ppxscal/embedding_network huggingface dataset:
Well-structured languages
Authors: Gilles Geeraerts, Jean-Fran&#x00e7;ois Raskin, Laurent Van Begin
Venue: Acta Informatica (2007)

This paper introduces the notion of well-structured language. A well-structured language can be defined by a labelled well-structured transition system, equipped with an upward-closed set of accepting states. That peculiar class of transition systems has been extensively studied in the field of computer-aided verification, where it has direct an important applications. Petri nets, and their monotonic extensions (like Petri nets with non-blocking arcs or Petri nets with transfer arcs), for instance, are special subclasses of well-structured transition systems. We show that the class of well-structured languages enjoy several important closure properties. We propose several pumping lemmata that are applicable respectively to the whole class of well-structured languages and to the classes of languages recognized by Petri nets or Petri nets with non-blocking arcs. These pumping lemmata allow us to characterize the limits in the expressiveness of these classes of language. Furthermore, we exploit the pumping lemmata to strictly separate the expressive power of Petri nets, Petri nets with non-blocking arcs and Petri nets with transfer arcs.
A Graph Based Approach to Discover Conserved Regions in DNA and Protein Sequences
Authors: Santan Challa, Parimala Thulasiraman
Venue: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 01 (2007)

This paper attempts to provide a graph based approach to discover conserved regions such as motifs in either DNA or Protein sequences. The motif discovery problem has gained lot of significance in biological science over the past decade. Lately various approaches have been used successfully to discover motifs. Some of them are based on probabilistic approach and the others on a combinatorial approach. We have followed a graph-based combinatorial approach to solve this problem, in particular, using the idea of de Bruijn graphs. The de Bruijn graph has been successfully adopted to solve problems such as local alignment and DNA fragment assembly. Our method harnesses the power of the de Bruijn graph to discover the conserved regions in a DNA or protein sequence. We have found that the algorithm was successful in mining signals for larger number of sequences and at a faster rate when compared to some popular motif searching tools.
Generic extensions of WWW browsers
Authors: Ralf Hauser, Michael Steiner
Venue: Proceedings of the 1st conference on USENIX Workshop on Electronic Commerce - Volume 1 (1995)

Current WWW browsers provide two main services: communication and information rendering. While this is sufficient for some purposes, many future applications will need more sophisticated processing on the user side before server-data can be presented to the user or before the user input can be transferred to the servers. For example, electronic payments ought to be seamlessly integrated into a customer's browser to enable him to shop via the Web. This paper proposes two pragmatic approaches to fulfill these requirements without altering current browser technology. We conclude with the proposal of a generalized extension framework for WWW browsers.
Improved methods for vocal tract normalization
Authors: L. Welling
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02 (1999)

This paper presents improved methods for vocal tract normalization (VTN) along with experimental tests on three databases. We propose a new method for VTN in training: by using acoustic models with single Gaussian densities per state for selecting the normalization scales the need for the models to learn the normalization scales of the training speakers is avoided. We show that using single Gaussian densities for selecting the normalization scales in training results in lower error rates than using mixture densities. For VTN in recognition, we propose an improvement of the well-known multiple-pass strategy: by using an unnormalized acoustic model for the first recognition pass instead of a normalized model lower error rates are obtained. In recognition tests, this method is compared with a fast variant of VTN. The multiple-pass strategy is an efficient method but it is suboptimal because the normalization scale and the word sequence are determined sequentially. We found that for telephone digit string recognition this suboptimality reduces the VTN gain in recognition performance by 30% relative. On the German spontaneous scheduling task Verbmobil, the WSJ task and the German telephone digit string corpus SieTill the proposed methods for VTN reduce the error rates significantly.
Efficient and secure self-escrowed public-key infrastructures
Authors: Jaimee Brown, Juan M. Gonzalez Nieto, Colin Boyd
Venue: Proceedings of the 2nd ACM symposium on Information, computer and communications security (2007)

A self-escrowed public key infrastructure (SE-PKI) combines the usual functionality of a public-key infrastructure with the ability to recover private keys given some trap-door information. We present an additively homomorphic variant of an existing SE-PKI for ElGamal encryption. We also propose a new efficient SE-PKI based on the ElGamal and Okamoto-Uchiyama cryptosystems that is more efficient than the previous SE-PKI. This is the first SE-PKI that does not suffer from a key doubling problem of previous SE-PKI proposals. Additionally, we present the first self-escrowed encryption schemes secure against chosen-ciphertext attack in the standard model. These schemes are also quite efficient and are based on the Cramer-Shoup cryptosystem, and the Kurosawa-Desmedt hybrid variant in different groups.
Digital Circuit Testing on a Network of Workstations
Authors: Sanjay Srinivasan, James H. Aylor
Venue: Proceedings of the 1994 International Conference on Parallel Processing - Volume 03 (1994)

This paper presents preliminary results of research being conducted in the application of distributed/parallel algorithms to automatic test pattern generation for synchronous sequential circuits. The system is required to be portable across a wide variety of architectures -from workstations to dedicated parallel machines. This requirement necessitates the use of a parallel programming environment that provides a layer of abstraction between the application and the hardware. The first phase of the proposed system involves generation of circuit covers - input patterns that control the circuit outputs.
Design and evaluation of packet classification systems
Authors: Jonathan S. Turner
Venue:  (2006)

Although many algorithms and architectures have been proposed, the design of efficient packet classification systems remains a challenging problem. The diversity of filter specifications, the scale of filter sets, and the throughput requirements of high-speed networks all contribute to the difficulty. We need to review the algorithms from a, high-level point-of-view in order to advance the study. This level of understanding can lead to significant performance improvements. In this dissertation, we evaluate several existing algorithms and present several new algorithms as well. The previous evaluation results for existing algorithms are not convincing because they have not been done in a consistent way. To resolve this issue, an objective evaluation platform needs to be developed. We implement and evaluate several representative algorithms with uniform criteria. The source code and the evaluation results are both published on a web-site to provide the research community a benchmark for impartial and thorough algorithm evaluations. We propose several new algorithms to deal with the different variations of the packet classification problem. They are: (1) the Shape Shifting Trie algorithm for longest prefix matching, used in IP lookups or as a building block for general packet classification algorithms; (2) the Fast Hash Table lookup algorithm used for exact flow match; (3) the longest prefix matching algorithm using hash tables and tries, used in IP lookups or packet classification algorithms; (4) the 2D coarse-grained tuple-space search algorithm with controlled filter expansion, used for two-dimensional packet classification or as a building block for general packet classification algorithms; (5) the Adaptive Binary Cutting algorithm used for general multi-dimensional packet classification. In addition to the algorithmic solutions, we also consider the TCAM hardware solution. In particular, we address the TCAM filter update problem for general packet classification and provide an efficient algorithm. Building upon the previous work, these algorithms significantly improve the performance of packet classification systems and set a solid foundation for further study.
Metadata driven memory optimizations in dynamic binary translator
Authors: Chaohao Xu, Jianhui Li, Tao Bao, Yun Wang, Bo Huang
Venue: Proceedings of the 3rd international conference on Virtual execution environments (2007)

A dynamic binary translator offers solutions for translating and running source architecture binaries on target architecture at runtime. Regardless of its growing popularity, practical dynamic binary translators usually suffer from the limited optimizations performed when generating the translated code due to the lack of useful information available in the executable files and the requirement to conform to the binary-level compatibility. Trying to generate more efficient translated code, we propose in this paper a novel method of passing performance critical information to a dynamic binary translator through the metadata section generated during the static compilation phase. With the performance critical metadata, the dynamic binary translator is able to perform aggressive optimizations to generate higher quality code. We implemented a general and extensible framework in GCC 4.0 and IA-32® Execution Layer, and selected metadata related to memory optimizations as our target. The metadata enables IA-32 EL to perform memory optimizations such as registerization, memory ordering relaxation and address disambiguation of memory instructions. Experimental data shows an overall performance improvement of 15.03% for SPECfp2000 and 1.21% for SPECint2000. For some specific benchmarks, the performance improvement is even up to 37.09%.
Interpolation for wireless sensor network coverage
Authors: R. Tynan, G. M. P. O'Hare, D. Marsh, D. O'Kane
Venue: Proceedings of the 2nd IEEE workshop on Embedded Networked Sensors (2005)

One of the primary issues for any wireless sensor network (WSN) deployment is that of longevity of the network. The lifespan of the network must be maximized while maintaining the quality of the sensory data received from the network. Most current solutions for achieving this require the definition of a sensing radius for each sensor together with a coverage level k. The sensed area is covered if every point within the area is inside the sensing radius of at least k sensors. When some points are covered by more than k sensors, it may be possible to instruct the surplus sensors to enter a low power sleep mode. This will conserve the energy of the network while maintaining the required coverage level. In. this paper we propose a novel alternative to this approach based on interpolation. If the sensor network is capable of interpolating the sensed medium at a given sensor's location to a specified accuracy or higher, then we propose that this sensor is redundant and can be put into sleep mode. We demonstrate our approach using live sensory data.
Advanced OSGi Security Layer
Authors: Chi-Chih Huang, Pang-Chieh Wang, Ting-Wei Hou
Venue: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02 (2007)

This paper first discusses the inner security of OSGi and proposes an Advanced OSGi Security Layer to prevent services from attacking the OSGi platform. We review the existing threats in Java security and we rephrase the threats within OSGi service level. A rule-based control list and a threat detector are introduced to the OSGi framework. A software sensor is deployed in our design which detects service behaviors. The behaviors can be analyzed by the Detector, which notifies the Response Manager to perform pre-defined rules. Malicious services that are harmful to other services or OSGi framework can be stopped so that other services work safely in the open environment.
Compression with reversible embedded wavelets with an enhanced binary mode
Authors: A. Zandi
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04 (1996)

Compression with reversible embedded wavelets (CREW) is a unified lossless and lossy continuous-tone still image compression system. Wavelet coefficients are encoded in a bit-significance embedded order, allowing lossy compression by truncating the compressed data after encoding. CREW's context-based coding, called Horizon coding, takes advantage of the spatial and spectral information available in the wavelet domain and adapts well to the lessor significant bits. CREW's capabilities have been enhanced to include a binary mode for compression of binary and graphic images. This also improves compression on some images that do not use the full dynamic range. The binary mode encodes bit-planes of the image without using the transform. This JBIG-like system uses the resources already available in the CREW system. This paper introduces some basic concepts of CREW and describes the binary mode in detail.
Dynamic test input generation for database applications
Authors: Michael Emmi, Rupak Majumdar, Koushik Sen
Venue: Proceedings of the 2007 international symposium on Software testing and analysis (2007)

We describe an algorithm for automatic test input generation for database applications. Given a program in an imperative language that interacts with a database through API calls, our algorithm generates both input data for the program as well as suitable database records to systematically explore all paths of the program, including those paths whose execution depend on data returned by database queries. Our algorithm is based on concolic execution, where the program is run with concrete inputs and simultaneously also with symbolic inputs for both program variables as well as the database state. The symbolic constraints generated along a path enable us to derive new input values and new database records that can cause execution to hit uncovered paths. Simultaneously, the concrete execution helps to retain precision in the symbolic computations by allowing dynamic values to be used in the symbolic executor. This allows our algorithm, for example, to identify concrete SQL queries made by the program, even if these queries are built dynamically. The contributions of this paper are the following. We develop an algorithm that can track symbolic constraints across language boundaries and use those constraints in conjunction with a novel constraint solver to generate both program inputs and database state. We propose a constraint solver that can solve symbolic constraints consisting of both linear arithmetic constraints over variables as well as string constraints (string equality, disequality, as well as membership in regular languages). Finally, we provide an evaluation of the algorithm on a Java implementation of MediaWiki, a popular wiki package that interacts with a database back-end.
A Kleene Algebra Framework for Data Flow Analysis
Authors: Therrezinha Fernandes
Venue: Proceedings of the 2007 Australian Software Engineering Conference (2007)

Data flow analysis is concerned with the static determination of relevant properties of the execution state of programs. Using Kleene algebra we develop a general framework for the formalization of a set of well-known data flow analysis problems. This approach permits an elegant yet rigorous treatment of the data flow problems and provide an intuitive cookbook style description of the formalization. We also prove the soundness of the approach with respect to the standard approach and illustrate the method on a concrete example.
Active learning using inexpensive sound cards for circuits and communications experiments
Authors: D. Mehrl
Venue: Proceedings of the 28th Annual Frontiers in Education - Volume 03 (1998)

The sound card has become standard equipment in most computer ensembles. We discuss how Sound Blaster 16 cards, and their later generation successors, can be used to create a simple and inexpensive (audio frequency) network- or spectrum-analyzer. By use of existing shareware software, students may use the sound card to excite an external circuit with an audio tone, and simultaneously record the response of the circuit. In past work we have used various audio tones to excite the circuit, including linear- and exponentially-(frequency)-chirped tones, and white noise. By coupling the sound card inputs and outputs to an external breadboard containing simple circuits (such as RC low-pass and high-pass filters), we demonstrated the ability to excite these circuits, and through post-processing of the recorded data, extract both the magnitude and phase of the transfer function for the circuit under test. In this paper we focus on methods in which audio files can be passed among different applications. In particular, we illustrate the ability to import and export audio data from and into MatLab and Cool Edit, using Cool Edit's superior sound recording/playback capabilities in conjunction with MatLab's powerful signal and array-processing capabilities. We also present examples of several "communication theory" related experiments, designed to give students practical hands-on experience with basic analog (FM & AM) modulation/demodulation techniques.
Point-based stream surfaces and path surfaces
Authors: Tobias Schafhitzel, Eduardo Tejada, Daniel Weiskopf, Thomas Ertl
Venue: Proceedings of Graphics Interface 2007 (2007)

We introduce a point-based algorithm for computing and rendering stream surfaces and path surfaces of a 3D flow. The points are generated by particle tracing, and an even distribution of those particles on the surfaces is achieved by selective particle removal and creation. Texture-based surface flow visualization is added to show inner flow structure on those surfaces. We demonstrate that our visualization method is designed for steady and unsteady flow alike: both the path surface component and the texture-based flow representation are capable of processing time-dependent data. Finally, we show that our algorithms lend themselves to an efficient GPU implementation that allows the user to interactively visualize and explore stream surfaces and path surfaces, even when seed curves are modified and even for time-dependent vector fields.
Evolutionary music composer integrating formal grammar
Authors: Yaser M. A. Khalifa, Badar K. Khan, Jasmin Begovic, Airrion Wisdom, Andrew Maxymillian Wheeler
Venue: Proceedings of the 2007 GECCO conference companion on Genetic and evolutionary computation (2007)

In this paper, an autonomous music composition tool is developed using Genetic Algorithms. The production is enhanced by integrating formal grammar rules. A formal grammar is a collection of either or both descriptive or prescriptive rules for analyzing or generating sequences of symbols. In music, these symbols are musical parameters such as notes and their attributes. The composition is conducted in two Stages. The first Stage generates and identifies musically sound patterns (motifs). In the second Stage, methods to combine different generated motifs and their transpositions are applied. These combinations are evaluated and as a result, musically fit phrases are generated. Four musical phrases are generated at the end of each program run. The generated music pieces will be translated into Guido Music Notation (GMN) and have alternate representation in Musical Instrument Digital Interface (MIDI). The Autonomous Evolutionary Music Composer (AEMC) was able to create interesting pieces of music that were both innovative and musically sound.
Testing learning strategies
Authors: M. Hidalgo-Herrero, I. Rodriguez, F. Rubio
Venue: Proceedings of the Fourth IEEE International Conference on Cognitive Informatics (2005)

In this paper we present an experiment designed to test whether an automatic system can learn a set of rules in a similar way as human beings learn the same set of rules. In order to do that, we have conducted two experiments. The first of them has been done with a group of seventy people, while the second one has been done by running an automatic learning system designed by ourselves. The paper contains the results of both tests, and a comparison of the learning curves of both types of subjects: humans and automatic agents. We also analyze the differences and similarities by considering how humans and agents construct their knowledge about the rules. By using both types of analysis, we study how close is the learning process of our automatic agents to obtaining a success in a Turing test.
A new interpretation of data hiding capacity
Authors: C. Candan
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03 (2001)

We present a new definition of data hiding capacity which complements the established theory in the field and produces practical estimates under many attacks. We discuss the relation between the proposed definition and the current theoretical work on data hiding capacity. The definition proposed is applied to still images to estimate the hiding capacity of a particular image under attacks such as JPEG compression and additive noise.
Temporalising Tractable Description Logics
Authors: A. Artale, R. Kontchakov, C. Lutz, F. Wolter, M. Zakharyaschev
Venue: Proceedings of the 14th International Symposium on Temporal Representation and Reasoning (2007)

It is known that for temporal languages, such as first-order LT L, reasoning about constant (time-independent) relations is almost always undecidable. This applies to temporal description logics as well: constant binary relations together with general concept subsumptions in combinations of LT L and the basic description logic ALC cause undecidability. In this paper, we explore temporal extensions of two recently introduced families of "weak' description logics known as DL-Lite and EL. Our results are twofold: temporalisations of even rather expressive variants of DL-Lite turn out to be decidable, while the temporalisation of EL with general concept subsumptions and constant relations is undecidable.
A Quality Measure for Multi-Level Community Structure
Authors: Maylis Delest, Jean-Marc Fedou, Guy Melancon
Venue: Proceedings of the Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (2006)

Mining relational data often boils down to computing clusters, that is finding sub-communities of data elements forming cohesive sub-units, while being well separated from one another. The clusters themselves are sometimes terms "communities" and the way clusters relate to one another is often referred to as a "community structure". We study a modularity criterionMQintroduced by Mancoridis et al. in order to infer community structure on relational data. We prove a fundamental and useful property of the modularity measure MQ, showing that it can be approximated by a gaussian distribution, making it a prevalent choice over less focused optimization criterion for graph clustering. This makes it possible to compare two different clusterings of a same graph as well as asserting the overall quality of a given clustering relying on the fact that MQ is gaussian. Moreover, we introduce a generalization extending MQ to hierarchical clusterings of graphs which reduces to the original MQ when the hierarchy becomes flat.