ppxscal/embedding_network huggingface dataset:
Grammar-driven generation of domain-specific language testing tools using aspects
Authors: Jeff Gray
Venue:  (2007)

Domain-specific languages (DSLs) assist a software developer (or end-user) in writing a program using idioms that are similar to the abstractions found in a specific problem domain. Testing tool support for DSLs is lacking when compared to the capabilities provided for standard general-purpose languages (GPLs), such as Java and C++. For example, support for debugging and unit testing a program written in a DSL is often non-existent. The lack of a debugger and unit test engine at the proper abstraction level limits an end-user's ability to discover and locate faults in a DSL program. This dissertation describes a grammar-driven technique to build a debugging and unit testing tool generation framework by adaptations to existing DSL grammars. This approach leverages existing GPL testing tools to indirectly exercise the end-user's debug and test intentions at the DSL level. The adaptations to DSL grammars represent the hooks needed to interface with a supporting infrastructure constructed for an Integrated Development Environment (IDE) that assists in debugging and unit testing a program written in a DSL. The contribution represents a coordinated approach to bring essential software tools (e.g., debuggers and test engines) to different types of DSLs (e.g., imperative, declarative, and hybrid). This approach hides from the end-users the accidental complexities associated with expanding the focus of a language environment to include testing tools. During the testing tool generation process, crosscutting concerns were observed in representations of DSL grammars. To address these particular crosscutting concerns, an investigation into the principles of aspect-oriented programming applied to grammars has been conducted. A domain-specific aspect language, called AspectG, has been designed and implemented, which is focused within the domain of language specification. This dissertation outlines the challenges and issues that exist when designing aspect languages that assist in modularizing crosscutting concerns in grammars. The research described in the dissertation addresses a long-term goal of empowering end-users with development tools for particular DSL problem domains at the proper level of abstraction without depending on a specific GPL.
Rayleigh quotient maximization via matrix direct product based factorization
Authors: Irem Yaman, Metin Demiralp
Venue: Proceedings of the 1st WSEAS International Conference on Multivariate Analysis and its Application in Science and Engineering (2008)

In this paper we focus on the maximization of Rayleigh Quotients. It is very well known that a Rayleigh Quotient's maximum value is the greatest eigenvalue of its numerator core matrix under the weighing of its denominator core matrix. Here we use core matrices which is are somehow the matrix representation of an algebraic multiplication operator whose action on its operand is simply multiplication by a function, univariate or multivariate. Hence the basic process is the evaluation of the greatest eigenvalue and the corresponding eigenvector. In the univariate case this process can be handled in accordance with the type and characteristic of the matrix but in multivariate case this issue may become more complicated. For that reason here we develop a quite new technique which factorizes the multivariate Rayleigh Quotient to univariate ratios and deal with the optimization of the univariate parts instead of tackling with the whole multivariate structure, by using Direct Product of the matrices.
(Mem)brane automata
Authors: Erzsébet Csuhaj-Varjú, György Vaszil
Venue: Theoretical Computer Science (2008)

We introduce the notion of a P automaton with marked membranes, a P"p"p automaton for short, which is an accepting variant of P systems. The concept is motivated by the theory of P systems, brane calculi, and the traditional concept of automata. In P systems with marked membranes, bio-molecules (proteins) are allowed to move through the membranes and to attach onto or to de-attach from the membranes. The membrane system evolves according to rules which are defined over multisets of proteins and describe the above actions. In addition to these features, the P automaton with marked membranes is able to consume inputs from its environment, i.e. multisets of proteins, which might influence the behaviour of the system. The result of the computation is the set of multiset sequences consumed by the skin membrane, supposing that the P"p"p automaton started functioning in the initial configuration and entered a final configuration at halting. We show that any recursively enumerable language can be obtained as the language accepted by a P"p"p automaton modulo a simple computable mapping.
Automatic Design of FPGA Processor for the Backtracking of DNA Sequences Evolution Using Cellular Automata and Genetic Algorithms
Authors: Georgios Ch. Sirakoulis
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

In several cases, the DNA sequences of an organism are available in different stages of its evolution and it is desirable to reconstruct the DNA sequence in a previous evolution stage for which the exact sequence is not known. A CAD tool for backtracking the DNA sequence evolution based on Cellular Automata (CA) and Genetic Algorithms (GAs) was developed. Furthermore, the proposed system is able of automatic production of synthesizable VHDL code corresponding to the CA model. More specifically, DNA is modeled as a one-dimensional CA with four states per cell, i.e. the four DNA bases A, C, T and G. Linear evolution rules, represented by square matrices, are considered. The evolution rule can be determined using the global state of the DNA sequence in various evolution steps. This determination is accomplished using GAs. Moreover, because of the final produced CA's binary states and its local rule simplicity, the hardware implementation of the proposed model is straightforward. Finally, the FPGA processor that executes the CA model was fully designed, placed and routed.
HyLive: Hypervideo-Authoring for Live Television
Authors: Peter Hoffmann, Tobias Kochems, Michael Herczeg
Venue: Proceedings of the 6th European conference on Changing Television Environments (2008)

In this paper we discuss the commonalities and differences of hypervideo and interactive television. We show that, even if the interaction and presentation of both are similar, there are strong differences in handling the content and the link structure of those media. The production and editorial process for live interactive television with hyperlinks and added value including production and editorial workflows is examined. The results led to a concept and a prototypical implementation for an editing tool and a web-based client player for interactive live television with hypervideo structures, called HyLive.
A New ID-Based Deniable Authentication Protocol
Authors: Rongxing Lu, Zhenfu Cao, Shengbao Wang, Haiyong Bao
Venue: Informatica (2007)

Deniable authenticated protocol is a new cryptographic authentication protocol that enables a designated receiver to identify the source of a given message without being able to prove the identity of the sender to a third party. Therefore, it can be applied to some particular situations in electronic commerce. In this paper, we formally define the security model for the non-interactive ID-based deniable authentication protocol and present a new efficient ID-based deniable authentication protocol based on RSA assumption. What's more, we also use the techniques from provable security to analyze the security of our proposed protocol.
Signalling extensions for QoS support in a IEEE 802.16d/e domain
Authors: Fausto Andreotti, Nicola Ciulli, Marilia Curado, Giada Landi, Cristina Nardini
Venue: Proceedings of the 7th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications (2008)

The IEEE 802.16 standard (WiMAX) provides a specification for fixed and mobile broadband wireless access system, offering high data rate transmission of multimedia services with different Quality-of-Service (QoS) requirements through the air interface. The WiMAX Forum, going beyond the air interface, has defined an end-to-en WiMAX network architecture, based on an all-IP platform. This paper focuses on the signalling needed in a WiMAX domain to support Session Initiation Protocol (SIP) applications with particular QoS requirements. The choice to use SIP-based applications is due to the fact that this protocol is the de -facto standard in NGN architecture, like the IP Multimedia Subsystem (IMS) proposed by the 3GPP2 consortium. Our studies aim at integrating the IMS vision (SIP-based) with the emerging IEEE 802.16 standards in order to guarantee end-to-end QoS for multimedia applications. Besides SIP at the application layer, other lower-layer protocols shall be considered in order to provide a complete end-to-end QoS support. The Next Step In Signalling (NSIS) protocol suite is used to reserve resources in the access and core wired segments. NSIS was chosen due to its usability and adaptability to multi-domain and QoS contexts. In detail, the integration among SIP signalling, resource allocation in the WiMAX wireless link and NSIS signalling is investigated. Results presented in this paper are the summary of the work performed within the framework of the European IST project WEIRD (WiMAX Extension to Isolated Research Data networks).
Complexity of terminating preference elicitation
Authors: Toby Walsh
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

Complexity theory is a useful tool to study computational issues surrounding the elicitation of preferences, as well as the strategic manipulation of elections aggregating together preferences of multiple agents. We study here the complexity of determining when we can terminate eliciting preferences, and prove that the complexity depends on the elicitation strategy. We show, for instance, that it may be better from a computational perspective to elicit all preferences from one agent at a time than to elicit individual preferences from multiple agents. We also study the connection between the strategic manipulation of an election and preference elicitation. We show that what we can manipulate affects the computational complexity of manipulation. In particular, we prove that there are voting rules which are easy to manipulate if we can change all of an agent's vote, but computationally intractable if we can change only some of their preferences. This suggests that, as with preference elicitation, a fine-grained view of manipulation may be informative. Finally, we study the connection between predicting the winner of an election and preference elicitation. Based on this connection, we identify a voting rule where it is computationally difficult to decide the probability of a candidate winning given a probability distribution over the votes.
Crowd Segmentation from a Static Camera
Authors: Bin Lai, Deng Yi Zhang, Zhi Yong Yuan, Jian Hui Zhao
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

This paper presents a more enhanced and efficient method for crowd segmentation from background subtracted images using active basis model associated detection cascade. Firstly, the problem is significant because the case of inter-human occlusion usually appears in the image which may disturb the result of tracking and recognition, consequently debases the effect of the whole surveillance system. Secondly, the problem is challenging because the state space formed by the number, positions, and articulations of people is large, and the noisy may confluence the achievement of the shape of the crowd of background subtracted. We combine some effective methods into one system for improving the hit rate in crowded scene, such as the head position estimation, active basis model, etc. Especially, using the active basis model to verify the result from detection cascade, the system gives the excellent performance for detecting human in crowded scene.
Computational complexity of dynamical systems: The case of cellular automata
Authors: P. Di Lena, L. Margara
Venue: Information and Computation (2008)

Cellular Automata can be considered discrete dynamical systems and at the same time a model of parallel computation. In this paper we investigate the connections between dynamical and computational properties of Cellular Automata. We propose a classification of Cellular Automata according to the language complexities which rise from the basins of attraction of subshift attractors and investigate the intersection classes between our classification and other three topological classifications of Cellular Automata. From the intersection classes we can derive some necessary topological properties for a cellular automaton to be computationally universal according to our model.
Hard vs. Fuzzy Clustering for Speech Utterance Categorization
Authors: Amparo Albalate, David Suendermann
Venue: Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems (2008)

To detect and describe categories in a given set of utterances without supervision, one may apply clustering to a space therein representing the utterances as vectors. This paper compares hard and fuzzy word clustering approaches applied to `almost' unsupervised utterance categorization for a technical support dialog system. Here, `almost' means that only one sample utterance is given per category to allow for objectively evaluating the performance of the clustering techniques. For this purpose, categorization accuracy of the respective techniques are measured against a manually annotated test corpus of more than 3000 utterances.
An application of the Turán theorem to domination in graphs
Authors: Erfang Shan, T. C. E. Cheng, Liying Kang
Venue: Discrete Applied Mathematics (2008)

A function f:V(G)->{+1,-1} defined on the vertices of a graph G is a signed dominating function if for any vertex v the sum of function values over its closed neighborhood is at least 1. The signed domination number@c"s(G) of G is the minimum weight of a signed dominating function on G. By simply changing ''{+1,-1}'' in the above definition to ''{+1,0,-1}'', we can define the minus dominating function and the minus domination number of G. In this note, by applying the Turan theorem, we present sharp lower bounds on the signed domination number for a graph containing no (k+1)-cliques. As a result, we generalize a previous result due to Kang et al. on the minus domination number of k-partite graphs to graphs containing no (k+1)-cliques and characterize the extremal graphs.
HK Segmentation of 3D Micro-structures Reconstructed from Focus
Authors: Muhammet A. Hocaoglu, Mustafa Unel
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

This paper presents an evaluation of HK segmentation on 3D micro-structures reconstructed from focus. Due to the necessity of 3D shape and surface structure information for a precise micromanipulation, shape of the object is recovered using shape from focus (SFF). In the SFF procedure, using an image sequence, composed of images captured at different focusing levels, focused image of the micro-structure and its shape are acquired. Then the resulting shape, also called range image, is used in HK segmentation method to extract surface curvature information. Experimental results show that this technique works for both synthetic and real data.
Robotic introspection for exploration and mapping of subterranean environments
Authors: William (Red) Whittaker
Venue:  (2007)

This thesis identifies operational uncertainty as a significant problem affecting reliable robot performance in real environments. Operational uncertainty represents ambiguity in a robot's self-perceived state during the execution of a task. This ambiguity is introduced into a robotic system through events such as unanticipated environmental disturbances, failing hardware and software built upon invalid assumptions. Real environments such as forests, caves, oceans and space foster operational ambiguity, which confound robot software and hinder reliable performance.To address operational uncertainty in the general case, a robot is required to assess both the environment and itself to determine the nature of a problem and the appropriate means to react. Environmental assessment (i.e. perception) is a well-understood and highly addressed problem in robotics research. As such, this thesis focuses upon the latter topic: self assessment.This thesis develops a framework called robotic introspection to provide a self assessment mechanism for field-capable robots. Robotic introspection models and monitors operational state (i.e. a robot's computational state) to assist robotic decision-making. In particular, this research develops an architectural framework for observing, mapping, localizing and planning in the space of operating modes.For this thesis, the subterranean domain is used to describe and illustrate the problem of operational uncertainty and to implement and experiment with robotic introspection. This domain is an ideal medium for conveying these concepts and generalizes well to robots operating in other field environments. The work presented in this document is the first to develop robotic introspection for autonomy on a field robotic platform. This introspective framework is shown to effectively handle uncertain situations, thereby justifying its role on autonomous subterranean robots. In addition, this work provides irrefutable evidence establishing robots as capable, thorough, and efficient tools for subterranean data collection. Unique to this research, trials of robot deployment have occurred in an assortment of underground environments across a spectrum of conditions including flooded, dry, muddy, confined, open, smoke-filled, borehole entry, and portal entry. From these trials, this work has produced an unrivaled repository of subterranean data, including the largest 3-D metric models of interior underground surfaces known to date.
Client-Friendly Classification over Random Hyperplane Hashes
Authors: Shyamsundar Rajaram, Martin Scholz
Venue: Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II (2008)

In this work, we introduce a powerful and general feature representation based on a locality sensitive hash scheme called random hyperplane hashing. We are addressing the problem of centrally learning (linear) classification models from data that is distributed on a number of clients, and subsequently deploying these models on the same clients. Our main goal is to balance the accuracy of individual classifiers and different kinds of costs related to their deployment, including communication costs and computational complexity. We hence systematically study how well schemes for sparse high-dimensional data adapt to the much denser representations gained by random hyperplane hashing, how much data has to be transmitted to preserve enough of the semantics of each document, and how the representations affect the overall computational complexity. This paper provides theoretical results in the form of error bounds and margin based bounds to analyze the performance of classifiers learnt over the hash-based representation. We also present empirical evidence to illustrate the attractive properties of random hyperplane hashing over the conventional baseline representation of bag of words with and without feature selection.
Instance-Based Query Answering with Semantic Knowledge Bases
Authors: Nicola Fanizzi, Claudia D'Amato, Floriana Esposito
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

A procedure founded in instance-based learning is presented, for performing a form of analogical reasoning on knowledge bases expressed in a wide range of ontology languages. The procedure exploits a novel semi-distance measure for individuals, that is based on their semantics w.r.t. a number of dimensions corresponding to a committee of features represented by concept descriptions. The procedure can answer by analogy to class'membership queries on the grounds of the classification of a number of training instances (the nearest ones w.r.t. the semi-distance measure). Particularly, it may also predict assertions that are not logically entailed by the knowledge base. In the experimentation, where we compare the procedure to a logical reasoner, we show that it can be quite accurate and augment the scope of its applicability, outperforming previous prototypes that adopted other semantic measures.
Research on Affective Computing Model in E-Learning System
Authors: Ruiming Zhao, Zhenhui Ren, Li Zhang, Ruiguo Qin
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Emotion deficiency was a hot topic research in current E-learning system. A lot of negative effects were analyzed and corresponding counter- measures were proposed in the paper. Basing on it, affective computing model was set up and used in the traditional E-learning system. Affective computing model was constructed by using audiovisual emotion, which took both facial and audio features as input data. Rough set theory was used in audiovisual emotion recognition. Our simulation experiment results showed that Rough set theory was effective in emotion recognition, and a high recognition rate was resulted.
Adaptive Robust Motion Controller with Friction and Ripple Disturbance Compensation Via RBF Networks
Authors: Zi-Jiang Yang, Shunshoku Kanae, Kiyoshi Wada
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

In this paper, a practical adaptive robust nonlinear controller is proposed for motion control of an SISO nonlinear mechanical system, where the distrubances due to ripple force and friction are compensated by the RBF networks. Rigorous analysis of transient performance and ultimate bound is given. Numerical examples are included to verify the theoretical results.
On calculation of radiation field integrals for higher-order basis functions in conical thin wire MoM formulation
Authors: Albert A. Lysko
Venue: Proceedings of the 6th WSEAS International Conference on Applied Electromagnetics, Wireless and Optical (2008)

An efficient method of integration for far field calculations is derived. The method applies to the integrals arising from calculation of far field pattern with higher-order polynomial basis functions and moment method. The integral under consideration is a product of a power and exponential functions. Depending on the electrical length of the integration path and the required accuracy, either integration by parts or small parameter expansion is applied, in a recursive manner. The speed performance of a Matlab implementation indicates that the presented method is favorable compared to the commercial software "WIPL-D" used as a reference.