigate it as an algebra, and determine its automorphism group. In particular, we show that is it a characteristic subalgebra and that its automorphisms are exactly those induced by automorphisms of the containing truth value algebra of fuzzy sets of type-2.
A Rough Set and Fuzzy Neural Petri Net Based Method for Dynamic Knowledge Extraction, Representation and Inference in Cooperative Multiple Robot System
Authors: Hua Xu, Yuan Wang, Peifa Jia
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

In cooperative multiple robot systems (CMRS), dynamic knowledge representation and inference is the key in scheduling robots to fulfill the cooperation requirements. The first goal of this work is to use rough set based rules generation method to extract dynamic knowledge of our CMRS. Kang's rough set based rules generation method is used to get fuzzy dynamic knowledge from practical decision data. The second goal of this work is to use Fuzzy Neural Petri nets (FNPN) to represent and infer the dynamic knowledge on the base of dynamic knowledge extraction with self-learning ability. In particular, we investigate a new way to extract, represent and infer dynamic knowledge with self-learning ability in CMRS. Finally, the effectiveness of the dynamic knowledge extraction, representation and inference procedure are demonstrated.
Analysing All Polynomial Equations in ${\mathbb Z_{2^w}}$
Authors: Helmut Seidl, Andrea Flexeder, Michael Petter
Venue: Proceedings of the 15th international symposium on Static Analysis (2008)

In this paper, we present methods for checking and inferring all valid polynomial relations in ${\mathbb Z_{2^w}}$. In contrast to the infinite field ¿, ${\mathbb Z_{2^w}}$ is finite and hence allows for finitely many polynomial functions only. In this paper we show, that checking the validity of a polynomial invariant over ${\mathbb Z_{2^w}}$ is, though decidable, only PSPACE-complete. Apart from the impracticable algorithm for the theoretical upper bound, we present a feasible algorithm for verifying polynomial invariants over ${\mathbb Z_{2^w}}$ which runs in polynomial time if the number of program variables is bounded by a constant. In this case, we also obtain a polynomial-time algorithm for inferring all polynomial relations. In general, our approach provides us with a feasible algorithm to infer all polynomial invariants up to a low degree.
Image classification using principal feature analysis
Authors: Omid Khayat, Hamid Reza Shahdoosti, Mohammad Hosein Khosravi
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

Classification technology is essential for fast retrieval in large database. This paper proposes a combining Principal Feature Analysis (PFA) and SVM model to content-based image retrieval. The proposed method is also used to classification similar images from database. Joint HSV histogram and average entropy computed from gray-level co-occurrence matrices in the localized image region is employed as input vectors. PFA is employed to select feature subsets (choosing principal features) eliminated irrelevant factors as used inputs and to determine the optimal parameters of Support Vector Machine. Experimental results show that the proposed model outperforms existing method.
Evaluating the usefulness of software visualization in supporting software comprehension activities
Authors: Glauco de Figueiredo Carneiro, Rodrigo Chaves Magnavita, Eduardo Spinola, Fabio Spinola, Manoel Mendonça
Venue: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement (2008)

Modern IDEs offer built-in support for developing plug-ins. More recently, we have seen a growing number of plug-ins that offer non-conventional software visualization interfaces. They usually aim to help programmers to understand unfamiliar source code by representing it in visual structures such as trees, scatter-plots or graphs. Although very attractive visually, we need to know more about the effectiveness of these interfaces in conveying information to software engineers. In this paper, we propose an infrastructure to empirically evaluate how useful are non-conventional visual paradigms in supporting software comprehension activities. The results for the first pilot study indicated that our experimental environment was consistent and could move to a full scale controlled experiment.
Service-Oriented Architectures and Software Product Lines - Putting Both Together
Authors: Robert Krut, Sholom Cohen
Venue: Proceedings of the 2008 12th International Software Product Line Conference (2008)

product line (SPL) approaches to software development share a common goal. They both encourage an organization to reuse existing assets and capabilities, rather than repeatedly redevelop them for new systems.
Decentralised dynamic code management for OSGi
Authors: Holger Schmidt, Jon H. Yip, Franz J. Hauck, Rüdiger Kapitza
Venue: Proceedings of the 6th workshop on Middleware for network eccentric and mobile applications (2008)

Originally designed for the management of network-attached devices OSGi builds a de-facto standard to modularise all kinds of complex Java applications. It enables deployment and updating of components, which are called bundles, by supporting automatic resolution of inter-component dependencies. Despite these benefits the OSGi specification omits dedicated support for discovery, selection and loading of locally unavailable bundles. However, this is a key requirement for large distributed applications especially in dynamic and heterogeneous environments. Current solutions are server-based and provide a central bundle repository thereby representing a single point of failure. Furthermore, these approaches lack support for automatic bundle selection based on non-functional properties such as resource demand or performance. We introduce the D2CM infrastructure accounting these issues and enabling automatic discovery, selection and loading of bundles in a distributed system on basis of the peer-to-peer platform JXTA. By providing extended bundle descriptions, non-functional properties can be automatically evaluated for bundle selection and dependency resolution.
MAD Loss in Pattern Recognition and RBF Learning
Authors: Ewaryst Rafajłowicz, Ewa Skubalska-Rafajłowicz
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

We consider a multi-class pattern recognition problem with linearly ordered labels and a loss function, which measures absolute deviations of decisions from true classes. In the bayesian setting the optimal decision rule is shown to be the median of a posteriori class probabilities. Then, we propose three approaches to constructing an empirical decision rule, based on a learning sequence. Our starting point is the Parzen-Rosenblatt kernel density estimator. The second and the third approach are based on radial bases functions (RBF) nets estimators of class densities.
Highly Efficient Password-Based Three-Party Key Exchange in Random Oracle Model
Authors: Hung-Yu Chien, Tzong-Chen Wu
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

A password-based three-party encrypted key exchange (3PEKE) is a protocol enables any pair of two registered clients to establish session keys via the help of a trusted server such that each client shares only one password with the server. This approach greatly improves the scalability of key agreement protocol in distributed environments, and provides great user convenience. This paper proposes a new password-based 3PEKE scheme with only four message steps, which is the minimum among the published works. The proposed scheme is secure in the random oracle model.
Practical Techniques for Operating System Attestation
Authors: Paul England
Venue: Proceedings of the 1st international conference on Trusted Computing and Trust in Information Technologies: Trusted Computing - Challenges and Applications (2008)

This paper describes three practical techniques for authenticating the code and other execution state of an operating system using the services of the TPM and a hypervisor. The techniques trade off detailed reporting of the OS code and configuration with the manageability and comprehensibility of reported configurations. Such trade-offs are essential because of the complexity and diversity of modern general purpose operating systems makes simple code authentication schemes using code hashes or certificates infeasible.
An Alternative Splicing Predictor in C.Elegans Based on Time Series Analysis
Authors: Michele Ceccarelli, Antonio Maratea
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

Prediction of Alternative Splicing has been traditionally based on expressed sequences' study, helped by homology considerations and the analysis of local discriminative features. More recently, Machine Learning algorithms have been developed that try avoid the use of a priori information, with partial success. Here we approach the prediction of Alternative Splicing as a time series analysis problem and we show that it is possible to obtain results similar or better than the state of the art without any explicit modeling of homology, positions in the splice site, nor any use of other local features. As a consequence, our method has a better generality and a broader and simpler applicability with respect to previous ones. Results on pre-mRNA sequences in C.Elegans are reported.
Detection of Various Defects in TFT-LCD Polarizing Film
Authors: Sang-Wook Sohn, Dae-Young Lee, Hun Choi, Jae-Won Suh, Hyeon-Deok Bae
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

The increasing use of TFT-LCDs has generated a great deal of interest in manufacturing defects on TFT-LCD polarizing film because the poor quality of TFT-LCD polarizing film result in undesirable effects on the TFT-LCD display devices. In this paper, we propose a new inspection method that reliably detects various defects of TFT-LCD polarizing films. First, we apply a least mean squares adaptive filtering technique to remove background noise. Next, we use statistical characteristics to detect possible defects. Finally, we make a binary image to identify weather the TFT-LCD polarizing film has defects or not based on an adaptive threshold value. The performance of the proposed method has been evaluated on real TFT-LCD polarizing film samples.
An Infinite Automaton Characterization of Double Exponential Time
Authors: Salvatore Torre, P. Madhusudan, Gennaro Parlato
Venue: Proceedings of the 22nd international workshop on Computer Science Logic (2008)

Infinite-state automata are a new invention: they are automata that have an infinite number of states represented by words, transitions defined using rewriting, and with sets of initial and final states. Infinite-state automata have gained recent interest due to a remarkable result by Morvan and Stirling, which shows that automata with transitions defined using rational rewriting precisely capture context-sensitive (NLinSpace) languages. In this paper, we show that infinite automata defined using a form of multi-stack rewriting precisely defines double exponential time (more precisely, 2ETime, the class of problems solvable in $2^{2^{O(n)}}$ time). The salient aspect of this characterization is that the automata have no ostensible limits on time nor space, and neither direction of containment with respect to 2ETime is obvious. In this sense, the result captures the complexity class qualitatively, by restricting the power of rewriting.
Two neural networks architectures for detecting AVB
Authors: Salama Meghriche, Mohammed Boulemden, Amer Draa
Venue: Proceedings of the 8th WSEAS International Conference on Multimedia systems and signal processing (2008)

The purpose of the paper is to present two networks. These networks were fed with same measurements from one lead of the electrocardiogram (ECG) but in different architectures. The first one based on a compound neural network (CNN) composed of three different multilayer neural networks of the feed forward type, and the second one based on only a multi-layer perceptron (MLP). Such both of them have the capability to classify ECGs as carrying atrioventricular blocks (AVB) or not. For each test case in the test set the neural networks classifier present an output value between 0 and 1. A threshold in this interval was used above which all values were regarded as consistent with AVB. The difference in performance between the two neural networks classifiers was measured as the difference in area under the receiver operating characteristic (ROC) curves.
HESA: A Human-Centric Evolvable Situation-Awareness Model in Smart Homes
Authors: Hojun Jaygarl, Katsunori Oyama, Jinchun Xia, Carl K. Chang
Venue: Proceedings of the 6th international conference on Smart Homes and Health Telematics (2008)

Situation Awareness is a paradigm that contains data gathering, logic reasoning and responsive interaction to capture situations, which describe system states, from dynamic environments. Focusing on evolvability issue, we proposes a generic Situation Awareness System (SAS) model, called Human-centric Evolvable Situation-Awareness (HESA). In this paper, we present the HESA architecture, accommodation/evolution processes, and how we use Context/Situation Generation approach to provide human-centric fault-tolerant evolvability.
TTool for DIPLODOCUS: an environment for design space exploration
Authors: Ludovic Apvrille
Venue: Proceedings of the 8th international conference on New technologies in distributed systems (2008)

TTool for DIPLODOCUS is an open-source UML-based toolkit for the design space exploration of system-on-chip. DIPLODOCUS is the name of the underlying UML profile. This profile includes a three-step methodology: a description of application tasks, a description of candidate distributed architectures, and the mapping of application tasks onto those candidate architectures. Our contribution not only offers SystemC-based automatic simulation but also automatic formal verification, in both cases directly from UML diagrams.
A Comparative Evaluation of Anomaly Detectors under Portscan Attacks
Authors: Ayesha Binte Ashfaq, Maria Joseph Robert, Asma Mumtaz, Muhammad Qasim Ali, Ali Sajjad, Syed Ali Khayam
Venue: Proceedings of the 11th international symposium on Recent Advances in Intrusion Detection (2008)

Since the seminal 1998/1999 DARPA evaluations of intrusion detection systems, network attacks have evolved considerably. In particular, after the CodeRed worm of 2001, the volume and sophistication of self-propagating malicious code threats have been increasing at an alarming rate. Many anomaly detectors have been proposed, especially in the past few years, to combat these new and emerging network attacks. At this time, it is important to evaluate existing anomaly detectors to determine and learn from their strengths and shortcomings. In this paper, we evaluate the performance of eight prominent network-based anomaly detectors under malicious portscan attacks. These ADSs are evaluated on four criteria: accuracy (ROC curves), scalability (with respect to varying normal and attack traffic rates, and deployment points), complexity (CPU and memory requirements during training and classification,) and detection delay. These criteria are evaluated using two independently collected datasets with complementary strengths. Our results show that a few of the anomaly detectors provide high accuracy on one of the two datasets, but are unable to scale their accuracy across the datasets. Based on our experiments, we identify promising guidelines to improve the accuracy and scalability of existing and future anomaly detectors.
Closure of Hedge-Automata Languages by Hedge Rewriting
Authors: Florent Jacquemard, Michael Rusinowitch
Venue: Proceedings of the 19th international conference on Rewriting Techniques and Applications (2008)

We consider rewriting systems for unranked ordered terms, i.e. trees where the number of successors of a node is not determined by its label, and is not a priori bounded. The rewriting systems are defined such that variables in the rewrite rules can be substituted by hedges (sequences of terms) instead of just terms. Consequently, this notion of rewriting subsumes both standard term rewriting and word rewriting.We investigate some preservation properties for two classes of languages of unranked ordered terms under this generalization of term rewriting. The considered classes include languages of hedge automata (HA) and some extension (called CF-HA) with context-free languages in transitions, instead of regular languages.In particular, we show that the set of unranked terms reachable from a given HA language, using a so called inverse context-free rewrite system, is a HA language. The proof, based on a HA completion procedure, reuses and combines known techniques with non-trivial adaptations. Moreover, we prove, with different techniques, that the closure of CF-HA languages with respect to restricted context-free rewrite systems, the symmetric case of the above rewrite systems, is a CF-HA language. As a consequence, the problems of ground reachability and regular hedge model checking are decidable in both cases. We give several counter examples showing that we cannot relax the restrictions.
A class of residual distribution schemes and their relation to relaxation systems
Authors: James A. Rossmanith
Venue: Journal of Computational Physics (2008)

Residual distributions (RD) schemes are a class of high-resolution finite volume methods for unstructured grids. A key feature of these schemes is that they make use of genuinely multidimensional (approximate) Riemann solvers as opposed to the piecemeal 1D Riemann solvers usually employed by finite volume methods. In 1D, LeVeque and Pelanti [R.J. LeVeque, M. Pelanti, A class of approximate Riemann solvers and their relation to relaxation schemes, J. Comput. Phys. 172 (2001) 572] showed that many of the standard approximate Riemann solver methods (e.g., the Roe solver, HLL, Lax-Friedrichs) can be obtained from applying an exact Riemann solver to relaxation systems of the type introduced by Jin and Xin [S. Jin, Z.P. Xin, Relaxation schemes for systems of conservation-laws in arbitrary space dimensions, Commun. Pure Appl. Math. 48 (1995) 235]. In this work we extend LeVeque and Pelanti's results and obtain a multidimensional relaxation system from which multidimensional approximate Riemann solvers can be obtained. In particular, we show that with one choice of parameters the relaxation system yields the standard N-scheme. With another choice, the relaxation system yields a new Riemann solver, which can be viewed as a genuinely multidimensional extension of the local Lax-Friedrichs scheme. This new Riemann solver does not require the use Roe-Struijs-Deconinck averages, nor does it require the inversion of an mxm matrix in each computational grid cell, where m is the number of conserved variables. Once this new scheme is established, we apply it on a few standard cases for the 2D compressible Euler equations of gas dynamics. We show that through the use of linear-preserving limiters, the new approach produces numerical solutions that are comparable in accuracy to the N-scheme, despite being computationally less expensive.
The Challenging Face of Informatics Education in Poland
Authors: Maciej M. Sysło, Anna Beata Kwiatkowska
Venue: Proceedings of the 3rd international conference on Informatics in Secondary Schools - Evolution and Perspectives: Informatics Education - Supporting Computational Thinking (2008)

In this paper, a learning and teaching framework is described which is aimed at increasing student interest in studying computer science as a discipline, or at least in better understanding how a computer and its tools work and can be used in solving problems which may occur in different areas.In the beginning of information education in Poland, in the mid 80's, the informatics curricula for schools and teaching were focused on computer science. Then, in the beginning of the 90's, with the growing popularity and wide use of end-user friendly software, the emphasis in education has moved from computer science to information technology, from constructing computer solutions to using ready-made tools, from computer science for some students to information technology for all. We demonstrate here, however, how teaching and learning information technology can be used to enhance algorithmic and computational thinking in solving with computers, problems which arise in various school subjects, learning disciplines and in real life.We strongly believe that the learning methodology presented here, about computer use by students and applying computers and information technology to solving problems, would be a good motivation and preparation for their future decisions to study computing and become computer specialists.
Merry Christma: An Early Network Worm
Authors: Peter G. Capek, David M. Chess, Steve R. White
Venue: IEEE Security and Privacy (2003)

A computer worm, disguised as a benign holiday greeting, spread rapidly via email and clogged up networks worldwide. The story is all too common today, but this happened to corporate and university mainframes in 1987, in the infancy of the computer virus problem, even before the famous Internet, or Morris, worm.
Social Control of Herd Animals by Integration of Artificially Controlled Congeners
Authors: Nikolaus Correll, Mac Schwager, Daniela Rus
Venue: Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats (2008)

We study social control of a cow herd in which some of the animals are controlled by a sensing and actuation device mounted on the cow. The control is social in that it aims at exploiting the existing gregarious behavior of the animals, rather than controlling each individual directly. As a case study we consider the open-loop control of the herd's position using location-dependent stimuli. We propose a hybrid dynamical model for capturing the dynamics of the animals during periods of grazing and periods of stress. We assume that stress can either be induced by the sensing and actuation device or by social amplification due to observing/overhearing nearby stressed congeners. The dynamics of the grazing part of the proposed model have been calibrated using experimental data from 10 free-ranging cows, and various assumptions on the animal behavior under stress are investigated by a parameter sweep on the hybrid model. Results show that the gregarious behavior of the animals must be increased during stress for control by undirected stimuli to be successful. We also show that the presence of social amplification of stress allows for robust, low-stress control by controlling only a fraction of the herd.