ppxscal/embedding_network huggingface dataset:
Information retrieval facility symposium in Vienna
Authors: John Tait
Venue: ACM SIGIR Forum (2008)

On November 8-9, 2007 the new Information Retrieval Facility (www.ir-facility.org) held its first annual Symposium in Vienna. The focus of the symposium was patent retrieval, and it was attended by 125 experts in Information Retrieval, Intellectual Property Management and related areas. Delegates came from Korea, Hong Kong, Singapore, Australia, Canada, the US and 10 European Countries. In terms of organisations, delegates came from Universities, Patent Offices (EPO, WIPO) and from commercial organisations ranging from majors like Shell and GlaxoSmithKline to one and two person consultancies.
Proceedings of the 3rd ACM SIGOPS/EuroSys European Conference on Computer Systems 2008
Venue: European Conference on Computer Systems (2008)

It is our great pleasure to welcome you to the 3rd ACM European Conference on Computer Systems -- EuroSys'08. Although a relatively young conference, it already has a reputation for high quality, a broad and enthusiastic attendance, and a wide ranging remit. We're delighted that this year is no exception, with an excellent program in a classic venue. EuroSys'08 gives researchers and practitioners a unique opportunity to discuss (or defend!) their perspectives while learning from others interested in the broad area of systems research. The call for papers attracted 131 full paper submissions from all over the world (including Asia, Australia, Europe, North America, South America and the Middle East). The program committee had a difficult selection process, but ultimately accepted 24 papers that cover a variety of systems topics ranging from storage systems to trusted computing; from scheduling to fault tolerance; and from modeling to measurement. In addition, the program includes a poster session where researchers can present initial results, as well as a keynote speech by Andrew Herbert of Microsoft Research dealing with future challenges for systems research. We hope that these proceedings will serve as a valuable reference for systems researchers.
Finding bugs in dynamic web applications
Authors: Shay Artzi, Adam Kiezun, Julian Dolby, Frank Tip, Danny Dig, Amit Paradkar, Michael D. Ernst
Venue: Proceedings of the 2008 international symposium on Software testing and analysis (2008)

Web script crashes and malformed dynamically-generated Web pages are common errors, and they seriously impact usability of Web applications. Current tools for Web-page validation cannot handle the dynamically-generated pages that are ubiquitous on today's Internet. In this work, we apply a dynamic test generation technique, based on combined concrete and symbolic execution, to the domain of dynamic Web applications. The technique generates tests automatically, uses the tests to detect failures, and minimizes the conditions on the inputs exposing each failure, so that the resulting bug reports are small and useful in finding and fixing the underlying faults. Our tool Apollo implements the technique for PHP. Apollo generates test inputs for the Web application, monitors the application for crashes, and validates that the output conforms to the HTML specification. This paper presents Apollo's algorithms and implementation, and an experimental evaluation that revealed 214 faults in 4 PHP Web applications.
A generation model to unify topic relevance and lexicon-based sentiment for opinion retrieval
Authors: Min Zhang, Xingyao Ye
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

Opinion retrieval is a task of growing interest in social life and academic research, which is to find relevant and opinionate documents according to a user's query. One of the key issues is how to combine a document's opinionate score (the ranking score of to what extent it is subjective or objective) and topic relevance score. Current solutions to document ranking in opinion retrieval are generally ad-hoc linear combination, which is short of theoretical foundation and careful analysis. In this paper, we focus on lexicon-based opinion retrieval. A novel generation model that unifies topic-relevance and opinion generation by a quadratic combination is proposed in this paper. With this model, the relevance-based ranking serves as the weighting factor of the lexicon-based sentiment ranking function, which is essentially different from the popular heuristic linear combination approaches. The effect of different sentiment dictionaries is also discussed. Experimental results on TREC blog datasets show the significant effectiveness of the proposed unified model. Improvements of 28.1% and 40.3% have been obtained in terms of MAP and p@10 respectively. The conclusion is not limited to blog environment. Besides the unified generation model, another contribution is that our work demonstrates that in the opinion retrieval task, a Bayesian approach to combining multiple ranking functions is superior to using a linear combination. It is also applicable to other result re-ranking applications in similar scenario.
On the combinatorial and algebraic complexity of quantifier elimination
Authors: S. Basu
Venue: Proceedings of the 35th Annual Symposium on Foundations of Computer Science (1994)

In this paper we give a new algorithm for performing quantifier elimination from first order formulae over real closed fields. This algorithm improves the complexity of the asymptotically fastest algorithm for this problem, known to this date. A new feature of our algorithm is that the role of the algebraic part (the dependence on the degrees of the input polynomials) and the combinatorial part (the dependence on the number of polynomials) are separated, making possible our improved complexity bound. Another new feature is that the degrees of the polynomials in the equivalent quantifier-free formula that we output, are independent of the number of input polynomials. As special cases of this algorithm, we obtain new and improved algorithms for deciding a sentence in the first order theory over real closed fields, and also for solving the existential problem in the first order theory over real closed fields. Using the theory developed in this paper, we also give an improved bound on the radius of a ball centered at the origin, which is guaranteed to intersect every connected component of the sign partition induced by a family of polynomials. We also use our methods to obtain algorithms for solving certain decision problems in real and complex geometry which improves the complexity of the currently known algorithms for these problems.
Identification of best sets of actions in Influence Nets
Authors: Sajjad Haider, Abbas K. Zaidi, Alexander H. Levis
Venue: International Journal of Hybrid Intelligent Systems (2008)

This paper presents a heuristic approach to solve the problem of best set of actions determination in Influence Nets. Influence Nets are a special instance of Bayesian Networks that model uncertain situations by connecting a set of desired effects to a set of actionable events through chains of probabilistic cause and effect relationships. Once an Influence Net is specified, a system analyst is often interested in identifying the set of action which has the highest probability of achieving a desired effect. The existing techniques to solve this problem, such as sensitivity analysis and exhaustive search, have limitations of their own. The proposed algorithm, named SAF, attempts to overcome these limitations. The paper also shows that the problem of best set of actions determination can be formulated as an instance of Mixed Integer Non Linear Programming (MINLP). An empirical study is presented that compares the performance of sensitivity analysis, SAF, and MINLP.
Implementing fault-tolerance in real-time programs by automatic program transformations
Authors: Tolga Ayav, Pascal Fradet, Alain Girault
Venue: ACM Transactions on Embedded Computing Systems (TECS) (2008)

We present a formal approach to implement fault-tolerance in real-time embedded systems. The initial fault-intolerant system consists of a set of independent periodic tasks scheduled onto a set of fail-silent processors connected by a reliable communication network. We transform the tasks such that, assuming the availability of an additional spare processor, the system tolerates one failure at a time (transient or permanent). Failure detection is implemented using heartbeating, and failure masking using checkpointing and rollback. These techniques are described and implemented by automatic program transformations on the tasks' programs. The proposed formal approach to fault-tolerance by program transformations highlights the benefits of separation of concerns. It allows us to establish correctness properties and to compute optimal values of parameters to minimize fault-tolerance overhead. We also present an implementation of our method, to demonstrate its feasibility and its efficiency.
Area-optimal three-layer channel routing
Authors: R. Kuchem
Venue: Proceedings of the 30th Annual Symposium on Foundations of Computer Science (1989)

The channel routing problem in the knock-knee mode is considered. The algorithm presented always constructs a correct layout in a channel of bounded size, if there is one, and guarantees that it is wirable with only three conducting layers; that is, the layout is optimal with respect to the area and to the number of layers. The algorithm thus improves all previously known layout algorithms, which either use additional columns to produce a three-layer wirable layout or construct a layout for which the three-layer wirability is not proved. For the layer assignment only O(N) (N is the number of nets) vias are used. The algorithm can be implemented to run in O(N log N) time.
Adaptive congestion control of high speed ATM networks
Authors: Morteza Mosavi, Mahdi Jalili-Kharaajoo
Venue: Proceedings of the 4th WSEAS International Conference on Telecommunications and Informatics (2005)

Proportional control methods of controlling congestion in high speed ATM networks fail to achieve the desired performance due to the action delays, nonlinearities, and uncertainties in control loop. In this paper an adaptive minimum variance controller is proposed to minimize the rate of stochastic inputs from uncontrollable high priority sources. This method avoids the computations needed for pole placement design of the minimum variance controller, and utilizes an online recursive least squares algorithm in direct tuning of the controller parameters. The closed loop system is adaptive and robust to the uncertain network conditions and provides minimum cell loss ratio, efficient use of network resources, and fair allocation of the available bandwidth through the controlled sources.
A policy-based methodology for security evaluation: A Security Metric for Public Key Infrastructures
Authors: Valentina Casola, Antonino Mazzeo Nicola Mazzocca Valeria Vittorini
Venue: Journal of Computer Security (2007)

The security of complex infrastructures depends on many technical and organizational issues that need to be properly addressed by a security policy. For purpose of our discussion, we define a security policy as a document that states what is and what is not allowed in a system during normal operation; it consists of a set of rules that could be expressed in formal, semi-formal or very informal language. In many contexts, a system can be considered secure and trustworthy if the policy enforced by its security administrator is trustworthy too; from this standpoint it is possible to evaluate the system security by evaluating its policy. In this paper we present a policy-based methodology to formalize and compare policies, and a Security Metric to evaluate the security level that a system is able to grant. All the steps of the methodology will be illustrated with an operative approach, by directly applying it to a real case study: the semi-automated Cross Certification among Public Key Infrastructures.
AUTOMATIC MACHINE LEARNING OF KEYPHRASE EXTRACTION FROM SHORT HTML DOCUMENTS WRITTEN IN HEBREW
Authors: Yaakov HaCohen-Kerner, Ittay Stern, David Korkus, Erick Fredj
Venue: Cybernetics and Systems (2007)

Keyphrases extracted from documents may save precious time for tasks such as filtering, summarization, and categorization. A few such systems are available for documents written in English. In this paper, we propose a model called LEH_KEY (Learning to Extract Hebrew KEYphrases) that for the first time learns to extract keyphrases for documents written in Hebrew. Firstly, we introduce a relatively high number (15) of baseline extraction methods as opposed to other related systems that use combinations of a low number (two/three) of baseline extraction methods. In contrast, we have investigated various combinations of larger number of baseline methods and various machine learning methods have been tested. The best results have been achieved by a combination of six baseline methods using J48 (an improved variant of C4.5). Our results have been found to be at least of equal quality to those achieved by extraction systems for documents written in English, which are regarded as state-of-the art.
Missing data mask estimation with frequency and temporal dependencies
Authors: Sébastien Demange, Christophe Cerisara, Jean-Paul Haton
Venue: Computer Speech and Language (2009)

Automatic speech recognition (ASR) has reached a very high level of performance in controlled situations. However, the performance degrades drastically when environmental noise occurs during recognition. Nowadays, the major challenge is to reach a good robustness to adverse conditions. Missing data recognition has been developed to deal with this challenge. Unlike other denoising methods, missing data recognition does not match the whole data with the acoustic models, but instead considers part of the signal as missing, i.e. corrupted by noise. The main challenge of this approach is to identify accurately missing parts (also called masks). The work reported here focuses on this issue. We start from developing Bayesian models of the masks, where every spectral feature is classified as reliable or masked, and is assumed independent of the rest of the signal. This classification strategy results in sparse and isolated masked features, like the squares of a chess-board, while oracle reliable and unreliable features tend to be clustered into consistent time-frequency blocks. We then propose to take into account frequency and temporal dependencies in order to improve the masks' estimation accuracy. Integrating such dependencies leads to a new architecture of a missing data mask estimator. The proposed classifier has been evaluated on the noisy Aurora2 (digits recognition) and Aurora4 (continuous speech) databases. Experimental results show a significant improvement of recognition accuracy when these dependencies are considered.
Sink node mobility for ellipsoidal area coverage for efficient data collection in Wireless Sensor Networks
Authors: Maznah Kamat, Abd Samad Ismail, Stephan Olariu
Venue: International Journal of Autonomous and Adaptive Communications Systems (2008)

In this article, we explore the usage of Hilbert space filling curves in solving area covering for a target field, and also ensuring accurate gathering of periodic data collection. In covering the area, the mobility pattern that is based on modified Hilbert space filling curves suited best for ellipsoidal bounded area of interest. Comparative study demonstrates those circular and conventional Hilbert traversals are rejected due to non-adaptiveness to monitoring area shapes.
Randomized geometric algorithms and pseudo-random generators
Authors: K. Mulmuley
Venue: Proceedings of the 33rd Annual Symposium on Foundations of Computer Science (1992)

The so called randomized incremental algorithms in computational geometry can be thought of as a generalization of Quicksort to higher dimensional geometric problems. They all construct the geometric complex in the given problem, such as a Voronoi diagram or a convex polytope, by adding the objects in the input set, one at a time, in a random order. The author shows that the expected running times of most of the randomized incremental algorithms in computational geometry do not change (up to a constant factor), when the sequence of additions is not truly random but is instead generated using only O(log n) random bits. The pseudo-random generator used is a generalization of the well known linear congruential generator.
Potential benefits of corrected-errors in AVBL
Authors: Antonios Saravanos
Venue: Proceedings of the 13th annual conference on Innovation and technology in computer science education (2008)

This paper proposes the examination of the potential role that corrected-errors can play in asynchronous online video-based learning of troubleshooting education within the context of computer programming language pedagogy.
Brain-Computer Interfacing for Intelligent Systems
Authors: Anton Nijholt, Desney Tan, Gert Pfurtscheller, Clemens Brunner, José del R. Millán, Brendan Allison, Bernhard Graimann, Florin Popescu, Benjamin Blankertz, Klaus-R. Müller
Venue: IEEE Intelligent Systems (2008)

Advances in cognitive neuroscience and brain-imaging technologies give us the unprecedented ability to interface directly with brain activity. These technologies let us monitor physical processes in the brain that correspond with certain forms of thought. Researchers have begun using these technologies to build brain-computer interfaces (BCIs)—communication systems that don't depend on the brain's normal output pathways of peripheral nerves and muscles. Four short articles provide a quick overview of the past, present, and future of BCIs.
Solving selection problems combining relational learning and Bayesian learning
Authors: Tomofumi Nakano, Nobuhiro Inuzuka
Venue: International Journal of Knowledge-based and Intelligent Engineering Systems (2007)

This paper defines a selection problem where an appropriate object is selected from a set that is specified by parameters. We discuss inductive learning of selection problems and proposed a method combining inductive logic programming (ILP) and Bayesian learning. Our methods estimate probability of each choice by evaluating likelihood of an induced relation from an ideal binary relation. Bayesian learning combines a prior probability of objects and the estimated probability. By making several assumptions on probability estimation, we give several methods. The methods are applied to Part-of-Speech tagging.
A scatternet scheduling scheme with sniff slot in bluetooth
Authors: Jungmee Yun, Daehwan Kim
Venue: Proceedings of the 4th WSEAS International Conference on Applied Informatics and Communications (2004)

The ad-hoc network which used bluetooth technology consists of scatternet providing internetworking between piconet and them who are a basic communication unit. However, detailed technical study currently related to implementation of the scatternet which used bluetooth technology is short misgovernment. We are going to propose the bluetooth scatternet scheme which is adaptable in various network traffic patterns to have seen in this. In this paper, we proposed the Association-spot scheduling scheme that we modified sniff mode and can implement scatternet. Further, bluetooth standard additional several are unnecessary and it is currently possible implementation/ application with software with this function in commercialized bluetooth products.
On isomorphisms and similarities between generalized Petersen networks and periodically regular chordal rings
Authors: Behrooz Parhami
Venue: Information Processing Letters (2008)

Generalized Petersen (GP) networks and periodically regular chordal (PRC) rings have been proposed independently to ameliorate the high latency and extreme fragility of simple ring networks. In this paper, we note that certain GP networks are isomorphic to suitably constructed PRC rings, while other varieties correspond to PRC rings that closely approximate their topological and performance attributes. In the absence of equivalence and similarity proofs in the opposite direction, our results indicate that PRC rings may be preferable to GP networks in the sense of covering a broader family of networks and offering greater flexibility in cost-performance tradeoffs.
An Agent-Based Architecture for a Cooperation Information System Supporting the Homecare
Authors: Karim Zarour, Nacereddine Zarour
Venue: Proceedings of the 2008 International Workshop on Advanced Information Systems for Enterprises (2008)

Nowadays, the organization of homecare arouses an increasing interest. By organization, we mean particularly the choice of the partners, distribution’s problems, tasks’ coordination, and the resolution of all participants’ resources-conflicts. The quality of the homecare relies on the competences, the qualifications of the participating partners and their organization. It is evident that agent's paradigm is the most suitable among other paradigms because it is capable of taking into account all these aspects. In this paper we would like to present an agent-based architecture for a cooperation information system that supports the homecare and contains all the necessary constituents for its functioning
Proactive Handover in Heterogeneous Networks Using SIPs
Authors: Elin Sundby Boysen, Hkon Eyde Kjuus, Torleiv Maseng
Venue: Proceedings of the Seventh International Conference on Networking (2008)

In some areas, overlapping networks provide alternative wireless links like WLAN, GSM, 3G etc. Ideally, the user should be connected to the most attractive network any time according to predefined priorities. This is accomplished with automatic handover. The most likely commercial application of this type is designed for speech, and is using SIP to set up VoIP calls through WLAN networks or mobile networks. To make the handover time as short as possible is essential to make it attractive. This is best done by preparing the alternative networks before the handover is needed. This is called proactive handover. This paper suggests changes to some of the basic SIP messages that open for proactive handover in SIP and help reduce the delays when roaming.
A case study for mapping of spatial distribution of free surface heave in alluvial soils (Yalova, Turkey) by using GIS software
Authors: Işık Yilmaz
Venue: Computers Geosciences (2008)

A procedure for producing a surface heave map using GIS package in clayey alluvial soils is proposed. An active zone was first defined, and the layers in the active zone were subdivided according to their swelling characteristics. The free surface heave values for each cell of the digitized map of the study area were calculated by using the available equation in the literature, and a spatial distribution map was then constructed interpolating the data belonging to each borehole location. Soils having a high swelling capacity are widely distributed in the study area, and will cause serious heave problems on light structures. Clayey soils in the study area have generally moderate-very high swelling potentials, and swell pressures in many locations are much higher (up to 98kPa) for low-rise structures. Moreover, differential movements sourced from surface heave are also expected in many locations. It was calculated that the minimum expected heave was 0.00cm while the maximum was 12.24cm, indicating ''very severe'' differential movement. The results obtained in this paper can be used as basic data to assist surface heave hazard management and land use planning. The information derived from this study also has a special importance for assessing the probable deformations on intended light construction applications in Yalova city. The methods used in this study will be valid for generalized planning and assessment purposes; although they may be less useful on the site-specific scale, where local geology and geographic heterogeneities may prevail.